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Despite a rich extant literature, it is unclear what business models are. We assess three dominant conceptions of business models in the academic literature: as transactional structures, value extracting devices, and mechanisms for structuring the organization. To overcome the shortcomings of these approaches, we draw on theories of performativity, social typecasting, and managerial cognition. We propose an alternative conception of business models as performative representations that work in three ways: as narratives that convince, typifications that legitimate, and recipes that guide social action. Rather than actual features of firms, business models are representations that allow managers to articulate and instantiate the value of new technologies.

Reviews the latest management developments across the globe and pinpoints practical implications from cutting‐edge research and case studies.

This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context.

For commerical organizations to engage in strategic collaboration with universities is nothing new – especially in the more developed parts of the world – but the focus on desired outcomes has become more intense.

Provides strategic insights and practical thinking that have influenced some of the world's leading organizations.

The briefing saves busy executives and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy‐to digest format.

The innovation process demands an interaction between environment agents, knowledge generators and policies of incentive for innovation and not only development by companies. Universities have gradually become the core of the knowledge production system and, therefore, their role regarding innovation has become more important and diversified. This study is aimed at identifying the mechanisms of university–industry (U–I) collaboration, as well as the operationalization steps of the U–I collaboration process.

This study is aimed at identifying, based on a systematic literature review, the mechanisms of university–industry (U–I) collaboration, as well as the operationalization steps of the U–I collaboration process.

The analysis of the 72 selected articles enabled identifying 15 mechanisms of U–I collaboration, proposing a new classification for such mechanisms and developing a framework presenting the operationalization steps of the interaction process.

In this paper, the authors screened nearly 1,500 papers and analyzed in detail 86 papers addressing U–I collaboration, mechanisms of U–I collaboration and operationalization steps of the U–I collaboration process. This paper provides a new classification for such mechanisms and developing a framework presenting the operationalization steps of the interaction process. This research contributes to both theory and practice by highlighting managerial aspects and stimulating academic research on such timely topic.

Joan undertook the ground-breaking project originally reported in the 1958 pamphlet, Management and Technology, not at one of Britain's great universities, but at the unfashionable address of the South East Essex Technical College (then in the county of Essex but now part of the London Borough of Barking and Dagenham). The Human Relations Research Unit had been set up at the college, which is now part of the University of East London, in 1953 with support from a number of agencies including funding ultimately derived from the Marshall Plan. Its express purpose was to enhance the performance of industry and commerce through the application of social science. Those readers familiar with the area will know that, at the time, it was economically and culturally dominated by the Ford assembly plant in nearby Dagenham, but it was also home to a diverse range of small- and medium-sized industrial workshops that were typical of the pre-war Greater London economy (Woodward, 1965; Massey & Meegan, 1982). It was into this diverse industrial milieu that Joan and her research team ventured (Fig. 1), completing their main study in 1958.

What makes firms innovate their business models? Why do they engage in innovating how they create, deliver, and capture value? And how does such innovation translate into innovation performance? Despite the importance of business model innovation for achieving competitive advantage, existing evidence seems to be confined to firm-level antecedents and pays little attention to the impact of industry structure. This study investigates how different stages of an industry’s life cycle and levels of industry competition affect firms’ business model innovation, and how such innovation translates into innovation performance. Based on a cross-industry sample of 1,242 Austrian firms, we introduce a unique measure for the degree of innovation in a firm’s business model. The results indicate that the degree of business model innovation is highest toward the beginning of an industry life cycle, that is, in the emergent stage. Competitive industry pressures turn out to be negatively related to the degree of business model innovation. Moreover, we find that the degree of a firm’s business model innovation, conditional on it having introduced a new product or process recently, positively influences innovation performance. Our findings contribute to the ongoing dialog on the role of industry structure in business model innovation, and provide implications for the management of business model innovation.

The purpose of this paper is to develop a conceptual framework identifying and differentiating how knowledge and technology transfer organizations (KTTOs) create value from how they capture and transfer value.

The argument of the paper is developed in two steps. First, the knowledge and technology transfer process is conceptualized as a value chain. Second, the internal KTTO's value chain perspective is extended by integrating the knowledge and technology transfer value chain into a business model conceptual perspective in order to emphasize the value captured by the clients of KTTOs. Then, the authors examine how KTTO managers could describe, benchmark and improve their business models by altering or reinforcing how they are positioned with respect to the interdependent elements of their business model. Finally, the elements of the conceptual framework are used to derive emblematic types of business models and provide exemplary cases for each emblematic case.

Looking at KTTO management under the lenses of business models invites KTTO managers to look at knowledge and technology transfer as a whole. It suggests to managers to invest resources not only in the improvement of these elements where their organizations are strong, but also in these elements that constitute their weakest elements in the business model. Failure to improve the weakest elements of the business model might compromise the overall knowledge and technology transfer capabilities and performances of KTTOs.

The conceptual framework developed in this paper is intended as a starting point to explore how KTTO managers may be more effective in creating and capturing value from knowledge transfer.

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.