ارزیابی استراتژی برای توسعه پایدار: استدلال منطق فازی و تجزیه و تحلیل حساسیت

Sustainable decision-making involves political decisions at the local, regional, or national levels, which aim at a balanced development of socio–environmental systems. A fundamental question in sustainable decision-making is that of defining and measuring sustainable development. Many methods have been proposed to assess sustainability. Recently, a model has been developed, called Sustainability Assessment by Fuzzy Evaluation (SAFE), which uses fuzzy logic reasoning and basic indicators of environmental integrity, economic efficiency, and social welfare, and derives measures of human (HUMS), ecological (ECOS), and overall sustainability (OSUS). In this article, we perform sensitivity analysis of the SAFE model to identify the most important factors contributing to sustainable development. About 80 different indicators are tested and classified as promoting, impeding, or having no effect on the progress toward sustainable development. The proposed method is applied to the Greek and American economies. The conclusion is that there is no unique sustainable path and, accordingly, policy makers should choose different criteria and strategies to make efficient sustainable decisions for each country.

Sustainable development is nowadays the goal, in words at least, of most politicians and decision makers. Since the publication of the Brundtland report in 1987 [World Commisson on Environment and Development (WCED), 1987], the concept of sustainability has gained increasing attention among policy makers and scientists which culminated during the 1992 Earth Summit held in Rio de Janeiro. Among the results of the Earth Summit, Agenda 21 is a comprehensive list of actions needed to achieve sustainable development [United,NationsConfereon,Confereon,on,Environand,and,DevelopUNCED,UNCED,1992]. Leaders from over 150 states committed themselves to undertaking actions which will render future development sustainable but without the scientific tools to guide policy making towards a sustainable path (HMSO, 1994). Decisions leading to sustainable development ought to be based on good science and adequate information. Thus, data are needed about environmental, social, and economical factors known as indicators of sustainability. Sustainable projects and optimal strategies for development necessitate answering four fundamental questions: “why unsustainable development occurs”, “what is sustainability?”, “how can it be measured?”, and “which factors affect it?” (Atkinson et al., 1999). There is evidence that development is currently unsustainable. Ozone depletion, global warming, depletion of aquifers, species extinction, collapse of fisheries, soil erosion, and air pollution are among the obvious signs of ecological distress (Brown et al., 2000). Our society is also showing similar signs due to poverty, illiteracy, AIDS, social and political unrest, and violence International Union for the Conservation of Nature/United Nations Environment Program/WorldWide Fund for Nature (IUCN/UNEP/WWF), 1991 and United Nations Environment Programme (UNEP), 1992. Recently, fuzzy logic has been proposed as a systematic tool for the assessment of sustainability. Fuzzy logic is capable of representing uncertain data, emulating skilled humans, and handling vague situations where traditional mathematics is ineffective. Based on this approach, we have developed a model called Sustainability Assessment by Fuzzy Evaluation (SAFE), which uses basic indicators of environmental integrity, economic efficiency, and social welfare as inputs, and employs fuzzy logic reasoning to provide sustainability measures on the local, regional, or national levels (Phillis and Andriantiatsaholiniaina, 2001). This paper provides an approach to sustainable decision-making on the national level using sensitivity analysis of the SAFE model. Sensitivity analysis reveals the most important factors contributing to a sustainable society. The proposed method is applied to a number of selected economies. It becomes clear that there is no unique sustainable path and, accordingly, policy makers should choose different criteria and strategies to make efficient sustainable decisions for each country. It should be stressed that the present work expands on our previous paper (Phillis and Andriantiatsaholiniaina, 2001). The main contribution of this research, aside from refining several points of our past paper, is the introduction of derivatives (gradients) of linguistic variables with respect to indicators. This is a nontrivial task and a necessary step towards using the full decision-making potential of the model. There are indicators whose values are good but they tend towards deterioration. The sensitivity analysis spots such indicators and often provides counterintuitive results necessary to form the full picture of sustainability. Another point worth mentioning is that, although we provide a lot of explanation about our model, it is bound to remain a “black box” to some extent for the layman. To understand the model fully, one has to be reasonably versed in fuzzy logic and calculus. The software, however, can be used by the layman without difficulty. Knowledge of the inner workings of the model is required if one needs to change the knowledge bases or the membership functions. Our model, however, does not differ in this respect from most others. It is usable by the majority of interested agents but fully understood by the experts.

Policy makers need a tool based on scientific information to forecast the effects of future actions on sustainability and establish policies for sustainable development. In this paper, we use a previously developed model, called SAFE, in an attempt to provide an explicit and comprehensive description of the concept of sustainability. Using linguistic variables and linguistic rules, the model gives quantitative measures of human and ecological sustainability which are then combined into overall sustainability. A sensitivity analysis of the SAFE model permits to determine the evolution of sustainability variables subject to perturbations in the values of basic indicators. Then, the problem of sustainable decision-making becomes one of specifying priorities among basic indicators and designing appropriate policies that will guarantee sustainable progress. Successful policies differ from country to country. More developed countries need to focus mostly on the degradation of their environment, whereas less developed countries should strive to improve both the environment and the human system. The SAFE approach provides new insights of sustainable development, and it may serve as a practical tool for decision-making and policy design at the local or regional levels. Such approaches are urgently needed nowadays if we want to attack the problem of sustainable development systematically.