مدلسازی مسائل پیچیده تصمیم اخلاقی با تحقیق در عملیات
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|1623||2009||9 صفحه PDF||سفارش دهید||1 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Omega, Volume 37, Issue 6, December 2009, Pages 1100–1108
This paper discusses the practical contribution of operations research (OR) techniques to modelling decision-making problems with ethical dimensions. Such problems are frequent in the global world: they frequently appear today in sustainability issues, e.g., in conflicts in the triangle of society, economy and environment. We show that the prerequisites for ethical problem-modelling are: the definition of moral principles, the evaluation of the decision context, the participation of stakeholders, the multidisciplinary collection of data, and the understanding of systemic interconnections. Classical OR instruments, mainly used in logistics and optimisation problems, are not entirely satisfactory for coping with the new ethical dimensions of sustainability. It is recommended to use and to develop more advanced, or combined instruments from the multi-criteria/multi-stakeholder and systemic streams of OR. It is argued that an important added value of using OR techniques for modelling today ethical issues lies at least as much in the discovery of open questions as in finding closed-form solutions.
In previous papers published in this special issue ,  and , different aspects of promoting ethics in operations research (OR) practice have been developed.  is the umbrella introduction to all four papers. In  it is shown that good practice of OR, with the primary objective of quality control regarding the analyst's work already includes ethical considerations. The idea that good practice is necessary, but not sufficient is developed in . Other dimensions of the ethical process in OR are discussed, evidencing difficulties and ambiguities in the relationships to be established between the OR practitioners and his/her clients, decision-makers or stakeholders. It shows that neither the analysis and modelling work nor the choice of analytical tools are entirely ethically neutral; incomparability, incommensurability and uncertainties must be dealt with, and contribute to the existence of ethical values. Both articles  and  are centred on ethical dimensions to be found in the work and interaction of analysts and decision-makers in solving problems. This article concentrates on if, and how, OR instruments can significantly contribute to solving ethical problems in modern human societies. Put shortly, ‘ethics in OR modelling’ addressed in  and  is completed by the reverse point of view, i.e., ‘OR modelling for ethics’, in the present article. This paper primarily discusses how much, and by which techniques, OR may contribute to solving ethical challenges of our time. Many of them are located in the issues of ‘sustainable development’, i.e., according to : ‘sustainable development is development that meets the needs of the present without compromising the ability of future generations to meet their own needs’. The idea that OR techniques can provide a useful contribution to important community issues is certainly not new. The British mathematician Lewis Fry Richardson  built the very first mathematical model of conflicts between nations—the arms race—in the thirties of the last century. This model is comparable to the well-known predator–prey model of Lotka–Volterra , developed at about the same time with a similar purpose of gaining insight into complex systems. The founding fathers of OR during WWII were also very much conscious of the social and ethical issues to be addressed by OR techniques and models  and . In the 1970s and early 1980s in the aftermath of the first oil crisis in 1973 many OR papers were produced on energy issues (see  with many references on energy planning studies in this period). Although not yet coming under the label of sustainable development, this work has to be understood as a desire to contribute to a crucial issue in modern industrial societies. Later on, there were significant debates about the social and ethical role of OR (see for example ,  and ), also as part of the agenda of the Critical Systems Thinking movement (see , , ,  and ). An important contribution to OR modelling is the collection of papers in , of which several are mentioned in . A recent paper  reviews contributions of OR to ethics, and discusses recent attempts to revive the ethical debate within EURO from 2000 on. With the present article we hope to present a modest contribution pursuing similar lines of thought of our predecessors to better address important societal challenges with quantitative OR techniques. The article is organised as follows: Section 2 discusses several analyses that are prerequisites for modelling complex society problems with OR techniques. These preliminary tasks are made in interaction between OR practitioners and decision-makers, according to the principle of ethics in modelling detailed in  and . In these steps several of the complex dimensions of ethical problems should be accounted for: the identification of moral principles; the societal context of the decision; the multidisciplinary and multiple-stakeholders aspects; and the systemic dimension of the problem. Section 3 characterises OR techniques that are useful in evaluating decision-making problems, and how they may contribute in modelling problems with ethical dimensions. Section 4 gives conclusions.
نتیجه گیری انگلیسی
The aspects of ‘ethics for OR modelling’, of good practice and beyond, the validation and legitimacy of the analysts’ work, the ethical ambiguities in the relationship between the analysts, the OR model, the decision-makers, and the stakeholders have been thoroughly discussed in  and . In the present paper the authors discuss the reverse issue of ‘OR modelling for ethics’. As they have argued today's ethical problems get centred on the global problems of mankind encompassed in the broad concept of sustainable development. It is why the authors are pleading for increased modelling efforts in solving sustainability issues, as a major contribution of OR to ethics. To achieve this ambitious aim, a number of prerequisites for ethical OR modelling have been discussed in detail. A central issue is here to be able to apprehend the moral principles to be respected in approaching ethical problems in complex human systems. These problems have multidisciplinary facets; they involve multiple decision-makers, stakeholders and criteria, and they imply complex systemic interconnections in space and time. The authors argue that less conventional or sometimes innovative OR tools, should be increasingly used, developed, and/or combined. Many efforts in this direction are certainly already made today in excellent OR articles, like ,  and ; but this effort must be continued and amplified. Though the new sustainability problems may be from an analytical point of view less attractive, but also often more difficult, than well-defined mainstream OR problems, they must be placed at the top of the priority agenda. The tools needed for modelling these oft ill-defined problems are centred on systems thinking, and multi-criteria/multi-stakeholder techniques. An important incentive for reviving, developing, or combining less conventional OR practices, is that today the analytical process of mainstream OR would tend to reduce any complex problem to a structured and solvable form. In such approaches ethical concerns are either ignored, or abstracted, so that many dimensions are indeed missing in the analysis. The intention behind the proposed increased use of systemic and multi-criteria decision-aiding tools is to reintroduce into models otherwise hidden and value-loaded moral principles. The main purpose of OR modelling is, in the authors’ opinion, to conduct an extensive and exhaustive ethical process with all decision-makers and stakeholders, placed within a multidisciplinary framework. An essential result of this process is to discover what was left out, rather than what was covered with traditional quantitative instruments.