Although the electronic health (e-health) cloud computing system is a promising innovation, its adoption in the healthcare industry has been slow. This study investigated the adoption of e-health cloud computing systems in the healthcare industry and considered security functions, management, cloud service delivery, and cloud software for e-health cloud computing systems. Although numerous studies have determined factors affecting e-health cloud computing systems, few comprehensive reviews of factors and their relations have been conducted. Therefore, this study investigated the relations between the factors affecting e-health cloud computing systems by using a multiple criteria decision-making technique, in which decision-making trial and evaluation laboratory (DEMATEL), DANP (DEMATEL-based Analytic Network Process), and modified VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje) approaches were combined. The intended level of adoption of an e-health cloud computing system could be determined by using the proposed approach. The results of a case study performed on the Taiwanese healthcare industry indicated that the cloud management function must be primarily enhanced and that cost effectiveness is the most significant factor in the adoption of e-health cloud computing. This result is valuable for allocating resources to decrease performance gaps in the Taiwanese healthcare industry.
This article analyzes dynamic asset allocation for a defi ned-contribution pension fund whose benefi ts are paid in the form of annuities when a pension fund manager takes model misspecifi cation into consideration. In this paper, model misspecifi cation is determined from the level of ambiguity in asset returns, which follows Uppal and Wang's (2003) framework. Optimal pre-retirement and post-retirement strategies under model misspecifi cation will be used to illustrate the implications of asset and liability management constraint. We conclude that lower levels of ambiguity strengthen the "lifestyle strategy" eff ect based on our numecal applications. Numerical results demonstrate that when the overall level of ambiguity for an asset return disappears, our model will reduce to the model of Devolder et al., (2003).
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