Designing the Organizational Rumors Management Conceptual Model in Public Organizations (Case Study: Payame Noor University)

This study aims at developing an appropriate model for organizational rumor management in public organizations. Payame Noor University (PNU) was selected as the case study of this research. As it is a countrywide university with a variety of cultural backgrounds, it can be a good sample as a case study for this purpose. The research method is applied and descriptive-exploratory with a mixed-method approach. In the qualitative section, 30 experts were selected as Delfi Panel who were selected through snowball random sampling. In the quantitative section, the statistical population consisted of all managers of the university among whom 406 were selected through systematic counting from all PNU centers in addition to the international center and main campus. Reviewing the related literature, 50 strategies were extracted and became the basis for designing the questionnaires in three phases of the Delfi procedure. The reliability of the Delphi stages was calculated by Cronbach's alpha formula and the validity of the questions was evaluated through construct validity. Using exploratory factor analysis, 47 strategies were categorized into 9 groups that form the conceptual model of organizational rumors management at Payame Noor University: organizational health, information vaccination, rumor clinic, systemic justice, link building, glass organization, group orientation, organizational reconstruction, direct confrontation.The results of the research show that all 9 main components of the model include Organizational Healthing(0/76), Information Vaccination(0/83), Rumor Clinic(0/64), Systemic Justice(0/52), Link Building(0/67), Glass Organization(0/57), Group Orienting(0/44), Organizational Reconstruction(0/54), Direct Confrontation(0/67) have an impact on the organizational rumors management in Payame Noor University, and 0.72 variance of the Organizational Rumors Management are explained by the variables mentioned in the model.