System Thinking Approach for Investigation of Construction Safety Climate

Transcription

1 J. Civil Eng. Architect. Res. Vol. 1, No. 5, 2014, pp Received: July 1, 2014; Published: November 25, 2014 Journal of Civil Engineering and Architecture Research System Thinking Approach for Investigation of Construction Safety Climate Rehan Masood 1, Wajeeha Farooqi 1 and Hafiz Zahoor 2 1. Department of Civil Engineering, University of Lahore, Lahore 54500, Pakistan 2. Department of Building and Real Estate, Hong Kong Polytechnic University, Hung Hom, Kowloon , Hong Kong Corresponding author: Rehan Masood (rehan.masood@ce.uol.edu.pk, engr.rehan@yahoo.com) Abstract: Construction is highly labor intensive and considered as one of the most hazardous and vulnerable industries around the world. Safety perception of all tradesmen, performing different construction tasks simultaneously at the same work-site, has a significant relationship to the occurrence of accidents. Variation in workers perception about safety not only leads to hazardous conditions on work-site but it also results in a situation where a worker may become victim to an accident, whether it happens because of his negligence or his co-workers. To assess the safety perceptions of different tradesmen, a cross-level safety climate questionnaire survey (comprising of forty statements) was conducted on 36 construction sites in different cities of Pakistan. Respondents were belonging to different trades (15) and a good response rate of 73% was achieved. Data were analyzed using system thinking approach and a minimum of three responses were considered for analysis. Results showed that although plasters/painters had clear percpetions for safety but their thinking for safety performance was marginal. Nonetheless Electrician/Mechanicshave opposite opinion. Blacksmith/Welder and Electrician/Mechanic tradesmen have clear safety perceptions in comparison with all others. For cross-level safety climate, most of the workers (except one or two out of fifteen worker types) agree that management acts quickly on safety problems and supervisors are the major source to resolve safety issues. Sixteenassociated perception rules were developed by the application of system thinking on different trademen whichmay help the construction managers to enhance their safety climate by reducing accident rate. Key words: Cross-level safety climate, data mining, system thinking, construction workers, Pakistan. 1. Introduction Construction workers are backbone of construction industry especially in those countries where industries are less mechanized and more labor intensive. This becomes the prime reason for high rate of injuries and fatalities on the construction sites. Most accidents are not caused by workplace system failure but by human unsafe behavior [1]. This was identified that one of the root causes of construction accidents was unsafe site conditions [2]. Eighty percent of the accidents are caused by human behavior in United Kingdom [3]. Unsafe behavior can be regarded as the resultant action which is stimulated and reinforced by organizational factors like poor safety climate. Another important reason for occurrence of accidents highlighted is the difference in management s attitude and workers behavior [4]. Accident patterns are investigated with different methods using data-mining as well as system thinking causal loop diagram [5, 6]. This is recommended to provide and maintain a safe system of work to reduce the fatalities [7]. Hence, there is a need to study the behavior and safety perception of tradesmen so that causes of accidents can be identified with the ultimate aim to enhance the construction safety climate. Current study aims to investigate the reasons of accidents by studying safety perceptions of

2 System Thinking Approach for Investigation of Construction Safety Climate 347 construction workers belonging to different trades through the application of system thinking which has a strong association with safety climate. System thinking process helps to investigate the interaction of the elements of a system which influence each other, and it deals with the problems as a whole rather than dealing them individually [8]. Hence, it provides a better solution to the problem than other techniques. This study addresses the avoidance of accidents by investigating safety perception of all workers having different trades but working on same work-site. It may provide a yardstick which can be used to find the reasons for safety non-compliance on construction sites in the context of cross-level safety perceptions. 2. Literature Review Construction safety climate is workers attitude and perception regarding health and safety management [9]. Safety climate is also termed as snapshot of safety culture [10]. Recent meta-analytic evidence has confirmed that safety climate is associated with greater safety performance and decreased rate of accidents and injuries [11]. Safety culture and related aspects (subcultures) are vital part of construction research [12]. Culture and subculture are accepted as proactive stance towards safety [13]. Integration of both quantitative and qualitative approaches to measure safety climate, and verifying perceptions of safety climate shared by the workers and the management groups, effectively assists the organizations to further advance their safety-related policies, procedures, and practices. Implementation of multi-level safety climate needs assessment surveys so as to identify the major safety issues [11]. It was revealed that a significant cross-level interaction and a non-significant between-group interaction [14]. The climate variability showed that organization and group climates are globally aligned, resulting in full-mediation effects on safety behaviour in work groups. There also exists a significant variance, implying cross-level discrepancies. The dynamics of cross-level safety climate relationships thus present an interesting research agenda [15]. Current study focuses on subculture of construction workers. Specifically, safety climates of trades as Form worker, Steel bender/ fixer, Building service technician (e.g. A/C and Lift, etc), Plasterer/painter, Drain layer/plumber, Concreter, Blacksmith/welder, Laborer/Cleaner, Electrician/Mechanics, Mechanical plant Operator (e.g. crane, bulldozer and excavator etc.), Driller/pilling operator/piling worker, Scaffolder (bamboo or metal), Leveler/surveyor/Quantity Surveyor, Carpenter, and others(helpers). Differences, similarities and integration of safety perceptions at cross-level of trades portray that safety climate prevails in real situation at construction site. Concrete slab pouring can be considered as an example in which at the same time different trades are working on one work-site, where safety risk is entirely different to each tradesman but interconnected by hazardous conditions created due to malfunctions. In such a situation, cross-level safety climate comes up with greater importance. 2.1 System Thinking Application System thinking is the process of interaction of elements. The elements are the part of system which has influence on each other. System thinking deals with the problem as a whole rather than individual. System thinking focuses on the cyclic rather than linear cause and effect [8]. The effects and causes of elements interaction can be visualized through causal loop diagram. It consists of the nodes and arrows. The nodes define the elements. The arrows show the relationship between the elements. The arrows can be labelled as positive and negative. There are two types of loop in system thinking (1981), the positive and negative feedback loops. The delay factor is used in both the loops. The positive and negative signs are defined below: A causal link from one element A to another element B is positive (that is,+) if either (a) A adds to

3 348 System Thinking Approach for Investigation of Construction Safety Climate B or (b) a change in A produces a change in B in the same direction. A causal link from one element A to another element B is negative (that is, ) if either (a) A subtracts from B or (b) a change in A produces a change in B in the opposite direction. The positive feedback loop is also called reinforced loop which encourages the similar behavior in future. The elements have same influence either positive or negative. The manager gives all the safety measures at site to workers. The workers fulfill their task in time so that project manager can complete its works/assignments in time as shown in Fig. 1. Second is the balancing loop (i.e. goal orientation). If the current level of the variable of interest is above the goal, then the loop structure pushes its value down, while if the current level is below the goal, the loop structure pushes its value up. It is very helpful for the management. It shows the stability as well as needed changes. If the safety measures are not provided at work-site, the number of accidents increases and project gets delayed and halted as shown in Fig. 2. Studies showed that number of incidents and accidents on work-site can be reduced through application of System thinking. System thinking focuses on the systemic work rather than human action to learn to reduce the accidents [5]. There have identified the types of accidents with respect to incidents. This study has analyzed the investigation report of 140 accidents, produced by Organization System Development (OSD). In this report, accident variables have been identified and mapped on a Modified Loss Causation Model. It took lot of time to investigate each accident, identify variables and then to model them. Goh et al. [16] used system thinking to analyze the accidents through loop causal diagram, and demonstrated the use of system thinking and causal loop diagrams on a case study, applied on a Bellevue hazardous waste fire in Western Australia. This study focused to improve safety culture and improve the recurrence of accidents. Leveson et al. [17] analyze the petroleum industry accidents through system thinking. This study compares the accident analyses with the company standard accident analysis procedure. Cheng et al. [6] investigate the causes and distribution of occupational accidents in Taiwan construction industry by analyzing the accident database using data mining method such as classification and regression tree. In this study, 47% of accidents are due to fall, 19% due to collapse of objects, 8% shock and 5% fall of objects. It identifies the type of construction projects which are affected by the accidents (46% public and 67% private construction projects). Cross analysis shows the small scale private projects have more occupational injuries. 3. Research Problem Safety climate (perception) is pivotal construct of safety culture. Cross-level safety climate of workers has vital significance to mitigate risk of accidents which results in injury or fatality including lost work days. This study develops the rules, based on association of cross-level safety climate of workers, where workers of different trades do their job in same situation. In such a situations, responsible and victim of accidents can be effectively predicted through system thinking causal loop. Fig. 1 Reinforced loop: Project completion. Fig. 2 Balancing loop: Project halted.

4 System Thinking Approach for Investigation of Construction Safety Climate Methodology Following are the main phases of the research study: A safety climate questionnaire based on research study was used with statements related to Safety attitude and management commitment; Safety consultation and safety training; Supervisor s role and workmate s role; Risk taking behaviour; Safety resources; Appraisal of safety procedure and work risk; Improper safety procedure; Worker s involvement; Workmate s influence; and Competence [18]. The questionnaire in its final form consisted of 45 statements about safety issues at the organizational, group, and individual levels and consisted of four parts. The first part of the questionnaire sought general information about the respondents. The questions include the respondent s project name, name of the company, department and working group. Further questions included the respondent s trade classification of workers. The second part consisted of 40 safety climate items which asked the participants to indicate their level of endorsement to each statement by selecting a response on a five-point Likert-type (from 1 = strongly disagree to 5 = strongly agree ) scale. In the data collection phase, a questionnaire survey has been carried out on 36 construction projects (of different types such as industrial, facility, housing, community buildings etc) located in different cities in Pakistan, including both lower and higher categories of contractors (as per Pakistan Engineering Council). Cumulatively 70 valid responses were received from both self-interviews and post mail at about 72.94% of the distributed questionnaires. Apriori algorithm Evaluating predictive quality models derived from software measured: lesson learnedof data mining technique is used to generate the interesting association between workers perception against safety measures at site. Finally developed 16 rules show that accidents happen when the workers don t follow the rules. The rules are shown through causal loop diagram. Workers think that accident investigation is not a major concern; however, safety measures have been given higher priority by site workers. 5. Association Rule Mining Application The data consist of 63 instances against all (40) attributes. The attributes in the data show the questions, mentioned in the questionnaire. We apply apriori algorithm of association rule mining in Eq. (1). Apriori algorithm is used to find out the frequent item sets in the data. The most frequent items set in the data are the perception level of each worker against each question in the questionnaire. These frequent item sets determine the association rules. These rules highlight the trends (perception level against each question). Data mining tool Weka is used for applying apriori algorithm, and arff file is made which consists of 41 attributes, where 40 attributes show the questions mentioned in the questionnaire and one is special attribute showing the class (type) of worker. The number of worker types are fifteen (15). The data show the level of perception of each type of worker against each question. We apply the apriori algorithm on the data. The parameters set are: CAR = true; Minisupport = 0.1; Miniconfidence = 0.5 (1) The parameters of classified association rule are set as true because there is a need to classify the level of perception on question according to worker type. The parameter of support is minimum and confidence as maximum. Minimum the support, valid is the rules. The maximum is confidence logically true rules are calculated. The frequent item sets are calculated to generate the rules against each worker type. Blacksmith/welder and carpenter do not generate any rule. It has no frequent item set in data. The interested rule is the workers which have low perception against questions. We find the question1 has very low perception or workers strongly disagree with question 1, as shown in Table 1 (for form workers). Rest of twelve workers focused rules are not shown.

5 350 System Thinking Approach for Investigation of Construction Safety Climate Table 1 Workers focused rules (Example of Form worker). Form worker 1. q1=1, q28=4 7 ==> class=fw 7 2. q1=1, q40=4 7 ==> class=fw 7 3. q1=1, q2=4 6 ==> class=fw 6 4. q1=1, q3=4 6 ==> class=fw 6 5. q1=1, q10=4 6 ==> class=fw 6 conf: (1) 6. q1=1, q14=4 6 ==> class=fw 6 7. q1=1, q15=4 6 ==> class=fw 6 8. q1=1, q19=4 6 ==> class=fw 6 9. q1=1, q24=4 6 ==> class=fw q1=1, q25=4 6 ==> class=fw 6 For current study, rules from Table 1 only have been considered which have greater than or equal to 3 workers in same association. This limit of number of workers for specific situation is common e.g. form worker, steel fixer and electrician are working at the same place for preparing roof for concrete pour. Unsafe act by any of these workers may cause accident resulting into severe injury or fatality of any or all of the workers. 6. Results and Discussion System thinking (with methods of causal loop diagram and data mining) is used only for safety management specifically for construction accident identification [5], analysis [16, 17]; and investigation [6] but safety climate has not been addressed to assess the perception of workers and co-workers on construction sites in particular situations and conditions. By focusing on the safety perception of workers during work, we can find the reasons of accidents on work-sites in Pakistani construction industry. Current study is an effort to develop sixteen (16) rules based on safety climate data of construction workers. These rules are valid in situations when the relevant workers work in same working conditions. Associated rules have been developed, basing on safety climate data, with the consensus of workers belonging to different trades. These rules are valid in situations when the relevant workers (belonging to different trades) work in same working conditions (Table 2). Table 2 Associated Rules and Interpretations. Rules Description (accidents investigation are Questions not major concern i.e. q1) Rule1 Management has no capability to handle q1=1, q22= 4 the situation Rule2 Some of safety and health instruction are q1=1, q11 =4 not followed Rule3 High risk job at site q1=1, q19 =4 Rule4 Accidents are reported q1=1, q40 =4 Rule5 Not focus on safety measures q1=1, q3 =4 Rule6 Safety measure are equipped q1=1, q14 =4 Rule7 Complicated safety measure at site q1=1, q26 =4 Rule8 Try to maintain safety measures q1=1, q28 =4 Rule9 Self motivated to achieve safety measure q1=1, q32 =4 Type of workers Driller/pilling operator, Mechanical Plant Operator, Concreter, scaffolder, Drain layer/plumber, plastic painter, others (helper) plastic painter, Drain layer/plumber, Labourer/Cleaner, Mechanical Plant Operator, driller/pilling operator Form worker, plastic painter, Labourer/Cleaner, Mechanical Plant Operator, driller/pilling operator Form worker, Concreter, Mechanical Plant Operator, scaffolder, leveller Form worker, Drain layer/plumber, scaffolder, Mechanical Plant Operator Form worker, scaffolder, Labourer/Cleaner, Mechanical Plant Operator Leveller/surveyor, Labourer/Cleaner, Mechanical Plant Operator, driller/pilling operator Form worker, steel fixer, Drain layer/plumber, Mechanical Plant Operator Scaffolder, plastic painter, Concreter, Mechanical Plant Operator Rule10 Availability of safety measure q1=1, q7 =4 Scaffolder, Drain layer/plumber, Labourer/Cleaner Rule11 Try to follow safety measures q1=1, q15 =4 Form worker, scaffolder, Labourer/Cleaner Rule12 Try to giving respect to each other work q1=1, q18 =4 Drain layer/plumber, scaffolder, Mechanical Plant Operator Management try to motivate workers for Rule13 q1=1, q23 =4 Concreter, others (helper), scaffolder safety measures Manager talk on awareness of safety Rule14 q1=1, q29 =4 measure Leveller/surveyor, Concreter, driller/pilling operator Rule15 High priority of safety measures q1=1, q35 =4 Plastic painter, Mechanical Plant Operator, scaffolder Rule16 Hazardous situation q1=1, q39 =4 Mechanical Plant Operator, Concreter, others (helper)

6 System Thinking Approach for Investigation of Construction Safety Climate 351 Acknowledgment Funding and support from The University of Lahore, Lahore is acknowledged and appreciated. References [1] J. Mullen, Investigating factors that influence individual safety behaviour at work, Journal of Safety Research 35 (2004) [2] T.M. Toole, Construction site safety roles, Journal of Construction Engineering and Management 128 (2002) [3] HSE, Strategies to Promote Safe Behavior as Part of a Health and Safety Management System. Contract Research Report, in: Health and Safety Executive (HSE), UK, 2002, pp [4] C.A. Arboleda, D.M. Abraham, Fatalities in trenching operations-analysis using models of accident causation, Journal of Construction Engineering and Management 130 (2004) [5] Y. Goh, D. Chua, Identification of factors causing fatal construction accidents, in: Proc. CIB W99 3rd International Conference on Implementation of Safety and Health on Construction Sites, 2002, pp [6] C.W. Cheng, S.S. Leu, Y.M. Cheng, T.C. Wu, C.C. Lin, Applying data mining techniques to explore factors contributing to occupational injuries in Taiwan 's construction industry, Accident Analysis & Prevention 48 (2012) [7] A.P. Chan, F.K. Wong, D.W. Chan, M.C. Yam, A.W. Kwok, E.W. Lam, E. Cheung, Work at height fatalities in the repair, maintenance, alteration, and addition works, Journal of Construction Engineering and Management 134 (2008) [8] P.M. Senge, The fifth discipline: The art and practice of the learning organization, Random House LLC, [9] HSE, A review of safety culture and safety climate literature for the development of the safety culture inspection toolkit, in: Health and safety Executive (HSE), UK, [10] D. Fang, Y. Chen, L. Wong, Safety climate in construction industry: A case study in Hong Kong, Journal of Construction Engineering and Management 132 (2006) [11] J.L. Gittleman, P.C. Gardner, E. Haile, J.M. Sampson, K.P. Cigularov, E.D. Ermann, P. Stafford, P.Y. Chen, City center and cosmopolitan construction projects, Las Vegas, Nevada: Lessons learned from the use of multiple sources and mixed methods in a safety needs assessment, Journal of Safety Research 41 (2010) [12] F.W. Guldenmund, The nature of safety culture: A review of theory and research, Safety Science 34 (2000) [13] T. Lee, K. Harrison, Assessing safety culture in nuclear power stations, Safety Science 34 (2000) [14] D.A. Hofmann, F.P. Morgeson, S.J. Gerras, Climate as a moderator of the relationship between leader-member exchange and content specific citizenship: Safety climate as an exemplar, Journal of Applied Psychology 88 (2003) [15] D. Zohar, G. Luria, A multilevel model of safety climate: Cross-level relationships between organization and group-level climates, Journal of Applied Psychology 90 (2005) [16] Y.M. Goh, H. Brown, J. Spickett, Applying systems thinking concepts in the analysis of major incidents and safety culture, Safety Science 48 (2010) [17] N. Leveson, M. Stringfellow, J. Thomas, A Systems Approach to Accident Analysis, (2009). [Online], sunnyday.mit.edu/safer-world/refinery-edited.doc [18] R. Masood, R.M. Choudhry, Measuring Safety Climate to Enhance Safety Culture in the Construction Industry of Pakistan, in: CIB W099 Safety and Health in Construction Conference: Prevention: Means to the End of Construction Injuries, Illnesses, and Fatalities, (2011) [Online],