Guidelines for Enhancing Service Potential in Ageing Businesses

Abstract

Innovation in medical and healthcare services, aimed at creating added economic value in the health sector specifically in Medical
Service Businesses and Wellness Businesses is crucial for adapting to global dynamics. This adaptation is essential to accommodate an aging
society across diverse contexts, with a strong focus on personalized customer service and creating exceptional service experiences at every
touchpoint. This research aimed to investigate approaches for enhancing service potential in ageing businesses, subsequently developing these
insights into a structural equation model. The study employed both qualitative and quantitative research methodologies. The qualitative phase
involved in-depth interviews with 9 experts and a focus group discussion with 11 qualified individuals. The quantitative phase comprised a
survey administered to 500 executives of ageing businesses, utilizing questionnaires. Data analysis involved descriptive statistics, inferential
statistics, and multivariate statistics. The research findings revealed the following prioritized approaches for enhancing service potential in
businesses for the elderly across four key components: 1) Service Delivery ((X̅= 4.24); The most critical item in this category was understanding
and empathizing with the elderly and their relatives. 2) Contemporary Business Administration ((X̅ = 4.24); The most critical item was
establishing a clear vision for business operations serving the elderly. 3) Safety and Security ((X̅ = 4.22): The most critical item was developing
a security plan. 4)Workforce Readiness ((X̅ = 4.09): The most critical item was selecting personnel with qualifications suitable for elder care.
Hypothesis testing indicated that there was no statistically significant difference in the overall importance level of service potential enhancement
approaches for businesses serving the elderly when categorized by business type, at a significance level of 0.05. The analysis of the developed
structural equation model demonstrated good fit with the empirical data, meeting evaluation criteria. The model exhibited
a Chi-square probability value of 0.074, a relative Chi-square value of 1.133,
a Goodness-of-Fit Index (GFI) of 0.955, and a Root Mean Square Error of Approximation (RMSEA) of 0.016.