a b s t r a c tSmart technologies present numerous opportunities for enhancing mobile health care. However, some concerns regarding the viability of smart technology applications must be addressed. This study investigated these concerns by reviewing the current practices of smart technology applications to mobile health care. As a result, five factors critical to the applicability of a smart technology to mobile health care are identified, and the fuzzy geometric mean-fuzzy analytic hierarchy process (FGM-FAHP) approach is proposed to assess the relative importance levels of the identified factors. The experimental results showed that the three most critical factors identified include: (a) the relaxation of the related medical laws; (b) unobtrusiveness; and (c) the precise need and situation of a user. Accordingly, approximately 44%, 26%, and 15% of the budget should be allocated to the realization of the three critical factors, respectively. In addition, the challenges involved and opportunities for enhancing the effectiveness of existing applications are discussed.

No abstract

Existing fuzzy analytic hierarchy process (FAHP) methods usually aggregate the fuzzy pairwise comparison results produced by multiple decision-makers (DMs) rather than the fuzzy weights estimations. This is problematic because fuzzy pairwise comparison results are subject to uncertainty and lack consensus. To address this problem, a partial-consensus posterior-aggregation FAHP (PCPA-FAHP) approach is proposed in this study. The PCPA-FAHP approach seeks a partial consensus among most DMs instead of an overall consensus among all DMs, thereby increasing the possibility of reaching a consensus. Subsequently, the aggregation result is defuzzified using the prevalent center-of-gravity method. The PCPA-FAHP approach was applied to a supplier selection problem to validate its effectiveness. According to the experimental results, the PCPA-FAHP approach not only successfully found out the partial consensus among the DMs, but also shrunk the widths of the estimated fuzzy weights to enhance the precision of the FAHP analysis.

No abstract

The COVID-19 pandemic has severely impacted factories all over the world, which have been closed to avoid the spread of COVID-19. As a result, ensuring the long-term operation of a factory amid the COVID-19 pandemic becomes a critical but challenging task. To fulfill this task, the applications of smart and automation technologies have been regarded as an effective means. However, such applications are time-consuming and budget-intensive with varying effects and are not necessarily acceptable to workers. In order to make full use of limited resources and time, it is necessary to establish a systematic procedure for comparing various applications of smart and automation technologies. For this reason, an evolving fuzzy assessment approach is proposed. A case study has been conducted to demonstrate the effectiveness of the evolving fuzzy assessment approach in ensuring the long-term operation of a factory amid the COVID-19 pandemic.