Elsevier

Decision Support Systems

Volume 58, February 2014, Pages 31-42
Decision Support Systems

Capacity planning and performance contracting for service facilities

https://doi.org/10.1016/j.dss.2013.01.010Get rights and content

Abstract

Market demand uncertainty and time-based competition make capacity investment and managerial incentive decisions for service facilities such as high-end diagnostic medical imaging centers, modern IT services, or contract manufacturing shops particularly challenging. These facilities compete on service quality, short queuing times and speed. Therefore, having insufficient capacity can be economically devastating for them. Given the high up-front costs involved, firms want to make sure that they neither over- nor under-invest in service capacity. These problems get exasperated by the fact that typically firms are unfamiliar with the local market conditions and do not closely observe the demand-generating efforts of the hired managers. Most prior studies of cost allocation methodologies, contract design, and service resource management tend to address these aspects of the problem separately. They ignore the interaction effects between the capacity decisions and the managerial adverse selection and moral hazard issues, which are crucial elements for successfully running services with fixed capacity, random arrivals, and stochastic service times. Our paper instead focuses on the development of an integrated-approach to the simultaneous design of efficient managerial contracts and of capacity planning for capital intensive service facilities. We derive optimal linear contracting structures under information asymmetry between the firms and management, and analyze their impact on capacity decisions, service levels, service volumes, and the allocations of costs. Surprisingly, we prove that even though a franchise (charge-back) contract induces the first-best effort from the manager, it is not always the best choice for the firms as it may lead to inferior profits for them. In fact, our results explain why a firm's eventual contract choice should be a function of its prior on the probability distribution of the local market demand. We also explain when it may be optimal (for both the firm and the manager) to charge the manager up front a fixed franchising fee that is even greater than the total costs of capacity. Our study applies to many capital-intensive and congestion-prone service systems, where the success of significant up-front capacity investments also hinges on the daily operations of those facilities run by hired managers—who typically possess specific knowledge—that gives them a significant information advantage.

Introduction

Effectively managing service centers such as call centers, computerized diagnostic imaging facilities, data centers, SaaS businesses, and telecommunication networks has always been a challenging task. Owners of the centers (firms) are responsible for investing in capacity, which is often capital intensive and involves significant up-front fixed costs for equipment, software, and installation. While high utilization is a critical profitability driver, facing uncertain market demand, firms also have to maintain an acceptable service level and relatively short waiting times in order to compete in the market successfully. Managers of these centers are often contracted to run them as profit centers. As such, they are usually responsible for directing daily activities and generating demand through additional marketing or service quality efforts. For example, we have seen that at most free-standing radiology facilities that are run by the national networks in the US (such as Insight Imaging and Radnet Inc.), the local managers are responsible for staffing, scheduling, marketing, and other demand-generating activities in their territory.

What makes the issue complicated is that managers, as the agents running the service centers, often possess private information about local market conditions, referral patterns, demographic preferences, and their own demand-generating efforts, and they may not willingly or truthfully share that information with their firms. Working with a national firm that operates high-end diagnostic medical imaging centers in various states, we had to make the correct capacity investments in each market and to obtain the true market demand information from the local managers who are typically being incentivized by the patient volume at their center. If the local managers overestimate the demand, to allow ample capacity and fast turnaround times for all exams, the firm will find itself over-investing in capacity, such as MRI, CT, or PET-CT equipment. On the other hand, if the local managers underestimate the demand, in order to have a lower ‘service quota’ in their contract, the firm will under-invest in capacity, resulting in long lines and lost profit opportunities.

In this paper, we outline the solution to this problem that has been motivated by our practical experience and by the latest research on optimal mechanism design. In our model, the manager (agent) possesses private information regarding the local market and the level of his own demand-generating effort; facing uncertain market demand and the combined agency issues, the firm has to make up-front capacity investment decisions and design incentive contracts to motive the manager to truthfully share his specific market knowledge and to exert the desired level of effort to generate demand. Several studies [4], [10], [22], [27] have pointed out that optimal mechanisms predicated by economic theory are often sophisticated and rarely used in the real world, whereas linear contracts are commonly used in practice. Our focus is on evaluating three effective linear performance-based incentive contracts under information asymmetry: a uniform contract, a variable-rate contract, and a charge-back contract. We show that the uniform contract, which offers the same contract terms regardless of market conditions, fails to elicit market information from the manager and leads to a distorted capacity investment decision. The variable-rate and charge-back (franchise) contracts, on the other hand, can successfully elicit true market information from the manager. We show that the latter even induces the first-best (full-information) effort level from the manager and hence leads to the optimal capacity investment, the same as the full-information level.

We embed a queuing model within the principal-agent framework because most service firms are constrained by a finite installed capacity, yet they have to deliver reasonably fast turnaround times when both demand and service rates could be random and outside their control in the short run. Integrating the capacity decision with the incentive contract design and the service level constraints, therefore, enables us to address a complicated and yet practical problem that has not been fully studied before. We not only derive analytical solutions for this intricate problem but also find some interesting results. For example, we show that if the firm selects the proper fixed and variable charge terms, its franchise contract can induce the first-best demand-generating effort and it will successfully elicit truthful market information from the manager; however franchise contracting fails to produce the first-best profit and it may not always be the best choice for the firm. The fixed charge term in the franchise contract is naturally associated with the classical fixed cost allocation. It has been shown in managerial accounting that firms can benefit from fixed cost allocation because the allocation may influence agents' consumption of perquisites or serve as a proxy for the difficult-to-calculate opportunity costs [28]. Overall, the accounting literature tends to emphasize the role of fixed cost allocation as an effective cost control to hold agents accountable so that they will not over-consume resources at the expense of the firm [2], [15], [27]. We extend that literature and show here in a service queuing setting firms should also use cost allocation as a way to prevent the managers from under-consuming resources. A high capacity request is associated with a high fixed charge, and the managers have a natural incentive to request low capacity when they privately observe a high-demand market. By doing so, they can shirk in their demand-generating effort and gain greater utility. But, under-consuming resources can be harmful to the firms as well, because low capacity restricts the imaging center from serving more patients, for instance, and also causes long patients' waiting times, which translate to high delay costs and potential losses in future revenue due to a degraded service-level reputation. We show that with proper fixed cost allocations firms can avoid both over-investing and under-investing in capacity.

Our work contributes to the literature in multiple ways. First, we develop and analyze a new contracting problem in a service environment in which firms compete on meeting certain response times and local managers possess valuable private information on market demand. These managers can influence market demand by exerting demand-generating effort, such as marketing promotions or by providing an outstanding customer service experience. Second, we optimally integrate firms' operations capacity decision with their incentive contract decision for a business environment with stochastic arrivals of customers and randomly distributed service times per customer. We investigate three practical mechanisms and show that two of them can successfully solicit the manager's market information. Third, we demonstrate the value of the local manager's private information and prove that the firm's optimal contract choice is a function of the market demand distribution. As expected, we show that the cost of the manager's private information is associated with market demand variance, with a higher demand variance corresponding to a higher information cost. However, the manager's market knowledge is more valuable when there is a low demand variance. Overall, this research provides guidelines for firms that deal with congestion-prone systems and sheds light on how to effectively manage service facilities with combined moral hazard and adverse selection issues.

The rest of the paper is organized as follows. We first review the relevant literature in Section 2. Then we present the model setting in Section 3 and analyze the benchmark case with full information in Section 4. In Section 5, we derive three contracts for the information asymmetry case in which the manager's effort is not observable and the manager has private information regarding local market condition. We explain why two of these contracts can effectively solicit true market information from the manager. We then analyze the firm's optimal contract choice and evaluate the factors affecting the installed capacity, the average throughput rates, and the expected waiting times in Section 6 and conclude the paper with practice guidelines for cost allocation and incentive design for service systems in Section 7.

Section snippets

Literature review

This paper is related to research that applies agency theory as well as the service resource management and accounting cost allocation literature. Prior research on IT resource management has modeled IT service centers as queuing systems and mostly focused on capacity allocation within a firm through an internal pricing scheme [6], [7], [18]. In these works, demand is exogenous and there is no agency issue. Clearly, this model setting does not apply to many modern IT service centers that

The model

Consider a service facility with random demand, such as a data center or a computerized diagnostic imaging center. We model the service center as an M/M/1 queuing system, where the arrivals of service requests are independent and follow a Poisson process with a rate of λ requests per unit time, and the service time has an exponential distribution with a service rate μ. The firm is responsible for investing in capacity, and the hired manager is responsible for managing the center's daily

Full-information case

Suppose for now the firm can perfectly observe the expected local base demand θ and the manager's effort level α. Hence the firm will determine the optimal capacity μ, the manager's effort α, and the compensation to the manager s to maximize its net benefit given by revenue minus costs of capacity and compensation to the manager, subject to the service standard (SS) constraint and the manager's individual rationality (IR) constraint. Suppose the realized expected local base demand is θi (i = l, h

Information asymmetry case

In reality, the firm often cannot directly verify the manager's effort level, which is known only to the manager. In addition, the manager often observes the realized local base demand, whereas the firm only knows its distribution. Both parties can observe the realized demand N. In this section, we analyze three contracts: a uniform contract, a variable-rate contract, and a charge-back contract. We focus on linear contracts in the form of a fixed payment (or charge) plus a per-unit payment

Contract analysis

In this section, we first illustrate the operational and financial outcomes of the center in a simple numerical example. We then analyze the results under the three contracts with information asymmetry, recommend the contract choice for the firm, and evaluate the cost and value of the manager's private information.

Conclusions

Market demand uncertainty and time-based competition, make capacity investment and managerial incentives decisions for service facilities such as high-end diagnostic medical imaging centers, modern IT services, or contract manufacturing shops particularly challenging. These facilities compete on service quality, short queuing times and speed. Therefore, having insufficient capacity can be economically devastating for them. Given the high up-front costs involved, firms want to make sure that

Yabing Jiang is Assistant Professor of Information Systems & Operations Management at the Lutgert College of Business, Florida Gulf Coast University. She holds a Ph.D. in Computers Information Systems from the William E. Simon Graduate School of Business Administration, University of Rochester. Her research interests focus on employing economic theories and methodologies to study IT-related topics such as new business models and pricing strategies in electronic commerce, incentive contracting

References (28)

  • Y. Jiang et al.

    Integrated marketing and capacity contracting for capital-intensive service systems

    Decision Support Systems

    (2011)
  • S. Baiman et al.

    Informativeness, incentive compensation and the choice of inventory buffer

    The Accounting Review

    (2010)
  • R. Balakrishnan et al.

    The role of cost allocations in the acquisition and use of common resources

    Contemporary Accounting Research

    (1993)
  • A.K. Basu et al.

    Salesforce compensation plans: an agency theoretic perspective

    Marketing Science

    (1985)
  • S. Bhattacharyya et al.

    Double-sided moral hazard and the nature of share contracts

    The Rand Journal of Economics

    (1995)
  • F. Chen

    Salesforce incentives, market information, and production/inventory planning

    Management Science

    (2005)
  • S. Dewan et al.

    User delay costs and internal pricing for a service facility

    Management Science

    (1990)
  • P.S. Giridharan et al.

    Free-access policy for internal networks

    Information Systems Research

    (1994)
  • M. Harris et al.

    Asymmetric information, incentives and intrafirm resource allocation

    Management Science

    (1982)
  • S. Hasija et al.

    Call center outsourcing contracts under information asymmetry

    Management Science

    (2008)
  • B. Holmstrom et al.

    Aggregation and linearity in the provision of intertemporal incentives

    Econometrica

    (1987)
  • A.V. Iyer et al.

    A principal-agent model for product specification and production

    Management Science

    (2005)
  • S. Kim et al.

    Reliability or inventory? Analysis of product support contracts in the defense industry

  • R. Lal et al.

    Compensation plans for single- and multi-product salesforces: an application of the Holmstrom-Milgrom model

    Management Science

    (1993)
  • Yabing Jiang is Assistant Professor of Information Systems & Operations Management at the Lutgert College of Business, Florida Gulf Coast University. She holds a Ph.D. in Computers Information Systems from the William E. Simon Graduate School of Business Administration, University of Rochester. Her research interests focus on employing economic theories and methodologies to study IT-related topics such as new business models and pricing strategies in electronic commerce, incentive contracting in service facilities, outsourcing contract design, and the role of IT in corporate governance. Her research appears in Electronic Commerce Research and Applications, the Journal of Management Information Systems, the Journal of Revenue & Pricing Management, the Information Resources Management Journal, and Information Systems Management.

    Abraham Seidmann is Xerox Professor of Computers and Information Systems and Operations Management at the William E. Simon Graduate School of Business Administration, University of Rochester. He is the author of over 100 research articles, which appear in many of the leading scientific journals, and has been the founding department editor on interdisciplinary management research and applications in Management Science for 10 years. He is also an associate or area editor for IIE Transactions, the International Journal of Flexible Manufacturing Systems, Production Planning and Controls, the Journal of Intelligent Manufacturing, the Journal of Management Information Systems, and Production and Operations Management.

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