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Design for the environment: An ontology‐based knowledge management model for green product development

Abla Chaouni Benabdellah, Kamar Zekhnini, Anass Cherrafi, Jose Arturo Garza‐Reyes and Anil Kumar

Business Strategy and the Environment, 2021, vol. 30, issue 8, 4037-4053

Abstract: Through appropriate operations and policies, such as green processes and product development process (PDP), companies can respond to environmental sustainability. To remain competitive, one such approach, Design for X (DFX), involves considering different environment and sustainable strategies through different factors Xs. With regard to the availability of different DFX techniques that consider environmental issues, the decision as to which approach needs to be adopted remains absent. This paper aims at presenting an overview from 1980 to 2020 of the developed research, applications, and DFX techniques for assessing green issues. Selected DFX techniques are linked with strategies used in organizations. Following a literature analysis, a collaborative knowledge‐based framework that addresses the design concepts needed to assess environmental, safety, and health concerns in the development of green products is proposed. Furthermore, as a pillar for considering the Semantic Web and an evolving approach linked with natural language processing (NLP) and artificial intelligence (AI), an ontology‐based knowledge management model for green assessment is developed for the representation, acquisition, organization, and capitalization of knowledge in a computer interpretable manner. The findings are useful for both managers and practitioners as they provide a coherent domain ontology that can help them manage knowledge, improve teamwork, and make decisions in a collaborative green PDP. Besides, an understanding of the essential design considerations that are required to implement environmental, safety, and health issues, as well as competencies used in the PDP is presented. Key barriers, managerial and strategic implications, and mitigation actions are also identified in this paper.

Date: 2021
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