Some results concerning the quality of vertex solutions found by a method for multiple-objective linear programming

The Zionts-Wallenius algorithm for multiple-objective linear programming terminates with an extreme point solution that is locally but not necessary globally optimal. To find the globally optimal solution, a search along the facets of the solution space polyhedron may be required. In this paper we report the results of an experiment to determine how close the local and global optima are. We discuss the concept of closeness and propose one measure. Computer simulation is used to determine, in general, the quality of the solution found by the Zionts-Wallenius method for two types of non-linear utility functions. The merits of a search procedure are discussed in the context of the results.     

Future‐focussed thinking: combining scenario planning with decision analysis

This paper first describes current practice in decision analysis and argues that nothing in the technique's application is likely to challenge the strategic decision maker's current worldview of the course of future events that are modelled in the decision tree. By contrast, a scenario planning intervention in an organization has the potential to increase perceived threat and thus lead to a step change in strategic decision making. Strategic decisions are made against a backcloth of the operation of psychological processes that act, it is argued, to reduce the perceived level of environmental threat and result in strategic inertia. For this reason, it is recommended that scenario planning should be adopted as a standard procedure because of its ability to challenge individual and organizational worldviews. The use of scenario planning prior to conventional decision analysis is termed as ‘future‐focussed thinking’, and parallels are drawn between the current advocated approach and that of Keeney's value‐focussed thinking. Both serve to prompt the creation of enhanced options for subsequent evaluation by conventional decision analytic techniques. Copyright © 1999 John Wiley & Sons, Ltd.     

Valuing the future: a MADA example involving nuclear waste storage

Intertemporal decision making involves decisions that have consequences that span several periods of time and often extend far into the future. The purpose of this paper is to discuss and highlight the differences associated with different evaluation methods designed to cope with the long-term impacts of a decision including discounting. The concepts and ideas are illustrated in the context of a decision about a nuclear waste facility. We show how applying different discounting methodologies can greatly affect the decision made, especially over long time periods. © 1998 John Wiley & Sons, Ltd.     

Optimal trade-offs of multiple factors in transfer pricing problems

Transfer pricing problems have been extensively researched by a number of scholars. It is well recognized that transfer pricing problems have a multiple-criteria (objectives) feature and can be formulated as a model of multiple-criteria linear programming. However, few methods have the capability of dealing with all possible optimal trade-offs of multiple criteria in optimal solutions of the models. In this paper a linear multiple-factor model is developed to provide managers with a more systematic and comprehensive scenario of all possible optimal transfer prices depending on both multiple criteria and multiple constraint levels. The trade-offs of all possible optimal transfer prices can be used as a basis for managers of a corporation to make a high-quality decision in selecting their transfer pricing systems for business competition. © 1998 John Wiley & Sons, Ltd.     

A multiple-objective linear programming model for the citrus rootstock selection problem in Florida

Citrus is one of Florida's key agricultural crops, with annual production accounting for over 70% of all U.S. production. During the 1970s and 1980s, citrus blight, tristeza and freezes caused citrus rootstock selection to become a critical issue in Florida, and it remains so today. This paper describes a multiple-objective linear programming model that we have developed for solving the citrus roostock selection problem in Florida. The model has four objective functions. These functions, together with the constraints of the model, capture the main factors that Florida citrus growers use in choosing portfolios of rootstocks for planting in their groves. We tested the usefulness of this model by solving an experimental application for the Fort Pierce area with the interactive STEM algorithm. From our research we conclude that, when properly solved with the aid of STEM, the multiple-objective linear programming model has the potential to serve Florida citrus growers as a useful decision aid in formulating rootstock selection plans. © 1997 John Wiley & Sons, Ltd.     

A note on the use of goal programming for the multiplicative AHP

The main aim of this paper is to identify the opportunities of utilizing goal programming (GP) in the multiplicative analytic hierarchy process (MAHP). It starts with the issue of weight derivation from judgemental matrices. The use of GP for the weight derivation problem is not new, but GP is viewed in this paper from the perspective of augmenting the capabilities of the widely used row geometric mean method (RGMM) of the logarithmic least squares technique (LLST). Different possible approaches using GP are discussed. It is shown that the formulation of the GP problem can be easily modified to provide the same weights as those of the LLST. While this proposed GP technique is not superior to the RGMM in terms of computational ease or speed, it is quite useful in solving certain other problems of the MAHP, such as interval judgements and missing judgements, which cannot be readily solved by the RGMM. The proposed technique provides extensive scope for utilizing the vast literature on non-linear programming, say, for conducting sensitivity analysis. It also has the potential to be useful to more complicated issues of the MAHP, such as group decision making and interlevel dependence, hitherto little explored areas of the MAHP. © 1997 John Wiley & Sons, Ltd.     

Consumer evaluation of net utility: Effects of competition on consumer brand selection processes

This study explores how brand-related information is integrated within a competitive environment. Specifically, we develop a structural equation model of competition between two brands, which includes each brand's price-quality characteristics (i.e., net utility). The model simultaneously tests how the net utility of the focal and competing brands affects consumers' attitudes, intentions, and choice regarding the focal brand. This study extends existing research with the findings that price-quality evaluations of a focal brand and net utility perceptions of competing brands influence consumers' attitudes, intentions, and choice regarding the focal brand. Thus, in order to attract consumers to their brands, marketers should focus not only on improving the performance and net utility of their own brands, but also on studying competing brands in the marketplace.     

A Bibliographic Survey of the Activities and International Nature of Multiple Criteria Decision Making

One of the fascinating things about multiple criteria decision making (MCDM) is the degree to which the contributions that have built the field have come from all over the world. In this paper the international nature of the authorships of the 1216 refereed journal articles published on MCDM between 1987 and 1992, and the journals in which they have appeared, is examined. Also, an analysis of the 217 books and 31 journal special issues that have been published on MCDM, and 143 conferences that have been held on MCDM since the inception of the field, is similarly conducted. The paper concludes with a conference organizer, author and special issue guest editor index.     

Motivational Interviewing in Primary Care

Healthcare systems are in the process of reforming themselves to better meet the needs of people with, or at risk of developing, chronic diseases and long term conditions. One goal of these efforts is the coproduction of activated, informed, engaged and motivated patients and citizens. The clinical, public health and financial benefits of achieving such a goal may be dramatic. Motivational Interviewing (MI) is a proven and practical front-line approach which can help deliver this goal whilst also helping to deliver such policy objectives and intermediate outcomes as increased levels of patient centered care, participatory or shared decision making, evidence-based healthcare and improved clinician-patient relationships. Until now, MI has been passively diffusing through the system as a result of the innovation and early uptake by insightful individuals and organizations. If healthcare systems want to breakthrough to higher levels of performance, investment in the conscious and deliberate implementation of MI into front-line settings may prove helpful.