bluuebunny/crossref_metadata_2025_split huggingface dataset:
Thresholds and Transitivity in Stochastic Consumer Choice: A Multinomial Logit Analysis
Authors: Lioukas S. K. 
Published: November 2008

In previous work, thresholds have been introduced to describe situations where the consumer is indifferent between any two alternatives. Krishnan (Krishnan, K. S. 1977. Incorporating thresholds of indifference in probabilistic choice models. Management Sci. 23 (July) 1224–1233.) formalised thresholds as minimum perceivable differences between the utilities of the alternatives compared and incorporated such thresholds into the binary logit model. The present paper provides an extension and application of the theory to situations where the decision maker is confronted with more than two alternatives. In such situations thresholds can lead to systematic and predictable intransitivity of indifference, violating a basic postulate of utility theory. Explicit probabilities of transitive and intransitive choices are derived within the framework of the multinomial logit model and the stochastic consumer theory associated with this model. The empirical applicability and managerial usefulness of the proposed theory is illustrated using a transportation example with three alternatives. The data employed reflect actual travellers' use of interurban transport modes in Greece. Parameters are estimated by a maximum-likelihood technique, based on a gradient search method. The results support the existence of thresholds. The application has important policy implications.
An Overview of Techniques for Solving Multiobjective Mathematical Programs
Authors: Evans Gerald W. 
Published: November 2008

Multiobjective mathematical programming has been one of the fastest growing areas of OR/MS during the last 15 years. This paper presents: some reasons for the rapidly growing increase in interest in multiobjective mathematical programming, a discussion of the advantages and disadvantages of the three general approaches (articulation of the decision maker's preference structure over the multiple objectives prior to, during, or after the optimization) towards multiobjective mathematical programming, a nontechnical overview of many of the specific solution techniques for multiobjective mathematical programming, and a discussion of important areas for further research. The overview concentrates on those techniques which require an articulation of the decision maker's preference structure either during or after the optimization, since these are the areas where most of the recent research has been conducted. It differs from previous overviews in that, in addition to the timing of the elicited preference information, the techniques are also classified according to the types of decision variables contained in the model (i.e., only continuous decision variables, or at least some discrete decision variables). In addition, the types of preference information (e.g., a ranking of outcomes) required of the various techniques are also discussed.
An Empirical Investigation of Success Strategies for Businesses Along the Product Life Cycle
Authors: Thietart R. A. , Vivas R. 
Published: November 2008

Since the introduction of the concept of the product life cycle (PLC) some decades ago a great deal has been written on the subject and several empirical studies have been conducted. However, empirical research to date is often limited in scope. It is oriented towards the analysis of the growth and saturation stages and focused primarily on the study of consumer goods. Furthermore, the application of the PLC concept in strategic planning is largely disappointing, the normative orientation of most of this literature being somewhat naive and misleading. The aim of the present research is to study the efficiency of different strategies for achieving market share and cash flow objectives. This study is performed on different types of businesses producing both consumer and industrial products situated at various stages on the product life cycle: growth, maturity and decline. A sample of approximately 1,100 businesses (217 in the growth stage, 315 in the maturity stage, 569 in the decline stage) is drawn from the PIMS data base. A cluster analysis is run to identify natural groups of homogeneous businesses. For each of the nine identified groups, linear regression models are estimated to study the influence of strategic actions—finance, marketings, production, R&D, personnel—on two criteria of performance: market share and cash flow. The research indicates that strategies not only depend on the life cycle stage but also are influenced by the goal orientation of the firm—short-term (cash-flow) or long-term (market share)—and that success strategies appear to be contingent upon the business and the environmental characteristics.
A Goal Programming Example in Public Health Resource Allocation
Authors: Tingley Kim M. , Liebman Judith S. 
Published: November 2008

A model developed to aid a state-level resource allocation process in the United States Department of Agriculture Special Supplement Food Program for Women, Infants, and Children (WIC) is presented. The model is formulated as a linear integer goal program, utilizing service levels for six categories of WIC participants as goals. The model employs a methodical, consistent approach to the allocation process, yet allows ample flexibility for consideration of state-specific issues. By allowing the user to adjust the relative importance of each goal, the model can incorporate subjective attitudes of state-level WIC administrators. This is extremely important as these attitudes are the result of the administrators' familiarity with the WIC program in their states, and the significance of input of this nature should not be neglected. An application of the model to the Indiana WIC program is presented. Sensitivity of the model to changes in the objective function weights and in the target values for the goals is explored. Although orginally developed to allocate budget increases, the model may be used in allocating budget cuts as well; this form of the model is also presented. The model can be extended hierarchically to incorporate resource allocation at the federal level. This modeling approach should be useful in all public sector programs characterized by multiple objective and hierarchical decisionmaking.
Survival versus Consumption
Authors: Shepard Donald S. , Zeckhauser Richard J. 
Published: November 2008

We develop an indirect method to estimate utility and willingness to pay (WTP) for reductions in the risk of death at various ages. Using a life-cycle model of consumption, we assume that an individual sets his consumption level each year so as to maximize his expected lifetime utility. Alternative assumptions about opportunities for borrowing and annuities characterize two polar types of societies. In our Robinson Crusoe case, an individual must be entirely self-sufficient, and annuities are not available. In our perfect markets case, an individual can borrow against future earnings and purchase actuarially fair annuities; we show that under these assumptions WTP is the sum of livelihood (discounted expected future earnings) and consumer surplus. To illustrate our methods, we derive WTP for an average financially independent American man under plausible assumptions. The model is calibrated to 1978 earnings (e.g., $18,000 per year for men aged 45–54 with at least some income). In the Robinson Crusoe case, WTP increases from $500,000 at age 20 to a peak of $1,250,000 at age 40, and declines to $630,000 at age 60. In the perfect markets case, age variations are less pronounced; WTP is $1,050,000 at age 20, peaks at $1,070,000 at age 25, and declines to $600,000 at age 60. These results suggest that individuals value risks to their lives at several times the pro-rata share of their future earnings.
A Comparative Evaluation of Multiattribute Consumer Preference Models
Authors: Currim Imran S. , Sarin Rakesh K. 
Published: November 2008

In this paper the theory and estimation procedures for several consumer preference models are discussed. Predictive accuracy in the form of internal consistency of these models is compared in an empirical application. Consumer decision situations are classified into two classes: decisions under certainty and decisions under uncertainty. For each of the two classes of decision situations two modeling strategies have been used: statistical estimation and algebraic solution. An additive conjoint, an additive and a multiplicative measurable value, and an additive and a multiplicative utility model are considered. Our main finding is that the statistical estimation procedures outperform their algebraic counterparts on the criterion of predictive accuracy. The utility model provides better predictions for decisions under uncertainty than the widely used conjoint models. The relationship between models for decisions under certainty and decisions under uncertainty is discussed. It is shown how a conjoint or a measurable value function model can be transformed into a utility model with minimum additional information from the subjects. A concept of relative risk attitude is proposed to segment consumers by the degree of their risk aversion or risk seeking propensities.
A Budget Holdback Policy for Multi-Item Procurement Processes
Authors: Morey Richard C. , Sweeney Dennis J. 
Published: November 2008

This paper is concerned with the development of an optimal budget holdback policy for a multi-item procurement process. An annual budget is made available for the purchase and resupply of n items. The issue is to determine how much of the budget to commit initially and how much to hold back for spot purchases later in the year. An analytic solution to the problem is developed for the single item case and compared to the unconstrained “newsboy” solution. In the multi-item case we develop stochastic linear programming with resource models under two views of the organization's procurement process. The first view is that the overall budget is allocated to the individual item managers and spot purchase monies earmarked for one item cannot be used for another. The computational and data requirements for solution of this model are reasonable. The second view is that spot buy monies are pooled and allocated to individual items on an “as needed” basis. The linear programming model of this procurement process is much more complex and not computationally feasible for more than a few items. However, the budget allocation model of the first view is shown to be a good heuristic for determining the percent of funds to hold back for the pooled process. A numerical example and sensitivity analysis are included.
Sense-Making of Accounting Data as a Technique of Organizational Diagnosis
Authors: Boland Richard J. 
Published: November 2008

Planning is a process of inquiry. Inquiry can be enhanced if different views-of-the-world are used to inform each other. In an exploratory field study, a sense-making exercise was used in the initial, goal definition stage of planning. Its use is antithetical because sense-making denies that management action is based on preconceived goals or objectives. Instead, sense-making assumes management action is a continuous, equivocal stream of experience that can only be understood (or made sense of) when it is viewed in retrospect. Accounting reports were prepared to describe a fictitious, but plausible future scenario for an organization. A number of alternative future directions that the organization could have followed—different kinds of organization it could have become—were used as a basis for creating the accounting reports. The management group then imagined themselves even further out into the future, looking back over the accounting data. They tried to understand what they had done during this period, why they had done it, and how they felt about having done it. The impact of this exercise on the managers' cognitive and emotional experience and their commitment to use the method in other decisions suggest that sense-making can enhance the group process of inquiry during the initial stages of planning.
Stochastic Models of Internal Mail Delivery Systems
Authors: Nahmias Steven , Rothkopf Michael H. 
Published: November 2008

This paper develops two stochastic models of an internal mail delivery system in which a single clerk picks up, sorts and delivers mail to a closed loop of offices. The two models differ in whether deliveries are made at scheduled times or not. For a model in which all mail picked up each round is sorted before the next delivery, we assume that mail is generated in the system by a stationary Poisson process and derive an expression for the expected delay between generation of a letter and its ultimate delivery. These results are then extended to systems in which letters are generated according to a stationary compound Poisson process and to multiple clerk delivery systems. A second model in which mail is delivered at scheduled times only is shown to be equivalent to a classical storage process. For this model, we derive bounds on the expected number of letters left unsorted at the start of a scheduled delivery and the expected delivery delay. This model is also generalized to multiclerk systems.
A Measurement Error Approach for Modeling Consumer Risk Preference
Authors: Eliashberg Jehoshua , Hauser John R. 
Published: November 2008

Von Neumann-Morgenstern (vN-M) utility theory is the dominant theoretical model of risk preference. Recently, market researchers have adapted vN-M theory to model consumer risk preference. But, most applications assess utility functions by asking just n questions to specify n parameters. However, any questioning format, especially under market research conditions, introduces measurement error. This paper explores the implications of measurement error on the estimation of the unknown parameters in vN-M utility functions and provides procedures to deal with measurement error. We assume that the functional form of the utility function, but not its parameters, can be determined a priori through qualitative questioning. We then model measurement error as if question format and other influences cause the consumer to choose the unknown “risk parameter” from a probability distribution and to make his decisions accordingly. We provide procedures to estimate the unknown parameters when the measurement error is either (a) Normal or (b) Exponential. Uncertainty in risk parameters induces uncertainty in utility and expected utility, and hence uncertainty in choice outcomes. Thus, we derive the induced probability distributions of the consumer's utility and the estimators for the implied probability that an alternative is chosen. Results are obtained for both the standard decision analysis “preference indifference” question format and for a “revealed preference” format in which the consumer is asked simply to choose between two risky alternatives. Since uniattribute functions illustrate the essential risk preference properties of vN-M functions, we emphasize uniattribute results. We also provide multiattribute estimation procedures. Numerical examples illustrate the analytical results.
Probability Versus Certainty Equivalence Methods in Utility Measurement: Are they Equivalent?
Authors: Hershey John C. , Schoemaker Paul J. H. 
Published: November 2008

Certainty equivalence (CE) and probability equivalence (PE) methods are the two most frequently used procedures for constructing von Neumann-Morgenstern utility functions. In this paper, we compare these methods experimentally, using a two-stage within-subject design. By asking subjects first for a CE judgment and later for a related PE judgment (or vice versa), a consistency test is devised which any deterministic expectation model, including those allowing probability transformations, should meet. Using four related experiments, this consistency test is applied separately to gain and loss questions, and to the two sequences of linked equivalence judgments, namely CE-PE and PE-CE. The empirical results reveal serious inconsistencies between the CE and PE responses for each of the four experiments. The extent of discrepancy depends strongly on the subject's initial risk attitude and whether the gain or loss domain is examined. To explain the complex pattern of results, the second part of the paper explores several plausible hypotheses. The first of these concerns the role of random error, in either the responses or the utility function itself. It is shown that both can lead to bias, although not of a type that could explain our results. Thereafter shifts in reference points are examined. A particular reframing of the PE response mode is postulated in which a pure gamble is psychologically translated into a mixed one, leading to increased risk aversion. This hypothesis, which is also supported by other evidence, offers a complete and simple explanation of the results. Finally, several other behavioral hypotheses are examined, after developing a weighted average model to simulate them. They concern anchoring effects, differences in salience between the probability and outcome dimensions, strategic misrepresentation, regret or rejoice influences, and endowment effects. Although each hypothesis predicts some type of bias, none of these five could singly explain the particular pattern of bias observed. In general, the study demonstrates (1) that serious discrepancies exist between the CE and PE methods of utility measurement, (2) that the particular results are incompatible with traditional deterministic choice models, (3) how random response errors, through propagation, can induce systematic biases in the utility function, (4) that reframing of the PE mode offers a simple reference shift explanation of the complex findings, and (5) how various heuristics and biases can be operationalized and simulated to assess their effects on utility measurement. As such, this study represents a further step toward a systematic investigation of response mode biases in utility measurement.
Approximating the Criticality Indices of the Activities in PERT Networks
Authors: Dodin Bajis M. , Elmaghraby Salah E. 
Published: November 2008

A stochastic PERT network is a directed acyclic network in which the arc lengths are independent random variables with known distributions. A fundamental problem in PERT networks is to identify the activities which are critical to the achievement of the project objectives. In an activity network if the duration of each activity is not a random variable, then it is easy to identify the criticality of each activity represented by its float time. However, when the duration of any activity is a random variable, it is not easy to identify the criticality of each activity. In this case the criticality of an activity is known as the “criticality index,” which is defined as the sum of the criticality indices of the paths containing it. The criticality index of a path is the probability that the duration of the path is greater than or equal to the duration of every other path in the network. Clearly, the criticality index of an activity can be obtained by determining the criticality indices of the paths, which requires identifying all the paths, determining their criticality indices, then identifying the paths containing the activity. In this paper we develop a theory which leads to a procedure to approximate the criticality indices of all the activities without going through the above three steps. The procedure has been applied to large size PERT networks generated at random, and the results are found to be very close to those obtained by extensive Monte Carlo sampling.
The Dynamics of Organizational Proximity
Authors: Monge Peter R. , Rothman Lynda White , Eisenberg Eric M. , Miller Katherine I. , Kirste Kenneth K. 
Published: November 2008

The proximity among people in an organization is known to exert considerable influence on a variety of organizational outcomes such as performance, stress, and job satisfaction. Early research on proximity in organizations studied pairs of people in job locations that were at fixed distances (e.g., keypunch operators at their work stations). This research procedure ignores three critical features of organizational life. First, people are simultaneously proximate to everyone else in their organization. Second, this proximity changes throughout the day as people move about the organization. Finally, the opportunity and obligation for communication that people perceive by being physically close to others is often more important than the actual physical distance. The present paper develops a definition of organizational proximity that accounts for these previous limitations. Specifically, organizational proximity is defined as two or more people being in the same location where there is both the opportunity and psychological obligation for face-to-face communication. This measure, when aggregated across all people in an organization, provides a single value of how concentrated people are in the various locations of the firm. Further, given the proper data collection techniques, it reveals the degree to which organizational proximity changes throughout the workday and workweek. On the basis of this definition, research was conducted which examined the organizational proximity among employees in a research and development firm for each 15-minute interval of a typical workweek. Two major findings were obtained. First, the level of organizational proximity changed considerably during the course of a typical day, with peaks during the late morning and early afternoon and valleys during the early morning, lunch, and late afternoon hours. Second, the pattern was highly consistent from day-to-day. This consistency permitted the development of a model which enables accurate prediction of the level of organizational density for any time period during any day of the workweek. There are several rather interesting managerial implications in these results. First, they support Peters and Waterman's (Peters, T. J., R. H. Waterman. 1982. Search of Excellence: Lessons from America's Best-Run Companies. Harper & Row, New York, 3–26, 119–155, 200–234.) recent recommendation of “management by wandering around,” since that technique maximizes a manager's proximity to employees. Second, the results suggest managerial and electronic alternatives to traditional forms of communication such as face-to-face meetings and phonecalls. Third, they imply alternative strategies for managing the daily fluctuations in availability of people and communication that result from differences and changes in organizational proximity.