Article Preview
Top1. Introduction
In emerging economies, firms face a dilemma: continuing the low-cost and imitation-based competitive strategy or enhancing R&D to become leaders in innovation (Cao et al 2019; Chaudhry et al 2018; Hobday, et al., 2004; Xiao, et al., 2013). Recently, some industries in emerging economies have obtained global competitiveness via low labor costs. They achieved technological progress through technology introduction, absorption, and re-innovation. However, when firms in emerging economies try to catch up the industrial leaders for reducing the technological gap, sudden technological changes initiated by the industrial leaders cause these firms to fall behind again. Therefore, it is difficult for firms in emerging economics to follow the technological trajectories established by industrial leaders. As a result, technology leapfrogging becomes an option for firms in emerging economics to realize technology catchup (Lei, Lin, Sha 2016). Latecomers can catch up with industrial leaders through leapfrogging some phases of technological trajectories or creating new trajectories.
Adner and Kapoor (2015) point out that social-economic factor, such as institution, social concerns, industrial organization, and power allocation, play an important role in technological transition. However, they did not examine the mechanism how these factors affect technological transition. How socio-economic factors affect firms’ strategies in technology catching up and their innovation performance remains unknown. Accordingly, this paper categories technological trajectory transition into creative accumulative technological trajectory transition (CCT) and creative disruptive technological trajectory transition (CDT). It further proposes a theoretical framework to explore the relationship among innovation ecosystem, technological trajectory transition, and innovation performance. Particularly, this paper applies structural equation modeling to examine how some key socio-economic factors, namely organizational learning ability, network relationship strength, and environmental concerns, affect firms’ technological trajectory transition. Moreover, it examines how these factors and technological trajectory transition affect firms’ innovation performance.
Data collected from 366 firms in China is applied to examine the research model. The results indicate that that firms’ organizational learning ability positively affects their CCT, CDT, and innovation performance. Firms’ network relationship strength negative affects their CCT and CDT, whereas positively affect their innovation performance. Governments’ environmental concerns positively affect firms’ CCT, CDT, and innovation performance. Firms’ environmental concerns do not positively affect their CCT, CDT, and innovation performance. Firms’ CCT does not positively affect their innovation performance. In contrast, firms’ CDT positively affects their innovation performance.
Other than enriching the theories of technological trajectory, this paper provides implications for managers and policy-makers in emerging economies. In specific, it provides guidance on how to make strategic choices when facing different technology development paths, and on how to implement technological trajectory transition.
The remainder of this paper is organized as follows. We review relative literature in Section 2. We develop a research model and propose hypotheses in Section 3. We describe the research methodology and measurements in Section 4. Section 5 analyzes the structural equation model and discusses the empirical results. Section 6 summarizes the findings, outlines the managerial implications, discusses the limitations of our research, and points out directions for future research.