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The purpose of this study is to explore the role of spinoff entrepreneurs in the post-bubble Japan and ultimately to facilitate policy reforms that benefit entrepreneurs most in need of support.

This study adopts a survey of Japanese entrepreneurs from 2003 to 2013. Exploiting the survey questions, the authors separate spinoff startups from the non-spinoff startups. Using this data set, this study first performs a logistic regression, followed by a chi-squared independence test between spinoff startups and firm performance.

This study finds that while both human and social capital predict the probability of a firm’s positive performance, industry experience was the strongest predictor for the probability of performance.

As Garvin (1983) stated, most research on spinoffs are limited to both industry type and location. The theoretical contribution of this study is to broaden the applicability of current entrepreneurship theories by considering industries beyond technological startups. The practical value of this study is to begin evaluating policies and their interaction effect with cultural context.

By using the lens of effectuation and causation, this paper aims at exploring how the team is formed in high-tech academic spinoffs, by looking specifically at decisional heuristics in an academic context. Indeed, the team composition is a critical issue for the subsequent growth of the academic new venture: on the one hand, the scientific-centred knowledge of the academic entrepreneurs is one of the main elements that lay the foundation for the new venture; on the other hand, it has been widely recognized that the lack of market-related knowledge and experience often has detrimental effects on performance. Decisive is then to explore how team decisions pertaining to the team formation process are taken.

A qualitative methodology based on multiple case studies is adopted under an abductive approach.

Results shed light on how decisions pertaining to team formation are taken by academic entrepreneurs and with what effects on team composition, a fundamental element to foster the growth of academic new ventures. Specifically, this study derives some propositions about the adoption of effectuation and causation in the team formation process, their occurrence and sequence in the light of the scientific context in which academic new ventures spin out and the effects on the team composition.

This study contributes to the debate on academic entrepreneurs’ decisional heuristic and the use of effectuation or causation in the early stages of an academic new venture, by focusing on the team formation process. This study specifically considers three temporal micro-phases – the selection of founders before inception, the appointment of top management teams, and the integration of early employees after the inception – and whether the academic context influences the decisional heuristics. Managerial implications are also derived.

This paper aims to propose an integrated methodology for evaluating academic spin-offs (ASOs) for supporting both the development phase and performance evaluation. The ASOs have peculiar characteristics compared to other start-up companies and the debate on their evaluation is still open.

The proposed methodology, adopting a lean approach, faces the typical problems that characterize the growth of an ASO: the excessive attention to the technological aspects with respect to the commercial and managerial ones; and the need for evaluation systems that try to evaluate all risk areas and to highlight any misalignment. The methodology was built also starting from the results of an Erasmus + research project, co-funded by the European Commission, called spin-off lean acceleration.

The methodology proposes to monitor the main risk areas (market, technological, implementation, governance and financial). For each of these areas, at first, a framework and a checklist are proposed for supporting the qualitative assessment of the potential of each areas. In the second part, a set of metrics for monitoring the performances and to understand if the spinoff is developing in the right direction is proposed. Moreover, the methodology was applied to the spin-offs at the University of Calabria (Italy), and the paper reports the first results obtained.

A new canvas model (lean acceleration canvas), more specific and suited to the context of ASOs, was developed and tested. A lean approach has been adopted also for understanding the weakness of traditional methods. The proposed methodology could be used by the technology transfer offices in their institutional activity of supporting ASOs.

The purpose of this paper is to discuss the implication of Japanese government venture capital (VC) policies for future research and to provide basis for policymakers and practitioners.

This is an academic literature review of available peer-reviewed publications on government VC policies. This paper discusses and analyses the current state and issues of the Japanese government VC policies regarding three research questions: What do Japanese government VCs do? Do they contribute to their portfolios? and Do they contribute to the development of VC market?

There are mainly two findings in this paper: It is effective to establish a complementary relationship with private VCs for Japanese government VCs to contribute to their portfolios; Japanese government should simultaneously continue to make and review policies for the VC market, the stock market, the entrepreneur sector and the environment surrounding them by its strategic long-term commitment to contribute to the development of VC market and new technology-based firms in Japan.

As there are only a few studies on recently strengthened Japanese government VC policies, this paper provides an in-depth discussion on these Japanese VC policies, which can be used for future research and as a valuable resource for policymakers and practitioners.

Focusing on the adoption of Total Quality Management (TQM) principles in universities, this research paper explores how the “soft” dimensions of TQM trigger its “hard” dimensions considering them at the individual (micro-) and the university (meso-), and eventually at cluster (system-), levels.

Adopting a qualitative approach, this study presents an in-depth, longitudinal case study of University of Siena, one of the oldest Italian universities, that has been at the core of the research-based cluster on vaccines, today converged in the Tuscan Life Science Cluster. In particular, data were collected between 2018 and February 2022 and consists of archival data (press articles, websites, books), nine interviews to key informants, multiyear experience of the Life Sciences sector by two of the authors and other material put at disposal by university offices, and emails. Data analysis relied on a timeline, a coding procedure that considered three levels of analysis (individual, organization and cluster). Finally, the authors looked at the “how” and “why” the emerged themes have contributed to academic excellence.

This paper unveils how “soft” and “hard” sides of TQM are blended across multiple levels for reaching academic excellence. The grounded model emerged enlightens the importance of an individual “soft” dimension, academic passion (composed by its three subdimensions of individual research, teaching and entrepreneurial passion) and also sheds light on the organizational “soft” and “hard” sides that the university has been able to design for encouraging research, teaching and third mission quality. Academic excellence has been possible thanks to the capitalization of the individual and organizational “soft” sides into real outcomes as represented by the organizational and individual “hard” sides.

The paper suggests the importance of TQM principles applied at universities' level, providing an in-depth description of “soft” and “hard” sides dimensions of TQM and their impact on all the three pillars of academic excellence. The study findings suggest implications for managers and professionals in the higher education domain as well as for policymakers emphasizing the importance of supporting the individual and organizational soft sides of TQM. The authors provide practical implications recommending universities to consider not only the organizational dimensions but also individual ones when pursuing higher education excellence. In particular, individual passion plays a crucial role and universities need to identify ways of nurturing it. The authors also recommend policymakers to think about new ways to sustain universities as crucial actors in boosting a cluster development, as well as to consider higher education institutions, especially in more rural areas, as a privileged player not only capable of nurturing academic excellence but also able of creating an internationally renowned cluster.

TQM principles have been intensively analysed from an industrial perspective focusing on manufacturing and services, while this paper focuses on TQM in universities, presenting a grounded model that blends the individual and organizational “soft” and “hard” sides.

This research aims to shed new lights on the most shared constructs developed on Innovation Ecosystems, Entrepreneurial Ecosystems and Technology Transfer Ecosystem proposing an additional stand-alone ecosystem.

This research is built upon a qual-quantitative analysis of an empirical case. The latter analysis is performed through a single case study methodology on the San Giovanni Hub of the Federico II University of Naples.

Evidences show how a technological hub orchestrates three main ecosystems for the knowledge exploitation: the technology transfer ecosystem, devoted to gather knowledge form universities' labs towards industries; the innovation ecosystem, able to manage the exploration and exploitation of new knowledge and techniques; the entrepreneurial ecosystem, that supports startup/spinoff creation process.

Limitations mainly concern the fact that it is centred on just one case study.

Practical implications imply new opportunities of collaboration involving different stakeholders as university administrators, researchers, businesses and policymakers, creating a supportive environment for innovation.

The research offers a new vision about the role of Universities as creators and enablers of ecosystems pursuing diverse value propositions. The Academic Innovation Ecosystem is a new conceptualization of this role played by a university, and it can convey innovation and entrepreneurial attitude within its ecosystem leveraging on the transfer of university knowledge and technology.

The purpose of this paper is to analyze this phenomenon and identify its determinants using data from Brazilian higher education institutions.

Based on a data set comprehending 2,230 university students from 70 different institutions across the country, the authors develop five Probit models to assess impacts related to individual traits and systemic conditions on five dependent dimensions: entrepreneurial activity, potential entrepreneurs, high-impact entrepreneurship, serial entrepreneurship and innovation-driven entrepreneurship.

The lack of significance in many of the variables included in estimations suggests that student entrepreneurship seems to be a rather random phenomenon in Brazil.

Findings pose challenges for student entrepreneurship, as targets for intervention are not clear.

Over the past decades, universities have been receiving an increasing demand to go beyond their role of producing science and technology to explore its knowledge potential to produce novel commercial applications. However, while there is a growing interest in ways to foster scientific academic entrepreneurship, universities also serve as a positive environment for student entrepreneurship training, knowledge sharing, testing ideas and learning. So far, the importance of student entrepreneurship has received far less attention than it likely deserves.

Smart industry initiatives focus on intelligent and interconnected cyber-physical systems. These initiatives develop complex technical architectures that integrate heterogenous technologies, causing significant organizational complexity. Tapping into the digital capabilities of distant partners while capturing profit from such innovation is demanding. Furthermore, firms often need to establish and orchestrate inter-organizational collaborations without prior relations or established trust. As a result, smart industry initiatives bring together disparate organizational forms and institutional environments, distinctive knowledge bases, and geographically dispersed organizations. We conceptualize this organizational capability as ‘distant capabilities integration’. This research explores the governance mechanisms that support such integration and their relation to value capture. We analyse 11 IoT case studies organized in three categories (process, product and technologies) of smart industry initiatives. Building on existing literature, we consider different ways to describe distance, including knowledge heterogeneity and organizational, geographical, institutional, cultural and cognitive distance. Finally, we describe the governance mode appropriate for upstream (developing foundational technologies) and downstream (leveraging existing distant technologies) smart industry initiatives.