Trade credit in emerging economies: an interorganizational power perspective
Industrial Management & Data Systems
ISSN: 0263-5577
Article publication date: 28 March 2020
Issue publication date: 1 April 2020
Abstract
Purpose
The extant literature recognizes that trade credit is influenced by the power imbalance between buyers and suppliers but most studies focus on either buyer power or supplier power. The purpose of this study is to investigate how buyer power and supplier power interact and jointly influence trade credit. Moreover, this study examines the moderating effects of political ties in an emerging economy context.
Design/methodology/approach
A research framework was developed by combining resource dependence theory and institutional theory to investigate the interactive effects of market power (i.e. market share and supplier concentration) and non-market power (i.e. political ties) on trade credit. The proposed hypotheses were empirically tested by a fixed effects model using secondary data from 2,433 listed firms in China.
Findings
The results show that a buyer firm's market share promotes trade credit but this effect is weakened by supplier concentration. Moreover, the buyer's political ties enhance the impact of market share on trade credit and attenuate the negative moderating effect of supplier concentration.
Originality/value
This study contributes to the trade credit and supply chain power literature by identifying the interactive effects of market share, supplier concentration and political ties in trade credit. It advances our understanding of how trade credit is jointly determined by a variety of factors in emerging economies.
Keywords
Acknowledgements
This work was supported by the National Social Science Foundation of China under Grant No. 18BJY232, National Natural Science Foundation of China under Grant No. 71472166 and 71821002, and China Scholarship Council.
Citation
Liu, B., Wang, Y. and Shou, Y. (2020), "Trade credit in emerging economies: an interorganizational power perspective", Industrial Management & Data Systems, Vol. 120 No. 4, pp. 768-783. https://doi.org/10.1108/IMDS-05-2019-0292
Publisher
:Emerald Publishing Limited
Copyright © 2020, Emerald Publishing Limited