Dileep G. Dhavale

Integrating Fuzzy C-Means and TOPSIS for performance evaluation: An application and comparative analysis

In this paper we introduce a multi-method multiple criteria approach for evaluating the performance of organizations. Performance analysis may include both strategic and operational performance, as well as financial and other less tangible factors. This paper introduces the use of Fuzzy C-Means and TOPSIS for organizational performance evaluation purposes. Using real company data and balanced scorecard accounting and performance dimensions the methodology is applied and evaluated. The predictive abilities of the technique from an organizational performance evaluation approach are evaluated using this data. One of the results from the illustrative application is that economic performance evaluation is not the best predictor of overall viability of some organizations, especially e-commerce based organizations.

Complex investment decisions using rough set and fuzzy c-means: An example of investment in green supply chains

Green supplier development focuses on helping organizations integrate activities to improve the natural environmental performance of their supply chains. These green-supplier-development programs require substantial resources and investments by a buyer company. Investigation into investment management in this context has only begun. This paper introduces a methodology to help manage investment in green-supplier-development and business-supplier-development practices. Managing these practices and their outcomes requires managing of a large sets of data. We propose a combination of rough set theoretic and fuzzy clustering means (FCM) approaches; first to simplify, and then sharpen the focus on the complex environment of evaluation of the investment decisions. The combined methodology, based on performance measures of supplier practices and agreed-upon investment objectives, identifies a set of guidelines that can help make decisions about sound investments in the supplier practices more effectively and judiciously. Various steps involved in the methodology are illustrated through using an example developed to highlight the salient steps and issues of the methodology. We show how the results may be interpreted to obtain many insights useful from both practical and research perspectives. Although the impetus to developing this methodology came from sustainability considerations, the methodology is general enough to be applicable in other areas where management and evaluation of investments is based on large data sets.

A Note on the Severity of the Decline in Union Organizing Activity

Using data on representation elections conducted by the National Labor Relations Board from 1975 to 1987, the authors examine the extent of the recent decline in union organizing activity. An analysis of elections for selected unions and in major industry categories shows no widespread recovery from the sharp drop in organizing that occurred from 1981 to 1982. Although union success rates in new units have been fairly constant, the low number of new members recruited through elections points to a continuation of the downward trend in union density.

The choice between union membership and free-rider status

Free riders are employees who are covered by collective bargaining agreements but are not union members. This article examines the choice between free-rider status and union membership. A discriminant analysis of data from the 1988Current Population Survey identifies employee characteristics that distinguish free riders from union members. Factors influencing the decision to be a free rider, including the knowledge of available options, the preferential treatment of union members, the value of reputation, and union consciousness are discussed. A probit analysis determines the extent to which earnings and proxy measures for the value of reputation and union consciousness affect free-rider status. Suggestions are made for extending the study of the free riders and for the design of internal organizing campaigns.

A Manufacturing Cost Model for Computer‐integrated Manufacturing Systems

The product‐costing techniques developed for conventional job shops are unsuitable for use in computer‐integrated manufacturing systems (CIMS) and their continued use in the CIMS environment generates incorrect and misleading manufacturing costs. A new cost model particularly suited for CIMS that also satisfies all financial accounting requirements is described. The model has two components of manufacturing cost, direct material cost and transformation cost, instead of three in the conventional method, and uses actual machine usage to calculate manufacturing costs. To effect accurate allocation of the transformation cost, first to each machine and then to the product that uses the machine, intermediate pooling of costs and different allocation bases are used. A numerical example is presented to clarify the steps in the procedure.

The changing scope of union organizing

This paper presents a profile of the change in the scope of union organizing and provides empirical support for the numerous observations about the declining importance of jurisdictions in the selection of organizing targets. The scope of organizing is measured in terms of the distributions of the NLRB certification elections of 18 selected unions for 1973–1975 and 1983–1985. Diversity and concentration in organizing and its impact on election outcome are examined.

Integrating carbon market uncertainties into a sustainable manufacturing investment decision: a Bayesian NPV approach

Net present value (NPV) is a widely used technique in capital budgeting. In this paper, we develop a Bayesian NPV framework using a Gibbs sampler. This approach allows decision-makers to integrate their knowledge, past experience, and uncertain and volatile cash flows from carbon emissions credits into decisions dealing with energy efficient, sustainable manufacturing equipment. The results indicate NPV is highly dependent on the nature of volatility and uncertainty of the cash flows. Without inclusion of this information through the Bayesian framework results, NPV becomes overstated, and thus it may provide biased guidance for the investment. The results developed in this paper further show that the frequency of very high and low cash flows and to a lesser degree their variability adversely impacts NPV. The results may also explain reasons for the economic phenomenon known as the energy efficiency gap.

Stochastic internal rate of return on investments in sustainable assets generating carbon credits

Abstract Internal rate of return (IRR) is a widely used tool in ranking capital budgeting projects and eventual accept or reject decisions. In this paper, we consider an investment decision involving a sustainable, energy efficient, greenhouse gases (GHG) reducing asset and incorporate the value of carbon emission allowances for the investing company. These allowances create cash flows that may be characterized by significant volatility and uncertainty. The methodology developed in this paper allows decision makers to integrate their knowledge of carbon trading markets and the cash flows that result from sale of emissions credits. The novel methodology utilizes a Bayesian model for IRR that uses Gibbs sampler. Analysis of the results shows that IRR is influenced by volatility and uncertainty of carbon credit cash flows. Ignoring those uncertainty characteristics and simply using the expected values of cash flows can result in significantly inaccurate investment rate of returns. When compared to deterministic IRR calculations, the results show that the occurrence of very high and very low cash flows affects IRR positively, whereas higher variability of cash flow distribution affects IRR of GHG-reducing asset negatively. In other words, frequent large or small cash flows are preferred over fluctuating cash flows. The results may also provide a rationale for the existence of an anomalous consumer behavior known as the energy efficiency gap.

Computational approaches to estimating negative binomial parameters from count data

A FORTRAN program is presented that estimates parameters of the negative binomial distribution from count data using different methods of estimation. The program also computes negative binomial pro...

Scrap minimization in production processes with stochastic outputs

Abstract Occurrence of scrap due to uncertainties in a production process is considered in this paper. Two raw materials undergo preparatory processing before they are combined in a definite ratio to make a final product. During the processing, the materials expand or shrink by random amounts, so that at the end of the process one or the other material is in excess. This excess is worthless and is scrapped. A model is developed for the optimal ex ante ratio of the raw materials that would minimize the expected cost of scrap. Data from a field study are used to illustrate the effectiveness of the model.