FACTORS INFLUENCING CONSUMER’S NON-LIFE INSURANCE (NON-MOTOR) PURCHASE IN BANGKOK

Abstract

Nowadays, Non-Life Insurance industry is in high competition of Thailand is in high competition both domestic and foreign, so this business need to push their organizations to be accepted by consumers under the economy, society and technology change. Furthermore, Insurance company has to adapt for the efficient competition with foreign Insurance company or foreign investment. Hence, the Insurance company look for lead any efficient strategies to create competitive advantage. The researcher conducted a study of factors influencing consumer’s Non-Life Insurance (Non-Motor) purchase in Bangkok. The research purpose is studying demographic factors and marketing mix factors (7Ps) influencing the Non-Life Insurance purchase in Bangkok to apply the results for the marketing strategy, Non-Life Insurance forms and services development by using a questionnaire for collecting data from the Insured about 400 persons in Bangkok and the statistics used for analyzing the collected data as t-test and F-test (One - Way ANOVA). If the difference of F-test were found, Scheffe’s method will be used.

The sampling research results were found that most respondents were male at 50.2%, aged 30-39 years at 26.5%, bachelor’s degree at 63.2%, marital status at 51.8%, private business at 35.2% and average salary Baht 30,001-50,000 per month at 31.0%.

Most respondents gave the highest, high and medium opinion rate only for marketing mix factors (7Ps) be sorted as follows: people factors, process factors, product factors, price factors, promotion factors, physical evidence factors and place factors.

When comparing demographic characteristics with marketing mix factors (7Ps) at the statistical significance level 0.05 (*P ≤ 0.05), it was shown that 1) the respondents with different gender had different opinions on price factors, place factors, promotion factors and physical evidence factors. 2) the respondents with different aged had different opinions on place factors, and physical evidence factors. 3) the respondents with different education levels had different opinions on place factors and promotion factors. 4) the respondents with different marital statuses had different opinions on physical evidence factors. 5) the respondents with different careers had different opinions on product factors. 6) the respondents with different average salary had opinions similarly on marketing mix factors.