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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.

Lean Startup (LS) has gained considerable traction in the startup scene, especially within digital firms where the concept finds the concept's genesis. However, there are more and more calls in the entrepreneurship literature to study LS's application beyond the digital context. The purpose of this study is to explore the applicability of LS within the largely under-researched context of non-digital entrepreneurs. To structure the authors' understanding of the participating entrepreneurs' cognitive and behavioural logic, effectuation theory is applied.

To explore how LS is applied in non-digital settings, this study analyses the LS approach of 15 Dutch brick-and-mortar and click-and-mortar Small to Medium-sized Enterprises (SMEs) and startups.

This study provides empirical evidence that non-digital entrepreneurs pursue an effectual logic in their LS approach. However, the entrepreneurs' LS approach appeared to be contextualised to the non-digital contexts' inherent constraints and trade-offs. Such contextualisation calls for a particular set of skills and competencies, including applying mixed-methods cross-validation, affinity and passion for craftsmanship and aesthetics, inferring from limited, qualitative, and often skewed data, establishing an empathetic collaborative relationship with customers and suppliers, and leveraging prior market knowledge and experience.

This study advances the current understanding of the LS applicability and gives a more nuanced account of how LS is practised in the context of non-digital firms, the challenges entrepreneurs involved in non-digital firms need to overcome, and the skills and competencies they need to possess. In practical terms, the findings help non-digital entrepreneurs and coaches to be more heedful of the contextual peculiarities when employing LS.

Artificial intelligence (AI) has started to receive attention in the field of digital entrepreneurship. However, few studies propose AI-based models aimed at assisting entrepreneurs in their day-to-day operations. In addition, extant models from the product design literature, while technically promising, fail to propose methods suitable for opportunity development with high level of uncertainty. This study develops and tests a predictive model that provides entrepreneurs with a digital infrastructure for automated testing. Such an approach aims at harnessing AI-based predictive technologies while keeping the ability to respond to the unexpected.

Based on effectuation theory, this study identifies an AI-based, predictive phase in the “build-measure-learn” loop of Lean startup. The predictive component, based on recommendation algorithm techniques, is integrated into a framework that considers both prediction (causal) and controlled (effectual) logics of action. The performance of the so-called active learning build-measure-predict-learn algorithm is evaluated on a data set collected from a case study.

The results show that the algorithm can predict the desirability level of newly implemented product design decisions (PDDs) in the context of a digital product. The main advantages, in addition to the prediction performance, are the ability to detect cases where predictions are likely to be less precise and an easy-to-assess indicator for product design desirability. The model is found to deal with uncertainty in a threefold way: epistemological expansion through accelerated data gathering, ontological reduction of uncertainty by revealing prior “unknown unknowns” and methodological scaffolding, as the framework accommodates both predictive (causal) and controlled (effectual) practices.

Research about using AI in entrepreneurship is still in a nascent stage. This paper can serve as a starting point for new research on predictive techniques and AI-based infrastructures aiming to support digital entrepreneurs in their day-to-day operations. This work can also encourage theoretical developments, building on effectuation and causation, to better understand Lean startup practices, especially when supported by digital infrastructures accelerating the entrepreneurial process.

This study aims at exploring how small and medium enterprises (SMEs) can implement a more open and co-creational business model by actively collaborating with startups.

Because of the novelty of the SME–startup collaboration phenomenon and to the depth of the investigation required to grasp the mechanisms and logic of an open and co-creational business model, a single-case study has been performed related to investigating a collaboration between an SME and a startup.

The authors provide detailed empirical evidence on how SMEs may structure a “systematic” approach to design and execute an open business model enabled by startup collaboration. Moreover, this study suggests that the business model innovation process represents a necessary forerunner of an open business model. Finally, the authors contend that research on open business models should entail a broader perspective beyond the innovation process, to include business model validation through testing approaches like the lean startup.

This study takes as the locus of investigation the original perspective of the external partner of a focal firm willing to innovate. This study offers a unique contribution because, to date, few studies adopted such view within a relevant and under-remarked empirical setting linking SMEs and innovative startups.

The purpose of this study is to share how the learning impact of a remote workshop was improved through action research practices, especially action inquiry and critical reflexivity.

Research design detailed herein consists of one complete cycle of action and reflection. Methods used include: journaling into four territories of experience, free-form journaling, individual and joint reflection using four parts of speech and extended ways of knowing.

Action inquiry and critical reflexivity have shown themselves to be a potent means of improving the learning outcomes of remote Playing Lean workshops. Drawing on early insight, the author suggests several venues for further inquiry.

This paper contributes a novel combination of action research practices that can be used for improving other learning initiatives as well, and an example of how to question the veracity of qualitative findings.

This study aims to emphasize the integration of lean start-up and design thinking approaches and investigate how they may be used together.

The report uses a systematic literature review methodology to analyze and summarize previous research on combining lean start-up and design thinking. Inferences were discovered and analyzed after relevant publications were chosen based on predetermined inclusion criteria.

The research shows that combining lean start-up and design thinking significantly impacts entrepreneurship. Start-ups can efficiently uncover consumer needs, reduce risks and improve their product or service offerings by combining the client-centricity of design thinking with the iterative and data-driven concepts of lean start-up. This integration promotes an innovative culture, gives teams the freedom to try new things and learn from mistakes and raises the possibility of start-up success.

The dependence on pre-existing literature, which might cover only some potential uses and circumstances, is a weakness of this research. It is advised that more empirical research be conducted to determine the precise circumstances in which the integrated strategy performs best. Future studies should also explore the difficulties and drawbacks of using these approaches to offer suggestions for overcoming them and maximizing their advantages.

The findings have significant ramifications for business owners and other professionals working in the start-up environment. The combination of lean start-up and design thinking emphasizes the relevance of early customer interaction and empathy-driven design. To foster creativity and hasten the expansion of start-ups, practitioners are urged to create a comprehensive strategy that integrates the advantages of both techniques. Through this integration, business owners may develop solutions that appeal to their target market, increasing adoption rates and market competitiveness.

This study is interesting in comparing lean start-up and design thinking, emphasizing the overlaps and benefits of their application to entrepreneurship. This study discusses successful start-up methods by offering suggestions for future research and practice. It also provides a basis for further developing and adopting the integrated approach.

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.

It is the responsibility of the national governments to deliver healthcare services that are both effective and affordable to everyone. There are still gaps in this supply, which is extremely demanding. In this sense, companies are attempting to reach neglected markets and disrupt the marketplace with novel solutions. Although there are still anecdotal examples, a thorough literature evaluation is lacking. This study aims to provide a synthesis of the future of healthcare start-ups.

Papers that included the term “healthcare start-ups,” “health-tech start-ups,” “start-up,” “Artificial intelligence in healthcare,” and “Health tech start-ups in India” were considered for the analysis. The Biblioshiny package under the R programming tool was considered for a detailed analysis of the papers.

A total of 854 documents were related to healthcare start-ups, from which only 14 papers are related to health-tech start-ups and four papers are related to artificial intelligence in healthcare start-ups. It has been found from the past works of literature that the effectiveness of technology for information and communication in healthcare has significantly increased in recent years. Technology has already begun to permeate the healthcare market from other fields and industries. One way that the internet will help the industry evolve is by integrating digital health into daily life.

The study is not using other databases but is limited to Google Scholar and Scopus. A significant constraint of this study is the paucity of relevant literature in reputable publications on health and information systems. Another restriction was that gray literature, such as any journal or newspaper written by members of the health community about health-tech start-ups, was not taken into account.

Healthcare players should exhibit a fundamental openness to novel solutions to facilitate the digitalization of the healthcare system. Developing technology is widely used, and from an innovation perspective, a start-up should focus on innovation by employing technology and offering revolutionary healthcare solutions.

The novelty of this research is based on its presentation of an organized and thorough literature evaluation, which defines the current state of the art concerning green start-ups. To create a sustainable start-up, a thorough study of the information gained in respect of its healthcare start-up is presented.

The aim of this article is to propose and test a structural model of relationships between generic and specific competencies and entrepreneurial competencies in order to assess students' learning.

The study was carried out on a sample of 337 students enrolled on the entrepreneurship specialisation of the final bachelor's degree project course on the Bachelor's Degree in Business Administration and Management at the Universitat Oberta de Catalunya. A questionnaire was designed to gather information on students' perception of their level of acquisition of the different groups of competencies. The partial least squares (PLS) multivariate technique was used to analyse the model.

The results confirm that there are significant relationships between the different groups of competencies. Specifically, it shows that generic competencies influence specific competencies and that there is a strong relationship between systemic and professional competencies and entrepreneurial competencies. It also shows that the experience variable contributes positively to different competency groups, while the gender and age variables have no effect on the development of entrepreneurial competencies.

The study provides relevant information to the academic world on different factors that affect competency development.

The analysis provides an innovative research and contributes knowledge on entrepreneurial competency acquisition, providing an answer to whether generic and specific competencies influence entrepreneurial competencies.

The goal of this research is to investigate the relationship between two different sets of practices, lean startup and business planning, and their relation to entrepreneurial performance.

The authors collected data from 120 entrepreneurs across the US about a variety of new venture formation activities within the categories of lean startup or business planning. They use hierarchical regression to examine the relationship between these activities and new venture performance using both a subjective and objective measure of performance.

The results show that talking to customers, collecting preorders and pivoting based on customer feedback are lean startup activities correlated with performance; writing a business plan is the sole business planning activity correlated with performance.

This research lays the foundation for understanding the components of both lean startup and business planning. Moreover, these results demonstrate that the separation of lean startup and business planning represents a false dichotomy.

These findings suggest that entrepreneurs should engage in some lean startup activities and still write a business plan.

This article offers the first quantitative, empirical comparison of lean startup activities and business planning. Furthermore, it provides support for the relationship between specific lean startup activities and firm performance.