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Uncertainty in the early development of digital business startups can benefit from data-driven testing of hypotheses. Startups face uncertainty not only in product development, but also over the structure of the business model and the nature of the customer or market to address. The authors conceptualize a new model, the Lean Discovery Process (LDP), which focuses on market-based testing from the early business idea through to fully realized product stages of an innovation. The purpose of this paper is to highlight a methodology to help digital business reduce uncertainty and apply lean principles as early as possible in the development of a business concept.

Examining literature in lean startups, lean user experience and lean software development, the authors highlight underlying assumptions of existing lean models. The authors then examine the LDP using the case of raiserve, a social entrepreneurship startup that focuses on the management of cause-based voluntary service.

Existing literature focuses on product development against an assumed customer base. Early hypothesis testing can be applied to business concept development to substantially reduce cost and time to market.

Further investigation of different forms of uncertainty in digital startups can open up opportunities to further apply lean methodologies. A more extensive empirical study to measure the potential impact is warranted.

The authors conceptualize the minimum viable customer and support early testing with concepts from market research and collective intelligence. The authors demonstrate early opportunities to apply lean principles and rigorous hypothesis testing in an LDP that results in significant reductions in time and expense of product development.

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.

Startups have attracted increased attention over the past years. While entrepreneurs develop startups to capture new business opportunities, also large companies are turning to these fast-growing organizations in efforts to become more agile. However, managing business model innovation and validation is challenging. A number of methodologies, like the Lean Startup (LS), emerged to reduce uncertainties concerning innovation-based projects, and to contribute to business model validation. Despite its popularity, the literature on the LS and its key underpinnings (Agile Methodologies and Customer Development) is sparse, lacking an integrated and structured analysis of their impacts and potentialities. The paper aims to discuss this issue.

The authors conducted a comprehensive systematic literature review on the topic fully analyzing a final set of 71 papers.

There is a turning point in the research stream’s maturity with publications in conferences and major journals, with the predominance of empirical investigations in the European region. Articles on the topic are on the rise in several technology fields. However, the literature on the subject falls short on providing guidance to assist practitioners and scholars on the adoption and investigation of these methodologies.

The paper provides guidance for practice by presenting a staircase roadmap for the LS implementation drawing from the final set of papers reviewed.

The study categorizes the current literature through a concept map, and offers a structured research agenda beyond the categories from the thematic analysis.

Most studies investigating the adoption of lean startup (LS) practices by technology new ventures focus on software startups in mature entrepreneurial ecosystems and disregard their applicability for opportunity exploitation in other technological backgrounds. This study contributes to this research stream by exploring how Brazilian technology new ventures (in different technological fields) tentatively adopt LS to exploit opportunities and whether LS is suitable to their emerging economy context.

The authors adopt an exploratory multiple-case study based on qualitative data collection and analysis of nine Brazilian biotechnology, engineering and software startups.

The study shows how technology new ventures tackle the activities of opportunity exploitation – namely, developing a product or service, acquiring human resources, gathering financial resources and setting up the organization – by leveraging LS tools and practices for business model validation; also, it identifies six contextual constraints hindering the systematic adoption of LS and reveals how technology new ventures cope with such constraints in their early stages by integrating LS with complementary strategies and practices. Furthermore, the study reveals that the systematic and comprehensive adoption of LS nurtures the development of an entrepreneurial experimental capability to explore opportunities in a quasi-scientific and hypothesis-driven fashion.

The study investigates how Brazilian engineering, biotechnology and software startups exploit opportunities and overcome constraints to business model validation through the combined adoption of LS and complementary strategies and practices and provides a set of propositions to guide future research.

The primary goal of a startup is to find a viable business model that can generate value for its customers while being effectively captured by the startup itself. This business model, however, is not easily defined, being a consequence of the application of tools involving trials, data analyses and testing. The Lean Startup (LS) methodology proposes a process for agile and iterative validation of business models. Given the popularity and importance of such methodology in professional circles, the purpose of this paper is to conduct a historical literature review of existing academic and professional literature, correlating LS concepts and activities to previous theory and alternative business model validation methods.

A historically oriented systematic literature review employing snowball sampling was conducted in order to identify academic and professional literature and references for iterative validation of business models. A total of 12 scholarly journals and professional magazines dealing with strategy, innovation, entrepreneurship, startups and management were used as data sources. The extensive literature review resulted in 963 exploratory readings and 118 papers fully analyzed.

The results position the LS as a practical-oriented and up-to-date implementation of strategies based on the Learning School of strategy making and the effectuation approach to entrepreneurship; the authors also identify a number of methods and tools that can complement the LS principles.

This paper identified and synthesized the scientific, academic and professional foundations that precede, support and complement the main concepts, processes and methods advocated by the LS methodology.

Business model change (BMC) is a process new ventures are frequently involved in, especially in dynamic environments like the digital industry: copying with it is a key issue for entrepreneurs attempting to shorten the transition between current and new business models (BMs) and avoid losses in terms of revenue, image and customer retention, while acquiring experience and validated learning in the process. The purpose of this paper is to propose a lean framework to support digital new ventures in the BMC process.

The study builds its contribution on two pillars: a review on BM and the lean thinking theories, and a multiple case study on three digital new ventures which underwent BMC.

The study shows how BMC in a digital context can beneficially follow lean principles, and how these principles can be integrated in an original lean framework to experiment on, validate and subsequently change a BM.

The authors provide the “single minute exchange of die” for BMC framework that extends and complements lean startup approaches to further relate lean thinking and BMC, thus operationalizing the process of BM experimenting and validation that enables change.

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.

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 term Lean Startup (LS) was coined by Eric Ries, and his 2011 book has popularized the concept with organizations, both startups and established organizations, implementing LS. However the empirical grounding is thin and for a long time this subject has been neglected by academia. The purpose of this paper is to present a systematic literature review (SLR) on LS, while highlighting core knowledge and identify gaps.

A SLR was carried out based on the Preferred Reporting for Systematic Reviews and Meta-Analyses (PRISMA) protocol of Scopus and Web of Science databases. In total, 45 articles published in journals and conferences over 10 years were collected which revealed a number of LS research gaps.

The SLR revealed the tools and methods associated with LS, most cited pros and cons, reasons that cause LS failure, the challenges that companies face in the implementation of LS, and critical success factors (CSFs) that can support these challenges and minimize the reasons for failure.

The findings of the study can be beneficial to practitioners and senior managers in organizations who wish to delve into the journey of LS. The study also discloses challenges and barriers that can hinder the implementation of LS.

Academic publications regarding LS are sparse and this SLR is one of the first SLRs to explore both the critical failure factors (CFFs) and the CSFs based on peer-reviewed journal and conference proceedings.

As part of the entrepreneurial journey, high-tech entrepreneurs are faced with the need to develop a competitive value proposition and leverage emerging technology to strengthen the value proposition. Entrepreneurial pivoting can be adopted to address this requirement since it enables the startup to validate and refine the company’s strategy and business model. Therefore, this research study provides an empirical investigation of the pivoting concept explained in the context of the lean startup approach (LSA) and technology entrepreneurship to improve the understanding of the entrepreneurial journey for high-tech entrepreneurs.

A qualitative research method was conducted by interviewing 30 high-tech entrepreneurs across the United Kingdom to validate the theories behind the LSA and identify new insights on entrepreneurial pivoting.

The research study has validated the existing types of pivots and identified two new pivots (giving 16 in total). The study has validated the existing 11 factors that trigger a tech startup to change its direction and identified three new factors (giving 14 in total). The research study also determined that there can be a domino effect in pivoting and the value proposition can be created and sustained through pivoting.

This study provides empirical evidence on pivots and the factors associated with pivots. Furthermore, it helps in understanding the influence of the phases of technology entrepreneurship on pivoting. The study also discusses the challenges faced by tech startups while pursuing pivots, the domino effects in pivoting and has found evidence that pivoting eventually leads to achieving the desired results.