Due to the COVID-19 pandemic, every country faces numerous issues, and seemingly inadequate treatment of medical waste (MW) is one of them. If proper measurements are not taken about MW, then it will have hazardous effects on the environment and nature. In this study, we identified significant barriers to integrating blockchain (BC) and big data (BD) to manage MW and analyze their interrelationship effectively. This study was designed in three parts: Identifying barriers through a literature review, past studies, and expert judgments; and analyzing barriers and their impact using a hybrid approach, including Interpretive Structural Modeling (ISM), MICMAC, and the Analytic Hierarchy Process (AHP). In this study, 10 factors were mined from the literature review, and five were taken from experts' opinions, which influenced the adoption of BC and BD for managing medical waste management (MWM) in metropolitan city hospitals. The results from ISM-MICMAC indicated that the key barriers were: Insufficient resources, lack of management rules and policies, lack of technical infrastructures, and lack of skilled workforce. These were more most formidable challenges for the adoption of BDBC-MWM in the Pakistan medical industry, and the same as the results from AHP showed that the significant barriers and most formidable challenge for the adoption of BDBC-MWM were: Lack of research and development units, lack of training and education of staff, lack of management support, lack of rules, regulations, and policies, lack of international cooperation, and inadequate technological infrastructure.
Citation: Muhammad Ismail, Zhongdong Xiao, Abdul Waheed, Asifa Iqbal, El-Sayed M. El-Kenawy, Amel Ali Alhussan, Marwa M. Eid, Doaa Sami Khafaga. Sustainable medical waste management through blockchain technology and big data: A structural analysis and modeling of barriers using the ISM-MICMAC and AHP approach[J]. Journal of Industrial and Management Optimization, 2026, 22(1): 336-373. doi: 10.3934/jimo.2026013
Due to the COVID-19 pandemic, every country faces numerous issues, and seemingly inadequate treatment of medical waste (MW) is one of them. If proper measurements are not taken about MW, then it will have hazardous effects on the environment and nature. In this study, we identified significant barriers to integrating blockchain (BC) and big data (BD) to manage MW and analyze their interrelationship effectively. This study was designed in three parts: Identifying barriers through a literature review, past studies, and expert judgments; and analyzing barriers and their impact using a hybrid approach, including Interpretive Structural Modeling (ISM), MICMAC, and the Analytic Hierarchy Process (AHP). In this study, 10 factors were mined from the literature review, and five were taken from experts' opinions, which influenced the adoption of BC and BD for managing medical waste management (MWM) in metropolitan city hospitals. The results from ISM-MICMAC indicated that the key barriers were: Insufficient resources, lack of management rules and policies, lack of technical infrastructures, and lack of skilled workforce. These were more most formidable challenges for the adoption of BDBC-MWM in the Pakistan medical industry, and the same as the results from AHP showed that the significant barriers and most formidable challenge for the adoption of BDBC-MWM were: Lack of research and development units, lack of training and education of staff, lack of management support, lack of rules, regulations, and policies, lack of international cooperation, and inadequate technological infrastructure.
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Figures(10) / Tables(16)
Muhammad Ismail, Zhongdong Xiao, Abdul Waheed, Asifa Iqbal, El-Sayed M. El-Kenawy, Amel Ali Alhussan, Marwa M. Eid, Doaa Sami Khafaga. Sustainable medical waste management through blockchain technology and big data: A structural analysis and modeling of barriers using the ISM-MICMAC and AHP approach[J]. Journal of Industrial and Management Optimization, 2026, 22(1): 336-373. doi: 10.3934/jimo.2026013
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