A Causal Configuration Analysis of Payment Decision Drivers in Paid Q&A
, et | 08 mars 2021
À propos de cet article
Article Category: Research Paper
Publié en ligne: 08 mars 2021
Pages: 139 - 162
Reçu: 15 juil. 2020
Accepté: 09 févr. 2021
DOI: https://doi.org/10.2478/jdis-2021-0017
Mots clés
© 2021 Wenyu Chen et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
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Variable Description.
| Dimension | Variable | Definition |
|---|---|---|
| Consequent variable | The increase in the number of paid questions knowledge contributor i has answered within one month | |
| Antecedent variables in the systematic processing route | The effective average rating score that knowledge contributor i got during one month | |
| The average number of likes for each public answer knowledge contributor i shared for free during one month | ||
| Antecedent variables in the heuristic processing route | The number of consultations that knowledge contributor i has answered at the start of observation period | |
| The network centrality (sum up out-degree and in-degree) of knowledge contributor i at the start of observation period | ||
| The personal information integrity of knowledge contributor i | ||
| The number of honor labels that knowledge contributor i owns | ||
| Public antecedent variable | The consulting fee that knowledge contributor i asks for |
Analysis of necessary conditions for the presence of payment decision.
| Conditions | Consistency | Coverage |
|---|---|---|
| 0.868 | 0.452 | |
| 0.994 | 0.455 | |
| 0.752 | 0.474 | |
| 0.643 | 0.538 | |
| 0.823 | 0.768 | |
| 0.664 | 0.575 | |
| 0.742 | 0.464 | |
| 0.706 | 0.487 | |
| 0.633 | 0.575 | |
| Outcome variable: |
Calibration of variables.
| Variable | full membership (fuzzy score=0.95) | cross-over point (fuzzy score=0.5) | Full non-membership (fuzzy score=0.05) |
|---|---|---|---|
| 101.000 | 3.000 | 1.000 | |
| 5.000 | 4.875 | 3.857 | |
| 1652.340 | 186.378 | 15.725 | |
| 1446.000 | 94.000 | 13.000 | |
| 475946.000 | 81021.000 | 7288.000 | |
| 7.000 | 6.000 | 4.000 | |
| 5.000 | 1.000 | 0.000 | |
| 199.000 | 48.000 | 5.000 |
Configurations for achieving low/medium intention in payment decision.
| Condition | ||||||
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | ||
| • | ⊗ | ⊗ | ||||
| • | • | ⊗ | ||||
| ⊗ | ||||||
| • | ⊗ | • | ⊗ | • | ||
| • | • | ⊗ | ||||
| ⊗ | ⊗ | • | • | • | ||
| Raw Coverage | 0.284 | 0.138 | 0.153 | 0.166 | 0.213 | |
| Unique Coverage | 0.090 | 0.021 | 0.047 | 0.024 | 0.045 | |
| Consistency | 0.993 | 0.999 | 0.994 | 0.999 | 0.996 | |
| Solution Coverage | 0.444 | |||||
| Solution Consistency | 0.993 | |||||
Selected studies on payment decision in paid Q&A.
| Scholar | Method | Conclusion |
|---|---|---|
| 1. Perspective: knowledge contributors’ ability and credibility | ||
| Negative binomial panel regression | Knowledge contributors’ reputation, ability and personal information integrity play a positive role on askers’ willingness to pay while price plays a positive regulatory role. | |
| Granger causality test | Knowledge contributors’ structural capital and relational capital, such as personal information integrity and followers, have a positive influence on askers’ payment decision. | |
| 2. Perspective: askers’ perception about answers | ||
| Survey study | Answering speed and quality of answers can be valued as influencing factors when making payment decision. | |
| Semi-structured interviews | Askers participate in paid Q&A for answerers’ heterogeneous resources, credible answers and cognition of questions. | |
| 3. Perspective: price | ||
| Field study | Higher price will lead to askers’ trust in answer quality, which will encourage their payment intention. | |
| Text mining; Hierarchical OLS regression | The influence of price on askers’ motivation in making payment decision might differ according to their knowledge levels. Expert askers are less sensitive to price. | |
Correlations of variables.
| 1.000 | ||||||||
| −0.014 | 1.000 | |||||||
| 0.060 | 0.034 | 1.000 | ||||||
| 0.542 | −0.024 | 0.097 | 1.000 | |||||
| −0.027 | 0.032 | 0.477 | 0.022 | 1.000 | ||||
| −0.089 | 0.131 | −0.044 | −0.014 | 0.054 | 1.000 | |||
| −0.158 | −0.003 | −0.024 | −0.148 | 0.238 | 0.073 | 1.000 | ||
| −0.115 | 0.098 | 0.132 | −0.025 | 0.396 | 0.151 | −0.140 | .000 |
Complex configurations indicating high intention in payment decision for the subsample.
| Models from Subsample for High Intention in Payment Decision | Raw Coverage | Unique Coverage | Consistency |
|---|---|---|---|
| 0.230 | 0.058 | 0.800 | |
| 0.218 | 0.034 | 0.825 | |
| 0.175 | 0.046 | 0.904 | |
| 0.265 | 0.130 | 0.852 | |
| solution coverage | 0.468 | ||
| solution consistency | 0.837 |
Summary statistics of variables.
| Variable | Count | Mean | Std. | Min | Max |
|---|---|---|---|---|---|
| 95 | 22.074 | 77.262 | 1.000 | 696.000 | |
| 95 | 4.745 | 0.427 | 2.000 | 5.000 | |
| 95 | 486.745 | 689.375 | 3.950 | 3899.620 | |
| 95 | 379.358 | 1171.699 | 3.000 | 10673.000 | |
| 95 | 134364.421 | 163643.105 | 387.000 | 805492.000 | |
| 95 | 6.032 | 1.165 | 2.000 | 7.000 | |
| 95 | 1.726 | 1.469 | 0.000 | 6.000 | |
| 95 | 57.105 | 53.393 | 1.000 | 268.000 |
Configurations for achieving high intention in payment decision.
| Condition | ||||||
|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | ||
| ⊗ | • | ⊗ | ⊗ | ⊗ | ||
| ⊗ | • | • | ||||
| ⊗ | ⊗ | • | ||||
| ⊗ | ⊗ | |||||
| • | • | |||||
| • | ⊗ | • | ||||
| Raw Coverage | 0.250 | 0.301 | 0.293 | 0.220 | 0.212 | |
| Unique Coverage | 0.061 | 0.064 | 0.031 | 0.026 | 0.019 | |
| Consistency | 0.829 | 0.855 | 0.861 | 0.903 | 0.901 | |
| Solution Coverage | 0.515 | |||||
| Solution Consistency | 0.823 | |||||