A calibrated piecewise-linear FGM approach for travel destination recommendation during the COVID-19 pandemic

In a fuzzy group decision-making task, when decision makers lack consensus, existing methods either ignore this fact or force a decision maker to modify his/her judgment. However, these actions may be unreasonable. In this study, a fuzzy collaborative intelligence approach that seeks the consensus among experts in a novel way is proposed. Fuzzy collaborative intelligence is the application of biologically inspired fuzzy logic to a group task. The proposed methodology is based on the fact that a decision maker must make a choice even if he/she is uncertain. As a result, the decision maker’s fuzzy judgment matrix may not be able to represent his/her judgment. To solve such a problem, the fuzzy judgment matrix of each decision maker is decomposed into several fuzzy judgment submatrices. From the fuzzy judgment submatrices of all decision makers, a consensus can be easily identified. The proposed fuzzy collaborative intelligence approach and several existing methods have been applied to the case of the post-COVID-19 transformation of a Japanese restaurant in Taiwan. Because such transformation was beyond the expectation of the Japanese restaurant, the employees lacked consensus if existing methods were applied to identify their consensus. The proposed methodology solved this problem. The optimal transformation plan involved increasing the distance between tables, erecting screens between tables, and improving air circulation. In a fuzzy group decision-making task, an acceptable decision cannot be made without the consensus among decision makers. Ignoring this or forcing decision makers to modify their preferences is unreasonable. Identifying the consensus among experts from another point of view is a viable treatment.

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“…Step 3: (Each decision maker) Apply the calibrated fuzzy geometric mean (FGM) method [ 11 ] to derive the value of .…”

Section: Methodsmentioning

confidence: 99%

“…( 2 ) and ( 3 ) involve many fuzzy multiplication operations, they are difficult to solve. Therefore, the calibrated FGM method [ 11 ] is applied to derive the approximate value of :…”

Section: Methodsmentioning

confidence: 99%

A Fuzzy Collaborative Intelligence Approach to Group Decision-Making: a Case Study of Post-COVID-19 Restaurant Transformation

Chen

Chiu

2022

Cogn Comput

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“…Based on the above discussion, the CFGM-FTOPSIS [30] is applied to assess a smart technology application to support mobile healthcare after the COVID-19 pandemic. A fuzzy approach is suitable for considering the many uncertainties that people face during the COVID-19 pandemic.…”

Section: Assessing Smart Technology Applications After the Covid-19 Pandemicmentioning

confidence: 99%

“…To improve the approximation precision, Chen and Wang [30] proposed the CFGM approach to tune the values of fuzzy priorities:…”

Section: Deriving the Fuzzy Priorities Of Criteria Using Cfgmmentioning

confidence: 99%

Recommending Suitable Smart Technology Applications to Support Mobile Healthcare after the COVID-19 Pandemic Using a Fuzzy Approach

Chen

Wang

2021

Healthcare

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The COVID-19 pandemic seems to be entering its final stage. However, to restore normal life, the applications of smart technologies are still necessary. Therefore, this research is dedicated to exploring the applications of smart technologies that can support mobile healthcare after the COVID-19 pandemic. To this end, this study compares smart technology applications to support mobile healthcare within the COVID-19 pandemic with those before the pandemic, so as to estimate possible developments in this field. In addition, to quantitatively assess and compare smart technology applications that may support mobile healthcare after the COVID-19 pandemic, the calibrated fuzzy geometric mean (CFGM)-fuzzy technique for order preference by similarity to ideal solution (FTOPSIS) approach is applied. The proposed methodology has been applied to evaluate and compare nine potential smart technology applications for supporting mobile healthcare after the COVID-19 pandemic. According to the experimental results, “vaccine passport and related applications” and “smart watches” were the most suitable smart technology applications for supporting mobile healthcare after the COVID-19 pandemic.

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“…Therefore, the pcFGM-fuzzy VIKOR method divides the hotels considered by travelers into two types. Travelers may have different considerations when choosing different types of hotels ( [12] , [13] ). Therefore, the pcFGM-fuzzy VIKOR method asks a traveler to list his/her key factors in choosing these two types of hotels in order to recommend both types of hotels.…”

Section: Introductionmentioning

confidence: 99%

Analyzing the impact of COVID-19 vaccination requirements on travelers’ selection of hotels using a fuzzy multi-criteria decision-making approach

Wang¹,

Chen²

2022

Healthcare Analytics

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A calibrated piecewise-linear FGM approach for travel destination recommendation during the COVID-19 pandemic

Cited by 19 publications

References 71 publications

A Fuzzy Collaborative Intelligence Approach to Group Decision-Making: a Case Study of Post-COVID-19 Restaurant Transformation

A Fuzzy Collaborative Intelligence Approach to Group Decision-Making: a Case Study of Post-COVID-19 Restaurant Transformation

Recommending Suitable Smart Technology Applications to Support Mobile Healthcare after the COVID-19 Pandemic Using a Fuzzy Approach

Analyzing the impact of COVID-19 vaccination requirements on travelers’ selection of hotels using a fuzzy multi-criteria decision-making approach

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