Factors affecting elderly relatives’ decision to choose nursing home services in Huai Khwang, Bangkok

Abstract

This research aimed to: 1) examine the demographic factors of relatives of older adults that influence their decision-making in selecting elderly care service facilities in Huai Khwang District, Bangkok; and 2) investigate the service marketing mix factors affecting such decisions. The sample consisted of 400 relatives of older adults who played a role in decision-making regarding the selection of elderly care services. The sample size was determined using Cochran’s formula. The research instrument was a structured questionnaire with a reliability coefficient of 0.982. Data were analyzed using frequency, percentage, mean, standard deviation, one-way analysis of variance (One-Way ANOVA), and multiple regression analysis.

The findings revealed that:

1. The overall level of the service marketing mix factors was high, with the highest importance given to people and product aspects. Similarly, the overall decision-making process was at a high level, with the greatest emphasis on problem recognition and need awareness, as well as the service decision stage. Hypothesis testing indicated that gender, age, marital status, education level, and average monthly income significantly influenced the decision to use services at the 0.05 level, whereas occupation had no significant effect. These results were based on One-Way ANOVA (F-test), which examined differences among demographic groups.


2. The service marketing mix factors influencing the decision to use services were product, promotion, and people. In contrast, price, place, process, and physical evidence had no significant influence. Multiple regression analysis showed that the Variance Inflation Factors (VIF) of all independent variables ranged from 1.20 to 1.35, which were below 10, indicating no multicollinearity issues. The multiple correlation coefficient (R) was 0.973, indicating a very strong relationship between the independent variables and the decision to use services. The coefficient of determination (R²) was 0.947, meaning that the seven independent variables jointly explained 94.7% of the variance in service decision-making, while the adjusted R² was 0.946. The remaining 5.3% was attributed to other factors not included in the model. The overall model test showed an F-value of 1001.75 with a significance level of 0.001, which was lower than 0.01, indicating that the overall service marketing mix significantly influenced the decision to select elderly care service facilities.

The predictive equation in raw scores can be written as follows:

Y = 0.500 + 0.350(product) + 0.210(price) + 0.180(distribution channels) + 0.140(promotion) + 0.110(personnel) + 0.090(service process) + 0.080(physical characteristics)