bluuebunny/crossref_metadata_2025_split huggingface dataset:
Testing New Direct Marketing Offerings: The Interplay of Management Judgment and Statistical Models
Authors: Morwitz Vicki G. , Schmittlein David C. 
Published: November 2008

The launch of a new product or service via direct marketing is nearly always preceded by a test of that offering. Such a “live” test, conducted with a subset of the entire list of customer prospects, can sometimes be useful in a “go/no-go” decision regarding a full-scale launch of the offering. More commonly, the test is used to direct the offering more effectively toward the market segments that appear most promising. Specifically, test results are used and useful to determine whether a particular rental list of customer prospects should indeed be rented, and (for both rental and in-house lists) which specific customer segments should be contacted with the offering. This paper examines the effectiveness of managers' decisions related to designing a test and interpreting test results both conceptually—based on the literature of heuristics and biases in expert judgments—and empirically, for two new direct marketing offers. The paper describes how an interplay of management judgment and statistical models can lead to increased profits for new direct marketing offerings.
On the Equivalence of General and Specific Control in Organizations
Authors: Gersbach Hans 
Published: November 2008

Most principal-agent relationships in firms are multidimensional. In the presence of multiple tasks and multiple performance signals, the contract between principal and agent not only has to motivate the agent, but also has to direct the agent to allocate effort among different tasks. The value of efforts for a specific task accrues not only through the principal's expected returns, but also through its contribution to overall risk, and therefore to the risk diversification of the task portfolio. Hence, if the agent is risk-averse, multitask relationships can be considered as a portfolio problem coupled with incentive constraints. We examine the relationship between specific control (SC) and general control (GC) for multitask principal-agent problems. Under SC, the principal observes the outcome of each individual task and uses this set of information for compensation. Under GC, contracts are based only on the aggregate signal, such as cumulative profits of all tasks. We describe two sets of multitask problems for which GC and SC are equivalent. That is, contracts based only on aggregate performance signals impose the same incentives for the agent as a contract that is based on the outcome of each task. The first multitask problem is characterized by homogeneous tasks. In the second multitask problem, all activities are perfect substitutes in the cost function of the agent. The equivalence of SC and GC arises since GC provides insurance to the agent and yields the same overall risk premium as specific control. Moreover, GC allows the principal to set the same incentives as SC, since the marginal returns from GC are equal to the sum of the marginal returns for each task under SC. The results described in this paper can serve as benchmarks where GC and SC are equivalent. We show how the equivalence can be relevant for a variety of business situations, such as the compensation of sales persons or managers at all hierarchy levels. We also discuss the reasons when GC and SC differ. Suppose, for instance, that tasks are technologically separable and the precision of the performance of one task is low. Then, the principal is forced under GC to adopt an incentive scheme that implements only a low effort across all tasks since the average precision matters. Under SC, however, the principal can tailor the optimal efforts to each task.
Knowledge Acquisition from Multiple Experts: An Empirical Study
Authors: O'Leary Daniel E. 
Published: November 2008

Expert systems often employ a weight on rules to capture conditional probabilities. For example, in classic rule-based settings, Pr(h ∣ e) = x is used to mean “If e is known to be true then conclude h is true with probability x.” Further, other probability-based approaches, such as influence diagrams and Bayes' Nets are increasingly being used to support decision making through decision support systems. Although algorithms for these systems have received substantial attention, less attention has been given to knowledge acquisition of probabilities used in these systems. However, the underlying probabilities are critical because they lead the user to particular solutions. Accordingly, the purpose of this paper is to investigate the quality of probability knowledge when it is acquired from groups or individuals. This paper summarizes the results of an empirical cognitive study on the ability of individuals and groups to provide consistent sets of probabilities Pr(A), Pr(B), Pr(A ∣ B) and Pr(B ∣ A). The analysis of these probabilities allowed the study of the ability of subjects to account for Bayes' theorem reversals, a basic assumption made by virtually all algorithms. It was found that knowledge acquisition from groups provided more correct orderings to the probabilities than knowledge acquisition from individuals. This suggests that knowledge acquisition from groups is more likely to obtain correct probability knowledge.
The Quantity Flexibility Contract and Supplier-Customer Incentives
Authors: Tsay Andy A. 
Published: November 2008

Consider a supply chain consisting of two independent agents, a supplier (e.g., a manufacturer) and its customer (e.g., a retailer), the latter in turn serving an uncertain market demand. To reconcile manufacturing/procurement time lags with a need for timely response to the market, such supply chains often must commit resources to production quantities based on forecasted rather than realized demand. The customer typically provides a planning forecast of its intended purchase, which does not entail commitment. Benefiting from overproduction while not bearing the immediate costs, the customer has incentive to initially overforecast before eventually purchasing a lesser quantity. The supplier must in turn anticipate such behavior in its production quantity decision. This individually rational behavior results in an inefficient supply chain. This paper models the incentives of the two parties, identifying causes of inefficiency and suggesting remedies. Particular attention is given to the Quantity Flexibility (QF) contract, which couples the customer's commitment to purchase no less than a certain percentage below the forecast with the supplier's guarantee to deliver up to a certain percentage above. Under certain conditions, this method can allocate the costs of market demand uncertainty so as to lead the individually motivated supplier and customer to the systemwide optimal outcome. We characterize the implications of QF contracts for the behavior and performance of both parties, and the supply chain as a whole.
Flexible and Risk-Sharing Supply Contracts Under Price Uncertainty
Authors: Li Chung-Lun , Kouvelis Panos 
Published: November 2008

We study supply contracts for deterministic demand but in an environment of uncertain prices. We develop valuation methodologies for different types of supply contracts. A “time-inflexible contract” requires the firm to specify not only how many units it will purchase, but also the timing of the purchase. A “time-flexible contract” allows the firm to specify the purchase amount over a given period of time without specifying the exact time of purchase. Other than time flexibility, the suppliers may offer “quantity flexibility” to the firm as well, i.e., purchase quantities could be within a prespecified quantity window. Finally, “risk-sharing” features can be incorporated in the contract in terms of the purchase price that the firm eventually pays to a supplier. Within a prespecified price window the firm pays the realized price, but outside of it the firm shares, in an agreed way, added costs or benefits. Given the structure of a supply contract, we study the firm's decision when to purchase and how many units in each purchase such that the expected net present value of the purchase cost plus inventory holding cost is minimized. We discuss optimal purchasing strategies for both time-flexible and time-inflexible contracts with risk-sharing features. Other interesting results include the analysis of two-supplier sourcing environments and the exploitation of quantity flexibility in such contracts. Our discussion illustrates how time flexibility, quantity flexibility, supplier selection, and risk sharing, when carefully exercised can effectively reduce the sourcing cost in environments of price uncertainty.
The Use of a Neural Factory to Investigate the Effect of Product Line Width on Manufacturing Performance
Authors: Swamidass Paul M. , Nair Satish S. , Mistry Sanjay I. 
Published: November 2008

The dual goals of this study are: (1) to develop an empirically valid neural model of U.S. factories in a range of industries producing discrete products, and (2) to use the model to test the effect of changes in product line width on plant performance variables. Accordingly, a neural factory was developed using 59 input and 5 output/performance variables, and was trained using field data collected from 385 U.S. manufacturing plants. The model was validated using a holdout sample before conducting sensitivity tests. The study demonstrates that, through the use of parametric sensitivity analysis, the neural factory could be used to investigate the relationship between inputs and performance of a factory. While the focused factory principle would favor a smaller product line, economies of scope theory would favor a larger product line for the good of the factory; this implies a rather complex relationship between product line width (PLW) and plant performance. The neural factory was used to study the sensitivity of output/performance variables when product line width was varied over a range extending from 10% to 200% of the average values. The sensitivity analysis of the neural factory shows that, as the product line increases, it (1) does not affect cost-of-goods-sold (COGS), (2) decreases return on investment, (3) has a negative effect on the top management's perception of manufacturing performance, (4) increases inventory turns, and (5) increases sales per employee. The explanations for these findings show how complex and intertwined the relationships between PLW and performance variables are. They enhance our understanding of PLW and provide some new directions for future empirical research.
Price Versus Production Postponement: Capacity and Competition
Authors: Van Mieghem Jan A. , Dada Maqbool 
Published: November 2008

This article presents a comparative analysis of possible postponement strategies in a two-stage decision model where firms make three decisions: capacity investment, production (inventory) quantity, and price. Typically, investments are made while the demand curve is uncertain. The strategies differ in the timing of the operational decisions relative to the realization of uncertainty. We show how competition, uncertainty, and the timing of operational decisions influence the strategic investment decision of the firm and its value. In contrast to production postponement, price postponement makes the investment and production (inventory) decisions relatively insensitive to uncertainty. This suggests that managers can make optimal capacity decisions by deterministic reasoning if they have some price flexibility. Under price postponement, additional postponement of production has relatively small incremental value. Therefore, it may be worthwhile to consider flexible ex-post pricing before production postponement reengineering. While more postponement increases firm value, it is counterintuitive that this also makes the optimal capacity decision more sensitive to uncertainty. We highlight the different impact of more timely information, which leads to higher investment and inventories, and of reduced demand uncertainty, which decreases investment and inventories. Our analysis suggests appropriateness conditions for simple make-to-stock and make-to-order strategies. We also present technical sufficiency and uniqueness conditions. Under price postponement, these results extend to oligopolistic and perfect competition for which pure equilibria are derived. Interestingly, the relative value of operational postponement techniques seems to increase as the industry becomes more competitive.
A Punctuated-Equilibrium Model of Technology Diffusion
Authors: Loch Christoph H. , Huberman Bernardo A. 
Published: November 2008

We present an evolutionary model of technology diffusion in which an old and a new technology are available, both of which improve their performance incrementally over time. Technology adopters make repeated choices between the established and the new technology based on their perceived performance, which is subject to uncertainty. Both technologies exhibit positive externalities, or performance benefits from others using the same technology.We find that the superior technology will not necessarily be broadly adopted by the population. Externalities cause two stable usage equilibria to exist, one with the old technology being the standard and the other with the new technology the standard. Punctuations, or sudden shifts, in these equilibria determine the patterns of technology diffusion. The time for an equilibrium punctuation depends on the rate of incremental improvement of both technologies, and on the system’s resistance to switching between equilibria. If the new technology has a higher rate of incremental improvement, it is adopted faster, and adoption may precede performance parity if the system’s resistance to switching is low. Adoption of the new technology may trail performance parity if the system’s resistance to switching is high.
Variety Seeking, Purchase Timing, and the “Lightning Bolt” Brand Choice Model
Authors: Chintagunta Pradeep K. 
Published: November 2008

The “Lightning Bolt” (LB) model provides a comprehensive framework for accommodating the effects of habit persistence, unobserved heterogeneity, and state dependence on household brand choice behavior. This paper presents a discrete, dynamic brand-choice model that belongs to the LB class of models. We propose a method for incorporating the effects of variety seeking into the LB model formulation. The proposed formulation explicitly links brand choice and purchase timing behavior via the effect of state dependence. This state-dependence based linkage between brand choice and purchase timing comes about due to the attribute satiation notion associated with household variety seeking behavior. Empirical implementation of the model specification requires recognizing that interpurchase times, like brand choices, also depend upon marketing variables and household characteristics. A hazard model is specified to capture this relationship. Empirical results are presented using household-level data for two different products. Our results reveal the following. (1) State dependence effects decline over time. Hence, households' brand switching and repeat purchase probabilities vary over time, independent of any variation in marketing mix activities. (2) Accounting for the effects of marketing variables on interpurchase times may be important when empirically estimating the proposed model. While the nature of substantive implications is largely unchanged, the magnitudes of the different effects are nevertheless affected. (3) We find evidence for purchase reinforcement (and its effects declining over time), but no evidence for attribute satiation based variety seeking behavior. (4) A comparison of the model's predictive ability with those from two extant specifications reveals that the proposed model outperforms rival specifications.
Solving Semi-Markov Decision Problems Using Average Reward Reinforcement Learning
Authors: Das Tapas K. , Gosavi Abhijit , Mahadevan Sridhar , Marchalleck Nicholas 
Published: November 2008

A large class of problems of sequential decision making under uncertainty, of which the underlying probability structure is a Markov process, can be modeled as stochastic dynamic programs (referred to, in general, as Markov decision problems or MDPs). However, the computational complexity of the classical MDP algorithms, such as value iteration and policy iteration, is prohibitive and can grow intractably with the size of the problem and its related data. Furthermore, these techniques require for each action the one step transition probability and reward matrices, and obtaining these is often unrealistic for large and complex systems. Recently, there has been much interest in a simulation-based stochastic approximation framework called reinforcement learning (RL), for computing near optimal policies for MDPs. RL has been successfully applied to very large problems, such as elevator scheduling, and dynamic channel allocation of cellular telephone systems. In this paper, we extend RL to a more general class of decision tasks that are referred to as semi-Markov decision problems (SMDPs). In particular, we focus on SMDPs under the average-reward criterion. We present a new model-free RL algorithm called SMART (Semi-Markov Average Reward Technique). We present a detailed study of this algorithm on a combinatorially large problem of determining the optimal preventive maintenance schedule of a production inventory system. Numerical results from both the theoretical model and the RL algorithm are presented and compared.
Batch Construction Heuristics and Storage Assignment Strategies for Walk/Ride and Pick Systems
Authors: Ruben Robert A. , Jacobs F. Robert 
Published: November 2008

The retrieval of items from storage is a chore faced by virtually every business concern. Walk/ride and pick systems are a popular method for performing this chore in many applications. When retrieval requests consist of multiple items, order pickers must travel to numerous storage locations to complete each order. When these requests are made in sufficient volume, a method of order retrieval known as batch picking is often used. Batch picking is a popular approach in the mail-order industry and is employed in industrial settings such as tool cribs and in warehouses, which service assembly line operations. Batch construction heuristics are developed and tested under three strategies for assigning storage space to individual items that have been suggested in the literature. Our results are derived from the simulation of a single hypothetical warehouse model. Specifically, we employ a model that is square in travel distance and assume the walk and pick method of order retrieval with sequential one-way travel. Sensitivity analysis is performed on workforce level and batch size. Our results indicate that the methods used for constructing batches of orders and for assigning storage space to individual items can significantly impact order retrieval efforts in warehouses of this type.
Cross-Utilization of Workers Whose Capabilities Differ
Authors: Campbell Gerard M. 
Published: November 2008

This paper develops a model for allocating cross-trained workers at the beginning of a shift in a multidepartment service environment. It assumes departments are trying to maximize objective functions that are concave with respect to the number of workers assigned. Worker capabilities are described by parameters that range from zero to one, with fractional values representing workers who are less than fully qualified. The nonlinear programming model presented is a variant of the generalized assignment problem. The model is used in a series of experiments to investigate the value of cross-utilization as a function of factors such as demand variability and levels of cross-training. Results show that the benefits of cross-utilization can be substantial, and in many cases a small degree of cross-training can capture most of the benefits. Beyond a certain amount additional cross-training adds little additional value, and the preferred amount depends heavily on the level of demand variability.
Coordinating Investment, Production, and Subcontracting
Authors: Van Mieghem Jan A. 
Published: November 2008

We value the option of subcontracting to improve financial performance and system coordination by analyzing a competitive stochastic investment game with recourse. The manufacturer and subcontractor decide separately on their capacity investment levels. Then demand uncertainty is resolved and both parties have the option to subcontract when deciding on their production and sales. We analyze and present outsourcing conditions for three contract types: (1) price-only contractswhere an ex-ante transfer price is set for each unit supplied by the subcontractor; (2) incomplete contracts, where both parties negotiate over the subcontracting transfer; and (3) state-dependentprice-only and incomplete contracts for which we show an equivalence result. While subcontracting with these three contract types can coordinate productiondecisions in the supply system, only state-dependent contracts can eliminate all decentralization costs and coordinate capacity investmentdecisions. The minimally sufficient price-only contract that coordinates our supply chain specifies transfer prices for a small number (6 in our model) of contingent scenarios. Our game-theoretic model allows the analysis of the role of transfer prices and of the bargaining power of buyer and supplier. We find that sometimes firms may be better off leaving some contract parameters unspecified ex-ante and agreeing to negotiate ex-post. Also, a price-focused strategy for managing subcontractors can backfire because a lower transfer price may decrease the manufacturer's profit. Finally, as with financial options, the option value of subcontracting increases as markets are more volatile or more negatively correlated.
On the Translocation of Masses
Authors: Kantorovitch L. 
Published: November 2008

The following paper is reproduced from a Russian journal of the character of our own Proceedings of the National Academy of Sciences, Comptes Rendus (Doklady) de I'Académie des Sciences de I'URSS, 1942, Volume XXXVII, No. 7–8. The author is one of the most distinguished of Russian mathematicians. He has made very important contributions in pure mathematics in the theory of functional analysis, and has made equally important contributions to applied mathematics in numerical analysis and the theory and practice of computation. Although his exposition in this paper is quite terse and couched in mathematical language which may be difficult for some readers of Management Science to follow, it is thought that this presentation will: (1) make available to American readers generally an important work in the field of linear programming, (2) provide an indication of the type of analytic work which has been done and is being done in connection with rational planning in Russia, (3) through the specific examples mentioned indicate the types of interpretation which the Russians have made of the abstract mathematics (for example, the potential and field interpretations adduced in this country recently by W. Prager were anticipated in this paper). It is to be noted, however, that the problem of determining an effective method of actually acquiring the solution to a specific problem is not solved in this paper. In the category of development of such methods we seem to be, currently, ahead of the Russians.—A. Charnes, Northwestern Technological Institute and The Transportation Center.