TAM theory can analyze various influencing factors of book online marketing and explain the attitudes of online readers and users. It can be applied to different online book marketing methods, such as online bookstores and publishers' websites. Here, the online bookstore is taken as an example for research and design. This study takes the form of issuing questionnaires to online bookstore users to refine and score the above variables. Likertscaling was used in the questionnaire design of this case, and the answer options of each question were divided into completely disagree, disagree, agree and completely agree, and were assigned 1 ~ 5 respectively.
The purpose of this case is to verify the correlation between the basic functions of website, bibliographic information function, personalized service function and delivery service function and the use behavior of online bookstore. Because there is a positive correlation between perceived usefulness and usage behavior in TAM theory, this case mainly verifies the correlation between the above indicators and perceived usefulness.
In this study, the project scores corresponding to each index are added up and the average value is taken as the measurement result of each research variable, which is also well documented (Gerbing &: Anderson, 1988). The verification method used in this case is simple linear regression, and each test will give the main test indicators.
Basic data of (1) sample. This survey is conducted in the form of online questionnaire. * * * 250 questionnaires were distributed, and 94 valid questionnaires were recovered/kloc-0, with a questionnaire recovery rate of 77.6%. According to the statistics of the collected samples, 60.3% are men and 39.7% are women. Bachelor degree accounts for the largest proportion, reaching 60.8%; In the survey of the Internet age, 56.2% have been online for more than 2 years, accounting for the majority. This coincides with Zhang Zhiqiang's view in the article "From the Development of Online Bookstores in China".
(2) Regression analysis and related indicators. Regression analysis is based on a large number of statistical data, using mathematical statistics to establish the expression of regression function between dependent variables and independent variables.
Standardized β is a metric in regression analysis. A positive value indicates a positive correlation between independent variables and dependent variables, and a negative value indicates a negative correlation between independent variables and dependent variables.
The value of p is the decreasing index of the reliability of the result. The greater the p value, the less reliable the correlation of variables in the sample. In fact, the p value is the error probability that the observation results are considered valid, that is, they are generally representative. For example, p=0.05, indicating that 5% of the variables in the sample may be caused by accident. In many research fields, a p value of 0.05 is generally considered as the boundary level of acceptable error.