Search results

Aim of the present monograph is the economic analysis of the role of MNEs regarding globalisation and digital economy and in parallel there is a reference and examination of some legal aspects concerning MNEs, cyberspace and e‐commerce as the means of expression of the digital economy. The whole effort of the author is focused on the examination of various aspects of MNEs and their impact upon globalisation and vice versa and how and if we are moving towards a global digital economy.

The purpose of the study is to review and understand firm selection mechanism involved in government venture capital (GVC) funding and identify key factors influencing selection of tech-based firms for GVC funding.

This paper is based on real-time methodology. The data was generated from interviews of 60 young applicants, who applied for startup funding, and analyzed using statistical techniques to draw the results.

This review identifies financial viability, market viability and technological innovation to have the strongest predictive ability in firm selection process of the GVC funding program for tech-based youth-owned startups in the first round of interview. This review also highlighted that social impact is not a statistically significant variable in firm selection process in GVC funding.

This study tests the validity of the theory of GVC based on quantitative analysis of field data and identifies key factors with strong predictive abilities for GVC funding, more particularly for the youth-owned tech-based startups. This study brings to light the mechanism adopted for GVC funding and addresses gaps in the literature relevant to firm selection mechanism in GVC programs. This study would help GVC Fund Managers to review their own GVC programs in terms of selection mechanism and help them in appropriate designing of such programs.

New ventures search for external knowledge to break through the prevailing knowledge and resource constraints. The influence of search mechanisms can be assessed against the backdrop of internal factors such as the venture’s knowledge integration (KI) capability. The purpose of this paper is to study the effects of knowledge search depth (KSD) and knowledge search breadth (KSB) on innovation outcomes and asks to what extent such effects are mediated by levels of KI.

The authors distinguish between the current depth and width of the firm’s knowledge base as to detect their possible moderating effects. The authors test the model using data collected from 167 Chinese start-ups.

The results show that KSB has a positive effect on KI and innovation performance, but KSD has an inverted U-shaped effect on KI and innovation performance. KI plays a mediating role between external knowledge search and innovation performance, while the breadth of the venture’s knowledge base positively moderates the relationship between explorative KI and innovation performance, and the depth of knowledge base positively moderates the relationship between exploitive KI and innovation performance.

These results differ from earlier research focusing on mature enterprises.

Network structures are critical in the acquisition of resources; however, their impact on innovative performance remains unclear, especially in an uncertain environment. This study aims to advance research on network research by investigating how the configuration of the industrial environment shapes the relationship between network structures of a new venture and its innovative performance.

Empirical support was derived from entrepreneurial survey data. Data were collected through a survey of 1,510 new ventures in Taiwan for this research study.

The authors find that innovative performance is impacted by different aspects of the network structure, and that environmental uncertainty contributes to this impact. Overall, the authors find that network structure, innovative performance and environmental uncertainty together contribute to a contingent view of the conditions under which network boundary conditions impact innovative performance.

Given the contradictory role of network centrality and the cooperative network on innovativeness, managers need to focus on acquiring a critical position in the industrial network rather than expecting to obtain resources and information from strong relationships with cooperators, especially in an uncertain environment.

This research contributes to network theory in two ways. First, it provides descriptive data on different aspects of the network structure and how these aspects impact innovative performance. Second, it sheds light on the configuration of resources and allocations for new ventures, which must compete with rivals in an uncertain environment.

Why do some ventures grow to become dominant market players while most new ventures that do not fail limp along more modest trajectories? In comparison with our knowledge regarding determinants of venture creation or survival, the phenomenon of venture growth has been relatively neglected, both theoretically and empirically. Venture growth is a multi-level phenomenon co-occurring at different analytical and temporal levels. In this chapter we develop a theoretical model that accounts for venture growth as a process, drawing upon the mechanism-based theorizing approach. We offer nine social mechanisms that lead to venture growth, providing a foundation for empirical exploration and further theory building.

How general can a “general” theory of entrepreneurship be? Abstraction is a necessity but is it possible to include venture opportunity variation in a general theory of entrepreneurship building on two contrasting perspectives such as equilibrium economics and disequilibrium economics. Two important boundaries need to be explicated. First, defining entrepreneurship as the creation of new economic activity includes both the creation of new means – ends (cf. Schumpeter, 1934) – as well as optimizing within known means – ends frameworks (cf. Kirzner, 1997). Second, such a theory includes an opportunity – actor nexus because it is the first tangible or intangible evidence of existing venture opportunities. Formal models of entrepreneurship often start with a person and at some point in time an exchange of persons with firms take place which is confusing because both levels of analysis and outcome are mixed with each other. Apparently, there is no such thing as entrepreneurship without actors, but if we want to create knowledge about the creation of economic activity, we need to frame our boundary around the nascent initiative instead of single actors and/or teams of actors because value can only be assessed in relation to the costs of services withdrawn. Analogous to this is, for example, the theory of firm and the theory of organizations with boundaries well beyond single actors or groups of actors. Another factor behind a venture-based theory of entrepreneurship comes from empirical evidence from the Swedish PSED, which suggests that approximately 16% (n=97) nascent entrepreneurs are exchanged during the start-up process. Formal models of entrepreneurship could therefore start with the nexus of venture opportunities and enterprising actors as suggested by Shane (2003) or with resources as suggested by Davidsson (2000) and progress forward in the entrepreneurial process. Entrepreneurship models built around the economic activity itself needs to be dynamic allowing different outcomes and feedback loops because resource combinations alter our perception of value and diffuses information, which may lead to additional resource combinations (Hayek, 1945).

Entrepreneurial opportunity (EO) identification pertains to the core processes of entrepreneurship and innovation. The initial phase of this process starts with individual cognition, which is why cognition has been established as a critical theoretical perspective.

Knowledge and new information have been confirmed as essential cognitive impact factors. However, it is not understood well, how individuals apply those factors and how they actually identify innovative and economically viable EOs. To address the limitations of current research, this chapter investigates the current literature on underlying cognitive processes of opportunity identification.

The literature analysis demonstrates that there is not a single cognitive process but rather a magnitude of different micro-mechanisms that are necessary for the successful identification of EOs. The findings are grouped to four categories of cognitive processes and entail their micro-mechanisms: pattern recognition, information processing, and creative thinking. Furthermore, the analysis reveals that those micro-mechanisms have seldom been related to each other within the scope of opportunity identification. This chapter closes this gap by discussing and contrasting and the different process categories and respective micro-mechanisms and suggests an integrative theory development and avenues for future research.

Research has shown that business model innovation can facilitate most ventures to innovate and remain competitive, yet there has been limited work on how digital leadership capabilities influence business model innovation. Building on the dynamic capabilities view, we address this gap by linking digital leadership capabilities with business model innovation via managerial decision-making through provision of grants received by new ventures.

The study is cross-sectional research. Data have been collected utilizing purposive sampling from 313 founding members of new ventures in high-velocity markets, i.e. from Pakistan. SPSS has been used to conduct the moderated mediation analysis.

Digital leadership capabilities foster the business model innovation of the new ventures because they enable new ventures to capitalize on digital technologies and create new ways of generating value for the customers and themselves. Moreover, managerial decision-making mediates digital leadership capabilities and business model innovation relationship, whereas, grants moderate the indirect positive effect of digital leadership capabilities on business model innovation via managerial decision-making. The study generates initial evidence on the impact of digital leadership capabilities on business model innovation via managerial decision-making for new ventures. We advance knowledge on new ventures’ business model innovation by deep-diving into dynamic capabilities view and emphasizing digital leadership capabilities as a significant driver for business model innovation.

With the help of dynamic capabilities theory, this study analyzes how new ventures make use of digital leadership capabilities to promote business model innovation.

A corporate entrepreneurship (CE) strategy implies that a firm’s strategic intent is to continuously leverage entrepreneurial opportunities for growth- and advantage-seeking purposes. CE has gained greater research attention with a focus on the factors that influence an organization’s willingness to initiate and sustain a CE strategy. In the current disruptive age, firms acknowledge the importance of CE (also referred to as corporate innovation) as the critical element for sustained competitive advantage in the global economy. Yet, so many organizations struggle with the actual implementation of an innovative strategy. There are key challenges that must be addressed by today’s corporate entrepreneurial leaders in this age of disruptive innovation. These include framing the innovation, developing the internal architecture, coordinating the managerial levels, integrating design thinking, recognizing the grief associated with project failure, and demanding ethical standards. As research on corporate innovative activity has evolved, numerous researchers have acknowledged the importance of these leadership activities to enhance the effectiveness of corporate entrepreneurial activity. In this chapter, the authors discuss these critical elements confronting corporate entrepreneurial leaders.