Constructing a Decision Model for Health Club Members to Purchase Coaching Programs during the COVID-19 Epidemic

Liu, Jing-Wei; Chang, Che‐Wei; Wang, Yaoji; Liu, Yihui

doi:10.3390/su142013497

Cited by 1 publication

(2 citation statements)

References 38 publications

(59 reference statements)

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“…The mean value of the Dirichlet distribution is, and the non-negative parameter is γ. The w j i must be in the proximity of w agg i since it is the mean of the distribution, the proximity is determined by the parameter γ, and the distribution of the parameter γ obeys gamma distribution as in Equation (12).…”

Section: Bayesian Bwm Techniquementioning

confidence: 99%

“…Fitness influencers are more likely to be trusted by consumers than traditional celebrity endorsements when it comes to promoting fitness brands and sports products [7,[9][10][11]. The emergence of fitness influencers brings new business and development opportunities for the fitness industry [12,13]. In this study, a fitness influencer is defined as an individual who commands a significantly and actively engaged following of over 100,000 on major social media platforms, primarily focusing on delivering a range of fitness-related content, from workout routines to health and wellness advice.…”

Section: Introductionmentioning

confidence: 99%

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A Hybrid Model for Fitness Influencer Competency Evaluation Framework

Yang,

Hsu,

Yeh

et al. 2024

Sustainability

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Fitness influencers are an emerging profession in recent years. At present, the main research on fitness influencers focuses on their personal traits, professional knowledge and skills, and course content, while there is still a large research gap on the social media marketing strategies of fitness influencers, how they interact with fans, and the reasons for their influence on fans. There is a lack of a comprehensive evaluation framework for fitness influencer research, and there is no clear research on what competencies are required to become a qualified fitness influencer. Therefore, it has become an important issue to establish a comprehensive fitness influencer competency evaluation. In this study, a hybrid model of fitness influencer competency evaluation framework was developed based on government competency standards and expert knowledge using the Multiple Criteria Decision-Making (MCDM) model perspective. This evaluation should expand to include the principles of sustainable development, emphasizing the influencers’ role in advocating for environmental responsibility, social equity, and economic viability within the fitness industry. First, the study developed 21 criteria in six dimensions of fitness influencer competencies through a literature survey and interviews with several experts. The 21 criteria resonate with many of the Sustainable Development Goals (SDGs), including SDG 3 (Good Health and Well-being), SDG 4 (Quality Education), SDG 5 (Gender Equality), SDG 10 (Reduced Inequalities), and SDG 11 (Sustainable Cities and Communities). The Bayesian Best-Worst Method (Bayesian BWM) was used to generate the best group weights for fitness influencer competencies. Then, a modified Technique for Order Preference by Similarity to the Ideal Solution Based on Aspiration Level (modified TOPSIS-AL) was applied to evaluate the performance ranking of major fitness influencers in Taiwan by integrating the concept of the aspiration level. The results of the study revealed that behavioral standards were the most important dimension, emphasizing the need for fitness influencers to establish a comprehensive set of norms for their own behavioral standards. The top five criteria for fitness influencers’ competencies were self-review, punctuality and prudence, creativity, rapport and motivation, and the need to conform to one’s body image. The performance ranking was used to compare the evaluated subjects to the desired level to obtain a basis for improvement. This study effectively identifies key fitness industry competency indicators and refines business performance through the management implications proposed in this study to facilitate the development of the fitness industry.

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Section: Bayesian Bwm Techniquementioning

confidence: 99%