Wholesale Pricing or Agency Pricing on Online Retail Platforms: The Effects of Customer Loyalty

ABSTRACT

Traditionally, the online retailer has adopted the wholesale pricing model to work with heterogeneous manufacturers, that is, the retailer buys the products from the competitive manufacturers and then resells them to customers. Recently, the increasing prevalence of online retailing has given rise to a novel agency pricing model; that is, the manufacturers sell their products directly to customers on the retailer’s platform, and the retailer charges a commission fee for each sale. Meanwhile, customer loyalty is an important determinant of long-term business success for the retail platform. Considering the customer with loyalty, this paper investigates how the chosen pricing model (wholesale pricing model or agency pricing model) affects the online retailer’s profit, industry profit, consumer surplus, and social welfare. We find that the latter model always leads to a lower retail price and higher consumer surplus. More important, we also show that the industry profit and social welfare increase when the online retailer switches from the former model to the latter one. However, the online retailer’s profit critically depends on customer loyalty. Specifically, when customer loyalty is strong enough, the online retailer should adopt the agency pricing model. Otherwise, the wholesale pricing model dominates.

KEY WORDS AND PHRASES:

• Online pricing
• online retail
• customer loyalty
• online platform
• upstream competition
• agency pricing
• wholesale pricing

Acknowledgments

This research is partially supported by research grant from the National Science Foundation of China (No.71471128) and the Key Program of National Natural Science Foundation of China (No.71631003).

Additional information

Notes on contributors

Lin Chen

LIN CHEN ([email protected]) is a Ph.D. candidate in the College of Management and Economics, Tianjin University, China. His research interests include pricing of information goods and platform ecosystems, and uncertain network optimization. His recent papers have appeared in Applied Soft Computing, International Journal of Production Research, IEEE Transactions on Industrial Informatics, and Journal of Intelligent Manufacturing.

Guofang Nan

GUOFANG NAN ([email protected]; corresponding author) is a professor at the College of Management and Economics, Tianjin University. He received his Ph.D. in Management Information Systems from the College of Management and Economics, Tianjin University. His research interests are primarily in the area of economics of information systems and Internet services. His papers have appeared in Journal of Management Information Systems, Journal of the Association for Information Systems, Knowledge-Based Systems, IEEE Transactions on Industrial Informatics, IEEE Transactions on Multimedia, and other journals.

Minqiang Li

MINQIANG LI ([email protected]) is a professor in the Department of Information Management and Management Science, College of Management and Economics, Tianjin University. He received a Ph.D. in systems engineering and management science from Tianjin University. His research interests cover management science and decision support, IT strategy, e-commerce, data mining and business intelligence, and evolutionary computation. His papers have appeared in Journal of Management Information Systems, European Journal of Operational Research, IEEE Transactions on Neural Networks and Learning Systems, Information Sciences, and other venues.