Management Review ›› 2023, Vol. 35 ›› Issue (6): 123-133.

• Innovation and Entrepreneurship Management • Previous Articles     Next Articles

The State Quo of the Business Model Innovation Researches in China: A Dual Oriented Perspective of Anomaly and Typology

Bai Sheng, Shang Xing, Mi Jinlin   

  1. Business School, Southwest University of Political Science and Law, Chongqing 401120
  • Received:2021-09-13 Published:2023-07-27

Abstract: Nowadays, it is awkward that domestic business model innovation (BMI) researches contribute little to the science and this is because they, follow the thought of “finding and filling gaps” and use research tool-driven methods. In this paper, we introduce the idea of “double orientation perspective”: obtaining the anomaly-driven perspective of research targets from the conflict, and taking the optimization type as the typology-driven perspective of research objectives. And then we examine the performance of BMI literature in CSSCI (2019—2020). The research conclusions are as follows. (1) Anomaly problems can be divided into three categories: practice without theory, no strong theory and coexistence of multiple strong theory, which help to construct more interesting research targets. (2) The research results of solving anomaly problems fall into three categories: new theory, theoretical optimization and theoretical integration. This typology-driven idea will generate more research contributions in optimizing theory and guiding practitioners. (3) The existing BMI literature in China has accumulated a lot of achievements in antecedent variables, basic constructs, outcome variables and intermediate variables. However, there is an imbalance in giving research targets, implementing theorizing process, obtaining results and adopting theoretical test methods, which also opens new research space. These works provide meaningful reference for the existing BMI researches to find a way out, and add new contents to the existing management research methodology.

Key words: business model innovation, anomaly-driven, typology, CSSCI