# User Acceptance of Information Feed Advertising: A Hybrid Method Based on SEM and QCA
## 6 Conclusions
### Limitations and Future Work  
This study also has some limitations that are needed to be further investigated in the future. First, the questionnaire in this study mainly covered young people, i.e., 88.2% of them were under 30 years old, which might introduce cognitive bias and made the results of this study not popular for other user groups, e.g., old people. Although young people mostly adopt mobile Internet and information feed advertising, there are also some old people and many mid-aged people using the mobile Internet. Thus, it is better to conduct questionnaires over users of a wide range of ages. Second, currently, the samples of the questionnaire barely consider people with basic studies, which may make the results only valid for people with a high academic background. However, including people with basic studies in the survey is still a problem because many are not experienced using smartphones and mobile devices. Third, in this study, we did not consider the differences among information feed advertising platforms. It could be better to consider the influence of the platform in future work. Finally, although hundreds of valid questionnaires are theoretically enough to conduct data analysis, such a number is relatively small to draw reliable and robust conclusions in the big data era.  
Thus, in the future, some research issues are worth further investigating. First, a further study on secondary data collected from some crowdsourcing platforms like Amazon Mechanical Turk [46] could better analyze user acceptance of information feed advertising. Second, because other factors could impact users' decision-making behavior, future work can be focused on other possible factors, such as users' educational background and ages. Finally, in addition to the SEM and fsQCA model, it is also worth studying other research models within the big data and mobile Internet context [47]. Third, as current information feed advertising mechanisms need to collect user information, reflecting the impact of user privacy in user acceptance of information feed advertising is still an open problem [48]. Finally, with the development of social networks and web 2.0, incredible information, such as poisoned data and fake advertisement, becomes a critical issue in decision-making based on web information [49; 50]. Although evaluating data quality and information credibility is mainly related to computer algorithms, it is useful to consider the impact of data quality and advertising credibility in the user acceptance of information feed advertising in the future.  
J.Z., conceptualization, funding acquisition, project administration, supervision, and writing--review and editing; C.Y., data curation, methodology, validation, and writing--original draft preparation. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Science Foundation of China (Grant No. 71273010) and the National Statistical Science Research Project (Grant No. 2019 LY66).  
We would like to thank the editors and anonymous reviewers for their suggestions and comments to improve the quality of the paper.  
The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.