Marketing Mix Factors Influencing Tourists on Community-Based Tourism: A Case Study of Nakhon Nayok Province

Abstract

In this thesis, the researcher examines the demographic factors and the behaviors of tourists on community-based tourism; analyzes the components of the factors affecting these tourists; analyzes the differences in the demographic factors affecting the decisions of the tourists under study on community-based tourism; and analyzes the relationships of the factors affecting the decisions of the tourists under investigation on community-based tourism in Nakhon Nayok province. A questionnaire was used as a research instrument to collect data from 400 tourists visiting Thung Na Mui Bridge. The statistics used in the data analysis were frequency, percentage, mean, and standard deviation. The techniques of factor analysis, independent t test, one-way analysis of variance (ANOVA), and multiple regression analysis were also employed. Findings are as follows: 1. The highest proportion of the questionnaire respondents were females, aged between 17 and 36 years with a bachelor’s degree. They worked as company employees having a monthly income between 15,000 and 25,000 baht. Their domicile was in the Bangkok Metropolitan Region.

1. In regard to tourism behaviors, it was found that the respondents’ major objective for tourism was for recreation. They used personal vehicles for travel. They traveled with friends or colleagues. The travel periods were on Saturdays for one or two hours. In regard to the number of visiting times, it was found that they came for the first time. The expense of one journey was less than 1,000 baht. They received tourism information from websites. The problems in the tourist attractions were the difficulties in finding the location of ATM machines and insufficient parking spaces. They liked the location for picture taking at the highest level. 


2. The results of the variable input and the composition of the components found that there were forty-one variables that could be organized into eight components with an eigen value exceeding 1.0. All of these eight components could explain the total variance of all the variables at 68.129 percent. These eight components were (1) service; (2) personnel; (3) place; (4) values and lifestyles; (5) tourist information centers; (6) price; (7) incentives; and (8) the environment. 4. The factors affecting the tourists’ decisions on community-based tourism regarding tourist destinations enabled respondents to make decisions to travel at a high level. At the highest level was the aspect of values and lifestyles. Next in descending order was the aspect of personnel. The lowest level was the aspect of service. 5. The comparison of the service factors found that the variable influencing the decision to travel at the highest level was income. Next in descending order was occupation. The lowest level was domicile. The personnel factor found that the variable influencing the decision to travel at the highest level was age. Next in descending order was educational level. The factor of values and lifestyles found that the variable influencing the decision to travel at the highest level was occupation. Next in descending order was age. The lowest level was income. 6. The multiple regression analysis found that the factors of service; values and lifestyles; tourist information centers; incentives; and location affected the tourists’ decisions on community-based tourism at the statistically significant level of .05. They could predict the decisions to travel at 16.4 percent. The factor of service (β=0.232, sig.=0.000) affected the decision to travel at the highest level. Next in descending order were the factors of values and lifestyles (β=0.204, sig.=0.000); tourist information centers (β = 0.183, sig.=0.000); incentives (β =0.149, sig.=0.001); and location (β =0.114, sig.=0.014). The factors not affecting the decision to travel were price, the environment; and personnel. The regression equation appropriate for an estimate of the decision level of tourists on community-based tourism and the factor of marketing mix was the following = 54.688 + 3.941A + 3.466D + 3.110E + 2.542G + 1.939C. A was the factor of service. D was the factor of values and lifestyles. E was the factor of tourist information centers. G was the factor of incentives. C was the factor of location.

1. for picture taking at the highest level.