Digital transformation in the Central Bank of the Islamic Republic of Iran (with a focus on identifying knowledge areas and indicators)

Document Type : Original Article

Authors

1 PhD student in Information and Knowledge Management, Faculty of Management and Economics, Tarbiat Modares University

2 Department of Management & Economics, Faculty of Management and Economics, Tarbiat Modares University, Tehran

3 Assistant Professor, Department of Information Science and Knowledge, Faculty of Management and Economics, Tarbiat Modares University

4 Postdoctoral Research in Data-Driven Digital Transformation, Faculty of Management and Economics, Tarbiat Modares University

Abstract

abstract

Objective: The ever-increasing advances of emerging technologies in all fields have led to deep changes at the level of societies. Banks and credit institutions, as well as the central bank at its head, have also undergone technological transformation. Benefiting from transformative technologies as a solution to challenges as well as a potential to create new opportunities will be effective in providing better services of the central bank.This article has been compiled with the aim of identifying knowledge areas and indicators based on digital transformation in the Central Bank of the Islamic Republic of Iran in order to create a systematic view in line with the digital transformation in the Central Bank as well as banks and credit institutions.

Method: The present research was studied with the aim of identifying the effective indicators on the digital transformation of the central bank, with the approach of systematic background review. Also, in order to take advantage of the ideas and points of view of subject experts in order to develop the existing body of knowledge and validate and refine the research findings, the Delphi method was used.In order to evaluate the identified components, according to the selection of 24 experts, managers, researchers and faculty members of universities who had knowledge (at least a bachelor's degree) and sufficient experience (at least five years of work experience) and activity in the field of research, components and indicators It was sent to the expert group in the form of a questionnaire. Finally, the primary components and indicators were developed, refined and approved based on the opinions of 15 subject matter experts who were identified using targeted sampling. During this stage, the order of importance of each element of the research model was also determined. The Delphi method has been used to screen and ensure the importance of the identified indicators and to select the final indicators from the point of view of experts. The opinions of experts about the importance of each of the indicators have been collected in the form of a 5-point Likert spectrum in the form of a questionnaire. After reaching a consensus among the members of the Delphi panel, the final output of the study was compiled and explained in the form of a research conceptual model.In this study, Kendall's correlation coefficient was used to measure the agreement between panel members. This coefficient shows whether people use similar criteria in ranking the importance of several categories. In other words, Kendall's correlation coefficient shows the degree of consensus among people regarding the importance of each category. This coefficient is also used to decide whether to stop or continue the Delphi survey rounds.

Findings: Based on the qualitative analysis, the areas affecting the digital transformation of the central bank were identified with 16 components and 101 indicators in the field of digital transformation. But finally, the areas and indicators effective in digital transformation have been classified with 14 main components and 51 indicators.The results showed that the indicators of intelligentization of collection processes, statistical data analysis and performance indicators with an average of 4.93, management of analytical tools to identify opportunities obtained from data with an average of 4.66, strategic management of information technology architecture with an average of 4.66 and smartness of business processes to prevent The occurrence of fraud and criminal transactions have the highest score with an average of 4.6 and were identified as the most important indicators in the central bank.

Conclusion: During the process of analysis, interpretation and combination of findings, a conceptual model of the components and indicators of the central bank's digital transformation was drawn. The acquisition model can be used in the design of digital banking transformation models in future research. The important areas of digital transformation knowledge can be considered as an enabling factor in promoting the central bank's dynamism, agility, credibility and innovation. In this research, the results obtained from the Delphi method showed that the indicators considered by experts in the field of digital transformation of the Central Bank include 51 indicators. These indicators show that the organization will face complex challenges such as cyber security, big data management, intense competition and high customer expectations. To succeed in this dynamic environment, organizations must rely on new technologies, improve their processes, and view data as a valuable asset. To succeed in this dynamic environment, organizations must rely on new technologies, improve their processes, and view data as a valuable asset.

Knowledge enhancement: the attention of the central bank to the use of transformative technologies in banks and financial and credit institutions in order to improve financial performance.

Keywords: knowledge, knowledge fields, knowledge indicators, digital transformation indicators, digital transformation, Central Bank of the Islamic Republic of Iran

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