Merja Halme

Improving the accuracy of multisource forest inventory estimates to reducing plot location error — a multicriteria approach

Abstract A procedure is introduced to reassign satellite image information to field plot data of forest inventory by a multicriteria approach. The method can be utilised in satellite-image-aided forest inventories, e.g., as in the Finnish Multi-Source National Forest Inventory (FMS-NFI) since 1990. This inventory method presumes that the field sample plots are geographically accurately located and each individual field plot can be identified with a specific picture element of the applied satellite image. Small area estimation errors are highly sensitive to the location errors of field plots with respect to the satellite image. In spite of current GPS systems, an accurate location is extremely difficult to achieve due to map errors and errors in rectifying a satellite image on a map. Satellite image information is reassigned to the field plots within an n × n image window around the assumed location. A weighted function of the correlation coefficients of the selected image and field variables is used as a scaling function in this multicriteria optimisation approach. The root mean square errors (RMSEs) of estimates, produced with a nonparametric k -nearest-neighbour ( k -nn) estimation method, are applied as a criterion when judging the final goodness of the relocation. The relocation reduces the pixel-level RMSE of total volume per hectare by 36%.

Dealing with Interval Scale Data in Data Envelopment Analysis

This papaer considers the problem of interval scale data in the most widely used models of Data Envelopment Analysis (DEA), the CCR, and the BCC models. Radial models require inputs and outputs measured on the ratio scale. Our focus is on how to deal with interval scale variables especially when the interval scale variable is a difference of two ratio scale variables like profit or the decrease/increase in bank accounts. Using these ratio scale variables as variables in the DEA model we suggest radial models. An approach to how to deal with interval scale variables when we relax the radiality assumption is also discussed.

Estimation methods for choice-based conjoint analysis of consumer preferences

Conjoint analysis, a preference measurement method typical in marketing research, has gradually expanded to other disciplines. Choice-based conjoint analysis (CBC) is currently the most popular type. Very few alternative estimation approaches have been suggested since the introduction of the Hierarchical Bayes (HB) method for estimating CBC utility functions. Studies that compare the performance of more than one of the proposed approaches and the HB are almost non- existing. We compare the performance of four published optimization-based procedures and additionally we introduce a new one called CP. The CP is an estimation approach based on convex penalty minimization. In comparison with HB as the benchmark we use eight field data sets. We base the performance comparisons on holdout validation, i.e. predictive performance. Among the optimization based procedures CP performs best. We run simulations to compare the extent to which CP and HB can recover the true utilities. With the field data on the average, the CP and HB results are equally good. However, depending on the problem characteristics, one may perform better than the other. In terms of average performance, the other four methods were inferior to CP and HB.

Bank branch sales evaluation using extended value efficiency analysis

This article results from our collaborative project with a Finnish bank aiming to evaluate the sales performance of bank branches. The management wishes to evaluate the branches’ ability to generate profit, which rules out the pure technical efficiency considerations. The branches operate in heterogeneous environments. We deal with the heterogeneity by subdividing the branches according to the bank specification into overlapping clusters and analyze each cluster separately. The prices of the branch outputs are hard to assess as the results from the sales efforts can only be observed with long delays. We employ benchmark units similarly as in value efficiency analysis (VEA). However, we extend VEA in two ways. First, in standard VEA the benchmark unit is assumed to yield the maximum profit among the set of feasible technologies; instead, our benchmark technology may or may not be in the feasible set. Second, we consider efficiency tests employing a benchmark with respect to both profit and return. We propose a solution strategy for these extensions. The bank uses the study to support decisions concerning new branches, changes in the operations of inefficient branches, and actions aiming to more flexible deployment of the staff.

NONDOMINATED TRADEOFFS AND TERMINATION IN INTERACTIVE MULTIPLE OBJECTIVE LINEAR PROGRAMMING

This paper deals with the problem of finding, for a given nondominated solution, a set of nondominated tradeoffs. Such tradeoffs play a central role in interactive multiple objective linear programming procedures when direction-finding and termination are considered. If the current solution is preferred to all of the tradeoffs, it is optimal, provided that the decision maker’s value (utility) function is assumed to be (globally) pseudo-concave at the moment of consideration. If any of the tradeoffs is a direction of improvemet, a new search direction can be found and the procedure continues as earlier.

Likelihood estimation of consumer preferences in choice-based conjoint analysis

In marketing research the measurement of individual preferences and assessment of utility functions have long traditions. Conjoint analysis, and particularly choice-based conjoint analysis (CBC), is frequently employed for such measurement. The world today appears increasingly customer or user oriented wherefore research intensity in conjoint analysis is rapidly increasing in various fields, OR/MS being no exception. Although several optimization based approaches have been suggested since the introduction of the Hierarchical Bayes (HB) method for estimating CBC utility functions, recent comparisons indicate that challenging HB is hard. Based on likelihood maximization we propose a method called LM and compare its performance with HB using twelve field data sets. Performance comparisons are based on holdout validation, i.e. predictive performance. Average performance of LM indicates an improvement over HB and the difference is statistically significant. We also use simulation based data sets to compare the performance for parameter recovery. In terms of both predictive performance and RMSE a smaller number of questions in CBC appears to favor LM over HB.

Copyrighted Internet material in education—teacher needs and use arrangements

Teachers are in need of mechanisms to allow them routinely reproduce and distribute digitally copyrighted material. That was the starting point in the study on teachers’ Internet material use benefits in Finnish education. The study considers the use and reproduction of Internet material like text, graphs and pictures. In the study, which took place in 2005–2006, conjoint analysis was used to measure teachers’ individual benefits for different types of Internet material and special attention was given to how teachers wanted to reproduce the material as well how the price paid affected their choices. The demand for different types of uses was simulated on the basis of the benefits measured. The study interviewed a representative sample (n = 1,146) of teachers on all the levels from primary school to universities. The study produced information for all the players in the educational copyrights field. User studies of copyrighted digital goods in education or any other field are almost non-existing. We wish to highlight the value of such studies.

Using value efficiency analysis to benchmark nonhomogeneous units

We consider the problem of evaluating the performance of a set of heterogeneous units. The heterogeneity may originate from environmental conditions or the unit itself. We propose a comparison of the units with benchmark units that perform well and represent various types of heterogeneity. The benchmark units are specified by a decision maker and used as alternative most preferred units in the value efficiency analysis. Each unit is associated with the best benchmark unit, in the spirit of the data envelopment analysis. The approach simultaneously takes into account preference information and the heterogeneity of units. We developed the approach to provide a framework for quantitative performance comparison for the Helsinki parishes. The parishes have heterogeneous structures and operate in various environments leading to different emphases of outputs. The special feature of the approach is that it is does not require the characterization of the heterogeneity by quantitative measures.

Cone contraction and reference point methods for multi-criteria mixed integer optimization

Interactive approaches employing cone contraction for multi-criteria mixed integer optimization are introduced. In each iteration, the decision maker (DM) is asked to give a reference point (new aspiration levels). The subsequent Pareto optimal point is the reference point projected on the set of admissible objective vectors using a suitable scalarizing function. Thereby, the procedures solve a sequence of optimization problems with integer variables. In such a process, the DM provides additional preference information via pair-wise comparisons of Pareto optimal points identified. Using such preference information and assuming a quasiconcave and non-decreasing value function of the DM we restrict the set of admissible objective vectors by excluding subsets, which cannot improve over the solutions already found. The procedures terminate if all Pareto optimal solutions have been either generated or excluded. In this case, the best Pareto point found is an optimal solution. Such convergence is expected in the special case of pure integer optimization; indeed, numerical simulation tests with multi-criteria facility location models and knapsack problems indicate reasonably fast convergence, in particular, under a linear value function. We also propose a procedure to test whether or not a solution is a supported Pareto point (optimal under some linear value function).

Choice behavior of information services when prices are increased and decreased from reference level

The purpose of this study is to estimate the impact of price increases and decreases for three, at least partly, compensatory services. The existence of a reference effect in pricing has been commonly accepted. However, the observations of consumer choices with prices below and above the reference price have produced mixed results. Both symmetric and asymmetric behavior has been observed. The current study differs from the mainstream in the way that the object is a service and instead of scanner panel data, stated preferences measured by choice based conjoint analysis are used. Moreover, instead of dealing with changes in value caused by price changes, we consider changes in demand on the respondent level. The main outcome of the study was that with the traditional service the respondents reacted more strongly to price increases (loss) than to price decreases (gain), whereas in the two more modern services the reactions were more versatile; with the majority of respondents the reactions were stronger to price decreases (gain).