This study examines influencing factors for users' intentions to tap through mobile advertisements. This chapter uses a data set with 115,899 records of ad tap-through from a mobile advertising company in China to fit a logit model to examine how the probability of advertisement tap-through is related to the identified factors. The results show that the influencing variables are application type, mobile operators, scrolling frequency, and the regional income level as they are positively correlated with the likelihood whether users would tap on certain types of advertising. Moreover, a Bayesian network model is used to estimate the conditional probability for a user to tap on an advertisement in an application after the user already taps on another advertisement in the same application. Based on the findings, strategies for mobile advertisers to engage in effective and targeted mobile advertising are proposed.
Distribution characteristics and influencing factors of commercial center and hotspots based on big data: A case of the main urban area of Urumqi City
