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Al Haj, R A and El-Sayegh, S M (2015) Time–Cost Optimization Model Considering Float-Consumption Impact. Journal of Construction Engineering and Management, 141(05).

Bijleveld, F R, Miller, S R and Dorée, A G (2015) Making Operational Strategies of Asphalt Teams Explicit to Reduce Process Variability. Journal of Construction Engineering and Management, 141(05).

Che Ibrahim, C K I, Costello, S B and Wilkinson, S (2015) A Fuzzy Approach to Developing Scales for Performance Levels of Alliance Team Integration Assessment. Journal of Construction Engineering and Management, 141(05).

Fitch, G J, Odeh, I and William Ibbs, C (2015) Economic Sustainability of DBO Water Based on Wastewater Projects in the U.S.: Three Case Studies. Journal of Construction Engineering and Management, 141(05).

Jablonowski, C J (2015) Quantitative Method to Model the Underreporting of Safety Incidents. Journal of Construction Engineering and Management, 141(05).

Jafarzadeh, R, Ingham, J M, Walsh, K Q, Hassani, N and Ghodrati Amiri, G R (2015) Using Statistical Regression Analysis to Establish Construction Cost Models for Seismic Retrofit of Confined Masonry Buildings. Journal of Construction Engineering and Management, 141(05).

Lin, S (2015) An Analysis for Construction Engineering Networks. Journal of Construction Engineering and Management, 141(05).

Rodríguez-Garzón, I, Lucas-Ruiz, V, Martínez-Fiestas, M and Delgado-Padial, A (2015) Association between Perceived Risk and Training in the Construction Industry. Journal of Construction Engineering and Management, 141(05).

  • Type: Journal Article
  • Keywords: Risk perception; Safety in construction; Safety training; Prevention; Safety management; Psychometric paradigm; Organizational issues;
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0000960
  • Abstract:
    This paper studies risk perception of Spanish construction workers and its relation with the demographic variable of training. The study sample was analyzed by means of hierarchical conglomerate and cluster analyses. The model used to establish the clusters is based on the psychometric paradigm. Two different risk perception groups were singled out. There was an attempt to identify, after analyzing each cluster, their relation with different sociodemographic variables. Only the worker training variable showed a statistically significant relation with the two cluster analysis groups. As a result, the perception of risk of the best-trained group was higher than that of the less-trained group.

Shahtaheri, M, Nasir, H and Haas, C T (2015) Setting Baseline Rates for On-Site Work Categories in the Construction Industry. Journal of Construction Engineering and Management, 141(05).

Zhang, P, Lingard, H, Blismas, N, Wakefield, R and Kleiner, B (2015) Work-Health and Safety-Risk Perceptions of Construction-Industry Stakeholders Using Photograph-Based Q Methodology. Journal of Construction Engineering and Management, 141(05).