A framework to measure relative performance of Indian technical institutions using integrated fuzzy AHP and COPRAS methodology

There are many opportunities and challenges in area of Indian technical education due to liberalization and globalization of economy. One of these challenges is how to assess performance of technical institutions based on multiple criteria. This paper is focused on performance evaluation and ranking of seven Indian Institute of Technology (IITs) in respect to stakeholders’ preference using an integrated model consisting of fuzzy AHP and COPRAS. Findings based on 2007–2008 data show that performance of two IITs need considerable improvement. To the best of our knowledge it is one of few studies that evaluates performance of technical institutions in India.     

Who Loses when Prices are Negotiated? An Analysis of the New Car Market

We establish that there are large and persistent differences in final transaction prices for identical new cars, and that demographic characteristics explain at least 20% of the observed variation. Older consumers perform progressively worse in negotiations, and the age premium is greater for women than for men. Our results suggest that the complex nature of vehicle transactions leads to price dispersion in this market, and that the worst performing groups—older women—have the lowest rates of market participation. We conjecture that the results are driven by the sharp increases in women's education and labor force participation in recent decades.     

Speed-profile-based road segmentation for accident occurrence modelling for hilly terrains

Modelling the accident occurrences per unit length of the road requires segmentation of road stretch. In the case of hilly terrains, homogeneity-based approach results in extremely small sections thus creating a biased accident data. This result is due to the high variations in geometry along the length of the road stretch. Constant length sections do not consider the effect of road's characteristics, hence may lead to undesirable results. It is hypothesized that the speed profile of a vehicle moving in free-flow conditions is governed by the road geometry as well as the road side environment. In this paper, a new methodology based on speed profile of a test vehicle (passenger car) has been proposed for segmenting a road stretch passing through hilly terrain. Comparative analysis of the results obtained from the constant length segmentation approach and the proposed approach shows that the later approach is producing statistically better results. Relatively more parameters were found to be statistically significant in the model based on speed-profile-based segmentation. Grade length, which could be one of the major parameters in hilly terrains, was found to be statistically significant only in the model based on speed-profile-based segmentation.     

A Comparison of the Power of Parametric and Nonparametric Tests of Location Shift for Event Studies

This paper distinguishes between testing approach (parametric t, sign, cross-sectional rank, and longitudinal rank) and test type (conventional, standardized, and weighted least squares). Similar tests (i.e., tests of the same type) are compared for each testing approach using constant and unequal shift models. Thus the results given here are free of confounding effects present in prior comparisons of dissimilar tests. While all the tests compared are sensitive to the underlying location shift model, if the shift is independent of the security standard deviation, then the weighted least squares longitudinal rank test is most. powerful.     

Dynamic modelling of agroforestry and soil fertility interactions: implications for multi-disciplinary research policy

This paper attempts to contribute to one of the major aspects of international research agenda in agroforestry. A general framework is developed in this paper to capture the dynamic interactions of various components of agroforestry system. Using a multi-seasonal model of agroforestry, the competition among the system components in resource and input use and the trade-offs between different outputs of agroforestry system are analyzed. Policy implications for multi-disciplinary research are derived. It is argued that quantifying the potential benefits of agroforestry system requires reformulation of existing economic methods of analyzing agroforestry technology to contribute to the fuller understanding of the dynamic interactions among its various components.     

Model selection in univariate time series forecasting using discriminant analysis

When a large number of time series are to be forecast on a regular basis, as in large scale inventory management or production control, the appropriate choice of a forecast model is important as it has the potential for large cost savings through improved accuracy. A possible solution to this problem is to select one best forecast model for all the series in the dataset. Alternatively one may develop a rule that will select the best model for each series. Fildes (1989) calls the former an aggregate selection rule and the latter an individual selection rule. In this paper we develop an individual selection rule using discriminant analysis and compare its performance to aggregate selection for the quarterly series of the M-Competition data. A number of forecast accuracy measures are used for the evaluation and confidence intervals for them are constructed using bootstrapping. The results indicate that the individual selection rule based on discriminant scores is more accurate, and sometimes significantly so, than any aggregate selection method.     

Hybrid Choice Models: Progress and Challenges

We discuss the development of predictive choice models that go beyond the random utility model in its narrowest formulation. Such approaches incorporate several elements of cognitive process that have been identified as important to the choice process, including strong dependence on history and context, perception formation, and latent constraints. A flexible and practical hybrid choice model is presented that integrates many types of discrete choice modeling methods, draws on different types of data, and allows for flexible disturbances and explicit modeling of latent psychological explanatory variables, heterogeneity, and latent segmentation. Both progress and challenges related to the development of the hybrid choice model are presented.     

Comparison of test vs. control treatments using distance optimality criterion

We consider the problem of comparison of one test treatment (τ₀) with a set of v control treatments (τ₁, τ₂, …, τ_v) using distance optimality [DS-optimality] criterion introduced by Sinha (1970) in some treatment-connected design settings. It turns out that the nature of DS-optimal designs is quite similar to that for the usual A−, D− and E− optimality criteria. However, the optimality problem is quite complicated in most situations. First we deal with the CRD model and derive DS-optimal allocations for a given set of treatments. The results are almost identical to the A-optimal allocations for such problems. Then we consider a block design set-up and examine the nature of DS-optimal designs. In the process, we introduce the method of weighted coverage probability and maximize the resulting expression to obtain an optimal design. Received: December 1999     

A new approach to determining sectoral priorities in an economy: input–Output elasticities

This paper uses input–Output elasticities to identify important economic sectors. Elasticities of output employment and income are used to identify key sectors of the Greek economy. A comparison of the rankings of economic sectors based on input–output elasticities with those based on net backward linkages indicates significant divergence in sectoral rankings obtained from the two approaches. The elasticity approach yields more consistent estimates of sectoral output employment and income potentials than the net backward linkage approach. Measured in terms of the potential to generate output employment and income agriculture services and textiles are found to be the key sectors for the Greek economy.