PRIORITIZING THE ANTECEDENTS OF JOB SATISFACTION: A DATA MINING APPROACH

36422

Job satisfaction (JS) is important because it is related to the success of the organization. It has been found to bring about such outcomes as job performance, organizational citizenship behavior (OCB), absence, turnover, and so forth for the employees and organizations. The factors causing JS are composed of thoughts, feelings, and actions of a group of employees in a certain organizational culture. This study aims to identify and prioritize the contributory factors to job satisfaction in Turkish employees with the purpose of helping develop organizational policies that could increase JS. Being the first study using data mining approach (decision tree, association rules, Bayesian network, and attribute selection) with a sample of 44,820 employees in all sectors in Turkey, the study has found that a great majority of the employees are satisfied with their jobs. The most significant variable in job satisfaction is ‘problem with working conditions,’ followed by ‘problem with administrative issues,’ and ‘sector.’

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job satisfaction , working conditions , data mining , decision tree , classification methods

Journal Of Economics an‎d Administrative Sciences

922

Journal Of Economics an‎d Administrative Sciences