سید علیرضا درخشان

Central Bank Cryptocurrency (CBDC) is a semi-decentralized solution based on DLT. This money is issued electronically by central banks to facilitate payments without intermediaries. this research aims to model CBDC and is conducted with a mixed approach (qualitative and quantitative methods). In the qualitative part, a conceptual model was designed by asking the opinions of 20 experts through an open questionnaire and a coding approach was tested by a sample of 102, banking and payment experts. In the quantitative part, the reliability and validity features of the questionnaires were investigated, and in the structural part, the model coefficients were evaluated to check the research hypotheses. The results of this research, while determining many factors affecting the circulation of the central bank's currency, confirm that the circulation of money is the basis for the social acceptance of this phenomenon and emphasizes the necessity of its precise policy. Some background and intervening factors are also identified in the model. On the other hand, the consequences of publishing cryptocurrency in this model are influencing monetary policy, other businesses, banks, and some other micro and macro factors.

In today’s world, taking advantage of social capacities and national capabilities in manufacturing handicrafts requires the application of new state-of-the-arts production techniques. In this regard, social manufacturing is an emerging phenomenon that serves as a new production ecosystem equipped with modern technologies and social networks. Therefore, this qualitative study sought to identify the requirements and challenges of applying social manufacturing to the production of handicrafts using the Grounded theory (Glaser method). To collect the required data, semi-structured interviews were made with twelve experts in the field of handicrafts and information technology who were selected through the purposive sampling method. The collected data were then analyzed using the MaxQda 10 software. On the other hand, the validity, transferability, reliability, and verifiability of the study were also measured to strengthen the findings. Finally, the collected data were analyzed through actual and theoretical coding.According to the study’s results, altering the manufacturing structure, fostering relationships with consumers, developing research and education, developing the infrastructures, and establishing production networks were identified as the main requirements of applying social manufacturing to the production of handicrafts. Moreover, the conceptual map of the study was drawn, including nine categories and twenty-nine sub-categories. The current study can fill a number of gaps existing in the application of social manufacturing in Iran.

Multifunctional platforms with a social manufacturingapproach are emerging phenomena with less known business models. Given the valuable human resources and cultural capacities of Iran, there is a suitable opportunity for utilizing the multi-functional platform business model with a social manufacturingapproach for producing cultural products. The aim of this research is to identify and rank the dimensions and factors of these platform business models. Through in-depth interviews with 14 experts in this field and thematic analysis using MAXQDA software, data analysis was conducted in three stages: open coding, axial coding, and selective coding. After screening the results, 50 factors were identified in 10 dimensions using the fuzzy Delphi method. The impact and influence of these factors were determined using the fuzzy DEMATEL method, and ultimately, the factors and dimensions were ranked. The identified factors and dimensions assist stakeholders in the cultural product production field to better configure their current or future platforms, as well as helping investors make more informed decisions regarding this business model.

In recent years, studies on the paradigm of social Manufacturing and its applications have been developed as a new production paradigm and have led to the production of diverse and scattered knowledge in this field. Knowing the sub-fields, new topics and the research process of the social production paradigm can be of great help to researchers in this field. The current research has been carried out with the aim of identifying and categorizing research in the field of social Manufacturing, recognizing sub-fields and achieving a coherent view of its research process.This research has investigated the research field of social Manufacturing using bibliometric analysis. The data of this research was collected from 200 articles of the Scopus database and an analysis of the co-occurrence analysis of key words and bibliographic pairs was performed on them, and in this way the sub-fields and the research process of this field were identified.Based on the findings of this study, the research in the field of social Manufacturing has been categorized into 5 clusters and it has also been determined that in recent years, topics such as cloud computing, smart production, blockchain, Internet of Things, social physical cyber systems, innovation systems, society 5.0 and Digital twins have received more attention in research in this field. This research provides a framework of concepts and main topics of interest in the research field of social production, which provides a comprehensive perspective for researchers in this field that can help in choosing their research path.

The aim of this study is to present a technology transfer framework in the electronic banking industry, which is a mixed method and applied research type. The statistical population included 17 experts in the qualitative section and 451 information technology and technology transfer experts in the banking industry in the quantitative section, of which 207 were selected in a stratified sampling method with proportional allocation. To do this, a number of 14 components were identified from the expert analysis in order to form the technology transfer framework. Their content validity was verified through confirmatory factor analysis. In the survey of experts, in terms of being operational in the relevant industry, as well as the importance of their presence in the framework of technology transfer, through the T-Student test, it was reduced to 9 components. The findings include 9 meaningful components: identifying technology needs, updating, research and development, negotiation, technical knowledge transfer, operational knowledge acquisition, technical knowledge implementation, transfer plan presentation and infrastructure provision. Finally, using AHP analysis, the prioritization of the components in the implementation of the technology transfer framework was discussed.

In accordance with Simon's decision-making model, this study first tries to identify the key indicators of business intelligence systems as a set of technologies and processes enhancing the quality of decision-making system in organizations. Next, evaluates the existence of causal relationship between the decision stages and the key indicators. To identify the key indicators of business intelligence in each stage of Simon's decision making model, this paper uses Delphi method.Open-ended questions and in-depth interviews were conducted by snowball method with18 experts in the field of development and implementation of business intelligence systems in financial organizations and the final indicators were extracted. The main indicators were identified after analyzing the cause-and-effect relationships between the existing relationships and each stage of the Simon model. This paper uses dematel technique to determine effective and influential relationships and by prioritizing indicators in terms of impact and effectiveness, the results discussed. Finally, executive proposals provided to individuals responsible for development and implementation of business intelligence systems in financial organizations. The findings support that owning a business analysis department in the organization has the most interaction with extracted key indicators. Based on Simon's decision-making model, creating, implementing, and monitoring key performance indicators (KPIs) play a key role in enhancing decision quality in business intelligence systems, For financial institutions, the quality of decisions plays a crucial role in their success in a competitive market. Therefore, the results obtained through this research can be used by those responsible for the development and implementation of business intelligence systems.

This article firstly tries to identify the various dimensions of successful implementation and development business intelligence as a set of technologies and processes that promote the procedure of the decision-making in the organization. Next, the effect of these dimensions on the process of decision-making in Eghtesad-e-Novin Bank, as a financial organization in which the speed of decision-making is of importance will be discussed. The criteria are the cultural, strategic and environmental factors, human resources and business intelligence tools the effects of which are discussed on the variable of "the latency in decision- making" in four divisions of organizational decision environment. The research methodology is mixed in this research and for this purpose in the qualitative part, the different dimensions of success in implementation and development business intelligence were extracted on the quality of decision-making with the Delphi technique by using the method of interviews and open questions in three stages and with the snowball method with the opinions of 18 experts. In the quantitative part, the priorities were determined with the help of the Analysis Network Process and Super Decision software. Finally, the main questionnaire has been finalized for the distribution among 90 personnel of different levels of the development and implement of business intelligence systems and the direct users of these systems in the organization. With the help of Smart Plus software and structural equations, as well as the effect of research variables on the reduction in the latency in decision-making, the relevant assumptions have been examined in a descriptive and survey manner with factor analysis. The proposed factors and models for evaluating business intelligence presented in this article help organizations, especially financial organizations in which speed in decision-making is of particular importance, to promote decision-making and minimize possible latencies in decision-making.