The Application of Technology Acceptance Model 2 (TAM 2) E-Purchase Intention Among Health Tourist in Thailand

Thailand is considered as having an excellent potential for becoming a hub in health tourism in Asia. Indisputably, health tourism seems to be a lucrative business in Thailand. Thailand is increasingly enjoying international acclaim for its health care services while touring the country. Health tourism has seen a marked increase in the number of health tourists which reached 2 million in 2008 as compared to just 1.2 million in 2005 (Department of Export Promotion, 2009). However, in 2009, there is a marked decline of health tourism to only 1.3 million mainly due to political instability. Since the hospitals do not have electronic commerce (e-commerce) infrastructure for securing e-purchase intention, also due to the low internet penetration rate (2.1%) and low on-line purchase for health care services (4.2%) in Thailand, the health tourism slumps further. This may not happen if the health businesses in Thailand have proper e-commerce sites to offer e-purchase facilities to customers. Thus, the main objective of the study is to examine the predictors of electronic purchase intention of health tourism based on Technology Acceptance Model 2 (TAM 2) as the underpinning theory (Venkatesh and Davis, 2000). E-purchase intention is defined as the degree to which the consumer would like to purchase on-line in the future (Chu and Lu, 2007). Based on the literature, four factors (perceived usefulness, perceived ease of use image and price) could be hypothesized as affecting e-purchase intention and attitude. Also, attitude is hypothesized as a mediator on the relationship between the four predictors and e-purchase intention. Measurement constructs for purchase intention (5 items) was adapted from Heijden et al., (2003); perceived ease of use (6 items) was adapted from Davis (1989); perceived usefulness (5 items) was adapted from Lymperopoulos & Chaniotakis (2005), image (8 items)was adapted from Venkatesh & Davis (2000) and Yun and Good (2007; and attitude (8 items) was adapted from Lanseng and Andreassen (2007) and Lymperopoulos & Chaniotakis (2005); and price (5 items) was adapted from (Broekhuizen & Huizingh, 2009). All measures use the 7-point Likert-scale of “strongly disagree - strongly agree” continuum. The primary data was collected from 320 target respondents of international patients who came for health care services in Thailand’s private hospitals. The responses collected were 236 completed questionnaires representing 73.75% response rate. The data was analyzed using structural equation modeling (SEM) method. The result shows that the revised model achieves goodness of fit (p=0.242, CMIN/df=1.063, GFI=0.923, RMSEA=0.041, AGFI=0.903, TLI=0.997). This study found two direct significant predictors of e-purchase intention which are perceived usefulness (β=0.194; CR=2.494; P=0.013), thus asserting H7, and attitude (β=0.385; CR=7.562; P<0.001) thus asserting H5; and four direct significant predictors of attitude which are perceived ease of use (β=0.367; CR=7.511, p<0.001), H1 is asserted; perceived usefulness (β=0.385; CR=7.562; P<0.001), H2 is asserted; image (β=0.311; CR=6.170; P<0.001), H3 is asserted; price (β=0.139; CR=3.02, p<0.001), H4 is asserted. Attitude is also found to be a full mediator for all four linkages. The underpinning or competing model also achieves model fit, thus indicating the robustness of TAM2 model for explaining international patients e-purchase intention for health tourism. The findings of this study are discussed in the perspective of health tourism and its implications to patient’s e-purchase intention.