Compiling a Model to Foster Organizational Leaders According to Data-base Theory in Oil Company

Majid Arash, Hamid Rahimian, Abbas Abbaspour and Ali Delavar
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Majid Arash: Department of Educational Administration, Allameh Tabataba’i University, Tehran, Iran,
Hamid Rahimian: Allameh Tabataba’i University, Tehran, Iran,
Abbas Abbaspour: Allameh Tabataba’i University, Tehran, Iran,
Ali Delavar: Allameh Tabataba’i University, Tehran, Iran,

International Review of Management and Marketing, 2017, vol. 7, issue 3, 61-71

Abstract: The article looks for providing a model to explain the fosterage of the organizational leaders in Oil Company. To obtain the data according to the field of the study; the qualitative method of data base theory was used. The data was gathered through interview with 21 middle and top managers and experts of Oil Company. By classifying concepts, subordinate and central categories, and finding a central category by using open, central, and optional coding method, categories forming the fosterage of organizational leaders in Oil Company and relationships between them appear in the format of a paradigm which included causal conditions (4 categories), the central category (3 categories), strategy (1 category), intervening factors (2 categories), context factors (4 categories), and consequences (1 category). In the research, the qualitative method was used in order to achieve a deep understanding of phenomenon under study. Therefore, to conduct the plan, in the first stage, to identifying a system for fostering organizational leaders in Oil Company, undetermined situation, different dimensions of the system were known by using the context theory-systematic plan and conducting interview based on the theoretical sampling. This research improvement a model to foster organizational leaders according to data-base theory in Oil Company.

Keywords: Organizational Leadership; Desirable Model; Oil Company; Data-base Theory (search for similar items in EconPapers)
JEL-codes: L2 (search for similar items in EconPapers)
Date: 2017
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