دکتر محمدتقی تقوی فرد

Regional Electric companies are organizations that pursue both social and financial goals in order to fulfill their assigned missions, so fulfilling accountability for their dual goals is of fundamental importance. In this research, by examining the information needs of the users of the financial reports, the factors affecting the financial reporting of the sector have been studied. The aim of this research is to present a model for the environmental conditions and characteristics of regional electric companies in Iran. For this purpose, the required data, after a library study and exploratory search in the theoretical foundations and financial and accounting rules and regulations governing the relations of these entities, were collected using a questionnaire and analyzed using the fuzzy Delphi research method and appropriate statistical tests. The evidence from the analysis of the respondents’ views shows that the influencing factors are in four dimensions, including the compatibility of the model in achieving the organization's goals, the needs of information users, compliance with financial and accounting laws and regulations, and finally, budget control and credit status reporting. Experts also agree on the factors proposed by this research for designing and explaining the financial reporting model of regional power companies in Iran.

The government and other public sector institutions provide many goods and services essential to society. One of the most significant areas in which the government engages in commercial activities is the energy sector, particularly the electricity industry, which plays a key role in social and economic development and in improving the quality of life in society. The financial resources of the country’s regional electricity companies are derived from various sources and must be utilized for specific purposes in compliance with various laws and regulations. Given the fundamental importance of performance and the evaluation of accountability by authorities to stakeholders in democratic governments, it is necessary to produce clear and reliable reports on how resources are allocated and consumed in different areas. This research seeks to identify the weaknesses and shortcomings of the financial statements of these institutions by reviewing existing literature and employing other methods. Ultimately, the study presents a suitable model for the financial reporting of these institutions, enabling improved accountability and more effective economic decision-making.

What is the financial reporting model of Iran's regional electricity companies?

Sayedi and Babajani (2011) conducted research with the aim of achieving a desirable model of financial reporting in Islamic capital markets. The findings of their research confirmed the usefulness of relying on the fund theory to achieve reporting goals. The result of their study led to a financial reporting model in which the central focus is not the economic entity but rather the main business activities and departments of the company. Babajani and Shekarkhah (2012), using the Delphi method, investigated the appropriate accounting model for Islamic banking in Iran. According to their findings, the accounting system used by experts was unable to meet user needs and required changes, the generalities of which were presented as key factors in the proposed research model. Additionally, the research indicated that a conceptual framework based on accountability is more suitable than one based on decision-usefulness for financial reporting in the usury-free banking system. Mohammadi et al. (2020), in their research to develop a desirable model of financial reporting in the public sector, addressed the key factors influencing public sector financial reporting. The results showed that the quality of public sector financial reporting is influenced by factors such as budgeting structure, public sector infrastructure, the quality of human resources, the accounting system and basis, education, and the accountability system governing society. Weaknesses identified in the research include poor implementation of accrual accounting, incomplete implementation of operational budgeting, political influence in decision-making processes, lack of access to the annual budget performance statement and budget deduction report, and non-identification of certain financial statement items.

The current research is an applied and developmental study. It aims to analyze existing conditions and assist in the decision-making process, classifying it as descriptive research. Furthermore, since it seeks to gather the opinions of a large statistical community on the research subject, it is categorized as descriptive-survey research.
Using the fuzzy Delphi method, the statistical population includes experts selected based on three criteria: the presence of representatives from expert groups, deep knowledge of the research topic, and breadth of opinion and expertise. These experts were chosen from groups such as auditors, the head of the State Court of Audit, auditors of executive bodies, directors of audit organizations, and academic faculty members with relevant experience. Participants were selected through snowball sampling. Initially, to identify the dimensions, components, and indicators of the Financial Reporting Model for Regional Electric Companies in Iran, a review of the subject literature was conducted. After identification, examples of these cases in the public sector were examined based on expert opinions. Given the advantages of the fuzzy Delphi method (29FDM) compared to the traditional Delphi method (30TDM), the fuzzy Delphi method was employed in this research.

By examining the needs of users and the current state of financial reporting for regional electric companies, which is affected by several factors, it was found that the financial reporting models of private sector for-profit institutions cannot fully address the information needs of users in this sector. The findings of this research revealed that the operating environment and user needs in this sector differ significantly from those of private-sector for-profit institutions. These differences have created challenges in aligning the information needs of users with the form and content of the current financial reports, leaving report users facing difficulties.
In this research, by identifying and analyzing the factors influencing an appropriate financial reporting model for Iran's regional electric companies, a step has been taken to better meet the information needs of users. Identifying the set of influencing factors for the proposed model, in accordance with the conditions and laws governing the financial and accounting systems of this sector, and determining the importance of each factor in the desired framework are among the key findings of this research effort.

According to the findings of the research, the consistency of the model in reporting the degree of achievement of the set goals of regional electric companies, the consistency in supporting the goals of information users, its compliance with financial and accounting rules and regulations, as well as budget control and credit status reporting, were identified as the effective dimensions of the reporting model. Each of these dimensions comprises several components and indicators.

This research aimed to present a financial reporting model for Regional Electric Companies in Iran. Using the fuzzy Delphi method and based on expert opinions, the dimensions, components, and indicators of the proposed model were identified and presented.

Most research in the field of designing and planning bioethanol supply chains has been based on deterministic models, which do not consider dynamic environmental conditions and thus do not provide reliable outputs. Classic robust models did not have this weakness, but due to their excessive conservatism, they increased supply chain costs, making them unattractive to investors. Therefore, the aim of this study is to design and optimize the biomass-to-bioethanol supply chain network using data-driven robust optimization methods and disjunctive uncertainty sets.

The methodology of this study is a multi-methodology approach based on mathematical modeling and machine learning algorithms. Initially, uncertainty sets for the non-deterministic model parameter were created using K-means and SVC methods. Then, a data-driven optimization model was designed to optimize the biomass-to-bioethanol supply chain network, addressing the issues of previous classic approaches.

The findings of this study are presented in two categories: strategic and operational decisions. The strategic section focuses on determining the optimal locations for biomass cultivation, preprocessing centers, and refineries. In the operational section, the optimal amounts of biomass sent to preprocessing centers and refineries were determined.

This study, by producing robust solutions without the conservatism of traditional robust optimization approaches, can significantly attract public and private sector investors. Additionally, using a three-objective model based on a sustainable development approach that simultaneously considers economic, social, and environmental components, enhances the comprehensiveness of this research, providing more realistic and detailed results.

In this research, a multi-product and multi-period closed-loop supply chain design problem with three objectives of profitability, social responsibility, and reliability under uncertain conditions has been considered.

Triangular fuzzy numbers have been used for non-deterministic parameters, and a robust probabilistic programming approach with the Me scale has been used to deal with fuzzy constraints. The proposed approach eliminates the need for iterative consideration by decision-makers by providing unlimited choices from the optimism-pessimism spectrum. The mathematical model developed in this research is of mixed integer linear programming type, which is implemented in GAMS software to solve it and find Pareto optimal solutions.

The accuracy of the overall performance of the proposed model has been evaluated with four examples (based on the coefficients of the objective functions) from a case study in the aluminium industry. The sensitivity analysis of the demand parameter showed that the proposed model achieved more economic profit, less social responsibility, and less reliability with increasing demand.

The variability of the justified decision space in the Me criterion has helped to solve the supply chain network design problem more flexibly and closer to reality through the possibility of exchange between the objective function and the risk-taking level of the managers.

This research seeks to provide a model for explaining the dimensions of customer sentiment management of asset management services, including investment funds and portfolio-managed accounts, using meta-synthesis application. By reviewing and screening 254 papers written between 2002-2022, coding was done by studying 49 studies. Finally, the components were classified with 32 final codes as basic themes and 5 codes as organizing themes. The reliability and validity of the model were calculated by a Kappa coefficient equal to 0.78, which is at the level of excellent agreement. Since this study uses the meta-synthesis method, its innovation is a method that examines all national and international studies in this field and identifies the dimensions of the subject completely and comprehensively for the readers. According to the results, the components of customer sentiment management dimensions of asset management services were categorized with five themes including the importance of sentiment management, influencing factors on customer sentiments, sentiment characteristics, sentiment management practices, and results of sentiment management. The results can be used by managers of asset management institutions in designing strategies for managing customers' sentiments.

Crowdfunding is an effective way to achieve the non-profit goals of the charities which can be expanded using information and communication technology. In this regard, this study was conducted with the aim of providing an online donation intention model for collective financing of charitable institutions in Iran. The current research is an applied-developmental research in terms of its purpose, and it is considered a cross-sectional survey research from the data collection point of view. The statistical population in the qualitative section includes managers of charity institutions and university professors. Sampling was done using a purposeful method and theoretical saturation with 10 interviews. In the quantitative section, the views of 357 benefactors were used. The data collection tool is a semi-structured interview and a researcher-made questionnaire. To analyze the collected data, qualitative thematic analysis and partial least squares were used. The research findings showed that the technical infrastructure facilitating conditions, the quality and transparency of the website information, the security of the site and the application, and the preservation of privacy affect the perceived risk. Perceived risk affects the expectation of effort and the pleasure of helping others and leads to the expectation of performance and social influence. Finally, online donation intention is strengthened through trust.

The main objective of this research is to study the relationship between corporate default and key investment strategies in the Iranian stock market. These strategies are value strategies and continuation of past performance (momentum). The concept of market anomalies, including value, size, and momentum premium, has been studied mainly in the stock exchange of the United States or other countries. Research focusing exclusively on the Tehran Stock Exchange is limited and related to the past years. Considering Iran's influential role in the region's economy and its damage from the recent global crises, it will be important to answer whether there are abnormal returns resulting from value premium, size premium and continuation of past returns on the Tehran Stock Exchange. Another goal of this research is to establish and investigate the theoretical relationship between corporate default and investment strategies.

In this research, using four corporate default indicators, including the probability of default calculated by Campbell, Hilscher and Szilagyi (2008) (named as CHS score), the criterion based on Merton model (1974) (named as M score), Altman's Z score (1968) and Ohlson's O score (1980), the role of this factor in pricing capital assets, as well in explaining the profitability of investment strategies known as value premium, size premium and momentum premium, is investigated and analyzed. In this way, a total of 10 models are used and tested: (1) Fama-French three-factor model (1993), (2) Carhart four-factor model (1997), (3) augmented Fama-French model including CHS score, (4) augmented Carhart model including CHS score, (5) augmented Fama-French model including Z score, (6) augmented Carhart model including Z score, (7) augmented Fama-French model including O score, (8) augmented Carhart model including O score, (9) augmented Fama-French model including M score, and (10) augmented Carhart model including M score. This research uses data from 168 companies listed on the Tehran Stock Exchange and Iran Over the Counter Market over 114 months.

According to this research, including the corporate default factor in the Fama-French three-factor model (1993) and Carhart four-factor model (1997) improves the performance of these models in pricing stocks. In the meantime, the indicator of the probability of default calculated by Campbell, Hilscher and Szilagyi (2008) has the greatest contribution to increasing the explanatory power of the mentioned models. After that, Ohlson's O score (1980) and Altman's Z score (1968) are ranked second and third, and the measure based on Merton's model (1974) stands at the last place. Additionally, it is found that value premium, while indifferent to the presence or absence of the corporate default factor in asset pricing models, is mainly seen among small and big value stocks. After augmenting these models with the corporate default factor, the significance of the size effect disappears among big value stocks. However, this variable still maintains its influence in explaining the fluctuations of returns of three other stock portfolios, including small value stocks, small growth stocks and big growth stocks. In addition, the findings show that the excess returns of none of the stock portfolios contain momentum premiums. More importantly, the research results suggest that the probability of corporate default and the excess returns of stock portfolios are significantly negatively correlated.

According to the results, the first hypothesis of the research, “the corporate default factor explains the stock returns of firms listed on the Tehran Stock Exchange and Iran Fara Bourse,” is confirmed. The second hypothesis of the research, based on which “including the corporate default factor improves the performance of Fama-French three-factor model (1993) and Carhart four-factor model (1997) in the pricing of capital assets”, is also confirmed. The third hypothesis of the research, according to which “the corporate default factor changes the effect of risk factors related to size, book value to market value and momentum in Fama-French three-factor model (1993) and Carhart four-factor model (1997)”, is confirmed about size and value effects. Still, there is no evidence that with the inclusion of the corporate default factor in Carhart's four-factor model (1997), the impact of the momentum variable on the excess returns of stock portfolios will increase or decrease. The fourth research hypothesis, that “market-based corporate default criteria have more power in explaining the profitability of value premium, size premium, and momentum premium, compared to the criteria based on accounting data”, is not fully confirmed or rejected. According to the above findings, the effects of value, size, and momentum are not compensation for corporate default risk. It is suggested that individual and institutional investors in the stock market pay attention to the financial health of the firm, its size, and its book to market ratio, respectively, instead of focusing on the past performance of its stocks.

Today, one of the most important challenges of non-governmental organizations is financing. Due to the lack of government funding, these organizations use public assistance to continue their activities and realize their charitable goals and visions. With the increasing use of online donation platforms in the world, non-governmental organizations in Iran have not yet been able to use this opportunity to solve their financial challenges. This is an important issue that needs to be investigated and researched. The purpose of this article is to provide a model to explain the factors affecting the willingness to donate online in line with the collective financing of non-governmental organizations, which has been carried out using a Meta-synthesis method. In this regard, using the experiences of financial managers and charity experts and previous research, the collected information was coded using the content analysis method. The components were categorized with 55 descriptive open codes, 36 basic themes and 12 organizing themes, then the reliability and validity of the model was checked and then it was presented in the form of the final model. The results showed that these components are directly and indirectly effective in online donation in line with collective financing of non-governmental organizations. These components clearly state that providing transparent and timely financial information and effective activities of non-governmental organizations, emotional and social support for people, ease of use, privacy protection, trust and the principle of the plan and project is the right way. which can make the financing of non-governmental organizations successful.

Customers now care more than ever about the sustainability and reliability of products packaging. This research considers a multi-product and multi-period closed-loop supply chain design problem with three objectives of profitability, social responsibility, and reliability under uncertain conditions. Triangular fuzzy numbers have been used for non-deterministic parameters and a robust probabilistic programming approach with Me scale has been used to deal with fuzzy constraints. The proposed approach eliminates the need for iterative consideration by decision-makers by providing unlimited choices from the optimism-pessimism spectrum. The mathematical model developed in this study is of mixed integer linear programming type, which is implemented Augmented Epsilon Constraint (AEC) method in GAMS software to solve it and find Pareto optimal solutions. The accuracy of the overall performance of the proposed model has been evaluated with four examples (based on the coefficients of the objective functions) from a case study in the Carton-Making Industry. The obtained results indicate the existence of a conflict between the three objective functions. With this account, decision-makers should demand lower profits for increased environmental protection and improved reliability compared to the situation where only the economic aspect is considered. The variability of the justified decision space in the Me criterion has helped to solve the supply chain network design problem more flexibly and closer to reality through the possibility of exchange between the objective function and the risk-taking level of the managers.

Nowadays renewable energy sources, such as wind and solar, whether independently or integrated with other resources, are considered in power system, specifically self-scheduling, bidding and offering strategy problems. However, the uncertain nature of these sources has turned out the greatest challenge for their owners, which makes the bidding and offering in the restructured electricity market more complicated because wind energy generation may cause penalty fees for its generation mismatches. Hence, the primary objective of this paper is to suggest a novel bidding strategy framework based on fuzzy random variable for a wind-thermal system in the electricity market for the first time. The uncertainties associated with day ahead energy, spinning reserve market prices and imbalance prices, are characterized by random fuzzy variables and the uncertainties associated with wind power outputs are modeled as a LR fuzzy numbers. The proposed self-scheduling model maximizes the expected profits while it controls the risk by providing different possibility and probability levels for decision makers.A mathematical modeling approach is applied in this research by using a mixed-integer non-linear programming model which is implemented in Lingo software in a case study of thermal generation unit to investigate the efficiency of the proposed model. A sensitivity analysis is applied to validate the performance of the proposed model. Numerical results reveal that taking advantage of wind power generation alongside with thermal generation will substantially increase the profitability of the integrated generation company.

Subject and Purpose of the Article:

 Regional electricity companies are organizations that pursue both social goals and financial goals in order to fulfill the assigned missions, so fulfilling and evaluating the responsibility of accountability due to their dual goals is of fundamental importance. In this research, the weaknesses and inadequacies of the financial statements have been studied by examining the information needs of the users of the financial reports of these companies.

The data has been collected after library study and exploratory search in the theoretical foundations and financial and auditing laws and regulations of these companies and using questionnaires and has been analyzed using appropriate statistical.

The evidence from the analysis of the views of the respondents shows that the information provided in the financial statements is not sufficient for the purpose of fulfilling and evaluating the responsibility of accountability, which is a priority, and there is a significant gap between the current situation and the desired situation. The findings indicate that in addition to financial information regarding the organization as a whole, users also need information regarding the financial status, financial and budget performance of each organization's goals.

Conclusion, Originality and its Contribution to the Knowledge: 

According to the findings of the research, the users use the financial statements of regional electricity companies with the aim of evaluating the responsibility of accountability, it is necessary to design and implement a suitable reporting model to improve accountability.

Evaluation of service quality is one of the main concerns of government and non-government service providers. With the advancement of mobile technologies and the provision of government services to citizens in the framework of mobile government, the evaluation of the quality of this type of service has already received the attention of governments and researchers in the field of mobile government service quality. In this research, thematic analysis method and interpretive structural modeling (ISM) technique have been used. By analyzing the theme of the identified factors and themes and using the interpretive structural modeling method, the factors have been identified and classified among these factors.The method of theme analysis and interpretive structural modeling is based on the opinion of experts. The experts in this research consist of 14 expert professors, researchers and executives in the field of mobile government. The results of the research show that evaluating the quality of mobile government services at the first level, satisfying citizens at the second level, educating citizens and building trust in mobile government services at the third level, designing aapplication at the fourth level, data security and the culture of mobile government services at the fifth level, organizational policy, Web3 capabilities, and software and hardware infrastructure are at level six.

The present study aimed to develop a model for determining an optimal bidding strategy for electricity producers, including the recommended selling price and the amount of electricity to be offered for participation in both the competitive electricity market and the energy exchange market. Hourly bids are suggested for the electricity market, while a monthly package, comprising peak load, medium load, low load, and base load, is proposed for the exchange market. By modeling a self-scheduling problem, the study aimed to develop optimal power production plans that maximize net profit over a one-month period. The research approach involved mathematical modeling using mixed-integer non-linear programming, which was performed in Lingo software and then validated in terms of effectiveness through an application to the case of a thermal power station. Relying on fuzzy necessity, credibility, and possibility, the research presented a robust model against the uncertainty of price with an adjustable level of robustness. Sensitivity analysis and the simulation approach were used to validate the performance of the model, demonstrating that the optimal response from the robust model, compared to the deterministic model, can maintain its efficiency in the face of fluctuations in the parameter of price uncertainty. Furthermore, the findings indicated that offering a base load package on the energy exchange market can yield a higher net profit value for the producer. Finally, the fuzzy interest rate and decision-making based on fuzzy goals were also examined.

The current research has considered the design of the four-level supply chain of perishable goods, including manufacturing factories, distribution centers, wholesalers, and retailers, in conditions of uncertainty in important parameters. The aim is to make strategic and tactical decisions, including the location, number, and size of distribution centers and wholesalers, stock levels in stocking centers, determining the flow of goods between facilities at different supply chain levels, and choosing the type of means of transporting goods between facilities. This is achieved through a three-objective mathematical model. The goals include minimizing the expected total cost in the supply chain, achieving the shortest travel time of goods in the chain, and at the same time minimizing the amount of deviation from customer demand. The presented model tries to pay attention to environmental uncertainty and consider different operational scenarios, as well as the possible approach in important parameters. This takes into account the product life cycle, the different rate of spoilage of the goods in different storage facilities, the different capacity of the facilities in different scenarios, and considering different methods of product transportation with different rates of product spoilage. All of this aims to cover the lack of previous research in the field of perishable goods supply chain design. Considering the multi-objective nature of the model and the need to create flexibility in decision-making for decision-makers, this research uses Normal Boundary Intersection (NBI), which allows decision-makers to choose the most optimal solution according to the importance of different goals. GAMS 24 software and MILP solver were used to solve the mathematical model.

Today, many fields of research and business deal with the thoughts, images and mental patterns of their users and audiences. Knowing and being aware of the way of thinking of people, customers and audiences of a collection has a great impact on making appropriate decisions by the managers of that collection, in order to advance the goals and solve various problems. One of the important requirements of managers in any collection is to have sufficient knowledge of how they think about the collection and its performance. This helps them guide the group properly and make appropriate decisions in the way of advancing its goals. Therefore, collecting data from customers should be done with measured and accurate methods to achieve high quality information and obtain valid results. This research, by raising the question of "how can you use the analysis of people's feelings to find out how they think about a certain issue?", tries to provide a new approach on the platform of the Twitter social network to obtain reliable and high-quality information from people in relation to a certain topic. The purpose of the current research is to provide a new approach to collect data from people, in order to measure their perception about a specific issue. It will also examine the impact of the presented method on the speed, quality and cost of collecting data from people using a case study approach.

In this research, their comments on the social network Twitter were used to check the satisfaction of users of three internet taxi applications in Iran, namely Snap, Tapsi, and Carpino. The data collection approach used in this research was descriptive, with results used by users, managers, and researchers. The research population consisted of all users of the three applications and members of the Twitter social network who had published their thoughts about these applications. The research collected and analyzed a total of 682 relevant tweets cross-sectionally during the summer of 1400 using the Twitter application interface and related hashtags. The analysis steps included data collection, pre-processing of tweets - including linguistic, sentiment, and thematic analysis, followed by sentiment analysis.Discussion and

The comparison of the analysis results from this research to the face-to-face interview method showed that the participation of respondents was challenging, and the traditional field method came with its own disadvantages. However, this method is able to overcome those issues and provide reliable results at a lower cost and time. Moreover, the results obtained from analyzing the data collected were similar to the results obtained through the face-to-face interview method, which speaks to the accuracy and quality of the data. Overall, the proposed method can provide valuable insights into people's thoughts and opinions on a particular topic, at a lower cost and time.

The proposed method can be widely applicable to various fields, including business, research, and even everyday life. Managers, researchers, and business owners can use it to collect data and insights from their target audience, which can be analyzed to make informed decisions. Further development of the method can lead to even more useful and accurate reports, helping individuals and businesses stay ahead of their competitors. All students and researchers dealing with data collection can use this method to conduct their studies more effectively. Additionally, market research companies can use it to gain valuable feedback from consumers, informing their next steps in providing products and services.Overall, the applications of this research are far-reaching, and it provides a valuable resource for individuals and organizations looking to better understand their audience.Keywords: Sentiment analysis, text mining, how people think, Twitter, Internet taxi.

The purpose of this research is to design and plan the production and distribution supply chain in an integrated manner.

By using the bi-level programing approach, it is possible to maintain the integrity of decision-making while managing the conflict between the goals and interests of the decision-makers. In the proposed model, supply chain design decisions are considered at the leader level and production and distribution planning decisions are jointly considered at the follower level. At the leader level, the three goals of minimizing the costs of the entire supply chain, maximizing reliability and minimizing adverse environmental effects, and at the follower level, minimizing production costs and minimizing distribution costs are pursued. Therefore, the proposed bi-level programing model is multi-objective and multi-follower. To calculate the credibility of SCOR12 model parameters, hierarchical data analysis technique and fault tree analysis were used. The carbon dioxide emission factor was used to measure the adverse environmental effects. Finally, meta-heuristic technique has been used to solve the proposed model.

The findings indicate that due to the high accuracy of the MOEA/D algorithm, the findings of this algorithm can be trusted for the supply chain problem.

This research is considered a new approach in terms of leveling the problem and choosing the problem of leader and follower. If the decisions related to the design and planning of the supply chain are made with the cooperation of the supply chain links and in an integrated manner, the probability of achieving more favorable results increases

Over the past few decades, the mobile government has attracted a lot of attention around the world. The governments are seeking quality services to citizens to achieve the desired level of satisfaction. Therefore, in order to provide better services, it is necessary to study of the quality of mobile government services and ultimately explain the factors affecting the quality of its services. The present study is a type of qualitative research in terms of purpose, applied, and in terms of data collection.In this study, the method of meta synthesis and the approach of Barrosu and Sandeluski was used to investigate the research literature. Data collection tools are open coding to identify themes and components Drivers of of mobile government service quality. The validity of the analysis was assessed using the kappa coefficient, which was equal to 0.771 In this study, 39codes were identified as basic themes to identify the quality of service quality components. Of these, 21codes were selected as Sub themes and 7were identified and formed as Main themes:Quality orientation, meritocracy, personal privacy, commitment, infrastructural measures, pragmatism, efficient management.

Attention to things such as; The method of selection and special choice of judges, their special position and dignity compared to other professions, the significant impact on the creation of judicial procedure and legal doctrine ,.. ; and the existence of problems such as; Procrastination of proceedings, high volume of cases, lack of knowledge of some judges, ... in the judicial system, on the other hand, shows the need for judicial authorities to pay attention to the issue of judges' compensation system as one of the serious concerns of this authority.Based on this, the current research was conducted with the aim of developing a model of the compensation system for judges and validating it. The research design is qualitative and research in terms of practical purpose and in terms of how to collect information is a case study type. The participants included 15 experts and experienced judges of the judiciary with excellent resumes. The data was analyzed and coded with the help of MAXQDAv2020 software and by thematic analysis method, and to validate the research model, the acceptability indicators of Strauss and Corbin; The technique of visiting by members and the approach of self-review by the researcher have been used. The findings of the research show that the pattern of compensation for judges' services includes 2 overarching themes entitled compensation for financial services and compensation for non-financial services and 6 dimensions; Legal benefits, organizational benefits, rewards based on performance, development and learning, job relationships, environment and job and organizational conditions.

The establishment of justice in a country is primarily dependent on the health of the judiciary, and this directly depends on the health of its judges. In this regard, respecting the dignity of judges in the framework of a comprehensive service compensation system for the judicial system of the country is absolutely necessary and inevitable; Because it seems that the development of the compensation system policy for judges in the process of recruitment and employment, training and improvement, motivation and retention in line with the set strategic goals, is still one of the missing links. Based on this, the current research was conducted with the aim of developing a model of the compensation system for judges based on the requirements of training and improvement of human capital and its validation. The research design is qualitative and research in terms of practical purpose and in terms of how to collect information is a case study type. The participants included 15 experts and experienced judges of the judiciary with excellent resumes. Sampling was done with a purposeful snowball method and they were interviewed in a semi-structured way, The technique of visiting by members and the approach of self-review by the researcher have been used. The findings of the research showed that the most important dimensions of the compensation model for judges based on the requirements of training and human capital improvement are person-related motivators, performance-related motivators, job-related motivators, scientific motivators, and basic motivators.

Creating an information security culture helps to minimize threats, especially threats caused by humans, in order to protect information, and as a result, it leads to the reduction of data breaches or incidents in organizations. No study has been conducted to identify the components of information security culture in the country so far. Information security culture has been investigated and analyzed using different approaches and based on different theories. The purpose of this article is to review the existing researches in the field of information security culture in order to investigate the knowledge resulted and identify the dimensions and components of the information security culture and integrate the literature in this field.
In order to carry out this systematic review, all the studies conducted in the field of information security culture were extracted from reliable databases using relevant keywords. Finally, 310 related articles from 2000 to 2022 were reviewed. Based on the results of this study and according to the purpose of the research, the components and dimensions of information security culture with different approaches and perspectives were identified and compiled.
The research findings indicate that there is no widely accepted set of dimensions and components. Different researchers have considered different dimensions and components for the information security culture. They have used 3 theories and concepts in their studies. The frequency of theories used in different researches was determined and the most commonly used one is Schein’s organizational culture model. Also the mentioned researches have been carried out in various organizations and industries. There is no industry-specific model or framework provided. Also, most of the proposed models or frameworks are descriptive and have not been evaluated, and in terms of geographical division, the researches were also examined and it was found that most of the researches belong to developing countries

The continuity of any business depends on responding to customers' ever-changing needs. Production of innovative products is an effective way to meet this need. Design is one of the main tools for companies to achieve innovation. Designing a sustainable and reliable supply chain as an innovative strategy can gain customer satisfaction and ensure the company's survival. In this regard, the agenda of the present research is the descriptive analysis and content analysis of supply chain network design models, which considered sustainability and reliability in an integrated manner. This literature review includes 65 articles published in Web of Science and Scopus databases from 2011 to August 2022. The research result showed that the integration of sustainability and reliability in the supply chain network design is vibrant and rapidly growing in various industries. Developing countries and the energy industry with the most significant number of articles have been the research fields of the studies. Most of the studies have considered the structure of the supply chain as a forward flow. Mixed integer linear programming (MILP) is the most widely used modeling approach supported by heuristic and meta-heuristic algorithms. The results of the present review can be used as a guide by planners and policymakers to formulate strategies and policies to advance the sustainable-reliable program effectively.

 In this article, the role of letter repetition as a paralinguistic feature is studied in social media in order to help companies select the most repeated letters in words for devising brand names and the most effective sentences in marketing and advertising. The role of letter repetition as a paralinguistic element in advertising with the focus of the effect of this factor on the audience has not been studied in the Persian language. For this purpose, in order to find the frequency of the repeated letters, Instagram and Telegram social media were selected for data mining and five most repeated letters recognized. For the validation of the data at this phase, a questionnaire was devised and distributed among the students at the universities in Tehran and their families. In this way, the hypotheses regarding the most repeated letters and their use in advertising were also tested. Moreover, the quality of the words with letter repetition as being pronounceable was also studied and the use of four letters in case of being beautifully pronounceable was verified for the use in advertising and brand names.