The Moderating Role of Government Policy on Contractors’ Risk Attitudes in Malaysia Construction Companies The Moderating Role of Government Policy on Contractors’ Risk Attitudes in Malaysia Construction Companies
Abstract
Contractors’ risk attitudes influence their bidding decisions because of their exposure to uncertainties and competitions. The competing contractors may have, over time, developed different risk attitudes that are part of their own organizational culture. Different risk attitudes explain the peculiarity in how firms do their businesses. In a risky situation, individuals’ perceptions have influence on their own risk attitudes. Organizational risk attitude operates within an organization and it defines the accepted and unaccepted risks. This is attributed to how people perceived the control over the intended behaviour which relies on the availability of resources, competency, educational background, support from other people and past experience in the same project. Therefore, this study aims to identify the factors affecting contractors' risk attitudes and then determine the relationship with government policy. A total of 140 copies of questionnaire were randomly distributed to the construction companies in Malaysia. Out of the 140 copies of questionnaire distributed, 124 copies were returned. Conversely, 12 copies of the questionnaire were found to be unusable due to missing data or provided the same responses to all the questions. Thus, overall, 80% of the total copies of questionnaire were usable thereby making up an effective sample of 112. SmartPLS 3 for structural equation modelling was utilized in confirming the hypotheses developed for the study. The findings of this research confirmed that government policy (rules and regulations) played a moderating role in enhancing the factors affecting contractors’ risk attitudes in construction companies in Malaysia.
References
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Chauvin, B., Hermand, D., & Mullet, E. (2007). Risk perception and personality facets. Risk Analysis: An International Journal, 27(1), 171-185.
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Chin, W. W. (1998b). The partial least squares approach for structural equation modelling. In George A. Marcoulides (Ed.), Modern Methods for BusinessResearch, Lawrence Erlbaum Associates, Lawrence Erlbaum Associates, Mahwah, NJ, 295-336.
Chin, W. W., Marcolin, B. L., & Newsted, P. R. (2003). A partial least squares latent variable modeling approach for measuring interaction effects: Results from a Monte Carlo simulation study and an electronic-mail emotion/adoption study. Information systems research, 14(2), 189-217.
Chin, W. (2010). How to write up and report PLS analyses. In V. Esposito Vinzi. Handbook of Partial Least Squares (pp. 655-690): Springer Berlin Heidelberg.
Chun, Y., Tsai, C., & Hsu, Y. (2016). Research on the operational performance of ISO 14000 Certified Taiwan’s manufacturers.
Chung, T. S., Jiang, L. Y., Li, Y., & Kulprathipanja, S. (2007). Mixed matrix membranes (MMMs) comprising organic polymers with dispersed inorganic fillers for gas separation. Progress in polymer science, 32(4), 483-507.
Cohen, J. (1988). Statistical power analysis for the behavioural sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum Associates, Inc.
Diekola, A. M. (2016). The moderating effect of environmental regulation and policy on the relationship between total quality management (TQM) and organizational performance in the Malaysian food and beverage companies (Doctoral dissertation, Universiti Utara Malaysia).
Dikmen, I., Birgonul, M. T., & Han, S. (2007). Using fuzzy risk assessment to rate cost overrun risk in international construction projects. International Journal of Project Management.
Etemadinia, H., & Tavakolan, M. (2018). Using a hybrid system dynamics and interpretive structural modeling for risk analysis of design phase of the construction projects. International Journal of Construction Management, 1-20.
Falk, R. F., & Miller, N. B. (1992). A primer for soft modelling. Ohio: The University of Akron Press.
Flanagan, R., & Norman, G. (1993). Risk management and construction. Oxford, Blackwell Science Ltd.
Florescu, E. (2010). State of the Future. J. C. Glenn, & T. J. Gordon (Eds.). Washington DC: American Council for the United Nations University.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable and measurement error. Journal of Marketing Research, 18, 39- 50.
Gibb, K. (2011). Delivering new affordable housing in the age of austerity: housing policy in Scotland. International Journal of Housing Markets and Analysis, 4(4), 357-368.
Goleman, D. (1998a), “What makes a leader?” Harvard Business Review, pp. 93‐102.
Goleman, D. (1998b), “The emotional intelligence of leaders”, Leader to Leader, fall, pp.
Hair, J.F., Ringle, C.M., Sarstedt, M., 2011. PLS-SEM: indeed a silver bullet. J. Mark. Theory Pract. 19 (2), 139–151.
Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2006). Multivariate data analysis 6th ed. Uppersaddle River: Pearson Prentice Hall.
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. The Journal of Marketing Theory and Practice, 19(2), 139-152.
Hair, J. F., Sarstedt, M., Pieper, T. M., & Ringle, C. M. (2012). The Use of Partial Least Squares Structural Equation Modeling in Strategic Management Research: A Review of Past Practices and Recommendations for Future Applications. LongRange Planning, 45(6), 320-340.
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2013). Editorial-partial least squares structural equation modelling: Rigorous applications, better results and higher acceptance. Long Range Planning, 46(1-2), 1-12.
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2014). A primer on partial least squares structural equation modelling (PLS-SEM). Thousand Oaks: Sage Publications.
Hamid, A., Rahim, A., Yusuf, W., Zulkifli, W., & Singh, B. (2003). "Hazards at Construction Sites", the Proceedings of the fifth Asia-Pacific Structural Engineering and Construction Conference.
Hamzah, A. (2004). Policy and planning of the tourism industry in Malaysia. The sixth. ADRF General Meeting.
Hartono, B., Sulistyo, S. R., Praftiwi, P. P., & Hasmoro, D. (2014). Project risk: Theoretical concepts and stakeholders' perspectives.
Hasan, Nordin, A.A. Hear and Mohd, (2012). The evolution of environmental policy in
Malaysia. Natural Resources Forum 30 (2006) 37–50).
Helm, S., Eggert, A., & Garnefeld, I. (2010). Modelling the impact of corporate reputation on customer satisfaction and loyalty using partial least squares. In V. Esposito Vinzi, W. W.Chin, J. Henseler & H. Wang (Eds.), Handbook ofPartial Least Squares (pp. 515-534).
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