Data-driven food supply chain management and systems
| Pages | 1779-1781 |
| Date | 16 October 2017 |
| Published date | 16 October 2017 |
| DOI | https://doi.org/10.1108/IMDS-06-2017-0269 |
| Author | Dr Ray Y. Zhong,Professor Kim Tan,Professor Gopalakrishnan Bhaskaran |
| Subject Matter | Information & knowledge management,Information systems,Data management systems,Knowledge management,Knowledge sharing,Management science & operations,Supply chain management,Supply chain information systems,Logistics,Quality management/systems |
Guest editorial
Data-driven food supply chain management and systems
Food supply chain management (FSCM) plays an important role in our daily life since it
supplies us with the necessity for our lives (Marsden et al., 2000). However, inefficient and
inappropriate management systems may cause large number of food losses. Gustavsson
et al. (2011) pointed out that 492,000,000 tons of fruit and vegetables were wasted worldwide
in 2011. In order to reduce the food waste, advanced technologies such as various sensors,
Internet of Things (IoT), and cloud computing have been used to support FSCM (Yu et al.,
2001; Kelepouris et al., 2007; Manzini and Accorsi, 2013; Yu and Nagurney, 2013).
After deploying the advanced technologies like great myriad of sensors, vast data have been
collected (Zhong et al., 2015). Such massive and invaluable data from FSCM may bring new
challenges such as data processing, data visualization, data-driven decision models, decision
support systems, etc. in the era of IoT.
Big Data, an emerging technology for dealing with large and complex data sets, is able to
address the challenges (Tan et al., 2015; Zhong et al., 2016). Driven by the significant
awareness and concerns for the food sustainability, this special issue aims to highlight some
works like innovative research methodologies, Big Data-driven modeling and optimization
for FSCM, case studies, FSCM system, and so on. There are total 17 research studies which
could be categorized into the following dimensions.
FSCM modeling
For achieving a multi-objective approach under an RFID-enabled HMSC network design,
a cost-effective decision-making algorithm was proposed (Mohammed et al., 2017). A new
risk assessment model was introduced for agricultural products cold chain logistics
(Zhang et al., 2017). Chandrasekaran and Ranganathan (2017) introduced a modeling and
optimization of Indian traditional agriculture supply chain to reduce post-harvest loss and
CO
2
emission. Under the IoT-enabled fresh agricultural products supply chain, Yan et al.
(2017) proposed a three-level supply chain coordination model to consider the influence of
FAP on market demand and costs of controlling freshness on the road. To evaluate
sustainability of supply chain, a dynamic network DEA approach was proposed (Shokri
Kahi et al., 2017). Zhang et al. (2017) reported a modeling of an IoT-enabled supply chain for
perishable food with two-echelon supply hubs using the real-time data. In the food supply
network, a model for traffic flow routing and scheduling was illustrated to prevent traffic
flow congestion by Bocewicz et al. (2017). A constraint-driven model was introduced to
FSCM using generalization of data-based control (Sitek et al., 2017).
Industrial Management & Data
Systems
Vol. 117 No. 9, 2017
pp. 1779-1781
Emerald Publishing Limited
0263-5577
DOI 10.1108/IMDS-06-2017-0269
© Ray Y. Zhong, Kim Tan and Gopalakrishnan Bhaskaran. Published by Emerald Publishing Limited.
This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may
reproduce, distribute, translate and create derivative works of this article ( for both commercial &
non-commercial purposes), subject to full attribution to the original publication and authors. The full
terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode
The editors would like to thank all the reviewers who gave their significant comments and
suggestions for improving the published papers in this special issue. The editors give special thanks to
Professor Hing Kai Chan and Professor Alain Yee Loong Chong who gave their great support to this
special issue. The editors hope that this special issue will bridge the academic and practitioners so as to
enhance the food supply chain management in the future.
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Guest editorial
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