Multiple-Criteria Decision Support for a Sustainable Supply Chain: Applications to the Fashion Industry
Journal Title: Informatics - Year 2017, Vol 4, Issue 4
Abstract
With increasing globalization and international cooperation, the importance of sustainability management across supply chains has received much attention by companies across various industries. Companies therefore strive to implement effective and integrated sustainable supply chain management initiatives to improve their operational and economic performance while also minimizing unnecessary damage to the environment and maintaining their social reputation and images. The paper presents an easy-to-use decision-support approach based on multiple-criteria decision-making (MCDM) methodologies that aim to help companies develop effective models for timely decision-making involving sustainable supply chain management strategies. The proposed approach can be used by practitioners to ultimately build a comprehensive Analytic Network Process model that will adequately capture and reveal all the interrelationships and interdependency among the elements in the problem, which is often a very difficult task. To facilitate and simplify this complex process, we propose that hierarchical thinking be used first to structure the essences of the problem capturing only the major issues, and an Analytic Hierarchy Process (AHP) model be built. Users can learn from the modeling process and gain much insight into the problem. The AHP can then be extended to an Analytic Network Process (ANP) model so as to capture the relationships and interdependencies among the elements. Our approach can reduce the sustainable expertise, effort and information that are often needed to build an ANP model from scratch. We apply our approach to the evaluation of sustainable supply chain management strategies for the fashion industry. Three main dimensions of sustainability—environmental, economic and social—are considered. Based on the literature, we identified four alternative supply chain management strategies. It was found that the Reverse Logistics alternative appears to be the recommended solution by the AHP model. However, the Socially Leagile Supply Chain is recommended by the ANP model, thereby demonstrating the necessity and importance of considering interdependencies in the model.
Authors and Affiliations
Kim Leng Poh and Yiying Liang
Keywords
Related Articles
- EP ID EP44112
- DOI https://doi.org/10.3390/informatics4040036
- Views 289
- Downloads 0
A Novel Three-Stage Filter-Wrapper Framework for miRNA Subset Selection in Cancer Classification
Micro-Ribonucleic Acids (miRNAs) are small non-coding Ribonucleic Acid (RNA) molecules that play an important role in the cancer growth. There are a lot of miRNAs in the human body and not all of them are responsible f...
Older People Using e-Health Services—Exploring Frequency of Use and Associations with Perceived Benefits for Spouse Caregivers
ICT, information- and communication technologies, and e-health services are essential for meeting future care demands. Greater knowledge regarding the implementation of e-health services in long-term care for older peo...
Multidimensional Data Exploration by Explicitly Controlled Animation
Understanding large multidimensional datasets is one of the most challenging problems in visual data exploration. One key challenge that increases the size of the exploration space is the number of views that one can gen...
Analyzing Spatiotemporal Anomalies through Interactive Visualization
As we move into the big data era, data grows not just in size, but also in complexity, containing a rich set of attributes, including location and time information, such as data from mobile devices (e.g., smart phones),...
Exploiting Rating Abstention Intervals for Addressing Concept Drift in Social Network Recommender Systems
One of the major problems that social networks face is the continuous production of successful, user-targeted information in the form of recommendations, which are produced exploiting technology from the field of recom...