Margareta Soismaa

On the Use of Value Efficiency Analysis and Some Further Developments

The purpose of this paper is to discuss the use of Value Efficiency Analysis (VEA) in efficiency evaluation when preference information is taken into account. Value efficiency analysis is an approach, which applies the ideas developed for Multiple Objective Linear Programming (MOLP) to Data Envelopment Analysis (DEA). Preference information is given through the desirable structure of input- and output-values. The same values can be used for all units under evaluation or the values can be specific for each unit. A decision-maker can specify the input- and output-values subjectively without any support or (s)he can use a multiple criteria support system to assist him/her to find those values on the efficient frontier. The underlying assumption is that the most preferred values maximize the decision-makers implicitly known value function in a production possibility set or a subset. The purpose of value efficiency analysis is to estimate a need to increase outputs and/or decrease inputs for reaching the indifference contour of the value function at the optimum. In this paper, we briefly review the main ideas in value efficiency analysis and discuss practical aspects related to the use of value efficiency analysis. We also consider some extensions.

A multiple criteria model for pricing alcoholic beverages

Abstract In this paper we discuss the problem of determining optimal price changes in an alcohol sales monopoly. In Finland, the pricing of alcoholic beverages is entrusted to a State Monopoly (Alko Ltd.). The price decisions are considered to be among the most important alcohol policy measures. The pricing problem is not only a profit maximization problem. Other relevant objectives include the restriction of sales with the intention of reducing harmful effects due to alcohol consumption, and the minimization of the impact of price increases on the consumer price index. A multiple criteria model for finding the most preferred solution for the problem of pricing alcoholic beverages is developed. The model includes three criteria: profit (max.), consumption of absolute alcohol (min.), and impact on the consumer price index (min.). Using logarithms of relative changes instead of absolute criterion values makes it possible to operate with a fully linear model. The model can be solved by using any existing multiple criteria decision method. Reflecting our own bias, we use a visual interactive goal programming method developed by Korhonen and Laakso [3] and further refined by Korhonen and Wallenius [4]. The method is implemented on an IBM/PC1 under the name VIG (Visual Interactive Goal Programming).

Investment and harvest strategies of the Finnish forest sector under different forest-tax policies: A differential game approach with computer-based decision aid

Abstract This study deals with the simultaneous solution of the investment, harvest, and taxation problems of the Finnish forest sector. These strategic questions involve competitive and contradictory interests among forestry, the forest industry, and society. We build a computer-based decision aid to support a decision maker who wants to analyze the consequences of different forest-tax policies. It is essential to this computational approach that only minor mathematical manipulations are needed to produce equilibrium open-loop Nash harvest and investment strategies. Moreover, as a differential-game approach it allows us to study the tax incidence. We solve our model under three alternative tax policies: lump-sum, unit, and yield taxes.

A note on efficient solutions for the linear bilevel programming problem

The solutions of linear bilevel programming problems frequently are non-Pareto-optimal. The potential increase in payoffs generated by Pareto improvements makes it worthwhile to consider methods with which to move the solution to the efficient frontier. Bargaining models offer one class of solutions, which, contrary to the original non-cooperative, sequential decision-making situation, however, assume cooperation. We make an attempt to maintain the original power structure by introducing the asymmetric Nash bargaining solution.

Rank order for a rehabilitation program using multiple criteria

In this study we investigate an urban planning problem where an area is to be rehabilitated. The area is divided into several subareas any of which could be the starting point for the rehabilitation process. The ultimate goal is to find a rank order for the alternative subareas which specifies the rehabilitation process. If all information were given on the ordinal scale, we could use, for example, the classical minimum violation principle to solve this problem. In this paper, we have generalized this approach to cover the cardinal scale and pairwise information.