An increasing number of foreign companies want to enter the Chinese market. Online advertising is one of the indispensable means of the company's operation and marketing, and foreign companies poorly understood the online advertising channels in China. Therefore, this study uses the AISAS model to study the preferences of Chinese millennial generation Taobao users for online advertising channels. And research through three dimensions are gender, city level and different product categories. Specifically, this research through online questionnaires and finally collected 150 samples, it was found that Chinese millennial generation Taobao users favored the promotion of WeChat public accounts, followed by Pre-movie adverts. Further, the study confirms that consumers do have preferences for online advertising choices and that they will change as they are placed on different e-commerce platforms. Based on the previous study's interpretation of preferences, the preferences are defined as five exact post behaviors to better evaluate consumers' choices for online advertising. Moreover, through data analysis, it is found that there are differences between male and female online advertising channels among Chinese millennial generation Taobao users. Females prefer online advertising channels that are interactive than males such as live streaming. Males prefer online advertising channels that are dominated by pictures/images for instance mini banners in App and Web. In addition, live streaming has an advantage in the household goods category.

The purpose of this thesis is to investigate how the differences between the study and policy sites impact the performance of benefit function transfer. For this purpose, simulated data are created where all information necessary to conduct the benefit function transfer is available. We consider the six cases of difference between the study and policy sites- scale parameter, substitution possibilities, observable characteristics, population preferences, measurement error in variables, and a case of preference heterogeneity at the study site and fixed preferences at the policy site. These cases of difference were considered one at time and their impact on quality of transfer is investigated. RUM model based on reveled preference was used for this analysis. Function estimated at the study site is transferred to the policy site and willingness to pay for five different cases of policy changes are calculated at the study site. The willingness to pay so calculated is compared with true willingness to pay to evaluate the performance of benefit function transfer. When the study and policy site are different only in terms of scale parameter, equality of estimated and true expected WTP is not rejected for 89.7% or more when the sample size is 1000. Similarly, equality of estimated preference coefficients and true preference coefficients is not rejected for 88.8% or more. In this study, we find that benefit transfer performs better only in one direction. When the function is estimated at lower scale and transferred to the policy site with higher scale, the transfer error is less in magnitude than those which are estimated at higher scale and transferred to the policy site with lower scale. This study also finds that transfer error is less when the function from the study site having more site substitutes is transferred to the policy site having less site substitutes whenever there is difference in site substitution possibilities. Transfer error is magnified when measurement error is involved in any of the variables. This study do not suggest function transfer whenever the study site's model is missing one of the important variable at the policy site or whenever the data on variables included in study site's model is not available at the policy site for benefit transfer application. This study also suggests the use of large representative sample with sufficient variation to minimize transfer error in benefit transfer. / Master of Science