In this paper, we examine contracts to coordinate the capacity decision of a vendor who has been hired by a client to provide call center support. We consider a variety of contracts, all based on our observations of contracts used by one large vendor. We examine the role of different contract features such as pay-per-time, pay-per-call, service-level agreements, and constraints on service rates and abandonment. We show how different combinations of these contract features enable client firms to better manage vendors when there is information asymmetry about worker productivity. In particular, we focus on how different contracts can coordinate by yielding the system-optimal capacity decision by the vendor and consider how profits are allocated between the client and the vendor.call center, outsourcing, contracts, service supply chains, staffing

Problem definition: Studies have shown that the behavior of subjects in newsvendor experiments is not consistent with expected profit maximization—an assumption that is often made in operations management literature. Although prospect theory has been established as a popular model of behavioral decision making under uncertainty, it was considered to be inconsistent with observed newsvendor behavior (in particular, the pull-to-center effect) until a recent study by Long and Nasiry [Long X, Nasiry J (2015) Prospect theory explains newsvendor behavior: The role of reference points. Management Sci. 61(12):3009–3012.] proposed a prospect theory model that is consistent with the pull-to-center effect; however, this model’s ability in representing newsvendor behavior compared to other plausible prospect theory models is unexplored in the literature. This paper takes a more comprehensive approach in building several prospect theory-based newsvendor models and evaluates their competence in representing the observed newsvendor behavior. An important feature of these models is that they are not only consistent with the pull-to-center effect, but they can also, in accordance with the findings from recent research, accommodate individual-level heterogeneity in order quantities. Academic/practical relevance: Designing effective supply chain processes and inventory systems requires that the underlying models represent the observed newsvendor behavior reasonably well, especially in settings where most decisions are made by individuals. Our paper provides a rigorous basis for choosing a model when characterizing the decision making process of a newsvendor. Moreover, our novel approach to model building and testing could serve as a template for selecting appropriate prospect theory models in contexts other than the newsvendor problem. Methodology: Motivated by different types of reference points studied in the decision theory literature, we first build several newsvendor models that can theoretically accommodate individual-level heterogeneity in order quantities. Thereafter, using a multipronged approach based on theoretical criteria, goodness of fit, and empirical validity, we evaluate these models to determine the most appropriate model. Results: The model with mean demand as the stochastic reference point consistently outperforms other models, reducing the prediction error by as much as 31% on the experimental data used for this study. Moreover, all the empirical regularities considered in our paper are consistent only with this model. This suggests that mean demand is more likely to be adopted by experimental subjects as a reference point—perhaps because of its greater salience than the other plausible reference points considered. Managerial implications: Since decisions are made predominantly by human retailers in the emerging markets, we represent their behavior by the model with mean demand as the reference point and identify settings in which they could benefit from investing in decision support systems. We also demonstrate the benefits to a supplier from approximating his retailers’ behavior with this model relative to him using the other prospect theory models considered in this paper.

This paper examines the effect of the common practice of reserving slots for urgent patients in a primary health care practice on two service quality measures: the average number of urgent patients that are not handled during normal hours (either handled as overtime, referred to other physicians, or referred to the emergency room) and the average queue of non‐urgent or routine patients. We formulate a stochastic model of appointment scheduling in a primary care practice. We conduct numerical experiments to optimize the performance of this system accounting for revenue and these two service quality measures as a function of the number of reserved slots for urgent patients. We compare traditional methods with the advanced‐access system advocated by some physicians, in which urgent slots are not reserved, and evaluate the conditions under which alternative appointment scheduling mechanisms are optimal. Finally, we demonstrate the importance of patient arrival dynamics to their relative performance finding that encouraging routine patients to call for same‐day appointments is a key ingredient for the success of advanced‐access.

W e analyze the efficacy of different asset transfer mechanisms and provide policy recommendations for the design of humanitarian supply chains. As a part of their preparedness effort, humanitarian organizations often make decisions on resource investments ex ante because doing so allows for rapid response if an adverse event occurs. However, programs typically operate under funding constraints and donor earmarks with autonomous decision-making authority resting with the local entities, which makes the design of efficient humanitarian supply chains a challenging problem. We formulate this problem in an agency setting with two independent aid programs, where different asset transfer mechanisms are considered and where investments in resources are of two types: primary resources that are needed for providing the aid and infrastructural investments that improve the operation of the aid program in using the primary resources. The primary resources are acquired from earmarked donations. We show that allowing aid programs the flexibility of transferring primary resources improves the efficiency of the system by yielding greater social welfare than when this flexibility does not exist. More importantly, we show that a central entity that can acquire primary resources from one program and sell them to the other program can further improve system efficiency by providing a mechanism that facilitates the transfer of primary resources and eliminates losses from gaming. This outcome is achieved without depriving the individual aid programs of their decision-making autonomy while maintaining the constraints under which they operate. We find that outcomes with centralized resource transfer but decentralized infrastructural investments by the aid programs are the same as with a completely centralized system (where both resource transfer and infrastructural investments are centralized).

We discuss some recent developments in smart city initiatives across the world to motivate the opportunities and challenges that such initiatives pose, and we categorize them into three themes: data access and collection, end-user utility, and economic viability of different solutions. We recognize that the academic literature that can help in addressing some of these challenges is at its nascent state and provide guidelines on how manufacturing and service operations management scholars can contribute to the global smart city movement.

We explore the procurement of influenza vaccines by a government whose objective is to minimize the expected social costs (including vaccine, vaccine administration, and influenza treatment costs) when a for-profit vaccine supplier has production yield uncertainty, private information about its productivity (adverse selection), and potentially unverifiable production effort (moral hazard). Timeliness is important-costs for both the supplier and the government procurer may increase if part of the vaccine order is delivered after a scheduled delivery date. We theoretically derive the optimal menu of output-based contracts. Next, we present a menu that is optimal within a more restricted set of practically implementable contracts, and numerically show that such a menu leads to near-optimal outcomes. Finally, we present a novel way to eliminate that information rent if the manufacturer's effort is also verifiable, a counterintuitive result because the manufacturer has private productivity information. This provides an upper bound for the government on how much it should spend to monitor the manufacturer's effort.

We analyze optimal contractual arrangements in a bilateral research and development (R&D) partnership between a risk-averse provider that conducts early-stage research followed by a regulatory verification stage and a risk-neutral client that performs late-stage development activities, including production, distribution, and marketing. The problem is formulated as a sequential investment game with the client as the principal, where the investments are observable but not verifiable. The model captures the inherent incentive alignment problems of double-sided moral hazard, risk aversion, and holdup. We compare the efficacy of milestone-based options contracts and buyout options contracts from the client's perspective and identify conditions under which they attain the first-best outcome for the client. We find that milestone-based options contracts always attain the first-best outcome for the client when the provider has some bargaining power in renegotiation and identify their applicability to different R&D partnerships. This paper was accepted by Yossi Aviv, operations management.

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