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This paper investigates how a firm’s organizational culture profile (configuration of organizational culture types) influences the effectiveness of operations management (OM) practices in improving their targeted outcomes.

We developed alternative hypotheses based on contingency and paradox perspectives to predict the effectiveness of OM practices in dominant (one prevalent organizational culture type) vs eclectic (opposing organizational culture types at a similar level) organizational culture profiles. They were tested using data from over 7,000 respondents across 330 manufacturing plants in 15 countries.

Consistent with contingency theory, OM practices oriented toward innovation are more efficacious in plants with an adhocracy-dominant organizational culture profile and practices targeting supply chain (SC) control are less effective in a clan-dominant organizational culture profile. Consistent with paradox theory, OM practices oriented toward efficiency or SC control are more effective in plants with an eclectic organizational culture profile.

This study offers relevant practical implications regarding the effectiveness of various OM practices, whether they are used in an aligned dominant organizational culture profile or in an eclectic organizational culture profile.

Previous research on organizational culture provides a limited understanding of the effectiveness of OM practices in the presence of strategic tensions, such as opposing organizational cultures or opposing targeted outcomes. This research concludes that the validity of the contingency or paradox perspective depends on strategic tensions faced, with important implications for research and practice.

Lean construction (LC) consists of very effective techniques; however, its implementation varies considerably from one industry to another. Although numerous lean initiatives do exist in the construction industry, the research topic related to LC implementation is still unexplored due to the scarcity of validated assessment frameworks. This study aims to provide the first attempt in developing a structural model for successful LC implementation.

This study developed a Lean construction model (LCM) by critically reviewing seven previous LC frameworks from different countries, defining 18 subprinciples grouped into 6 major principles and formulating testable hypotheses. The questionnaire was pre-tested with 12 construction management experts and revised by 4 specialized academics. A pilot study with 20 construction units enhanced content reliability. Data from 307 Moroccan construction companies were collected to develop a measurement model. SPSS V. 26 was used for Exploratory Factor Analysis, followed by confirmatory factor analysis using AMOS version 23. Finally, a structural equation model statistically assessed each construct's contribution to the success of LC implementation.

This work led to the development of an original LCM based on valid and reliable LC constructs, consisting of 18 measurement items grouped into 6 LC principles: Process Transparency, People involvement, Waste elimination, Planning and Continuous improvement, Client Focus and Material/information flow and pull. According to the structural model, LC implementation success is positively influenced by Planning and Scheduling/continuous improvement (β = 0.930), followed by Elimination of waste (β = 0.896). Process transparency ranks third (β = 0.858). The study demonstrates that all these factors are mutually complementary, highlighting a positive relationship between LC implementation success and the holistic application of all LC principles.

To the best of the authors’ knowledge, this study is the first attempt to develop a statistically proven model of LC based on structural equation modelling analysis, which is promising for stimulating construction practitioners and researchers for more empirical studies in different countries to obtain a more accurate reflection of LC implementation. Moreover, the paper proposes recommendations to help policymakers, academics and practitioners anticipate the key success drivers for more successful LC implementation.