RISK ASSESSMENT FOR PHARMACEUTICAL INDUSTRY IN UNCERTAIN ENVIRONMENT: AN INTEGRATED MULTICRITERIA DECISION-MAKING APPROACH

被引:0
作者
Sharma A. [1 ]
Kumar D. [1 ]
Arora N. [1 ]
机构
[1] Department of Mechanical and Industrial Engineering, Indian Institute of Technology, Uttarakhand, Roorkee
来源
Decision Making: Applications in Management and Engineering | 2023年 / 6卷 / 02期
关键词
COVID-19; Delphi; IF-AHP; Pharmaceutical industry; Risk assessment;
D O I
10.31181/dmame622023688
中图分类号
学科分类号
摘要
The pharmaceutical industry is the backbone of the healthcare system for any country. However, this industry faces various risks, which hamper its efficient working in providing life-saving medicines/services to the people. In this context, the purpose of the study is to improve the resilience and performance of the pharmaceutical industry (PI) with identification, and assessment of supply chain (SC) risks. A case illustration has also been presented in the Indian context. The study utilizes an extensive literature survey and Delphi method for identifying, finalizing, and classifying the risks into seven categories. The Intuitionistic Fuzzy Analytic Hierarchy Process (IFAHP) has been used to analyze and prioritize the risks to determine their criticality. The results show that the three most important risks are financial, supplier, and demand/customer/market. Within these risks, the three most critical sub-risks are found to be loss of customers, raw material (RM) issues, and bad reputation of the company, respectively. The study provides managers with an extensive list of PI risks for their consideration. The results also present the critical risks which need to be mitigated for enhanced performance and resilience of the industry. The study also emphasizes the importance of interconnection between various SC partners for better risk management. © 2023 by the authors.
引用
收藏
页码:293 / 340
页数:47
相关论文
共 114 条
[71]  
Onar S. C., Oztaysi B., Otay I., Kahraman C., Multi-expert wind energy technology selection using interval-valued intuitionistic fuzzy sets, Energy, 90, pp. 274-285, (2015)
[72]  
Ortiz-Barrios M., Gul M., Yucesan M., Alfaro-Sarmiento I., Navarro-Jimenez E., Jimenez-Delgado G., A fuzzy hybrid decision-making framework for increasing the hospital disaster preparedness: The colombian case, International Journal of Disaster Risk Reduction, 72, (2022)
[73]  
Ortiz-Barrios M., Silvera-Natera E., Petrillo A., Gul M., Yucesan M., A multicriteria approach to integrating occupational safety & health performance and industry systems productivity in the context of aging workforce: A case study, Safety Science, 152, (2022)
[74]  
Otay I., Oztaysi B., Cevik Onar S., Kahraman C., Multi-expert performance evaluation of healthcare institutions using an integrated intuitionistic fuzzy AHP&DEA methodology, Knowledge-Based Systems, 133, pp. 90-106, (2017)
[75]  
Ouabouch L., Amri M., Analysing Supply Chain Risk Factors: A Probability-Impact Matrix Applied to Pharmaceutical Industry, Journal of Logistics Management, 2, 2, pp. 35-40, (2013)
[76]  
Ouyang X., Guo F., Intuitionistic fuzzy analytical hierarchical processes for selecting the paradigms of mangroves in municipal wastewater treatment, Chemosphere, 197, pp. 634-642, (2018)
[77]  
Paul S., Kabir G., Ali S. M., Zhang G., Examining transportation disruption risk in supply chains: A case study from Bangladeshi pharmaceutical industry, Research in Transportation Business & Management, 37, (2020)
[78]  
Percin S., Circular supplier selection using interval-valued intuitionistic fuzzy sets, Environment, Development and Sustainability, 24, 4, pp. 5551-5581, (2022)
[79]  
Counterfeit incidents concerning pharmaceuticals worldwide in 2019, by region* [Graph], Statista, (2020)
[80]  
Impact of the COVID-19 outbreak on digital payments, (2020)