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Alvanchi, A and JavadiAghdam, S (2019) Job site weather index: an indicator for open environment construction projects. Construction Innovation , 19(01), 110–24.

• Type: Journal Article
• Keywords:
• ISBN/ISSN: 1471-4175
• URL: https://doi.org/10.1108/CI-12-2017-0097
• Abstract:
  Many construction projects are implemented in open-environment job sites and can be significantly affected by various weather conditions. Evaluating the overall impacts of the weather conditions on a project can assist project managers to prepare effectively. Nevertheless, methods measuring the overall adverse impacts of the job sites’ weather condition on the project performance are still missing. This study aims to address this gap. In this investigation, a survey-based method was proposed to evaluate the overall impacts of the weather conditions on the construction project resources through a new indicator called job site weather index (JWI). The target survey population includes practitioners directly involved in the on-site construction operations. The JWI suggests the direction of the resource change in new construction projects based on the weather condition. The method was implemented in the road construction projects of Iran and successfully applied to four sample cities. In this experiment, construction workers were identified as the most susceptible resources to the unfavorable weather conditions. Hot temperature above 50°C and cold temperature below −10°C were ranked as the most influential factors for the workers. The results achieved showed high accordance with the trends currently followed in the country. This research was the first structured method for capturing impacts of weather conditions on the performance of construction resources in open environment construction projects. Implementation of the method in road construction projects of Iran revealed new results that have not been previously identified. The impacts of the company-specific factors on the final productivity rate, however, were not investigated in the research. Investigations accounting impacts of various company-specific factors on the final productivity rate are required.

Azadeh, A, Kalantari, M, Ahmadi, G and Eslami, H (2019) A flexible genetic algorithm-fuzzy regression approach for forecasting. Construction Innovation , 19(01), 71–88.

Janné, M and Fredriksson, A (2019) Construction logistics governing guidelines in urban development projects. Construction Innovation, 19(01), 89–109.

Majava, J, Haapasalo, H and Aaltonen, K (2019) Elaborating factors affecting visual control in a big room. Construction Innovation , 19(01), 34–47.

Saini, M, Arif, M and Kulonda, D J (2019) Challenges to transferring and sharing of tacit knowledge within a construction supply chain. Construction Innovation, 19(01), 15–33.

Shoar, S, Nasirzadeh, F and Zarandi, H R (2019) Quantitative assessment of risks on construction projects using fault tree analysis with hybrid uncertainties. Construction Innovation, 19(01), 48–70.

Sundling, R, Blomsterberg, & and Landin, A (2019) Enabling energy-efficient renovation: the case of vertical extension to buildings. Construction Innovation, 19(01), 2–14.