Manufacturing & Service Operations Management current issue

Introduction to the Special Issue on Behavioral Operations

Gans, N., Croson, R. — 2008-10-01

The observed behavior of customers and managers often does not fit the assumptions of theoretical models used in the operations management (OM) literature. New research in behavioral OM is emerging to bridge the gap between traditional models and these newer observational findings. This work is both deductive and inductive, and it draws on multiple reference disciplines: experimental and behavioral economics, judgment and decision making from psychology, and organizational behavior and decision analysis from management. This special issue presents seven interesting papers that reflect the wide range of current research activity in behavioral OM. These papers provide insightful and thought-provoking introduction to this new direction in OM research.

Bounded Rationality in Newsvendor Models

Su, X. — 2008-10-01

Many theoretical models adopt a normative approach and assume that decision makers are perfect optimizers. In contrast, this paper takes a descriptive approach and considers bounded rationality, in the sense that decision makers are prone to errors and biases. Our decision model builds on the quantal choice model: While the best decision need not always be made, better decisions are made more often. We apply this framework to the classic newsvendor model and characterize the ordering decisions made by a boundedly rational decision maker. We identify systematic biases and offer insight into when overordering and underordering may occur. We also investigate the impact of these biases on several other inventory settings that have traditionally been studied using the newsvendor model as a building block, such as supply chain contracting, the bullwhip effect, and inventory pooling. We find that incorporating decision noise and optimization error yields results that are consistent with some anomalies highlighted by recent experimental findings.

Newsvendor "Pull-to-Center" Effect: Adaptive Learning in a Laboratory Experiment

Bostian, A. A., Holt, C. A., Smith, A. M. — 2008-10-01

In the newsvendor game, the expected-profit-maximizing order quantity is higher in the demand interval when the per-unit profit margin is high and lower in the demand interval when the per-unit profit margin is low. However, laboratory experiments show a "pull-to-center" effect: average order quantities are too low when they should be high and vice versa. We replicate this pull-to-center effect in laboratory experiments and construct an adaptive learning model that incorporates memory, reinforcement, and probabilistic choice to explain individual decisions. The intuition underlying the model's prediction is that the most recent demand observation is more likely to have been greater than the optimal order quantity if the optimal order quantity is low, in which case a recency bias tends to pull the order quantity upward. A countervailing downward pull exists if the optimal order quantity is high. The recency effect may be augmented by a reinforcement bias, which causes subjects to focus more on the profitability of decisions they actually make and less on counterfactual payoffs that would have resulted from other order quantities. The predictions of this model track the observed data patterns across treatments. A pull-to-center pattern is also observed in designs involving doubled payoffs and reduced order frequency.

Inventory Service-Level Agreements as Coordination Mechanisms: The Effect of Review Periods

Katok, E., Thomas, D., Davis, A. — 2008-10-01

Asupplier stocking goods for delivery to a retailer may face a (finite-horizon) service-level agreement (SLA). In this context, the SLA is a commitment by a supplier to achieve a minimum fill rate over a specified time horizon. This kind of SLA is an important, but understudied coordination mechanism. We focus on the impact of two contract parameters: the length of the review period and the magnitude of the bonus for meeting or exceeding the service-level target. For a supplier following a base stock (order-up-to) inventory policy, increasing the bonus increases optimal supplier stocking levels, whereas lengthening the review period may increase or decrease optimal stocking levels. We investigate these mechanisms in a controlled laboratory setting and find that longer review periods are generally more effective than shorter review periods in inducing higher stocking levels. As in several earlier laboratory studies, the explanation lies in the improved feedback reliability that longer review periods provide. The primary managerial implication of our findings is that, in practice, longer review periods may be more effective than shorter ones at inducing service improvements.

Decision Biases in Revenue Management: Some Behavioral Evidence

Bearden, J. N., Murphy, R. O., Rapoport, A. — 2008-10-01

We study a problem of selling a fixed number of goods over a finite and known horizon. After presenting a procedure for computing optimal decision policies and some numerical results of a simple heuristic policy for the problem, we describe results from three experiments involving financially motivated subjects. The experiments reveal that decision makers employ decision policies of the same form of the optimal policy. However, they show systematic biases to demand too much when they have many units to sell and too little when they have few to sell, resulting in significant revenue losses.

A Model of Fair Process and Its Limits

Wu, Y., Loch, C. H., Heyden, L. V. d. — 2008-10-01

Fair process research has shown that people care not only about outcomes, but also about the process that produces these outcomes. For a decision process to be seen as fair, the people affected must have the opportunity to give input and possibly to influence the decision, and the decision process and rationale must be transparent and clear. Existing research has shown empirically that fair process enhances both employee motivation and performance in execution. However, work to date has not addressed why fair process is so often violated in practice. This paper breaks new ground by analytically examining the subtle trade-offs involved. We develop a model of fair process in a principal-agent (i.e., manager-employee) context, rooted in psychological preferences for autonomy and fairness. We show that indeed fair process will not always be used, and why the hoped-for benefits may be insufficient to convince management to use fair process.

Dual Sales Channel Management with Service Competition

Chen, K.-Y., Kaya, M., Ozer, O. — 2008-10-01

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

Toward a Theory of Behavioral Operations

Gino, F., Pisano, G. — 2008-10-01

Human beings are critical to the functioning of the vast majority of operating systems, influencing both the way these systems work and how they perform. Yet most formal analytical models of operations assume that the people who participate in operating systems are fully rational or at least can be induced to behave rationally. Many other disciplines, including economics, finance, and marketing, have successfully incorporated departures from this rationality assumption into their models and theories. In this paper, we argue that operations management scholars should do the same. We explore the theoretical and practical implications of incorporating behavioral and cognitive factors into models of operations management and suggest fruitful avenues for research in behavioral operations.