International Journal of Emerging Research in Engineering, Science, and Management
Vol. 5, Issue 4, pp. 11-26, Oct-Dec 2026.
https://doi.org/10.58482/ijeresm.v5i4.2

Received: 23 Aug 2026 | Revised: 11 Oct 2026 | Accepted: 16 Oct 2026 | Published: 24 Oct 2026

This work is licensed under a Creative Commons Attribution 4.0 International License.

Synchronising People, Processes and Business Environment for Project Management Effectiveness: A Mixed-Methods Study of the Indian Steel Industry

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1Biplab Kumar Dey

2Souren Sarkar

1Research Scholar, Chhattisgarh Swami Vivekanand Technical University, Bhilai, India.
2Professor & Head, Shri Shankaracharya Technical Campus, Bhilai, India.

Abstract: Executing projects in India’s integrated steel plants depends on properly synchronizing people, processes, and the business environment. However, empirical evidence on the relationships between these three dimensions and project management effectiveness (PME) remains limited. This paper tests a model in which People Synchronisation (PS), Process Synchronisation (PR), and Business Environment (BE) are hypothesized to positively affect PME, using a quantitative approach followed by a qualitative documentary analysis of industry literature. The study administered a 16-item, five-point Likert-scale questionnaire to 160 individuals from the project, operations, quality, procurement, human resource management, and technical departments of 21 Indian integrated steel and long-products companies. The data were analyzed using descriptive statistics, reliability analysis, the Kaiser-Meyer-Olkin (KMO) measure, Bartlett’s test of sphericity, Exploratory Factor Analysis (EFA), Pearson correlation, Confirmatory Factor Analysis (CFA), Structural Equation Modeling (SEM), and multiple regression. All computations have been made through Python with SPSS output conventions. The Cronbach’s alpha values for all four constructs were well below the commonly used threshold of 0.70 (alpha = 0.12–0.22), and the KMO value was 0.491. Bartlett’s test of sphericity was non-significant (χ² = 127.31, df = 120, p = 0.307), indicating that the correlation matrix does not provide sufficient evidence of relationships among the items for factor analysis. The CFA four-factor model produced an inadmissible (Heywood) solution, and all structural paths from PS, PR, and BE to PME were non-significant. In the composite-score multiple regression, the model explained 2.7% of the variance in PME (R² = 0.027, F(3,156) = 1.44, p = 0.233). Because the instrument lacked latent structure, none of the hypothesized relationships were validated. The findings are discussed in detail, along with possible reasons related to instrument- and sample-related issues and methodological problems, including common method variance and single-source bias.

Keywords: Project management effectiveness, people synchronisation, process synchronisation, business environment, structural equation modelling, steel industry, reliability analysis.

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