A Neural Network Classifier Model for Forecasting Safety Behavior at Workplaces

Fakhradin Ghasemi, Omid Kalatpour, Abbas Moghimbeigi, Iraj Mohammadfam


The construction industry is notorious for having an unacceptable rate of fatal accidents. Unsafe behavior has been recognized as the main cause of most accidents occurring at workplaces, particularly construction sites. Having a predictive model of safety behavior can be helpful in preventing construction accidents. The aim of the present study was to build a predictive model of unsafe behavior using the Artificial Neural Network approach.
A brief literature review was conducted on factors affecting safe behavior at workplaces and nine factors were selected to be included in the study. Data were gathered using a validated questionnaire from several construction sites. Multilayer perceptron approach was utilized for constructing the desired neural network. Several models with various architectures were tested to find the best one. Sensitivity analysis was conducted to find the most influential factors.
The model with one hidden layer containing fourteen hidden neurons demonstrated the best performance (Sum of Squared Errors=6.73). The error rate of the model was approximately 21 percent. The results of sensitivity analysis showed that safety attitude, safety knowledge, supportive environment, and management commitment had the highest effects on safety behavior, while the effects from resource allocation and perceived work pressure were identified to be lower than those of others.
The complex nature of human behavior at workplaces and the presence of many influential factors make it difficult to achieve a model with perfect performance.


Safety Behavior, Multilayer Perceptron, Artificial Neural Network, Predictive Model, Safety Attitude, Safety Knowledge.

Full Text:



Mehrdad R, Seifmanesh S, Chavoshi F, Aminian O, Izadi N. Epidemiology of occupational accidents in Iran based on social security organization database. Iranian Red Crescent Medical Journal. 2014;16(1):1-5.

Mahmoudi S, Ghasemi F, Mohammadfam I, Soleimani E. Framework for Continuous Assessment and Improvement of Occupational Health and Safety Issues in Construction Companies. Safety and Health at Work.5(3):125-30.

Haslam RA, Hide SA, Gibb AGF, Gyi DE, Pavitt T, Atkinson S, et al. Contributing factors in construction accidents. Applied Ergonomics. 2005;36(4):401-15.

Heinrich HW. Industrial Accident Prevention. A Scientific Approach. Industrial Accident Prevention A Scientific Approach. 1941(Second Edition), McGraw-Hill, Torento, Canada, pp. 300-20 .

Vinodkumar MN, Bhasi M. Safety management practices and safety behaviour: Assessing the mediating role of safety knowledge and motivation. Accident Analysis & Prevention. 2010;42(6):2082-93.

Guo BHW, Yiu TW, González VA. Predicting safety behavior in the construction industry: Development and test of an integrative model. Safety Science. 2016;84(1):1-11.

Jitwasinkul B, Hadikusumo BHW, Memon AQ. A Bayesian Belief Network model of organizational factors for improving safe work behaviors in Thai construction industry. Safety Science. 2016;82(1):264-73.

Ghasemi F, Mohammadfam I, Soltanian AR, Mahmoudi S, Zarei E. Surprising Incentive: An Instrument for Promoting Safety Performance of Construction Employees. Safety and Health at Work. 2015;6(3):227-32.

Detienne KB, Detienne DH, Joshi SA. Neural Networks as Statistical Tools for Business Researchers. Organizational Research Methods. 2003;6(2):236-65.

Hornik K, Stinchcombe M, White H. Multilayer feedforward networks are universal approximators. Neural Networks. 1989;2(5):359-66.

Lek S, Delacoste M, Baran P, Dimopoulos I, Lauga J, Aulagnier S. Application of neural networks to modelling nonlinear relationships in ecology. Ecological Modelling. 1996;90(1):39-52.

Patel D, Jha K. Neural network approach for safety climate prediction. Journal of Management in Engineering. 2014;31(6):05014027-6.

Goh YM, Chua D. Neural network analysis of construction safety management systems: a case study in Singapore. Construction Management and Economics. 2013;31(5):460-70.

Lawshe CH. A quantitative approach to content validity. Personnel psychology. 1975;28(4):563-75.

Cronbach LJ. Coefficient alpha and the internal structure of tests. psychometrika. 1951;16(3):297-334.

Mohammadfam I, Ghasemi F, Kalatpour O, Moghimbeigi A. Constructing a Bayesian network model for improving safety behavior of employees at workplaces. Applied Ergonomics. 2017;58(1):35-47.

Raykov T, Marcoulides GA. A first course in structural equation modeling: Routledge, Psychology Press; 2012, USA, pp. 20-150.

Haykin SS, Haykin SS, Haykin SS, Haykin SS. Neural networks and learning machines: Pearson Upper Saddle River, NJ, USA:; 2009,pp.122-00.

Gardner MW, Dorling SR. Artificial neural networks (the multilayer perceptron)—a review of applications in the atmospheric sciences. Atmospheric Environment. 1998;32(14–15):2627-36.

IBM Corporation. IBM SPSS Neural Networks 20. Chicago, IL, US, 2011, 8-20.

Zhang G, Eddy Patuwo B, Y. Hu M. Forecasting with artificial neural networks:: The state of the art. International Journal of Forecasting. 1998;14(1):35-62.

Lippmann R. An introduction to computing with neural nets. IEEE ASSP Magazine. 1987;4(2):4-22.

Zhou Q, Fang D, Wang X. A method to identify strategies for the improvement of human safety behavior by considering safety climate and personal experience. Safety Science. 2008;46(10):1406-19.

Greiner M, Pfeiffer D, Smith RD. Principles and practical application of the receiver-operating characteristic analysis for diagnostic tests. Preventive Veterinary Medicine. 2000;45(1–2):23-41.

Zou KH, O’Malley AJ, Mauri L. Receiver-Operating Characteristic Analysis for Evaluating Diagnostic Tests and Predictive Models. Circulation. 2007;115(5):654-57.

Swets JA. Measuring the accuracy of diagnostic systems. Science. 1988;240(4857):1285-93.

Ghasemi F, Kalatpour O, Moghimbeigi A, Mohammadfam I. Selecting Strategies to Reduce High-Risk Unsafe Work Behaviors Using the Safety Behavior Sampling Technique and Bayesian Network Analysis. Journal of Research in Health Sciences. 2017;17(1): 1-6.

Patel D, Jha K. Neural network model for the prediction of safe work behavior in construction projects. Journal of Construction Engineering and Management. 2014;141(1):04014066-6.

Zarei E, Mohammadfam I, Aliabadi MM, Jamshidi A, Ghasemi F. Efficiency prediction of control room operators based on human reliability analysis and dynamic decision-making style in the process industry. Process Safety Progress. 2016;35(2):192-9.

Eagly AH, Chaiken S. The psychology of attitudes: Harcourt Brace Jovanovich College Publishers; 1993, USA, pp.120-80.

Shin M, Lee H-S, Park M, Moon M, Han S. A system dynamics approach for modeling construction workers’ safety attitudes and behaviors. Accident Analysis & Prevention. 2014;68(1):95-105.

Tam CM, Fung IWH, Chan APC. Study of attitude changes in people after the implementation of a new safety management system: the supervision plan. Construction Management and Economics. 2001;19(4):393-403.

Haapala I, Probart C. Food Safety Knowledge, Perceptions, and Behaviors among Middle School Students. Journal of Nutrition Education and Behavior. 2004;36(2):71-76.

Levesque DL, Arif AA, Shen J. Effectiveness of Pesticide Safety Training and Knowledge About Pesticide Exposure Among Hispanic Farmworkers. Journal of Occupational and Environmental Medicine. 2012;54(12):1550-56.

Beseler CL, Stallones L. Safety knowledge, safety behaviors, depression, and injuries in Colorado farm residents. American Journal of Industrial Medicine. 2010;53(1):47-54.

Griffin MA, Neal A. Perceptions of safety at work: A framework for linking safety climate to safety performance, knowledge, and motivation. Journal of Occupational Health Psychology. 2000;5(3):347-58.

Vredenburgh AG. Organizational safety: Which management practices are most effective in reducing employee injury rates? Journal of Safety Research. 2002;33(2):259-76.

Choudhry RM, Fang D. Why operatives engage in unsafe work behavior: Investigating factors on construction sites. Safety Science. 2008;46(4):566-84.

Mullen J. Investigating factors that influence individual safety behavior at work. Journal of Safety Research. 2004;35(3):275-85.

Mohamed S. Safety climate in construction site environments. Journal of construction engineering and management. 2002;128(5):375-84.

Zohar D. Safety climate in industrial organizations: Theoretical and applied implications. Journal of Applied Psychology. 1980;65(1):96-02.

Iranian Journal of Health, Safety and Environment e-ISSN: :2345-5535 Iran university of Medical sciences, Tehran, Iran