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Advances in Decision Making and Data Analysis for Sustainable Operations and Supply Chain Management in the Industry 4.0 Era

A special issue of Sustainability (ISSN 2071-1050).

Deadline for manuscript submissions: closed (31 March 2020) | Viewed by 25223

Special Issue Editor


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Guest Editor
Disaster Preparedness and Emergency Management, University of Hawaii, 2540 Dole Street, Honolulu, HI 96822, USA
Interests: epidemiology and prevention of congenital anomalies; psychosis and affective psychosis; cancer epidemiology and prevention; molecular and human genome epidemiology; evidence synthesis related to public health and health services research
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Sustainable operations and sustainable supply chain management require an inclusive comprehensive and multitier perspective, with a focus on decision support and data analysis for green development, life cycle assessment, and sustainable supply chains. By leveraging Industry 4.0 technology, decision support and big data have begun to yield unprecedented advances in green development and sustainable operations management at every step of the industrial process, thereby improving the quality and sustainability of supply chains and helping organizations to develop innovative social and environmental responsibility initiatives. Decision models and data analysis for sustainable operations also help to reduce and even eliminate downtime, because the models and data provide insights on optimal maintenance schedules.

Hence, this Special Issue will comprise a selection of theoretical and empirical papers covering the breadth of decision making and data analysis for the sustainability and operational considerations faced by corporations in the Industry 4.0 Era. Issues pertaining to corporate social and environmental responsibility will be emphasized. The effective use of decision making and data analysis for green manufacturing strategies can lead to technologic breakthroughs in sustainable packaging, cleaner production, and closed loop systems in supply chains. Innovative topics may include the use of deep learning for sustainable sourcing and supplier management; advances in computational intelligence and data analysis for sensor development and supply chain digitalization; and autonomous systems for sustainable product design as well as green warehousing and transportation. Papers should include novel ideas that address the challenges, opportunities, and strategies involved with implementing decision making tools for sustainable operations and supply chain management from the perspectives of Industry 4.0

Papers selected for this Special Issue will be subject to a rigorous peer review procedure with the aim of rapid and wide dissemination of research results, developments, and applications in the field.

Prof. Dr. Jason K. Levy
Guest Editor

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. Sustainability is an international peer-reviewed open access semimonthly 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 2400 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

  • decision models
  • sustainable supply chain management
  • corporate social responsibility
  • big data
  • value chains
  • manufacturing strategies
  • Industry 4.0
  • sustainable warehousing
  • green logistics and transportation
  • data analysis
  • sustainable product design and packaging
  • corporate social responsibility cleaner production
  • supply chain digitalization
  • corporate social innovation

Published Papers (2 papers)

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Research

32 pages, 2909 KiB  
Article
Creating Sustainable Order Fulfillment Processes through Managing the Risk: Evidence from the Disposable Products Industry
by Mohammad Heydari, Kin Keung Lai and Xiaohu Zhou
Sustainability 2020, 12(7), 2871; https://doi.org/10.3390/su12072871 - 3 Apr 2020
Cited by 10 | Viewed by 5538
Abstract
Retailers face a major operational challenge in fulfilling online orders while managing their traditional store-based distribution processes. In this context, the following order fulfillment options available to retailers are considered: store-facing distribution centers (DCs), dedicated order fulfillment facilities (DTCs), retail stores, and direct-fill [...] Read more.
Retailers face a major operational challenge in fulfilling online orders while managing their traditional store-based distribution processes. In this context, the following order fulfillment options available to retailers are considered: store-facing distribution centers (DCs), dedicated order fulfillment facilities (DTCs), retail stores, and direct-fill by vendors. The current study provides an order fulfillment evaluation for the Disposable Products Industry, which is one of the industries that have a tremendous effect over the downstream industries, as it is the source for production. Also, the differences in the factor focus are provided for various parties and countries. The results show that the order fulfillment risk factors identified from various research studies are good enough for the Disposable Products Industry, even though they are not intentionally designed for this highly diversified industry. Among them, sustainability is the most important factor that the companies in the Disposable Products Industry should pay attention to. This is because sustainability is believed to lead to large deviations in various types of order fulfillment losses and incur a higher chance of having the order fulfillment failure for the companies with an international customer base. The companies should focus on how to improve the sustainability (long-term relationships with the various parties along the chain) rather than over-emphasis on the short-term documentation accuracy as the long-term improvement is likely to result in an overall improvement in performance on order fulfillment. Full article
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22 pages, 2240 KiB  
Article
The Impact of Big Data Analytics on Company Performance in Supply Chain Management
by Ionica Oncioiu, Ovidiu Constantin Bunget, Mirela Cătălina Türkeș, Sorinel Căpușneanu, Dan Ioan Topor, Attila Szora Tamaș, Ileana-Sorina Rakoș and Mihaela Ștefan Hint
Sustainability 2019, 11(18), 4864; https://doi.org/10.3390/su11184864 - 5 Sep 2019
Cited by 48 | Viewed by 18932
Abstract
Big data analytics can add value and provide a new perspective by improving predictive analysis and modeling practices. This research is centered on supply-chain management and how big data analytics can help Romanian supply-chain companies assess their experience, strategies, and professional capabilities in [...] Read more.
Big data analytics can add value and provide a new perspective by improving predictive analysis and modeling practices. This research is centered on supply-chain management and how big data analytics can help Romanian supply-chain companies assess their experience, strategies, and professional capabilities in successfully implementing big data analytics, as well as assessing the tools needed to achieve these goals, including the results of implementation and performance achievement based on them. The research method used in the quantitative study was a sampling survey, using a questionnaire as a data collection tool. It included closed questions, measured with nominal and ordinal scales. A total of 205 managers provided complete and useful answers for this research. The collected data were analyzed with the Statistical Package for the Social Sciences (SPSS) package using frequency tables, contingency tables, and main component analysis. The major contributions of this research highlight the fact that companies are concerned with identifying new statistical methods, tools, and approaches, such as cloud computing and security technologies, that need to be rigorously explored. Full article
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