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Measuring organizational climate via psychological networks analysis

Igor Menezes (University of Hull, Hull, UK)
Ana Cristina Menezes (AdaptPsy Analytics, Feira de Santana, Brazil)
Elton Moraes (Fundação Getúlio Vargas, São Paulo, Brazil)
Pedro P. Pires (Federal University of Rio de Janeiro, Rio de Janeiro, Brazil)

International Journal of Organization Theory & Behavior

ISSN: 1093-4537

Article publication date: 28 September 2021

Issue publication date: 16 November 2021




This study investigates organizational climate under the thriving at work perspective using a network approach. The authors demonstrate how organizational climate functions as a complex system and what relationships between variables from different dimensions are the most important to characterize the construct.


By surveying 119,266 workers from 284 companies based in Brazil, the authors estimated a Gaussian graphical model with LASSO regularization for the complete dataset and for two subsets of cases randomly drawn from the whole dataset. The walktrap algorithm was applied for community detection, and a strong model for measurement invariance was fit to test whether the organizational climate is perceived similarly across groups.


Results show that the networks estimated for both groups are quite consistent, with similar number of communities and items detected. The same pattern was found for the expected influence of each item. Measurement invariance was confirmed, showing that organizational climate is perceived similarly in both groups. The most important community detected and whose items have higher levels of centrality was organizational commitment, followed by a community centered around macro-organizational aspects covering cultural integrity, organizational agility and responsible leadership.

Research limitations/implications

Studies in the field have attested to the possibility of investigating the phenomenon from four (Campbell et al., 1970) to over 80 dimensions (Koys and DeCottis, 1991). As a result, since several dimensions have been produced to investigate organizational climate, there is no consensus on the quality and number of dimensions that should be considered to measure such a vast and multifaceted construct. Built on thriving at work perspective, eight dimensions were devised to cover a wide range of characteristics that distinguish organizational climate, including those related to Industry 4.0 (Coetzee, 2019). However, one may argue that a few dimensions, namely social responsibility, diversity and inclusion, or even more items describing work-life balance could expand the depth and breadth of the instrument and potentially trigger new associations that might eventually impose a new logic to the comprehension of climate as a system. Future studies combining the dimensions investigated in this study with other dimensions are therefore highly recommended for an even more comprehensive investigation.

Practical implications

The results of this investigation show how to apply psychological networks to gain insights into different variables and dimensions of organizational climate. These findings can be used for the development of organizational policies focused on the most relevant aspects of organizational climate. This information would allow organizations to go beyond simply describing the individual frequencies for each item and could even be used to create a weighted scoring model that could prioritize variables with higher levels of centrality.


To the authors’ knowledge, this is the first study that investigates organizational climate using psychological networks; it provides a better understanding of the relationships established between items from different dimensions as opposed to the common cause framework whose focus is on the investigation of dimensions separately.



The authors acknowledge the VIPER high-performance computing facility of the University of Hull and its support team.


Menezes, I., Menezes, A.C., Moraes, E. and Pires, P.P. (2021), "Measuring organizational climate via psychological networks analysis", International Journal of Organization Theory & Behavior, Vol. 24 No. 3, pp. 229-250.



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