Several studies this past decade have examined differences between holistic and decomposed approaches to determining weights in additive utility models. Some have argued that it matters little which procedure is used, whereas others strongly favored particular methods. In this paper we address this controversy experimentally by comparing five conceptually different approaches in terms of their weights and predictive ability. The five methods are (1) multiple linear and non-linear regression analyses of ten and fifteen holistic assessments, (2) direct decomposed tradeoffs as proposed by Keeney and Raiffa (Keeney, R. L., H. Raiffa. 1977. Decisions with Multiple Objectives. Wiley, New York.), (3) a recent eigen-vector technique of Saaty (Saaty, T. L. 1977. A scaling method for priorities in hierarchical structures. J. Math. Psych. 15 (3) 234–281.) involving redundant pairwise comparisons of attributes, (4) a straightforward allocation of hundred importance points, and (5) unit weighting (i.e., equal weighting after standardizing the attributes). The decision task involved college admissions. Subjects were asked to evaluate hypothetical college applicants on the basis of verbal SAT, quantitative SAT, high-school grade point average, and a measure of extra-curricular activity. Linear as well as nonlinear attribute utility functions were used in constructing the additive models. The nonlinear functions were specified graphically by the subjects through selection from five different shapes (i.e., one per attribute). To test the predictive ability of the various models, each subject made twenty separate pairwise comparisons of alternatives (including direction and strength of preference). The prediction criteria were percentage correct predictions as well as correlations (using these twenty pairs). Seventy subjects were tested, using an (order-controlled) within-subject design, in comparing the different methods of weight determination. Monetary incentives were used to enhance motivation. In terms of findings, the methods generally differed systematically concerning the weights given to the various attributes, as well as the variances of the resulting predictions. On average, however, the methods predicted about equally well, except for unit weighting which was clearly inferior. The findings differ in this regard from the general literature. Furthermore, nonlinear models were found to be inferior to linear ones. Finally, subjects judged the methods to differ significantly in difficulty and trustworthiness, which were found to correlate inversely. The overall results raise various applied and theoretical issues, which are discussed.

This paper investigates the efficiency of antithetic variate simulation for estimating the expected completion time of stochastic networks. The method is compared with Monte Carlo simulation and considers both computation effort and the variance of the estimators. An efficiency ratio is first developed and then investigated within a theoretical framework. We then provide analytical proof of the superiority of the antithetic variate method for some networks whose activity durations are distributed symmetrically about their means. Next, experimental analysis of the efficiency ratio is carried out using test networks that are randomly structured and whose activity distributions are randomly assigned. The study shows that on the average the antithetic variate method can provide the same precision as Monte Carlo simulation, but with approximately 1/4 the computation effort. Furthermore, when activity distributions are symmetric, we can expect the antithetic variate method to require less than 1/10 the computation effort.

We devise and apply a new method for estimating demand for local public goods from survey data. Individuals' responses to questions about whether they wanted more, less, or the same amount of various local public goods are combined with observations of their incomes, tax rates, and the amounts of actual spending in their home communities. Parameter estimates turn out to be quite similar to those found with studies like Bergstrom and Goodman's study based on total expenditures across communities.

W. S. Hopwood, J. C. Mckeown, P. Newbold, The Additional Information Content of Quarterly Earnings Reports: Intertemporal Disaggregation, Journal of Accounting Research, Vol. 20, No. 2, Part I (Autumn, 1982), pp. 343-349

Noting that a suggested measure of natural resource scarcity, resource rent, is unobservable, we show that rent is linked to (observable) marginal exploration cost. A two-period model of extraction and exploration reveals that rent is equal to this cost when discovery is certain. Under risky exploration, cost data can be used to bound rent. The model also indicates how exploration uncertainty affects the competitive firm's extraction and exploration decisions. Finally, the behavior of U.S. oil and gas exploration costs suggests that these costs were rising in the postwar era, which has different implications for scarcity than indicated by other measures of scarcity.

Samuel E. Bodily, Chelsea C. White, Optimal Consumption and Portfolio Strategies in a Discrete-Time Model with Summary-Dependent Preferences, The Journal of Financial and Quantitative Analysis, Vol. 17, No. 1 (Mar., 1982), pp. 1-14

It is found that the welfare gain per unit of revenue raised is maximized for an export tariff on technology transfer, followed by an import tariff on goods, with an export tariff on goods the poorest policy alternative. These results are derived within a monopolistic competition model, where the production of any good requires some initial research and development (R&D), and technology transfer occurs when R&D is done in one country for production of goods in the other. An intuitive explanation is presented, based on the public-good nature of R&D and also the elasticity of demand for technologies from firms.

This study compares the relative accuracy and practical utility of seven different job evaluation approaches. Results of 657 position evaluations indicate that traditional and hybrid systems are at least as accurate, reliable, and objective in predicting grade level as are statistical policy-capturing methods when based on a standardized job analysis tool.

In this study of employees in five multinational corporations, assessment was made of (a) employees' beliefs regarding the types of personal information stored by their companies, (b) the accuracy of those perceptions, (c) reactions to various internal and external uses of this personal information, and (d) evaluations of the companies' information handling policies and practices.