Governance modes in supply chains and financial performance at buyer, supplier and dyadic levels: the positive impact of power balance

Abstract

Purpose

This study analyzes whether power in the supply chain, based on governance modes and network centrality, explain financial performance at different levels of analysis: buyers, suppliers and dyads.

Design/methodology/approach

The study employs a dual macro-micro lens based on global value chain (i.e. market, modular, relational and captive governance modes) and social network analysis (network centrality) to assess the impact of power (im)balance onto financial performance. Different from previous research, this study adopts information reliability techniques – such as information entropy – to differentiate the weights of distinct financial performance metrics in terms of the maximal entropy principle. This principle states that the probability distribution that best represents the current state of knowledge given prior data is the one with largest entropy. These weights are used in TOPSIS analysis.

Findings

Results offer insightful reflections to SCM research. We show that buyers outperform suppliers due to power asymmetry. We ground our findings both analyzing across governance modes and comparing network centrality. We show that market and modular governances (where power balance prevails) outperform relational and captive modes at the dyadic level – thus inferring that in the long run these governance modes may lead to financially healthier supply chains.

Originality/value

This study advances SCM research by exploring the impact of governance modes and network centrality on performance at both firm and dyadic levels while employing an innovative combination of secondary data and robust set of techniques including TOPSIS, WASPAS and information entropy.

Citation

Marques, L., Lontra, P., Wanke, P. and Antunes, J.J.M. (2022), "Governance modes in supply chains and financial performance at buyer, supplier and dyadic levels: the positive impact of power balance", Benchmarking: An International Journal, Vol. 29 No. 1, pp. 255-284. https://doi.org/10.1108/BIJ-03-2020-0114