mohammadhasan maleki

One of the most important applications of blockchain technology is smart contracts. Smart contracts carry out transactions and processes in a completely guaranteed way and without the involvement of third parties. The current research seeks to identify and analyze the drivers affecting the future of smart contracts in the banking industry. The present study is applied in terms of orientation and has a quantitative nature in terms of methodology. In this research, two fuzzy Delphi and Marcos techniques were used for data analysis. In the first stage, 37 drivers were obtained through literature review and interviews with banking experts. These drivers were screened in the next stage by distributing expert questionnaires and fuzzy Delphi technique. 10 drivers were selected for final ranking with Marcos technique. Screened drivers were prioritized by distributing priority questionnaires and Marcos technique. Based on the scores of the Marcos method and taking into account the three indicators of experts' expertise, the intensity of importance and the degree of certainty, the drivers of the level of coordination and integration of the country's banks in accepting new technologies and contracts, the level of integration of information systems in the banking industry, regulatory policies in the country and the type of interaction of banks with fintechs and financial startups respectively having the highest priority in terms of influencing the future of smart contracts in the banking industry.  Practical proposals were developed based on the most prioritized drivers. Carrying out joint research and development projects by the country's banks, paying attention to the compatibility of blockchain technology and smart contracts with other modern banking technologies, comprehensive regulatory policies with the presence of all stakeholders, and the strategic cooperation and partnership of banks with fintechs were among the main suggestions of the research.

The environmental requirements and the need of many transportation projects in the maritime sector for financing have made it important to examine the future of sustainable financing in the maritime transportation industry.Despite extensive research in the field of future study in the transportation sector,little research has been done on the future of maritime transportation and its financing.The current research seeks to identify the drivers and future scenarios of sustainable financing in the maritime transportation industry with a scenario-based approach.It is applied and a mixed study.The theoretical population of the research is consultants and specialists in sustainable financing and future study in the maritime transportation industry.The sample size was 10 people.Interview and questionnaire were two important data collection tools.25 drivers were extracted through literature review and interviews with experts and screened by distribution of expert questionnaires and fuzzy Delphi method.the screened drivers were ranked by distributing priority questionnaires and the CoCoSo method.Finally the research scenarios were developed based on priority drivers and interview method with focus groups.These scenarios were:plural financing,bank-based financing,technology-based financing and black hole financing.

Corporate governance is an integral and necessary part of the governance of today's societies. There are different viewpoints and selection of agency theory (shareholder-oriented approach) or stakeholder theory (community-oriented approach) in the corporate governance system of societies. Present study seeks to identify the most important drivers of corporate governance in Iran.

The theoretical population of research is managers and senior experts active in the stock market who are experts in the field of corporate governance. The sampling method was done judgementally according to the expertise of experts in the field of corporate governance. The sample size in this study was 10 people. Research drivers were extracted through literature review and interviews with corporate governance experts. Then, two questionnaires of expertise and effect assessment were used to screen and analyze the effectiveness of the drivers. These questionnaires were analyzed by two methods of fuzzy Delphi and fuzzy dematel.

20 drivers were extracted through literature review and eight drivers were extracted through interviews with experts. Among the research drivers, 10 drivers had a defuzzy number greater than 0.7 and were selected for final prioritization. The effectiveness of the residual drivers was investigated with fuzzy dematel. According to the Net Effect Index, the drivers of government policies and actions on corruption, the monitoring of laws and regulations imposed by the Securities and Exchange Organization, the transparency of the business environment, and the legal regulations and challenges had the highest impact, respectively.

Financial technology, through the use of advanced innovations and technologies,has profoundly transformed the financial industry and its traditional institutions, such as banks and insurance companies. FinTech startups operate across various sectors, including payments, lending, financing, investing, cryptocurrencies, regulation, banking, and insurance. Numerous drivers are influencing the future of these startups. This study aims to identify and analyze the key drivers shaping the future of FinTech startups.

This study is applied in its orientation and employs a mixed-methods approach. Both quantitative and qualitative techniques were utilized to analyze the data. The Fuzzy Delphi method was employed to screen the drivers, while the Fuzzy DEMATEL method was used to assess the effects of these drivers. The Best-Worst Method (BWM) was employed to determine the weights of the drivers based on the severity of uncertainty. Subsequently, the Root Definition method was applied to present the desired research scenario. The theoretical population comprised experts in the field of fintech startups, and the sampling method employed was purposive. Data were collected through a literature review, expert interviews, and three fuzzy questionnaires: screening, impact assessment, and prioritization.

Initially, 21 drivers were identified through a literature review and expert interviews. These drivers were subsequently screened using the Fuzzy Delphi technique. Eleven drivers, which had defuzzified values of less than 0.7, were excluded from the study. The remaining ten drivers were analyzed based on two indicators: effectiveness and severity of uncertainty, using the Fuzzy DEMATEL and Best-Worst Fuzzy methods. The drivers related to the familiarity of executive, legal, and regulatory institutions with fintech business models, along with the performance of regulators in legislation, exhibited the most significant net effects. Additionally, the drivers concerning regulatory performance in legislation, as well as the familiarity of executive, legal, and regulatory institutions with fintech business models, exhibited higher levels of uncertainty, as evidenced by their greater weights.

Considering the drivers related to regulatory performance in legislation, as well as the familiarity of executive, legal, and regulatory institutions with fintech business models, a preferred research scenario was developed. To develop this scenario, six components—namely, customers, actors, the transformation process, stakeholder worldview, problem environment, and problem owner—were utilized based on the Root Definition technique.

Corporate governance plays an important role in strengthening good governance in banks and realizing a resilient economy.The current research seeks to identify and prioritize factors affecting corporate governance in the banking system with the resistance economy approach.

The current research is a mixed study. The theoretical population of the research was experts in corporate governance and resistance economy in the banking system.Sampling was done by judgment and based on the expertise of experts.Interview and questionnaire are the most important data collection tools.In this research, qualitative and quantitative techniques were used together.

At first, 34 factors affecting corporate governance in the form of seven main factors were extracted through theme analysis.The main research factors were: technological and innovative factors, legal and regulatory factors, transparency and reporting factors, structural factors, managerial factors, sustainability factors and educational-consulting factors.In the next step, sub-factors were screened by distribution of expert questionnaires and fuzzy Delphi method.11 factors had a defuzzified number higher than 0.7.The screened factors were evaluated by the Cocoso method.The priority factors were:the extent use of advisors and experts in resistance economy and corporate governance issues, the extent of banks' attention to indicators of resistance economy in sustainability reports, the extent of banks' transparency in the selection, hiring and promotion of managers, the use from data-driven technologies for transparency of contracts and the extent to which banks move towards sustainability.

Functional suggestions were developed based on the most important factors. Some of the most important suggestions were: the bank's use of the expert opinions of strong consultants in resistance economy and corporate governance, creating indicators in resistance economy and corporate governance and paying attention to these indicators in bank reports, using fourth generation industry technologies for the integrity of the bank and Strengthening data-driven decisions and banks' attention to sustainability indicators and sustainable financing.

In today's world, the application of circular economy policies and programs plays a significant role in guiding the mining industries toward sustainable development. However, efforts to achieve sustainable development in Iran's mining industries have not been sufficiently serious. This study aims to explore the future of Iran's mining industries with a focus on the circular economy. Methodologically, this research employs a mixed-method approach and is exploratory in purpose. The study uses fuzzy Delphi, Cuckoo, and focus group interviews to assess the drivers and develop scenarios. In the first step, 33 drivers were identified through a literature review and interviews with experts in the mining industries. The drivers were then screened using expert validation questionnaires and the fuzzy Delphi technique. Nine drivers were selected for the final assessment using the Cuckoo method. These final drivers were prioritized through preference questionnaires and the Cuckoo method. Finally, future scenarios for the mining industries, focusing on the circular economy, were developed based on two prioritized drivers and interviews with focus groups. Based on the Cuckoo method scores and expert opinions, the drivers of government and large financial institutions' support, such as banks for waste management and recycling projects, and energy pricing policies in the country were the most prioritized factors influencing the future of mining industries with a focus on the circular economy. Four scenarios were developed based on the two final drivers and interviews with focus groups. These scenarios included: Generous Supporter, Sustainable Mining Industries, Dark Era, and Future-Oriented Policymakers. Practical recommendations were developed based on the most important drivers and the optimal scenario (Sustainable Mining Industries). Key recommendations include prioritizing waste management and recycling projects for financing by banks, shifting from directive policy-making to market-based and competitive policy-making, and leveraging green startups in research and development projects in the mining industries.

Blockchain technology, with its advantages such as reducing intermediaries, controlling costs, and increasing security, has garnered attention from the financial industry. This technology, besides centralizing banking processes, can help improve operational efficiency. This study aims to identify and analyze the drivers influencing the future of banking in Iran, with a focus on blockchain technology. The research is applied in terms of orientation and quantitative in terms of methodology. Two methods, fuzzy Delphi and Marcus, were used for data analysis. Initially, 29 drivers were extracted through a literature review and interviews with banking experts. Subsequently, nine drivers were selected for final prioritization using the Marcus method after distributing expert questionnaires and screening them with the fuzzy Delphi method. The final drivers were ranked through a questionnaire distribution. The perceived organizational benefits, the compatibility of blockchain technology with the IT systems of the banking sector, the development of RegTech in the country, and the regulatory approaches of lawmakers regarding digital financial technologies were, respectively, identified as the highest-priority drivers. The most important practical recommendations of the study include developing a tool to measure the benefits of blockchain technology, adopting a systemic view towards the implementation of new technologies, making necessary changes before transferring the technology to the banking sector, leveraging RegTech capacities to assess the risks of using digital financial technologies, and ensuring the integration of regulatory policies and comprehensive regulation.

The current research seeks to identify and prioritize factors affecting the maturity of knowledge-based companies in the food industry, focusing on the approach of the fourth-generation industry.

The current research is applied in terms of orientation and it is a quantitative study from the point of view of methodology. The theoretical population of the research is the specialists of organizational maturity and the fourth-generation industry in the food industry. Sampling in this research was done based on the expertise of experts in the field of research. In this research, the fuzzy Delphi method was used to screen the factors and Copras and Mabac techniques were used to prioritize the screened factors. Interviews with focus groups were also used to provide practical suggestions.

The present research was carried out in several stages. In the first step, factors affecting the maturity of knowledge-based companies in the food industry were extracted through literature review and interviews with experts. To screen the factors, expert questionnaires were distributed among the experts, and the experts expressed their opinions about each of the factors in the form of a five-degree fuzzy spectrum. 10 factors had a favorable defuzzified number and were selected for final prioritization. Screened factors were evaluated by distributing priority questionnaires and Copras and Mabac techniques. The experts expressed their opinions in the form of a spectrum of 10 point on four indicators. The priority factors were: governance of data-driven decision-making culture, the use of new learning methods in the organization, the use of cloud platforms in the organization, the use of smart machines and equipment in the company, and innovation policies in the organization.

Originality/Value: 

Practical research proposals were developed based on the most important factors. Some suggestions were: the use of data-driven technologies such as business intelligence and big data to strengthen data-driven decision-making, the use of a hybrid approach in training and the application of new technologies in the field of training such as Metaverse, the use of Internet of Things and blockchain technologies to automate and intelligentize processes and finally Moving towards an open innovation policy.

The food industry is one of the vital industries for the health and well-being of society. The aim of the current research is to provide a model of factors affecting organizational maturity in knowledge-based companies of the food industry in Iran with the approach of the fourth-generation industry. The research consists of two qualitative and quantitative parts, in the first part, the main and secondary factors of the model were obtained through metacomposition. In the second part, the relationships between the main factors were determined through cross impact analysis.

The current research is applied in terms of orientation and is a mixed study in terms of methodology. Also, the current research is a pragmatic study in terms of philosophical foundations and exploratory research in terms of the goal. The theoretical population of the research is the experts of the food industry and the sampling was mainly done in a judgmental and purposeful way. In the judgmental sampling method, cases and samples are selected based on the expertise of experts. In this research, the meta-synthesis method was used to extract factors and the cross-impact analysis was used to determine the relationships between the main factors. Validation of articles was done by CASP tool. The extracted articles were screened step by step to identify the most qualitative articles for study.In this research, meta-synthesis method was used to extract factors and cross impact analysis technique was used to determine the relationships between the main factors. In order to get experts' opinions about the relationships between the research factors, influence evaluation questionnaires were used. The experts were asked to express their opinions on a scale of 0 to 3. Also, to measure the validity of the meta-synthesis part, the Lawshe content coefficient was used, and the Kappa coefficient was used to measure the reliability of the codings. Validity and reliability values in this research were appropriate.

This research was done in two steps. In the first step, factors affecting organizational maturity were extracted using a systematic background review and meta-combination method. The output was 6 main factors and 27 secondary factors. The main factors affecting organizational maturity were: structural factors, training and learning, technological factors, factors related to the nature of governance, factors related to innovation, and factors related to decision-making. In the following, these factors were evaluated with the approach of structural analysis of cross impact analysis. The results of this technique showed that decision-making, structural and governance factors are effeinfluential variables. Also, technological and innovative factors were evaluated as impressionable variables.

Practical suggestions of the research were developed based on the influencing factors. Some suggestions were: the use of data-driven technologies such as business intelligence and big data to strengthen data-driven decision-making, paying attention to the compatibility and integration of technologies and information systems in knowledge-based companies in the food industry, and the use of technologies such as blockchain to improve governance and improve the transparency of knowledge-based companies in the food industry. By using technologies such as big data, a large amount of data can be collected and analyzed, and based on that, many risks and threats can be identified and managed. Business intelligence can be used to classify and predict key variables. Blockchain is also a key technology to enhance transparency and develop smart contracts. It should not be forgotten that the fourth-generation technologies are mainly integrated and systemic, so before the introduction of new technology, attention should be paid to system adaptation.

This study aims to establish a framework for evaluating the fintech partners of banks.

The present study is applied in its orientation and quantitative in its methodology. In this study, three methods were employed: fuzzy Delphi, best-worst fuzzy, and fuzzy similarity. The fuzzy Delphi method was utilized to screen the research criteria, the best-worst fuzzy method was applied to assign weights to the research criteria, and finally, the fuzzy similarity technique was used to prioritize fintech partners within the banking sector. To collect research data, we utilized interview and questionnaire tools. The research questionnaires included a criteria screening questionnaire, a paired comparison questionnaire, and a priority assessment questionnaire.

First, a review of the literature and interviews with banking experts identified 17 criteria for evaluating banking fintechs. In the subsequent step, these criteria were assessed using the fuzzy Delphi method. Five criteria, which had a defuzziness value greater than 0.7, were selected for the evaluation of fintechs. The weights of these criteria were determined using the fuzzy Best-Worst Method (BWM). Among the research criteria, the criterion assessing fintech capability for establishing long-term strategic relationships with banks received the highest relative importance, with a weight of 0.35.
Finally, three fintech companies collaborating with Bank Mellat were assessed based on the research criteria and the fuzzy similarity technique. Fintech "C" with a score of 0.82, received the highest priority for collaboration with Bank Mellat.

Rather than viewing fintech companies with negativity and competition, banks can foster strategic partnerships with them. By investing in these firms, banks can enhance their research and development efforts, ultimately delivering more innovative and high-quality services to their customers.

As an endogenous antioxidant, bilirubin has surprisingly been inversely correlated with the risk of non-alcoholic fatty liver disease (NAFLD). Thereupon, the current evaluation was designed to assess the positive effects of bilirubin on the autophagy flux, as well as the other pathogenic processes and parameters involved in the expansion of NAFLD.

Experimental approach: 

Thirty adult male rats weighing 150-200 g with free access to sucrose solution (18%) were randomly subdivided into 5 groups (n = 6). Subsequently, the animals were euthanized, and their blood specimens and liver tissue samples were collected to measure serum biochemical indices, liver histopathological changes, intrahepatic triglycerides content, and tissue stereological alterations. Furthermore, the expression levels of autophagy-related genes (Atgs) were measured to assess the state of the autophagy flux.

Fasting blood glucose, body weight, as well as liver weight, liver-specific enzyme activity, and serum lipid profile indices markedly decreased in rats that underwent a six-week bilirubin treatment compared to the control group. In addition, histopathological studies showed that hepatic steatosis, fibrosis, inflammation, and necrosis significantly decreased in the groups that received bilirubin compared to the control animals. Bilirubin also caused significant alterations in the expression levels of the Atgs, as well as the Beclin- 1 protein.

Conclusion and implication: 

Bilirubin may have potential ameliorative effects on NAFLD-associated liver damage. Moreover, the beneficial effects of bilirubin on intrahepatic lipid accumulation and steatosis were comparable with the group that did not ever receive bilirubin.

Religious tourism has been the subject of many studies in recent years, leading to the development of a wide variety of cultural and spiritual entrepreneurial projects, ideas, and businesses to provide cultural products and services. However, the success of such projects mainly depends on proper financing as a basic requirement in this regard. Thus, considering the special nature of businesses related to religious tourism, it seems that crowdfunding can perform well in financing such projects and businesses. Therefore, this applied quantitative study sought to identify and prioritize the factors involved in building confidence in investors to participate in crowdfunding projects defined in religious tourism. To this end, fuzzy DELPHI, DEMATEL, and CODAS methods were used to analyze the collected data. In this regard, first, fifteen factors that may influence the confidence of investors in crowdfunding projects regarding religious tourism were identified through a systematic review of the related literature, which were then screened via the fuzzy Delphi technique, and six factors were excluded. Then, the remaining nine factors were examined in terms of impact rate using the DEMATEL technique. Accordingly, five factors were found to have a net positive effect, indicating that they were more effective than other identified factors. Finally, those five factors were prioritized using the CODAS distance technique. According to the results of the study, cultural policy-making at the macro level, positive cultural and spiritual influence of the project on society, and the entrepreneur's experiences and expertise in cultural and spiritual projects were found to bear the highest priorities, respectively.

Fintechs play an important role in improving financial industry services by providing new innovations and technologies. However, due to various obstacles, Iranian fintechs have not developed much and have little diversity. Most Iranian fintechs are of the payment type. Considering this challenge, the current research seeks to identify and analyze the most important obstacles to the development of Iranian fintechs in the financial industry. The current research is applied in terms of orientation and has a quantitative methodology. The theoretical population of the research is fintech experts in the country and sampling was done based on expertise in the field of financial technologies with a judgmental method. The sample size in the research was equal to 10 people. At first, 24 fintech development barriers were extracted through literature review and structured interviews with experts. The extracted barriers were screened by distribution of expert questionnaires and fuzzy Delphi method. 11 obstacles had a defuzzy number greater than 0.7 and were selected for final prioritization. The final obstacles were investigated by distributing priority questionnaires and the CoCoSo method. Since the content validity index of all the extracted barriers was higher than 0.79, all the research questionnaires had good validity. Priority obstacles were: low depth and variety of financial markets in Iran, closed innovation policies of large financial institutions, lack of trust of customers in innovative financial services and low budget for research and development projects in large financial institutions.

Today, higher education is considered one of the most important bases for the development of societies. Today, higher education is considered one of the most important bases for the development of societies. Blockchain technology affects many areas, one of these areas is education and universities. Therefore, the current research seeks to identify and analyze the effective drivers of the future of higher education with a focus on blockchain technology.

The current research is applied in terms of orientation and is post- positivism in terms of philosophical foundations. Fuzzy-Delphi and Marcus methods were used in this research. The theoretical community of the research, the educational managers of the large public universities of Iran, and the judgmental sampling method and the samples were selected based on the expertise and experience of experts in the fields of higher education and blockchain technology and the sample size was equal to 10 people. Data collection tools are interviews and questionnaires.

At first, through background review and interviews with experts, 18 drivers were extracted, 14 of which were from the background and 4 through interviews. In the following, they were screened by distributing expert questionnaires and fuzzy Delphi method. 9 drivers were considered as final drivers. The final drivers were prioritized by the Marcus method.

3 drivers, the approach of universities towards new technologies, the coordination of the educational system with the systems and infrastructures of other universities, and the support of the senior managers of the universities were the highest priority respectively.

The transition from branch-based banking to technology-based banking improves performance, reduces costs, and makes banks more agile. But the opportunities created for banks are not without challenges. The current research seeks to identify and prioritize the challenges faced by banks in the transition from branch-based banking to technology-based banking. Due to its benefits for the banking sector, the current research has an applied orientation and its methodology is quantitative. In this research, two quantitative methods, fuzzy Delphi and Marcos, were used for data analysis. Research challenges were extracted through literature review and interviews with experts. In the following, these challenges were screened by distribution of expert questionnaire and fuzzy Delphi method. Finally, the priority level of the screened challenges was determined by distributing priority questionnaires and the Marcos method. The content coefficient of the research factors was acceptable, which means the validity of the research questionnaires. The theoretical community of the research was the managers and senior experts of Refah Bank and university professors, and the sampling method was done as a judgment based on the experts' expertise. The sample size in this study was equal to 15 people. At first, 26 challenges were extracted through literature review and interviews with experts. These challenges were screened by the fuzzy Delphi method and nine challenges had a fuzzy number higher than 0.7. Screened challenges were prioritized by Marcos method. The prioritization results showed that the challenges of cooperation with financial startups and FinTechs, the occurrence of unknown risks and problems during the implementation of new technologies, the decision-making style in the organization, and the regulation of new technologies were the highest priorities, respectively. Finally, the research proposals were developed based on the priority challenges with the focus group interview method. Some of these suggestions were: using RegTechs to identify and analyze the risk of cooperation with fintechs, using risk analysis and foresight committees to identify and predict future risks, strengthening the data-driven decision-making style by using technologies such as business intelligence and big data and paying attention to fair and comprehensive regulation considering the interests of all stakeholders involved.

One of the challenges faced by managers in the field of social networks in virtual space is the lack of understanding of the reasons for the decrease or increase in the number of users across various social networks in cyberspace. Despite the appropriate capabilities of some domestic social networks, their popularity is much lower compared to foreign-based networks. Research conducted in the field of social networks has mainly focused on pathology and the identification of positive and negative effects. Additionally, most of these studies have been conducted on foreign social networks such as Instagram. On the other hand, the research has only focused on certain factors and has not taken a comprehensive look at all the effective factors. The main question of the current research is: What are the most important factors affecting the use of internal social networks in Iran's virtual space?

The primary goal of this research is to identify and prioritize the factors affecting the use of internal social networks in Iran's virtual space. To achieve this, fuzzy Delphi, best-worst fuzzy, and COCOSO methods were employed to rank these factors. All three methods are part of quantitative techniques and utilize judgmental quantitative data for analysis and prioritization. The fuzzy Delphi method was used to screen the research factors, while the COCOSO technique was employed to rank the factors affecting the use of internal social networks in Iran's virtual space. The weight of the evaluation indicators for the research factors was also calculated using the fuzzy best-worst technique. Due to the quantitative nature of the techniques used in this research, it adopts a multi-method quantitative methodology. Furthermore, given the practical implications of the research findings for internal social networks, this study has a practical orientation. Data were collected using two interview tools and a questionnaire. Factors affecting the use of internal social networks were extracted from an analytical review of studies on social media and social networks. Subsequently, to evaluate these factors, three questionnaires—fuzzy screening, pairwise comparison, and COCOSO priority assessment—were distributed among experts. Screening questionnaires were evaluated using the fuzzy Delphi method; pairwise comparison questionnaires were assessed with the best-worst fuzzy method, and priority evaluation questionnaires were analyzed using the COCOSO method.

The present research was conducted in three stages. In the first step, 24 factors were extracted through literature review and interviews with experts. In the next step, these factors were screened by distributing expert questionnaires and employing the fuzzy Delphi method. Eight factors had a defuzzified score higher than 0.7 and were selected for final ranking. Finally, the screened factors were ranked through the distribution of priority questionnaires and the COCOSO method. The prioritized factors included: the variety of services provided by the social network, users' trust in the social network, users' privacy and security, and social networks' monetization policies.

The current research seeks to identify and prioritize factors affecting the use of internal social networks in Iran. Most of the research conducted in this field pertains to foreign social networks such as Instagram. Conversely, previous studies have only considered certain variables, and the factors have not been comprehensively investigated and evaluated. The present research was conducted in three stages. In the first step, 24 factors were extracted through literature review and interviews with experts. The interviews with some experts were conducted to enrich the list prepared from the literature. Despite utilizing qualitative methods for thematic analysis, since most of the methods employed in this research were quantitative in nature, it is classified as a quantitative study in terms of methodology. Seven factors were added to this list by experts. Eight factors were in good condition in terms of their defuzzified scores and were selected for final ranking. The screened factors were evaluated and ranked using the COCOSO method. According to the scores of the final factors, the diversity of services provided by the desired social network, users' trust in the desired social network, users' privacy and security, and the social network's income generation policies were prioritized, respectively. Practical research proposals were developed based on the most important factors. Some practical suggestions include developing a specific business model, gaining users' trust, establishing regulations, creating a specific revenue plan, and paying attention to technology ethics.

The purpose of the present study is to investigate the influencing factors on the quality of implementation of performance-based budgeting in project-oriented organizations in the housing sector of Iran.

This research is a qualitative-quantitative study. In the qualitative aspect, theme analysis was employed, while the Fuzzy-Delphi technique and developed Kepras were utilized in the quantitative aspect. The research factors were derived from interviews with experts and theme analysis. The statistical population of the study comprises employees specializing in project planning and budgeting within project-based companies operating in Iran's housing sector. The sampling method was purposive, and the sample size consisted of 20 experts with relevant knowledge and experience in project-based organizations in the housing sector. To screen and prioritize dimensions and indicators, two questionnaires for expert assessment and prioritization were utilized, and fuzzy techniques - Delphi and Kapras - were employed for analysis.

Among the indicators calculated from interviews with experts, using the theme analysis tool and employing the Fuzzy-Delphi technique for screening, 13 indicators had a fuzzy number higher than 0.7. The developed Kepras technique was utilized for the final prioritization. Through the Kepras technique, three indicators of importance intensity (weight 0.33), degree of certainty (weight 0.33), and expertise of experts (weight 0.33) were analyzed. According to the results, the indicators with the highest priority are business intelligence, information technology infrastructure, transparency, stakeholders, drafting laws in line with performance-oriented budget, and supervision.

For the optimal implementation of performance-based budgeting in the housing sector, business intelligence, information technology infrastructure, transparency, and stakeholder engagement hold special priority.

Attracting talents is one of the most important actions in talent management. The purpose of this research, was to provide a framework for identifying and analyzing the factors affecting the recruitment of talents in startups. The current research is applied in terms of orientation and has a mixed nature from the methodology point of view due to the use of qualitative and quantitative methods. The statistical population of the research was human resources experts in startup companies. The data collection tools in this study were semi-structured interviews in the qualitative phase and questionnaires in the quantitative phase. The present research was conducted in three stages. In the qualitative phase, 13 interviews were conducted with startup experts. The interviews were conducted in a semi-structured manner and the sampling method was snowball. The interviews were analyzed using the theme analysis method and MAXQDA version 2020 software. Seven overarching themes and 33 main themes were obtained. In the second stage, the main themes were screened by distribution of expert questionnaires and fuzzy Delphi method. Eight themes had a higher defuzzy number of 0.7 and were selected for final prioritization. Screened themes were analyzed by distributing priority questionnaires and Marcos method. At this stage, 10 experts participated. Based on the evaluation indicators in the Marcos method, the priority themes were: compensation for financial services, learning work environment, welfare and personal communication. Practical research proposals were presented based on the most important main themes.

Fintech and its entrepreneurial opportunities have the ability to play an effective role in the development of the financial industry. Therefore, it is necessary to make a correct and effective policy in this area to identify its probable future. This study is exploratory in terms of purpose and practical in terms of orientation. Interviews and questionnaires were used to collect data. 28 drivers were extracted by reviewing the background and interviewing experts. In order to screen the propellants, expert questionnaire and fuzzy Delphi method were used. Then the propellants screened were ranked through the priority assessment questionnaire and the developed COPRAS technique. The two drivers of the development of smart contracts in the financial industry and the tendency of financial institutions towards open innovation had the highest priority and were used to write research scenarios. Based on these two drivers, 4 scenarios of the era of pristine opportunities, the era of conservative managers, the era of dilapidated infrastructure and the ice age were developed. Then, using the MABAC technique, the scenario of the age of dilapidated infrastructures was selected as the possible scenario of the research. Research proposals were proposed based on priority drivers and possible scenarios. Government support, providing sufficient funds in order to create the necessary infrastructure for the development of smart contracts by banks or establishing a cooperative relationship between banks and financial institutions, fair legislation, development of regtechs, creating compatibility between current systems with new technologies were the most important practical proposals of the study.

Designing a payment system for healthcare workers- doctors and nurses, in particular- in the hospitals is more intricate than that for other organizations. Beyond the legal compliance, the unique features of the medical professions and nursing work environment should be considered. Due to the lack of adequate researches on payment methods for doctors and nurses in Iran, especially regarding the recent changes in “fee for services” (FFS) payment, the present study aimed to investigate the payment challenges faced by the doctors and nurses in Iranian public hospitals.

Challenges were identified by interviews, and prioritized by adopting the MARCOS method. The study population included the hospital managers, healthcare payment method experts, and doctors and nurses in the public hospitals. Targeted sampling and semi-structured interviews were conducted to collect the data. In the MARCOS method, criteria determination, weighting, and scoring of the challenges were performed by five experts in the field of healthcare payment. Criteria included decreased motivation (25%), reduced productivity (15%), correction cost (40%), and implementation difficulty of the correction (20%). Calculations were performed using Excel software and determining the relevant priorities.

A total of 16 interviews were conducted in this study, with 10 interviews about the academic faculty and hospital managers in Isfahan University of Medical Sciences, three about the nursing experts in Tehran, and three about the Ministry of Health experts. According to MARCOS method calculations, the top 4 challenges in compensating doctors were identified as: low FFS ceiling, lack of job difficulty incentives, the inadequate impact of full-time work, and the progressive taxing. Additionally, the 2 primary challenges in compensating nurses were: irregular payment of FFS, and collective payment of FFS instead of individual payment.

At the time of this study, Iranian public hospitals provided the doctors with individual rights, benefits, and allowances, while it provided the nurses with collective rights, benefits, and overtime pay. Although these compensation methods often posed different challenges, most of the issues were associated with the allowance payments. By prioritizing key challenges, authorities may have developed the necessary solutions for addressing the challenges as well as enhancing the satisfaction of doctors and nurses in Iranian public hospitals.

Tourism is one of the areas that due to cultural and economic effects, has caused many countries to pay attention to the development of infrastructure and promoting its services. Due to its economic, geographical, cultural and historical advantages, Iran can be successful if it develops the necessary infrastructure and makes the right policies in this regard. One of these infrastructures is business intelligence. Business intelligence tools provide users with accurate information about the nature of the business by analyzing data and presenting reports, summaries, dashboards, maps, charts and diagrams. The present study seeks to identify the drivers that affect the future of business intelligence in Iranian tourism. The present study is pragmatic from the point of view of philosophical foundations; It is applied in terms of orientation and exploratory in terms of purpose. To conduct the research, in the first stage, the research drivers were extracted through a systematic review of the literature and interviews with experts. At this stage, 30 drivers were obtained, which were screened by Binominal test. After key drivers screening, 12 factors were eliminated and the remaining 18 drivers were prioritized using the best-worst fuzzy technique. The results showed that the drivers of tourism business environment, data-driven decision-making culture and foreign sanctions and are the most influential drivers on the future of business intelligence in tourism.

Developed within the past decades as a key concept in international and power relations, soft power emphasizes diplomacy, culture, art, and propaganda instead of hard and coercive aspects of power. As soft power affects the international prestige and credit of countries, this applied exploratory study sought to elaborate on the role of soft power and its componential elements in attracting foreign tourists. The theoretical population of the study comprised fifteen experts in soft power and tourism who were selected via convenience sampling. To conduct the study, twenty-seven factors were identified by reviewing the related literature on tourism and soft power. The factors were then screened via the Binomial test, out of which seventeen factors were excluded due to their over 5% significance coefficient. The remaining ten factors were then analyzed using the cross-impact analysis (CIA) technique.The results of the study indicated that successful organization of political, artistic, scientific, sports, and literary events at the international level, the presence of foreign companies in the business environment of Iran, cyberspace and social networks, and improving tolerance among influential reference groups in society contributed the most to attracting tourists to Iran. The study was also replicated using the DEMATEL method, producing very similar results compared to the previous test, and the same four factors were identified as the most influential factors in attracting foreign tourists. It should be noted that the DEMATEL method and cross-impact analysis are based on a critical realism approach, considering the fact that they both enjoy structural analysis.

This research has been done with the aim of developing Iran's banking scenarios with an emphasis on big data. The current research is practical in terms of orientation and exploratory in terms of the goal. It is also mixed in terms of its philosophical, pragmatic and methodological foundations. To carry out the research in the first stage, 20 key drivers of the research were extracted through literature review and interviews with banking and technology experts. After screening with the fuzzy Delphi method, 8 factors were removed and the rest were evaluated with the Marcus decision making technique. The findings of the research show that the two factors of "technology regulation" and "technology transfer costs" were chosen as key uncertainties for developing research scenarios. Based on these two key uncertainties, four scenarios were developed based on interviews with the focus group with the titles of comprehensive banking, static banking, searching banking, wandering banking. In the comprehensive banking scenario, everything is in its optimal state; Technology transfer costs have decreased and regulators are supportive of the technologies. According to the findings of the research, considering drivers, key uncertainties and alternative scenarios by managers and decision makers can improve the performance and increase the competitive advantage of banks.

Financial innovations has been challenged the banking sector and can improve it. They cover a variety of financial businesses such as online lending, asset management platforms, trading management, mobile payment platforms, etc. All these services generate a large amount of data every day (Hasan et al, 2020: 1). Analyzing this volume of data is difficult, giving rise to the concept of "big data" (Munawar et al, 2020: 2). Big data as one of the important fields of future technology has attracted the attention of various industries (Raguseo & Vitari, 2018: 5206). In general, big data refers to a large volume of structured or unstructured data that is generated and stored at a high speed (Dicuonzo et al, 2019: 41). Big data has found its position in the banking industry; Because of the useful data they have stored in recent years (Rakhman et al, 2019: 1632). Recent applications of big data in banking have been for improving customer relationship management, marketing, optimizing strategic management and human resources (Parmar, 2018: 33; Hassani et al, 2018: 2). Therefore, it can be said that nowadays big data plays a major role in providing financial and banking services, and the realization of its potential benefits in banking is more from technical aspects and affects the organizational structure of banking and mobilizes a large number of different actors (Diniz et al, 2018: 151- 152). With changes in customer expectations and increased competition, the banking industry is no longer able to ignore technological innovations in the banking sector. Due to the numerous applications and benefits of big data in various industries, including the banking industry, and it's becoming more widespread in the future, this technology is becoming a prominent research topic (Phan & Tran, 2022: 6.)

What are the plausible scenarios for banking in Iran with an emphasis on big data?

Many studies conducted in the field of banking and big data deal with the role of big data in improving the performance of the banking industry (for instance: Shakya & Smys, 2021; Gonsalves & Jadhav, 2020; Hung et al, 2020; Parmar, 2018). Also, another part of the studies conducted with a future research approach in the banking sector without focusing on innovative financial technologies and specifically big data (for instance: Baumgartner & Peter, 2022; Eskandari et al,2020). The focus on innovative banking and financial technologies with a Futures Studies approach has been weak (for instance: Maja & Letaba, 2022; Murinde et al, 2022; Hajiheydari et al, 2021; Broby, 2021; Harris & Wonglimpiyarat, 2019). And the role of big data in the Futures Studies of the banking industry has been seen to be very limited due to the relatively large amount of data available in banks and its effect on performance and gaining a competitive advantage (for instance: Valero et al, 2020). Therefore, despite the studies conducted in the field of banking and big data, some of these researches have paid attention to the present time, and the researches conducted in the future of the banking industry have also been without focusing on the role of big data. Now, the most important theoretical gap in research is the lack of studies on the future of banking in Iran with an emphasis on big data.

The current research is pragmatism due to the use of qualitative and quantitative methods from the perspective of philosophical foundations. It is also exploratory in terms of purpose due to the identification of drivers and practical in terms of direction due to the application of the results in the analysis of the future of banking in Iran. In the current research, two methods of literature review and interviews with experts are used to identify drivers, both of which are qualitative methods. According to Popper, the interview tool is based on the expert dimension. The literature review is evidence-based and uses articles and scientific texts to identify factors. Fuzzy Delphi, which is semi-quantitative and evidence-based, is used to screen and determine key drivers that require great accuracy. Then, to determine the key uncertainties, the MARCOS technique is used based on the importance and uncertainty indicators of the Global Business Network (GBN) approach, which is a quantitative and evidence-based technique. Finally, interviews with focus groups are used to write the scenario, which is a qualitative method based on the expert dimension. The theoretical community of the research includes academic experts and managers of the banking sector and are aware of new banking and financial technologies (Fintechs) and specifically big data. The selection of the participants is based on their knowledge and nobility of the research topic and the importance of their presence in the research, and finally 15 people were selected by purposeful sampling using the snowball method. Experts have at least 10 years of relevant work experience and a master's degree.

This research has clarified the situation of this area by identifying the shaping factors and drivers of the future of banking in Iran. Two factors of "technology regulation" and "technology transfer costs" were chosen as key uncertainties for developing research scenarios. Based on these two key uncertainties, four scenarios were developed based on interviews with the focus group with the titles of comprehensive banking, static banking, searching banking, wandering banking. In the comprehensive banking scenario, everything is in its optimal state; Technology transfer costs have decreased and regulators are supportive of the technologies. Considering drivers, key uncertainties and alternative scenarios by managers and decision makers can improve the performance and increase the competitive advantage of banks.

The current study seeks to identify drivers and future scenarios of corporate governance in health companies.

The current research is practical in terms of orientation and its methodology is mixed. The theoretical community of the research are active experts in the capital market and corporate governance. The sampling method was done in a judgmental manner according to the expertise. The number of samples was equal to 10 people. The drivers of the research were obtained through literature review and interviews with experts. Screening and prioritization of drivers was done using two questionnaires, expert assessment and prioritization. These questionnaires were analyzed with two methods, fuzzy Delphi and Marcus.

24 drivers were obtained through literature review and 7 drivers were obtained through interviews with experts. Among the drivers of the research, 10 drivers had a diffusion number higher than 0.7 and were selected for the final ranking. The degree of priority of drivers screened with Marcus and considering three indicators of experts' expertise, severity of importance and degree of certainty was determined. The drivers, policies of governments regarding economic corruption and monitoring regulations of the TSE were respectively the most important drivers and were used to formulate research scenarios. To strengthen the research scenarios, the components of the root definition tool were used. The scenarios were: glass room, weak mechanisms, scattered world and dark room.

The practical proposals of the research were presented according to the ideal scenario (glass room). In this context, suggestions such as improving the organizational culture, strengthening the administrative organization, developing decision support systems for ranking health companies and continuously revising the corporate governance rules according to the necessities of business will help to improve corporate governance in the long term.

Before the coronavirus pandemic, higher education centers and companies paid little attention to e-learning. The outbreak of the pandemic and the development of digital technologies have caused companies to pay much attention to e-learning. Therefore, companies are looking for the effective use of e-learning tools. The current research seeks to provide a framework to improve the effectiveness of the e-learning system in Hyper Famili chain stores. The current research is applied in terms of orientation and has a quantitative nature in terms of methodology. This study used two Fuzzy Delphi and Marcos methods for data analysis. The theoretical population of the research was managers, experts, and consultants in the field of education in Hyper Famili. Sampling was done as a judgment based on the expertise of experts in eLearning. The sample size was equal to 10 people. Interviews and questionnaires were used to collect data. The questionnaires used in this research were expert and priority questionnaires. In the first stage, 32 factors were obtained through literature review and interviews with eLearning experts. As a next step, these factors were screened by the distribution of expert questionnaires and the fuzzy Delphi method. Ten factors were selected for final prioritization with Marcos. The screened factors were prioritized by distributing priority questionnaires and Marcos. According to the scores, the most important factors have been found. Practical research proposals were developed based on the most prioritized factors. Some practical suggestions of the research were holding a training workshop on the benefits and applications of e-learning for senior managers, considering the appropriate budget for purchasing and preparing the necessary infrastructure in the field of e-learning, preparing strategic and operational documents based on future developments of new technologies in Iran and the world and the use of instructors with electronic teaching skills.</span>