Alireza Badeleh; Rohollah Sameie
Abstract
Abstract Introduction The current study seeks to develop the Productivity Measurement Model (PMM) at Farhangian University to maximize the use of resources, manpower, facilities, reduce production costs, expand markets and increase employment.Methodology In the qualitative phase, using an exploratory ...
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Abstract Introduction The current study seeks to develop the Productivity Measurement Model (PMM) at Farhangian University to maximize the use of resources, manpower, facilities, reduce production costs, expand markets and increase employment.Methodology In the qualitative phase, using an exploratory data collection, the participating team including academic experts in different fields of humanities including the directors of Farhangian University (n=50), were selected by a non-probability (purposive) manner and the snowball method to develop and validate the PMM. Fifteen interviews were conducted with university faculty members until theoretical saturation was reached. To rank and fit the PMM, a questionnaire consistent with the findings of the qualitative section was sent to the academic staff at random. The validity and reliability indices of the questionnaires were calculated by experts; factor analysis and Cronbach's alpha-test of 0.70 were all confirmed. Out of 274 questionnaires distributed, 221 complete questionnaires were returned used as the basis for statistical analysis. Findings After conducting interviews and reviewing previous research, indicators related to productivity measurement by content analysis method (142) and interviews with experts (34) were identified and finally by Delphi method 138 indicators in the areas of "design, planning and resource development" "Education", "Research and Technology" and "Student, Cultural and Social" were approved. In the quantitative phase, the structural equation model was used for validation.DiscussionConsidering that all productivity measurement indicators in Farhangian University have been approved using confirmatory factor analysis in each field, the indicators in the field of research and technology with a path coefficient of 0.977 have a value of t, higher than 1.96. The coefficient of determination of this index is 95.4% of the productivity measurement and it has the first rank and the indicators of the student, cultural and social field with a path coefficient of 0.947 have a value of t, higher than 1.96. The coefficient of determination of this index (89.7%) explains the productivity measurement and is in the second place, and the indicators of the field of education with a path coefficient of 0.937 have a value of t, higher than 1.96. The coefficient of determination of these indicators of 87.9% explains the productivity measurement and has the third rank and the coefficient of determination of this index of 87.7% explains the productivity measurement and ranks fourth among other factors. After determining the productivity indicators, calculations related to productivity indicators and factors affecting productivity changes can be determined.
