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This paper concerns the pivotal role that entrepreneurial universities can play in developing knowledge transfer and translation processes tailored to the cultural ecosystem.

The paper examines IncubiAmo Cultura, an innovative project that aims to mentor potential entrepreneurs and offer incubation and acceleration for cultural start-ups. The research methodology is based on action research and theory building from cases. An interventionist approach has been adopted, as one of the authors is also the founder of the ongoing project.

The in-depth collection of first-hand information on this pilot project has allowed the authors to formulate an analytical reflection and generate the design of a knowledge translation model driven by an entrepreneurial university that manifests itself through the creation of cultural and creative start-ups.

This article offers an original contribution to scholarship by offering a conceptual model for knowledge translation in cultural ecosystems. Common values (i.e. social, cultural, ethical and aesthetic ones) emerge as the basis on which to build open innovation and knowledge circulation.

For local policymakers, this study provides a clue to understand the need for both an integrated vision of knowledge translation and policies that aim to make an impact at the cultural ecosystem level. For entrepreneurial university governance, our investigation offers suggestions on the design and implementation of knowledge translation processes that fit with the specificity of the cultural ecosystem. For practitioners in the cultural field, a change of mindset is required to combine resources, energies and knowledge.

This work fills several gaps in the literature, as research generally concerns knowledge transfer from entrepreneurial universities to the market with regard to high-tech sectors. In contrast, the cultural sector is often neglected, despite its importance in the renewal and development of a territory.

Entrepreneurs are increasingly relying on artificial intelligence (AI) to assist in creating and scaling new ventures. Research on entrepreneurs’ use of AI algorithms (machine learning, natural language processing, artificial neural networks) has focused on the intra-organizational implications of AI. The purpose of this paper is to explore how entrepreneurs’ adoption of AI influences their inter- and meta-organizational relationships.

To address the limited understanding of the consequences of AI for communities of entrepreneurs, this paper develops a theory to explain how AI algorithms influence the micro (entrepreneur) and macro (system) dynamics of entrepreneurial ecosystems.

The theory’s main insight is that substituting AI for entrepreneurial ecosystem interactions influences not only entrepreneurs’ pursuit of opportunities but also the coordination of their local entrepreneurial ecosystems.

The theory contributes by drawing attention to the inter-organizational implications of AI, explaining how the decision to substitute AI for human interactions is a micro-foundation of ecosystems, and motivating a research agenda at the intersection of AI and entrepreneurial ecosystems.

Contemporary entrepreneurial ecosystem models and frameworks advocate that culture is a criterion for entrepreneurial intention and central to entrepreneurship discourse. However, there is limited research from resource-constrained economies, such as sub-Saharan Africa and at a sub-national level. Responding to calls for bottom-up perspectives hinged on local context and heterogeneous nature, this paper aims to provide an in-depth understanding from multiple perspectives about the effect that culture and entrepreneurial intention have on the entrepreneurship process and performance in Nelson Mandela Bay, South Africa.

A mixed-method research design followed a sequential independent process consisting of two phases. Phase 1 included the dissemination of questionnaires to economically active participants, and 300 responses were statistically analysed. In Phase 2, 15 semi-structured interviews with influential economic development agents were conducted.

The results indicated that social legitimacy towards entrepreneurship existed and self-employment was viewed positively. However, self-employment endeavours were mainly necessity driven, and the systemic low levels of innovation, poor business competitiveness and the inability to scale were highlighted. The findings indicated that individuals venturing into business had a culture of being dependant on the government, lacking a risk appetite, fearing failure, with disparate groups suffering from a poor legacy of entrepreneurship.

Despite research done on the role of culture and entrepreneurial intention on entrepreneurial ecosystems, there are few case studies showing their influence at a sub-national level. This study responds to calls for studies on a sub-national level by exploring the influence that culture and entrepreneurial intention have on entrepreneurship in a resource-constrained metropole.

The aim of the study is to explore the genesis of entrepreneurial ecosystems (EE) and highlight the role played by intellectual capital (IC) in that process. Specifically, the paper adopts the collective intelligence approach, and the study shows how human capital (HC), structural capital (SC) and relational capital (RC) interact to create an entrepreneurial ecosystem.

The paper adopts a single case study of an Italian EE. The data analysis is based upon the collection of different sources of data: semi-structured interviews with representatives of each actor of the ecosystem; email correspondence; meetings report; a 24-months period of direct observation. Given the novelty of the topic, the qualitative method seems well suited for studying innovation-based EE since the method offers rich data about a phenomenon in real-life context.

The case is a top-down, innovation-based EE in which all main components of the IC play a crucial role from the initial stage. Findings show how the constant interchange between IC components occurs at two different levels: the micro and the meso level. HC and RC play major roles at both levels, whilst SC only occurs at a meso level, representing the environment in which the whole ecosystem takes place. Additionally, the use case, a new intangible asset integrating all three components of IC, emerged as one of the main outcomes of this innovation-based EE.

The paper contributes to a rather unexplored topic in the existing literature on EE and IC, namely the formation process of EE and the role played by IC within that process. Additionally, through the application of the collective intelligence approach, the authors shed light on the need to manage IC at both micro and meso level in the creation of an EE.

Business Model Innovation is increasingly created by an ecosystem of related companies. This paper aims to investigate the transition of a manufacturing ecosystem toward electric vehicles from a business model perspective.

The authors investigate an automotive manufacturing ecosystem that is in transition toward electric and electrified vehicles, conducting semi-structured interviews with 46 informants from 27 ecosystem members.

The results reveal that the actions of several ecosystem members are driven by regulations relating to emissions. Novel requirements regarding components and complementary offers necessitate the entry of actors from other industries and the formation of new ecosystem members. While the newly emerged ecosystem has roots in an established ecosystem, it relies on new value offers. Further, the findings highlight the importance of ecosystem governance, while the necessary degree of change in the members' business models depends on their roles and positions in the ecosystem. Therefore, upstream suppliers of components must perform business model adaptation, whereas downstream providers must perform more complex business model innovation.

The paper is among the first to investigate an entire manufacturing ecosystem and analyze its transition toward electric vehicles and the implications for business model innovation.