Business Models and Digital Technology Platforms: Implementation and Complexities for Digital Business

Bartczak, Krzysztof Book Business Models and Digital Technology Platforms: Implementation and Complexities for Digital Business Routledge Studies in Innovation, Organizations and Technology Provided in Cooperation with: Taylor & Francis Group Suggested Citation: Bartczak, Krzysztof (2024) : Business Models and Digital Technology Platforms: Implementation and Complexities for Digital Business, Routledge Studies in Innovation, Organizations and Technology, ISBN 978-1-040-05002-6, Routledge, Abingdon, Oxon, https://doi.org/10.4324/9781003473022 This Version is available at: https://hdl.handle.net/10419/305363 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may be saved and copied for your personal and scholarly purposes. You are not to copy documents for public or commercial purposes, to exhibit the documents publicly, to make them publicly available on the internet, or to distribute or otherwise use the documents in public. If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by-nc-nd/4.0/ Business Models and Digital Technology Platforms This book examines the influence exerted by digital technology platforms (DTPs) on changes to business models. The author identifies critical factors for the successful implementation and usage of such platforms, including barriers which may be related, for example, to the absence of sufficient knowledge about DTPs or the inability to obtain a sufficient amount of financial resources. Business Models and Digital Technology Platforms develops a comprehensive model of DTPs based on empirical research in Poland. It demonstrates how platforms influence changes in the operations of companies, their level of competitiveness, the consumer’s role in the process of joint development of innovations and the consumer’s experience as well as implications of the use of AI for the autonomy of DTPs. This book offers a unique, holistic understanding of the complexities involved and showcases their role within digital business. Combining theory with practice, this book is a valuable resource for researchers and academics of business model innovation, strategic management, innovation management, digital transformation and organisational change. Krzysztof Bartczak is an academic researcher and assistant professor at the Faculty of Management of the Warsaw University of Technology. In 2014 he completed a postgraduate international MBA (Master of Business Administration) programme at the Warsaw University of Technology Business School. (This programme was established by the Warsaw University of Technology, HEC School of Management – Paris, London Business School and the Norwegian School of Economics.) In 2015–2021 he followed a doctoral programme at the Collegium of Business Administration of the Warsaw School of Economics (academic discipline: Management Science). He is professionally associated as a founder with the first Digital Technology Platform for Renewable Energy Sources in Poland (https://easyoze.pl) and founder of the global Digital Technology Platform Solares PRO – a sales platform for RES companies for the entire world (https://solarespro.com). Impact of Artificial Intelligence in Business and Society Opportunities and Challenges Davide La Torre, Francesco Paolo Appio, Hatem Masri, Francesca Lazzeri and Francesco Schiavone Management System for Strategic Innovation Building Dynamic Capabilities View of the Firm Mitsuru Kodama Digital Business Strategy Content, Context and Cases Anders Pehrsson Cyber Security and Business Intelligence Innovations and Machine Learning for Cyber Risk Management Edited by Mohammad Zoynul Abedin and Petr Hajek Internet of Things in the Food Industry Challenges and Opportunities for the Internet of Food Things Edited by Anna Rogala, Renata Nestorowicz and Ewa Jerzyk Corporate Entrepreneurship and Innovation in Tourism and Hospitality Global Post Covid‑19 Recovery Strategies Edited by Teresa Aguiar‑Quintana, Jonathon Day and Francisca Rosa Álamo Vera Grassroots Innovation Discourse, Policy and Practice in the Global South Hemant Kumar and Gautam Sharma Business Models and Digital Technology Platforms Implementation and Complexities for Digital Business Krzysztof Bartczak For more information about this series, please visit: www.routledge.com/Routledge‑Studies‑in‑ Innovation‑Organizations‑and‑Technology/book‑series/RIOT Routledge Studies in Innovation, Organizations and Technology Business Models and Digital Technology Platforms Implementation and Complexities for Digital Business Krzysztof Bartczak LONDON AND NEW YORK First published 2024 by Routledge 4 Park Square, Milton Park, Abingdon, Oxon OX14 4RN and by Routledge 605 Third Avenue, New York, NY 10158 Routledge is an imprint of the Taylor & Francis Group, an informa business © 2024 Krzysztof Bartczak The right of Krzysztof Bartczak to be identified as author of this work has been asserted in accordance with sections 77 and 78 of the Copyright, Designs and Patents Act 1988. The Open Access version of this book, available at www.taylorfrancis. com, has been made available under a Creative Commons AttributionNon-Commercial-No Derivative Licence (CC-BY-NC-ND) International license. Trademark notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation without intent to infringe. British Library Cataloguing‑in‑Publication Data A catalogue record for this book is available from the British Library ISBN: 978-1-032-75229-7 (hbk) ISBN: 978-1-032-75234-1 (pbk) ISBN: 978-1-003-47302-2 (ebk) DOI: 10.4324/9781003473022 Typeset in Times New Roman by codeMantra The publication is co-financed by the state budget under the program of the Minister of Education and Science called “Excellent Science”, project number DNM/SP/548969/2022, amount of co-financing: PLN 79,927.05, total value of the project: PLN 88,809.22. Contents List of Figures vii List of Tables ix List of Graphs xi Introduction 1 1 Digital Transformation of Businesses 5 1.1 The Origin of Digital Technologies 5 1.2 Diversity of Digital Technologies 8 1.3 Digital Transformation of a Company Viewed as a Process 12 1.4 Organisational Changes Accompanying Digitalisation 18 1.5 Impact of Digitalisation on Company Management 21 2 Digital Technology Platforms 30 2.1 Concept of a Digital Technology Platform 30 2.2 Properties of Digital Technology Platforms 34 2.3 Typology of Digital Technology Platforms 39 2.4 Global Market of Digital Technology Platforms 47 2.5 Fields of Application and Achieved Benefits 53 2.6 Development Prospects Based on Artificial Intelligence 62 3 Innovative Changes to Business Models 71 3.1 Business Model – Theoretical Approach 71 3.2 The Essence of Innovative Organisation 76 3.3 Concept and Model of Digital Business 80 3.4 Innovative Changes to the Business Model Based on a Digital Technology Platform 83 3.5 Impact of Changes in Business Models on the Competitiveness of Companies 89 3.6 Development Prospects for Digital Business Models 92 vi Contents 4 Findings of Empirical Research 102 4.1 Research Methodology 102 4.2 Changes to Business Models Based on Technology Platforms 110 4.3 A Consumer as a Co‑Originator of Innovative Changes to Business Models 140 4.4 Digital Opportunities for Expanding Consumer Experience 143 4.5 Artificial Intelligence as a Factor Increasing the Autonomy of Digital Platforms 146 Final Conclusions 151 Appendix 1: Survey Questionnaire 155 Appendix 2: Tabular Results of Quantitative Data Collected during the CATI Survey 163 References 175 Index 189 Figures 1.1 “Waves” of economic development according to J. Schumpeter and his followers 6 1.2 Areas where digital transformation is implemented in a company 14 1.3 Areas of digital transformation according to Q. Corver and G. Elkhuizen 15 1.4 Stages of digital transformation of a company according to B. Solis 16 1.5 Areas of organisational changes resulting from digitalisation 19 1.6 Evolution of organisational structures of contemporary companies from a model characteristic of the industrial age to a model of the age of knowledge 21 1.7 Key aspects of marketing in a digital company 24 2.1 Components of a business ecosystem 36 2.2 Classification of digital technology platforms according to H. LeHong, C. Howard, D. Gaughan, D. Logan 40 2.3 Types of digital platforms in historical perspective according to the UN 44 2.4 Planned architecture of the Polish Artificial Intelligence Platform with the use of the Polish Data Integration Hub 63 3.1 A template according to the concept of Business Model Canvas 75 3.2 Triple Helix Theory 79 3.3 VOPA leadership model 88 3.4 Sharing Business Model Compass 95 3.5 The Triple Layered Business Model Canvas architecture 97 4.1 Components of the optimal scaling model produced with the top‑down method – visual interpretation taking into account the proportional importance of each factor in the model 116 4.2 Digital technology platform as a tool for companies’ cooperation with consumers 142 2 Introduction intensively. This creates the need to take a scientific approach to digital technology platforms and fill in the gap arising from the absence of a sufficiently broad discussion in the literature on the subject matter regarding the impact of the platforms on digital business and companies’ capabilities to implement them. The main purpose of this monograph is to examine the influence exerted by digital technology platforms on changes to business models. The utilitarian aim is to identify critical factors for the successful implementation and usage of such platforms, including barriers which may be related, for example, to the absence of sufficient knowledge about digital technology platforms or the inability to obtain a sufficient amount of financial resources. Detailed objectives related to the foregoing include the scope and nature of benefits that may be generated owing to the use of digital technology platforms as well as business areas where they may be utilised. Moreover, what should be also noted is the desire to fulfil aims and objectives relating to determination of the extent to which Polish companies are prepared to implement digital technology platforms and the degree to which Polish businesses and managers are aware how such platforms may be used. Thus, the scientific aim of this monograph may be divided into two basic areas. The first one concerns the benefits associated with the implementation of digital technology platforms, while the other one is about their practical use by Polish companies. The achievement of the said aims will help answer the following questions: Should digital technology platforms be treated as mere supporting tools for the existing models used by specific companies? Should they be regarded as the basis for the development and implementation of innovative changes to business models? A discussion of these topics requires the formulation of specific problems and research hypotheses. The key research problem has been defined as follows: What is the role played by digital technology platforms in the process of preparing and implementing business models in a company? Considering that this monograph also focuses on achieving a utilitarian aim, it is worth formulating a problem relating strictly to this aim. The problem in question concerns the barriers which hinder the implementation and use of digital technology platforms. Referring to the research problem stated above, the following central research proposition has been put forward: Digital technology platforms are tools supporting the functioning of companies and form the basis for implementing innovative changes to business models. The central proposition is supplemented by the following more detailed hypotheses: H1. Digital technology platforms facilitate the introduction of changes to the operations of companies, especially in the area of management, marketing and sales. H2. Innovative changes to the business model based on a digital technology platform make it possible to include the consumer in the processes of co‑creating innovations. H3. Digital technology platforms create new opportunities, not encountered to date, for increasing customer experience. Introduction 3 H4. The use of artificial intelligence makes digital platforms increasingly more autonomous in customer service applications. H5. Digital technology platforms are a new factor for companies’ competitiveness in the digital economy. To verify these hypotheses, a survey was conducted on a randomly selected group of respondents comprised of people representing companies directly involved in using digital technology platforms. To attain the objectives stated above and to solve the problems posed, it was necessary to use three distinct research methods in this monograph. The first of these, content analysis of the literature on the subject matter, was applied during preliminary studies and attempting to confirm the research hypotheses. During the analysis, the following kinds of sources were examined – publications about the concept of technological determinism, assigning a critical role to technical and technological issues and related transformations in shaping modern society and the economy as well as showing the impact of digital technology platforms on companies’ business activities. The second method is called CATI or computer‑assisted telephone interviewing. It is a modification of the classic method of quantitative research – direct standardised interviews using tabular analysis (two‑variable tables) and inductive tests of inter‑group differences. The third research method is called CATREG (categorical regression) and takes the form of optimal scaling within regression analysis for qualitative variables whose purpose is to assess qualitative data in quantitative terms. Under the method, the correlatives of opinions about the degree to which DTPs impact the operation of companies were taken into consideration. This monograph is broken down into four chapters. The first chapter discusses basic issues concerning the digital transformation of companies. It describes various aspects of the origin and diversification of digital technologies, the digital transformation of businesses viewed as a process, organisational changes associated with the transformation and the impact of digitisation on broadly construed company management. The second chapter focuses on the basic aspects of digital technology platforms. First of all, based on the literature, an original definition of the concept is proposed, with a specification of features associated with the functioning of the platforms. What follows is a presentation of typologies of DTPs, a description of the functioning of the global market for such platforms and an indication of fields where they may be used as well as benefits achieved from their use. Furthermore, development prospects of the platforms have been determined based on technologies involving artificial intelligence. Chapter three deals with issues having to do with innovative changes in business models resulting from the use of digital technology platforms. This, however, is preceded by a description of the nature of business models and innovative organisations as well as a presentation of the concept and model of digital business. Furthermore, that part of this monograph describes development prospects of digital business models, taking also into consideration the use of DTPs. 4 Introduction The fourth chapter presents findings of empirical research. The point of departure was a description of the research methodology, showing how the model of digital technology platforms was built. Further on in the chapter, based on the conducted surveys, each of the research hypotheses is discussed, pointing out how digital technology platforms influence changes in the operations of companies, their level of competitiveness, the consumer’s role in the processes of joint development of innovations and the consumer’s experience as well as implications of the use of artificial intelligence for the autonomy of DTPs. This monograph is about issues concerning the science of management and quality. All pertinent analyses and their findings may contribute in a significant manner to the development of this scientific discipline. This work, for the first time, taking into consideration both Polish and foreign literature, discusses extensively the impact of digital technology platforms on innovative business models. The discussion herein focuses not only on various aspects of usefulness of digital platforms in the context of development of modern business models, including those based on consumers’ knowledge or experience, but additionally examines which areas of companies’ operations may be perceived as especially favourably affected by DTPs and how important artificial intelligence is in this respect. Such discussions not just deepen the research rooted in literature that has been performed to date but also provide grounds for taking up completely new issues in the science of management and quality. Thus, an important research gap has been filled in regarding the knowledge of how modern business models are developed based on various types of digital platforms. The central point of the discussions in this monograph is the construction of a model of digital technology platforms based on findings from measurement of company managers’ attitudes to DTPs. The approach to the research problem proposed in this monograph is innovative in nature because, first, no attempt has been made so far to build such a model, and, second, such an approach may form the basis for constructing further models of digital technology platforms which would take into consideration other areas of business activity, including, for example, those which concern their strictly technical (technological) aspects. Determined on the basis of analysis of literature and findings of the author’s own research, they may be used by company managers in management processes. Owing to the constructed model, directions for further research were outlined, noting that significant correlatives of attitudes to digital technology platforms may be factors concerning the structures of companies, including industries in which they operate and the number of employees. It is worth emphasising that a certain novelty is also the integration, within management theory, of two important research methods, namely a CATI quantitative survey and CATREG with optimal scaling. Such integration seems to provide great possibilities and, most importantly, may bring about measurable effects, which is shown by the model presented herein. Accordingly, this monograph demonstrates the importance and the breadth of perspectives for management and quality sciences brought about by the simultaneous use of such methods. DOI: 10.4324/9781003473022-2 1.1 The Origin of Digital Technologies In the contemporary world, digital technologies play an enormous role in the functioning of each country, society and organisation. According to E. Brynjolfsson and A. McAfee, “the key building blocks are already in place for digital technologies to be as important and transformational to society and the economy as the steam engine.”1 In turn, A. Łaszek stated that “of key importance for economic growth and, consequently, for our standard of living is the deployment of new technologies.”2 It is worth noting that, contrary to appearances, it is not true that such technologies were invented and become popular only in the 21st century. It needs to be observed though that the 21st century is precisely when the enormous role of technologies in the global economy became visible, to which, among other factors, the intensive development of mobile technologies contributed,3 but their origin should be already traced back to a much earlier period. Digital technologies began to appear in the second half of the 20th century. In literature on the subject matter,4 the first mention of the term digitalisation (digitisation) with reference to the wide‑ranging changes in the global economy involving the increasingly popular use of digital technologies is found in a 1971 essay by R. Wachal entitled “Humanities and Computers. A Personal View.”5 It discussed the impact on various societies and their members that was to be exerted by computers, which included future social consequences of development of the related technologies. Such development, according to R. Wachal, was likely to lead to the said digitalisation. At present, digit(al) isation is thought of as a process which involves the conversion of analogue information into a digital format. Such a process is also described as digital inclusion, which is connected with the fact that in the course of digitisation, an analogue item is gradually transformed into a digital format, with no other substantive changes taking place.6 Importantly, according to some authors, it is possible to talk about digit(al)isation or digital technologies with reference to a period as early as the 1950s.7 Analysing issues regarding the origin of the technology, it is worth going back to the concepts which proposed phases of economic growth in the world. This is because those concepts have devoted a lot of space to issues of transformation related to digitalisation. One of those concepts was developed by Austrian economist J. Schumpeter and continuators of his work, namely, C. Freeman and L. Soete. 1 Digital Transformation of Businesses This chapter has been made available under a CC‑BY‑NC‑ND license. 6 Digital Transformation of Businesses The authors distinguished five “waves” in the construction of the global economic system. They are presented in Figure 1.1. Analysing the concept of “waves” of economic growth advanced by J. Schumpeter and his continuators, it is clear that the concept refers to digitalisation and digital technologies. According to this view, a breakthrough in the use of digital networks or new media occurred around 1999, when these inventions began to impact, to an increasingly greater extent, numerous transformations in the world economy or in the system of goods and their distribution. It is therefore a considerably later period than the 1950s or 1970s, when people already started talking about the digital or computer revolution.8 It should be pointed out, though, that J. Schumpeter and his followers distinguished each “wave” by taking into consideration the decisive impact that each invention had on economic development. In this respect, speaking of a “wave” related to digital networks or new media in the context of the turn of the 21st century becomes justified, which follows from the fact that it was exactly then that the use of the Internet started to be more and more popular and that has had profound impact on promoting the use of knowledge being the main “driving force” of contemporary economies.9 A different distribution of distinct phases of economic growth was conceived by American writer and futurologist A. Toffler. In his opinion, the world has witnessed three breakthrough periods which should be referred to as “waves,” just like in Schumpeter’s concept. For the topics discussed in this work, the most important of those is the third “wave,” which, according to A. Toffler, began to be observable as early as in the second half of the 1950s and whose most distinctive feature became the number of white‑collar workers and service employees being higher than the number of blue‑collar workers. Therefore, even as long ago as then one could refer to it as the age of a knowledge society, which has become to be characterised by the mass use of digital technologies.10 Likewise, D. Bell, discussing the division of history into developmental periods of society, distinguished a phase inextricably connected with digitalisation and an increasingly more common use of digital technologies. He called that phase a post‑industrial society or post‑industrial economy. The most important characteristics of this kind of economy mentioned by D. Bell include: – shifted importance of economic sectors in the direction of those whose potential is built on knowledge; – a change from energy‑based technology prevailing till then into information technology; Figure 1.1 “Waves” of economic development according to J. Schumpeter and his followers Source: Author’s own work based on A. Kukliński, Gospodarka oparta na wiedzy jako wyzwanie dla Polski XXI wieku, Komitet Badań Naukowych, Warsaw 2001, p. 14. Digital Transformation of Businesses 7 – increased importance of processes associated with planning or monitoring of technologies; – explosive growth of “intellectual technology,” that is one which is based to the greatest extent on knowledge; – domination of the service sector.11 A team of German scientists doing research on technology, represented by K. Schwab, four industrial revolutions are talked about, two of which refer directly to the development of digital technologies. The third of these was the computer or digital revolution, which started in the 1960s, when the production of mainframe computers began (large‑sized computers for processing quite a lot of data), and continued in the 1970s, when personal computers appeared, and in the 1990s, when the Internet was applied for commercial purposes. The fourth industrial revolution is characterised by the dissemination of mobile technologies (Internet, smartphones, tablets) or devices based on artificial intelligence.12 Following M. Olender‑Skorek, one may claim that there have been four industrial (civilisation, technological) revolutions in the history of the world, each marked by a specific breakthrough invention. Apart from steam engine and electricity, it was computer and digitisation.13 Thus, the origin of digital technologies should be closely associated with the third and fourth revolutions, the former referred to by many authors14 as the digital revolution, while the latter known as industry 4.0 or digitalisation 4.0.15 The birth of the digital revolution is usually dated to the 1980s, although some authors argue that it already started in the 1950s16 or the 1960s.17 Its characteristic feature was a considerable technological progress, enabling the promotion of digital solutions, which gradually began supplanting analogue devices. At the same time, computers started to a greater and greater extent be used to perform specific projects in a virtual environment.18 This revolution was followed by a stage referred to as industry 4.0, which is also strictly related to digital technologies and which involves the construction of smart systems, increasingly more interconnected, creating value by initiating and reinforcing coordination and cooperation among various organisations and processes.19 It should be noted that the digital revolution would be impossible without creating conditions for a fast and automated collection, processing or transmission of information. The revolution brought about the possibility of generating and analysing information much easier than ever. It is therefore justified to state that the revolution accompanying digital technologies should be actually called a “digital information revolution.”20 Numerous diverse factors contributed to the creation and development of digital technologies. The following ones should be mentioned in this context: – ever‑increasing technological progress, reducing barriers to access to information; – free‑market competition; – increased importance of knowledge within the operation of organisations; – high supply of new products and services; 8 Digital Transformation of Businesses – need for increasing effectiveness and efficiency and reducing the costs of business processes and operations to achieve a high level of competitiveness; – gradual disappearance of various barriers against business exchange among states, which made faster flow of information or goods possible, including know‑how; – unpredictability of economic and technological development and high growth rate of this development, making it necessary to continue seeking more and more innovative and competitive systems, tools and solutions; – necessity to satisfy increasingly changing needs of customers; – requirement that organisations should adjust to the dynamic situation in the environment.21 Based on the above description, it may be concluded that while the origin of digital technologies should be traced back to the 1950s or the 1960s, their real and intensive development occurred when the use of personal computers and the Internet became widespread. It should be remarked at this point that only in the 1990s did the term “digital economy” appear in scientific literature. It was coined by D. Tapscott. He claimed that the new form of the global economy differs considerably from the old economic order, the greatest differences being that digital economy is inherently characterised by a quick turn to virtual reality (virtualisation), the power of digital technologies (digitisation and digitalisation), integration through interconnectivity, promotion of using and sharing knowledge as an immaterial asset by organisations as well as reinforcing the pursuit of innovation.22 So even if digital technologies started to appear already in the middle of the 20th century, it would be unreasonable to talk about their actual development until the second half of the 1990s or even the beginning of the 21st century.23 1.2 Diversity of Digital Technologies Because digital technologies have been developing for many years, it is possible now to distinguish their numerous and diverse kinds. But first, these technologies should be defined. They are generally regarded as any systems, applications, services or tools that employ digital technique and IT systems. Such technologies may be also construed as a type of organisational, technical or economic activity which involves the adaptation of new systems and digital devices to the activity conducted by companies in various segments of the economy or market sectors. Furthermore, they are distinguished by covering all the systems and tools which use digitally encoded content, so mainly by a binary (consisting of the numerals 0 and 1) sequence of digits which may be read by specific electronic devices.24 Digital technologies understood in this manner include not only the Internet and everything that is connected with it (intra– and extranets, virtual communities and organisations, etc.), but also the entire cyberspace or a certain environment which functions on the basis of multiple systems, networks and types of software and which enables an individual or an organisation to engage in diverse activities.25 Digital Transformation of Businesses 9 The term digital technologies is very often used interchangeably and identified with the terms information technologies or information and communication technologies (ICTs).26 It seems, however, that such practice is not justified. This is shown by the fact that ICTs cover only the technologies for collecting, recording, storing, processing, analysing, synthesising, sending and presenting data and information in electronic form, but it is also possible, through them, to create and use multimedia messages, to communicate with other entities or ensure the security of various systems and data.27 In turn, “digital technologies” are a term broader than ICTs, because such technologies refer to any applications, Internet tools or systems which are digital in nature and which are used, for example, to perform procurement, production or distribution processes. Their essence is not simply the collection or processing of certain data and information, but also the operation of many other processes. What both of them have in common is that they are implemented in a digital environment, so their nature and scope may be very broad. In addition, it should be emphasised that digital technologies, as described above, are also perceived as a form of activity whose effect is to introduce modern digital systems to specific areas of the economy. It is worth pointing out that the current transformations, which are related to the increasingly stronger influence of digital technologies to the functioning of states and societies, are described and classified in different ways by various authors. As already mentioned above, such authors as J. Schumpeter would regard such changes as a certain stage or “wave” in the development of the global economy. In the literature, one may encounter, though, many other terms to describe the present state of the economy where digital technologies play an enormous role. Those terms determine how digital technologies are perceived or classified. They include: cyber econ‑ omy, digital economy, information economy, new economy or web economy.28 The terms referring to digital technologies in the world economy have been analysed by M. Goliński with regard to their frequency of appearance in the Internet. The analysis has showed that the most frequently used expressions are new economy, digital economy or industry 4.0.29 Such studies demonstrate that the themes of digit(al) isation and digital technologies, and their impact on the global economy, is very wide‑ranging, which undoubtedly follows from the fact that there are a great many such technologies now and their number is on the increase all the time. At present, it may be quite difficult to attempt to identify or classify these technologies, precisely because of their large number and constant development. What is also greatly important here is that potential areas where these technologies could be used are extended all the time. Furthermore, innovative projects and activities are initiated with the aim to build completely new technologies or integrate ones which have already been used. In spite of all of that, many authors do attempt to distinguish the most important digital technologies which are currently used. According to J. Pieriegud, contemporary digital technologies primarily include: – hyperconnectivity, which will be discussed below at length; – Internet of Things (IoT) and Internet of Everything (IoE) – these terms refer to a global network due to which things, such as household appliances (in the case 10 Digital Transformation of Businesses of IoT) and also human beings and processes (in the case of IoE) may collect, process and share data, for instance, about the manner the things are functioning. – applications based on cloud computing, which is a kind of service entirely provided on a specific server, which makes it unnecessary to purchase and have specialist hardware or software; – systems based on automation and robotisation; – technologies which allow for collecting and analysing big data sets (big data analytics, BDA), including those based on the operation of cloud computing (big‑data‑as‑a‑service, BdaaS); – artificial intelligence (AI), or any technologies and systems making it possible for machines or computer programs to simulate and perform specific operations typical for the human brain; – mobile systems which make it possible to perform specific operations in the Internet in a wireless manner; – modern security systems – assuming the form of both definite products and digital platforms, guaranteeing for users an ever‑increasing level of security; – social media, which allow people to communicate and initiate various interactions as well to share content (e.g. Facebook, Twitter, Instagram, YouTube); – models of multi‑channel and omni‑channel distribution of products and services, where, apart from the traditional channel, some products and services are also offered online.30 It should be emphasised that within the said technologies, many other ancillary digital tools, systems or solutions may be distinguished. So, for example, as far Internet of Things is concerned, it is possible to distinguish some of its types and modifications, such as cyber physical systems (which control, among other things, road traffic, which is possible owing to integration of computational algorithms with physical systems), networked control, machine learning (self‑learning of machines), high performance computing (which refer to Big Data) or embedded systems (which allow for autonomous operation of cars or airplanes).31 Issues concerning digital technologies have been discussed in one study on digital transformation prepared by the European Commission. It stated that apart from Internet of Things, Big Data and robotics, digital technologies which are the most important now and have the greatest impact on the world economy also include blockchain technology (which is used for recording financial operations and is open and transparent without, however, a centralised form), 3D printing and advanced manufacturing (which use systems, devices and machines controlled by computers or microelectronics and used for designing, manufacturing and transporting various products).32 In turn, in a report prepared by UNCTAD (United Nations Conference on Trade and Development), many digital technologies are mentioned and characterised as “frontier technologies for the sustainable development.” These are said to include Internet of Things (IoT), 3D printing, 5G mobile phones, various data sharing technologies, massive open online courses, smart electricity grids and financial transaction systems (e.g. digital wallets or mobile money).33 Digital Transformation of Businesses 11 The analysis made by D. Batorski, E. Bendyk, M. Filiciak and A. Płoszaj lists the most important trends in digital technologies and manifestations of their use in the contemporary world. A list of the most important of those is given in Table 1.1. Among the most important trends which are relevant to digital technologies there are many of those in which the key role is played by digital technology platforms. Such platforms, after all, give grounds for increasing effectiveness of the performance of distribution tasks or globalisation of competition, resulting in, on the one hand, the appearance of completely new opportunities for companies connected with internationalisation of activity conducted by them and acquisition of new outlets for their own products, and on the other, an increase in the level of competition, entailing, among others, a better quality of customer service. Table 1.1 The most important trends in digital technologies according to D. Batorski, E. Bendyk, M. Filiciak and A. Płoszaj Trends in digital technologies Types of digital technologies Autonomysation of customers • Systems for customising the digital offer Cyborgisation • Controlling a smartphone with your voice, which is a manifestation of close coupling of the contemporary human being with various systems, applications and digital devices Network distribution • Digital technology platforms Evolution of business models • SaaS – software as a service, providing an access to the licence authorising to use the software Globalisation of competition • Digital technology platforms Convergence of bits and atoms • 3D printing Convergence of ICT networks • Triple and quadruple play, or broadband and wireless access to the Internet • Internet of Things Mobility • Mobile Internet, smartphones, mobile first strategies, where mobile systems are built first before physical systems Openness as a new business model • Curated computing system, in which the manufacturer renounces control, to a considerable extent, of its products in exchange for cooperation with other companies or users themselves Platformisation • Digital technology platforms Online availability of computing resources • Cloud computing Network of Things (autonomysation of electronic devices) • Monitoring of health condition or condition of household appliances Declining importance of intermediaries • Just‑in‑time system, making it possible to perform deliveries of raw materials and products exactly at the moment when there is demand for them Exchangeability of functions among devices • Home entertainment centres making it possible to use digital content on many different devices Source: D. Batorski, E. Bendyk, M. Filiciak, A. Płoszaj, Cyfrowa gospodarka. Kluczowe trendy re‑ wolucji cyfrowej. Diagnoza, prognozy, strategie reakcji, MGG Conferences, Warsaw 2012, pp. 14–43. 18 Digital Transformation of Businesses case so that the level of the company’s competitiveness or pursuit of innovation might grow fast. When viewed as a process, then, digital transformation should be regarded as a sequence of precisely planned, thought out, coordinated actions, implemented at the level of the entire company, aiming to bring about the situation where digital technologies are effectively deployed in the company, which may contribute to the achievement of competitive advantage and an appropriate degree of innovativeness. In principle, such transformation may be carried out at each stage of a company’s functioning but at present, considering hypercompetition, highly volatile environment and extremely intensive development of digital technologies, it becomes nearly necessary to transform for all the enterprises that still operate in a traditional manner. 1.4 Organisational Changes Accompanying Digitalisation In any case, digitalisation causes many changes of organisational nature. According to W. Dobrowolski and A. Dobrowolska, “scientific and technological progress, especially dynamic as regards IT solutions, has an impact on the changes introduced to the organisation’s processes.”50 First, it should be noticed that in the contemporary world, digitisation has been progressing very quickly. It is proved by data showing that digital technologies are spreading in the world much more intensively than any of the inventions from the industrial age. As an example, it may be observed that while it took 30 years for electricity to reach 10% market penetration in households in the United States, the same process for landline telephones took 25 years, for television sets, mobile phones and personal computers – 10 years, and tablets – merely 2.5 years.51 This shows how fast digitalisation is spreading in the world. And the process actually applies not only to developed countries but also to developing ones. An example can be Vietnam, where computers were launched within 15 years after they were invented, while for mobile phones and the Internet, it was merely a few years.52 What is also significant is that in 2014, for the first time in history, the number of users of mobile devices became higher than the number of desktop computers connected to the Internet. Considering this, various companies to an increasingly larger extent place an emphasis on using the mobile first strategy, where mobile solutions and technologies are implemented first, before those related to brick‑and‑mortar activities.53 The transformations described above have a great impact on the organisational sphere of companies. Digitalisation in companies may take place at an ever‑faster rate due to many various factors. According to D. Andriessen, the most important of these include: – globalisation, which has two kinds of consequences – first of all, it leads to the development of various types of ties and co‑dependencies among states, societies or organisations, which brings about the necessity of their constant cooperation, to a large extent with the use of digital technologies, and furthermore Digital Transformation of Businesses 19 forces those enterprises which want to be competitive to show their uniqueness based on wide‑ranging deployment of intangible resources, such as knowledge and expertise; – gradual deregulation of key sectors of the economy, such as transport, telecommunications or power industry, which results in intensification of global flows of resources and information; – dramatic technology‑related changes which, through the emergence of new information technologies or communication channels (the global mobile phone network, the Internet), lead to a considerable reduction of costs of acquiring, storing, processing or sharing information.54 Fast progress of digitalisation entails changes in company management. According to a report by Capgemini Consulting and the MIT Center for Digital Business,55 organisational changes accompanying digitalisation can be seen in three fundamental areas of a company’s operations. They are presented in Figure 1.5. As for the customer service area, digitalisation allows, primarily, for better understanding and identification of customers’ needs. As a result, responding to these needs becomes effective but also new needs are generated. Furthermore, customer segmentation is performed fully effectively on the basis of the mass of data collected due to digital technologies as well as numerous areas of cooperation created between a company and customers, for example, with regard to the kind of offered products or services or ways of delivering them to locations of consumption, including, for example, digital or self‑service sales.56 With respect to operational processes, as a result of the implementation of digital technologies, the processes are performed more efficiently and completely new functions may be introduced in them. In addition, considerable opportunities are created Figure 1.5 Areas of organisational changes resulting from digitalisation Source: Author’s own work based on A. Sobczak, “Koncepcja cyfrowej transformacji sieci organizacji publicznych,” Roczniki Kolegium Analiz Ekonomicznych 2013, no. 29, p. 280. 20 Digital Transformation of Businesses for implementing some innovations to specific workstations. Such innovations may pertain, in particular, to doing work at any place and time, development of multi‑channel, automatic ways of communication or finally sharing one’s own professional knowledge in the workplace with other company employees, for example via Intranet or articles published in a newsletter.57 Digitalisation also contributes to modifying existing business models or creating entirely new ones. In this respect, such models may function based on a digitally modified activity which focuses on constant expansion of the offering of products and services, changing from physical form of goods into digital form and using digital packaging. What is also important is digital globalisation of activity, which may take place through integrating a company with numerous entities operating on the market and offering by them joint digital services.58 According to M. Goliński, digitalisation causes many transformations in the functioning of companies. First and foremost, these amount to: – considerable increase in the flexibility level of each organisational structure and business processes performed within those structures; – continuously growing effectiveness of such structures, which translates into more effective performance of strategic objectives; – globalisation of conducted activity, supported by gradual removal of organisational or language barriers as a result of using modern digital technologies, including communication technologies; – accelerated speed of responding to changes taking place in the company’s surroundings; – possibility of adjusting the company’s organisational structure exactly to the needs and expectations of not just customers but also any other stakeholders (suppliers, local authorities, society in general), which is in turn conducive to building the so‑called experience economy; – promoting and strengthening the pursuit of innovation on a large scale, at each level of the organisational structure, which becomes possible by generating completely novel consumer needs; – possibility of offering smart products and services in which information component is playing an increasingly greater role; – expansion of the network of business connections; – decrease of the role of human factor in multiple organisational processes, which then makes it possible to reduce the risk of errors made by managers or employees while fulfilling their professional duties; – opportunities for sharing resources with other organisations and business entities (known as sharing economy).59 Digitalisation leads companies to gradual evolution, which follows from the fact that their organisational structures are getting closer and closer to a model typical of the age of knowledge. This is shown in Figure 1.6. Among the most important changes associated with the transformation of a company from a model characteristic of the industrial age to a model of the age of Digital Transformation of Businesses 21 knowledge, the following should be mentioned: considerable streamlining of the organisational structure, focusing on processes rather than functions, and on intangible resources rather than on financial or tangible goods, dominance of teamwork, constant implementation of innovative ideas and initiatives as well as handing over certain management functions to specialised external entities (possibly on the basis of outsourcing). It follows from the above discussion that organisational changes resulting from digitalisation are complex in nature. In turn, they result more than once in a complete metamorphosis of a company’s organisational structure. The aim of such transformation is for the company to use digital technologies effectively, generate innovative ideas and put them into practice and take advantage as far as possible from employees’ skills, abilities and knowledge. 1.5 Impact of Digitalisation on Company Management Apart from the organisational sphere, digitalisation also has a great influence on company management. As emphasised by E. Czyż‑Gwiazda, universal digitalisation […] created opportunities for the emergence of a new digital business model and the birth of the so‑called digital economy. It is digitalisation that determines the contemporary level of operational effectiveness of an organisation and implies deep changes in production systems and management systems of organisations.60 Figure 1.6 Evolution of organisational structures of contemporary companies from a model characteristic of the industrial age to a model of the age of knowledge Source: Author’s own work based on K. Beyer, Od epoki agrarnej…, op. cit., p. 14. 22 Digital Transformation of Businesses According to O. Kohnke, digitisation makes it necessary for company management to consider four major areas. They are as follows: – aligning leadership to increase employees’ participation in company management activities; – mobilising the organisation for action, including mainly to demonstrate innovative attitudes on a large scale; – building capabilities, including digital skills; – ensuring sustainability of a company’s operation, for example, by continuing to improve and modify digital technologies used, aiming to respond to challenges presented by the market more effectively than to date.61 The impact of digitalisation on the management sphere is visible through creating plenty of opportunity for company growth, which thereby entails the nature of company management. Such opportunities, which follows from the conception of creative destruction proposed by Joseph Schumpeter, are provided by innovative (and thus based on digital technologies) activity strictly oriented to customer needs and creating their needs, which is able to bring about collapse of entire industries or economies if they cannot meet the requirements connected with building a digital economy. Due to the above, there is a growth of competitiveness for those companies whose activity is based on digital technologies, which in turn creates wide‑ranging prospects for managing them and directing their development effectively.62 It is worth pointing out that surveys conducted in 2015 by the Global Center for Digital Business Transformation showed that by 2020, as many as 40% of companies could disappear from the following markets as a result of digitalisation: telecommunications, media, entertainment, commercial and financial, in spite of holding strong market positions now. It would be so just because it is precisely those market sectors that are affected most by the changes associated with the implementation of cutting‑edge technologies.63 Digitalisation is furthermore conducive to intensive deployment of modern technological solutions and their integration, which is manifested, for instance, by hyperconnectivity,64 or omnipresent connectedness.65 This term has been used for the first time by Canadians, A. Quan‑Haase and B. Wellman. These authors noticed that in the contemporary economy, enormous numbers of interactions are initiated and, what is significant, they do not refer to people only (P2P – people‑to‑people), but also, more and more often, people and machines (P2M – people‑to‑machine) or even machines themselves (M2M – machine‑to‑machine). This way, the discussed hyperconnectivity takes place, with tools such as online messengers, mobile phones, e‑mail or Web 2.0 services.66 This omnipresent connectivity makes it easier to manage a company. It happens because at present, it takes a few minutes or even seconds to get in touch with a person staying several thousand kilometres away and furthermore the opportunity to build long‑term business relations using communication technologies allows for obtaining data and information about the most effective ways to manage a company. Besides, many barriers connected with space, time, technology, languages or industries are disappearing, which creates Digital Transformation of Businesses 23 nearly unlimited opportunities for managing an organisation. It is not irrelevant, either, that digitalisation entails full automation of information exchange and creates conditions for developing completely new business models, innovative in organisational, technological, social or cultural terms, based on a combination of modern digital technologies.67 It should be emphasised that new technologies make it necessary for management to be based to a great extent on a simply enormous amount of various kinds of data and information. They are needed to get indispensable knowledge, which is the foundation for the operation of modern organisations and which makes it possible to manage contemporary companies on the basis of building and reinforcing the pursuit of innovation, creativity and entrepreneurship.68 As already mentioned in one of the preceding sections, digitisation brings along a considerable volatility of conditions in which various companies operate. One of the results of this as far as the management sphere is concerned is that in order to measure organisational results, it is necessary now to use much more complex and comprehensive ratios than those used several decades ago or even between ten and twenty years ago. Such ratios have to cover not only financial indicators but also those which are able to measure intangible values, including those connected with knowledge.69 Here, however, digitalisation not just creates additional problems concerning measurement of results but furthermore provides entirely new possibilities in this area. It is a fact, after all, that, for example, big data systems create ample opportunity for collecting nearly unlimited amount of data to perform complex measurements on them.70 Managing a digital enterprise, compared to a traditional organisation, has to a much greater degree strategic and social character. This means being oriented not just strictly to the operational or internal sphere of the organisation but being based on establishing broad relations with various stakeholders. Such relations may aim, for instance, at cooperation in the area of performing complex, advanced, innovative projects or sharing specific digital technologies. Thus, digitalisation make company management to become increasingly open to influences from the outside.71 Under the influence of digitalisation, management undergoes a major evolution with regard to marketing. Considering a wide access of society to digital technologies, including also the elderly, as well as a variety of available marketing forms, managing a digital enterprise in the sphere of marketing must be based on possibly most widespread activities. It is important that these activities should be carried out all the time, even 24 hours a day (this is possible, for example, with online advertisements), should be addressed to all groups of consumers, should use on a large scale all types of digital technologies (mobile apps, social media, cloud computing), exploiting their interactive nature. Furthermore, these activities should convey as much content as possible, providing information not only about specific features of a product or service but also about added value or smart offers.72 This is shown in Figure 1.7. Managers are significantly affected by changes resulting from digitalisation. This is because the implementation of digital technologies forces them to acquire completely new competences and to change their approach to many issues in the area of management. It is characteristic in that regard that digitalisation causes 24 Digital Transformation of Businesses each manager to act in a decentralised and flexible manner, adjusting leadership strategies to make it possible to ensure the highest level of innovation, to get the full innovation potential out of their employees and to use digital technologies as effectively as possible. In addition, a modern manager is obliged to establish and support the functioning of teams or working projects and to use new media to communicate with employees.73 What plays an enormous role is also providing employees with the opportunity to take an active part in the performance of management tasks and making decisions of key importance from the perspective of ensuring the appropriate level of innovativeness and effectiveness.74 According to W. Gonciarski, changes in the sphere of management following from digitisation amount to the construction of the so‑called management 2.0 (new generation management). Such management is based on multi‑aspectual use of digital technologies. The fundamental features of such management include: – limiting hierarchical structures in favour of flexible, networked and decentralised and flattened systems; – using more and more complex digital technologies within management of relations within the organisation and those which concern external stakeholders; – attaching overriding importance to resources which are intangible in nature; – transferring a major part of an enterprise to a virtual level, continuing, however, its activity in the real zone; Figure 1.7 Key aspects of marketing in a digital company Source: Author’s own work based on W. Świeczak, “Wpływ współczesnych technologii na zmianę działań marketingowych w organizacji. Marketing 4.0,” Marketing Instytucji Naukowych i Badawczych 2017, no. 26, p. 183. Digital Transformation of Businesses 25 – focusing attention of the environment, including customers and their needs; – dispersed leadership based on limitation of directive power of managers and promotion of multifaceted cooperation and use of collective intelligence; – acting both on a global and local scale; – continual implementation of modern solutions in the area of knowledge and AI management to adjust to ever changing conditions in the environment; – constant search for innovative business models due to which it is possible to use cutting‑edge solutions in management.75 Issues of the impact of digitalisation on the sphere of company management have been discussed in a synthetic manner by K. Jasińska. The author singles out manifestations of the impact in the context of each function of management. They are discussed in Table 1.2. Table 1.2 Impact of digitalisation on various management functions Management function Impact Monitoring • Strong determination to ensure self‑monitoring of managers and employees • Putting an emphasis on monitoring effectiveness of the performance of each process • Monitoring resources, taking into consideration growth possibilities and based on feedback received from employees Motivating • Reinforcing any attitudes promoting innovation by rewarding them with bonuses • Promoting a management style based on building a leader position • Motivating in order to build new competences, including digital skills Organising • Implementing a flat organisational structure • Orientation towards performing processes generating specific values • Organisational culture promoting the pursuit of innovation • Constant development of new business models • Risk taking • Implementing structures and solutions in the area of knowledge management and automation • Building structures making it possible to acquire, store and process data to create value • Sharing information and messages in an interactive manner • Pro‑active decision‑making Planning • Formulating plans on the basis of continuous observation of the situation in the environment • Analysing many alternative solutions • Short‑term planning for projects being performed • Taking digitalisation into consideration in the company’s strategy • Ensuring the opportunity to modify plans • Allowing for improvisation in planning Source: K. Jasińska, “Konsekwencje cyfryzacji gospodarki dla systemu zarządzania przedsiębiorstwem z sektora IT,” [in:] J. Gajewski, W. Paprocki, J. Pieriegud, eds., Cyfryzacja gospodarki i społeczeństwa. Szanse i wyzwania dla sektorów infrastrukturalnych, Instytut Badań nad Gospodarką Rynkową – Gdańska Akademia Bankowa, Gdańsk 2016, pp. 100–101. 26 Digital Transformation of Businesses Finally, one may describe as an example a company whose way of management was completely redirected as a result of using digital technology. The company’s name is Nike. Management there is at present strongly oriented towards digitalisation and in principle most or perhaps even all the management decisions are strongly dependent on the use of modern digital technologies. This can be seen primarily in management decisions about marketing (promoting products by initiating a global dialogue about healthy lifestyle or sports events, obtaining information on customers and their preferences from the company’s activity in social media), customer service (customers may design the colour of footwear on their own), sales (numerous digital products, such as sport bands which allow for monitoring running parameters but also taking advantage of a virtual trainer’s advice and making data on running achievements available to others) or distribution (online channel). For Nike, digitalisation changed completely the management philosophy, as a result of which the company’s activity may be conducted in a much more innovative and complex manner than before.76 Summing up, it should be observed that the essence of company management through digitalisation is aiming directly, first, to have any processes and actions performed in a most efficient, coordinated and effective manner, using any available digital technologies, and also, second, to create, also with the use of these technologies, the grounds for establishing broad cooperation with any stakeholders. Such management places an emphasis on innovativeness, which thus generates the need for a completely new approach compared to the traditional model to issues connected with managing employees or contacts with the environment. Notes 1 E. Brynjolfsson, A. McAfee, The Second Machine Age. Work, Progress, and Prosperity in a Time of Brilliant Technologies, W. W. Norton Company 2014, p. 9. 2 A. Łaszek, E‑rozwój. Cyfrowe technologie a gospodarka, Forum Obywatelskiego Rozwoju, Warsaw 2018, p. 6. 3 J. Pieriegud, “Cyfryzacja gospodarki i społeczeństwa – wymiar globalny, europejski i krajowy,” [in:] J. Gajewski, W. Paprocki, J. Pieriegud, eds., Cyfryzacja gospodarki i społeczeństwa. Szanse i wyzwania dla sektorów infrastrukturalnych, Instytut Badań nad Gospodarką Rynkową – Gdańska Akademia Bankowa, Gdańsk 2016, pp. 11–38. 4 F. Wåhlin, S. Karlsson, Digital Strategies and Strategic Alignment. The Existence of Digital Strategies and their Alignment with Business Strategies for Small and Medium‑ sized Swedish Manufacturing Firms, Lund University, Lund 2017, p. 18; J. Pieriegud, op. cit., p. 12. 5 R. Wachal, “Humanities and Computers. A Personal View,” North American Review 1971, vol. 256, no. 8, pp. 30–33. 6 Digitisation, https://www.gartner.com/it‑glossary/digitisation/ [accessed 3 October 2019]. 7 N. Nakicenovic et al., The Digital Revolution and Sustainable Development. Opportu‑ nities and Challenges. Report Prepared by the World in 2050 Initiative, International Institute for Applied Systems Analysis, Laxenburg 2019, pp. 8–9. 8 E.V. Ustyuzhanina, A.V. Sigarev, I.P. Komarova, E.S. Novikova, “The Impact of the Digital Revolution on the Paradigm Shift in the Economic Development,” Espacios 2017, vol. 62, no. 38, p. 5. Digital Transformation of Businesses 27 9 M. Becla, “Nowe trendy i wyzwania w transferze wiedzy z sektora nauki do biznesu w polskiej gospodarce,” Studia Prawno‑Ekonomiczne 2015, no. 94, p. 220. 10 K. Beyer, “Od epoki agrarnej po gospodarkę opartą na wiedzy,” Studia i Prace Wydziału Nauk Ekonomicznych i Zarządzania Uniwersytetu Szczecińskiego 2012, no. 30, p. 13. 11 B. Mikuła, Wprowadzenie do gospodarki i organizacji opartych na wiedzy, [in:] B. Mikuła, A. Pietruszka‑Ortyl, A. Potocki, eds., Podstawy zarządzania przedsiębiorstwami w gospodarce opartej na wiedzy, Wydawnictwo Difin, Warsaw 2007, pp. 20–21. 12 K. Schwab, The Fourth Industrial Revolution, World Economic Forum, Geneva 2016, p. 30. 13 M. Olender‑Skorek, “Czwarta rewolucja przemysłowa a wybrane aspekty teorii ekonomii,” Nierówności Społeczne a Wzrost Gospodarczy 2017, no. 3, p. 38. 14 J. Growiec, The Digital Era, Viewed from a Perspective of Millennia of Economic Growth, Szkoła Główna Handlowa, Warsaw 2018, p. 7; N. Nakicenovic et al., op. cit., p. 8; M. Xu, J.M. David, S.H. Kim, “The Fourth Industrial Revolution: Opportunities and Challenges,” International Journal of Financial Research 2018, vol. 9, no. 2, p. 91. 15 M. Olender‑Skorek, op. cit., p. 41. 16 N. Nakicenovic et al., op. cit., p. 8. 17 M. Xu, J.M. David, S.H. Kim, op. cit., p. 90. 18 Digital Revolution, https://www.techopedia.com/definition/23371/digital‑revolution [accessed 8 October 2019]. 19 M. Götz, J. Gracel, “Przemysł czwartej generacji (industry 4.0) – wyzwania dla badań w kontekście międzynarodowym,” Kwartalnik Naukowy Uczelni Vistula 2017, no. 1, p. 221. 20 R.D. Atkinson, “Why Is the Digital Information Revolution so Powerful,” [in:] R.D. Atkinson, D.D. Castro, eds., Digital Quality of Life: Understanding the Personal and Social Benefits of the Information Technology Revolution, Information Technology and Innovation Foundation, Washington 2008, p. 8. 21 M. Goliński, “Gospodarka cyfrowa, gospodarka informacyjna, gospodarka oparta na wiedzy – różne określenia tych samych zjawisk czy podobne pojęcia określające różne zjawiska?” Roczniki Kolegium Analiz Ekonomicznych Szkoły Głównej Handlowej 2018, no. 49, pp. 184–185; E. Radomska, “Rozwój gospodarki cyfrowej i społeczeństwa cyfrowego w aspekcie dynamicznych zmian w otoczeniu zewnętrznym na przykładzie Wielkiej Brytanii,” Myśl Ekonomiczna i Polityczna 2019, no. 1, pp. 121–122. 22 D. Tapscott, The Digital Economy. Rethinking Promise and Peril in the Age of Net‑ worked Intelligence, Mc Graw Hill Education, New York – London – Sydney 2015, pp. 56–77. 23 J. Growiec, op. cit., p. 7. 24 https://sjp.pwn.pl/slowniki/cyfrowy.html [accessed 8 October 2019]. 25 J. Wasilewski, “Zarys definicyjny cyberprzestrzeni,” Przegląd Bezpieczeństwa Wewnętrznego 2013, no. 9, pp. 232–233. 26 Por. S. Łobejko, “Strategie cyfryzacji przedsiębiorstw,” [in:] R. Knosala, ed., XXI Kon‑ ferencja Innowacje w Zarządzaniu i Inżynierii. Materiały konferencyjne, vol. 2, Polskie Towarzystwo Zarządzania Produkcją, Zakopane 2018, pp. 641–642. 27 A.W. Tomaszewska, “Dostęp do technologii informacyjno‑komunikacyjnych w społeczeństwie informacyjnym. Przykład polskich regionów,” Acta Universitatis Lodziensis. Folia Oeconomica 2013, no. 290, pp. 25–26. 28 J. Unold, “Basic Aspects of the Digital Economy,” Acta Universitatis Lodziensis. Folia Oeconomica 2003, no. 167, p. 42. 29 M. Goliński, op. cit., p. 179. 30 J. Pieriegud, op. cit., s. 11; see also: A. Ghosh, D. Chakraborty, A. Law, “Artificial Intelligence in Internet of Things,” CAAI Transactions on Intelligence Technol‑ ogy 2018, vol. 3, no. 4, pp. 208–218; L. Wang, C.A. Alexander, “Big Data Analytics and Cloud Computing in Internet of Things ”, American Journal of Information 34 Digital Technology Platforms 2.2 Properties of Digital Technology Platforms Each DTP, in view of the scope and nature of conducted activity, may have distinct characteristics. It is a fact, though, that about a dozen features may be found which are common to all DTPs. These common properties will be discussed at this point. First, the properties should be mentioned which are inextricably connected with digital economy and which therefore may be extended also to the sphere of the operation of DTPs. These properties include: Table 2.1 The most important definitions of digital technology platforms according to R. Sun, B. Keating and S. Gregor Definition authors Year of formulating the definition Digital technology platform Banker 2011 A website that allows participants to perform certain trading practices Basole 2009 Multi‑sided market that brings together various types of market participants Ceccagnoli 2012 The set of components used in common across a product family that can be extended by new applications Fichman 2004 A general‑purpose technology that includes a variety of applications Heitkotter 2012 A combination of hardware, operating systems and app store Markus and Loebbecke 2013 A tool supporting business processes which may be simultaneously used by multiple companies Meyer and Seliger 1998 A set of subsystems that form a common structure from which derivative products can be efficiently developed and produced Rai et al. 2006 A platform which enables real‑time transfer of information between various applications and functions that are distributed across partners Richardson 2014 A tool for building a business infrastructure that shapes the capacity of companies to launch competitive actions Saarikko 2014 A core of fixed set of attributes that can be extended and supplemented with applications and functionalities to the benefit of its users Shaw and Holland 2010 A structural solution which makes it possible to support development of some phenomena Tan et al. 2015 Two‑sided markets, which brings together two distinct sides (interacting partners) allowing them to benefit from network effect Taudes et al. 2000 A software package that enables the realisation of certain systems and applications Tiwana 2015 “A technological foundation” with various interfaces used by extensions that interoperate with it Giessmann and Stanoevska 2012 A set of technologies that are developed and evolve in certain systems Source: R. Sun, B. Keating and S. Gregor, op. cit., p. 5. Digital Technology Platforms 35 – being strictly based on digital components; – putting a heavy emphasis on innovativeness, flexibility and effectiveness; – hyperconnectivity concerning all the entities and elements of a DTP; – combination of elements of traditional and digital economies in many aspects (for example, co‑existence within a DTP distribution channel based on brick‑and‑mortar facilities and an online channel), in many cases it being impossible to demarcate the two areas precisely; – being innovative; – disappearance of many barriers, including spatial and temporal ones; – nearly unlimited development opportunities; – intensification of business relations; – use of cutting‑edge technologies; – great importance of knowledge; – correlation and convergence of many areas in which the economy and various enterprises function, including mostly IT technology, telecommunications and digital content; – development and deployment of novel, innovative business models; – ensuring maximum benefits to any stakeholders; – a consumer quite often acting as a manufacturer; – work and integration in a network; – automated information sharing; – molecularisation as a result of which DTPs are developed whose application is restricted to a relatively narrow scope of activity (for example, platforms for start‑ups operating in a specific market sector).35 The fact should be emphasised that all the said properties traditionally assigned to digital economy are also characteristic for DTPs. This is so since their operation involves first of all integration and coordination of activities of many diverse entities, with key importance being acquired by the use of cutting‑edge technologies or business models. This implies that DTPs are based on innovativeness and operational flexibility, that within them there is a large‑scale promotion of processes of searching, collecting and disseminating knowledge on various areas of human activity and that they lead to intensification of business relations and, furthermore, they are developed to reduce various types of barriers. One document prepared by the European Commission lists five basic characteristics of online platforms. They include: – the ability to create and shape new markets, to challenge traditional ones, which is possible due to collecting, processing and editing large amounts of data; – operation in multi‑sided markets but with each platform exercising varying degrees of control over users; – benefiting from “network effect,” which may be reinforced, for example, by an increase in the number of users; – strict reliance on cutting‑edge technologies to be able to reach their users instantly; – playing a key role in digital value creation, which is achieved by initiating new business ventures and reinforcing strategic dependencies.36 36 Digital Technology Platforms The discussed document focuses to a large extent on those properties of online platforms which are connected with their operation within specific markets. This is because such platforms may even contribute to the development of entirely new markets. A perfect example in this respect are online marketplaces, therefore online markets, where it is possible to perform buying and selling transactions and which are regarded as one of the most important type of a DTP.37 Among properties of the platforms which may be pointed out is the their functioning on many markets (many platforms have a global character, which is exemplified by Skype) and also taking advantage, due to establishment of various connections among participants, of the network effect, which contributes to the creation of digital values, resulting, for example, from innovations. One of the most significant properties of all DTPs is the fact that they are highly complex tools, systems or technologies consisting of many diverse elements. In the previous section, it was mentioned that DTPs bring together stakeholders within a certain ecosystem. Figure 2.1 presents basic layers and elements of such an ecosystem. A business ecosystem, around which DTPs usually operate, is made up of various layers, including the environment consisting of many diverse entities. They include, for example, customers, suppliers or research institutions supporting the Figure 2.1 Components of a business ecosystem Source: Author’s own work based on A. Lipińska, op. cit., p. 48. Digital Technology Platforms 37 operation of platforms with technical knowledge and an innovative approach to performing processes. The construction of a business ecosystem shows it clearly that DTPs are very developed and complex systems, in which frequently an enormous number of entities participate. For this, examples may be provided by auction services, such as Allegro or eBay, which bring together millions of entrepreneurs, suppliers and private users. It should be observed here, though, that a business ecosystem, discussed in the context of DTPs, is made up of not only certain entities which collaborate within the platforms but also refers to any add‑ons in the form of, say, applications which are provided to the platform by some organisations.38 Construed in this manner, a business ecosystem within a DTP becomes an even more complex system which has a really enormous number of components. Considering that DTPs operate on the basis of business ecosystems, many properties may be indicated which are typical for such ecosystems. Apart from a large number of stakeholders and numerous connections among them, they are also characterised by: – sharing various resources, mainly knowledge and technology, by those stakeholders, while maintaining, though, a high level of competitiveness (this is known as co‑opetition, or cooperative competition); – members of a DTP play specific roles, and each change of position of one element in the system affects the remaining ones; – dynamic structure, constantly changing under the influence of market conditions or social needs, as a result of which ecosystems may evolve and develop on the basis of modern technologies; – possibility of competing with other ecosystems; – multi‑directional and complex interaction with the environment, which refers to the sphere of politics, technology, market or human resources.39 These properties may be also assigned to DTPs. After all, these platforms provide access to various technologies and related knowledge to be shared by participants, cause the participants to play strictly defined roles (e.g. sellers, suppliers and buyers, as in auction systems, or teachers and students, as in e‑learning platforms), and DTPs are subject to large amount of interaction with the environment (this can be seen, for example, in the possibility of co‑creating specific functionalities of platforms by users) and DTPs constantly develop, using cutting‑edge technologies, due to which they can compete with other platforms effectively. What definitely distinguishes DTPs is also the possibility of continuing improvement and expansion with newer and newer functionalities and elements. This feature is emphasised in many definitions of DTPs.40 M. de Reuver, C. Sørensen and R. C. Basole described the above possibility as openness of a DTP.41 In this context, T. Saariko stated accurately that the architecture of any platform, including a DTP, is made up of a stable core, which is relatively nearly invariable, and many complements or add‑ons, which are characterised by high variety. This causes each platform to be highly flexible.42 38 Digital Technology Platforms The discussed property of DTPs is very significant because due to it is becomes possible to ensure a high degree of innovativeness of their operation, which follows from the fact that they are constantly improved using most recent technologies. This way, they are able to respond effectively to continuously changing requirements and needs of customers as well as market or industry transformations. In addition, H. LeHong, C. Howard, D. Gaughan and D. Logan observed that the discussed openness may refer to the following five perspectives connected with the operation of a DTP: – an infrastructure and operations perspective, including data centres or cloud computing; – a data management and retention perspective; – a security and risk perspective; – a comprehensive integration strategy, which assumes maximum flexibility to support shifting market or business demands; – outsourcing or cloud sourcing guidelines, which may assume a broad combination of internal and external resources and services received from various partners.43 Analysing fundamental properties of DTPs, it is also worth drawing attention to the proposals by R. Sun, B. Keating and S. Gregor about the most important dimensions of these platforms, and therefore also their components. These dimensions are presented in Table 2.2. In addition, it gives examples of alternative terminologies relative to these dimensions, used by other authors. The fundamental features of a DTP may be described taking into consideration the dimensions distinguished in Table 2.2. The one which appears to be the leading dimension is the so‑called technological base, which entails both openness and complexity of DTPs and related add‑ons or standards, as well as interoperability, transactionality and platform governance. Each of these dimensions is part of every DTP, so the existence of such dimensions is one of the key distinguishing features of such platforms, which makes them distinct from, for example, IT or ICT systems. To recapitulate the issues discussed in this section, it should be stressed that DTPs have many characteristic properties. Some of them follow directly from the manner of operating of the entire digital economy (e.g. innovativeness, hyperconnectivity, unlimited development opportunities, disappearance of many barriers, creation of new business models) or business ecosystems (sharing specific resources by DTP users, playing by them various roles, a dynamic structure). Others concern furthermore large complexity, openness, interoperability, transactionality and platform governance. In view of such a great number of properties, DTPs should be regarded as systems or tools strongly developed technologically which are constantly improved and have a considerable impact on the contemporary economy as a whole. These issues will be discussed in more depth in the further part of the chapter. Digital Technology Platforms 39 2.3 Typology of Digital Technology Platforms At present, a huge number of DTPs are available on the market. For this reason, it is impossible to list all of their kinds. A description of the most important typologies connected with DTPs will be presented below. One of such classification is that proposed by to H. LeHong, C. Howard, D. Gaughan and D. Logan It is presented in Figure 2.2. Table 2.2 Dimensions of digital technology platforms according to R. Sun, B. Keating and S. Gregor Dimension Description Alternative terminology Technological base • Foundation which allows for using various add‑ons, as a result of which DTPs are technologies used over long term • Set of components • General‑purpose technology • Extensible code base • Core fixed set of attributes • Core products or services • Common architecture, resource or structure Add‑ons • A software extension to the technological base to add functionality of a DTP • Applications, distributed applications • Complementary extensions (elements, products), including modules • Associated components • Plug‑ins • Complementors offering products or services complementary to the offer of a DTP Interoperability • The ability to interact between a technological base and add‑ons • Real‑time connectivity • Ways of connecting Standards • Design rules that allow programmers to access a DTP on the same terms and conditions, which is especially important for effective integration of add‑ons with the technological base • A set of rules • Platform or programming interfaces Transactionality • Possibility of performing certain transactions on a DTP, such as buying and selling, which supports interests of platform users • Interactions • Transactions Governance • Structures, principles, policies, mechanisms, communication and relation models or license agreements involved in managing a DTP • Coordination • Platform management • Transparency Source: R. Sun, B. Keating, S. Gregor, op. cit., p. 6. 40 Digital Technology Platforms According to the authors, DTPs may be divided into five types, with the division being based on the criterion regarding main areas of application of DTPs, or customers, partners, employees and things. It is typical that each kind of a DTP operates in all of the above areas, although obviously the scope of operation is different depending on a particular platform. The kind of platforms which participate to a greatest extent in each of the areas are data and analytics platforms, which is connected with the fact that they enable information management and analysis, and thus effective decision‑making based on available data. Another kind of DTPs are customer experience platforms, which are strongly oriented to consumers by offering them access to applications dedicated to them or omni‑channel distribution systems. Ecosystem platforms make it possible to create systems external to a DTP for cooperation with other entities and their integration, while information systems platforms are solutions due to which it is possible to control certain entities, including with the use of such systems as, for example, ERP (enterprise resource planning). The last kind of a DTP distinguished by H. LeHong, C. Howard, D. Gaughan and D. Logan is Internet of Things (IoT) platforms. They are used to combine resources, systems and physical devices to monitor, control and optimise their operation.44 A slightly different classification of DTPs was proposed in one publication by Oxera, a consulting firm. The classification is based on surveys performed by the firm in many European countries, including France, Germany, Spain and Poland, Figure 2.2 Classification of digital technology platforms according to H. LeHong, C. Howard, D. Gaughan, D. Logan Source: Author’s own work based on H. LeHong, C. Howard, D. Gaughan, D. Logan, op. cit., p. 3. Digital Technology Platforms 41 among 6,000 consumers (including 1,502 from Poland). The surveys were about the level of use of digital platforms by consumers as well as related benefits or concerns.45 The above classification of DTPs is presented below: – communication platforms – platforms for communication among various entities; – information platforms – platforms for obtaining and sharing all sorts of information; – comparison platforms – platforms for comparing various products or services; – entertainment platforms – platforms for accessing and sharing content used for entertainment; – online marketplaces – platforms for entering into buying or selling transactions.46 A still different typology of DTPs was presented by A. Kosieradzka and K. Rostek. This typology distinguishes four types of platforms, which are restricted to “technology platforms accessible via web browsers”: – communication platforms – aiming to support group decisions; – analytics and communication platforms – make it possible to make decisions aiming to, for example, increase a company’s competitiveness; – integration and information platforms – used mainly in the area of data and information analysis; – platforms for solving problems and perform tasks with the use of knowledge and potential of external entities.47 Issues connected with types of DTPs were discussed in a slightly more limited manner by A. Gawer. She listed only three types. They are described in Table 2.3. According to A. Gawer, technology platforms, including digital ones, include internal platforms, operating within one company, platforms operating within one supply chain as well as those defined as industrial ones. The differ from one another, in principle, in all components and aspects, starting from the level of use, up to coordination mechanisms or innovations. One common element regarding their construction may be nevertheless found. This is architecture, which is modular, making it possible to attach to the core (technological base) further elements, such as modules or applications. R. G. Fichman distinguished four basic types of DTPs. These are as follows: computer platforms (for example, operating systems dedicated to mobile devices, such as Android), infrastructural platforms (wireless networks), corporate application platforms (for example, ERP) and platforms for programming (Java).48 In turn, according to K. Mohanty, various DTPs which are claimed to be earmarked primarily to deliver technology‑based services for business, may be divided into: social media platforms (Facebook, Twitter, Instagram, Pinterest), which are used by companies to advertise their products and services and establish relations with stakeholders, remaining advertising platforms, including Google or various blogs, cloud computing platforms (for example, Microsoft Azure or Amazon Web Services), offering data storage or hosting, as well as platformy in the form of 42 Digital Technology Platforms separate e‑commerce business models, such as Amazon or eBay, making it possible to buy products without leaving home.49 DTPs may be also divided into types on the basis of relations that take place between participants of activities in the digital environment, including e.g. within e‑business. This way, platforms may be distinguished where the following types of relations occur: – B2B (business‑to‑business) – “classic” relationships on the market between two enterprises; – B2C (business‑to‑consumer or business‑to‑client) – relations concerning DTPs, which make interactions between enterprises and consumers possible; – B2G (business‑to‑government) – relations between enterprises and public administration (platforms for tenders or public procurement); – C2C (customer‑to‑customer) – transactions between consumers using platforms in the form of auction systems and portals; – C2B (customer‑to‑business) – relations between consumers and enterprises, initiated by the former (for instance, comparison‑shopping websites); – C2G (customer‑to‑government) – transactions between citizens and public administration performed through public platforms for taxes or social insurance; – G2C (government‑to‑citizen) – flow of administrative information between offices and citizens; Table 2.3 Kinds of technology platforms according to A. Gawer Platform dimensions Internal platforms Supply‑chain platforms Industry platforms Architecture • Modular construction • Core and add‑ons Access to innovations • Wide • Innovations within a supply chain • Potentially unlimited Interface • Closed – accessible to platform users but not to external entities • Selectively open, therefore accessible only within a supply chain • Open for all Coordination mechanisms • Strictly defined governance hierarchy • Contractual relationships within a supply chain • Ecosystem governance Level of use • Enterprise • Supply chain • Industrial ecosystems Entity establishing the platform • One enterprise and its subcontractors • Supply‑chain members • Platform leader and complementors Examples • Black and Decker (production of tools) • Sony (production of electronics) • Boeing (production of airplanes) • Renault – Nissan (production of cars) • Apple (mobile technology) • Facebook (social portal) • Google (search engine) Source: A. Gawer, “Bridging Differing Perspectives on Technological Platforms: Toward an Integrative Framework,” Research Policy. Elsevier 2014, vol. 43, no. 7, p. 1244. Digital Technology Platforms 43 – G2B (government‑to‑business) – flow of economic information between offices and enterprises; – G2G (government‑to‑government) – relations between public administration authorities making it possible for them to coordinate internal processes.50 It should be added that at present DTPs most often concern initiation and intensification of B2B, B2C, C2C and C2B relationships, therefore between consumers and enterprises. It is a fact, though, that increasingly faster development can be observed also with respect to platforms for communication between citizens and enterprises on the one hand and public administration on the other. Examples of these are platforms operating in Poland, e.g. ePUAP (Electronic Platform of Public Administration Services), PUE ZUS (Electronic Service Platform of the Social Insurance Company) or CEIDG (Central Registration and Information on Business).51 A decisive majority of B2B, B2C, C2C or C2B platforms operate within e‑commerce, which T. Wallace regards as applications allowing enterprises conducting activity in the Internet to manage websites, sales and marketing, in addition offering integration with traditional business tools.52 The United Nations also prepared its own classification of DTPs. It considered a gradual development of the platforms, dividing it into three basic periods, which also entails three kinds of DTPs. This is depicted in Figure 2.3. As shown in Figure 2.3, the gradual dissemination of digital platforms in the world began with the emergence of mainframe computers, which, as already mentioned, took place in the 1960s. The stage lasted to the second half of 1980s and the beginning of the 1990s, when personal computers were invented and started to be commonly used, as well as the Internet, which the UN considers as the second type of digital technologies. That made it possible to build more developed digital platforms. The third platform growth stage, which started in the beginning of the second decade of the 21st century and is ongoing, when mobile technologies began to be ubiquitous and more and more solutions appeared such as big data analytics, the Internet of Things, cloud services or social media, allowing for promotion of innovative business models and services. Importantly, combined use of digital technologies and platforms is now possible, which gives rise to completely new opportunities, not only just to individual users or enterprises but also the public sector and social organisations. What should be also emphasised is that whereas at the first stage of development, DTPs were used by several millions of people, at the second and third stages, the number of users reached hundreds of millions and several billions of users respectively. This demonstrates an unusually intensive growth of DTPs.53 The classifications of DTPs presented above are undoubtedly general in nature. Others concentrate on singling out more specific platforms from the classification, applying for that various kinds of criteria. So, for example, in the report by Aleo and Deloitte, quoted above, platforms were selected which are used in the performance of procurement processes, known as source‑to‑settle platforms. Such procurement platforms include: 50 Digital Technology Platforms Global DTPs play dominant roles not just in the market of technology platforms but in general in the entire world economy. This is shown by the data presented in Table 2.5. Among the ten most valuable brands in the world which affect the word economy to the greatest extent, the four leading positions are held by companies offering DTPs, while the sixth position is taken by Amazon. Those brands generate just enormous revenues. In 2018, the total revenues were 714 billion dollars, with profit of 135.5 billion dollars, which means profitability of approximately 19%. Such results show that revenues of the “digital giants” are higher by USD 100 billion than what the Polish economy is able to produce on an annual basis, while the profits alone would be sufficient to cover all the expenditures of the Polish budget.79 The technologies implemented by “Big Tech” are without any doubt decisive about the level of development and innovativeness in the world economy. It should be observed that the brands are growing intensively all the time, which can be seen from the fact that in the years 2016–2017, they recorded increase in value of 10% (Apple) up to over 50% (Amazon). In this context, it should be added that the biggest DTPs achieve their unusually strong position at the cost of enterprises from other industries. It is equally relevant that the document entitled “Polityka Rozwoju Sztucznej Inteligencji w Polsce na lata 2019–2027” (“Policy for the Development of Artificial Intelligence in Poland for 2019–2027”), which is at present a draft for social consultation, stressed that during several recent decades, with lightning speed, a new economic reality unfolded, where the key role is no longer played by raw materials, workforce or even financial capital but by knowledge or intangible assets. For example, oil companies and car manufacturers disappeared from the leading positions on the list of the most valuable companies in the world, replaced by corporations operating digital platforms, whose major assets are invisible but affect the assessment of the value of each of them.80 Table 2.5 The most valuable brands in the world in 2017 according to Forbes’ report Rank Brand Brand value (in USD billion) 2017/2016 growth (as %) Revenues (in USD billion) Industry 1 Apple 170.0 10 214.2 Technology 2 Google 101.8 23 80.5 Technology 3 Microsoft 87.0 16 85.3 Technology 4 Facebook 73.5 40 25.6 Technology 5 Coca‑Cola 56.4 −4 23.0 Beverages 6Amazon 54.1 54 133.0 Technology 7 Disney 43.9 11 30.7 Entertainment 8 Toyota 41.1 −2 168.8 Motor industry 9 McDonald’s 40.3 3 85.0 Catering 10 Samsung 38.2 6166.7 Technology Source: M. Lewicki, “E‑handel w Polsce – stan i perspektywy rozwoju,” Handel Wewnętrzny 2018, no. 4, p. 177. Digital Technology Platforms 51 This is correct and shows a quickly increasing role of DTPs in today’s economy. Here, however, it must be noted that ever more important roles are played in the global DTP market by brand different from “Big Five.” They are primarily companies with registered offices in China, including Alibaba, Tencet and the like. As shown by the data presented in Graph 2.1, they have already begun to hold ranks just below “Big Tech” in terms of capitalisation. In addition, an intensive growth in the share of Chinese brands in the capitalisation can be seen. In 2018, the share was already 40%, while it was 48% for American companies, but with a decrease by 15% compared to 2017.81 The data show that even though US companies continue to dominate in the global DTP market, they may nevertheless gradually face an increasingly growing competition from Chinese brands. It Is necessary still to stress that the global market of DTPs is not made up of commercial solutions only but also of those which use a great contribution from the public sphere and entities operating there. Good examples are European technology platforms and Polish technology platforms (ETPs and PTPs, respectively).82 They will be discussed in detail in the next section. It should be noted that what is conducive to promoting such platforms is the policy carried out in many countries. This is also true for Poland. In this area, it is possible to invoke provisions of the Future Industry Platform Foundation (“Fundacja Platforma Przemysłu Przyszłości”) Act83 (the foundation will be further also referred to as the FIPF). Those provisions envisage the establishment of the Foundation to support digital transformation of enterprises, which is to be performed with reference to processes or products which use cutting‑edge achievements from the areas of ICT technology, artificial intelligence, automation or human‑machine communication. The main tasks of the FIPF include: to increase entrepreneurs’ awareness how to use modern digital technologies, to support purchases of innovative technological solutions or data sharing systems and to initiate international cooperation for promoting the use of digital technology. Between 2019 and 2018, over PLN 236 million is to be earmarked for the activities carried out by the Foundation.84 These activities will also include initiatives for supporting the development of DTPs. Furthermore, what should be mentioned is the Programme entitled “From Paper Poland to Digital Poland,” were plenty activities have been specified for the development of DTPs in the public sphere. These activities are to be performed in five basic areas, concerning, among others, the development of digital competences in the public sector, provision of secure and convenient access to online public services and acceleration of the development of modern telecommunications infrastructure. The performance of the Programme involves, for example, continued modernisation and increasing the functionality of digital public platforms, such as PUE ZUS or ePUAP.85 Finally, it should be noticed that intensive growth of DTPs makes it necessary to introduce new regulations or amendments to laws. This follows from the increasingly higher impact of the platforms on various enterprises and consumers, and consequently also on entire markets and economies. Significantly, the impact does not have to be positive; very often, it also has adverse consequences. These include unfair trade practices, such as: 52 Digital Technology Platforms – imposition by a DTP unfair conditions on users regarding mainly access to databases; – unilateral introduction by a DTP of amendments to conditions of access to digital market or even effective prevention of such access, which also includes access to significant commercial data; – playing a double role by platforms by facilitating access to market for other entities and simultaneously competing with them, which may lead to excessive promotion of the platforms’ products or services; – application of unfair equality clauses within the operation of DTPs; – a lack of transparency regarding tariffs applied by platforms, the extent to which they use users’ data or search results, which may entail losses for suppliers.86 In response to such type of problems, Regulation (EU) 2019/1150 of the European Parliament and of the Council of 20 June 2019 on promoting fairness and transparency for business users of online intermediation services was adopted and published in 2019.87 The regulation applies to about 7,000 enterprises operating online, including primarily digital sales platforms, application stores, social media services and shopping comparison websites.88 The key provisions include statements about fair treatment of all users of a DTP by formulating terms and conditions of using the platforms, taking into account requirements for, among others, plain and intelligible language, ready accessibility at all stages of commercial relations with a supplier or consideration of the effect of the terms and conditions on the control of intellectual property rights vested in users.89 Similarly important are also provisions about vendors of DTP services which are obliged to inform users about the extent of access to personal data90 and to ensure an internal system for handling users’ complaints.91 The said regulation demonstrates that the situation on the global market of DTP is very dynamic and constantly changes. Transformations concern not only amendments to law but also types and character of offered systems, technologies, applications or online tools. Although such systems or technologies are developed by many diverse enterprises, the decisive impact on the global DTP market is exerted by the so‑called “Big Five,” or Google, Amazon, Facebook, Apple and Microsoft. In the coming years, the situation will completely change, in connection with the constant strengthening of the position of the corporations on the digital market, which offer more and more platforms and functionalities operating within them and additionally get involved in other segments of the market. It is worth pointing out that these companies show increasingly higher activity in the financial market, offering their users access to personal accounts through online communication platforms (WhatsApp for Facebook or Messenger by Microsoft).92 However, the growing role of Chinese brand should not be overlooked. The global DTP market is first and foremost the five biggest players, or “Big Tech.” It is important that the market is more and more bringing about a situation which may be referred to as platform economy or online platform economy.93 This shows the constantly growing dependence of the world economy on DTPs. Digital Technology Platforms 53 Additionally, in the years to come, the global DTP market may undergo a far‑reaching evolution. Even now, a strong tendency may be observed for DTPs to be based on an approach where designing is of utmost importance. Such an approach, based on the combination of business strategy and design thinking, makes it possible, first of all, to effectively build and develop business ecosystems as well as wide‑ranging implementation of innovations, better understanding of customers’ needs, placing an emphasis of cooperation, continuing experimentation and achievement of high flexibility level.94 2.5 Fields of Application and Achieved Benefits DTPs may be employed in many diverse areas in which enterprises and the economy function. There seems to be simply an unlimited number of such areas now. This follows from the fact that ever newer DTPs appear all the time in the market, therefore the potential scope of their application in business practice continues to grow. Based on the typologies of DTPs presented in the previous section, it may be stated that the platforms are applicable in all business processes performed both inside an enterprise (production, internal transport, storage, information and document flow, human resource management, including training) as well as in the external environment (relations with stakeholders, cooperation within supply chains, sharing data and documents, procurement, sales of products and services on various markets, operation of distribution channels). According to A. Kosieradzka and K. Rostek, the key uses of contemporary digital platforms include operational management (access to knowledge, initiating and intensifying collaboration with other enterprises and scientific or consulting institutions, intermediation in technology sharing) and inter‑organisational management (benchmarking of groups of companies, identification of training needs and organisation of relevant training courses and programmes, organisational learning).95 In addition, DTPs perform activities, among others, in the area of education (e‑learning platforms) and entertainment or in the public sector (PTP). With regard to the operation of enterprises, R. Kapur indicates in particular that digital platforms allow for creating digital jobs, and thus digital organisations. In addition, such platforms may relate to such areas as: communication, cooperation, inter‑organisational ties, information management strategies (collecting, analysing and monitoring information and data), roles and duties of organisation members, training and certification, crisis management, policy regarding innovations and increasing operational flexibility and efficiency, recruitment of employees.96 U. Dolata conducted an analysis of the most important fields of application of DTPs in relation to the functioning of the “digital giants,” or Apple, Amazon, Facebook, Google and Microsoft. The areas are presented in Table 2.6. The fields of application of the biggest DTPs in the world as presented above naturally do not exhaust all the areas. A greater number of those may be given, for example, for Google or Facebook platforms, they are marketing and advertising. The list of uses of DTPs in Table 2.6 aims to demonstrate in how many aspects of human activity and the business sphere such platforms may be used. 54 Digital Technology Platforms What shows a very wide applicability of DTPs is the practice of implementing ETPs and PTPs, as mentioned above (in the EU – since 2003, in Poland – since 2004). These platforms are a great joint project of the European Commission, the industry, scientific and financial institutions, decision‑making groups and the society to prepare development strategies for sectors of the economy important for Europe and technologies of the future. The initiatives are aimed to concentrate the efforts of key European partners to perform these strategies in the form of large scientific and technological projects. Technology platforms are expected to play a major role in the activation of research ideas and financial resources at the European level. One of the main tasks of the platforms is to be establishment of effective public and private partnership for the implementation of the developed strategies.97 Both European and Polish technology platforms form associations of “practically all the key innovative firms in Poland in priority sectors for the economy,”98 making Table 2.6 Fields of application of DTPs using opportunities offered by the biggest technological companies in the world Platforms Fields of application Elements and functionalities of platforms Apple • Media, entertainment • App Store, iTunes Store, music streaming • Mobile technologies • iPhone, iPad, iPod, iOS operating system, Safari Mobile web browser • Software and corporate equipment • Apple‑IBM systems • Cloud computing • iCloud • Smart solutions • Internet of Things (Apple Car) • Artificial intelligence • Turi Create Amazon • Digital sales • Amazon.com, Zappos.com • Media, entertainment • Lovefilm.com, AmazonGames.com, Prime Instant Video • Mobile technologies • Kindle (e‑book reader), Fire Phone • Cloud computing • Amazon Web Services Facebook • Media, entertainment • Instagram (photography) • Communication • WhatsApp • Software, virtual reality • Oculus VR Google • Media, entertainment • YouTube, Google Books, Google+ social portal, Picasa (photography) • Application stores • Google Play • Mobile technologies • Browsers Chrome and Chromecast, Android operating system • Smart solutions • Internet of Things (smart home and car) Microsoft • Media, entertainment • LinkedIn social network, Xbox console • Communication • Outlook, Skype • Mobile technologies • Nokia, Bing Source: U. Dolata, op. cit., pp. 12, 14. Digital Technology Platforms 55 it possible for them to take joint actions to perform innovative projects, including also in the area of implementing DTPs. At present, in the territory of Poland, several dozen technology platforms are operating and their functioning covers many diverse fields. The following areas should be listed: – new technologies having impact on radical transformation of sectors – nanoelectronics, hydrogen fuel and fuel cells; – new technologies for manufacturing products and services – wireless and mobile technology, innovative medications; – sustainable development – biotechnology, water supply; – strategic sectors of the economy – aeronautics; – traditional industrial sectors in the context of their development, modernisation and structuring – steel.99 Table 2.7 lists PTPs operating in the territory of Poland. There are 30 of them altogether. Polish technology platforms are implemented within several fundamental areas, including energy, transport or biotechnology. It might be thought that it is just those areas that have been regarded in Poland as the most important from the perspective of using digital technologies and platforms, development factors for the economy. It should be noted that in the activities concerning PTPs, a very large number of entities participate including enterprises, scientific and research institutes or higher education institutions. It is a fact that all the PTPs may be classified as DTPs as they exploit digital technologies on a large scale, enabling them to establish cooperation between platform participants and to implement innovative solutions. It should be added that ETPs and PTPs strongly support activities which contribute to (sustainable) development of the economy of the European Union. In this context, they should be associated with Europe 2020 Strategy,100 where three mutually reinforcing priorities were put forward. In principle, each of them may be related to the system of building ETPs and PTPs because they describe kinds of growth: – smart growth – developing an economy based on knowledge and innovation; – sustainable growth – promoting a more resource efficient, greener and more competitive economy; – inclusive growth – fostering a high‑employment economy delivering social and territorial cohesion.101 Within ETPs and PTPs, it is crucially important to support any projects which are innovative in nature. Within the projects, the most important thing is to promote specific organisational solutions, systems or tools, including IT systems or tools, which aim to improve effectiveness and efficiency of the operation of enterprises conducting activity in various sectors as well as to reinforce cooperation between diverse entities. The effect is achievement of sustainable growth objectives referred to in Europe 2020 Strategy – owing to ETPs and PTPs, technologies may be 56 Digital Technology Platforms Table 2.7 Types of PTP operating in Poland Thematic area Types of PTPs Coordinators Aims of activity Security Work Safety in Przemyśl Central Institute for Labour Protection – National Research Institute (CIOP PIB) To increase work safety by implementing modern technologies Internal Security University of Białystok Automated voice recognition and text processing technologies Security Systems Military University of Technology Promotion of new technologies for security Biotechnology, agriculture, medicine Biotechnology Jagiellonian Centre of Innovation (JCI) Development of bioprocesses, production of biomaterials Innovative Medicine Pomeranian Medical Academy in Szczecin Supporting innovations in the production of new medicines Forest and Wood Sector Wood Technology Institute (ITD) Increase competitiveness and effectiveness of the sector Environment Institute for Ecology of Industrial Areas (IETU) Supporting projects for the protection of natural environment Food University of Warmia and Mazury in Olsztyn Development of new technologies for food production Energy Biofuels and Biocomponents Automotive Industry Institute (PIMot) Introduction of biofuels in Poland Nuclear Technologies National Centre for Nuclear Research (NCBJ) Performance of projects in the area of nuclear energy Hydrogen and Fuel Cells Industrial Chemistry Institute (ICP) Promoting hydrogen technology Sustainable Energy Systems and Pure Carbon Energy Institute of Heat Technology at Warsaw University of Technology Development of energy and fuel sector Metals Non‑ferrous Metals Institute of Non‑ferrous Metals Performance of research projects in the industry of non‑ferrous metals Founding Founding Institute Development of founding technologies Steel Institute of Ferrous Metallurgy Development of steel industry IT technologies Photonics PCO S.A. Development of the photonics sector Opto– and Nanoelectronics Central Technical Organisation (NOT) Performance of research and projects in the areas of opto – and nanotechnology (Continued) Digital Technology Platforms 57 implemented which allow for generating and using knowledge effectively, reducing resources necessary to perform production processes and also to create new jobs in sectors in which innovations are generated on a large scale. An example may be a European technology platform “Smart Grids” (ETP SmartGrids). Its major aim is to develop and disseminate a technology to make Table 2.7 (Continued) Thematic area Types of PTPs Coordinators Aims of activity IT Technologies Polish Chamber of IT Technology and Telecommunications Implementation of innovative IT technologies Mobile Technology and Wireless Communication MOST Foundation Development of mobile and wireless technologies Transport Smart Transport Systems Motor Transport Institute (ITS) Development of smart transport Systems Aviation WSK “PZL – Rzeszów” Construction of new generation engines Space Technologies Space Research Centre of the Polish Academy of Sciences (CBK PAN) Development of new technologies for space activities Road Transport Road and Bridge Research Institute (IBDiM) Construction of electric cars and cars powered by alternative fuels Track Transport Warsaw University of Technology Production of new track vehicles Water Transport Maritime Advanced Research Centre (CTO) Development of water transport infrastructure Advanced materials Construction ASM Market Research and Analysis Centre Development of the construction sector Production Processes Wrocław University of Science and Technology Development of cutting‑edge machines and devices Textile Industry Łódź University of Technology Development of the textile sector Advanced Materials Institute of High‑Pressure Physics of the Polish Academy of Sciences (Unipress, IWC PAN) Supporting innovative solutions in the automotive, aviation and defence industry Sustainable Chemistry Polish Chamber of Chemical Industry Development of technology of chemical materials Source: A. Siemaszko, M. Snarska‑Świderska, “Polskie Platformy Technologiczne,” [in:] A. Bąkowski, M. Mażewska, eds., Ośrodki innowacji i przedsiębiorczości w Polsce. Raport 2012, Polska Agencja Rozwoju Przedsiębiorczości, Warsaw 2012, pp. 169–172; B. Szumiec‑Presch, Utworzono nowe polskie platformy technologiczne, http://laboratoria.net/aktualnosci/_item,3691,print,1.html [accessed 28 November 2019]; http://7pr.kpk.gov.pl/ppt/ppt.html‑id=815.htm [accessed 29 November 2019]. 58 Digital Technology Platforms it possible to supply electricity or, more broadly, to provide energy services, to consumers, using digital technology. In this respect, tools are tested and introduced within SmartGrids allowing for bi‑directional energy flows as well as integration of dispersed sources, including those based on renewable resources. Due to this, it is possible to generate large savings, to ensure greater operating effectiveness of electricity systems (they are more resistant to failures) as well as to promote technologies which reduce greenhouse gas emissions (photovoltaic panels, small wind turbines or small hydroelectric power plants). This way, sustainable growth objectives are achieved, including those concerning environmental protection or innovativeness, effectiveness and competitiveness of enterprises.102 Describing fields of application of DTPs, it is also worth presenting data about to what extent such platforms are used within each sphere of enterprises’ operation. Relevant data come from, among other sources, a survey performed in 2013 by Amarach Research and Deloitte on a sample of 201 decision‑makers working in the IT sector in Poland (Graph 2.2). In Polish companies, needs for using modern technologies, including DTPs, are satisfied the most in such areas as customer service (high and very high satisfaction level was declared by 37% of respondents), efficiency (32%), costs (31%) and vendor management (29%), while they are satisfied the least in employee training (low or very low satisfaction level was indicated by 56% of respondents), recruitment management (51%) or supply chain management (41%). The data show that digital technologies in Poland are used mainly to perform sales, procurement or customer service processes, while these technologies, therefore also DTPs, are needed most for human resources management. The wide range of using DTPs in the modern economy follows mostly from the fact that they generate many benefits. In one regulation of the European Commission and of the Council, it is stressed that Graph 2.2 Level of using digital technologies to meet needs of Polish enterprises according to a 2013 survey by Amarach Research and Deloitte Source: Cyfrowa przyszłość Polski…, op. cit., p. 46. Digital Technology Platforms 59 [o]nline intermediation services are key enablers of entrepreneurship and new business models, trade and innovation, which can also improve consumer welfare and which are increasingly used by both the private and public sectors. They offer access to new markets and commercial opportunities allowing undertakings to exploit the benefits of the internal market. They allow consumers in the Union to exploit those benefits, in particular by increasing their choice of goods and services, as well as by contributing to offering competitive pricing online, but they also raise challenges that need to be addressed in order to ensure legal certainty. […] Online intermediation services can be crucial for the commercial success of undertakings who use such services to reach consumers.103 Thus, DTPs, create grounds not only for growth of enterprises, offering them access to new markets, but also contribute to improvement of consumers’ welfare by, for example, allowing them to purchase specific products or services at competitive prices. Considering that the use of a DTP in many cases is associated with performing in enterprises system transformation, benefits generated due to the platforms largely result just from such transformation. It is mostly connected with: – transformation of business processes which became completely digitised, making it possible to manage human resources more effectively, make better decisions, intensify cooperation with various entities and increase employee participation; – redefinition of business models in which the major role begins to be played by development of digital products, extending activity to more and more markets in the world and also building new distribution channels shared by many entities; – increasing effectiveness of customer service by gaining deeper insights on consumers, including their needs for products and services.104 E. J. Altman and M. L. Tushman indicated two main aspects of using DTPs. First, they allow for a considerable growth of interdependence among entities operating on the market, which includes all kinds of relationships, such as B2B or B2C. Second, the platforms, because of their openness, may be modernised and updated all the time, which in turn cause them, on the one hand, to group more and more programmers and users, contributing to the construction of business ecosystems, and on the other, to be continuously adjusted to ever changing market requirements or customers’ needs. Thus, their operation is constantly optimised so that they are modern and be able to compete effectively with other IT systems or tools. This provides users with many benefits, including access to cutting‑edge technologies.105 R. Telles broadly referred to the potential benefits that may be associated with the use of online platforms, including in the context of the above‑mentioned sharing economy. According to him, the use of DTPs leads to the development of the 66 Digital Technology Platforms 7 M. Kulka, op. cit., p. 4. 8 D.A. Myślak, “Telewizja cyfrowa i jej cyfrowe pochodne a oczekiwania współczesnego odbiorcy,” Media, Kultura, Komunikacja Społeczna 2017, no. 1, pp. 31–55. 9 B. Twardowski, SaaS: Zmieniamy podejście z lokalnych rozwiązań na platformy usługowe, https://www.erp‑view.pl/it_solutions/saas_zmieniamy_podejscie_z_lokalnych_rozwiazan_na_platformy_uslugowe.html [accessed 30 October 2019]. 10 Digitalisacja rynku B2B. Cyfrowe platformy zakupowe – raport Aleo i Deloitte, Aleo – Deloitte, Warsaw 2017. 11 B. Gregor, A. Łaszkiewicz, M. Stawiszyński, “Obszary generowania wartości przez wirtualne platformy wymiany handlowej w sektorze B2B ma tle doświadczeń operatorów platform w Polsce,” Studia i Materiały Polskiego Stowarzyszenia Zarządzania Wiedzą 2009, no. 21, p. 22. 12 K. Wyrwińska, M. Wyrwiński, “Platformy internetowe jako narzędzia ekonomii współdzielenia,” Transformacje Prawa Prywatnego 2018, no. 2, pp. 91–112. 13 Cf. R. Sun, B. Keating, S. Gregor, op. cit., p. 2. 14 T. Saarikko, An Inquiry into the Nature and Causes of Digital Platforms, Department of Informatics Umea University, Umea 2016, p. 11. 15 M.A. Cusumano, “Platforms Versus Products: Observations from the Literature and History,” [in:] S. Kahl, B. Silverman, M.A. Cusumano, eds., Advances in Strategic Management, Emerald Group Publishing, Bingley 2012, p. 36. 16 L.D.W. Thomas, E. Autio, D.M. Gann, “Architectural Leverage: Putting Platforms in Context,” Academy of Management Perspectives 2015, vol. 28, no. 2, pp. 199–201. 17 Such an approach may be found in the following studies: Digitalisacja rynku B2B…, op. cit., p. 3; R. Sun, B. Keating, S. Gregor, op. cit., pp. 1–2. 18 P. Constantinides, O. Henfridsson, G. Parker, op. cit., p. 1. 19 Technology Platforms from Definition to Implementation of a Common Research Agenda, European Commission, Luxembourg 2004, p. 15. 20 M. Kulka, op. cit., p. 4. 21 M. de Reuver, C. Sørensen, R.C. Basole, op. cit., p. 5. 22 W. Pisarek, ed., Słownik terminologii medialnej, Towarzystwo Autorów i Wydawców Prac Naukowych Universitas, Kraków 2006, p. 147. 23 L. Morgan, F. Hintermann, M. Vazirani, Five Ways to Win with Digital Platforms, Accenture, Dublin 2016, p. 8. 24 D. Corin Stig, op. cit., p. 17. 25 H. LeHong, C. Howard, D. Gaughan, D. Logan, op. cit., p. 4. 26 R. Sun, B. Keating, S. Gregor, op. cit., p. 5. 27 C. Busch, G. Dannemann, H. Schulte‑Nölke, A. Wiewiórkowska‑Domagalska, F. Zoll (Research Group on the Law of Digital Services), “Discussion Draft of a Directive on Online Intermediary Platforms,” Journal of European Consumer and Market Law 2016, no. 5, p. 164. 28 K. Wyrwińska, M. Wyrwiński, op. cit., p. 97. 29 R.G. Fichman, “Real Options and IT Platform Adoption: Implications for Theory and Practice,” Information Systems Research 2004, no. 15, p. 132. 30 A. Faber, F. Matthes, F. Michel, Digital Mobility Platforms and Ecosystems. State of the Art Report, Technical University of Munich, Munich 2016, p. 2. 31 Ibid., p. 2. 32 A. Lipińska, “Koncepcje i kluczowe czynniki rozwoju ekosystemów startupów,” Studia Ekonomiczne. Zeszyty Naukowe Uniwersytetu Ekonomicznego w Katowicach 2018, no. 351, p. 48. 33 A. Siemaszko, Platformy technologiczne w Polsce, Akademickie Mazowsze 2030, Warsaw 2012, p. 11. 34 B. Gregor, A. Łaszkiewicz, M. Stawiszyński, op. cit., p. 22. 35 M. Goliński, op. cit., pp. 181–182. Digital Technology Platforms 67 36 Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions. Online Platforms and the Digital Single Market. Opportunities and Challenges for Europe. Brussels, 25 May 2016, https://eur‑lex.europa.eu/legal‑content/PL/ TXT/?uri=CELEX%3A52016DC0288 [accessed 12 November 2019], pp. 2–3. 37 Cf. S. Kirchner, E. Schüßler, “The Organisation of Digital Marketplaces: Unmasking the Role of Internet Platforms in the Sharing Economy ”, [in:] G. Ahrne, N. Brunsson, eds., Organisation Outside Organisation, Cambridge University Press, Cambridge 2018, p. 131. 38 M. de Reuver, C. Sørensen, R.C. Basole, op. cit., p. 5. 39 A. Lipińska, op. cit., p. 49. 40 For example: T. Saarikko, op. cit., p. 11; M. de Reuver, C. Sørensen, R.C. Basole, op. cit., p. 5; R. Sun, B. Keating, S. Gregor, op. cit., p. 5. 41 M. de Reuver, C. Sørensen, R.C. Basole, op. cit., p. 5. 42 T. Saarikko, op. cit., p. 15. 43 H. LeHong, C. Howard, D. Gaughan, D. Logan, op. cit., p. 4–5. 44 Ibid., p. 4. 45 Benefits of Online Platforms, https://www.oxera.com/getmedia/84df70f3‑8fe0‑4ad1‑ b4ba‑d235ee50cb30/The‑benefits‑of‑online‑platforms‑main‑findings‑(October‑2015). pdf.aspx?ext=.pdf [accessed 14 November 2019]. 46 Ibid., pp. 2–3. 47 A. Kosieradzka, K. Rostek, “Koncepcja platformy komunikacyjno‑usługowej dla struktur sieciowych,” [in:] R. Knosala, ed., XXI Konferencja Innowacje w Zarządzaniu i Inżynierii. Materiały konferencyjne, vol. 1, Polskie Towarzystwo Zarządzania Produkcją, Zakopane 2015, p. 462. 48 R.G. Fichman, op. cit., p. 132. 49 K. Mohanty, Trends in Digital Technology Platform, https://www.tutorialspoint.com/ articles/trends‑in‑digital‑technology‑platform [accessed 14 November 2019]. 50 C. Combe, Introduction to e‑Business, Management and Strategy, Routledge, Amsterdam – Boston – Heidelberg – London – New York – Oxford – Paris 2006, p. 67. 51 E. Chilmon, “Administracja publiczna wymyślona na nowo,” IT w Administracji 2013, special issue, pp. 8–11. 52 T. Wallace, The State of Ecommerce Platforms in 2018. Cloud Commerce, Open SaaS and The API Economy, https://www.bigcommerce.com/blog/ecommerce‑platforms/ [accessed 18 November 2019]. 53 A. Bárcena, A. Prado, M. Cimoli, R. Pérez, op. cit., p. 29. 54 Digitalisacja rynku B2B…, op. cit., p. 10. 55 K. Wyrwińska, M. Wyrwiński, op. cit., p. 97. 56 A. Adamski, Media w analogowym i cyfrowym świecie. Wpływ cyfrowej rewolucji na rekonfigurację komunikacji społecznej, Dom Wydawniczy Elipsa, Warsaw 2012, pp. 40–41. 57 M. Odlanicka‑Poczobutt, S. Olko, M. Kramnich, op. cit., p. 18. 58 Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions. Online Platforms and the Digital Single Market. Brussels, 6 May 2015, https://eur‑lex.europa.eu/ legal‑content/PL/ALL/?uri=celex%3A52015DC0192 [accessed 18 November 2019], p. 12. 59 Benefits of online platforms…, op. cit., p. 3. 60 N. Khan, A. Noraziah, E.I. Ismail, M.M. Deris, “Cloud Computing. Analysis of Various Platforms,” International Journal of E‑Entrepreneurship and Innovation 2012, vol. 3, no. 2, p. 51. 61 T. Bartuś, “Rozpoznanie wybranych ofert rynku cloud computing,” Studia Ekonom‑ iczne. Zeszyty Naukowe Uniwersytetu Ekonomicznego w Katowicach 2016, no. 270, 68 Digital Technology Platforms pp. 10–11; P. Sroczkowski, Cloud. Iaas v Paas v Saas v Daas v FaaS v DBaas, https:// brainhub.eu/blog/cloud‑architecture‑saas‑faas‑xaas/ [accessed 20 November 2019]. 62 H. Elmeleegy, Y. Li, Y. Qi, P. Wilmot, M. Wu, S. Kolay, A. Dasdan, “Overview of Turn Data Management Platform for Digital Advertising,” Proceedings of the VLDB Endow‑ ment 2013, vol. 11, no. 6, pp. 1138–1139. 63 https://www.erp24.pl/rynek‑it‑swiat/5‑kluczowych‑systemow‑big‑data‑na‑swiecie. html [accessed 20 November 2019]. 64 Ł. Piecuch, “Platformy e‑learningowe,” Edukacja – Technika – Informatyka 2010, no. 2, pp. 234–235. 65 A. Kędzierska‑Szczepaniak, “The Initiatives Supported by Reward‑Based Crowdfunding in Poland,” Management Sciences 2018, vol. 23, no. 4, pp. 19–20. 66 D. Howcroft, B. Bergvall‑Kareborn, “A Typology of Crowdwork Platforms,” Work, Employment and Society 2018, no. 1, pp. 21–23. 67 G. Parker, M. Van Alstyne, A Digital Postal Platform. Definitions and a Roadmap, MIT Sloan School of Management, Boston, MA 2012, pp. 6–7. 68 Cyfrowa Polska, McKinsey&Company – Forbes, Warsaw 2016, p. 20. 69 Klient w świecie cyfrowym, PwC, Warsaw 2016, p. 16. 70 Cyfrowa przyszłość Polski. Fundamenty rozwoju konkurencyjnej gospodarki w dobie cyfryzacji, Amarach Research – Deloitte, Warsaw 2018, p. 56. 71 C. Busch, G. Dannemann, H. Schulte‑Nölke, A. Wiewiórkowska‑Domagalska, F. Zoll, op. cit., p. 164. 72 https://www.forbes.pl/wiadomosci/w‑2017‑roku‑mniej‑aplikacji‑i‑rozwoj‑platform‑ cyfrowych/h4fnkcp [accessed 20 November 2019]. 73 K. Mohanty, op. cit. 74 S. Galloway, The Four: The Hidden DNA of Amazon, Apple, Facebook, and Google, Corgi Books, London 2018, p. 1. 75 R. Milic‑Czerniak, “Rola fintechów w rozwoju innowacji finansowych,” Studia BAS 2019, no. 1, p. 41. 76 U. Dolata, Apple, Amazon, Google, Facebook, Microsoft: Market Concentration – Competition – Innovation Strategies, Universität Stuttgart, Stuttgart 2017, p. 5. 77 N. Smyrnaios, Internet Oligopoly. The Corporate Takeover of Our Digital World, Emerald Publishing, Bingley 2017. 78 S. Stodolak, Cyfrowy feudalizm. Internetem zawładnęło pięciu gigantów, https://forsal. pl/artykuly/1421723,cyfrowy‑feudalizm‑internetem‑zawladnelo‑pieciu‑gigantow.html [accessed 20 November 2019]. 79 Ibid. 80 Polityka Rozwoju Sztucznej Inteligencji w Polsce na lata 2019–2027. Godna zaufania sztuczna inteligencja, autonomia i konkurencja, draft for social consultation, https:// www.gov.pl › attachment [accessed 20 November 2019], p. 11. 81 https://forsal.pl/artykuly/1225653,najwieksze‑firmy‑na‑swiecie‑apple‑amazon‑ tencent‑alibaba.html [accessed 20 November 2019]. 82 A. Siemaszko, op. cit., p. 11; https://www.kpk.gov.pl/?page_id=11408 [accessed 20 November 2019]. 83 Journal of Laws of the Republic of Poland (Dz.U.) of 2019, Item 229. 84 Article 1 Section 1–2 and Article 32 Section 1 of the Act on the Industry of the Future Platform Foundation (‘Fundacja Platforma Przemysłu Przyszłości’) of 17 January 2019. 85 Program “Od papierowej do cyfrowej Polski” – najważniejsze informacje i aktualny status prac, https://www.gov.pl/web/cyfryzacja/dokumenty33 [accessed 20 November 2019], pp. 5, 20. 86 Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions. Online Platforms and the Digital Single Market..., op. cit., p. 14. Digital Technology Platforms 69 87 OJ UE L 186 of 11 July 2019. 88 https://businessinsider.com.pl/wiadomosci/relacje‑biznesowe‑na‑rynku‑platform‑ cyfrowych/684sxbm [accessed 20 November 2019]. 89 Article 3(1) of Regulation (EU) 2019/1150 of the European Parliament and of the Council. 90 Article 9(1) of Regulation (EU) 2019/1150 of the European Parliament and of the Council. 91 Article 11 of Regulation (EU) 2019/1150 of the European Parliament and of the Council. 92 M. Ciesielski, Firmy technologiczne wchodzą na rynek finansowy bocznymi drzwiami, https://m.interia.pl/innowacje/news,nId,2660442 [accessed 20 November 2019]. 93 Item 2 of Regulation (EU) 2019/1150 of the European Parliament and of the Council. 94 N. Ismail, Digital Platforms Emerging as a Critical Business Building Block – Gartner, http://www.information‑age.com/digital‑platforms‑emerging‑critical‑business‑ 123465429/ [accessed 20 November 2019]. 95 A. Kosieradzka, K. Rostek, op. cit., p. 458. 96 R. Kapur, Significance of Digital Technology, https://www.researchgate.net/publica‑ tion/323829721_Significance_of_Digital_Technology [accessed 27 November 2019], pp. 2–4. 97 https://www.kpk.gov.pl/?page_id=11408 [accessed 28 November 2019]. 98 A. Siemaszko, op. cit., p. 11 99 https://www.kpk.gov.pl/?page_id=11408 [accessed 28 November 2019]. 100 Communication from the Commission Europe 2020. A strategy for smart, sustainable and inclusive growth, Brussels, 3.3.2010, https://ec.europa.eu/eu2020/pdf/1_PL_ ACT_part1_v1.pdf. [accessed 14 April 2021]. 101 Europe 2020, p. 5. 102 J. Malko, H. Wojciechowski, “Europejska platforma technologiczna sieci inteligent‑ nych ‘SmartGrids’,” Instal 2009, no. 12, pp. 1–4. 103 Items (1) and (2) of the preamble to Regulation (EU) 2019/1150 of the European Par‑ liament and of the Council. 104 S. Locken, The Definitive Guide to the Business Benefits of Digital Transformation, https://www.edialliance.com/blog/the‑definitive‑guide‑to‑the‑business‑benefits‑ of‑digital‑transformation [accessed 2 December 2019]. 105 E.J. Altman, M.L. Tushman, Platforms, Open/User Innovation, and Ecosystems. A Strategic Leadership Perspective, Harvard Business School, Cambridge 2017, pp. 11–12. 106 R. Telles, “Digital Matching Firms. A New Definition in the “Sharing Economy” Space,” ESA Issue Brief 2016, no. 1, pp. 3, 11–15. 107 E.G. Anderson, G.G. Parker, B. Tan, “Platform Performance Investment in the Presence of Network Externalities ”, Information Systems Research 2014, no. 1, pp. 152–156. 108 E. Brousseau, T. Penard, “The Economics of Digital Business Models: A Framework for Analyzing the Economics of Platforms,” Review of Network Economics 2007, vol. 6, no. 2, pp. 82–93. 109 Digitalisacja rynku B2B…, op. cit., p. 6. 110 B. Gregor, A. Łaszkiewicz, M. Stawiszyński, op. cit…, pp. 22, 27–28. 111 A. Kosieradzka, K. Rostek, op. cit., pp. 467–468. 112 Examining the Impact of Technology on Small Business. How Small Business Use Social Media and Digital Platforms to Grow, Sell and Hire, https://www.uschamber. com/sites/default/files/ctec_sme‑rpt_v3.pdf [accessed 2 December 2019], p. 3. 113 Ibid., pp. 3, 7. 114 K. Mohanty, op. cit. 115 The Post‑Digital Era Is Upon Us. Are You Ready for What’s Next? Accenture Technology Vision 2019, Accenture, Dublin 2019, pp. 10–15. 70 Digital Technology Platforms 116 The Foundation is to support digital transformation of Polish companies, among other things, in the area of artificial intelligence, see Article 1 of the Act on the Industry of the Future Platform Foundation. 117 Założenia do strategii AI w Polsce. Plan działań Ministerstwa Cyfryzacji (‘Assumptions for the AI Strategy in Poland. Action Plan of the Ministry of Digital Affairs’), Ministerstwo Cyfryzacji, Warsaw 2018, pp. 33–34. 118 B. Kiljan, RankBrain – sztuczna inteligencja w wyszukiwarce Google, https://mobiletry.com/blog/rankbrain‑sztuczna‑inteligencja‑w‑wyszukiwarce‑google [accessed 10 December 2019]. 119 T. Pielas, O rozwiązaniach AI, o których marketerom się nawet nie śniło, https://aibusiness.pl/o‑rozwiazaniach‑ai‑o‑ktorych‑marketerom‑sie‑nawet‑nie‑snilo/ [accessed 10 December 2019]. 120 https://hematoonkologia.pl/aktualnosci/news/id/3545‑nowa‑polska‑platforma‑ze‑ sztuczna‑inteligencja‑moze‑wykrywac‑nowotwory‑juz‑na‑wczesnym‑etapie [accessed 10 October 2019]. 121 S. Bhattacharya, B. Czejdo, R. Agrawal, E. Erdemir, “Open Source Platforms and Frameworks for Artificial Intelligence and Machine Learning,” [in:] IEEE Southeast‑ Con 2018, Tampa Bay 2018, pp. 2–3. 122 K. Mohanty, op. cit. 123 M. Ciesielski, op. cit. 124 Alphabet is a conglomerate set up by Google in 2015. DOI: 10.4324/9781003473022-4 3.1 Business Model – Theoretical Approach The term of key importance for the discussion in this monograph is “business model.” It is therefore necessary to examine it in depth to isolate its most important aspects from the point of view of innovativeness and the use of digital communication platforms. First, the very term “model” should be defined. One of the basic definitions was formulated by J. Zieleniewski. The author stressed the fact that a model is a theory which allows for acquiring knowledge about the environment and also for using reasoning in which values of particular variables are changed to verify the impact of such operations on the remaining variables. In a model, it is important to manipulate diverse variables which are part of it. This way, a model becomes useful for the application of specific theoretical solutions to practical matters.1 According to B. Glinkowska, a model may be examined from two basic perspectives – structural and functional. Adopting the first perspective, the model is a construct with the use of which a certain object is represented, either real or abstract one. Therefore, such an approach stresses that a model has an instrumental function, demonstrating an object by revealing its specific characteristics. The functional perspective, in turn, emphasises that a model is a construct which in the course of cognitive operations and experiments replaces a specific real object.2 Z. Martyniak distinguishes three possible senses of the term “model.” First, it may be perceived as a theory consisting of a set of statements which may be found to be true. In this meaning, a model may be not as much as a theory but also a supplement to or simplification of a theory. In the second sense, a model is a specific pattern, therefore a represented object. Finally, in the third sense, a model turns out to be a representation, so it should be treated as a representing object.3 In the scientific literature, a much greater number of definitions of a model can be found. There is no need to discuss all of them here. For example, it might be just mentioned that R. L. Ackoff thought that a model is a representation of a certain state, object or event, taking into consideration relevant characteristics of the reality; according to T. Gospodarek, a model is a coherent or complete system of arguments or logical sequences regarding a specific object or event; still, according to E. V. Krick, a model should be construed as something which allows for describing 3 Innovative Changes to Business Models This chapter has been made available under a CC‑BY‑NC‑ND license. 72 Innovative Changes to Business Models the character or behaviour of the respective original, so representing something, with the use of numbers, symbols, schematic diagrams and graphs.4 As far as a “business model” is concerned, it should be stressed that so far a great number of definitions of the term have been formulated and in general none of them can be regarded as fully comprehensive.5 This is so because each author focuses on selected elements of a business model, in addition offering a different classification of such models.6 In connection with this, it is worth presenting only some of the proposed scientific definitions of a business model. First of all, however, it should be noted that the term “business model” goes back to the 1950s.7 It was then discussed mainly in reference to the razor and blades model, in which companies sell their own products at low prices, often at a loss, while the basic income is generated from selling goods and services complementary to the product.8 One definition of a business model comes from T. Doligalski. The author suggested that such a model is an image of a specific organisation captured at the respective moment which to a large extent pertains to activities aimed to create economic value and to internal mechanisms of the organisation’s operation. This way, a business model may be treated as the essence of an enterprise and, first of all, as those aspects of its operation which are crucial for its strength.9 A. Jabłoński stated that a business model should be regarded as a representation of a structure of relations which may be discerned in the respective organisation and its environment, with the proviso that it is a representation at a specific place, time and business space. According to that author, such a model is inextricably connected with factors which influence the satisfaction of the needs of customers, business partners or social organisations, which in turn condition the achievement of competitive advantage, making the most adequate decisions and unrestricted growth of the organisation.10 According to B. Nogalski, a business model is a general conception of conducting business activity, which takes into consideration diverse aspects related to it. Primary importance among these must be attached to the value offered to the customer as well relations with partners, innovativeness or resources available to the organisation.11 In turn, K. Obłój concluded that a business model is a concept relating primarily to the achievement of a dominant competitive advantage by an enterprise, its utilisation of its own resources and skills as well as configuration of a value chain.12 Definitions of a business model proposed by other researchers than the Polish authors can be seen to take a different or more developed approach to issues related to the essence of the model. This is shown, for example, by the definition proposed by A. Osterwalder, Y. Pigneur and C. L. Tucci. The authors underlined that a business model is a conceptual tool which makes it possible to present the business logic of a firm, including the way in which profit is generated from the created value. Such a model contains all the components of a firm and relationships observed between them.13 According to A. Afuah and C. L. Tucci, a business model is the method of increasing resources adopted by a firm to offer its customers better value of products and services than its competitors and to achieve profit doing so.14 A. A. Thompson and A. J. Strickland resolved that a business model refers primarily to streams of revenues, also future ones, as well as to the structure of Innovative Changes to Business Models 73 costs incurred by a firm or the level of margin. In most general terms, the authors noticed that a business model amounts to relations between a firm’s revenues, costs and profits.15 In turn, E. Fielt stressed the fact that a business model should be regarded as the logic of an organisation’s operation primarily in terms of how it creates customer value.16 M. Morris, M. Schindehutte and J. Allen indicated that it is possible to sort out the basic approaches to a business model. Having analysed thirty definitions, the authors concluded that a business model may be viewed from the economic, operational or strategic perspectives, with each of them involving a unique set of decision variables affecting the business model’s construction. In the economic perspective, a business model describes how the firm generates profits or how it makes money and sustains its profit stream over time. In this perspective, the decision variables include revenue sources, cost structures, margin level or company valuation methods. The second, operational, perspective assumes that a business model refers to all the internal processes making it possible for the firm to create value. In this approach, the key decision variables include production and administrative processes, resource flows or service provision methods. Finally, in the strategic perspective, a business model pertains to all the aspects of the firm’s operation related to its growth, market positioning and cooperation with other entities. This perspective also considers the firm’s vision and values. Furthermore, according to the authors, using any business model, regardless of the perspective, should lead to the achievement of a sustainable competitive advantage.17 According to S. Slavik and R. Bednar, business models should be described in two perspectives – purely economic (economic business model) as well as in that which combines the financial aspects with creating value (economic and value business model).18 Examples of defining a business models from these two points of view are presented in Table 3.1. An interesting approach to the essence of a business model was proposed by S. M. Shafer, H. J. Smith and J. C. Linder. In particular, the authors described the term, taking into account key words used in its numerous definitions. These key words were put in four groups. They relate to the following aspects: – strategic choices – in this respect, a business model is about customers, strategy, mission, revenues or competitors; – creating value – resources, assets or processes; – capturing value – financial issues concerning the relation between costs and profits; – value network – relationships with customers and suppliers, product, service and information flows.19 In turn, A. Osterwalder and Y. Pigneur distinguished many elements making up a business model. They are presented by the authors within four areas of business activity. Such elements within the infrastructure are key resources, activities and partners, and for customers – customer segments (potential recipients of the organisation’s offer), relationships with them as well as distribution channels 74 Innovative Changes to Business Models (communication with customers and ways of delivering them value propositions), with respect to the offer – value proposition (a bundle of products and services bringing specific value to customers), and with respect to financial position – revenue streams and cost structure.20 As shown by the definitions presented above, a business model is a term which may be understood very broadly. In addition, it is possible to distinguish various theories of business models which, significantly, are considered to be part of business management theory. An example may be the economic theory of the firm and business model approach to financial reporting. This invokes the said economic business models. Here a business model is examined from the point of view of three aspects associated with the activity conducted by the organisation. They are as follows: – financial reporting should be a kind of test on practical execution of a specific business model; – historical cost may be the most reliable measurement when the business model is to contribute to the development of new assets or services; – fair value may be the most effective measure when the business model involves buying and selling some assets using changes in market prices.21 One of the approaches within business management theories which is used more and more frequently by companies is a tool for business model generation known as the Business Model Canvas. It is a template which shows how to do business to Table 3.1 Example definitions of economic business model and economic and value business mode Definition authors Business model Economic business model H. Chesbrough Framework to link new ideas and technologies to economic outcomes D. Debelak Instrument by which a business is able to generate profits A. Ganbardella, A. McGahan Mechanism for transformation of ideas to revenues J. Mullins, R. Komisar Basis of economic activity in all its aspects regarding cash flows T. Wheelen, D. Hunger Method for making money in business activity, in which specific characteristics of the company are of key importance Economic and value business model J. Magretta Description of how an enterprise is able to earn money, who its customers are and how to deliver specific value to them M. Rappa Method of doing business by which a company can generate revenue and create value D. J. Teece Tool for defining methods of generating value to the customer D. Watson Description of a company’s operations, including all of its processes and functions which result in value for the organisation and customers Source: S. Slavik, R. Bednar, op. cit., pp. 20–21. Innovative Changes to Business Models 75 generate concrete real benefits. The concept is based on a logical juxtaposition of elements making up a business model so as to present a full picture and to facilitate planning processes and assessment of changes to the model.22 According to the author of this concept, A. Osterwalder, the basic task of a business model is to describe the rationale of how an organisation creates, delivers and captures value.23 The rationale refers to customers, finance, infrastructure or offer. And the business model should be presented on one sheet of paper (“Canvas”) to simplify its construction as far as possible and, at the same time, show its essence in an innovative manner. It is just for this reason that the concept is increasingly more used in business practice.24 A template according to the concept of Business Model Canvas is presented in Figure 3.1. The Business Model Canvas is made up of nine building blocks which are strongly interconnected. The point of departure are customer segments and the related value proposition. Summing up, it should be emphasised that a business model is defined in many aspects, also as a concept for conducting business activity, an image of the organisation’s operation or the way to achieve competitive advantage based on generating profits and creating value. Such a model may be explained using business management theories (the economic theory of the firm and reporting, the Business Model Canvas), and furthermore even a business model itself may be regarded as a separate theory.25 All of this show its high complexity and great relevance to the functioning of today’s organisations. Figure 3.1 A template according to the concept of Business Model Canvas Source: author’s own work based on J. Bis, op. cit., p. 59. 82 Innovative Changes to Business Models and information sharing effected mainly through digital platforms. If follows from this that digital business and the related implementation of digital strategies would be impossible without these platforms.61 Digital business may be conducted on the basis of many different models. According to M. Kardas, these models include: – manufacturing model – use of the Internet by organisations to initiate direct relationships with customers; – brokerage model – in this model, organisations create virtual markets for performing purchase and sale transactions with brokers usually collecting commission for arranging these transactions; – merchant model – sale of products or services through the Internet or together with traditional distribution channels (for example brick and mortar facilities); – infomediary model – collecting, processing data of customers and manufacturers’ offers by organisations which provide the information for a fee; – advertising model – generating revenues by improving the attractiveness of websites; – affiliate model – reaching broad masses of customers by establishing cooperation with affiliated partners who add links to the organisation’s portal on their websites; – subscription model – providing a periodical access to digital services in exchange for payment; – utility model – it is a model similar to the subscription model, with the difference that the amount of fees for using digital services depends on their actual use (for example, a fee for some quantity of downloaded data); – community model – using voluntary workers to perform marketing activities.62 An attempt to distinguish the most important digital business models used the most frequently in the market was also made by H. R. Varian. Their descriptions are given in Table 3.2, but it must be added that they refer mainly to the business models involving distribution of digital content which can be sent over the web (music, films, books, games). H. R. Varian provided a classification of digital business models with different ways of marketing, selling and distributing digital products. In such models, it is possible for an organisation not only to perform these processes on its own but also with the aid and support of business partners or even state administration (public support) or customers themselves (e.g. the “ransom” model). Summing up, it should be said that digital business, understood as performing business processes based on various technologies, mainly online ones, may be implemented within many different models. The ones described above do not exhaust the related topics, and furthermore it is important that changes to the models are made aiming to increase their innovativeness. Such changes take place mostly owing to the operation of DTPs. Issues connected with the changes will be discussed in the next section of this work. Innovative Changes to Business Models 83 3.4 Innovative Changes to the Business Model Based on a Digital Technology Platform Business models are subject to continual transformations and, which is especially important for the thematic area of the work, DTPs have a great impact on them. First, it is necessary to stress, as mentioned by C. M. Olszak, that nowadays, to increase their innovativeness and competitiveness, many organisations draw up digital strategies. Such strategies become the point of departure for innovative business models which are based on digital resources. In addition, such models typically go beyond the traditional view of the role of IT in a company’s activity; instead, they demonstrate implementation of a resource‑based view and are strictly connected with generating value for the company and its stakeholders. This way, the major reason for implementing modern business models, also those based on DTPs, are limitations of the traditional models, the development of technologies and a greater awareness of these among business users.63 Table 3.2 Types of digital business models according to H. R. Varian Model name Description The original cheaper than a copy Sales of digital products considerably cheaper than in regular distribution by, for example, adding them as extra items to newspapers and magazines A copy more expensive than the original Use of technological of legal protections by manufacturers Physical complements Various additional items supplied with digital content, for example a T‑shirt or a code for free music downloads to promote a CD Information complements Providing users who have been given digital content for free with additional components or services (for example access to new functionalities) for a fee Subscriptions Regular delivery of specific content in exchange for a fee Personalised version Adding to purchased content original exceptional items Advertise yourself A digital product delivered free of charge is an advertisement for the same product in physical form available for a fee Advertise other things Broadcasting advertisements related to digital content, for example on an Internet portal Licences Collective fees for groups of users Ransom Potential users bid for content which is provided if the total amount of the bids is sufficiently high, for example, Stephen King offered instalments of his book The Plant and then indicated he would continue posting instalments after receiving payments of a specified amount Public provision Co‑financing the publication of digital content by public institutions or the European Union Prizes, awards and commissions For example, commissions from public institutions Source: H.R. Varian, “Copying and Copyrights,” Journal of Economic Perspectives 2005, vol. 19, no. 2, pp. 134–136. 84 Innovative Changes to Business Models Innovative changes to business models are introduced to a great extent due to establishment and growth of DTPs. In this context, it needs to be noticed that, as for example in the media industry, there has been a gradual convergence of many different tools and channels to create large integrated platforms. The changes were also connected with the appearance of new communication channels, including those based on mobile technology. In addition, such channels made it possible to develop new business models.64 The changes described above may be traced by analysing stages in the development of the SMAC technology. This is discussed in Table 3.3. The development of SMAC technologies, which affect considerably the creation of innovative digital business models, would not have been possible without DTPs. This is because these technologies have been accompanied by the emergence of such platforms, ensuring, among other things, exploitation of networked effect or convergence as well as a greater scope of offered services and functionalities. It may be concluded then that owing to DTPs, the approach which prevails in the contemporary business models is based on promoting cooperation and partnership between various entities to achieve specific business objectives. Such an approach assumes a gradual replacement of hierarchical and vertically integrated management structures or supply chains in favour of network Table 3.3 Stages in the development of the SMAC technology and the related role of DTPs Type of technology SMAC 1.0 SMAC 2.0 SMAC 3.0 Social media Creating conditions for faster communication between acquaintances Development of DTPs oriented to communication among all people and creation of new marketing channels Integration of platforms with CRM (customer relationship management) systems to increase the level of cooperation with consumers Mobile technologies Development of BYOD (bring your own device) concept, or use of private mobile devices by employees for the needs of an organisation Increase in mobility of employees because of using increasingly greater number of devices Cooperation of employees from various organisations within digital technology platforms Big data Description of present trends with the aid of a great amount of data Setting future trends based on complex DTPs designed for data analysis Integration of many different tools, including DTPs, to make data analysis more efficient Cloud computing Cloud testing Development of cloud uses Uploading more and more amount of data in a cloud, development of cloud management Source: SMAC 3.0: digital is here. Enterprise IT trends and investments, Ernst & Young LLP, Kolkata 2015, pp. 14–25. Innovative Changes to Business Models 85 organisations which show a divergent level of formalisation of relationships between various entities. Such organisations operated very frequently on a global scale, which is possible due to latest technologies, including also those involving DTPs. Modern business models, however, focus not only on increasing collaboration between organisations but also on reinforcing interactions with customers. In such models, it is not just a company itself but also the customer that generates specific values for the company. They might concern the customer’s comments or recommendations about what should be done by the organisation to effectively meet consumers’ needs and requirements to a greater extent than so far. This is what recommendation and opinion systems, commonly used in many DTPs, are for. In this context, W. Rudny stated that “analysis of business models of many companies that have achieved a spectacular market success shows a reconstruction of the models with the use of digital technologies for mutual communication with customers and joint creation of values.”65 E. Brousseau and T. Penard noticed that the contemporary business models which are digital in nature, do not entail changes only in the digital sphere. The authors indicated that the changes should be perceived as “intermodal” or such that are visible in various areas of a company’s operation. The changes then concern not only digital content but also physical products and services and the related infrastructure. What is more, digital business models to a large extent “are crossed” with traditional models, which thus bring about implementation and use of new marketing strategies also in the industries not directly associated with the digital market. This shows a great complexity of changes caused in modern business models, also on the basis of the functioning of DTPs.66 The aim of innovative changes within the present business model based on the platforms is mainly to ensure quality and timeliness of services at the highest possible level so that diverse expectations of customers are met and, simultaneously, the platforms receive satisfactory, increasingly higher profits. In such a model, the aim is to make customers autonomous so that they are able to have influence on the shape of the respective product or service, thus generating value for the platform or the organisations creating it. What is also very significant is personalisation of the offer addressed to customers (the platforms make it possible to configure products and services, not just use ready‑made packages), algorithimisation and automation of product and service sales (many choices about the shape of products and services are made automatically by various platforms based on various algorithms, which makes it easier for customers to purchase goods) as well as providing customers, within specific platforms, with access to content in the widest possible scope rather than to selected works or book files only (e.g. video on demand services). In turn, what should be mentioned is the development of curated computing model, based on which the App Store platform operates. Such a platform contains digital content selected strictly on the basis of consumers’ needs, which makes it possible to prevent the problem of consumers having an excessive amount of such content and being unable to choose items which would match their preferences as closely as possible. Both models, video on demand and curated computing, in spite of differences, are responses to more and more rapidly changing consumer needs.67 86 Innovative Changes to Business Models In connection with increasingly strongly progressing digitalisation and implementation of recent technologies or management methods, organisations applying traditional business models (referred to as “incumbent”) start to be gradually driven out by entities using innovative business models. This situation is described in terms of a phenomenon known as uberisation (from Uber, a company which has introduced a simply revolutionary way of offering transport services based on a DTP). This phenomenon causes the dissemination of modern business models, i.e. those which lead to supplanting patterns and methods of functioning on the market which have worked well to date. These new models are referred to as hyper‑disruptive business models.68 A description of the most important of them is found in Table 3.4. The innovativeness of the business models described above results not only from the fact that all of them use advanced technologies, including frequently Table 3.4 The most important hyper‑disruptive business models Model name Description Examples of platforms using the model Access over Ownership Using products and services without the need to purchase them Panek CarSharing and Zipcar platforms for car rental for minutes Experience Persuading users to purchase products and services for higher prices due to positive experience of previous purchases on the respective platform Apple, Tesla (platform of the manufacturer of electric cars) Freemium Model (free + premium) A product or service are available free of charge but fees must be paid for using additional, expanded functionalities Dropbox (data storage), Skype, Spotify (access to music) Free Model Free access to products and services in exchange for being forced to view advertisements and send data about the user’s preferences and behaviour in the digital market Facebook, Google Hyper market E‑commerce companies Amazon, Zalando Market place Operation of a platform designed for performing purchase and sale transactions by other entities Alibaba, eBay On demand Offering products and services instantly as soon as demand for them arises Netflix, Uber Subscription model Fixed fee for using a product or service Kindle (platform for reading e‑books), Netflix The ecosystem Creating a closed ecosystem, which causes users to be in a way forced to get other products and services available on the respective platform Apple, Google The pyramid Offering products and services by different organisations from those which manage the respective platform E‑stores, such as Amazon Source: J. Pieriegud, op. cit., p. 19. Innovative Changes to Business Models 87 artificial intelligence. Such innovativeness also follows from a novel approach to responding to consumers’ needs and requirements. Many business models and DTPs concentrate on providing customers with access to the widest possible range of products and services, including those offered by different companies from the entities managing the respective platform (Amazon, eBay), on offering goods which may well be expensive but match closely consumers’ preferences (Experience model), on starting to provide a service instantly when it is demanded (video on demand) and even on free access to various services (Google, Skype). In this respect, it may be observed that the concept of sharing economy, which amounts to a practical application of the Access over Ownership model, is becoming more and more popular, also in the Polish society. The above concept makes it possible to borrow or rent a good without making a purchase to own it. This is also an innovative approach to implementing business models as it is based on increasingly widespread belief in the society that the resources available in the environment are being depleted and cannot be replaced therefore people should take care of them without consuming them needlessly. Consequently, platforms for sharing goods between users are becoming more and more popular, for example BlaBlaCar (sharing a car), Airbnb (sharing accommodation) or EatWith (cooking meals).69 It should be added that the operation of such type of platforms as well as the Market Place model are both manifestations of economics of intermediation, in which a platform serves as an intermediary between users who want to make a purchase or sale or exchange goods.70 At present, DTPs have much more uses than those described above. As a result of this, further business models are being developed. According to W. Szpringer, the most innovative of those, except for models earmarked for e‑commerce or for sharing technologies or software with users, include the following: – crowd financing – in the model, a platform is used to search for sources of financing as well as collaborators and new customers and markets (for example, Kickstarter); – micro‑manufacturing – the model makes it possible to design and manufacture goods using tools available online (Ponoko, MakerBot Industries); – innovation marketplaces – in this model, various organisations have the opportunity to purchase technologies (InnoCentive, NineSigma).71 Therefore, innovative business models based on DTPs also make it possible to transfer technologies between various organisations or even to arrange manufacturing processes. Owing to these models, enterprises active in diverse industries are provided with opportunities to initiate and intensify activity. Innovative transformations of business models based on the operation of DTPs also include the development of the said ecosystems. This is the aim of, among others, the PFI model which is being more and more commonly used. This model allows organisations to plan and perform innovative activities, including to make a decision how to implement them, that is either on their own or in cooperation with another enterprise. If cooperation is chosen, then an ecosystem is gradually created, 88 Innovative Changes to Business Models having in its centre a digital platform which is characterised by interoperability and the possibility of expanding it all the time.72 The innovativeness of business models which exploit the possibilities offered by DTPs is also connected with issues concerning leadership 4.0. Such leadership must fully respond to the challenges posed before organisations by digitalisation. This way, every manager, apart from traditional competences, must also have be able to use new digital media effectively in the course of ongoing activity, also for communicating with employees and for adjusting the leadership strategies to the digital reality, which means creating an atmosphere conducive to creativity and innovativeness or promotion of cooperative network. A response to such challenges is the VOPA leadership model, in which the key importance is attached to networking (German: Vernetzung), openness (Offenheit), employee participation (Partizipation) and agility (Agilität).73 This is presented in Figure 3.3. To sum up the above discussion, it is worth observing that at present numerous changes are taking place in business models. They are caused to a large extent by digitalisation and technological progress, including the growth of DTPs. Such platforms greatly contribute to promoting modern business models, in which innovation plays a key role. There are plenty such models, for example hyper‑disruptive business models or innovation marketplaces, which aim to promote modern technologies. Current changes which concern business models based on DTPs relate mostly to promoting modern technologies and digital tools or even various behaviours of consumers (platforms such as Uber or those involving sharing economy), increasing the number of entities that cooperate with one another while being centred around these models and platforms (due to network effect and synergy, they are able to implement innovations more effectively and faster) as well as establishing Figure 3.3 VOPA leadership model Source: author’s own work based on U. S. Foerster‑Metz, K. Marquardt, N. Golowko, A. Kompalla, C. Hell, op. cit., p. 7. Innovative Changes to Business Models 89 the broadest cooperation with customers by the organisations (they participate, for example, in product designing activities). Such changes are possible first of all due to the functionalities provided by DTPs. 3.5 Impact of Changes in Business Models on the Competitiveness of Companies The nature and type of business models used by organisations affects significantly their competitiveness. The latter term refers for the most part to enterprises’ capability to remain on the respective market and to grow its own activity, which also includes standing up to other entities operating on the market. The capability allows for continual development of an organisation, for achieving profits and for gaining advantage over the remaining enterprises. It is not irrelevant either that due to competitiveness, a company is able to deliver goods to customers in accordance with their needs in terms of time, quality or location.74 In view of the above discussion, the term “competitive advantage” is highly important as well. In the scientific literature, this term is defined primarily in terms of greater attractiveness of the respective company’s offer compared to competitors.75 In other approaches, it is stressed that competitive advantage lies in the overall distinctiveness of a company from its competitors or anything that a company does better from other entities active on the same market.76 With regard to competitiveness of an organisation, what is of great importance is digitalisation and the related processes of more and more wide‑ranging use of new technologies and DTPs in the activity of companies. As noted by S. Łobejko, the progressing digitalisation exerts an increasingly stronger influence on the traditional business relations, offering new business models making it possible to capture values at each stage of the value chain and to gain competitive advantage. Companies which achieve success in the face of competition have their business models, operation and internal culture based on the idea of digitalisation. Intending to develop, they must invest in new technologies allowing for digitisation of business activity, changing the business model as well as ways and methods of competing on the market.77 In the scientific literature, it is indicated that the achievement of competitive advantage may be expressed by various kinds of actions, successes or financial indicators. In this respect, two approaches may be distinguished. In the first, the advantage is thought to be demonstrated by a company’s greater efficiency compared to competing organisations. In turn, the efficiency is connected with better financial indicators, the company’s high profitability or relatively low costs of doing business. The second approach places emphasis on analysing competitive advantage from the perspective of its sources or determinants. These relate in particular to technologies used by the company, resources held by it, capabilities of operating on a competitive market or finally cost leadership.78 It is a fact that innovative changes to business models may be considered within both of the presented approaches. 90 Innovative Changes to Business Models After all, such changes contribute to minimisation of costs, which consequently improves the company’s financial standing and leads to an increase in its profitability (the first approach), and furthermore, they are inextricably connected with innovative activities and with effective use of available resources (the second approach), which, according to S. Łobejko, results from completely new combinations of information, human capital and technological potential.79 According to A. Afuah and C. L. Tucci, a business model has become the most important determinant of an organisation’s efficiency. This is because it is exactly due to such a model a firm is able to build and then use its resources to offer its customers better value than its competitors and to achieve higher profits. A business model allows for defining methods for making money, both now and in the future. It is a factor which has an impact on a firm’s competitiveness.80 It must be emphasised that each business model, even a traditional one, may be a source of competitive advantage. It is so since, according to H. Chesbrough, all business models have similar functions, including, apart from generating value for customer or describing cost structure and profit potential, the formulation of the competitive strategy by which the firm will gain competitive advantage.81 When such models, however, are built in an innovative manner, advantages that may be gained by enterprises are much greater. This happens because, among other things, any innovations help identify various opportunities that appear in the firm’s environment, which by itself provides grounds for taking advantage of any chances for increasing growth. This is especially important when an organisation operates in conditions, many of which are not conducive to its growth, for example legal restrictions (regulated activity), contracting raw material supplies or social pressures.82 According to W. Szpringer, innovative business models, including innovative changes introduced to them, become the source of gaining competitive advantage. They do so because they greatly accelerate and facilitate the performance of business processes and, in addition, they provide the opportunity to offer a relatively large quantity of goods on many diverse markets (internationalisation of activity). Since within innovative business models, modern technologies, including DTPs, are used, they make it possible to communicate with customers faster, deploy various distribution channels and create new values. Such opportunities, and many others, follow from the use of DTPs in innovative business models. An example that can be given here is innovation marketplaces, due to which modern technologies which are sources of competitive advantage are transferred between companies.83 According to J. Bis, innovative business models contribute to increasing companies’ profitability. Products and services may be copied by rivals very quickly, whereas a business model is much harder to reproduce by competitors because it consists of all relevant activities performed in a specific manner.84 This is undoubtedly true. Many among business models developed in recent years are characterised by originality, because of the scope of applied solutions and technologies, and competitors could not copy them although they have tried Innovative Changes to Business Models 91 many times; such attempts have not been entirely successful. What may be of key importance in such cases is implementation of protection for the respective model, which may be based on a system of copyrights or trademarks.85 An example may be the model used within the Uber platform, which offers transport services to customers. In the model, which is an element of sharing economy or on demand system, a DTP is used due to which customers may look for drivers offering transport services. The innovation or even a revolutionary nature of the model follows from the fact that it is not used within any taxi corporation or firm, therefore it is completely independent of them. The model makes it possible to order rides on vehicles which are suitable for customers at a given time (for example, higher standard vehicles – UberSELECT). What is more, customers may select drivers on the basis of opinions written about them by other users and they pay for a ride not by taximeter rates but depending on the length of the actual route (measured by GPS receivers). It is also worth pointing out that Uber initiates cooperation only with strictly selected group of drivers (the must have vehicles not older than the set age limit and conduct business activity in the scope of transporting people) and furthermore offers fast resolution of complaints (they may be reported via an app or email) as well as automatic cashless payments for rides. Even though there have appeared competitors against the Uber platform (in Europe, it is in particular Estonian start‑up Taxify) but still Uber definitely dominates on the market of passenger transport. This follows from the highly innovative business model applied by the company, including mainly the use of an appropriate digital platform for associating service providers with consumers.86 Such innovative model of operation is imitated by many other enterprises, not only those operating on the market of passenger transport, for example the Airbnb platform on the real property market). This way the phenomenon of “uberisation” takes place, whose essence is that various companies and platforms managed by them are not service providers but only deliver an app which allows for contacting business people with their customers. So, in the process of generating value, what is mostly used are resources controlled by users of the platforms. What is important, such a model leads to price reductions because intermediaries are eliminated (Uber does not cooperate with taxi corporations). Furthermore, the model allows for being active in many different areas of activity, also with regard to the government sector. For several years, Uber has made available to the authorities of Boston company data about routes ridden by customers of the platform, which contributes to, among other things, more effective public transport management (planning routes). In turn, San Francisco uses data received from the Airbnb platform about the frequency and location of accommodation where customers of the platform stay. This helps, among other things, in the expansion of the hotel infrastructure.87 Many studies have shown that innovativeness is one of the most important factors for achieving competitive advantage. Thus, for instance, according to analyses carried out in 2005 by the Economist Intelligence Unit agency, more than half of the four thousand surveyed managers thought that implementing innovations is more important than launching new products or services to achieve a competitive advantage in the market.88 Then, based on studies conducted in 2014 on a group of 98 Innovative Changes to Business Models Notes 1 J. Zieleniewski, Organizacja i zarządzanie, PWE, Warsaw 1979, pp. 44–45. 2 B. Glinkowska, “Modelowanie w procesach usprawniania organizacji – uwagi teoretyczno‑ metodyczne,” Acta Universitatis Lodziensis. Folia Oeconomica 2010, no. 234, pp. 257–258. 3 Z. Martyniak, Modele metod stosowanych w badaniach organizatorskich, Wyższa Szkoła Ekonomiczna, Kraków 1973, p. 22. 4 M. Szarucki, “Modelowanie w rozwiązywaniu problemów zarządzania,” [in:] J. Czekaj, M. Lisiński, eds., Rozwój koncepcji i metod zarządzania, Fundacja Uniwersytetu Ekonomicznego w Krakowie, Kraków 2011, pp. 268–269. 5 E. Fielt, “Conceptualising Business Models: Definitions, Frameworks and Classifications,” Journal of Business Models 2013, vol. 1, no. 1, p. 87. 6 J. Bis, “Innowacyjny model biznesowy – sposób na zwiększenie przewagi konkurencyjnej,” Przedsiębiorczość i Zarządzanie 2013, vol. 13, p. 55. 7 Ibid., p. 54. 8 M. Kowalczuk, O. Kosch, D. Mucha, “Modele biznesu w teorii zarządzania,” Security, Economy & Law 2017, no. 2, p. 63. 9 T. Doligalski, Modele biznesu w Internecie. Teoria i studia przypadków, PWN, Warsaw 2014, p. 23. 10 A. Jabłoński, Modele biznesu w sektorach pojawiających się i schyłkowych. Tworzenie przewagi konkurencyjnej przedsiębiorstwa opartej na jakości i kryteriach ekologicznych, Wydawnictwo Wyższej Szkoły Biznesu w Dąbrowie Górniczej, Dąbrowa Górnicza 2008, p. 19. 11 B. Nogalski, “Rozważania o modelach biznesowych przedsiębiorstw jako ciekawym poznawczo kierunku badań problematyki zarządzania strategicznego,” [in:] R. Krupski, ed., Zarządzanie strategiczne. Problemy, kierunki badań, Wałbrzyska Wyższa Szkoła Zarządzania i Przedsiębiorczości, Wałbrzych 2009, p. 45. 12 K. Obłój, Tworzywo sztucznych strategii, PWE, Warsaw 2002, pp. 98–100. 13 A. Osterwalder, Y. Pigneur, C.L. Tucci, “Clarifying Business Models: Origins, Present and Future of the Concept,” Communications of the Association for Information Sys‑ tems 2005, vol. 16, no. 1, pp. 1–25. 14 A. Afuah, C. Tucci, Internet Business Models and Strategies: Text and Cases. McGraw‑Hill, New York 2003, p. 9. 15 A.A. Thompson, A.J. Strickland, Strategic Management: Concepts and Cases, McGraw‑Hill, New York 2003, p. 3. 16 E. Fielt, op. cit., p. 92. 17 M. Morris, M. Schindehutte, J. Allen, “The Entrepreneur’s Business Model: Toward a Unified Perspective,” Journal of Business Research 2005, no. 58, pp. 726–727. 18 S. Slavik, R. Bednar, “Analysis of Business Models,” Journal of Competetiveness 2014, vol. 6, no. 4, pp. 20–21. 19 S.M. Shafer, H.J. Smith, J.C. Linder, “The Power of Research Models,” Business Hori‑ zons 2005, no. 48, p. 200. 20 A. Osterwalder, Y. Pigneur, Business Model Generation: A Handbook for Visionar‑ ies, Game Changers, and Challengers. John Wiley and Sons, Inc., Hoboken, NJ 2013, pp. 22–47. 21 B. Bek‑Gaik, “Model biznesu w sprawozdawczości organizacji – przegląd badań,” Stu‑ dia Ekonomiczne. Zeszyty Naukowe Uniwersytetu Ekonomicznego w Katowicach 2016, no. 268, p. 48. 22 J. Drzewiecki, A. Równicka, “Model biznesu jako narzędzie planowania i opisu projektu na przykładzie Electrolux Polska sp. z o.o.,” Nauki o Zarządzaniu 2015, no. 3, p. 70. 23 A. Osterwalder, Y. Pigneur, C. Tucci, op. cit., p. 18. 24 M. Pierścieniak, “The Business Model Canvas – narzędzie zarządzania dla start‑upów,” Przedsiębiorstwo i Region 2016, no. 8, p. 58. Innovative Changes to Business Models 99 25 J. Magretta, What Management Is: How It Works and Why It’s Everyone’s Business, Profile Books, London 2003, p. 44. 26 J. Sikora, A. Uziębło, “Innowacja w przedsiębiorstwie – próba zdefiniowania,” Zarządzanie i Finanse 2013, no. 2, p. 353. 27 T. Nicholas, “Why Schumpeter Was Right: Innovation, Market Power, and Creative Destruction in 1920s America,” Journal of Economic History 2003, vol. 63, no. 4, p. 1023. 28 M. Ścigała, “Innowacyjność jako cecha organizacji – systematyzacja i konceptualizacja,” Zeszyty Naukowe Politechniki Śląskiej. (Series: Organizacja i Zarządzanie) 2016, vol. 96, pp. 194–195. 29 J.A. Schumpeter, Theory of Economic Development: An Inquiry into Profits, Capital, Credit, Interest, and the Business Cycle, Oxford University Press, London 1934, p. 66. 30 P. Mielcarek, “Innowacje a kształtowanie przewagi konkurencyjnej przedsiębiorstwa,” [in:] M. Sławińska, ed., Gospodarka, technologia, zarządzanie, Wydawnictwo Uniwersytetu Ekonomicznego w Poznaniu, Poznań 2012, pp. 177–188. 31 C. Freeman, The Economic of Industrial Innovation, Pinter, London 1982, p. 7. 32 M. Haffer, Determinanty strategii nowego produktu polskich przedsiębiorstw przemysłowych, Wydawnictwo UMK, Toruń 1998, p. 27. 33 M.C. Schippers, M.A. West, J.F. Dawson, “Team Reflexivity and Innovation: The Moderating Role of Team Context,” Journal of Management 2012, vol. 41, no. 3, p. 771. 34 M.E. Porter, On Competition. Updated and Expaned Edition. Harvard Business School Publishing, Boston, MA 2008, P. 179. 35 W. Janasz, K. Kozioł, Determinanty działalności innowacyjnej przedsiębiorstw, PWE, Warsaw 2007, p. 57. 36 A. Olejniczuk‑Merta, “Od innowacyjności konsumentów do innowacyjnej gospodarki,” Handel Wewnętrzny 2018, no. 4, p. 255. 37 E. Stawasz, “Przedsiębiorstwo innowacyjne,” [in:] K.B. Matusiak, ed., Innowacje I transfer technologii – słownik pojęć, PARP, Warsaw 2005, p. 133. 38 Oslo Manual. Proposed Guidelines for Collecting and Interpreting Technological In‑ novation Data, OECD, Paris 2005, p. 11. 39 A. Sosnowska, S. Łobejko, A. Kłopotek, Zarządzanie firmą innowacyjną, Wydawnictwo Difin, Warsaw 2000, p. 13. 40 L. Białoń, “Firma innowacyjna,” [in:] Białoń, L., ed., Zarządzanie działalnością innowacyjną, Wydawnictwo Placet, Warsaw 2010, p. 172. 41 P.M. Senge, The Fifth Discipline. The Art & Practice of the Learning Organisation, Random House, London 1990, p. 14. 42 K. Kudelska, “Organizacja ucząca się w świetle współczesnych koncepcji zarządzania,” Warmińsko‑Mazurski Kwartalnik Naukowy. Nauki Społeczne 2013, no. 3, pp. 23–24. 43 Y.Y. Yusuf, M. Sarhadi, A. Gunasekaran, “Agile Manufacturing: The Drivers, Concepts and Attributes,” International Journal of Production Economics 1999, vol. 62, no. 1–2, p. 39. 44 U. Słupska, “Proces kreowania organizacji wirtualnej we współczesnym świecie biznesu,” Roczniki Ekonomiczne Kujawsko‑Pomorskiej Szkoły Wyższej w Bydgoszczy 2016, no. 9, pp. 142–143. 45 A. Sosnowska, S. Łobejko, A. Kłopotek, op. cit., p. 11. 46 L. Białoń, op. cit., pp. 172–173. 47 Działalność innowacyjna, https://stat.gov.pl/metainformacje/slownik‑pojec/pojecia‑ stosowane‑w‑statystyce‑publicznej/759,pojecie.html [accessed 15 January 2020]. The definition of innovative activity provided by Statistics Poland is based on the approach proposed by the OECD, see: Oslo Manual…, op. cit., p. 10. 48 K. Kozioł‑Nadolna, “Modele zarządzania innowacjami w XXI wieku,” [in:] B. Mikuła, ed., Historia i powstanie nauk o zarządzaniu, Wydawnictwo Uniwersytetu Ekonomicznego w Krakowie, Kraków 2012, pp. 297–298. 49 W.H. Chesbrough, Open Innovation. The New Imperative for Creating and Profiting from Technology, Harvard Business School Press, Boston, MA 2003, pp. 43–52. 100 Innovative Changes to Business Models 50 K. Kozioł‑Nadolna, op. cit., p. 300. 51 A. Busłowska, “Triple Helix Model – Possibilities of Sustainable Development,” Roc‑ zniki Ekonomiczne Kujawsko‑Pomorskiej Szkoły Wyższej w Bydgoszczy 2016, no. 9, pp. 45–46. 52 M. Poniatowska‑Jasch, “Biznes cyfrowy – wyzwania wobec strategii internacjonalizacji przedsiębiorstwa,” Horyzonty Polityki 2016, no. 20, p. 162. 53 C. Zott, R. Amit, L. Massa, “The Business Model: Recent Developments and Future Research,” Journal of Management 2011, vol. 37, no. 4, pp. 1019–1042. 54 M. Cigaina, U.V. Riss, Digital Business Modeling. A Structural Approach Toward Digital Transformation. Version 2, https://news.sap.com/2016/05/digital‑business‑modeling‑ a‑structural‑approach‑toward‑digital‑transformation/ [accessed 30 January 2020], p. 7. 55 B. Ocicka, “CyfrowaI)ewolucja w zarządzaniu łańcuchem dostaw,” Studia Ekonomic‑ zne. Zeszyty Naukowe Uniwersytetu Ekonomicznego w Katowicach 2017, no. 337, p. 94. 56 E. Brousseau, T. Penard, op. cit., pp. 83–86. 57 C.M. Olszak, “Strategia cyfrowa współczesnej organizacji,” Studia Ekonomiczne. Zeszyty Naukowe Uniwersytetu Ekonomicznego w Katowicach 2015, no. 232, pp. 164–165. 58 M.H. Ismail, M. Khater, M. Zaki, Digital Business Transformation and Strategy: What Do We Know So Far?, University of Cambridge, Cambridge 2017, p. 15; A. Bharadwaj, O.A. El Sawy, P.A. Pavlou, N. Venkatraman, “Digital Business Strategy: Toward a Next Generation of Insights ”, MIS Quarterly 2013, vol. 37, no. 2, p. 472. 59 C. Tärnell, Implementing Digital Business Strategies. A Study of the Impact and Appli‑ cation in the Medical Technology Industry, KTH Royal Institute of Technology School of Industrial Engineering and Management, Stockholm 2018, p. 8. 60 S. Łobejko, op. cit., p. 645. 61 C.M. Olszak, op. cit., pp. 169–170. 62 M. Kardas, “PojęIia i typy modeli biznesu,” [in:] K. Klincewicz, ed., Zarządzanie, organizIcja i organizowanie, Wydawnictwo Naukowe Wydziału Zarządzania Uniwersytetu Warszawskiego, Warsaw 2016, p. 304. 63 C.M. Olszak, op. cit., pp. 168–169. 64 C. Zott, R. Amit, L. Massa, op. cit., p. 1026. 65 W. Rudny, “Modele biznesowe a proces tworzenia wartości w gospodarce cyfrowej,” ZarządIanie i Finanse 2015, no. 1, p. 140. 66 E. Rousseau, T. Penard, op. cit., p. 83. 67 M. Filiciak, Treści cyfrowe. Przemiany modeli bizneIowych i relacji między produIen‑ tami i konsumentami, MGG Conferences, Warsaw 2012, pp. 38–40. 68 J. Pieriegud, op. cit., p. 18. 69 M. Such‑Pyrgiel, “Nowe modele biznesu w dobie transformacji cyfrowej,” [in:] M. Sitek, M. Such‑Pyrgiel, eds., SIołeczne i ekonomiczne aspekty zarządzania w organizac‑ jach przyszłości, Wydawnictwo Wyższej Szkoły Gospodarki Euroregionalnej, Józefów 2018, pp. 48–49; K. Wyrwińska, M. Wyrwiński, op. cit., p. 92. 70 E. Brousseau, T. Penard, op. cit., pp. 86–90. 71 W. Szpringer, “Innowacyjne modele e‑biznesowe – perspektywy rozwojowe,” Prob‑ lemy Zarządzania 2012, no. 3, pp. 73–74. 72 D.J. Teece, G. Linden, “Business Models, Value Capture, and the Digital Enterprise,” Journal of Organisation Design 2017, vol. 8, no. 6, pp. 8–10. 73 U.S. Foerster‑Metz, K. Marquardt, N. Golowko, A. Kompalla, C. Hell, op. cit., pp. 6–7. 74 M. Kraszewska, K. Pujer, Konkurencyjność przedsiębiorstw. Sposoby budowania prze‑ wagi konkurencyjnej, Wydawnictwo Exante, Wrocław 2017, p. 9. 75 A.S. Hosseini, S. Soltani, M. Mehdizadeh, “Competitive Advantage and Its Impact on New Product Development Strategy (Case Study: Toos Nirro Technical Firm) ”, Journal of Open Innovation: Technology, Market, and Complexity 2018, vol. 17, no. 4, pp. 2–3. 76 K. Beyer, “Kapitał intelektualny jako podstawa przewagi konkurencyjnej przedsiębiorstw,” Zeszyty Naukowe Uniwersytetu Szczecińskiego. Studia i Prace Wydziału Nauk Ekonom‑ icznych i Zarządzania 2012, no. 25, p. 243. Innovative Changes to Business Models 101 77 S. Łobejko, op. cit., p. 645. 78 C. Sigalas, “Competitive Advantage: The Known Unknown Concept,” Management Decision 2015, vol. 53, no. 9, p. 2007. 79 S. Łobejko, op. cit., p. 644. 80 A. Afuah, C.L. Tucci, op. cit., p. 10. 81 H. Chesbrough, “Business Model Innovation: Opportunities and Barriers,” Long Range Planning 2010, vol. 43, no. 2–3, p. 355. 82 N.M.P. Bocken, S.W. Short, P. Rana, S. Evans, “A Literature and Practice Review to Develop Sustainable Business Model Archetypes,” Journal of Cleaner Production 2014, no. 65, p. 44. 83 W. Szpringer, op. cit., p. 68. 84 J. Bis, op. cit., p. 58. 85 A. Szcześniak, “Innowacyjne modele biznesowe,” [in:] M. Bąk, P. Kulawczuk, A. Szcześniak, eds., Modele biznesowe przedsiębiorstw tworzonych na bazie szkół wyższych, Fundacja Instytut Badań nad Demokracją i Przedsiębiorstwem Prywatnym, Warsaw 2011, pp. 28–29. 86 Ł. Kryśkiewicz, Innowacje – zmieniają reguły. Studium przypadku Ubera, http:// di.com.pl/innowacje‑zmieniaja‑reguly‑studium‑przypadku‑ubera‑56572 [accessed 18 February 2020]. 87 (Współ)dziel i rządź. Twój nowy model biznesowy jeszcze nie istnieje, PwC, Warsaw 2016, pp. 10–11. 88 D. Gajda, “Rola innowacji w modelach biznesu,” Studia Ekonomiczne. Zeszyty Nau‑ kowe Uniwersytetu Ekonomicznego w Katowicach 2014, no. 183, p. 67. 89 M.K. Gąsowska, “Rola innowacji w procesie zarządzania przedsiębiorstwem w warunkach wahań koniunktury na przykładzie wybranych przedsiębiorstw,” Zeszyty Naukowe Politechniki Śląskiej. (Series: Organizacja i Zarządzanie) 2014, vol. 74, p. 519. 90 A. Szcześniak, op. cit., pp. 34–35. 91 S. Łobejko, op. cit., p. 644. 92 T. Koch, J. Windsperger, “Seeing Through the Network: Competitive Advantage in the Digital Economy,” Journal of Organisation Design 2017, vol. 6, no. 6, pp. 1, 23. 93 D. Tilson, K. Lyytinen, C. Sørensen, “Digital Infrastructures: The Missing IS Research Agenda,” Information Systems Research 2010, vol. 21, no. 4, p. 749. 94 J. Papińska‑Kacperek, K. Polańska, “Analiza zaawansowania realizacji idei Open Government Data w wybranych krajach,” Zeszyty Naukowe Uniwersytetu Szczecińskiego. Studia Informatica 2015, no. 37, p. 104. 95 M. Jabłoński, “Open Data Business Model: innowacyjne aspekty projektowania modeli biznesu,” Studia i Prace Wydziału Nauk Ekonomicznych i Zarządzania Uniwer‑ sytetu Szczecińskiego 2018, no. 2, p. 45. 96 F.W. Donker, “Funding Open Data,” [in:] B. van Oleven, G. Vancauwenberghe, J. Crompvoets, eds., Open Data Exposed, Springer, Berlin 2018, pp. 58–59; S. Turki, S. Martin, S. Renault, “Stimulation of Open Data Ecosystems: Learnings from Theory and Practice,” [in:] A.L. Mention, ed., Digital Innovation. Harnessing the Value of Open Data, World Scientific Publishing, Singapore 2019, pp. 56–57. 97 P. Munoz, B. Cohen, “A Compass for Navigating Sharing Economy Business Models,” California Management Review 2018, vol. 61, no. 1, p. 129. 98 Ibid., pp. 129–130. 99 E. Okoń‑Horodyńska, “W poszukiwaniu modelu biznesowego dla technologiczno‑ społecznej innowacji: przypadek SyNat,” Przedsiębiorczość i Zarządzanie 2013, no. 13, pp. 12–19. 100 A. Jabłoński, “Twórczy model biznesu w koncepcji gospodarki sieciowej,” Studia i Prace Kolegium Zarządzania i Finansów Szkoły Głównej Handlowej w Warszawie 2018, no. 162, pp. 175–179. 101 A. Joyce, R.L. Paquin, op. cit., pp. 1476–1483. DOI: 10.4324/9781003473022-5 4.1 Research Methodology In surveys conducted for this monograph, three research methods have been used. The first of these, or content analysis of the literature on the subject matter, was performed during preliminary studies as well as attempts to confirm several research hypotheses. The first method involved analysis of publications about the concept of technological determinism, assigning a critical role to technical and technological issues and related transformations in shaping the modern society and the economy as well as showing the impact of digital technology platforms (DTPs) on companies’ business activities. The second method is CATI or computer‑assisted telephone interviews. It is a modification of the classic method of quantitative research – direct standardised interviews. Standardised structured interviews originate from the neo‑positivistic research paradigm, although the interpretative paradigm and the critical post‑ modernistic paradigm also contributed to their development. In this research paradigm, known as quantitative, the aim is to discover the truth about the world using methods which are systematic, standardised, based on facts, synthesising, non‑ subjective and cumulative.1 The origin of this established research method can be traced back to the surveys conducted by Arthur Bowley and William Benett‑Hurst in Great Britain in 1912 to get to know the living conditions of the working class in the towns of Stanley and Reading. However, the most important contribution to the development of the method is thought to have been made by George Gallup, who in 1940, during the population census, conducted surveys on a five‑percent sample of American population.2 In contrast to the classic standardised interviews, computer‑assisted telephone interviews have many methodological characteristics which make them particularly useful in this research project. First, CATI is a technique standardised to a very high degree and making it possible to enter only pre‑defined data with regard to their form and content. Second, telephone surveys allow for ongoing supervision of interviewers who collect data and continuous monitoring of sample size and respondents’ answers. Third, the CATI technique ensures the opportunity to make surveys in the sector of enterprises which are representative because of the availability of the entire sampling frame, elimination of the clustering of 4 Findings of Empirical Research This chapter has been made available under a CC‑BY‑NC‑ND license. Findings of Empirical Research 103 entities around locations geographically close to each other and because of possible (as the database was in electronic form) sampling procedures. Furthermore, CATI surveys may be combined with online surveys as well as with qualitative techniques, including projection tests. CATI is a technique which requires lower financial and organisational expenditures than the classic structured F2F (face to face) interview. The CATI technique makes it possible to modify the research tools even after the field research phase has started. Questions, or even blocks of questions, may be then added or modified. The most important advantage and at the same time a description of this research method is the fact that on the basis of a cor‑ rectly selected sample, satisfying appropriate requirements, it is possible to generalise the findings to the population. The quantitative data collected during computer‑assisted telephone interviews (CATI) were subjected to quantitative analysis in accordance with the classic paradigm of such surveys. A tabular analysis was carried out, taking into account bivariate tables and then inductive tests of inter‑group differences were used. The survey using CATI was conducted on 18–28 February 2019. Standardised structured interviews included questions in strictly defined order and unchangeable wording, generally closed (see Appendix 1). In the survey, a modern version of the method presented above was used. The face‑to‑face conversation of interviewer and respondent was replaced by a telephone interview, and the traditional printed questionnaire – by a computer. The sample was selected at random. The interviews were conducted with representatives of managerial staff having knowledge on the operation of DTPs and how they are used by the company. The sampling frame in the survey was a group of beneficiaries of the Innovative Economy Operational Programme performed by the Polish Agency for Enterprise Development (PARP), who received co‑financing under the programme for the implementation and development of DTPs. The total number of beneficiaries was N=320. To ensure the possibility of generalising the collected findings on the tested population, a minimum research sample was calculated before starting the survey. Calculations were performed on the basis of the following formula: =    +         α n 1 4d u 1 N , 2 2 where: d – maximum estimation error expressed as a fraction, is potentially contained in the range from 0 to 1. In general, estimation error is determined arbitrarily at acceptable levels as accepted in research and analytical practice of social sciences – from 0.03 to 0.1. For example, an error assumed at the level of 0.08 means that we accept that specific distribution results obtained in the survey when estimating whether they are representative for the population may contain an error up to ±8 percentage points. The value of coefficient d assumed as acceptable in the survey was 5% (at the level of 0.05); 104 Findings of Empirical Research α u2 – confidence level or interval. Commonly accepted in social sciences at the level of 95%. The value means that there is a merely five percent (100%–95% = 5%) probability of committing the so‑called Type I error, or rejecting a result which is in fact true. At a 95% confidence level, the value α u2 is 1.96; N – size of fixed population, which in this survey was equal to the number of companies, therefore it is 320. Having substituted the above values in the formula, we have received the minimum necessary sample size of n = 122. Because the survey was conducted on a fixed population, while setting the minimum sample size, a sample size adjustment factor should be applied. It is calculated by applying the following formula: nnN Nns, ′= ++ where: n′ – unknown value; n – originally defined sample size; N – size of the surveyed population; s – confidence interval is expressed by the formula, s p1 p n () =− with p in the confidence interval set at the most disadvantageous level, therefore safe for the researcher, or 0.5 (it is assumed that the surveyed population is, as far as possible, non‑homogeneous, or diversified). After substituting values in the formula, we get adjusted sample size equal to 88. To ensure the possibility of conducting analyses of collected data and taking advantage of various statistical tests, it was decided to increase the realised sample size to N = 120 (requirements of parametric and non‑parametric tests assume the minimum size at the level of 120). A randomisation algorithm embedded in the software for telephone surveys (algorithms embedded in the software for quantitative surveys use the so‑called random number generators, whose task is to ensure the same probability of drawing each of the records from the sampling frame; in this survey, this means that each of the 320 beneficiaries of the programme had equal chances of being included in the sample) ensured that each record in the database was equally likely to be found in the sample. While conducting the survey, each of the companies were contacted on the telephone. The interviews with beneficiaries were carried out by a team of qualified interviewers, trained on the subject of the survey. Their task was to reach the right person in a company who would have knowledge on the operation and utilisation of DTPs. Data collection and interviews were strictly supervised ad hoc and post hoc, in accordance with the requirements of the Interviewers’ Work Quality Programme, which guarantees high quality of obtained results. 120 interviews were conducted, 49 Findings of Empirical Research 105 companies refused to participate in the survey, two of them declared that they had not implemented any platforms and with the remaining ones it was impossible to carry out interviews on the arranged dates. A company could be included in the sample if it satisfied one of the following to criteria: • declared use of DTPs by the company; • planning to implement DTPs in the company in the near future. The interviewers conducted interviews with representatives of managerial staff having knowledge on the operation and use of DTPs in the company. The tabular data can be found in Appendix 2. The third research method is regression analysis. This analysis is for making a quantitative assessment of qualitative data, which is based on assigning specific values to certain categories. Within the method, optimal scaling was used in the form of categorical regression (CATREG), or regression analysis for qualitative variables, to predict values of certain variables. Analytical technique made is possible to disclose correlation coefficients for assessments of the impact of DTPs on the company’s operation. Optimal scaling belongs to the family of regression methods. It is a method involving prediction of the value of a selected variable on the basis of values adopted by other variables, also selected by the researcher. What is important is the fact that optimal scaling makes it possible to include in analyses variables at each measurement level: nominal, ordinal, interval and ratio. This is a definite advantage of the method, which makes it impossible to include in analyses nominal variables (because of that, we cannot get to know what role they play). This method may be regarded as the “first choice” in social sciences because variables are generally measured here at the qualitative level. The aim of using the method is to quantify correlations between many independent variables and one dependent variable. It is “regression for qualitative variables,” which mainly involves testing overall effect of variables (interaction means “the product” of all variables). The concept of optimal scaling is derived from several sources – correspondence analysis3 and multidimensional scaling (MDS)4 – and it is regarded as the successor of these two methods. It is, however, more correct and more statistically rigorous.5 One of the main objectives of this monograph is to construct a model of DTPs. Accordingly, the relevant procedure should be discussed here. Constructing a model of a phenomenon involves some kind of mathematisation of hypotheses (in the form of an appropriate equation or a system of equations), therefore presenting them in a parametrised manner in the so‑called “statistical space.” Such a model presents a simplified but basic and most important connections between studied phenomena. For this purpose, tools of inductive statistics are used, most often regression models. This model concerns measurement of attitudes to DTPs in companies. The concept of “attitude” is deeply rooted in social sciences, in particular in sociology, but it is also widely used in economy.6 Scientists agree that an attitude has a three‑part structure: affective (what is felt), cognitive (what is known) and 106 Findings of Empirical Research behavioural (what is done).7 The concept of attitude served to formulate the question indicating an independent variable: Question 13. To what extent do digital technology platforms affect an in‑ crease in quality and intensity of relations established by the company in which you perform your professional duties with any stakeholders, including mainly suppliers, business partners, distributors or customers? The question made it possible to measure attitudes to the phenomenon of DTPs. There are following elements here: evaluative elements referring to knowledge and elements referring to the appraisal of the phenomenon (“increase in the quality and intensity”). What is of key importance is correlation of the general assessment of the impact of DTPs on the quality and intensity of the company’s operation with the remaining evaluative, cognitive elements (questions 5 and 12 – about affective elements and question 9 – about affective and cognitive elements) and behavioural ones (questions: 1, 4, 8, 10, 11, 14). The impact of socio‑demographic variables concerning the company was also studied (questions 22 and 23) as well as the probable impact of the so‑called latent variables concerning the very respondent (questions 16, 17, 18, 19, 20). Each indicator may be also classified from another important perspective – aspects of the company’s operation (a list of variables taken into account is presented in Table 4.1). It was assumed that a company may be transformed by DTPs in the following dimensions: human (evaluation of the phenomenon by people, the extent to which platforms are used, expectations, etc.), cybersecurity (new IT challenges related to hardware and software), eco‑ nomic (connected with the calculation of actual and potential profits and losses) and social (changes in the structure of the company and in the manner, type and intensiveness of its relationships with the environment). Using the above variables, a model was built, indicating which variables and how strongly affect the independent variable. As mentioned above, CATREG optimal scaling was used for the analysis. Such scaling is a technique which ensures multidimensional data exploration: the acceptable number of predictors is two hundred, although only one independent variable may be predicted. It is also justified, however, to limit the number of variables. In fact, each variable should be assigned to at least ten, and ideally twenty, units of analysis; otherwise, we may experience instability of regression line. This means that in this analysis, where the set is N = 121, at most twelve independent variables may be used, and optimally, not more than six. This is highly important in the context of the selected above (Table 4.1) number of sixteen variables. It means that at least four of them should be eliminated a priori. The variables selected for elimination were those which in various systems of variables, tested many times, showed the lowest interaction with other independent variables and the dependent variable. At this point, ways of interpreting the regression model for qualitative variables should be discussed. Interpretations are similar to an ordinary regression model,8 although it has more indicators and they are more refined. Findings of Empirical Research 107 Table 4.1 Classification of indicators of entrepreneurs’ attitudes to the phenomenon of digital technology platforms Interview question Dimension of the company’s operation Comments Question 1. Does your company use digital technology platforms, which are tools that allow for connecting business partners and provide opportunities for intensifying contacts and performing transactions between them? Human factor Variable measurement level: ordinal Question 4. Please state which kind of digital technology platforms is used or will be used (if there are plans for implementation) in your company? (please select all possible responses) Structural factor Variable measurement level: nominal (multi‑choice question), converted into ratio variable – counting the number of selections Question 5. Please state what attitude is taken by the personnel in your company about the implementation and use of digital technology platforms? Human factor Variable measurement level: ordinal Question 8. Please state whether in connection with the implementation of digital technology platforms in the company in which you perform your professional duties any of the following adverse cybersecurity events and threats have occurred directly as a result of using these platforms? Cybersecurity factor Variable measurement level: nominal (multi‑choice question), converted into ratio variable – counting the number of selections Question 10. In which areas of your company’s operation digital technology platforms are or will be used (if there are plans for their implementation)? (please select all possible responses) Structural factor Variable measurement level: nominal (multi‑choice question), converted into ratio variable – counting the number of selections Question 11. Please state what basic benefits are generated due to the use of digital technology platforms in your company? Economic factor Variable measurement level: nominal (not subject to, e.g. factor analysis) Question 12. Do you agree with the statement that digital technology platforms make it possible to create and develop innovative business models? Structural factor Variable measurement level: ordinal Question 14. Has the implementation of digital technology platforms in the company in which you perform your professional duties forced the company to introduce specific changes to its organisational structure or will you be forced to do so? Structural factor Variable measurement level: ordinal Question 22. Please state in what kind of company in terms of headcount size you perform your professional duties? Structural factor Variable measurement level: interval (Continued) 114 Findings of Empirical Research Table 4.5 (Continued) Name of the component (predictor) Beta coefficient The number of degrees of freedom (df) FSignificance Zero‑order correlation Partial correlation Semi‑partial correlation Importance Tolerance after transformation Tolerance before transformation Question 19. Please state how long you have been employed in the company in which you perform your professional duties now. 0.235 2 3.527 0.034 0.150 0.290 0.225 0.079 0.917 0.828 Question 4. Please state what kind of digital technology platforms are or will be used (if there are plans for their implementation) in your company (please select all possible responses). 0.202 1 1.941 0.167 0.130 0.245 0.188 0.059 0.865 0.847 Question 12. Do you agree with the statement that digital technology platforms make it possible to create and develop innovative business models? 0.209 2 1.675 0.193 0.116 0.265 0.204 0.055 0.955 0.914 Findings of Empirical Research 115 Question 10. In which areas of your company’s operation digital technology platforms are or will be used (if there are plans for their implementation)? (please select all possible responses) 0.153 1 1.919 0.170 0.135 0.197 0.150 0.046 0.954 0.918 Question 21. Please state your position in the company in which you perform your professional duties now. 0.187 2 3.443 0.036 0.100 0.236 0.181 0.042 0.936 0.828 Question 18. Please state your education level. −0.114 1 0.981 0.325 −0.066 −0.146 −0.110 0.017 0.934 0.931 Source: Author’s own work. 116 Findings of Empirical Research the industry in which the enterprise operates and the intensiveness of transformations in the enterprise’s internal structure (this is altogether 47.5%, or nearly a half of the model’s components). It should be stressed that it has been commonly perceived for many years that the structural factor is far from being irrelevant. Douglas North, a Nobel prize winning economist, maintained that development takes place more as a result of organisational rather than technological progress.13 In turn, human factors, therefore factors strictly socio‑psychological and demographic features of respondents, are of low importance (in terms of explanatory power), and they are represented by such items as years of employment, position and education (13.8%). This is presented in Figure 4.1. An alternative model was attempted to be built with the bottom‑up method, or by adding further variables through trial and error. However, it turned out to be impossible to complete. An attempt was made to base correlation by the bottom‑up method on assumptions derived from the cognitive theory. The major factor was sought among both “hard” elements referring to econographic features of an enterprise, and “soft,” referring to features of the respondent in their professional role (education, experience and other socio‑psycho‑demographic characteristics). Selected groups of factors showed moderately high values with regard to F statistic, correlation and importance but they were statistically insignificant (a high risk of committing Type I error). It Is possible to base a model also on synthetic indicators – indexes or scales. In such a case, independent variables would be synthetic values derived from two or more direct indicators (interview questions). A direct advantage of this approach is reduction of the number of independent variables, which allows for decreasing the distance between the R‑squared and adjusted R‑squared coefficients. As a result, a model explaining a greater part of variation of the dependent variable could be potentially Figure 4.1 Components of the optimal scaling model produced with the top‑down method – visual interpretation taking into account the proportional importance of each factor in the model Source: Author’s own work. Findings of Empirical Research 117 generated. An undeniable advantage of such an approach is obtaining transparency by introducing orderliness and structuring factors by putting them into groups. Data were synthesised by summing them up in a simple arbitrary manner and then averaging sets of indicators. From the methodological point of view, these are the so‑called reflexive indicators, therefore not related to one another due to a common cause but in accordance with the research assumptions, classified to a more general category. Five synthetic indexes were distinguished: cybersecurity (represented by one indicator), economic (one indicator), human (eight partial indicators), structural (four indicators) and structural‑demographic (two partial indicators). This is presented in Table 4.6. Table 4.6 Classification of indicators of entrepreneurs’ attitudes to the phenomenon of digital technology platforms Index Interview question Comments Cybersecurity Question 8. Please state whether in connection with the implementation of digital technology platforms in the company in which you perform your professional duties any of the following adverse cybersecurity events and threats have occurred directly as a result of using these platforms? Variable measurement level: nominal (multi‑choice question), converted into ratio variable – counting the number of selections Economic Question 11. Please state what basic benefits are generated due to the use of digital technology platforms in your company? Variable measurement level: nominal (not subject to, e.g. factor analysis) Human Question 1. Does your company use digital technology platforms, which are tools that allow for connecting business partners and provide opportunities for intensifying contacts and performing transactions between them? Variable measurement level: ordinal Question 5. Please state what attitude is taken by the personnel in your company about the implementation and use of digital technology platforms? Variable measurement level: ordinal Question 16. Please state your gender. Variable measurement level: nominal (not subject to, e.g. factor analysis) Question 17. Please state your age. Variable measurement level: interval Question 18. Please state your education level. Variable measurement level: interval Question 19. Please state how long you have been employed in the company in which you perform your professional duties now. Variable measurement level: interval (Continued) 118 Findings of Empirical Research The attempt to construct a model using question no. 13 as the dependent variable and the indexes described above as independent variables generated the following results, presented in Tables 4.7 and 4.8. In social sciences, results of calculations in inductive statistics which show the value of coefficient p (probability value) above 0.05 are regarded as statistically insignificant. Sometimes, an exception is made to the principle, quoting results of tests which actually exceeded the value of 0.05 but are not higher than 0.1. Table 4.6 (Continued) Index Interview question Comments Question 20. Please state how long has the company in which you perform your professional duties been active on the market. Variable measurement level: interval Question 21. Please state your position in the company in which you perform your professional duties now. Variable measurement level: nominal (not subject to, e.g. factor analysis) Structural Question 4. Please state what kind of digital technology platforms are or will be used (if there are plans for their implementation) in your company (please select all possible responses). Variable measurement level: nominal (multi‑choice question), converted into ratio variable – counting the number of selections Question 10. In which areas of your company’s operation digital technology platforms are or will be used (if there are plans for their implementation)? (please select all possible responses) Variable measurement level: nominal (multi‑choice question), converted into ratio variable – counting the number of selections Question 12. Do you agree with the statement that digital technology platforms make it possible to create and develop innovative business models? Variable measurement level: ordinal Question 14. Has the implementation of digital technology platforms in the company in which you perform your professional duties forced the company to introduce specific changes to its organisational structure or will you be forced to do so? Variable measurement level: ordinal Structural (socio‑ demographic) Question 22. Please state in what kind of company in terms of headcount size you perform your professional duties? Variable measurement level: interval Question 23. Which industry does your company operate in? Variable measurement level: nominal (not subject to, e.g. factor analysis) Source: Author’s own work. Findings of Empirical Research 119 There is a high risk here (at the level of 10%) of committing Type I error, such a result should be nevertheless at least recorded as a marginal note. The model based on synthetic indexes explains to a considerably lower extent than the model built as the first the variation in question 13. The most relevant explanatory factor over one fourth (25.4%) of the variation of an independent variable is the structural (socio‑demographic) factor, which includes the company’s size and industry. This may be a reason for exploring the issue further. During a systematic analysis of variables, a regularity was discovered, confirmed above and already mentioned, at the level of single indicators of inductive statistics using Pearson’s chi‑squared test. The result is presented in Table 4.9. In a summary, it should be underlined that the hypothesis of joint impact of characteristics, referred to in the statistical literature as interaction, has been verified. To this end, a regression model for qualitative variables was built using the top‑down method. It turned out to be satisfactory in terms of obtained results. Constructing the model with the use of the top‑down method, in the first phase, all the variables were included to it, and then those with the lowest tolerance level were systematically eliminated in order to start rejecting, step by step, variables with the lowest goodness of fit expressed by F statistic. The most significant factor, strongly connected with the attitude to DTPs, turned out to be the economic factor, or financial benefits from using the platforms. The assessment of DTPs is also affected by numerous structural elements of the external and internal environment of the company. A small, though significant role is played by characteristics of the respondent – their length of employment, position in the company and education. In addition, the model was built on the basis of arbitrary indexes (Table 4.10). It turned out to be borderline statistically significant and was excluded from further discussion, but it was decided that the direction of research indicated by it should Table 4.7 Summary of general coefficients of the optimal scaling model produced with the top‑down method Multiple R 0.361 R‑squared 0.131 Adjusted R‑squared 0.052 Source: Author’s own work. Table 4.8 ANOVA variance analysis for the optimal scaling model produced with the top‑down method The sum of the squares The number of degrees of freedom (df) Mean square FSignificance Regression 15.805 10 1.580 1.653 p ≤ 0.1 Residual 105.195 110 0.956 Total 121.000 120 Source: Author’s own work. 120 Findings of Empirical Research Table 4.9 Structural (socio‑demographic) index – chi‑squared test of correlation significance Structural (socio‑ demographic) index Question 13. To what extent do digital technology platforms affect an increase in quality and intensity of relations established by the company? To a very large extent To a large extent Neither to a large nor to a small extent To a small extent To a very small extent I have no opinion Total N % N % N % N % N % N % N % 0–25 4 30.8 6 46.2 2 15.4 0 0.0 0 0.0 1 7.7 13 100.0 26–50 10 35.7 11 39.3 3 10.7 2 7.1 0 0.0 2 7.1 28 100.0 51–75 15 36.6 16 39.0 5 12.2 0 0.0 5 12.2 0 0.0 41 100.0 76–100 15 38.5 14 35.9 1 2.6 0 0.0 1 2.6 8 20.5 39 100.0 Kruskal‑Wallis test of inter‑group comparisons Statistically insignificant Pearson’s chi‑square test of associations between variables and Cramér’s V contingency coefficient χ² (15, N = 121) = 26.27; p ≤ 0.05, V = 0.269 Source: Author’s own work. Findings of Empirical Research 121 Table 4.10 Components of the optimal scaling model produced with the top‑down method Name of the component (predictor) Beta coefficient The number of degrees of freedom (df) FSignificance Zero‑order correlation Partial correlation Semi‑partial correlation Importance Tolerance after transformation Tolerance before transformation Index – structural (socio‑ demographic) factor 0.261 0.201 1 10.682 0.197 0.274 0.262 0.254 0.547 0.944 Index – structural factor 0.147 0.163 3 0.816 0.488 0.140 0.154 0.145 0.157 0.975 Index – human factor 0.141 0.163 2 0.749 0.475 0.145 0.148 0.139 0.157 0.972 Index – economic factor 0.070 0.207 3 0.114 0.952 0.105 0.072 0.067 0.056 0.932 Index – cybersecurity factor −0.138 0.159 1 0.756 0.386 −0.078 −0.141 −0.133 0.083 0.928 Source: Author’s own work. 122 Findings of Empirical Research continue to be explored (factors connected with the enterprise’s structure, such as the industry and the number of employees, as correlatives of attitudes to DTPs). Further research was done with the use of cross tables. Question 13 was juxtaposed with questions: P2, P4, P5, P9, P10, P11, P16, P17, P18, P19, P20, P21, P22, P23. The cross (two‑variable) tables were used to carry out analysis and to support inductive tests of inter‑group differences (Tables 4.11–4.14). To find differences and similarities among groups selected during conceptual work, two tests were used: the Kruskal‑Wallis test by ranks, also known as non‑parametric variance analysis, and the Mann‑Whitney U test. The first statistical tool was introduced to scientific practice in the 1950s by William H. Kruskal and W. Allen Wallis.14 The test makes it possible to determine whether in a large (k > 2) group consisting of many elements, there are statistically significant differences between the elements. If the test shows such differences, then the next test is conducted – one introduced by Henry B. Mann and Donald R. Whitney to compare pairs of elements making up the group.15 The second test allows for stating statistically significant differences between elements or their absence. The tests may be applied when the variables to be tested have been measured at least at the ordinal level and also at the interval or ratio level. The result of the Kruskal‑Wallis test is recorded in the following way: () () [] [] [] [] χ= =≤ α Hx ,N yz;p 2 It is interpreted as follows: – x is the number of degrees of freedom; – y is the size of the sample which was tested; – z is the value of chi‑squared test; – α is the significance level of completed Kruskal‑Wallis test. The result of the Mann‑Whitney U test is recorded in the following way: () [] [] [] == ≤α UN xy;p It is interpreted as follows: – x is the size of the sample which was tested; – y is the value of the Mann‑Whitney U test; – α is the significance level of completed test. In these tests, similarly to other inductive tests, the following two statistical hypotheses are formulated: the null hypothesis (H0), assuming that the compared groups are identical, and alternative hypothesis (H1), according to which they are different. A test is found to be statistically significant if p ≤ 0.05. The tables below present the assessment of changes caused as a result of using DTPs, taking into consideration many variables. Those variables which had been found not to Findings of Empirical Research 123 Table 4.11 Assessment of the impact of DTPs v. the type of platform used in the company Question 4. Please state which kind of digital technology platforms is used or will be used? Question 13. To what extent do digital technology platforms affect an increase in quality and intensity of relations established by the company? To a very large extent To a large extent Neither to a large extent nor to a small extent To a small extent To a very small extent I have no opinion Total N % N % N % N % N % N % N % Communication 37 38.9 36 37.9 9 9.5 2 2.1 3 3.2 8 8.4 95 100.0 Information 28 32.9 36 42.4 7 8.2 2 2.4 4 4.7 8 9.4 85 100.0 Comparison tools, for example for comparing prices or product features 3 25.0 5 41.7 3 25.0 1 8.3 0 0.0 0 0.0 12 100.0 Entertainment 2 22.2 5 55.6 0 0.0 0 0.0 0 0.0 2 22.2 9 100.0 Online markets 13 27.1 18 37.5 8 16.7 2 4.2 3 6.3 4 8.3 48 100.0 All of the above 0 0.0 2 100.0 0 0.0 0 0.0 0 0.0 0 0.0 2 100.0 Kruskal‑Wallis test of inter‑group comparisons Communication platforms v. degree of impact – statistically insignificant Information platforms v. degree of impact – statistically insignificant Comparison platforms, for example for comparing prices or product features – statistically insignificant Entertainment platforms v. degree of impact – statistically insignificant Online markets v. degree of impact – statistically insignificant All of the above v. degree of impact – statistically insignificant Pearson’s chi‑square test of associations between variables and Cramér’s V contingency coefficient Communication platforms v. degree of impact – statistically insignificant Information platforms v. degree of impact – statistically insignificant Comparison platforms, for example for comparing prices or product features – statistically insignificant Entertainment platforms v. degree of impact – statistically insignificant Online markets v. degree of impact – statistically insignificant All of the above v. degree of impact – statistically insignificant Source: Author’s own work. 130 Findings of Empirical Research Question 4. Please state what kind of digital technology platforms are or will be used (if there are plans for their implementation) in your company (please select all possible responses) Question 22. Please state in what kind of company in terms of headcount size you perform your professional duties? At this point, the results which refer strictly to hypotheses H1 and H5 will be presented (in Tables 4.15–4.24). With regard to them, correlation between questions 2 and 6 should be described. The relevant data are presented in Table 4.15. The marginal distributions in Table 4.15 show the following divergence: the longer a company uses DTPs, the more the employees are willing to participate in training and active in generating new ideas connected with the use of DTPs. At the same time, the following similarities are observed: both groups most often pointed out the following factors: (1) giving consent to any changes resulting from the implementation of DTPs, including changes connected with the organisational structure (85.4% of those using platforms for three years or shorter and 85.2% for those using the longer), (2) great involvement in the performance of tasks (75% from the first group and 85.2% from the second) and (3) being interested in next investments regarding the implementation of DTPs (68.8% and 77.8% respectively) as effects of a positive attitude to performed projects. In this respect, there are no statistically significant differences between the analysed groups. Both agree nearly in 100% with the statement that DTPs make it possible to create and develop innovative business models. It should be noted that the force of positive conviction that the statement is true is higher for those companies which use platforms longer (more than three years). Both groups of the surveyed enterprises adopt the same position about a high or very high impact of using DTPs on increase in quality and intensiveness of relations established by the companies. In this case, there are no statistically significant differences between the groups. There are no significant differences between both groups also with regard to the issue of the necessity to introduce changes in the company’s organisational structure as a result of using DTPs. In both groups, a similar percentage of respondents declare that such changes should have been introduced (60.4% of the respondents using platforms for three years or shorter and 53.2% of those using them longer). A cautious interpretation of the results is that people using DTPs for more than three years no longer notice very well the already implemented or potential changes in the organisational structure. Both groups make similar declarations about the changes which have taken place as a result of the introduction of DTPs. The most frequent of these include creation of a new job/position(s) for persons who will be responsible for the maintenance of the platforms (51.4% – enterprises using platforms for three years or shorter and 63.6% – those using them longer than three years), and transformations in the governance and managerial structure (28.6% and 45.5% respectively). The only statistically significant difference is found in selections about liquidation of existing jobs. In enterprises using platforms for more than three years, there are Findings of Empirical Research 131 Table 4.15 Duration of using digital technology platforms v. involvement of managerial staff Question 6. What shows the positive attitude of the personnel to the implementation and use of digital technology platforms in your company? Question 2. Please state how long digital technology platforms have been used in the company in which you perform your professional duties? Up to three years More than three years N % N % Active involvement in the performance of tasks related to the implementation and use of digital technology platforms 36 75.0 46 85.2 Great spontaneous willingness to participate in training in this area 26 54.2 37 68.5 Active generation of new ideas connected with the use of digital technology platforms 33 68.8 42 77.8 Giving consent to any changes resulting from the implementation of digital technology platforms, including changes connected with the organisational structure 41 85.4 46 85.2 Being highly ready for changes concerning one’s own professional duties 37 77.1 43 79.6 Being interested in next investments regarding the implementation of digital technology platforms 33 68.8 42 77.8 Mann‑Whitney U test of inter‑group comparisons Involvement in the performance of tasks v. duration of use – statistically insignificant Willingness to participate in training v. duration of use – statistically insignificant Active generation of new ideas v. duration of use – statistically insignificant Consent to changes v. duration of use – statistically insignificant Readiness for changes of own professional duties v. duration of use – statistically insignificant Further investments v. duration of use – statistically insignificant Pearson’s chi‑square test of associations between variables and Cramér’s V contingency coefficient Involvement in the performance of tasks v. duration of use – statistically insignificant Willingness to participate in training v. duration of use – statistically insignificant Active generation of new ideas v. duration of use – statistically insignificant Consent to changes v. duration of use – statistically insignificant Readiness for changes of own professional duties v. duration of use – statistically insignificant Further investments v. duration of use – statistically insignificant Source: Author’s own work. 132 Findings of Empirical Research Table 4.17 Duration of using digital technology platforms v. improvement in the quality of the enterprise’s relations Question 13. To what extent do digital technology platforms affect an increase in quality and intensity of relations established by the company? Question 2. Please state how long digital technology platforms have been used in the company in which you perform your professional duties? Up to 3 years More than 3 years N % N % To a very large extent 21 36.2 23 37.1 To a large extent 22 37.9 24 38.7 Neither to a large extent nor to a small extent 5 8.6 6 9.7 To a small extent 0 0.0 2 3.2 To a very small extent 3 5.2 3 4.8 I have no opinion about that topic 7 12.1 4 6.5 Mann‑Whitney U test of inter‑group comparisons statistically insignificant Pearson’s chi‑square test of associations between variables and Cramér’s V contingency coefficient statistically insignificant Source: Author’s own work. Table 4.16 Duration of using digital technology platforms v. development of innovative business models Question 12. Do you agree with the statement that digital technology platforms make it possible to create and develop innovative business models? Question 2. Please state how long digital technology platforms have been used in the company in which you perform your professional duties? Up to three years More than three years N % N % Definitely agree 25 43.1 37 59.7 Rather agree 29 50.0 16 25.8 Neither agree nor disagree 4 6.9 8 12.9 Rather disagree 0 0.0 1 1.6 Definitely disagree 0 0.0 0 0.0 Mann‑Whitney U test of inter‑group comparisons Statistically insignificant Pearson’s chi‑square test of associations between variables and Cramér’s V contingency coefficient Statistically insignificant Source: Author’s own work. Findings of Empirical Research 133 Table 4.18 Duration of using digital technology platforms v. necessity of organisational changes Question 14. Has the implementation of digital technology platforms in the company in forced the company to introduce specific changes to its organisational structure or will it be forced to do so? Question 2. Please state how long digital technology platforms have been used in the company in which you perform your professional duties? Up to three years More than three years N % N % Definitely so 8 13.8 7 11.3 Rather so 27 46.6 26 41.9 Neither agree nor disagree 13 22.4 7 11.3 Rather not 9 15.5 17 27.4 Definitely not 1 1.7 5 8.1 Mann‑Whitney U test of inter‑group comparisons Statistically insignificant Pearson’s chi‑square test of associations between variables and Cramér’s V contingency coefficient Statistically insignificant Source: Author’s own work. Table 4.19 Duration of using digital technology platforms v. organisational changes Question 15. What are (will be) the changes in the company’s organisational structure resulting from the implementation of digital technology platforms? Question 2. Please state how long digital technology platforms have been used in the company in which you perform your professional duties? Up to three years More than three years N % N % Opening a new branch of the enterprise 0 0.0 0 0.0 Liquidation of an existing branch of the enterprise 0 0.0 1 3.0 Setting up a new department(s) of the enterprise 10 28.6 11 33.3 Liquidation of an existing department/existing departments of the enterprise 0 0.0 2 6.1 Creation of a new job/position(s) 18 51.4 21 63.6 Liquidation of an existing job/ position(s) 0 0.0 4 12.1 Transferring specific groups of employees to another department/ other departments of the enterprise 1 2.9 4 12.1 Transformations in the governance and managerial structure 10 28.6 15 45.5 (Continued) 134 Findings of Empirical Research Table 4.19 (Continued) Question 15. What are (will be) the changes in the company’s organisational structure resulting from the implementation of digital technology platforms? Question 2. Please state how long digital technology platforms have been used in the company in which you perform your professional duties? Up to three years More than three years N % N % Mann‑Whitney U test of inter‑group comparisons Opening a new branch of the enterprise v. duration of use – statistically insignificant Liquidation of an existing branch of the enterprise v. duration of use – statistically insignificant Setting up a new department(s) of the enterprise v. duration of use – statistically insignificant Liquidation of an existing department/existing departments of the enterprise v. duration of use – statistically insignificant Creation of a new job/position(s) v. duration of use – statistically insignificant Liquidation of an existing job/position(s) v. duration of use – U(N = 68) = 507.5; p ≤ 0.05 Transferring specific groups of employees to another department/other departments of the enterprise v. duration of use – statistically insignificant Transformations in the governance and managerial structure v. duration of use – statistically insignificant Pearson’s chi‑square test of associations between variables and Cramér’s V contingency coefficient Opening a new branch of the enterprise v. duration of use – statistically insignificant Liquidation of an existing branch of the enterprise v. duration of use – statistically insignificant Setting up a new department(s) of the enterprise v. duration of use – statistically insignificant Liquidation of an existing department/existing departments of the enterprise v. duration of use – statistically insignificant Creation of a new job/position(s) v. duration of use – statistically insignificant Liquidation of an existing job/position(s) v. duration of use – χ² (1, N = 121) = 4.50; p ≤ 0.05, V = 257 Transferring specific groups of employees to another department/other departments of the enterprise v. duration of use – statistically insignificant Transformations in the governance and managerial structure v. duration of use – statistically insignificant Source: Author’s own work. Findings of Empirical Research 135 Table 4.20 Company size v. benefits from using the platforms Question 11. Benefits are generated due to the use of digital technology platforms in the company Company size Micro Small Medium Large Rank sum Rank Rank sum Rank Rank sum Rank Rank sum Rank Growth of profits 75.9 2 100.0 1 100.0 1 100.0 1 Growth of competitiveness 100.0 1 74.8 2 70.9 2 73.6 3 Enlarging the product offering 70.7 3 48.9 4 51.5 4 66.7 4 Increase in market share 41.4 645.8 5 33.5 635.8 6 Increase in the level of innovativeness 43.1 5 30.5 9 37.4 5 35.8 6 Increase in the number of customers 70.7 3 38.9 613.7 11 14.4 9 Improvement of customer service and increased consumer satisfaction level 44.8 4 36.6 7 17.6 10 8.0 12 Increase in the number of markets in which the company is active 8.6 9 31.3 8 28.6 8 28.9 7 Increasing the number of business partners, including those operating on in a virtual environment — — 29.8 10 33.0 7 37.8 5 Optimisation of performance of various business processes, including those relating to customer service 12.1 8 74.0 3 63.9 3 87.6 2 Development of digital supply chains — — 16.8 11 12.8 13 3.0 13 Increase in the general effectiveness of the company’s operations 29.3 7 30.5 9 13.2 12 22.4 8 Increasing flexibility of operations, which shows in the capability for launching new products and services quickly 8.6 9 15.3 12 7.5 14 11.4 11 Opportunity to get involved actively in programmes initiated in the virtual space to expand the range of goods and services or the database of customers — — 8.4 13 20.7 9 12.9 10 Source: Author’s own work. 136 Findings of Empirical Research Table 4.22 Company size v. company’s relationships with the environment Question 13. To what extent do digital technology platforms affect an increase in quality and intensity of relations established by the company? Company size Micro Small Medium Large N % N % N % N % To a very large extent 4 33.3 10 35.7 15 36.6 15 38.5 To a large extent 5 41.7 11 39.3 16 39.0 14 35.9 Neither to a large extent nor to a small extent 2 16.7 3 10.7 5 12.2 1 2.6 To a small extent 0 0.0 2 7.1 0 0.0 0 0.0 To a very small extent 0 0.0 0 0.0 5 12.2 1 2.6 Kruskal‑Wallis test of inter‑group comparisons Statistically insignificant Pearson’s chi‑square test of associations between variables and Cramér’s V contingency coefficient Statistically insignificant Source: Author’s own work. Table 4.21 Company size v. creating innovative business models Question 12. Do you agree with the statement that digital technology platforms make it possible to create and develop innovative business models? Company size Micro Small Medium Large N % N % N % N % Definitely agree 10 83.3 18 64.3 15 36.6 19 48.7 Rather agree 1 8.3 5 17.9 24 58.5 15 38.5 Neither agree nor disagree 1 8.3 5 17.9 1 2.4 5 12.8 Rather disagree 0 0.0 0 0.0 1 2.4 0 0.0 Definitely disagree 0 0.0 0 0.0 0 0.0 0 0.0 Kruskal‑Wallis test of inter‑group comparisons Statistically insignificant Pearson’s chi‑square test of associations between variables and Cramér’s V contingency coefficient Statistically insignificant Source: Author’s own work. Findings of Empirical Research 137 Table 4.23 Company size v. changes in the company’s organisational structure Question 14. Has the implementation of digital technology platforms in the company in forced the company to introduce specific changes to its organisational structure or will it be forced to do so? Company size Micro Small Medium Large N % N % N % N % Definitely so 3 25.0 3 10.7 5 12.2 4 10.3 Rather so 2 16.7 13 46.4 18 43.9 20 51.3 Neither agree nor disagree 1 8.3 3 10.7 7 17.1 9 23.1 Rather not 4 33.3 621.4 11 26.8 5 12.8 Definitely not 2 16.7 3 10.7 0 0.0 1 2.6 Kruskal‑Wallis test of inter‑group comparisons statistically insignificant Pearson’s chi‑square test of associations between variables and Cramér’s V contingency coefficient statistically insignificant Source: Author’s own work. Table 4.24 Company size v. organisational changes Question 15. What are (will be) the changes in the company’s organisational structure resulting from the implementation of digital technology platforms? Company size Micro Small Medium Large N % N % N % N % Opening a new branch of the enterprise 0 0.0 0 0.0 0 0.0 0 0.0 Liquidation of an existing branch of the enterprise 1 20.0 0 0.0 0 0.0 0 0.0 Setting up a new department(s) of the enterprise 3 60.0 9 56.3 626.1 3 12.5 Liquidation of an existing department/existing departments of the enterprise 0 0.0 1 6.3 0 0.0 1 4.2 Creation of a new job/position(s) 5 100.0 8 50.0 13 56.5 13 54.2 Liquidation of an existing job/ position(s) 1 20.0 1 6.3 0 0.0 2 8.3 Transferring specific groups of employees to another department/other departments of the enterprise 0 0.0 3 18.8 0 0.0 2 8.3 Transformations in the governance and managerial structure 1 20.0 8 50.0 7 30.4 9 37.5 (Continued) 138 Findings of Empirical Research cases of liquidating jobs as a result of the introduction of new solutions. In the situation, there is also a statistically significant relation between variables but it is not strong. For all enterprises, regardless of the headcount level, the most important benefits generated due to the use of digital platforms include growth of profits and increase in the competitiveness level. For companies employing up to 49 people, the factors Table 4.24 (Continued) Question 15. What are (will be) the changes in the company’s organisational structure resulting from the implementation of digital technology platforms? Company size Micro Small Medium Large N % N % N % N % Kruskal‑Wallis test of inter‑group comparisons Opening a new branch of the enterprise v. duration of use – statistically insignificant Liquidation of an existing branch of the enterprise v. duration of use – statistically insignificant Setting up a new department(s) of the enterprise v. duration of use – statistically insignificant Liquidation of an existing department/existing departments of the enterprise v. duration of use – statistically insignificant Creation of a new job/position(s) v. duration of use – statistically insignificant Liquidation of an existing job/position(s) v. duration of use – statistically insignificant Transferring specific groups of employees to another department/other departments of the enterprise v. duration of use – statistically insignificant Transformations in the governance and managerial structure v. duration of use – statistically insignificant Pearson’s chi‑square test of associations between variables and Cramér’s V contingency coefficient Opening a new branch of the enterprise v. duration of use – statistically insignificant Liquidation of an existing branch of the enterprise v. duration of use – statistically insignificant Setting up a new department(s) of the enterprise v. duration of use – statistically insignificant Liquidation of an existing department/existing departments of the enterprise v. duration of use – statistically insignificant Creation of a new job/position(s) v. duration of use – statistically insignificant Liquidation of an existing job/position(s) v. duration of use – statistically insignificant Transferring specific groups of employees to another department/other departments of the enterprise v. duration of use – statistically insignificant Transformations in the governance and managerial structure v. duration of use – statistically insignificant Source: Author’s own work. Findings of Empirical Research 139 of increasing the number of customers, improving customer service and raising the customer satisfaction level ranked higher than in the case of medium‑sized and large companies. In turn, for companies employing over 250 people, in contrast to the remaining types of enterprises, a higher rank is given to increasing the number of business partners. Representatives of all enterprises, regardless of the headcount level, nearly completely agree with the statement that DTPs make it possible to create and develop innovative business models. For all the enterprises, the typical responses are that using DTPs affects “to a very large” or “large extent” an increase in quality and intensity of relations established by the company with other entities operating in the environment. There are no significant differences in this respect among the analysed groups. For most companies, the implementation of DTPs was connected with the introduction of changes in the organisational structure. For enterprises employing over ten people, selections of changes were more than half (small – 57.1%, medium‑ sized – 56.1%, large – 61.6%). There are no significant differences between the groups when considering this aspect. The most frequently introduced changes in the companies’ organisational structure should include creation of new jobs, and for those employing up to 49 people – opening new departments. Transformations in the governance and managerial structure were selected by respondents from companies employing over ten employees. However, the populations of the groups are too small to draw conclusions about significant differences between the groups. Summing up this part of the work, it should be stressed that a model was built using the CATREG regression model for qualitative variables, which made it possible to verify the main proposition and research hypotheses H1 and H5. The model turned out to be statistically significant and explained 21.8% of variation of the dependent variable (P13). The model included nine independent variables. The most significant impact factors for the extent to which DTPs affect an increase in quality and intensity of relations established by the company with stakeholders are: – the variable concerning benefits generated by using DTPs (P11) – explains 38.6% of the variation of the dependent variable; – the industry in which the company operates (P23) – explains 20.8% of the variation of the dependent variable; – current or future changes made necessary by the implementation of DTPs (P14) – explains 10.7% of the variation of the dependent variable. The model was supplemented with additional meticulous analyses. Many weak but promising trails have been found, but they will need to be confirmed in further research. In this respect, it may be only mentioned that according to representatives of the surveyed companies, a correlative of the dependent variable is the conviction about a multifaceted impact of DTPs on a company (P10 v. P13). Furthermore, attention should be drawn to the following disclosed co‑variances (they are not too high but regular and statistically significant; they should be