Transformational leadership and talent retention: how to validate workplace measurement instruments

The relationship between transformational leadership and talent retention is one of the most productive objects of study in Organizational Wellbeing, but its strength depends on an often-overlooked step: the rigorous validation of the instruments used to measure both constructs.

Theoretical framework: from Bass and Riggio to leader-member exchange

Transformational leadership, formalized by Bass and Riggio (2006), is structured in four dimensions —idealized influence, inspirational motivation, intellectual stimulation and individualized consideration— that move employees beyond immediate self-interest. Its effect on retention is usually explained through leader-member exchange (LMX) theory, whereby the quality of the relationship with the supervisor activates reciprocity, commitment and, consequently, lower intention to leave. Recent evidence confirms this link: Tian et al. (2020) showed transformational leadership increases retention mediated by organizational citizenship behavior, and Xiong, Wu and Sui (2023) replicated the negative effect on turnover intention among knowledge workers.

Why talent retention is a measurable problem

Turnover is not just a human loss: it represents a direct cost of 50% to 200% of the position’s annual salary, factoring in recruitment, training and the productivity curve. For the student, this justifies operationalizing retention as intention to stay or intention to leave, latent variables that are only comparable across studies if measured with scales whose psychometric properties have been demonstrated. Berettera, Pujol-Cols and Arraigada (2023) illustrate this rigor by linking transformational leadership with retention in IT organizations.

How to validate a workplace measurement instrument: step by step

Validation is a cumulative process, not a formality. Its stages are:

• Content validity via expert judgment. Select three to seven judges and compute Aiken’s V coefficient or the content-validity ratio (CVR). Each item is assessed for clarity, coherence, relevance and sufficiency.
• Pilot test. Apply it to an independent sample (30 to 50 subjects) to refine wording and detect social-desirability bias.
• Reliability. Report Cronbach’s alpha, but complement it with McDonald’s omega (ω), more stable when the tau-equivalence assumption is violated.
• Exploratory factor analysis (EFA). Check KMO (≥ .80), Bartlett’s test and the extraction method.
• Confirmatory factor analysis (CFA). Acceptable fit indices: CFI and TLI ≥ .95, RMSEA ≤ .08 and SRMR ≤ .08.

Recognized scales and modeling methods

Don’t build from scratch if accumulated evidence exists. The Multifactor Leadership Questionnaire (MLQ-5X) is the most-used instrument for transformational leadership; the Spanish adaptation by Moreno-Casado et al. (2021), with a 34-item, five-factor solution, is a replicable base. For retention, start from validated intention-to-stay or intention-to-leave scales. For analyzing relationships between constructs, partial least squares structural equation modeling (PLS-SEM) is suitable when the model is complex or the sample moderate, as Thomas and Aurora (2024) did.

Frequent mistakes that invalidate a thesis

• Insufficient samples. A stable CFA requires at least 10 subjects per item; publishing with n = 150 on a 30-item instrument compromises the factor solution.
• Omitting content validity. Computing only alpha does not prove the scale measures what it claims.
• Reporting alpha as the only evidence. A high alpha can hide multidimensionality; without EFA/CFA, factor interpretation remains unproven.
• Ignoring invariance. If you compare sectors or countries, you must test measurement invariance; otherwise differences are spurious.

References

• Bass, B. M., & Riggio, R. E. (2006). Transformational leadership (2nd ed.). Lawrence Erlbaum Associates. https://doi.org/10.4324/9781410617095
• Berettera, C., Pujol-Cols, L., & Arraigada, M. (2023). Retención del talento en organizaciones IT: el rol del liderazgo transformacional y los acuerdos de empleo idiosincráticos. Cuadernos de Administración, 36. https://doi.org/10.11144/Javeriana.cao36.rtorl
• Moreno-Casado, H., Leo-Marcos, F. M., López-Gajardo, M. Á., García-Calvo, T., Cuevas, R., & Sánchez-Oliva, D. (2021). Adaptation and validation of the MLQ-5X leadership scale to the Spanish educational context. Anales de Psicología, 37(2), 311-322. https://doi.org/10.6018/analesps.425351
• Thomas, S. R., & Aurora, S. R. (2024). The dynamic effects of transformational leadership on employee retention and employability over time: An agent-based model. Computational and Mathematical Organization Theory, 30(4), 350-380. https://doi.org/10.1007/s10588-024-09385-y
• Tian, H., Iqbal, S., Akhtar, S., Qalati, S. A., Anwar, F., & Khan, M. A. S. (2020). The impact of transformational leadership on employee retention: Mediation and moderation through organizational citizenship behavior and communication. Frontiers in Psychology, 11, 314. https://doi.org/10.3389/fpsyg.2020.00314
• Xiong, B., Wu, X., & Sui, Q. (2023). The impact of transformational leadership on the turnover intention of the new generation of knowledgeable employees: A moderated mediation model. Frontiers in Psychology, 13, 1090987. https://doi.org/10.3389/fpsyg.2022.1090987