Sustainable Supply Chain Analytics: Grand Challenges and Future Opportunities
- Publication Type:
- Conference Proceeding
- Citation:
- https://aisel.aisnet.org/pacis2017/44, 2017, (2017)
- Issue Date:
- 2017-01-01
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| Filename | Description | Size | |||
|---|---|---|---|---|---|
| Sustainable Supply Chain Analytics- Grand Challenges and Future O.pdf | Published version | 827.01 kB |
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Over the last few years, the pressure for decreasing environmental and social footprints has motivated supply chain organizations to significantly progress sustainability initiatives. Since supply chains have implemented sustainability strategies, the volume of economic, environmental and social data has rapidly increased. Dealing with this data, business analytics has already shown its capability for improving supply chain monetary performance. However, there is limited knowledge about how business analytics can be best leveraged to grow social, environmental and financial performance simultaneously. Therefore, in reviewing the literature around sustainable supply chain, this research seeks to further illuminate the role business analytics plays in addressing this issue. A literature survey methodology is outlined, scrutinizing key papers published between 2012 and 2016 in the research fields of Information/Computing Science, Business and Supply Chain Management. From examination of 311 journal papers, 39 were selected as meeting defined criteria for further categorization into three distinct research groups including: (a) sustainable supply chain configuration; (b) sustainable supply chain implementation; (c) sustainable supply chain evaluation. The issues involved within each grouping are identified and the business analytics processes (i.e. prescriptive, predictive, prescriptive analytics) to specifically address them are discussed. This wide-ranging review of sustainable supply chain analytics can assist both scholars and practitioners to better appreciate the current grand challenges and future research opportunities posed by this area.
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