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The capacity of a country to develop new products, services and transform them into innovative technologies and create successful, sustainable businesses to promote development is of paramount importance for all economies. Startups are an effective way of doing this. A startup is a temporary organisation in search of a scalable, repeatable, profitable business model and a small startup founded by two or three entrepreneurs can produce and test the feasibility of tens of possibilities for a new business idea. At the risk of sounding glitzy: leadership in startups is an important topic that has received far too little attention. Furthermore, it can be argued that leadership plays an essential role in new venture creation as it shapes startups’ fates in this dynamic environment. Startups require different leadership than established firms due to their unique difficulties and opportunities. Therefore, on a socio-economic level, one can reasonably argue that leadership in startups is a worthy research topic and hence adopting an exploratory approach with a systematic literature review, and with multi-case approach this article explores startup leadership styles in emerging market with focus on India.

We provide large-scale evidence on the occurrence and value of FinTech innovation. Using data on patent filings from 2003 to 2017, we apply machine learning to identify and classify innovations by their underlying technologies. We find that most FinTech innovations yield substantial value to innovators, with blockchain being particularly valuable. For the overall financial sector, internet of things (IoT), robo-advising, and blockchain are the most valuable innovation types. Innovations affect financial industries more negatively when they involve disruptive technologies from nonfinancial startups, but market leaders that invest heavily in their own innovation can avoid much of the negative value effect.

Purpose 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. Design/methodology/approach 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. Findings 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. Originality/value 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.

This paper is one of the first studies to examine the link between infrastructure and entrepreneurship. Because infrastructure can enhance connectivity and linkages that facilitate the recognition of entrepreneurial opportunities and the ability of entrepreneurs to actualize those opportunities, a hypothesis is developed suggesting that startup activity is enhanced by infrastructure. However, not all types of infrastructure have a homogeneous impact on the entrepreneurial decision, so that a second hypothesis is developed suggesting that certain types of infrastructure which facilitate connectivity and linkages among people are more conducive to startup activity. The empirical results suggest that startup activity is positively linked to infrastructure in general, but that certain specific types of infrastructure, such as broadband are more conducive to infrastructure than are highways and railroads. Finally, we hypothesize that the types of infrastructure have varying influences in different sectors. Our empirical analyses support this view and we conclude that particular infrastructure policies can be used to facilitate regional startup activities and, furthermore, to foster startup activities in desired industries.

In recent year, the new digital era provides a wider opportunity to tap the worldwide market, facilitate trade, and ease the transaction process without borders. However, companies need to acknowledge and be able to seize these opportunities in entering the global market.  This work examines the influence of entrepreneur orientation, Cultural intelligence, and social capability on network capability. Besides, this work further extends to investigate the impact of network capability on born global performance. The Dynamic Capability Theory was used as a foundation of the present conceptual framework.  This study surveyed 75 born global firms, the sample of this study consist of 300 employees and founders. The Structural equation Modelling found that entrepreneur orientation, cultural intelligence, and social capital are important factors that have a positive influence on network capability. Besides, the findings found that network capability foster born global performance. The findings can be used as a guide for startups and entrepreneurs to explore global opportunities and give a competitive advantage in exploring foreign markets.  Furthermore, this work provides a significant contribution to the literature and the limitation of the study set a venue for future research agenda. 

The lean startup model emerging from the Silicon Valley recently has become worldwide practice. In this model, search and execution are the two primary activities conducted by entrepreneurial firms. Search activities focus on learning and discovery, such as exploring new customer and market segments, while execution activities focus on implementing well-defined plans and scaling up. Effectuation and causation are two different cognitive approaches an entrepreneur might use to conduct strategic moves. We argue that entrepreneurial effectuation cognition is associated with more search behaviors and that entrepreneurial causation cognition is associated with more execution behaviors. We test these hypotheses in a survey of 160 firms and find evidence in support of our arguments.

Understanding the circumstances and reasons which facilitate digital entrepreneurship (DE) is of interest to academic research, and guides business practice, as well as public policies aiming at supporting this phenomenon given its positive impacts in terms of job creation and economic growth. We define some relevant concepts and briefly map current research using a perspective that focuses on the way digital entrepreneurs create digital value by acquiring, processing, and distributing digital information. Through the adoption of a digital information processing perspective, we provide a micro-level approach to research on digital entrepreneurship (DE) that complements existing literature on DE focused at the systemic level (digital entrepreneurship ecosystems and in the digital platforms economy). We show how these two approaches can be jointly used to identify major research streams on DE: digital business models, the digital entrepreneurship process and the creation of digital start-ups, DE in digital platforms, and entrepreneurial digital ecosystems. As is the case with existing DE frameworks, our approach concurs in putting emphasis on the new collaborative and social dynamics enabled by digital tools to support knowledge sharing and facilitate opportunity recognition.

In this paper, we explore which local factors affect the creation of cleantech startups in a geographical area. Specifically, we note that these startups combine innovation and attention to the environment. Thus, we consider two primary sets of local factors: the availability of scientific and technological knowledge and the environmental awareness of local governments and communities as the main drivers of the creation of cleantech startups. Using a dataset of 393 cleantech startups created between 2012 and 2014 and extracted from the Italian official database of innovative startups, we estimate negative binomial regressions whose dependent variable is the number of cleantech startups created in each of the 110 Italian provinces. The results highlight that both the local availability of scientific and technological knowledge and the local environmental awareness are crucial determinants of cleantech entrepreneurship in a geographical area. We discuss the implications of these results for policymakers who intend to stimulate this type of entrepreneurship.

PurposeThis study investigates specific challenges that tech startups in Catalonia face in complying with the General Data Protection Regulation (GDPR) from the perspective of Technology-Organization-Environment (TOE) framework. It also examines how factors such as startup’s size, age, and sector influence compliance experiences.Design/methodology/approachA mixed-methods approach was employed, combining survey data from 107 Catalonian tech startups with in-depth interviews with senior executives from three startups to provide qualitative insights for triangulation. GDPR compliance challenges were analysed using regression analysis and One-Way ANOVA.FindingsThe results of the study underscore the interconnected nature of GDPR compliance challenges, revealing that staff training mediates the relationship between regulatory and technical complexities and compliance costs. While compliance costs, regulatory complexity, and technical complexity are viewed as significant challenges of equal importance, staff training is not considered a primary concern for Catalonian startups. Additionally, factors such as the startup’s size, age, and sector significantly influence how these challenges are perceived and addressed, with smaller, younger, and non-tech startups experiencing greater difficulties.Research limitations/implicationsRelatively small sample size and geographic focus on Catalonia potentially limit generalizability of the findings.Practical implicationsThe findings have implications for startups, policymakers, and industry regulators, emphasizing the need for simplified regulatory guidance, accessible technical support, and tailored compliance training programs for startups.Originality/valueThis study fills a literature gap by applying the TOE framework to explore regulatory adoption challenges by tech startups. It reveals how staff training mediates the effect of regulatory and technical complexities on compliance costs highlighting the role of organizational capabilities in regulatory adoption.