## 3 Methodology
### Data Analysis and Results
#### 3.3.2 Fuzzy Set Qualitative Comparative Analysis  
First, we used the fsQCA to calibrate variables with set scores ranging from 0-1 in order to assess the membership degree of each variable. Fuzzy set scores were calculated using three anchors for each condition. In this study, all the constructs were measured by a 7-point Likert-type scale. Following the work of [PERSON] (2007) [52], we coded full membership as six and non-membership as two; the crossover anchor is four which is the neutral point in a 7-point Likert scale. We identified the anchors based on the number of the items for each construct. Second, to conduct the fsQCA, we generated the full truth table for the specified outcome (participation intention) using the specified causal conditions (information quality, marketers-interactivity, customers-interactivity, platform-interactivity, brand-interactivity and flow) for fsQCA 2.5. Finally, we reduced the initial truth table by specifying the frequency, consistency and consistency proportion thresholds. We set our frequency threshold at two [14]. The consistency score measured the degree to which combinations are subsets of high scores in the outcome. In this study, we set the consistency cut-off at 0.9, which agrees with prior studies [14]. Moreover, as suggested by [PERSON] (2013) [14], we also set a consistency proportion threshold of 0.9. This threshold specifies the minimum ratio of consistent to inconsistent cases required for classifying a configuration as one that meets the sufficiency requirement. The consistency proportion analysis can be accomplished using the Kirq software. As such, if a configuration that meets these three conditions is coded 1, then all the other configurations are coded as 0. _Research findings._ The fsQCA produces three solutions, including a complex, intermediate, and parsimonious solution. Generally, intermediate solutions are superior to the other two solutions [14]. Therefore, we reported intermediate solutions in this study. Table 5 presents the results of high community participation intention using the fsQCA and presents four configurations. The four configurations are regarded as sufficient conditions leading to high engagement in the micro-blog of a brand. These configurations imply some rules for high participation intention. As shown in Table 4, the fsQCA results are consistent with SEM in several ways, but also provide evidence of additional complex contextual effects. First, configurations indicate that high degrees of information quality, customers-interactivity, platform-interactivity and brand-interactivity, combined with a low degree of marketers-interactivity and the absence of flow, can lead to high membership score for community participation intention. Second, the pathway indicates that the combination of high degrees of information quality, platform-interactivity, brand-interactivity and flow, result in high community participation intention despite the absence of other conditions. Third, the pathway shows that the joint influence of high degrees of information quality, marketers-interactivity, customers-interactivity, platform-interactivity and flow lead to high participation intention despite the absence of brand-interactivity. Configuration four indicates that high degrees of information quality, marketers-interactivity, platform-interactivity and brand-interactivity coupled with a low degree of customers-interactivity and the absence of flow, also lead to a high membership score for community participation intention. Each configuration is fairly consistent and explains a satisfactory amount of cases with high community participation intention. The solution as a whole also has a high consistency of 0.97 and a satisfactory coverage of 0.74. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Goodness of Model Fit/Values** & **Original Value** & **HI95** & **HI99** \\ \hline SRMR & 0.044 & 0.046 & 0.049 \\ d\({}_{\text{ULS}}\) & 0.502 & 0.527 & 0.597 \\ d\({}_{\text{G}}\) & 0.386 & 0.395 & 0.405 \\ \hline \hline \end{tabular}
\end{table}