| Author: | Zhao, Xue |
| Title: | The impact of social influence on retail operations |
| Advisors: | Xiao, Guang (LMS) Guo, Pengfei (LMS) |
| Degree: | Ph.D. |
| Year: | 2024 |
| Subject: | Retail trade -- Management Teleshopping Consumer behavior Consumers -- Psychology Social influence Hong Kong Polytechnic University -- Dissertations |
| Department: | Department of Logistics and Maritime Studies |
| Pages: | xv, 148 pages : color illustrations |
| Language: | English |
| Abstract: | Consumers are influenced by the purchasing behavior of others, which can have a positive or negative impact on their own willingness to pay. Social influence plays a critical role in shaping consumer behavior, which can ultimately impact firms’ operational strategies. Therefore, we conducted two studies to examine the impact of social influence on retail operations. The first study examines how social influence affects the competitive strategies of brick-and-mortar and online channels. Unlike online channels, traditional brick-and-mortar channels usually suffer from congestion, which reduces consumers’ utility when too many individuals shop in the same brick-and-mortar store simultaneously, resulting in a negative social network effect (NSNE). In this paper, we study price competition between a brick-and-mortar channel and an online channel, in which only the former experiences NSNE. We investigate the impacts of NSNE on the two channels’ pricing decisions and profits. Our findings reveal that when NSNE is weak, it leads to higher prices for both channels in a competitive market. Although directly hurting the demand for the brick-and-mortar channel, a stronger NSNE tends to benefit both channels, resulting in a win-win scenario. When the strength of NSNE increases to the point that two channels exactly fully cover the market, a continuum of equilibria can be formed. Our analysis of the bounds of these equilibria indicates that a stronger NSNE tends to lower the prices of both channels. In this case, the brick-and-mortar channel suffers due to demand loss, whereas the online channel obtains a higher profit since more consumers switch from offline to online. When the strength of NSNE becomes extremely high, the brick-and-mortar channel and the online channel act as local monopolists, with the former being hurt by a stronger NSNE whereas the latter is not affected. We further conduct several model extensions, including asymmetric levels of social network effect and consumer heterogeneity in accessing online channels, to both confirm the robustness of our key results and derive additional insights. Our findings could offer unique insights to understand competing channels’ pricing behaviors in various business contexts exhibiting NSNE. The second study delves into the impact of social influence on livestream shopping and strategies for managing associated returns. Livestream shopping creates an immersive and interactive environment where consumers are susceptible to influence from fellow buyers, leading to impulsive consumption and potential returns. This study aims to explore methods for effectively handling returns associated with social influence: one, retailers can impose a penalty fee (deducted from the commission) on returned products to shape the influencer’s behavior, impacting initial demand and returns; and two, retailers can restrict the quantity of products supplied to the influencer, reducing both demands and returns. The study investigates how penalty fees and quantity decisions affect the influencer’s selling efforts, initial demand, returns, and ultimately, the profits of both the retailer and the influencer. Our main results are as follows. First, a higher penalty fee for returns leads the influencer to exert either more or less effort in selling products, revealing two return control mechanisms: reducing returns by enhancing consumer’s utility (i.e., exerting a high effort) or reducing returns by reducing demand (i.e., exerting a low effort). We provide specific conditions for each mechanism. Second, the retailer’s profit follows a non-monotonic trend with the penalty fee, as a higher penalty fee may discourage the influencer, resulting in lower initial demand and negative consequences for the retailer. The impact of the penalty fee on the influencer varies based on whether the product quantity is exogenously given or endogenously decided. When the product quantity is exogenous, the influencer consistently prefers a lower penalty fee. However, with endogenous product quantity, the influencer’s profit exhibits a non-monotonic pattern with the penalty fee, as a higher penalty induces the retailer to supply more, consequently boosting the influencer’s income. Thirdly, a larger product quantity consistently motivates the influencer to exert more effort. Nonetheless, the retailer may not desire a high sales volume when factoring in potential returns. We present four distinct closed-form optimal quantities that the retailer should offer for sale during the livestream shopping event. These quantities vary based on the strength of social network effects, the cost of handling returns, and the level of the penalty fee. |
| Rights: | All rights reserved |
| Access: | open access |
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