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Best–worst method to prioritize indicators effective in making logistics systems more sustainable in fast-moving consumer goods industry in developing countries

    Mahsa Pishdar Affiliation
    ; Fatemeh Ghasemzadeh Affiliation
    ; Jurgita Antuchevičienė Affiliation

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
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Aug 22, 2022
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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