Investigating the Dimensions and Components of Knowledge-Based Decision Making in Iranian National Tax Administration

Agricultural Marketing and Commercialization Journal

مقاله 12، دوره 3، شماره 1، شهریور 2019، صفحه 128-134   

نوع مقاله: Original Research

چکیده

The purpose of this study was to investigate the status of knowledge-based decision-making dimensions in the Iranian National Tax Administration. The present study is applied, and a survey method is used. The statistical population of the present study was comprised of 2115 senior, basic and middle managers of the Iranian National Tax Administration. The sample size was estimated to be 325 people based on Cochran formula who were selected by stratified random sampling. To collect the data, a questionnaire of 69 questions with a 5-point Likert-scale from completely inappropriate to completely appropriate was used. The conceptual and face validity of the research questionnaire was evaluated and approved by 15 experts. The content validity ratio or CVR of the questionnaire was calculated by 0.93.8 by 15 experts and university professors. Cronbach's alpha coefficient was estimated at 94.6, which was higher than 0.7, indicating the internal consistency of the items and confirming the reliability. One-sample t-test using SPSS software was used for data analysis. The significance level of the test (0.000) was smaller than the significance level (0.05), so considering the mean of variables of knowledge-based decision making (3.519), functional factors (3.572), behavioral factors (3.639), attitudinal factors (3.297), motivational factors (3.503), and structural factors (3.542) which were above the base mean (3), the variables were in a desirable condition. The mean of the variables indicated that this amount is not high enough to indicate that the variables of knowledge-based decision making are being well applied in these organizations. Therefore, planning is needed in this regard.

کلیدواژه‌ها

Attitudinal and Behavioral factors؛ Functional factors؛ Knowledge-based decision making؛ Motivational factors؛ Structural factors