• DOI: 10.62304/jieet.v3i02.81
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INNOVATIVE APPROACHES TO SUSTAINABLE SUPPLY CHAIN MANAGEMENT IN THE MANUFACTURING INDUSTRY: A SYSTEMATIC LITERATURE REVIEW

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Supply Chain Management 4.0: A Literature Review and Research Framework

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literature review for supply chain management

Supply chain management is constantly evolving. The business world is transitioning from one paradigm to the next. In the corporate sector, supply chain 4.0 is the most recent trend. This article examines and analyses the existing state-of-the-art literature on Supply Chain Management 4.0 (SCM 4.0) and the interaction between digital technologies and Supply Chain Management. A bibliometric study and a literature assessment of state-of-the-art publications in the relevant topic were done. The impact of emerging technology on various supply chain operations is examined in this research. In addition, the study establishes a foundation for future research and practice. Because it describes the pillar components for any supply chain change, the suggested work is valuable for both academics and practitioners. It also suggests a set of study questions that might be utilized as a foundation for the field's future research. This research presents a fresh and original literature review-based study on SCM4.0, as there is currently no comprehensive evaluation accessible that includes bibliometric analysis, motives, impediments, and the impact of technologies on distinct SC processes.

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  • Chaimaa Bentaher, Examining the Necessary Conditions for Successful Digital Transformation: A Case Study of Moroccan Companies , European Journal of Business and Management Research: Vol. 8 No. 2 (2023)

literature review for supply chain management

Smart Supply Chain Management: A Literature Review

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literature review for supply chain management

  • Nabila Bouti 11 &
  • Fatima El Khoukhi 12  

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 668))

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  • International Conference on Digital Technologies and Applications

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Industry 4.0 (I4.0) is an innovative way of improving organizations' production methods by using new technologies that revolutionize the Supply Chain (SC). Traditionally, SC managers focused on simple tasks such as delivering products to customers and assuring that a company maintains a sufficient supply of raw materials to sustain ongoing operations. However, with the fast progress in logistics, SC Management (SCM) has become a complicated process involving forecasting demands, establishing lucrative partnerships, and optimizing business performance. To overcome this challenge, Smart Supply Chain Management (SSCM) uses several technologies such as Big Data (BD), the Internet of things (IoT), Blockchain, Artificial Intelligence (AI), and Advanced Robotics (AR) to analyze data, and identifies trends and opportunities in the market that enhance the effectiveness of logistics, whether inside or outside of the company. This paper examines the available literature on SSCM. It aims to assess the impact of new technologies on SSCM.

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Ballou, R.H.: The evolution and future of logistics and supply chain management. Eur. Bus. Rev. 19 , 332–348 (2007). https://doi.org/10.1108/09555340710760152

Cooper, M.C., Lambert, D.M., Pagh, J.D.: Supply chain management: more than a new name for logistics. Int. J. Logist. Manag. 8 , 1–14 (1997). https://doi.org/10.1108/09574099710805556

Arnold, J.R.T., Chapman, S.N., Clive, L.M.: Introduction to materials management. Pearson Prentice Hall, Upper Saddle River, N.J (2008)

Google Scholar  

Ng, T.C., Lau, S.Y., Ghobakhloo, M., Fathi, M., Liang, M.S.: The application of industry 4.0 technological constituents for sustainable manufacturing: a content-centric review. Sustainability  14 , 4327 (2022). https://doi.org/10.3390/su14074327

Montabon, F.L., Pagell, M., Wu, Z.: Making sustainability sustainable. Journal of Supply Chain Management. 52, (2016)

Bai, C., Dallasega, P., Orzes, G., Sarkis, J.: Industry 4.0 technologies assessment: A sustainability perspective. Int. J. Production Econ. 229 , 107776 (2020). https://doi.org/10.1016/j.ijpe.2020.107776

van Goor, A.R., van Amstel, M.J.P., van Amstel, W.P.: Trends in supply chain management. In: European distribution and supply chain logistics, pp. 45–75. Routledge (2019)

Zhang, G.: Supply chain opportunities in industry 4.0. In: The 6th international Asia Conference on Industrial Engineering and Management Innovation (2015)

Militello, M., Camperlingo, L., Bortoleto, W.C.: Supply Chain 4.0 Results: A Systematic Literature Review. Presented at the Online Platform October 14 (2020)

Lee, S.J.: Review pf Literature and Curricula in Smart Supply Chain & Transportation, p. 26 (2018)

Shao, X.-F., Liu, W., Li, Y., Chaudhry, H.R., Yue, X.-G.: Multistage implementation framework for smart supply chain management under industry 4.0. Technol. Forecasting  Social Change 162 , 120354 (2021). https://doi.org/10.1016/j.techfore.2020.120354

Abdirad, M., Krishnan, K.: Industry 4.0 in logistics and supply chain management: a systematic literature review. Eng. Manag. J. 33 , 187–201 (2021). https://doi.org/10.1080/10429247.2020.1783935

Elkazini, R., Hadini, M., Ali, M.B., Sahaf, K., Rifai, S.: Impacts of adopting Industry 4.0 technologies on supply chain management:  Literat. Rev. 31 , 7 (2021)

Witkowski, K.: Internet of Things, Big Data, Industry 4.0 – Innovative solutions in logistics and supply chains management. elsevier. Proc. Eng., 763–769 (2017)

Büyüközkan, G., Göçer, F.: Digital Supply Chain: Literature review and a proposed framework for future research. Comput. Ind. 97 , 157–177 (2018). https://doi.org/10.1016/j.compind.2018.02.010

Zekhnini, K., Cherrafi, A., Bouhaddou, I., Benghabrit, Y., Garza-Reyes, J.A.: Supply chain management 4.0: a literature review and research framework. BIJ 28 , 465–501 (2020). https://doi.org/10.1108/BIJ-04-2020-0156

Tamym, L., Benyoucef, L., Moh, A.N.S.: Big data for supply chain management in industry 4.0 context : A comprehensive survey. In: 3th International Conference on Modeling, Optimization and Simuation - MOSIM 2020, p. 11 (2020)

Awwad, M., Kulkarni, P., Bapna, R., Marathe, A.: Big data analytics in supply chain: A Literat. Rev., 9 (2018)

Nguyen, T., Zhou, L., Spiegler, V., Ieromonachou, P., Lin, Y.: Big data analytics in supply chain management: A state-of-the-art literature review. Comput. Oper. Res. 98 , 254–264 (2018). https://doi.org/10.1016/j.cor.2017.07.004

Wang, G., Gunasekaran, A., Ngai, E.W.T., Papadopoulos, T.: Big data analytics in logistics and supply chain management: Certain investigations for research and applications. Int. J. Prod. Econ. 176 , 98–110 (2016). https://doi.org/10.1016/j.ijpe.2016.03.014

Tachizawa, E.M., Alvarez-Gil, M.J., Montes-Sancho, M.J.: How “smart cities” will change supply chain management. Supply Chain Manag. Int. J. 20 , 237–248 (2015). https://doi.org/10.1108/SCM-03-2014-0108

Min, H.: Artificial intelligence in supply chain management: theory and applications. Int J Log Res Appl 13 , 13–39 (2010). https://doi.org/10.1080/13675560902736537

Gunduz, M.A., Demir, S., Paksoy, T.: Matching functions of supply chain management with smart and sustainable Tools: A novel hybrid BWM-QFD based method. Comput. Ind. Eng. 162 , 107676 (2021). https://doi.org/10.1016/j.cie.2021.107676

Valan, J.A., Raj, Dr.E.B: Machine learning and big data analytics in iot based blood bank supply chain management system. IJAEMS 4 , 805–811 (2019). https://doi.org/10.22161/ijaems.4.12.4

Bhaveshkumar Pasi, Rane, S.B.: Smart supply chain management: a perspective of industry 4.0. Int. J. Adv. Sci. Technol. 29 , 3016–3030 (2020). https://doi.org/10.13140/RG.2.2.29012.01920

Frazzon, E.M., Rodriguez, C.M.T., Pereira, M.M., Pires, M.C., Uhlmann, I.: Towards supply chain management 4.0. BJO&PM 16 , 180–191 (2019). https://doi.org/10.14488/BJOPM.2019.v16.n2.a2

Fernández-Caramés, T.M., Blanco-Novoa, O., Froiz-Míguez, I., Fraga-Lamas, P.: towards an autonomous industry 4.0 Warehouse: A UAV and blockchain-based system for inventory and traceability applications in big data-driven supply chain management. Sensors 19 , 2394 (2019). https://doi.org/10.3390/s19102394

Issaoui, Y., Khiat, A., Bahnasse, A., Ouajji, H.: Smart logistics: study of the application of blockchain technology. Proc. Comput. Sci. 160 , 266–271 (2019). https://doi.org/10.1016/j.procs.2019.09.467

Wu, Y., Zhang, Y.: An integrated framework for blockchain-enabled supply chain trust management towards smart manufacturing. Adv. Eng. Inform. 51  (2022)

Nguyen, T.H., Nguyen, H.D., Tran, K.D., Nguyen, D.D.K., Tran, K.P.: Enabling smart supply chain management with artificial intelligence. In: Machine Learning and Probabilistic Graphical Models for Decision Support Systems, pp.  294–310. CRC Press, Boca Raton (2022)

Sardar, S.K., Sarkar, B., Kim, B.: Integrating machine learning, radio frequency identification, and consignment policy for reducing unreliability in smart supply chain management. Processes 9 , 247 (2021). https://doi.org/10.3390/pr9020247

Tirkolaee, E.B., Sadeghi, S., Mooseloo, F.M., Vandchali, H.R., Aeini, S.: Application of machine learning in supply chain management: a comprehensive overview of the main areas. Math. Probl. Eng. 2021 , 1–14 (2021). https://doi.org/10.1155/2021/1476043

Wisetsri, W., Donthu, S., Mehbodniya, A., Vyas, S., Quiñonez-Choquecota, J., Neware, R.: An investigation on the impact of digital revolution and machine learning in supply chain management. Materials Today: Proceedings. 56 , 3207–3210 (2022). https://doi.org/10.1016/j.matpr.2021.09.367

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Bouti, N., El Khoukhi, F. (2023). Smart Supply Chain Management: A Literature Review. In: Motahhir, S., Bossoufi, B. (eds) Digital Technologies and Applications. ICDTA 2023. Lecture Notes in Networks and Systems, vol 668. Springer, Cham. https://doi.org/10.1007/978-3-031-29857-8_89

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Supply Chain Management

ISSN : 1359-8546

Article publication date: 1 September 2005

The purpose of this paper is to review a sample of the literature relating to the integration and implementation of supply chain management practices from a strategic viewpoint.

Design/methodology/approach

The literature is examined from three perspectives. First, supply chain integration covers issues relating to integration of core processes across organizational boundaries through improved communication, partnerships, alliances and cooperation. Second, strategy and planning examines supply chain management as a strategic matter for trading partners, along with factors relating to the amount of planning required. Third, implementation issues concern factors critical for successful implementation, as well as issues specific to inter and intra‐organizational aspects of supply chain initiatives are contained in this sub‐group

An important emergent theme from the literature is the importance of taking a holistic view, and the systemic nature of interactions between the participants. At the same time, it is also apparent that this requirement to take such an holistic and systemic view of the supply chain acts as an impediment to more extensive implementation. The strategic nature of adopting a supply chain wide perspective, on the one hand provides significant potential benefit, and on the other requires trading partners to think and act strategically. This is easier said than done within a stand‐alone organization, let alone across a diverse and dispersed group of trading partners.

Research limitations/implications

The scope of this review is by design limited to a cross‐section of the literature in this area. As such, it cannot, and does not, attempt to be an examination of the full range of the literature, but a sampling of important and influential works.

Practical implications

This review of the literature serves to highlight the inter‐dependence between integration (technologies, logistics, and partnerships), a strategic view of supply chain systems, and implementation approach. All three need to inform and underpin each other in order for management of supply chains to be able to deliver on the promise of benefits for all trading partners.

Originality/value

This study reviews a sample of recent and classic literature in this field, and in doing so provides some clear guidelines for the conduct of future research.

  • Supply chain management
  • Integration
  • Management strategy

Power, D. (2005), "Supply chain management integration and implementation: a literature review", Supply Chain Management , Vol. 10 No. 4, pp. 252-263. https://doi.org/10.1108/13598540510612721

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Two decades of advancements in cold supply chain logistics for reducing food waste: a review with focus on the meat industry.

literature review for supply chain management

1. Introduction

Objective and scope of study.

  • What is the current state of the art on beef CSCL in terms of management, sustainability, network design, and the use of information technologies for red meat waste reduction?
  • To provide an overview of the current state of the art and to identify the gaps and contemporary challenges to red meat waste reduction;
  • To identify key research themes and their potential role and associated elements in mitigating red meat waste reduction, especially across the beef CSCL systems;
  • To pinpoint the directions in each theme that warrant further research advancement.

2. Materials and Methods

2.1. literature retrieval and selection, 2.2. extracting the research themes, 3.1. the literature review identified themes and subjects, 3.2. the literature’s evolution and descriptive results, 3.3. management, 3.3.1. logistics management and chronological evolution, 3.3.2. management and regulations, 3.3.3. management and collaboration, 3.3.4. management and costs, 3.3.5. management and inventory, 3.3.6. management and decision-making, 3.3.7. management and risks, 3.3.8. management and waste reduction, 3.3.9. management and information, 3.3.10. management and cold chain deficiencies, 3.4. sustainability, 3.4.1. sustainability and closed-loop scs (clscs), 3.4.2. sustainability and business models, 3.4.3. sustainability and wastage hotspots, 3.4.4. sustainability and packing, 3.4.5. sustainability and information flow, 3.5. network design optimisation, 3.5.1. network design and decision levels, 3.5.2. network design and the location–inventory problem, 3.5.3. network design and routing-inventory problem, 3.5.4. network design and the location routing problem, 3.5.5. network design and the integrated location–inventory routing problem, 3.5.6. network design and sustainability, 3.5.7. network design and information flow, 3.6. information technologies, 3.6.1. it and meat sc transformation, 3.6.2. emerging information technologies and meat scs, technical instruments, technological systems, 4. discussion, 4.1. management, 4.2. sustainability, 4.3. network design, 4.4. information technology, 5. conclusions.

  • Management: ◦ Effective management practices are crucial for addressing FLW in beef CSCL systems. ◦ There is a notable transition from LM to FLM and SFLM, with the potential for emerging technologies to create an “Intelligent Sustainable Food Logistics Management” phase. ◦ Suboptimal management practices continue to contribute significantly to FLW, underscoring the need for enhanced strategies and adherence to regulations and standards.
  • Sustainability: ◦ Sustainability in beef CSCL involves addressing social, economic, and environmental benefits. ◦ Reducing FLW can lead to increased profits, improved customer satisfaction, public health, equity, and environmental conservation by minimising resource use and emissions. ◦ Comprehensive research integrating all sustainability dimensions is needed to fully understand and mitigate FLW. Current efforts often address only parts of sustainability. A more holistic approach is required to balance environmental, economic, and social dimensions effectively.
  • Network Design: ◦ Effective network design and optimisation are pivotal in reducing FLW within beef CSCL systems. ◦ There is a necessity for integrating all three levels of management decisions in the logistics network design process. Decision levels in network design must be considered to understand trade-offs among sustainability components in this process. ◦ Future research should focus on integrating management decisions and network design, CSCL uncertainties, sustainability dimensions, and advanced technologies to enhance efficiency and reduce waste in beef CSCL systems.
  • Information Technologies: ◦ Information technologies such as Digital Twins (DTs) and Blockchain (BC) play a significant role in improving efficiency and reducing FLW in beef CSCL. ◦ The integration of these technologies can enhance understanding of fluid dynamics, thermal exchange, and meat quality variations, optimising the cooling process and reducing energy usage. ◦ Challenges like data security and management efficiency need to be addressed to maximise the benefits of these technologies.

Author Contributions

Data availability statement, acknowledgments, conflicts of interest.

Scholar, Ref.YearSubjectObjectives
I
IIMethodologyIndustry (Product)Measures to Reduce FLW
Gunasekaran et al. [ ]2008Logistics managementTo improve the responsiveness of SCsTo increase the competitiveness of SCsGroup Process and Analytical Hierarchy ProcessMulti-industry-
Dabbene et al. [ ]2008Food logistics management To minimise logistic costsTo maintain food product qualityStochastic optimisationFresh food -
Lipinski et al. [ ]2013Food logistics managementTo minimise the costs associated with food wasteTo reduce food wasteQualitative analysisFood productsProposing appropriate strategies
van der Vorst et al. [ ]2011Food logistics managementTo improve the competitiveness level, maintaining the quality of productsTo improve efficiency and reduce food waste levelsQualitative analysisAgrifood productsThe development of a diagnostic instrument for quality-controlled logistics
Soysal et al. [ ]2012Sustainable logistics management To enhance the level of sustainability and efficiency in food supply chainsTo reduce FLW levelsQualitative analysisFood supply chainsThe analysis of existing quantitative models, contributing to their development
Bettley and Burnley [ ]2008Sustainable logistics management (SLM) To improving environmental and social sustainabilityTo reduce costs and food wasteQualitative analysisMulti-industryapplication of a closed-loop supply chain concept to incorporate sustainability into operational strategies and practices
Zokaei and Simons, [ ]2006 SML, Collaboration, Regulation, Cost, Inventory, Waste reduction, Information sharing,To introduce the food value chain analysis (FVCA) methodology for improving consumer focus in the agri-food sectorTo present how the FVCA method enabled practitioners to identify the misalignments of both product attributes and supply chain activities with consumer needsStatistical analysis/FVCARed meatSuggesting the application of FVCA can improve the overall efficiency and reduce the waste level
Cox et al. [ ]2007SML, Cost, Decision-making, Risks, Waste reduction, Sustainability To demonstrate the proactive alignment of sourcing with marketing and branding strategies in the red meat industryTo showcase how this alignment can contribute to competitive advantage in the food industryQualitativeBeef and Red meatEmphasising the role of the lean approach, identifying waste hotspots, and collaboration in reducing food loss and waste
Jie and Gengatharen, [ ]2019SML, Regulation, Collaboration, Cost, Inventory, Waste reduction, Info. Sharing, IT, Sustainability, ScoTo empirically investigate the adoption of supply chain management practices on small and medium enterprises in the Australian food retail sectorTo analyse the structure of food and beverage distribution in the Australian retail marketStatistical analysisFood/Beef Meat IndustryAdopting lean thinking and improving information sharing in the supply chains
Knoll et al. [ ]2017SML, Collaboration, Regulation, Cost, Inventory, Decision-making, Risks, Information sharing, Deficiencies, Network designTo characterise the supply chain structureTo identify its major fragilitiesQualitativeBeef meat-
Schilling-Vacaflor, A., [ ] 2021Regulation, SustainabilityTo analyse the institutional design of supply chain regulationsTo integrate human rights and environmental concerns into these regulationsQualitativeBeef and Soy Industries-
Knoll et al. [ ]2018Regulation, Collaboration, Cost, Risks, Deficiencies, Decision-making, Sustainability, Information sharingTo analyse the information flow within the Sino-Brazilian beef trade, considering the opportunities presented by the Chinese beef market and the vulnerabilities in the supply chainTo investigate the challenges and opportunities in the information exchange process between China and Brazil within the beef trade sectorMixed methodBeef Industry-
E-Fatima et al. [ ]2022Regulation, Risks, Safety, Collaboration, Business model, Packing, information sharingTo critically examine the potential barriers to the implementation and adoption of Robotic Process Automation in beef supply chainsTo investigate the financial risks and barriers to the adoption of RPA in beef supply chainsMixed methodBeef supply chain-
Jedermann et al. [ ] 2014Regulations and Food SafetyTo reduce food loss and wasteTo improve traceabilityQualitative analysisMeat and Food productsProposing appropriate strategies to improve quality monitoring
Kayikci et al. [ ]2018Regulations, Sustainability, Waste reductionTo minimise food waste by investigating the role of regulations To improve sustainability, social and environmental benefitsGrey prediction methodRed meatProposing circular and central slaughterhouse model and emphasising efficiency of regulations based on circular economy comparing with the linear economy model
Storer et al. [ ]2014Regulation, Collaboration, Cost, Inventory, Decision-making, Risks, IT, Sustainability To examine how forming strategic supply chain relationships and developing strategic supply chain capability influences beneficial supply chain outcomesTo understand the factors influencing the utilisation of industry-led innovation in the form of electronic business solutionsMixed methodsBeef supply chain-
Liljestrand, K., [ ]2017Collaboration, FLW, Information sharingTo analyse sustainability practices adopted in collaboration, including vertical collaboration in the food supply chainTo explore the role of collaboration in tackling food loss and wasteQualitative analysisMeat and Food productsInvestigating how Food Policy can foster collaborations to reduce FLW
Mangla et al. [ ]2021Collaboration, food safety and traceabilityTo enhance food safety and traceability levels through collaboration lensTo examine traceability dimensions and decrease information hidingQualitative analysisMeat and Food productsOffering a framework for collaboration role in reducing info hiding and FLW in the circular economy
Liljestrand, K. [ ]2017Collaboration, FLW, Information sharingTo investigate the role of logistics management and relevant solutions in reducing FLWTo explore the role of collaboration in food supply chainsQualitative analysisMeat and Food productsExamining the role of collaborative forecasting in reducing food waste
Esmizadeh et al. [ ]2021Cost and Network designTo investigate the relations among cost, freshness, travel time, and Hub facilities vs Distribution centresTo investigate the product perishability effect in the distribution phase under hierarchical hub network designDeterministic optimisationMeat and food products-
Cristóbal et al. [ ]2018Cost, FLW and SustainabilityTo consider the cost factor in the planning to reduce FLWTo develop a method to reduce costs and FLW environmental effects and improve the sustainability levelMixed methodMeat and Food productsProposing novel methods and programmes for cost effective and sustainable FLW management
Esmizadeh et al. [ ]2021Cost and Network designTo investigate the relations among cost, freshness, travel time, and Hub facilities vs Distribution centresTo investigate the product perishability effect in the distribution phase under hierarchical hub network designDeterministic optimisationMeat and food products-
Faisal. M. N., [ ]2015Cost, Risks, Regulations, Deficiencies, Collaboration, Decision-making, IT, Information sharing To identify variables that act as inhibitors to transparency in a red meat supply chainTo contribute to making the supply chain more transparentMixed methodRed meat-
Shanoyan et al. [ ]2019Cost, Risks, Information sharingTo analyse the incentive structures at the producer–processor interface within the beef supply chain in BrazilTo assess the dynamics and effectiveness of incentive mechanisms between producers and processors in the Brazilian beef supply chainQualitativeBeef Industry-
Nakandala et al. [ ]2016Cost, SustainabilityTo minimise transportation costs and CO emissionsTo maximise product freshness and qualityStochastic optimisationMeat and food products-
Ge et al. [ ]2022Cost, Decision-making, To develop an optimal network model for the beef supply chain in the Northeastern USTo optimize the operations within this supply chainMathematical modellingBeef meat-
Hsiao et al. [ ]2017Cost, Inventory, Network designTo maximise distribution efficiency and customer satisfactionZTo minimise the quality drop of perishable food products/meatDeterministic optimisationMeat products-
Shanoyan et al. [ ]2019Cost, Risks, Information sharingTo analyse the incentive structures at the producer–processor interface within the beef supply chain in BrazilTo assess the dynamics and effectiveness of incentive mechanisms between producers and processors in the Brazilian beef supply chainQualitativeBeef Industry-
Magalhães et al. [ ]2020Inventory and FWTo identify FLW causes in the beef supply chain in Brazil and explore the role of inventory management strategies and demand forecasting in FLW issueTo investigate their interconnectionsMixed methodBeef meat industryProviding a theoretical basis to implement appropriate FLW mitigation strategies
Jedermann et al. [ ] 2014Inventory and Food SafetyTo reduce food loss and wasteTo improve traceabilityQualitative analysisMeat and Food productsProposing appropriate strategies to improve quality monitoring
Meksavang et al. [ ]2019Inventory, Cost, Decision-making, Information sharing, SustainabilityTo develop an extended picture fuzzy VIKOR approach for sustainable supplier managementTo apply the developed approach in the beef industry for sustainable supplier managementMixed methodsBeef meat-
Herron et al. [ ]2022Inventory and SustainabilityTo identify the minimum shelf life required to prevent food waste and develop FEFO modelsTo identify the risk of food products reaching the bacterial danger zone Deterministic optimisationMeat productsBuilding a decision-making model and incorporating quality and microbiological data
Rahbari et al. [ ]2021Decision-making and Network designTo minimise distribution cost, variable costTo reduce inventory costs, the total costDeterministic optimisationRed meat-
Taylor D.H., [ ]2006Decision-making, Cost Risks, Inventory, Waste Reduction, Deficiencies, Sustainability, Env.To examine the adoption and implementation of lean thinking in food supply chains, particularly in the UK pork sectorTo assess the environmental and economic impact of lean practices in the agri-food supply chainQualitativeRed meatSuggesting the combination of Value Chain Analysis and Lean principles
Erol and Saghaian, [ ]2022Risks, Cost, RegulationTo investigate the dynamics of price adjustment in the US beef sector during the COVID-19 pandemicTo analyse the impact of the pandemic on price adjustments within the US beef sectorMixed methodBeef Industry-
Galuchi et al. [ ]2019Risks, Regulations, Sustainability, Soc., Env.To identify the main sources of reputational risks in Brazilian Amazon beef supply chainsTo analyse the actions taken by slaughterhouses to manage these risksMixed methodBeef supply chainMitigating risks
Silvestre et al. [ ]2018Risks, Collaboration, Regulation, Management, Sustainability To examine the challenges associated with sustainable supply chain managementTo propose strategies for addressing identified challengesQualitativeBeef Industry-
Bogataj et al. [ ]2020Risks, Cost, Sustainability, InventoryTo maximise the profitTo improve sustainability performanceMixed methodBeef industryIncorporating the remaining shelf life in the decision-making process
Nguyen et al. [ ]2023Risks, Waste reduction, Sustainability, Cost, InventoryTo improve the operational efficiencyTo reduce carbon footprint and food wasteStatistical analysisBeef industryIdentifying the root causes of waste and proposing a framework composed of autonomous agents to minimise waste
Amani and Sarkodie, [ ]2022Risks, Information technologies, SustainabilityTo minimise overall cost and wasteTo improve the sustainability performanceStochastic optimisationMeat productsIncorporating artificial intelligence in the management context
Klein et al. [ ]2014Risks, Information TechnologiesTo analyse the use of mobile technology for management and risk controlTo identify drivers and barriers to mobile technology adoption in risk reduction-Beef meatIntroducing a framework that connects the challenges associated with the utilisation of mobile technology in SCM and risk control
Gholami-Zanjani et al. [ ]2021Risk, ND, Inventory, Wastage Hot Spots, SustainabilityTo reduce the risk effect and improve the resiliency against disruptionsTo minimise environmental implicationsStochastic optimisationMeat products-
Buisman et al. [ ]2019Waste reductionTo reduce food loss and waste at the retailer levelTo improve food safety level and maximise the profitStochastic optimisationMeat and Food productsEmploying a dynamically adjustable expiration date strategy and discounting policy
Verghese et al. [ ]2015Waste reduction, Information Technologies and SustainabilityTo reduce food waste in food supply chains and relevant costsTo improve the sustainability performanceQualitative analysisMeat and Food productsApplying of information technologies and improved packaging
Jedermann et al. [ ] 2014Waste reductionTo reduce food loss and wasteTo improve traceabilityQualitative analysisMeat and Food productsIntroducing some initiatives and waste reduction action plans
Mohebi and Marquez, [ ]2015Waste reduction and Information TechnologiesTo improve the customer satisfaction and the quality of food productsTo reduce food waste and lossQualitative analysisMeat productsProposing strategies and technologies for meat quality monitoring during the transport and storage phases
Kowalski et al. [ ]2021Waste reduction and Information TechnologiesTo reduce food wasteTo create a zero-waste solution for handling dangerous meat wasteMixed methodMeat productsRecovering meat waste and transforming it into raw, useful materials
Beheshti et al. [ ]2022Waste reduction, Network design, and Information TechnologiesTo reduce food waste by optimising the initial rental capacity and pre-equipped capacity required for the maximisation of profitTo optimise CLSCs and to improve cooperation level among supply chain stakeholdersStochastic optimisationMeat productsApplying optimisation across reverse logistics and closed-loop supply chains
Albrecht et al. [ ]2020Waste reduction, IT, Decision-making, InventoryTo examine the effectiveness of sourcing strategy in reducing food loss and waste and product quality To validate the applicability of the TTI monitoring system for meat productsMixed methodMeat productsApplying of new information technologies in order to monitor the quality of products
Eriksson et al. [ ]2014Waste reduction and SustainabilityTo compare the wastage of organic and conventional meatsTo compare the wastage of organic and conventional food productsMixed methodMeat and perishable food productsProviding hints to reduce the amount of food loss and waste based on research findings
Accorsi et al. [ ]2019Waste reduction, Decision support, Sustainability (Eco., Soc., Env.)To address sustainability and environmental concerns related to meat production and distributionTo maximise the profitDeterministic optimisationBeef and meat productsProviding a decision-support model for the optimal allocation flows across the supply chain and a system of valorisation for the network
Jo et al. [ ]2015Information technologies, SustainabilityTo reduce food loss and waste levels, improve food traceability and sustainabilityTo minimise CO emissionsMixed methodBeef meat productsIncorporating blockchain technology
Ersoy et al. [ ]2022Information technologies, Sustainability, Food loss and WasteTo improve collaboration among multi-tier suppliers through knowledge transfer and to provide green growth in the industry To improve traceability in the circular economy context through information technology innovationsStatistical analysisMeat productsSuggesting a validated conceptual framework expressing the role of information technologies in information sharing
Kler et al. [ ]2022Information technologies, SustainabilityTo minimise transport CO emission level and food waste levelTo improve traceability and demand monitoring levelsData AnalyticsMeat productsEmploying information technologies (IoT) and utilising data analytics for optimising the performance
Singh et al. [ ]2018IT, Information sharing, Waste reduction, Decision-making, and PackingTo explore the application of social media data analytics in enhancing supply chain management within the food industryTo investigate how social media data analytics can be utilised to improve decision-making processes and operational efficiencyMixed methodBeef and food supply chainHighlighting the role of content analysis of Twitter data obtained from beef supply chains and retailers
Martinez et al. [ ]2007Deficiencies, Regulation, Cost, InventoryTo improve food safetyTo lower regulatory costStatistical analysisMeat and food products-
Kayikci et al. [ ]2018Deficiencies, Regulations, Waste reduction, Sustainability To minimise food waste by investigating the role of regulationsTo improve sustainability, social and environmental benefitsGrey prediction methodRed meatProposing circular and central slaughterhouse model and emphasising efficiency of regulations based on circular economy comparing with the linear economy model
Nychas et al. [ ]2008Deficiencies, Waste reduction, Information TechnologiesTo characterise the microbial spoilage of meat samples during distributionTo assess the factors contributing to meat spoilageMixed methodMeat productsIdentifying and discussing factors contributing to meat spoilage
Sander et al. [ ]2018Deficiencies, Risks, Information TechnologiesTo investigate meat traceability by outlining the different aspects of transparency To understand the perspectives of various stakeholders regarding BCTQualitative analysisMeat products-
Scholar, Ref.YearSubjectObjectives
I
IIMethodologyIndustry (Product)Measures to Reduce FLW
Mahbubi and Uchiyama, [ ] 2020Eco, Soc., Evn., Management, Collaboration, IT, Information sharing To identify the Indonesian halal beef supply chain’s basic systemTo assess the sustainability level in the Indonesian halal beef supply chainLife cycle assessmentBeef IndustryIdentifying waste in different actors’ sections
Bragaglio et al. [ ]2018Env., Management, Inventory, Decision-makingTo assess and compare the environmental impacts of different beef production systems in ItalyTo provide a comprehensive analysis of the environmental implicationsLife cycle assessmentBeef Industry-
Zeidan et al. [ ]2020Env., Management, Collaboration, CostTo develop an existence inductive theoryTo study coordination failures in sustainable beef productionQualitativeBeef Industry-
Santos and Costa, [ ]2018Env., Packing, Management, Cost, RegulationsTo assess the role of large slaughterhouses in promoting sustainable intensification of cattle ranching in the Amazon and the CerradoTo evaluate the environmental and social impacts of large slaughterhouses Statistical AnalysisBeef Industry-
E-Fatima et al. [ ]2023Business model, Packing, Eco., Socio., Env., Management, Waste reductionTo investigate the financial risks and barriers in the adoption of robotic process automation (RPA) in the beef supply chainsTo examine the potential influence of RPA on sustainability in the beef industrySimulationBeef IndustryAdopting Robotic Process Automation
Huerta et al. [ ]2015Env., Packing, Waste Management, WasteTo assess the environmental impact of beef production in MexicoTo conduct a life cycle assessment of the beef production processLife cycle assessmentBeef IndustrySuggesting utilising generated organic waste to produce usable energy
Cox et al. [ ]2007Env., Business model, Packing, Management, Waste reduction, Information sharing, Cost, Risk To explore the creation of sustainable strategies within red meat supply chainsTo investigate the development of sustainable practices and strategies in the context of red meat supply chainsQualitativeRed meat IndustryProposing the adoption of lean strategies in the red meat supply chain industry
Teresa et al. [ ]2018Eco., Env., Business model, Management, Deficiencies, Regulation, Collaboration, CostTo provide current perspectives on cooperation among Irish beef farmersTo explore the future prospects of cooperation within the context of new producer organisation legislationQualitativeBeef IndustryHighlighting the role of legislation in the joint management of waste
Kyayesimira et al. [ ]2019Eco., Waste hotspots, Management, RegulationsTo identify and analyse the causes of losses at various post-harvest handling points along the beef value chain in UgandaTo estimate the economic losses incurred due to those factors Statistical analysisBeef IndustryProviding insights into potential improvements in the beef value chain management
Ranaei et al. [ ]2021Env., Eco., Wastage hotspots Management, deficiencies, Waste reduction, Regulation, Collaboration To identify the causes of meat waste and meat value chain losses in IranTo propose solutions to reduce meat value chain lossesQualitativeMeat/Red Meat IndustryIdentifying the causes and hotspots of wastage points and proposing solutions
Wiedemann et al. [ ]2015Env., Eco., Waste hotspots, Manag., InventoryTo assess the environmental impacts and resource use associated with meat exportTo determine the environmental footprintLife Cycle AssessmentRed meat IndustryProviding insights into potential improvements
Pinto et al. [ ]2022Sustainability (Eco., Evo., Soc.) Management To explore the sustainable management and utilisation of animal by-products and food waste in the meat industryTo analyse the food loss and waste valorisation of animal by-productsMixed methodMeat products and industryEmploying the CE concept in the context of the meat supply chain suggested the development of effective integrated logistics for wasted product collection
Chen et al. [ ]2021Sustainability (Env.) and ManagementTo identify existing similarities among animal-based supply chains To measure the reduction effect of interventions appliedMixed methodBeef meat and food productsApplying the food waste reduction scenario known to be effective in emission reduction
Martínez and Poveda, [ ] 2022Sustainability (Env.), ManagementTo minimise environmental impacts by exploring refrigeration system characteristicsTo develop refrigeration systems-based policies for improving food qualityMixed methodMeat and food products-
Peters et al. [ ]2010Sustainability (Env.), Wastage hotspotsTo assess the environmental impacts of red meat in a lifecycle scopeTo compare the findings with similar cases across the worldLife Cycle Impact AssessmentBeef meat and red meat-
Soysal et al. [ ]2014Sustainability (Env.), Wastage hotspots, Network DesignTo minimise inventory and transportation costs To minimise CO emissions Deterministic optimisationBeef meat-
Mohebalizadehgashti et al. [ ]2020Sustainability (Env.), Wastage hotspots, Network DesignTo maximise facility capacity, minimise total cost To minimise CO emissions Deterministic optimisationMeat products-
Fattahi et al. [ ]2013Sustainability (Env.), Packing, ManagementTo develop a model for measuring the performance of meat SCTo analyse the operational efficiency of meat SCMixed methodMeat products-
Florindo et al. [ ]2018Sustainability (Env.), Wastage hotspots, ManagementTo reduce carbon footprint To evaluate performance Mixed methodBeef meat-
Diaz et al. [ ]2021Sustainability (Env.), Wastage hotspotsTo conduct a lifecycle-based study to find the impact of energy efficiency measuresTo evaluate environmental impacts and to optimise the energy performanceLife Cycle Impact AssessmentBeef meatReconversing of Energy from Food Waste through Anaerobic Processes
Schmidt et al. [ ]2022Sustainability (Env.), Wastage hotspots, Management, Information TechnologiesTo optimise the supply chain by considering food traceability, economic, and environmental issuesTo reduce the impact and cost of recalls in case of food safety issuesDeterministic optimisationMeat products-
Mohammed and Wang, [ ]2017Sustainability (Eco.) Management, Decision-making, Network designTo minimise total cost, To maximise delivery rateTo minimise CO emissions and distribution time Stochastic optimisationMeat products-
Asem-Hiablie et al. [ ]2019Sustainability (Env.), energy consumption, greenhouse gasTo quantify the sustainability impacts associated with beef productsTo identify opportunities for reducing its environmental impactsLife cycle assessment Beef industry -
Bottani et al. [ ]2019Sustainability (Eco., and Env.), Packaging, Waste managementTo conduct an economic assessment of various reverse logistics scenarios for food waste recoveryTo perform an environmental assessment for themLife cycle assessmentMeat and food industryExamining and employing different reverse logistics scenarios
Kayikci et al. [ ]2018Sustainability (Eco., Soc., Env.) Management, Regulations, Waste reductionTo minimise food waste by investigating the role of regulations To improve sustainability, social and environmental benefitsGrey prediction methodRed meatProposing circular and central slaughterhouse model and emphasising efficiency of regulations based on circular economy comparing with the linear economy model
Tsakiridis et al. [ ]2020Sustainability (Env.), Information technologiesTo compare the economic and environmental impact of aquatic and livestock productsTo employ environmental impacts into the Bio-Economy modelLife cycle assessmentBeef and meat products-
Jo et al. [ ]2015Sustainability (Eco. and Env.), Management, Cost, Food Safety, Risks, Information TechnologiesTo reduce food loss and waste levels, improve food traceability and sustainabilityTo minimise CO emissionsMixed methodBeef meat productsIncorporating blockchain technology
Jeswani et al. [ ]2021Sustainability (Env.), Waste managementTo assess the extent of food waste generation in the UKTo evaluate its environmental impactsLife cycle assessmentMeat productsQuantifying the extent of FW and impact assessment
Accorsi et al. [ ]2020Sustainability (Eco. and Env.), Waste Management, Decision-making, Network design (LIP)To reduce waste and enhance sustainability performanceTo assess the economic and environmental implications of the proposed FSCDeterministic optimisationMeat and food industryDesigning a closed-loop packaging network
Chen et al. [ ]2021Sustainability (Env.) and Waste ManagementTo identify the environmental commonality among selected FSCsTo measure the reduction effect of novel interventions for market characteristicsLife cycle assessmentBeef meat and food productsConfirming the efficiency of food waste management and reduction scenario
Sgarbossa et al. [ ]2017Sustainability (Eco., Evo., Soc.) Network designTo develop a sustainable model for CLSCTo incorporate all three dimensions of sustainability Deterministic optimisationMeat productsConverting food waste into an output of a new supply chain
Zhang et al. [ ]2022Sustainability (Eco. and Env.), Packaging, Network designTo maximise total profitTo minimise environmental impact, carbon emissionsStochastic optimisationMeat and food productsUsing Returnable transport items instead of one-way packaging
Irani and Sharif., [ ]2016Sustainability (Soc.) Management, ITTo explore sustainable food security futuresTo provide perspectives on FW and IT across the food supply chainQualitative analysisMeat and food productsDiscussing potential strategies for waste reduction
Martindale et al. [ ]2020Sustainability (Eco. and Env.), Management, food safety, IT (BCT)To develop CE theory application in FSCs by employing a large geographical databaseTo test the data platforms for improving sustainabilityMixed methodMeat and food products-
Mundler, and Laughrea, [ ]2016Sustainability (Eco., Env., Soc.)To evaluate short food supply chains’ contributions to the territorial developmentTo characterise their economic, social, and environmental benefitsMixed methodMeat and food products-
Vittersø et al. [ ]2019Sustainability (Eco., Env., Soc.)To explore the contributions of short food supply chains to sustainabilityTo understand its impact on all sustainability dimensionsMixed methodMeat and food products-
Bernardi and Tirabeni, [ ]2018Sustainability (Eco., Env., Soc.)To explore alternative food networks as sustainable business modelsTo explore the potentiality of the sustainable business model proposedMixed methodMeat and food productsEmphasising the role of accurate demand forecast
Bonou et al. [ ]2020Sustainability (Env.)To evaluate the environmental impact of using six different cooling technologiesTo conduct a comparative study of pork supply chain efficiencyLife cycle assessmentPork products-
Apaiah et al. [ ] 2006Sustainability (Env.), Energy consumptionTo examine and measure the environmental sustainability of food supply chains using exergy analysisTo identify improvement areas to diminish their environmental implications Exergy analysisMeat products-
Peters et al. [ ]2010Sustainability (Env.), energy consumption, greenhouse gasTo assess greenhouse gas emissions and energy use levels of red meat products in AustraliaTo compare its environmental impacts with other countriesLife cycle assessmentRed meat products-
Farooque et al. [ ]2019Sustainability (Env., and Eco.) Management, Regulation, CollaborationTo identify barriers to employing the circular economy concept in food supply chainsTo analyse the relationship of identified barriersMixed methodFood productsEmploying the CE concept in the context of the food supply chain
Kaipia et al. [ ]2013Sustainability (Eco. and Env.) Management, Inventory, Information TechnologiesTo improve sustainability performance via information sharingTo reduce FLW levelQualitative analysisFood productsIncorporating demand and shelf-life data information sharing effect
Majewski et al. [ ]2020Sustainability (Env.) and Waste managementTo determine the environmental impact of short and longfood supply chainsTo compare the environmental sustainability of short and long-food supply chains Life cycle assessmentFood products-
Rijpkema et al. [ ]2014Sustainability (Eco. and Env.) Management, Waste reduction, Information Technologies To create effective sourcing strategies for supply chains dealing with perishable productsTo provide a method to reduce food waste and loss amountsSimulation modelFood productsProposing effective sourcing strategies
Scholar, Ref.YearModelling Stages:
Single or Multi
Solving ApproachObjectives
I
II/IIIModel TypeSupply Chain Industry (Product)Main Attributes
Domingues Zucchi et al. [ ]2011MMetaheuristic/GA and CPLEXTo minimise the cost of facility installationTo minimise costs for sea and road transportation MIPBeef meatLP
Soysal et al. [ ]2014Sε-constraint methodTo minimise inventory and transportation cost To minimise CO emissions LPBeef meatPIAP
Rahbari et al. [ ]2021MGAMSTo minimise total cost To minimise inventory, transport, storage costs MIPRed meatPLIRP
Rahbari et al. [ ]2020SGAMSTo minimise total cost MIPRed meatPLIRP
Neves-Moreira et al. [ ]2019SMetaheuristicTo minimise routing cost To minimise inventory holding cost MIPMeatPRP
Mohammadi et al. [ ]2023SPre-emptive fuzzy goal programmingTo maximise total profitTo minimise adverse environmental impactsMINLPMeat/Perishable food productsLIP
Mohebalizadehgashti
et al. [ ]
2020Sε-constraint methodTo maximise facility capacity, minimise total cost To minimise CO emissions MILPMeatLAP
Mohammed and Wang, [ ]2017aSLINGOTo minimise total cost To minimise number of vehicles/delivery timeMOPPMeatLRP
Mohammed and Wang, [ ]2017bSLINGOTo minimise otal cost, to maximise delivery rateTo minimise CO emissions and distribution time FMOPMeatLRP
Gholami Zanjani et al. [ ] 2021MMetaheuristicTo improve the resilience and sustainabilityTo minimise inventory holding cost MPMeatIP
Tarantilis and Kiranoudis, [ ]2002SMetaheuristicTo minimise total costTo maximise the efficiency of distributionOMDVRPMeatLRP
Dorcheh and Rahbari, [ ]2023MGAMSTo minimise total cost To minimise CO emissions MPMeat/PoultryIRP
Al Theeb et al. [ ]2020MHeuristic CPLEXTo minimise total cost, holding costs, and penalty costTo maximise the efficiency of transport and distribution phaseMILPMeat/Perishable food productsIRP
Moreno et al. [ ]2020SMetaheuristic/hybrid approachTo maximise the profitTo minimise the costs, delivery times MIPMeatLRP
Javanmard et al. [ ]2014SMetaheuristic/Imperialist competitive algorithmTo minimise inventory holding cost To minimise total cost NSFood and MeatIRP
Ge et al. [ ]2022SHeuristic algorithm To develop an optimal network model for the beef supply chain in the Northeastern USTo optimize the operations within this supply chainMILPBeef meatLRP
Hsiao et al. [ ]2017SMetaheuristic/GATo maximise distribution efficiency and customer satisfactionTo minimise the quality drop of perishable food products/meatMILP *Meat/Perishable food productsLRP
Govindan et al. [ ]2014MMetaheuristic/MHPVTo minimise carbon footprint To minimise of the cost of greenhouse gas emissions MOMIP *Perishable food productsLRP
Zhang et al. [ ]2003SMetaheuristicTo minimise cost, food safety risksTo maximise the distribution efficiencyMP *Perishable
food products
LRP
Wang and Ying, [ ]2012SHeuristic, Lagrange slack algorithmTo maximise the delivery efficiencyTo minimise the total costsMINLP *Perishable
food products
LRP
Liu et al. [ ]2021SYALMIP toolboxTo minimise cost and carbon emission To maximise product freshnessMP/MINLPPerishable
food products
LIRP
Dia et al. [ ]2018SMetaheuristic/GATo minimise total cost To reduce greenhouse gas emissions/maximise facility capacity MINLPPerishable
food products
LIP
Saragih et al. [ ]2019SSimulated annealingTo fix warehouse costTo minimise nventory cost, holding cost, and total cost MINLPFood productsLIRP
Biuki et al. [ ]2020MGA and PSOTo incorporate the three dimensions of sustainabilityTo minimise total cost, maximise facility capacity MIP *Perishable
products
LIRP
Hiassat et al. [ ]2017SGenetic algorithmTo implement facility and inventory storage costTo minimise routing cost MIPPerishable productsLIRP
Le et al. [ ]2013SHeuristic- Column generationTo minimise transport cost To minimise inventory cost MPPerishable productsIRP
Wang et al. [ ]2016STwo-phase Heuristic and Genetic algorithmTo minimise total cost To maximise the freshness of product quality MPPerishable
food products
RP
Rafie-Majd et al. [ ]2018SLagrangian relaxation/GAMSTo minimise total cost To minimise product wastage MINLP *Perishable productsLIRP
Scholar, Ref.YearSubject Objectives
I
IIMethodologyIndustry (Product)Measures to Reduce FLW
Singh et al. [ ]2018Information technologies, Sustainability, Regulations, ManagementTo measure greenhouse emission levels and select green suppliers with top-quality productsTo reduce carbon footprint and environmental implicationsMixed methodBeef supply chain-
Singh et al. [ ]2015Information technologies, Sus. (Env.), Inventory, Collaboration, ManagementTo reduce carbon footprint and carbon emissionsTo propose an integrated system for beef supply chain via the application of ITSimulationBeef supply chain-
Juan et al. [ ]2014Information technologies, Management, Inventory, Collaboration, ManagementTo explore the role of supply chain practices, strategic alliance, customer focus, and information sharing on food qualityTo explore the role of lean system and cooperation, trust, commitment, and information quality on food qualityStatistical analysisBeef supply chainBy application of IT and Lean system strategy
Zhang et al. [ ]2020Information technologies, Management, Inventory, Food quality and safetyTo develop a performance-driven conceptual framework regarding product quality information in supply chainsTo enhance the understanding of the impact of product quality information on performanceStatistical analysisRed meat supply chain-
Cao et al. [ ]2021IT, Blockchain, Management, Regulation, Collaboration, Risks, Cost, Waste reductionTo enhance consumer trust in the beef supply chain traceability through the implementation of a blockchain-based human–machine reconciliation mechanismTo investigate the role of blockchain technology in improving transparency and trust within the beef supply chain
Mixed methodBeef productsBy applying new information technologies
Kassahun et al. [ ]2016IT and ICTsTo provide a systematic approach for designing and implementing chain-wide transparency systemsTo design and implement a transparency system/software for beef supply chainsSimulationBeef meat IndustryBy improving the traceability
Ribeiro et al. [ ]2011IT and ICTsTo present and discuss the application of RFID technology in Brazilian harvest facilitiesTo analyse the benefits and challenges of implementing RFIDQualitativeBeef Industry-
Jo et al. [ ]2015IT (BCT) Sustainability (Eco. and Env.), Management, Cost, Food safety, RisksTo reduce food loss and waste levels, improve food traceability and sustainabilityTo minimise CO emissionsMixed methodBeef meat productsBy incorporating blockchain technology
Rejeb, A., [ ]2018IT (IoT, BCT), Management, risks, food safetyTo propose a traceability system for the Halal meat supply chainTo mitigate the centralised, opaque issues and the lack of transparency in traceability systemsMixed methodBeef meat and meat products-
Cao et al. [ ]2022IT and blockchain, Management, Collaboration, Risk, Cost, SustainabilityTo propose a blockchain-based multisignature approach for supply chain governanceTo present a specific use case from the Australian beef industryA novel blockchain-based multi-signature approachBeef Industry-
Kuffi et al. [ ]2016Digital 3D geometry scanningTo develop a CFD model to predict the changes in temperature and pH distribution of a beef carcass during chillingTo improve the performance of industrial cooling of large beef carcasses SimulationsBeef meat products-
Powell et al. [ ]2022Information technologies, (IoT and BCT)To examine the link between IoT and BCT in FSC for traceability improvementTo propose solutions for data integrity and trust in the BCT and IoT-enabled food SCsMixed methodBeef meat products-
Jedermann et al. [ ] 2014Management, Regulations and Food Safety, FW, Information sharing, RFIDTo reduce food loss and wasteTo improve traceabilityQualitative analysisMeat and Food productsBy proposing appropriate strategies to improve quality monitoring
Liljestrand, K., [ ]2017Collaboration, FLW, Information sharingTo analyse sustainability practices adopted in collaboration, including vertical collaboration in the food supply chainTo explore the role of collaboration in tackling food loss and wasteQualitative analysisMeat and Food productsBy investigating how Food Policy can foster collaborations to reduce FLW
Liljestrand, K., [ ]2017Collaboration, FLW, Information sharingTo analyse sustainability practices adopted in collaboration, including vertical collaboration in the food supply chainTo explore the role of collaboration in tackling food loss and wasteQualitative analysisMeat and Food productsBy investigating how Food Policy can foster collaborations to reduce FLW
Harvey, J. et al. [ ]2020IT and ICTs, Sustainability (Env. and Sco.), waste reduction, Management, decision-makingTo conduct social network analysis of food sharing, redistribution, and waste reductionTo reduce food waste via information sharing and IT applicationMixed methodFood productsBy examining the potential of social media applications in reducing food waste through sharing and redistribution
Rijpkema et al. [ ]2014IT (Sharing), Sustainability Management, Waste reduction To create effective sourcing strategies for SCs dealing with perishable productsTo provide a method to reduce food waste and loss amountsSimulation modelFood productsBy proposing effective sourcing strategies
Wu, and Hsiao., [ ]2021Information technologies, Management, Inventory, Food quality and safety, RisksTo identify and evaluate high-risk factorsTo mitigate risks and food safety accidentsMixed methodFood supply chainBy reducing food quality and safety risks and employing improvement plans
Kaipia et al. [ ]2013IT (Sharing), Sustainability (Eco. and Env.) Management, InventoryTo improve sustainability performance via information sharingTo reduce FLW levelQualitative analysisFood productsBy incorporating demand and shelf-life data information sharing effect
Mishra, N., and Singh, A., [ ]2018IT and ICTs, Sustainability (Env.), waste reduction, Management, decision-makingTo utilise Twitter data for waste minimisation in the beef supply chainTo contribute to the reduction in food wasteMixed methodFood productsBy offering insights into potential strategies for reducing food waste via social media and IT
Parashar et al. [ ]2020Information sharing (IT), Sustainability (Env.), FW Management (regulation, inventory, risks)To model the enablers of the food supply chain and improve its sustainability performanceTo address the reducing carbon footprints in the food supply chainsMixed methodFood productsBy facilitating the strategic decision-making regarding reducing food waste
Tseng et al. [ ]2022Regulations, Sustainability, Information technologies, (IoT and BCT)To conduct a data-driven comparison of halal and non-halal sustainable food supply chainsTo explore the role of regulations and standards in ensuring the compliance of food products with Halal requirements and FW reductionMixed methodFood productsBy highlighting the role of legislation in reducing food waste and promoting sustainable food management
Mejjaouli, and Babiceanu, [ ]2018Information technologies (RFID-WSN), Management, Decision-making To optimise logistics decisions based on actual transportation conditions and delivery locationsTo develop a logistics decision model via an IT applicationStochastic optimisationFood products-
Wu et al. [ ]2019IT (Information exchange), Sustainability (Eco., and Env.)To analyse the trade-offs between maintaining fruit quality and reducing environmental impactsTo combine virtual cold chains with life cycle assessment to provide a holistic approach for evaluating the environmental trade-offsMixed methodFood/fruit productsBy suggesting a more sustainability-driven cold chain scenario
  • Ren, Q.-S.; Fang, K.; Yang, X.-T.; Han, J.-W. Ensuring the quality of meat in cold chain logistics: A comprehensive review. Trends Food Sci. Technol. 2022 , 119 , 133–151. [ Google Scholar ] [ CrossRef ]
  • Nastasijević, I.; Lakićević, B.; Petrović, Z. (Eds.) Cold chain management in meat storage, distribution and retail: A review. In IOP Conference Series: Earth and Environmental Science ; IOP Publishing: Bristol, UK, 2017. [ Google Scholar ]
  • Brodribb, P. A Study of Waste in the Cold Food Chain and Opportunities for Improvement ; Expert Group: Hefei, China, 2020. [ Google Scholar ]
  • Castonguay, A.C.; Polasky, S.; Holden, M.H.; Herrero, M.; Mason-D’Croz, D.; Godde, C.; Chang, J.; Gerber, J.; Witt, G.B.; Game, E.T. Navigating sustainability trade-offs in global beef production. Nat. Sustain. 2023 , 6 , 284–294. [ Google Scholar ] [ CrossRef ]
  • FAO. FAOSTAT Online Database. 2021. Available online: http://faostat.fao.org/ (accessed on 20 September 2023).
  • Australia, M.L. Global Beef Industry and Trade Report ; Meat & Livestock Australia: Sydney, NSW, Australia, 2022. [ Google Scholar ]
  • Juan Ding, M.; Jie, F.; Parton, K.A.; Matanda, M.J. Relationships between quality of information sharing and supply chain food quality in the Australian beef processing industry. Int. J. Logist. Manag. 2014 , 25 , 85–108. [ Google Scholar ] [ CrossRef ]
  • Li, H.; Pan, P. (Eds.) Food waste in developed countries and cold chain logistics. In E3S Web of Conferences ; EDP Sciences: Les Ulis, France, 2021. [ Google Scholar ]
  • Ishangulyyev, R.; Kim, S.; Lee, S.H. Understanding food loss and waste—Why are we losing and wasting food? Foods 2019 , 8 , 297. [ Google Scholar ] [ CrossRef ]
  • National Food Waste Strategy: Halving Australia’s Food Waste by 2030. Department of Climate Change, Energy, the Environment and Water, Canberra, Australia. 2024. Available online: https://www.dcceew.gov.au/environment/protection/waste/food-waste#:~:text=Australia’s%20National%20Food%20Waste%20Strategy,the%20National%20Food%20Waste%20Strategy (accessed on 8 February 2024).
  • Keegan, E.; Breadsell, J.K. Food waste and social practices in Australian households. Sustainability 2021 , 13 , 3377. [ Google Scholar ] [ CrossRef ]
  • Aschemann-Witzel, J.; De Hooge, I.; Amani, P.; Bech-Larsen, T.; Oostindjer, M. Consumer-related food waste: Causes and potential for action. Sustainability 2015 , 7 , 6457–6477. [ Google Scholar ] [ CrossRef ]
  • Gokarn, S.; Kuthambalayan, T.S. Analysis of challenges inhibiting the reduction of waste in food supply chain. J. Clean. Prod. 2017 , 168 , 595–604. [ Google Scholar ] [ CrossRef ]
  • Yan, H.; Song, M.-J.; Lee, H.-Y. A Systematic Review of Factors Affecting Food Loss and Waste and Sustainable Mitigation Strategies: A Logistics Service Providers’ Perspective. Sustainability 2021 , 13 , 11374. [ Google Scholar ] [ CrossRef ]
  • Brennan, A.; Browne, S. Food waste and nutrition quality in the context of public health: A scoping review. Int. J. Environ. Res. Public Health 2021 , 18 , 5379. [ Google Scholar ] [ CrossRef ]
  • Neff, R.A.; Kanter, R.; Vandevijvere, S. Reducing food loss and waste while improving the public’s health. Health Aff. 2015 , 34 , 1821–1829. [ Google Scholar ] [ CrossRef ]
  • Luo, N.; Olsen, T.; Liu, Y. A Conceptual Framework to Analyze Food Loss and Waste within Food Supply Chains: An Operations Management Perspective. Sustainability 2021 , 13 , 927. [ Google Scholar ] [ CrossRef ]
  • Parashar, S.; Sood, G.; Agrawal, N. Modelling the enablers of food supply chain for reduction in carbon footprint. J. Clean. Prod. 2020 , 275 , 122932. [ Google Scholar ] [ CrossRef ]
  • Ma, L.; Qin, W.; Garnett, T.; Zhang, F. Review on drivers, trends and emerging issues of the food wastage in China. Front. Agric. Sci. Eng. 2015 , 2 , 159–167. [ Google Scholar ] [ CrossRef ]
  • Lan, S.; Tseng, M.-L.; Yang, C.; Huisingh, D. Trends in sustainable logistics in major cities in China. Sci. Total Environ. 2020 , 712 , 136381. [ Google Scholar ] [ CrossRef ]
  • Farooque, M.; Zhang, A.; Liu, Y. Barriers to circular food supply chains in China. Supply Chain Manag. Int. J. 2019 , 24 , 677–696. [ Google Scholar ] [ CrossRef ]
  • Han, J.-W.; Zuo, M.; Zhu, W.-Y.; Zuo, J.-H.; Lü, E.-L.; Yang, X.-T. A comprehensive review of cold chain logistics for fresh agricultural products: Current status, challenges, and future trends. Trends Food Sci. Technol. 2021 , 109 , 536–551. [ Google Scholar ] [ CrossRef ]
  • Martinez, M.G.; Fearne, A.; Caswell, J.A.; Henson, S. Co-regulation as a possible model for food safety governance: Opportunities for public–private partnerships. Food Policy 2007 , 32 , 299–314. [ Google Scholar ] [ CrossRef ]
  • Wang, K.Y.; Yip, T.L. Cold-chain systems in China and value-chain analysis. In Finance and Risk Management for International Logistics and the Supply Chain ; Elsevier: Amsterdam, The Netherlands, 2018; pp. 217–241. [ Google Scholar ]
  • Liu, M.; Dan, B.; Zhang, S.; Ma, S. Information sharing in an E-tailing supply chain for fresh produce with freshness-keeping effort and value-added service. Eur. J. Oper. Res. 2021 , 290 , 572–584. [ Google Scholar ] [ CrossRef ]
  • An, J.; Wang, L.; Lv, X. Research on agri-food cold chain logistics management system: Connotation, structure and operational mechanism. J. Serv. Sci. Manag. 2015 , 8 , 894–902. [ Google Scholar ] [ CrossRef ]
  • Zhang, J.; Cao, W.; Park, M. Reliability analysis and optimization of cold chain distribution system for fresh agricultural products. Sustainability 2019 , 11 , 3618. [ Google Scholar ] [ CrossRef ]
  • Zhang, H.; Qiu, B.; Zhang, K. A new risk assessment model for agricultural products cold chain logistics. Ind. Manag. Data Syst. 2017 , 117 , 1800–1816. [ Google Scholar ] [ CrossRef ]
  • Chauhan, C.; Dhir, A.; Akram, M.U.; Salo, J. Food loss and waste in food supply chains. A systematic literature review and framework development approach. J. Clean. Prod. 2021 , 295 , 126438. [ Google Scholar ] [ CrossRef ]
  • Luo, N.; Olsen, T.; Liu, Y.; Zhang, A. Reducing food loss and waste in supply chain operations. Transp. Res. Part E Logist. Transp. Rev. 2022 , 162 , 102730. [ Google Scholar ] [ CrossRef ]
  • Broeze, J.; Guo, X.; Axmann, H. Trade-Off Analyses of Food Loss and Waste Reduction and Greenhouse Gas Emissions in Food Supply Chains. Sustainability 2023 , 15 , 8531. [ Google Scholar ] [ CrossRef ]
  • Kumar, A.; Mangla, S.K.; Kumar, P. An integrated literature review on sustainable food supply chains: Exploring research themes and future directions. Sci. Total Environ. 2022 , 821 , 153411. [ Google Scholar ] [ CrossRef ]
  • Stindt, D. A generic planning approach for sustainable supply chain management-How to integrate concepts and methods to address the issues of sustainability? J. Clean. Prod. 2017 , 153 , 146–163. [ Google Scholar ] [ CrossRef ]
  • Tranfield, D.; Denyer, D.; Smart, P. Towards a methodology for developing evidence-informed management knowledge by means of systematic review. Br. J. Manag. 2003 , 14 , 207–222. [ Google Scholar ] [ CrossRef ]
  • Cerchione, R.; Esposito, E. A systematic review of supply chain knowledge management research: State of the art and research opportunities. Int. J. Prod. Econ. 2016 , 182 , 276–292. [ Google Scholar ] [ CrossRef ]
  • Ali, I.; Gölgeci, I. Where is supply chain resilience research heading? A systematic and co-occurrence analysis. Int. J. Phys. Distrib. Logist. Manag. 2019 , 49 , 793–815. [ Google Scholar ] [ CrossRef ]
  • VOSviewer. Available online: https://www.vosviewer.com/getting-started (accessed on 20 May 2023).
  • Chopra, S. Designing the distribution network in a supply chain. Transp. Res. Part E Logist. Transp. Rev. 2003 , 39 , 123–140. [ Google Scholar ] [ CrossRef ]
  • Gunasekaran, A.; Lai, K.-h.; Cheng, T.E. Responsive supply chain: A competitive strategy in a networked economy. Omega 2008 , 36 , 549–564. [ Google Scholar ] [ CrossRef ]
  • Dabbene, F.; Gay, P.; Sacco, N. Optimisation of fresh-food supply chains in uncertain environments, Part I: Background and methodology. Biosyst. Eng. 2008 , 99 , 348–359. [ Google Scholar ] [ CrossRef ]
  • Trienekens, J.; Zuurbier, P. Quality and safety standards in the food industry, developments and challenges. Int. J. Prod. Econ. 2008 , 113 , 107–122. [ Google Scholar ] [ CrossRef ]
  • Lipinski, B.; Hanson, C.; Lomax, J.; Kitinoja, L.; Waite, R.; Searchinger, T. Reducing Food Loss and Waste ; World Resources Institute: Washington, DC, USA, 2013. [ Google Scholar ]
  • van der Vorst, J.G.; van Kooten, O.; Luning, P.A. Towards a diagnostic instrument to identify improvement opportunities for quality controlled logistics in agrifood supply chain networks. Int. J. Food Syst. Dyn. 2011 , 2 , 94–105. [ Google Scholar ]
  • Wognum, P.N.; Bremmers, H.; Trienekens, J.H.; Van Der Vorst, J.G.; Bloemhof, J.M. Systems for sustainability and transparency of food supply chains–Current status and challenges. Adv. Eng. Inform. 2011 , 25 , 65–76. [ Google Scholar ] [ CrossRef ]
  • Soysal, M.; Bloemhof-Ruwaard, J.M.; Meuwissen, M.P.; van der Vorst, J.G. A review on quantitative models for sustainable food logistics management. Int. J. Food Syst. Dyn. 2012 , 3 , 136–155. [ Google Scholar ]
  • Koberg, E.; Longoni, A. A systematic review of sustainable supply chain management in global supply chains. J. Clean. Prod. 2019 , 207 , 1084–1098. [ Google Scholar ] [ CrossRef ]
  • Brandenburg, M.; Govindan, K.; Sarkis, J.; Seuring, S. Quantitative models for sustainable supply chain management: Developments and directions. Eur. J. Oper. Res. 2014 , 233 , 299–312. [ Google Scholar ] [ CrossRef ]
  • Bettley, A.; Burnley, S. Towards sustainable operations management integrating sustainability management into operations management strategies and practices. In Handbook of Performability Engineering ; Springer: Berlin/Heidelberg, Germany, 2008; pp. 875–904. [ Google Scholar ]
  • Zhong, R.; Xu, X.; Wang, L. Food supply chain management: Systems, implementations, and future research. Ind. Manag. Data Syst. 2017 , 117 , 2085–2114. [ Google Scholar ] [ CrossRef ]
  • Van der Meulen, B.M. The structure of European food law. Laws 2013 , 2 , 69–98. [ Google Scholar ] [ CrossRef ]
  • Kayikci, Y.; Ozbiltekin, M.; Kazancoglu, Y. Minimizing losses at red meat supply chain with circular and central slaughterhouse model. J. Enterp. Inf. Manag. 2020 , 33 , 791–816. [ Google Scholar ] [ CrossRef ]
  • Jedermann, R.; Nicometo, M.; Uysal, I.; Lang, W. Reducing food losses by intelligent food logistics. Philos. Trans. R. Soc. A Math. Phys. Eng. Sci. 2014 , 372 , 20130302. [ Google Scholar ] [ CrossRef ] [ PubMed ]
  • Yu, Z.; Liu, Y.; Wang, Q.; Sun, L.; Sun, S. (Eds.) Research on food safety and security of cold chain logistics. In IOP Conference Series: Earth and Environmental Science ; IOP Publishing: Bristol, UK, 2021; p. 012176. [ Google Scholar ]
  • Centobelli, P.; Cerchione, R.; Ertz, M. Food cold chain management: What we know and what we deserve. Supply Chain Manag. Int. J. 2021 , 26 , 102–135. [ Google Scholar ]
  • Lee, J.C.; Daraba, A.; Voidarou, C.; Rozos, G.; Enshasy, H.A.E.; Varzakas, T. Implementation of food safety management systems along with other management tools (HAZOP, FMEA, Ishikawa, Pareto). The case study of Listeria monocytogenes and correlation with microbiological criteria. Foods 2021 , 10 , 2169. [ Google Scholar ] [ CrossRef ] [ PubMed ]
  • Singh, R.K.; Luthra, S.; Mangla, S.K.; Uniyal, S. Applications of information and communication technology for sustainable growth of SMEs in India food industry. Resour. Conserv. Recycl. 2019 , 147 , 10–18. [ Google Scholar ] [ CrossRef ]
  • Nayak, R.; Waterson, P. Global food safety as a complex adaptive system: Key concepts and future prospects. Trends Food Sci. Technol. 2019 , 91 , 409–425. [ Google Scholar ] [ CrossRef ]
  • Tseng, M.-L.; Ha, H.M.; Tran, T.P.T.; Bui, T.-D.; Lim, M.K.; Lin, C.-W.; Helmi Ali, M. Data-driven on sustainable food supply chain: A comparison on Halal and non-Halal food system. J. Ind. Prod. Eng. 2022 , 39 , 430–457. [ Google Scholar ] [ CrossRef ]
  • Bortolini, M.; Faccio, M.; Ferrari, E.; Gamberi, M.; Pilati, F. Fresh food sustainable distribution: Cost, delivery time and carbon footprint three-objective optimization. J. Food Eng. 2016 , 174 , 56–67. [ Google Scholar ] [ CrossRef ]
  • Chan, F.T.; Wang, Z.; Goswami, A.; Singhania, A.; Tiwari, M.K. Multi-objective particle swarm optimisation based integrated production inventory routing planning for efficient perishable food logistics operations. Int. J. Prod. Res. 2020 , 58 , 5155–5174. [ Google Scholar ] [ CrossRef ]
  • Fikar, C. A decision support system to investigate food losses in e-grocery deliveries. Comput. Ind. Eng. 2018 , 117 , 282–290. [ Google Scholar ] [ CrossRef ]
  • Soysal, M.; Bloemhof-Ruwaard, J.M.; Haijema, R.; van der Vorst, J.G. Modeling a green inventory routing problem for perishable products with horizontal collaboration. Comput. Oper. Res. 2018 , 89 , 168–182. [ Google Scholar ] [ CrossRef ]
  • Liljestrand, K. Logistics solutions for reducing food waste. Int. J. Phys. Distrib. Logist. Manag. 2017 , 47 , 318–339. [ Google Scholar ] [ CrossRef ]
  • Halloran, A.; Clement, J.; Kornum, N.; Bucatariu, C.; Magid, J. Addressing food waste reduction in Denmark. Food Policy 2014 , 49 , 294–301. [ Google Scholar ] [ CrossRef ]
  • Cattaneo, A.; Sánchez, M.V.; Torero, M.; Vos, R. Reducing food loss and waste: Five challenges for policy and research. Food Policy 2021 , 98 , 101974. [ Google Scholar ] [ CrossRef ] [ PubMed ]
  • Wang, X. Research on Food Cold Chain Logistics System Collaboration. Carpathian J. Food Sci. Technol. 2016 , 8 , 131. [ Google Scholar ]
  • Weng, X.; An, J.; Yang, H. The analysis of the development situation and trend of the city-oriented cold chain logistics system for fresh agricultural products. Open J. Soc. Sci. 2015 , 3 , 70–80. [ Google Scholar ] [ CrossRef ]
  • Dania, W.A.P.; Xing, K.; Amer, Y. Collaboration behavioural factors for sustainable agri-food supply chains: A systematic review. J. Clean. Prod. 2018 , 186 , 851–864. [ Google Scholar ] [ CrossRef ]
  • Seuring, S.; Brix-Asala, C.; Khalid, R.U. Analyzing base-of-the-pyramid projects through sustainable supply chain management. J. Clean. Prod. 2019 , 212 , 1086–1097. [ Google Scholar ] [ CrossRef ]
  • Yu, Y.; Jaenicke, E.C. Estimating food waste as household production inefficiency. Am. J. Agric. Econ. 2020 , 102 , 525–547. [ Google Scholar ] [ CrossRef ]
  • Huang, H.; He, Y.; Li, D. Pricing and inventory decisions in the food supply chain with production disruption and controllable deterioration. J. Clean. Prod. 2018 , 180 , 280–296. [ Google Scholar ] [ CrossRef ]
  • Li, X.; Zhou, K. Multi-objective cold chain logistic distribution center location based on carbon emission. Environ. Sci. Pollut. Res. 2021 , 28 , 32396–32404. [ Google Scholar ] [ CrossRef ] [ PubMed ]
  • Dai, J.; Che, W.; Lim, J.J.; Shou, Y. Service innovation of cold chain logistics service providers: A multiple-case study in China. Ind. Mark. Manag. 2020 , 89 , 143–156. [ Google Scholar ] [ CrossRef ]
  • Al Theeb, N.; Smadi, H.J.; Al-Hawari, T.H.; Aljarrah, M.H. Optimization of vehicle routing with inventory allocation problems in Cold Supply Chain Logistics. Comput. Ind. Eng. 2020 , 142 , 106341. [ Google Scholar ] [ CrossRef ]
  • Zhao, H.; Liu, S.; Tian, C.; Yan, G.; Wang, D. An overview of current status of cold chain in China. Int. J. Refrig. 2018 , 88 , 483–495. [ Google Scholar ] [ CrossRef ]
  • Tang, J.; Zou, Y.; Xie, R.; Tu, B.; Liu, G. Compact supervisory system for cold chain logistics. Food Control 2021 , 126 , 108025. [ Google Scholar ] [ CrossRef ]
  • Badia-Melis, R.; Mc Carthy, U.; Ruiz-Garcia, L.; Garcia-Hierro, J.; Villalba, J.R. New trends in cold chain monitoring applications-A review. Food Control 2018 , 86 , 170–182. [ Google Scholar ] [ CrossRef ]
  • Liu, G.; Hu, J.; Yang, Y.; Xia, S.; Lim, M.K. Vehicle routing problem in cold Chain logistics: A joint distribution model with carbon trading mechanisms. Resour. Conserv. Recycl. 2020 , 156 , 104715. [ Google Scholar ] [ CrossRef ]
  • Esmizadeh, Y.; Bashiri, M.; Jahani, H.; Almada-Lobo, B. Cold chain management in hierarchical operational hub networks. Transp. Res. Part E Logist. Transp. Rev. 2021 , 147 , 102202. [ Google Scholar ] [ CrossRef ]
  • Chen, J.; Dan, B.; Shi, J. A variable neighborhood search approach for the multi-compartment vehicle routing problem with time windows considering carbon emission. J. Clean. Prod. 2020 , 277 , 123932. [ Google Scholar ] [ CrossRef ]
  • Wu, J.; Haasis, H.-D. The freight village as a pathway to sustainable agricultural products logistics in China. J. Clean. Prod. 2018 , 196 , 1227–1238. [ Google Scholar ] [ CrossRef ]
  • Tsamboulas, D.A.; Kapros, S. Freight village evaluation under uncertainty with public and private financing. Transp. Policy 2003 , 10 , 141–156. [ Google Scholar ] [ CrossRef ]
  • Pekkaya, M.; Keleş, N. Determining criteria interaction and criteria priorities in the freight village location selection process: The experts’ perspective in Turkey. Asia Pac. J. Mark. Logist. 2022 , 34 , 1348–1367. [ Google Scholar ] [ CrossRef ]
  • Shashi, S.; Cerchione, R.; Singh, R.; Centobelli, P.; Shabani, A. Food cold chain management: From a structured literature review to a conceptual framework and research agenda. Int. J. Logist. Manag. 2018 , 29 , 792–821. [ Google Scholar ] [ CrossRef ]
  • Magalhães, V.S.; Ferreira, L.M.D.; da Silva César, A.; Bonfim, R.M.; Silva, C. Food loss and waste in the Brazilian beef supply chain: An empirical analysis. Int. J. Logist. Manag. 2020 , 32 , 214–236. [ Google Scholar ] [ CrossRef ]
  • Hülsmann, M.; Brenner, V. Causes and Effects of Cold Chain Ruptures: Performance of Fragmented Versus Integrated Cold Chains ; Jacobs University, School of Engineering and Science, Internat. Logistics, Systems Management: Bremen, Germany, 2011. [ Google Scholar ]
  • Buisman, M.; Haijema, R.; Bloemhof-Ruwaard, J. Discounting and dynamic shelf life to reduce fresh food waste at retailers. Int. J. Prod. Econ. 2019 , 209 , 274–284. [ Google Scholar ] [ CrossRef ]
  • Kibler, K.M.; Reinhart, D.; Hawkins, C.; Motlagh, A.M.; Wright, J. Food waste and the food-energy-water nexus: A review of food waste management alternatives. Waste Manag. 2018 , 74 , 52–62. [ Google Scholar ] [ CrossRef ] [ PubMed ]
  • Herron, C.B.; Garner, L.J.; Siddique, A.; Huang, T.-S.; Campbell, J.C.; Rao, S.; Morey, A. Building “First Expire, First Out” models to predict food losses at retail due to cold chain disruption in the last mile. Front. Sustain. Food Syst. 2022 , 6 , 1018807. [ Google Scholar ] [ CrossRef ]
  • Mendes, A.; Cruz, J.; Saraiva, T.; Lima, T.M.; Gaspar, P.D. (Eds.) Logistics strategy (FIFO, FEFO or LSFO) decision support system for perishable food products. In Proceedings of the 2020 International Conference on Decision Aid Sciences and Application (DASA), Sakheer, Bahrain, 8–9 November 2020; IEEE: New York, NY, USA, 2020; pp. 173–178. [ Google Scholar ]
  • Plan, W.R.A. Reducing Food Waste through Retail Supply Chain Collaboration ; WRAP: Banbury, UK, 2011. [ Google Scholar ]
  • Nikolicic, S.; Kilibarda, M.; Maslaric, M.; Mircetic, D.; Bojic, S. Reducing food waste in the retail supply chains by improving efficiency of logistics operations. Sustainability 2021 , 13 , 6511. [ Google Scholar ] [ CrossRef ]
  • Kaipia, R.; Dukovska-Popovska, I.; Loikkanen, L. Creating sustainable fresh food supply chains through waste reduction. Int. J. Phys. Distrib. Logist. Manag. 2013 , 43 , 262–276. [ Google Scholar ] [ CrossRef ]
  • Govindan, K.; Kadziński, M.; Sivakumar, R. Application of a novel PROMETHEE-based method for construction of a group compromise ranking to prioritization of green suppliers in food supply chain. Omega 2017 , 71 , 129–145. [ Google Scholar ] [ CrossRef ]
  • Rahbari, M.; Hajiagha, S.H.R.; Mahdiraji, H.A.; Dorcheh, F.R.; Garza-Reyes, J.A. A novel location-inventory-routing problem in a two-stage red meat supply chain with logistic decisions: Evidence from an emerging economy. Kybernetes 2021 , 51 , 1498–1531. [ Google Scholar ] [ CrossRef ]
  • Yazdani, M.; Chatterjee, P.; Zavadskas, E.K.; Zolfani, S.H. Integrated QFD-MCDM framework for green supplier selection. J. Clean. Prod. 2017 , 142 , 3728–3740. [ Google Scholar ] [ CrossRef ]
  • Kieu, P.T.; Nguyen, V.T.; Nguyen, V.T.; Ho, T.P. A spherical fuzzy analytic hierarchy process (SF-AHP) and combined compromise solution (CoCoSo) algorithm in distribution center location selection: A case study in agricultural supply chain. Axioms 2021 , 10 , 53. [ Google Scholar ] [ CrossRef ]
  • Mihajlović, J.; Rajković, P.; Petrović, G.; Ćirić, D. The selection of the logistics distribution center location based on MCDM methodology in southern and eastern region in Serbia. Oper. Res. Eng. Sci. Theory Appl. 2019 , 2 , 72–85. [ Google Scholar ] [ CrossRef ]
  • Zanoni, S.; Zavanella, L. Chilled or frozen? Decision strategies for sustainable food supply chains. Int. J. Prod. Econ. 2012 , 140 , 731–736. [ Google Scholar ] [ CrossRef ]
  • Aravendan, M.; Panneerselvam, R. Literature review on network design problems in closed loop and reverse supply chains. Intell. Inf. Manag. 2014 , 6 , 104–117. [ Google Scholar ] [ CrossRef ]
  • Mejjaouli, S.; Babiceanu, R.F. Cold supply chain logistics: System optimization for real-time rerouting transportation solutions. Comput. Ind. 2018 , 95 , 68–80. [ Google Scholar ] [ CrossRef ]
  • Titiyal, R.; Bhattacharya, S.; Thakkar, J.J. The distribution strategy selection for an e-tailer using a hybrid DANP VIKOR MCDM model. Benchmarking Int. J. 2019 , 26 , 395–433. [ Google Scholar ] [ CrossRef ]
  • Gallo, A.; Accorsi, R.; Baruffaldi, G.; Manzini, R. Designing sustainable cold chains for long-range food distribution: Energy-effective corridors on the Silk Road Belt. Sustainability 2017 , 9 , 2044. [ Google Scholar ] [ CrossRef ]
  • Yakavenka, V.; Mallidis, I.; Vlachos, D.; Iakovou, E.; Eleni, Z. Development of a multi-objective model for the design of sustainable supply chains: The case of perishable food products. Ann. Oper. Res. 2020 , 294 , 593–621. [ Google Scholar ] [ CrossRef ]
  • Sel, Ç.; Pınarbaşı, M.; Soysal, M.; Çimen, M. A green model for the catering industry under demand uncertainty. J. Clean. Prod. 2017 , 167 , 459–472. [ Google Scholar ] [ CrossRef ]
  • Van Der Vorst, J.G.; Tromp, S.-O.; Zee, D.-J.v.d. Simulation modelling for food supply chain redesign; integrated decision making on product quality, sustainability and logistics. Int. J. Prod. Res. 2009 , 47 , 6611–6631. [ Google Scholar ] [ CrossRef ]
  • Bortolini, M.; Galizia, F.G.; Mora, C.; Botti, L.; Rosano, M. Bi-objective design of fresh food supply chain networks with reusable and disposable packaging containers. J. Clean. Prod. 2018 , 184 , 375–388. [ Google Scholar ] [ CrossRef ]
  • Li, Q.; Yu, P.; Wu, X. Shelf life extending packaging, inventory control and grocery retailing. Prod. Oper. Manag. 2017 , 26 , 1369–1382. [ Google Scholar ] [ CrossRef ]
  • Verghese, K.; Lewis, H.; Lockrey, S.; Williams, H. Packaging’s role in minimizing food loss and waste across the supply chain. Packag. Technol. Sci. 2015 , 28 , 603–620. [ Google Scholar ] [ CrossRef ]
  • Ghadge, A.; Kaklamanou, M.; Choudhary, S.; Bourlakis, M. Implementing environmental practices within the Greek dairy supply chain: Drivers and barriers for SMEs. Ind. Manag. Data Syst. 2017 , 117 , 1995–2014. [ Google Scholar ] [ CrossRef ]
  • Sajjad, A.; Eweje, G.; Tappin, D. Managerial perspectives on drivers for and barriers to sustainable supply chain management implementation: Evidence from New Zealand. Bus. Strategy Environ. 2020 , 29 , 592–604. [ Google Scholar ] [ CrossRef ]
  • Hien, D.N.; Thanh, N.V. Optimization of cold chain logistics with Fuzzy MCDM Model. Processes 2022 , 10 , 947. [ Google Scholar ] [ CrossRef ]
  • Saaty, T.L. Decision making with the analytic hierarchy process. Int. J. Serv. Sci. 2008 , 1 , 83–98. [ Google Scholar ] [ CrossRef ]
  • Karanam, M.; Krishnanand, L.; Manupati, V.K.; Antosz, K.; Machado, J. Identification of the critical enablers for perishable food supply chain using deterministic assessment models. Appl. Sci. 2022 , 12 , 4503. [ Google Scholar ] [ CrossRef ]
  • Kutlu Gündoğdu, F.; Kahraman, C. A novel VIKOR method using spherical fuzzy sets and its application to warehouse site selection. J. Intell. Fuzzy Syst. 2019 , 37 , 1197–1211. [ Google Scholar ] [ CrossRef ]
  • Ali, S.M.; Rahman, M.H.; Tumpa, T.J.; Rifat, A.A.M.; Paul, S.K. Examining price and service competition among retailers in a supply chain under potential demand disruption. J. Retail. Consum. Serv. 2018 , 40 , 40–47. [ Google Scholar ] [ CrossRef ]
  • Ali, S.M.; Nakade, K. Optimal ordering policies in a multi-sourcing supply chain with supply and demand disruptions-a CVaR approach. Int. J. Logist. Syst. Manag. 2017 , 28 , 180–199. [ Google Scholar ] [ CrossRef ]
  • Singh, A.; Shukla, N.; Mishra, N. Social media data analytics to improve supply chain management in food industries. Transp. Res. Part E Logist. Transp. Rev. 2018 , 114 , 398–415. [ Google Scholar ] [ CrossRef ]
  • Tang, C.S. Perspectives in supply chain risk management. Int. J. Prod. Econ. 2006 , 103 , 451–488. [ Google Scholar ] [ CrossRef ]
  • Ali, S.M.; Moktadir, M.A.; Kabir, G.; Chakma, J.; Rumi, M.J.U.; Islam, M.T. Framework for evaluating risks in food supply chain: Implications in food wastage reduction. J. Clean. Prod. 2019 , 228 , 786–800. [ Google Scholar ]
  • Govindan, K. Sustainable consumption and production in the food supply chain: A conceptual framework. Int. J. Prod. Econ. 2018 , 195 , 419–431. [ Google Scholar ] [ CrossRef ]
  • de Oliveira, U.R.; Marins, F.A.S.; Rocha, H.M.; Salomon, V.A.P. The ISO 31000 standard in supply chain risk management. J. Clean. Prod. 2017 , 151 , 616–633. [ Google Scholar ] [ CrossRef ]
  • Khan, O.; Burnes, B. Risk and supply chain management: Creating a research agenda. Int. J. Logist. Manag. 2007 , 18 , 197–216. [ Google Scholar ] [ CrossRef ]
  • Mangla, S.K.; Kumar, P.; Barua, M.K. An integrated methodology of FTA and fuzzy AHP for risk assessment in green supply chain. Int. J. Oper. Res. 2016 , 25 , 77–99. [ Google Scholar ] [ CrossRef ]
  • Bogataj, D.; Hudoklin, D.; Bogataj, M.; Dimovski, V.; Colnar, S. Risk mitigation in a meat supply chain with options of redirection. Sustainability 2020 , 12 , 8690. [ Google Scholar ] [ CrossRef ]
  • Nguyen, A.H.T.; Singh, A.; Kumari, S.; Choudhary, S. Multi-agent architecture for waste minimisation in beef supply chain. Prod. Plan. Control 2023 , 34 , 1082–1096. [ Google Scholar ] [ CrossRef ]
  • Deng, X.; Yang, X.; Zhang, Y.; Li, Y.; Lu, Z. Risk propagation mechanisms and risk management strategies for a sustainable perishable products supply chain. Comput. Ind. Eng. 2019 , 135 , 1175–1187. [ Google Scholar ] [ CrossRef ]
  • Srivastava, S.K.; Chaudhuri, A.; Srivastava, R.K. Propagation of risks and their impact on performance in fresh food retail. Int. J. Logist. Manag. 2015 , 26 , 568–602. [ Google Scholar ] [ CrossRef ]
  • Amani, M.A.; Sarkodie, S.A. Mitigating spread of contamination in meat supply chain management using deep learning. Sci. Rep. 2022 , 12 , 5037. [ Google Scholar ] [ CrossRef ] [ PubMed ]
  • Klein, A.Z.; Da Costa, E.G.; Vieira, L.M.; Teixeira, R. The use of mobile technology in management and risk control in the supply chain: The case of a Brazilian beef chain. J. Glob. Inf. Manag. (JGIM) 2014 , 22 , 14–33. [ Google Scholar ] [ CrossRef ]
  • Mohebi, E.; Marquez, L. Intelligent packaging in meat industry: An overview of existing solutions. J. Food Sci. Technol. 2015 , 52 , 3947–3964. [ Google Scholar ] [ CrossRef ] [ PubMed ]
  • Martins, C.; Melo, M.; Pato, M. Redesigning a food bank supply chain network in a triple bottom line context. Int. J. Prod. Econ. 2019 , 214 , 234–247. [ Google Scholar ] [ CrossRef ]
  • Kowalski, Z.; Kulczycka, J.; Makara, A.; Harazin, P. Quantification of material recovery from meat waste incineration–An approach to an updated food waste hierarchy. J. Hazard. Mater. 2021 , 416 , 126021. [ Google Scholar ] [ CrossRef ]
  • Teigiserova, D.A.; Hamelin, L.; Thomsen, M. Towards transparent valorization of food surplus, waste and loss: Clarifying definitions, food waste hierarchy, and role in the circular economy. Sci. Total Environ. 2020 , 706 , 136033. [ Google Scholar ] [ CrossRef ]
  • Beheshti, S.; Heydari, J.; Sazvar, Z. Food waste recycling closed loop supply chain optimization through renting waste recycling facilities. Sustain. Cities Soc. 2022 , 78 , 103644. [ Google Scholar ] [ CrossRef ]
  • Aschemann-Witzel, J.; Jensen, J.H.; Jensen, M.H.; Kulikovskaja, V. Consumer behaviour towards price-reduced suboptimal foods in the supermarket and the relation to food waste in households. Appetite 2017 , 116 , 246–258. [ Google Scholar ] [ CrossRef ] [ PubMed ]
  • Porpino, G. Household food waste behavior: Avenues for future research. J. Assoc. Consum. Res. 2016 , 1 , 41–51. [ Google Scholar ] [ CrossRef ]
  • Gholami-Zanjani, S.M.; Jabalameli, M.S.; Pishvaee, M.S. A resilient-green model for multi-echelon meat supply chain planning. Comput. Ind. Eng. 2021 , 152 , 107018. [ Google Scholar ] [ CrossRef ]
  • Rijpkema, W.A.; Rossi, R.; van der Vorst, J.G. Effective sourcing strategies for perishable product supply chains. Int. J. Phys. Distrib. Logist. Manag. 2014 , 44 , 494–510. [ Google Scholar ] [ CrossRef ]
  • Albrecht, A.; Ibald, R.; Raab, V.; Reichstein, W.; Haarer, D.; Kreyenschmidt, J. Implementation of time temperature indicators to improve temperature monitoring and support dynamic shelf life in meat supply chains. J. Packag. Technol. Res. 2020 , 4 , 23–32. [ Google Scholar ] [ CrossRef ] [ PubMed ]
  • Ndraha, N.; Vlajic, J.; Chang, C.-C.; Hsiao, H.-I. Challenges with food waste management in the food cold chains. In Food Industry Wastes ; Elsevier: Amsterdam, The Netherlands, 2020; pp. 467–483. [ Google Scholar ]
  • Thyberg, K.L.; Tonjes, D.J. Drivers of food waste and their implications for sustainable policy development. Resour. Conserv. Recycl. 2016 , 106 , 110–123. [ Google Scholar ] [ CrossRef ]
  • Saeed, M.A.; Kersten, W. Drivers of sustainable supply chain management: Identification and classification. Sustainability 2019 , 11 , 1137. [ Google Scholar ] [ CrossRef ]
  • Kumar, A.; Choudhary, S.; Garza-Reyes, J.A.; Kumar, V.; Rehman Khan, S.A.; Mishra, N. Analysis of critical success factors for implementing industry 4.0 integrated circular supply chain–Moving towards sustainable operations. Prod. Plan. Control 2023 , 34 , 984–998. [ Google Scholar ] [ CrossRef ]
  • Chauhan, A.; Debnath, R.M.; Singh, S.P. Modelling the drivers for sustainable agri-food waste management. Benchmarking Int. J. 2018 , 25 , 981–993. [ Google Scholar ] [ CrossRef ]
  • Jo, J.; Yi, S.; Lee, E.-k. Including the reefer chain into genuine beef cold chain architecture based on blockchain technology. J. Clean. Prod. 2022 , 363 , 132646. [ Google Scholar ] [ CrossRef ]
  • Kler, R.; Gangurde, R.; Elmirzaev, S.; Hossain, M.S.; Vo, N.V.; Nguyen, T.V.; Kumar, P.N. Optimization of Meat and Poultry Farm Inventory Stock Using Data Analytics for Green Supply Chain Network. Discret. Dyn. Nat. Soc. 2022 , 2022 , 8970549. [ Google Scholar ] [ CrossRef ]
  • Handfield, R.B.; Cousins, P.D.; Lawson, B.; Petersen, K.J. How can supply management really improve performance? A knowledge-based model of alignment capabilities. J. Supply Chain Manag. 2015 , 51 , 3–17. [ Google Scholar ] [ CrossRef ]
  • Qi, L.; Xu, M.; Fu, Z.; Mira, T.; Zhang, X. C2SLDS: A WSN-based perishable food shelf-life prediction and LSFO strategy decision support system in cold chain logistics. Food Control 2014 , 38 , 19–29. [ Google Scholar ] [ CrossRef ]
  • Matta, V.; Moberg, C. Defining the Antecedents for Adoption of RFID in the Supply Chain. Issues Inf. Syst. 2007 , 8 , 449–454. [ Google Scholar ]
  • Nychas, G.-J.E.; Skandamis, P.N.; Tassou, C.C.; Koutsoumanis, K.P. Meat spoilage during distribution. Meat Sci. 2008 , 78 , 77–89. [ Google Scholar ] [ CrossRef ]
  • Papargyropoulou, E.; Lozano, R.; Steinberger, J.K.; Wright, N.; bin Ujang, Z. The food waste hierarchy as a framework for the management of food surplus and food waste. J. Clean. Prod. 2014 , 76 , 106–115. [ Google Scholar ] [ CrossRef ]
  • Joshi, R.; Banwet, D.; Shankar, R.; Gandhi, J. Performance improvement of cold chain in an emerging economy. Prod. Plan. Control 2012 , 23 , 817–836. [ Google Scholar ] [ CrossRef ]
  • Sharma, S.; Pai, S.S. Analysis of operating effectiveness of a cold chain model using Bayesian networks. Bus. Process Manag. J. 2015 , 21 , 722–742. [ Google Scholar ] [ CrossRef ]
  • Cousins, P.D.; Menguc, B. The implications of socialization and integration in supply chain management. J. Oper. Manag. 2006 , 24 , 604–620. [ Google Scholar ] [ CrossRef ]
  • Beulens, A.J.; Broens, D.-F.; Folstar, P.; Hofstede, G.J. Food safety and transparency in food chains and networks Relationships and challenges. Food Control 2005 , 16 , 481–486. [ Google Scholar ] [ CrossRef ]
  • Mangla, S.K.; Sharma, Y.K.; Patil, P.P.; Yadav, G.; Xu, J. Logistics and distribution challenges to managing operations for corporate sustainability: Study on leading Indian diary organizations. J. Clean. Prod. 2019 , 238 , 117620. [ Google Scholar ] [ CrossRef ]
  • Balaji, M.; Arshinder, K. Modeling the causes of food wastage in Indian perishable food supply chain. Resour. Conserv. Recycl. 2016 , 114 , 153–167. [ Google Scholar ]
  • Kuo, J.-C.; Chen, M.-C. Developing an advanced multi-temperature joint distribution system for the food cold chain. Food Control 2010 , 21 , 559–566. [ Google Scholar ] [ CrossRef ]
  • Smigic, N.; Antic, D.; Blagojevic, B.; Tomasevic, I.; Djekic, I. The level of food safety knowledge among meat handlers. Br. Food J. 2016 , 118 , 9–25. [ Google Scholar ] [ CrossRef ]
  • Sander, F.; Semeijn, J.; Mahr, D. The acceptance of blockchain technology in meat traceability and transparency. Br. Food J. 2018 , 120 , 2066–2079. [ Google Scholar ] [ CrossRef ]
  • Patel, S.; Dora, M.; Hahladakis, J.N.; Iacovidou, E. Opportunities, challenges and trade-offs with decreasing avoidable food waste in the UK. Waste Manag. Res. 2021 , 39 , 473–488. [ Google Scholar ] [ CrossRef ]
  • Raak, N.; Symmank, C.; Zahn, S.; Aschemann-Witzel, J.; Rohm, H. Processing-and product-related causes for food waste and implications for the food supply chain. Waste Manag. 2017 , 61 , 461–472. [ Google Scholar ] [ CrossRef ] [ PubMed ]
  • Wittstruck, D.; Teuteberg, F. Understanding the success factors of sustainable supply chain management: Empirical evidence from the electrics and electronics industry. Corp. Soc. Responsib. Environ. Manag. 2012 , 19 , 141–158. [ Google Scholar ] [ CrossRef ]
  • Paul, A.; Shukla, N.; Paul, S.K.; Trianni, A. Sustainable supply chain management and multi-criteria decision-making methods: A systematic review. Sustainability 2021 , 13 , 7104. [ Google Scholar ] [ CrossRef ]
  • Parfitt, J.; Barthel, M.; Macnaughton, S. Food waste within food supply chains: Quantification and potential for change to 2050. Philos. Trans. R. Soc. B Biol. Sci. 2010 , 365 , 3065–3081. [ Google Scholar ] [ CrossRef ]
  • Pinto, J.; Boavida-Dias, R.; Matos, H.A.; Azevedo, J. Analysis of the food loss and waste valorisation of animal by-products from the retail sector. Sustainability 2022 , 14 , 2830. [ Google Scholar ] [ CrossRef ]
  • Mota, B.; Gomes, M.I.; Carvalho, A.; Barbosa-Povoa, A.P. Towards supply chain sustainability: Economic, environmental and social design and planning. J. Clean. Prod. 2015 , 105 , 14–27. [ Google Scholar ] [ CrossRef ]
  • Mohammed, A.; Wang, Q. The fuzzy multi-objective distribution planner for a green meat supply chain. Int. J. Prod. Econ. 2017 , 184 , 47–58. [ Google Scholar ] [ CrossRef ]
  • Zhang, X.; Zhao, G.; Qi, Y.; Li, B. A robust fuzzy optimization model for closed-loop supply chain networks considering sustainability. Sustainability 2019 , 11 , 5726. [ Google Scholar ] [ CrossRef ]
  • Ko, H.J.; Evans, G.W. A genetic algorithm-based heuristic for the dynamic integrated forward/reverse logistics network for 3PLs. Comput. Oper. Res. 2007 , 34 , 346–366. [ Google Scholar ] [ CrossRef ]
  • Mosallanezhad, B.; Arjomandi, M.A.; Hashemi-Amiri, O.; Gholian-Jouybari, F.; Dibaj, M.; Akrami, M.; Hajiaghaei-Keshteli, M. Metaheuristic optimizers to solve multi-echelon sustainable fresh seafood supply chain network design problem: A case of shrimp products. Alex. Eng. J. 2023 , 68 , 491–515. [ Google Scholar ] [ CrossRef ]
  • Accorsi, R.; Ferrari, E.; Gamberi, M.; Manzini, R.; Regattieri, A. A closed-loop traceability system to improve logistics decisions in food supply chains: A case study on dairy products. In Advances in Food Traceability Techniques and Technologies ; Elsevier: Amsterdam, The Netherlands, 2016; pp. 337–351. [ Google Scholar ]
  • Alinezhad, M.; Mahdavi, I.; Hematian, M.; Tirkolaee, E.B. A fuzzy multi-objective optimization model for sustainable closed-loop supply chain network design in food industries. Environ. Dev. Sustain. 2022 , 24 , 8779–8806. [ Google Scholar ] [ CrossRef ]
  • Sgarbossa, F.; Russo, I. A proactive model in sustainable food supply chain: Insight from a case study. Int. J. Prod. Econ. 2017 , 183 , 596–606. [ Google Scholar ] [ CrossRef ]
  • Zhang, Y.; Che, A.; Chu, F. Improved model and efficient method for bi-objective closed-loop food supply chain problem with returnable transport items. Int. J. Prod. Res. 2022 , 60 , 1051–1068. [ Google Scholar ] [ CrossRef ]
  • Amin, S.H.; Zhang, G.; Eldali, M.N. A review of closed-loop supply chain models. J. Data Inf. Manag. 2020 , 2 , 279–307. [ Google Scholar ] [ CrossRef ]
  • MahmoumGonbadi, A.; Genovese, A.; Sgalambro, A. Closed-loop supply chain design for the transition towards a circular economy: A systematic literature review of methods, applications and current gaps. J. Clean. Prod. 2021 , 323 , 129101. [ Google Scholar ] [ CrossRef ]
  • Tavana, M.; Kian, H.; Nasr, A.K.; Govindan, K.; Mina, H. A comprehensive framework for sustainable closed-loop supply chain network design. J. Clean. Prod. 2022 , 332 , 129777. [ Google Scholar ] [ CrossRef ]
  • Martindale, W.; Duong, L.; Swainson, M. Testing the data platforms required for the 21st century food system using an industry ecosystem approach. Sci. Total Environ. 2020 , 724 , 137871. [ Google Scholar ] [ CrossRef ] [ PubMed ]
  • Vlajic, J.V.; Mijailovic, R.; Bogdanova, M. Creating loops with value recovery: Empirical study of fresh food supply chains. Prod. Plan. Control 2018 , 29 , 522–538. [ Google Scholar ] [ CrossRef ]
  • Liu, Z.; de Souza, T.S.; Holland, B.; Dunshea, F.; Barrow, C.; Suleria, H.A. Valorization of food waste to produce value-added products based on its bioactive compounds. Processes 2023 , 11 , 840. [ Google Scholar ] [ CrossRef ]
  • Mangla, S.K.; Luthra, S.; Mishra, N.; Singh, A.; Rana, N.P.; Dora, M.; Dwivedi, Y. Barriers to effective circular supply chain management in a developing country context. Prod. Plan. Control 2018 , 29 , 551–569. [ Google Scholar ] [ CrossRef ]
  • Sehnem, S.; Jabbour, C.J.C.; Pereira, S.C.F.; de Sousa Jabbour, A.B.L. Improving sustainable supply chains performance through operational excellence: Circular economy approach. Resour. Conserv. Recycl. 2019 , 149 , 236–248. [ Google Scholar ] [ CrossRef ]
  • Wiskerke, J.S.; Roep, D. Constructing a sustainable pork supply chain: A case of techno-institutional innovation. J. Environ. Policy Plan. 2007 , 9 , 53–74. [ Google Scholar ] [ CrossRef ]
  • Ilbery, B.; Maye, D. Alternative (shorter) food supply chains and specialist livestock products in the Scottish–English borders. Environ. Plan. A 2005 , 37 , 823–844. [ Google Scholar ] [ CrossRef ]
  • Mundler, P.; Laughrea, S. The contributions of short food supply chains to territorial development: A study of three Quebec territories. J. Rural Stud. 2016 , 45 , 218–229. [ Google Scholar ] [ CrossRef ]
  • Rucabado-Palomar, T.; Cuéllar-Padilla, M. Short food supply chains for local food: A difficult path. Renew. Agric. Food Syst. 2020 , 35 , 182–191. [ Google Scholar ] [ CrossRef ]
  • Vittersø, G.; Torjusen, H.; Laitala, K.; Tocco, B.; Biasini, B.; Csillag, P.; de Labarre, M.D.; Lecoeur, J.-L.; Maj, A.; Majewski, E. Short food supply chains and their contributions to sustainability: Participants’ views and perceptions from 12 European cases. Sustainability 2019 , 11 , 4800. [ Google Scholar ] [ CrossRef ]
  • Blanquart, C.; Gonçalves, A.; Vandenbossche, L.; Kebir, L.; Petit, C.; Traversac, J.-B. (Eds.) The logistic leverages of short food supply chains performance in terms of sustainability. In Proceedings of the 12th World Conference on Transport Research, Lisbonne, Portugal, 11–15 July 2010. 10p. [ Google Scholar ]
  • Majewski, E.; Komerska, A.; Kwiatkowski, J.; Malak-Rawlikowska, A.; Wąs, A.; Sulewski, P.; Gołaś, M.; Pogodzińska, K.; Lecoeur, J.-L.; Tocco, B. Are short food supply chains more environmentally sustainable than long chains? A life cycle assessment (LCA) of the eco-efficiency of food chains in selected EU countries. Energies 2020 , 13 , 4853. [ Google Scholar ] [ CrossRef ]
  • Collison, M.; Collison, T.; Myroniuk, I.; Boyko, N.; Pellegrini, G. Transformation trends in food logistics for short food supply chains-what is new? Stud. Agric. Econ. 2019 , 121 , 102–110. [ Google Scholar ] [ CrossRef ]
  • De Bernardi, P.; Tirabeni, L. Alternative food networks: Sustainable business models for anti-consumption food cultures. Br. Food J. 2018 , 120 , 1776–1791. [ Google Scholar ] [ CrossRef ]
  • Loiseau, E.; Colin, M.; Alaphilippe, A.; Coste, G.; Roux, P. To what extent are short food supply chains (SFSCs) environmentally friendly? Application to French apple distribution using Life Cycle Assessment. J. Clean. Prod. 2020 , 276 , 124166. [ Google Scholar ] [ CrossRef ]
  • Chen, W.; Jafarzadeh, S.; Thakur, M.; Ólafsdóttir, G.; Mehta, S.; Bogason, S.; Holden, N.M. Environmental impacts of animal-based food supply chains with market characteristics. Sci. Total Environ. 2021 , 783 , 147077. [ Google Scholar ] [ CrossRef ]
  • Hill, A. Whole of Meat Supply Chain Food Loss and Waste Mapping and Interventions-Phase 1–Final Report ; Meat and Livestock Australia (MLA): Sydney, NSW, Australia, 2023. [ Google Scholar ]
  • Bonou, A.; Colley, T.A.; Hauschild, M.Z.; Olsen, S.I.; Birkved, M. Life cycle assessment of Danish pork exports using different cooling technologies and comparison of upstream supply chain efficiencies between Denmark, China and Australia. J. Clean. Prod. 2020 , 244 , 118816. [ Google Scholar ] [ CrossRef ]
  • Chen, Q.; Qian, J.; Yang, H.; Wu, W. Sustainable food cold chain logistics: From microenvironmental monitoring to global impact. Compr. Rev. Food Sci. Food Saf. 2022 , 21 , 4189–4209. [ Google Scholar ] [ CrossRef ]
  • Caldeira, C.; De Laurentiis, V.; Corrado, S.; van Holsteijn, F.; Sala, S. Quantification of food waste per product group along the food supply chain in the European Union: A mass flow analysis. Resour. Conserv. Recycl. 2019 , 149 , 479–488. [ Google Scholar ] [ CrossRef ] [ PubMed ]
  • Betz, A.; Buchli, J.; Göbel, C.; Müller, C. Food waste in the Swiss food service industry–Magnitude and potential for reduction. Waste Manag. 2015 , 35 , 218–226. [ Google Scholar ] [ CrossRef ]
  • Apaiah, R.K.; Linnemann, A.R.; Van Der Kooi, H.J. Exergy analysis: A tool to study the sustainability of food supply chains. Food Res. Int. 2006 , 39 , 1–11. [ Google Scholar ] [ CrossRef ]
  • Peters, G.M.; Rowley, H.V.; Wiedemann, S.; Tucker, R.; Short, M.D.; Schulz, M. Red meat production in Australia: Life cycle assessment and comparison with overseas studies. Environ. Sci. Technol. 2010 , 44 , 1327–1332. [ Google Scholar ] [ CrossRef ] [ PubMed ]
  • Asem-Hiablie, S.; Battagliese, T.; Stackhouse-Lawson, K.R.; Alan Rotz, C. A life cycle assessment of the environmental impacts of a beef system in the USA. Int. J. Life Cycle Assess. 2019 , 24 , 441–455. [ Google Scholar ] [ CrossRef ]
  • Tsakiridis, A.; O’Donoghue, C.; Hynes, S.; Kilcline, K. A comparison of environmental and economic sustainability across seafood and livestock product value chains. Mar. Policy 2020 , 117 , 103968. [ Google Scholar ] [ CrossRef ]
  • Gerbens-Leenes, P.W.; Mekonnen, M.M.; Hoekstra, A.Y. The water footprint of poultry, pork and beef: A comparative study in different countries and production systems. Water Resour. Ind. 2013 , 1 , 25–36. [ Google Scholar ] [ CrossRef ]
  • Bottani, E.; Vignali, G.; Mosna, D.; Montanari, R. Economic and environmental assessment of different reverse logistics scenarios for food waste recovery. Sustain. Prod. Consum. 2019 , 20 , 289–303. [ Google Scholar ] [ CrossRef ]
  • Omolayo, Y.; Feingold, B.J.; Neff, R.A.; Romeiko, X.X. Life cycle assessment of food loss and waste in the food supply chain. Resour. Conserv. Recycl. 2021 , 164 , 105119. [ Google Scholar ] [ CrossRef ]
  • Lipińska, M.; Tomaszewska, M.; Kołożyn-Krajewska, D. Identifying factors associated with food losses during transportation: Potentials for social purposes. Sustainability 2019 , 11 , 2046. [ Google Scholar ] [ CrossRef ]
  • León-Bravo, V.; Caniato, F.; Caridi, M.; Johnsen, T. Collaboration for sustainability in the food supply chain: A multi-stage study in Italy. Sustainability 2017 , 9 , 1253. [ Google Scholar ] [ CrossRef ]
  • Accorsi, R.; Baruffaldi, G.; Manzini, R. A closed-loop packaging network design model to foster infinitely reusable and recyclable containers in food industry. Sustain. Prod. Consum. 2020 , 24 , 48–61. [ Google Scholar ] [ CrossRef ]
  • Tonn, B.; Frymier, P.D.; Stiefel, D.; Skinner, L.S.; Suraweera, N.; Tuck, R. Toward an infinitely reusable, recyclable, and renewable industrial ecosystem. J. Clean. Prod. 2014 , 66 , 392–406. [ Google Scholar ] [ CrossRef ]
  • Pålsson, H.; Hellström, D. Packaging logistics in supply chain practice–current state, trade-offs and improvement potential. Int. J. Logist. Res. Appl. 2016 , 19 , 351–368. [ Google Scholar ] [ CrossRef ]
  • Mahmoudi, M.; Parviziomran, I. Reusable packaging in supply chains: A review of environmental and economic impacts, logistics system designs, and operations management. Int. J. Prod. Econ. 2020 , 228 , 107730. [ Google Scholar ] [ CrossRef ]
  • Wikström, F.; Verghese, K.; Auras, R.; Olsson, A.; Williams, H.; Wever, R.; Grönman, K.; Kvalvåg Pettersen, M.; Møller, H.; Soukka, R. Packaging strategies that save food: A research agenda for 2030. J. Ind. Ecol. 2019 , 23 , 532–540. [ Google Scholar ] [ CrossRef ]
  • Goossens, Y.; Berrens, P.; Custers, K.; Van Hemelryck, S.; Kellens, K.; Geeraerd, A. How origin, packaging and seasonality determine the environmental impact of apples, magnified by food waste and losses. Int. J. Life Cycle Assess. 2019 , 24 , 667–687. [ Google Scholar ] [ CrossRef ]
  • McMillin, K.W. Advancements in meat packaging. Meat Sci. 2017 , 132 , 153–162. [ Google Scholar ] [ CrossRef ] [ PubMed ]
  • Domínguez, R.; Barba, F.J.; Gómez, B.; Putnik, P.; Kovačević, D.B.; Pateiro, M.; Santos, E.M.; Lorenzo, J.M. Active packaging films with natural antioxidants to be used in meat industry: A review. Food Res. Int. 2018 , 113 , 93–101. [ Google Scholar ] [ CrossRef ] [ PubMed ]
  • Fang, Z.; Zhao, Y.; Warner, R.D.; Johnson, S.K. Active and intelligent packaging in meat industry. Trends Food Sci. Technol. 2017 , 61 , 60–71. [ Google Scholar ] [ CrossRef ]
  • Chowdhury, E.; Morey, A. Intelligent packaging for poultry industry. J. Appl. Poult. Res. 2019 , 28 , 791–800. [ Google Scholar ] [ CrossRef ]
  • Realini, C.E.; Marcos, B. Active and intelligent packaging systems for a modern society. Meat Sci. 2014 , 98 , 404–419. [ Google Scholar ] [ CrossRef ]
  • Moustafa, H.; Youssef, A.M.; Darwish, N.A.; Abou-Kandil, A.I. Eco-friendly polymer composites for green packaging: Future vision and challenges. Compos. Part B Eng. 2019 , 172 , 16–25. [ Google Scholar ] [ CrossRef ]
  • Ocampo, L.A.; Villegas, Z.V.A.; Carvajal, J.-a.T.; Apas, C.-A.A. Identifying significant drivers for sustainable practices in achieving sustainable food supply chain using modified fuzzy decision-making trial and evaluation laboratory approach. Int. J. Adv. Oper. Manag. 2018 , 10 , 51–89. [ Google Scholar ]
  • Irani, Z.; Sharif, A.M. Sustainable food security futures: Perspectives on food waste and information across the food supply chain. J. Enterp. Inf. Manag. 2016 , 29 , 171–178. [ Google Scholar ] [ CrossRef ]
  • Jeswani, H.K.; Figueroa-Torres, G.; Azapagic, A. The extent of food waste generation in the UK and its environmental impacts. Sustain. Prod. Consum. 2021 , 26 , 532–547. [ Google Scholar ] [ CrossRef ]
  • Shafiee-Jood, M.; Cai, X. Reducing food loss and waste to enhance food security and environmental sustainability. Environ. Sci. Technol. 2016 , 50 , 8432–8443. [ Google Scholar ] [ CrossRef ] [ PubMed ]
  • Kamble, S.S.; Gunasekaran, A.; Parekh, H.; Joshi, S. Modeling the internet of things adoption barriers in food retail supply chains. J. Retail. Consum. Serv. 2019 , 48 , 154–168. [ Google Scholar ] [ CrossRef ]
  • Rejeb, A. Halal meat supply chain traceability based on HACCP, blockchain and internet of things. Acta Tech. Jaurinensis 2018 , 11 , 218–247. [ Google Scholar ] [ CrossRef ]
  • Harvey, J.; Smith, A.; Goulding, J.; Illodo, I.B. Food sharing, redistribution, and waste reduction via mobile applications: A social network analysis. Ind. Mark. Manag. 2020 , 88 , 437–448. [ Google Scholar ] [ CrossRef ]
  • Mishra, N.; Singh, A. Use of twitter data for waste minimisation in beef supply chain. Ann. Oper. Res. 2018 , 270 , 337–359. [ Google Scholar ] [ CrossRef ]
  • Biuki, M.; Kazemi, A.; Alinezhad, A. An integrated location-routing-inventory model for sustainable design of a perishable products supply chain network. J. Clean. Prod. 2020 , 260 , 120842. [ Google Scholar ] [ CrossRef ]
  • Alkaabneh, F.; Diabat, A.; Gao, H.O. Benders decomposition for the inventory vehicle routing problem with perishable products and environmental costs. Comput. Oper. Res. 2020 , 113 , 104751. [ Google Scholar ] [ CrossRef ]
  • Elhedhli, S.; Merrick, R. Green supply chain network design to reduce carbon emissions. Transp. Res. Part D Transp. Environ. 2012 , 17 , 370–379. [ Google Scholar ] [ CrossRef ]
  • Daskin, M.S.; Coullard, C.R.; Shen, Z.-J.M. An inventory-location model: Formulation, solution algorithm and computational results. Ann. Oper. Res. 2002 , 110 , 83–106. [ Google Scholar ] [ CrossRef ]
  • Liu, A.; Zhu, Q.; Xu, L.; Lu, Q.; Fan, Y. Sustainable supply chain management for perishable products in emerging markets: An integrated location-inventory-routing model. Transp. Res. Part E Logist. Transp. Rev. 2021 , 150 , 102319. [ Google Scholar ] [ CrossRef ]
  • Diabat, A.; Dehghani, E.; Jabbarzadeh, A. Incorporating location and inventory decisions into a supply chain design problem with uncertain demands and lead times. J. Manuf. Syst. 2017 , 43 , 139–149. [ Google Scholar ] [ CrossRef ]
  • Bravo, J.J.; Vidal, C.J. Freight transportation function in supply chain optimization models: A critical review of recent trends. Expert Syst. Appl. 2013 , 40 , 6742–6757. [ Google Scholar ] [ CrossRef ]
  • Javid, A.A.; Azad, N. Incorporating location, routing and inventory decisions in supply chain network design. Transp. Res. Part E Logist. Transp. Rev. 2010 , 46 , 582–597. [ Google Scholar ] [ CrossRef ]
  • Benders, J.F. Partitioning procedures for solving mixed-variables programming problems. Comput. Manag. Sci. 2005 , 2 , 3–19. [ Google Scholar ] [ CrossRef ]
  • Savelsbergh, M. A branch-and-price algorithm for the generalized assignment problem. Oper. Res. 1997 , 45 , 831–841. [ Google Scholar ] [ CrossRef ]
  • Talkhestani, H.R.A.; Jahromi, M.H.M.A.; Keshavarzfard, R. A Location-Inventory Model for Multi-Product Supply Chain with Perishable Products and Price-Dependent Demand. Adv. Ind. Eng. 2023 , 56 , 1–12. [ Google Scholar ]
  • Mohammadi, Z.; Barzinpour, F.; Teimoury, E. A location-inventory model for the sustainable supply chain of perishable products based on pricing and replenishment decisions: A case study. PLoS ONE 2023 , 18 , e0288915. [ Google Scholar ] [ CrossRef ] [ PubMed ]
  • Tarantilis, C.; Kiranoudis, C. Distribution of fresh meat. J. Food Eng. 2002 , 51 , 85–91. [ Google Scholar ] [ CrossRef ]
  • Zhang, G.; Habenicht, W.; Spieß, W.E.L. Improving the structure of deep frozen and chilled food chain with tabu search procedure. J. Food Eng. 2003 , 60 , 67–79. [ Google Scholar ] [ CrossRef ]
  • Wang, Y.; Yu, L.y. (Eds.) Optimization model of refrigerated food transportation. In Proceedings of the ICSSSM12, Shanghai, China, 2–4 July 2012; IEEE: New York, NY, USA, 2012; pp. 220–224. [ Google Scholar ]
  • Neves-Moreira, F.; Almada-Lobo, B.; Cordeau, J.-F.; Guimarães, L.; Jans, R. Solving a large multi-product production-routing problem with delivery time windows. Omega 2019 , 86 , 154–172. [ Google Scholar ] [ CrossRef ]
  • Govindan, K.; Jafarian, A.; Khodaverdi, R.; Devika, K. Two-echelon multiple-vehicle location–routing problem with time windows for optimization of sustainable supply chain network of perishable food. Int. J. Prod. Econ. 2014 , 152 , 9–28. [ Google Scholar ] [ CrossRef ]
  • Mohammed, A.; Wang, Q. Developing a meat supply chain network design using a multi-objective possibilistic programming approach. Br. Food J. 2017 , 119 , 690–706. [ Google Scholar ] [ CrossRef ]
  • Moreno, S.; Pereira, J.; Yushimito, W. A hybrid K-means and integer programming method for commercial territory design: A case study in meat distribution. Ann. Oper. Res. 2020 , 286 , 87–117. [ Google Scholar ] [ CrossRef ]
  • Rahbari, M.; Hajiagha, S.H.R.; Dehaghi, M.R.; Moallem, M.; Dorcheh, F.R. Modeling and solving a five-echelon location–inventory–routing problem for red meat supply chain: Case study in Iran. Kybernetes 2020 , 50 , 66–99. [ Google Scholar ] [ CrossRef ]
  • Qu, S.; Zhou, Y.; Ji, Y.; Dai, Z.; Wang, Z. Robust maximum expert consensus modeling with dynamic feedback mechanism under uncertain environments. J. Ind. Manag. Optim. 2024 . [ Google Scholar ] [ CrossRef ]
  • Soysal, M.; Bloemhof-Ruwaard, J.M.; Van Der Vorst, J.G. Modelling food logistics networks with emission considerations: The case of an international beef supply chain. Int. J. Prod. Econ. 2014 , 152 , 57–70. [ Google Scholar ] [ CrossRef ]
  • Mohebalizadehgashti, F.; Zolfagharinia, H.; Amin, S.H. Designing a green meat supply chain network: A multi-objective approach. Int. J. Prod. Econ. 2020 , 219 , 312–327. [ Google Scholar ] [ CrossRef ]
  • Aung, M.M.; Chang, Y.S. Traceability in a food supply chain: Safety and quality perspectives. Food Control 2014 , 39 , 172–184. [ Google Scholar ] [ CrossRef ]
  • Ketzenberg, M.; Bloemhof, J.; Gaukler, G. Managing perishables with time and temperature history. Prod. Oper. Manag. 2015 , 24 , 54–70. [ Google Scholar ] [ CrossRef ]
  • Bottani, E.; Casella, G.; Nobili, M.; Tebaldi, L. An analytic model for estimating the economic and environmental impact of food cold supply chain. Sustainability 2022 , 14 , 4771. [ Google Scholar ] [ CrossRef ]
  • Vrat, P.; Gupta, R.; Bhatnagar, A.; Pathak, D.K.; Fulzele, V. Literature review analytics (LRA) on sustainable cold-chain for perishable food products: Research trends and future directions. Opsearch 2018 , 55 , 601–627. [ Google Scholar ] [ CrossRef ]
  • De Keizer, M.; Haijema, R.; Bloemhof, J.M.; Van Der Vorst, J.G. Hybrid optimization and simulation to design a logistics network for distributing perishable products. Comput. Ind. Eng. 2015 , 88 , 26–38. [ Google Scholar ] [ CrossRef ]
  • Coelho, L.C.; Laporte, G. Optimal joint replenishment, delivery and inventory management policies for perishable products. Comput. Oper. Res. 2014 , 47 , 42–52. [ Google Scholar ] [ CrossRef ]
  • Hasani, A.; Zegordi, S.H.; Nikbakhsh, E. Robust closed-loop supply chain network design for perishable goods in agile manufacturing under uncertainty. Int. J. Prod. Res. 2012 , 50 , 4649–4669. [ Google Scholar ] [ CrossRef ]
  • Song, B.D.; Ko, Y.D. A vehicle routing problem of both refrigerated-and general-type vehicles for perishable food products delivery. J. Food Eng. 2016 , 169 , 61–71. [ Google Scholar ] [ CrossRef ]
  • de Keizer, M.; Akkerman, R.; Grunow, M.; Bloemhof, J.M.; Haijema, R.; van der Vorst, J.G. Logistics network design for perishable products with heterogeneous quality decay. Eur. J. Oper. Res. 2017 , 262 , 535–549. [ Google Scholar ] [ CrossRef ]
  • Mohammed, A.; Govindan, K.; Zubairu, N.; Pratabaraj, J.; Abideen, A.Z. Multi-tier supply chain network design: A key towards sustainability and resilience. Comput. Ind. Eng. 2023 , 182 , 109396. [ Google Scholar ] [ CrossRef ]
  • Tavakkoli Moghaddam, S.; Javadi, M.; Hadji Molana, S.M. A reverse logistics chain mathematical model for a sustainable production system of perishable goods based on demand optimization. J. Ind. Eng. Int. 2019 , 15 , 709–721. [ Google Scholar ] [ CrossRef ]
  • Mohammed, A.; Wang, Q.; Li, X. A cost-effective decision-making algorithm for an RFID-enabled HMSC network design: A multi-objective approach. Ind. Manag. Data Syst. 2017 , 117 , 1782–1799. [ Google Scholar ] [ CrossRef ]
  • Alfian, G.; Syafrudin, M.; Farooq, U.; Ma’arif, M.R.; Syaekhoni, M.A.; Fitriyani, N.L.; Lee, J.; Rhee, J. Improving efficiency of RFID-based traceability system for perishable food by utilizing IoT sensors and machine learning model. Food Control 2020 , 110 , 107016. [ Google Scholar ] [ CrossRef ]
  • Verghese, K.; Lewis, H.; Lockrey, S.; Williams, H. The Role of Packaging in Minimising Food Waste in the Supply Chain of the Future: Prepared for: CHEP Australia ; RMIT University Report: Melbourne, VIC, Australia, 2013. [ Google Scholar ]
  • Singh, A.; Kumari, S.; Malekpoor, H.; Mishra, N. Big data cloud computing framework for low carbon supplier selection in the beef supply chain. J. Clean. Prod. 2018 , 202 , 139–149. [ Google Scholar ] [ CrossRef ]
  • Thakur, M.; Forås, E. EPCIS based online temperature monitoring and traceability in a cold meat chain. Comput. Electron. Agric. 2015 , 117 , 22–30. [ Google Scholar ] [ CrossRef ]
  • Kittipanya-Ngam, P.; Tan, K.H. A framework for food supply chain digitalization: Lessons from Thailand. Prod. Plan. Control 2020 , 31 , 158–172. [ Google Scholar ] [ CrossRef ]
  • Luo, H.; Zhu, M.; Ye, S.; Hou, H.; Chen, Y.; Bulysheva, L. An intelligent tracking system based on internet of things for the cold chain. Internet Res. 2016 , 26 , 435–445. [ Google Scholar ] [ CrossRef ]
  • Rodrigues, V.S.; Demir, E.; Wang, X.; Sarkis, J. Measurement, mitigation and prevention of food waste in supply chains: An online shopping perspective. Ind. Mark. Manag. 2021 , 93 , 545–562. [ Google Scholar ] [ CrossRef ]
  • Fung, F.; Wang, H.-S.; Menon, S. Food safety in the 21st century. Biomed. J. 2018 , 41 , 88–95. [ Google Scholar ] [ CrossRef ]
  • Siems, E.; Land, A.; Seuring, S. Dynamic capabilities in sustainable supply chain management: An inter-temporal comparison of the food and automotive industries. Int. J. Prod. Econ. 2021 , 236 , 108128. [ Google Scholar ] [ CrossRef ]
  • Gholami-Zanjani, S.M.; Klibi, W.; Jabalameli, M.S.; Pishvaee, M.S. The design of resilient food supply chain networks prone to epidemic disruptions. Int. J. Prod. Econ. 2021 , 233 , 108001. [ Google Scholar ] [ CrossRef ]
  • Wang, J.; Yue, H. Food safety pre-warning system based on data mining for a sustainable food supply chain. Food Control 2017 , 73 , 223–229. [ Google Scholar ] [ CrossRef ]
  • Esmaeilian, B.; Sarkis, J.; Lewis, K.; Behdad, S. Blockchain for the future of sustainable supply chain management in Industry 4.0. Resour. Conserv. Recycl. 2020 , 163 , 105064. [ Google Scholar ] [ CrossRef ]
  • McKinna, D.; Wall, C. Commercial Application of Supply Chain Integrity and Shelf Life Systems ; Technical Report; Meat and Livestock Australia Limited: Sydney, NSW, Australia, 2020. [ Google Scholar ]
  • Jia, L.; Evans, S. Improving food allergen management in food manufacturing: An incentive-based approach. Food Control 2021 , 129 , 108246. [ Google Scholar ] [ CrossRef ]
  • Nyarugwe, S.P.; Linnemann, A.R.; Luning, P.A. Prevailing food safety culture in companies operating in a transition economy-Does product riskiness matter? Food Control 2020 , 107 , 106803. [ Google Scholar ] [ CrossRef ]
  • Sestino, A.; Prete, M.I.; Piper, L.; Guido, G. Internet of Things and Big Data as enablers for business digitalization strategies. Technovation 2020 , 98 , 102173. [ Google Scholar ] [ CrossRef ]
  • Astill, J.; Dara, R.A.; Campbell, M.; Farber, J.M.; Fraser, E.D.; Sharif, S.; Yada, R.Y. Transparency in food supply chains: A review of enabling technology solutions. Trends Food Sci. Technol. 2019 , 91 , 240–247. [ Google Scholar ] [ CrossRef ]
  • Singh, M.; Corradini, M.G. Big data and its role in mitigating food spoilage and quality deterioration along the supply chain. In Harnessing Big Data in Food Safety ; Springer: Berlin/Heidelberg, Germany, 2022; pp. 93–112. [ Google Scholar ]
  • Tiwari, S.; Wee, H.-M.; Daryanto, Y. Big data analytics in supply chain management between 2010 and 2016: Insights to industries. Comput. Ind. Eng. 2018 , 115 , 319–330. [ Google Scholar ] [ CrossRef ]
  • Wang, G.; Gunasekaran, A.; Ngai, E.W.; Papadopoulos, T. Big data analytics in logistics and supply chain management: Certain investigations for research and applications. Int. J. Prod. Econ. 2016 , 176 , 98–110. [ Google Scholar ] [ CrossRef ]
  • Addo-Tenkorang, R.; Helo, P.T. Big data applications in operations/supply-chain management: A literature review. Comput. Ind. Eng. 2016 , 101 , 528–543. [ Google Scholar ] [ CrossRef ]
  • Feng, H.; Wang, X.; Duan, Y.; Zhang, J.; Zhang, X. Applying blockchain technology to improve agri-food traceability: A review of development methods, benefits and challenges. J. Clean. Prod. 2020 , 260 , 121031. [ Google Scholar ] [ CrossRef ]
  • Sanka, A.I.; Irfan, M.; Huang, I.; Cheung, R.C. A survey of breakthrough in blockchain technology: Adoptions, applications, challenges and future research. Comput. Commun. 2021 , 169 , 179–201. [ Google Scholar ] [ CrossRef ]
  • Azzi, R.; Chamoun, R.K.; Sokhn, M. The power of a blockchain-based supply chain. Comput. Ind. Eng. 2019 , 135 , 582–592. [ Google Scholar ] [ CrossRef ]
  • Powell, W.; Foth, M.; Cao, S.; Natanelov, V. Garbage in garbage out: The precarious link between IoT and blockchain in food supply chains. J. Ind. Inf. Integr. 2022 , 25 , 100261. [ Google Scholar ] [ CrossRef ]
  • Verboven, P.; Defraeye, T.; Datta, A.K.; Nicolai, B. Digital twins of food process operations: The next step for food process models? Curr. Opin. Food Sci. 2020 , 35 , 79–87. [ Google Scholar ] [ CrossRef ]
  • Kuffi, K.D.; Defraeye, T.; Nicolai, B.M.; De Smet, S.; Geeraerd, A.; Verboven, P. CFD modeling of industrial cooling of large beef carcasses. Int. J. Refrig. 2016 , 69 , 324–339. [ Google Scholar ] [ CrossRef ]
  • Wu, W.; Beretta, C.; Cronje, P.; Hellweg, S.; Defraeye, T. Environmental trade-offs in fresh-fruit cold chains by combining virtual cold chains with life cycle assessment. Appl. Energy 2019 , 254 , 113586. [ Google Scholar ] [ CrossRef ]
  • Agalianos, K.; Ponis, S.; Aretoulaki, E.; Plakas, G.; Efthymiou, O. Discrete event simulation and digital twins: Review and challenges for logistics. Procedia Manuf. 2020 , 51 , 1636–1641. [ Google Scholar ] [ CrossRef ]
  • Wang, Y.; Ma, X.; Liu, M.; Gong, K.; Liu, Y.; Xu, M.; Wang, Y. Cooperation and profit allocation in two-echelon logistics joint distribution network optimization. Appl. Soft Comput. 2017 , 56 , 143–157. [ Google Scholar ] [ CrossRef ]
  • Zhu, Z.; Bai, Y.; Dai, W.; Liu, D.; Hu, Y. Quality of e-commerce agricultural products and the safety of the ecological environment of the origin based on 5G Internet of Things technology. Environ. Technol. Innov. 2021 , 22 , 101462. [ Google Scholar ] [ CrossRef ]
  • Osman, S.A.; Xu, C.; Akuful, M.; Paul, E.R. Perishable Food Supply Chain Management: Challenges and the Way Forward. Open J. Soc. Sci. 2023 , 11 , 349–364. [ Google Scholar ] [ CrossRef ]
  • Verhoef, P.C.; Lemon, K.N. Successful customer value management: Key lessons and emerging trends. Eur. Manag. J. 2013 , 31 , 1–15. [ Google Scholar ] [ CrossRef ]
  • Tseng, M.-L. Modeling sustainable production indicators with linguistic preferences. J. Clean. Prod. 2013 , 40 , 46–56. [ Google Scholar ] [ CrossRef ]
  • Derqui, B.; Fayos, T.; Fernandez, V. Towards a more sustainable food supply chain: Opening up invisible waste in food service. Sustainability 2016 , 8 , 693. [ Google Scholar ] [ CrossRef ]
  • Heising, J.K.; Claassen, G.; Dekker, M. Options for reducing food waste by quality-controlled logistics using intelligent packaging along the supply chain. Food Addit. Contam. Part A 2017 , 34 , 1672–1680. [ Google Scholar ] [ CrossRef ] [ PubMed ]
  • Ravindran, R.; Jaiswal, A.K. Exploitation of food industry waste for high-value products. Trends Biotechnol. 2016 , 34 , 58–69. [ Google Scholar ] [ CrossRef ]
  • Lin, C.S.K.; Pfaltzgraff, L.A.; Herrero-Davila, L.; Mubofu, E.B.; Abderrahim, S.; Clark, J.H.; Koutinas, A.A.; Kopsahelis, N.; Stamatelatou, K.; Dickson, F. Food waste as a valuable resource for the production of chemicals, materials and fuels. Current situation and global perspective. Energy Environ. Sci. 2013 , 6 , 426–464. [ Google Scholar ] [ CrossRef ]
  • Krishnan, R.; Arshinder, K.; Agarwal, R. Robust optimization of sustainable food supply chain network considering food waste valorization and supply uncertainty. Comput. Ind. Eng. 2022 , 171 , 108499. [ Google Scholar ] [ CrossRef ]
  • Cristóbal, J.; Castellani, V.; Manfredi, S.; Sala, S. Prioritizing and optimizing sustainable measures for food waste prevention and management. Waste Manag. 2018 , 72 , 3–16. [ Google Scholar ] [ CrossRef ]
  • Karwowska, M.; Łaba, S.; Szczepański, K. Food loss and waste in meat sector—Why the consumption stage generates the most losses? Sustainability 2021 , 13 , 6227. [ Google Scholar ] [ CrossRef ]
  • Dani, S.; Deep, A. Fragile food supply chains: Reacting to risks. Int. J. Logist. Res. Appl. 2010 , 13 , 395–410. [ Google Scholar ] [ CrossRef ]
  • Corrêa, H.L.; Xavier, L.H. Concepts, design and implementation of Reverse Logistics Systems for sustainable supply chains in Brazil. J. Oper. Supply Chain Manag. 2013 , 6 , 1. [ Google Scholar ] [ CrossRef ]
  • Pagell, M.; Shevchenko, A. Why research in sustainable supply chain management should have no future. J. Supply Chain Manag. 2014 , 50 , 44–55. [ Google Scholar ] [ CrossRef ]
  • Difrancesco, R.M.; Huchzermeier, A. Closed-loop supply chains: A guide to theory and practice. Int. J. Logist. Res. Appl. 2016 , 19 , 443–464. [ Google Scholar ] [ CrossRef ]
  • Battini, D.; Bogataj, M.; Choudhary, A. Closed Loop Supply Chain (CLSC): Economics, Modelling, Management and Control ; Elsevier: Amsterdam, The Netherlands, 2017; Volume 183, pp. 319–321. [ Google Scholar ]
  • Meneghetti, A.; Monti, L. Greening the food supply chain: An optimisation model for sustainable design of refrigerated automated warehouses. Int. J. Prod. Res. 2015 , 53 , 6567–6587. [ Google Scholar ] [ CrossRef ]
  • Adekomaya, O.; Jamiru, T.; Sadiku, R.; Huan, Z. Sustaining the shelf life of fresh food in cold chain–A burden on the environment. Alex. Eng. J. 2016 , 55 , 1359–1365. [ Google Scholar ] [ CrossRef ]
  • Benn, S.; Edwards, M.; Williams, T. Organizational Change for Corporate Sustainability ; Routledge: London, UK, 2014. [ Google Scholar ]
  • Chopra, S.; Meindl, P. Supply Chain Management. Strategy, Planning & Operation ; Springer: Berlin/Heidelberg, Germany, 2007. [ Google Scholar ]
  • Li, Q.; Liu, A. Big data driven supply chain management. Procedia CIRP 2019 , 81 , 1089–1094. [ Google Scholar ] [ CrossRef ]
  • Nagy, G.; Salhi, S. Location-routing: Issues, models and methods. Eur. J. Oper. Res. 2007 , 177 , 649–672. [ Google Scholar ] [ CrossRef ]
  • Kamariotou, M.; Kitsios, F.; Charatsari, C.; Lioutas, E.D.; Talias, M.A. Digital strategy decision support systems: Agrifood supply chain management in smes. Sensors 2021 , 22 , 274. [ Google Scholar ] [ CrossRef ] [ PubMed ]
  • Trstenjak, M.; Opetuk, T.; Đukić, G.; Cajner, H. Logistics 5.0 Implementation Model Based on Decision Support Systems. Sustainability 2022 , 14 , 6514. [ Google Scholar ] [ CrossRef ]
  • Cai, L.; Li, W.; Luo, Y.; He, L. Real-time scheduling simulation optimisation of job shop in a production-logistics collaborative environment. Int. J. Prod. Res. 2022 , 61 , 1373–1393. [ Google Scholar ] [ CrossRef ]
  • Stijn, E.v.; Phuaphanthong, T.; Keretho, S.; Pikart, M.; Hofman, W.; Tan, Y.-H. Implementation Framework for e-solutions for Trade Facilitation. In Accelerating Global Supply Chains with IT-Innovation ; Springer: Berlin/Heidelberg, Germany, 2011; pp. 285–317. [ Google Scholar ]
  • Yavas, V.; Ozkan-Ozen, Y.D. Logistics centers in the new industrial era: A proposed framework for logistics center 4.0. Transp. Res. Part E Logist. Transp. Rev. 2020 , 135 , 101864. [ Google Scholar ] [ CrossRef ]
  • Zokaei, A.K.; Simons, D.W. Value chain analysis in consumer focus improvement: A case study of the UK red meat industry. Int. J. Logist. Manag. 2006 , 17 , 141–162. [ Google Scholar ] [ CrossRef ]
  • Cox, A.; Chicksand, D.; Yang, T. The proactive alignment of sourcing with marketing and branding strategies: A food service case. Supply Chain Manag. Int. J. 2007 , 12 , 321–333. [ Google Scholar ] [ CrossRef ]
  • Jie, F.; Gengatharen, D. Australian food retail supply chain analysis. Bus. Process Manag. J. 2019 , 25 , 271–287. [ Google Scholar ] [ CrossRef ]
  • Knoll, S.; Marques, C.S.S.; Liu, J.; Zhong, F.; Padula, A.D.; Barcellos, J.O.J. The Sino-Brazilian beef supply chain: Mapping and risk detection. Br. Food J. 2017 , 119 , 164–180. [ Google Scholar ] [ CrossRef ]
  • Schilling-Vacaflor, A. Integrating human rights and the environment in supply chain regulations. Sustainability 2021 , 13 , 9666. [ Google Scholar ] [ CrossRef ]
  • Knoll, S.; Padula, A.D.; dos Santos, M.C.; Pumi, G.; Zhou, S.; Zhong, F.; Barcellos, J.O.J. Information flow in the Sino-Brazilian beef trade. Int. Food Agribus. Manag. Rev. 2018 , 21 , 17–38. [ Google Scholar ] [ CrossRef ]
  • E-Fatima, K.; Khandan, R.; Hosseinian-Far, A.; Sarwar, D.; Ahmed, H.F. Adoption and Influence of Robotic Process Automation in Beef Supply Chains. Logistics 2022 , 6 , 48. [ Google Scholar ] [ CrossRef ]
  • Storer, M.; Hyland, P.; Ferrer, M.; Santa, R.; Griffiths, A. Strategic supply chain management factors influencing agribusiness innovation utilization. Int. J. Logist. Manag. 2014 , 25 , 487–521. [ Google Scholar ] [ CrossRef ]
  • Mangla, S.K.; Börühan, G.; Ersoy, P.; Kazancoglu, Y.; Song, M. Impact of information hiding on circular food supply chains in business-to-business context. J. Bus. Res. 2021 , 135 , 1–18. [ Google Scholar ] [ CrossRef ]
  • Faisal, M.N. A study of inhibitors to transparency in red meat supply chains in Gulf cooperation council (GCC) countries. Bus. Process Manag. J. 2015 , 21 , 1299–1318. [ Google Scholar ] [ CrossRef ]
  • Shanoyan, A.; Schiavi Bankuti, S.M.; Colares-Santos, L. Analysis of incentive structures at producer–processor interface of beef supply chain in Brazil. J. Agribus. Dev. Emerg. Econ. 2019 , 9 , 159–174. [ Google Scholar ] [ CrossRef ]
  • Nakandala, D.; Lau, H.; Zhang, J. Cost-optimization modelling for fresh food quality and transportation. Ind. Manag. Data Syst. 2016 , 116 , 564–583. [ Google Scholar ] [ CrossRef ]
  • Ge, H.; Gómez, M.; Peters, C. Modeling and optimizing the beef supply chain in the Northeastern US. Agric. Econ. 2022 , 53 , 702–718. [ Google Scholar ] [ CrossRef ]
  • Hsiao, Y.-H.; Chen, M.-C.; Chin, C.-L. Distribution planning for perishable foods in cold chains with quality concerns: Formulation and solution procedure. Trends Food Sci. Technol. 2017 , 61 , 80–93. [ Google Scholar ] [ CrossRef ]
  • Meksavang, P.; Shi, H.; Lin, S.-M.; Liu, H.-C. An extended picture fuzzy VIKOR approach for sustainable supplier management and its application in the beef industry. Symmetry 2019 , 11 , 468. [ Google Scholar ] [ CrossRef ]
  • Taylor, D.H. Strategic considerations in the development of lean agri-food supply chains: A case study of the UK pork sector. Supply Chain Manag. Int. J. 2006 , 11 , 271–280. [ Google Scholar ] [ CrossRef ]
  • Erol, E.; Saghaian, S.H. The COVID-19 pandemic and dynamics of price adjustment in the US beef sector. Sustainability 2022 , 14 , 4391. [ Google Scholar ] [ CrossRef ]
  • Galuchi, T.P.D.; Rosales, F.P.; Batalha, M.O. Management of socioenvironmental factors of reputational risk in the beef supply chain in the Brazilian Amazon region. Int. Food Agribus. Manag. Rev. 2019 , 22 , 155–171. [ Google Scholar ] [ CrossRef ]
  • Silvestre, B.S.; Monteiro, M.S.; Viana, F.L.E.; de Sousa-Filho, J.M. Challenges for sustainable supply chain management: When stakeholder collaboration becomes conducive to corruption. J. Clean. Prod. 2018 , 194 , 766–776. [ Google Scholar ] [ CrossRef ]
  • Eriksson, M.; Strid, I.; Hansson, P.-A. Waste of organic and conventional meat and dairy products—A case study from Swedish retail. Resour. Conserv. Recycl. 2014 , 83 , 44–52. [ Google Scholar ] [ CrossRef ]
  • Accorsi, R.; Bortolini, M.; Gallo, A. Modeling by-products and waste management in the meat industry. In Sustainable Food Supply Chains ; Elsevier: Amsterdam, The Netherlands, 2019; pp. 339–349. [ Google Scholar ]
  • Ersoy, P.; Börühan, G.; Kumar Mangla, S.; Hormazabal, J.H.; Kazancoglu, Y.; Lafcı, Ç. Impact of information technology and knowledge sharing on circular food supply chains for green business growth. Bus. Strategy Environ. 2022 , 31 , 1875–1904. [ Google Scholar ] [ CrossRef ]
  • Mahbubi, A.; Uchiyama, T. Assessing the sustainability of the Indonesian halal beef supply chain. Int. J. Food Syst. Dyn. 2020 , 11 , 468–481. [ Google Scholar ]
  • Bragaglio, A.; Napolitano, F.; Pacelli, C.; Pirlo, G.; Sabia, E.; Serrapica, F.; Serrapica, M.; Braghieri, A. Environmental impacts of Italian beef production: A comparison between different systems. J. Clean. Prod. 2018 , 172 , 4033–4043. [ Google Scholar ] [ CrossRef ]
  • Zeidan, R.; Van Holt, T.; Whelan, T. Existence inductive theory building to study coordination failures in sustainable beef production. J. Clean. Prod. 2020 , 267 , 122137. [ Google Scholar ] [ CrossRef ]
  • Santos, A.B.; Costa, M.H. Do large slaughterhouses promote sustainable intensification of cattle ranching in Amazonia and the Cerrado? Sustainability 2018 , 10 , 3266. [ Google Scholar ] [ CrossRef ]
  • E-Fatima, K.; Khandan, R.; Hosseinian-Far, A.; Sarwar, D. The Adoption of Robotic Process Automation Considering Financial Aspects in Beef Supply Chains: An Approach towards Sustainability. Sustainability 2023 , 15 , 7236. [ Google Scholar ] [ CrossRef ]
  • Huerta, A.R.; Güereca, L.P.; Lozano, M.d.l.S.R. Environmental impact of beef production in Mexico through life cycle assessment. Resour. Conserv. Recycl. 2016 , 109 , 44–53. [ Google Scholar ] [ CrossRef ]
  • Cox, A.; Chicksand, D.; Palmer, M. Stairways to heaven or treadmills to oblivion? Creating sustainable strategies in red meat supply chains. Br. Food J. 2007 , 109 , 689–720. [ Google Scholar ] [ CrossRef ]
  • Teresa, H.; Áine, M.-W.; Olive, M.; Carol, P.; Maeve, H. Co-operation among Irish beef farmers: Current perspectives and future prospects in the context of new producer organisation (PO) legislation. Sustainability 2018 , 10 , 4085. [ Google Scholar ] [ CrossRef ]
  • Kyayesimira, J.; Wangalwa, R.; Kagoro Rugunda, G.; Lejju, J.B.; Matofari, J.W.; Andama, M. Causes of losses and the economic loss estimates at post-harvest handling points along the beef value chain in Uganda. J. Agric. Ext. Rural. Dev. 2019 , 11 , 176–183. [ Google Scholar ]
  • Ranaei, V.; Pilevar, Z.; Esfandiari, C.; Khaneghah, A.M.; Dhakal, R.; Vargas-Bello-Pérez, E.; Hosseini, H. Meat value chain losses in Iran. Food Sci. Anim. Resour. 2021 , 41 , 16–33. [ Google Scholar ] [ CrossRef ] [ PubMed ]
  • Wiedemann, S.; McGahan, E.; Murphy, C.; Yan, M.-J.; Henry, B.; Thoma, G.; Ledgard, S. Environmental impacts and resource use of Australian beef and lamb exported to the USA determined using life cycle assessment. J. Clean. Prod. 2015 , 94 , 67–75. [ Google Scholar ] [ CrossRef ]
  • Martínez, C.I.P.; Poveda, A.C. Characterization of cooling equipment in the food industry: Case study of the Colombian meat, dairy, and fruit and vegetable sectors. Environ. Dev. 2022 , 41 , 100693. [ Google Scholar ] [ CrossRef ]
  • Fattahi, F.; Nookabadi, A.S.; Kadivar, M. A model for measuring the performance of the meat supply chain. Br. Food J. 2013 , 115 , 1090–1111. [ Google Scholar ] [ CrossRef ]
  • Florindo, T.; Florindo, G.d.M.; Talamini, E.; da Costa, J.; de Léis, C.; Tang, W.; Schultz, G.; Kulay, L.; Pinto, A.; Ruviaro, C.F. Application of the multiple criteria decision-making (MCDM) approach in the identification of Carbon Footprint reduction actions in the Brazilian beef production chain. J. Clean. Prod. 2018 , 196 , 1379–1389. [ Google Scholar ] [ CrossRef ]
  • Diaz, F.; Vignati, J.A.; Marchi, B.; Paoli, R.; Zanoni, S.; Romagnoli, F. Effects of energy efficiency measures in the beef cold chain: A life cycle-based study. Environ. Clim. Technol. 2021 , 25 , 343–355. [ Google Scholar ] [ CrossRef ]
  • Schmidt, B.V.; Moreno, M.S. Traceability optimization in the meat supply chain with economic and environmental considerations. Comput. Ind. Eng. 2022 , 169 , 108271. [ Google Scholar ] [ CrossRef ]
  • Domingues Zucchi, J.; Zeng, A.Z.; Caixeta-Filho, J.V. Optimum location for export-oriented slaughterhouses in Mato Grosso, Brazil: A dynamic mathematical model. Int. J. Logist. Res. Appl. 2011 , 14 , 135–148. [ Google Scholar ] [ CrossRef ]
  • Dorcheh, F.R.; Rahbari, M. Greenhouse gas emissions optimization for distribution and vehicle routing problem in a poultry meat supply chain in two phases: A case study in Iran. Process Integr. Optim. Sustain. 2023 , 7 , 1289–1317. [ Google Scholar ] [ CrossRef ]
  • Javanmard, S.; Vahdani, B.; Tavakkoli-Moghaddam, R. Solving a multi-product distribution planning problem in cross docking networks: An imperialist competitive algorithm. Int. J. Adv. Manuf. Technol. 2014 , 70 , 1709–1720. [ Google Scholar ] [ CrossRef ]
  • Dai, Z.; Aqlan, F.; Zheng, X.; Gao, K. A location-inventory supply chain network model using two heuristic algorithms for perishable products with fuzzy constraints. Comput. Ind. Eng. 2018 , 119 , 338–352. [ Google Scholar ] [ CrossRef ]
  • Saragih, N.I.; Bahagia, N.; Syabri, I. A heuristic method for location-inventory-routing problem in a three-echelon supply chain system. Comput. Ind. Eng. 2019 , 127 , 875–886. [ Google Scholar ] [ CrossRef ]
  • Hiassat, A.; Diabat, A.; Rahwan, I. A genetic algorithm approach for location-inventory-routing problem with perishable products. J. Manuf. Syst. 2017 , 42 , 93–103. [ Google Scholar ] [ CrossRef ]
  • Le, T.; Diabat, A.; Richard, J.-P.; Yih, Y. A column generation-based heuristic algorithm for an inventory routing problem with perishable goods. Optim. Lett. 2013 , 7 , 1481–1502. [ Google Scholar ] [ CrossRef ]
  • Wang, X.; Wang, M.; Ruan, J.; Zhan, H. The multi-objective optimization for perishable food distribution route considering temporal-spatial distance. Procedia Comput. Sci. 2016 , 96 , 1211–1220. [ Google Scholar ] [ CrossRef ]
  • Rafie-Majd, Z.; Pasandideh, S.H.R.; Naderi, B. Modelling and solving the integrated inventory-location-routing problem in a multi-period and multi-perishable product supply chain with uncertainty: Lagrangian relaxation algorithm. Comput. Chem. Eng. 2018 , 109 , 9–22. [ Google Scholar ] [ CrossRef ]
  • Singh, A.; Mishra, N.; Ali, S.I.; Shukla, N.; Shankar, R. Cloud computing technology: Reducing carbon footprint in beef supply chain. Int. J. Prod. Econ. 2015 , 164 , 462–471. [ Google Scholar ] [ CrossRef ]
  • Zhang, Y.; Baker, D.; Griffith, G. Product quality information in supply chains: A performance-linked conceptual framework applied to the Australian red meat industry. Int. J. Logist. Manag. 2020 , 31 , 697–723. [ Google Scholar ] [ CrossRef ]
  • Cao, S.; Powell, W.; Foth, M.; Natanelov, V.; Miller, T.; Dulleck, U. Strengthening consumer trust in beef supply chain traceability with a blockchain-based human-machine reconcile mechanism. Comput. Electron. Agric. 2021 , 180 , 105886. [ Google Scholar ] [ CrossRef ]
  • Kassahun, A.; Hartog, R.J.; Tekinerdogan, B. Realizing chain-wide transparency in meat supply chains based on global standards and a reference architecture. Comput. Electron. Agric. 2016 , 123 , 275–291. [ Google Scholar ] [ CrossRef ]
  • Ribeiro, P.C.C.; Scavarda, A.J.; Batalha, M.O. The application of RFID in brazilian harvest facilities: Two case studies. Int. J. Eng. Bus. Manag. 2011 , 3 , 1–63. [ Google Scholar ] [ CrossRef ]
  • Cao, S.; Foth, M.; Powell, W.; Miller, T.; Li, M. A blockchain-based multisignature approach for supply chain governance: A use case from the Australian beef industry. Blockchain Res. Appl. 2022 , 3 , 100091. [ Google Scholar ] [ CrossRef ]
  • Wu, J.-Y.; Hsiao, H.-I. Food quality and safety risk diagnosis in the food cold chain through failure mode and effect analysis. Food Control 2021 , 120 , 107501. [ Google Scholar ] [ CrossRef ]

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Davoudi, S.; Stasinopoulos, P.; Shiwakoti, N. Two Decades of Advancements in Cold Supply Chain Logistics for Reducing Food Waste: A Review with Focus on the Meat Industry. Sustainability 2024 , 16 , 6986. https://doi.org/10.3390/su16166986

Davoudi S, Stasinopoulos P, Shiwakoti N. Two Decades of Advancements in Cold Supply Chain Logistics for Reducing Food Waste: A Review with Focus on the Meat Industry. Sustainability . 2024; 16(16):6986. https://doi.org/10.3390/su16166986

Davoudi, Sina, Peter Stasinopoulos, and Nirajan Shiwakoti. 2024. "Two Decades of Advancements in Cold Supply Chain Logistics for Reducing Food Waste: A Review with Focus on the Meat Industry" Sustainability 16, no. 16: 6986. https://doi.org/10.3390/su16166986

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IMPACT OF TOTAL QUALITY MANAGEMENT, SUPPLY CHAIN RESILIENCE AND ORGANIZATIONAL CULTURE ON SUSTAINABILITY AND OPERATIONAL PERFORMANCE, AN EMPIRICAL STUDY OF PHARMACEUTICAL INDUSTRY IN PAKISTAN

  • Nadeem-ul-Hassan, Dr Atif Hussain, Maria Tahseen Akhtar, Mubeen Shoukat, Naveed Suleman, Muhammad Sajjad, Atif Munir

Background: The pharmaceutical industry's performance in the global economy has been significantly influenced by the increasing competition stemming from globalization, economic liberalization, and the Trade-Related Aspects of Intellectual Property Rights (TRIPS) agreement. To maintain excellence and sustain competitiveness in the global market, organizations need to integrate Total Quality Management (TQM), Supply Chain Resilience (SCR), Organizational Culture (OC), and sustainability practices into their core objectives. This research aims to investigate the impact of TQM, SCR, and OC on the sustainability and operational performance (OP) of the pharmaceutical industry in Pakistan, and to explore their interlinkages. Methodology: A conceptual framework was developed to test hypotheses based on existing literature. A quantitative research approach was adopted, with data collected through a survey of pharmaceutical professionals across Pakistan using convenient sampling, resulting in 203 completed questionnaires. The research model was tested using Partial Least Squares Structural Equation Modelling (PLS-SEM). Finding: The results demonstrate that TQM, SCR, and OC have significant positive impacts on both sustainability practices and operational performance. Additionally, sustainability mediates the relationship between TQM and OP, SCR and OP, and OC and OP. These findings contribute to the literature by showing that implementing TQM, SCR, and OC practices can significantly enhance sustainability and operational performance in the pharmaceutical industry. Conclusion: This study is the first to examine the direct and indirect effects of TQM, SCR, and OC on OP, considering the mediating role of sustainability. The insights from this research can guide policymakers and industry leaders in implementing these practices to achieve a competitive advantage in the pharmaceutical sector.

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