حسنعلی آقاجانی

INTRODUCTION: A good organizational citizen is a thought and idea that includes various behaviors of employees such as accepting and assuming additional duties and responsibilities, following organizational rules and procedures, maintaining and developing a positive attitude, being patient, and tolerating dissatisfaction and problems in the workplace. The increase in the level of organizational citizenship behavior (OCB) in the organization makes the organization an attractive environment for work. In other words, the desired level of OCBs affects the improvement of the performance of employees and, in general, the organization. The Iranian Red Crescent Society is one of the human-centered organizations, and observing the indicators of citizenship behavior is one of the effective factors in the success of its performance. Therefore, this study aimed to investigate the OCB from a social perspective in the Iranian Red Crescent Society. METHODS: The present applied study was conducted based on an exploratory qualitative approach. The statistical population of this study consisted of all managers and employees of the Iranian Red Crescent Society. The required data were collected using in-depth semi-structured interviews, which reached saturation after holding 14 interviews. To analyze the data, content analysis, meta-synthesis, and fuzzy Delphi methods using grounded theory were applied. The MAXQDA software (version 10) was used in the theory analysis process. FINDINGS: In this study, the results were classified into 78 concepts, 14 sub-criteria, and 2 main criteria, including the dimensions of citizenship behavior and the consequences of citizenship behavior. The most important dimensions of OCB consisted of the categories of helpful behaviors, individual creativity, organizational obedience, organizational loyalty, chivalry, civic virtue, and personal growth. CONCLUSION: The results of data analysis showed that the categories of increasing performance productivity and effectiveness, promoting positive relationships among employees, boosting efficiency in resource allocation, reducing maintenance costs, creating the necessary flexibility for innovation, improving customer service, using rare resources effectively were the most important consequences of observing OCB from a social perspective in the IRCS.

Organizational anomie (OA) is defined as the lack of law, as well as violations or weaknesses in the implementation of laws and norms in the organization, which can have detrimental effects on the performance of the organization and its members. The main focus of this study is to establish and validate an organizational anomie scale that can be employed to implement and operate this tool in field studies. The present research is applied-exploratory in terms of purpose and descriptive-survey in terms of method. To conduct this research, issues related to organizational anomie using factor analysis approach and content analysis method of scientific texts as well as from the perspective of qualified and experienced thinkers and experts and a researcher-made questionnaire on organizational anomie in COVID-19 pandemic are analyzed. it placed. Completed by experts and managers. The reliability coefficient of the test was calculated to be 0.85 using Cronbach's alpha test. Exploratory factor analysis of organizational questions revealed that the components of this questionnaire may explain more than 78.512 % of the desired variance. After one rotation of Varimax factors, the correlation between each item with each component was determined in the best situation and accordingly, twelve components were selected and extracted with the most weight: conflicting goals of the individual and organization, weakness in communication, standard selection ,ambiguity in goals, level of trustworthiness, negative attitude of employees towards themselves, feeling useless, understanding justice, weak control, common norms, organizational indifference, lack of socialization. According to the research findings, it can be concluded that organizational anomie is a multidimensional concept with many dimensions and components and cannot be studied with limited dimensions and components.

Purpose : The present study aimed to present an interpretive structural model based on DEMATEL for the Entrepreneur University among top universities in the northern region of Iran. Methodology : This study was applied in terms of objective and combined (qualitative and quantitative) in terms of implementation method. The research population in the qualitative section were documents and texts of the Entrepreneurship University and experts in this field that 35 documents and texts and 30 experts were selected as samples according to the principle of theoretical saturation by purposive sampling method. The research population in the quantitative section consisted of the same 30 experts who rated the components. The research tools included text review, semi-structured interview, and 77-item researcher-made questionnaire that their psychometric indices were confirmed. Data were analyzed by Delphi methods and interpretive structural modeling based on DEMATEL in SPSS-23 and LISREL. Findings: The results showed that the Entrepreneurship University included 77 concepts, 24 sub-components in 6 main components. So that among the 6 main components, three components of infrastructure (with four sub-components), management (with five sub-components), and communication with the population (with four sub-components) were identified as effective variables, and three components of services (with three sub-components), knowledge-based entrepreneurship (with five sub-components) and output and outcome (with three sub-components) were identified as affected variables. The results of DEMATEL-based interpretive structural modeling showed that in the first level with 10 components, the component of commercialization of knowledge and research and revenue generation from advanced technology, in the second level with 7 components, the component of entrepreneurial research, R&D, and dissemination of academic results, in the third level with 14 components, the component of entrepreneurial research, R&D and dissemination of academic results, and in the fourth level with 1 component, the core component of strong leadership and change in structural and managerial dimensions were at a higher level. Conclusion : According to the results of the present study, planners and higher education professionals can take advantage of the results of this study and plan for the improvement and growth of the Entrepreneur University through the effective components identified in it.

Nowadays, most of Businesses have faced a great challenge for entering a new market. The existence conditions have forced the managers to apply the innovative methods for simultaneous analyzing of various factors for arrival to special markets. This paper prioritizes a few target markets using two methods. First, the problem is solved by the combined method of hierarchical analysis and Monte Carlo simulation, and then by the method of fuzzy hierarchical analysis and finally the results of both methods are compared. The considered problem in this study relates to a factory of prefabricated building components that is looking for establishing the sale agencies in appropriate towns in order to introduce and distribute the new products. In order to prioritize cities, desired criteria are determined through interviews with experts and investigating the previous studies. The research findings have shown that based on the four main criteria and seven related sub-criteria, the prioritization of selected cities as markets has been A-D-C-B respectively. In the end, it is concluded that based on the findings of this study, managers and stakeholders should pay attention to these priorities in choosing the target market. In this research, for the first time, the combined Monte Carlo technique and hierarchical analysis have been used to select the market. Market selection is one of the issues that has always been a concern of managers and has been associated with a lot of risk. Using Monte Carlo simulation algorithm and hierarchical analysis, by considering different decision intervals, greatly reduces the risk of selection, so this technique is recommended to managers of organizations as a practical method in market selection.