Typology of the mentality of experts of government organizations in the field of establishing big data governance using Q methodology

Abstract

In recent years, organizations in the public and private sectors have been faced with large volumes of structured and unstructured data that require a big data governance framework. Big data governance, by using environment monitoring and data collection, data storage and data analysis, provides the information needed by organizational decision makers. Establishing a big data governance framework enables organizations in the public and private sectors to make better decisions based on evidence and insight. Therefore, the purpose of this study is to investigate the mentality of experts in the field of establishing big data governance and for this purpose, Q methodology has been used. The statistical population of the present study included experts of government organizations and based on purposive sampling; 38 experts were selected for the study. In the present study, the discourse atmosphere included authentic domestic and foreign books and articles and semi-structured interviews. The number of propositions that were identified in the discourse atmosphere included 52 propositions, and by modifying and removing duplicate propositions, 48 final propositions were identified. Then, each of the Q propositions was numbered and the experts were asked to sort the number of each Q proposition in the Q diagram. Exploratory factor analysis and correlation matrix used to analyze the resulting data from the discourse atmosphere. Cronbach's alpha test, KMO index and Bartlett test used to evaluate the validity and reliability of the research method. The results of the present study showed three types of mentality that the total amount of variance explained was equal to 80.81%. The percentage of explained variance was 30.59% for the first type, 26.31% for the second type, and 23.90% for the third type. Evaluation of propositions related to the mentality of expert’s shows that most experts emphasize the results of establishing big data governance; They emphasize such things as facilitating knowledge flow, efficient and effective decision making, innovative performance, strengthening teamwork, and strategic planning and analysis. Experts, on the other hand, focus on drivers such as information technology, data control and oversight, structural mechanisms, democratization capacity, and legal capacity. In general, to take advantage of big data governance in public organizations and reduce the data gap, there must be coordination and consistency between the propositions and the results of establishing big data governance, and this research can serve as a stepping stone to this.

Keywords

• big data
• big data governance
• typology of the mentality of experts
• q methodology.