Common Error 2: Insufficient Theoretical Justification for Moderation Hypotheses

Many studies lack sufficient theoretical justification for their moderation hypotheses, a persistent issue documented by several scholars (Carte & Russell, 2003; Dawson, 2014; Landis & Dunlap, 2000; Rasoolimanesh et al., 2021). Rasoolimanesh et al. (2021) found that only 25.61% of 600 moderation studies provided theoretical rationales. Our review shows improvement, yet 32.85% of IS studies still fail to articulate clear causal arguments. This can lead to adverse outcomes, like causal direction misspecification, which can alter statistical significance and risk post-hoc theorizing, especially with cross-sectional data (Carte & Russell, 2003). To mitigate this, researchers should prespecify causal paths using empirical/theoretical evidence (Dawson, 2014), use panel data where possible, and conduct exploratory tests when ambiguity persists (Hayes, 2018).

常见问题二：调节假设缺乏充分的理论论证

尽管在信息系统（IS）领域的研究中这一问题已有所改善，但我们的综述显示，仍有32.85%的研究未能清晰阐明调节关系的因果论证或理论依据。这一方法的根本性问题在于，理论论证的缺失会引发一系列严重后果。正如Carte和Russell（2003）所警示的，尤其是在使用横截面数据时，若错误指定了自变量（X）与因变量（Y）的因果方向，可能会得出截然不同的调节结果，甚至导致缺乏因果支持的“事后理论化”。Rasoolimanesh等人（2021）对600项调节研究的分析更揭示了此问题的普遍性——高达74.39%的研究未能为其调节假设提供理论依据。

问题实质：

调节分析不仅仅是检验一个交互项是否显著。若缺乏坚实的理论来界定“谁在调节谁”以及“为何调节”，整个分析就失去了逻辑根基，所得结论可能完全是统计假象或因果误判。

解决建议：

• 预先明确因果路径：在分析前，必须依据现有理论或实证证据，明确界定核心变量之间的因果关系方向（Dawson，2014）。

• 升级数据与设计：在可行的情况下，优先使用面板数据或其他能更好推断因果的研究设计。

• 进行稳健性探针：当因果关系存在理论上的模糊性时，可以尝试检验不同因果方向的备选模型，并辅以调节效应探针分析（Hayes, 2018），以全面理解数据所呈现的关系。

Reference

• Carte, T. A., & Russell, C. J. (2003). In pursuit of      moderation: Nine common errors and their solutions. MIS Quarterly,      27(3), 479-501.

• Dawson, J. F. (2014). Moderation in management research: What,      why, when, and how. Journal of Business and Psychology, 29(1),      1-19.

• Glaser, B. G., & Strauss, A. L. (2017). The Discovery      of Grounded Theory: Strategies for Qualitative Research. Routledge.

• Landis, R. S., & Dunlap, W. P. (2000). Moderated multiple      regression tests are criterion specific. Organizational Research      Methods, 3(3), 254-266.

• Rasoolimanesh, S. M., Wang, M., Mikulić, J., &      Kunasekaran, P. (2021). A critical review of moderation analysis in      tourism and hospitality research toward robust guidelines. International      Journal of Contemporary Hospitality Management, 33(12), 4311-4333.

• Xu, Y., & Shiau, W. L. (2026). Moderation analysis in      business and management research: Common issues, solutions, and guidelines      for future research. International Journal of Information      Management, 86, 102995.