The infrequency of purchase (IP) model was used to explore the impact of financial factors, limiting factors, social status and household life cycle on family travel intention and travel expenditure in Taiwan. The empirical results indicate that family travel intention and level of expenditure vary at different stages of the household life cycle. Additionally, family incomes, the education level of the head of the household, women's employment and home ownership have significantly positive impacts on travel intention and level of expenditure. The findings also suggest that the presence of a family member's health problems or the number of seniors over 65 years of age in a household will reduce travel intention and thus the level of travel expenditure.

can indeed increase customer trust in e-commerce. It also finds that different types of avatar elicit different types of customer trust. Customers have higher cognitive trust in the expert avatar than in the attractive one, and customers have higher emotional trust in the attractive avatar than in the expert avatar. It was also found that an avatar is effective for customers with either knowledge or low product knowledge, while the effect of the type of avatar on trust is stronger for customers with high product knowledge. The effect of emotional trust on purchase intention is stronger than that of cognitive trust. For cosmetic skin care products, attractiveness may be more important than expertise factors when designing the avatar for an online retailer, and an attractive avatar may be the reference point of consumer's ideal vision of herself.

No abstract

Applying Regression Model forChanges in Population Age Structure on Domestic Tourism Demand. Eng.

<p>Seasonality is one of the significant features in tourism market. This study employs the X-13 ARIMA-SEATS method to tourism market in Taiwan. Tourists who had come to Taiwan from 1981 to 2016 mainly came from Asia, followed by the Americas and Europe. In Asian area, tourists from Mainland China account for the highest percentage, followed by Hong Kong and Japan, whose overall resources provide favourable conditions for industrial development. Rapid growth in the number of tourists coming to Taiwan gives rise to the issue of uniform distribution of tourists during the year, namely, tourism seasonality. The empirical results show that tourism seasonality of tourists coming to Taiwan is randomly changing. Analysis should be conducted concerning sustainable planning, environmental dynamic carrying capacity and sustainable development. The high tourism seasons are March, April, November and December. However, January, July and September every year are off-season in Taiwan’s tourism market, with gradual decreasing number of tourists compared with those in high-season months. The contribution of this research is the analysis of data from high-season and off-season months, The local transport routes and environmental facilities can be planned for the high-season months, in order to develop diversified tourism marketing and strategies, improve the utilisation of space, and enhance business performance. During off-season months, Stay at Home Economic may be developed through Internet or platform marketing to provide distance-free remote services. For the overall environment, The analysis between off-season and high-season months not only helps to generate economic development, but can provide a sustainable planning direction, and link environmental dynamic carrying capacity and sustainable development. </p>