Factors Affecting Safety in Highway Construction Industry

The construction industry has grown with the rapid advancements in technology along with it there has been an increasing number of worker fatalities during construction. This study is aimed at determining the relevant factors which will help to make safety improvements in highway construction [9]. The research will help to improve the safety measures being implemented in the construction workplace so that worker fatalities can be significantly reduced. In this research the focus of the researcher is to utilize statistical tools for analyzing the data that will gathered from survey on the chosen topic. The discussion are also carried out on future scope of this study along with the expected outcomes from this study.

You Kim [3] stated that the highway construction industry is perceived as required into the development of country. The construction projects are associated with poor performance, lack of control; therefore it is encountered uncertainties in terms of safety that can threaten the completion of project work. Thomson and McLeod [6] argued that the construction industry is known for their complexities to deal with the construction safety. The industry has high workforce turnover that can impact on safety awareness of the workers. Following data provides circumstances of work-related deaths in Australia:

From the year 2003-2016, 3414 workers lost the lives in work related incidents. In the year 2016, there were approximately 182 workers fatalities equate to the fatality rate of 1.5 fatalities per 100,000 workers. It was the lowest rate from beginning of the year 2003 [5].    

In order to reduce the risks, risk management plan is used to determine possibility of the physical damage and injury into the construction site [1]. The risk responses commonly used are risk transfer, retention, avoidance and reduction. Zhao, Fu and Zhang [2] reported that brainstorming is popular tool used by the construction industry to overcome with the safety issues. The risk management into Highway construction industry is relied on risk identification as well as qualitative risk analysis [4]. Risk register is a management tool that is assisted the project team to go through the risks through the project lifecycle.  It helps to identify the project sources, risk events and risk impact.

This section provides detailed processes as well as techniques to be utilized while conducting a study for analyzing the improvements of safety in Highway construction industry by project risk management. The research analyst selected of positivism as the research philosophy to conduct the study. This philosophy ensured about the application of scientific processes and also logic. It is selected as it allows revealing of hidden information related to improvements of safety in Highway construction industry by project risk management. At the time of selecting of research approach, the research analyst has selected of deductive research approach to conduct the data collection from primary sources. It allowed revealing path for conducting research study in efficient manner [7]. It also allowed the research analyst to define as well as use of past concepts along with theories to conduct the study. Descriptive research design is selected for this study as it is opted to gather relevant information from the journals as well as reports published by organization. This method is used to evaluate key improvement factors of safety in Highway construction industry by project risk management. The research analyst described the process followed into the risk management for highway construction. Primary data collection method is selected to collect of raw data helps to cater as per the research requirements. The raw data are used to validate the sources in terms of reliability [10]. As the data are obtained from the survey questionnaire, therefore the researcher has conducted of quantitative data analysis method. The questionnaire survey is distributed among the safety experts in highway construction [6]. It helps to get statistical data related to the research topic. Those statistical data are analyzing validity of developed hypothesis. The risk factor assessment is also implemented to classify the risk factors based on degree of importance.

Risk Management in Highway Construction Industry

For this particular research a hypothesis has been set to determine whether Use of mobile tool and hazard assessment and safety plans are the major effective factors of improving the safety in highway construction by project risk management. The hypothesis is presented as below:

Null hypothesis (H₀): Use of mobile tool and hazard assessment and safety plans are not the major effective factors of improving the safety in highway construction by project risk management.

Alternative hypothesis (H₁): Use of mobile tool and hazard assessment and safety plans are the major effective factors of improving the safety in highway construction by project risk management.

The statistical data which is used to provide identified hypothesis are regression analysis. It is a technique that can serve basis for drawing inferences about the relationships among the interrelated variables [8]. Based on the regression model, the research analyst can identify both dependent as well as independent variable resent into this particular study. The regression model is:

Safety improvements in highway construction = A + B * Use of Mobile tool + C * Use of hazard assessment + D * Use of safety plans + e

Where;

A = Intercept of Linear Regression Model

B = Coefficient of Use of Mobile tool

C = Use of hazard assessment

D = Use of safety plans

E = Error term

The benefits of regression analysis are that it can indicate if the independent variables have significant relationships with the dependent variable. It also indicates relative strength of various independent variables effect on the dependent variable as well as helps to make predictions.

Table 1. Descriptive Statistics for the survey responses

Statistics	Use of Mobile tool	Use of Hazard assessment	Use of Safety Plans
Mean	2.1	1.95	1.55
Standard Error	0.190567021	0.198348444	0.169752141
Median	2	2	1
Mode	2	2	1
Standard Deviation	0.852241626	0.887041208	0.759154655
Sample Variance	0.726315789	0.786842105	0.576315789
Kurtosis	1.01177459	-0.245946277	4.587477325
Skewness	0.929631348	0.60703103	1.818493104
Range	3	3	3
Minimum	1	1	1
Maximum	4	4	4
Sum	42	39	31
Count	20	20	20

The above table 1 shows the descriptive statistics of the data being collected through survey questionnaire. The table represents the statistics that has been calculated for the independent variables. The statistics shows the total responses that has been gathered in context to the independent variables. The above table shows the validity of the data being collected as responses through survey questionnaire. 

Regression Statistics
Multiple R	0.187765265
R Square	0.035255795
Adjusted R Square	-0.145633744
Standard Error	1.37158711
Observations	20

ANOVA
	df	SS	MS	F	Significance F
Regression	3	1.099980793	0.366660264	0.194902342	0.898326131
Residual	16	30.10001921	1.8812512
Total	19	31.2

	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%	Lower 95.0%	Upper 95.0%
Intercept	2.843320849	1.464342023	1.941705424	0.069993321	-0.260945566	5.947587264	-0.260945566	5.947587264
Use of Mobile tool	0.019927014	0.377429907	0.052796596	0.95854755	-0.780188645	0.820042674	-0.780188645	0.820042674
Use of Hazard assessment	-0.101219629	0.369447469	-0.273975701	0.787608828	-0.884413276	0.681974017	-0.884413276	0.681974017
Use of Safety Plans	-0.314702775	0.42280816	-0.744315757	0.46747726	-1.211016034	0.581610483	-1.211016034	0.581610483

 The above table 2 shows the regression statistics for the data being collected through the survey questionnaire. ANOVA is being used for this research as a statistical technique for assessment of the potential differences in a dependent variable with the help of independent variables of 2 or more categories. In the table, df is denoted as the mean squares formed by dividing sum of squares by their associated degrees of freedom. SS means the statistics that is used for testing hypothesis and the means of population. MS is denoted as mean squares and the value of each mean square is computed by dividing the value of sum of squares by their associated degrees of freedom. F is the distribution of all possible values of the f statistic in the analysis. Significance F is the value that is calculated for finding that means between two populations are different.

From the overall analysis represented above on Table 2, it can be concluded that the independent variables that is Use of Mobile tool, Use of hazard assessment, Use of safety plans is positively linked with safety improvements in highway construction. In Table 1, the analysis reflects that the use of mentioned factors as dependent variables will help to improve the safety conditions in the workplace during highway construction.

Expected outcomes and Conclusion

The outcomes that were expected from this research has been achieved successfully with the help of analyzing the data gathered from survey. The outcomes of this research reflect that the use of mobile tool, hazard assessment and safety plans are the major effective factors of improving safety in highway construction by project risk management.

From the data gathered during this research, it can be concluded that the utilization of risk management practices will help to improve the safety measures being implemented in highway construction. The risk management in construction projects will ensure that successful outcomes are achieved from projects with standard quality. It has been identified that for reducing the risks, risk management plan is used to determine possibility of the physical damage and injury into the construction site. Risk register is a management tool that is assisted the project team to go through the risks through the project lifecycle.  

This research is limited to determining the use of mobile tool, hazard assessment and safety plans for making improvements in safety for construction of highways. Further research can be carried out to cover up the gaps in this study and in-depth analysis to check the validity of undertaken topic. 

References

• Diugwu and D. Baba, “A Health and Safety Improvement Roadmap for the Construction Industry”, Journal of Construction Engineering and Project Management, vol. 4, no. 1, pp. 37-44, 2014.
• Zhao, X. Fu and Y. Zhang, “Research on Risk Assessment and Safety Management of Highway Maintenance Project”, Procedia Engineering, vol. 137, pp. 434-441, 2016.
• Kim, “The Role of Ergonomics for Construction Industry Safety and Health Improvements”, Journal of Ergonomics, vol. 07, no. 02, 2017.
• Oikonomou and G. Tsoulfas, “Risk management in a major highway construction joint venture project”, International Journal of Decision Sciences, Risk and Management, vol. 5, no. 4, p. 311, 2014.
• gov.au, “Fatality statistics”, Safe Work Australia, 2016. [Online]. Available: https://www.safeworkaustralia.gov.au/statistics-and-research/statistics/fatalities/fatality-statistics. [Accessed: 23- Sep- 2018].
• Thomson and J. McLeod, “New frontiers in qualitative longitudinal research: an agenda for research”, International Journal of Social Research Methodology, vol. 18, no. 3, pp. 243-250, 2015.
• Thiem, “Designing research in the social sciences”, International Journal of Social Research Methodology, vol. 18, no. 4, pp. 453-454, 2015.
• Hwang, X. Zhao and L. Toh, “Risk management in small construction projects in Singapore: Status, barriers and impact”, International Journal of Project Management, vol. 32, no. 1, pp. 116-124, 2014.
• Szyma?ski, “Risk management in construction projects”, Procedia Engineering, vol. 208, pp. 174-182, 2017.Maseko, “IDENTIFICATION OF RISK FACTORS AFFECTING CONSTRUCTION OF PROJECTS: THE CASE OF EMERGING ECONOMY”, Risk Governance and Control: Financial Markets & Institutions, vol. 7, no. 4-2, pp. 247-260, 2017.