Quality information disclosure and advertising strategy in a supply chain

Abstract

Existing research on advertising structures in a supply chain has mainly been conducted with symmetric quality information and the interaction between quality information disclosure and advertising has not been clarified. To identify the optimal advertising structure and disclosure strategy for a manufacturer, we explore manufacturer advertising and cooperative advertising in the context of product quality information asymmetry. We examine the implications of the manufacturer’s product quality information disclosure on his advertising strategies and the impact of advertising on quality information disclosure decisions. When cooperative advertising is more effective than manufacturer advertising and the product quality is low, the manufacturer should adopt manufacturer advertising, which leads to higher perceived quality and improves the retailer’s economic condition. We find that advertising can inspire the manufacturer to disclose more product quality information regardless of the advertising structure, which occurs when the effectiveness of advertising is large. Furthermore, the manufacturer, the retailer, and consumers can benefit from cooperative advertising when cooperative advertising is more effective than manufacturer advertising and the product quality is high. We also consider an extension where the manufacturer and retailer advertise simultaneously and find that advertising leads to more quality information being disclosed when the disclosure cost is low.

KEYWORDS:

• Supply chain
• product quality
• quality information asymmetry
• voluntary disclosure
• manufacturer advertising
• cooperative advertising

Acknowledgements

The authors gratefully acknowledge the editor and anonymous referees for their valuable comments, which helped significantly improve this paper.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The parameters we used in this paper refer to the numerical study of Huang, Chen, and Xiao (2020), Gou et al. (2020), Song et al. (2017), and Yan (2010).

Additional information

Funding

This research was supported in part by the National Natural Science Foundation of China [grant numbers 72271107, 71672071, 72001189], the Fundamental Research Funds for the Central Universities [grant number 2662021JGPYG01], Zhejiang Business Research Institute [grant number 22ZSKT02YB]. Yeming GONG was partially supported by BIC Center, AIM Institute.

Notes on contributors

Xianpei Hong

Xianpei Hong is a Professor in the College of Economics and Management, Huazhong Agricultural University, China. He received his Ph.D. degree in Business Administration from Huazhong University of Science & Technology, China. His primary research areas are supply chain management, innovation management, and decision-making problems. He has published articles in journals such as International Journal of Production Research, European Journal of Operational Research, International Journal of Production Economics, Annals of Operations Research, IEEE Transactions on Engineering Management, Transportation Research Part E: Logistics and Transportation Review.

Meiling Zhou

Meiling Zhou is currently Ph.D. candidate at College of Economics and Management, Huazhong Agricultural University, China. Her research focuses on supply chain management and innovation management.

Yeming (Yale) Gong

Yeming Gong is a Professor of Management Science at Emlyon Business School, France. He is institute head of ‘Artificial Intelligence for Management Institute’ (AIM) and director of ‘Business intelligence Center’ (BIC). He holds a Ph.D. of Management Science from Rotterdam School of Management, Erasmus University, Netherlands. He was a post-doc researcher at University of Chicago, USA. He has published two books in Erasmus and Springer, and published 90 articles in peer reviewed journals like International Journal of Production Research, Production and Operations Management, Transportation Science, European Journal of Information Systems, International Journal of Research in Marketing, European Journal of Operational Research, International Journal of Production Economics, Transportation Research (E, D), International Journal of Operations & Production Management, Journal of Business Research, Annals of Operations Research, Journal of the Operational Research Society, OMEGA, Information & Management, IISE Transactions, IEEE Transactions on Network Science and Engineering, and IEEE Transactions on Engineering Management.

Wanying Chen

Wanying Chen is an Associate Professor at Zhejiang Gongshang University, Hangzhou, China. She holds a Ph.D. and MSc from INSA de Lyon, University of Lyon, France. She was a post-doc researcher at DISP, France. She also worked in the CIRRELT, Canada, as a researcher. She published more than 10 research articles, in journals like International Journal of Production Research, Transportation Science, European Journal of Operational Research, International Journal of Production Economics, Transportation Research Part E: Logistics and Transportation Review, and Omega.