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Universities as Knowledge Integrators and Cross-Industry Ecosystems: Self-Organizational Perspective:

Universities as Knowledge Integrators and Cross-Industry Ecosystems: Self-Organizational... Universities play a vital role in innovation ecosystems. Besides, their role is being transformed and reinforced due to the interdisciplinary nature of modern innovations and inter-sectoral collaboration in the process of implementing cross-industry projects. The article’s main objective is to reveal the emerging new goals, functions, and goals of university as knowledge integrator and consolidator within cross-industry ecosystem. The article introduces the approaches to the implementation of the cross-industry ecosystem integrator functions as an “entry point” for the creation of new ideas, competencies, technological solutions, and projects for the development and testing of new technologies. The research results are useful for academics and policy makers in emerging economies to adopt and consider, so as to improve the contribution of the universities to the country’s economic and innovation development. Keywords university, cross-industry ecosystem, self-organization, integrator, university–industry collaborations, knowledge generation, knowledge exchange, innovation ecosystem “multi-cross-industry innovation” is a process of creating Introduction new products, services, or their combinations by combining The emergence and development of new markets, industries, key knowledge elements from at least three different indus- products, and professions in the modern world is proceeding tries and considered the process as a fundamentally new way rapidly. The main catalyst for these processes is the transfor- to successfully develop and create innovative businesses. We mation of the economy, which brings results at the intersection note also that the term “ecosystem” is quite complex and has of industries, using multidisciplinary knowledge, establishing been used in a different sense. It is often used as a metaphor cross-industry processes, developing infrastructure, digital for a network and network external factors, for a particular platforms, and creating new market formats and models for market or market niche, to reflect the complementarity of the interaction of market participants on their base. physical, human, and intellectual assets, or even spillover The ever-increasing complexity of products leads to the effects arising from joint activities (Gamidullaeva et al., fact that innovative processes of enterprises are dependent on 2020). The fundamental idea of this concept is that, in an external knowledge (Chesbrough, 2003; Chesbrough et al., unstable and turbulent environment, economic agents are 2006; von Hippel, 1988, 2001) and interaction with a variety building their strategies and creating competitive advantages of market participants. “The boundaries of firms and their based on resource sharing, network externalities (external corporate hierarchies are breaking down under the impact of effects), and knowledge “flows” (spillover effects). This the forces of interface standards, lowered transaction costs and increasingly modular production” (Foss, 2019). The key National University of Science and Technology “MISIS”, Moscow, Russia strategic direction in these conditions should be the interac- Plekhanov Russian University of Economics, Moscow, Russia tion of different economic sectors through the creation of new Penza State University, Penza, Russia business models and end to end digital processes based on the Razumovsky MSUTM (FCU), Moscow, Russia intersections of industries and through cross-border coopera- Corresponding Author: tion. This interaction is called cross-industrial innovation. Leyla Gamidullaeva, Professor, Penza State University, Krasnaya st., 40, First, the term “multi-cross-industry innovation” was intro- Penza 440026, Penza Region, Russia. Email: gamidullaeva@gmail.com duced by the authors (Khan et al., 2013). They suggested that Creative Commons CC BY: This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). 2 SAGE Open requires the development of new theories and approaches that of the innovation ecosystem was formulated in a recent work reflect real trends, one of which is the theory of ecosystems. by the authors (Granstranda & Holgerssonb, 2020): “the In an economic sense, an ecosystem consists of exogenously evolving set of actors, activities, and artifacts, and the insti- defined components, the environment, and agents acting tutions and relations, including complementary and substi- endogenously together as a system associated with capitaliz- tute relations that are important for the innovative ing on the relationship (Acs et al., 2016). Similar to natural performance of an actor or a population of actors.” At the processes, various kinds of companies, multinational enter- same time, the use of the new term “cross-industry ecosys- prises, small and medium firms, and households coexist and tem” is especially relevant today in view of the need to focus develop within their own ecosystem : on the interdisciplinary nature of modern innovations and knowledge as a consequence of inter-sectoral collaboration. Such ecosystems can be formed on a variety of unifying This thesis was confirmed by N. Farhadi (2019) in his book principles (from geographic and political to industrial and “Cross-Industry Ecosystems,” where the author develops the environmental), as well as at different levels—from local (within theoretical and methodological foundations of the new con- organizations, companies, clusters, science parks) to global, that cept, emphasizing the growing complexity of inter-sectoral is, wherever stable relationships and a joint vision of the economic growth. The main features of cross-industry proj- participants arise. (Smorodinskaya, 2014, p. 28) ects include the following: “blurring” of territorial borders, An ecosystem cannot be rigidly connected to a specific busi- interdisciplinary knowledge and inter-sectoral technologies, ness or industry, but combines interconnected enterprises subprojects in several (at least two) sectors at different lev- from many industries that together create differentiated offers els, involvement and use of infrastructure and resource base and receive additional value (Khan et al., 2013). For example, of various regions, and unlimited implementation of the proj- Apple leads an ecosystem that includes at least four indus- ect in time (one project initiates the implementation of oth- tries—personal computers, consumer electronics, informa- ers). A cross-industry ecosystem approach allows for tion and communications, and, more recently, music and developing the innovation perspective through the self- television. organizational principles, when all participating actors, We agree with authors who criticize the inconsistent use regardless of their size and field of activity, benefit from net- and vague wording of the term “ecosystem” in scientific working and collaboration. Cross-industry ecosystem can be research (Brown & Mason, 2017). Often, there is a substitu- described as a dynamic system, characterized by interactions tion of concepts: An ecosystem is represented by cluster for- among a huge amount and diversity of stakeholders—uni- mations (network innovative ecosystems of a special class) versities, enterprises, public institutions, society, and so on. or a triple helix model based on a university–business–state Many authors highlight that their interaction is based on the partnership (Etzkowitz and Leydesdorff, 2000). Alongside principle of self-organization (De Toni et al., 2012; the triple helix is the quadruple helix theory (Carayannis & Gamidullaeva, 2019; Gamidullaeva & Tolstykh, 2017; Grigoroudis, 2016), which identifies relations between vari- Gamidullaeva et al., 2017; Jucevičius & Grumadaitė, 2014; ous stakeholders (civil society, media, and the culture-based Laihonen, 2006; Shmeleva, 2019; Tolstykh, Gamidullaeva, public) and integrates top-down policies and grassroots & Shmeleva, 2020; Tolstykh, Gamidullaeva, Shmeleva, innovations. Lapygin, 2020; Tolstykh, Shmeleva, & Gamidullaeva, 2020; According to Bruns et al. (2017), the “ecosystem” metaphor and others). reflects a tendency in scientific studies to describe the well- This article is an attempt to further develop the concept of known phenomenon of agglomeration effects of regions a cross-industry ecosystem as a dynamic complex nonhierar- (urban, regional, and national ecosystems), industries (agricul- chical model in terms of studying the changing processes of ture, chemical industry, manufacturing, mass media, and finan- creating and transferring new knowledge. The authors argue cial ecosystems), associations of firms (business ecosystems, that universities should play a key role in these processes. entrepreneurial ecosystems), or activities (services, innovations, Traditionally, the role of universities has been to educate and digital ecosystems). As a result, today we have “business students and implement basic research, which often had ecosystems” (Moore, 1993), “innovation ecosystems” (Adner, positive spillover effects for the industry, as well as stimu- 2006), “digital ecosystems” (Sussan & Acs, 2017), “university lating regional economic growth (Etzkowitz & Leydesdorff, ecosystems” (Hayter, 2017; Meoli et al., 2017), or “financial 2000; Trippl, Sinozic, & Lawton Smith, 2015). University ecosystems” (Cumming et al., 2017; Ghio et al., 2017). project technology transfer offices are extensively The idea of cross-industry ecosystems is a collaboration researched and best practices carefully analyzed (Phan & of actors from various industries in the implementation of Siegel, 2006; Youtie and Shapira, 2008). However, most of cross-industry projects. Therefore, one of the main tasks of the recommendations do not work in every ecosystem; it all the ecosystem is the transfer and exchange of knowledge depends on the maturity and development of the existing between economic entities. In this sense, the concept of ecosystem. We believe that more attention should be paid to “cross-industry ecosystem” is most closely related to the the role that universities can play in strengthening and term “innovation ecosystem.” In turn, a complete definition developing the ecosystem as a whole (Vasin et al., 2018). Tolstykh et al. 3 A university can act as an ecosystem integrator, applying The increasing complexity of interactions between differ- its intellectual, reputational, and financial capital to create ent stakeholders in the process of innovation lead to the fact and maintain a strong ecosystem (Heaton et al., 2019). For that universities have to balance between solving traditional this, it is also necessary to take into account the ecosystem’s and new problems and, as a result, the organizational model ability for self-organization. of universities is in transition in many countries (Guerrero The article’s main objective is to reveal emerging new et al., 2016; Miller et al., 2014). The organization of close roles of university as an integrator of cross-industry ecosys- interaction with the environment and with all stakeholders is tem in the age of digital transformation of industries and ser- a key element of the University 4.0 concept (Dewar, 2017). vices. The remainder of this article is organized as follows. The interaction of enterprises with universities provides First, we outline the role of universities in ecosystems to them with access to knowledge and opportunities for research acknowledge the previous research on the issue and then we at a high-quality level (Hussler et al., 2010; von Raesfeld present a self-organization of cross-industry ecosystem et al., 2012), as well as for innovative development framework that we will use to analyze this role in more (Dahlander & Gann, 2010; Estrada et al., 2016; Galán-Muros detail. Self-organization approach takes into account the & Plewa, 2016). Various studies are conducted to identify the complex dynamic nature of the system and is based on pro- conditions for effective collaboration between enterprises moting the productive self-organization rather than imposing and universities (Bruneel et al., 2010; Mueller, 2006; the top-bottom linear solutions. Organization for Economic Cooperation and Development We then apply this perspective to the case study of the [OECD], 2019). At the same time, the report of the OECD university, “MISIS” (Moscow, Russia), engaging with local (OECD, 2019) identifies the main formal and informal chan- economies for launching new industries, fostering entrepre- nels for such interaction. neurship, and strengthening cross-industry ecosystem. The Formal channels include the following: research collabora- article concludes with a brief summary and discussion, plus tions (Perkmann & Walsh, 2007), operations with intellectual suggestions for future scholarship. property (e.g., selling licenses, patents), scientific mobility The contribution of this article is the revealing of main fea- (Rosli et al., 2018), spin-off organizations in the university tures, functions, and emerging goals of universities in knowl- environment, and university graduates employed in industry edge integration and consolidation within the cross-industry (Balconi & Laboranti, 2006). Informal channels include pub- ecosystem. The research results are useful for academic lishing research results (Perkmann & Walsh, 2007), confer- researchers and policy makers in emerging economies to adopt ences and networking (Steinmo & Rasmussen, 2018), and consider, so as to improve the contribution of the universi- geographic or territorial vicinity (OECD, 2019), technology ties to the country’s economic and innovation development. sharing (research centers, laboratories; Claussen, 2019), and ongoing training for business employees (OECD, 2019). It is important to emphasize that knowledge spillover in Theoretical Background all directions between all actors of the ecosystem. In this way, universities can help organize the free knowledge flows Ecosystems and the University in an ecosystem through the formal and informal channels The universities face a number of challenges due to the described above. A good example is Kendall Square in increasing complexity of innovation processes. Cambridge around Massachusetts Institute of Technology First, the share of international and interdisciplinary (MIT). This is an example of a dynamic innovation ecosys- knowledge is constantly increasing, which creates problems tem around a major university. MIT has actively used univer- for traditional areas of academic research, and which often sity-owned land to support partnerships between universities depends on individual researchers and their scientific and industrial enterprises and to take its unique advantages, schools. Interdisciplinary innovations make new higher helping to develop an internationally significant cluster of demands on their organization and management. biological and pharmaceutical sciences (Heaton et al., 2019). Second, increasing organizational and coordination com- Thus, at the stage of ecosystem development, universities plexity implies the use of systemic innovative approaches. help it achieve its maturity and unite and strengthen relations Third, the exchange of innovative knowledge is moving between all actors. toward the complexity of cooperation and knowledge mod- Meanwhile, in cross-industry ecosystems, there is the els (e.g., innovation clusters, multifactor centers led by uni- problem of harmonizing and coordinating the interests of all versities or industry, and public–private partnerships between participants and, accordingly, maintenance of self-organiz- the government, industry, and universities). ing processes is increasing. Thus, due to economic transformation, the role of univer- In this context, it is expedient to take the perspective of sities in the innovation ecosystem as a traditional center of the quadruple helix approach as a network of relationships. knowledge creation is changing, and inter-sectoral innova- By studying the interdependencies of the ecosystem actors, tion networks should be organized. resources, and activities from a self-organizational perspective, 4 SAGE Open we aim at enhancing our understanding of the relationships complex systems cannot impose their development paths. We between actors in the quadruple helix model. should strive to understand trends to manage them. The prob- In addition, the development of a complex nonhierarchi- lem of managing both ecosystem actors and the ecosystem is cal ecosystem gains substantial importance. The key aspect to create an infrastructure for self-directed development. is stimulating relations and interactions between the ecosys- Second, ecosystems often are established spontaneously, tem actors in nonhierarchical ways and facilitating the self- as a reaction to digital transformations processes of all mar- organization of its actors. Cross-industry and innovation ket participants. Hence, we can diagnose the so-called ecosystems can be characterized by a combination of top- chaos as the second postulate of the synergetic approach. A down and bottom-up initiatives (Jucevičius & Grumadaitė, chaotic state contains uncertainty, probability, and random- 2014) that stimulate networking and innovation develop- ness, which are described using the concepts of information ment. The approach of complexity theory toward cross- and entropy. The collaborative ecosystem links are formed industry ecosystem means that responses to environment are at different levels through chaos. Furthermore, it is interest- emerging from spontaneous bottom-up interaction without a ing to note that, at times of ecosystem instability, even central control (Jucevičius & Grumadaitė, 2014). small fluctuations that occur inside the ecosystem can gen- In previous works, we pointed out that the main limiting erate large macro processes. That is, the actions of each point of network models is that horizontal synergistic inter- ecosystem actor can significantly affect macroeconomic action between participants is subject to vertical manage- processes. ment from above. The management system can be either a The assessment of knowledge creation (intellectualiza- state structure or a large enterprise, building network rela- tion) in the ecosystem should reflect the economic return on tions with other enterprises for their interests. Elements of investment in the development of digital technologies and the management vertical initially violate the principles of human resources, and increase the level of intellectual harmonization and balanced development of individual par- potential. The effect of system intellectualization occurs ticipants as the interests and priorities of the governing body when technologies stimulate the transfer of knowledge and (governmental, business, and societal or any other structures) business innovations, and lead to increased productivity do not always coincide with the interests of other participants within the company, in the supply chain and between indus- (Tolstykh, Gamidullaeva, & Shmeleva, 2020). tries, and to the sustainable development of each of the par- In this way, the article aims to contribute to the literature ticipants in digital cross-industry interaction along the entire on the innovation ecosystem and quadruple helix model by added chain cost. offering a novel view on self-organizing perspective. We For the creation of dissipative structures from a systemic conclude that, to fully understand the complexity of the perspective, certain conditions must be met: cross-industry ecosystem model, we need to address the challenge of organizing and maintenance of spontaneous •• Dissipative structures can be formed only in open bottom-up interaction without a central control. With this systems. An inflow of energy is possible, compensat- aim, we suggest that the universities play the role of ecosys- ing for the losses and ensuring the existence of tem integrator and consolidator. Meanwhile, the existing lit- ordered states. Due to this, along with the production erature in the research field is inconclusive with regard to of entropy, there is a flow of “negative entropy” from identification of the new roles and functions of universities the outside. One of the main properties of complex in the cross-industry collaboration and knowledge creation self-organizing systems is the accelerated production processes. of entropy, that is, when a new ordered structure arises, the rate of knowledge entropy production increases sharply; Self-Organization of Cross-Industry •• Dissipative structures arise in systems consisting of a Ecosystem Framework large number elements. The ordered movement in The study of the cross-industry ecosystem as a system of such systems is always cooperative and integrated as integrating knowledge is based on the methodology of a sys- a large number of objects are involved in it; tematic approach and self-organization law. •• Dissipative structures arise only in nonlinear systems. First, ecosystems belong to the class of nonlinear systems. Self-organization exists under special internal and Nonlinear systems are those in which the linearity of the sta- external conditions of the system and the environ- tistical characteristic is violated in at least one link or there is ment. Dissipative structures are stable formations, but a violation of the link dynamics equations. Nonlinearity pre- their stability is determined by the stability of the determines the uncertainty of system behavior at any time sources of incoming energy and depends on the time interval. Most processes in the ecosystem and in its links with of their existence; other systems reaction are currently undergoing crisis devel- •• If, as a result of self-organization, several competing opment, which is a consequence of the system reaction to dissipative structures arise, then one of them that pro- external and internal challenges. Moreover, it is obvious that duces entropy with the highest rate survives. Thus, by Tolstykh et al. 5 Figure 1. Cross-industry ecosystem model. calculating the entropy of an ecosystem, we can predict •• Nonequilibrium as the initial state is a source of the the rate of change. And this, in turn, will make it pos- system self-movement; sible to assess with the greatest probability the sustain- •• Time is an internal characteristic of a system that ability of the ecosystem as a complex self-organizing expresses the irreversibility of processes in a system. system; •• The creation of ecosystems as new ordered struc- From our point of view, the ecosystem is not only the abil- tures occurs according to the bifurcation scenario ity to respond and reflect technological and digital challenges, (Preobrazhensky & Tolstykh, 2004). but also to create intelligent technical environments that mini- mize negative consequences and create optimal conditions At the time of crisis transformations, a bifurcation point for the implementation of projects at any level. In accordance arises. There can be many possible development strategies with the principles of ecosystem, we will understand the from this point, but nevertheless, a certain predetermination actor’s cognition as the mechanisms for achieving strategic of the processes of deployment exists, which performs the goals by actors based on the processes of new knowledge for- present not only through the past, but also the future state in mation, their transfer and exchange, and on the theory of self- accordance with the upcoming order. organization, information, and digital technologies. The distinctive features of ecosystems as complex self- However, the technological environment surrounding the organizing systems include the following: actor can be simpler (“the whole is less than a part”) and, in creating a cognitive mechanism, can appear as a synergistic •• Coherence (interconnectedness): they behave as a effect. Such an effect is possible in cases of subsequent collec- whole; tive actions, when the intellectual environment leads to the •• Deviations occurring in the system, instead of decay- generation of knowledge, ideas, and the implementation of cre- ing, can intensify, and the system evolves in the direc- ative and effective solutions. The knowledge management tion of “spontaneous” self-organization; becomes a priority in ensuring the effectiveness of cross-indus- •• Chaos is a constructive mechanism of self-organiza- try interaction, creating an ecosystem, and a unified business tion complex systems as the birth of a new one is asso- environment, predetermining the need for the formation of new ciated with a violation of the usual system ordering; cross-professional competencies (Tolstykh & Shkarupeta, •• Evolution contains both deterministic and stochastic 2019). The development of a knowledge management mecha- elements, representing a mixture of necessity and risks; nism in the context of a cross-industry ecosystem formation 6 SAGE Open will optimally manage the economic, social, and technological a given period of time. These functions in the indus- processes of ecosystem actors to achieve high socioeconomic trial ecosystem can be performed by digital plat- efficiency, as well as measure the effects of the cross-industry forms, new technologies, materials, innovative transformation through intellectualization. projects, and start-ups. The main indicator of the ecosystem development is pro- 2. Integrator—is an actor who unites other actors for posed to consider knowledge, which plays the role of system an idea or project and analyzes and evaluates the “energy” source (Figure 1). necessary competencies of actors and the degree of The ecosystem management system can be considered as their economic security for other participants. This a system with two closed control loops. One of the loops is task can be performed by universities, research the usual feedback, providing the traditional management organizations, project offices, and digital platforms process: input-output-input. Feedback compares the input that accumulate knowledge, competencies, and and output parameters, being a standard response to the chal- international experience. lenges of micro and macro environments. 3. Developers—actors involved in the development and The other loop performs self-customization. As a rule, a prototyping of new technologies, materials, and pro- particular criterion of the quality of the system’s work (in cesses. This role can be implemented by technoparks, this case, the quality of the cross-industry project) is laid start-ups, engineering companies, and research down in the self-organizing system for the external condi- structures. tions of the system. The system itself chooses a structure in 4. Implementers—actors implementing new projects which a given quality criterion of the entire system is satis- and processes on their site; fied. A self-organizing system must have an analyzer or qual- 5. Promoters—actors providing promotion of imple- ity optimizer. The optimizer is designed to find and implement mented projects and conversion of past projects’ the highest possible quality in a given system. This function experi ence into new projects and project commer- is the main aim of the university as an ecosystem actor. cialization. The source of the ecosystem’s intellectual “energy” is the knowledge generated by universities. University education In effectiveness of the cross-industry ecosystem, a signifi- has always been a reflection of the processes taking place in cant role should be given to the “integrator,” namely, to ensure society. Hence, the universities have to become the bridge- the creativity, innovativeness, and balance of the effects and head of the cross-industry ecosystem for innovation in tech- interests of a variety of the ecosystem’s actors based on the nology, research, and management. creation and transfer of new knowledge. Universities can take The law of self-organization and self-preservation for the up such a role in the cross-industry ecosystem. ecosystem works when the sum of the potentials of the system Key performance indicators (KPIs) are used to assess significantly exceeds the total effects of the micro and macro whether and how well the objectives of each ecosystem actor environment. The basis for implementing preventive measures are met and what they can do to improve. for the ecosystem is the constant work to increase the amount KPIs reflects the requirements of the ecosystem and its of knowledge accumulated by ecosystem actors; the constant type. Currently, there are many different approaches to processing and transformation of information into knowledge; KPIs’ building (Bosch, 2009; Chapin et al., 1996; Cokins, the generation of new information, knowledge, and creative 2009; Government Accountability Office, 2011; Iansiti & ideas; and the training of competitive specialists. Richards, 2006; Parmenter, 2010; Rapport et al., 1998; Next, we move on to the detailed description of the for- Santos et al., 2012). mation principles and performance criteria of cross-industry The literature indicates that KPI for industrial ecosystems ecosystems. This is necessary for a deeper understanding of is a thin area. A wide range of literature exist although for- the role, functions, and tasks of universities in the cross- mulation of KPIs is insufficient (Fotrousi et al., 2014). industry ecosystem. The considered research on ecosystem KPI mostly addresses measurements of satisfaction, performance indi- cators, and freedom from risks. Meanwhile, a broader Indicators for Measuring a Cross- understanding of KPI would help to use them for Industry Ecosystem decision-support. The ecosystem actors are large industrial enterprises, tech- The following blocks of indicators were used to assess the noparks, engineering structures, start-ups, venture funds and KPIs of ecosystem actors: financial institutions, universities and research organiza- tions, various business structures, and government authori- 1. Business processes: ties. The key roles of actors in the ecosystem are as follows: 9 Compliance of processes in the organization with the principles of lean production; 1. Pacemaker—is an actor who initiates an idea, proj- 9 Compliance of processes in the organization with ect, or process that inspires ecosystem unification in the principles of quality management; Tolstykh et al. 7 9 Project-oriented organizational structure; 3. For each ith actor P , i = 1, . . ., m, the values of the 9 Technological level of business processes. jth indicator are determined, j = 1, . . ., n, and the 2. Relations with partners and clients: matrix h is formed. ij 9 Existence of long-term partnerships with suppliers; 4. For each group of factors, a standard is formed with 9 The presence of long-term partnerships with customers; the maximum values of indicators, , hh j = max ij 9 Level of customer loyalty; j = 1, . . ., n, i = 1, . . ., m. 9 Speed of response to changing client requests. 5. Furthermore, the indicators of the ith actor are nor- 3. Digital maturity: malized, where j = 1, . . ., n, i = 1, . . ., m. 9 Level of digital competence of personnel; 9 Level of digitalization of enterprise management ij k = ij processes; 9 Level of digitalization of business processes; 6. Setting the weight coefficients wj for n indicators is 9 Number of completed digital projects. carried out based on the analysis of the matrix of 4. Innovative susceptibility: paired comparisons: 9 Financial level of the organization’s readiness for implementation; w = 1. 9 Management efficiency; ∑ j j=1 9 Level of legal protection of all processes of the enterprise; The integral coefficient of competitiveness of the ith actor 9 Time of implementation of an innovative project is calculated as the arithmetic average of the weighted 1 of from its initiation to launch; the normalized performance indicators: 9 Level of qualifications and intellectual potential m m of the personnel; Kw = kw . ∑∑ ij ij j 9 Innovative motivation of personnel. j== 11 j For each KPI value, a score is correlated depending on the result of the indicator. University as an Integrator (Seizing) The KPI assessment as a whole (taking into account all its Within Cross-Industry Ecosystem blocks, namely, business processes relations with partners and clients, digital maturity, and innovation susceptibility) is As the actor in the cross-industry ecosystem, the university proposed to be determined in the following sequence. should change its role from a highly specialized university to an innovative university in the new economy. 1. Calculate the relative scores of KPI indicators for each The aim of the university is to increase the amount of of the evaluation blocks, using the following formula: knowledge accumulated by the ecosystem, process and transfer the information into knowledge, and generate new O = *, n ii Ni information and knowledge. Thus, the influence of the uni- versity on other actors in the ecosystem is to transfer knowl- where О is the relative estimate of the ith block, N is the i i edge along the following chains: number of KPIs in the block, and n is the point in accordance with the zones of values of threshold values of KPI of the ith •• University—cross-industry project—production— block. economics; •• University—cross-industry project—science— 2. Determine the weights B of each block. It is pro- inno vations—economics. posed to use a scale from 1 to 5, where 1 is the least significant and 5 is the most significant. The total The roles of universities in the cross-industry ecosystem can value of the weights must be 5. be represented as a scheme (Figure 2) containing the follow- 3. Calculate the integral evaluation as a weighted aver- ing tasks: age of the components. The closer it is to 1, the higher the KPI level. A score below 0.5 indicates insufficient 1. Define and formulate a vision of the ecosystem as a ecosystem maturity of the actor. whole; 2. Evaluate the role of each actor, predict ecosystem The methodology for assessing ecosystem performance development, and develop strategies; based on KPIs consists of the following stages: 3. Form a community of actors, finding them according 1. Allocation of actors making up m groups of the to the maturity level of KPI. ecosystem. 4. Find existing projects for inclusion in the ecosystem 2. Determination of a complete list of KPI indicators. as subprojects in new cross-sectoral projects; 8 SAGE Open Figure 2. The role of universities in the cross-industry ecosystem. 5. Integrate knowledge on technologies, competencies, 3. Joint distributed activity and cooperation of all eco- and best practices, and bring them to ecosystem systems’ actors based on the integration, reproduc- actors; tion, and processing of knowledge; 6. Initiate new ideas and technology projects in the 4. Personalization of educational activities, taking into interests of the ecosystem actors; account the cognitive, intellectual level of the 7. Provide ecosystem services to other communities. student; 5. Multilingualism and multiculturalism; 6. Interdisciplinary communication skills; The Objectives of the University as an Ecosystem 7. Customer focus on both individual and corporate Integrator clients; 8. Process orientation and ability to work in projects: The university creates the space for resources and actors to 9. Ability to work in high uncertainty and quick change more consistently and systematically align as a means of of task, management of complex automated systems, addressing regional problems/needs (Celuch et al., 2017). and work with artificial intelligence; Thus, universities have a great impact in their host regions. 10. Practical orientation (Tolstykh et al., 2017). They function as key institutions by communicating with the actors of their ecosystem, providing innovation, and sharing resources, knowledge, competences. It is advisable for uni- versities to create the necessary support structures, play a Universities, Cross-Industry Ecosystem, leading role in partnership with public and private authori- and Self-Organization: A Case of ties, and, more importantly, show their ability to provide a National University of Science and leading role in developing the necessary partnerships. Technology (NUST) MISIS (Russia) By “integrator” we have in mind universities that are able to address a set of ever-changing in demand market prefer- We will now take a closer look at a case study that dem- ences and exert considerable control over an ecosystem. onstrates the integrating role that the university plays The main objectives of the university as an integrator in within a cross-industry ecosystem from a self-organizing the ecosystem should be the following: perspective. To analyze the complex interorganizational relationships 1. Holistic systematic view of all processes taking place of the ecosystem and the corresponding governance require- in the world, studying the phenomena of science and ments at the university, we decided to use a case study society on the basis of interdisciplinary, the ability to approach (Eisenhart, 1989; Yin, 2003). define complex systems and work with them, and Our research began with a review of the academic litera- system engineering; ture and other documentation related to the formation and 2. Learning in communication as the main feature of development of various cross-industry ecosystems in digital education; Russia. We decided to dwell in detail on the experience of Tolstykh et al. 9 Table 1. Characteristics of the Ecosystem Actors—“Developers.” Group of actors (A ) Goals KPIs • Laboratory “Nanochemistry and Ecology,” NUST • Development of new technologies for • Total innovation index SII; MISIS; resource conservation and processing • The level of digital maturity; • The center of resource-saving technologies for of industrial and man-made waste; • The share of unique processing mineral raw materials, NUST MISIS; • Commercialization of technologies; technologies in the overall • Industrial technology engineering center; • R&D structure; • Innovative scientific and educational center “Romelt,” • Research and development NUST MISIS. costs. Note. KPI = key performance indicator; NUST = National University of Science and Technology. Table 2. Characteristics of the Ecosystem Actors—“Implementers.” Group of actors (A ) Goals KPIs “Moscow State University of Civil Engineering • Commercialization of technologies; • The level of cooperation (National research University),” BSTU named • R&D; development between actors; after V. G. Shukhov, Samara National Research • Implementation of complex high- • The number and cost of joint University named after S. P. Koroleva, University budget projects for large industrial projects in which ecosystem of the Basque Country, MEPhI. companies. actors are involved. Note. KPI = key performance indicator. Table 3. Characteristics of the Ecosystem Actors—“Promoters.” Group of actors A Goals KPIs PJSC “Inter-RAO,” Increasing competitiveness and profitability • Balanced financial result of the actor; PJSC “RusHydro,” through the introduction of innovative • Correspondence of resources to the SC “Rosatom,” technologies and processes. strategic goals of the actor; PJSC “Alrosa,” • Transfer of knowledge, technologies, GC “Novolipetsk Metallurgical Plant,” Federal and results within the ecosystem. Agency for Special Construction of Russia (Spetsstroy of Russia), “Zabsibgazprom” Note. KPI = key performance indicator. one of the largest universities in our country—NUST MISIS. complex processing of natural and associated gases, This university has achieved a great success as an innova- as well as biogas using various processes; tion center. •• Project 2. Development of technologies for the pro- In this article, the case study method is used to illustrate duction and use of composite binders for the construc- one crucial aspect of cross-industry relations, namely, the tion of transport and hydraulic structures, using role of the university as an integrator of knowledge in the large-tonnage waste from mining and processing of ecosystem. This allowed us to conceptualize this aspect mineral raw materials; within the emerging theory of cross-industry ecosystems. •• Project 3. Development of an integrated innovative technology for the extraction and processing of mineral raw materials, with underground waste isolation for Participants in the NUST MISIS Cross-Industry solving state scientific and technological problems of Ecosystem energy and environmental security (Tolstykh, Shmeleva, NUST MISIS plays the role of integrator in the discussed et al., 2020). ecosystem, and the domain of the ecosystem is the projects aimed at sustainable development in the raw materials and NUST MISIS, which takes an active part in innovative processing sectors: projects through the system of interaction and partnership with enterprises of various industries and scales, includes the •• Project 1. Development of a new generation of flexi- following main actors (see Tables 1 to 3). ble and high-performance catalytic reactor systems This ecosystem integrates the industries shown in based on structured catalysts (adsorbents) for the Figure 3. 10 SAGE Open Figure 3. Structure of a cross-industry ecosystem. Note. NUST = National University of Science and Technology. The strategic direction of the presented cross-industry 1. Represent an open system that exchanges matter, ecosystem is project cooperation of enterprises through the energy, and information with the environment; creation of new business models and end-to-end digital pro- 2. Demonstrate the ability to accumulate and use useful cesses through both traditional intersections of industries and experience; through cross-border cooperation. Within the framework of 3. Are capable of adaptive activity due to which useful this direction, MISIS University has formed a combination abilities increase and useless abilities decrease. of fundamental and applied science with access to the real sector of the economy on the basis of the following strategic An ecosystem is an integration mechanism between gener- academic units (SAU) of NUST MISIS: ating new knowledge and using it to create shared value •• SAU 1. Metamaterials and post-silicon electronics between actors. An effective mechanism for redistributing and materials design. value within an ecosystem is based on the diffusion of inno- •• SAU 2. Autonomous energy and energy efficiency. vations, knowledge spillovers, and externalities. Knowledge •• SAU 3. Materials and technologies to increase the spillover is a process aimed at developing interactions duration and quality of life. between exchange participants, simplifying decision-making, •• SAU 4. Industrial design and technologies for rein- and stimulating innovation through the evolution of collabo- dustrialization of the economy. ration between actors. Within an ecosystem, several projects •• SAU 5. Green technologies for resource conservation. can be implemented simultaneously and each actor of the ecosystem has the opportunity to participate simultaneously Functions, Features, and Principles of Forming in different projects in different roles. The mechanism of interaction between ecosystem actors and the assessment of a Cross-Industry Ecosystem Based on NUST the potential of the ecosystem actor for compliance with a MISIS: New Models for the Implementation of particular role in the initiated project is described in detail by Educational Programs the authors in Tolstykh, Gamidullaeva, and Shmeleva (2020). The mechanism of interaction between actors within an eco- The mechanism of interaction between actors is imple- system is based on the theory of complex adaptive systems. mented through cross-validation as a new self-tuning cir- Complex adaptive systems have the following basic features: cuit within the ecosystem. To assess the effectiveness of Tolstykh et al. 11 Figure 4. The structure of NUST MISIS as an integrator of the cross-industry ecosystem. interaction processes, the system potential method was events in the digital industry, including forums, com- used (Pushnoi, 2017). petitions (e.g., hackathons), as well as events aimed at The university as an ecosystem integrator should pro- attracting investors and demonstrating opportunities. vide functions such as generating ideas, organizing access 4. The management and educational system of profes- to the technological potential of the best centers of excel- sional and national competencies and fundamentally lence in the relevant industries, creating resource support new forms of forming the competencies for digital for the innovation process (analytical, predictive, infra- ecosystems and custom-made innovative, inter- structural, and investment and financial), and building sectoral, and interterritorial projects based on the human resources for high-tech businesses and industries principles of interdisciplinarity, cognitiveness, and (Preobrazhensky et al., 2017). project-oriented work, allowing the usage of all the As an integrator of the cross-industry ecosystem, NUST possibilities of fully accessible digital capabilities MISiS is the “entry point” for the formation of new ideas, and industry interaction. Figure 4 shows the structure competencies, technological solutions, and initiating proj- of NUST MISIS, providing the implementation of ects for development, using the following functions: the above functions. 1. Consolidation. Development of strategies and pro- The elements of educational models implemented at the grams for the formation of a digital economy, devel- university are flexible, allowing them to be formed modularly opment, and production—operation and development and assembled according to the mosaic principle for individ- of innovative systems within the framework of a ual or corporate needs of customers—projects implemented closed production process. within the framework of a cross-industry ecosystem. The 2. Innovation and research. Initiation, development, and trends of globalization and digitalization make it necessary to promotion of innovative full-cycle solutions: avoid unification in the educational programs, especially in − At the stage of planning and designing products the cross-industry ecosystem. This is possible through the fol- (digital factory); lowing educational components (Tolstykh et al., 2017): − At the stages of production planning (smart factory); − At stages of operation and maintenance (virtual •• Modularity of distributed courses; factory). •• Active use of network programs, gamification, train- 3. Congress, exhibition, and marketing activities in the ings, cases, and mini hackathons; framework of exhibits of intelligent solutions, with •• Deliver research seminars and classes in small groups; the presentation of innovative complexes, technolo- •• Mobility and educational programs with international gies, and products for participants in inter-sectoral universities; interactions, the promotion of advanced technologies •• Unique courses that have no analogues in other uni- and business models, and international and national versities or in a small number of universities; 12 SAGE Open Table 4. Comparative Analysis of the Proposed Models. Models Freedom of choice (focus on Favorites (orientation on the Characteristic the mass approach) development of the students’ potential) Premium (focus on corporate order) Program selection Determined by the The selection of the best in the first Selection by customer demands criteria conditions of the university semesters of university education entry campaign Educational Free as part of profile Fixed in the program and flexible in Designed to meet customer trajectory distributed requirements requirements Interdisciplinary Implemented by small project Project work and as part of a research Project work and as part of a research teams seminar, network programs seminar, network programs Practical Achieved through training in Internship, summer schools, design Internship, summer schools, orientation enterprises, participation work, and thesis as a cross- design work, thesis as a cross- in projects and graduation interdisciplinary project interdisciplinary project thesis Mobility — One-semester studies at international One-semester studies at international universities, summer schools, universities, summer schools, international internships, and network international internships, and network programs programs Mentoring Tutoring, scientific leader Supervisor, navigator in the construction Tutors both from the university and of knowledge the ecosystem actor enterprises Uniqueness — Unique courses that have no analogues Unique courses developed under in other universities requirements of a cross-industry project Individualization — Individual educational trajectory, formed Individual educational trajectory, depending on the cognitive and formed according to customer intellectual potential of the student requirements •• The possibility of completing additional courses in presence of stakeholders acting as guarantor and customer of related programs; a particular education model. But the most important thing is •• Obtaining skills on modern research equipment to “restart,” that is, to realize one’s identity and independence with subsequent certification and confirmation of in making strategic decisions. qualifications. The above analysis made it possible to identify the main •• Programs in English; functions of universities in a cross-industry ecosystem. •• Preparation and defense of the thesis as an end-to-end interdisciplinary project (based on the Conceive 1. The formation of human resources for high-tech Design, Implement, Operate [CDIO] principle—the businesses and industries: standard of engineering training). (a) Introducing an interdisciplinary approach into training programs and teaching methods. Options for implementation of these principles in educa- Interdisciplinary curricula and project train- tional programs differ from each other in the goals and level ing serve to combine the exact sciences and the of the program’s uniqueness, individualization, and selec- humanities with the aim of introducing techno- tion of students for a particular educational program (see logical development into the context of human Table 4). activity. The concept of educational programs for the cross-indus- (b) Increased focus on project learning as a key com- try ecosystem faces the so-called “restart” problem, which ponent of training programs. It is imperative to implies “disassembling” and “assembling” educational mod- combine theoretical education with solving the ules, staff, and management approaches of the university. The real problems of individual enterprises. Students university should take the main strategic decisions as an eco- in multidisciplinary groups solve these problems system integrator on its own, taking responsibility for all pos- under the guidance of teachers or representatives sible risks, including reputational. For this, the university of business. needs to constantly adjust its research vectors, finding its own (c) The development of entrepreneurial skills and guidelines that will remain relevant and in demand for all thinking through additional modules, special actors in the ecosystem. The risks can be minimized by the projects, or mentoring. Implementation of special Tolstykh et al. 13 projects in which students work in multidisci- mechanisms responsible for this are complex and constantly plinary teams to solve a task on time. The ideas of evolving (Tolstykh & Shkarupeta, 2019). self-organization, teamwork, and training based The effect of cross-industry projects is manifest when on a project approach are extremely important. technologies stimulate the transfer of knowledge in the busi- (d) Large-scale implementation of digital competen- ness environment and lead to increased productivity within cies (knowledge, skills) in training programs. the company in the supply chain and between industries, and 2. The joint production of knowledge for the cross- to the sustainable development of each of the participants in industry projects implementation is a driver of inno- cross-industry interaction. vation. New knowledge should reflect cutting-edge In previous studies in the framework of national innova- research in a specific field that enterprises and other tion systems theory, the role of universities looks relatively interested parties can get through global challenges. passive and limited, and regional agglomeration is naturally The knowledge created must be transferred to inter- explained, namely, the dissemination of knowledge from uni- ested parties in an appropriate form. versity research. However, it is increasingly recognized that (a) Promotion of interdisciplinary research, which the interaction between universities, industry, and the state in requires systemic competencies and partner- the framework of the triple helix should be coordinated ships. Accordingly, the creation of interdisciplin- (Etzkowitz and Leydesdorff, 2000; Gunasekara, 2006). This ary networks is a key organizational task of any indicates the growing importance of researching the role of innovative university. the university, embedded in the ecosystem, as a knowledge (b) Specialization. Each university has its own integrator and consolidator. This aspect is poorly studied in development priorities (research area where the literature. there are strengths), depending on the region The authors in the article analyzed the role of the univer- features. In general, regional research priorities sity within the cross-industry ecosystem as an integrator of are connected with the areas of science that have knowledge, as well as the goals, objectives, and functions of economic and social significance, both in terms the university from the standpoint of the effectiveness break- of their application and implementation of end- through development strategies both for individual ecosys- to-end technologies. tem actors and within the framework of cross-industry (c) A significant increase in revenues from external interaction. research and their share in industry, as well as Using the example of NUST MISIS, the approaches to experience in conducting applied joint research, implementation of the cross-industry ecosystem integrator is a key factor in the development of the ecosys- functions as an “entry point” are given for generating new tem. ideas, competencies, technological solutions, and initiating 3. Engaging with external concerned parties to share projects for the development and testing of new technologies knowledge is the next important function of universi- and products. New formats for creating the necessary com- ties in cross-industry ecosystems. Universities should petencies for the cross-industry ecosystem and on the order foster collaborative interdisciplinary innovation with of innovative inter-sectoral and interterritorial projects based other actors. Knowledge sharing and collaboration on the principles of interdisciplinarity, cognitiveness, and with external partners and the university plays a key project orientation, allowing to use the opportunities of role in this exchange. cross-industry interaction are presented. The theoretical significance of this article includes cross- industry ecosystems theory development in terms of under- Discussion and Conclusion standing of creating and sharing knowledge processes. The Active information and technological development in the practical significance of the research allows using certain world poses new challenges for all sectors. One of them is states and results in the practice of university management, the transformation of interaction processes between eco- as well as in the development of program documents and nomic agents and the construction of cross-industry ecosys- strategies for the socioeconomic development of the country tems with high economic efficiency. and individual regions. Breakthrough innovations and cross-industry impacts The proposed KPIs for assessing the effectiveness of the have become the standard in many processes. At the same university playing the role of an integrator formed the basis of time, integration within the framework, by which various cross-validation of ecosystem actors based on the method of systems interact with each other and create value from vari- analytic hierarchy process (AHP). The results of the imple- ous data streams, is critical. Cross-industry interaction mentation of this mechanism are described by the authors in implies that each participant invests in the development of the article, Tolstykh, Gamidullaeva, and Shmeleva (2020). the digital ecosystem and makes the most of it. At the same The main task of the integrator is to maintain a favorable time, companies, in addition to a direct increase in productiv- environment for all actors in the ecosystem. In previous stud- ity, receive advantages along the entire value chain. The ies, the authors proposed to assess the ecosystem using the 14 SAGE Open entropy approach as the category of ecosystem entropy allows Balconi, M., & Laboranti, A. (2006). University–industry inter- actions in applied research: The case of microelectronics. to describe and analyze the qualitative properties of the internal Research Policy, 35, 1616–1630. environment of the ecosystem. The entropy approach to eco- Bosch, J. 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Building an innovation hub: A case of circular and integration potentials of innovation ecosystems study of the transformation of university roles in regional tech- for industrial sustainability. Sustainability, 12, 4574. https:// nological and economic development. Research Policy, 37(8), doi.org/10.3390/su12114574 1188–1204. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png SAGE Open SAGE

Universities as Knowledge Integrators and Cross-Industry Ecosystems: Self-Organizational Perspective:

SAGE Open , Volume 11 (1): 1 – Feb 12, 2021

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Abstract

Universities play a vital role in innovation ecosystems. Besides, their role is being transformed and reinforced due to the interdisciplinary nature of modern innovations and inter-sectoral collaboration in the process of implementing cross-industry projects. The article’s main objective is to reveal the emerging new goals, functions, and goals of university as knowledge integrator and consolidator within cross-industry ecosystem. The article introduces the approaches to the implementation of the cross-industry ecosystem integrator functions as an “entry point” for the creation of new ideas, competencies, technological solutions, and projects for the development and testing of new technologies. The research results are useful for academics and policy makers in emerging economies to adopt and consider, so as to improve the contribution of the universities to the country’s economic and innovation development. Keywords university, cross-industry ecosystem, self-organization, integrator, university–industry collaborations, knowledge generation, knowledge exchange, innovation ecosystem “multi-cross-industry innovation” is a process of creating Introduction new products, services, or their combinations by combining The emergence and development of new markets, industries, key knowledge elements from at least three different indus- products, and professions in the modern world is proceeding tries and considered the process as a fundamentally new way rapidly. The main catalyst for these processes is the transfor- to successfully develop and create innovative businesses. We mation of the economy, which brings results at the intersection note also that the term “ecosystem” is quite complex and has of industries, using multidisciplinary knowledge, establishing been used in a different sense. It is often used as a metaphor cross-industry processes, developing infrastructure, digital for a network and network external factors, for a particular platforms, and creating new market formats and models for market or market niche, to reflect the complementarity of the interaction of market participants on their base. physical, human, and intellectual assets, or even spillover The ever-increasing complexity of products leads to the effects arising from joint activities (Gamidullaeva et al., fact that innovative processes of enterprises are dependent on 2020). The fundamental idea of this concept is that, in an external knowledge (Chesbrough, 2003; Chesbrough et al., unstable and turbulent environment, economic agents are 2006; von Hippel, 1988, 2001) and interaction with a variety building their strategies and creating competitive advantages of market participants. “The boundaries of firms and their based on resource sharing, network externalities (external corporate hierarchies are breaking down under the impact of effects), and knowledge “flows” (spillover effects). This the forces of interface standards, lowered transaction costs and increasingly modular production” (Foss, 2019). The key National University of Science and Technology “MISIS”, Moscow, Russia strategic direction in these conditions should be the interac- Plekhanov Russian University of Economics, Moscow, Russia tion of different economic sectors through the creation of new Penza State University, Penza, Russia business models and end to end digital processes based on the Razumovsky MSUTM (FCU), Moscow, Russia intersections of industries and through cross-border coopera- Corresponding Author: tion. This interaction is called cross-industrial innovation. Leyla Gamidullaeva, Professor, Penza State University, Krasnaya st., 40, First, the term “multi-cross-industry innovation” was intro- Penza 440026, Penza Region, Russia. Email: gamidullaeva@gmail.com duced by the authors (Khan et al., 2013). They suggested that Creative Commons CC BY: This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). 2 SAGE Open requires the development of new theories and approaches that of the innovation ecosystem was formulated in a recent work reflect real trends, one of which is the theory of ecosystems. by the authors (Granstranda & Holgerssonb, 2020): “the In an economic sense, an ecosystem consists of exogenously evolving set of actors, activities, and artifacts, and the insti- defined components, the environment, and agents acting tutions and relations, including complementary and substi- endogenously together as a system associated with capitaliz- tute relations that are important for the innovative ing on the relationship (Acs et al., 2016). Similar to natural performance of an actor or a population of actors.” At the processes, various kinds of companies, multinational enter- same time, the use of the new term “cross-industry ecosys- prises, small and medium firms, and households coexist and tem” is especially relevant today in view of the need to focus develop within their own ecosystem : on the interdisciplinary nature of modern innovations and knowledge as a consequence of inter-sectoral collaboration. Such ecosystems can be formed on a variety of unifying This thesis was confirmed by N. Farhadi (2019) in his book principles (from geographic and political to industrial and “Cross-Industry Ecosystems,” where the author develops the environmental), as well as at different levels—from local (within theoretical and methodological foundations of the new con- organizations, companies, clusters, science parks) to global, that cept, emphasizing the growing complexity of inter-sectoral is, wherever stable relationships and a joint vision of the economic growth. The main features of cross-industry proj- participants arise. (Smorodinskaya, 2014, p. 28) ects include the following: “blurring” of territorial borders, An ecosystem cannot be rigidly connected to a specific busi- interdisciplinary knowledge and inter-sectoral technologies, ness or industry, but combines interconnected enterprises subprojects in several (at least two) sectors at different lev- from many industries that together create differentiated offers els, involvement and use of infrastructure and resource base and receive additional value (Khan et al., 2013). For example, of various regions, and unlimited implementation of the proj- Apple leads an ecosystem that includes at least four indus- ect in time (one project initiates the implementation of oth- tries—personal computers, consumer electronics, informa- ers). A cross-industry ecosystem approach allows for tion and communications, and, more recently, music and developing the innovation perspective through the self- television. organizational principles, when all participating actors, We agree with authors who criticize the inconsistent use regardless of their size and field of activity, benefit from net- and vague wording of the term “ecosystem” in scientific working and collaboration. Cross-industry ecosystem can be research (Brown & Mason, 2017). Often, there is a substitu- described as a dynamic system, characterized by interactions tion of concepts: An ecosystem is represented by cluster for- among a huge amount and diversity of stakeholders—uni- mations (network innovative ecosystems of a special class) versities, enterprises, public institutions, society, and so on. or a triple helix model based on a university–business–state Many authors highlight that their interaction is based on the partnership (Etzkowitz and Leydesdorff, 2000). Alongside principle of self-organization (De Toni et al., 2012; the triple helix is the quadruple helix theory (Carayannis & Gamidullaeva, 2019; Gamidullaeva & Tolstykh, 2017; Grigoroudis, 2016), which identifies relations between vari- Gamidullaeva et al., 2017; Jucevičius & Grumadaitė, 2014; ous stakeholders (civil society, media, and the culture-based Laihonen, 2006; Shmeleva, 2019; Tolstykh, Gamidullaeva, public) and integrates top-down policies and grassroots & Shmeleva, 2020; Tolstykh, Gamidullaeva, Shmeleva, innovations. Lapygin, 2020; Tolstykh, Shmeleva, & Gamidullaeva, 2020; According to Bruns et al. (2017), the “ecosystem” metaphor and others). reflects a tendency in scientific studies to describe the well- This article is an attempt to further develop the concept of known phenomenon of agglomeration effects of regions a cross-industry ecosystem as a dynamic complex nonhierar- (urban, regional, and national ecosystems), industries (agricul- chical model in terms of studying the changing processes of ture, chemical industry, manufacturing, mass media, and finan- creating and transferring new knowledge. The authors argue cial ecosystems), associations of firms (business ecosystems, that universities should play a key role in these processes. entrepreneurial ecosystems), or activities (services, innovations, Traditionally, the role of universities has been to educate and digital ecosystems). As a result, today we have “business students and implement basic research, which often had ecosystems” (Moore, 1993), “innovation ecosystems” (Adner, positive spillover effects for the industry, as well as stimu- 2006), “digital ecosystems” (Sussan & Acs, 2017), “university lating regional economic growth (Etzkowitz & Leydesdorff, ecosystems” (Hayter, 2017; Meoli et al., 2017), or “financial 2000; Trippl, Sinozic, & Lawton Smith, 2015). University ecosystems” (Cumming et al., 2017; Ghio et al., 2017). project technology transfer offices are extensively The idea of cross-industry ecosystems is a collaboration researched and best practices carefully analyzed (Phan & of actors from various industries in the implementation of Siegel, 2006; Youtie and Shapira, 2008). However, most of cross-industry projects. Therefore, one of the main tasks of the recommendations do not work in every ecosystem; it all the ecosystem is the transfer and exchange of knowledge depends on the maturity and development of the existing between economic entities. In this sense, the concept of ecosystem. We believe that more attention should be paid to “cross-industry ecosystem” is most closely related to the the role that universities can play in strengthening and term “innovation ecosystem.” In turn, a complete definition developing the ecosystem as a whole (Vasin et al., 2018). Tolstykh et al. 3 A university can act as an ecosystem integrator, applying The increasing complexity of interactions between differ- its intellectual, reputational, and financial capital to create ent stakeholders in the process of innovation lead to the fact and maintain a strong ecosystem (Heaton et al., 2019). For that universities have to balance between solving traditional this, it is also necessary to take into account the ecosystem’s and new problems and, as a result, the organizational model ability for self-organization. of universities is in transition in many countries (Guerrero The article’s main objective is to reveal emerging new et al., 2016; Miller et al., 2014). The organization of close roles of university as an integrator of cross-industry ecosys- interaction with the environment and with all stakeholders is tem in the age of digital transformation of industries and ser- a key element of the University 4.0 concept (Dewar, 2017). vices. The remainder of this article is organized as follows. The interaction of enterprises with universities provides First, we outline the role of universities in ecosystems to them with access to knowledge and opportunities for research acknowledge the previous research on the issue and then we at a high-quality level (Hussler et al., 2010; von Raesfeld present a self-organization of cross-industry ecosystem et al., 2012), as well as for innovative development framework that we will use to analyze this role in more (Dahlander & Gann, 2010; Estrada et al., 2016; Galán-Muros detail. Self-organization approach takes into account the & Plewa, 2016). Various studies are conducted to identify the complex dynamic nature of the system and is based on pro- conditions for effective collaboration between enterprises moting the productive self-organization rather than imposing and universities (Bruneel et al., 2010; Mueller, 2006; the top-bottom linear solutions. Organization for Economic Cooperation and Development We then apply this perspective to the case study of the [OECD], 2019). At the same time, the report of the OECD university, “MISIS” (Moscow, Russia), engaging with local (OECD, 2019) identifies the main formal and informal chan- economies for launching new industries, fostering entrepre- nels for such interaction. neurship, and strengthening cross-industry ecosystem. The Formal channels include the following: research collabora- article concludes with a brief summary and discussion, plus tions (Perkmann & Walsh, 2007), operations with intellectual suggestions for future scholarship. property (e.g., selling licenses, patents), scientific mobility The contribution of this article is the revealing of main fea- (Rosli et al., 2018), spin-off organizations in the university tures, functions, and emerging goals of universities in knowl- environment, and university graduates employed in industry edge integration and consolidation within the cross-industry (Balconi & Laboranti, 2006). Informal channels include pub- ecosystem. The research results are useful for academic lishing research results (Perkmann & Walsh, 2007), confer- researchers and policy makers in emerging economies to adopt ences and networking (Steinmo & Rasmussen, 2018), and consider, so as to improve the contribution of the universi- geographic or territorial vicinity (OECD, 2019), technology ties to the country’s economic and innovation development. sharing (research centers, laboratories; Claussen, 2019), and ongoing training for business employees (OECD, 2019). It is important to emphasize that knowledge spillover in Theoretical Background all directions between all actors of the ecosystem. In this way, universities can help organize the free knowledge flows Ecosystems and the University in an ecosystem through the formal and informal channels The universities face a number of challenges due to the described above. A good example is Kendall Square in increasing complexity of innovation processes. Cambridge around Massachusetts Institute of Technology First, the share of international and interdisciplinary (MIT). This is an example of a dynamic innovation ecosys- knowledge is constantly increasing, which creates problems tem around a major university. MIT has actively used univer- for traditional areas of academic research, and which often sity-owned land to support partnerships between universities depends on individual researchers and their scientific and industrial enterprises and to take its unique advantages, schools. Interdisciplinary innovations make new higher helping to develop an internationally significant cluster of demands on their organization and management. biological and pharmaceutical sciences (Heaton et al., 2019). Second, increasing organizational and coordination com- Thus, at the stage of ecosystem development, universities plexity implies the use of systemic innovative approaches. help it achieve its maturity and unite and strengthen relations Third, the exchange of innovative knowledge is moving between all actors. toward the complexity of cooperation and knowledge mod- Meanwhile, in cross-industry ecosystems, there is the els (e.g., innovation clusters, multifactor centers led by uni- problem of harmonizing and coordinating the interests of all versities or industry, and public–private partnerships between participants and, accordingly, maintenance of self-organiz- the government, industry, and universities). ing processes is increasing. Thus, due to economic transformation, the role of univer- In this context, it is expedient to take the perspective of sities in the innovation ecosystem as a traditional center of the quadruple helix approach as a network of relationships. knowledge creation is changing, and inter-sectoral innova- By studying the interdependencies of the ecosystem actors, tion networks should be organized. resources, and activities from a self-organizational perspective, 4 SAGE Open we aim at enhancing our understanding of the relationships complex systems cannot impose their development paths. We between actors in the quadruple helix model. should strive to understand trends to manage them. The prob- In addition, the development of a complex nonhierarchi- lem of managing both ecosystem actors and the ecosystem is cal ecosystem gains substantial importance. The key aspect to create an infrastructure for self-directed development. is stimulating relations and interactions between the ecosys- Second, ecosystems often are established spontaneously, tem actors in nonhierarchical ways and facilitating the self- as a reaction to digital transformations processes of all mar- organization of its actors. Cross-industry and innovation ket participants. Hence, we can diagnose the so-called ecosystems can be characterized by a combination of top- chaos as the second postulate of the synergetic approach. A down and bottom-up initiatives (Jucevičius & Grumadaitė, chaotic state contains uncertainty, probability, and random- 2014) that stimulate networking and innovation develop- ness, which are described using the concepts of information ment. The approach of complexity theory toward cross- and entropy. The collaborative ecosystem links are formed industry ecosystem means that responses to environment are at different levels through chaos. Furthermore, it is interest- emerging from spontaneous bottom-up interaction without a ing to note that, at times of ecosystem instability, even central control (Jucevičius & Grumadaitė, 2014). small fluctuations that occur inside the ecosystem can gen- In previous works, we pointed out that the main limiting erate large macro processes. That is, the actions of each point of network models is that horizontal synergistic inter- ecosystem actor can significantly affect macroeconomic action between participants is subject to vertical manage- processes. ment from above. The management system can be either a The assessment of knowledge creation (intellectualiza- state structure or a large enterprise, building network rela- tion) in the ecosystem should reflect the economic return on tions with other enterprises for their interests. Elements of investment in the development of digital technologies and the management vertical initially violate the principles of human resources, and increase the level of intellectual harmonization and balanced development of individual par- potential. The effect of system intellectualization occurs ticipants as the interests and priorities of the governing body when technologies stimulate the transfer of knowledge and (governmental, business, and societal or any other structures) business innovations, and lead to increased productivity do not always coincide with the interests of other participants within the company, in the supply chain and between indus- (Tolstykh, Gamidullaeva, & Shmeleva, 2020). tries, and to the sustainable development of each of the par- In this way, the article aims to contribute to the literature ticipants in digital cross-industry interaction along the entire on the innovation ecosystem and quadruple helix model by added chain cost. offering a novel view on self-organizing perspective. We For the creation of dissipative structures from a systemic conclude that, to fully understand the complexity of the perspective, certain conditions must be met: cross-industry ecosystem model, we need to address the challenge of organizing and maintenance of spontaneous •• Dissipative structures can be formed only in open bottom-up interaction without a central control. With this systems. An inflow of energy is possible, compensat- aim, we suggest that the universities play the role of ecosys- ing for the losses and ensuring the existence of tem integrator and consolidator. Meanwhile, the existing lit- ordered states. Due to this, along with the production erature in the research field is inconclusive with regard to of entropy, there is a flow of “negative entropy” from identification of the new roles and functions of universities the outside. One of the main properties of complex in the cross-industry collaboration and knowledge creation self-organizing systems is the accelerated production processes. of entropy, that is, when a new ordered structure arises, the rate of knowledge entropy production increases sharply; Self-Organization of Cross-Industry •• Dissipative structures arise in systems consisting of a Ecosystem Framework large number elements. The ordered movement in The study of the cross-industry ecosystem as a system of such systems is always cooperative and integrated as integrating knowledge is based on the methodology of a sys- a large number of objects are involved in it; tematic approach and self-organization law. •• Dissipative structures arise only in nonlinear systems. First, ecosystems belong to the class of nonlinear systems. Self-organization exists under special internal and Nonlinear systems are those in which the linearity of the sta- external conditions of the system and the environ- tistical characteristic is violated in at least one link or there is ment. Dissipative structures are stable formations, but a violation of the link dynamics equations. Nonlinearity pre- their stability is determined by the stability of the determines the uncertainty of system behavior at any time sources of incoming energy and depends on the time interval. Most processes in the ecosystem and in its links with of their existence; other systems reaction are currently undergoing crisis devel- •• If, as a result of self-organization, several competing opment, which is a consequence of the system reaction to dissipative structures arise, then one of them that pro- external and internal challenges. Moreover, it is obvious that duces entropy with the highest rate survives. Thus, by Tolstykh et al. 5 Figure 1. Cross-industry ecosystem model. calculating the entropy of an ecosystem, we can predict •• Nonequilibrium as the initial state is a source of the the rate of change. And this, in turn, will make it pos- system self-movement; sible to assess with the greatest probability the sustain- •• Time is an internal characteristic of a system that ability of the ecosystem as a complex self-organizing expresses the irreversibility of processes in a system. system; •• The creation of ecosystems as new ordered struc- From our point of view, the ecosystem is not only the abil- tures occurs according to the bifurcation scenario ity to respond and reflect technological and digital challenges, (Preobrazhensky & Tolstykh, 2004). but also to create intelligent technical environments that mini- mize negative consequences and create optimal conditions At the time of crisis transformations, a bifurcation point for the implementation of projects at any level. In accordance arises. There can be many possible development strategies with the principles of ecosystem, we will understand the from this point, but nevertheless, a certain predetermination actor’s cognition as the mechanisms for achieving strategic of the processes of deployment exists, which performs the goals by actors based on the processes of new knowledge for- present not only through the past, but also the future state in mation, their transfer and exchange, and on the theory of self- accordance with the upcoming order. organization, information, and digital technologies. The distinctive features of ecosystems as complex self- However, the technological environment surrounding the organizing systems include the following: actor can be simpler (“the whole is less than a part”) and, in creating a cognitive mechanism, can appear as a synergistic •• Coherence (interconnectedness): they behave as a effect. Such an effect is possible in cases of subsequent collec- whole; tive actions, when the intellectual environment leads to the •• Deviations occurring in the system, instead of decay- generation of knowledge, ideas, and the implementation of cre- ing, can intensify, and the system evolves in the direc- ative and effective solutions. The knowledge management tion of “spontaneous” self-organization; becomes a priority in ensuring the effectiveness of cross-indus- •• Chaos is a constructive mechanism of self-organiza- try interaction, creating an ecosystem, and a unified business tion complex systems as the birth of a new one is asso- environment, predetermining the need for the formation of new ciated with a violation of the usual system ordering; cross-professional competencies (Tolstykh & Shkarupeta, •• Evolution contains both deterministic and stochastic 2019). The development of a knowledge management mecha- elements, representing a mixture of necessity and risks; nism in the context of a cross-industry ecosystem formation 6 SAGE Open will optimally manage the economic, social, and technological a given period of time. These functions in the indus- processes of ecosystem actors to achieve high socioeconomic trial ecosystem can be performed by digital plat- efficiency, as well as measure the effects of the cross-industry forms, new technologies, materials, innovative transformation through intellectualization. projects, and start-ups. The main indicator of the ecosystem development is pro- 2. Integrator—is an actor who unites other actors for posed to consider knowledge, which plays the role of system an idea or project and analyzes and evaluates the “energy” source (Figure 1). necessary competencies of actors and the degree of The ecosystem management system can be considered as their economic security for other participants. This a system with two closed control loops. One of the loops is task can be performed by universities, research the usual feedback, providing the traditional management organizations, project offices, and digital platforms process: input-output-input. Feedback compares the input that accumulate knowledge, competencies, and and output parameters, being a standard response to the chal- international experience. lenges of micro and macro environments. 3. Developers—actors involved in the development and The other loop performs self-customization. As a rule, a prototyping of new technologies, materials, and pro- particular criterion of the quality of the system’s work (in cesses. This role can be implemented by technoparks, this case, the quality of the cross-industry project) is laid start-ups, engineering companies, and research down in the self-organizing system for the external condi- structures. tions of the system. The system itself chooses a structure in 4. Implementers—actors implementing new projects which a given quality criterion of the entire system is satis- and processes on their site; fied. A self-organizing system must have an analyzer or qual- 5. Promoters—actors providing promotion of imple- ity optimizer. The optimizer is designed to find and implement mented projects and conversion of past projects’ the highest possible quality in a given system. This function experi ence into new projects and project commer- is the main aim of the university as an ecosystem actor. cialization. The source of the ecosystem’s intellectual “energy” is the knowledge generated by universities. University education In effectiveness of the cross-industry ecosystem, a signifi- has always been a reflection of the processes taking place in cant role should be given to the “integrator,” namely, to ensure society. Hence, the universities have to become the bridge- the creativity, innovativeness, and balance of the effects and head of the cross-industry ecosystem for innovation in tech- interests of a variety of the ecosystem’s actors based on the nology, research, and management. creation and transfer of new knowledge. Universities can take The law of self-organization and self-preservation for the up such a role in the cross-industry ecosystem. ecosystem works when the sum of the potentials of the system Key performance indicators (KPIs) are used to assess significantly exceeds the total effects of the micro and macro whether and how well the objectives of each ecosystem actor environment. The basis for implementing preventive measures are met and what they can do to improve. for the ecosystem is the constant work to increase the amount KPIs reflects the requirements of the ecosystem and its of knowledge accumulated by ecosystem actors; the constant type. Currently, there are many different approaches to processing and transformation of information into knowledge; KPIs’ building (Bosch, 2009; Chapin et al., 1996; Cokins, the generation of new information, knowledge, and creative 2009; Government Accountability Office, 2011; Iansiti & ideas; and the training of competitive specialists. Richards, 2006; Parmenter, 2010; Rapport et al., 1998; Next, we move on to the detailed description of the for- Santos et al., 2012). mation principles and performance criteria of cross-industry The literature indicates that KPI for industrial ecosystems ecosystems. This is necessary for a deeper understanding of is a thin area. A wide range of literature exist although for- the role, functions, and tasks of universities in the cross- mulation of KPIs is insufficient (Fotrousi et al., 2014). industry ecosystem. The considered research on ecosystem KPI mostly addresses measurements of satisfaction, performance indi- cators, and freedom from risks. Meanwhile, a broader Indicators for Measuring a Cross- understanding of KPI would help to use them for Industry Ecosystem decision-support. The ecosystem actors are large industrial enterprises, tech- The following blocks of indicators were used to assess the noparks, engineering structures, start-ups, venture funds and KPIs of ecosystem actors: financial institutions, universities and research organiza- tions, various business structures, and government authori- 1. Business processes: ties. The key roles of actors in the ecosystem are as follows: 9 Compliance of processes in the organization with the principles of lean production; 1. Pacemaker—is an actor who initiates an idea, proj- 9 Compliance of processes in the organization with ect, or process that inspires ecosystem unification in the principles of quality management; Tolstykh et al. 7 9 Project-oriented organizational structure; 3. For each ith actor P , i = 1, . . ., m, the values of the 9 Technological level of business processes. jth indicator are determined, j = 1, . . ., n, and the 2. Relations with partners and clients: matrix h is formed. ij 9 Existence of long-term partnerships with suppliers; 4. For each group of factors, a standard is formed with 9 The presence of long-term partnerships with customers; the maximum values of indicators, , hh j = max ij 9 Level of customer loyalty; j = 1, . . ., n, i = 1, . . ., m. 9 Speed of response to changing client requests. 5. Furthermore, the indicators of the ith actor are nor- 3. Digital maturity: malized, where j = 1, . . ., n, i = 1, . . ., m. 9 Level of digital competence of personnel; 9 Level of digitalization of enterprise management ij k = ij processes; 9 Level of digitalization of business processes; 6. Setting the weight coefficients wj for n indicators is 9 Number of completed digital projects. carried out based on the analysis of the matrix of 4. Innovative susceptibility: paired comparisons: 9 Financial level of the organization’s readiness for implementation; w = 1. 9 Management efficiency; ∑ j j=1 9 Level of legal protection of all processes of the enterprise; The integral coefficient of competitiveness of the ith actor 9 Time of implementation of an innovative project is calculated as the arithmetic average of the weighted 1 of from its initiation to launch; the normalized performance indicators: 9 Level of qualifications and intellectual potential m m of the personnel; Kw = kw . ∑∑ ij ij j 9 Innovative motivation of personnel. j== 11 j For each KPI value, a score is correlated depending on the result of the indicator. University as an Integrator (Seizing) The KPI assessment as a whole (taking into account all its Within Cross-Industry Ecosystem blocks, namely, business processes relations with partners and clients, digital maturity, and innovation susceptibility) is As the actor in the cross-industry ecosystem, the university proposed to be determined in the following sequence. should change its role from a highly specialized university to an innovative university in the new economy. 1. Calculate the relative scores of KPI indicators for each The aim of the university is to increase the amount of of the evaluation blocks, using the following formula: knowledge accumulated by the ecosystem, process and transfer the information into knowledge, and generate new O = *, n ii Ni information and knowledge. Thus, the influence of the uni- versity on other actors in the ecosystem is to transfer knowl- where О is the relative estimate of the ith block, N is the i i edge along the following chains: number of KPIs in the block, and n is the point in accordance with the zones of values of threshold values of KPI of the ith •• University—cross-industry project—production— block. economics; •• University—cross-industry project—science— 2. Determine the weights B of each block. It is pro- inno vations—economics. posed to use a scale from 1 to 5, where 1 is the least significant and 5 is the most significant. The total The roles of universities in the cross-industry ecosystem can value of the weights must be 5. be represented as a scheme (Figure 2) containing the follow- 3. Calculate the integral evaluation as a weighted aver- ing tasks: age of the components. The closer it is to 1, the higher the KPI level. A score below 0.5 indicates insufficient 1. Define and formulate a vision of the ecosystem as a ecosystem maturity of the actor. whole; 2. Evaluate the role of each actor, predict ecosystem The methodology for assessing ecosystem performance development, and develop strategies; based on KPIs consists of the following stages: 3. Form a community of actors, finding them according 1. Allocation of actors making up m groups of the to the maturity level of KPI. ecosystem. 4. Find existing projects for inclusion in the ecosystem 2. Determination of a complete list of KPI indicators. as subprojects in new cross-sectoral projects; 8 SAGE Open Figure 2. The role of universities in the cross-industry ecosystem. 5. Integrate knowledge on technologies, competencies, 3. Joint distributed activity and cooperation of all eco- and best practices, and bring them to ecosystem systems’ actors based on the integration, reproduc- actors; tion, and processing of knowledge; 6. Initiate new ideas and technology projects in the 4. Personalization of educational activities, taking into interests of the ecosystem actors; account the cognitive, intellectual level of the 7. Provide ecosystem services to other communities. student; 5. Multilingualism and multiculturalism; 6. Interdisciplinary communication skills; The Objectives of the University as an Ecosystem 7. Customer focus on both individual and corporate Integrator clients; 8. Process orientation and ability to work in projects: The university creates the space for resources and actors to 9. Ability to work in high uncertainty and quick change more consistently and systematically align as a means of of task, management of complex automated systems, addressing regional problems/needs (Celuch et al., 2017). and work with artificial intelligence; Thus, universities have a great impact in their host regions. 10. Practical orientation (Tolstykh et al., 2017). They function as key institutions by communicating with the actors of their ecosystem, providing innovation, and sharing resources, knowledge, competences. It is advisable for uni- versities to create the necessary support structures, play a Universities, Cross-Industry Ecosystem, leading role in partnership with public and private authori- and Self-Organization: A Case of ties, and, more importantly, show their ability to provide a National University of Science and leading role in developing the necessary partnerships. Technology (NUST) MISIS (Russia) By “integrator” we have in mind universities that are able to address a set of ever-changing in demand market prefer- We will now take a closer look at a case study that dem- ences and exert considerable control over an ecosystem. onstrates the integrating role that the university plays The main objectives of the university as an integrator in within a cross-industry ecosystem from a self-organizing the ecosystem should be the following: perspective. To analyze the complex interorganizational relationships 1. Holistic systematic view of all processes taking place of the ecosystem and the corresponding governance require- in the world, studying the phenomena of science and ments at the university, we decided to use a case study society on the basis of interdisciplinary, the ability to approach (Eisenhart, 1989; Yin, 2003). define complex systems and work with them, and Our research began with a review of the academic litera- system engineering; ture and other documentation related to the formation and 2. Learning in communication as the main feature of development of various cross-industry ecosystems in digital education; Russia. We decided to dwell in detail on the experience of Tolstykh et al. 9 Table 1. Characteristics of the Ecosystem Actors—“Developers.” Group of actors (A ) Goals KPIs • Laboratory “Nanochemistry and Ecology,” NUST • Development of new technologies for • Total innovation index SII; MISIS; resource conservation and processing • The level of digital maturity; • The center of resource-saving technologies for of industrial and man-made waste; • The share of unique processing mineral raw materials, NUST MISIS; • Commercialization of technologies; technologies in the overall • Industrial technology engineering center; • R&D structure; • Innovative scientific and educational center “Romelt,” • Research and development NUST MISIS. costs. Note. KPI = key performance indicator; NUST = National University of Science and Technology. Table 2. Characteristics of the Ecosystem Actors—“Implementers.” Group of actors (A ) Goals KPIs “Moscow State University of Civil Engineering • Commercialization of technologies; • The level of cooperation (National research University),” BSTU named • R&D; development between actors; after V. G. Shukhov, Samara National Research • Implementation of complex high- • The number and cost of joint University named after S. P. Koroleva, University budget projects for large industrial projects in which ecosystem of the Basque Country, MEPhI. companies. actors are involved. Note. KPI = key performance indicator. Table 3. Characteristics of the Ecosystem Actors—“Promoters.” Group of actors A Goals KPIs PJSC “Inter-RAO,” Increasing competitiveness and profitability • Balanced financial result of the actor; PJSC “RusHydro,” through the introduction of innovative • Correspondence of resources to the SC “Rosatom,” technologies and processes. strategic goals of the actor; PJSC “Alrosa,” • Transfer of knowledge, technologies, GC “Novolipetsk Metallurgical Plant,” Federal and results within the ecosystem. Agency for Special Construction of Russia (Spetsstroy of Russia), “Zabsibgazprom” Note. KPI = key performance indicator. one of the largest universities in our country—NUST MISIS. complex processing of natural and associated gases, This university has achieved a great success as an innova- as well as biogas using various processes; tion center. •• Project 2. Development of technologies for the pro- In this article, the case study method is used to illustrate duction and use of composite binders for the construc- one crucial aspect of cross-industry relations, namely, the tion of transport and hydraulic structures, using role of the university as an integrator of knowledge in the large-tonnage waste from mining and processing of ecosystem. This allowed us to conceptualize this aspect mineral raw materials; within the emerging theory of cross-industry ecosystems. •• Project 3. Development of an integrated innovative technology for the extraction and processing of mineral raw materials, with underground waste isolation for Participants in the NUST MISIS Cross-Industry solving state scientific and technological problems of Ecosystem energy and environmental security (Tolstykh, Shmeleva, NUST MISIS plays the role of integrator in the discussed et al., 2020). ecosystem, and the domain of the ecosystem is the projects aimed at sustainable development in the raw materials and NUST MISIS, which takes an active part in innovative processing sectors: projects through the system of interaction and partnership with enterprises of various industries and scales, includes the •• Project 1. Development of a new generation of flexi- following main actors (see Tables 1 to 3). ble and high-performance catalytic reactor systems This ecosystem integrates the industries shown in based on structured catalysts (adsorbents) for the Figure 3. 10 SAGE Open Figure 3. Structure of a cross-industry ecosystem. Note. NUST = National University of Science and Technology. The strategic direction of the presented cross-industry 1. Represent an open system that exchanges matter, ecosystem is project cooperation of enterprises through the energy, and information with the environment; creation of new business models and end-to-end digital pro- 2. Demonstrate the ability to accumulate and use useful cesses through both traditional intersections of industries and experience; through cross-border cooperation. Within the framework of 3. Are capable of adaptive activity due to which useful this direction, MISIS University has formed a combination abilities increase and useless abilities decrease. of fundamental and applied science with access to the real sector of the economy on the basis of the following strategic An ecosystem is an integration mechanism between gener- academic units (SAU) of NUST MISIS: ating new knowledge and using it to create shared value •• SAU 1. Metamaterials and post-silicon electronics between actors. An effective mechanism for redistributing and materials design. value within an ecosystem is based on the diffusion of inno- •• SAU 2. Autonomous energy and energy efficiency. vations, knowledge spillovers, and externalities. Knowledge •• SAU 3. Materials and technologies to increase the spillover is a process aimed at developing interactions duration and quality of life. between exchange participants, simplifying decision-making, •• SAU 4. Industrial design and technologies for rein- and stimulating innovation through the evolution of collabo- dustrialization of the economy. ration between actors. Within an ecosystem, several projects •• SAU 5. Green technologies for resource conservation. can be implemented simultaneously and each actor of the ecosystem has the opportunity to participate simultaneously Functions, Features, and Principles of Forming in different projects in different roles. The mechanism of interaction between ecosystem actors and the assessment of a Cross-Industry Ecosystem Based on NUST the potential of the ecosystem actor for compliance with a MISIS: New Models for the Implementation of particular role in the initiated project is described in detail by Educational Programs the authors in Tolstykh, Gamidullaeva, and Shmeleva (2020). The mechanism of interaction between actors within an eco- The mechanism of interaction between actors is imple- system is based on the theory of complex adaptive systems. mented through cross-validation as a new self-tuning cir- Complex adaptive systems have the following basic features: cuit within the ecosystem. To assess the effectiveness of Tolstykh et al. 11 Figure 4. The structure of NUST MISIS as an integrator of the cross-industry ecosystem. interaction processes, the system potential method was events in the digital industry, including forums, com- used (Pushnoi, 2017). petitions (e.g., hackathons), as well as events aimed at The university as an ecosystem integrator should pro- attracting investors and demonstrating opportunities. vide functions such as generating ideas, organizing access 4. The management and educational system of profes- to the technological potential of the best centers of excel- sional and national competencies and fundamentally lence in the relevant industries, creating resource support new forms of forming the competencies for digital for the innovation process (analytical, predictive, infra- ecosystems and custom-made innovative, inter- structural, and investment and financial), and building sectoral, and interterritorial projects based on the human resources for high-tech businesses and industries principles of interdisciplinarity, cognitiveness, and (Preobrazhensky et al., 2017). project-oriented work, allowing the usage of all the As an integrator of the cross-industry ecosystem, NUST possibilities of fully accessible digital capabilities MISiS is the “entry point” for the formation of new ideas, and industry interaction. Figure 4 shows the structure competencies, technological solutions, and initiating proj- of NUST MISIS, providing the implementation of ects for development, using the following functions: the above functions. 1. Consolidation. Development of strategies and pro- The elements of educational models implemented at the grams for the formation of a digital economy, devel- university are flexible, allowing them to be formed modularly opment, and production—operation and development and assembled according to the mosaic principle for individ- of innovative systems within the framework of a ual or corporate needs of customers—projects implemented closed production process. within the framework of a cross-industry ecosystem. The 2. Innovation and research. Initiation, development, and trends of globalization and digitalization make it necessary to promotion of innovative full-cycle solutions: avoid unification in the educational programs, especially in − At the stage of planning and designing products the cross-industry ecosystem. This is possible through the fol- (digital factory); lowing educational components (Tolstykh et al., 2017): − At the stages of production planning (smart factory); − At stages of operation and maintenance (virtual •• Modularity of distributed courses; factory). •• Active use of network programs, gamification, train- 3. Congress, exhibition, and marketing activities in the ings, cases, and mini hackathons; framework of exhibits of intelligent solutions, with •• Deliver research seminars and classes in small groups; the presentation of innovative complexes, technolo- •• Mobility and educational programs with international gies, and products for participants in inter-sectoral universities; interactions, the promotion of advanced technologies •• Unique courses that have no analogues in other uni- and business models, and international and national versities or in a small number of universities; 12 SAGE Open Table 4. Comparative Analysis of the Proposed Models. Models Freedom of choice (focus on Favorites (orientation on the Characteristic the mass approach) development of the students’ potential) Premium (focus on corporate order) Program selection Determined by the The selection of the best in the first Selection by customer demands criteria conditions of the university semesters of university education entry campaign Educational Free as part of profile Fixed in the program and flexible in Designed to meet customer trajectory distributed requirements requirements Interdisciplinary Implemented by small project Project work and as part of a research Project work and as part of a research teams seminar, network programs seminar, network programs Practical Achieved through training in Internship, summer schools, design Internship, summer schools, orientation enterprises, participation work, and thesis as a cross- design work, thesis as a cross- in projects and graduation interdisciplinary project interdisciplinary project thesis Mobility — One-semester studies at international One-semester studies at international universities, summer schools, universities, summer schools, international internships, and network international internships, and network programs programs Mentoring Tutoring, scientific leader Supervisor, navigator in the construction Tutors both from the university and of knowledge the ecosystem actor enterprises Uniqueness — Unique courses that have no analogues Unique courses developed under in other universities requirements of a cross-industry project Individualization — Individual educational trajectory, formed Individual educational trajectory, depending on the cognitive and formed according to customer intellectual potential of the student requirements •• The possibility of completing additional courses in presence of stakeholders acting as guarantor and customer of related programs; a particular education model. But the most important thing is •• Obtaining skills on modern research equipment to “restart,” that is, to realize one’s identity and independence with subsequent certification and confirmation of in making strategic decisions. qualifications. The above analysis made it possible to identify the main •• Programs in English; functions of universities in a cross-industry ecosystem. •• Preparation and defense of the thesis as an end-to-end interdisciplinary project (based on the Conceive 1. The formation of human resources for high-tech Design, Implement, Operate [CDIO] principle—the businesses and industries: standard of engineering training). (a) Introducing an interdisciplinary approach into training programs and teaching methods. Options for implementation of these principles in educa- Interdisciplinary curricula and project train- tional programs differ from each other in the goals and level ing serve to combine the exact sciences and the of the program’s uniqueness, individualization, and selec- humanities with the aim of introducing techno- tion of students for a particular educational program (see logical development into the context of human Table 4). activity. The concept of educational programs for the cross-indus- (b) Increased focus on project learning as a key com- try ecosystem faces the so-called “restart” problem, which ponent of training programs. It is imperative to implies “disassembling” and “assembling” educational mod- combine theoretical education with solving the ules, staff, and management approaches of the university. The real problems of individual enterprises. Students university should take the main strategic decisions as an eco- in multidisciplinary groups solve these problems system integrator on its own, taking responsibility for all pos- under the guidance of teachers or representatives sible risks, including reputational. For this, the university of business. needs to constantly adjust its research vectors, finding its own (c) The development of entrepreneurial skills and guidelines that will remain relevant and in demand for all thinking through additional modules, special actors in the ecosystem. The risks can be minimized by the projects, or mentoring. Implementation of special Tolstykh et al. 13 projects in which students work in multidisci- mechanisms responsible for this are complex and constantly plinary teams to solve a task on time. The ideas of evolving (Tolstykh & Shkarupeta, 2019). self-organization, teamwork, and training based The effect of cross-industry projects is manifest when on a project approach are extremely important. technologies stimulate the transfer of knowledge in the busi- (d) Large-scale implementation of digital competen- ness environment and lead to increased productivity within cies (knowledge, skills) in training programs. the company in the supply chain and between industries, and 2. The joint production of knowledge for the cross- to the sustainable development of each of the participants in industry projects implementation is a driver of inno- cross-industry interaction. vation. New knowledge should reflect cutting-edge In previous studies in the framework of national innova- research in a specific field that enterprises and other tion systems theory, the role of universities looks relatively interested parties can get through global challenges. passive and limited, and regional agglomeration is naturally The knowledge created must be transferred to inter- explained, namely, the dissemination of knowledge from uni- ested parties in an appropriate form. versity research. However, it is increasingly recognized that (a) Promotion of interdisciplinary research, which the interaction between universities, industry, and the state in requires systemic competencies and partner- the framework of the triple helix should be coordinated ships. Accordingly, the creation of interdisciplin- (Etzkowitz and Leydesdorff, 2000; Gunasekara, 2006). This ary networks is a key organizational task of any indicates the growing importance of researching the role of innovative university. the university, embedded in the ecosystem, as a knowledge (b) Specialization. Each university has its own integrator and consolidator. This aspect is poorly studied in development priorities (research area where the literature. there are strengths), depending on the region The authors in the article analyzed the role of the univer- features. In general, regional research priorities sity within the cross-industry ecosystem as an integrator of are connected with the areas of science that have knowledge, as well as the goals, objectives, and functions of economic and social significance, both in terms the university from the standpoint of the effectiveness break- of their application and implementation of end- through development strategies both for individual ecosys- to-end technologies. tem actors and within the framework of cross-industry (c) A significant increase in revenues from external interaction. research and their share in industry, as well as Using the example of NUST MISIS, the approaches to experience in conducting applied joint research, implementation of the cross-industry ecosystem integrator is a key factor in the development of the ecosys- functions as an “entry point” are given for generating new tem. ideas, competencies, technological solutions, and initiating 3. Engaging with external concerned parties to share projects for the development and testing of new technologies knowledge is the next important function of universi- and products. New formats for creating the necessary com- ties in cross-industry ecosystems. Universities should petencies for the cross-industry ecosystem and on the order foster collaborative interdisciplinary innovation with of innovative inter-sectoral and interterritorial projects based other actors. Knowledge sharing and collaboration on the principles of interdisciplinarity, cognitiveness, and with external partners and the university plays a key project orientation, allowing to use the opportunities of role in this exchange. cross-industry interaction are presented. The theoretical significance of this article includes cross- industry ecosystems theory development in terms of under- Discussion and Conclusion standing of creating and sharing knowledge processes. The Active information and technological development in the practical significance of the research allows using certain world poses new challenges for all sectors. One of them is states and results in the practice of university management, the transformation of interaction processes between eco- as well as in the development of program documents and nomic agents and the construction of cross-industry ecosys- strategies for the socioeconomic development of the country tems with high economic efficiency. and individual regions. Breakthrough innovations and cross-industry impacts The proposed KPIs for assessing the effectiveness of the have become the standard in many processes. At the same university playing the role of an integrator formed the basis of time, integration within the framework, by which various cross-validation of ecosystem actors based on the method of systems interact with each other and create value from vari- analytic hierarchy process (AHP). The results of the imple- ous data streams, is critical. Cross-industry interaction mentation of this mechanism are described by the authors in implies that each participant invests in the development of the article, Tolstykh, Gamidullaeva, and Shmeleva (2020). the digital ecosystem and makes the most of it. At the same The main task of the integrator is to maintain a favorable time, companies, in addition to a direct increase in productiv- environment for all actors in the ecosystem. In previous stud- ity, receive advantages along the entire value chain. The ies, the authors proposed to assess the ecosystem using the 14 SAGE Open entropy approach as the category of ecosystem entropy allows Balconi, M., & Laboranti, A. (2006). University–industry inter- actions in applied research: The case of microelectronics. to describe and analyze the qualitative properties of the internal Research Policy, 35, 1616–1630. environment of the ecosystem. The entropy approach to eco- Bosch, J. 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Journal

SAGE OpenSAGE

Published: Feb 12, 2021

Keywords: university; cross-industry ecosystem; self-organization; integrator; university–industry collaborations; knowledge generation; knowledge exchange; innovation ecosystem

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