Journal of Marketing Science ›› 2024, Vol. 4 ›› Issue (3): 113-130.

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A meta-analysis on the relationship between customer concentration and enterprise innovation

Shen Lu, Li Yanling, Feng Yunhuan   

  1. Shen Lu, School of Maritime Economics and Management, Dalian Maritime University  Li Yanling, School of Maritime Economics and Management, Dalian Maritime University  Feng Yunhuan,School of Maritime Economics and Management, Dalian Maritime University
  • Online:2024-07-16 Published:2024-09-26

Abstract: Customer concentration is an important factor that affects enterprise innovation. However, there is no consensus on whether customer concentration promotes or inhibits enterprise innovation. This study employs a meta-analysis method to quantitatively integrate the existing research and clarifies the impact of customer concentration on enterprise innovation by distinguishing between innovation inputs and innovation outputs. Meanwhile, based on resource  dependence theory (RDT) and organizational learning theory (OLT), this study examines the boundary conditions under which customer concentration exerts stronger (or weaker) impacts on enterprise innovation. By re-analyzing 38 empirical studies containing 72 observations of effect sizes, this study finds that customer concentration has negative impacts on both innovation inputs and innovation outputs. In addition, the negative effect of customer concentration on innovation inputs is strengthened in small and medium-sized enterprises (SMEs) and in financially sound enterprises. Moreover, the negative impact of customer concentration on innovation outputs is stronger in mature enterprises and enterprises with better prior financial performance. Finally, the results not only reconcile the debate of the existing literature, but also deepen the understanding of the mechanisms and pathways of how customer concentration affects enterprise innovation inputs and innovation outputs.

Key words: customer concentration, enterprise innovation, resource dependence, organizational learning, knowledge search, meta-analysis