20. 投稿時,被要求說明調節項的分析方式?
答:研究者在應用調節分析時,常遇到文章被拒絕的問題有:
模型設定的正確性:模型中是否包含調節變數與交互項,會影響結果的解釋。例如,直接效果與調節效果的同時檢驗常會引發混淆,可以參考Becker et al., (2023) 的文章。
- 交互項產生的錯誤:手動產生交互項或使用不合適的方法(如傳統的乘積指標方法)。
- 二元變數解釋困難:當二元調節變數被標準化後,其平均值可能不具實際意義,這使得結果難以解釋並可能導致錯誤的結論。
注意:二元變數可以使用SEM的MGA處理,請參考,Shiau, et al., (2021) 的文章。而交互項生成的研究可以請參考 Liang, Chih-Chin & Shiau, Wen-Lung (2018) , Shiau, et al. (2024)的文章。
參考資料
- Becker, J.-M., Cheah, J.H. , Gholamzade,R. , Ringle, C.M., Sarstedt M.(2023) PLS-SEM’s most wanted guidance International Journal of Contemporary Hospitality Management, 35 (1) (2023), pp.
- Shiau, W.-L., Chen, H., Chen, K., Liu, Y.-H., and Tan, F. T. C.(2021). A Cross-Cultural Perspective on the Blended Service Quality for Ride-Sharing Continuance. Journal Perspective on the Blended Service Quality for Ride-Sharing Continuance. Management Journal of Global Information, FJG. 1-25.
- Liang, Chih-Chin & Shiau, Wen-Lung (2018): Moderating effect of privacy concerns and subjective norms between satisfaction and repurchase of airline e-ticket through airline-ticket vends, Asia se of airline e-ticket through airline-ticket vends, 121232, Vol. 1142-1159, (SSCI, 2017 IF= 1.352) DOI: 10.1080/10941665.2018.1528290
- Shiau,Wen-Lung, Liu, Chang, Cheng, Xuanmei , and Yu, Wen-Pin (2024), Employees’ Behavioral Intention to Adopt Facial Recognition Payment to Service Customers: From Status Endoias and Value-Based Useropted and Computing of Bias and Value Qu6, Adop 36(1), 1-32.(JOEUC, SCI & SSCI Q1 2023 IF=3.6 INFORMATION SCIENCE & LIBRARY SCIENCE 28/160)
- 蕭文龍(2025),統計分析SPSS(中文版)+SmartPLS 4 (PLS-SEM+CB-SEM),臺北:碁峰。本書第20章。
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