Great question. In practice, extending established theoretical frameworks is often necessary to reflect contemporary contexts or emerging phenomena. The key is justification. Reviewers typically welcome thoughtful adaptations if they’re grounded in literature, address empirical gaps, and enhance explanatory power without distorting the core logic of the theory. Many top journals now favor theoretical relevance over rigid purity. A good strategy is to clearly state where your adaptation departs from the original, explain why, and support it with precedents or conceptual arguments. Cross-disciplinary borrowings (e.g., adding “learning” to Dynamic Capabilities) are accepted when well-argued.

Thank you, Dr. Kwan Hong Tan — that’s very helpful. I appreciate your emphasis on justification and preserving core theoretical logic. I’m especially interested in how cross-disciplinary adaptations are handled—do you have any examples you’d recommend?

An effective strategy for adding new constructs to existing theoretical specifications is to set up a hierarchical framework, where you first enter all the prior required predictors, and then enter your new variables. This two-step process allows you to determine whether your new variables generate additional explanatory power.

Thank you again, Professor Morgan, for your helpful and structured response.

Your suggestion about using a hierarchical framework to assess the added value of new constructs is very insightful.

If I may follow up with a clarification:

Would this stepwise approach also help identify cases of multicollinearity—specifically when a newly added variable overlaps conceptually or statistically with existing predictors? I’m wondering whether entering variables in blocks could help pinpoint which ones might be contributing to multicollinearity issues.

I appreciate your time and thoughtful guidance.

My Perspective: When Is Extension or Adherence Acceptable?

From my perspective, theoretical extension is often more productive in scholarly research because it opens new avenues for understanding complex phenomena, particularly in dynamic contexts like digital transformation or social change. For instance, extending the Dynamic Capabilities framework to include “digital agility” in a study on tech startups can shed light on how organizations adapt to accelerating technologies. However, I believe adherence to original frameworks is essential when the goal is to validate findings or apply established theories to well-defined problems, such as replicating studies using the Resource-Based View to confirm its validity in new sectors.

Extensions enhance explanatory power when built on robust foundations: a thorough literature review, logical linkage to the original theory, and empirical support. Without these, extensions may be seen as superficial attempts that weaken theoretical rigor. Conversely, excessive adherence can stifle innovation, especially in fast-evolving fields like AI ethics or sustainability, where emerging challenges demand expanded frameworks.

Do Extensions Enhance Explanatory Power or Weaken Theoretical Rigor?

From my perspective, extensions enhance explanatory power if they are justified and supported. For example, introducing “organizational learning” as a new dimension in Institutional Theory can help explain how firms adapt to regulatory pressures in emerging markets. I’ve observed that studies carefully extending frameworks, such as those published in Academy of Management Review, are often respected for sparking new discussions while maintaining coherence. However, unjustified extensions—such as adding vague dimensions without supporting data—undermine rigor and invite criticism. I believe the balance lies in using extensions to address specific gaps while preserving the core of the original theory.

How Do Journal Reviewers Perceive Extensions?

Based on my analysis of academic publishing practices, journal reviewers welcome extensions if they add clear value and are rigorously justified. From my experience analyzing literature, reviewers appreciate studies that demonstrate a deep understanding of the theory (e.g., referencing Teece et al.’s original work on Dynamic Capabilities) and link new dimensions to literature gaps. For instance, a study extending the Resource-Based View to include “digital social capital” was accepted in Strategic Management Journal because it used qualitative data to support the new dimension.

However, reviewers can be skeptical if extensions appear arbitrary or disconnected from the original theory. I’ve noted that studies failing to empirically test new dimensions or lacking a clear conceptual framework are often rejected. Thus, I advise researchers to focus on transparency and logical integration to avoid such critiques.

Best Practices for Balancing Theoretical Purity and Contextual Relevance

From my perspective, there are several practical strategies to justify theoretical extensions while maintaining academic rigor:

Cross-Disciplinary Insights

From my perspective, the importance of extension versus adherence varies by field:

• Management: Encourages extensions to keep pace with market changes, but they must be backed by robust data.
• Sociology: Extensions are common to address cultural shifts (e.g., adding “digital identity” to social identity theories), emphasizing qualitative insights.
• Technical Sciences: Extensions are necessary in fields like AI to address issues like bias, but adherence is preferred in technical validations.
• Environmental Sciences: Adherence ensures consistency in models (e.g., carbon cycles), but extensions are needed for new phenomena like unexpected climate shifts.

From my perspective, theoretical extension is the engine of innovation in scholarly research, but it requires solid methodological foundations to avoid fragmentation. Adherence plays a role in ensuring reliability, particularly in established contexts, but extensions are what propel knowledge forward. I advise researchers to pursue a hybrid approach: using adherence to ground the study and extension to explore new horizons, while ensuring transparency and empirical support. This balance secures reviewer acceptance and contributes to the field’s advancement.

Innovation and development are required, but they must be based on sound and scientific principles.

Great insight. Thank you for this thoughtful contribution, Mr. Shady!