Testing Prospect Theory in a Deterministic Multiple Criteria Decision-Making Environment*

Prospect theory by Kahneman and Tversky [7] is tested in a deterministic multiple criteria decision-making context. In two experiments conducted in classroom settings subjects made pairwise preference comparisons of condominiums for sale. The results of the experiments indicate that the traditional value model did not explain the subjects' revealed preferences as well as the prospect model. We conclude that prospect theory is a reasonable model of choice for many individuals in such a context.     

Gender differences in risk behavior and the link to household effects and individual wealth

This study examined the differences in risk behavior between men and women using a household survey that captured the risk preferences of two members in a household and recorded wealth at the individual level instead of the usual approach of representing wealth at the household level. After controlling for commonly used explanatory variables, such as gender, education, age, and wealth, household fixed effects explain about 15% of the variation in risk behavior. This highlights the magnitude of household effects in shaping one’s risk behavior. In general, females in the study area are more risk averse than males based on a risk game with real payout. The gender differences disappear when focusing on only the top land owners. However, even in those cases, females consider themselves more risk averse, supporting results from previous studies that link culture and societal norms to the gender differences in risk behavior.     

The experiences of privately practising midwives in Australia who have been reported to the Australian Health Practitioner Regulation Agency: A qualitative study

BackgroundIn Australia the majority of homebirths are attended by privately practising midwives (PPMs). In recent years PPMs have been increasingly reported to the Australian Health Practitioner Regulation Agency (AHPRA) mostly by other health professionals.Purposeto explore the experiences of PPMs in Australia who have been reported to the AHPRA.MethodsA qualitative interpretive approach, employing in-depth interviews with eight PPMs was undertaken and analysed using thematic analysis. A feminist theoretical framework was used to underpin the research.ResultsThe majority of reports made to AHPRA occurred when midwives supported women who chose care considered outside the recommended Australian College of Midwives (ACM) Consultation and Referral Guidelines. During data analysis an overarching theme emerged, “Caught between women and the system”, which described the participants’ feelings of working as a PPM in Australia. There were six themes and several sub-themes: The suppression of midwifery, A flawed system, Lack of support, Devastation on so many levels, Making changes in the aftermath and Walking a tight rope forever. The findings from this study reveal that midwives who are under investigation suffer from emotional and psychological distress. Understanding the effects of the process of investigation is important to improve the quality of professional and personal support available to PPMs who are reported to AHPRA and to streamline processes.ConclusionIt is becoming increasingly difficult for PPMs to support the wishes and needs of individual women and also meet the requirements of the regulators, as well as the increasingly risk averse health service.     

A Path Analytic Model of a Theory of Quality Management Underlying the Deming Management Method: Preliminary Empirical Findings*

Despite the impact that Deming and his 14 Points have had on the practice of quality management, empirical support for the effectiveness of the Deming Management Method has not advanced beyond the presentation of anecdotal, case-study evidence. In part, this is because theory to guide the conduct of empirical research has not been available. Only recently has such a theory of quality management to describe and explain the effectiveness of the Deming Management Method been articulated in the literature. This paper continues the journey of theory development; it reports the results of an exploratory empirical analysis of an articulated theory of quality management underlying the Deming Management Method. The constructs in the proposed theory are operationalized using measurement statements developed by the World-Class Manufacturing research project team at the University of Minnesota and Iowa State University. Path analysis is applied to the World-Class Manufacturing project data to explore the empirical strength of relationships advanced in the theory. The path analytic results provide support for several of the proposed relationships in the theory, and more importantly, suggest a number of new relationships which have not heretofore been proposed.     

A Decision Model for the Robot Selection Problem Using Robust Regression*

Industrial robots are increasingly used by many manufacturing firms. The number of robot manufacturers has also increased with many of these firms now offering a wide range of models. A potential user is thus faced with many options in both performance and cost. This paper proposes a decision model for the robot selection problem. The proposed model uses robust regression to identify, based on manufacturers' specifications, the robots that are the better performers for a given cost. Robust regression is used because it identifies and is resistant to the effects of outlying observations, key components in the proposed model. The robots selected by the model become candidates for testing to verify manufacturers' specifications. The model is tested on a real data set and an example is presented.     

A Generalization of Wendell's Tolerance Approach to Sensitivity Analysis in Linear Programming

A criticism of linear programming has been that the data which are available in practice are too inexact and unreliable for linear programming to properly work. Managers are therefore concerned with how much actual values may differ from the estimates that were used in the model before the results become irrelevant. Sensitivity analysis emerged to help deal with the uncertainties inherent in the linear programming model. However, the ranges calculated are generally valid only when a single coefficient is varied. An extension of sensitivity analysis, the 100 Percent Rule, allows the simultaneous variation of more than one element in a vector, but does not permit the independent variation of the elements. A tolerance approach to sensitivity analysis enables the consideration of simultaneous and independent change of more than one coefficient. However, the ranges developed are unnecessarily restricted and may be reduced in width to zero when primal or dual degeneracy exists. This paper presents an extension of the tolerance approach which reduces the limitations of both the traditional and tolerance approaches to sensitivity analysis.     

Some Comments on the Validity of EOQ Formula under Inflationary Conditions

In an earlier issue of Decision Sciences, Jesse, Mitra, and Cox [1] examined the impact of inflationary conditions on the economic order quantity (EOQ) formula. Specifically, the authors analyzed the effect of inflation on order quantity decisions by means of a model that takes into account both inflationary trends and time discounting (over an infinite time horizon). In their analysis, the authors utilized two models: Current-dollars model and Constant-dollars model. These models were derived, of course, by setting up a total cost equation in the usual manner then finding the optimum order quantity that minimizes the total cost. Jesse, Mitra, and Cox [1] found that EOQ is approximately the same under both conditions; with or without inflation. However, we disagree with the conclusion drawn by [2] and show that EOQ will be different under inflationary conditions, provided that the inflationary conditions are properly accounted for in the formulation of the total cost model.     

Pearson-Tukey Three-Point Approximations Versus Monte Carlo Simulation

Accuracy of the Pearson-Tukey three-point approximation is measured in units of standard deviation and compared with that of Monte Carlo simulation. Using a variety of well-known distributions, comparisons are made for the mean of a random variable and for common functions of one and two random variables. Comparisons are also made for the mean of an assortment of risk-analysis (Monte Carlo) models drawn from the literature. The results suggest that the Pearson-Tukey approximation is a useful alternative to simulation in risk-analysis situations.     

When Restrictive Constraints Are Nonbinding: Illustrations and Implications

For convex and concave mathematical programs restrictive constraints (i.e., their deletion would change the optimum) will always be binding at the optimum, and vice versa. Less well-known is the fact that this property does not hold more generally, even for problems with convex feasible sets. This paper demonstrates the latter fact using numerical illustrations of common classes of problems. It then discusses the implications for public policy analysis, econometric estimation, and solution algorithms.     

Sensitivity Analysis in Linear Programming Models with Common Inputs

The importance of sensitivity analysis information in linear programming has been stressed in the management science literature for some time. Indeed, Gal [3] has devoted an entire text to just this issue. Linear programs with common inputs (cost coefficients or right-hand-side values) present a problem in that classical sensitivity analysis does not allow for the simultaneous changes required to determine the sensitivity of these models to common inputs. We first survey the approaches previously developed for simultaneous-change sensitivity analysis and cast them in the framework of the special common input case. These general techniques are compared to a simple aggregate variable technique that has not received attention in the literature.