Knowledge that Transforms

Consumer reservation price is a key concept in marketing and economics. Theoretically, this concept has been instrumental in studying consumer purchase decisions,competitive pricing strategies,and welfare economics. Managerially,knowledge of consumer reservation prices is critical for implementing many pricing tactics such as bundling,tar get promotions,nonlinear pricing,and one-to-one pricing,and for assessing the impact of marketing strategy on demand. Despite the practical and theoretical importance of this concept, its measurement at the individual level in a practical setting proves elusive. We propose a conjoint-based approach to estimate consumer-level reservation prices. This approach integrates the preference estimation of traditional conjoint with the economic theory of consumer choice. This integration augments the capability of traditional conjoint such that consumers' reservation prices for a product can be derived directly from the individuallevel estimates of conjoint coefficients. With this augmentation,we can model a consumer's decision of not only which product to buy,but also whether to buy at all in a category. Thus, we can simulate simultaneously three effects that a change in price or the introduction of a new product may generate in a market: the customer switching effect,the cannibalization effect,and the market expansion effect. We show in a pilot application how this approach can aid product and pricing decisions. We also demonstrate the predictive validity of our approach using data from a commercial study of automobile batteries.

Compensation is critical in attracting and retaining information technology (IT) professionals. However, there has been very little research on IT compensation. Juxtaposing theories of compensation that focus on human capital endowments and labor market segmentation, we hypothesize multilevel and cross-level determinants of compensation. We use hierarchical linear modeling to analyze archival salary data for 1,576 IT professionals across 39 institutions. Results indicate that compensation is directly determined by human capital endowments of education and experience. Institutional differentials do not directly drive compensation, but instead moderate the relationship of human capital endowments to compensation. Large institutions pay more than small institutions to IT professionals with more education, while small institutions pay more than large institutions to IT professionals with less education. Not-for-profit institutions pay more than for-profits to IT professionals with more or IT-specific education. Further, information-intensive institutions pay more than non information-intensive institutions to IT professionals with more or IT-specific education. We interpret these results in the context of institutional rigidity, core competencies, and labor shortages in the IT labor market.

This paper examines several different policies for an inventory control problem in which the demand process is nonstationary and partially observed. The probability distribution for the demand in each period is determined by the state of a Markov chain, the core process. However, the state of this core process is not directly observed, only the actual demand is observed by the decision maker. Given this demand process, the inventory control problem is a composite-state, partially observed Markov decision process (POMDP), which is an appropriate model for a number of dynamic demand problems. In practice, managers often use certainty equivalent control (CEC) policies to solve such a problem. However, this paper presents results that demonstrate that there are other practical control policies that almost always provide much better solutions for this problem than the CEC policies commonly used in practice. The computational results also indicate how specific problem characteristics influence the performance of each of the alternative policies.

Column generation is a well-known and widely practiced technique for solving linear programs with too many variables or constraints to include in the initial formulation explicitly. Instead, the required column information is generated at each iteration of the simplex algorithm. This paper shows that, even if the number of variables is low enough for explicit inclusion in the model with the available technology, it may still be more efficient to resort to column generation for some class of problems.

The objective of this study is to examine a performance contingency effect between product competitive strategy and organization design using an archival approach. Specifically, this study examines a sample of 194 firms from 20 industries based on the data collected by Center for Advanced Purchasing Studies (CAPS) in its benchmarking surveys between 1989-1994 and links the benchmarking data to the COMPUSTAT (Standard & Poor's) financial data of these firms. The results of the study reveal a contingency relationship among product competitive strategies, purchasing design characteristics, and overall firm financial performance (return on assets). Specifically, the nature of this contingency relationship suggests that a firm's product competitive strategy must be enabled with a complementary design in purchasing management to promote firm performance. Given the growing practice of benchmarking at the functional level, this study also examines whether or not a firm achieving a congruency in product strategy and design will necessarily enjoy higher operational efficiency at the purchasing management level. The results show that this is true only under specific conditions. The implications of the preceding findings are discussed accordingly.

Prospect theory is a paradigm challenging the expected utility paradigm. One of the fundamental components of prospect theory is the S-shaped value function. The value function is mainly justified by experimental investigation of the certainty equivalents of prospects confined either to the negative or to the positive domain, but not of mixed prospects, which characterize most actual investments. We conduct an experimental study with mixed prospects, using, for the first time, recently developed investment criteria called Prospect Stochastic Dominance (PSD) and Markowitz Stochastic Dominance (MSD). We reject the S-shaped value function, showing that at least 62%–76% of the subjects cannot be characterized by such preferences. We find support for the Markowitz utility function, which is a reversed S-shaped function—exactly the opposite of the prospect theory value function. It is possible that the previous results supporting the S-shaped value function are distorted because the prospects had only positive or only negative outcomes, presenting hypothetical situations which individuals do not usually face, and which are certainly not common in financial markets.

We consider a capacitated supply system that produces a single item that is demanded by several classes of customers. Each customer class may have a different backorder cost, so stock allocation arises as a key decision problem. We model the supply system as a multi customer make-to-stock queue. Using dynamic programming, we show that the optimal allocation policy has a simple and intuitive structure. In addition, we present an efficient algorithm to compute the parameters of this optimal allocation policy. Finally, for a typical supply chain design problem, we illustrate that ignoring the stock allocation dimension—a frequently encountered simplifying assumption—can lead to incorrect managerial decisions.

Brownian motion and normal distribution have been widely used in the Black–Scholes option-pricing framework to model the return of assets. However, two puzzles emerge from many empirical investigations: the leptokurtic feature that the return distribution of assets may have a higher peak and two (asymmetric) heavier tails than those of the normal distribution, and an empirical phenomenon called “volatility smile” in option markets. To incorporate both of them and to strike a balance between reality and tractability, this paper proposes, for the purpose of option pricing, a double exponential jump-diffusion model. In particular, the model is simple enough to produce analytical solutions for a variety of option-pricing problems, including call and put options, interest rate derivatives, and path-dependent options. Equilibrium analysis and a psychological interpretation of the model are also presented.

Organ exchanges are expected to increase the utilization of living donors and to alleviate the critical shortage of organs for transplantation. The typical arrangement involves a direct exchange between two blood-type incompatible donor-candidate pairs. An alternate possibility is an indirect exchange between one such pair and the highest priority candidate on the regular waiting list for cadaveric organs. This paper focuses on the mix of direct and indirect exchanges that maximizes the expected total discounted quality-adjusted life years (QALY) of the candidates in the participating pairs. Direct exchanges are preferable because the candidate receives a living-donor organ instead of the inferior cadaveric organ an indirect exchange provides. However, the latter involves a shorter wait. To capture this tradeoff, we develop a double-ended queueing model for an exchange system with two types of donorcandidate pairs, and obtain an optimal dynamic exchange policy by invoking a Brownian approximation. The policy takes the form of a two-sided regulator in which new pairs will join the exchange system to wait for a direct exchange if and only if the process modeling the exchange system is within the regulator's two barriers. In all other circumstances, new pairs will participate in an indirect exchange. Expressions for the optimal barriers are obtained under a variety of assumptions about the objective function, including one of complete candidate autonomy. The analysis identifies three design principles that will amplify the likelihood of an exchange program's success. First, exchange programs must involve the coordinated activities of multiple local transplant centers to enjoy the substantial benefits of resource pooling. Second, participant wait must be controlled through indirect exchanges. Third, the program must respect participants' autonomy and weigh that autonomy against the broader goal of maximizing their overall welfare.

In this paper, we develop approximations that yield insight into the joint optimization of capacity and inventory,and how the optimal inventory policy varies with capacity investment in a single-product, single-station, make-to-stock manufacturing system in which inventory is managed through a base-stock policy. We allow for a correlated demand stream as we analyze our models in an asymptotic regime,in which the penalty and holding costs are small relative to the cost of capacity. Although our approximations are asymptotically correct,our Brownian approximation is accurate even under moderate traffic intensity.