Safety Science, ( ISI ), Year (2018-3)

Title : ( An investigation of the required vigilance for different occupations )

Authors: morteza masoudian , Hamideh Razavi ,

Citation: BibTeX | EndNote


Understanding work parameters affecting vigilance can help classify occupations based on perceived vigilance demand. This classification is used for risk control, environmental conditioning, work-rest scheduling and assigning appropriate personnel in order to reduce individual errors and increase productivity. The present study was carried out in order to classify occupations based on their required vigilance using clustering and decisionmaking techniques. Initially 10 occupational factors were recognized particularly influential on the vigilance level. Because of the limitations on the objective methods and experimental tests, a subjective approach was takenandaquestionnairewithaLikertscalewasdesignedforevaluationoftherelevanceofoccupationalfactors to each job performance. The questionnaires were filled by 110 occupants working in 11 different jobs. Using these data, 9 jobs were classified into 5 groups by K-means clustering technique with a 3.1 Dunn index. Then each category of jobs was allocated to the appropriate level of vigilance using hierarchical decision making method -AHP-. For verification of the results, remaining jobs as well as two other jobs were also classified using soft independent modeling algorithm -SIMCA-. The results showed the capability of the model for ranking the jobs in terms of vigilance required


, Vigilance, Sustained attention, Job classification , SIMCA
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author = {Masoudian, Morteza and Razavi, Hamideh},
title = {An investigation of the required vigilance for different occupations},
journal = {Safety Science},
year = {2018},
month = {March},
issn = {0925-7535},
keywords = {Vigilance; Sustained attention; Job classification ; SIMCA},


%0 Journal Article
%T An investigation of the required vigilance for different occupations
%A Masoudian, Morteza
%A Razavi, Hamideh
%J Safety Science
%@ 0925-7535
%D 2018