A technique using analytical hierarchy process in multiobjective planning models

Social and economic planning usually includes the need to consider and reconcile multiple, conflicting objectives. A number of multiple objective planning models have been proposed, using goal programming as well as other multiple objective techniques. Goal programming provides a useful tool which quickly provides a solution matching the set of ranked objective targets provided, but does not provide much exploratory analysis of planning problems. Other techniques have been used which provide generation of new alternatives for consideration, but these other techniques often are limited to original model extreme points. This paper presents an alternative means of generating planning alternatives, utilizing Analytic Hierarchy Process as a means of obtaining a good starting point, and imposition of objective attainment levels through constraints. The proposed process provides a means of decision maker learning, easily allows adjustment of objective attainment levels and is not limited to the original model extreme points.     

Essential new PLS-SEM analysis methods for your entrepreneurship analytical toolbox

Rigorous research across the wide spectrum of entrepreneurship is important for developing knowledge and innovation in the field, which in turn offers building blocks for future inquiry, practice, innovation, and economic growth. For this reason, scholars continually seek new empirical analysis tools to examine constructs and variables included in their research. While many familiar tools remain at the core of the scholar’s tool box, PLS-SEM offers valuable options that have been accentuated by recent developments. This article provides a thorough review of PLS-SEM and its application to current entrepreneurship research, summarizes the emergent confirmatory composite analysis (CCA) processes for applying and interpreting the analysis, explains why PLS-SEM can be especially advantageous for research in this field, and concludes with suggestions for scholars as they plan future research projects. In addition, recent PLS-SEM developments are shared that may effectively apply to entrepreneurship research.

     

Labor market search and capital accumulation: Some analytical results

This paper integrates labor market search into an intertemporal utility maximization framework and analytically solves for equilibrium dynamics. The integrated model improves upon a neoclassical model by generating the realistic hump-shaped response of output to a productivity shock and the counterclockwise dynamics of job vacancies and unemployment around the Beveridge curve. In contrast to a standard search model, our model endogenizes agents' reservation wage as the marginal rate of substitution between leisure and consumption, through which agents' intertemporal consumption decision directly affects the labor market behavior. As a result, even a permanent productivity shock generates non-monotonic dynamics in employment.     

Some tests for the constancy of regressions under heteroscedasticity

For testing the equality of coefficients of a linear regression model under heteroscedasticity, we suggest an F criterion conditioned on the posterior mean of the ratio of standard deviations of error terms in two subsamples. For pairable subsamples, and exact F test is derived. Sampling experiments show that the Chow test differs substantially from the nominal significance level when the two subsample sizes are unequal, and that the F test conditioned on the posterior mean is superior to other tests when sample sizes are small.     

Detecting a shift in location: Some robust tests

The test statistic W, suggested by Hawkins (1977) and Worsley (1979) for testing a sequence of observations for a shift in location, is sensitive to the assumption that the distribution of the population being sampled is normal. A modification of this statistic is proposed which is robust against ‘heavy tailed’ distributions. We also study the performance of several alternative testing procedures by means of a simulation experiment. The Farley-Hinich test (1975) and the Homogeneity test discussed in Brown, Durbin and Evans (1975) perform well in the Simulation experiment against ‘heavy tailed’ distributions. Some applications to economic data are also discussed in the paper.     

Some robust exact results on sample autocorrelations and tests of randomness

Several exact results on the second moments of sample autocorrelations, for both Gaussian and non-Gaussian series, are presented. General formulae for the means, variances and covariances of sample autocorrelations are given for the case where the variables in a sequence are exchangeable. Bounds for the variances and covariances of sample autocorrelations from an arbitrary random sequence are derived. Exact and explicit formulae for the variances and covariances of sample autocorrelations from a Gaussian white noise are given. It is observed that the latter results hold for all spherically symmetric distributions. A simulation experiment, with Gaussian series, indicates that normalizing each sample autocorrelation with its exact mean and variance, instead of the usual approximate moments, can improve considerably the accuracy of the asymptotic N(0,1) distribution to obtain critical values for tests of randomness. The exact second moments of rank autocorrelations are also studied.     

Some remarks on the average sample number of sequential and non-sequential tests

Summary We prove some inequalities concerning the (mean) number of observations needed to attain a prescribed error sum and apply them to some examples.     

Critical essay on the methodology of multiobjective analysis

This paper presents a discussion of methodological issues in multiobjective analysis, encompassing various approaches to multiobjective optimization and decision making. The main thesis is that while there are already many methods for multiobjective analysis, this field would gain from further methodological reflection.     

The use of multi-criteria decision-making methods in the integrated assessment of climate change: implications for IA practitioners

Integrated assessment (IA) considers interactions of physical, biological, and human systems in order to assess long-term consequences of environmental and energy policies such as limits on greenhouse gas emissions, and other strategies to negate climate change. Users of IA face the daunting task of interpreting large amounts of data and uncertainties. Multi-criteria decision-making (MCDM) methods can help users process IA data, understand policy tradeoffs, and learn how their value judgments affect decisions. We held a workshop during which climate change experts tested several MCDM methods for using IA outputs to rank hypothetical policies for abating greenhouse gas emissions. Participants also evaluated several methods for visualizing tradeoffs under both certainty and uncertainty cases. This paper explores potential roles for MCDM in IA identified during the workshop, along with implications for IA design and implementation. We summarize the workshops’ results regarding intertemporal discounting (a type of MCDM weighting judgment), visualization of impacts, how MCDM methods can help users to incorporate their background knowledge, and how MCDM can improve understanding of tradeoffs and the importance of value judgments. A key result is that the interest rates IA experts recommend for discounting future impacts depend strongly on what type of impact is being discounted, as well as upon the exact phrasing of questions used to elicit rates from the experts.     

Some new mathematical methods in dynamic programming over infinite horizon

Two properties of the potentialsU(x, y) are studied. They are the acyclicity and the strong convexity. By mean of them, information on the dynamic behavior of the optimal choice functions is obtained. The previous results are then applied,via Dynamic Programming, to the models of optimization over an infinite horizon (discounted Ramsey models). Qualitative information on the dynamics in such models is derived and some new stability results are given.

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Riassunto Nel presente lavoro vengono proposte due proprietà dei potenzialiU(x, y): l'aciclicità e la convessità forte. Entrambe permettono di ottenere informazioni sul comportamento dinamico delle funzioni di scelta ottimale .La precedente teoria viene poi applicata, utilizzando la programmazione dinamica, al problema di dedurre informazioni qualitative sulle dinamiche nei modelli di ottimizzazione ad orizzonte infinito (modelli di Ramsey con utilità scontate). Si ottengono in questo modo alcuni nuovi risultati di stabilità delle soluzioni in questo modello.

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The research of the author was partially supported by a grant from the «Ministero della Pubblica Istruzione». A first version of this paper was delivered at the «VIII Convegno A.M.A. S.E.S., Modena 26–29 September 1984». In am grateful to E. Castagnoli and P. Mazzoleni for helpful suggestions. For any remaining errors, I am entirely responsible.     

Some simple structure significance tests for exploratory component analysis with market survey data

Several uncertainties continue to hinder researchers using exploratory factor analysis. Among other decisions, the choice of the number of factors to retain and the interpretability of the rotated solution remain problematical. In this paper, we suggest a simple structure criterion as a general framework for choosing the number of factors and for interpreting the rotated factor structure matrix. The proposed methodology is demonstrated with demographic data from a consumer panel. The results show the importance of increasing the information yield from exploratory factor analysis.     

An approach to the display and analysis of multiobjective problems

In all operations research applications, the problem of implementation rests on the information conveyed to the decision maker. The presentation of results is a critical link in the success of a project. An ineffective transfer of information will reduce the chance of decision maker acceptance. This final step in the analysis is particularly difficult in multiobjective analyses, where the amount of relevent information increases with each performance measure.This paper will describe an alternative to the typical graphical approach to multiobjective display, which is adaptable to any number of objectives. A real world example is given and some theoretical insights are developed.     

A survey and critique of multiobjective power plant siting decision rules

This paper reviews the use of multiobjective decision rules for solving power plant siting problems. After a discussion of exclusionary site screening methods for bounding the decision space, classes of multiobjective and goal programming desicion rules are discussedin the context of final site selection. Advances and limitations of these methods are highlighted. Although multiobjective decision rules have seen numerous applications to power plant siting in the literature, few electric utility companies have used these methods in practice. A review of the use of multiobjective methods in actual power plant siting decisions is also presented, and reasons for the paucity of real-world applications are suggested.     

Some methods for assessing the need for non-linear models in business cycle analysis

It is often suggested that non-linear models are needed to capture business cycle features. In this paper, we subject this view to some critical analysis. We examine two types of non-linear models designed to capture the bounce-back effect in US expansions. This means that these non-linear models produce an improved explanation of the shape of expansions over that provided by linear models. But this is at the expense of making expansions last much longer than they do in reality. Interestingly, the fitted models seem to be influenced by a single point in 1958 when a large negative growth rate in GDP was followed by good positive growth in the next quarter. This seems to have become embedded as a population characteristic and results in overly long and strong expansions. That feature is likely to be a problem for forecasting if another large negative growth rate was observed.     

On the suitability of income inequality measures for regional analysis: Some evidence from simulation analysis and bootstrapping tests

The paper looks at the sensitivity of commonly used income inequality measures to changes in the ranking, size and number of regions into which a country is divided. During the analysis, several test distributions of populations and incomes are compared with a ‘reference’ distribution, characterized by an even distribution of population across regional subdivisions. Random permutation tests are also run to determine whether inequality measures commonly used in regional analysis produce meaningful estimates when applied to regions of different population size. The results show that only the population weighted coefficient of variation (Williamson’s index) and population-weighted Gini coefficient may be considered sufficiently reliable inequality measures, when applied to countries with a small number of regions and with varying population sizes.