Do employees care about diversity and inclusion? Why academic research should not be politically biased

The article below provides a good example of a robust path analysis employing WarpPLS. It suggests, among other things, that the degree to which a company promotes diversity and inclusion has a negligible effect on how an employee rates the company (which reflects job satisfaction). This is in fact not the main theme of the article, but it is something that received plenty of pushback from reviewers. The analysis was conducted a while ago, when research results that did not strongly support diversity and inclusion were typically viewed rather unfavorably by review panels in many academic journals. We thank the prestigious journal Personnel Review for their academic integrity.

Kock, N., Haddoud, M.Y., Onjewu, A.-K., & Yang, S. (2025). Unveiling workplace dynamics: Insights from voluntary disclosures on business outlook and CEO approval. Personnel Review, 54(2), 474–497.

Links to full-text versions of the article:

https://scriptwarp.com/pubs/Kock_etal_2025_PR_WorkplaceDynamics.pdf

https://pure-oai.bham.ac.uk/ws/portalfiles/portal/253297641/KockN2025Unveiling_AAM.pdf

https://www.emerald.com/insight/content/doi/10.1108/pr-03-2024-0251/full/html

Abstract:

Purpose: This inquiry extends the discourse on job satisfaction and employee referral. It aims to examine the moderating effects of perceived business outlook and CEO approval in the dynamics of job satisfaction and employee referral. A model predicting job satisfaction and employee referral through the lens of Herzberg’s two-factor theory is developed and tested. Design/methodology/approach: To remedy the overreliance on self-reported surveys, impeding generalization and representativeness, this study uses large evidence from 14,840 voluntary disclosures of US employees. A structural equation modeling technique is adopted to test the hypotheses. Findings: The inherent robust path analysis revealed intriguing findings highlighting culture and values as exerting the most substantial positive impact on job satisfaction, while diversity and inclusion played a relatively trivial role. Moreover, employees’ view of the firms’ outlook and their approval of the incumbent CEO were found to strengthen the job satisfaction–referral nexus. Originality/value: The study revisits the relationship between job satisfaction and employee referral by capturing the moderating effects of perceived business outlook and CEO approval. We believe that this investigation is one of the first to capture the impact of these two pivotal factors.

The figure below summarizes the results of the study. The overall rating variable reflects satisfaction with one’s job at a particular company, which predictably influences the probability that a person will recommend the company to a friend as a potential employer. If we had relied only on statistical significance tests, the effect of diversity and inclusion on job satisfaction would actually be negative and statistically significant. But based on the small effect size, we felt that it would be more scholarly to report the effect in question as indistinguishable from zero. With large samples, the likelihood of type I errors (false positives) increases dramatically in statistical significance tests, whether P values or confidence intervals are used.

Shiyu got us the awesome Glassdoor dataset, while Yacine and Adah-Kole did most of the theory development and later discussion work (thank you, my talented co-authors). The curious thing is that I did the analyses for this article, using WarpPLS and double-checking with other analysis tools, and was not only surprised but rather displeased with the results. But why was I displeased with the results? Well, as an academic, I work in a very diverse environment, and find that diversity stimulating. In particular, I am very interested about countries and regions (domestically and abroad), their cultures, and histories. Furthermore, as someone with a diverse background, I have lived in Brazil and New Zealand, before settling in the US. While in the US, Belgium was like a second home for several years, as I travelled there often to consult for the European Commission.

Yet, regardless of personal background, and for the sake of societal credibility, academics must report research results as they are, to the best of their ability. Furthermore, they must report research results independently from political orientation and how they personally feel about those results. Finally, they have to resign themselves to the fact that all empirical studies provide incomplete views of the world, and usually call for more research using different approaches and epistemologies.

Best regards to all!

PS: I thank Nadya Larumbe for her comments on a previous version of this post.

Conducting a difference-in-differences analysis with PLS-SEM: The classic 2x2 approach

The article below shows how one can conduct a difference-in-differences analysis employing the classic 2x2 approach for this type of analysis, using structural equation modeling via partial least squares (PLS-SEM).

Kock, N. (2024). Conducting a difference-in-differences analysis with PLS-SEM: The classic 2x2 approach. Data Analysis Perspectives Journal, 5(5), 1-8.

Link to full-text file for this and other DAPJ articles:

https://scriptwarp.com/dapj/#Published_Articles

Abstract:

Difference-in-differences analyses often employ a classic 2x2 scenario, which involves two conditions, control and treatment; and two points in time, before and after an intervention that may be tied to one of the conditions. In our analysis, we assess the impact on labor productivity of being in a more technology-intensive US state, instead of a more manufacturing-intensive one. Consistently with the difference-in-differences analysis scenario, we also assess the full latent growth effect of a government-driven age discrimination crackdown, in the technology-intensive state, on the previous effect – of being in a technology-intensive state on labor productivity. We do this by employing a model analyzed in the context of structural equation modeling via partial least squares (PLS-SEM). We also discuss advantages of using PLS-SEM in this scenario; which include assessments of causality, common method bias, and endogeneity.

Best regards to all!

Conducting a nonlinear robust path analysis

What if a researcher has only one measure for each latent variable, and still wants to perform a nonlinear “robust” analysis where no parametric assumptions (e.g., univariate or multivariate normality) are made beforehand?

This would call for a new nonlinear robust multivariate analysis approach – a nonlinear robust path analysis. Through this approach the variables in the structural model would not be “latent”, strictly speaking, and thus other assessments would have to be performed in place of a confirmatory factor analysis. That is, without multiple indicators per latent variable measurement, quality assessments must deviate somewhat from what would be used in a traditional structural equation modeling analysis.

An article illustrating a nonlinear robust path analysis with WarpPLS is available. To the best of our knowledge, this is one of the first published articles employing this type of analysis. The full reference, link to full text PDF file maintained by the University of California, and abstract for the article are available below.

Kock, N. (2015). Wheat flour versus rice consumption and vascular diseases: Evidence from the China Study II data. Cliodynamics, 6(2), 130–146.

PDF file:

http://escholarship.org/uc/item/7hk1254d

Why does wheat flour consumption appear to be significantly associated with vascular diseases? To answer this question we analyzed data on rice consumption, wheat flour consumption, total calorie consumption, and mortality from vascular diseases obtained from the China Study II dataset. This dataset covers the years of 1983, 1989 and 1993; with data related to biochemistry, diet, lifestyle, and mortality from various diseases in 69 counties in China. Our analyses point at a counterintuitive conclusion: it may not be wheat flour consumption that is the problem, but the culture associated with it, characterized by: decreased levels of physical activity, decreased exposure to sunlight, increased consumption of processed foods, and increased social isolation. Wheat flour consumption may act as a proxy for the extent to which this culture is expressed in a population. The more this culture is expressed, the greater is the prevalence of vascular diseases.

While this is an academic article, I think that the main body of the article is fairly easy to read; which was one of the expectations communicated to us by the Editor and the reviewers. WarpPLS users may find themselves in this same situation – having to prevent more technical statistical material from “spoiling” the reading experience of a non-technical audience. In this case, more technical readers may want to check under “Supporting material”, which is one of the links on the left, where they will find a detailed description of the data used and the results of some specialized statistical tests.

Enjoy!

How do I conduct a robust path analysis?

What if a researcher has only one measure for each latent variable, and still wants to perform a “robust” analysis where no parametric assumptions (e.g., univariate or multivariate normality) are made beforehand?

This would call for a new robust multivariate analysis approach – a robust path analysis. In it, the variables in the structural model would not be “latent”, and thus other assessments would have to be performed in place of a confirmatory factor analysis.

An article illustrating a robust path analysis with WarpPLS is available. To the best of our knowledge, this is the first published article employing this type of analysis. The full reference, link to full text PDF file, and abstract for the article are available below.

Kock, N., & Gaskins, L. (2014). The mediating role of voice and accountability in the relationship between Internet diffusion and government corruption in Latin America and Sub-Saharan Africa. Information Technology for Development, 20(1), 23-43.

PDF file:

http://www.scriptwarp.com/warppls/pubs/Kock_Gaskins_2014_ITD_NetCorrup.pdf

We examine relationships among Internet diffusion, voice and accountability, and government corruption based on data from 24 Latin American and 23 sub-Saharan African countries from 2006 to 2010. Our study suggests that greater levels of Internet diffusion are associated with greater levels of voice and accountability and that greater levels of voice and accountability are associated with lower levels of government corruption. Also, there seems to be an overall relationship between Internet diffusion and government corruption, which is primarily indirect and mediated by voice and accountability. Our study builds on modernization theory, and employs the method of robust path analysis, implemented through the software WarpPLS. Policy-makers in developing countries aiming at increasing voice and accountability at the national level, and thus the degree to which their citizens participate in the country’s governance, should strongly consider initiatives that broaden Internet access in their countries.