Minimizing losses at red meat supply chain with circular and central slaughterhouse model

Purpose: The purpose of this paper is to find solutions to improve the red meat sector in an emerging economy, Turkey, from the circular economy point of view, and taking sustainability approach. The need for circular management within the red meat sector in Turkey is emphasized by using Grey method. As theoretical contribution of this study, the investigation of the causes of losses at the slaughter stages of the red meat supply chain leads to proposals for sustainable and circular solutions. Design/methodology/approach: Grey method is used to predict the number of slaughtered cattle and the amount of bone and blood waste in the slaughtering process between 2018 and 2020. Findings: It is revealed that according to Grey prediction calculations, although the amount of slaughtered cattle, bone and blood waste seem have decreased between 2018 and 2020, there are still significant losses in Turkish red meat sector. For bone waste, this is expected to be 56,581,200 kg in 2018, 48,235,840 kg in 2019 and 41,121,380 kg in 2020. For blood waste, it is expected to be 24,754,275 kg in 2018, 21,103,180 kg in 2019 and 17,990,604 kg in 2020. Social implications: The proposed model in the study will contribute on sector revitalization, increase in product safety, quality and hygiene, development in the management of training and education centers for farmers/labors and increase in employment. Originality/value: This paper represents policymakers with a proposal for triple bottom line (TBL) based circular and central slaughterhouse model, based on TBL, which brings social, economic and environmental benefits for the red meat sector in Turkey

Analysing the Adoption Barriers of Low-Carbon Operations: A Step Forward for Achieving Net-Zero Emissions

In November 2021, the 26th United Nations Climate Change Conference (COP26) was held in Glasgow, UK, the global leaders from nearly 200 countries stressed taking immediate action on the climate issue and how to ensure global net-zero emissions by 2030. It is possible to accelerate the transition to low-carbon energy systems, the present study seeks to identify and analyse key barriers to Low Carbon Operations (LCO) in emerging economies. A critical literature review was undertaken to recognise the barriers linked to the adoption of LCO. To validate these barriers, an empirical study with a dataset of 127 respondents from the Indian automobile industry was conducted. The validated barriers were analysed using Best Worst Method (BWM) and Decision-Making Trial and Evaluation Laboratory (DEMATEL) techniques. BWM is used to determine the priority ranking of barriers, while the DEMATEL method is employed to elucidate the cause-effect inter-relationships among the listed barriers. The results suggest that ‘Economic’ is the most influential category of barriers followed by ‘Infrastructure’ and ‘Operational’. The results also show that the barriers ‘Economic’, ‘Environmental’, ‘Infrastructure’ and ‘Organizational Governance’ belong to the cause group. Some significant managerial implications are recommended to overcome these barriers and to assist firms in the successful adoption of LCO and achieving net-zero emissions. The work was carried out in the automotive industry in India but provides findings that may have wider applicability in other developing countries and beyond

Analysing Critical Factors of Strategic Alignment Between Operational Excellence and Industry 4.0 Technologies in Smart Manufacturing

The manufacturing sector is highly competitive and operationally complex. Therefore, the strategic alignment between operational excellence methodologies and Industry 4.0 technologies is one of the issues that need to be addressed. The main aim of the study is to determine the critical factors of strategic alignment between operational excellence methodologies and Industry 4.0 technologies for manufacturing industries and make comparative analyses between automotive, food, and textile industries in terms of strategic alignment between operational excellence methodologies and Industry 4.0 technologies. Firstly, determining the critical factors based on literature review and expert opinions, these criteria are weighted, and Analytical Hierarchy Process is run to calculate the weights of these criteria. Afterwards, the best sector is determined by the Gray Relational Analysis method according to the criteria for the three manufacturing industries selected for the study. As a result of AHP, ‘Infrastructure for Right Methodology, Techniques and Tools, is in the first place, ‘Organizational Strategy, is in the second place, while the third highest critical factor is ‘Capital Investment’. Moreover, based on Gray Relational Analysis results, the automotive industry is determined as the best alternative in terms of strategic alignment between OPEX methodologies and I4.0 technologies. This study is unique in that it is primarily possible to obtain the order of importance within the criteria and to make comparisons between three important manufacturing industries that are important for the economies of the world

Integration of lean approach with energy efficiency: Application in kitchenware manufacturing company

Energy efficiency in the industries is one of the leading problems of the 21st century. The main aim for the companies to deal with the energy efficiency paradigm is to save the resources in the manufacturing operations. Manufacturing opera-tions involve activities that creates wastes in any case; therefore, these wastes should be eliminated, or minimized as much as possible. In this paper, it is aimed to integrate the energy efficiency term with lean management principles. The barriers and the drivers of the energy efficiency was discussed, and the 8 wastes within lean perspective were translated into energy counterparts. 8 wastes of lean approach were defined as energy efficiency perspective, and used as criteria. The study will reveal the important criteria using Fuzzy Analytic Network Process (Fuzzy ANP) method to make impli-cations about how to eliminate these wastes

Decision making for risk evaluation: integration of prospect theory with failure modes and effects analysis (FMEA)

The aim of the present study is to overcome some of the limitations of the FMEA method by presenting a theoretical base for considering risk evaluation into its assessment methodology and proposing an approach for its implementation. Fuzzy AHP is used to calculate the weights of the likelihood of occurrence (O), severity (S) and difficulty of detection (D). Additionally, the Prospect Theory-based TODIM method was integrated with fuzzy logic. Thus, fuzzy TODIM was employed to calculate the ranking of potential failure modes according to their RPNs. In order to verify the results of the study, in-depth interviews were conducted with the participation of industry experts. The results are very much in line with Prospect Theory. Therefore, practitioners may apply the proposed method to FMEA. The most crucial failure mode for a firm’s attention is furnace failure followed by generator failure, crane failure, tank failure, kettle failure, dryer failure, and operator failure, respectively. The originality of this paper consists in integrating Prospect Theory with the FMEA method in order to overcome the limitations naturally inherent in the calculation of the FMEA’s Risk Priority Numbers (RPNs).N/

Assessing the Impact of COVID-19 on Sustainable Food Supply Chains

Recently, it has become an important issue to ensure sustainability, especially in food supply chains, against the rapidly growing population, increasing demand, and sudden disruptions caused by uncertain times such as that caused by COVID-19. Since food supply chains has vulnerable products and processes, it is critical to understand the sustainability factors of food supply chains especially in uncertain times such during the COVID-19 pandemic. This study aims to determine sustainability factors of food supply chains. An Interpretive Structural Modelling method is used to state the relations between sustainability factors of food supply chains. As a result of the study, Information Sharing and Managerial Approaches are classified as driving factors; Food Safety and Security, Know-How Transfer, Logistics Networking, Risk Mitigation, Employee Commitment, Innovation, Traceability and Responsiveness are categorized as linkage factors. This article will be beneficial for managers in helping them develop sustainable food supply chains during uncertain times by focusing on traceability, information sharing, know-how transfer, food safety and security

Identifying the drivers of circular food packaging: a comprehensive review for the current state of the food supply chain to be sustainable and circular

The resilience of food systems is jeopardized by using food packaging materials that have adverse impacts on the environment, food quality, food safety, shelf-life, food loss, and waste. Therefore, a transition into a more sustainable system can only be possible by adopting circular economy principles and practices that can facilitate the elimination of unsustainable packaging, irresponsible disposal behaviors, and waste management. This paper mainly focuses on circular packaging practices in the existing literature to reveal the drivers of circular food packaging applications. The study also displays the triple combinations of material-sector, material-CE, and sector-CE principles. As a methodology, a systematic literature review (SLR) has been used for this study. Furthermore, this study investigates the literature findings, such as the most frequently mentioned food sector and sub-sector, CE principles, materials adopted for food packaging, and so on. The primary contribution of this study to the body of literature is the synthesis and mapping of the literature as a whole from the perspectives of CE principles, both sector-based and national, and the materials used through circular food packaging, and the attempt to facilitate this transition into a more circular system by outlining the drivers of circular food packaging

DECARBONISATION OF FREIGHT TRANSPORT WITH SYSTEM DYNAMICS IN FOOD SUPPLY CHAINS IN UK

In this study, decarbonisation (reduction of carbon emissions) on food supply chain considering forward and reverse logistics operations will be analysed. The main concern in proposed system dynamics (SD) model is to measure emissions caused by forward and reverse logistics activities

A Hybrid Fuzzy Multi-criteria Decision Making Model to Evaluate the Overall Performance of Public Emergency Departments: A Case Study

[EN] Performance evaluation is relevant for supporting managerial decisions related to the improvement of public emergency departments (EDs). As different criteria from ED context and several alternatives need to be considered, selecting a suitable Multicriteria Decision-Making (MCDM) approach has become a crucial step for ED performance evaluation. Although some methodologies have been proposed to address this challenge, a more complete approach is still lacking. This paper bridges this gap by integrating three potent MCDM methods. First, the Fuzzy Analytic Hierarchy Process (FAHP) is used to determine the criteria and sub-criteria weights under uncertainty, followed by the interdependence evaluation via fuzzy Decision-Making Trial and Evaluation Laboratory(FDEMATEL). The fuzzy logic is merged with AHP and DEMATEL to illustrate vague judgments. Finally, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is used for ranking EDs. This approach is validated in a real 3-ED cluster. The results revealed the critical role of Infrastructure (21.5%) in ED performance and the interactive nature of Patient safety (C+R =12.771). Furthermore, this paper evidences the weaknesses to be tackled for upgrading the performance of each ED.Ortiz-Barrios, M.; Alfaro Saiz, JJ. (2020). A Hybrid Fuzzy Multi-criteria Decision Making Model to Evaluate the Overall Performance of Public Emergency Departments: A Case Study. International Journal of Information Technology & Decision Making. 19(6):1485-1548. https://doi.org/10.1142/S0219622020500364S14851548196Lord, K., Parwani, V., Ulrich, A., Finn, E. B., Rothenberg, C., Emerson, B., … Venkatesh, A. K. (2018). Emergency department boarding and adverse hospitalization outcomes among patients admitted to a general medical service. The American Journal of Emergency Medicine, 36(7), 1246-1248. doi:10.1016/j.ajem.2018.03.043Sørup, C. M., Jacobsen, P., & Forberg, J. L. (2013). 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(2018). A Fuzzy AHP–TOPSIS-Based Group Decision-Making Approach to IT Personnel Selection. International Journal of Fuzzy Systems, 20(5), 1576-1591. doi:10.1007/s40815-018-0474-7CHEN, M.-F., TZENG, G.-H., & TANG, T.-I. (2005). FUZZY MCDM APPROACH FOR EVALUATION OF EXPATRIATE ASSIGNMENTS. International Journal of Information Technology & Decision Making, 04(02), 277-296. doi:10.1142/s0219622005001520Gul, M., Celik, E., Gumus, A. T., & Guneri, A. F. (2016). Emergency department performance evaluation by an integrated simulation and interval type-2 fuzzy MCDM-based scenario analysis. European J. of Industrial Engineering, 10(2), 196. doi:10.1504/ejie.2016.075846Jovčić, Průša, Dobrodolac, & Švadlenka. (2019). A Proposal for a Decision-Making Tool in Third-Party Logistics (3PL) Provider Selection Based on Multi-Criteria Analysis and the Fuzzy Approach. Sustainability, 11(15), 4236. doi:10.3390/su11154236Saaty, T. L., & Vargas, L. G. (2012). 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Computers & Industrial Engineering, 132, 84-97. doi:10.1016/j.cie.2019.04.023Emrouznejad, A., & Yang, G. (2018). A survey and analysis of the first 40 years of scholarly literature in DEA: 1978–2016. Socio-Economic Planning Sciences, 61, 4-8. doi:10.1016/j.seps.2017.01.008Arya, A., & Yadav, S. P. (2017). Development of FDEA Models to Measure the Performance Efficiencies of DMUs. International Journal of Fuzzy Systems, 20(1), 163-173. doi:10.1007/s40815-017-0325-yMufazzal, S., & Muzakkir, S. M. (2018). A new multi-criterion decision making (MCDM) method based on proximity indexed value for minimizing rank reversals. Computers & Industrial Engineering, 119, 427-438. doi:10.1016/j.cie.2018.03.045Kaliszewski, I., & Podkopaev, D. (2016). Simple additive weighting—A metamodel for multiple criteria decision analysis methods. Expert Systems with Applications, 54, 155-161. doi:10.1016/j.eswa.2016.01.042Mousavi-Nasab, S. H., & Sotoudeh-Anvari, A. (2018). A new multi-criteria decision making approach for sustainable material selection problem: A critical study on rank reversal problem. Journal of Cleaner Production, 182, 466-484. doi:10.1016/j.jclepro.2018.02.062Chen, Z., Ming, X., Zhang, X., Yin, D., & Sun, Z. (2019). A rough-fuzzy DEMATEL-ANP method for evaluating sustainable value requirement of product service system. Journal of Cleaner Production, 228, 485-508. doi:10.1016/j.jclepro.2019.04.145Jumaah, F. M., Zadain, A. A., Zaidan, B. B., Hamzah, A. K., & Bahbibi, R. (2018). Decision-making solution based multi-measurement design parameter for optimization of GPS receiver tracking channels in static and dynamic real-time positioning multipath environment. Measurement, 118, 83-95. doi:10.1016/j.measurement.2018.01.011Singh, A., & Prasher, A. (2017). Measuring healthcare service quality from patients’ perspective: using Fuzzy AHP application. 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Multi-criteria decision analysis for supporting the selection of medical devices under uncertainty. European Journal of Operational Research, 247(1), 216-228. doi:10.1016/j.ejor.2015.05.075Kovacs, E., Strobl, R., Phillips, A., Stephan, A.-J., Müller, M., Gensichen, J., & Grill, E. (2018). Systematic Review and Meta-analysis of the Effectiveness of Implementation Strategies for Non-communicable Disease Guidelines in Primary Health Care. Journal of General Internal Medicine, 33(7), 1142-1154. doi:10.1007/s11606-018-4435-5Morley, C., Unwin, M., Peterson, G. M., Stankovich, J., & Kinsman, L. (2018). Emergency department crowding: A systematic review of causes, consequences and solutions. PLOS ONE, 13(8), e0203316. doi:10.1371/journal.pone.0203316Hermann, R. M., Long, E., & Trotta, R. L. (2019). Improving Patients’ Experiences Communicating With Nurses and Providers in the Emergency Department. Journal of Emergency Nursing, 45(5), 523-530. doi:10.1016/j.jen.2018.12.001Hawley, K. L., Mazer-Amirshahi, M., Zocchi, M. S., Fox, E. R., & Pines, J. M. (2015). Longitudinal Trends in U.S. Drug Shortages for Medications Used in Emergency Departments (2001-2014). Academic Emergency Medicine, 23(1), 63-69. doi:10.1111/acem.12838Stang, A. S., Crotts, J., Johnson, D. W., Hartling, L., & Guttmann, A. (2015). Crowding Measures Associated With the Quality of Emergency Department Care: A Systematic Review. Academic Emergency Medicine, 22(6), 643-656. doi:10.1111/acem.12682Chanamool, N., & Naenna, T. (2016). Fuzzy FMEA application to improve decision-making process in an emergency department. Applied Soft Computing, 43, 441-453. doi:10.1016/j.asoc.2016.01.007Farup, P. G. (2015). Are measurements of patient safety culture and adverse events valid and reliable? Results from a cross sectional study. BMC Health Services Research, 15(1). doi:10.1186/s12913-015-0852-xCarter, E. J., Pouch, S. M., & Larson, E. L. (2013). 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Investigating barriers to circular supply chain in the textile industry from Stakeholders’ perspective

The objectives of this study are to understand the circular supply chain barriers for textile companies to implement the circular economy. Main contributions of the study were to propose a specific framework that reveals circular supply chain barriers in transition to circular economy with holistic view by encompassing all stakeholders, to reveal causal relationships among the circular supply chain barriers within textile industry. Causal relationships between the proposed circular supply chain barriers were identified by Fuzzy-Decision Making Trial and Evaluation Laboratory (DEMATEL) method. The barriers are classified under cause and effect groups and related implications are proposed. The findings of this study are lack of collecting, sorting and recycling, reluctance for acceptance of CE model, and problems related to uniformity and standardisation are revealed as the most important barriers, respectively. Moreover, lack of technical knowledge is the most influencing factor, whereas, challenges in product design is the most influenced factor. © 2020 Informa UK Limited, trading as Taylor & Francis Group