Ends, means, beginnings: environmental technocracy, ecological deliberation or embodied disagreement

Technocratic attitudes suggest that decisions about environmental policy should be led by scientific experts. Such decisions, it is expected, will be more rational than any arrived at by a democratic mediation between the narrow, short-term interests and uninformed preferences of the general public. Within green political theory, deliberative democracy has emerged as the dominant repost to technocracy, offering an account of how democratic polities can deal with complex scientific and technological decisions through the emergence of communicative rationality. This article argues that neither appeals to expert knowledge, nor communicative rationality, are likely to deliver the optimal green outcomes that proponents suggest, but rather will cover up the inevitable disagreements over environmental policy making. Instead the article suggests that more ecologically-sensitive and democratic decision making about complex scientific and technological issues can emerge if we acknowledge the differently embodied perspectives of decision-makers – from scientists to citizens. This prioritises democratic means over green ends, yet incorporates the environment at the beginning of the decision-making process. The article aims to sketch out the theoretical and practical implications of such an embodied turn for responding to the anti-democratic tendencies of environmental technocracy.

Partner selection in green supply chains using PSO - a practical approach

Partner selection is crucial to green supply chain management as the focal firm is responsible for the environmental performance of the whole supply chain. The construction of appropriate selection criteria is an essential, but often neglected pre-requisite in the partner selection process. This paper proposes a three-stage model that combines Dempster-Shafer belief acceptability theory and particle swarm optimization technique for the first time in this application. This enables optimization of both effectiveness, in its consideration of the inter-dependence of a broad range of quantitative and qualitative selection criteria, and efficiency in its use of scarce resources during the criteria construction process to be achieved simultaneously. This also enables both operational and strategic attributes can be selected at different levels of hierarchy criteria in different decision-making environments. The practical efficacy of the model is demonstrated by an application in Company ABC, a large Chinese electronic equipment and instrument manufacturer.

Partner selection for reverse logistics centres in green supply chains: a fuzzy artificial immune optimization approach

The design of reverse logistics networks has now emerged as a major issue for manufacturers, not only in developed countries where legislation and societal pressures are strong, but also in developing countries where the adoption of reverse logistics practices may offer a competitive advantage. This paper presents a new model for partner selection for reverse logistic centres in green supply chains. The model offers three advantages. Firstly, it enables economic, environment, and social factors to be considered simultaneously. Secondly, by integrating fuzzy set theory and artificial immune optimization technology, it enables both quantitative and qualitative criteria to be considered simultaneously throughout the whole decision-making process. Thirdly, it extends the flat criteria structure for partner selection evaluation for reverse logistics centres to the more suitable hierarchy structure. The applicability of the model is demonstrated by means of an empirical application based on data from a Chinese electronic equipment and instruments manufacturing company.