Platform Patterns—Using Proven Principles to Develop Digital Platforms

Drewel, Marvin; Özcan, Leon; Gausemeier, Jürgen; Dumitrescu, Roman Article — Published Version Platform Patterns—Using Proven Principles to Develop Digital Platforms Journal of the Knowledge Economy Provided in Cooperation with: Springer Nature Suggested Citation: Drewel, Marvin; Özcan, Leon; Gausemeier, Jürgen; Dumitrescu, Roman (2021) : Platform Patterns—Using Proven Principles to Develop Digital Platforms, Journal of the Knowledge Economy, ISSN 1868-7873, Springer US, New York, NY, Vol. 12, Iss. 2, pp. 519-543, https://doi.org/10.1007/s13132-021-00772-3 This Version is available at: https://hdl.handle.net/10419/286988 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/4.0/ Vol.:(0123456789) https://doi.org/10.1007/s13132-021-00772-3 1 3 Platform Patterns—Using Proven Principles toDevelop Digital Platforms MarvinDrewel1 · LeonÖzcan1· JürgenGausemeier1· RomanDumitrescu1 Received: 27 February 2020 / Accepted: 14 February 2021 © The Author(s) 2021 Abstract Hardly any other area has as much disruptive potential as digital platforms in the course of digitalization. After serious changes have already taken place in the B2C sector with platforms such as Amazon and Airbnb, the B2B sector is on the threshold to the so-called platform economy. In mechanical engineering, pioneers like GE (PREDIX) and Claas (365FarmNet) are trying to get their hands on the act. This is hardly a promising option for small and medium-sized companies, as only a few large companies will survive. Small and medium-sized enterprises (SMEs) are already facing the threat of losing direct consumer contact and becoming exchangeable executers. In order to prevent this, it is important to anticipate at an early stage which strategic options exist for the future platform economy and which adjustments to the product program should already be initiated today. Basically, medium-sized companies in particular lack a strategy for an advantageous entry into the future platform economy. The paper presents different approaches to master the challenges of participating in the platform economy by using platform patterns. Platform patterns represent proven principles of already existing platforms. We show how we derived a catalogue with 37 identified platform patterns. The catalogue has a generic design and can be customized for a specific use case. The versatility of the catalogue is underlined by three possible applications: (1) platform ideation, (2) platform development, and (3) platform characterization. Keywords Digitalization · Digital platforms· Platform economy· Foresight· Strategic product planning· Multisided markets· B2B-platforms· Platform markets * Marvin Drewel [email protected] Extended author information available on the last page of the article / Published online: 10 March 2021 Journal of the Knowledge Economy (2021) 12:519–543 1 3 The Disruptive Potential ofDigital Platforms In the course of digitization, the concept of digital platforms or IT platforms has been the subject of a veritable hype in recent years (Engels etal.,,2017) and is experiencing an impressive renaissance (Linz etal., 2017). Digital platforms are putting established companies across industries under pressure. Former wellestablished enterprises like Nokia or Blackberry are now dominated by platform enterprises like Apple. Based on these changes, van Alstyne etal. have formulated the somewhat bold thesis that “only those who understand the principle and transform their business model will survive” (Alstyne etal., 2016). Up to now, this thesis has been mainly applied to the business-to-consumer (B2C) sector. There, digital platforms such as Uber, Airbnb, or Amazon have radically changed their industries and displaced formerly established companies (Libert etal., 2016). At present, such a development is also apparent in the B2B sector and here in particular in mechanical engineering and related sectors such as the electronics industry, automotive industry, or medical technology (Lerch et al., 2019). Leading companies are stepping out of their core business and develop own platforms. Additionally, agile start-ups begin to build platform solutions and services for digital platforms (Koldewey etal., 2019). Driven by digitization, such platforms can link actors who have never been in contact with each other (Altman etal., 2013). Following Parker etal., the disruptive potential of digital platforms is based on two major economic advantages: (1) marginal costs and (2) network effects. These advantages enable companies to expand their platform businesses with relatively low investments compared with traditional businesses (Cusumano etal., 2019; Parker etal., 2017). Marginal costs describe the additional costs that occur if an additional unit of a certain product or service is being produced (O’Sullivan & Sheffrin, 2003). For instance, if the Hilton Worldwide Holdings Inc. decides to expand to a new market, they need to invest in new buildings and new personal staff. Contrary to this, if Airbnb decides to expand to a new market, they do not need such investments. The new accommodations are provided by private home owners who also act as staff for the consumers of Airbnb. The additional costs for these new accommodations are almost not existing which allows platforms to expand their business with minimal costs, once their platforms are established and running (Alstyne etal., 2016). The network effect describes how the consumer value of a product changes when the number of consumers of the same product or complementary products changes. A distinction is made between the direct and indirect network effect. The direct network effect was described in 1986 by Katz and Shapiro and states that a product’s value changes with the total number of consumers of that product (Farrell & Saloner, 1992; Funk, 2009; Katz & Shapiro, 1986). Often referred examples for this effect are telephones and fax machines. Within the context of digital platforms, the direct network effect occurs, e.g., on social media platforms such as Facebook. The indirect network effect occurs when the value of a product changes as soon as the number of consumers of another product changes without 520 Journal of the Knowledge Economy (2021) 12:519–543 1 3 a direct relationship between these products (Shapiro & Varian, 1998). The indirect network effect is characteristic for two- or multisided markets. Thereby, an increased number of participants on the one side of the market tends to increase the number of participants on the other side of the market. This effect is the driving force behind digital platforms like Airbnb or Uber. Positive network effects are the foundation for digital platforms. Thus, the more participants a platform has, the more attractive it becomes for other participants. This is referred to as self-reinforcing “chain reactions” which—once initiated—lead to the rapid growth of digital platforms. This is the reason why for each market only a very limited number of platforms can economically exist (Eisenmann etal., 2006). An analysis of the historical development of the most valuable companies worldwide impressively visualizes the disruptive potential of digital platforms (Fig.1). While classic companies dominated the ranking in 1995, six of the ten most valuable companies were platform companies in 2018.1 It is striking that the number of valuable platform companies has increased rapidly in recent times. Companies can conduct classic activities along an input/output process and create a platform ecosystem while doing so. For example, the development, production, and distribution of Apple’s iPhone follow a classic value chain. At the same Fig. 1 The ten most valuable companies from 1995 to 2018 by market capitalization in billion US dollars (fortiss Gmbh, 2016; Kempe, 2011; Payment & Banking, 2019) 1 In order to distinguish classic companies from platform companies, the term pipeline company has established itself in the scientific literature. Classic companies operate according to the value chain described by Porter in 1985. The dominant activities of these companies take place in a classical input/ output process (Porter, 1985). Platform companies on the other hand place the operation of a digital platform at the center of their business activities and pursue the goal of maximum ecosystem value (Parker etal., 2017). 521Journal of the Knowledge Economy (2021) 12:519–543 1 3 time, Apple has created a platform ecosystem around its iOS operating system in which the iPhone is embedded. With the introduction of the iOS platform in 2007, Apple was able to capture a significant share of the global smartphone market within just a few years. Apple’s core business is the sale of hardware components, which accounts for 80% of its revenues. However, the success of the company and thus also the sale of the hardware is significantly influenced by the platform character of the company (Reillier & Reillier, 2017). In the following section, we will discuss the way digital platforms work in order to understand the reasons for the success of digital platforms. The Way Digital Platforms Work andWhy Established Enterprises Struggle withIt The success of a digital platform is not based on internal resources, but on the ecosystem in which the platform is embedded. The acatech–National Academy of Science and Engineering takes up the concept of the platform ecosystem and states that a platform ecosystem describes the economic mechanisms behind digital platforms as well as the stakeholders involved and their relationships (Engels etal., 2017). According to Evans and Schmalensee, these stakeholders include all persons, companies, institutions, and other environmental factors that influence the value created by a platform (Evans & Schmalensee, 2016). This value is created by platforms using stakeholder data to orchestrate physical and digital resources across the ecosystem (Choudary, 2015). We therefore understand a digital platform as a two or multisided market in which the different actors are brought together by an intermediary and propose an arrangement of roles within a digital platform as shown in Fig.2. The different actors are assigned to the category platform core, platform participants, and platform environment (Drewel etal., 2018). If, for example, the number of producers increases, the platform becomes more attractive for consumers and vice versa (Eisenmann etal., 2006). The core value of a platform company is not a classic physical value unit, but an infrastructure that enables interactions between producers and consumers. The design of the key interaction is therefore the core of each digital platform. The key interaction is the reason why participants use digital platforms (Jaekel, 2017; Parker etal., 2017). The anatomy of a key interaction consists of four characteristics (Choudary, 2015), (Moazed & Johnson, 2016): (1) Value creation: Each key interaction involves at least one producer who creates the value unit. The production of value units by the producer marks the starting point of a platform interaction (Parker etal., 2017), (Jaekel, 2017), (Moazed & Johnson, 2016). (2) Connection: The connection of producers and consumers is enabled through filtering and individualization of the platform content. Filtering ensures that only high-quality value units are offered. Filter mechanisms support desirable and punish undesirable behavior (Choudary, 2015; Jaekel, 2017). With the help of filters, a specific consumer gains access to the content relevant to him. Digital 522 Journal of the Knowledge Economy (2021) 12:519–543 1 3 platforms that are able to provide their consumers with individualized content encourage them to continue participating (Parker etal., 2017). (3) Consumption: Each key interaction involves at least one platform participant who consumes the value unit that is relevant for him or her. Consumption can take different forms depending on the value unit. For example, the consumption of digital value units often takes place directly via the platform (Choudary, 2015; Jaekel, 2017; Moazed & Johnson, 2016). (4) Compensation: The key interaction is completed with compensation. It is characteristic that the consumer transmits a return service to the producer for the value unit received (Moazed & Johnson, 2016). In a key interaction, information, value units, and payments are exchanged between the platform participants. A producer and a consumer first exchange information. Then, the producer transmits a value unit to the consumer and receives a payment in return. The payment does not always have to be monetary, but can also take the form of data, evaluations, etc. The payment can also be made in form of a payment slip. The number of key interactions increases with the scope of services/products offered and the number of participants in the platform ecosystem. The constantly repeating key interactions are made possible by three basic functions of a platform (Choudary, 2015; Cusumano etal., 2019; Moazed & Johnson, 2016; Parker etal., 2017): Fig. 2 Roles in a digital platform (Baums, 2015; Drewel etal., 2018; Tiwana, 2014) 523Journal of the Knowledge Economy (2021) 12:519–543 1 3 • Match: The most relevant value units must always be provided for the consumers. With an increasing number of producers, the scope of the platform offerings increases, making it more difficult for consumers to identify the desired offer. Filters are suitable for merging the value unit provided by the producer with the corresponding consumer. • Facilitate: Platform companies do not control value creation, but provide an infrastructure that enables value creation. Programs are introduced and policies established that regulate interactions and promote desired behavior. Filter mechanisms ensure that high-quality content is provided on the platform and that desirable interactions are enabled. • Pull: Key interactions are made possible by luring participants to the platform and keeping them there. Platforms have to overcome the chicken and egg problem (Who joins the platform first? Producer or consumer?). The aim is to make participation on the platform as easy as possible for potential participants. Since the focus of business activities is on repetitive interactions, it must be ensured that the participants are regularly active. In order to prevent unwanted behavior of the platform participants, membership checks can be useful. In summary, the pull effect enables the quantitative scaling of a platform by promoting production and consumption. Filter mechanisms ensure that the quality of the consumer experience is guaranteed as the platform grows (Jaekel, 2017). On the basis of the filtered and individualized content, suitable producers and consumers can interact in key interactions and initiate the exchange. Figure3 shows an aggregated representation of the functionality of a digital platform. While the awareness of the economic potential of the platform model is growing (Evans & Gawer, 2016), many established companies have considerable difficulties mastering the challenges of developing own platforms and initiating the Fig. 3 Aggregated representation of the functionality of a digital platform 524 Journal of the Knowledge Economy (2021) 12:519–543 1 3 powerful chain reactions based on network effects (Parker etal., 2017). Two reasons for this are the lack of knowledge concerning the development of digital platforms and new ways to monetarize the platform business (Engels etal., 2017). Evans and Schmalensee underline the lack of knowledge concerning multisided markets and the connected difficulties in understanding how digital platforms work as a central challenge (Evans & Schmalensee, 2016). Choudary describes three primary shifts in the way towards multisided markets (Choudary, 2015): (1) Shift in markets: Traditionally, the consumer was at the end of a pipeline where producers produced the good for the consumer. Digital platforms do not create the end value but enable value creation between various producers and consumers. As a result, participants on digital platforms can take on production as well as consumption. (2) Shift in competitive advantage: Pipeline enterprises compete through managing resources and intellectual property. This does not apply to digital platforms. Platform enterprises focus on orchestrating and enabling value-exchanging interactions and using data about the various participants within the ecosystem. The management of ecosystems is therefore the key competitive advantage in platform economies. (3) Shift in value creation: The value in pipeline markets is created through processes that organize a company’s labor and resources. Such markets focus on the efficiency of business processes. The value creation in platform markets, however, is focused on the number and quality of interactions. It is based on orchestrating these interactions between consumers and producers. The three described shifts show that the rules in platform markets are completely different from pipeline markets. The way companies interact with markets, build competitive advantage, and create value is new for the majority of traditional companies. The disruptive potential of digital platforms is promising for those companies that are able to establish a digital platform, but involves some risks that are connected to the development of a platform: • Reaching critical mass is a prerequisite for entering the lucrative growth phase of a digital platform. To achieve this, platform owners must overcome the chicken-and-egg problem, which has already caused many platforms to fail (Caillaud & Jullien, 2003). • Digital platforms require high investments in the underlying IT infrastructure. Furthermore, in the first phases of a platform’s life, a considerable marketing effort is necessary to attract sufficient participants. Platform operators need a high amount of money to bridge the initial costs (Libert etal., 2016). • The platform owner must be aware of the risk of liability issues. The unclear legal situation currently leads to an increased liability of platform operators (Härting, 2015). • Digital platforms are changing the way companies create value. For traditional pipeline activities, the focus is on maximizing consumer value; for platform 525Journal of the Knowledge Economy (2021) 12:519–543 1 3 activities, the focus is on maximizing ecosystem value. This may require subsidizing certain consumer groups to attract others. These changes are often confronted with opponents within your own company (Parker etal., 2017). • Building a digital platform requires new skills (e.g., developing platform business models) and resources (new IT systems), which are often not available in established companies. Especially for small- and medium-sized enterprises, the development of the necessary skills represents a risk when entering the platform economy (Engels etal., 2017). The development of a platform is associated with significant opportunities such as increased sales and consumer loyalty. However, companies must also be aware of the risks. Many platforms fail to achieve critical mass and the high initial costs of successful platform operation. Small- and medium-sized companies in particular lack opportunities to enter the platform economy. These companies need knowledge of existing platforms and best practices to master the leap into the platform economy. These knowledge deficits of companies can be eliminated by using patterns. Platform patterns represent proven principles of already existing platforms. Therefore, they are considered in the following analysis of approaches to develop digital platforms. Approaches toDevelop Digital Platforms There are several approaches in the scientific literature that are dedicated to the entry into the platform economy. These can be roughly divided into three categories: (1) canvas-based approaches to design a platform business, (2) specific approaches to develop digital platforms, and (3) pattern-based approaches to develop digital platforms. (1) Canvas-based approaches: In holistic framework models, several relevant elements of digital platforms are considered in aggregated form. The aim of these framework models is to support companies in planning and building their own digital platforms. An example is provided by Choudary, who describes a four-stage process for building a digital platform based on key interaction. This construction process is tangled by a platform canvas, which shows all elements relevant for the platform construction (Choudary, 2015). Similar canvas-based approaches for platform construction are provided by Walter and Lohse as well as Cicero (Walter & Lohse, 2018; Boundaryless S.r.l., 2019). The approaches of Cicero as well as Walter and Lohse include a comprehensive portfolio of tools to analyze the needs of platform participants in detail and to develop a validated concept for a digital platform. The high level of interactivity through supporting software solutions as well as the comprehensive analysis of the platform potential are to be positively emphasized. However, the multitude of tools and the required comprehensive know-how make the application considerably more difficult for the practitioner. (2) Specific approaches to develop digital platforms: In order to successfully complete the platform construction, more than mere knowledge of a corresponding procedure is required. Against this background, approaches have been incorporated 526 Journal of the Knowledge Economy (2021) 12:519–543 1 3 Platform Patterns asaWay toGenerate New Ideas The developed patterns can be used as a creativity technique to generate new ideas for digital platforms. As stated by Csik, patterns have a positive effect on the results of creativity processes. The effect is based on the fact that patterns cause certain stimuli which promote creativity (Csik, 2014). In extension of Gassmann etal., the generation of ideas by means of patterns is based on two principles: (1) pattern association and (2) pattern confrontation (Amshoff etal., 2015; Gassmann etal., 2014). The principles are shown in Fig.9. Pattern association: Here, an idea for a digital platform is already available in advance, which can be assigned to a pattern from the framework. In this way, existing ideas can be further concretized (Amshoff etal., 2015). Pattern confrontation: With this principle, a pattern is chosen at random and presented to the persons involved. This provocation allows existing thought patterns to be broken through; completely new ideas for digital platforms with the potential for radically new functions emerge (Gassmann etal., 2014). We used our framework for both principles within various workshops and validated its applicability to generate new ideas for digital platforms. The validation was carried out as part of a research project to initiate a digital marketplace for artificial intelligence applications for product engineering. In the following, an exemplary approach to pattern association and pattern confrontation is presented. Pattern Association The starting point of the pattern association is an idea provided in advance. In our workshops we discussed the idea of a marketplace for applications of artificial intelligence in product engineering. The aim of the workshop was to concretize this idea on the basis of the identified patterns. The workshop was carried out with 35 participants from SMEs, research institutes and associations and federations within the field of product engineering. Figure10 shows the concept of the workshop. The workshop participants used characteristic platform participnts of the marketplace and their problems to generate and improve their ideas to form a holistic concept for the AI-Marketplace. Fig. 9 Principles to generate ideas for platforms in accordance with Amshoff etal., (2015) 533Journal of the Knowledge Economy (2021) 12:519–543 1 3 We conducted a second workshop with 30 participants with the same task. Within the second workshop, we did not use the patterns for digital platforms but also the characteristic platform participants of the digital marketplace. We found that the group without the patterns had considerable difficulties in developing ideas for such a marketplace. The concept of digital marketplaces had to be explained more than once and in much more detail. Moreover, the generated ideas were often not applicable for a digital marketplace but rather for a “simple” application for a potential marketplace. The differences between the idea generation with patterns and without patterns are presented in “Differences in the Generation of Ideas with and Without Patterns”. Pattern Confrontation We conducted another workshop to generate ideas for a digital platform based on the concept pattern confrontation. The ideas were generated with 38 participants from research institutes and employees of machine learning companies. The participants used the platform patterns to directly generate ideas for an Fig. 10 Pattern association workshop to generate ideas for a digital marketplace 534 Journal of the Knowledge Economy (2021) 12:519–543 1 3 AI-Marketplace (see Fig.11). The patterns were randomly selected from the pattern catalogue in order to determine the greatest possible heterogeneity between the different ideas. We found that the participants of the workshop understood the new concept of digital platforms much faster and easier than in workshops with a similar task but without the pattern confrontation. Moreover, the participants were enthusiastic about the task and developed quite radical new ideas. The differences between the two approaches and workshops without patterns are presented in “Differences in the Generation of Ideas with and Without Patterns”. Differences intheGeneration ofIdeas withandWithout Patterns Within our workshops, we found clear distinguishing factors between the generation of ideas for a digital platform by pattern association, pattern confrontation, and without any patterns at all. The analysis of the factors is based on one workshop for each approach with 30 to 38 participants. Within these workshops, we formed small groups of five participants which gives us six to eight data sets for each approach. The presented findings are based on the results of the workshops which can be grouped into three categories: Hard facts: Number of ideas Soft facts: Feasibility of the ideas, radicality of ideas, user orientation of ideas Gut feeling: Understanding of the task, enthusiasm of the participants Figure12 represents the findings of the workshops. The qualitative results show that the application of patterns leads to better results and better workshops. While both approaches work well, we could still see clear differences between the pattern association and pattern confrontation. The pattern association generates more ideas with a high feasibility and user orientation. The pattern confrontation on the other hand delivers less, but much more radical ideas. Also, the understanding of the task and the enthusiasm of the participants is a little higher than by pattern association. In order to summarize the findings, it can be stated that the pattern association is particularly suitable for workshops with the goal of many user-oriented ideas. Fig. 11 Pattern confrontation to generate ideas for a digital marketplace 535Journal of the Knowledge Economy (2021) 12:519–543 1 3 Pattern confrontation, on the other hand, should be used to generate more radical ideas. In addition, both approaches can be combined, e.g., by first developing ideas via characteristic platform participants of a possible marketplace and the association of patterns. In order to further develop these ideas, new patterns from the catalogue can then be used. Pattern‑Based Development ofDigital Platforms The pattern-based development of digital platforms includes the phases ideation, conception, and development of digital platforms (Amshoff etal., 2015). The basic Fig. 12 Distinguishing factors between the generation of ideas for a digital platforms by pattern association, confrontation, and without patterns Fig. 13 Basic principle of pattern-based platform development (Amshoff, 2015) 536 Journal of the Knowledge Economy (2021) 12:519–543 1 3 principle is shown in Fig.13. Following Amshoff, an abstract and a specific area are distinguished. The specific area describes the point of view of a company which wants to realize a platform idea. The abstract area contains the generalization of the platform in the form of patterns. The different phases of the pattern-based development of digital platforms are explained below. This process must be conducted every time a new platform is initiated. Part of the platform ideation is the formulation of a specific platform idea, which is called platformization mission. Subsequently, the process for applying platform patterns (beginning “How to Use Patterns for Digital Platforms”) is used to assign patterns to each of the design fields according to the platform mission described. The guiding questions provided for this purpose support the applying user when assigning appropriate patterns to the design fields. Once all the design fields are characterized by answering the guiding questions and applying the patterns, a company can define its concept for a digital platform. For this purpose, the individually selected patterns are brought together, avoiding the combination of conflicting patterns and taking into account the choice of patterns that favor each other. This pattern combination corresponds to the core of the platform conception. The result of this analysis step is an abstract platform concept. The concept is documented and is exemplarily shown in Fig.14. The platform development addresses the transformation of the abstract platform concept into an elaborated and company-specific digital platform. Characterization ofPopular Platform Enterprises Platform companies currently have an unprecedented economic dominance. Established companies not only find it difficult to participate in the economic rise of the Fig. 14 Concept for a digital platform within the machine building industry 537Journal of the Knowledge Economy (2021) 12:519–543 1 3 platform economy. It is often the case that they do not even have the necessary platform knowledge to understand the business activities of major platform companies. Against this background, the identified platform patterns can be used to make the business activities of successful platform companies transparent. The investigation of these existing platform companies allows to reveal potential gaps in the existing pattern catalogue. Moreover, established companies gain insights into platform companies and can understand what they do differently. This offers the possibility of generating new ideas, e.g. by addressing the weaknesses of existing platforms (Köster, 2014). The patterns are then used to generate ideas for better solutions (Markides, 2008). In the following, it is exemplary presented with which patterns the well-known B2C platform Uber (see Fig.15) became successful and which patterns were used for the mentioned B2B platform “AI-Marketplace” (see Fig.16). Uber is a platform for the brokerage of driving services and thus relies on the value unit (level 1) pattern standardized service. In order to attract both drivers and passengers to the platform, various patterns of participant acquisition were and are used (level 2). One example is the micromarket. By using this pattern, Uber initially set up its services locally limited in selected cities such as San Francisco to be able to benefit more quickly from positive network effects. In anatomy of transaction (level 3), the pattern information and return is used. This means that only the value unit (the trip) is directly transmitted between driver and passenger outside the platform. The exchange of information and money takes place via the platform. For the design of the platform infrastructure (level 4), the exemplary pattern active filter is used. Passengers actively transmit data to Uber so that the best driver can Fig. 15 Characterization of the B2C platform Uber with platform patterns (extract) 538 Journal of the Knowledge Economy (2021) 12:519–543 1 3 be provided to the consumer. The fifth level monetization is served with the pattern transaction fees. By using this pattern, Uber retains a portion of the passenger’s compensation payment for each completed transaction between driver and passenger. At the final layer further ecosystem participants, Uber relies on the pattern partner relationship and offers external partners access to the platform through APIs to increase the functionality. In addition to the transport service provider Uber, the AI-Marketplace will be presented as an example of a B2B platform (see Fig.16). The AI-Marketplace is a digital platform that connects producers of AI-applications for the product development with manufacturing companies. For example, manufacturing companies can have existing design drawings optimized using an AI-application (e.g. in terms of material consumption or stiffness). Virtual goods (AI-applications) and standardized services (AI-Consulting) are the value provided by the marketplace (level 1) of this platform. The platform starts in a small region of Germany and uses an existing innovation-ecosystem (it´s OWL). The companies within this ecosystem trust each other and some of these companies are even part of the project behind the AI-Marketplace. The pattern micromarket was therefore used to attract initial participants. Further on, the patterns marketing push and acquiring Fig. 16 Characterization of the B2B platform AI-Marketplace with platform patterns 539Journal of the Knowledge Economy (2021) 12:519–543 1 3 participants were used to attract platform participants from whole Germany (level 2). Producers of AI-Applications and manufacturing companies were already in contact before the AI-Marketplace came into existence. The AI-Marketplace has established itself between these actors by facilitating exchanges and offering complementary value units. For the transaction anatomy (level 3), the pattern complete ownership is used. Value unit, information, and monetary consideration are handled via the digital platform. Editorial curating as well as active filter are used for the platform infrastructure (level 4). The AI-Marketplace charges transaction fees for the procurement of AI-applications. In addition, a listing fee is charged for selected advertisements and highlighting of offers is made possible in order to generate further revenues (level 5). The AI-Marketplace is open for further owners, which will mostly be from the leading edge innovation-ecosystem it’s OWL. Therefore, the pattern ownership structure is used (level 6). The presented examples show that the pattern catalogue can be used to characterize any given digital platform. We found that by doing so, companies can understand the business of potential competitors and were even able to develop their own digital platforms. Moreover, some companies used the characterization of potential competing platforms in order to improve their own solution. Summary andOutlook Digital platforms are becoming increasingly widespread in the industry and companies are on their way into the platform economy. While the awareness of the economic potential of the platform model is growing, many established companies have considerable difficulties mastering the challenges of participating in the platform economy. An exemplary challenge is the completely new form of value creation of platform companies, which is largely unknown to manufacturing companies. To overcome the challenges of the platform economy, clever strategic action is more important than ever. A first starting point for entering the platform economy is the methodical approach presented here. The patterns and methods provided help to master the entry into the platform economy and to reduce uncertainties. Patterns represent proven principals and can thereby provide valuable know-how for business activities in the platform economy. We identified 37 patterns and structured them in a catalogue which makes the patterns useable. To do so, we provide a process model which systematizes the design fields of a digital platform. Due to the high dynamics and short innovation cycles, the catalogue provided should be regularly reviewed and updated or expanded. It goes without saying that the entry into the platform economy does not stop with the development of promising concepts. Further approaches, such as specification techniques to describe platforms, are needed to support companies in coping with the transformation from pipeline to platform markets. The characterization of the first platforms has yielded promising results. In the future, a large number of established platforms will be characterized using the patterns to identify common combinations. Moreover, we were able to gain some additional theoretical insights, e.g., (a) platform categories are often taken up in the scientific discussion but a uniform 540 Journal of the Knowledge Economy (2021) 12:519–543 1 3 differentiation does not exist yet. (b) Besides technical knowledge gaps companies often do not know how to earn money with platforms. (c) The manufacturing industry is particularly concerned about the loss of consumer access due to digital platforms. Funding Open Access funding enabled and organized by Projekt DEAL. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creat iveco mmons .org/ licen ses/by/4.0/. References Alexander, C. (1979). The timeless way of building (24th ed.). New York, NY: Oxford Univ. Press. Alexander, C., Ishikawa, S., & Silverstein, M. (1977).A pattern language: Towns, buildings, construction, 18th edn. Alstyne, M. W., Parker, G. G., & Choudary, S. P. (2016). Pipelines, platforms and the new rules of strategy. Harvard Business Review, 94(4), 54–62. Altman, E. J., Nagle, F., & Tushman, M. L. (2013). Innovating without information constraints: Organizations, communities, and innovation when information costs approach zero [Online], Cambridge, Mass. (Harvard Business School working paper). Available at http://www.hbs.edu/facul ty/ Pages /item.aspx?num=45932 Amshoff, B., Dülme, C., Echterfeld, J., & Gausemeier, J. (2015). Business model patterns for disruptive technologies. International Journal of Innovation Management, 19(03), 1540002. Baums, A. (2015). Analyse: Was sind digitale Plattformen? In A. Baums, M. Schlössler, & B. Scott (Eds.), Kompendium Industrie 4.0: Wie digitale Plattformen die Wirtschaftverändern – und wie die Politik gestalten kann (pp. 13–24). Berlin: Kompendium Digitale Standortpolitik. Blessing, L. T. M. & Chakrabarti, A. (2009).DRM, a Design Research Methodology [Online], London, Springer London. Available at http://site.ebrar y.com/lib/allti tles/docDe tail.actio n?docID =10310 350 Boundaryless. (2019). Platform Design Toolkit 2.2 – User Guide. Caillaud, B., & Jullien, B. (2003). Chicken & egg: Competition among intermediation service providers. The RAND Journal of Economics, 34(2), 309. Choudary, S. P. (2015). Platform scale: How an emerging business model helps startups build large empires with minimum investment. Boston: Platform Thinking Labs Pte. Csik, M. (2014). Muster und das Generieren von Ideen für Geschäftsmodellinnovationen [Online], Bamberg. Available at http://www1.unisg .ch/www/edis.nsf/SysLk pById entifi er/4263 Cusumano, M. A., Gawer, A., & Yoffie, D. B. (2019). The business of platforms: Strategy in the age of digital competition, innovation, and power. New York, NY: HarperCollins Publishers. Lerch, C., Meyer, N., Horvat, D., Jackwerth-Rice, T., Jäger, A., Lobsiger, M., & Weidner, N. (2019).Die volkswirtschaftliche Bedeutung von digitalen B2B-Plattformen im Verarbeitenden Gewerbe. Drewel, M., Gausemeier, J., Koldewey, C. & Özcan, L. (2018). ‘Pattern based development of digital platforms’, Proceedings of ISPIM Connects Fukuoka: Solving Challenges Through Innovation. Fukuoka, Japan, 2.12.-5.12.2018. Fukuoka, ISPIM. Edelmann, B. (2015). How to launch your digital platform. Harvard Business Review, Heft, 4, 90–97. Eisenmann, T., Parker, G. G., & Alstyne, M. W. (2006). Strategies for two-sided markets. Harvard Business Review, Heft, 10, 92–101. Engels, G., Plass, C., & Rammig, F. J. (Eds.). (2017). IT-Plattformen für die Smart Service Welt (acatech Diskussion). München: Herbert Utz Verlag. 541Journal of the Knowledge Economy (2021) 12:519–543 1 3 Evans, D. S., & Schmalensee, R. (2016). Matchmakers: The new economies of multisided platforms. Boston: Harvard Business Review Press. Evans, P. C., & Gawer, A. (2016). ‘The Rise of the Platform Enterprise: A Global Survey’, The Emerging Platform Economy Series, No. 1. Farrell, J., & Saloner, G. (1992). Converters, compatibility, and the control of interfaces. The Journal of Industrial Economics, 40, 9–35. fortiss Gmbh. (2016). Digitale Transformation: Wie Informations- und Kommunikationstechnologie etablierte Branchen grundlegend verändern, München, fortiss GmbH. Funk, J. L. (2009). Direct network effects, small-world networks, and industry formation. Telecommunications Policy, 33(5–6), 241–252. Gassmann, O., Frankenberger, K., & Csik, M. (2014).The business model navigator: 55 models that will revolutionise your business, Harlow, England, London, New York, Boston, San Francisco, Pearson. Hagiu, A., & Altman, E. J. (2017). Finding the platform in your product. Harvard business review: HBR, 95(4), 94–100. Härting, N. (2015). Haftungsverschärfungen für Plattform-Betreiber: Der Beginn des Zeitalter der Plattformregulierung? In A. Baums, M. Schlössler, & B. Scott (Eds.), Kompendium Industrie 4.0: Wie digitale Plattformen die Wirtschaftverändern – und wie die Politik gestalten kann (pp. 98–107). Berlin: Kompendium Digitale Standortpolitik. Jaekel, M. (2017).Die Macht der Digitalen Plattformen: Wegweiser Im Zeitalter Einer Expandierenden Digitalsphäre und Künstlicher Intelligenz [Online], Wiesbaden, Vieweg. Available at https :// ebook centr al.proqu est.com/lib/gbv/detai l.actio n?docID =51222 11 Katz, M., & Shapiro, C. (1986). Product compatibility choice in a market with technological progress. Oxford Economic Papers, 38, 146–165. Kempe, C. (2011). ‘Die größten Unternehmen im Wandel der Zeit’, Portfolio Institutionell, Ausgabe 1. Kohls, C. (2014). The theories of design patterns and their practical implications exemplified for e-learning patterns, Eichstätt-Ingolstadt, Katholische Universität Eichstätt-Ingolstadt, Diss., 2014, Eichstätt-Ingolstadt, Katholische Universität Eichstätt-Ingolstadt. Koldewey, C., Evers, H. H., Dumitrescu, R., Frank, M., Gausemeier, J., & Reinhold, J. (2019). ‘Development Process for Smart Service Strategies: Grasping the Potentials of Digitalization for Servitization’, proceedings of The XXX ISPIM INNOVATION CONFERENCE - Celebrating Innovation - 500 Years Since Da Vinci. Florence, Italy, 16–19 June. Florence, ISPIM. Köster, O. (2014). Systematik zur Entwicklung von Geschäftsmodellen in der Produktentstehung (Dissertation, Fakultät für Maschinenbau, Universität Paderborn) [Online], Paderborn. Available at https ://katal og.ub.uni-pader born.de/recor ds/PAD_ALEPH 00172 7007 Libert, B., Beck, M., & Wind, J. (2016). The network imperative: How to survive and grow in the age of digital business models. Boston: Harvard Business Review Press. Linz, C., Müller-Stewens, G., & Zimmermann, A. (2017). Radical Business Model Transformation: Gaining the Competitive Edge in a Disruptive World [Online], London, Kogan Page. Available at https ://ebook centr al.proqu est.com/lib/gbv/detai l.actio n?docID =47736 46 Markides, C. (2008). Game-changing strategies: How to create new market space in established industries by breaking the rules [Online], San Francisco, CA, Jossey-Bass. Available at http://searc h. ebsco host.com/login .aspx?direc t=true&scope =site&db=nlebk &db=nlabk &AN=23313 4 Moazed, A., & Johnson, N. L. (2016). Modern monopolies: What it takes to dominate the 21st-century economy. New York: Martin’s Press. O’Sullivan, A., & Sheffrin, S. M. (2003). Economics: Principles in action. Needham, Mass: Prentice Hall. Parker, G., van Alstyne, M., & Choudary, S. P. (2017).Platform revolution: How networked markets are transforming the economy - and how to make them work for you, New York, London, W.W. Norton & Company. Payment & Banking. (2019).Infografik: Die wertvollsten Unternehmen (1990–2018) [Online]. Available at https ://payme ntand banki ng.com/die-wertv ollst en-unter nehme n-1990-2018/(Accessed 1 July 2019). Porter, M. E. (1985). Competitive Advantage – Creating and Sustaining Superior Performance. New York: The Free Press. Reillier, L. C., & Reillier, B. (2017).Platform Strategy: How to unlock the power of communitites and networks to grow your business, London, Routledge. Shapiro, C., & Varian, G. R. (1998). Information rules: A strategic guide to the network economy. Boston: Harvard Business Review Press. 542 Journal of the Knowledge Economy (2021) 12:519–543