Driving Factors of Remanufacturing Adoption for Diagnostic Radiology Medical Devices in Thailand
Article Sidebar
Main Article Content
Abstract
Remanufacturing medical devices has become a key strategy for improving resource efficiency, lowering healthcare costs, and promoting a circular economy. Despite this, the integration of remanufactured medical devices into healthcare systems faces obstacles, primarily due to stakeholder acceptance issues. This study aims to create and validate a structural model that explains the factors influencing the adoption of remanufactured diagnostic radiology medical devices in Thailand. The model being studied includes several factors, such as economic considerations, cost, environmental policy, environmental friendliness, attitude, social influence, facilitating conditions, regulatory aspects, quality, and information. Data were collected from a group of 400 experts and professionals involved in medical device management and then analyzed using Structural Equation Modeling (SEM). The findings reveal that the majority of the examined factors—including attitude, cost considerations, economic influences, governmental policy, environmental sustainability, social influence, quality, and information availability—exhibited statistically significant correlations with the adoption of medical devices. Conversely, the impact of enabling conditions and regulatory elements was found to be negligible. The model demonstrated a substantial capacity to elucidate the data, explaining 69.5% of the observed variance in adoption behavior (R² = 0.695). This study contributes to the existing body of knowledge by offering empirical evidence regarding the key determinants that shape the adoption of remanufacturing practices in the medical device sector. Furthermore, the findings provide actionable and policy-relevant recommendations for stakeholders, including policymakers, manufacturers, and healthcare administrators, thus supporting the enduring incorporation of remanufactured medical devices within Thailand's healthcare system.
Downloads
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
References
[1] Office of Industrial Economics. Action Plan for the Development of the Medical Device Industry, Phase 1 (2023–2027); Office of Industrial Economics: Bangkok, 2023.
[2] Global Wellness Institute. 2025 Global Wellness Economy Monitor; Global Wellness Institute, 2025. https://globalwellnessinstitute.org/industry-research/2025-global-wellness-economy-monitor/.
[3] Yardi, S. Medical Imaging Statistics: Key Facts and Global Market Insights; Market.us, January 14, 2025. https://media.market.us/medical-imaging-statistics/.
[4] Goodall, P.; Rosamond, E.; Harding, J. A Review of the State of the Art in Tools and Techniques Used to Evaluate Remanufacturing Feasibility. J. Cleaner Prod. 2014, 81, 1–15. https://doi.org/10.1016/j.jclepro.2014.06.014
[5] Eze, S.; Ijomah, W.; Wong, T. Accessing Medical Equipment in Developing Countries through Remanufacturing. J. Remanuf. 2019, 9(3), 207–233. https://doi.org/10.1007/s13243-018-0065-7
[6] Ministry of Public Health. Ministerial Regulation on Safety Standards for Diagnostic Medical Radiation Generators Required to Be Notified for Possession or Use, B.E. 2566 (2023). Royal Thai Government Gazette 2023, 140, Section 53 Kor, 31–36.
[7] International Electrotechnical Commission. IEC 63077:2019 Good Refurbishment Practices for Medical Imaging Equipment; International Electrotechnical Commission, 2019.
[8] Rogers, E. M. Diffusion of Innovations, 5th ed.; Free Press: New York, 2003.
[9] Worsøe Andersen, A.; Fritze Jørgensen, S.; Gunn, W.; Niero, M. Remanufacturing as a Circular Design Strategy in Healthcare: Integrating Socio-Technical and Environmental Economic Assessments. In Proceedings of DESIGN 2024; Vol. 4; Cambridge University Press, 2024; pp 1179–1188. https://doi.org/10.1017/pds.2024.120
[10] Greenhalgh, T.; Robert, G.; Macfarlane, F.; Bate, P.; Kyriakidou, O. Diffusion of Innovations in Service Organizations: Systematic Review and Recommendations. Soc. Sci. Med. 2004, 58 (9), 1733–1744. https://doi.org/10.1016/j.socscimed.2004.03.027
[11] Ijomah, W. L.; McMahon, C. A.; Hammond, G. P.; Newman, S. T. Development of Robust Design-for-Remanufacturing Guidelines to Support Sustainable Manufacturing. Robot. Comput.-Integr. Manuf. 2007, 23(6), 712–719. https://doi.org/10.1016/j.rcim.2007.02.017
[12] Vasantha, G. A.; Acur, N.; Corney, J. Assessment of Rural Digital Imaging and Creativity Abilities for Potential Crowdsourcing Case; University of Strathclyde: Glasgow, U.K., 2015.
[13] Meister, J. A.; Sharp, J.; Wang, Y.; Nguyen, K. A. Assessing Long-Term Medical Remanufacturing Emissions with Life Cycle Analysis. Processes 2023, 11 (1), 36. https://doi.org/10.3390/pr11010036
[14] Ministry of Public Health. Notification of the Ministry of Public Health: Designation of Radiological Equipment, B.E. 2549 (2006). Royal Thai Government Gazette 2006, 123, Special Issue 100 Ng, September 28, 2006.
[15] Disnivet, K. Radiological Equipment; Radiological Society of Thailand, n.d. https://www.radiologythailand.org/th/เครื่องมือทางรังสีวิทยา/.
[16] Shang, Y.; Li, S. Hybrid Combinatorial Remanufacturing Strategy for Medical Equipment in the Pandemic. Comput. Ind. Eng. 2022, 174, 108811. https://doi.org/10.1016/j.cie.2022.108811
[17] European Remanufacturing Network. About Remanufacturing; European Remanufacturing Network, n.d. https://www.remanufacturing.eu/about-remanufacturing.php.
[18] European Parliament; Council of the European Union. Regulation (EU) 2017/745 of the European Parliament and of the Council of 5 April 2017 on Medical Devices; Official Journal of the European Union, 2017.
[19] U.S. Food and Drug Administration. Quality System Regulation (21 CFR Part 820); U.S. Food and Drug Administration, 2020. https://www.fda.gov/medical-devices/quality-system-qs-regulation-medical-device-good-manufacturing-practices.
[20] Paul, M.; Eickholt, D.; Reinhart, G. Framework for Adaptable Remanufacturing. Prod. Manuf. Res. 2024, 12(1), 2362692. https://doi.org/10.1080/21693277.2024.2362692
[21] Zhang, X.; Yu, P.; Yan, J.; Spil, T. A. M. Using Diffusion of Innovation Theory to Understand the Factors Impacting Patient Acceptance and Use of Consumer E-Health Innovations: A Case Study in a Primary Care Clinic. BMC Health Serv. Res. 2015, 15, 71. https://doi.org/10.1186/s12913-015-0726-2
[22] Damar, S.; Koksalmis, G. H. Integrating Metaverse Technologies in Medical Education: Examining Acceptance Factors among Healthcare Providers; arXiv, 2025. https://arxiv.org/abs/2510.16984
[23] Davis, F. D. Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Q. 1989, 13 (3), 319–340. https://doi.org/10.2307/249008
[24] Tripathy, S.; Srivastava, S. Acceptance of Remanufactured Products in the Circular Economy: An Empirical Study. Manage. Decis. 2019, 57 (4), 953–970. https://doi.org/10.1108/MD-06-2018-0686
[25] Duberg, J. V.; Sundin, E.; Tang, O. Assessing the Profitability of Remanufacturing Initiation: A Literature Review. J. Remanuf. 2024, 14(1), 69–92. https://doi.org/10.1007/s13243-023-00132-1
[26] Boorsma, N.; Peck, D.; Bakker, T.; Bakker, C.; Balkenende, R. The Strategic Value of Design for Remanufacturing: A Case Study of Professional Imaging Equipment. J. Remanuf. 2022, 12, 187–212. https://doi.org/10.1007/s13243-021-00107-0
[27] Bansal, M.; Sharma, M.; Singh, S. A Methodological Approach for Estimating and Analysing Remanufacturing Cost-Effectiveness. Am. J. Math. Manage. Sci. 2022, 41(1), 25–42. https://doi.org/10.1080/01966324.2022.2030367
[28] Oturu, K.; Ijomah, W. L.; Broeksmit, A.; Hernandez Reig, D.; Millar, M.; Peacock, C.; Rodger, J. Investigation of Remanufacturing Technologies for Medical Equipment in the UK and Context in Which Technology Can Be Exported in the Developing World. J. Remanuf. 2021, 11, 227–242.
[29] Alyahya, S.; Wang, Y.; Bennett, D. A Sustainable Step Forward: Understanding Factors Affecting Customers’ Behaviour to Purchase Remanufactured Products. Sustainability 2023, 15(3), 2301. https://doi.org/10.3390/su15032301
[30] Eze, S.; Ijomah, W.; Wong, T. C. Remanufacturing: A Potential Sustainable Solution for Increasing Medical Equipment Availability. J. Remanuf. 2020, 10, 141–159. https://doi.org/10.1007/s13243-020-00080-0
[31] Yamane, T. Statistics: An Introductory Analysis, 2nd ed.; Harper & Row, 1967.
[32] Hair, J. F.; Hult, G. T. M.; Ringle, C. M.; Sarstedt, M. A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM), 2nd ed.; Sage Publications, 2017.
[33] Hu, L.; Bentler, P. M. Cutoff Criteria for Fit Indexes in Covariance Structure Analysis: Conventional Criteria versus New Alternatives. Struct. Equ. Modeling 1999, 6(1), 1–55. https://doi.org/10.1080/10705519909540118
[34] Hair, J. F.; Ringle, C. M.; Sarstedt, M. PLS-SEM: Indeed a Silver Bullet. J. Mark. Theory Pract. 2011, 19(2), 139–152. https://doi.org/10.2753/MTP1069-6679190202
[35] Hair, J. F., Jr.; Matthews, L. M.; Matthews, R. L.; Sarstedt, M. PLS-SEM or CB-SEM: Updated Guidelines on Which Method to Use. Int. J. Multivar. Data Anal. 2017, 1(2), 107–123. https://doi.org/10.1504/IJMDA.2017.087624
[36] Kline, R. B. Principles and Practice of Structural Equation Modeling, 4th ed.; Guilford Press, 2015.
[37] Cronbach, L. J. Essentials of Psychological Testing, 3rd ed.; Harper & Row, 1970.
[38] Hair, J. F., Jr.; Hult, G. T. M.; Ringle, C. M.; Sarstedt, M.; Danks, N. P.; Ray, S. Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R: A Workbook; Springer, 2021. https://doi.org/10.1007/978-3-030-80519-7
[39] Fornell, C.; Larcker, D. F. Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. J. Mark. Res. 1981, 18(1), 39–50. https://doi.org/10.1177/002224378101800104
[40] Efron, B.; Tibshirani, R. J. An Introduction to the Bootstrap; Monographs on Statistics and Applied Probability, Vol. 57; Chapman & Hall, 1993. https://doi.org/10.1007/978-1-4899-4541-9
[41] Hair, J. F., Jr.; Sarstedt, M.; Hopkins, L.; Kuppelwieser, V. G. Partial Least Squares Structural Equation Modeling (PLS-SEM): An Emerging Tool in Business Research. Eur. Bus. Rev. 2014, 26(2), 106–121. https://doi.org/10.1108/EBR-10-2013-0128