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The purpose of this paper is to examine how entrepreneurship culture affects start-up and venture capital co-evolution during the early evolution of an entrepreneurial ecosystem (EE) and its ability to foster the emergence of ambitious entrepreneurship as an outcome of its activity. Unlike studies that capture entrepreneurship culture at the national level, this study focusses specifically on the culture of venture capital-financed entrepreneurship and understanding its implications to the development of venture capital markets and successful firm-level outcomes within ecosystems.

Relying on EE and organisational imprinting theory, this study specifies characteristics of venture capital-financed entrepreneurship of Silicon Valley to illustrate the American way of building start-ups and examine whether they have as imprints affected to the entrepreneurship culture and start-up and venture capital co-evolution in Finland during the early evolution of its EE between 1980 and 1997.

The results illustrate venture capital-financed entrepreneurship culture as a specific example of entrepreneurship culture beneath the national level that can vary across geographies like the findings concerning Finland demonstrate. The findings show that this specific culture matters through having an impact on the structural evolution and performance of EEs and on the ways how they deliver or fail to deliver benefits to entrepreneurs.

The results show that venture capital-financed entrepreneurship and the emergence of success stories as outcomes of start-up and venture capital co-evolution within an EE are connected to a specific type of entrepreneurship culture. This paper also contributes to the literature by connecting the fundamentals of organisational imprinting to EE research.

This study aims to answer the question of how business models (BMs) maintain stability while coping with environmental uncertainties. This study proposes a dynamic co-evolution of knowledge management and business model transformation based on a comparative analysis of the focal firms’ BMs and their main partners in two e-commerce ecosystems in China.

The open data of listed companies regarding the introduction of emerging topics on the transformation tendency of BMs in the post-COVID-19 business world is qualitatively analysed. The theoretical foundation is based on a critical review of the literature.

Three aspects of the co-evolution between knowledge management and business model transformation are introduced. These three aspects are as follows: knowledge integration helps with multi-system business integration and decision-making collaborations; knowledge sharing helps to enhance cognitive ability and network value based on businesses; and the creation of new knowledge helps enrich the knowledge base and promote the transformation of BMs.

Solely attributing a firm’s ability to cope with environmental uncertainties to its business model weakens the importance of its knowledge management. This study argues that the co-evolution between knowledge management and business model transformation also plays a key role in a firm’s response to issues post-COVID-19.

This study calls for the development of a normative theory of co-evolution between knowledge management and business model transformation, implying uncharted territories of knowledge management based on interaction with business model designs in e-business ecosystems.

The purpose of this paper is to elucidate the dynamic interactions and co‐evolution of institutions with the technology and organization fields in emerging industry development. Insights and inspirations from comparison of the triangle relationship among government, market and local community in different institutional contexts could contribute to possible institutional innovation in the context of large‐scale institutional transition. In this way, this paper is expected to offer insights to the development of emerging industries in China.

The paper reviews the focal literature focusing on institutional change and the co‐evolution of institution, industry and technology. A multi‐level conceptual framework is put forward to explain the mechanism for the co‐evolution of technology, organization and institution. A multi‐case comparison method was applied to compare and disclose the process of co‐evolution of institutions, and the technology and organizational fields, as well as varied paths of industry development in different institutional contexts.

Emerging industry development in China is still presenting the character of path dependence to a great extent under traditional institutional arrangement, while the power and possible contribution from broader actors in the local community have been ignored. Driving force for a more innovative institutional transition towards emerging industry development should consider decentralized institutional arrangement and actions at local community instead of “command and control” from central planning.

First, the comparison of wind energy industry development in three countries creates possibilities for further analysis and reference for China's emerging industry. Second, the illustration of the triangle relationship among government, market and local community in different countries helps policy makers in China reconsider and redesign an effective institutional framework for balancing the powers among indigenous community, local government and market. Institutional alignment should be listed as an important consideration during the process of the policy design of such an effective institutional framework.

The paper presents a model to understand the dynamic co‐evolution of the institution, technology and organizational fields. It confirms the role of institution in promoting emerging industry development. Particularly, it offers inspirations for the development of emerging industries in nations facing large‐scale institutional transition.

This paper aims to contribute to understanding of strategy development by reporting a detailed case study of one pharmaceutical company over an 11‐year period using a framework for classifying strategic actions developed from a broader study of strategic behaviour in the industry.

The paper utilises a longitudinal text analysis using published documentary sources to explore the strategic actions and grand strategies realised by Bioglan during 1992‐2002.

The findings develop concepts from the economics, ecology and strategy literature in order to highlight that, rather than strategy research focusing on “with whom and how do firms compete?” the emphasis should be on “with whom and how do firms co‐evolve?”

The paper only explored the realised strategies of one firm during an 11‐year period using only published documentary sources.

Previous research does not appear to have explored the evolution and co‐evolution of a firm's strategic actions prior to its death, a gap that this paper aims to help to fill.

This paper seeks to understand how software systems and organisations co‐evolve in practice during an IS engagement. Seeks also to argue that complex adaptive system theory (CAS) provides an excellent lens to study the motor of co‐evolution due to its ability to frame the strategies and reinforcement models of actors and to illustrate this by recounting four narratives of the interaction, selection and adaptation of actors arising from a longitudinal case study of an IS engagement. Then sets out to consider how the complexity of the engagement emerges from the interrelationship of these narratives and how the adaptive behaviour of the various actors is both a response to and a driver of co‐evolution within the engagement.

An interpretive case study was undertaken to examine the implementation of a novel academic scheduling and resource allocation system at a research‐intensive Australian university. The research was conducted over ten months, employing ethnographic methods and semi‐structured interviews. This analysis is conducted within the theoretical framework of CAS.

By analysing this case study it is demonstrated how CAS can help designers and managers of IS engagements conceptualise the attendant complexities that they encounter. It is also demonstrated how complexity within IS engagements emerges through the interactions and goal‐seeking behaviour of actors employing a variety of context‐bound strategies within neighbourhoods, and how the adaptive behaviour of the various actors is both a response to and a driver of co‐evolution within the engagement.

This work builds on Organization Science, Vol. 10 Nos 3 and 5, by applying CAS theory to organisational and IS research on co‐evolution, where the findings are grounded in a longitudinal case study and not computational models.

The purpose of this study is to explore the conceptualisation of co-evolution using a corporate history research approach. While the application of the co-evolutionary perspective to the organisational-environmental relationships has uncovered significant evidences, little is understood about how the co-evolutionary process occurs over time between organisations and their institutional environment.

A co-evolutionary corporate history approach in used, as the authors investigated Sainsbury’s historical trajectory, exploring the role specific family members played in the evolution of the firm and the co-evolution of Sainsbury’s with its environment. This research design framework encompasses longitudinal archival analysis which incorporates both external and internal engagement which fostered Sainsbury’s joint evolution.

The findings from this study clearly suggest that certain organisations can and do co-evolve with their environment. However, organisations need to build legitimate cases for co-evolution to occur. In addition, they need to acquire certain resources that can be used to stimulate changes within their institutional environment.

Through a corporate history archival analysis, this study presents a UK company’s evolutionary narrative. The authors contribute to the growing literature on co-evolution in management studies by presenting a detailed historical narrative and interpretation of Sainsbury’s evolution at different time periods.

The main purpose of this research is to construct a generalized set of innovation processes that occur at the ecosystem level based on the academic research. The study analyzes the cultural and creativity-driven over-the-top (OTT) platform that encompasses diverse network of ecosystem members by utilizing the four cooperation practices.

This study begins with the literature review that discusses various topics related to ecosystem (e.g. service innovation, innovative ecosystem). Then, this study introduces a new conceptual framework that describes how cooperations occur in the ecosystem. Finally, a qualitative and explorative case study of the OTT platforms in the global context is conducted.

The application of the framework reveals how co-innovative business ecosystems demonstrate co-evolution through different structures and directions. An ecosystem can evolve by incorporating other industries (i.e. horizontal growth or broadening strategy) to deepen and broaden the industry integration.

As an explorative approach that opens the discussion on how co-innovation and co-evolution occur at the ecosystem level, particularly in the culture and creativity-driven industry, the value of this research extends to other similar industries where diverse actors such as technology firms, Internet firms, direct consumers, government and even the society impact the type of product and service and shape the evolution of the entire ecosystem.

The purpose of this paper is to juxtapose chaos theory with organizational learning theory to examine whether public organizations co-evolve into a new order or rather institutionalize newly gained knowledge in times of a highly complex public health crisis.

The research design utilizes the results from a survey administered to 200 emergency management and public health officials in the Dallas–Fort Worth metroplex.

The findings of this paper suggest that public entities were more likely to represent organizational learning through the coordination of professionals, access to quality information, and participation in daily communication. Leadership was associated with the dissemination of knowledge through the system rather than the development of new standard operating procedures (as suggested by chaos theory and co-evolution).

There are limitations to this study given the purposive sample of emergency management and public health officials employed in the Dallas–Fort Worth metroplex.

The authors find that public organizations that learn how to respond to unprecedented events through reliance on structure, leadership, and culture connect decision makers to credible information resulting in organizational learning.

As a result, public administrators need to focus and rely on their organization’s capacity to receive and retain information in a crisis.

This research contributes to our understanding of organizational learning in public organizations under highly complex public health situations finding decisions makers rely on both organizational structure and culture to support the flow of credible information.

The purpose of this paper is to: first, explain why a new model of the provision of welfare services to citizens arises from the digital society; second explore some core elements of the competition between the new model of the provision of welfare services and the classic ideal model of the professionals’ provision of welfare services; third, suggest why it is most likely that the two models of the provision of services are combined into a symbiotic co-evolution scenario; and fourth, examine why and how this symbiotic co-evolution scenario results in new participatory spaces for the main actors associated with the provision of welfare services.

The review of the literature examines how the new model for the provision of welfare services facilitated by big data challenges the traditional professional model for the provision of welfare services. The authors use the Danish case to illustrate a number of themes related to this looking at the hospital sector as an example.

The proposition is that a symbiotic co-evolution scenario will emerge. A mix of the classic ideal model and practice of the service professionals’ provision of services and the digital society’s model of the provision of services is the most likely scenario in the years to come. Furthermore, Data-driven management (DDM) as an integrated key element in a symbiotic co-evolution creates (opens up) participatory environments and spaces for the main actors and agents associated with the provision of welfare services to the citizens.

DDM’s impact on the provision of welfare services is still being realised and worked out, and more empirical research is needed before it is possible to point at the most likely scenario. However, according to the authors’ analytical framework, the institutional logics perspective, as presented in Section 2, a symbiotic co-evolution is most likely such that DDM will constitute a new logic within the provision of welfare services on the basis of which citizens as end-users could be provided with welfare services, but it is not likely that the new logic of DDM can displace the classic service professionals’ model of the provision of welfare services. Therefore, the new logic of DDM will be combined with and integrated into the existing logics within service provision, such as the Weberian bureaucracy, the Street-Level Bureaucracy, the New Public Governance and the Market. In spite of this, DDM can successfully be promoted by international management consulting firms, as a management concept which can remedy all the problems of the classic service professionals’ model of the provision of welfare services to citizens.

As a consequence of this, new relationships among professionals, data analytics, (middle) managers and citizens will be created regarding the provision of welfare services. Considering the new participatory environments and spaces and the new relationships among the classic service professionals, the data analytics, the (middle) managers and the citizens as end-users, the provision of welfare services may become an arena for negotiation of a new future model of the provision of welfare services to citizens.

The digital society has emerged from and developed further via: digitising, online information in almost real time, algorithms, data-informed decision-making processes, DDM and, ultimately, big data. The authors expect to see further digitising, more sophisticated algorithms and more big data. The authors suggest that a new model of the provision of welfare services to citizens will emerge from the development of the digital society. The authors also suggest that this new model will compete with the classic model of the provision of welfare services.

This study aims to show the inconsistency of the approach to the development of artificial intelligence as an independent tool (just one more tool that humans have developed); to describe the logic and concept of intelligence development regardless of its substrate: a human or a machine and to prove that the co-evolutionary hybridization of the machine and human intelligence will make it possible to reach a solution for the problems inaccessible to humanity so far (global climate monitoring and control, pandemics, etc.).

The global trend for artificial intelligence development (has been) was set during the Dartmouth seminar in 1956. The main goal was to define characteristics and research directions for artificial intelligence comparable to or even outperforming human intelligence. It should be able to acquire and create new knowledge in a highly uncertain dynamic environment (the real-world environment is an example) and apply that knowledge to solving practical problems. Nowadays artificial intelligence overperforms human abilities (playing games, speech recognition, search, art generation, extracting patterns from data etc.), but all these examples show that developers have come to a dead end. Narrow artificial intelligence has no connection to real human intelligence and even cannot be successfully used in many cases due to lack of transparency, explainability, computational ineffectiveness and many other limits. A strong artificial intelligence development model can be discussed unrelated to the substrate development of intelligence and its general properties that are inherent in this development. Only then it is to be clarified which part of cognitive functions can be transferred to an artificial medium. The process of development of intelligence (as mutual development (co-development) of human and artificial intelligence) should correspond to the property of increasing cognitive interoperability. The degree of cognitive interoperability is arranged in the same way as the method of measuring the strength of intelligence. It is stronger if knowledge can be transferred between different domains on a higher level of abstraction (Chollet, 2018).

The key factors behind the development of hybrid intelligence are interoperability – the ability to create a common ontology in the context of the problem being solved, plan and carry out joint activities; co-evolution – ensuring the growth of aggregate intellectual ability without the loss of subjectness by each of the substrates (human, machine). The rate of co-evolution depends on the rate of knowledge interchange and the manufacturability of this process.

Resistance to the idea of developing co-evolutionary hybrid intelligence can be expected from agents and developers who have bet on and invested in data-driven artificial intelligence and machine learning.

Revision of the approach to intellectualization through the development of hybrid intelligence methods will help bridge the gap between the developers of specific solutions and those who apply them. Co-evolution of machine intelligence and human intelligence will ensure seamless integration of smart new solutions into the global division of labor and social institutions.

The novelty of the research is connected with a new look at the principles of the development of machine and human intelligence in the co-evolution style. Also new is the statement that the development of intelligence should take place within the framework of integration of the following four domains: global challenges and tasks, concepts (general hybrid intelligence), technologies and products (specific applications that satisfy the needs of the market).