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Lucerne University of Applied Sciences and Arts (LUASA) uses a holistic approach to foster entrepreneurial thinking and behavior of students and employees. Students and participants of the program shall be motivated to start own ventures during the study program or later in the life.

An entrepreneurial eco-system shall be built and a close partnership with regional key actors established.

A combination of Design Thinking and Lean Start-up is used for the entrepreneurial education. Fostering experimentation, early customer feedback, and interdisciplinary teamwork is essential. An enhanced Lean Canvas version is used for having a guideline to work on the important questions and documenting the learnings in the iterative process.

The program “Smart-up” of LUASA is running since three years as a pilot in two departments and is now rolled out to the entire University. Since program start more than 120 start-ups have been founded.

In all study programs, an “entrepreneurial track” is defined and students can earn credits while working on their own projects. Two interdisciplinary modules are offered. The proposed Smart-up Lean Canvas has been proven to be a key tool to develop innovative ideas in start-ups and in existing companies.

The combination of Design Thinking and Lean Start-up in a holistic setup proved that students can learn the methods and tools and are able to use them now or later as entre- or intrapreneurs.

Students are motivated to start their own business, meet role models and participating at different (networking) events.

The combination of Design Thinking and Lean Start-up with analytical approaches like Systems Thinking and Data Analytics supports the problem understanding and solution (product/service and business) design.

While Big Data offer marketing managers information that is high in volume, variety, velocity, and veracity (the 4Vs), these features wouldn’t necessarily improve their decision-making. Managers would still be vulnerable to confirmation bias, control illusions, communication problems, and confidence issues (the 4Cs). The authors argue that traditional remedies for such biases don’t go far enough and propose a lean start-up approach to data-based learning in marketing management. Specifically, they focus on the marketing analytics component of Big Data and how adaptations of the lean start-up methodology can be used in some combination with such analytics to help marketing managers improve their decision-making and innovation process. Beyond the often discussed technical obstacles and operational costs associated with handling Big Data, this chapter contributes by analyzing the various learning and decision-making problems that can emerge once the 4Vs of Big Data have materialized.

The emergence of the lean start-up movement has cast doubt and skepticism among entrepreneurship educators and practitioners regarding the usefulness of writing a formal business plan for training the next generation of entrepreneurs. In one camp, there is a group of entrepreneurship education professionals who continue to advocate for the usefulness and necessity for teaching students these basic business plan development skills. In an alternative camp, there is another faction of education professionals who believe that the business plan process is counterproductive and is an unnecessary distraction for today’s millennial entrepreneurs seeking to create their own new ventures. In this chapter, we argue why it is important to adopt a lean start-up framework and approach in both entrepreneurship courses and in curriculum design in early-stage venturing. We offer 10 reasons why entrepreneurship educators should place less emphasis on business planning and more emphasis on business modeling during the early stages of evaluating the feasibility of a venture. We believe that educators and curriculum designers need to rethink the traditional approach of building an entrepreneurship program based upon the business plan as the guiding framework. We then conclude our discussion with suggestions on where and how elements of the business plan can and should be introduced into the new venture development process and appropriately positioned in entrepreneurship curricula. We propose a renewed and reconciled view of the Lean Start-up versus Business Plan debate, as both are considered necessary but neither is sufficient to support the full lifecycle of the venturing process.

Entrepreneurship education has been largely treated as a pedagogical “black box.” Despite the emergence of popular entrepreneurship models such as business planning, the lean startup, or business model canvas, neither theoretical nor pedagogical foundations are typically evident. This limits the accumulation of useful evidence that could inform better teaching practices. In this chapter, we develop a set of conceptual models anchored in learning theory regarding how entrepreneurship education should be taught to students. These conceptual models are built on the techniques of entrepreneurship pedagogy such as experiential education. They are developed for three groups of students: students without any entrepreneurship experience, students with previous entrepreneurship experience, and students who are currently running their start-ups. A set of potential variables that could be used for course evaluation purposes is also included. The proposed models meet the needs of students with different levels of entrepreneurship experience. Theoretically, we demonstrate that entrepreneurship students should not be treated as a homogeneous group, as they have different levels of startup experience and different educational needs. Lecturers of entrepreneurship programs could choose the suitable model proposed in this chapter in teaching based on the characteristics of their students. The chapter provides novel insights with regard to how entrepreneurship programs should be designed for students with different levels of entrepreneurship experience.

Following the triple helix (TH) model and the way knowledge is transferred into the industry domain, this chapter aims to define features interface that should be implemented in order to facilitate the University–Industry (UI) relationship and thus encourage the spin-off creation.

In order to support this relationship, a new business model configuration of an entrepreneurial ecosystem is proposed, aiming at creating a sustainable environment, where business entities can grow. The field of the Governance of Entrepreneurial Ecosystems is also investigated in order to define a framework for launching, developing, and sustaining a company over time.

This chapter presents a case study developed within the University of Salento (Italy). It capitalizes results from three different research analyses, based on questionnaires and interviews with actors of the spin-off network (professors and researchers, graduating students, admin-tech staff of the Technology Transfer Office, spin-offs’ CEOs/Associates, and R&D managers of external companies) and on results coming from scientific publications and regional/national reports in the innovation context.

A research methodology based on semantic network analysis and sentiment analysis has been applied in order to identify which features an interface should implement in order to facilitate the UI relationship and encourage the spin-off creation.

To support the start-up overcoming the “death valley,” the creation of a link between the strategy used to transfer value to the market and the phase of innovation is proposed inside the business model configuration. Some aspects of a governance model of an entrepreneurial ecosystem were also presented in order to support the business evolution of a single business entity and assuring sustainability over time.

Business plan writing seems the panacea to gain stakeholder legitimacy and financial backing. Our chapter explores the contributions and disconnections between business plan writing and the start-up process for incubated technology entrepreneurs. The study is set in the South East Enterprise Platform Programme (SEEPP), an incubator programme for technology graduate entrepreneurs in the South East of Ireland. Using a purposive sample of technology entrepreneurs in start-up mode, we took a qualitative approach consisting of content analysis of 40 business plans and in-depth interviews with 25 technology entrepreneurs. Our research found that writing a detailed business plan constrains the technology entrepreneur’s natural penchant for action, compelling them to focus on business plan writing rather than enactment. Technology entrepreneurs favour a market-led rather than funding-led operational level document to plan, and learn from, near-term activities using milestones.

In this chapter, we examine two theorized approaches to entrepreneurial activity: experiential versus prediction based strategies. We empirically assess the comparative performance of several commonly recommended approaches – researching customer needs, researching the competitive landscape, writing a business plan, conceptually adapting the business plan or experimentally adapting the primary business activity. We found that the majority of nascent entrepreneurs began with a business plan, but only about a third adapted their plan in later stages. We also found that talking with customers and examining the competitive landscape were normative activities. Those who started a plan were more likely to create a venture, although the effects much stronger for those who changed their plan later on, as well as for those who researched customer needs.

Our results show that the selection of these activities is both ubiquitous and driven by pre-start-up experience and new venture characteristics. The activities themselves do not robustly link with successful new venture foundation. Hence, pre-start-up experiences, venture characteristics, and the institutional environment are more important in explaining successful performance than recommended activities. Implications for research, practice, and pedagogy are discussed.

Entrepreneurial activity is currently a primary concern of many developed economies that struggle with changes in their industrial structures. Many of the traditionally strong industries are encountering strong global competition and declining markets, and national competitiveness is often said to be built on new entrepreneurial firms that are able to grow in global markets. The facilitating national systems for these firms are covered in the emerging start-up ecosystem discussion. This chapter aims to contribute to this discussion by incorporating an analysis of the variety of actors and activities needed in start-up industries that rely on competence bloc theory. Furthermore, inspired by cultural-historical activity theory, the study specifies the contextual-, temporal- and renewal-related determinants of the activity of start-up ecosystems. As a result, a framework for examining start-up ecosystems as platforms for high-growth entrepreneurship is proposed in terms of its core constituencies that influence the emergence and non-emergence of high-growth firms.

In this chapter, we reflect on the impact of the Covid-19 pandemic on an Innovation and Entrepreneurship educational programme by comparing two editions of the Start-up Lab, a three-month hands-on laboratory organised at the University of Trento (Italy), focused on the development of entrepreneurial ideas by international students. The 2019 edition of the course, before the Covid-19 pandemic outbreak, was held in attendance, whereas the 2021 edition was held online. For the latter, the authors decided to introduce a self-directed learning approach, assuming it could better support remote teamwork and the acquisition of transversal skills. In this chapter, the authors critically question the effectiveness of remote working and the self-directed learning approach in innovation and entrepreneurship education programmes. The authors provide early evidence about some critical aspects of online and distance learning and teamwork, mostly related to self-efficacy skills, such as the ability to motivate others to work together and collaborative work. Despite the negative effects of distance working on some entrepreneurial skills, the authors demonstrate that the ability to reflect on learning experience is a driver for improving specific entrepreneurial and innovation skills. Students who have had the opportunity to reflect on their learning experiences feel more confident about becoming entrepreneurs or working in companies with a stronger entrepreneurial mindset.