Distant or Local? The Roles of Knowledge Search on General Purpose Technology Innovation in Emerging Industries

• Published in: Journal of innovation & knowledge Vol. 8; no. 2; p. 100331
• Main Authors: Cen, Jie, Fu, Feng, Yang, Yan, Yan, Jingxin, Li, Jing
• Format: Journal Article
• Language: English
• Published: Elsevier España, S.L.U 01.04.2023; Elsevier
• Subjects: Distant, local and balanced search; General purpose technology; Industry alliance heterogeneity; Distant, local and balanced search; Industry alliance heterogeneity; General purpose technology
• ISSN: 2444-569X; 2444-569X
• DOI: 10.1016/j.jik.2023.100331

Due to the inherent complex tensions in General Purpose Technology (GPT) in emerging industries, namely those between “generality” and “emergance,” firms in emerging industries often face the dilemma of choosing distant search or local search in GPT innovation. The core research question of this paper is: How do the different knowledge search strategies affect GPT innovation in emerging industries? And do industry alliances play a moderating role between them? Based on a knowledge-based view, this paper takes 380 firms in emerging industries as total samples and 196 firms in emerging industries as subsamples to examine the impact of distant, local, and balanced knowledge search on the GPT innovation in emerging industries, finding: (1) Different knowledge search strategies have differential effects on the GPT innovation in emerging industries. (2) The heterogeneity of industry alliances positively moderates the relationship between distant search, balanced search, and GPT innovation in emerging industries, and weakens the relationship between local search and GPT innovation in emerging industries. This paper clarifies the relationship between knowledge search strategies and GPT innovation in emerging industries, and also provides management inspiration for the emergence and improvement of GPT innovation.