Worldwide innovation and technology environments: Research and future trends involving open innovation

Baierle, Ismael Cristofer et al. Article Worldwide innovation and technology environments: Research and future trends involving open innovation Journal of Open Innovation: Technology, Market, and Complexity Provided in Cooperation with: Society of Open Innovation: Technology, Market, and Complexity (SOItmC) Suggested Citation: Baierle, Ismael Cristofer et al. (2021) : Worldwide innovation and technology environments: Research and future trends involving open innovation, Journal of Open Innovation: Technology, Market, and Complexity, ISSN 2199-8531, MDPI, Basel, Vol. 7, Iss. 4, pp. 1-18, https://doi.org/10.3390/joitmc7040229 This Version is available at: https://hdl.handle.net/10419/274289 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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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/ Journal of Open Innovation: Technology, Market, and Complexity Article Worldwide Innovation and Technology Environments: Research and Future Trends Involving Open Innovation Ismael Cristofer Baierle * , Julio Cezar Mairesse Siluk , Vinicius Jaques Gerhardt , Cláudia de Freitas Michelin, Álvaro Luiz Neuenfeldt Junior and Elpidio Oscar Benitez Nara   Citation: Baierle, I.C.; Siluk, J.C.M.; Gerhardt, V.J.; Michelin, C.d.F.; Junior, Á.L.N.; Nara, E.O.B. Worldwide Innovation and Technology Environments: Research and Future Trends Involving Open Innovation. J. Open Innov. Technol. Mark. Complex. 2021,7, 229. https://doi.org/ 10.3390/joitmc7040229 Received: 30 September 2021 Accepted: 21 October 2021 Published: 25 November 2021 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). Department of Production and Systems Engineering, Federal University of Santa Maria, Santa Maria 97105-900, Brazil; [email protected] (J.C.M.S.); viniciusgerhar[email protected] (V.J.G.); [email protected] (C.d.F.M.); [email protected] (Á.L.N.J.); [email protected] (E.O.B.N.) *Correspondence: [email protected] Abstract: Innovation environments are places where open innovation and technology are boosted. The purpose of this paper is to present the evolution of innovation and technology environments through the most covered topics in the scientific literature. In this sense, technology transfer has been the subject of research since 1975; however, in the period from 2006–2021, the focus shifted to innovation. It was possible to observe an exponential growth of the term, “innovation”, but it is no longer the central theme and is linked to different terms related to different ways of innovating, characterizing open innovation variables. In this article, 4650 academic studies involving innovation environments were reviewed. The analysis identified the nomenclatures that characterized innovation environments and the particularities of these environments. The contributions, such as which countries developed more research in this area, and the analysis of which environments were more common in these countries were also presented. Additionally, some methodological and theoretical gaps in the current research were identified, providing pathways to support future research and practices seeking a better understanding and development of innovation environments. This article can also serve as a basis for a consultation for members of the quadruple helix, who wish to install or create environments for innovation and attract companies or investments to develop any open innovation activity. Keywords: innovation environment; technology transfer; innovation ecosystem; open innovation 1. Introduction Innovation environments are places where technology and innovation are boosted and encouraged among companies [ 1 ]. These spaces for research and development aim to sustain the character of “public good”, uniting and creating compatible public policies and scientific studies [ 2 ]. A region with a better innovation environment can provide companies with a better infrastructure, better human capital, and greater knowledge resources [ 3 ]. The companies seeking innovation environments must rely on capabilities based on the technologies transmitted and supported by larger companies geographically placed in prominent clusters [ 4 ]. An innovation environment focusing on dynamics and co-evolution is considered as one of the main drivers of open innovation and subsequent technology transfer [5]. Due to risk and uncertainty [ 6 ], it is difficult to predict the achievements of innovation initiatives [ 7 ]. Seeking help in an innovation environment best suited to a particular type of innovation can aid the development of different types of open innovation, increasing the positive impacts and reducing risks and uncertainty [ 6 ]. On the other hand, managers have doubts about how to achieve higher levels of industrial performance through the correct use of technologies generated by open innovation processes [ 8 ], which can be accelerated by technology transfer. The technology transfer process allows the actors of the quadruple helix to access new manufacturing methods, technologies, or specific knowledge [ 9 ]. This J. Open Innov. Technol. Mark. Complex. 2021,7, 229. https://doi.org/10.3390/joitmc7040229 https://www.mdpi.com/journal/joitmc J. Open Innov. Technol. Mark. Complex. 2021,7, 229 2 of 18 expands the access to scientific and technological innovations and, to this end, allows the creation of new products, services, materials, and applications [10]. Given the adherence of contextualized themes, and based on the literature, innovation and technology transfer are stimulated in innovation environments, but these environments must be dynamic, entrepreneurial, and be integrated with academic and scientific research. Over the years, different studies have characterized innovation environments, encompassing different research areas and regions into different clusters. The data from European countries show that countries that are leaders in innovation perform better economically than countries with low levels of investment in innovation activities and technology transfer [ 11 ]. Analyzing the level of development and the characteristics of innovation environments in different countries with relationship networks, can aid in setting a future trend for research that helps emerging countries, as well as countries that are looking to expand their research and public policies of innovation environments [ 12 ]. In this sense, the purpose of this paper is to present the evolution of the innovation and technology environment through the most covered topics in the scientific literature. To achieve this goal, five research questions (RQ) will be answered: RQ1—What is the evolution of studies related to the innovation and technology environments over time?; RQ2—Which research areas have the greatest connection to the development of the innovation and technology environments?; RQ3—Studies related to the innovation and technology environments are most prominent in which countries?; RQ4—In the innovation and technology environments, is there evidence of cross-country specifications?; RQ5—What is the trend for open innovation and future research related to innovation and technology environments? To answer these questions, a bibliometric review was developed, which presented an analysis of all the research conducted over the years involving innovation and technology environments. This study indicates opportunities for developing research focused on the most widespread environments, showing which countries stand out in this theme, showing the future trends, and indicating in which environments company managers can seek support. 2. Materials and Methods In this section, we present a brief review of the literature on open innovation and then present the methodology of the scientific research. 2.1. Literature Review of Open Innovation The challenges introduced by global competition force companies to grow and lead innovation initiatives [ 13 ]. Therefore, innovation has become the goal for companies interested in expanding business, involves different types of change, and depends on the organization’s resources, capabilities, strategies, and requirements [ 14 ]. The Organization for Economic Cooperation and Development [ 15 ] classifies innovation into product, service, process, management, and marketing innovations [ 16 , 17 ]. Open innovation covers many areas, such as the development of new products, services, methods, processes, raw materials, markets, marketing, and organizational structures [ 18 , 19 ]. According to [ 20 ], different types of innovation influence companies’ overall performance, generating risk, and uncertainty that may hinder organizations’ decision-making processes [21,22]. So, it is important to explore different types of innovation and digital processes [ 23 ], as well as studying the impact that innovation can have in academic and practical spheres [24,25] . Thus, during this study of different types of innovation, the process of open innovation emerges and is adapted according to companies’ needs [ 26 ]. Open innovation is cyclical and follows a quadruple helix, composed of actors from the industry, government, universities, and society [ 27 ]. A critical part of the open innovation process involves the knowledge management required to achieve higher levels of industrial performance through the correct use of technologies [ 8 ]. Innovation is a cutting-edge goal for companies interested in expanding their businesses, involves different types of change and depends on an organization’s resources, capabilities, strategies, and requirements [ 25 ]. As a result, J. Open Innov. Technol. Mark. Complex. 2021,7, 229 3 of 18 customer attraction and company performance are influenced by innovative strategies and activities [ 27 ]. For [ 8 ], the dynamics of innovation are cyclical and follow a quadruple helix, composed of actors from the industry, government, and universities, and could be leveraged in innovation environments. Without the need of developers, companies manage to keep up-to-date through research and creations developed mainly by universities, startups, and professional specialists [28]. In general, companies tend to innovate to react to a market opportunity [ 29 ], where cooperative agreements between governments and companies, induced by the innovation environment, can generate the effective production of innovation [30]. 2.2. Methodology of Scientific Research This study uses the bibliometric review method (keyword co-occurrence and conceptual thematic mapping) to explore the research questions, being a transparent and reproducible study and review, increasing the reliability of the results [ 31 ]. Bibliometric review techniques were based on a quantitative approach designed to identify, describe and evaluate the existing research [ 32 ]. The steps followed in the bibliometric review are presented in Figure 1. J. Open Innov. Technol. Mark. Complex. 2021, 7, x FOR PEER REVIEW 3 of 18 through the correct use of technologies [8]. Innovation is a cutting-edge goal for companies interested in expanding their businesses, involves different types of change and depends on an organization’s resources, capabilities, strategies, and requirements [25]. As a result, customer attraction and company performance are influenced by innovative strategies and activities [27]. For [8], the dynamics of innovation are cyclical and follow a quadruple helix, composed of actors from the industry, government, and universities, and could be leveraged in innovation environments. Without the need of developers, companies manage to keep up-to-date through research and creations developed mainly by universities, startups, and professional specialists [28]. In general, companies tend to innovate to react to a market opportunity [29], where cooperative agreements between governments and companies, induced by the innovation environment, can generate the effective production of innovation [30]. 2.2. Methodology of Scientific Research This study uses the bibliometric review method (keyword co-occurrence and conceptual thematic mapping) to explore the research questions, being a transparent and reproducible study and review, increasing the reliability of the results [31]. Bibliometric review techniques were based on a quantitative approach designed to identify, describe and evaluate the existing research [32]. The steps followed in the bibliometric review are presented in Figure 1. Figure 1. Bibliometric analysis steps. The basis for this review is a collection of bibliographic data available in databases. The two main bibliographic databases used are Web of Science (WoS) and Scopus [33]. The WoS database has more restricted coverage than Scopus. The Scopus database has more than 20,000 peer-reviewed journals, while Web of Science includes only ISI-indexed journals and is limited to 12,000 journals [34]. As the article seeks to investigate worldwide innovation and technology environments, the keywords searched were “technology park” OR “innovation ecosystem” OR “innovation environment” OR “agro-technology park” OR “science and technology parks” OR “Technoparks” OR “Technological pole” OR “agricultural technology park” OR “technological cluster” OR “business incubators” OR “Technology incubators” OR “agritech”. The keywords searched were defined according to [35], which explains the main innovation and technology environments, according to a literature review, and how companies benefit from these environments. No additional filters were added, so the searches include articles from all areas that have some keywords in the title, abstract, keywords, or topics, from 1975 to 2021. The only exclusion criterion was the removal of duplicate articles. Figure 1. Bibliometric analysis steps. The basis for this review is a collection of bibliographic data available in databases. The two main bibliographic databases used are Web of Science (WoS) and Scopus [ 33 ]. The WoS database has more restricted coverage than Scopus. The Scopus database has more than 20,000 peer-reviewed journals, while Web of Science includes only ISI-indexed journals and is limited to 12,000 journals [ 34 ]. As the article seeks to investigate worldwide innovation and technology environments, the keywords searched were “technology park” OR “innovation ecosystem” OR “innovation environment” OR “agro-technology park” OR “science and technology parks” OR “Technoparks” OR “Technological pole” OR “agricultural technology park” OR “technological cluster” OR “business incubators” OR “Technology incubators” OR “agritech”. The keywords searched were defined according to [ 35 ], which explains the main innovation and technology environments, according to a literature review, and how companies benefit from these environments. No additional filters were added, so the searches include articles from all areas that have some keywords in the title, abstract, keywords, or topics, from 1975 to 2021. The only exclusion criterion was the removal of duplicate articles. To perform the bibliometric analysis, we used the VOSviewer software, as it can adjust and customize different graphical representations of bibliometric maps [ 36 ]. It offers a high degree of flexibility for sorting, building, and modifying network maps, selecting and adjusting different combinations to create keyword maps based on the strength of the J. Open Innov. Technol. Mark. Complex. 2021,7, 229 4 of 18 co-occurrence data. This flexibility builds multiple network maps of our large dataset to obtain meaningful insights into the publishing behavior and performance of the innovation and technology environment search domain, which would not be feasible using manual methods [ 37 ]. To aid in the analysis, the multivariate analysis technique PCA (Principal Component Analysis) procedure using ChemoStat ® software was used. Through the PCA procedure, we organized the most predominant characteristics in each innovation environment [38]. 3. Results In this section, the results found through the analysis of the current literature were presented, with a bibliometric analysis of the chronological scheme of changing the meaning of the basic terms and main research theme depending on three periods under consideration, the environmental characteristics and, finally, the analyses of the countries. 3.1. Bibliometric Analysis A total of 4848 studies were found, which, after removing the duplicates, resulted in a final sample of 4650 studies. Figure 2shows the evolution of studies involving the innovation and technology environment, from 1975 to the present day. J. Open Innov. Technol. Mark. Complex. 2021, 7, x FOR PEER REVIEW 4 of 18 To perform the bibliometric analysis, we used the VOSViewer software, as it can adjust and customize different graphical representations of bibliometric maps [36]. It offers a high degree of flexibility for sorting, building, and modifying network maps, selecting and adjusting different combinations to create keyword maps based on the strength of the co-occurrence data. This flexibility builds multiple network maps of our large dataset to obtain meaningful insights into the publishing behavior and performance of the innovation and technology environment search domain, which would not be feasible using manual methods [37]. To aid in the analysis, the multivariate analysis technique PCA (Principal Component Analysis) procedure using ChemoStat® software was used. Through the PCA procedure, we organized the most predominant characteristics in each innovation environment [38]. 3. Results In this section, the results found through the analysis of the current literature were presented, with a bibliometric analysis of the chronological scheme of changing the meaning of the basic terms and main research theme depending on three periods under consideration, the environmental characteristics and, finally, the analyses of the countries. 3.1. Bibliometric Analysis A total of 4848 studies were found, which, after removing the duplicates, resulted in a final sample of 4650 studies. Figure 2 shows the evolution of studies involving the innovation and technology environment, from 1975 to the present day. Figure 2. Evolution of studies involving innovation environment over the years. The figure with the evolution of the studies shows the behavior of the number of studies, and the trend line helps to show how the studies will behave in the coming years. The trend line indicates that, until 2015, the number of studies was below average, but in 2016 there was a considerable increase, which is predicted to continue increasing in the coming years. However, to indicate the trend for the coming years, it is first necessary to understand how the studies have evolved since 1975 and why there was an exponential growth in 2016. To understand the study’s evolution, bibliometric performance analyzes were performed over the periods with the help of the VOSviewer software. VOSviewer also used 0 100 200 300 400 500 600 1975 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 Scopus Web of Science Linear (Scopus) Linear (Web of Science) Figure 2. Evolution of studies involving innovation environment over the years. The figure with the evolution of the studies shows the behavior of the number of studies, and the trend line helps to show how the studies will behave in the coming years. The trend line indicates that, until 2015, the number of studies was below average, but in 2016 there was a considerable increase, which is predicted to continue increasing in the coming years. However, to indicate the trend for the coming years, it is first necessary to understand how the studies have evolved since 1975 and why there was an exponential growth in 2016. To understand the study’s evolution, bibliometric performance analyzes were performed over the periods with the help of the VOSviewer software. VOSviewer also used distance-based mapping instead of graphics-based maps. Distance-based mapping is best suited for mapping the performance, networks, and knowledge structure of the domain being surveyed, and they are represented as colored circles in the network. The size of the circle reflects the size of the entity, and the closer the two entities are to each other on the map, the more closely they are related to each other in reality. The colors represent J. Open Innov. Technol. Mark. Complex. 2021,7, 229 5 of 18 groups of strongly linked entities [ 39 ]. When two entities in a network are directly connected, VOSviewer will draw a line between them to show this [ 37 ]. For the analysis, all 4650 studies were included in VOSviewer, and then analyzed using the following parameters: (i) type of analysis: co-occurrence of keywords; (ii) minimum number of co-occurrence of a keyword: 10; (iii) number of keywords to be selected: 423; (iv) verify selected keywords. In the latter step, a manual analysis of each of the identified keywords was performed, and similar keywords such as “business incubator” and “business incubators” were gathered in the same cluster. For a better analysis, the studies were divided into five periods, from 1975 to 1999, from 2000 to 2005, from 2006 to 2010, from 2011 to 2015, and from 2016 to the present day. The period-by-period analyses answer RQ1—What is the evolution of studies related to the innovation and technology environments over time? Each of these periods is marked by some advancement or world event related to technology or innovation, which are explained in the following sections. 3.1.1. Bibliometric Performance of 1975 to 1999 The first period is from 1975 to 1999, characterized by the consistency of studies, but with few representations (158 papers), as shown in Figure 3. J. Open Innov. Technol. Mark. Complex. 2021, 7, x FOR PEER REVIEW 5 of 18 distance-based mapping instead of graphics-based maps. Distance-based mapping is best suited for mapping the performance, networks, and knowledge structure of the domain being surveyed, and they are represented as colored circles in the network. The size of the circle reflects the size of the entity, and the closer the two entities are to each other on the map, the more closely they are related to each other in reality. The colors represent groups of strongly linked entities [39]. When two entities in a network are directly connected, VOSViewer will draw a line between them to show this [37]. For the analysis, all 4650 studies were included in VOSViewer, and then analyzed using the following parameters: (i) type of analysis: co-occurrence of keywords; (ii) minimum number of co-occurrence of a keyword: 10; (iii) number of keywords to be selected: 423; (iv) verify selected keywords. In the latter step, a manual analysis of each of the identified keywords was performed, and similar keywords such as “business incubator” and “business incubators” were gathered in the same cluster. For a better analysis, the studies were divided into five periods, from 1975 to 1999, from 2000 to 2005, from 2006 to 2010, from 2011 to 2015, and from 2016 to the present day. The period-by-period analyses answer RQ1—What is the evolution of studies related to the innovation and technology environments over time? Each of these periods is marked by some advancement or world event related to technology or innovation, which are explained in the following sections. 3.1.1. Bibliometric Performance of 1975 to 1999 The first period is from 1975 to 1999, characterized by the consistency of studies, but with few representations (158 papers), as shown in Figure 3. Figure 3. Cluster map 1975–1999. The 1975–1999 period has four clusters: blue cluster, red cluster, green cluster, and yellow cluster. Figure 3 shows that the keywords do not have strong relationships with each other. Nevertheless, the technology park cluster stands out among the others. The red cluster has the largest number of studies and “technology park” is the main keyword used. In [40], a technology park is conceptualized as an “enterprise-generating enterprise” that assists businesses during the start-up and take-off stages. The definition of a technology park is similar to the definition of the keyword “business incubator” that represents the green cluster, which also offers assistance to early-stage companies [11]. Figure 3. Cluster map 1975–1999. The 1975–1999 period has four clusters: blue cluster, red cluster, green cluster, and yellow cluster. Figure 3shows that the keywords do not have strong relationships with each other. Nevertheless, the technology park cluster stands out among the others. The red cluster has the largest number of studies and “technology park” is the main keyword used. In [ 40 ], a technology park is conceptualized as an “enterprise-generating enterprise” that assists businesses during the start-up and take-off stages. The definition of a technology park is similar to the definition of the keyword “business incubator” that represents the green cluster, which also offers assistance to early-stage companies [ 11 ]. Nevertheless, the two clusters relate to words with different characteristics. A technology park relates to research development, the high technology industry, and economic growth. On the other hand, a business incubator is related to keywords that refer to the development of a specific space, represented by a developing country and local development. The keyword “small business” is also related to the green cluster, demonstrating the influence of business incubators on small businesses [41]. J. Open Innov. Technol. Mark. Complex. 2021,7, 229 6 of 18 Regarding the red cluster, “research and development” is the keyword that most closely relates to the technology park, proving the link between institutions that stimulate research for the development of organizations. In the historical context, [ 42 ] cites the industrial policy changes in Japan in the late 1970s and early 1980s, a time that represented the country’s recovery from the damage of World War II. The authors point out that, among these changes, the proximity between research associations and industrial organizations increased, resulting in the creation of knowledge and collaboration in the development of industries in the country. The blue cluster and yellow cluster present as main keywords: “technology transfer” and “technology”. According to [ 43 ], technology transfer involves the transfusion of knowledge between educational and research institutions and industrial environments and emphasizes the importance of business incubators. The authors state that the know-how is the indispensable component for this process, representing the ability to mold talent, technology, and capital to expand companies. The analysis of this period showed the concern and attention to research related to technology. Among the main keywords of the four clusters, three presented the word “technology”. The keyword “innovation” did not stand out and was connected to the technology transfer concept. 3.1.2. Bibliometric Performance of 2000 to 2005 In the period from 2000 to 2005, there was an increase in studies, but not to the level of later studies, with 226 published papers. The technology transfer reached higher levels in the scientific literature, while the relevance of topics involving innovation and business incubators increased. Figure 4shows the period cluster map. J. Open Innov. Technol. Mark. Complex. 2021, 7, x FOR PEER REVIEW 7 of 18 Figure 4. Cluster map 2000–2005. The period from 2000–2005 also has four clusters. Technology transfer is the central research theme, but with an increase in the research of innovation compared to the previous period. “Technology transfer” (red cluster) presents a connection to all the other keywords. The keyword defines the transfer of technologies, techniques, or knowledge that were developed in one organization and then adopted by another institution [44]. In the early 2000s, the expansion of telecommunication technologies occurred [45], which may have generated an influence on the themes related to the exchange of knowledge and technologies between organizations. The keyword “innovation” (green cluster) is relevant in the scientific scenario. The emergence of startups in the early 2000s [45], may be a factor that explains the beginning of the increase in studies related to the innovation of organizations. The startups stood out by using technologies and innovations to transform businesses into scalable and replicable organizations [46]. The startups demonstrated an organizational concept that uses innovation as a basis for business structure, demonstrating a transformation of the industrial environment. With the emergence of startups, the concept of open innovation also began to emerge, bringing the possibility of developing new businesses and new solutions in the most diverse areas, as shown in Figure 4. The yellow and blue clusters appear with less expressions. The yellow cluster presents, for the first time, the keyword “entrepreneurship”, still with little relevance to studies, associated with the keywords “marketing”, as well as the country of the United States. The blue cluster presents keywords related to the development of technology in the industry. The keyword “science and technology” has the greatest relevance, associated with the country of China. Figure 4. Cluster map 2000–2005. The period from 2000–2005 also has four clusters. Technology transfer is the central research theme, but with an increase in the research of innovation compared to the previous period. “Technology transfer” (red cluster) presents a connection to all the other J. Open Innov. Technol. Mark. Complex. 2021,7, 229 7 of 18 keywords. The keyword defines the transfer of technologies, techniques, or knowledge that were developed in one organization and then adopted by another institution [ 44 ]. In the early 2000s, the expansion of telecommunication technologies occurred [ 45 ], which may have generated an influence on the themes related to the exchange of knowledge and technologies between organizations. The keyword “innovation” (green cluster) is relevant in the scientific scenario. The emergence of startups in the early 2000s [ 45 ], may be a factor that explains the beginning of the increase in studies related to the innovation of organizations. The startups stood out by using technologies and innovations to transform businesses into scalable and replicable organizations [ 46 ]. The startups demonstrated an organizational concept that uses innovation as a basis for business structure, demonstrating a transformation of the industrial environment. With the emergence of startups, the concept of open innovation also began to emerge, bringing the possibility of developing new businesses and new solutions in the most diverse areas, as shown in Figure 4. The yellow and blue clusters appear with less expressions. The yellow cluster presents, for the first time, the keyword “entrepreneurship”, still with little relevance to studies, associated with the keywords “marketing”, as well as the country of the United States. The blue cluster presents keywords related to the development of technology in the industry. The keyword “science and technology” has the greatest relevance, associated with the country of China. 3.1.3. Bibliometric Performance of 2006 to 2015 The period from 2006 to 2015 confirmed the rise and consolidation of innovation as the main research theme concerning technological development environments. Figure 5 shows the period cluster map. J. Open Innov. Technol. Mark. Complex. 2021, 7, x FOR PEER REVIEW 8 of 18 3.1.3. Bibliometric Performance of 2006 to 2015 The period from 2006 to 2015 confirmed the rise and consolidation of innovation as the main research theme concerning technological development environments. Figure 5 shows the period cluster map. Figure 5. Cluster map 2006–2015. In the period from 2006 to 2015, there was also a significant increase in studies related to the research themes, representing 1571 papers. “Innovation” represented the main keyword of the period, was present as the central theme, and linked to a large network of terms used in the research. With the growth of startups in the industrial environment, the activities of technology accelerators and incubators were required, and themes related to innovation received much attention [47]. Innovation was the central theme of the research, showing that most of the studies analyzed bring some kind of innovation. Although not appearing as the predominant keyword, the increase in the number of studies and the large volume of secondary keywords showed that open innovation and the different ways of innovating received increasing attention over the years. “Business incubators”, which had already been prominent in previous periods, received great attention from researchers in the 2006–2015 period, representing the top keyword after “innovation”. Other innovation environments also began to emerge during this period. Figure 3 demonstrates the emergence of studies involving technology parks and science and technology parks, and keywords referring to the creation of a context for technology development began to gain prominence, such as “ecosystems,” “regional planning,” and “economic development”. Innovation environments are also called innovation ecosystems in some studies, which approached universities to accelerate innovation processes. During this period, studies began to spread to different countries and regions, involving regional development and public policies. Studies became more widespread and were observed from different points of view, becoming increasingly specific to different industry and research contexts. Figure 5. Cluster map 2006–2015. In the period from 2006 to 2015, there was also a significant increase in studies related to the research themes, representing 1571 papers. “Innovation” represented the main keyword of the period, was present as the central theme, and linked to a large network of terms used in the research. With the growth of startups in the industrial environment, the J. Open Innov. Technol. Mark. Complex. 2021,7, 229 8 of 18 activities of technology accelerators and incubators were required, and themes related to innovation received much attention [ 47 ]. Innovation was the central theme of the research, showing that most of the studies analyzed bring some kind of innovation. Although not appearing as the predominant keyword, the increase in the number of studies and the large volume of secondary keywords showed that open innovation and the different ways of innovating received increasing attention over the years. “Business incubators”, which had already been prominent in previous periods, received great attention from researchers in the 2006–2015 period, representing the top keyword after “innovation”. Other innovation environments also began to emerge during this period. Figure 3demonstrates the emergence of studies involving technology parks and science and technology parks, and keywords referring to the creation of a context for technology development began to gain prominence, such as “ecosystems,” “regional planning,” and “economic development”. Innovation environments are also called innovation ecosystems in some studies, which approached universities to accelerate innovation processes. During this period, studies began to spread to different countries and regions, involving regional development and public policies. Studies became more widespread and were observed from different points of view, becoming increasingly specific to different industry and research contexts. From this period, an exponential growth in studies began, marked by the emergence of the concept of Industry 4.0, an initiative of the German government, in partnership with universities and the private sector, to boost the long-term competitiveness of the manufacturing industry through the digitization of processes, which aroused the interest of the international academic community [48]. The great marker of this period is the beginning of research involving Industry 4.0. In addition to the opportunities that new forms of management and the use of technologies brought, Industry 4.0 presented the need to build collaborative networks involving government agencies, research institutions, consulting firms, non-profit institutions, and startups [ 49 ]. The interest of the academic community in how to internationally expand this concept and apply it to the day-to-day activities of companies has motivated many subsequent studies. 3.1.4. Bibliometric Performance of 2016 to 2021 From 2016 to 2021, the focus of research began to change. As of 2016, there is a worldwide growth in public policies aimed at open innovation and technological development. In emerging countries, such as Brazil, in 2016, the National Innovation Policy was launched [ 50 ]. In China, also in 2016, the government became a subsidiary in research and development [ 51 ]. During this same period, the United States also started to develop a National Innovation System, encouraging research in this area [ 52 ]. Both technology and industry are evolving to a high level, which may explain this change in the research trend. Figure 6shows the cluster map of the studies from 2016–2021. The period from 2016 to 2021 is the most representative period since 1975 in terms of the number of studies, which can be represented by four clusters. This period stands out due to the relationship among the clusters identified, demonstrating an increase in the connections between studies, as well as a great number of keywords, based on 2695 papers published in this period (2016–2021). The keyword “innovation” (green cluster) still appears prominently, but no longer represents the central cluster, evidencing that it is no longer the driving theme, but is always related to the other research themes and the concept of the emerging open innovation, and therefore remains a representative cluster. In this period, a new phase of industrial maturity emerges, characterized by the need for connectivity and the use of digital technologies and how these can be applied in practice [ 53 ] As it occurs in many ways, open innovation is linked to the issues discussed by researchers and represents the basis for the development of a technological ecosystem. J. Open Innov. Technol. Mark. Complex. 2021,7, 229 15 of 18 on the subject were also identified, as well as the evidence of specifications. By having a greater knowledge of the characteristics of each environment and which countries stand out, new research can be conducted, including the creation of a network for knowledge exchange. Author Contributions: Conceptualization, I.C.B., J.C.M.S., V.J.G., C.d.F.M., Á.L.N.J. and E.O.B.N.; methodology, I.C.B., J.C.M.S., V.J.G., C.d.F.M., Á.L.N.J. and E.O.B.N.; software, I.C.B., J.C.M.S., V.J.G.; validation I.C.B., J.C.M.S., V.J.G., C.d.F.M., Á.L.N.J.; formal analysis, I.C.B., J.C.M.S., V.J.G., C.d.F.M., Á.L.N.J. and E.O.B.N.; investigation, I.C.B., J.C.M.S., V.J.G., C.d.F.M., Á.L.N.J.; resources, I.C.B., J.C.M.S., V.J.G., C.d.F.M., Á.L.N.J.; data curation, I.C.B., J.C.M.S., V.J.G.; writing—original draft preparation, I.C.B., J.C.M.S., V.J.G., C.d.F.M., Á.L.N.J. and E.O.B.N.; writing—review and editing, I.C.B., J.C.M.S., V.J.G., C.d.F.M., Á.L.N.J.; visualization, I.C.B., J.C.M.S., V.J.G.; supervision, I.C.B., J.C.M.S., V.J.G.; project administration, I.C.B., J.C.M.S., V.J.G.; funding acquisition, J.C.M.S. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by the [CAPES—Brazil] under Grant [CAPES process Baierle No. 88887.464876/2019-00]; [CNPq—Brazil] under Grant [CNPq process Siluk No. 308057/2020-1]; and [CAPES—Brazil] under Grant [CAPES process Gerhardt No. 88887.605036/2021-00]. Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable. Data Availability Statement: Not applicable. Conflicts of Interest: The authors declare no conflict of interest. References 1. Al-Kfairy, M.; Khaddaj, S.; Mellor, R.B. Evaluating the effect of organizational architecture in developing science and technology parks under differing innovation environments. Simul. Model. Pract. Theory 2020,100, 115. [CrossRef] 2. Wang, X.; Zou, H.; Zheng, Y.; Jiang, Z. How will different types of industry policies and their mixes affect the innovation performance of wind power enterprises? Based on dual perspectives of regional innovation environment and enterprise ownership. J. Environ. Manag. 2019,251, 1452. [CrossRef] 3. Lei, Y.; Guo, Y.; Zhang, Y.; Cheung, W. Information technology and service diversification: A cross-level study in different innovation environments. Inf. Manag. 2021,11, 244. 4. Raymond, L.; Uwizeyemungu, S.; Fabi, B.; St-Pierre, J. IT capabilities for product innovation in SMEs: A configurational approach. Inf. Technol. Manag. 2018,19, 75–87. [CrossRef] 5. Rong, K.; Lin, Y.; Yu, J.; Zhang, Y.; Radziwon, A. Exploring regional innovation ecosystems: An empirical study in China. Ind. Innov. 2020,28, 545–569. [CrossRef] 6. Alonso, A.D.; Bressan, A. Micro and small business innovation in a traditional industry. Int. J. Innov. Sci. 2016 ,8, 311–330. [CrossRef] 7. Quintane, E.; Casselman, R.M.; Reiche, B.S.; Nylund, P.A. Innovation as a knowledge-based outcome. J. Knowl. Manag. 2011 ,15, 928–947. [CrossRef] 8. Da Costa, M.B.; Dos Santos, L.M.A.L.; Schaefer, J.L.; Baierle, I.C.; Nara, E.O.B. Industry 4.0 technologies basic network identification. Scientometrics 2019,121, 115. [CrossRef] 9. Villani, E.; Lechner, C. How to acquire legitimacy and become a player in a regional innovation ecosystem? The case of a young university. J. Technol. Transf. 2021,46, 1017–1045. [CrossRef] 10. Thompson, T.A.; Purdy, J.M.; Ventresca, M.J. How entrepreneurial ecosystems take form: Evidence from social impact initiatives in Seattle. Strateg. Entrep. J. 2018,12, 96–116. [CrossRef] 11. Autio, E.; Klofsten, M. A comparative study of two European business incubators. J. Small Bus. Manag. 1998,36, 30–43. 12. Nara, E.O.B.; Schaefer, J.L.; de Moraes, J.; Tedesco, L.P.C.; Furtado, J.C.; Baierle, I.C. Sourcing research papers on small- and medium-sized enterprises’ competitiveness: An approach based on authors’ networks. Rev. Esp. Doc. Cient. 2019,42. 13. Schaefer, J.L.; Baierle, I.C.; Sellitto, M.A.; Siluk, J.C.M.; Furtado, J.C.; Nara, E.O.B. Competitiveness Scale as a Basis for Brazilian Small and Medium-Sized Enterprises. Eng. Manag. J. 2020,11, 1–17. [CrossRef] 14. Baierle, I.C.; Benitez, G.B.; Nara, E.O.B.; Schaefer, J.L.; Sellitto, M.A. Influence of Open Innovation Variables on the Competitive Edge of Small and Medium Enterprises. J. Open Innov. Technol. Mark. Complex. 2020,6, 179. [CrossRef] 15. OECD. Proposed Guidelines for Collecting and Interpreting Technological Innovation Data. Available online: https: //www.oecd-ilibrary.org/science-and-technology/proposed-guidelines-for-collecting-and-interpreting-technological- innovation-data_9789264192263-en (accessed on 3 April 1997). 16. Lee, C.; Hallak, R.; Sardeshmukh, S.R. Creativity and innovation in the restaurant sector: Supply-side processes and barriers to implementation. Tour. Manag. Perspect. 2019,31, 54–62. [CrossRef] J. Open Innov. Technol. Mark. Complex. 2021,7, 229 16 of 18 17. Hjalager, A.M. A review of innovation research in tourism. Tour. Manag. 2010,31, 1–12. [CrossRef] 18. Escola De Comércio, F.; Penteado, Á.; Biancolino, B.; Maccari, A.; Antonio, E.; Pereira, F. Innovation as a Tool for Generating Value in the IT Services Sector. Rev. Bras. De Gestão De Negócios 2013,15, 410–426. 19. Varis, M.; Littunen, H. Types of innovation, sources of information and performance in entrepreneurial SMEs. Eur. J. Innov. Manag. 2010,13, 128–154. [CrossRef] 20. Guarascio, D.; Tamagni, F. Persistence of innovation and patterns of firm growth. Res. Policy 2019,48, 1493–1512. [CrossRef] 21. Tavassoli, S.; Karlsson, C. Persistence of various types of innovation analyzed and explained. Res. Policy 2015 ,44, 1887–1901. [CrossRef] 22. Zabeo, A.; Keisler, J.M.; Hristozov, D.; Marcomini, A.; Linkov, I. Value of information analysis for assessing risks and benefits of nanotechnology innovation. Environ. Sci. Eur. 2019,31, 1–8. [CrossRef] 23. Yevgenievich Barykin, S.; Mikhailovich Sergeev, S.; Vladimirovna Kalinina, O. Developing the physical distribution digital twin model within the trade network. Mark. Manag. Strateg. Plan. 2021,20, 111. 24. Gerhardt, V.J.; Mairesse Siluk, J.C.; Baierle, I.C.; Michelin, C.d.F. Theoretical model for identifying market development indicators. Int. J. Product. Perform. Manag. 2021,14, 844. 25. Davies, G.H.; Flanagan, J.; Bolton, D.; Roderick, S.; Joyce, N. University knowledge spillover from an open innovation technology transfer context. Knowl. Manag. Res. Pract. 2021,19, 84–93. [CrossRef] 26. Borchardt, P.; dos Santos, G.V. Gestão de ideias para inovação: Transformando a criatividade em soluções práticas. Rev. Adm. Innov. RAI 2014,11, 203. [CrossRef] 27. Bindabel, W. M&A Open Innovation, and Its Obstacle: A Case Study on GCC Region. J. Open Innov. Technol. Mark. Complex. 2020 , 6, 138. 28. Daniel, A.D.; Alves, L. University-industry technology transfer: The commercialization of university’s patents. J. Open Innov. Technol. Mark. Complex. 2019,18, 276–296. [CrossRef] 29. Gunday, G.; Ulusoy, G.; Kilic, K.; Alpkan, L. Effects of innovation types on firm performance. Int. J. Prod. Econ. 2011 ,133, 662–676. [CrossRef] 30. Bruce, J.R.; Figueiredo, J.M.; Silverman, B.S. Public contracting for private innovation: Government capabilities, decision rights, and performance outcomes. Strateg. Manag. J. 2019,40, 533–555. [CrossRef] 31. Maditati, D.R.; Munim, Z.H.; Schramm, H.J.; Kummer, S. A review of green supply chain management: From bibliometric analysis to a conceptual framework and future research directions. Resour. Conserv. Recycl. 2018,139, 150–162. [CrossRef] 32. Bretas, V.P.G.; Alon, I. Franchising research on emerging markets: Bibliometric and content analyses. J. Bus. Res. 2021 ,133, 51–65. [CrossRef] 33. Aria, M.; Cuccurullo, C. bibliometrix: An R-tool for comprehensive science mapping analysis. J. Informetr. 2017 ,11, 959–975. [CrossRef] 34. Fahimnia, B.; Sarkis, J.; Davarzani, H. Green supply chain management: A review and bibliometric analysis. Int. J. Prod. Econ. 2015,162, 101–114. [CrossRef] 35. Gerhardt, V.; Siluk, J.C.M.; Júnior, A.N.; Zen, G.; Rech dos Santos, J.G. Ambientes onde o Desenvolvimento Tecnológico Acontece. Available online: https://www.researchgate.net/publication/344239018_Ambientes_onde_o_desenvolvimento_tecnologico_ acontece (accessed on 1 September 2021). 36. BROWN, T.; PARK, A.; PITT, L. A 60-Year Bibliographic Review Of the Journal of Advertising Research. J. Advert. Res. 2020,60, 353–360. [CrossRef] 37. Pitt, C.; Park, A.; McCarthy, I.P. A bibliographic analysis of 20 years of research on innovation and new product development in technology and innovation management (TIM) journals. J. Eng. Technol. Manag. 2021,61, 101632. [CrossRef] 38. Prieto-Moreno, A.; Llanes-Santiago, O.; García-Moreno, E. Principal components selection for dimensionality reduction using discriminant information applied to fault diagnosis. J. Process Control 2015,33, 14–24. [CrossRef] 39. Perianes-Rodriguez, A.; Waltman, L.; van Eck, N.J. Constructing bibliometric networks: A comparison between full and fractional counting. J. Informetr. 2016,10, 1178–1195. [CrossRef] 40. Bozzo, U. Technology Park: An enterprise model. Prog. Plann. 1998,49, 215–225. [CrossRef] 41. Thayer, A.M. Business incubators provide start-up help, resources for small companies. Chem. Eng. News 1996 ,74, 10–13. [CrossRef] 42. Nonaka, I.; Ray, T.; Umemoto, K. Japanese organizational knowledge creation in Anglo-American environments. Prometh 1998 , 16, 421–439. [CrossRef] 43. Hisrich, R.D.; Smilor, R.W. The university and business incubation: Technology transfer through entrepreneurial development. J. Technol. Transf. 1988,13, 14–19. [CrossRef] 44. Phillips, R.G. Technology business incubators: How effective as technology transfer mechanisms? Technol. Soc. 2002 ,24, 299–316. [CrossRef] 45. Granstrand, O.; Holgersson, M. Innovation ecosystems: A conceptual review and a new definition. Technovation 2020 ,90, 102098. [CrossRef] 46. Gerhardt, V.J.; Santos, J.R.G.; Rubin, E.D.; Júnior, A.L.N.; Siluk, J.C.M. Stakeholders ´ Perception to Characterize the Start-ups Success. J. Technol. Manag. Innov. 2021,16, 38–50. [CrossRef] J. Open Innov. Technol. Mark. Complex. 2021,7, 229 17 of 18 47. Hausberg, J.P.; Korreck, S. Business incubators and accelerators: A co-citation analysis-based, systematic literature review. J. Technol. Transf. 2020,45, 151–176. [CrossRef] 48. Dos Santos, L.M.A.L.; da Costa, M.B.; Kothe, J.V.; Benitez, G.B.; Schaefer, J.L.; Baierle, I.C.; Nara, E.O.B. Industry 4.0 collaborative networks for industrial performance. J. Manuf. Technol. Manag. 2020,32, 245–265. [CrossRef] 49. Industrie 4.0 Maturity Index. Managing the Digital Transformation of Companies–UPDATE 2020-Acatech-National Academy of Science and Engineering. Available online: https://en.acatech.de/publication/industrie-4-0-maturity-index-update-2020/ (accessed on 22 April 2020). 50. Hatakeyama, K.; de Melo Pinto, N. The innovation system in the brazilian scenario. In Proceedings of the 29th International Conference of the International Association for Management of Technology: Towards the Digital World and Industry X.0, IAMOT 2020; Pretorius, L., Pretorius, M., Eds.; Curran Associates, Inc.: Red Hook, NY, USA, 2020; pp. 795–806. 51. Guo, D.; Guo, Y.; Jiang, K. Government-subsidized R&D and firm innovation: Evidence from China. Res. Policy 2016 ,45, 1129–1144. 52. Melaas, A.; Zhang, F. National Innovation Systems in the United States and China A Brief Review of the Literature. Res. Policy 2016,11, 241. 53. Frank, A.G.; Dalenogare, L.S.; Ayala, N.F. Industry 4.0 technologies: Implementation patterns in manufacturing companies. Int. J. Prod. Econ. 2019,210, 15–26. [CrossRef] 54. Carayannis, E.G.; Dezi, L.; Gregori, G.; Calo, E. Smart Environments and Techno-centric and Human-Centric Innovations for Industry and Society 5.0: A Quintuple Helix Innovation System View Towards Smart, Sustainable, and Inclusive Solutions. J. Knowl. Econ. 2021,365, 842. 55. Monsson, C.K.; Jørgensen, S.B. How do entrepreneurs’ characteristics influence the benefits from the various elements of a business incubator? J. Small Bus. Enterp. Dev. 2016,23, 224–239. [CrossRef] 56. Guan, H.; Zhang, Z.; Zhao, A.; Jia, J.; Guan, S. Research on innovation behavior and performance of new generation entrepreneur based on grounded theory. Sustainability 2019,11, 2883. [CrossRef] 57. Ghazinoory, S.; Phillips, F.; Afshari-Mofrad, M.; Bigdelou, N. Innovation lives in ecotones, not ecosystems. J. Bus. Res. 2021 ,135, 572–580. [CrossRef] 58. Andrade, E.K.P.; Andrade, A.R.S.; Zamora, V.R.O.; Silva, P.R.L.A.; Santos, M.K.S.; Azevedo, P.R. Periodicidades na distribuição homogênea da precipitação no Agreste de Pernambuco. J. Environ. Anal. Prog. 2018,3, 100–117. [CrossRef] 59. Yang, R.-C.; Crossa, J.; Cornelius, P.L.; Burgueño, J. Biplot Analysis of Genotype × Environment Interaction: Proceed with Caution. Crop Sci. 2009,49, 1564–1576. [CrossRef] 60. Gao, Q.; Cui, L.; Lew, Y.K.; Li, Z.; Khan, Z. Business incubators as international knowledge intermediaries: Exploring their role in the internationalization of start-ups from an emerging market. J. Int. Manag. 2021,27, 100861. [CrossRef] 61. Xu, L. Business incubation in China: Effectiveness and perceived contributions to tenant enterprises. Manag. Res. Rev. 2010 ,33, 90–99. [CrossRef] 62. Chen, Y.; Watson, E.; Cornacchione, E.; Ferreira Leitão Azevedo, R. “Flying High, Landing Soft”: An innovative entrepreneurial curriculum for Chinese SMEs going abroad. J. Chinese Entrep. 2013,5, 122–143. [CrossRef] 63. Shelomentsev, A.G.; Goncharova, K.S.; Stepnov, I.M.; Kovalchuk, J.A.; Lan, D.H.; Golov, R.S. Strategic Innovation as a Factor of Adaptation of National Economies to the Development of Global Value Chains. Sustainability 2021,13, 9765. [CrossRef] 64. Zhao, J.; Wu, G. Evolution of the chinese industry-university-research collaborative innovation system. Complexity 2017 , 2017, 156 . [CrossRef] 65. Tang, M.F.; Lee, J.; Liu, K.; Lu, Y. Assessing government-supported technology-based business incubators: Evidence from China. Int. J. Technol. Manag. 2014,65, 24–48. [CrossRef] 66. Laspia, A.; Sansone, G.; Landoni, P.; Racanelli, D.; Bartezzaghi, E. The organization of innovation services in science and technology parks: Evidence from a multi-case study analysis in Europe. Technol. Forecast. Soc. Change 2021 ,173, 121095. [CrossRef] 67. Albahari, A.; Klofsten, M.; Rubio-Romero, J.C. Science and Technology Parks: A study of value creation for park tenants. J. Technol. Transf. 2018,44, 1256–1272. [CrossRef] 68. Xie, K.; Song, Y.; Zhang, W.; Hao, J.; Liu, Z.; Chen, Y. Technological entrepreneurship in science parks: A case study of Wuhan Donghu High-Tech Zone. Technol. Forecast. Soc. Chang. 2018,135, 156–168. [CrossRef] 69. Millers, M.; Gaile-Sarkane, E. Management Practice in Small and Medium-Sized Enterprises: Problems and Solutions from the Perspective of Open Innovation. J. Open Innov. Technol. Mark. Complex. 2021,7, 214. [CrossRef] 70. Kleber, D.M.S.; Juusola, K. Open Innovation—An Explorative Study on Value Co-Creation Tools for Nation Branding and Building a Competitive Identity. J. Open Innov. Technol. Mark. Complex. 2021,7, 206. [CrossRef] 71. Kroon, N.; Alves, M.C.; Martins, I. The Impacts of Emerging Technologies on Accountants’ Role and Skills: Connecting to Open Innovation—A Systematic Literature Review. J. Open Innov. Technol. Mark. Complex. 2021,7, 163. [CrossRef] 72. Vinichenko, M.V.; Rybakova, M.V.; Chulanova, O.L.; Barkov, S.A.; Makushkin, S.A.; Karacsony, P. Views on Working with Information in a Semi-Digital Society: Its Possibility to Develop as Open Innovation Culture. J. Open Innov. Technol. Mark. Complex. 2021,7, 160. [CrossRef] 73. Giourka, P.; Kilintzis, P.; Samara, E.; Avlogiaris, G.; Farmaki, P.; Bakouros, Y. A Business Acceleration Program Supporting Cross-Border Enterprises: A Comparative Study. J. Open Innov. Technol. Mark. Complex. 2021,7, 152. [CrossRef] J. Open Innov. Technol. Mark. Complex. 2021,7, 229 18 of 18 74. Sánchez-Teba, E.M.; Rodríguez-Fernández, M.; Gaspar-González, A.I. Social Networks and Open Innovation: Business Academic Productivity. J. Open Innov. Technol. Mark. Complex. 2021,7, 158. [CrossRef] 75. Mairesse Siluk, J.C.; Kipper, L.M.; Benitez Nara, E.O.; Neuenfeldt Junior, A.L.; Dal Forno, A.J.; Soliman, M.; da Silva Chaves, D.M. A performance measurement decision support system method applied for technology-based firms’ suppliers. J. Decis. Syst. 2017 , 26, 93–109. [CrossRef] 76. Costa, R.; Siluk, J.; Neuenfeldt Júnior, A.; Soliman, M.; Nara, E. A gestão da competitividade industrial por meio da aplicação dos métodos UP e multicritério no setor frigorífico de bovinos The management of industrial competitiveness through the application of methods UP and multi-criteria in a bovine slaughterhouse. Rev. Chil. Ing. 2015,23, 383–394. [CrossRef]