Greening the pillars of pharmaceuticals: Sustainable supplier selection in emerging economies

Abstract: The pharmaceutical industry is vital for global health, supplying necessary medicines, yet its conventional supply chain has notable environmental and social impacts. Amid a growing sustainability focus across sectors, the pharmaceutical industry must also adopt sustainable practices throughout its supply chain. This includes lessening its ecological impact, curbing waste, and endorsing social responsibility. Assessing a supplier's environmental performance, or "green performance," is of great interest. This involves gauging their eco-friendly actions like energy efficiency, waste management, and carbon footprint reduction. Metrics cover certifications, resource conservation, and responsible sourcing. In a study within a renowned Bangladeshi pharmaceutical firm, a key drugs manufacturer, seven criteria were used to evaluate suppliers' green performance. For this multi-criteria decision-making (MCDM) task, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) was applied, considering a fuzzy environment. It ranked alternative suppliers via a widely used approach using linguistic terms expressed as Triangular Fuzzy Numbers (TFN). Important weights were determined via the Center of Area (COA) method. The study revealed supplier 4 as the top performer in green performance among five alternatives. This study introduces an innovative strategy for manufacturing decision-makers to choose the most suitable green supplier. It's anticipated to aid decision-makers in emerging economy pharmaceutical industries, facilitating the efficient evaluation of economically viable and environmentally sustainable suppliers for the long term.

How to cite this paper

 Siddiquee, M., Shaha, P & Hasin, A. (2024). Greening the pillars of pharmaceuticals: Sustainable supplier selection in emerging economies.Journal of Future Sustainability, 4(3), 159-168.

Refrences

Abdel-Baset, M., Chang, V., Gamal, A., & Smarandache, F. (2019). An integrated neutrosophic ANP & VIKOR method for achieving sustainable supplier selection: A case study in importing field. Computers in Industry, 106, 94-110.
Al-Awamleh, H., Alhalalmeh, M., Alatyat, Z., Saraireh, S., Akour, I., Alneimat, S., & Al-Hawary, S. (2022). The effect of green supply chain on sustainability: Evidence from the pharmaceutical industry. Uncertain Supply Chain Man-agement, 10(4), 1261-1270.
Ashraf, S., Saleem, S., Chohan, A. H., Aslam, Z., & Raza, A. (2020). Challenging strategic trends in green supply chain management. International Journal of Resource Engineering Application Science, 5(2), 71-74.
Badi, I., & Ballem, M. (2018). Supplier selection using the rough BWM-MAIRCA model: A case study in pharmaceuti-cal supplying in Libya. Decision Making: Applications in Management & Engineering, 1(2), 16-33.
Çalık, A. (2021). A novel Pythagorean fuzzy AHP & fuzzy TOPSIS methodology for green supplier selection in the In-dustry 4.0 era. Soft Computing, 25(3), 2253-2265.
Chang, B., Chang, C.-W. & Wu, C.-H. (2011). Fuzzy DEMATEL method for developing supplier selection criteria. Ex-pert Systems with Applications, 38(3), 1850-1858.
Guo, Z., Liu, H., Zhang, D., & Yang, J. (2017). Green supplier evaluation & selection in apparel manufacturing using a fuzzy multi-criteria decision-making approach. Sustainability, 9(4), 650.
Kabir, G., & Hasin, M. A. A. (2011). Comparative analysis of AHP & fuzzy AHP models for multicriteria inventory classification. International Journal of Fuzzy Logic Systems, 1(1), 1-16.
Lee, A. H., Kang, H. Y., Hsu, C. F., & Hung, H. C. (2009). A green supplier selection model for high-tech industry. Ex-pert systems with applications, 36(4), 7917-7927.
Opricovic, S., & Tzeng, G. H. (2004). Compromise solution by MCDM methods: A comparative analysis of VIKOR & TOPSIS. European journal of operational research, 156(2), 445-455.
Pamucar, D., Torkayesh, A. E., & Biswas, S. (2022). Supplier selection in healthcare supply chain management during the COVID-19 pandemic: a novel fuzzy rough decision-making approach. Annals of Operations Research, 1-43.
Papathanasiou, J., Ploskas, N., Papathanasiou, J., & Ploskas, N. (2018). TOPSIS Multiple Criteria Decision Aid: Meth-ods, Examples and Python Implementations, 1-30.
Puška, A., & Stojanović, I. (2022). Fuzzy multi-criteria analyses on green supplier selection in an agri-food company. Journal of Intelligence Management Decisions, 1(1), 2-16.
Rahman, M. M., Bari, A. M., Ali, S. M., & Taghipour, A. (2022). Sustainable supplier selection in the textile dyeing in-dustry: An integrated multi-criteria decision analytics approach. Resources. Conservation & Recycling Advances, 15, 200117
Rashidi, K., & Cullinane, K. (2019). A comparison of fuzzy DEA & fuzzy TOPSIS in sustainable supplier selection: Im-plications for sourcing strategy. Expert Systems with Applications, 121, 266-281.
Remadi, F. D., & Frikha, H. M. (2020). The Intuitionistic Fuzzy Set FlowSort methodology for green supplier Evalua-tion. Proceedings of International Conference on Decision Aid Sciences & Application (DASA), 719-725.
Salimian, S., Mousavi, S. M., & Antucheviciene, J. (2022). An interval-valued intuitionistic fuzzy model based on extended VIKOR & MARCOS for sustainable supplier selection in organ transplantation networks for healthcare devices. Sustainability, 14(7), 3795.
Thanh, N. V., & Lan, N. T. K. (2022). Solar Energy Deployment for the Sustainable Future of Vietnam: Hybrid SWOC-FAHP-WASPAS Analysis. Energies, 15(8), 2798.
Tian, Z. P., Zhang, H. Y., Wang, J. Q., & Wang, T. L. (2018). Green supplier selection using improved TOPSIS & best-worst method under intuitionistic fuzzy environment. Informatica, 29(4),773-800.