According to W. Edwards Deming, American companies require nothing less than a transformation of management style and of governmental relations with industry. In Out of the Crisis, originally published in 1982, Deming offers a theory of management based on his famous 14 Points for Management. Management's failure to plan for the future, he claims, brings about loss of market, which brings about loss of jobs. Management must be judged not only by the quarterly dividend, but by innovative plans to stay in business, protect investment, ensure future dividends, and provide more jobs through improved product and service. In simple, direct language, he explains the principles of management transformation and how to apply them.

Out of the Crisis

(1991). Soft Systems Methodology in Action. European Journal of Information Systems: Vol. 1, No. 3, pp. 215-216.

https://link.springer.com/content/pdf/10.1057%2Fejis.1991.37.pdf

Soft Systems Methodology in Action

In this paper, we address several issues related to the use of data envelopment analysis (DEA). These issues include model orientation, input and output selection/definition, the use of mixed and raw data, and the number of inputs and outputs to use versus the number of decision making units (DMUs). We believe that within the DEA community, researchers, practitioners, and reviewers may have concerns and, in many cases, incorrect views about these issues. Some of the concerns stem from what is perceived as being the purpose of the DEA exercise. While the DEA frontier can rightly be viewed as a production frontier, it must be remembered that ultimately DEA is a method for performance evaluation and benchmarking against best-practice. DEA can be viewed as a tool for multiple-criteria evaluation problems where DMUs are alternatives and each DMU is represented by its performance in multiple criteria which are coined/classified as DEA inputs and outputs. The purpose of this paper is to offer some clarification and direction on these matters.

http://www.deafrontier.net/papers/OMEGAPriori.pdf

Data envelopment analysis: Prior to choosing a model

A review of the recent contribution of systems thinking to operational research and management science

The paper aims to investigate the achievements of the theoretical and practical basis of environmental policy analysis in order to study their works and point out the future possible research direction. It sorts out researches about environmental efficiency assessment and reviews the works about the theory and application of efficiency analysis around the world. It is suggested that environmental efficiency evaluation theory under small samples and DEA method with undesirable outputs will further extend the research on environmental efficiency evaluation. Also, this review confirms that more studies in methods and their applications in this area are in urgent need.

Environmental efficiency evaluation based on data envelopment analysis: A review

Data Envelopment Analysis (DEA) models with undesirable inputs and outputs have been frequently discussed in DEA literature, e.g., via data transformation. These studies were scatted in the literature, and often confined to some particular applications. In this paper we present a systematic investigation on model building of DEA without transferring undesirable data. We first describe the disposability assumptions and a number of different performance measures in the presence of undesirable inputs and outputs, and then discuss different combinations of the disposability assumptions and the metrics. This approach leads to a unified presentation of several classes of DEA models with undesirable inputs and/or outputs.

DEA models with undesirable inputs and outputs

This paper is primarily concerned with data envelopment analysis (DEA) of systems where negative outputs and negative inputs arise naturally. Examples of situations in which both negative inputs and negative outputs occur are given. More attention has been paid, in the literature, to the former type of problem. Most available DEA software does not solve this type of problem or copes with negative outputs and possibly negative inputs by assigning zero weights to them. A modified slacks-based measure (MSBM) model is presented, in which both negative outputs and negative inputs occur. The MSBM model overcomes the lack of translation invariance in the slacks-based measure model by drawing on the ideas from the range directional model (RDM). The MSBM model takes into account individual input and output slacks, which provides more precise evaluation of inefficient decision-making units (DMUs). It therefore, generally leads to lower efficiencies for inefficient DMUs than the RDM.

https://link.springer.com/content/pdf/10.1057%2Fpalgrave.jors.2602318.pdf

A modified slacks-based measure model for data envelopment analysis with ‘natural’ negative outputs and inputs

In performance evaluations, data without explicit inputs (such as index data, pure output data) are widely used. To directly use such data, this paper presents a study on building DEA models without explicit inputs, so-called DEA-WEI models, which are applicable to the evaluation applications where inputs are not directly considered. We provide an axiom foundation of these kinds of models, and further discuss how to incorporate value judgments of decision makers into these DEA-WEI models. Several such models are derived. Finally, applications of the DEA-WEI models are presented.

A study of DEA models without explicit inputs

It is well known that the discrimination power of data envelopment analysis (DEA) models will be much weakened if too many input or output indicators are used. It is a dilemma if decision makers wish to select comprehensive indicators, which often have some hierarchical structures, to present a relatively holistic evaluation using DEA. In this paper we show that it is possible to develop DEA models that utilize hierarchical structures of input-output data so that they are able to handle quite large numbers of inputs and outputs. We present two approaches in a pilot evaluation of 15 institutes for basic research in the Chinese Academy of Sciences using the DEA models. (C) 2008 Elsevier Ltd. All rights reserved.

Two-level dea approaches in research evaluation

It is well known that Olympic Games often use Lexicographic preference to rank the nations that won the medals. However, Lexicographic preference is not the underlying preference that is used in the standard DEA models. Hence, we discuss the issue of the underlying preferences in DEA models for measuring the performance of nations at the Olympic Games, and then propose new DEA models with Lexicographic preference to measure the performance of the nations.

https://link.springer.com/content/pdf/10.1057%2Fpalgrave.jors.2602638.pdf

Wei Meng

Papers

DEA models with undesirable inputs and outputs

A modified slacks-based measure model for data envelopment analysis with ‘natural’ negative outputs and inputs

A study of DEA models without explicit inputs

Two-level dea approaches in research evaluation

Measuring the performance of nations at the Olympic Games using DEA models with different preferences