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Assessment of Barriers to Effective Permit to Work (PTW) Implementation in Selected Oil and Gas Companies in Nigeria

Nwafor Chinenye, John N Ugbebor and, Onuoha Forman

Abstract

The Permit to Work (PTW) is a vital safety management tool designed to ensure safe work practices in hazardous environments. This study evaluates the barriers to effective PTW implementation in enhancing safety within selected Nigerian oil and gas industries, using both qualitative and quantitative methods. Data was collected via self-structured, electronically administered 5-point Likert Scale Questionnaires, ranging from 5 (Strongly Agree) to 1 (Strongly Disagree). Instrument reliability was assessed using Cronbach's alpha, and content validity was verified. A proportionate stratified sample technique was used to distribute 368 questionnaires across four oil and gas industries (one local and three multinational), with 350 responses selected for analysis. The data was analyzed using descriptive statistics, correlation, regression, principal component analysis (PCA), Bartlett's sphericity test, and the Kaiser- Meyer-Olkin (KMO) test, utilizing IBM SPSS version 26 and XLSTAT version 18. Results indicated good reliability of barriers between PTW and safety outcomes. Management support showed the highest reliability (Cronbach’s Alpha 0.857), followed by communication, resources, and equipment sharing (0.836, 0.845 respectively). Training and competence, awareness, and attitude had the lowest reliability scores (0.690 and 0.684) but were still acceptable. High mean values for training and competence, awareness and attitude, communication, and resources and equipment (4.22, 4.45, 4.17, 4.23, respectively) indicated strong agreement among respondents. CA revealed significant negative correlations between policies and procedures and safety outcomes: accidents (r = -0.5), near misses (r = -0.35), and regulatory violations (r = -0.39). Bartlett's sphericity test (?² = 1717.093, p < 0.0001) and KMO test (0.706) confirmed data suitability for PCA. Regression analysis showed the model was statistically significant (F = 43.14, p < 0.001),

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