Telephone call centers are an integral part of many businesses, and their economic role is significant and growing. They are also fascinating sociotechnical systems in which the behavior of customers and employees is closely intertwined with physical performance measures. In these environments traditional operational models are of great value--and at the same time fundamentally limited--in their ability to characterize system performance.We review the state of research on telephone call centers. We begin with a tutorial on how call centers function and proceed to survey academic research devoted to the management of their operations. We then outline important problems that have not been addressed and identify promising directions for future research.

/pdf/commissioned-paper-telephone-call-centers-tutorial-review-3kz951v5q4.pdf

Commissioned Paper: Telephone Call Centers: Tutorial, Review, and Research Prospects

Game theory (hereafter GT) is a powerful tool for analyzing situations in which the decisions of multiple agents affect each agent’s payoff. As such, GT deals with interactive optimization problems. While many economists in the past few centuries have worked on what can be considered game-theoretic models, John von Neumann and Oskar Morgenstern are formally credited as the fathers of modern game theory. Their classic book “Theory of Games and Economic Behavior”, von Neumann and Morgenstern (1944), summarizes the basic concepts existing at that time. GT has since enjoyed an explosion of developments, including the concept of equilibrium by Nash (1950), games with imperfect information by Kuhn (1953), cooperative games by Aumann (1959) and Shubik (1962) and auctions by Vickrey (1961), to name just a few. Citing Shubik (2002), “In the 50s ... game theory was looked upon as a curiosum not to be taken seriously by any behavioral scientist. By the late 1980s, game theory in the new industrial organization has taken over ... game theory has proved its success in many disciplines.”

https://pubsonline.informs.org/doi/pdf/10.1287/educ.1063.0023

Game Theory in Supply Chain Analysis

Scale economies are commonplace in operations, yet because of analytical challenges, relatively little is known about how firms should compete in their presence. This paper presents a model of competition between two firms that face scale economies; (i.e., each firm's cost per unit of demand is decreasing in demand). A general framework is used, which incorporates competition between two service providers with price- and time-sensitive demand (a queuing game), and competition between two retailers with fixed-ordering costs and pricesensitive consumers (an Economic Order Quantity game). Reasonably general conditions are provided under which there exists at most one equilibrium, with both firms participating in the market. We demonstrate, in the context of the queuing game, that the lower cost firm in equilibrium may have a higher market share and a higher price, an enviable situation. We also allow each firm to outsource their production process to a supplier. Even if the supplier's technology is no better than the firms' technology and the supplier is required to establish dedicated capacity (so the supplier's scale can be no greater than either firm's scale), we show that the firms strictly prefer to outsource. We conclude that scale economies provide a strong motivation for outsourcing that has not previously been identified in the literature.

/pdf/competition-and-outsourcing-with-scale-economies-4i21xy9ue2.pdf

Competition and Outsourcing with Scale Economies

We study a manufacturer’s problem of managing his direct online sales channel together with an independently owned bricks-and-mortar retail channel, when the channels compete in service. We incorporate a detailed consumer channel choice model in which the demand faced in each channel depends on the service levels of both channels as well as the consumers’ valuation of the product and shopping experience. The direct channel’s service is measured by the delivery lead time for the product; the retail channel’s service is measured by product availability. We identify optimal dual channel strategies that depend on the channel environment described by factors such as the cost of managing a direct channel, retailer inconvenience, and some product characteristics. We also determine when the manufacturer should establish a direct channel or a retail channel if he is already selling through one of these channels. Finally, we conduct a sequence of controlled experiments with human subjects to investigate whether our model makes reasonable predictions of human behavior. We determine that the model accurately predicts the direction of changes in the subjects’ decisions, as well as their channel strategies in response to the changes in the channel environment. These observations suggest that the model can be used in designing channel strategies for an actual dual channel environment. 1

http://www.utdallas.edu/~oozer/pdf/DualChannel.pdf

Dual Sales Channel Management with Service Competition

This paper presents a current, accessible, and overarching view of work system theory. WST is the core of an integrated body of theory that emerged from a long-term research project to develop a systems analysis and design method for business professionals called the work system method (WSM). After discussing WST’s basic premises and its two central frameworks, this paper summarizes the relationship between WST and WSM. It shows how experience with early versions of WSM led to three extensions of WST that addressed limitations-inuse in one of the central frameworks in WST. After comparisons with related theories, this paper closes with an evaluation of progress to date, new directions for research related to WST, and implications for the IS discipline. The two appendices summarize the long term research from which WST emerged and use a positioning map to show how WST is related to other topics in the IS discipline.

/pdf/work-system-theory-overview-of-core-concepts-extensions-and-4o4vwbu3cb.pdf

Work System Theory: Overview of Core Concepts, Extensions, and Challenges for the Future

We investigate a simple dynamic model of firm behavior in which firms compete by investing in capacity that is used to provide a good or service to their customers. There is a fixed total market of customers whose demands for the good or service are random and who divide their patronage between the firms in each period. Periodically, the market shares of the two firms can change based on the realized level of customer service provided in the prior period. We assume that the expected level of customer service can be expressed as a function of the (per customer) capacity of the firms' service delivery systems, and that service declines as the capacity decreases. The firms differ in their customers' willingness to defect when confronted by service failure. The primary issue we address is the firms' capacity decisions in response to customer service concerns and competitive pressure. We provide conditions under which the firms' optimal (i.e., equilibrium) capacity levels in a period are proportional to the size of their respective customer bases in that period. Further, we develop expressions for the value of a firm's customers and the implicit cost of service failure. Results for both single-period and finite-horizon problems are investigated and applied to two examples: (1) competition between Internet service providers who operate systems that we approximate by simple loss-type queueing models, and (2) competition between make-to-stock producers who operate systems that we approximate by newsvendor inventory models. For both examples, solutions are derived and interpreted.

Customer Service Competition in Capacitated Systems

The modern mania for process standardization overlooks one important fact: Many processes are more art than science. And when managers try to rigidly control art, they end up squashing flexibility, creativity, and dynamism.

When Should a Process Be Art

This paper provides a framework for retailer pricing and ordering decisions in a dynamic category management setting. In this regard, the key contributions of this paper are as follows. First, we develop a multi-brand ordering and pricing model that endogenizes retailer forward buying and maximizes proﬁtability for the category. The model considers (i) manufacturer trade deals to retailers, (ii) ordering costs incurred by the retailer, (iii) retailer forward buying behavior, and (iv) both own- and cross-price effects of all the brands in the category. Second, we use this model to compare differences in ordering and pricing decisions, and in proﬁts, resulting from using a category management versus a brand-by-brand management approach. Our approach allows us to derive implications in a dynamic setting about the impact of interdependence among the brands upon decisions on pass-through of trade deals and retailer order quantity. We show that category management results in noticeably higher proﬁts versus brand-by-brand and cost-plus (markup) approaches. Further, our results suggest an interaction between a brand’s own-price effect and its cross-price effect emerges. If the cross-price effect for a brand is low – that is, the brand takes away relatively few sales from the other brands – the retail pass-through should increase with that brand’s own-price effect. On the other hand, when the cross-price effect is high, the retail pass-through decreases with the brand’s own-price effect.

https://papers.ssrn.com/sol3/Delivery.cfm/SSRN_ID2552122_code579161.pdf?abstractid=2552122&mirid=2

Retailers' Dynamic Pricing and Ordering Decisions: Category Management Versus Brand-by-Brand Approaches

Retailer Dynamic Pricing and Ordering Decisions: Category Management versus Brand-by-Brand Approaches

Recent years have seen advances in research and management practice in the area of pricing, and particularly in dynamic pricing and revenue management. At the same time, researchers and managers have made dramatic improvements in production and supply chain management. The interactions between pricing and production/supply chain performance, however, are not as well understood. Can a firm benefit from knowing the status of the supply chain or production facility when making pricing decisions? How much can be gained if pricing decisions explicitly and optimally account for this status? This paper addresses these questions by examining a make-to-order manufacturer that serves two customer classes - core customers who pay a fixed negotiated price and are guaranteed job acceptance, and "fill-in" customers who make job submittal decisions based on the instantaneous price set by the firm for such orders. We examine four pricing policies that span a range of complexity and required knowledge about the status of the production system at the manufacturer, including the optimal policy of setting a different price for each possible state of the queue. We demonstrate properties of the optimal policy, and we illustrate numerically the financial gains a firm can achieve by following this policy vs. simpler pricing policies. The four policies we consider are (1) state-independent (static) pricing, (2) allowing fill-in orders only when the system is idle, (3) setting a uniform price up to a cut-off state, and (4) general state-dependent pricing. Although general state-dependent pricing is optimal in this setting, we find that charging a uniform price up to a cut-off state performs quite well in many settings and presents an attractive trade-off between ease of implementation and profitability. Thus, a fairly simple heuristic policy may actually out-perform the optimal policy when costs of design and implementation are taken into account.

/pdf/static-and-dynamic-pricing-of-excess-capacity-in-a-make-to-4p2kcdycf6.pdf

Joseph M. Hall

Papers

Customer Service Competition in Capacitated Systems

When Should a Process Be Art

Retailers' Dynamic Pricing and Ordering Decisions: Category Management Versus Brand-by-Brand Approaches

Retailer Dynamic Pricing and Ordering Decisions: Category Management versus Brand-by-Brand Approaches

Static and Dynamic Pricing of Excess Capacity in a Make-to-Order Environment