Pricing Strategies under Behavioral Observational Learning in Social Networks

Qiu, Liangfei; Whinston, Andrew B.

doi:10.1111/poms.12693

Cited by 57 publications

(33 citation statements)

References 88 publications

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“…Studies in this group primarily investigate consumer and seller behavior under various pricing strategies (Ovchinnikov, ; Mak, Rapoport, Gisches, & Han, ; Li & Jain, ; Özer & Zheng, ; Kremer, Mantin, & Ovchinnikov, ; Qiu & Whinston, ). Another stream of research in this group studies capacity management issues and customer behavior in terms of capacity expectations (Liu & Ryzin, ), retention decisions (Ovchinnikov, Boulu‐Reshef, & Pfeifer, ), and change of buying behavior using different incentives (Liu & Ryzin, ).…”

Section: Literature Classification Based On Operations Contextsmentioning

confidence: 99%

Behavioral Operations and Supply Chain Management–A Review and Literature Mapping

et al. 2019

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Behavioral operations research has proliferated greatly over the decade since its first formal review in 2006. The growth of the field warrants an objective mapping of contributions to the literature and the identification of trends. We conduct a systematic review of the literature of behavioral operations and supply chain management (BOSCM) across eight key operations and supply chain management journals, with publication dates through the end of June 2018. Collected articles are categorized into 12 operations contexts as well as emerging topic considerations. Key research trends, theoretical foundations, and methodological choices are discussed in each context. The results show that supply chain management, inventory management, and procurement/auctions have been the most popular operations contexts for BOSCM researchers. The results of our co‐citation analysis shows that the fundamental research areas that have informed and shaped the field include supply chain risk management, marketing, cognitive psychology, and social psychology. Based on these findings and a survey of the most prolific authors in the field, we discuss possible avenues for future research.

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Section: Literature Classification Based On Operations Contextsmentioning

confidence: 99%

Behavioral Operations and Supply Chain Management–A Review and Literature Mapping

et al. 2019

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“…First, the unprecedented growth of social network users in the last decade has resulted in significant increases in the availability of individual specific information such as holiday pictures, mobile check-ins at restaurants, to everyday purchases (Susarla et al 2012, Bai et al 2017, Huang et al 2017, Sun et al 2017. Second, consumers shopping through social network channels are increasingly using this information in making their purchase decisions (Newberry 2016, Qiu and Whinston 2017, Li and Wu 2018, Xu and Liu 2018. These aspects motivate the overall focus of this paper: In a social network setting, how do consumers evaluate available prior information to make a product purchase decision?…”

Section: Motivation and Research Focusmentioning

confidence: 99%

“…A handful of prior studies investigate relaxing Assumption 2 from different perspectives. (Acemoglu et al 2011, Zhang et al 2015, Qiu and Whinston 2017. Our observation is that on social networks, a user has access to prior information from both friends and strangers.…”

mentioning

confidence: 99%

Multi-Dimensional Observational Learning in Social Networks: Theory and Experimental Evidence

2019

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The prevalence of consumers sharing their purchases on social media platforms (e.g., Instagram, and Pinterest) and the use of this information by potential future consumers have substantial implications for online retailing. In this study, we examine how product characteristics and the type of information provider jointly moderate the purchase decision in a social network setting. We first propose an analytical observational learning framework integrating the impact of product differentiation and social ties. Then, we use two experimental studies to validate our analytical results and provide additional insights. Our key findings are that the effect of learning from strangers is stronger for vertically differentiated products than for horizontally differentiated products. However, the effect of learning from friends does not depend on whether the underlying product is horizontally or vertically differentiated. What is more interesting is the nuanced role of social ties: For horizontally differentiated products, the effect of learning increases with the strength of social ties. In addition, "contact-based" tie strength is more important than "structurebased" tie strength in accelerating observational learning. These findings provide a motivation for online retailers to generate alternative strategies for increasing product sales through social networks. For example, online retailers offering horizontally differentiated products have strong incentives to cooperate with social media platforms (e.g., Instagram and Pinterest) in encouraging customers to share their purchase information.

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“…They find consumer surplus can decrease due to the consumer-generated quality information. Qiu and Whinston (2017) focus on the optimal operational strategies of a monopolistic firm when consumers share purchase decisions which enables behavioral observational learning in social networks. Papanastasiou and Savva (2017) finds that the presence of social learning has significant structural implications for optimal pricing policies with forward-looking consumers using a simple two-period model.…”

Section: Influence Of Social Interactions On Customers' Purchase Behamentioning

confidence: 99%

Managing Price and Service Rate in Customer-Intensive Services Under Social Interactions

Jiang

Yuan

2019

Journal of Business Economics and Management

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This paper investigates the price and service rate decisions in a customer-intensive service in an M/M/1 queue system under the influence of social interactions, where a higher value of the service is perceived if more customers purchase the service. The customer-intensive nature of the service requires a low service speed to maintain its quality, which may increase the congestion of the system. Two cases where customers are either homogeneous or heterogeneous in terms of the customer intensity are considered. It is found that social interactions can always benefit the service provider as more expected revenue can be achieved, and potential profits would be lost if the influence of social interactions is ignored. For the case with heterogeneous customers, the optimal price and service rate decisions are solved with or without considering social interaction effect. The study finds the proportions of high and low sensitive customers and the social interaction intensity are critical to the operational decisions and the market coverage strategies. These results offer a better understanding on the interplay between the quality-speed conundrum and the influence of social interactions in customers’ purchase behaviour in managing customer-intensive services.

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Pricing Strategies under Behavioral Observational Learning in Social Networks

Cited by 57 publications

References 88 publications

Behavioral Operations and Supply Chain Management–A Review and Literature Mapping

Behavioral Operations and Supply Chain Management–A Review and Literature Mapping

Multi-Dimensional Observational Learning in Social Networks: Theory and Experimental Evidence

Managing Price and Service Rate in Customer-Intensive Services Under Social Interactions

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