Best–worst method to prioritize indicators effective in making logistics systems more sustainable in fast-moving consumer goods industry in developing countries
Abstract
Logistics systems constitute the backbone of international trade. For developing countries, establishment of sustainable logistics systems reduces costs, and makes supply chains strong to become able to compete. Without setting indicators for sustainable logistics, it is not possible to understand what policies are necessary for success. Logistics systems situations become worse in especial industries such as Fast-Moving Consuming Goods (FMCG) industry that are facing observable challenges such as old-fashioned goods or product corruption. The objective of this paper is to determine a set of indicators, which can be helpful in enhancement of sustainable logistics systems in developing countries. An initial set of indicators is determined through literature review and justified by asking experts’ opinions who have experience of management in logistics systems in developing countries such as Iran and Afghanistan, especially in logistics management in FMCG industry. The indicators are prioritized using Best–Worst Method (BWM), which is a newly introduced decision-making model. Results of prioritization of finalized dimensions and indicators by use of BWM show that “Governance” has the highest importance among dimensions and “management commitment to sustainability” is the most important indicator among all indicators. The results are applicably acceptable as we can see in business circumstances that only when managers believe in perusing sustainability principles as an important factor under each type of economic circumstance, an efficient vision will be set. Risk management has gained the least weight in this study. Based on experts’ opinions, if policies and procedures are set and performed correctly, risks will be less probable by themselves. The results help mangers in assignment of limited budgets to improvement projects related to each indicator.
Keyword : best–worst method (BWM), developing countries, fast moving consumer goods (FMCG), logistics systems, sustainability, prioritization model
How to Cite
Pishdar, M., Ghasemzadeh, F., & Antuchevičienė, J. (2022). Best–worst method to prioritize indicators effective in making logistics systems more sustainable in fast-moving consumer goods industry in developing countries. Transport, 37(3), 190–200. https://doi.org/10.3846/transport.2022.17449
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
Abbasi, M.; Nilsson, F. 2016. Developing environmentally sustainable logistics: exploring themes and challenges from a logistics service providers’ perspective, Transportation Research Part D: Transport and Environment 46: 273–283. https://doi.org/10.1016/j.trd.2016.04.004
Amindoust, A.; Ahmed, S.; Saghafinia, A.; Bahreininejad, A. 2012. Sustainable supplier selection: a ranking model based on fuzzy inference system, Applied Soft Computing 12(6): 1668–1677. https://doi.org/10.1016/j.asoc.2012.01.023
Azadi, M.; Jafarian, M.; Saen, R. F.; Mirhedayatian, S. M. 2015. A new fuzzy DEA model for evaluation of efficiency and effectiveness of suppliers in sustainable supply chain management context, Computers & Operations Research 54: 274–285. https://doi.org/10.1016/j.cor.2014.03.002
Bergsten, A.; Jiren, T. S.; Leventon, J.; Dorresteijn, I.; Schultner, J.; Fischer, J. 2019. Identifying governance gaps among interlinked sustainability challenges, Environmental Science & Policy 91: 27–38. https://doi.org/10.1016/j.envsci.2018.10.007
Brunelli, M.; Rezaei, J. 2019. A multiplicative best–worst method for multi-criteria decision making, Operations Research Letters 47(1): 12–15. https://doi.org/10.1016/j.orl.2018.11.008
BWM. 2021. BWM Solvers. Best Worst Method (BWM) Home. Available from Internet: https://bestworstmethod.com/software
Chung, K. H.; Ko, S. Y.; Lee, C. U.; Ko, C. S. 2016. Sustainable collaboration model with monopoly of service centers in express delivery services based on Shapley value allocation, International Journal of Industrial Engineering: Theory, Applications, and Practice 23(3): 166–173. https://doi.org/10.23055/ijietap.2016.23.3.2841
Cuthbertson, R.; Cetinkaya, B.; Ewer, G.; Klaas-Wissing, T.; Piot¬rowicz, W.; Tyssen, C. 2011. Sustainable Supply Chain Management: Practical Ideas for Moving Towards Best Practice. Springer Science. 283 p. https://doi.org/10.1007/978-3-642-12023-7
Dang, V. L.; Yeo, G. T. 2018. Weighing the key factors to improve Vietnam’s logistics system, The Asian Journal of Shipping and Logistics 34(4): 308–316. https://doi.org/10.1016/j.ajsl.2018.12.004
Das, R.; Shaw, K. 2017. Uncertain supply chain network design considering carbon footprint and social factors using two-stage approach, Clean Technologies and Environmental Policy 19(10): 2491–2519. https://doi.org/10.1007/s10098-017-1446-6
Dyllick, T.; Hockerts, K. 2002. Beyond the business case for corporate sustainability, Business Strategy and the Environment 11(2): 130–141. https://doi.org/10.1002/bse.323
Entezaminia, A.; Heydari, M.; Rahmani, D. 2016. A multi-objective model for multi-product multi-site aggregate production planning in a green supply chain: considering collection and recycling centers, Journal of Manufacturing Systems 40: 63–75. https://doi.org/10.1016/j.jmsy.2016.06.004
Erol, I.; Sencer, S.; Sari, R. 2011. A new fuzzy multi-criteria framework for measuring sustainability performance of a supply chain, Ecological Economics 70(6): 1088–1100. https://doi.org/10.1016/j.ecolecon.2011.01.001
Fallahpour, A.; Olugu, E. U.; Musa, S. N.; Wong, K. Y.; Noori, S. 2017. A decision support model for sustainable supplier selection in sustainable supply chain management, Computers & Industrial Engineering 105: 391–410. https://doi.org/10.1016/j.cie.2017.01.005
Fazlollahtabar, H. 2018. Operations and inspection cost minimization for a reverse supply chain, Operational Research in Engineering Sciences: Theory and Applications 1(1): 91–107.
Genovese, A.; Acquaye, A. A.; Figueroa, A.; Koh, S. C. L. 2017. Sustainable supply chain management and the transition towards a circular economy: evidence and some applications, Omega 66: 344–357. https://doi.org/10.1016/j.omega.2015.05.015
Ghadimi, P.; Heavey, C. 2014. Sustainable supplier selection in medical device industry: toward sustainable manufacturing, Procedia CIRP 15: 165–170. https://doi.org/10.1016/j.procir.2014.06.096
Govindan, K.; Kadziński, M.; Ehling, R.; Miebs, G. 2019. Selection of a sustainable third-party reverse logistics provider based on the robustness analysis of an outranking graph kernel conducted with ELECTRE I and SMAA, Omega 85: 1–15. https://doi.org/10.1016/j.omega.2018.05.007
Govindan, K.; Khodaverdi, R.; Jafarian, A. 2013. A fuzzy multi criteria approach for measuring sustainability performance of a supplier based on triple bottom line approach, Journal of Cleaner Production 47: 345–354. https://doi.org/10.1016/j.jclepro.2012.04.014
Hansmann, R.; Mieg, H. A.; Frischknecht, P. 2012. Principal sustainability components: empirical analysis of synergies between the three pillars of sustainability, International Journal of Sustainable Development & World Ecology 19(5): 451–459. https://doi.org/10.1080/13504509.2012.696220
Hashemkhani Zolfani, S.; Chatterjee, P.; Yazdani, M. 2019a. A structured framework for sustainable supplier selection using a combined BWM-CoCoSo model, in International Scientific Conference “Contemporary Issues in Business, Management and Education”, 9–10 May 2019, Vilnius, Lithuania, 797–804. https://doi.org/10.3846/cibmee.2019.081
Hashemkhani Zolfani, S.; Mosharafiandehkordi, S.; Kutut, V. 2019b. A pre-planning for hotel locating according to the sustainability perspective based on BWM-WASPAS approach, International Journal of Strategic Property Management 23(6): 405–419. https://doi.org/10.3846/ijspm.2019.10844
Hsu, C.-W.; Hu, A.-H. 2009. Applying hazardous substance management to supplier selection using analytic network process, Journal of Cleaner Production 17(2): 255–264. https://doi.org/10.1016/j.jclepro.2008.05.004
Husted, B. W.; De Sousa-Filho, J. M. 2017. The impact of sustainability governance, country stakeholder orientation, and country risk on environmental, social, and governance performance, Journal of Cleaner Production 155: 93–102. https://doi.org/10.1016/j.jclepro.2016.10.025
Irigoyen, J. L. 2014. To Feed the Future, Let’s Make Logistics and Transport Sustainable. Word Bank Blogs. Available from Internet: https://blogs.worldbank.org/transport/feed-future-let-s-make-logistics-and-transport-sustainable
ISO 14001:2015. Environmental Management Systems – Requirements with Guidance for Use.
Jayal, A. D.; Badurdeen, F.; Dillon, O. W.; Jawahir, I. S. 2010. Sustainable manufacturing: modeling and optimization challenges at the product, process and system levels, CIRP Journal of Manufacturing Science and Technology 2(3): 144–152. https://doi.org/10.1016/j.cirpj.2010.03.006
Kaiser, J.; Urnauer, C.; Metternich, J. 2019. A framework for planning logistical alternatives in value stream design, Procedia CIRP 81: 180–185. https://doi.org/10.1016/j.procir.2019.03.032
Kayikci, Y. 2018. Sustainability impact of digitization in logistics, Procedia Manufacturing 21: 782–789. https://doi.org/10.1016/j.promfg.2018.02.184
Kheybari, S.; Kazemi, M.; Rezaei, J. 2019. Bioethanol facility location selection using best-worst method, Applied Energy 242: 612–623. https://doi.org/10.1016/j.apenergy.2019.03.054
Klassen, R. D.; McLaughlin, C. P. 1996. The impact of environmental management on firm performance, Management Science 42(8): 1199–1214. https://doi.org/10.1287/mnsc.42.8.1199
Kumar, A.; Aswin, A.; Gupta, H. 2020. Evaluating green performance of the airports using hybrid BWM and VIKOR methodology, Tourism Management 76: 103941. https://doi.org/10.1016/j.tourman.2019.06.016
Kusi-Sarpong, S.; Gupta, H.; Sarkis, J. 2019. A supply chain sustainability innovation framework and evaluation methodology, International Journal of Production Research 57(7): 1990–2008. https://doi.org/10.1080/00207543.2018.1518607
Leal Filho, W.; Platje, J.; Gerstlberger, W.; Ciegis, R.; Kääriä, J.; Klavins, M.; Kliucininkas, L. 2016. The role of governance in realising the transition towards sustainable societies, Journal of Cleaner Production 113: 755–766. https://doi.org/10.1016/j.jclepro.2015.11.060
Liao, H.; Mi, X.; Yu, Q.; Luo, L. 2019. Hospital performance evaluation by a hesitant fuzzy linguistic best worst method with inconsistency repairing, Journal of Cleaner Production 232: 657–671. https://doi.org/10.1016/j.jclepro.2019.05.308
Lin, C.-C.; Chang, C.-H. 2018. Evaluating skill requirement for logistics operation practitioners: based on the perceptions of logistics service providers and academics in Taiwan, The Asian Journal of Shipping and Logistics 34(4): 328–336. https://doi.org/10.1016/j.ajsl.2018.12.006
Lin, Y.-H.; Tseng, M.-L. 2016. Assessing the competitive priorities within sustainable supply chain management under uncertainty, Journal of Cleaner Production 112: 2133–2144. https://doi.org/10.1016/j.jclepro.2014.07.012
Liu, A.; Xiao, Y.; Ji, X.; Wang, K.; Tsai, S.-B.; Lu, H.; Cheng, J.; Lai, X.; Wang, J. 2018a. A novel two-stage integrated model for supplier selection of green fresh product, Sustainability 10(7): 2371. https://doi.org/10.3390/su10072371
Liu, J.; Yuan, C.; Hafeez, M.; Yuan, Q. 2018b. The relationship between environment and logistics performance: evidence from Asian countries, Journal of Cleaner Production 204: 282–291. https://doi.org/10.1016/j.jclepro.2018.08.310
Liu, S.; Zhang, G.; Wang, L. 2018c. IoT-enabled dynamic optimisation for sustainable reverse logistics, Procedia CIRP 69: 662–667. https://doi.org/10.1016/j.procir.2017.11.088
Luthra, S.; Govindan, K.; Kannan, D.; Mangla, S. K.; Garg, C. P. 2017. An integrated framework for sustainable supplier selection and evaluation in supply chains, Journal of Cleaner Production 140: 1686–1698. https://doi.org/10.1016/j.jclepro.2016.09.078
Mafakheri, F.; Breton, M.; Ghoniem, A. 2011. Supplier selection-order allocation: A two-stage multiple criteria dynamic programming approach, International Journal of Production Economics 132(1): 52–57. https://doi.org/10.1016/j.ijpe.2011.03.005
Malek, J.; Desai, T. N. 2019. Prioritization of sustainable manufacturing barriers using best worst method, Journal of Cleaner Production 226: 589–600. https://doi.org/10.1016/j.jclepro.2019.04.056
Manzardo, A.; Ren, J.; Mazzi, A.; Scipioni, A. 2012. A grey-based group decision-making methodology for the selection of hydrogen technologies in life cycle sustainability perspective, International Journal of Hydrogen Energy 37(23): 17663–17670. https://doi.org/10.1016/j.ijhydene.2012.08.137
Mohammadi, M.; Rezaei, J. 2020. Bayesian best-worst method: a probabilistic group decision making model, Omega 96: 102075. https://doi.org/10.1016/j.omega.2019.06.001
Mohanty, M.; Shankar, R. 2017. Modelling uncertainty in sustainable integrated logistics using fuzzy-TISM, Transportation Research Part D: Transport and Environment 53: 471–491. https://doi.org/10.1016/j.trd.2017.04.034
Moldan, B.; Janoušková, S.; Hák, T. 2012. How to understand and measure environmental sustainability: Indicators and targets, Ecological Indicators 17: 4–13. https://doi.org/10.1016/j.ecolind.2011.04.033
Mulky, A. G. 2013. Distribution challenges and workable solutions, IIMB Management Review 25(3): 136. https://doi.org/10.1016/j.iimb.2013.06.010
Murphy, P. R.; Poist, R. F.; Braunschweig, C. D. 1996. Green logistics: comparative views of environmental progressives, moderates, and conservatives, Journal of Business Logistics 17(1): 191–212.
Narayana, S. A.; Pati, R. K.; Padhi, S. S. 2019. Market dynamics and reverse logistics for sustainability in the Indian pharmaceuticals industry, Journal of Cleaner Production 208: 968–987. https://doi.org/10.1016/j.jclepro.2018.10.171
Nawaz, F.; Asadabadi, M. R.; Janjua, N. K.; Hussain, O. K.; Chang, E.; Saberi, M. 2018. An MCDM method for cloud service selection using a Markov chain and the best-worst method, Knowledge-Based Systems 159: 120–131. https://doi.org/10.1016/j.knosys.2018.06.010
Nayak, R.; Akbari, M.; Maleki Far, S. 2019. Recent sustainable trends in Vietnam’s fashion supply chain, Journal of Cleaner Production 225: 291–303. https://doi.org/10.1016/j.jclepro.2019.03.239
Novack, R. A. 1984. Transportation standard cost budgeting, in NCPDM: National Council of Physical Distribution Management – Fall Meeting: 22 Annual Conference, 16–19 September 1984, Dallas, TX, US, 309–320.
Pamučar, D.; Gigović, L.; Bajić, Z.; Janošević, M. 2017. Location selection for wind farms using GIS multi-criteria hybrid model: an approach based on fuzzy and rough numbers, Sustainability 9(8): 1315. https://doi.org/10.3390/su9081315
Punniyamoorthy, M.; Mathiyalagan, P.; Parthiban, P. 2011. A strategic model using structural equation modeling and fuzzy logic in supplier selection, Expert Systems with Applications 38(1): 458–474. https://doi.org/10.1016/j.eswa.2010.06.086
Puška, A.; Maksimović, A.; Stojanović, I. 2018. Improving organizational learning by sharing information through innovative supply chain in agro-food companies from Bosnia and Herzegovina, Operational Research in Engineering Sciences: Theory and Applications 1(1):76–90.
Quarshie, A. M.; Salmi, A.; Leuschner, R. 2016. Sustainability and corporate social responsibility in supply chains: the state of research in supply chain management and business ethics journals, Journal of Purchasing and Supply Management 22(2): 82–97. https://doi.org/10.1016/j.pursup.2015.11.001
Rashidi, K.; Cullinane, K. 2019. Evaluating the sustainability of national logistics performance using data envelopment analysis, Transport Policy 74: 35–46. https://doi.org/10.1016/j.tranpol.2018.11.014
Ren, J.; Tan, S.; Goodsite, M. E.; Sovacool, B. K.; Dong, L. 2015. Sustainability, shale gas, and energy transition in China: Assessing barriers and prioritizing strategic measures, Energy 84: 551–562. https://doi.org/10.1016/j.energy.2015.03.020
Rezaei, J. 2015. Best-worst multi-criteria decision-making method, Omega 53: 49–57. https://doi.org/10.1016/j.omega.2014.11.009
Rezaei, J.; Nispeling, T.; Sarkis, J.; Tavasszy, L. 2016. A supplier selection life cycle approach integrating traditional and environmental criteria using the best worst method, Journal of Cleaner Production 135: 577–588. https://doi.org/10.1016/j.jclepro.2016.06.125
Sabah, S. 2017. The impact of self-construal and self-concept clarity on socially motivated consumption: The moderating role of materialism, Journal of Global Scholars of Marketing Science 27(1): 31–45. https://doi.org/10.1080/21639159.2016.1265321
Shankar, R.; Gupta, R.; Pathak, D.K. 2018. Modeling critical success factors of traceability for food logistics system, Transportation Research Part E: Logistics and Transportation Review 119: 205–222. https://doi.org/10.1016/j.tre.2018.03.006
Simchi-Levi, D.; Kaminsky, P.; Simchi-Levi, E. R. 2021. Designing and Managing the Supply Chain: Concepts, Strategies and Case Studies. 4th edition. McGraw-Hill Higher Education. 1101 p.
Speranza, M. G. 2018. Trends in transportation and logistics, European Journal of Operational Research 264(3): 830–836. https://doi.org/10.1016/j.ejor.2016.08.032
Stević, Ž.; Pamučar, D.; Subotić, M.; Antuchevičienė, J.; Zavadskas, E. K. 2018. The location selection for roundabout construction using rough BWM-rough WASPAS approach based on a new rough hamy aggregator, Sustainability 10(8): 2817. https://doi.org/10.3390/su10082817
Stević, Ž.; Pamučar, D.; Zavadskas, E. K.; Ćirović, G.; Prentkovskis, O. 2017. The selection of wagons for the internal transport of a logistics company: a novel approach based on rough BWM and rough SAW methods, Symmetry 9(11): 264. https://doi.org/10.3390/sym9110264
Su, C.-M.; Horng, D.-J.; Tseng, M.-L.; Chiu, A. S. F.; Wu, K.-J.; Chen, H.-P. 2016. Improving sustainable supply chain management using a novel hierarchical grey-DEMATEL approach, Journal of Cleaner Production 134: 469–481. https://doi.org/10.1016/j.jclepro.2015.05.080
Sueyoshi, T.; Wang, D. 2014. Sustainability development for supply chain management in U.S. petroleum industry by DEA environmental assessment, Energy Economics 46: 360–374. https://doi.org/10.1016/j.eneco.2014.09.022
Suhi, S. A.; Enayet, R.; Haque, T.; Ali, S. M.; Moktadir, M. A.; Paul, S. K. 2019. Environmental sustainability assessment in supply chain: an emerging economy context, Environmental Impact Assessment Review 79: 106306. https://doi.org/10.1016/j.eiar.2019.106306
Tavasszy, L.; De Bok, M.; Alimoradi, Z.; Rezaei, J. 2020. Logistics decisions in descriptive freight transportation models: a review, Journal of Supply Chain Management Science 1(3–4): 74–86. https://doi.org/10.18757/jscms.2020.1992
Tseng, M.-L.; Chiu, A. S. F. 2013. Evaluating firm’s green supply chain management in linguistic preferences, Journal of Cleaner Production 40: 22–31. https://doi.org/10.1016/j.jclepro.2010.08.007
Turnheim, B.; Berkhout, F.; Geels, F.; Hof, A.; McMeekin, A.; Nykvist, B.; Van Vuuren, D. 2015. Evaluating sustainability transitions pathways: Bridging analytical approaches to address governance challenges, Global Environmental Change 35: 239–253. https://doi.org/10.1016/j.gloenvcha.2015.08.010
Vachon, S. 2007. Green supply chain practices and the selection of environmental technologies, International Journal of Production Research 45(18–19): 4357–4379. https://doi.org/10.1080/00207540701440303
Validi, S.; Bhattacharya, A.; Byrne, P. J. 2014. A case analysis of a sustainable food supply chain distribution system – a multi-objective approach, International Journal of Production Economics 152: 71–87. https://doi.org/10.1016/j.ijpe.2014.02.003
Walton, S. V.; Handfield, R. B.; Melnyk, S. A. 1998. The green supply chain: integrating suppliers into environmental management processes, International Journal of Purchasing and Materials Management 34(1): 2–11. https://doi.org/10.1111/j.1745-493X.1998.tb00042.x
Wang, H.; Liu, H.; Kim, S. J.; Kim, K. H. 2019. Sustainable fashion index model and its implication, Journal of Business Research 99: 430–437. https://doi.org/10.1016/j.jbusres.2017.12.027
Wong, C. Y.; Wong, C. W.; Boon-Itt, S. 2015. Integrating environmental management into supply chains: a systematic literature review and theoretical framework, International Journal of Physical Distribution & Logistics Management 45(1/2): 43–68. https://doi.org/10.1108/IJPDLM-05-2013-0110
Yousefi, S.; Shabanpour, H.; Fisher, R.; Saen, R. F. 2016. Evaluating and ranking sustainable suppliers by robust dynamic data envelopment analysis, Measurement 83: 72–85. https://doi.org/10.1016/j.measurement.2016.01.032
Yu, H.; Solvang, W. D. 2018. Incorporating flexible capacity in the planning of a multi-product multi-echelon sustainable reverse logistics network under uncertainty, Journal of Cleaner Production 198: 285–303. https://doi.org/10.1016/j.jclepro.2018.07.019
Zavadskas, E. K.; Stević, Ž.; Tanackov, I.; Prentkovskis, O. 2018. A novel multicriteria approach – rough step-wise weight assessment ratio analysis method (R-SWARA) and its application in logistics, Studies in Informatics and Control 27(1): 97–106. https://doi.org/10.24846/v27i1y201810
Zhu, Q.; Sarkis, J.; Lai, K.-H. 2008. Confirmation of a measurement model for green supply chain management practices implementation, International Journal of Production Economics 111(2): 261–273. https://doi.org/10.1016/j.ijpe.2006.11.029
Amindoust, A.; Ahmed, S.; Saghafinia, A.; Bahreininejad, A. 2012. Sustainable supplier selection: a ranking model based on fuzzy inference system, Applied Soft Computing 12(6): 1668–1677. https://doi.org/10.1016/j.asoc.2012.01.023
Azadi, M.; Jafarian, M.; Saen, R. F.; Mirhedayatian, S. M. 2015. A new fuzzy DEA model for evaluation of efficiency and effectiveness of suppliers in sustainable supply chain management context, Computers & Operations Research 54: 274–285. https://doi.org/10.1016/j.cor.2014.03.002
Bergsten, A.; Jiren, T. S.; Leventon, J.; Dorresteijn, I.; Schultner, J.; Fischer, J. 2019. Identifying governance gaps among interlinked sustainability challenges, Environmental Science & Policy 91: 27–38. https://doi.org/10.1016/j.envsci.2018.10.007
Brunelli, M.; Rezaei, J. 2019. A multiplicative best–worst method for multi-criteria decision making, Operations Research Letters 47(1): 12–15. https://doi.org/10.1016/j.orl.2018.11.008
BWM. 2021. BWM Solvers. Best Worst Method (BWM) Home. Available from Internet: https://bestworstmethod.com/software
Chung, K. H.; Ko, S. Y.; Lee, C. U.; Ko, C. S. 2016. Sustainable collaboration model with monopoly of service centers in express delivery services based on Shapley value allocation, International Journal of Industrial Engineering: Theory, Applications, and Practice 23(3): 166–173. https://doi.org/10.23055/ijietap.2016.23.3.2841
Cuthbertson, R.; Cetinkaya, B.; Ewer, G.; Klaas-Wissing, T.; Piot¬rowicz, W.; Tyssen, C. 2011. Sustainable Supply Chain Management: Practical Ideas for Moving Towards Best Practice. Springer Science. 283 p. https://doi.org/10.1007/978-3-642-12023-7
Dang, V. L.; Yeo, G. T. 2018. Weighing the key factors to improve Vietnam’s logistics system, The Asian Journal of Shipping and Logistics 34(4): 308–316. https://doi.org/10.1016/j.ajsl.2018.12.004
Das, R.; Shaw, K. 2017. Uncertain supply chain network design considering carbon footprint and social factors using two-stage approach, Clean Technologies and Environmental Policy 19(10): 2491–2519. https://doi.org/10.1007/s10098-017-1446-6
Dyllick, T.; Hockerts, K. 2002. Beyond the business case for corporate sustainability, Business Strategy and the Environment 11(2): 130–141. https://doi.org/10.1002/bse.323
Entezaminia, A.; Heydari, M.; Rahmani, D. 2016. A multi-objective model for multi-product multi-site aggregate production planning in a green supply chain: considering collection and recycling centers, Journal of Manufacturing Systems 40: 63–75. https://doi.org/10.1016/j.jmsy.2016.06.004
Erol, I.; Sencer, S.; Sari, R. 2011. A new fuzzy multi-criteria framework for measuring sustainability performance of a supply chain, Ecological Economics 70(6): 1088–1100. https://doi.org/10.1016/j.ecolecon.2011.01.001
Fallahpour, A.; Olugu, E. U.; Musa, S. N.; Wong, K. Y.; Noori, S. 2017. A decision support model for sustainable supplier selection in sustainable supply chain management, Computers & Industrial Engineering 105: 391–410. https://doi.org/10.1016/j.cie.2017.01.005
Fazlollahtabar, H. 2018. Operations and inspection cost minimization for a reverse supply chain, Operational Research in Engineering Sciences: Theory and Applications 1(1): 91–107.
Genovese, A.; Acquaye, A. A.; Figueroa, A.; Koh, S. C. L. 2017. Sustainable supply chain management and the transition towards a circular economy: evidence and some applications, Omega 66: 344–357. https://doi.org/10.1016/j.omega.2015.05.015
Ghadimi, P.; Heavey, C. 2014. Sustainable supplier selection in medical device industry: toward sustainable manufacturing, Procedia CIRP 15: 165–170. https://doi.org/10.1016/j.procir.2014.06.096
Govindan, K.; Kadziński, M.; Ehling, R.; Miebs, G. 2019. Selection of a sustainable third-party reverse logistics provider based on the robustness analysis of an outranking graph kernel conducted with ELECTRE I and SMAA, Omega 85: 1–15. https://doi.org/10.1016/j.omega.2018.05.007
Govindan, K.; Khodaverdi, R.; Jafarian, A. 2013. A fuzzy multi criteria approach for measuring sustainability performance of a supplier based on triple bottom line approach, Journal of Cleaner Production 47: 345–354. https://doi.org/10.1016/j.jclepro.2012.04.014
Hansmann, R.; Mieg, H. A.; Frischknecht, P. 2012. Principal sustainability components: empirical analysis of synergies between the three pillars of sustainability, International Journal of Sustainable Development & World Ecology 19(5): 451–459. https://doi.org/10.1080/13504509.2012.696220
Hashemkhani Zolfani, S.; Chatterjee, P.; Yazdani, M. 2019a. A structured framework for sustainable supplier selection using a combined BWM-CoCoSo model, in International Scientific Conference “Contemporary Issues in Business, Management and Education”, 9–10 May 2019, Vilnius, Lithuania, 797–804. https://doi.org/10.3846/cibmee.2019.081
Hashemkhani Zolfani, S.; Mosharafiandehkordi, S.; Kutut, V. 2019b. A pre-planning for hotel locating according to the sustainability perspective based on BWM-WASPAS approach, International Journal of Strategic Property Management 23(6): 405–419. https://doi.org/10.3846/ijspm.2019.10844
Hsu, C.-W.; Hu, A.-H. 2009. Applying hazardous substance management to supplier selection using analytic network process, Journal of Cleaner Production 17(2): 255–264. https://doi.org/10.1016/j.jclepro.2008.05.004
Husted, B. W.; De Sousa-Filho, J. M. 2017. The impact of sustainability governance, country stakeholder orientation, and country risk on environmental, social, and governance performance, Journal of Cleaner Production 155: 93–102. https://doi.org/10.1016/j.jclepro.2016.10.025
Irigoyen, J. L. 2014. To Feed the Future, Let’s Make Logistics and Transport Sustainable. Word Bank Blogs. Available from Internet: https://blogs.worldbank.org/transport/feed-future-let-s-make-logistics-and-transport-sustainable
ISO 14001:2015. Environmental Management Systems – Requirements with Guidance for Use.
Jayal, A. D.; Badurdeen, F.; Dillon, O. W.; Jawahir, I. S. 2010. Sustainable manufacturing: modeling and optimization challenges at the product, process and system levels, CIRP Journal of Manufacturing Science and Technology 2(3): 144–152. https://doi.org/10.1016/j.cirpj.2010.03.006
Kaiser, J.; Urnauer, C.; Metternich, J. 2019. A framework for planning logistical alternatives in value stream design, Procedia CIRP 81: 180–185. https://doi.org/10.1016/j.procir.2019.03.032
Kayikci, Y. 2018. Sustainability impact of digitization in logistics, Procedia Manufacturing 21: 782–789. https://doi.org/10.1016/j.promfg.2018.02.184
Kheybari, S.; Kazemi, M.; Rezaei, J. 2019. Bioethanol facility location selection using best-worst method, Applied Energy 242: 612–623. https://doi.org/10.1016/j.apenergy.2019.03.054
Klassen, R. D.; McLaughlin, C. P. 1996. The impact of environmental management on firm performance, Management Science 42(8): 1199–1214. https://doi.org/10.1287/mnsc.42.8.1199
Kumar, A.; Aswin, A.; Gupta, H. 2020. Evaluating green performance of the airports using hybrid BWM and VIKOR methodology, Tourism Management 76: 103941. https://doi.org/10.1016/j.tourman.2019.06.016
Kusi-Sarpong, S.; Gupta, H.; Sarkis, J. 2019. A supply chain sustainability innovation framework and evaluation methodology, International Journal of Production Research 57(7): 1990–2008. https://doi.org/10.1080/00207543.2018.1518607
Leal Filho, W.; Platje, J.; Gerstlberger, W.; Ciegis, R.; Kääriä, J.; Klavins, M.; Kliucininkas, L. 2016. The role of governance in realising the transition towards sustainable societies, Journal of Cleaner Production 113: 755–766. https://doi.org/10.1016/j.jclepro.2015.11.060
Liao, H.; Mi, X.; Yu, Q.; Luo, L. 2019. Hospital performance evaluation by a hesitant fuzzy linguistic best worst method with inconsistency repairing, Journal of Cleaner Production 232: 657–671. https://doi.org/10.1016/j.jclepro.2019.05.308
Lin, C.-C.; Chang, C.-H. 2018. Evaluating skill requirement for logistics operation practitioners: based on the perceptions of logistics service providers and academics in Taiwan, The Asian Journal of Shipping and Logistics 34(4): 328–336. https://doi.org/10.1016/j.ajsl.2018.12.006
Lin, Y.-H.; Tseng, M.-L. 2016. Assessing the competitive priorities within sustainable supply chain management under uncertainty, Journal of Cleaner Production 112: 2133–2144. https://doi.org/10.1016/j.jclepro.2014.07.012
Liu, A.; Xiao, Y.; Ji, X.; Wang, K.; Tsai, S.-B.; Lu, H.; Cheng, J.; Lai, X.; Wang, J. 2018a. A novel two-stage integrated model for supplier selection of green fresh product, Sustainability 10(7): 2371. https://doi.org/10.3390/su10072371
Liu, J.; Yuan, C.; Hafeez, M.; Yuan, Q. 2018b. The relationship between environment and logistics performance: evidence from Asian countries, Journal of Cleaner Production 204: 282–291. https://doi.org/10.1016/j.jclepro.2018.08.310
Liu, S.; Zhang, G.; Wang, L. 2018c. IoT-enabled dynamic optimisation for sustainable reverse logistics, Procedia CIRP 69: 662–667. https://doi.org/10.1016/j.procir.2017.11.088
Luthra, S.; Govindan, K.; Kannan, D.; Mangla, S. K.; Garg, C. P. 2017. An integrated framework for sustainable supplier selection and evaluation in supply chains, Journal of Cleaner Production 140: 1686–1698. https://doi.org/10.1016/j.jclepro.2016.09.078
Mafakheri, F.; Breton, M.; Ghoniem, A. 2011. Supplier selection-order allocation: A two-stage multiple criteria dynamic programming approach, International Journal of Production Economics 132(1): 52–57. https://doi.org/10.1016/j.ijpe.2011.03.005
Malek, J.; Desai, T. N. 2019. Prioritization of sustainable manufacturing barriers using best worst method, Journal of Cleaner Production 226: 589–600. https://doi.org/10.1016/j.jclepro.2019.04.056
Manzardo, A.; Ren, J.; Mazzi, A.; Scipioni, A. 2012. A grey-based group decision-making methodology for the selection of hydrogen technologies in life cycle sustainability perspective, International Journal of Hydrogen Energy 37(23): 17663–17670. https://doi.org/10.1016/j.ijhydene.2012.08.137
Mohammadi, M.; Rezaei, J. 2020. Bayesian best-worst method: a probabilistic group decision making model, Omega 96: 102075. https://doi.org/10.1016/j.omega.2019.06.001
Mohanty, M.; Shankar, R. 2017. Modelling uncertainty in sustainable integrated logistics using fuzzy-TISM, Transportation Research Part D: Transport and Environment 53: 471–491. https://doi.org/10.1016/j.trd.2017.04.034
Moldan, B.; Janoušková, S.; Hák, T. 2012. How to understand and measure environmental sustainability: Indicators and targets, Ecological Indicators 17: 4–13. https://doi.org/10.1016/j.ecolind.2011.04.033
Mulky, A. G. 2013. Distribution challenges and workable solutions, IIMB Management Review 25(3): 136. https://doi.org/10.1016/j.iimb.2013.06.010
Murphy, P. R.; Poist, R. F.; Braunschweig, C. D. 1996. Green logistics: comparative views of environmental progressives, moderates, and conservatives, Journal of Business Logistics 17(1): 191–212.
Narayana, S. A.; Pati, R. K.; Padhi, S. S. 2019. Market dynamics and reverse logistics for sustainability in the Indian pharmaceuticals industry, Journal of Cleaner Production 208: 968–987. https://doi.org/10.1016/j.jclepro.2018.10.171
Nawaz, F.; Asadabadi, M. R.; Janjua, N. K.; Hussain, O. K.; Chang, E.; Saberi, M. 2018. An MCDM method for cloud service selection using a Markov chain and the best-worst method, Knowledge-Based Systems 159: 120–131. https://doi.org/10.1016/j.knosys.2018.06.010
Nayak, R.; Akbari, M.; Maleki Far, S. 2019. Recent sustainable trends in Vietnam’s fashion supply chain, Journal of Cleaner Production 225: 291–303. https://doi.org/10.1016/j.jclepro.2019.03.239
Novack, R. A. 1984. Transportation standard cost budgeting, in NCPDM: National Council of Physical Distribution Management – Fall Meeting: 22 Annual Conference, 16–19 September 1984, Dallas, TX, US, 309–320.
Pamučar, D.; Gigović, L.; Bajić, Z.; Janošević, M. 2017. Location selection for wind farms using GIS multi-criteria hybrid model: an approach based on fuzzy and rough numbers, Sustainability 9(8): 1315. https://doi.org/10.3390/su9081315
Punniyamoorthy, M.; Mathiyalagan, P.; Parthiban, P. 2011. A strategic model using structural equation modeling and fuzzy logic in supplier selection, Expert Systems with Applications 38(1): 458–474. https://doi.org/10.1016/j.eswa.2010.06.086
Puška, A.; Maksimović, A.; Stojanović, I. 2018. Improving organizational learning by sharing information through innovative supply chain in agro-food companies from Bosnia and Herzegovina, Operational Research in Engineering Sciences: Theory and Applications 1(1):76–90.
Quarshie, A. M.; Salmi, A.; Leuschner, R. 2016. Sustainability and corporate social responsibility in supply chains: the state of research in supply chain management and business ethics journals, Journal of Purchasing and Supply Management 22(2): 82–97. https://doi.org/10.1016/j.pursup.2015.11.001
Rashidi, K.; Cullinane, K. 2019. Evaluating the sustainability of national logistics performance using data envelopment analysis, Transport Policy 74: 35–46. https://doi.org/10.1016/j.tranpol.2018.11.014
Ren, J.; Tan, S.; Goodsite, M. E.; Sovacool, B. K.; Dong, L. 2015. Sustainability, shale gas, and energy transition in China: Assessing barriers and prioritizing strategic measures, Energy 84: 551–562. https://doi.org/10.1016/j.energy.2015.03.020
Rezaei, J. 2015. Best-worst multi-criteria decision-making method, Omega 53: 49–57. https://doi.org/10.1016/j.omega.2014.11.009
Rezaei, J.; Nispeling, T.; Sarkis, J.; Tavasszy, L. 2016. A supplier selection life cycle approach integrating traditional and environmental criteria using the best worst method, Journal of Cleaner Production 135: 577–588. https://doi.org/10.1016/j.jclepro.2016.06.125
Sabah, S. 2017. The impact of self-construal and self-concept clarity on socially motivated consumption: The moderating role of materialism, Journal of Global Scholars of Marketing Science 27(1): 31–45. https://doi.org/10.1080/21639159.2016.1265321
Shankar, R.; Gupta, R.; Pathak, D.K. 2018. Modeling critical success factors of traceability for food logistics system, Transportation Research Part E: Logistics and Transportation Review 119: 205–222. https://doi.org/10.1016/j.tre.2018.03.006
Simchi-Levi, D.; Kaminsky, P.; Simchi-Levi, E. R. 2021. Designing and Managing the Supply Chain: Concepts, Strategies and Case Studies. 4th edition. McGraw-Hill Higher Education. 1101 p.
Speranza, M. G. 2018. Trends in transportation and logistics, European Journal of Operational Research 264(3): 830–836. https://doi.org/10.1016/j.ejor.2016.08.032
Stević, Ž.; Pamučar, D.; Subotić, M.; Antuchevičienė, J.; Zavadskas, E. K. 2018. The location selection for roundabout construction using rough BWM-rough WASPAS approach based on a new rough hamy aggregator, Sustainability 10(8): 2817. https://doi.org/10.3390/su10082817
Stević, Ž.; Pamučar, D.; Zavadskas, E. K.; Ćirović, G.; Prentkovskis, O. 2017. The selection of wagons for the internal transport of a logistics company: a novel approach based on rough BWM and rough SAW methods, Symmetry 9(11): 264. https://doi.org/10.3390/sym9110264
Su, C.-M.; Horng, D.-J.; Tseng, M.-L.; Chiu, A. S. F.; Wu, K.-J.; Chen, H.-P. 2016. Improving sustainable supply chain management using a novel hierarchical grey-DEMATEL approach, Journal of Cleaner Production 134: 469–481. https://doi.org/10.1016/j.jclepro.2015.05.080
Sueyoshi, T.; Wang, D. 2014. Sustainability development for supply chain management in U.S. petroleum industry by DEA environmental assessment, Energy Economics 46: 360–374. https://doi.org/10.1016/j.eneco.2014.09.022
Suhi, S. A.; Enayet, R.; Haque, T.; Ali, S. M.; Moktadir, M. A.; Paul, S. K. 2019. Environmental sustainability assessment in supply chain: an emerging economy context, Environmental Impact Assessment Review 79: 106306. https://doi.org/10.1016/j.eiar.2019.106306
Tavasszy, L.; De Bok, M.; Alimoradi, Z.; Rezaei, J. 2020. Logistics decisions in descriptive freight transportation models: a review, Journal of Supply Chain Management Science 1(3–4): 74–86. https://doi.org/10.18757/jscms.2020.1992
Tseng, M.-L.; Chiu, A. S. F. 2013. Evaluating firm’s green supply chain management in linguistic preferences, Journal of Cleaner Production 40: 22–31. https://doi.org/10.1016/j.jclepro.2010.08.007
Turnheim, B.; Berkhout, F.; Geels, F.; Hof, A.; McMeekin, A.; Nykvist, B.; Van Vuuren, D. 2015. Evaluating sustainability transitions pathways: Bridging analytical approaches to address governance challenges, Global Environmental Change 35: 239–253. https://doi.org/10.1016/j.gloenvcha.2015.08.010
Vachon, S. 2007. Green supply chain practices and the selection of environmental technologies, International Journal of Production Research 45(18–19): 4357–4379. https://doi.org/10.1080/00207540701440303
Validi, S.; Bhattacharya, A.; Byrne, P. J. 2014. A case analysis of a sustainable food supply chain distribution system – a multi-objective approach, International Journal of Production Economics 152: 71–87. https://doi.org/10.1016/j.ijpe.2014.02.003
Walton, S. V.; Handfield, R. B.; Melnyk, S. A. 1998. The green supply chain: integrating suppliers into environmental management processes, International Journal of Purchasing and Materials Management 34(1): 2–11. https://doi.org/10.1111/j.1745-493X.1998.tb00042.x
Wang, H.; Liu, H.; Kim, S. J.; Kim, K. H. 2019. Sustainable fashion index model and its implication, Journal of Business Research 99: 430–437. https://doi.org/10.1016/j.jbusres.2017.12.027
Wong, C. Y.; Wong, C. W.; Boon-Itt, S. 2015. Integrating environmental management into supply chains: a systematic literature review and theoretical framework, International Journal of Physical Distribution & Logistics Management 45(1/2): 43–68. https://doi.org/10.1108/IJPDLM-05-2013-0110
Yousefi, S.; Shabanpour, H.; Fisher, R.; Saen, R. F. 2016. Evaluating and ranking sustainable suppliers by robust dynamic data envelopment analysis, Measurement 83: 72–85. https://doi.org/10.1016/j.measurement.2016.01.032
Yu, H.; Solvang, W. D. 2018. Incorporating flexible capacity in the planning of a multi-product multi-echelon sustainable reverse logistics network under uncertainty, Journal of Cleaner Production 198: 285–303. https://doi.org/10.1016/j.jclepro.2018.07.019
Zavadskas, E. K.; Stević, Ž.; Tanackov, I.; Prentkovskis, O. 2018. A novel multicriteria approach – rough step-wise weight assessment ratio analysis method (R-SWARA) and its application in logistics, Studies in Informatics and Control 27(1): 97–106. https://doi.org/10.24846/v27i1y201810
Zhu, Q.; Sarkis, J.; Lai, K.-H. 2008. Confirmation of a measurement model for green supply chain management practices implementation, International Journal of Production Economics 111(2): 261–273. https://doi.org/10.1016/j.ijpe.2006.11.029