The proposed model of the body of knowledge of digital transformation for the Central Bank of the Islamic Republic of Iran.

Purpose: A body of knowledge is a formal description of a field that includes a complete set of theories, methods, concepts in a structured way, and technologies. If we consider knowledge alone as the factor of individual superiority, the flow of knowledge is the factor of group superiority. Knowledge flow is considered as one of the important paths of action for digital transformation. The central bank has always tried to use different methods and tools in order to continuously improve and upgrade its performance level. It is very important to use transformative tools in order to respond to changing environmental conditions and customer expectations. Considering the rapid changes of new technologies, the role of the central bank in replacing the traditional and conventional methods of providing services with new methods with the help of new technologies is very important. Therefore, digital transformation is a change from thinking to action, centered on transformative technologies. Digital transformation in the central bank makes it easier, faster and cheaper to provide services to customers. Also make it agile, smart and flexible with innovative services. Considering the importance of digital transformation in the central bank, this article was compiled with the aim of the proposed model of the body of knowledge of digital transformation for the Central Bank of the Islamic Republic of Iran.
Methodology: In terms of the division of scientific research, the current research is in the category of applied-developmental research. The purpose of modeling is to provide a clear and comprehensive picture of the body of knowledge of the central bank's digital transformation, which helps to solve the problem of determining the status of the organization's current capabilities and extracting its measurement metrics. Therefore, it is considered an applied research.On the other hand, considering the increase in knowledge resulting from the design of the model and examining the effects of variables affecting it, the research also has a developmental orientation. 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 opinion of experts about the importance of each of the indicators has been collected in the form of a 5-point Likert spectrum in the form of a questionnaire.The components and indicators were sent to the expert group in the form of a questionnaire. The sample selection method was purposeful and available. 15 people were selected to be a member of the expert panel from experts, managers, researchers and faculty members of universities. In the first stage of the research, the components and indicators of the body of knowledge of digital transformation were finalized by obtaining content validity and experts' opinions. Kendall's correlation coefficient was used to measure the level of consensus among panel members. The decision criterion is to achieve a strong consensus among the panel members, which is calculated based on Kendall's coefficient. After the second round of Delphi, Kendall's coordination coefficient was calculated in order to re-examine the degree of coordination of the Delphi panel about research factors and indicators, and the total coefficient was 0.81, which indicates a strong consensus among the members. Selected components and indicators were coded using MAXQDA software. In the second stage of the research, which is the quantitative stage, the researcher-made questionnaire was validated. For this purpose, the questionnaire was distributed among 159 managers and experts of Central Bank based on the classification of specified knowledge areas. After distributing and collecting the data from the questionnaire, confirmatory factor analysis was used with the help of SMART PLS software to estimate the parameters and all calculations. After conducting the content validity of the designed indicators in the next step, the construct validity was checked. To determine construct validity, confirmatory factor analysis was used, which is a sub-branch of structural equation modeling, a method for examining construct validity in studies where the measured indicators are a questionnaire with quantitative and qualitative items. Cronbach's alpha coefficient was used to determine reliability. Also, the indicators of path coefficient, standard deviation, t-statistic and probability value have been determined to examine the intensity and significance of the relationship between different knowledge areas of transformation in the central bank.
Findings: By identifying the knowledge areas and coding results, it showed 14 components and 51 indicators in the field of digital transformation Intelligence indicators of collection processes, statistical data analysis and performance indicators with an average of 4.93, were identified as the most important indicators in the central bank. The results of the quantitative part of the research show the correctness and confirmation of the designed relationships. In total, the areas of "new technology system" and "money and credit operation system" were identified as the most key factors in advancing the digital transformation of the central bank. On the other hand, areas such as "securities paper production system" and "payment systems" with less impact, need special attention and more investment to improve their role in this model. The high accuracy of the results and strong significance make this analysis a valid tool for improving digital transformation programs. The conceptual model of the research obtained from the body of knowledge of digital transformation in the central bank was designed by interpreting and combining the findings. The results show that all relationships between domains and digital transformation model are significant. The path coefficient, as a measure of the intensity of the effect, shows that the "development of the central bank's new technologies system" has the highest effect on the digital transformation model with a coefficient of 0.159.This shows the key role of this field in the development of digital transformation. The standard deviation for all relationships is low and in the range of 0.003 to 0.015, which indicates high accuracy in measurements and stability of results.
Research limitations/implications: This study's limitations included Experts' different definition of digital transformation & The dispersion of knowledge fields in different buildings of the Central Bank can be mentioned. Access to up-to-date and accurate data is one of the limitations due to the confidentiality levels of information in the central bank.
Originality/value: With the rapid changes of new technologies, the role of the central bank in replacing the traditional methods of providing services with new methods is very important.