Authors:
Prasanta Roy,Purnachandra Saha,Moitreyee Paul,Prattyush Roy,DOI NO:
https://doi.org/10.26782/jmcms.2025.09.00006Keywords:
Amos,Oil and gas construction,Risk impact,Scale development,SPSS,Abstract
Risk management is a crucial element in ensuring the success of construction activities in the oil and gas sector, which are inherently complex and susceptible to numerous risks. This study aims to develop a scale of multiple items to evaluate the contribution of different types of risk towards the total risk of an oil and gas construction project. A structured questionnaire was distributed among industry professionals and academicians, capturing their insights on risk impact and likelihood. The reliability analysis has been performed in SPSS software, and confirmatory factor analysis (CFA) has been performed in AMOS software. Findings highlight that scaled 13 risks cover all the important segments of the construction project in 3 categories. It is also observed that the individual impact of risk groups like fin & tech, project management, and procurement is maximum on total risk rather than the combination of these three.Refference:
I. Akhavan Tabassi, A., Ramli, M., Bakar, A. H. A., & Pakir, A. H. (2012). “Transformational leadership and team effectiveness in construction teams: The mediating role of teamwork planning and the moderating role of task structure.” Project Management Journal, 43(6), 17-29. 10.1002/pmj.21319.
II. Assaf, S. A., & Al-Hejji, S. (2006). “Causes of delay in large construction projects.” International Journal of Project Management, 24(4), 349–357. 10.1016/j.ijproman.2005.11.010
III. Chan, D. W. M., & Kumaraswamy, M. M. (1997). “A comparative study of causes of time overruns in Hong Kong construction projects.” International Journal of Project Management, 15(1), 55–63. 10.1016/S0263-7863(96)00039-7
IV. Cheung, S. O., Suen, H. C. H., & Chow, P. T. (2004). “PPMS: A web-based construction project performance monitoring system.” Automation in Construction, 13(3), 361–376. 10.1016/j.autcon.2003.12.001
V. Cheung, S. O., Yiu, T. W., & Yeung, S. F. (2006). “A study of construction dispute negotiation strategies.” Journal of Construction Engineering and Management, 132(8), 805–814. 10.1061/(ASCE)0733-9364(2006)132:8(805)
VI. Clark, Lee Anna, and David Watson. 1995. “Constructing Validity: Basic Issues in Objective Scale Development.” Psychological Assessment 7 (3): 309–319.
VII. Colwell, S. R., Aung, M., Kanetkar, V., & Holden, A. L. (2008). Toward a measure of service convenience: multiple‐item scale development and empirical test. Journal of Services Marketing, 22(2), 160-169.
VIII. Cortina, J.M. (1993). What is coefficient alpha? An examination of theory and applications. Journal of Applied Psychology, 78(1), 98–104.
IX. Doloi, H., Sawhney, A., Iyer, K. C., &Rentala, S. (2012). “Analysing factors affecting delays in Indian construction projects.” International Journal of Project Management, 30(4), 479–489. 10.1016/j.ijproman.2011.10.004
X. Erol, H., Dikmen, I., Atasoy, G., &Birgonul, M. T. (2022). An analytic network process model for risk quantification of mega construction projects. Expert Systems with Applications, 191, 116215.
XI. Godovykh, M., Hacikara, A., Baker, C., Fyall, A., &Pizam, A. (2023). Measuring the perceived impacts of tourism: a scale development study. Current Issues in Tourism, 27(15), 2516–2532. 10.1080/13683500.2023.2243003
XII. Hair, J. F. J., W. C. Black, B. J. Babin, and R. E. Anderson. 2010. Multivariate Data Analysis. 7th ed. Prentice Hall, NJ: Pearson.
XIII. Hinkin, T. R. 1995. “A Review of Scale Development Practices in the Study of Organizations.” Journal of Management 21 (5): 967–988.
XIV. Hwang, B.-G., & Lim, E. T. K. (2013). “Critical success factors for key project players and objectives: Case study of Singapore.” Journal of Construction Engineering and Management, 139(2), 204–215. 10.1061/(ASCE)CO.1943-7862.0000590
XV. Jaf, D. K. I., Abdulrahman, P. I., Mohammed, A. S., Kurda, R., Qaidi, S. M., &Asteris, P. G. (2023). Machine learning techniques and multi-scale models to evaluate the impact of silicon dioxide (SiO2) and calcium oxide (CaO) in fly ash on the compressive strength of green concrete. Construction and Building Materials, 400, 132604.
XVI. Kautish, P., Sharma, R., & Khare, A. (2020). Multi-Item Scale Development for Online Consumption Emotion Construct And Psychometric Evaluation for Relationship Marketing. Journal of Relationship Marketing, 20(2), 91–134. 10.1080/15332667.2020.1717282
XVII. Kotnala, V., & Singh, A. P. (2024). Construction and Validation of Conduct Disorder Scale: A Clinician and Self-Report Measure. In Health Psychology in Integrative Health Care (pp. 266-273). Routledge.
XVIII. Love, P. E. D., Edwards, D. J., & Irani, Z. (2012). “Moving beyond optimism bias and strategic misrepresentation: An explanation for social infrastructure project cost overruns.” IEEE Transactions on Engineering Management, 59(4), 560–571. 10.1109/TEM.2012.2183357
XIX. Love, P. E. D., Edwards, D. J., & Smith, J. (2005). “A forensic examination of the causal mechanisms of rework in a structural steel supply chain.” Managerial Auditing Journal, 20(3), 187–197. 10.1108/02686900510585610
XX. MacKenzie, Scott B., Philip M. Podsakoff, and Nathan P. Podsakoff. 2011. “Construct Measurement and Validation Procedures in MIS and Behavioral Research: Integrating New and Existing Techniques.”MIS Quarterly 35 (2): 293–334.
XXI. MacKenzie, Scott B., Philip M. Podsakoff, and Nathan P. Podsakoff. 2011. “Construct Measurement and Validation Procedures in MIS and Behavioral Research: Integrating New and Existing Techniques.” MIS Quarterly 35 (2): 293–334.
XXII. Malhotra, N. K., and S. Dash. 2010. Marketing Research: An Applied Approach. New Delhi: Dorling Kindersley.
XXIII. O’Connor, J. T., Rusch, J. J., & Schulz, M. J. (1987). “Constructability concepts for engineering and procurement.” Journal of Construction Engineering and Management, 113(2), 235–248. 10.1061/(ASCE)0733-9364(1987)113:2(235)
XXIV. Ozorhon, B., Arditi, D., Dikmen, I., &Birgonul, M. T. (2008). “Implications of culture in the performance of international construction joint ventures.” Journal of Construction Engineering and Management, 134(5), 361–370. 10.1061/(ASCE)0733-9364(2008)134:5(361)
XXV. Papadopoulou, T. C., & Dimopoulos, T. (2018). “Critical risk factors in the construction industry: A review.” Engineering, Construction and Architectural Management, 25(9), 1100–1120. 10.1108/ECAM-03-2017-0059
XXVI. Park, J., Woo, S. E., & Kim, J. (2024). Attitudes towards artificial intelligence at work: Scale development and validation. Journal of Occupational and Organizational Psychology, 97(3), 920-951.
XXVII. Podsakoff, P. M., and D. W. Organ. 1986. “Self-reports in Organizational Research: Problems and Prospects.” Journal of Management 12 (4): 531–544.
XXVIII. Podsakoff, P. M., S. B. MacKenzie, J. Y. Lee, and N. P. Podsakoff. 2003. “Common Method Biases in Behavioral Research: A Critical Review of the Literature and Recommended Remedies.” Journal ofApplied Psychology 88 (5): 879–903.
XXIX. Raja, M. W., Anand, S., & Kumar, I. (2020). Multi-item scale construction to measure consumers’ attitude toward advertising music. Journal of Marketing Communications, 26(3), 314-327.
XXX. Tuck, A. B., & Thompson, R. J. (2023). The Social Media Use Scale: Development and Validation. Assessment, 31(3), 617-636. (Original work published 2024). 10.1177/10731911231173080
XXXI. Tavakol, M., & Dennick, R. (2011). Making sense of Cronbach’s alpha. International Journal of Medical Education, 2, 53–55.
XXXII. Zwikael, O., &Smyrk, J. (2012). Project Management for the Creation of Organisational Value. Springer. 10.1007/978-1-4614-1373-9