Rebate incentive strategy for online reviews
Abstract
Purpose
We attempt to analyze the impact of retailer’s rebate strategy on consumer reviews and retailer’s profits.
Design/methodology/approach
Retailers' rebates have a chance to affect sales and their profits by encouraging customers to submit product reviews. To investigate the impact of retailer’s rebate strategy on consumer reviews and retailer’s profits, we describe the consumer’s utility function and the number of consumer-written reviews by introducing the concepts of product demand mismatch and consumer review effort, then develop a two-stage model of the retailer’s rebate strategy and examine how the retailer’s rebate affects online reviews, the consumer’s perceived utility and the retailer’s profit. Finally, a number case verifies the validity and rationality of the proposed model.
Findings
The results show that the rebate strategy can effectively reduce consumer dissatisfaction caused by excessive product demand mismatch, improve the consumer utility, prompt more positive comments, and thus increase product sales.
Originality/value
In this paper, we focus on the impact of retailers' rebate strategy on consumer purchase decisions. The research can accurately reflect the influence of online reviews on consumers and retailers, assisting merchants in making the best selections. The analysis indicates that the retailer’s rebate strategy can have a direct impact on consumers' evaluation choices and product sales.
Keywords
Acknowledgements
This work is partially funded by the National Natural Science Foundation of China (71503103; 72372059); National Social Science Foundation of China (19FGLB031; 22AJL002); Outstanding Youth in Social Sciences of Jiangsu Province; Qinglan Project of Jiangsu Province and National Vocational Education Innovation Team Building System Research Project (TX20200801); Humanities and Social Sciences of Education Ministry (17YJC630224); Engineering Research Center of Integration and Application of Digital Learning Technology, Ministry of Education (1321005) and the Tender Project from Wuxi Federation of Philosophy and Social Sciences (WXSK24-A-05). Even so, this work does not involve any conflict of interest.
Citation
Zhao, H.-h., Liu, Y. and Ren, W.-w. (2024), "Rebate incentive strategy for online reviews", Marketing Intelligence & Planning, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/MIP-07-2023-0367
Publisher
:Emerald Publishing Limited
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