Designing a Behavioral Equivalence Model Based on Organizational Culture Using the Grounded Theory Approach (Case Study: General Directorate of Education in Kerman Province)
Keywords:
Behavioral equivalence, Organizational culture, Data-based approach, Max Qoda SoftwareAbstract
The main objective of this study is to design a behavioral equivalence model based on organizational culture. This research is classified as an applied-developmental study in terms of its purpose, descriptive in terms of data collection method, and mixed (quantitative and qualitative) in terms of data nature. The study consists of two parts: qualitative and quantitative. The statistical population of the qualitative section included 15 experts and specialists, while the quantitative section consisted of experts from the General Directorate of Education in Kerman City. The quantitative sample (N = 317) was estimated using the simple random sampling formula based on the Krejcie-Morgan table. The data collection tools included two components: a review of the research literature, semi-structured interviews, and a researcher-made questionnaire for the field study. Upon completion of the qualitative phase, the process of coding and textual analysis of the interviews was carried out using the MAXQDA qualitative data analysis software. The findings indicated that the behavioral equivalence model based on organizational culture, using the grounded theory approach, comprises causal factors (organizational structure, internal communication, training, and leadership), contextual factors (individual personality, experience, education and literacy, and cultural intelligence), intervening conditions (motivation, organizational climate, and workplace relationships), strategies (communication, trust, and social learning), and consequences (socialization, promotion of participatory culture, and promotion of extra-role behavior culture). In the next phase, the researcher-made questionnaire derived from the qualitative section was distributed among the quantitative sample. After collecting the statistical data, the model fit was assessed using the Partial Least Squares (PLS) method. The results revealed that the model had a desirable level of fit and strong adequacy.
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