bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of Color as an Executional Cue in Advertising: They're in the Shade
Authors: Gorn Gerald J. , Chattopadhyay Amitava , Yi Tracey , Dahl Darren W.
Published: November 2008

In designing print ads, one of the decisions the advertiser must make is which color(s) to use as executional cues in the ad. Typically, color decisions are based on intuition and anecdotal evidence. To provide guidelines for these decisions, this research proposes and tests a conceptual framework linking the hue, chroma, and value of the color(s) in an ad to consumers' feelings and attitudes. In an experimental study, the three dimensions of color used in an ad are manipulated using a between-subjects design. The results support the hypotheses that ads containing colors with a higher level of value lead to greater liking for the ad, and this effect is mediated by the greater feelings of relaxation elicited by the higher value color. Feelings play an equally important role in the effect of chroma. Consistent with the hypotheses, higher levels of chroma elicit greater feelings of excitement, which in turn increase ad likeability. A follow-up study found that although managers often select higher value and higher chroma colors, in a large number of cases they do not. The findings of both studies are integrated in our discussion of the importance of value and chroma in increasing the range of options available to a manager faced with the selection of colors in an ad.
A Methodology for Evaluating Military Systems in a Counterproliferation Role
Authors: Stafira Stanley , Parnell Gregory S. , Moore James T.
Published: November 2008

This paper illustrates a methodology to evaluate how dissimilar military systems support the accomplishment of the United States' counterproliferation objectives. The key questions in evaluating counterproliferation systems are identified. By using decision analysis, an influence diagram model is developed that represents military activities in the counterproliferation process. A value model is developed that enables systems to be evaluated against common criteria. An analysis of intelligence, defensive, and offensive counterproliferation systems suggests that intelligence system improvements may provide the greatest potential to meet the United States' counterproliferation objectives. Sensitivity analysis is conducted to determine which factors in the model are most important. To demonstrate the model, nine systems from the Air Force Vulcan's Forge 1995 wargame are evaluated. This paper illustrates the value of decision analysis, and influence diagrams in particular, by involving decision makers and subject matter experts in structuring complex problems for analysis.
Reply to “Comments on ‘Fortune Favors the Prepared Firm’”
Authors: Cohen Wesley M. , Levinthal Daniel A.
Published: November 2008

Joglekar, Bohl, and Hamburg (JBH) make two basic sets of criticisms of our paper (Cohen and Levinthal [Cohen, W. M., D. A. Levinthal. 1994. Fortune favors the prepared firm. Management Sci. 40 227–251.]) in their comment. First, they object to two key elements of the model structure: the relevance of the monopoly analysis and the appropriateness of modeling competition via an entry model. Second, JBH express concern over the manner in which we have modeled the updating process. With regard to the basic model structure, we argue that the initial monopoly analysis allows us to capture some important notions regarding the path dependent nature of investment in technical capabilities. Further, the analysis of competition by an entry model does not presume that an established firm takes the initiative which is one of JBH's key objections. The structure merely implies that some firm, possibly a start-up enterprise, moves first. With regard to the concerns over the modeling of updating, we acknowledge that our notation could have been clearer in some instances but that does not negate the correctness of the analysis. Furthermore, JBH's recommendations regarding the updating process have the same qualitative properties as our own specification. Indeed, at no point in their critique do JBH ever indicate how their proposed specification would change the results of our analysis.
Meta-Analysis of the Impact of Research Methods on Findings of First-Mover Advantage
Authors: VanderWerf Pieter A. , Mahon John F.
Published: November 2008

A long-standing hypothesis is that firms that enter a market early (“first movers”) tend to have higher performance than their followers (“first-mover advantage”). Recently, researchers have begun to argue that the statistical tests that support this relationship are limited in their applicability. That is, it is suggested that because of the methods used, these tests show the relationship only for certain subsets of firms, markets, and types of performance.

We performed a meta-analysis to determine whether the findings are in fact sensitive to the methods used. We discovered that tests using market share as their performance measure were sharply and significantly more likely to find a first-mover advantage than tests using other measures (such as profitability or survival). Also significantly more likely to find an advantage were tests that sample from individually selected industries and those that include no measures of the entrants' competitive strength. Conversely, we found little evidence that “survivor bias” (the exclusion of nonsurviving entrants from the sample) affects a test's findings.

The data further suggest that tests that use none of the questioned research practices will find a first-mover advantage no more often than can be accounted for by random statistical error alone.
Analysis of a Production/Inventory System Subject to Random Disruptions
Authors: Moinzadeh Kamran , Aggarwal Prabhu
Published: November 2008

In this paper we study an unreliable bottleneck production/inventory system with a constant production and demand rate that is subject to random disruptions. We assume that the restoration times are constant, the time between breakdowns is exponential, the production setup cost and/or setup time is positive, and excess demand is backordered. We propose an (s, S) production policy for such systems and develop expressions for the operating characteristics of the system. The properties of the policy parameters that minimize the expected total cost rate are investigated and a procedure for finding their optimal values is developed. In addition, we devise and test a simple heuristic procedure for finding near optimal production policies. The results of a numerical experiment suggest that (i) setup cost reduction is more effective in reducing total operating cost when the production system is more reliable, (ii) setup cost reduction in unreliable production systems results in higher optimal safety stock level, and (iii) proper determination of the safety stock levels is extremely important in Just-in-Time systems, which are susceptible to disruptions.
Path-Dependent Options: Extending the Monte Carlo Simulation Approach
Authors: Grant Dwight , Vora Gautam , Weeks David
Published: November 2008

Monte Carlo simulation has been used to value options since Boyle's seminal paper. Monte Carlo simulation, however, has not been used to its fullest extent for option valuation because of the belief that the method is not feasible for American-style options. This paper demonstrates how to incorporate optimal early exercise in the Monte Carlo method of valuing options by linking forward-moving simulation and the backward-moving recursion of dynamic programming through an iterative search process. To demonstrate the potential of this method, we use it to value American-style options on the average price (or Asian options). The computational experience reveals a flexible valuation technique with potential for application to a range of securities and financial decision problems.
Note: Dynamic Conjectural Variations in a Lanchester Oligopoly
Authors: Erickson Gary M.
Published: November 2008

An approach based on dynamic conjectural variations is advanced for developing dynamic advertising strategies in a Lanchester oligopoly differential game. The approach allows competitors to anticipate rival reactions to market-share state variables, and maintains the computational advantage of open-loop Nash equilibrium strategies. In an empirical application to the ready-to-eat cereal industry, it is shown that advertising strategies based on dynamic conjectural variations can better explain the advertising of the cereal competitors than can open- loop advertising strategies.
Information Technology and Screen-Based Securities Trading: Pricing the Stock and Pricing the Trade
Authors: Clemons Eric K. , Weber Bruce W.
Published: November 2008

Many major stock exchanges rely on their member firms to act as dealer intermediaries, risking their own capital to trade as dealers with investor customers. A confluence of forces will dramatically alter the role of these intermediaries and the strategies available to them. Information technology is increasing the diversity of trading strategies used by investors; these impose different costs and risks upon intermediaries. Alternative electronic trading venues—off-exchange trading systems—are increasing the competition faced by established exchanges, and have been especially effective in targeting investors who impose low risks upon intermediaries. Finally, many of the automated systems developed by existing exchanges have stripped of many of the cues that have in the past been used by intermediaries to assess the riskiness of an investor's trade and to price accordingly. We believe that competitive pressure from alternative trading venues will drive exchanges to develop mechanisms to support risk-based pricing. We explore, through a stylized model of trading, how the use of risk-based pricing can preserve the established central market. This enables intermediaries to separate pricing the shares traded from pricing the services for dealing these shares, and provides low-cost execution while preserving the benefits of intermediation. Our model uses a detailed computer simulation, in which dealers interact with order flow to produce a sequence of trades, which determine market prices, which in turn influence order flow; the model enables us to calculate trading costs for different classes of investor, various other standard measures of market quality, and market maker profitability.
A Field Study of Scale Economies in Software Maintenance
Authors: Banker Rajiv D. , Slaughter Sandra A.
Published: November 2008

Software maintenance is a major concern for organizations. Productivity gains in software maintenance can enable redeployment of Information Systems resources to other activities. Thus, it is important to understand how software maintenance productivity can be improved. In this study, we investigate the relationship between project size and software maintenance productivity. We explore scale economies in software maintenance by examining a number of software enhancement projects at a large financial services organization. We use Data Envelopment Analysis (DEA) to estimate the functional relationship between maintenance inputs and outputs and employ DEA-based statistical tests to evaluate returns to scale for the projects. Our results indicate the presence of significant scale economies in software maintenance, and are robust to a number of sensitivity checks. For our sample of projects, there is the potential to reduce software maintenance costs 36% by batching smaller modification projects into larger planned releases. We conclude by rationalizing why the software managers at our research site do not take advantage of scale economies in software maintenance. Our analysis considers the opportunity costs of delaying projects to batch them into larger size projects as a potential explanation for the managers' behavior.
Perceived Risk Attitudes: Relating Risk Perception to Risky Choice
Authors: Weber Elke U. , Milliman Richard A.
Published: November 2008

This paper provides empirical evidence that distinguishes between alternative conceptualizations of the risky decision making process. Two studies investigate whether cross-situational differences in choice behavior should be interpreted in the expected utility framework as differences in risk attitude (as measured by risk-averse vs. risk-seeking utility functions) or as differences in the perception of the relative riskiness of choice alternatives as permitted by risk-return interpretations of utility functions, leaving open the possibility of stable cross-situational risk preference as a personality trait. To this end, we propose a way of assessing a person's inherent risk preference that factors out individual and situational differences in risk perception. We document that a definition of risk aversion and risk seeking as the preference for options perceived to be more risky or less risky, respectively, provides the cross-situational stability to a person's risk preference that has eluded more traditional definitions. In Experiment 1, commuters changed their preferences for trains with risky arrival times when the alternatives involved gains in commuting time rather than losses. However, changes in preference coincided with changes in the perception of the riskiness of the choice alternatives, leaving the perceived risk attitudes of a majority of commuters unchanged. Experiment 2, a stockmarket investment task, investigated changes in risk perception, information acquisition, and stock selection as a function of outcome feedback. Investors' stock selections and their perception of the risk of the same stocks were different in a series of decisions in which they lost money than in a series in which they made money. As in Experiment 1, differences in choice and in risk perception were systematically related, such that the majority of investors had the same preference for perceived risk in both series of decisions. Our results provide empirical support for the usefulness of recent risk-return conceptualizations of risky choice (Bell [Bell, D. E. 1995. Risk, return, and utility. Management Sci. 41 23–30.], Jia and Dyer [Jia, J., J. S. Dyer. 1994. A standard measure of risk and risk-value models. Working paper, University of Texas at Austin.], M. Weber and Sarin 1993).
Fleet Sizing and Empty Equipment Redistribution for Center-Terminal Transportation Networks
Authors: Du Yafeng , Hall Randolph
Published: November 2008

Fleet sizing and empty equipment redistribution are important issues in managing transportation systems. Most of the mathematical models that have been developed for these problems are complex and computationally demanding, including dynamic linear programming and stochastic/dynamic mathematical programs. Our research takes an alternate approach by building from inventory theory and developing decentralized stock control policies for empty equipment. This approach is applied to hub-and-spoke networks (i.e., center-terminal networks), by first analytically modeling the stochastic processes representing various stock-control variables, and then comparing the analytical results to monte-carlo simulations. A decomposition approach is also developed to determine stock-out probabilities as a function of the fleet size as a whole, and as a function of localized control parameters.
An Inventory Model Embedded in Designing a Supply Contract
Authors: Henig Mordechai , Gerchak Yigal , Ernst Ricardo , Pyke David F.
Published: November 2008

To reduce lead-time and its variability, modern supply and transportation contracts often specify the frequency of, and volume available for, future deliveries in advance even when final demand is somewhat uncertain (Yano and Gerchak [Yano, C. A., Y. Gerchak. 1989. Transportation contracts and safety stocks for just-in-time deliveries. Manufacturing and Oper. Management 2 314–330.]). We explore the joint optimization of contract parameters and inventory control policy in such environments. We first model and derive the optimal periodic review inventory policy corresponding to a given supply contract, which generates piecewise-linear convex ordering costs. The optimal policy has two critical levels, and there is a range of stock levels for which the quantity ordered equals the contract volume. To numerically compute the critical levels, we model consecutive inventory levels as a Markov Chain, whose steady-state distribution is used to compute the holding, shortage and transportation costs. We then use the resulting total costs to derive the optimal contract volume. Various examples are provided. The optimal contracted delivery frequency can also be computed.
On the Relative Importance of Duration Constraints
Authors: Paroush Jacob , Prisman Eliezer Z.
Published: November 2008

This paper uncovers an implicit assumption, and its implications, made in the process of maximizing yield (or minimizing costs) subject to the duration constraints. Using linear programming results, it is shown that this technique is sensible only if the yield of a bond is a linear function of its duration measures. Utilizing this result the paper analyzes the relative importance of the duration constraints. Former studies have hinted that the first order duration may be the most important. It is shown here there is no reason to satisfy the first duration constraint with priority over satisfaction of a higher order duration constraint. Practitioners who use duration techniques for portfolio immunization must be aware of such an important counter-intuitive result.
Static and Dynamic Time-Space Strategic Models and Algorithms for Multilevel Rail-Car Fleet Management
Authors: Sherali Hanif D. , Tuncbilek Cihan H.
Published: November 2008

This paper deals with the design of dynamic time-space and calibrated static strategic planning models, along with solution algorithms, for the multilevel rail-car fleet management problem faced by RELOAD®, a branch of the Association of American Railroads (AAR). We discuss a prevalent fleet sizing management model that is static in nature, and propose an alternative dynamic model based on a time-space network representation. This model accurately represents the problem, and also provides information regarding the issue of storing and retrieving empty cars. A suitable decomposition heuristic, that is based on solving subproblems defined for overlapping time segments, is developed to solve this model. This heuristic is shown to recover an optimal solution for all the test problems with a reasonable effort. We also investigate a procedure for calibrating the static model based on this improved time-space representation. Our results show that for the static model, a calibrated use of available data can yield near-optimal total fleet size requirements. This enables the use of such a simple, calibrated static model for accurately conducting fleet sizing, the determination of fleet size allocations among railroads, as well as for analyzing various “what-if” scenarios. The proposed methodology is being currently implemented at the AAR, and the status of this process as well as some test results are presented.
Nonlinearities in the Relation Between the Equity Risk Premium and the Term Structure
Authors: Boudoukh Jacob , Richardson Matthew , Whitelaw Robert F.
Published: November 2008

This paper investigates the relation between the conditional expected equity risk premium and the slope of the term structure of interest rates. Theoretically, these variables are linked, the relation may be nonlinear, and negative risk premiums are consistent with equilibrium. Given these implications, we employ a nonparametric estimation technique to document the empirical relation between the risk premium and the slope of the term structure using almost two hundred years of data. Of particular interest, the risk premium is increasing in the term structure slope; however, for either small or negative slopes, the risk premium is much more sensitive to changes in interest rates. In addition, the empirical results imply negative expected equity risk premiums for some inverted term structures. Finally, variations in the risk premium do not appear to be related to variations in the variance of equity returns. We illustrate these features in a stylized consumption-based model, and provide the economic intuition behind the results.
A Model-Based Framework to Overlap Product Development Activities
Authors: Krishnan Viswanathan , Eppinger Steven D. , Whitney Daniel E.
Published: November 2008

Intense competition in many industries forces manufacturing firms to develop new, higher quality products at an increasingly rapid pace. Overlapping product development activities is an important component of concurrent product development that can help firms develop products faster. However, since product development activities may be coupled in complex ways, overlapping interrelated activities can present many difficulties. Without careful management of the overlapped product development process, the development effort and cost may increase, and product quality may worsen. This paper goes beyond the common recommendation to simply overlap activities as much as possible. We present a model-based framework to manage the overlapping of coupled product development activities. The model and framework identify conditions under which various types of overlapping are appropriate for a pair of coupled activities. We illustrate the model and framework with industrial applications involving the development of electronic pagers and automobile doors.
Competing in Product and Service: A Product Life-Cycle Model
Authors: Cohen Morris A. , Whang Seungjin
Published: November 2008

In this paper we develop a product life-cycle model that studies a set of strategic choices facing manufacturers as they design the joint product/service bundle for a product which may require maintenance and repair support after its sale. The choice parameters of interest include the product price, the quality of after-sales service and the price to be charged for the after-sales service. We adopt a competitive, game-theoretic (as opposed to single-firm optimization) framework, where there is competition for the provision of after-sales service between the manufacturer and an independent service operator. The product price and the service quality/price are characterized by an equilibrium to a sequential game. The resulting outcome is applied to support the valuation of alternative product designs in explicit consideration of the tradeoff between profit from product sale and from the provision of after-sales service. The model can also be used to evaluate the asset value of a firm's customer base.
Quick Response in Manufacturer-Retailer Channels
Authors: Iyer Ananth. V. , Bergen Mark E.
Published: November 2008

Quick Response (QR) is a movement in the apparel industry to shorten lead time. Under QR, the retailer has the ability to adjust orders based on better demand information. We study how a manufacturer-retailer channel impacts choices of production and marketing variables under QR in the apparel industry. Specifically, we build formal models of the inventory decisions of manufacturers and retailers both before and after QR. Our models allow us to address who wins and who loses under QR, and suggest actions such as service level, wholesale price and volume commitments that can be used to make QR profitable for both members of the channel, i.e., Pareto improving. Detailed discussions with a major retailer, and information from industry sources provide supporting evidence for the structure and conclusions of the model.
“Bi-Matching”: A New Preference Assessment Method to Reduce Compatibility Effects
Authors: Delquié Philippe
Published: November 2008

Preference models and utility functions are often assessed by eliciting value trade-offs among attributes. Prior research has shown that trade-off judgments can be biased in systematic ways: for example, the attribute which is used as response receives more relative subjective weight, i.e. the so-called scale compatibility effects (Tversky et al. [Tversky, A., S. Sattath, P. Slovic. 1988. Contingent weighting in judgment and choice. Psych. Rev. 95 371–384.]). This paper proposes a new procedure to elicit value trade-offs called bidimensional matching, or “bi-matching”, designed to alleviate this effect. Bi-matching differs from traditional trade-off judgments, in that both attributes are adjusted simultaneously to reach indifference judgments. Bi-matching is compared with simple matching and choice in four experimental studies, to measure preferences for lotteries and riskless multiattribute alternatives. The main results are: (1) bi-matching produces trade-offs intermediate between those derived from matching on the “more important” attribute and matching on the less important attribute, although closer to the former; (2) the trade-offs derived from choice reflect more relative weight on the more important dimension than those from bi-matching; (3) bi-matching appears to reduce response error compared to standard matching. These results are generally consistent with theoretical predictions. We discuss the normative question of which preference assessment method is preferable. The current results as a whole and the built-in features of the bi-matching procedure already position this elicitation method as a worthwhile alternative to traditional methods for helping decision-makers introspect and construct their value trade-offs.
Performance in Principal-Agent Dyads: The Causes and Consequences of Perceived Asymmetry of Commitment to the Relationship
Authors: Ross William T. , Anderson Erin , Weitz Barton
Published: November 2008

We focus on the principal-agent relationship in a distribution channel. In a services context (insurance), we examine how two facets of performance, from the point of view of both the principal and the agent, are influenced by the perceiver's belief that it is more committed to the relationship than is the other party. Using primary data from 255 insurance agent-insurance provider dyads, we show that each side's assessment of how much it benefits from the dyad is related in a potentially dysfunctional manner to its perception of asymmetric commitment. Perceivers rate their performance outcomes from the dyad (i.e., harmony and profit) highest when they believe they are less committed than their counterpart. Conversely, they rate their own performance outcomes lowest when they believe they are more committed than the other party. We explain this finding in terms of suspected opportunism and offer a partial test of this explanation compared with explanations from theories of equity and power/dependence. Further, we demonstrate that each party's perception of asymmetric commitment partially reflects actual asymmetry, as measured by confidential data collected from both sides. Perceived asymmetric commitment is also shown to be related to levels of communication and dependence in the dyad. Managerial implications for reducing perceived asymmetric commitment and improving the performance outcomes of each dyad member are discussed.
Effects of the User Participation Process and Task Meaningfulness on Key Information System Outcomes
Authors: Hunton James E. , Price Kenneth H.
Published: November 2008

In this study, 144 professional accounting data entry clerks took part in a fully randomized field experiment using a 4 (mode of participation) × 2 (task meaningfulness) design. Participants were full-time, mandatory users of payroll applications. The nature of the experiment engaged these users in hands-on activity (Hartwick and Barki [Hartwick, J., H. Barki. 1994. Explaining the role of user participation in information system use. Management Sci. 40 440–465.]) regarding the development of a payroll input screen. User mode of participation was manipulated by varying the extent of decision input used to execute hands-on activity in accordance with procedural justice theory. Perceptions of decision control, procedural justice, and outcome satisfaction, as well as objective levels of task performance escalated with corresponding increases in decision input. Task meaningfulness was manipulated by creating either high or low expectations of using the payroll input screen in the near future. As the development task became more meaningful, procedural justice, decision control, task commitment, and task performance responses also increased. An underlying theoretical model of treatment effects was tested using path analysis which supported the control-oriented theory of procedural justice. The strong attitudinal and behavioral results observed in this experiment enhance understanding of the user participation and involvement model proposed by Hartwick and Barki (Hartwick, J., H. Barki. 1994. Explaining the role of user participation in information system use. Management Sci. 40 440–465.) by incorporating process considerations from procedural justice theory into their framework. Implications of this research are discussed.
Daily Aircraft Routing and Scheduling
Authors: Desaulniers Guy , Desrosiers Jacques , Dumas Yvan , Solomon Marius M. , Soumis François
Published: November 2008

In this paper we consider the daily aircraft routing and scheduling problem (DARSP). It consists of determining daily schedules which maximize the anticipated profits derived from the aircraft of a heterogeneous fleet. This fleet must cover a set of operational flight legs with known departure time windows, durations and profits according to the aircraft type. We present two models for this problem: a Set Partitioning type formulation and a time constrained multicommodity network flow formulation. We describe the network structure of the subproblem when a column generation technique is applied to solve the linear relaxation of the first model and when a Dantzig-Wolfe decomposition approach is used to solve the linear relaxation of the second model. The linear relaxation of the first model provides upper bounds. Integer solutions to the overall problem are derived through branch-and-bound. By exploiting the equivalence between the two formulations, we propose various optimal branching strategies compatible with the column generation technique. Finally we report computational results obtained on data provided by two different airlines. These results show that significant profit improvement can be generated by solving the DARSP using our approach and that this can be obtained in a reasonable amount of CPU time.
The Influence Prism in SMEs: The Power of CEOs' Perceptions on Technology Policy and Its Organizational Impacts
Authors: Lefebvre Louis A. , Mason Robert , Lefebvre Élisabeth
Published: November 2008

The research proposes a model, which relates the following variables: (a) the CEO's perceptions of the environment, (b) the strategic business orientation, scanning, and structural characteristics, (c) technology policy, (d) realized innovative efforts of the firm, and (e) measures of firm performance. The empirical data from small manufacturing enterprises (SMEs) that share a common economic and industrial environment show that CEOs' perceptions of external environment—and not objective measures—are key significant issues with respect to technology policy formulation and enactment in SMEs and its subsequent organizational impacts. In particular, perceived environmental hostility and dynamism are shown to have specific and differing moderating roles on the form and strength of the relationships between technology policy and its determinants and between technology policy and realized innovative efforts. Furthermore, a more aggressive technology policy leads to greater realized innovative efforts, which in turn are positively related to export performance and, to a lesser extent, to financial performance.
Adaptation on Rugged Landscapes
Authors: Levinthal Daniel A.
Published: November 2008

A simple model is developed to explore the interrelationship between processes of organizational level change and population selection forces. A critical property of the model is that the effect on organizational fitness of the various attributes that constitute an organization's form is interactive. As a result of these interaction effects, the fitness landscape is “rugged.” An organization's form at founding has a persistent effect on its future form when there are multiple peaks in the fitness landscape, since the particular peak that an organization discovers is influenced by its starting position in the space of alternative organizational forms. Selection pressures influence the distribution of the organizational forms that emerge from the process of local adaptation. The ability of established organizations to respond to changing environments is importantly conditioned by the extent to which elements of organizational form interact in their effect on organizational fitness. Tightly coupled organizations are subject to high rates of failure in changing environments. Furthermore, successful “reorientations” are strongly associated with survival for tightly coupled organizations, but not for more loosely coupled organizations that are able to engage in effective local adaptation.
Process Range in Manufacturing: An Empirical Study of Flexibility
Authors: Upton David M.
Published: November 2008

This paper examines the relationship between one form of manufacturing flexibility—process range—and structure, infrastructure, and managerial policy at the plant level. The paper provides evidence of the strength of the links between manufacturing flexibility and such factors as scale, technology vintage, computer integration, and workforce management. Data from 54 plants in the fine-paper industry are presented, and a model of the determinants of short-term flexibility is developed. The plants examined differed by a factor of 20 in their ability to accommodate large process variation. The evidence suggests that flexibility is strongly negatively related to scale and degree of computer integration, yet positively related to newer vintages of mechanical technology and workforce experience. Some results differ significantly from the prevailing view of the industry, in particular, that newer plants are less flexible. The paper shows that newer machine technology is more flexible once other factors are controlled for. In the longer term, the results show that management has a significant impact on the improvement of flexibility in operations, regardless of the technology and infrastructure in place. Plant network managers' views of flexibility are important. The data suggest that inflexible plants may be inflexible partly as a result of their being considered inflexible by network managers, and never being assigned the product range needed to improve the capability.
Using Computers to Realize Joint Gains in Negotiations: Toward an “Electronic Bargaining Table”
Authors: Rangaswamy Arvind , Shell G. Richard
Published: November 2008

Multiissue negotiations present opportunities for tradeoffs that create gains for one or more parties without causing any party to be worse off. The literature suggests that parties are often unable to identify and capitalize on such trades. We present a Negotiation Support System, called NEGOTIATION ASSISTANT, that enables negotiators to analyze their own preferences and provides a structured negotiation process to help parties move toward optimal trades. The underlying model is based on a multiattribute representation of preferences and communications over a computer network where offers and counteroffers are evaluated according to one's own preferences. The parties can send and receive both formal offers and informal messages. If and when agreement is reached, the computer evaluates the agreement and suggests improvements based on the criteria of Pareto-superiority. In this paper, we motivate the system, present its analytical foundations, discuss its design and development, and provide an experimental assessment of its “value-in-use.” Our results strongly suggest that parties using the system in structured negotiation settings would achieve better outcomes than parties negotiating face to face or over an e-mail messaging facility, other things being equal. For example, only 4 of the 34 dyads (11.1%) negotiating a simulated sales transaction face to face or over e-mail reached an “integrative” settlement, as compared with 29 of the 68 dyads (42.6%) using NEGOTIATION ASSISTANT. Systems such as NEGOTIATION ASSISTANT have the potential to be used in emerging “electronic markets.”
Coordinating Production and Inventory to Improve Service
Authors: Sox Charles R. , Thomas L. Joseph , McClain John O.
Published: November 2008

Customer service has assumed strategic importance in most manufacturing environments. Corporate reputations often depend on how reliably promised lead times are met. A goal of filling orders within a service window of T time units is often encountered in practice. This goal ignores the differences among types of units, treating all customers as equally important. Keeping finished goods inventory of all items is only one, and often not the best, way to achieve this objective. High-demand items naturally have safety stock assigned to them, but in many organizations there are so many very-low-demand items that keeping any stock in these items is prohibitively expensive. Customer service can be maintained for these low-demand items by giving them higher production priority when a demand occurs. In this paper, stochastic analysis and simulation are employed to test the merit of this idea. Changes in management structure to allow this type of system are discussed.
Partial Deductive Closure: Logical Simulation and Management Science
Authors: Kamps Jaap , Masuch Michael
Published: November 2008

This research is part of a larger effort to build machine-based tools for developing scientific theories. In analogy with the research process in empirical research, we describe a logical cycle of theory development: (1) starting with an informal version of a theory, (2) then moving to its formal representation, (3) applying formal logic to investigate this representation, and (4) using the results as feedback for the update/revision of the original theory. A central aspect of the logical cycle is the detection of the (hidden) implications of a theory (called “partial deductive closure”). In this paper, we present an algorithm that performs the partial deductive closure for a relevant class of theorems, while filtering out trivial results. The algorithm is applied to an important organization theory, Organizational Ecology, and is shown to generate new theorems of interest.
Does Implementing an Effective TQM Program Actually Improve Operating Performance? Empirical Evidence from Firms That Have Won Quality Awards
Authors: Hendricks Kevin B. , Singhal Vinod R.
Published: November 2008

This study explores the hypotheses that implementing effective total quality management (TQM) programs improves the operating performance of firms. The winning of quality awards is used as a proxy for the effective implementation of TQM programs. Changes in various performance measures for a test sample of quality-award winners are compared against a sample of control firms. Our statistical tests provide strong evidence that firms that have won quality awards outperform the control firms on operating income-based measures. Over a 10-year period, from 6 years before to 3 years after the year of winning the first quality award, the mean (median) change in the operating income for the test sample is 107% (48%) higher than that of the control sample. There is reasonably strong evidence that firms that have won quality awards do better on sales growth than the control firms. Over the 10-year period, the mean (median) change in sales for the test sample is 64% (24%) higher than that of the control sample. We also find weak evidence that firms in our test sample are more successful in controlling costs when compared with the firms in the control sample. In addition, the results indicate that firms in our test sample increased their capital expenditures more than the control sample over the time period prior to winning quality awards. Compared with the control sample, the test sample shows higher growth in both employment and total assets.
Note. Optimal Storage Assignment Policies for Automated Storage and Retrieval Systems with Stochastic Demands
Authors: Thonemann Ulrich W. , Brandeau Margaret L.
Published: November 2008

In existing AS/RS research, storage assignment policies are evaluated based on the probability that item type j will be stored (and subsequently retrieved). This note applies the turnover-based and class-based assignment policies of Hausman et al. (1976) to a stochastic environment by identifying the kth pallet of item type j: Frequently demanded pallets are stored close to the input/output point and rarely demanded pallets are stored at the end of the storage rack. We consider a discrete storage rack and a continuous storage rack. For the continuous rack case, we develop an expression for expected one-way travel time given uniform and exponentially distributed demand. We show that the turnover-based policy applied to the stochastic environment is optimal (it minimizes one-way travel time) and that both the turnover-based and class-based assignment policies applied in the stochastic environment reduce expected storage/retrieval time compared with random assignment. These savings can be directly translated into increased throughput capacity for existing systems and can be used to improve the design of proposed systems.
Financial Asset-Pricing Theory and Stochastic Programming Models for Asset/Liability Management: A Synthesis
Authors: Klaassen Pieter
Published: November 2008

Practical portfolio investment problems under uncertainty can be modeled well as multiperiod stochastic programs. However, the numerical optimization methods that need to be used to solve such models seriously limit the level of detail in the uncertainty about future asset prices and returns that can be incorporated. Somewhat surprisingly, the question how this necessarily approximate description of the uncertainty should be constructed has received relatively little attention in the stochastic programming literature. Moreover, many of the descriptions that have been used are not arbitrage-free, and therefore inconsistent with modern financial asset-pricing theory. In this paper we will present aggregation methods that can be used in combination with financial asset-pricing models to obtain a description of the uncertainty that is arbitrage-free, consistent with observed market prices as well as concise enough for a stochastic programming model. Furthermore, we will discuss how these aggregation methods can form the basis of an iterative solution approach.
SPOT: Scheduling Programs Optimally for Television
Authors: Reddy Srinivas K. , Aronson Jay E. , Stam Antonie
Published: November 2008

This paper introduces SPOT (Scheduling Programs Optimally for Television), an analytical model for optimal prime-time TV program scheduling. Due in part to the advent of new cable TV channels, the competition for viewer ratings has intensified substantially in recent years, and the revenues of the major networks have not kept pace with the costs of the programs. As profit margins decrease, the networks seek to improve their viewer ratings with innovative scheduling strategies. Our SPOT models for scheduling network programs combine predicted ratings for different combinations of prime-time schedules with a novel, mixed-integer, generalized network-based flow, mathematical programming model, which when solved provides an optimal schedule. In addition to historical performance, subjective inputs from actual network managers were used as input to the network flow optimization model. The optimization model is flexible. It can utilize the managers' input and maximize profit (instead of ratings) by considering not only the revenue potential but also the costs of the shows. Moreover, SPOT can describe the scheduling problem over any time period (e.g., day, week, month, season), and designate certain shows to, and restrict them from, given time slots. The methodology of SPOT is illustrated using data for the first quarter of 1990, obtained from a cable network. The optimization model produces solutions that would have generated an increase of approximately 2% in overall profitability, representing over $6 million annually for the cable network. SPOT not only produces more profitable TV schedules for this network, but also provides valuable general insights into the development of mixed programming strategies for improving future schedules.
Tree Diversity, Landscape Diversity, and Economics of Maple-Birch Forests: Implications of Markovian Models
Authors: Lin Ching-Rong , Buongiorno Joseph
Published: November 2008

Markov decision process (MDP) models were effective in analyzing forest management policies. Even the simplest standard results gave useful insights into forest ecology, such as how landscape diversity is shaped by natural catastrophes, and how forests mature through successional phases. The methods were also useful to predict the effects of different management policies on ecological and economic criteria. Optimization augmented the usefulness of the approach, suggesting that income from Wisconsin's maple-birch forests could be increased without ruining their diversity of landscape, tree size, and tree species. It showed that maximizing species diversity, defined by the distribution of trees in shade-tolerance classes, would require some harvest. Instead, maximum tree size diversity occurred in unmanaged forests, but this gave a less diverse landscape and no income. The MDP method allowed for the design of compromise policies that would maximize income while keeping diversity above specified limits. The opportunity cost of increasing tree size diversity was found to be much higher than for species diversity. Comparing the maximum timber income owners could have got with what they actually cut suggested that the amenity value of forests was four times that of timber. Advantages of the methods reside in the ability to model complex ecosystem processes with simple probability matrices, and in the rich MDP theory and algorithms. Limitations include the difficulty of defining a space set large enough for accurate discretization, but small enough for practical application.
A Probabilistic Decision Model for Entity Matching in Heterogeneous Databases
Authors: Dey Debabrata , Sarkar Sumit , De Prabuddha
Published: November 2008

In recent years, there has been a proliferation of database systems in all types of organizations. In many cases, these databases are developed in different departments and maintained autonomously. Much is to be gained, however, if databases across departments, divisions, or even organizations can be related to one another. One main problem of relating data stored in different databases is the differences in their representation of real-world entities, such as the use of different identifiers or primary keys. We present a decision theoretic model for matching entities across different databases. The decision to match two entities from two different databases inherently involves some uncertainty since an exact match may not be found because of errors in data collection, data entry, and data representation. We model this uncertainty using probability theory and propose an integer programming formulation that minimizes the total cost associated with the entity matching decision. The model has been implemented and validated on real-world data.