Economics of Service Operations: Information, Simplified Controls and Omnichannel Services

Ghosh, Abhishek

doi:https://doi.org/10.21985/n2-w4w2-aa04

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Economics of Service Operations: Information, Simplified Controls and Omnichannel Services

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In this dissertation we consider how simple operational levers affect a firm's revenue and consumer surplus. In particular, we focus on information disclosure as an useful control for omnichannel services.In the first chapter we consider a revenue-maximizing service firm that caters to price and delay-sensitive customers. The firm offers a menu of service grades where each grade is associated with a posted price and expected delay. An optimal menu size could be as large as the number of customer classes. However, in practice, we do observe that firms offer a handful number of service grades. We study the revenue loss when the firm offers a simplified menu with a few service grades. Our analysis utilizes a large system approximations under the assumption that the firm has ample capacity to serve the entire market. We set up an optimization model and make use of Taylor series and asymptotic arguments to obtain the revenue loss. We show that, under a simplified menu, the firm could lose a significant fraction of its revenue in the worst case scenario. This happens when there is significant heterogeneity between the customer classes in terms of their delay sensitivities and their valuation for service. In contrast, noting that customer heterogeneity may typically be less extreme, we show that the firm can in fact provide a simplified menu while providing a guarantee on worst case revenue that can be obtained as a fraction of the optimal. We characterize the worst case optimal menu and provide asymptotic bounds to the worst case revenue loss as the number of customer types grow without bound. Characterization of the firm's worst case revenue loss in terms of a measure of heterogeneity can be used to guide decision making when offering a simplified menu of service grades. In the second chapter we examine the role of information disclosure in omnichannel services. With evolving mobile technologies, an increasing number of firms are running multiple channels to serve customers. Due to the novelty of these systems, questions related to the design of such omnichannel systems and their implications for the firm and customers remain open. In particular, the question of whether or not a firm should disclose queue information to its customers in an omnichannel setting has not been extensively addressed in prior literature. Using a queuing game-theoretic framework, we address some of these open questions of design of omnichannel service system, especially focusing on the issue of congestion information disclosure and its impact on customer channel choice behavior. We benchmark the omnichannel model against a conventional single channel model, and compare these settings in terms of the firm’s throughput and average consumer surplus. We find that from the firm’s perspective there is no silver bullet; no channel arrangement delivers the highest throughput for all system parameters. From the customers’ perspective, we once again find that neither the omnichannel nor the single channel system dominates the other in terms of the average consumer surplus for both type of customers combined. The overall consumer surplus depends on the relative proportion of app users and non-app users in the system. Indeed, it is possible that both segments are worse-off when online ordering is offered. In the third chapter, we extend the omnichannel setting to a competitive environment. Increasingly many firms in the quick service industry are offering digital ordering apps to customers. While the option of app-ordering is attractive to customers, still, not all firms offer an app. Even if we ignore the upfront cost of implementation of an app, it is not clear whether offering an app necessarily leads to an increase in revenue for the firm in a competitive setting. A proper evaluation needs to take into consideration the relative capacity of the firms and the sizes of their customer bases. To this end, we examine what is the best-response for a firm when faced with a competitor who offers an app. We find that it might not always be in the firm's best interest to match its competitor in offering an app.

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