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In this Special Issue, we consider sustainable innovation ecosystems as complex adaptive systems, in which many autonomous and heterogeneous actors leverage their resources and capabilities and create new ones, by interacting with each other at multiple levels, to allow innovative solutions to new problems to emerge, in a very short time.
Guest editors:
Linda Ponta,
Università di Genova, Italy
linda.ponta@unige.it;
Giovanna Ferraro,
University of Rome Tor Vergata, Italy;
giovanna.ferraro@uniroma2.it;
Raffaella Manzini,
LIUC - Cattaneo University, Castellanza, Italy;
rmanzini@liuc.it;
Andrew W. H. Ip
University of Saskatchewan, Department of Mechanical engineering, Canada
wh.ip@polyu.edu.hk
Cristina Ponsiglione,
University of Naples Federico II, Italy;
ponsigli@unina.it;
Andreas Pyka,
University of Hohenheim, Germany;
a.pyka@uni-hohenheim.de;
Ben Vermeulen,
University of Bremen, Germany;
ben.vermeulen@uni-bremen.de;
Special issue information:
Background and Motivation
In the last decade, the number of scientific articles on ecosystems has dramatically increased, and more generally, the adoption of the ecosystem concept in innovation and entrepreneurship studies has become increasingly popular.
The concept of ecosystem was borrowed from the field of ecology during the late 1980s (Van de Ven, 1986), where ecosystems are characterized by strongly interconnected groups of organisms that interact with each other and with the physical environment where they live, to maintain the dynamic equilibrium of the system (Jackson, 2011).
The ecosystem metaphor marked a substantial shift in innovation and entrepreneurship studies, away from an individualistic perspective toward deeper attention to collectivity and community, thus including social, cultural, and economic forces in the entrepreneurship process (Stam & Van de Ven, 2021). However, despite many years passed since its first introduction, the concept of ecosystem gained momentum only recently (Stam, 2015), especially in the fields of management and innovation, as the growing number of papers published after 2010 proves (Tsujimoto et al., 2018).
The concept of ecosystem is strongly debated in scientific literature and introduces different concepts focused on specific aspects. Most of the studies dealing with this topic adopt a qualitative approach, hence analyzing ecosystems in a descriptive way aimed at pointing out the founding elements and policies that encourage the establishment of an innovation ecosystem. What mostly emerges is that innovation and entrepreneurial ecosystems include a combination of social, institutional, financial, and cultural components (Van de Ven, 1993; Spigel, 2017; Ancona et al., 2023).
According to Granstrand and Holgersson (2020, p.3) “an innovation ecosystem is the evolving set of actors, activities, and artifacts, and the institutions and relations, including complementary and substitute relations, that are important for the innovative performance of an actor or a population of actors”.
Specifically, the set of actors, structures, and activities, as well as the institutions and relations that characterize ecosystems, could lead to innovation and vice versa. (Granstrand & Holgersson, 2020).
Among the innovation ecosystems, a subset is represented by sustainable innovation ecosystems where also the environment is considered an important element (Zeng et al., 2017). More in detail, sustainable innovation ecosystems are ecosystems in which the collaborations between the internal departments of organizations and external organizations have been assumed to play a strategic role to target social and environmental sustainability matters, developing ethical, social, economic, and environmental rules (Stubbs and Cocklin, 2008, Pham and Vu, 2022).
Sustainability and the sustainability transition are salient concerns for sustainable development and social well-being and have become an imperative for governments, policymakers, and organizations as underlined also by the 2030 Agenda for Sustainable Development. Thus, studying sustainable innovation ecosystems and their complex dynamics could be of prominent interest for scholars and policymakers.
Several authors describe ecosystems and in particular, sustainable innovation ecosystems as complex systems, thus borrowing concepts from complexity theory. Isenberg (2016) claims that the ecosystem implies the existence of a largely self-organizing, self-sustaining, and self-regulating system, and this aspect needs to be considered in the development of pro competition policies. The theme of self-organization is also treated by Tan et al. (2020), whose studies depict ecosystems as robust, scalable architectures that can automatically solve complex and dynamic problems, possessing several properties, including self-organization, self-management, sustainability, and scalability.
Self-organization is a term typically used in literature to describe a process in which small units assemble into larger structures without external intervention (Burnes, 2005); this process often combines with a co-evolutionary perspective that is frequently adopted in studies of complex adaptive systems and economy (Moore, 2006). According to Han et al. (2019), self-organization and co-evolution are just two of the interrelated complex properties that an entrepreneurial ecosystem exhibits, as well as non-linear interactions, (in)sensitivity to initial conditions, adaptation to the environment, and the emergence of successful actors.
In this Special Issue, we consider sustainable innovation ecosystems as complex adaptive systems, in which many autonomous and heterogeneous actors leverage their resources and capabilities and create new ones, by interacting with each other at multiple levels, to allow innovative solutions to new problems to emerge, in a very short time. Adopting the perspective and the methodological approaches of complexity could be advantageous in this field, not only to take into account the non-linear interactions among multiple diverse and independent agents belonging to the ecosystem, but also to capture the self-organizing emergent structures and properties at the collective level, and the interplay among the social, environmental, and economic dimensions of their evolution (Ponsiglione, 2021; Ponta, 2023).
The use of complexity science and the related methodologies, in the field of innovation management, is still very limited and, hence, it is not clear yet how studying sustainable innovation ecosystems through the lens of complexity science would produce benefits and limitations. In particular, there is a need to understand how the complexity theory and related methods can be applied in this field. Thus, also empirical analysis and case studies can be useful for a deep understanding of this topic. The best practices, possible implications, and impacts on policy making can be very relevant for government authorities and also for the scientific community.
Topics and Research Questions
This special issue aims to attract high-quality contributions that use these approaches and address the issue of complexity concerning this specific topic. Papers that adopt innovative theoretical and empirical methodologies are particularly appreciated as well as papers addressing the relationship between theory and practice.
We invite researchers aimed at investigating the following sub-topics
Manuscript submission information:
The timeline of this special issue is as follows:
Submission dates: September 1st, 2024 to August 31st, 2025.
Review process: On a rolling basis from September 2024 to December 2025.
Papers can be submitted here: https://www.editorialmanager.com/jik/default2.aspx and by selecting article type "VSI: Innovation Ecosystems"
Publication: This is a VSI; accepted papers will be published online immediately once accepted and will be included in the next available issue of the journal.
Before submitting a manuscript, please read carefully the Journal of Innovation & Knowledge Guide for authors.
In particular, authors should disclose in their manuscript the use of AI and AI-assisted technologies and a statement will appear in the published work. Declaring the use of these technologies supports transparency and trust between authors, readers, reviewers, editors, and contributors and facilitates compliance with the terms of use of the relevant tool or technology. Plagiarism in all its forms constitutes unethical behaviour and is unacceptable.
More information can be found at the following link:
https://www.sciencedirect.com/journal/journal-of-innovation-and-knowledge/publish/guide-for-authors
References:
Ancona, A., Cinelli, M., Ferraro, G., Iovanella, A. (2023). Network-based principles of entrepreneurial ecosystems: a case study of a start-up network. Small Business Economics, 61, 1497–1514.
Burnes, B. (2005). Complexity theories and organizational change. International Journal of Management Reviews, 7(2), 73-90.
Granstrand, O. and Holgersson, M. (2020). Innovation ecosystems: A conceptual review and a new definition. Technovation, 90-91, 102098.
Han, J., Ruan, Y., Wang, Y., Zhou, H. (2019). Toward a complex adaptive system: The case of the Zhongguancun entrepreneurship ecosystem. Journal of Business Research, 128, 537-550.
Isenberg, D.J. (2016). Applying the ecosystem metaphor to entrepreneurship: Uses and abuses. The Antitrust Bulletin, 61(4), 564-573.
Jackson, D.J. (2011). What is an innovation ecosystem? National Science Foundation, 1(2), 1-13.
Moore, J.F. (2006). Business ecosystems and the view from the firm. The Antitrust Bulletin, 51(1), 31-75.
Pham, Q.H. and Vu, K.P. (2022), "Digitalization in small and medium enterprise: a parsimonious model of digitalization of accounting information for sustainable innovation ecosystem value generation", Asia Pacific Journal of Innovation and Entrepreneurship, Vol. 16 No. 1, pp. 2-37. https://doi.org/10.1108/APJIE-02-2022-0013
Ponsiglione, C., Cannavacciuolo, L., Primario, S., Quinto, I., & Zollo, G. (2021). The ambiguity of natural language as resource for organizational design: A computational analysis. Journal of Business Research, 129, 654-665.
Ponta, L., Puliga, G., Lazzarotti, V., Manzini, R., & Cincotti, S. (2023). To copatent or not to copatent: An agent-based model for firms facing this dilemma. European Journal of Operational Research, 306(3), 1349-1363.
Spigel, B. (2017). The relational organization of entrepreneurial ecosystems. Entrepreneurship Theory and Practice, 41(1), 49-72.
Stam, E. (2015). Entrepreneurial ecosystems and regional policy: A sympathetic critique. European Planning Studies, 23(9), 1759-1769.
Stam, E. and Van de Ven, A.H. (2021). Entrepreneurial ecosystem elements. Small Business Economics, 56(2), 809-832.
Stubbs, W. and Cocklin, C. (2008),“An ecological modernist interpretation of sustainability: the case of interface INC”, Business Strategy and the Environment, Vol. 17 No. 8, pp. 512-523, doi: 10.1002/bse.544
Tan, F.T.C., Ondrus, J., Tan, B. and Oh, J. (2020). Digital transformation of business ecosystems: Evidence from the Korean pop industry, Information Systems Journal, 30(5), 866-898.
Tsujimoto, M., Kajikawa, Y., Tomita, J., Matsumoto, Y. (2018). A review of the ecosystem concept – Towards coherent ecosystem design, Technological Forecasting & Social Change, 136(July 2017), 49-58.
Van de Ven, A.H. (1986). Central problems in the management of innovation. Management Science, 32(5), 590-607.
Van de Ven, A.H. (1993). The development of an infrastructure for entrepreneurship. Journal of Business Venturing, 8(3), 211-230.
Zeng D, Hu J, Ouyang T. Managing Innovation Paradox in the Sustainable Innovation Ecosystem: A Case Study of Ambidextrous Capability in a Focal Firm. Sustainability. 2017; 9(11):2091. https://doi.org/10.3390/su9112091
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Background and Motivation
Artificial Intelligence (AI) stands at the forefront of disruptive technologies, driving transformative changes across the business world (Almansour, 2023). Sachs (2023) highlights a significant surge in market interest in AI, noting that investments could reach $100 billion in the United States and $200 billion globally by the end of 2025. As firms increasingly invest in AI-based technologies, recent studies further confirm AI’s positive influence on innovation management. Wael AL-Khatib (2023) and Khan et al. (2024) affirm that AI based tools has a positive influence on both exploitable and exploratory innovation. Indeed, the capacity of AI to quickly create new content is completely in line with the concept of exploratory innovation, which focuses on experimenting with new ideas, technologies, and markets to create disruptive advancements. On the other side, its ability to analyze data patterns and generate tailored solutions can support exploitable innovation, which emphasizes refining and optimizing existing processes, products, or services to maximize efficiency and profitability (Jansen et al., 2006). Furthermore, Xu et al. (2024) identify the quality of AI-generated content as a key factor in stimulating enterprise innovation behavior.
While AI adoption is undoubtedly accelerating innovation, sustained organizational success in this domain also depends on humans’ interaction dynamics and knowledge-related processes. Human interactions are essential for enhancing innovation, as effective interpersonal relationships positively influence the innovation process (Lee and Wu, 2010). Collaboration creates an environment where new ideas can emerge and be refined (Walsh et al., 2016), while teamwork and cooperation serve as key drivers of innovation (West and Hirst, 2005). Additionally, effective conflict management has been shown to positively impact innovation performance (Chen et al., 2012). Furthermore, trust plays a crucial role in encouraging innovative behaviors among employees and strengthening organization’s overall capacity for innovation (Lee, 2008).
Beyond human interactions, knowledge management processes also serve as a cornerstone of innovation (Costa and Monteiro, 2016; Idrees et al., 2023; Mubarak et al., 2025). Acquiring, creating, sharing, and applying knowledge enable organizations to engage in open innovation which leads to improved innovation performance (Laursen and Salter, 2006). Organizations that implement structured knowledge-sharing practices can accelerate the innovation process (Wang and Wang, 2012). Additionally, according to Soomro et al. (2024) team knowledge-sharing encourages team members to look for innovative solutions.
The interconnection between human interactions and knowledge management is also fundamental to driving innovation. In fact, human interactions serve as the foundation for effective knowledge exchange (He et al., 2009) and successful knowledge management (Jiarui et al., 2022), both of which are critical for enhancing innovation (Corvello et al., 2023).
Within this research framework, it is necessary to recognize that AI adoption in the workplace is also fundamentally transforming these two interconnected factors. On the one hand, AI exerts a significant influence on critical aspects of human interactions (Zimmerman et al., 2023; Fahad et al., 2024). On the other hand, AI is reshaping knowledge-related processes (Al Mansoori et al., 2021; Taherdoost and Madanchian, 2023; Fahad et al., 2024). A thorough understanding of how AI influences these factors is essential for organizations aiming to leverage AI’s capabilities while promoting innovation and continuous learning.
Despite the acknowledged importance of AI adoption, human interactions, and knowledge management in advancing innovation, a significant gap remains in the academic literature regarding the interconnections among these factors. While AI is widely acknowledged as a powerful enabler of innovation, its broader implications for human interactions and knowledge-related processes within organizations are still insufficiently explored.
Therefore, this special issue seeks to examine the interplay between AI adoption, human interactions, and knowledge-related processes to advance innovation within organizational contexts. The special issue will benefit scholars, practitioners, and policymakers. Academics in innovation management, AI, human interaction, and knowledge management will gain insights into the complex relationships between AI, human interactions and knowledge processes. Managers and executives will find practical guidance on leveraging AI to drive innovation and develop strategies for sustainable growth. Additionally, policymakers and organizational leaders will understand how AI can be integrated to optimize innovation processes and address its broader impact on the workforce and organizational culture.
Topics and Research Questions
The special issue aims at examining the impact of AI adoption on both human interactions and knowledge management processes for advancing innovation. To achieve this, the issue will focus on two primary objectives. First, it aims to explore the impact of AI on human relationships within organizations, specifically assessing its effects on key interpersonal dynamics such as teamwork, collaboration, trust, cooperation, conflict resolution, and coordination. As these social and relational factors are central for enhancing innovation, it is essential to investigate whether AI acts as an enabler or a disruptor of these processes. Second, the special issue will examine AI’s role in shaping knowledge-related processes within organizations, with particular emphasis on how AI affects knowledge acquisition, creation, transfer, sharing, retention, application, and evolution. The goal is to explore how AI can enhance or hinder these processes in a way that drives innovation. Moreover, it is essential to recognize that human interactions and knowledge-related processes are not isolated factors but are deeply interconnected, both playing a vital role in driving innovation. Therefore, examining AI’s impact on these factors may also lead to a deeper understanding of the nature of their interconnections.
We invite researchers to contribute to the following subtopics, including but not limited to:
AI and human interactions in innovation-driven workplaces
AI and knowledge management for continuous innovation
AI enhanced decision making and open innovation ecosystems
The interplay between AI, human interactions, and knowledge sharing
Measuring and evaluating AI’s long-term impact on human relationships and knowledge management for innovation
This special issue seeks to attract high-quality contributions that explore the complexity of the proposed research topic. Furthermore, we welcome a diverse range of submissions, including qualitative studies, empirical research, theoretical contributions, conceptual and methodological papers, as well as longitudinal, interdisciplinary, and case studies.
Submission deadline 30 de November de 2025 The research topic proposed in the special issue allows advancing knowledge regarding the interrelationship between Circular Economy (CE) and Open Innovation (OI), aiming to promote the green transition. The environmental emergency requires the transition to new models of sustainable development. Consequently, governments worldwide are taking action to develop green policies (i.e., The European Green Deal, the United Nations 2030 Agenda, etc.). Specifically, the UN organization has compiled a list of 17 Sustainable Development Goals, among which can be found to ensure sustainable production and consumption patterns. Underlying this goal is the concept of the CE, which is considered the economic approach to be embraced to reduce the pressure on natural systems.
For this reason, implementing CE principles supports the green transition. This subject particularly appeals to governments, practitioners, and academics, justifying an in-depth study of how organizations can effectively implement CE principles to accomplish a green transition. In this context, OI represents a viable approach to foster and speed up the implementation of circular initiatives. Specifically, the literature (elucidated in the following paragraphs) highlights how the ecosystem approach enabled by OI facilitates this process, thus deserving attention. For the reasons stated here and for relevance to the journal’s scope, the research topic related to the transition from Linear to CE through OI deserves an entire issue.
Submission deadline 31 de December de 2025 Global financial and governance systems are increasingly critical in achieving sustainable development. The United Nations Sustainable Development Goals (SDGs) highlight the interconnectedness of economic growth, social equity, and environmental stewardship, urging institutions and decision-makers to align their practices with broader societal objectives (United Nations, 2015; Ahmad et al., 2024). In parallel, Environmental, Social, and Governance (ESG) frameworks have gained traction among investors, businesses, and policymakers, recognizing that non-financial factors significantly influence long-term financial performance and social welfare (Kwilinski et al., 2025; Cai et al., 2022). This evolution underscores the importance of knowledge-sharing, innovation, and stakeholder collaboration in reimagining finance and governance for more equitable and sustainable outcomes (UNEP FI, 2022). Integrating SDGs and ESG objectives into financial decision-making, risk management, and regulatory frameworks can support resilient business models while fostering broader societal benefits (Delgado-Ceballos et al., 2023). This special issue explores how forward-thinking strategies and practices can transform traditional finance and governance, supporting the global transition toward sustainable and inclusive development.
Background and Motivation of the Special Issue
Historically, financial markets have prioritized short-term profitability, often overlooking long-term social and environmental consequences (Elkington, 1999). However, mounting evidence indicates that sustainable investing and stronger governance practices can drive financial performance and broader value creation (Lins et al., 2017). Many organizations now recognize the urgency of integrating SDGs into their strategic agendas, focusing on issues such as climate action (SDG 13), responsible consumption and production (SDG 12), and reduced inequalities (SDG 10), among others (Fallah Shayan et al., 2022). Simultaneously, ESG considerations have become integral to corporate disclosure requirements, emphasizing transparency, stakeholder engagement, and risk mitigation (Cai et al., 2022). Innovative digital technologies—such as blockchain, big data analytics, and artificial intelligence—create opportunities for new financial instruments (e.g., green bonds, carbon offsets) and governance models (e.g., decentralized autonomous organizations), helping entities meet ESG benchmarks and SDG targets more effectively (Umar et al., 2022; Kolk, 2021; UNEP FI, 2022). As the global community seeks mechanisms to address pressing challenges like climate change, biodiversity loss, and social inequality, integrating knowledge and innovation into financial and governance spheres is a critical priority (World Economic Forum, 2023).
The motivation for this Special Issue stems from the growing consensus that finance and governance systems must undergo transformative change to meet 21st-century challenges (Helfaya & Bui, 2025; United Nations, 2015). Scholars, practitioners, and policymakers are increasingly called upon to design innovative frameworks and methodologies that integrate SDG and ESG imperatives into financial decision-making, corporate reporting, and public policy. This evolution hinges on interdisciplinary collaborations that fuse technology, data science, organizational behavior, and policy studies (Fallah Shayan et al., 2022).
By providing a dedicated platform in the Journal of Innovation & Knowledge (JIK), we aim to foster research that advances finance and governance innovations, ultimately positioning sustainability at the forefront of global economic development. We hope that contributions to this Special Issue will serve as a blueprint for these transformative efforts.
Topics and Research Questions
We invite original research articles that provide novel insights and significant contributions at the nexus of finance, governance, knowledge, innovation, and sustainability. Possible topics of interest include but are not limited to:
Submission deadline 30 de April de 2026 