Exploring Sustainable Smart Long-Term Care Systems Using Fuzzy Trade-Off-Aware Scoring with Conflicts Framework
Kuen-Suan Chen1,2,3, Tsai-Sung Lin4, Ruey-Chyn Tsaur4,*, Minh T. N. Nguyen5
1 Department of Industrial Engineering and Management, National Chin-Yi University of Technology, Taichung, Taiwan
2 Department of Business Administration, Chaoyang University of Technology, Taichung, Taiwan
3 Department of Business Administration, Asia University, Taichung, Taiwan
4 Department of Management Sciences, Tamkang University, New Taipei City, Taiwan
5 Faculty of Business Administration, Vietnam National University HCM, University of Economics and Law, Ho Chi Minh City, Vietnam
* Corresponding Author: Ruey-Chyn Tsaur. Email: 
Computers, Materials & Continua https://doi.org/10.32604/cmc.2026.079476
Received 22 January 2026; Accepted 28 February 2026; Published online 20 March 2026
Abstract
As artificial intelligence, the Internet of Things, edge computing, and blockchain are increasingly integrated into long-term care (LTC) services, policymakers face complex and often non-compensatory trade-offs among affordability, workforce sustainability, service reliability, and data governance. Conventional compensatory evaluation models tend to mask critical structural weaknesses and limiting their usefulness for Smart LTC policy assessment. This study proposes and applies a Fuzzy Trade-Off-Aware Scoring with Conflicts (Fuzzy TASC) framework to evaluate Smart LTC system performance. Four digital-integration configurations—conventional cloud-based LTC, AI+IoT, AI+Edge, and AI+Blockchain—were compared across 12 OECD countries. A Monte Carlo perturbation procedure was incorporated to assess the robustness and stability of country rankings under data uncertainty. The results indicate that smart technologies generally enhance LTC performance, particularly in terms of service coverage and operational efficiency. Nevertheless, these gains are unevenly distributed and accompanied by a pronounced intensification of cost–workforce trade-offs as digital complexity increases. Germany and Japan exhibit higher adaptive resilience, maintaining strong overall performance across configurations, while Estonia, Ireland, and Portugal display structural vulnerabilities that become more evident under advanced digital integration. Monte Carlo simulations confirm that these patterns are stable across a wide range of uncertainty scenarios. The findings demonstrate that the sustainability of Smart LTC systems depends not only on technological advancement but also on the capacity to manage structural trade-offs that cannot be compensated by performance gains elsewhere. The proposed Fuzzy TASC framework offers policymakers a robust, transparent tool for evaluating Smart LTC strategies, enabling more informed decisions that balance innovation, equity, and long-term system resilience.
Keywords
Smart long-term care; fuzzy trade-off-aware scoring with conflicts; structural conflict; robustness analysis; policy sandbox
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