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The purpose of this paper is to examine how the instructions of the lean startup methodology influence entrepreneurs. It explores what happens when such instructions are enacted by entrepreneurs in the context of a “prescriptive accelerator”. The goal is to shine a light onto the mechanisms by which these instructions are acquired and then utilised by entrepreneurs and to outline in some detail the implications of adhering to the lean startup methodology.

This paper employs an in-depth phenomenological semi-structured interview design. Two rounds of interviews were conducted, one at the beginning and one at the end of the programme with the CEOs and founders of 11 entrepreneurial ventures, totalling 22 interviews. The analysis of the interviews resulted in five second-order themes that are discussed in light of the processes of experiential and vicarious learning.

The findings suggest that through two distinct modes of vicarious and experiential learning, the instructions of the lean startup methodology are acquired, internalised and consequently put into practice by entrepreneurs. The paper further highlights the modifications to entrepreneurs’ governing variables and action strategies, as well as the resulting consequences of these modifications. This provides insights into possible outcomes of following the lean startup methodology in the context of a prescriptive accelerator where a strong focus on adhering to a systematic entrepreneurial methodology is a characteristic feature.

This paper contributes to our understanding of the under-studied and novel phenomena of the lean startup methodology and prescriptive accelerators. It complements the prevailing understanding of entrepreneurial learning as being largely experiential by accounting for the vicarious learning processes that occur in pedagogical settings such as prescriptive accelerators. It therefore shows that prescriptive accelerators provide unique learning situations where the combination of vicarious and experiential learning impacts the business development activities. Further, it provides a model of entrepreneurs’ theory of action as the outcome of the interactions between the lean startup methodology and the two modes of vicarious and experiential learning.

Given the growing recognition that learning plays a crucial role in entrepreneurship, this paper aims to systematically review the literature on entrepreneurial learning (EL), take account of its progress and analyze the unique characteristics of EL as a concept.

This paper uses a systematic approach to reviewing the literature on EL and critically assess the EL concept through the criteria of resonance, attributes (involving consistency, fecundity and differentiation), domain and causal utility.

A synthesis and assessment of extant literature reveals that a key challenge is the clear articulation of EL as a concept. This paper takes the first steps toward the specification of EL through a discussion of its unique properties. In this respect, the paper proposes the understanding of EL as an undertaking of entrepreneurial (i.e. proactive, exploratory and collaborative) learning behaviors (a crucial component of the EL concept) and recommends the context of new venture creation as an appropriate domain for the study of EL.

This paper paves the way toward a more robust specification of EL as a concept.

This systematic literature review initiates a discussion about how EL literature can find convergence on key issues, thus helping the field move forward. It does so by articulating central attributes of the EL concept.

The purpose of this study is to answer the following questions. What kind of entrepreneurial identities do students have that motivate them to choose either of the entrepreneurship course and university-based incubator? How do students involve in the entrepreneurship ecosystem at university based on their entrepreneurial identity?

For this study, the author began to gather information using previous knowledge and any aspect of a work, namely, from the literature review to represent interpretive syntheses of the meaning-making literature review addressing the research question.

This study suggests what happens to entrepreneur students from academia and the reason that they end up in one of the two aforementioned paradigms. This paper aims to underpin the issue of how various entrepreneurial identities of students cause substantial contributing factors in forming such entrepreneurial activities at university and throughout the entire innovation ecosystem.

Almost all of the content of the entrepreneurship education (EE) courses and incubator training is oriented towards consensual entrepreneurship methods, in accordance with entrepreneurship education. Although the core contents of the EE courses and university-based incubators’ training are the same, the outcomes are quite different.

This study considers the students’ entrepreneurial identities with a focus on their point of view that led them to end up in one of the two common entrepreneurship resources at universities: the EE course and entrepreneurial activities related to university-based incubators.

The purpose of this paper is to explore the efficacy of Osterwalder and Pigneur’s Business Model Canvas for 271 teams competing in a venture pitch competition during a cleantech accelerator program.

It uses competition results and data from a website used by participants to track their hypothesis construction and testing.

Teams that used the elements of customer segment, value proposition, key activities or key partnerships performed significantly better in the competition. Yet of all nine elements in the Canvas, only customer segmentation showed a significant linear bivariate correlation between the number of validated hypotheses and performance. Finally, teams that heavily used a triumvirate of elements composed of customer segmentation, value proposition and channel performed two times better than teams that barely used these elements.

The findings of this exploratory analysis imply that the components of a business model that explain and predict early success might be different than those for a more mature firm.

These results suggest that practitioners could improve early performance by narrowing their scrutiny to just the triumvirate, because the Canvas may contain components that are unhelpful for entrepreneurs as they form a business model for their nascent venture.

This paper fills a gap by empirically testing the prediction that application of the Business Model Canvas drives venture success and providing a revise definition for a business model that is more appropriate for start-up ventures.

Although business incubators are widely used support mechanisms for innovative entrepreneurship, the literature still lacks theoretically based explanations of how the incubation process creates value for stakeholders. This study aims to address this gap by developing a conceptual model, and related research propositions, that explains how the entrepreneurial logic in use by an incubator influences the incubation process (selection criteria and service offering) and performance.

Integrating the effectuation and entrepreneurial opportunities literature, which shares common conceptualizations about how the predictability of the future affects entrepreneurial action, the authors posit two archetypes of entrepreneurial logic that are associated with different incubation processes (causal or effectual) and two archetypes of opportunity attributes (discovery- or creation-based) that affect the incubation process needed to support their development.

Juxtaposing these archetypes, the proposed cross-level conceptual model specifies four levels of fit (ideal, surplus, deficit and mismatch) between the incubation process and the opportunity attributes of individual ventures, which directly influence venture performance (high, moderate and low). In turn, an incubator's performance is largely shaped by the overall performance of ventures in its portfolio.

This paper responds to the call for theory-building that links the antecedents and outcomes of the incubation process across levels of analysis. In addition to developing a conceptual model and research agenda at the intersection of entrepreneurship and business incubation, the proposed model also has implications for incubator directors deciding how to allocate limited resources, and for public/private sector administrators interested in leveraging investment in business incubators.

A lot of literature has been generated showing the high unemployment rate in Africa and especially among the youth aged between 18 and 35 years. This glaring state of unemployment among the youth, including many educated graduates, has led them, in the course of time to despair, disillusionment, and consequent susceptibility to their involvement in anti-social behaviour including crime. For instance, the infamous radicalisation of the youth and great insecurity threats that come with this as currently being experienced in Libya, Mali, Nigeria, the Lake Chad Basin, Somalia, Sudan, South Sudan, and the Democratic Republic of Congo as advanced by Boko Haram, al-Shabaab, and al-Qaeda in the Islamic Maghreb and affiliates are all related to unemployment challenges. Additionally, the Arab Spring in North Africa experienced in 2010, as well as the xenophobic insurgences in South Africa, South Sudan, Nigeria, and in other countries across the continent, have all been attributed to youth unemployment and disillusionment. As a way of intervention, the African Union declared a decade of youth empowerment between 2008 and 2019 which set the tempo for countries, organisations, and agencies across the continent in coming up with mitigation measures. Motivated by this spirit of assisting the youth towards a mindset change to be job and wealth creators and not job-seekers, Mount Kenya University (MKU) established the Graduate Enterprise Academy (GEA) in 2013. This chapter showcases the double-pronged approach adopted by MKU, an ISO 9001:2015 certified university in East Africa, towards promotion of entrepreneurial mindset among the youth in Africa through the GEA. More specifically, in collaboration with leading indigenous institutions and agencies in Kenya, the GEA was established in MKU in 2013 with a clear mandate of promoting youth-driven enterprises throughout the country and across the continent. More recently, since 2017, in collaboration with the Kenya National Commission for UNESCO, Leuphana University of Germany, and other stakeholders, MKU has embraced the Students Training for Entrepreneurial Promotion (STEP). STEP has thus been rolled out by MKU as a co-curriculum activity for undergraduate students as well as for training youth outside universities at various counties in Kenya. The STEP and GEA initiatives at MKU are presented in this chapter as a case study in terms of their implementation, strengths, challenges, and recommendations for possible replication and up-scaling to cover the entire continent.

The creation of a new venture is at the heart of entrepreneurship and shares parallels with project-based organizing: embedded in an institutional context, founders have to assemble a team that works on specified tasks within a strict time constraint, while the new venture undergoes various transitions. The purpose of this paper is to explore parallels between both streams of research and an increasing projectification of entrepreneurship.

The study is based upon a case study of the Berlin start-up ecosystem including the analysis of interviews (n=52), secondary documents, and field observations.

The paper reveals that – shaped by their institutional context – patterns of project-like organizing have become pertinent to the new venture creation process. It identifies a set of facets from the entrepreneurial ecosystems – more specifically different types of organizational actors, their occupational backgrounds, and epistemic communities – that enable and constrain the process of new venture creation in a way that is typical for project-based organizing.

This study thus elaborates on how institutional settings enforce what has been called “projectification” in the process of new venture creation and discuss implications for start-up ecosystems.

The purpose of this paper is to explore trends in entrepreneurship spaces developed by universities to support entrepreneurship education. It identifies characteristics that make a space conducive to innovation and explains whether current spaces adequately conform to those characteristics. More generally, this paper seeks to clarify what is being built, for which purposes and with what results.

Given the novelty of this research, the paper uses a multiple-method approach to allow for an iterative examination between theory and data. Multiple data and methods were used, including an action research method, a systematic survey of 57 entrepreneurship spaces at US universities and a thematic and content analyses of interviews carried out with individuals directly involved in the functioning of such spaces.

The paper presents a prescriptive model aimed at guiding the practitioner in the design of an entrepreneurship space. It identifies five types of entrepreneurship spaces that differentially support entrepreneurial activities and rely on different characteristics. These characteristics are centrally important for innovation and entrepreneurship spaces.

There are a number of practical implications from the work. It identifies key challenges in the design of entrepreneurship spaces and shows which questions to consider in the decision-making process.

The paper advances research on entrepreneurship spaces, an important yet poorly understood phenomenon. It reviews and introduces the literature on how space can support innovation, entrepreneurship education and entrepreneurial “spirit’” and proposes a typology of entrepreneurship spaces, providing a path toward more robust and comprehensive theory building.

The rise of the digital economy has led to a focus on how to manage big data and business intelligence for entrepreneurial purposes. The aim of this chapter is to discuss how to plan for open innovative ecosystems that harness the potential of new data analytics techniques in order to progress society. This means concentrating on the increasingly complex world of data analytics in order to derive information about potential entrepreneurial opportunities. The role of knowledge management in influencing an open innovation ecosystem predicated on big data and computing acumen is stated. This helps to understand how the future of the global economy relies on an open data policy that encourages the sharing and dissemination of information. Implications for managers are also suggested that emphasize the role of innovation ecosystems, data and government.