Service Systems with Experience‐Based Anecdotal Reasoning Customers

Huang, Tingliang; Chen, Ying‐Ju

doi:10.1111/poms.12298

Cited by 56 publications

(33 citation statements)

References 33 publications

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“…Using our general but intuitive approach, we calibrate the impact of information revelation on the performance of the queueing system, without any restrictions on the distribution of the initial customer beliefs. We can apply the results from our general model on belief structures that may emerge from specific behaviors such as Quantal-response based bounded rationality (Luce (1959), Su (2008), Huang et al (2013), out-of-queue learning through sampling from past experiences (Xu et al 2007), anecdotal reasoning (Huang and Chen 2014) and other cognitive biases to characterize their effects on revenues and consumer welfare.…”

Section: Conclusion and Future Researchmentioning

confidence: 99%

Blind Queues: The Impact of Consumer Beliefs on Revenues and Congestion

Cui

Veeraraghavan

2016

Management Science

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In many service settings, customers have to join the queue without being fully aware of the parameters of the service provider (for e.g., customers at check-out counters may not know the true service rate prior to joining). In such "blind queues", customers make their joining/balking decisions based on the limited information about the service provider's operational parameters (from past service experiences, reviews, etc.), and queue lengths. We analyze a firm serving customers making decisions under arbitrary beliefs about the service parameters in an observable queue for a service with known price.We propose an ordering for the balking threshold distributions in customer population, which allows for comparing the effects of customer beliefs on the queue. We show that while revealing the service information to customers improves revenues under certain conditions, it may however destroy consumer welfare or social welfare. Given a market size, the consumer welfare can be significantly reduced when a fast server announces its true service parameter. When revenue is higher under some beliefs, one would expect the congestion to also be higher because more customers join, but we show the congestion may not necessarily increase.

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Section: Conclusion and Future Researchmentioning

confidence: 99%

Blind Queues: The Impact of Consumer Beliefs on Revenues and Congestion

Cui

Veeraraghavan

2016

Management Science

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“…On the other extreme, customers are fully irrational and join or balk with equal probability. Along similar lines, Huang and Chen (2015) and Ren et al (2018) assume customers resort to a heuristic, which involves sampling experiences of previous customers (referred to as anecdotal reasoning). In our model based on rational inattention, customers can also make mistakes.…”

Section: Literature Reviewmentioning

confidence: 99%

Opaque Queues: Service Systems with Rationally Inattentive Customers

Canyakmaz

Boyacı

2018

SSRN Journal

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte.Classical models of service systems with rational and strategic customers assume queues to be either fully visible or invisible. In practice, however, most queues are only partially visible or opaque, in the sense that customers are not able to discern precise queue length upon arrival. This is because assessing queue length and associated delays require time, attention, and cognitive capacity which are all limited. Service rms may inuence this information acquisition process through their choices of physical infrastructure and technology.In this paper, we study rational queueing behavior when customers have limited time and attention. Following the theory of rational inattention, customers optimally select the type and amount of information to acquire and ignore any information that is not worth obtaining, trading o the benets of information against its costs before deciding to join. We establish the existence and uniqueness of a customer equilibrium and delineate the impact of information costs. We show that although limited attention is advantageous for a rm in a congested system that customers value highly, it can be detrimental for less popular services that customers deem unrewarding. These insights remain valid when the rm optimally selects the price. We also discuss social welfare implications and provide prescriptive insights regarding information provision. Our framework naturally bridges visible and invisible queues, and can be extended to analyze richer customer behavior and complex queue structures, rendering it a valuable tool for service design.

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“…This fits a setting in which new customers can learn about service quality from old customers who experienced the service during the last period. Huang and Chen () call this type of customer the experience‐based anecdotal reasoning customer. In this section, we assume that customers in period

n

can learn their perceived utilities from the actual arrivals in period

(n - 1)

.…”

Section: A Dynamic Evolution Systemmentioning

confidence: 99%

“…A group of studies examine customer herding behavior caused by limited information on service quality; see Afèche, Baron, and Kerner (2013), Cui and Veeraraghavan (2016), Debo and Veeraraghavan (2014) and Kremer and Debo (2015). Another group of works studies customers' decisions using anecdotal reasoning; that is, given a limited sample size, customers make purchase decisions by following others' experience (Huang & Chen, 2015;Huang & Liu, 2015).…”

Section: Introductionmentioning

confidence: 99%

Price and capacity decisions of service systems with boundedly rational customers

Guo

Lian³

2017

Naval Research Logistics

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We consider price and capacity decisions for a profit‐maximizing service provider in a single server queueing system, in which customers are boundedly rational and decide whether to join the service according to a multinomial logit model. We find two potential price‐capacity pair solutions for the first‐order condition of the profit‐maximizing problem. Profit is maximized at the solution with a larger capacity, but minimized at the smaller one. We then consider a dynamically adjusting capacity system to mimic a real‐life situation and find that the maximum can be reached only when the initial service rate is larger than a certain threshold; otherwise, the system capacity and demand shrink to zero. We also find that a higher level of customers’ bounded rationality does not necessarily benefit a firm, nor does it necessarily allow service to be sustained. We extend our analysis to a setting in which customers’ bounded rationality level is related to historical demand and find that such a setting makes service easier to sustain. Finally we find that bounded rationality always harms social welfare.

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Service Systems with Experience‐Based Anecdotal Reasoning Customers

Cited by 56 publications

References 33 publications

Blind Queues: The Impact of Consumer Beliefs on Revenues and Congestion

Blind Queues: The Impact of Consumer Beliefs on Revenues and Congestion

Opaque Queues: Service Systems with Rationally Inattentive Customers

Price and capacity decisions of service systems with boundedly rational customers

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