# User Acceptance of Information Feed Advertising: A Hybrid Method Based on SEM and QCA
## 5 Qualitative Comparative Analysis (QCA)
#### 3.1.2 Adequacy analysis  
The truth table should be constructed first for adequacy analysis. Different combinations of multiple antecedent variables form different constructs. The truth table is the result list of all cases classified according to different constructs. Then, the consistency threshold and frequency threshold are set to remove the construct with lower consistency or frequency in the truth table. Among them, consistency refers to how the result variable can be deduced for the combination, and the consistency threshold is generally set as 0.8. For the frequency threshold, the sample size should not be less than 80% of the total sample size [45]. In this study, the consistency threshold is set to 0.8, and the frequency threshold is set to 2. The optimal solution and the simplified solution of the user's willingness to accept information feed advertising are obtained through the truth table obtained. We use the symbol \(\otimes\) to indicate that the antecedent variable needs not to exist in the construct. The symbol \(\ominus\) is used to indicate that the existence of the antecedent variable does not affect the results [41]. Furthermore, the antecedent variables included in both the reduced solution and the optimized solution are regarded as the core condition, and the antecedent variables only included in the optimal solution but excluded by the reduced solution are regarded as the marginal conditions. This study concludes that the core condition is informativeness and the absence of perceived advertising clustering. In the construct table, the core conditions are represented by the symbol \(\otimes\), and the marginal conditions are represented by the symbol \(\otimes\), as shown in Table 7. \begin{table}
\begin{tabular}{c c c} \hline \hline  & **Coherence** & **Coverage** \\ \hline Consistency & 0.793424 & 0.754576 \\ \(\sim\)Consistency & 0.453408 & 0.577646 \\ Accuracy & 0.654932 & 0.798182 \\ \(\sim\)Accuracy & 0.501603 & 0.493763 \\ Informativeness & 0.876503 & 0.805453 \\ \(\sim\)Informativeness & 0.410425 & 0.548553 \\ Sociality & 0.706415 & 0.816707 \\ \(\sim\)Sociality & 0.544988 & 0.561004 \\ Advertising Reward & 0.725661 & 0.773023 \\ \(\sim\)Advertising Reward & 0.499519 & 0.556458 \\ Perceived Advertising Clustering & 0.564715 & 0.624733 \\ \(\sim\)Perceived Advertising Clustering & 0.643303 & 0.689886 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Necessity analysis results (\(\sim\)indicates that the antecedent variable does not exist or the level is low). In Table 7, coherence reflects the degree to which a given construct is a sufficient condition for the result, and the coverage assessment interprets the result by the set relation of consistency test, which reflects the empirical correlation of constructs, that is, how much the given construct determines the result variable. As shown in Table 7, the overall coherence is higher than the acceptable threshold (0.75), which indicates that all constructs have good reliability and are sufficient conditions for user acceptance of information feed advertising. The overall coverage is about 0.727, indicating that these seven constructs account for a considerable proportion of the results. All constructs provide different combinations of factors. According to the fsQCA analysis, we have the following conclusions:  
* Construct 1 indicates that information feed advertising is highly informative, consistent, accurate, and social. No matter what the advertising reward is, users will accept the information feed advertising if they do not perceive the advertising clustering. * Construct 2 indicates that information feed advertising is highly informative, consistent, and social, and there is no advertising reward. No matter how accurate it is, users will accept the information feed advertising when they do not perceive advertising clustering. * Construct 3 indicates that information feed advertising is highly informative and accurate, with advertising rewards and low sociality.