Special Issue "Decision Support for Sustainable Supply Chain Design and Management"

A special issue of Informatics (ISSN 2227-9709).

Deadline for manuscript submissions: closed (30 June 2017) | Viewed by 12751

Special Issue Editors

Prof. Dr. Chun-Hsien Chen
E-Mail Website
Guest Editor
School of Mechanical & Aerospace Engineering, Nanyang Technological University, Singapore 50 Nanyang Avenue, Singapore 639798, Singapore
Interests: design science in product design and development; engineering/design informatics for managing/supporting digital design and manufacturing; human factors and management of human performance
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Wei Yan
E-Mail Website
Guest Editor
Shanghai Maritime University, 1550 Port Avenue, Shanghai 201306, China
Interests: supply chain management and logistics engineering
Prof. Dr. Junliang He
E-Mail Website
Guest Editor
Logistics Engineering School, Shanghai Maritime University, Shanghai 201306, China
Interests: supply chain management and logistics engineering

Special Issue Information

Dear Colleagues,

In the last few decades, sustainable supply chain management (SSCM) practices have been developed to integrate environmental concerns into organizations by reducing unintended negative consequences on the environment by production and consumption processes. Existing SSCM literature shows barriers, including complexity and uncertainty, and requirements, including organizational culture and strategy. Decision theory (DT), which provides deeper insight into this, is being studied as a theoretical perspective in SSCM. Thus, at the current time, it is worthwhile to investigate a set of key themes (planning, execution, coordination, and collaboration) and associated research opportunities (with respect to governance, risk, compliance, performance management, and the sustainability dimensions) of SSCM using DT supported techniques and methodology. This Special Issue of Informatics welcomes submissions on the topic of decision support for sustainable supply chain design and management. This inherently interdisciplinary topic draws from research in information science, environmental engineering, management science, artificial intelligence, knowledge engineering and management, and information systems. We encourage authors to submit their original research articles, work in progress, surveys, reviews, and viewpoint articles in this field. This Special Issue welcomes applications, theories, models, and frameworks that are concerned with (but not limited to) the following topics:

Prof. Dr. Wei Yan
Prof. Dr. Junliang He
Prof. Dr. Chun-Hsien Chen
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Informatics is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Supply Chain
  • Decision Support
  • Design and Management
  • Sustainability
  • Environment Engineering
  • Planning
  • Production
  • Logistics
  • Optimization
  • Problem Solving
  • Knowledge Engineering
  • Artificial Intelligence
  • Logic and Reasoning
  • Data Mining
  • Complex Cognition
  • Information Systems
  • Case Study
  • Learning
  • Simulation
  • Data and Information Visualization

Published Papers (2 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

Article
Multiple-Criteria Decision Support for a Sustainable Supply Chain: Applications to the Fashion Industry
Informatics 2017, 4(4), 36; https://doi.org/10.3390/informatics4040036 - 12 Oct 2017
Cited by 9 | Viewed by 6798
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 [...] Read more.
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. Full article
(This article belongs to the Special Issue Decision Support for Sustainable Supply Chain Design and Management)
Show Figures

Figure 1

Article
Assessing the Cost Impact of Multiple Transportation Modes to Enhance Sustainability in an Integrated, Two Stage, Automotive Supply Chain
Informatics 2017, 4(4), 34; https://doi.org/10.3390/informatics4040034 - 28 Sep 2017
Viewed by 5821
Abstract
As the automotive industry has been striving to enhance its efficiency, competitiveness, and sustainability, great focus is often placed on opportunities for improving its supply chain operations. We study the effect of introducing multiple modes of transportation in an industry-motivated production and transportation [...] Read more.
As the automotive industry has been striving to enhance its efficiency, competitiveness, and sustainability, great focus is often placed on opportunities for improving its supply chain operations. We study the effect of introducing multiple modes of transportation in an industry-motivated production and transportation problem involving short-term automotive supply chain planning. We consider multiple, heterogeneous modes of transportation that offer a cost vs. delivery time option to the manufacturer. Having multiple modes of transportation in the system promotes supply chain sustainability. We present an integer linear programming model that captures the availability of multiple transportation modes. We then provide a solution approach based on a hybrid simulated annealing algorithm that we use to analyze the problem. Experimental results demonstrate the impact of additional transportation mode lead times compared to costs in the integrated supply chain. Full article
(This article belongs to the Special Issue Decision Support for Sustainable Supply Chain Design and Management)
Show Figures

Figure 1

Back to TopTop