عملکرد رشد راه اندازی فناوری پیشرفته
Abstract
1. Introduction
2. Background
3. Hypotheses formulation
4. Research design and methodology
5. Results
6. Discussion and conclusions
Declarations of interest
Appendix A.
References
Abstract
Focusing on the role of efficiency and novelty design themes, this paper examines how (a) the initial business model of a start-up, (b) the subsequent changes in the design themes and (c) the combinative effect of efficiency and novelty (contextual ambidexterity) impact a start-up’s growth performance. The study is based on a survey involving 267 new ventures from high-tech industries. The results highlight the importance of pursuing higher efficiency over the life cycle of a start-up, although not at the moment of its establishment. In relation to business model ambidexterity, the findings highlight the different effect that contextual ambidexterity can have on the growth performance of a start-up firm in different stages of its life cycle. While initial ambidexterity is found to have a negative effect on growth performance, successive increases in the level of ambidexterity have a positive influence on growth.
Introduction
High-tech start-ups are often seen as engines of economic development and as effective vehicles for job creation (Adelino, Ma, & Robinson, 2017; Hathaway, 2013). Yet, although a handful of such firms do achieve incredible success, on average high-tech start-ups have a limited impact on employment and reach only moderate rates of growth, as confirmed by academic research (Pe’er, Vertinsky, & Keil, 2016; Song, Podoynitsyna, Van Der Bij, & Halman, 2008), and by an increasing amount of statistical data (European Commission, 2017; Kauffman Foundation, 2017; OECD, 2018). Such poor performance is caused by several limitations and weaknesses intrinsic to these firms, pertaining to entrepreneurial, strategic and organisational aspects (Pugliese, Bortoluzzi, & Zupic, 2016) and – ultimately – to their precarious business models (BMs). Indeed, it is anything but easy for a start-up to guess the ‘right’ (meaning scalable and profitable) BM since the very beginning (Andries & Debackere, 2007; Reymen, Berends, Oudehand, & Stultiëns, 2016). Most of the time, such firms must dynamically adapt and fine-tune their BMs, through flexibility (Bock, Opsahl, George, & Gann, 2012), experimentation (Andries, Debackere, & Van Looy, 2013) and the use of trial-and-error heuristics (Chesbrough, 2010; Sosna, Trevinyo-Rodríguez, & Velamuri, 2010).