Designing a Model of Barriers to the Implementation of the 4th Generation Industry in the Health Care Sector with a Fuzzy Total Interpretative Structural Modeling Approach
Subject Areas : Health Management Services
esmaeil MazrouiNasrabadi
1
(Assistant professor, department of business administration, faculty of financial science, management and entrepreneurship, university of Kashan, Kashan, Iran)
Zahra Kheirkhah Maraghi
2
(Master graduate, department of business administration, faculty of financial science, management and entrepreneurship, university of Kashan, Kashan, Iran)
Keywords: Interpretive Structural Modeling, Industry 4.0, Healthcare 4.0, Barriers,
Abstract :
Introduction: The extensive advantages of the 4th generation of industry led to the entry of these technologies into the healthcare sector. Many countries have been able to create many competitive advantages by successfully implementing Healthcare 4.0. In Iran, the fourth generation of health care has not yet been properly investigated and implemented. Identifying implementation barriers and relationships between them can help decision makers in making appropriate decisions to facilitate Healthcare 4.0 implementing. This research was done with the aim of identifying these barriers and analyzing and relationship between them. Methods: This research was done in 2 stages. In the first stage, using semi-structured interviews with experts and the use of thematic analysis, barriers were identified, and in the second stage, using a researcher-made questionnaire and the method of fuzzy total interpretative structural modeling, a causal model of relationships between barriers was designed to identify the most fundamental barriers. The method of sampling in both stages was judgment and snowball and the sample size in them is 16 and 10 people, respectively. Results: The results of interviews with experts led to the identification of 44 main barriers, which are divided into 7 categories: " barriers due to sanctions", "Financial and economic barriers", "Hardware and software barriers", "Cooperation barriers", "competitive barriers", "management barriers" and "human resource barriers" were categorized. The modeling results showed that "barriers caused by sanctions", "competitive barriers" and "human resource barriers" are respectively the most important barriers and should be given special attention in policy making. Conclusion: The results of the research presented a new perspective on the barriers to healthcare 4.0. This perspective is about barriers related to sanctions and competitive issues. As a result, it is recommended to facilitate international communication, train decision-making and problem-solving skills, and develop knowledge-based activities to remove sanctions barriers. Also, facilitating public-private partnership and facilitating the presence of international companies in the field of healthcare can help increase competition.
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24- Horváth D & Szabó R. Z. Driving forces and barriers of Industry 4.0: Do multinational and small and medium-sized companies have equal opportunities? Technological forecasting and social change, 2019; 146: 119-132.
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27- Kamble S. S, Gunasekaran A & Sharma, R. Analysis of the driving and dependence power of barriers to adopt industry 4.0 in Indian manufacturing industry. Computers in Industry, 2018; 101: 107-119.
28- Senna P. P, Ferreira L. M. D, Barros A. C, Roca J. B & Magalhães V. Prioritizing barriers for the adoption of Industry 4.0 technologies. Computers & Industrial Engineering, 2022; 171: 108428.
29- Chauhan C, Singh, A & Luthra S. Barriers to industry 4.0 adoption and its performance implications: An empirical investigation of emerging economy. Journal of Cleaner Production, 2021; 285: 124809.
30- Kumar S, Raut R. D, Nayal K, Kraus S, Yadav V. S & Narkhede, B. E. To identify industry 4.0 and circular economy adoption barriers in the agriculture supply chain by using ISM-ANP. Journal of Cleaner Production, 201; 293: 126023.
_||_1- Ahsan M. M Siddique Z. Industry 4.0 in Healthcare: A systematic review. International Journal of Information Management Data Insights, 2022; 2(1): 100079.
2- Iyengar K. P, Vaishya R, Bahl S & Vaish A. Impact of the coronavirus pandemic on the supply chain in healthcare. British Journal of Healthcare Management, 2020; 26(6): 1-4.
3- Karatas M, Eriskin L, Deveci M, Pamucar D & Garg H. Big Data for Healthcare Industry 4.0: Applications, challenges and future perspectives. Expert Systems with Applications; 2022: 116912.
4- Ravi C, Tomar A & Yadav T. K. INDUSTRY 4.0: Digitalization and Sustainability Opportunities. International Research Journal of Modernization in Engineering Technology and Science, 2023; 5(1): 210-215.
5- Mwanza J, Telukdarie A & Igusa T. Impact of industry 4.0 on healthcare systems of low-and middle-income countries: a systematic review. Health and Technology; 2023: 1-18.
6- Weerasinghe W. P. T. D, Vidanagamachchi K & Nanayakkara L. D. J. F. Employee competencies development framework for industry 4.0 adaptation in the healthcare sector. In Proc. Int. Conf. Ind. Eng. Oper. Manag; 2020: 1063-1075.
7- Mustapha I, Khan N, Qureshi M. I, Harasis A. A Van N. T. Impact of industry 4.0 on healthcare: a systematic literature review (SLR) from the last decade, 2021; 15(18): 116-128.
8- Fanta G. B, Pretorius L. E. O. N Nunes B. R. E. N. O. Enabling circular economy in healthcare using industry 4.0 digital technologies. In Proceedings of the 30th International Conference of the International Association for Management of Technology, IAMOT; 2021.
9- Sood S. K, Rawat K. S Kumar D. A visual review of artificial intelligence and Industry 4.0 in healthcare. Computers and Electrical Engineering, 2022; 101: 107948.
10- Ow J. The Future of Healthcare in Singapore. The Challenges and Benefits of Integrated Use of Industry 4.0 Technologies and How Likely the General Public and Institutions Are to Adopt the Integration of Industry 4.0 Technologies. Available at SSRN 3957676; 2021.
11- Kotzias K, Bukhsh F. A, Arachchige J. J, Daneva M Abhishta, A. Industry 4.0 and healthcare: Context, applications, benefits and challenges. IET Software; 2022:1-54.
12- Machado C. G, Winroth M, Carlsson D, Almström P, Centerholt V & Hallin, M. Industry 4.0 readiness in manufacturing companies: challenges and enablers towards increased digitalization. Procedia Cirp, 2019; 81: 1113-1118.
13- Attiany M, Al-kharabsheh S, Abed-Qader M, Al-Hawary S, Mohammad A & Rahamneh, A. Barriers to adopt industry 4.0 in supply chains using interpretive structural modeling. Uncertain Supply Chain Management, 2023; 11(1): 299-306.
14- Govindan K & Arampatzis, G. A framework to measure readiness and barriers for the implementation of Industry 4.0: A case approach. Electronic Commerce Research and Applications; 2023: 101249.
15- Ajmera P & Jain, V. Modelling the barriers of Health 4.0–the fourth healthcare industrial revolution in India by TISM. Operations Management Research, 2019; 12(3-4): 129-145.
16- Tortorella G. L, Fogliatto F. S, Espôsto K. F, Vergara A. M. C, Vassolo R, Mendoza D. T & Narayanamurthy, G. Effects of contingencies on healthcare 4.0 technologies adoption and barriers in emerging economies. Technological Forecasting and Social Change, 2020; 156: 120048.
17- Rezaeizadeh M; Ansari M & Morphi, I. A practical guide to the research method: interactive management (IM) and Interpretive Structural Modeling (ISM). Tehran: Jihad Daneshgahi Publications, first edition; 2013. [In Persian].
18- Braun Virginia & Clarke Victoria. Using Thematic Analysis in Psychology. Qualitative Research in Psychology, 2006; 3(2): 77-101.
19- Opricovic S & Tzeng G. H. Defuzzification within a multicriteria decision model. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 2003; 11(05): 635-652.
20- Wu W. W & Lee Y. T. Developing global managers’ competencies using the fuzzy DEMATEL method. Expert systems with applications, 2007; 32(2): 499-507.
21- Majumdar A, Garg H & Jain R. Managing the barriers of Industry 4.0 adoption and implementation in textile and clothing industry: Interpretive structural model and triple helix framework. Computers in Industry, 2021; 125: 103372.
22- Taqi H. M, Nur S. M, Salman S, Ahmed T, Sarker S, Ali S. M & Sankaranarayanan, B. Behavioural factors for Industry 4.0 adoption: implications for knowledge-based supply chains. Operations Management Research; 2023: 1-18.
23- Virmani N, Sharma S, Kumar A & Luthra, S. Adoption of industry 4.0 evidence in emerging economy: Behavioral reasoning theory perspective. Technological Forecasting and Social Change, 2023; 188: 122317.
24- Horváth D & Szabó R. Z. Driving forces and barriers of Industry 4.0: Do multinational and small and medium-sized companies have equal opportunities? Technological forecasting and social change, 2019; 146: 119-132.
25- Cugno M, Castagnoli R & Büchi G. Openness to Industry 4.0 and performance: The impact of barriers and incentives. Technological Forecasting and Social Change, 2021; 168: 120756.
26- Raj A, Dwivedi G, Sharma A, de Sousa Jabbour A. B. L & Rajak, S. Barriers to the adoption of industry 4.0 technologies in the manufacturing sector: An inter-country comparative perspective. International Journal of Production Economics, 2020; 224: 107546.
27- Kamble S. S, Gunasekaran A & Sharma, R. Analysis of the driving and dependence power of barriers to adopt industry 4.0 in Indian manufacturing industry. Computers in Industry, 2018; 101: 107-119.
28- Senna P. P, Ferreira L. M. D, Barros A. C, Roca J. B & Magalhães V. Prioritizing barriers for the adoption of Industry 4.0 technologies. Computers & Industrial Engineering, 2022; 171: 108428.
29- Chauhan C, Singh, A & Luthra S. Barriers to industry 4.0 adoption and its performance implications: An empirical investigation of emerging economy. Journal of Cleaner Production, 2021; 285: 124809.
30- Kumar S, Raut R. D, Nayal K, Kraus S, Yadav V. S & Narkhede, B. E. To identify industry 4.0 and circular economy adoption barriers in the agriculture supply chain by using ISM-ANP. Journal of Cleaner Production, 201; 293: 126023.