Multi-Objective Relief Distribution System Model for Volcano Disaster Victims

Because of its location in the ring of fire, Indonesia has around 30% of all volcanoes in the world. After the volcano erupted, the area around the volcano was damaged and many people lost their houses, jobs, and possibilities to live in there. Before the volcano erupts, people who live around the volcano must be evacuated as soon as possible to one of the available shelters. In the shelters, drinking water, food, and medicine are needed by victims who were evacuated to survive aftermath of a disaster. To distribute reliefs to all shelters effectively, we developed a multi-objective relief distribution model. This distribution system model aims to determine the allocation of various types of relief items to several shelters with a minimum total cost and balanced service level between locations. This multiobjective relief distribution model considered multi-item, multi-period, multi-vehicle, and multi-trip by using a pre-emptive goal programming approach. This optimization model was applied to the numerical example based on Semeru Mount as the highest active volcanoes in Indonesia, which is located in Lumajang, East Java

Logistics and Agri\u2010Food: Digitization to Increase Competitive Advantage and Sustainability. Literature Review and the Case of Italy

This paper examines the current challenges faced by logistics with a focus on the agri\u2010food sector. After outlining the context, a review of the literature on the relationship between logistics and strategic management in gaining and increasing competitiveness in the agri\u2010food sector is con-ducted. In particular, the flow of the paper is as follows: after examining the aforementioned managerial problem and its broader repercussions, the paper proceeds to address two main research questions. First, how and by which tools can digitization contribute to improving supply chain management and sustainability in logistics? Second, what are the main managerial and strategic implications and consequences of this for the agri\u2010food sector in terms of efficiency, effectiveness, cost reduction, and supply chain optimization? Finally, the paper presents Italy as a case study, chosen both for its peculiar internal differences in logistical infrastructures and entrepreneurial management between Northern and Southern regions (which could be at least partially overcome with the use of new technologies and frameworks) and for the importance of the agri\u2010food sector for the domestic economy (accounting about 25% of the country\u2019s GDP), on which digitization should have positive effects in terms of value creation and sustainability

A Conceptual Framework to Manage Resilience and Increase Sustainability in the Supply Chain

[EN] The challenges of global economies foster supply chains to have to increase their processes of collaboration and dependence between their nodes, generating an increase in the level of vulnerability to possible impacts and interruptions in their operations that may affect their sustainability. This has developed an emerging area of interest in supply chain management, considering resilience management as a strategic capability of companies, and causing an increase in this area of research. Additionally, supply chains should deal with the three dimensions of sustainability (economic, environmental, and social dimensions) by incorporating the three types of objectives in their strategy. Thus, there is a need to integrate both resilience and sustainability in supply chain management to increase competitiveness. In this paper, a systematic literature review is undertaken to analyze resilience management and its connection to increase supply chain sustainability. In the review, 232 articles published from 2000 to February 2020 in peer-reviewed journals in the Scopus and ScienceDirect databases are analyzed, classified, and synthesized. With the results, this paper develops a conceptual framework that integrates the fundamental elements for analyzing, measuring, and managing resilience to increase sustainability in the supply chain. Finally, conclusions, limitations, and future research lines are exposed.This study was supported by the Valencian Government in Spain (Project AEST/2019/019).Zavala-Alcívar, A.; Verdecho Sáez, MJ.; Alfaro Saiz, JJ. (2020). A Conceptual Framework to Manage Resilience and Increase Sustainability in the Supply Chain. Sustainability. 12(16):1-38. https://doi.org/10.3390/su12166300S1381216Roberta Pereira, C., Christopher, M., & Lago Da Silva, A. (2014). Achieving supply chain resilience: the role of procurement. Supply Chain Management: An International Journal, 19(5/6), 626-642. doi:10.1108/scm-09-2013-0346Pettit, T. J., Fiksel, J., & Croxton, K. L. (2010). ENSURING SUPPLY CHAIN RESILIENCE: DEVELOPMENT OF A CONCEPTUAL FRAMEWORK. Journal of Business Logistics, 31(1), 1-21. doi:10.1002/j.2158-1592.2010.tb00125.xPettit, T. J., Croxton, K. L., & Fiksel, J. (2013). Ensuring Supply Chain Resilience: Development and Implementation of an Assessment Tool. Journal of Business Logistics, 34(1), 46-76. doi:10.1111/jbl.12009Ponis, S. T., & Koronis, E. (2012). Supply Chain Resilience: Definition Of Concept And Its Formative Elements. Journal of Applied Business Research (JABR), 28(5), 921. doi:10.19030/jabr.v28i5.7234Seuring, S., & Müller, M. (2008). From a literature review to a conceptual framework for sustainable supply chain management. Journal of Cleaner Production, 16(15), 1699-1710. doi:10.1016/j.jclepro.2008.04.020Qorri, A., Mujkić, Z., & Kraslawski, A. (2018). A conceptual framework for measuring sustainability performance of supply chains. Journal of Cleaner Production, 189, 570-584. doi:10.1016/j.jclepro.2018.04.073Verdecho, M.-J., Alarcón-Valero, F., Pérez-Perales, D., Alfaro-Saiz, J.-J., & Rodríguez-Rodríguez, R. (2020). A methodology to select suppliers to increase sustainability within supply chains. Central European Journal of Operations Research, 29(4), 1231-1251. doi:10.1007/s10100-019-00668-3Edgeman, R., & Wu, Z. (2016). Supply chain criticality in sustainable and resilient enterprises. Journal of Modelling in Management, 11(4), 869-888. doi:10.1108/jm2-10-2014-0078Marchese, D., Reynolds, E., Bates, M. E., Morgan, H., Clark, S. S., & Linkov, I. (2018). Resilience and sustainability: Similarities and differences in environmental management applications. Science of The Total Environment, 613-614, 1275-1283. doi:10.1016/j.scitotenv.2017.09.086Ahern, J. (2012). Urban landscape sustainability and resilience: the promise and challenges of integrating ecology with urban planning and design. Landscape Ecology, 28(6), 1203-1212. doi:10.1007/s10980-012-9799-zRamezankhani, M. J., Torabi, S. A., & Vahidi, F. (2018). Supply chain performance measurement and evaluation: A mixed sustainability and resilience approach. Computers & Industrial Engineering, 126, 531-548. doi:10.1016/j.cie.2018.09.054Shashi, Centobelli, P., Cerchione, R., & Ertz, M. (2019). Managing supply chain resilience to pursue business and environmental strategies. Business Strategy and the Environment, 29(3), 1215-1246. doi:10.1002/bse.2428Ivanov, D. (2017). Revealing interfaces of supply chain resilience and sustainability: a simulation study. International Journal of Production Research, 56(10), 3507-3523. doi:10.1080/00207543.2017.1343507Fahimnia, B., & Jabbarzadeh, A. (2016). Marrying supply chain sustainability and resilience: A match made in heaven. Transportation Research Part E: Logistics and Transportation Review, 91, 306-324. doi:10.1016/j.tre.2016.02.007Ruiz-Benitez, R., López, C., & Real, J. C. (2019). Achieving sustainability through the lean and resilient management of the supply chain. International Journal of Physical Distribution & Logistics Management, 49(2), 122-155. doi:10.1108/ijpdlm-10-2017-0320Pavlov, A., Ivanov, D., Pavlov, D., & Slinko, A. (2019). Optimization of network redundancy and contingency planning in sustainable and resilient supply chain resource management under conditions of structural dynamics. Annals of Operations Research. doi:10.1007/s10479-019-03182-6Khot, S. B., & Thiagarajan, S. (2019). Resilience and sustainability of supply chain management in the Indian automobile industry. International Journal of Data and Network Science, 339-348. doi:10.5267/j.ijdns.2019.4.002Roostaie, S., Nawari, N., & Kibert, C. J. (2019). Sustainability and resilience: A review of definitions, relationships, and their integration into a combined building assessment framework. Building and Environment, 154, 132-144. doi:10.1016/j.buildenv.2019.02.042Davoudabadi, R., Mousavi, S. M., & Sharifi, E. (2020). An integrated weighting and ranking model based on entropy, DEA and PCA considering two aggregation approaches for resilient supplier selection problem. Journal of Computational Science, 40, 101074. doi:10.1016/j.jocs.2019.101074Carvalho, H., Duarte, S., & Cruz Machado, V. (2011). Lean, agile, resilient and green: divergencies and synergies. International Journal of Lean Six Sigma, 2(2), 151-179. doi:10.1108/20401461111135037Wang, Z., & Zhang, J. (2019). Agent-based evaluation of humanitarian relief goods supply capability. International Journal of Disaster Risk Reduction, 36, 101105. doi:10.1016/j.ijdrr.2019.101105Alikhani, R., Torabi, S. A., & Altay, N. (2019). Strategic supplier selection under sustainability and risk criteria. International Journal of Production Economics, 208, 69-82. doi:10.1016/j.ijpe.2018.11.018Zahiri, B., Zhuang, J., & Mohammadi, M. (2017). Toward an integrated sustainable-resilient supply chain: A pharmaceutical case study. Transportation Research Part E: Logistics and Transportation Review, 103, 109-142. doi:10.1016/j.tre.2017.04.009Aboah, J., Wilson, M. M. J., Rich, K. M., & Lyne, M. C. (2019). Operationalising resilience in tropical agricultural value chains. Supply Chain Management: An International Journal, 24(2), 271-300. doi:10.1108/scm-05-2018-0204Statsenko, L., & Corral de Zubielqui, G. (2020). Customer collaboration, service firms’ diversification and innovation performance. Industrial Marketing Management, 85, 180-196. doi:10.1016/j.indmarman.2019.09.013Duong, L. N. K., & Chong, J. (2020). Supply chain collaboration in the presence of disruptions: a literature review. International Journal of Production Research, 58(11), 3488-3507. doi:10.1080/00207543.2020.1712491Bhamra, R., Dani, S., & Burnard, K. (2011). Resilience: the concept, a literature review and future directions. International Journal of Production Research, 49(18), 5375-5393. doi:10.1080/00207543.2011.563826Heckmann, I., Comes, T., & Nickel, S. (2015). A critical review on supply chain risk – Definition, measure and modeling. Omega, 52, 119-132. doi:10.1016/j.omega.2014.10.004Hohenstein, N.-O., Feisel, E., Hartmann, E., & Giunipero, L. (2015). Research on the phenomenon of supply chain resilience. International Journal of Physical Distribution & Logistics Management, 45(1/2), 90-117. doi:10.1108/ijpdlm-05-2013-0128Kamalahmadi, M., & Parast, M. M. (2016). A review of the literature on the principles of enterprise and supply chain resilience: Major findings and directions for future research. International Journal of Production Economics, 171, 116-133. doi:10.1016/j.ijpe.2015.10.023Ali, A., Mahfouz, A., & Arisha, A. (2017). Analysing supply chain resilience: integrating the constructs in a concept mapping framework via a systematic literature review. Supply Chain Management: An International Journal, 22(1), 16-39. doi:10.1108/scm-06-2016-0197Umar, M., Wilson, M., & Heyl, J. (2017). Food Network Resilience Against Natural Disasters: A Conceptual Framework. SAGE Open, 7(3), 215824401771757. doi:10.1177/2158244017717570Stone, J., & Rahimifard, S. (2018). Resilience in agri-food supply chains: a critical analysis of the literature and synthesis of a novel framework. Supply Chain Management: An International Journal, 23(3), 207-238. doi:10.1108/scm-06-2017-0201Colicchia, C., Creazza, A., Noè, C., & Strozzi, F. (2019). Information sharing in supply chains: a review of risks and opportunities using the systematic literature network analysis (SLNA). Supply Chain Management: An International Journal, 24(1), 5-21. doi:10.1108/scm-01-2018-0003Annarelli, A., & Nonino, F. (2016). Strategic and operational management of organizational resilience: Current state of research and future directions. Omega, 62, 1-18. doi:10.1016/j.omega.2015.08.004Behzadi, G., O’Sullivan, M. J., Olsen, T. L., & Zhang, A. (2018). Agribusiness supply chain risk management: A review of quantitative decision models. Omega, 79, 21-42. doi:10.1016/j.omega.2017.07.005Kochan, C. G., & Nowicki, D. R. (2018). Supply chain resilience: a systematic literature review and typological framework. International Journal of Physical Distribution & Logistics Management, 48(8), 842-865. doi:10.1108/ijpdlm-02-2017-0099Hosseini, S., Ivanov, D., & Dolgui, A. (2019). Review of quantitative methods for supply chain resilience analysis. Transportation Research Part E: Logistics and Transportation Review, 125, 285-307. doi:10.1016/j.tre.2019.03.001Tranfield, D., Denyer, D., & Smart, P. (2003). Towards a Methodology for Developing Evidence-Informed Management Knowledge by Means of Systematic Review. British Journal of Management, 14(3), 207-222. doi:10.1111/1467-8551.00375Rousseau, D. M., Manning, J., & Denyer, D. (2008). 11 Evidence in Management and Organizational Science: Assembling the Field’s Full Weight of Scientific Knowledge Through Syntheses. Academy of Management Annals, 2(1), 475-515. doi:10.5465/19416520802211651Zimmer, K., Fröhling, M., & Schultmann, F. (2015). Sustainable supplier management – a review of models supporting sustainable supplier selection, monitoring and development. International Journal of Production Research, 54(5), 1412-1442. doi:10.1080/00207543.2015.1079340Natarajarathinam, M., Capar, I., & Narayanan, A. (2009). Managing supply chains in times of crisis: a review of literature and insights. International Journal of Physical Distribution & Logistics Management, 39(7), 535-573. doi:10.1108/09600030910996251Tang, C., & Tomlin, B. (2008). The power of flexibility for mitigating supply chain risks. International Journal of Production Economics, 116(1), 12-27. doi:10.1016/j.ijpe.2008.07.008Kleindorfer, P. R., & Saad, G. H. (2009). Managing Disruption Risks in Supply Chains. Production and Operations Management, 14(1), 53-68. doi:10.1111/j.1937-5956.2005.tb00009.xChristopher, M., & Peck, H. (2004). Building the Resilient Supply Chain. The International Journal of Logistics Management, 15(2), 1-14. doi:10.1108/09574090410700275Wu, T., Huang, S., Blackhurst, J., Zhang, X., & Wang, S. (2013). Supply Chain Risk Management: An Agent-Based Simulation to Study the Impact of Retail Stockouts. IEEE Transactions on Engineering Management, 60(4), 676-686. doi:10.1109/tem.2012.2190986Fang, H., & Xiao, R. (2013). Resilient closed-loop supply chain network design based on patent protection. International Journal of Computer Applications in Technology, 48(1), 49. doi:10.1504/ijcat.2013.055566Gong, J., Mitchell, J. E., Krishnamurthy, A., & Wallace, W. A. (2014). An interdependent layered network model for a resilient supply chain. Omega, 46, 104-116. doi:10.1016/j.omega.2013.08.002Mari, S., Lee, Y., & Memon, M. (2014). Sustainable and Resilient Supply Chain Network Design under Disruption Risks. Sustainability, 6(10), 6666-6686. doi:10.3390/su6106666Bueno-Solano, A., & Cedillo-Campos, M. G. (2014). Dynamic impact on global supply chains performance of disruptions propagation produced by terrorist acts. Transportation Research Part E: Logistics and Transportation Review, 61, 1-12. doi:10.1016/j.tre.2013.09.005Costantino, F., Gravio, G. D., Shaban, A., & Tronci, M. (2014). Replenishment policy based on information sharing to mitigate the severity of supply chain disruption. International Journal of Logistics Systems and Management, 18(1), 3. doi:10.1504/ijlsm.2014.062119Kristianto, Y., Gunasekaran, A., Helo, P., & Hao, Y. (2014). A model of resilient supply chain network design: A two-stage programming with fuzzy shortest path. Expert Systems with Applications, 41(1), 39-49. doi:10.1016/j.eswa.2013.07.009Raj, R., Wang, J. W., Nayak, A., Tiwari, M. K., Han, B., Liu, C. L., & Zhang, W. J. (2015). Measuring the Resilience of Supply Chain Systems Using a Survival Model. IEEE Systems Journal, 9(2), 377-381. doi:10.1109/jsyst.2014.2339552LOH, H. S., & THAI, V. V. (2015). Cost Consequences of a Port-Related Supply Chain Disruption. The Asian Journal of Shipping and Logistics, 31(3), 319-340. doi:10.1016/j.ajsl.2015.09.001Torabi, S. A., Baghersad, M., & Mansouri, S. A. (2015). Resilient supplier selection and order allocation under operational and disruption risks. Transportation Research Part E: Logistics and Transportation Review, 79, 22-48. doi:10.1016/j.tre.2015.03.005Cardoso, S. R., Paula Barbosa-Póvoa, A., Relvas, S., & Novais, A. Q. (2015). Resilience metrics in the assessment of complex supply-chains performance operating under demand uncertainty. Omega, 56, 53-73. doi:10.1016/j.omega.2015.03.008Salehi Sadghiani, N., Torabi, S. A., & Sahebjamnia, N. (2015). Retail supply chain network design under operational and disruption risks. Transportation Research Part E: Logistics and Transportation Review, 75, 95-114. doi:10.1016/j.tre.2014.12.015Dixit, V., Seshadrinath, N., & Tiwari, M. K. (2016). Performance measures based optimization of supply chain network resilience: A NSGA-II + Co-Kriging approach. Computers & Industrial Engineering, 93, 205-214. doi:10.1016/j.cie.2015.12.029Liu, F., Song, J.-S., & Tong, J. D. (2016). Building Supply Chain Resilience through Virtual Stockpile Pooling. Production and Operations Management, 25(10), 1745-1762. doi:10.1111/poms.12573Fahimnia, B., Jabbarzadeh, A., & Sarkis, J. (2018). Greening versus resilience: A supply chain design perspective. Transportation Research Part E: Logistics and Transportation Review, 119, 129-148. doi:10.1016/j.tre.2018.09.005Hasani, A., & Khosrojerdi, A. (2016). Robust global supply chain network design under disruption and uncertainty considering resilience strategies: A parallel memetic algorithm for a real-life case study. Transportation Research Part E: Logistics and Transportation Review, 87, 20-52. doi:10.1016/j.tre.2015.12.009Azhmyakov, V., Fernández-Gutiérrez, J. P., Gadi, S. K., & Pickl, S. (2016). A Novel Numerical Approach to the MCLP Based Resilent Supply Chain Optimization. IFAC-PapersOnLine, 49(31), 137-142. doi:10.1016/j.ifacol.2016.12.175Ivanov, D., Sokolov, B., Solovyeva, I., Dolgui, A., & Jie, F. (2016). Dynamic recovery policies for time-critical supply chains under conditions of ripple effect. International Journal of Production Research, 54(23), 7245-7258. doi:10.1080/00207543.2016.1161253Jabbarzadeh, A., Fahimnia, B., Sheu, J.-B., & Moghadam, H. S. (2016). Designing a supply chain resilient to major disruptions and supply/demand interruptions. Transportation Research Part B: Methodological, 94, 121-149. doi:10.1016/j.trb.2016.09.004Babich, V., Burnetas, A. N., & Ritchken, P. H. (2007). Competition and Diversification Effects in Supply Chains with Supplier Default Risk. Manufacturing & Service Operations Management, 9(2), 123-146. doi:10.1287/msom.1060.0122Bogataj, D., Aver, B., & Bogataj, M. (2016). Supply chain risk at simultaneous robust perturbations. International Journal of Production Economics, 181, 68-78. doi:10.1016/j.ijpe.2015.09.009Wang, X., Herty, M., & Zhao, L. (2015). Contingent rerouting for enhancing supply chain resilience from supplier behavior perspective. International Transactions in Operational Research, 23(4), 775-796. doi:10.1111/itor.12151Zeng, B., & Yen, B. P.-C. (2017). Rethinking the role of partnerships in global supply chains: A risk-based perspective. International Journal of Production Economics, 185, 52-62. doi:10.1016/j.ijpe.2016.12.004Lücker, F., & Seifert, R. W. (2017). Building up Resilience in a Pharmaceutical Supply Chain through Inventory, Dual Sourcing and Agility Capacity. Omega, 73, 114-124. doi:10.1016/j.omega.2017.01.001Fattahi, M., Govindan, K., & Keyvanshokooh, E. (2017). Responsive and resilient supply chain network design under operational and disruption risks with delivery lead-time sensitive customers. Transportation Research Part E: Logistics and Transportation Review, 101, 176-200. doi:10.1016/j.tre.2017.02.004Kırılmaz, O., & Erol, S. (2017). A proactive approach to supply chain risk management: Shifting orders among suppliers to mitigate the supply side risks. Journal of Purchasing and Supply Management, 23(1), 54-65. doi:10.1016/j.pursup.2016.04.002Li, H., Pedrielli, G., Lee, L. H., & Chew, E. P. (2016). Enhancement of supply chain resilience through inter-echelon information sharing. Flexible Services and Manufacturing Journal, 29(2), 260-285. doi:10.1007/s10696-016-9249-3Otto, C., Willner, S. N., Wenz, L., Frieler, K., & Levermann, A. (2017). Modeling loss-propagation in the global supply network: The dynamic agent-based model acclimate. Journal of Economic Dynamics and Control, 83, 232-269. doi:10.1016/j.jedc.2017.08.001Rezapour, S., Farahani, R. Z., & Pourakbar, M. (2017). Resilient supply chain network design under competition: A case study. European Journal of Operational Research, 259(3), 1017-1035. doi:10.1016/j.ejor.2016.11.041Ledwoch, A., Yasarcan, H., & Brintrup, A. (2018). The moderating impact of supply network topology on the effectiveness of risk management. International Journal of Production Economics, 197, 13-26. doi:10.1016/j.ijpe.2017.12.013Al-Othman, W. B. E., Lababidi, H. M. S., Alatiqi, I. M., & Al-Shayji, K. (2008). Supply chain optimization of petroleum organization under uncertainty in market demands and prices. European Journal of Operational Research, 189(3), 822-840. doi:10.1016/j.ejor.2006.06.081Ivanov, D., Dolgui, A., & Sokolov, B. (2017). Scheduling of recovery actions in the supply chain with resilience analysis considerations. International Journal of Production Research, 56(19), 6473-6490. doi:10.1080/00207543.2017.1401747Das, K. (2019). Integrating Lean, Green, and Resilience Criteria in a Sustainable Food Supply Chain Planning Model. International Journal of Mathematical, Engineering and Management Sciences, 4(2), 259-275. doi:10.33889/ijmems.2019.4.2-022Das, K. (2018). Integrating resilience in a supply chain planning model. International Journal of Quality & Reliability Management, 35(3), 570-595. doi:10.1108/ijqrm-08-2016-0136Arora, V., & Ventresca, M. (2018). Modeling topologically resilient supply chain networks. Applied Network Science, 3(1). doi:10.1007/s41109-018-0070-7Almeida, J. F. de F., Conceição, S. V., Pinto, L. R., de Camargo, R. S., & Júnior, G. de M. (2018). Flexibility evaluation of multiechelon supply chains. PLOS ONE, 13(3), e0194050. doi:10.1371/journal.pone.0194050Mancheri, N. A., Sprecher, B., Deetman, S., Young, S. B., Bleischwitz, R., Dong, L., … Tukker, A. (2018). Resilience in the tantalum supply chain. Resources, Conservation and Recycling, 129, 56-69. doi:10.1016/j.resconrec.2017.10.018Namdar, J., Li, X., Sawhney, R., & Pradhan, N. (2017). Supply chain resilience for single and multiple sourcing in the presence of disruption risks. International Journal of Production Research, 56(6), 2339-2360. doi:10.1080/00207543.2017.1370149Rozhkov, M., & Ivanov, D. (2018). CONTINGENCY PRODUCTION-INVENTORY CONTROL POLICY FOR CAPACITY DISRUPTIONS IN THE RETAIL SUPPLY CHAIN WITH PERISHABLE PRODUCTS. IFAC-PapersOnLine, 51(11), 1448-1452. doi:10.1016/j.ifacol.2018.08.311Sabouhi, F., Pishvaee, M. S., & Jabalameli, M. S. (2018). Resilient supply chain design under operational and disruption risks considering quantity discount: A case study of pharmaceutical supply chain. Computers & Industrial Engineering, 126, 657-672. doi:10.1016/j.cie.2018.10.001Zavitsas, K., Zis, T., & Bell, M. G. H. (2018). The impact of flexible environmental policy on maritime supply chain resilience. Transport Policy, 72, 116-128. doi:10.1016/j.tranpol.2018.09.020Mitra, K., Gudi, R. D., Patwardhan, S. C., & Sardar, G. (2009). Towards resilient supply chains: Uncertainty analysis using fuzzy mathematical programming. Chemical Engineering Research and Design, 87(7), 967-981. doi:10.1016/j.cherd.2008.12.025Lücker, F., Seifert, R. W., & Biçer, I. (2018). Roles of inventory and reserve capacity in mitigating supply chain disruption risk. International Journal of Production Research, 57(4), 1238-1249. doi:10.1080/00207543.2018.15041

An Investigation into Factors Affecting the Chilled Food Industry

With the advent of Industry 4.0, many new approaches towards process monitoring, benchmarking and traceability are becoming available, and these techniques have the potential to radically transform the agri-food sector. In particular, the chilled food supply chain (CFSC) contains a number of unique challenges by virtue of it being thought of as a temperature controlled supply chain. Therefore, once the key issues affecting the CFSC have been identified, algorithms can be proposed, which would allow realistic thresholds to be established for managing these problems on the micro, meso and macro scales. Hence, a study is required into factors affecting the CFSC within the scope of Industry 4.0. The study itself has been broken down into four main topics: identifying the key issues within the CFSC; implementing a philosophy of continuous improvement within the CFSC; identifying uncertainty within the CFSC; improving and measuring the performance of the supply chain. However, as a consequence of this study two further topics were added: a discussion of some of the issues surrounding information sharing between retailers and suppliers; some of the wider issues affecting food losses and wastage (FLW) on the micro, meso and macro scales. A hybrid algorithm is developed, which incorporates the analytic hierarchical process (AHP) for qualitative issues and data envelopment analysis (DEA) for quantitative issues. The hybrid algorithm itself is a development of the internal auditing algorithm proposed by Sueyoshi et al (2009), which in turn was developed following corporate scandals such as Tyco, Enron, and WorldCom, which have led to a decline in public trust. However, the advantage of the proposed solution is that all of the key issues within the CFSC identified can be managed from a single computer terminal, whilst the risk of food contamination such as the 2013 horsemeat scandal can be avoided via improved traceability

Energy use in the EU food sector: State of play and opportunities for improvement

The amount of energy necessary to cultivate, process, pack and bring the food to European citizens tables accounts for the 17 % of the EU's gross energy consumption, equivalent to about 26 % of the EU's final energy consumption in 2013. Challenges and solutions for decreasing energy consumption and increasing the use of renewable energy in the European food sector are presented and discussed.JRC.F.7-Renewables and Energy Efficienc

B2B Supply Chain Risk Measurement Systems: A SCOR Perspective

PurposeGlobalisation, trade barriers, unprecedented health crises and geo-political crises have forced organisations to revisit their performance measurement systems (PMS) to better prepare their supply chain against the risk and improve performance in times of crisis. This study aims to review the supply chain operation reference (SCOR)-based PMS and propose a dynamic SCOR-based PMS for supply chain risk management (SCRM).Design/methodology/approachDue to the need for multi-stakeholder perspectives on SCOR-based PMS for the SCRM, the authors aimed to develop a theory rather than to elaborate upon or test the theory. Hence, the authors adopted an inductive theory-building approach to build research propositions. The authors also gathered 12 semi-structured interviews with knowledgeable managers from B2B international companies.FindingsThe findings of the study highlight the challenges faced by the organisations during the implementation of the SCOR-based performance indicators and the positive impacts they have on decision-making and on the continuous improvement strategy of organisations to tackle supply chain risks and improve performance. The findings suggest that the effects of these indicators are more felt during risk management and risk monitoring stages.Research limitations/implicationsLike any other study, this study has some rules, and, thus, the authors caution the readers that they must interpret the findings of the research considering these limitations. The study is based on semi-structured qualitative interviews. The interviews were conducted with 12 knowledgeable managers from France; thus, the insights drawn from the study cannot be generalised to other settings. Furthermore, the samples represent something other than small and medium enterprises. In the future, the samples from small and medium firms can offer a nuanced understanding of the performance indicators for SCRM.Originality/valueTo the best of the authors’ knowledge, this is one of the few studies which has attempted to revisit the SCOR-based PMS in the B2B supply chain for risk management. The study’s findings help expand the SCOR-based PMS literature and offer numerous insights to the management and consultants facing challenges in SCOR implementation

Supplier collaboration for sustainability: a study of UK food supply chains

A thesis submitted to the University of Bedfordshire, in partial fulfilment of the requirements for the degree of doctor of Philosophy.Achieving sustainability in the supply chain is not a choice but an inevitable necessity for the organisation to survive and thrive in the long run. Supplier collaboration to achieve sustainability is widely recognised but poorly studied phenomena. While there is a handful of studies that focused on collaboration for sustainability in food supply chains, only a few considered sustainable (i.e. environmental, cost and social) or Triple Bottom Line (TBL) performance, and in the context of UK food industry, there is hardly any study. Building on previous studies, this thesis addressed these concerns conceptually and empirically by: a) examining supplier collaboration for sustainable performance; b) assessing supplier collaboration for environment friendly and socially responsible practices; c) measuring environment friendly and socially responsible practices for sustainable performance; and d) validating environment friendly and socially responsible practices as the mediators for supplier collaboration and sustainable performance. To achieve these objectives, first, a structured literature review was performed and identified 61 studies that documented supplier collaboration for sustainability, and a comprehensive review was also conducted to expand the research domain. Second, underpinned by Relational View (RV) theory, a set of 17 testable hypotheses (including sub-hypotheses) were developed, and a survey method was used to collect 203 useable data from UK based food businesses who maintain collaborative relationships with their suppliers. Finally, for data analysis, Partial Least Squared- Structural Equations Modelling (PLS-SEM) technique was used with SmartPLS3 software. The empirical findings validated that: a) supplier collaboration improves environmental, cost and social performance; b) supplier collaboration contributes to improved environment friendly and socially responsible practices; c) environment friendly practices enhance environmentally, cost and social performance; d) socially responsible practices have an impact on environmental and social performance, however socially responsible practices do not have an impact on cost performance; e) environment friendly and socially responsible practices mediate the relationship between supplier collaboration and sustainable performance. The results suggest that supplier collaboration enhances environment-friendly and socially responsible practices which will lead to enhanced environmental, cost and social performance. The contributions of this research to supply chain management literature are: a) to achieve sustainable performance in the food supply chain, collaboration with the suppliers is essential; b) collaborating with the suppliers, firms can improve their environment friendly and socially responsible practices; c) socially responsible practices in the supply chain enhance environmental and social performance but do not improve cost performance; c) this study extends the Relational View theory (RV) from the relation-specific assets for sustainable performance to the relation-specific assets for environmentally friendly and socially responsible practices which lead to sustainable performance. This study found that inter-organisational relationship facilitates environment-friendly and socially responsible practices which will lead to improved sustainable performance. For practitioners, this study offers the sustainability framework that suggests for greater collaboration with the suppliers to improve environment-friendly and socially responsible practices which should lead to a sustainable performance in the food industry. For the policymakers, this study offers a unique proposition to encourage a collaborative environment in the supply chain to achieve sustainable performance in the food industry

Social impact of artificial intelligence in Europe

La Inteligencia Artificial (IA) puede ser una herramienta de gran ayuda para el crecimiento y desarrollo de la sociedad. Para conseguir un enfoque más cercano y una evolución más eficaz de esta tecnología, la Comision Europea ha creado la red AI DIH, la cual centra su visión en el soporte de las pymes y sector público para implementar la IA en las diferentes regiones de Europa, ayudando a reducir la brecha entre las grandes corporaciones especializadas. En este documento se contextualiza la funcionalidad de la red DIH y cómo está actuando de cara a la IA, para introducir el análisis de los diferentes centros colaborativos enfocados a la IA. El resultado es una propuesta de técnicas, modelos y parámetros que pueden implementarse en esta red de centros, con el apoyo de Living Labs, para incrementar la efectividad y mejorar el producto/servicio final.Artificial intelligence (AI) can be a very useful tool for the growth and development of society. To achieve a closer approach and a more effective evolution of this technology, the European Commission has created the AI DIH network, which focuses its vision on supporting SMEs and the public sector to implement AI in the different regions of Europe, helping to close the gap between large specialized corporations. This document contextualizes the functionality of the DIH network and how it is acting in the face of AI, to introduce the analysis of the different collaborative centers focused on AI. The result is a proposal of techniques, models and parameters that can be implemented in this network of centers, supported by Living Labs, to increase effectiveness and improve the final product/service

Evolution of the mobile phone supply chain : the case of Ecuador

Thesis (S.M. in Technology and Policy)--Massachusetts Institute of Technology, Engineering Systems Division, 2010.Cataloged from PDF version of thesis.Includes bibliographical references (p. 87-88).The cell phone industry is growing at a vertiginous pace. It has a life-changing impact on individuals and businesses in developing countries, where it can make up for the lack of infrastructure. In Latin America, the cell phone supply chain faces challenges specific to developing countries. Success in these environments requires creative solutions and adaptable supply chains. Ecuador is no exception, and the rapid evolution of the industry over the last decade has led to various changes in the supply chain of mobile devices. This thesis characterizes the supply chain challenges faced by the cell phone industry in Latin America. Key challenges characterizing emerging markets are highlighted. By using the case of a leading wireless network service provider in Ecuador, the document explores changes in the supply chain structure resulting from the evolution of its relationship with a supply chain solutions company, Brightstar. This evolution is represented by three different cell phone supply chains. The supply chains provide examples of responses to the supply chain challenges. The performances of the supply chains are compared based on the notion of responsiveness. To this end, system dynamics is used as a tool to analyze the different systems and the dynamics in action. Based on this analysis, recommendations are formulated regarding the current supply chain structure.by Santolina Savannet.S.M.in Technology and Polic