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Resiliency in Green Supply Chains of Pharmaceuticals

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Decision Making in Healthcare Systems

Part of the book series: Studies in Systems, Decision and Control ((SSDC,volume 513))

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Abstract

The pharmaceutical industry, a vital stakeholder in the global market, places a high priority on research and development, and the COVID-19 pandemic led to concerns in April 2020 about possible disruptions in the supply chain of medicines. The pharmaceutical industry must prioritize resilient green supply chain operations in order to mitigate potential disruptions, as indicated in industrial reports. As per the literature, green supply chain management involves the incorporation of the reduce, reuse, recycle, reclaim, and degradable principle into green supply chains, beginning from manufacturing to operations and culminating with end-of-life management. Thus, the purpose of this study is to extract the concepts to achieve the green supply chain for pharmaceutical industry, and to obtain a conceptual framework via cognitive mapping process. The findings of the analysis reveal that biodiversity and corporate social responsibility together provide a basis for the green chemistry and green pharmaceutical production. In case the medical institutions adopt recycling, reverse logistics and waste management operations, a green supply chain can be achieved. Moreover, by adding the digitalization and risk management practices, finally the resiliency in green supply chain of medicine can be attained. As a result, this paper contributes to the literature by extracting the concepts to be green in pharmaceutical supply chain and by analyzing these cognitive maps for these defined concepts. As of the knowledge of the author, this is the first paper conducting a cognitive map for green pharmaceutical supply chains. In addition, practitioner can benefit from this research findings to determine the tactical and strategical plans for their institutions. Accordingly, risk management and digitalization applications plus the green pharmaceutical supply chain brings resiliency.

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References

  1. Mikulic, M.: Global Pharmaceutical Industry. Statista (2023). https://www.statista.com/topics/1764/global-pharmaceutical-industry/

  2. Mikulic, M.: COVID-19 Caused Possible Drug Supply Chain Disruptions 2020. Statista (2020). https://www.statista.com/statistics/1110180/concern-on-drug-supply-chain-disruption-due-to-covid-19/

  3. Silva, A.C., Marques, C.M., de Sousa, J.P.: A simulation approach for the design of more sustainable and resilient supply chains in the pharmaceutical industry. Sustainability 15(9), 9 (2023). https://doi.org/10.3390/su15097254

  4. Le, T.T.: The association of corporate social responsibility and sustainable consumption and production patterns: the mediating role of green supply chain management. J. Clean. Prod. 414, 137435 (2023). https://doi.org/10.1016/j.jclepro.2023.137435

    Article  Google Scholar 

  5. Karadayi-Usta, S.: A novel neutrosophical approach in stakeholder analysis for sustainable fashion supply chains. J. Fash. Market. Manag. Int. J. 27(2), 370–394 (2023). https://doi.org/10.1108/JFMM-03-2022-0044

    Article  Google Scholar 

  6. Vann Yaroson, E., Breen, L., Hou, J., Sowter, J.: The role of power-based behaviours on pharmaceutical supply chain resilience. Supply Chain Manag. Int. J. 28(4), 738–759 (2023). https://doi.org/10.1108/SCM-08-2021-0369

    Article  Google Scholar 

  7. Veleva, V.R., Cue, B.W., Todorova, S.: Benchmarking green chemistry adoption by the global pharmaceutical supply chain. ACS Sustain. Chem. Eng. 6(1), 2–14 (2018). https://doi.org/10.1021/acssuschemeng.7b02277

    Article  Google Scholar 

  8. Nyirimanzi, J.D., Ngenzi, J., Kagisha, V., Bizimana, T., Kayitare, E.: Assessment of medicines cold chain storage conformity with the requirements of the World Health Organization in health facilities of the Eastern Province of Rwanda. J. Pharm. Policy Pract. 16(1) (2023). https://doi.org/10.1186/s40545-023-00534-3

  9. Lima, P.A.B., Delgado, F.C.M., dos Santos, T.L., Florentino, A.P.: Medications reverse logistics: a systematic literature review and a method for improving the Brazilian case. Clean. Logist. Supply Chain 3, 100024 (2022). https://doi.org/10.1016/j.clscn.2021.100024

    Article  Google Scholar 

  10. Karadayi-Usta, S.: Kullanılmayan ve atik ilaçlarin tersine lojistik faaliyetleri ile toplanmasina tüketicinin bakiş açisinin değerlendirilmesi. Int. J. Adv. Eng. Pure Sci. 34(4), 4 (2022a)

    Google Scholar 

  11. Tat, R., Heydari, J.: Avoiding medicine wastes: Introducing a sustainable approach in the pharmaceutical supply chain. J. Clean. Prod. 320, 128698 (2021). https://doi.org/10.1016/j.jclepro.2021.128698

    Article  Google Scholar 

  12. Martin, N.L., Kononova, N., Cerdas, F., Herrmann, C.: LCA-based framework to support planning of centralized vs. Decentralized production of solid pharmaceuticals. Procedia CIRP 105, 128–133 (2022). https://doi.org/10.1016/j.procir.2022.02.022

    Article  Google Scholar 

  13. Khan, F., Ali, Y.: Implementation of the circular supply chain management in the pharmaceutical industry. Environ. Dev. Sustain. 24(12), 13705–13731 (2022). https://doi.org/10.1007/s10668-021-02007-6

    Article  Google Scholar 

  14. Shamkishore, L., Manmadha Reddy, K., Pathy, A.P.: Energy conservation in pharmaceutical manufacturing. Pharm. Technol. Sourc. Manag. 7(11) (2011). https://www.pharmtech.com/view/energy-conservation-pharmaceutical-manufacturing

  15. Demir, M., Min, M.: Consistencies and discrepancies in corporate social responsibility reporting in the pharmaceutical industry. Sustain. Account. Manag. Policy J. 10(2), 333–364 (2019). https://doi.org/10.1108/SAMPJ-03-2018-0094

    Article  Google Scholar 

  16. Giuliani, A., Undurraga, J.T., Dunkel, T., Aung, S.M.: Access and benefit sharing and the sustainable trade of biodiversity in Myanmar: the case of Thanakha. Sustainability (Switzerland) 13(22) (2021). https://doi.org/10.3390/su132212372

  17. Brown, L.: Nature’s Medicine: The Link Between The Pharmaceutical Industry and Biodiversity. Nature Positive (2022). https://naturepositive.com/natures-medicine-the-link-between-the-pharmaceutical-industry-and-biodiversity/

  18. Clark, J.H.: Green chemistry for the second generation biorefinery—sustainable chemical manufacturing based on biomass. J. Chem. Technol. Biotechnol. 82(7), 603–609 (2007). https://doi.org/10.1002/jctb.1710

    Article  Google Scholar 

  19. Bø, E., Hovi, I.B., Pinchasik, D.R.: COVID-19 disruptions and Norwegian food and pharmaceutical supply chains: Insights into supply chain risk management, resilience, and reliability. Sustain. Fut. 5 (2023). https://doi.org/10.1016/j.sftr.2022.100102

  20. Ding, B.: Pharma industry 4.0: literature review and research opportunities in sustainable pharmaceutical supply chains. Process Saf. Environ. Prot. 119, 115–130 (2018). https://doi.org/10.1016/j.psep.2018.06.031

    Article  Google Scholar 

  21. Babu, E.S., Kavati, I., Nayak, S.R., Ghosh, U., Al Numay, W.: Secure and transparent pharmaceutical supply chain using permissioned blockchain network. Int J Log Res Appl 1, 28 (2022). https://doi.org/10.1080/13675567.2022.2045578

  22. Ma, J.-Y., Shi, L., Kang, T.-W.: The effect of digital transformation on the pharmaceutical sustainable supply chain performance: the mediating role of information sharing and traceability using structural equation modeling. Sustainability 15(1), 1 (2023). https://doi.org/10.3390/su15010649

  23. Song, Z., He, S., Wang, Y., An, J.: Green pharmaceutical supply chain coordination considering green investment, green logistics, and government intervention. Environ. Sci. Pollut. Res. 29(42), 63321–63343 (2022). https://doi.org/10.1007/s11356-021-18275-8

    Article  Google Scholar 

  24. Santos, J.A.M., Sousa, J.M.C., Vieira, S.M., Ferreira, A.F.: Many-objective optimization of a three-echelon supply chain: a case study in the pharmaceutical industry. Comput. Ind. Eng. 173, 108729 (2022). https://doi.org/10.1016/j.cie.2022.108729

    Article  Google Scholar 

  25. Nematollahi, M., Hosseini-Motlagh, S.-M.: A collaborative decision-making model for collecting unused medications in an environmentally responsible pharmaceutical supply chain. Int. J. Environ. Sci. Technol. 19(3), 1907–1924 (2022). https://doi.org/10.1007/s13762-021-03332-z

    Article  Google Scholar 

  26. Hossain, M.K., Thakur, V.: Drivers of sustainable healthcare supply chain performance: multi-criteria decision-making approach under grey environment. Int. J. Qual. Reliab. Manag. 39(3), 859–880 (2022). https://doi.org/10.1108/IJQRM-03-2021-0075

    Article  Google Scholar 

  27. Sharma, V., Tsai, M-L., Chen, C-W., Sun, P-P., Nargotra, P., Dong, C-D.: Advances in machine learning technology for sustainable biofuel production systems in lignocellulosic biorefineries. Sci. Total Environ. 886 (2023) https://doi.org/10.1016/j.scitotenv.2023.163972

  28. Wang, H.S.-H., Yao, Y.: Machine learning for sustainable development and applications of biomass and biomass-derived carbonaceous materials in water and agricultural systems: a review. Resour. Conserv. Recycl. 190 (2023). https://doi.org/10.1016/j.resconrec.2022.106847

  29. Mawengkang, T.A.H.: An optimization model for hospitals inventory management in pharmaceutical supply chain. Syst. Rev. Pharm. 11(3), 324–332 (2020). https://doi.org/10.5530/srp.2020.3.38

  30. Harpring, R., Maghsoudi, A., Fikar, C., Piotrowicz, W.D., Heaslip, G.: An analysis of compounding factors of epidemics in complex emergencies: a system dynamics approach. J. Human. Log. Supply Chain Manag. 11(2), 198–226 (2021). https://doi.org/10.1108/JHLSCM-07-2020-0063

    Article  Google Scholar 

  31. Kress, D.H., Su, Y., Wang, H.: Assessment of primary health care system performance in Nigeria: using the primary health care performance indicator conceptual framework. Health Syst. Reform 2(4), 302–318 (2016). https://doi.org/10.1080/23288604.2016.1234861

    Article  Google Scholar 

  32. Halim, I., Ang, P., Adhitya, A.: A decision support framework and system for design of sustainable pharmaceutical supply chain network. Clean Technol. Environ. Policy 21(2), 431–446 (2019). https://doi.org/10.1007/s10098-018-1646-8

    Article  Google Scholar 

  33. Low, Y.S., Halim, I., Adhitya, A., Chew, W., Sharratt, P.: Systematic framework for design of environmentally sustainable pharmaceutical supply chain network. J. Pharm. Innov. 11(3), 250–263 (2016). https://doi.org/10.1007/s12247-016-9255-8

    Article  Google Scholar 

  34. Pastakia, S.D., Tran, D.N., Manji, I., Schellhase, E., Karwa, R., Miller, M.L., Aruasa, W., Khan, Z.M.: Framework and case study for establishing impactful global health programs through academia—biopharmaceutical industry partnerships. Res. Soc. Adm. Pharm. 16(11), 1519–1525 (2020). https://doi.org/10.1016/j.sapharm.2020.07.018

    Article  Google Scholar 

  35. Nitsche, B., Straube, F., Kämper, T-L., Zarnitz, S.: Implementation framework for blockchain-based traceability to tackle drug-counterfeiting: embracing sustainable pharma logistics networks. Lect. Notes Mech. Eng. 630–637 (2023). https://doi.org/10.1007/978-3-031-28839-5_71

  36. Swan, J.A.: Exploring knowledge and cognitions in decisions about technological innovation: mapping managerial cognitions. Hum. Relat. 48(11), 1241–1270 (1995). https://doi.org/10.1177/001872679504801101

    Article  Google Scholar 

  37. Siau, K., Tan, X.: Improving the quality of conceptual modeling using cognitive mapping techniques. Data Knowl. Eng. 55(3), 343–365 (2005). https://doi.org/10.1016/j.datak.2004.12.006

    Article  Google Scholar 

  38. Asan, U., Kadaifçi, Ç.: A new product positioning approach based on fuzzy cognitive mapping. J. Fac. Eng. Arch. Gazi University 35(2) (2020). https://doi.org/10.17341/gazimmfd.528766

  39. Rahmani, A., Lotfi, F.H., Rostamy-Malkhalifeh, M., Allahviranloo, T.: A new method for defuzzification and ranking of fuzzy numbers based on the statistical beta distribution. Adv. Fuzzy Syst. 2016, 1–8 (2016). https://doi.org/10.1155/2016/6945184

    Article  MathSciNet  Google Scholar 

  40. van Eck, N.J., Waltman, L.: VOSviewer—Visualizing Scientific Landscapes [English; VOSviewer]. Leiden University’s Centre for Science and Technology Studies (2023). https://www.vosviewer.com

  41. Seddigh, M.R., Targholizadeh, A., Shokouhyar, S., Shokoohyar, S.: Social media and expert analysis cast light on the mechanisms of underlying problems in pharmaceutical supply chain: an exploratory approach. Technol. Forecast. Soc. Chang. 191, 122533 (2023). https://doi.org/10.1016/j.techfore.2023.122533

    Article  Google Scholar 

  42. Pathy, S.R., Rahimian, H.: A resilient inventory management of pharmaceutical supply chains under demand disruption. Comput. Ind. Eng. 180, 109243 (2023). https://doi.org/10.1016/j.cie.2023.109243

    Article  Google Scholar 

  43. Wang, Z., Wang, X., Guo, J.: Research on collaborative optimization of pharmaceutical cold chain logistics inventory and distribution. In: ACM International Conference Proceeding Series, Par F180470 (2022). https://doi.org/10.1145/3529299.3530205

  44. Alhomoud, F.: “Don’t let medicines go to waste”—a survey-based cross-sectional study of pharmacists’ waste-reducing activities across gulf cooperation council countries. Front. Pharmacol. 11, 1334 (2020). https://doi.org/10.3389/fphar.2020.01334

    Article  Google Scholar 

  45. Ahmad, A., Patel, I., Khan, M.U., Babar, Z.: Pharmaceutical waste and antimicrobial resistance. Lancet. Infect. Dis. 17(6), 578–579 (2017). https://doi.org/10.1016/S1473-3099(17)30268-2

    Article  Google Scholar 

  46. Abbas, H., Farooquie, J.A.: Reverse logistics practices in Indian pharmaceutical supply chains: a study of manufacturers. Int. J. Logist. Syst. Manag. 35(1), 72–89 (2020). https://doi.org/10.1504/IJLSM.2020.103863

    Article  Google Scholar 

  47. Parashar, N., Hait, S.: Plastics in the time of COVID-19 pandemic: protector or polluter? Sci. Total Environ. 759, 144274 (2021). https://doi.org/10.1016/j.scitotenv.2020.144274

    Article  Google Scholar 

  48. Sazvar, Z., Zokaee, M., Tavakkoli-Moghaddam, R., Salari, S.A., Nayeri, S.: Designing a sustainable closed-loop pharmaceutical supply chain in a competitive market considering demand uncertainty, manufacturer’s brand and waste management. Ann. Oper. Res. 315(2), 2057–2088 (2022). https://doi.org/10.1007/s10479-021-03961-0

    Article  MathSciNet  Google Scholar 

  49. Siegert, M., Lehmann, A., Emara, Y., Finkbeiner, M.: Harmonized rules for future LCAs on pharmaceutical products and processes. Int. J. Life Cycle Assess. 24 (2019). https://doi.org/10.1007/s11367-018-1549-2

  50. Kayani, S.A., Warsi, S.S., Liaqait, R.A.: A smart decision support framework for sustainable and resilient supplier selection and order allocation in the pharmaceutical industry. Sustainability (Switzerland) 15(7) (2023). https://doi.org/10.3390/su15075962

  51. Lotfi, A., Shakouri, M., Abazari, S.R., Aghsami, A., Rabbani, M.: A multi-objective optimization for a closed-loop sustainable pharmaceutical supply chain network design: a case study. J. Adv. Manag. Res. (2023). https://doi.org/10.1108/JAMR-05-2022-0100

    Article  Google Scholar 

  52. Moosivand, A., Rangchian, M., Zarei, L., Peiravian, F., Mehralian, G., Sharifnia, H.: An application of multi-criteria decision-making approach to sustainable drug shortages management: evidence from a developing country. J. Pharm. Health Care Sci. 7(1) (2021). https://doi.org/10.1186/s40780-021-00200-3

  53. Karadayi-Usta, S.: Sustainable digital servicization: conceptual modeling of the car sharing business model. J. Yasar University 17(67), 754–775 (2022b)

    Google Scholar 

  54. Ziya-Gorabi, F., Ghodratnama, A., Tavakkoli-Moghaddam, R., Asadi-Lari, M.S.: A new fuzzy tri-objective model for a home health care problem with green ambulance routing and congestion under uncertainty. Expert Syst. Appl. 201 (2022). https://doi.org/10.1016/j.eswa.2022.117093

  55. Hosny, H., El-Henawey, I., Abo-Elhadid, S.: Selection a suitable supplier for enhancing supply chain management under neutrosophic environment. Neutrosoph. Sets Syst. 47, 332–450 (2021)

    Google Scholar 

  56. Ishizaka, A., Khan, S.A., Kheybari, S., Zaman, S.I.: Supplier selection in closed loop pharma supply chain: a novel BWM–GAIA framework. Ann. Oper. Res. 324(1–2), 13–36 (2023). https://doi.org/10.1007/s10479-022-04710-7

    Article  MathSciNet  Google Scholar 

  57. Khan, M.M., Bashar, I., Minhaj, G.M., Wasi, A.I., Hossain, N.U.I.: Resilient and sustainable supplier selection: an integration of SCOR 4.0 and machine learning approach. Sustain. Resilient Infrast. (2023). https://doi.org/10.1080/23789689.2023.2165782

  58. Taleizadeh, A.A., Haji-Sami, E., Noori-daryan, M.: A robust optimization model for coordinating pharmaceutical reverse supply chains under return strategies. Ann. Oper. Res. 291(1–2), 875–896 (2020). https://doi.org/10.1007/s10479-019-03200-7

    Article  MathSciNet  Google Scholar 

  59. Wang, S., He, L., Cheng, G.: Energy consumption optimization management mechanism based on drug green crowd data in biological pharmaceutical cloud environment. Eurasip J. Embed. Syst. 2017(1) (2017). https://doi.org/10.1186/s13639-017-0071-0

  60. Tsolakis, N., Srai, J.S.: Mapping supply dynamics in renewable feedstock enabled industries: a systems theory perspective on ‘green’ pharmaceuticals. Oper. Manag. Res. 11(3–4), 83–104 (2018). https://doi.org/10.1007/s12063-018-0134-y

    Article  Google Scholar 

  61. Nadkarni, S., Nah, F.F.-H.: Aggregated causal maps: an approach to elicit and aggregate the knowledge of multiple experts. Commun. Assoc. Inform. Syst. 12(1) (2003). https://doi.org/10.17705/1CAIS.01225

  62. Axelrod, R.: Structure of Decision: The Cognitive Maps of Political Elites. Princeton University Press (1976). https://www.jstor.org/stable/j.ctt13x0vw3

  63. Mahmoodirad, A., Allahviranloo, T., Niroomand, S.: A new effective solution method for fully intuitionistic fuzzy transportation problem. Soft Comp. 23(12), 4521–4530 (2019). https://doi.org/10.1007/s00500-018-3115-z

  64. Eden, C.: Analyzing cognitive maps to help structure issues or problems. Eur. J. Oper. Res. 159(3), 673–686 (2004). https://doi.org/10.1016/S0377-2217(03)00431-4

    Article  Google Scholar 

  65. Nakayama, V.K., Armstrong, D.J.: Causal Mapping for Research in Information Technology. Idea Group Publishing (2005)

    Google Scholar 

  66. Özesmi, U., Özesmi, S.L.: Ecological models based on people’s knowledge: a multi-step fuzzy cognitive mapping approach. Ecol. Model. 176(1), 43–64 (2004). https://doi.org/10.1016/j.ecolmodel.2003.10.027

    Article  Google Scholar 

  67. Shapiro, M.J., Bonham, G.M.: Cognitive process and foreign policy decision-making. Int. Stud. Quart. 17(2), 147–174 (1973). https://doi.org/10.2307/2600226

    Article  Google Scholar 

  68. Çoban, O., Seçme, G.: Prediction of socio-economical consequences of privatization at the firm level with fuzzy cognitive mapping. Inf. Sci. 169(1), 131–154 (2005). https://doi.org/10.1016/j.ins.2004.02.009

    Article  Google Scholar 

  69. Kandasamy, W.B.V., Smarandache, F.: Fuzzy Cognitive Maps and Neutrosophic Cognitive Maps. Xiquan, (2003)

    Google Scholar 

  70. Karadayi-Usta, S.: The role of the paper packaging industry in the circular economy: the causal relationship analysis via neutrosophic cognitive maps. In: Broumi, S. (ed.) Handbook of research on advances and applications of fuzzy sets and logic, pp. 605–618. IGI Global, Hershey, PA (2022c). https://doi.org/10.4018/978-1-7998-7979-4

  71. Emel, G.G., Saraç, M., Kabak, C.: A two-phase model for strategic decision making: activation of scenarios with cognitive maps and an application on automotive industry. Anadolu Üniversitesi Sosyal Bilimler Dergisi 12(4), 85–99 (2012)

    Google Scholar 

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Karadayi-Usta, S. (2024). Resiliency in Green Supply Chains of Pharmaceuticals. In: Allahviranloo, T., Hosseinzadeh Lotfi, F., Moghaddas, Z., Vaez-Ghasemi, M. (eds) Decision Making in Healthcare Systems. Studies in Systems, Decision and Control, vol 513. Springer, Cham. https://doi.org/10.1007/978-3-031-46735-6_14

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