مدیریت بهره وری

The aim of this research was to improve the productivity of resources and present the optimal combination of revenues and expenses in higher education, focusing on Islamic Azad University, in order to achieve financial sustainability. Revenue diversity is an important factor in achieving the financial sustainability of higher education around the world, and in recent years, Islamic Azad University has been able to achieve financial sustainability at different levels by optimal management of resources in order to diversify revenues. Achieving financial sustainability through diversification requires identifying the optimal mix of revenue types. Also, due to the necessity of covering expenses for the productivity and survival of the organization and the nature of the types of expenses, the combination of expenses is also important. This research, with a problem-solving approach, based on portfolio theory and nonlinear planning modeling, has presented the optimal weight of types of revenues and expenses of university branches and compared the current situation with the optimal point. The data was extracted from the database of Islamic Azad University. The university branches were classified into six groups according to experts' opinions and the optimal weight of revenue and expenses for each group was evaluated. The comparison of the current situation with the optimal model showed that the branches of Groups 1, 2 and 6 need planning to increase the share of non-tuition revenues. The branches in Group 3 should plan to increase the share of non-tuition revenue and decrease the share of salary expenses. The branches of Group 5 need to increase the share of non-tuition revenue and reduce the share of other expenses, and in the branches of Group 4, the combination of revenues is optimal, however, other expenses must be reduced. Key Words: financial sustainability, higher education, portfolio optimization, resources productivity, revenue diversification 1.Introduction Financial sustainability is one of the main challenges facing higher education institutions worldwide, as insufficient sustainability can lead to a decline in their ability to carry out the activities needed to achieve their goals. Higher education institutions are committed to identifying revenue-generating potential and reducing their dependence on budgets and limited resources by diversifying their revenue structure. In our country, Islamic Azad University, as the largest in-person university in the world and with a forty percent share in the country's higher education, has been offering flexible educational, research, and knowledge-based product programs, which have made a significant contribution to achieving the country's higher education goals. In recent years, due to severe fluctuations in revenue due to various factors, the administrators of Islamic Azad University, in addition to paying attention to fulfilling the duties of higher education systems, sought to create various sources of revenue in order to improve resource efficiency and achieve financial sustainability, and as a result, an appropriate revenue structure became important. The structure of revenue refers to the type, composition, and share of each source of revenue. In the present study, first, based on portfolio theory, the optimal weight of various types of revenue and expenses in the revenue and expense portfolio of different university branches was calculated, and then the current status of the university was evaluated in comparison with the desired point in different categories of university branches. Literature Review Developed countries consider financial sustainability to be an important part of university sustainability, the absence of which threatens the ability of higher education institutions to perform their duties effectively and respond to changes in the surrounding environment. Financial sustainability is one of the most important, yet, intractable issues for nonprofit organizations. At the same time, these organizations must continue their activities and reduce risks by combining various sources of revenue (Baba et al., 2014, p. 2). Researchers and practitioners use portfolio theory to reflect the concept of diversification and incorporate more detailed information from revenue sources to account for revenue diversification. Portfolio theory can provide important guidance for nonprofit managers to assess the current revenue mix and plan for necessary changes in the long term. The findings of Fitriyani' s (2021) research, show that the Markowitz Method is accurate in determining the optimal portfolio. The formation of a revenue portfolio is done by solving an optimization problem, or in other words, by maximizing portfolio returns or minimizing portfolio risks. Methodology The present study was applied in terms of purpose and adopted a problem-solving approach. Regarding its nature and methodology, the portfolio optimization section aimed to identify and present optimal weighting patterns for each type of revenue and expense in the university's revenue and expense portfolio, based on nonlinear programming and optimization mathematical models. Then, in order to compare the current situation with the optimal point in different categories of university branches, statistical inference and the test of comparing the mean with a fixed number were used. The statistical population included revenue and expense data of all Islamic Azad University branches, which were processed during the 4-year period of 2019-2022. In the portfolio optimization section, through risk and return optimization and considering revenue and expenses, weight and return data related to revenue and expenses of university branches in six groups was used. Considering different conditions and characteristics, university branches were first classified into six groups and each group was analyzed as a separate portfolio for optimization. In each group, revenue was defined in two types, tuition revenue (T) and non-tuition revenue (NT), and expenses were defined in two types, salaries and wages (P) and other expenses (O). Then, with the objective of optimization by simultaneously considering both risk and return criteria, where risk is expected to be minimized and return maintained within the defined range, the optimal weight of each type of revenue and expense was estimated for each group. 4. Result Based on the results of the data analysis in the optimization section, except for the expenses of Group 6, the software did not extract an appropriate answer regarding the expenses based on modeling and model limitations, despite various possible adjustments; other optimal revenue and expense weights were obtained. The results showed that tuition revenues and salary and wage expenses account for a significant share and weight of the total revenue and expenses of university branches, and that the combination of revenue and expenses obtained in each group is logical. According to the results of the second stage, namely the assessment of the current situation with the optimal point, the average weight of tuition revenue in Groups 1, 2, 3, 5, and 6 was higher than the optimal weight, and the average weight of non-tuition revenue was lower than the optimal weight in these groups. Only in Group 4, the optimal weight of revenue types did not differ significantly from the current situation, which does not confirm the first hypothesis. According to the results, the weight of unit expenses in Groups 1 and 2 did not differ significantly from the optimal situation, and the second research hypothesis was not confirmed for these groups. In Group 6, for which the optimal weight of expenses was not estimated, it was not testable. The average weight of salary and wage expenses in Groups 3 and 5 was higher and lower than the optimal weight, respectively, and the average weight of other expenses was lower and higher than the optimal weight in these groups, respectively. Group 4 expenses show that the average weight of Group 4 salary and wage expenses is also lower than the optimal weight, and the average weight of other expenses is higher than the optimal weight in this group. Discussion As revealed by the portfolio analyses results, to achieve financial sustainability in university branches, managers and decision-makers should consider the organizational ranking of the branches and the specific group among the six categories to which they belong. In planning and budgeting revenue and expenses, they should pay attention to the optimal weight of each type of revenue and expense. From an operational perspective, they should also plan, develop, and use resources and facilities in order to achieve budgetary goals. In planning and budgeting to create and increase non-tuition revenues , university branches should always consider the optimal combination by identifying the capacity and potentials of their respective branches for generating or expanding non-tuition revenues based on knowledge and services or productivity-based revenues, such as the existing capacities of buildings and land, economic capacities and non-knowledge-based companies, as well as the potential of organizational and public donations and endowment funds. Also, when planning and budgeting salaries and wages and other expenses, they should consider the optimal weight of expenses. In cases where there is a need to reduce the share of other expenses, identifying and reducing or eliminating non-value-added costa, or adopting approaches such as digitalization and system outsourcing can be highly effective. On the other hand, identifying and eliminating revenue sources that generate additional expenses that cannot cover expenses can also be effective in this regard. In cases where there is a need to reduce the share of salary and wage expenses, managers should proceed with caution, as reducing such costs is often difficult due to their structural nature, as well as challenges arising from inflation and concerns related to employee satisfaction. Therefore, managers can maintain employee satisfaction and loyalty by adopting non-financial compensation strategies or alternatives that impose a lower financial burden. Declaration of interest: none

The first step toward increasing productivity and efficiency is the evaluation and planning to improve the performance of industrial units. Productivity is a broad concept including efficiency, and its growth leads to improved living standards for society. Therefore, enhancing productivity is considered one of the primary concerns of economic and political authorities. The present article is the first study, to the best of the authors’ knowledge, to examine productivity in the chemical production industry. This research investigates the total factor productivity of the chemical industry, including eight subsectors of chemical production classified under ISIC code 20, using Data Envelopment Analysis (DEA) and the Malmquist Productivity Index over the period 1381-1397. DEA was employed under the assumptions of constant and variable returns to scale. The results indicate that the lowest level of efficiency with a score of 0.082 belonged to the sub-code 2022 while the highest negative growth was observed for the sub-code 2030 during the study period. Key Words: total factor productivity, chemical production industry, Malmquist Index, Data Envelopment Analysis 1.Introduction The scarcity of productive resources is considered a fundamental reason for the emergence of economics as a discipline. In fact, according to this principle, goods and services are insufficient to satisfy all the needs of human society. As production increases, a larger share of these needs can be met. Since production depends on the availability of factors of production, increasing production can be achieved in two ways: by increasing the factors of production or by making optimal use of existing resources. Due to limited resources, today, increasing production is mostly done through the optimal combination of production factors. Therefore, increasing productivity as a source of economic growth has become more important than ever before. The economic development of developing countries depends on improving efficiency and productivity in various economic sectors. Furthermore, efficiency and productivity provide countries with a competitive advantage in the global market, making them highly significant in economic policy. As it was mentioned, limitation and scarcity of resources is the most important reason for the emergence of economics. Given these limitations, goods and services do not meet all the needs of human society. Therefore, more goods and services must be produced and supplied to cover more needs. As highlighted above, increasing production is possible in two ways; one is by increasing production resources and the other is by making optimal use of existing resources and facilities through employing newer methods and adopting more appropriate management policies. Human economic efforts have always focused on achieving maximum production with minimal resources. Such a desire to achieve a better result is called efficiency and productivity. Productivity, as a comprehensive concept, includes efficiency, the increase of which improves individuals’ living standards, and has always been the focus of political and economic officials. One of the key determinants of a country’s economic growth is the expansion and development of its industry sector. The industrial sector accounts for a large share of national development and is known as the economic driving force of the country. A comparative analysis of the trends of developing and advanced industrial countries shows that developed countries, instead of increasing production resources, make the best use of existing resources and facilities. This optimal use of resources leads to faster economic growth in these countries. In contrast, developing countries often try to increase production by expanding production resources, but this strategy has not been as successful as in advanced industrialized countries. Following food industry and automotive industry, the chemical materials and products industry is the third largest industry in the world. In Iran’s economy, which is the world's fourth largest oil producer and has the world's third largest gas reserves, chemical products have an important role on the growth of the country's non-oil exports. A study of countries that have a high share of production and exports in this industry shows that they have always been trying to increase production productivity in various ways. From an economic perspective, efficiency and productivity are among the most desirable criteria with which the current situation can be continuously improved. The chemical products industry is one of the sub-sectors of Iran's industry under the ISIC code 20 and is one of the leading industries in the country. This industry supplies the chemicals needed in various industries by converting primary raw materials into various industrial products and is therefore known as an intermediary and upstream industry. According to the reports published in the Central Bank’s publications and a review of export items based on international classification in 2018, it is revealed that, in terms of value, the “chemicals” group has accounted for the largest share of the customs export value with 27.1 percent. Also, the chemical industry accounted for the largest share of customs export value in 2014, 2015, 2017, and 2018, with shares of 31.1%, 29.1%, 28.3%, and 28.1%, respectively. Therefore, the products produced by the chemical industry supply raw materials for many sectors of Iran’s economy and, in this regard, are highly importance to the country’s economic policymakers. One of the important features of this industry is its high added value. According to the statistical yearbooks published by the Statistical Center of Iran, the amount of added value generated by the chemical industry is higher than that of other industries. Therefore, based on this criterion, the chemical industry is considered one of the leading industries, as shown below. Hence, the present study examines the efficiency and performance of companies operating in this industry, representing the first research conducted in this field, using Data Envelopment Analysis and the Malmquist Productivity Index. Data Envelopment Analysis (DEA) is one of the efficiency calculation methods. DEA is a linear programming method for measuring the performance of economic enterprises. In this study, efficiency was first measured and evaluated using input-based models under constant returns to scale (CRS) and variable returns to scale (VRS). Subsequently, total factor productivity was analyzed using the Malmquist Productivity Index for eight subgroups of the chemical manufacturing industry classified under ISIC code 20 during the period 2002 to 2018. 2.Literature review Measuring productivity is considered an important issue. Basically, the concept of total factor productivity became important when organizations realized that output growth cannot be achieved in the long run from input growth due to the limited resources used. In other words, the more resources are used, the less sustainable output growth is guaranteed. Therefore, this issue requires more attention from managers to achieve improved and more accurate values ​​for productivity growth, which itself requires continuous activity. The term "productivity" was first formally introduced by an author named Quincey in 1776, and more than a century later, in 1883, Litter defined productivity as "the power and ability to produce". Since the early 20th century, the word has acquired a more precise meaning and has been introduced to mean the relationship between output and input, defined by Early in 1900. In 1950, the Organization for Economic Cooperation and Development (OECD) provided another definition of productivity, stating that productivity is the ratio of output to one of the factors of production. In general, our country's economy has two characteristics: first, it is heavily dependent on foreign exchange earnings from crude oil exports, and second, it has faced a high population growth rate. The increasing trend of importing consumer goods takes more and more money out of the country's foreign exchange earnings and investment flows every year, and if this continues, it will reduce investment opportunities for the production of goods. The use of foreign capital has also not been considered due to the lack of necessary platforms; therefore, the main solution to increase the production of goods and services is to increase the level of productivity. By improving productivity, it is possible to produce better quality products at lower prices and prepare the necessary grounds for entering the global market. In this way, not only can the entire production capacity of the country be utilized, but also the possibility of developing these production capacities is provided (Meybadi, 2011) Among the domestic and foreign research conducted in the field of data envelopment analysis and the Malmquist index, the following can be mentioned. Alcala et al. (2023), in their study, analyzed service productivity in Central and Eastern European countries using the Malmquist index. The Malmquist index methodology was applied with output orientation and its decomposition into technical changes, pure technical efficiency, and scale efficiency during the period 2000 to 2019. The results show that service productivity in recently integrated countries increased by an average of 1.3 percent per year compared to 1.6 percent in the manufacturing sector. Shah, et al. (2023) assessed energy efficiency, trends in change and determinants of energy efficiency growth in South Asian countries using SBM-DEA and Malmquist approaches. The results show that the average energy efficiency score across all six countries for the study period is 0.7278. This score indicates that these countries still have a potential of 27.22% to improve their energy efficiency to minimize inputs to achieve optimal output levels with the lowest emissions. The results show that energy efficiency and productivity in these countries have declined over the period and the potential causes of inefficiency in the energy conversion process are extensive use of inputs and lower production growth. 3.Methodology This study employs data from the Statistical Center of Iran covering the period 2002–2018 for eight subgroups of the chemical and chemical products industry (ISIC Rev. 4 code 20). The dataset includes labour inputs, research costs, energy use, and capital, as well as output indicators such as the value of manufactured products and industrial value added. The aim of the study is to investigate efficiency and the total factor productivity index using Data Envelopment Analysis (DEA) and the Malmquist productivity index. In the literature, the non-parametric DEA approach is widely known in most fields as one of the most commonly used methods for evaluating efficiency and productivity. It is generally considered an alternative to parametric approaches. For the first time, Farrell in 1957 proposed a method similar to the Data Envelopment Analysis to evaluate efficiency. Later, Charnes, Cooper, and Rhodes introduced the data envelopment analysis method in 1978 by extending Farrell's approach to efficiency measurement. In the DEA method, the linear programming technique is used and efficiency is calculated by performing a series of optimizations separately for each firm. In this method, production factors and products can have different measurement units. In this method, a group is identified and presented as a reference set for each inefficient observation in order to model and increase efficiency. In the present study, input-oriented envelopment analysis models have been used. In input-driven models, the goal is to reduce inputs while considering a certain number of outputs. DEA models, regardless of their nature, are written in two forms: multiplicative and enveloping, where the enveloping form is obtained from the dual of the multiplicative form and vice versa. In terms of scale, DEA models also operate under two assumptions: constant returns to scale (CRS) and variable returns to scale (VRS). 4.Results According to the values ​​obtained from the implementation of the input-based CCR model, units with efficiency values ​​of one are considered efficient. Industry 3 has been efficient during the period under consideration. In fact, it has been able to maintain low efficiency during the years under review. The lowest efficiency score is for Industry 1 in 2005. Table 4-3 shows the results for the input-to-axis BCC model, which have increased compared to the efficiency scores presented in Table 4-3 for the efficiency values ​​obtained from the input-to-axis CCR model, which results in an increase in the number of efficient units in the input-to-axis BCC model compared to the input-to-axis CCR model. An efficiency score of 1 indicates efficient units and a score less than 1 indicates inefficient units in the model. In the input-to-axis BBC model, industrial units 3, 4, and 6 were efficient during the period under study. The results of the Malmquist productivity index showed that in some years during the period under review, productivity growth was positive and in some other years, productivity growth was negative. This productivity growth trend was irregular, sometimes declining into negative growth and at other times showing positive growth. Among the 8 sub-sectors of the chemical materials and products industry under ISIC (20) code, Industries 3 and 6 were respectively in the constant return to scale model with unit efficiency and the highest efficiency during the period 1381-1397. Also, Industries 3, 4 and 6 were in the variable return to scale model with unit efficiency. In this study, after presenting the generality of the research, theoretical foundations and results of empirical studies conducted in relation to the research topic were presented. Next, the research framework and methodology, including indicators and empirical models, were presented, and then the calculation of indicators and estimation of research models were discussed. After performing calculations and results, the estimates were also analyzed. According to the values ​​of the table of changes in total factor productivity for the first industry (production of basic chemicals) during the period under review, there has been an increasing trend in some years, indicating productivity growth and progress, and the highest productivity growth rate was 2.26. The second industry (production of chemical fertilizers and nitrogen compounds) had the highest productivity growth rate in 2008 with a value of 2.168, and there has been no regular productivity growth trend during the period under review. The third industry-production of plastics and synthetic rubber in the first form-recorded the highest productivity growth rate in 2004. However, this was followed by a decreasing trend, with negative productivity growth until 2010. Afterward, the industry experienced a positive productivity growth continued until 2013. 5.Discussion Considering that the total factor productivity and technological efficiency values were greater than one across all eight sub-sectors of the industry, it can be concluded that the main factors in improving productivity during the study years are technological progress and the use of new technologies. This reflects the optimization of industries during the years under study. Calculating efficiency and productivity, and the insights gained from assessing the performance and productivity status of the chemical production industry over several consecutive periods, can help organizational managers formulate strategic goals and make more informed decisions. It should be noted that measuring productivity is only part of the productivity improvement cycle. Therefore, the results of these calculations alone cannot lead to higher productivity; improving productivity also requires effective planning and the development of a comprehensive productivity improvement roadmap. However, effective and practical planning for increasing productivity requires measuring and evaluating productivity performance over previous periods. Accordingly, nonparametric models, the most widely used of which is Data Envelopment Analysis (DEA), were employe in this study. Based on the results obtained, the third industry, which had total productivity and efficiency scores of one, can serve as a reference set for improving productivity in other sectors. One of the main limitations of the present study was the lack of access to up-to-date data for recent years, which restricted the accuracy of the calculations and recommendations. Access to more up-to-date information and data would have enabled a more precise analysis and better recommendations based on the existing conditions. Considering the efficiency values obtained, industries with lower efficiency than Industries 3, 4, and 6 should be more careful in using their resources and increase their efficiency by increasing the industrial added value. It is also worth noting that, in order to compare the results obtained from two different models of parametric and non-parametric methods, another study can be conducted using parametric methods to measure efficiency and productivity. Moreover, efficiency and productivity evaluation as well as other indicators and models, such as collective and multiplicative models, are recommended to achieve more accurate results in the chemical production industry. Furthermore, for policy-making and operational planning, additional studies are recommended focusing on inefficient industries, as well as on the development of reform and improvement programs aimed at enhancing efficiency and productivity. Declaration of interest: none

Dedicated banking is the main and exclusive subset of wealth management, whose main goal is to provide financial and non-financial services to wealthy clients. The purpose of this research is to design a dedicated digital banking model based on a Grounded Theory approach. The research is applied and exploratory. The statistical population included managers and subject-matter experts in digital and private banking at Pasargad Bank, along with university professors. Interviews were used to collect the data. For verification and validation, the opinions of 11 specialized experts in banking were used. In this research, grounded theory was used as the analytical method to categorize the interview data. Eighty-one categories were identified in the central coding stage and finally, in the advanced coding stage, these categories were organized into six dimensions of the paradigm model, with the relationships between them clearly established. Strategic factors revealed 11 key strategies including: (1) Mobile Bank, (2) Internet Bank, (3) Electronic Banking, (4) Omnichannel Banking, (5) Cognitive Banking, (6) Social Banking, (7) Blockchain Banking, (8) Open Banking, (9) Metaverse Banking, (10) The use of artificial intelligence in the data mining process, and (11) the use of recommender systems. Based on the results it can be concluded that the digitalization of dedicated banking increases the level of profitability, competition and market share for the bank while also increasing satisfaction and loyalty and fostering customers’ positive attitudes towards the brand. Key Words: dedicated banking, digital banking, digitalization, Pasargad Bank 1.Introduction Private banking is a sub-branch of comprehensive banking that provides differentiated services to wealthy individuals. The core of this sector's services is wealth management for these individuals. In recent years, the expansion of financial technology and the increasing complexity of customer relationships with banks have presented the banking industry with numerous challenges. These days, retail banks are facing a challenging environment because the diversity of customers, the diversity of demands, and the need to meet these demands are highly complex. Accordingly, the private banking process will undergo significant changes with the introduction of digital transformations into this field. Therefore, it is necessary to examine this approach, which has entered the banking system in the form of an innovation, and analyze the changes that can be applied in this field. Therefore, this article evaluates the digital transformation of Pasargard Bank in the field of private banking with regard to strategy transformation, business transformation, and management transformation. The first objective of this research is to consider the various dimensions of digital transformation in private banking, and the second objective is to develop a private banking model with an emphasis on digitalization at Pasargad Bank. Literature Review Banking is largely dependent on information technology to provide convenient, reliable, and convenient services and retain customers. Banks have increased their investments in online services and, accordingly, have reduced the number of automated teller machines (ATMs) and branch offices. The implementation of e-banking projects has highlighted the importance of digital transformation for the survival of contemporary organizations in the digital economy. At the same time, the global luxury goods market is constantly expanding, yet, research on the service quality of luxury brands of online banking is scarce. In theoretical foundations, it has been suggested that dedicated banking and customer segmentation can simultaneously increase bank profitability and customer satisfaction. In their study, Imran Khan et al. (2023), after modeling the behavior of bank customers, depending on each customer class, proposed policies to increase customer activity and their satisfaction. Li and Li (2020) also found that general and VIP customers perceive service quality related to customer satisfaction differently. Similarly, Baghani et al. (1402) showed that customer segmentation enhances the ability to meet customers’ needs and improve their satisfaction. Methodology This study employes a qualitative research approach based on grounded theory. Grounded theory can be defined as a research approach in which new theories are developed based on real data through a scientific method. Grounded theory is a method that aims to recognize and understand individuals’ experiences of events and occurrences within a specific context. In traditional approaches to research, data collection is a separate stage in the research that is usually completed before data analysis. In grounded theory, the data collection process follows a different, with data collection and analysis conducted simultaneously. In this regard, interviewing is an appropriate method for collecting data in grounded theory. Accordingly, and in line with the study’s objectives, the data collection was carried out through interviews with experts. This research is applied and exploratory in nature. The statistical population consisted of managers and experts in the field of digital banking and private banking of Pasargad Bank as well as university professors in the relevant fields. The data was collected through interviews. The opinions of 11 experts in the field of private banking were used for verification and validation. In this study, grounded theory was used to analyze and categorize the interviews. In the axial coding stage, 81 categories were identified, and in the advanced coding stage, these categories were organized in the model within six dimensions of the paradigm model, along with the relationships that existed between them. In terms of time, the study was carried out during the years 1401-1402, and in terms of subject matter, it was in the field of digital banking. Result Private banking is one of the main and exclusive subsets of wealth management, primarily aimed at providing both financial and non-financial services to wealthy clients. Accordingly, the researchers developed a private banking model with a digital orientation, using a data-driven approach at Pasargad Bank. Based on the results, 11 drivers for the digitalization of this process were identified, including: (1)Mobile Bank, (2) Internet Bank, (3) Electronic Banking, (4) Omnichannel Banking, (5) Cognitive Banking, (6) Social Banking, (7) Blockchain Banking, (8) Open Banking, (9) Metaverse Banking, (10) The use of artificial intelligence in the data mining process, and (11) the use of recommender systems. Considering the results, it can be concluded that the digitalization of private banking increases the level of profitability, competitiveness, and market share for the bank while increasing satisfaction and loyalty, and improving customers’ attitudes toward the brand. Discussion Given that most VIP bank customers have limited need for banking facilities, the use of recommender systems can provide services such as insurance, capital management, management of domestic and international bank trips, provision of medical services, etc. The use of artificial intelligence services and recommender systems for VIP customers, enhances service personalization, thereby improving both customer satisfaction and loyalty level. Additionally, the use of cognitive internet-based banking services to get acquainted with the spirit and cognitive and intellectual processes of VIP customers promotes the bank's brand perception in customers’ minds. Based on the results and considering the importance of service specialization in private banking, it seems that private banks are dependent on other parties to provide innovative products, which are usually business partners of investment banks and other specialized companies. A good example in this regard is the adoptation of investment funds focused on securities and equities. Therefore, the private banking sector should collaborate with other external suppliers and organizational units. The services offered by wealth managers are extensive and include commercial banking, investment banking, brokerage services and other professional advisory services that are both interesting and attractive to customers. As indicated by the results and the importance of investment in various fields, it is recommended that the bank prioritize the establishment of investment funds in various economic fields such as land, housing, foreign exchange, insurance, leasing, industry and mining, etc. Furthermore, given the significance of advisory services, it appears essential, to implement a comprehensive information management system, and identify and train the required specialized consultants in order to implement the next stages of private banking implementation and its expansion in the coming years. Declaration of interest: none

Citizenship rights are one of the important topics that widely pays attention to justice and equality and holds a significant place in social, political and legal theories. The concept of citizenship is fully realized when all members of a society participate in various domains and have the right to assume duties and responsibilities that contribute to effective management of the society and maintenance of social order. The purpose of this article is to present a model of citizenship rights grounded in Islamic jurisprudence and principles. To this end, a mixed-methods approach was employed. In the qualitative part content analysis and in the quantitative part a survey method was utilized to validate the proposed model. The survey was conducted with 20 experts in the field of citizenship rights and law professors. The research findings in the qualitative part show that the dimensions of the model of citizenship rights from the perspective of Islamic jurisprudence and fundamentals include five dimensions: 1-human dignity, 2-supervision of citizens over managers, 3-realization of justice and service, 4-citizenship rights and welfare standards, and 5-citizenship rights and participation, and in the quantitative part, the five aforementioned dimensions were validated by the expert community using the structural equation modeling . Key Words: legal foundations, citizenship rights, Islam, human capital productivity management 1.Introduction Citizenship rights, as a framework of rules and regulations that govern the rights of individuals and the government and the limits of their authority against each other, are a central topic in today’s world. In the Islamic government of Iran, the legal relationship between individuals and the government has a special place, and the rights and privileges of individuals have been comprehensively explained in the constitution. The main sources of fundamental rights in Iran are derived from Islamic jurisprudence, within which the recognition of fundamental individual rights and freedom constitute a core element. Although the term "citizen's rights" is not explicitly mentioned in the Constitution of Iran, related concepts such as "nation's rights", "public rights" and "individual and social rights" are used. This research, with an analytical and descriptive method, seeks to examine the juridical and legal foundations of citizenship rights in Islamic jurisprudence. Additionally, a comparative study will be conducted on Iran's legal system, focusing on the status of citizenship rights. This analysis will examine both the correspondences and contradictions between Iran's legal system and Islamic jurisprudence, and will propose recommendations for updating jurisprudential sources and legal system in Iran. Considering the position of citizenship rights within Iran's constitutional law, it is necessary to examine their legal and jurisprudential foundations within the Iranian legal system and adapt them to authentic Islamic principles. In this regard, several researches have been carried out, some of which are mentioned below. Literature Review Nasiri et al. (1401) developed a model for citizenship rights in which attention to organizational culture, legal and social requirements, and technological barriers are considered as key components. They believed that discovering talents and preserving human dignity can play an effective role in improving citizenship rights. In this regard, Mohammadi Moghadam and colleagues (1400) sought to explain the principles of social justice and the importance of respecting the rights of citizens by emphasizing Nahj al-Balagha. Khodabakhsh et al. (1400) investigated the mutual role of the government and citizens with a jurisprudential approach and came to the conclusion that the government is obliged to guarantee the rights of citizens, while the citizens are also obliged to comply with the laws. Also, Tadzkiri et al. (2018) showed that personal development and professional ethics can lead to the improvement of organizational performance. Finally, Habibzadeh and Marandi (2015) emphasizing human dignity and human rights within the framework of the Islamic Republic of Iran's constitution, emphasized that respect for these values ​​is the basis of legitimate government. Methodology The present research employs a mixed qualitative-quantitative approach. In the qualitative phase, legal texts and relevant materials pertaining to the subject will be examined and analyzed. The statistical population of this research, in the qualitative section, includes all the texts, books, articles, etc. related to the subject of the research. The statistical population also includes 20 experts in the field of citizenship rights and law professors. In the qualitative section, in order to investigate the role of citizenship rights indicators from the perspective of Islamic jurisprudence and principles in human resource productivity management, the data was collected through library-based research, and thematic analysis was employed to analyze the data. Based on the aforementioned research methodology, in order to design a model of citizenship rights from the perspective of Islamic jurisprudence and principles, and to explore its role in improving the human capital productivity management system, the existing lectures, field notes, interviews and relevant academic articles were utilized. Finally, to ensure greater validity, the identified categories were presented to 20 experts in citizenship law and professors of public law. The categories were then evaluated and validated in terms of their relevance to and effectiveness in achieving the research objectives. Finally, in order to test the proposed model within the statistical population, the structural equation modeling based on the partial least squares approach was employed, using a researcher-made questionnaire. Result Using the qualitative method, five categories, 14 concepts and 86 indicators were developed for the proposed model. In the subsequent stage of the research, the confirmatory factor analysis was used to assess and validate the applicability of the model as well as to determine the relative importance and ranking of the variables. Since the t values obtained from the t-test for all paths in the model of citizenship rights from the perspective of Islamic jurisprudence and principles and its role in improving the human capital productivity management system are greater than 1.96, the relationships are statistically significant at the 0.05 level of significance between citizenship rights from the perspective of Islamic jurisprudence and principles and the identified categories, indicating that these categories appropriately measure citizenship rights within this framework. Overall, the results reported in the relevant figures and tables, along with the values of factor loadings and significant coefficients, confirm the validity of the relationship between citizenship rights from the perspective of Islamic jurisprudence and principles and the identified categories, concepts, and codes. In the general conclusion of this section, the dimensions, components and results of the final model of citizenship rights from the perspective of Islamic jurisprudence and principles demonstrate a strong level of interdependence and coherence at the 95% confidence level. Based on the results, the examined five categories of human dignity, citizens’ oversight of managers, the realization of justice and service provision, and citizenship rights and welfare standards have significant weights and at the 95% confidence level, they exhibit meaningful factor loadings. Discussion Citizenship rights are among the emerging concepts that emphasize equality and justice and have gained an important place in social, political and legal theories. Citizenship is realized when all members of an organization enjoy full civil and political rights and have easy access to the desired opportunities of life in economic and social terms. Employees as members of an organization participate in different areas and along with the rights they have, they also assume responsibilities in order to better manage society and create order. This article examines the concept, components and indicators of citizenship rights based on Islamic jurisprudence and principles, as well as their impact on human resource productivity management. It examines the observance of the productivity management of human resources and states that the observance and guarantee of the productivity management of human resources cannot be achieved without the realization of the indicators of citizenship rights. Declaration of interest: none

The numerous challenges startups face throughout their life cycle (from initial launch to survival and growth, and ultimately to exit) require various support programs, among which accelerators play a particularily important role as they provide mentoring services. With the widespread integration of the Internet into all aspects of daily life along with the impact of the COVID-19 epidemic, providing these services online— under the concept of electronic mentoring— has become increasingly important. Therefore, the aim of this research is to identify a framework for electronic mentoring based on the real needs of startups accelerators. In terms of its objective, this research is applied and developmental which was conducted using a qualitative phenomenographic approach, with data collected through interviews. The reliability, using the test-retest and double-coding methods, was 82.63% and 86%, respectively. The statistical population included the startup accelerators that faced the spread of COVID. Using a purposive sampling method, 15 startups were selected, and one of the main founders from each was interviewed. The analysis identified three main dimensions including technical, managerial and communication, each encompassing concepts that are suitable for the implementation of electronic mentoring programs. Among these, the most critical factors include access to a wide network of mentors along with a suitable schedule for the accelerator; the mentor’s previous experience and the fit with the startup's specific needs; and finally, the startup's autonomy in choosing mentors, and the platform’s capability to record mentoring sessions. Keywords: startup, accelerator, mentoring, COVID-19, phenomenography 1.Introduction Entrepreneurs and startups face numerous challenges (Jean & Audet, 2012, p. 120), leading to the creation of support programs like accelerators (Clarysee et al., 2015, p. 59), which are crucial in entrepreneurial ecosystems (Leitao et al., 2022, p. 17). Accelerators provide capital, industry connections, and visibility to investors, helping startups to face the real world as quickly as possible and navigate their path (Pauwels et al., 2016, p. 11). Despite their growing acceptance, there is limited research on accelerators' specific characteristics and challenges, particularly in attracting quality mentors. Mentoring is a vital element of accelerators, significantly impacting their success. However, the mentoring process is often unstructured, and accelerators struggle to attract top mentors (Busulwa et al., 2020, p. 20). Furthermore, the COVID-19 pandemic has complicated this by disrupting communication between mentors and startups, forcing accelerators to adapt. This research aims to address these gaps by developing an online e-mentoring platform tailored to the needs of startups during the pandemic. The study integrates theoretical and practical perspectives, focusing on the Iranian entrepreneurial ecosystem, which has been underrepresented in accelerator and e-mentoring research. The goal is to create a framework that enhances the efficiency of accelerators through effective e-mentoring, considering cultural, economic, social, and technological differences. The research seeks to identify the dimensions of e-mentoring that align with startups' needs within accelerators. 2.Literature Review Accelerators as key players in entrepreneurial ecosystems, have gained significant popularity in recent years. Various definitions of accelerators have been proposed, with one of the most prominent being that of Cohen and Hochberg (2014, p.4), who describe them as fixed-term, cohort-based programs that include extensive mentoring and training, culminating in a public demo day. This definition underscores the importance of mentoring, which has been widely recognized as a fundamental and critical component of accelerators. Accelerators typically consist of five core elements: strategic focus, structured programming, initial funding, a rigorous selection process, and post-graduation services. Doukakis et al. (2019, p. 5) outline the steps involved in creating a mentoring program, which include designing a guide, setting goals, scheduling, defining the roles of both parties, training mentors and mentees, selecting participants, matching mentors with mentees, adapting to unexpected changes, and finally, conducting evaluations and follow-ups. Iqbal (2020, p. 55) further identifies the key elements of mentoring as initiation, scheduling, formalization, intensity, planning, role clarity, awareness of responsibilities, encouragement, support, and constructive feedback. Silver and Gavini (2023, p.2) propose a mentoring model that includes the following elements: developing comprehensive educational programs, including workshops, training sessions, and courses focused on mentoring, aimed at equipping mentees with essential skills and knowledge, such as active listening, empathy, goal-setting, and providing constructive feedback encouraging and promoting peer-to-peer mentoring among current mentees to facilitate skill development and the sharing of valuable experiences establishing and facilitating collaboration between mentors and mentees with clear expectations and well-defined goals providing opportunities for mentees to observe experienced mentors in action and participate in mentoring-related events, learning from real-world examples ensuring institutional support and recognition by establishing supportive structures, resources, and adequate acknowledgment of mentors' efforts through financial incentives or other forms of support and awards 3.Methodology The present study is exploratory in terms of its purpose with an applied-developmental orientation, conducted through a qualitative approach grounded in a phenomenographic research strategy. Phenomenography is a research method aimed at mapping the different ways individuals perceive, experience, and conceptualize phenomena (Beagon & Bowe, 2023, p.1113). While the phenomenon of e-mentoring has been described and conceptualized in the literature, what remains underexplored is its implementation and adaptation to the needs and perceptions of its users. Therefore, the researchers adopted this method to identify and describe the diverse perceptions of startups regarding e-mentoring within accelerators. Given that phenomenography is applicable in both academic and professional settings—addressing questions and challenges related to teaching and learning in scientific, academic, and workplace environments—it was deemed suitable for this study, which seeks to uncover the understanding, feelings, and experiences of startup founders regarding e-mentoring within accelerators during the COVID-19 pandemic. The primary tool in phenomenography is interviews (Khanifer & Moslemi, 2019, p. 518), and in this study, semi-structured interviews were utilized. The statistical population of this research consists of startups undergoing acceleration programs within an accelerator, whose programs coincided with the peak of the COVID-19 pandemic and faced disruptions. Thus, the temporal scope of the study is spring and summer of 2020. Phenomenographic research is typically conducted with small groups of participants, and purposive sampling, involving at least 15 individuals from a similar population, is considered appropriate for achieving meaningful interpretation. Accordingly, a public accelerator that continued its operations during the pandemic and took steps, albeit limited and incomplete, toward e-mentoring was selected (a key aspect of phenomenography is the participants' experience with the phenomenon under study). This accelerator attempted to continue its services online. Ease of access to the accelerator and the possibility of interviewing its startups were additional selection criteria. After selecting the accelerator and obtaining consent from its administrators, startups within the accelerator (both in the acceleration phase and pre-acceleration, as well as those utilizing co-working spaces and mentoring services) were chosen for the study. Ultimately, 15 startups (A1 to A15) were prepared for interviews. Interviews were conducted with one of the founders of each startup, lasting between 40 minutes to 1 hour. Due to social distancing requirements and travel restrictions, interviews were conducted via Skype, recorded, and downloaded. The interviews were interactive and conversational, starting with general questions such as, "What challenges did you face regarding mentoring within accelerators during COVID-19?", "What is your perception of an e-mentoring platform within accelerators?", and "What are your expectations from an e-mentoring platform within accelerators?" More specific questions were asked as the interviews progressed to maintain focus on mentoring. After recording and transcribing the interviews, the analysis process began, following the phenomenographic method in an iterative manner, aiming for inductive interpretation. In this study, the statements of interviewees were carefully examined, and similar meanings were marked (e.g., with the same colour) and labeled to distinguish categories and subcategories (in this method, all data must be treated equally as a single set). This was done using open coding to identify the problems, suggestions, and expectations of startups related to mentoring within accelerators, thereby outlining the essential dimensions of an e-mentoring framework within accelerators. After converting the data into text and examining it sentence by sentence, the problems, suggestions, and expectations formed the basis of open codes. Following extensive analysis, the main categories were identified. A key aspect of this method is hierarchical organization and categorization. To calculate reliability, two methods were used: test-retest and dual coding. In the test-retest method, three interviews were selected and coded twice at a specific time interval. Codes that matched over time were labeled as "agreement," while non-matching codes were labeled as "disagreement." The test-retest reliability of the interviews in this study was calculated at 82.63%, which, being above 60%, confirms the reliability of the coding. In the dual-coding method, a doctoral student in entrepreneurship, who was an employee at one of the accelerators, assisted, and the reliability obtained was 86%, again confirming reliability as it exceeded 60%. 4.Results After conducting interviews and analyzing the resulting data with a focus on mentoring using the phenomenographic method, the understanding of startups regarding e-mentoring within accelerators—coinciding with the COVID-19 pandemic—was examined. This understanding can serve as a foundation for launching an e-mentoring platform within accelerators. To create such a platform, the perspectives of startups were categorized into three dimensions: technical, managerial and relational. Technical dimensions focus on the capabilities and technical features of an e-mentoring platform, such as various communication media, discussion forums, online shared workspaces, demo capabilities, and other technological tools that facilitate interaction and collaboration. Managerial dimensions emphasize the role of the accelerator as the facilitator in coordinating and managing mentoring in an online environment. This includes aspects such as access to mentors, mentor rating systems, and ensuring smooth communication between mentors and startups. Relational dimensions highlight the interaction between the main parties (the startup team and the mentor) and the characteristics of a mentor, such as mentor availability, expertise, commitment, and the alignment of the mentor's skills with the startup's needs. In the analysis of the interview data, eight interviewees primarily viewed the platform through a technical and technological lens, three interviewees emphasized managerial aspects, and four interviewees highlighted relational dimensions as particularly significant. It is important to note that the responses of the interviewees exhibited significant overlap (for example, eight interviewees discussed both technical and relational dimensions together, while five interviewees combined technical and managerial aspects in their discussions). However, the dimensions that were more prominently and frequently mentioned were considered the dominant reference points for categorization and the primary perspective of the interviewees. 5.Discussion The expansion of entrepreneurship has brought with it numerous concepts, including startups. Consequently, due to the myriad challenges faced by startups (Jean & Audet, 2012, p 120), various support programs have emerged, with participation in accelerators currently being one of the most popular. Numerous studies suggest that accelerators can serve as effective organizations in shaping the startup ecosystem (Pauwels et al., 2016, pp. 5-8; Sharma & Meyer, 2019, p. 88). Acceleration programs encompass various features, cycles, stages, and mechanisms, among which mentoring is one of the most critical (Kuratko et al., 2021, p. 201). With the pervasive influence of the internet and the digitization of most aspects of life on one hand, and disruptive phenomena such as infectious diseases on the other, coupled with geographical distances and the widespread deprivation of many segments of society from receiving education-particularly mentoring in business and entrepreneurship-electronic mentoring has gained significant importance. Electronic mentoring refers to the application of technology in facilitating communication between mentors and mentees (Oosthuizen & Perks, 2019, p. 602). Based on the primary research question and insights derived from interviews, three key dimensions-technical, managerial, and relational-play a fundamental role in implementing this concept, each encompassing multiple factors. The managerial dimension includes aspects where the accelerator, as the overseer of acceleration programs, must act as the primary lever for supervision and coordination to ensure effective communication between mentors and mentees on an online platform. In this regard, the accelerator must play a central role in developing a broad network of experienced and specialized mentors, categorizing them, and scheduling and coordinating sessions. These findings align with the results of studies by Barrehag et al. (2012, p.10), Clarysse et al. (2015, p. 66), Pauwels et al. (2016, p. 17), and Stayton and Mangematin (2018, p. 1176), which emphasize the accelerator’s role as the primary overseer and coordinator of the entire acceleration process. The technical dimension includes factors that enhance the quality of mentoring. Specifically, the electronic mentoring platform, given its expected functionality, should be equipped with various communication media and tools required by startups, as highlighted in research by Chang et al. (2019, p. 14). This ensures the facilitation of effective, peer-to-peer (Leppisaari, 2019, pp. 98-99), and real-time communication among startups and with mentors. The platform should allow startups the freedom to choose mentors and consider diverse subcultures and languages. It should also provide shared spaces similar to those in physical accelerators, along with additional features such as discussion forums, seminars, group meetings, assignment definitions, session recordings, demo practices, and mentor evaluations for startups in subsequent cohorts. Alongside these two dimensions, the relational dimension, which pertains to the interaction between mentors and mentees, encompasses factors that shape the ease and quality of this communication. Mentors are viewed as crucial by startups, a perspective supported by research from Sánchez et al. (2017, p. 2), Yitshaki and Drori (2018, p. 3), Staton and Mangematin (2018, p. 1178), Cohen et al. (2019, 1791), Avinmelech and Rechter (2019, pp. 18-24), and Walker et al. (2020, pp. 11-37). From the startups' perspective, mentors must first believe in and be familiar with the concept of electronic mentoring. They should possess expertise and experience, demonstrate commitment, and align with the diverse and varied needs of startups. The accessibility of mentors is also considered a critical factor by startups. Declaration of interest: none

Increasing productivity is a central issue in economic development; therefore, it is essential to identify and evaluate the economic factors affecting the level of productivity growth. The main objective of this study is to investigate the total factor productivity (TFP) growth in Iran's crop sector as well as to investigate the economic factors affecting TFP growth in this sector. In this study, total factor productivity and its components were estimated using the Malmquist index, and the effect of economic factors on TFP growth of was analyzed using a linear regression model based on macroeconomic variables. The results showed that in the entire period, the average total factor productivity growth of Iran's crop sector was positive by 13.7%. Based on the regression results, the foreign investment variable and the export value of agricultural products have a positive effect on the total factors productivity while the variable of the export value of the crop sector, the import value of the agricultural sector, and Iran's oil export value have negative effects on total factor productivity. According to the results, the most important factors in increasing and decreasing the growth of the total factor productivity of Iran's crops are the effect of technology and technical efficiency, respectively. Overall, based on the findings of this study, it is recommended that policymakers implement effective policies and provide appropriate support to promote crop exports and attract foreign investment as these factors can enhance the growth of total factor productivity in the crop sector. Key Words: total factor productivity, technology, Malmquist index, crops, Iran 1.Introduction Economic growth is one of the most important indicators of a country's economic development. Resource scarcity, limited accessibility, and the rising costs of exploiting new resources all necessitate humans to make the most of existing resources and to be more productive. Consequently, increasing productivity and adopting advanced technologies and more efficient methods have gained growing attention. In recent years, productivity growth has been one of the key points that researchers are seeking to examine. The issue of productivity growth and preventing its decline is a challenge that even developed countries in the world have recently been involved in. Labor and capital are two important factors of production in the economy. Therefore, examining the factors affecting the productivity of these two items can be effective in setting the goals of economic development policies over time. The general purpose of this study is to investigate the productivity growth of the total factor productivity (TFP) of Iran's crop sector as well as to investigate the economic factors affecting TFP growth in this sector. 2.Literature Review In a study, total factor productivity in the Indian agricultural sector was examined using the Malmquist index by Chaudhary (2016). The results showed that total productivity and changes in technical efficiency increased in a few regions of the country and total productivity decreased in most regions. Rahman and Salim (2013) studied total factor productivity in the agricultural sector in 17 regions of Bangladesh during the period 2008-2018 using the Malmquist index. The results showed that the average growth rate of total factor productivity in the agricultural sector was 0.57 percent. Also, the determining role of technological progress, farm size, investment in research and development activities, and land reform measures on the growth of total factor productivity were evident. In the study of Sisman and Tekiner (2022), using the Malmquist index, agricultural productivity in Turkey was analyzed for the years 2006-2015. The results showed that agricultural productivity has decreased by an average of 2 percent per year. In a study by Baion et al. (2023), the extent and nature of agricultural total factor productivity growth in 44 sub-Saharan African countries over a 59-year period was examined using the Malmquist index method, and the results showed a decrease in agricultural total factor productivity growth from 1961 to 2019. 3.Methodology Productivity is calculated in two forms: partial productivity and total factor productivity of production. Partial productivity expresses the ratio of output productivity to one of the inputs, such as human labor productivity. In other words, the average production rate of each factor of production is called partial productivity. One of the shortcomings of this method is that the productivity of other factors of production is ignored and their impact is not considered and the change made is only considered as an input. However, total factor productivity (TFP) expresses the ratio of total output to all factors used in production. The growth of total factor productivity can be considered as a result of technical efficiency and technological change and can be a suitable model for policymakers in the agricultural industry to reduce the weaknesses and shortcomings in production. In general, two approaches are used to calculate TFP: parametric (econometric) and non-parametric approaches. In the parametric approach, productivity can be obtained by calculating the production function, cost function, or supply and demand relationships of the product with the factors of production. In the non-parametric approach, productivity can be calculated using mathematical programming or index-based methods. The Malmquist method and the Data Envelopment Analysis (DEA) are among the most widely used non-parametric methods. In this study, the Malmquist method is used to obtain TFP in the agricultural sector. This method is particularly suitable because it identifies the components of productivity growth and shows the most important positive and negative factors of growth. 4.Results According to the results, during the period under study, the growth in TFP of all agricultural products was positive, about 13.7 percent, which is mainly driven by technological growth. While efficiency experienced a slight decline of 0.2%, technological change contributed a substantial positive growth of 13.9%. An important point is that the positive growth in TFP of all agricultural products does not necessarily mean that the effects of both efficiency and technology are positive; rather, it indicates the positive outcome of the effects of these two factors. For example, in the case of irrigated wheat, although the results indicate a growth of 15.1 % in total factor productivity, considering the components of this growth, it is clear that the efficiency factor had a negative and decreasing effect, reducing total productivity by about 2.2 %. However, due to the positive and relatively strong effect of the technology factor, contributing to about 16.5% on this productivity, the overall outcome has led to a growth of 15.1 % in the TPF of wheat production. Additionally, the analysis of the factors affecting total factor productivity show that, with the exception of the inflation rate and the official exchange rate, all other variables have significant effects. Specifically, agricultural exports and foreign investment have a positive and significant effect on TFP growth, whereas total agricultural import value, oil export value, and agricultural exports have a negative and significant effect on the growth of total factor productivity. According to these results, a one million dollars increase in agricultural exports and foreign investment raises the growth of TFP in the agricultural sector by approximately 1% and 0.15 %, respectively. In contrast, a one-million -dollar increase in total agricultural imports, oil exports, and agricultural exports, reduces TFP growth by about 0.06%, 0.005%, and 0.15 % in the agricultural sector, respectively. Discussion In general, based on the findings of this study, technological change is the most important component that increases total productivity growth, whereas weak technical efficiency is the most important component that reduces this growth. Therefore, it is essential for the government and policymakers to make the necessary plans to improve farmers’ managerial capabilities, including more effective dissemination of modern sciences and skills. Moreover, given the positive and significant impact of technology on productivity, efforts should be made to provide a more supportive environment for further productivity growth in this sector by developing and granting facilities. It is also suggested that policymakers provide appropriate facilities and implement effective planning to support the development of agricultural exports and attract foreign investment. At the same time, the import of agricultural products should be controlled and only limited to essential circumstances. Together, all these measures can enhance the productivity growth of the entire agricultural sector. Declaration of interest: none

Effective leadership and management in universities are critical concerns for policy makers, academic staff, and institutional leaders. Accordingly, this study was conducted with the aim of developing a model of shared leadership components in the established units of the Islamic Azad University in West Azarbaijan province. The research design was cross-sectional and mixed in nature. In the qualitative stage, theme analysis was used and in the quantitative stage, structural-interpretive modeling was implemented. In order to design the model in the qualitative stage, interviews were conducted with ten university experts who were selected through purposeful sampling. The qualitative data analysis yielded 84 primary codes derived from 401 themes. The 84 primary codes were subsequently grouped into the form of 16 main categories-organizational leadership communication, organizational communication, functional outcome, organizational teams, organizational behavior, organizational structure, different leadership styles, human resource management system, organizational environment, strategic management, organizational change management, management performance, competitive advantage, organizational resources, organizational skills, and leaders’ behavioral characteristics— and integrated into a model. In the quantitative stage, 16 senior managers were selected through simple random sampling. The validity of the model was assessed using Kappa coefficient, which yielded a value of 0.763 indicating a substantial level of agreement. The results of the interpretive structural modeling revealed that the variables of organizational resources, different leadership styles, organizational change management, competitive advantage, and organizational skills, have high influence power and low susceptibility to influence and are placed among ​​independent variables. On the other hand, functional outcome, and organizational communication, had high dependence but low influence; therefore, they are classified as dependent variables. In contrast, the variables of organizational teams, organizational structure, performance management, human resource management system, strategic management, leaders’ behavioral characteristics, organizational leadership communication, organizational behavior, and organizational environment, demonstrated both high influence and high dependence, and thus are identified as linkage variables. Key Words: leadership, leadership styles, shared leadership Introduction The contemporary era is characterized by escalating complexities and rapid environmental shifts, presenting organizations, particularly higher education institutions, with multifaceted challenges that necessitate a re-evaluation of leadership approaches. Leadership style, as a composite of managers’ attributes, skills, and behaviors, plays a crucial role in organizational success. The traditional hierarchical leadership models are increasingly inadequate, prompting educational administrators to explore novel leadership concepts. Shared leadership has emerged as a promising approach, emphasizing mutual interaction, improved human relations, and enthusiastic participation. This style, rooted in decentralization and accountability, empowers employees. This research aims to design a model of shared leadership components within the Islamic Azad University (IAU) units in West Azerbaijan province, addressing the critical need for effective leadership in higher education. The study explores the key elements of shared leadership and develops a model tailored to the unique context of the IAU. The central research question is: what are the components of shared leadership in the IAU units in West Azerbaijan province, and what model can be proposed for successful implementation of this leadership style? Literature Review Elmore (2000) proposed five key dimensions for shared leadership: mission and vision, organizational culture, decision-making, evaluation and professional development, and leadership experiences. This model was later reduced to four dimensions by Gordon (2005): mission and vision, organizational culture, shared responsibility, and leadership experiences. Spillian et al. (2004) emphasize that these dimensions are strongly linked to real leadership experiences and training. In the academic environment, shared leadership is particularly important. Jones et al. (2014) believe that this leadership style enhances effectiveness in higher education, especially during times of change. In universities, faculty, academic staff, and even students can contribute their knowledge and abilities to shape the university’s future. Strategic shared leadership, as a source of dynamic capabilities, involves sharing strategic decisions among the dominant coalition of the organization. This approach, initiated by a strategic leader, ensures that shared leadership is both genuine and effective. Nicoloides et al. (2014) found that the common thread in overlapping leadership structures is the distribution of leadership among multiple individuals. Bass and Avolio (1993) and Pearce and Sims (2002) noted that a recurring problem in leadership studies is the tendency to ignore existing theories in favor of introducing new ways of thinking. Recent studies have explored the impact of shared leadership in various contexts. Vogel (2022) found that shared leadership in school leadership teams enhances agility in addressing changing organizational priorities. Wang et al. (2022) identified three network criteria (i.e., density, reciprocity, and degree centrality) that collectively measure distributed leadership in school teams. Imam and Zaheer (2021) demonstrated that shared leadership enhances project success through knowledge sharing and cohesion. Wu and Cormican (2021) found that shared leadership positively impacts team effectiveness in engineering design teams. Wu et al. (2020) confirmed the positive relationship between shared leadership and team outcomes, while Ali et al. (2020) highlighted the role of adaptive leadership in promoting shared leadership and team creativity. Methodology This research employed a mixed-methods (qualitative-quantitative) approach, utilizing an exploratory sequential design. The qualitative phase involved in-depth, semi-structured interviews with ten purposefully selected academic experts in higher education management. The selection criteria included a doctoral degree, a minimum academic rank of assistant professor, at least five years of management experience in a university, and a willingness to participate in the study. The data were collected until theoretical saturation was reached. Thematic analysis was used to analyze the qualitative data, aided by MAXQDA software. In the quantitative phase, a survey was administered to 26 randomly selected vice-presidents and heads of IAU units in West Azerbaijan province. A researcher-developed questionnaire, based on the findings of the qualitative phase, was used. The questionnaire’s validity was confirmed through content and construct validity, and its reliability was established using Cronbach’s alpha. The Structural Interpretive Modeling (ISM) method was employed to develop the model. This method, introduced by Warfield (1974) and Sage (1977), is an interactive learning process that structures a set of different constructs into a systematic and comprehensive model, allowing for the examination of complex relationships between multiple elements. The quantitative data were analyzed using MICMAC software. The variables examined included 16 components: organizational leadership communication, organizational communication, functional outcome, organizational teams, organizational behavior, organizational structure, different styles of leadership, human resource management system, organizational environment, strategic management, organizational change management, performance management, competitive advantage, organizational resources, organizational skills, and leader behavioral characteristics. Results The qualitative data analysis yielded 84 initial codes from 401 interview segments. These codes were categorized into 16 main categories. For instance, regarding “organizational leadership communication,” interviewees noted the continuous exchange of ideas and bidirectional leader-follower relationships. For “functional outcome”, they emphasized increased innovation and improved organizational performance. In “organizational teams”, they highlighted collaborative leadership and strong team support. For “organizational environment”, they stressed the need for a supportive organizational climate and a culture of participation. The frequency of coded categories varied across the interviews, with “functional outcome” receiving the most codes (66), followed by “different styles of leadership” and “organizational teams” (38 each). “Organizational environment” was the third most frequently coded category (32). The analysis also revealed that 100% of the interviewees mentioned the “functional outcome” category, indicating its importance. The inter-rater reliability of the coding process was assessed using Cohen’s kappa, which yielded a value of 0.763, indicating a valid level of agreement. In the quantitative phase, 16 categories were used to construct a Structural Self-Interaction Matrix (SSIM). This matrix, based on expert opinions, identified the relationships between the variables. The SSIM was then transformed into a reachability matrix, which was used to determine the level of each variable. The analysis revealed that “functional outcome” was at level 1, indicating its high dependence on other variables. “Organizational communication” was at level 2, while “organizational teams”, “organizational structure”, and “performance management” were at level 3. The MICMAC analysis, based on the reachability matrix, categorized the variables into four groups: autonomous, dependent, independent, and linkage. The results showed that “organizational resources”, “different styles of leadership”, “organizational change management”, “competitive advantage” and “organizational skills” were independent variables, characterized by high driving power and low dependence. “Functional outcome” and “organizational communication” were dependent variables, with high dependence and low driving power. “Organizational teams”, “organizational structure”, “performance management”, “human resource management system”, “strategic management”, “leader behavioral characteristics”,“organizational leadership communication”, “organizational behavior”, and “organizational environment” were linkage variables, with both high driving power and high dependence. Conclusion This research identified 16 key components of shared leadership within the Islamic Azad University and developed a model that categorizes these components into eight levels. The findings highlight that “functional outcome” is the most dependent variable, emphasizing the importance of achieving organizational goals through shared leadership. “Organizational communication” plays a critical role in the successful implementation of shared leadership. The linkage variables, such as “organizational teams”, “organizational structure”, and “performance management” are crucial for the overall effectiveness of the model. The independent variables, including “organizational resources”, “different styles of leadership”, and “organizational change management” are the most influential factors in the model. The study underscores that successful implementation of shared leadership requires a holistic approach, addressing multiple factors simultaneously. The emphasis on leadership styles and organizational skills at the foundational level highlights the need for focused development in these areas. The importance of organizational resources and change management underscores the need for universities to be prepared for change and allocate sufficient resources. The central role of organizational communication and environment emphasizes the need for open communication and a supportive culture. The model provides a comprehensive framework for the implementation of shared leadership in the IAU, offering valuable insights for university leaders seeking to enhance organizational effectiveness. The findings underscore the importance of a balanced approach, addressing both the foundational and outcome-oriented aspects of shared leadership. This research provides a valuable contribution to the literature on shared leadership in higher education and offers practical guidance for university administrators. Declaration of interest: none

Today's rapid changes have highlighted a different set of skills from those emphasized in traditional career approaches. The concept of proactive career behavior emerged several decades ago as a key factor of job performance and organizational success. Since then, this concept has attracted the attention of many researchers across various scientific fields. Given the growing interest in this issue, and its diverse nature, the need to combining the existing literature is inevitable. Hence, the present study was conducted to identify the factors influencing employees’ proactive career behavior and to examine the effects of such behaviors. This research was done using a scoping review and thematic analysis approach. To achieve the objectives of the study, scientific databases, both internationally and domestic, such as Scopus, Web of Science, ScienceDirect, Emerald, Ebesco, Wiley, MagIran, IranDoc, SID and Normags were searched and a total of 544 studies were retrieved. After removing duplicates and screening studies, 65 studies were included in the review process. The extracted data were categorized based on the objectives of the scoping review and were reported in a table. Both China and the United States have conducted extensive research in this field. Based on the analysis of study population, most of the studies focused on employees’ proactive career behaviors. By examining the studies, the factors affecting employees’ proactive career behaviors and their effects were classified into four categories: individual, occupational, organizational and environmental factors. The findings suggest that recognizing proactive career behaviors and their effects can provide a useful mechanism for managers and employees to support employees’ career success and enhance organizational effectiveness. Key Words: proactive career behavior, proactive behavior, proactive personality, scoping review 1.Introduction Proactive career behavior is considered an important behavioral pattern for increasing the likelihood of individuals' employability and their promotion or career success. In the current dynamic business environment, characterized by constant change and declining job security, individuals are primarily responsible for managing their own careers. This issue implies that employees should engage in a range of proactive career behaviors to create career options and thereby achieve their career goals. A number of studies in the field of career activities have focused on individual characteristics, attitudes, competencies, and resources. Such constructs are significantly related to career foresight. These factors can be significant predictors of proactive career behaviors (Akkermans & Hirshci, 2023). Since its emergence as a scientific concept, proactive career behavior has always attracted the attention of numerous researchers in various scientific fields. However, no research has yet comprehensively examined both the factors influencing proactive career behaviors and the consequences arising from those behaviors. There is also a gap in understanding which dimensions of individual, organizational, or career dimensions are influenced by proactive career behaviors. The findings of this study can be used and applied both by academic researchers, employees of organizations and their managers. Another significance of this study is that it can help design more comprehensive and in-depth researches in the field of proactive career behavior. 2.Literature Review Over the past three decades, the concept of career leadership has received increased attention, and its theoretical basis has been linked to two somewhat distinct research streams, namely organizational behavior and professional research in the study of proactive career behaviors. Despite conceptualization and measurement, the underlying constructs of career proactivity typically emphasize the self-initiating, change-inducing, and future-oriented characteristics of career management activities (Klehe et al., 2021, p.126; Smale et al., 2019). Parker et al. (2006) believe that an individual's proactive career behavior is characterized by two characteristics: proactive idea implementation and proactive problem solving. Individual actions that share and implement ideas to improve working conditions are referred to as proactive idea implementation, whereas proactive problem solving refers to future-focused actions initiated by individuals with the aim of preventing problems from occurring. Grant and Ashford (2008) described proactive career behavior as individuals' proactive actions to influence themselves or their environment, and defined it as consisting of two key elements: proactive action and intended impact. Bindel and Parker (2010) define proactive career behavior as individual actions in the organization that are self-directed and forward-looking, and are carried out with the intention of creating change in oneself and the surrounding environment. De Vos and Younes (2018) reviewed a wide range of proactive behaviors and categorized them into two general components: cognitive and behavioral. The cognitive component refers to the insights that individuals develop into their career aspirations and the behavioral component refers to the behaviors and actions that employees use to manage their careers and achieve career goals. According to Briscoe and Hall (2006), the prospect of a new job necessitates the acquisition of new skills in self-management and career management behaviors. New skills include gathering information about values, interests, skills, strengths and weaknesses, identifying career goals, and engaging in career strategies that increase the likelihood of achieving career goals. These factors are also known as proactive professional management behaviors. These behaviors are actually a type of forward-looking competency that a person must possess. Such behaviors become a navigation system and serve as a guide for employees. Individuals use these practices to obtain information about their qualities, aspirations, expertise, capabilities, and vulnerabilities (career exploration), or to establish a career goal (career goal development), or to engage in career initiatives (career strategy implementation), thereby improving the likelihood of career advancement and achieving their career goals (Wang et al., 2024). 3.Method In this study, a scoping review method along with thematic analysis were used to identify relevant literature on proactive career behavior and synthesize the evidence. The main objectives of these reviews were to identify areas of research as well as research gaps and to highlight areas that require further research. This review employed Arksey and O'Malley’s (2005) approach which includes five steps: defining the question, identifying studies, selecting studies, extracting information, and synthesizing and reporting the results. The present study also used the content analysis method. To answer the research questions, the selected sources were carefully studied and their content was examined to find a theme or themes related to employees’ proactive career behavior. The content analysis process in this study was conducted using two frameworks: the three-stage coding process proposed by Attride-Stirling (2001, p. 389) and the two-stage coding approach by Ryan and Bernard (2003, p. 89). In the first approach, the position of themes within the thematic network is categorized into three levels, namely global themes, organizing themes, and basic themes. Global themes are at the heart of the thematic network; organizing themes are the interface between the global and basic themes; and basic themes express an important point in the text. The second approach also includes analyzing and classifying themes into two categories: main themes and sub-themes. 4.Results The analysis of the characteristics of the relevant studies shows that proactive behavior has been examined in various organizational and national contexts. Private sector organizations were the dominant organizations surveyed, likely due to their unstable and competitive operating environment, which requires employees with the ability to adapt quickly to changes. From a national perspective, China and the United States account for the majority of research on proactive behavior. These countries are leading the world in terms of both population and job opportunities and workforce. The results indicated that the largest number of studies examined employees’ proactive behaviors at the individual level of analysis. The objectives of this study were to identify factors affecting employees’ proactive career behavior, which were introduced in four categories: individual factors, job factors, organizational factors, and environmental factors. Individual factors include four aspects of individual motivation, individual attitude, self-efficacy and self-improvement, and proactive personality, which show that proactive behavior is closely related to individual characteristics. Job factors were categorized into three categories: job exploration, task interdependence, and proactive career behavior management. Job exploration can be thought of as an exploration of the nature and characteristics of a job. Job exploration focuses on the organization's human resource management system, job complexity, job demand, job reinvention, job personalization, job importance, work life, job facilitation, problem visualization, and explanation of job challenges and job limitations. Organizational factors were shown to be another dimension affecting the formation of proactive career behavior, with four sub-factors: interaction and networking, creative and positive imagery, organizational leadership influence, and organizational climate. The ability to interact and build network within and outside the organization is a fundamental aspect of proactive career behavior, which was demonstrated by indicators such as communicating with managers and supervisors, contacting people for professional help, informing the boss to pursue career goals, and consulting with the boss and experienced colleagues for useful guidance. Environmental factors, as the last category affecting proactive behavior, are often influenced by the external environment of the organization such as having a prominent career perspective, searching for resources, anticipating the future, orienting towards learning goals, physical work space, career goal setting, actively designing a professional future, sustainable employability, extra-occupational thinking, personal and professional development, normative knowledge, strategic knowledge, lifelong learning, 21st century competencies, independent learning, political skills and knowledge, psychological safety, proficiency in modern technological tools, keeping up with current developments, content creation, virtual work, and responsible use of technology. Another objective of the research was to identify the effects of employees' proactive career behavior, which resulted in four categories of effects: individual effects, job effects, organizational effects, and social effects. The results showed that the effects of proactive career behavior were dominated by individual effects and consequences. Most studies have attempted to study the effects of proactive career behavior on individuals as agents. The impact of proactive career behavior on individuals is characterized by two main trends: positive effects and negative effects. The positive effects were seen in items such as job satisfaction, individual performance, perceived competence, intention to stay, psychological well-being, emotional commitment, organizational commitment, and innovative work behavior. In discussing the negative effects, some studies have attempted to reveal the dark side of proactive career behavior. Findings suggest that individuals with proactive behavior are likely to experience burnout and work avoidance, work-family conflict, workplace anxiety, and intention to quit the organization. 5.Discussion Given the findings on the importance and outcomes of proactive work behavior, it is crucial not only to encourage employees to develop proactive career behaviors, but also to foster these behaviors by the organization and managers. This can help managers gain a clearer and more concrete understanding of the factors influencing proactive career behavior and manage them appropriately to enhance employee satisfaction and prevent talent attrition. By encouraging employees to engage in proactive career behaviors, managers can improve organizational performance while facilitating employees’ career growth. For example, creating an open and psychologically safe work environment can motivate employees to show initiative without fear of punishment. Additionally, it is recommended that managers incorporate proactive career behaviors into appraisal system as one of the performance evaluation criteria. Moreover, managers can create a more purposeful and meaningful work life for employees by providing personal development coaching sessions to support the development of proactive career behavior. Other recommended management practices include implementing training courses and programs, allocating space for innovation, introducing mechanisms to encourage proactive behavior, strengthening organizational communications, fostering an organizational culture that supports proactive behaviors, and coaching programs that benefit from employees’ experiences. In addition, policy-making aimed at creating innovative work environments can encourage employees’ creativity and idea generation while building an organizational culture that supports proactive behaviors. Declaration of interest: none

The present study aims to design and evaluate a model for nonverbal selling techniques, explaining their role in enhancing sales interactions. The research adopts a qualitative approach based on the grounded theory approach. The data were collected through in-depth semi-structured interviews with academic experts, managers, and senior specialists involved in sales-related processes and decision-making. Purposive sampling was used, and theoretical saturation was achieved after conducting 15 in-depth interviews. Data analysis was carried out in three stages-open, axial, and selective coding-which ultimately led to the identification of 23 main categories within a paradigmatic model. This model encompasses causal conditions, contextual factors, intervening variables, core phenomena, strategies, and outcomes. The findings indicate that nonverbal selling techniques-such as body language, eye contact, posture, and facial expressions-play a significant role in enhancing communication effectiveness with customers, building trust, and strengthening sales interactions. Finally, a conceptual framework was developed to illustrate the position of nonverbal selling in the development of resilient sales approaches. This framework can serve as a decision-making tool for managers and as a means to improve sales quality in dynamic environments. Key Words: nonverbal selling, nonverbal communication, grounded theory, customer interaction. 1.Introduction In the era of digital transformation, fundamental changes in consumer behavior, the emergence of new technologies, and intensified market competition have compelled organizations to rethink their customer engagement strategies. One often-overlooked dimension in sales training and execution is nonverbal communication or silent selling, which constitutes a significant portion of human interaction. This study aims to design and evaluate a model for nonverbal selling techniques and to explain their role in enhancing sales interactions. The central focus is on identifying the components, mechanisms, and outcomes of nonverbal selling in both face-to-face and digital contexts. 2.Methodology The research adopts a qualitative methodology based on the grounded theory approach developed by Strauss and Corbin (1998). The data were collected through semi-structured interviews with 15 experts, including university faculty members, sales managers, marketing consultants, and customer interaction specialists. Purposeful sampling and snowball techniques were used until theoretical saturation was achieved. Data analysis followed a three-stage coding process-open, axial, and selective-and the validity of the findings was confirmed using Lincoln and Guba’s (1985) criteria and Cohen’s kappa coefficient (86.9%). 3.Results The results led to the identification of 23 core categories within a paradigmatic model comprising causal conditions, contextual factors, intervening variables, central phenomena, strategies, and outcomes. Causal conditions included shifts in buying behavior, expansion of nonverbal channels, and the growing importance of speed in customer decision-making. Contextual factors involved digital infrastructure transformation, customers’ psychological readiness, and brand policies aimed at optimizing the sales experience. Intervening variables included cultural barriers, technological limitations, and resistance from some sales personnel. The central phenomenon was defined as the effective application of nonverbal selling techniques to increase influence in the buying process. This included four main categories: visual techniques, body language, interactive technologies, and environmental cues. Proposed strategies involved training salespeople in nonverbal communication, designing sales environments based on visual cues, and leveraging smart technologies to analyze customer behavior. The identified outcomes included increased customer trust, reduced cognitive resistance, improved shopping experience, and enhanced conversion rates. 4.Discussion The findings of the present study highlights that nonverbal techniques play a complementary and sometimes decisive role in sales success, especially in crisis situations, sensitive negotiations, and high-stress environments. With the rise of digital and video-based selling, the importance of nonverbal cues in virtual spaces has grown significantly, necessitating a redesign of organizational training and execution strategies. These techniques not only convey emotional and brand-related messages but also shape positive customer experiences and loyalty. 5.Conclusion In the current study a conceptual framework was developed that positions nonverbal selling as a strategic tool for developing resilient sales approaches. This framework can guide managerial decision-making, inform sales training programs, and improve the quality of customer interactions in dynamic environments. The findings also offer a foundation for brand policy development, sales environment design, and the use of advanced technologies in customer behavior analysis. Future research is recommended to empirically test the effectiveness of this model across various industries and digital platforms. Conflict of interest: none

With the advent of the digital age, the advancement of artificial intelligence science and changes in the management system of organizations, the move towards the application of artificial intelligence in management is inevitable. Predicting the relationship between taxpayers is one of the challenges that has been neglected compared to other tasks. This study is an attempt to use the data related to the purchase and sale (seasonal transactions) of taxpayers, to predict their financial relationships in the future, and to discover tax evasion if these transactions are not recorded in the subsequent observations. The present research is an applied research study with a practical purpose, conducted using the algorithm implementation method. The information sources of this research were the studies regarding detecting fraud and preventing tax evasion with graph analysis tools and using machine learning, conducted between 2017 and 2023. Based on these studies and the combination of machine learning algorithms such as neural networks and graph analysis, the proposed algorithm was formed, tested and evaluated. The outputs of this research are associated with the algorithm testing of 107,797 records that were related to the purchases of summer 1401 (sent to the National Tax Administration). All the simulations were done in Python and tested in the PyCharm environment, which provided acceptable results to recognize tax evasion. By using the proposed method, that is, neural graph network as well as machine learning algorithms, it is possible to determine whether there is a transaction that the parties did not state. In other words, with the proposed method, it is possible to prevent tax evasion due to the advancements in prediction and detection methods. The results of this research help increase the productivity of tax administration by using graph analysis and machine learning techniques to identify and detect fraud, aiming to prevent tax evasion. Key Words: graph analysis, graph neural networks, organizational productivity, tax evasion, tax fraud detection 1.Introduction Tax evasion is an illegal activity in which individuals or entities deliberately avoid paying their tax liabilities. Tax evasion leads to the loss of tax revenue and the loss of the fair principle of taxation, and since it has such a strong economic and social impact, almost all governments are faced with it. There are various methods to deal with tax evasion and detect fraud. In recent years, graph learning methods using machine learning algorithms, extract features related to graphs and take advantage of both to detect and prevent tax evasion. A graph neural network is a class of neural networks for processing data that can be represented as graphs. Graph neural networks have emerged as a powerful tool for fraud detection tasks where fraudulent nodes are identified by collecting neighboring information through various relationships. Literature Review Tax risk detection has gone through two main stages of evolution: traditional case-based selection and data mining-based selection. Considering the use of input data, tax risk detection methods based on artificial intelligence and data mining can be divided into two categories of relational and non-relational (Zheng et al., 2024) methods. Since 2006, non-relational tax risk detection methods were used to identify people or companies at risk. These methods first extracted the characteristics of people with risk, then, trained the classifier, and finally recognized the risk. Relational data mining methods developed after 2016, and researchers gradually began to use the aggregation of relationships in tax networks to consider both contextual and behavioral characteristics to identify risks. Relational methods can easily extract deeper knowledge from the complex and rich structural information in the tax network. Consequently, to improve the accuracy of risk detection in the tax risk detection process, models should focus on as much information in the tax scenario as possible. A tax scenario includes many types of entities with rich interactions between them, while non-relational methods do not examine the behavioral characteristics that describe the interactions between taxpayers (Zheng et al., 2024). Graph neural networks have become a potential method for fraud detection tasks, identifying fraudulent nodes by gathering neighboring information to consider multiple relationships (Liu et al., 2018; Li et al., 2019; Du et al., 2020; Zhou et al., 2020; Wang et al., 2021; Liu et al., 2022; Zhao et al., 2022). Methodology Predicting the relationship between taxpayers is one of the challenges that has been neglected compared to other tasks. In this research, the aim was to use the data related to the purchase and sale (seasonal transactions) of taxpayers, to predict their financial relationships in the future, and to discover tax evasion if these transactions are not recorded in the subsequent observations. In general, in the tax system, buying from a seller is giving a tax credit to it, which must be returned to the tax authority; so, it is important to report the purchase or sale in order to pay the relevant tax. The existence of directional graphs that show the path of purchase from the seller is the main distinction and complexity of our method. The proposed method is based on graph neural networks in which each node is a buyer or seller and the edge between them is the transaction weight. In a nut shell, in the first stage, the data is refined and the seller and buyer are considered as the nodes and their relational link, i.e., transaction fee, is considered as the edge, which is then converted into a vector based on the algorithm of neural networks. After graph analysis, the best prediction result is obtained by expanding the machine learning classification tool. In the present study, the output related to the algorithm test and the prediction of tax evasion for 107,797 records were related to the purchases of summer 1401, and the records related to the transactions below 1 billion Rials (not significant) were not considered. All simulations were written in Python and tested in PyCharm environment. Result From the total number of the data sent to the Iranian national tax administration in summer 1401, the trained data were tested for approximately 25% of the reported records (14533 records) which were discarded in the training process. The noteworthy point is that the display of the vectors was binary and classification algorithms such as regression and the like were used to display them. Finally, a number of nodes (buyers or sellers) were obtained who had hidden transactions and had not reported them to the tax administration. Among a number of machine learning classification tools, the best result was awarded to the 4-layer neural network algorithm with a ROC value of 0.91 and an accuracy of 0.85. In the proposed method, the place of tax evasion is identified when new data is given to the model and the real connection (link) between the nodes is received in the output and matched with the existing reality. If the other party did not report the transaction and the model detected a link, tax evasion would be detected. With this method, the objectives and, as a result, the efficiency of the tax administration were achieved in the test phase. Discussion This research recommends a new method to identify and prevent tax evasion by combining the strengths of graph analysis and machine learning. In these networks, patterns and anomalies indicate fraudulent behavior that are difficult to be detected in conventional fraud detection technologies. The proposed method fills this gap by integrating graph analysis and machine learning. Using sophisticated graph algorithms allows us to discover previously unseen patterns and identify outliers that may indicate fraudulent behavior. Machine learning approaches complement graph analysis by providing the capacity to learn complex patterns from massive data sets. When graph-derived features are combined with machine learning algorithms, sometimes unseen patterns are found that might otherwise go undetected. In this research, the experiments were conducted on the real tax data sets, the results of which show a significant improvement in the prediction accuracy of fraud detection, with fewer false positives. It is suggested that, to use this method in the national tax administration, a decision-making support system with graphic display of financial interaction cycles should be available to tax investigation and detection groups to detect fraudulent evasion. Additionally, the application of this model in the taxpayer system will be very effective if as soon as the buyer or seller is notified, the tracking of goods or services is started and the warning of non-submission of value-added declaration is activated for taxpayers who have been in this cycle but evaded notification and payment to prevent tax evasion from the beginning of the cycle. Conflict of interest: none

approach focusing on involvement in decisions, can increase the ability, skill and creativity of employees and their internal morale and motivation. This research was conducted to provide a model for human resource management with high involvement in Iran's government organizations. First, the theoretical literature and pertinent empirical studies were reviewed to identify the dimensions and components of the human resource management conceptual framework with high involvement based on the AMO (Ability, Motivation, and Opportunity) theory, and then, it was screened and finalized by experts using the Delphi method and structured questionnaires. The statistical population of the literature review section included all valid scientific research related to human resource management with high involvement between 2000 and 2022. After multi-stage screening, 53 articles were selected to extract concepts. Moreover, 12 experts of the Delphi department consisting of university professors with experience in the field of human resources management, were selected as the participants through targeted sampling procedure. In the quantitative phase, the factor structure of the proposed framework was assessed using confirmatory factor analysis and a sample of 252 managers of public organizations in Tabriz. The estimation of the measurement model, and the reliability and validity (convergent and divergent) of the constructs were confirmed at the desired level. The results revealed that the conceptual framework of high-involvement human resources management, in the dimension of ability aligned with the functions of selection and recruitment, training and development, regarding the dimension of motivation was in line with the functions of performance-related pay and reward, performance evaluation, and considering opportunity it aligned with the functions of employee involvement and job design. The present study proposed a comprehensive framework for human resource management with high involvement based on the correspondence between AMO theory and human resource management functions, which strengthens employee involvement in government organizations. Key Words: empowering actions, high involvement, human resource management, motivational actions, opportunity-enhancing actions. 1.Introduction In the current era, characterized by rapid environmental changes and increasing competition, competent and capable human resources play a crucial role in the success of organizations. The high-involvement human resource management approach is recognized as an effective method for enhancing employees' abilities, skills, and creativity. This approach, focusing on employee participation in decision-making processes, can improve their morale and intrinsic motivation, leading to increased organizational performance. Studies have shown that this approach positively impacts organizational innovation, flexibility, proactive employee behaviors, and knowledge absorption capacity. It also affects individual aspects such as job satisfaction, work-life balance, and reduced job burnout. The three-dimensional framework of Ability, Motivation, and Opportunity (AMO) can be effective in developing employees' competencies and improving their innovative behaviors. Given the existing challenges in Iranian public organizations, such as low employee participation in decision-making and the lack of effective knowledge transfer mechanisms, providing a localized framework for high-involvement human resource management seems necessary. This research aims to provide such a framework, seeking to answer the question of what the conceptual framework explaining high-involvement human resource management based on the AMO theory in Iranian public organizations is. This framework can help improve the performance and well-being of employees in Iranian public organizations. 2.Literature Review High-involvement human resource management (HIHRM) encompasses a set of modern managerial practices that enhance organizational performance and facilitate the development of employees' knowledge, skills, and abilities (Hussain & Chalara, 2019). This approach not only encourages employees to work hard but also boosts their creativity and job-related skills (Chen & Wang, 2021). The Ability, Motivation, and Opportunity (AMO) theory provides a framework for explaining the relationship between human resource management and performance (Bloomberg & Pringle, 1982). Enablers (A) include practices to enhance employees' knowledge and skills (Senanayake, 2021); motivation (M) pertains to employees' motivation to perform tasks, which can be strengthened through performance-based rewards and pay (Klenner et al., 2019); and opportunity (O) includes actions that allow employees to showcase their skills (Yasir & Majid, 2020). HIHRM positively impacts individual and organizational performance through these three components (Hussain & Chalara, 2019). This approach leads to increased organizational innovation (Elaghari, 2021; Nupur, 2021; Cao et al., 2021), flexibility (Kay & Ruble, 2021), proactive behaviors (Chen & Wang, 2021; Renkema et al., 2021), and knowledge absorption capacity (Salas-Varela et al., 2020). It also affects individual aspects such as job satisfaction, work-life balance, emotional intelligence (Wang, 2020), and reduced job burnout (Kilroy et al., 2020). By creating a dynamic and creative environment, HIHRM allows employees to participate in work issues and make decisions themselves. Studies show that HIHRM leads to team creativity (Song et al., 2020), productivity (Piotr et al., 2020), and organizational citizenship behaviors (Wasim et al., 2020). This approach is more human-centered compared to traditional human resource management methods (Edwards & Wright, 2001) and emphasizes efficient employee participation in organizational decision-making (Macky & Boxall, 2009). Overall, HIHRM, by focusing on empowerment, motivation, and creating opportunities for employees, can lead to improved individual and organizational performance, increased innovation and creativity, and the creation of a positive and dynamic work environment. 3.Methodology This research aims to provide a conceptual framework for high-involvement human resource management in Iranian public organizations, employing a developmental-applied study with a mixed-method approach. Data collection involved two main stages: initially, a systematic literature review of credible sources from 2000 to 2022 was conducted, resulting in the selection of 53 articles through multi-stage screening for concept extraction. Subsequently, the Delphi method was used with the participation of 12 selected experts in human resource management. These experts were chosen based on criteria such as a minimum of five years of teaching experience, experience in human resource strategies, associate professor rank, and having at least five related scientific-research articles. The data were collected through structured questionnaires in two stages and analyzed using descriptive statistics, content validity index, and Kendall's coefficient. To ensure the validity and reliability of the research, multiple credible sources, diverse expert opinions, and the calculation of the content validity index were used. The results were analyzed with Excel software, incorporating the Delphi notes and common ideas. Finally, a conceptual framework was proposed based on the AMO theory, resulting from expert consensus on the variables influencing high-involvement human resource management. 4.Result To achieve a conceptual framework for high-involvement human resource management, a systematic literature review was conducted, including six steps: formulating the research question, developing a search strategy, selecting suitable studies, assessing study quality, extracting data, analyzing and reporting. The main research question was defined based on the AMO theory in Iranian public organizations. A comprehensive search in reputable internal and external databases identified 1425 articles, which after applying inclusion and exclusion criteria, 53 final articles were reviewed. The quality of the studies was assessed using qualitative and quantitative methods, and the data were extracted and analyzed from each study. Eventually, 73 initial concepts were identified and, after summarization and homogenization, were categorized into 48 final concepts in the context of high-involvement human resource management. In the second stage, the research's conceptual framework was redesigned using the opinions of 12 experts. This framework included 6 main HR functions categorized based on the AMO theory. The Delphi method was used to collect and analyze the expert opinions, and the components with an index below 0.96 or agreement percentage below 70% in the first Delphi round were removed. In the second round, 100% expert agreement was achieved. The final results showed that the components such as digital skills training, competency-based performance evaluation, competency-based selection, performance-based pay, and creating a participatory atmosphere were confirmed as the key concepts in high-involvement human resource management in Iranian public organizations. 5.Discussion Employee participation in decision-making allows for a broader range of perspectives and ideas, leading to more informed and effective decisions. Therefore, this study designed a comprehensive conceptual framework for high-involvement human resource management based on the AMO theory through a mixed-method study. The results indicate that the components of the conceptual framework for high-involvement HRM based on the AMO theory include enabling actions, motivational actions, and opportunity-creating actions. Enabling actions include competency-based selection and recruitment, and training and development of human resources. Motivational actions include compensation and rewards, and performance evaluation. Opportunity-creating actions include employee participation and job design. This study integrated the AMO theory with HRM practices to enhance organizational capabilities and outcomes and used the Delphi method to screen the dimensions and components of the proposed model. The innovation of this study lies in applying the AMO theory to the context of Iranian public organizations, providing a management model tailored to the country's cultural and social conditions. This model can help Iranian public organizations improve organizational productivity and innovation. However, the findings and proposed conceptual framework are designed for the context of Iranian public organizations and may not be generalizable to different cultural settings; therefore, future researchers are recommended to conduct comparative studies to explore differences and similarities in the implementation and effectiveness of high-involvement practices in various types of organizations. Conflict of interest: none

The aim of this study is to develop a comprehensive model for marketing knowledge‑based companies operating in the field of information technology, with a specific focus on branding processes. In the first phase, the research followed a qualitative approach based on Grounded Theory. The data were collected through semi‑structured interviews with 21 experts, including university faculty members and managers of knowledge‑based companies. The data analysis was conducted through open, axial, and selective coding, resulting in the extraction of 331 open codes, 72 concepts, and 17 main categories organized under causal conditions, contextual conditions, intervening conditions, strategies, and consequences. To assess the validity of the qualitative model and examine the relationships among the variables, in the second phase of the study, the researchers employed a quantitative approach using Structural Equation Modeling (SEM). The data for the quantitative phase were gathered from a sample of 250 practitioners and managers of knowledge-based IT companies. The results of the confirmatory factor analysis indicated that the model fit indices were within acceptable ranges. Moreover, the structural model analysis showed that all major paths were statistically significant at the 0.05 level. The relationships among causal, contextual, and intervening conditions and the strategies, as well as the effect of strategies on branding outcomes, were all confirmed. The path coefficients for the paths from intervening conditions reflected strong effects of these constructs. The combined qualitative and quantitative findings demonstrate that the proposed model possesses the necessary theoretical and empirical coherence, offering an effective framework for enhancing marketing and branding in knowledge‑based companies within the information technology sector. Key Words: marketing, branding, knowledge-based IT companies 1.Introduction In today's globalized world, organizations are focusing on enhancing their business strategies to stay competitive, with brand equity playing a crucial role in marketing efforts. Knowledge-based companies specializing in technological products must prioritize recognizing marketing management as a valuable asset and view marketing as a continuous process. By utilizing up-to-date knowledge and technology in product development, these companies can create value and establish themselves in the market. Regularly reviewing and adapting marketing strategies is essential to keep up with changing market conditions and customer preferences. The innovative products and services offered by knowledge-based companies contribute to economic development and social wealth, inspiring innovation and influencing customer preferences. However, the lack of a strong corporate brand can lead to elimination from the competitive landscape, making it crucial for these companies to establish a strong brand to reach suppliers, acquire customers, and strengthen innovation in business models. Despite facing challenges such as building consumer trust and creating demand for their offerings, implementing co-creative branding can help companies collaborate with customers to enhance brand image, increase brand equity, and secure a competitive advantage in the market. Knowledge-based IT companies in the northwest of Iran are facing challenges in marketing and branding, requiring specific strategies tailored to their innovative and technological nature to succeed in competitive markets. Developing a marketing model based on branding can help these companies differentiate themselves and increase market recognition; however, there are gaps in the research on the impact of branding on competitive intelligence and market performance, as well as a lack of localized models and innovative marketing strategies. With a significant number of knowledge-based start-ups in provinces like East Azerbaijan, West Azerbaijan, Ardabil, and Zanjan, there is a clear need for attention to marketing, especially branding, to ensure success. The traditional four Ps of marketing (product, price, distribution, and advertising) remain fundamental, but there is a call for localized and innovative strategies to effectively market knowledge-based products in the region. Branding is a crucial aspect of business strategy, as it shapes the mental image that customers have of a product or company through communication and knowledge. The goal of branding is to increase awareness and customer loyalty by influencing how customers perceive and rely on the business to meet their needs. Key elements in branding include brand salience, imagery, performance, emotions, judgments, and fit, with brand equity being achieved when a brand reaches the top of this pyramid. In the IT sector, branding plays a significant role in enhancing brand equity and competitive advantage, with innovation, marketing, networking, and dynamic capabilities being key factors. Integrating IT into marketing and branding strategies is essential for gaining a competitive edge, with digital transformation allowing businesses to engage with consumers effectively. Employer branding in IT companies can also help attract and retain top talent. Furthermore, branding as an intangible asset can significantly contribute to a company's value in the knowledge-based economy. Studies have shown that branding affects the marketing expansion and export of products from knowledge-based companies to neighboring markets, with leadership, marketing strategy, infrastructure, and market analysis playing crucial roles in their success. The studies conducted by Azad-Armaki (2021), Hosseinpour (2021) and Saadatmand (2019) all highlight the importance of relationship marketing strategies in increasing brand equity for knowledge-based companies. Azad-Armaki's (2021) research model focuses on contextual marketing, entrepreneurial networks, internal guiding core, and innovative entrepreneurship, while Hosseinpour's (2021) model outlines steps for creating and developing knowledge-based companies. Saadatmand (2019) emphasizes the need for a branding ecosystem framework that considers innovative intermediaries, customers, government, and businesses. Hosseinpour (2021) underscores the significance of marketing in knowledge-based companies for economic growth and job creation. Additionally, Trou et al.'s study on brand building in Mexican small businesses emphasizes the importance of brand building for improving business results and market performance. Overall, these studies provide valuable insights for companies seeking to enhance their brand equity through effective marketing strategies. 2.Research Methodology The qualitative phase of the study was conducted based on Strauss and Corbin’s (2008) Grounded Theory approach, which enables the development of a coherent theoretical model derived directly from empirical data. Sampling The sampling in this phase was carried out purposively and complemented by snowball sampling. The criteria for participant selection included having direct experience and sufficient expertise in the field of marketing and branding within knowledge-based IT companies. The final sample consisted of 21 participants, and data collection continued until theoretical saturation was achieved. Data Collection Method The data were gathered through semi‑structured interviews. The interviews primarily focused on identifying factors influencing branding, the strategies adopted, and their resulting outcomes in these companies. Data Analysis Method The data analysis followed a systematic process consisting of three coding stages: Open Coding: Initial identification of concepts and preliminary categorization of raw codes. (Outcome: 331 open codes) Axial Coding: Identifying relationships among the extracted categories and grouping them within the theoretical paradigm. (Outcome: 72 concepts) Selective Coding: Developing the core paradigm and extracting the central phenomenon of the study. (Outcome: 17 main categories) Qualitative Validation To ensure the credibility and transferability of the qualitative model, techniques such as peer debriefing, theoretical saturation, and member checking with key participants were employed. Quantitative Phase Structural Equation Modeling (SEM) was employed in the quantitative phase. Research Design In the second phase, a survey strategy was employed with the aim of empirically testing the conceptual model developed during the qualitative phase. Population and Sample The statistical population consisted of middle and senior managers, as well as senior experts working in knowledge-based IT companies located in East Azerbaijan Province. Based on Cohen’s guidelines for SEM and considering the number of variables in the model, the final sample size was determined to be 250 individuals. Measurement Instruments The research instruments consisted of a combination of standardized questionnaires and customized scales developed based on the conceptual model constructed in the qualitative phase. All scales were designed using a five‑point Likert format. Data Analysis The data analysis was performed using the following software tools: SPSS 25: for descriptive statistics and preliminary validity and reliability assessments (Cronbach’s alpha). AMOS 24: for confirmatory factor analysis (CFA) and structural equation modeling (SEM). 3.Results Qualitative Findings In the qualitative phase, the data were collected through semi‑structured interviews with 21 experts, including university faculty members and managers of knowledge‑based IT companies. The analysis followed the systematic grounded theory approach and was conducted through open, axial, and selective coding. During open coding, 331 initial codes were identified and organized into 72 concepts and 17 core categories. The final outcome of the qualitative analysis was the development of a comprehensive paradigm model explaining “branding‑based marketing in IT knowledge‑based companies” in relation to causal conditions, contextual factors, intervening conditions, strategies, and outcomes. The model revealed that branding in such companies is a multifaceted phenomenon shaped by environmental factors, organizational capabilities, and managerial strategies, ultimately leading to improved market development, better risk management, and strengthened brand positioning. Quantitative Findings In the quantitative phase of the study, structural equation modeling (SEM) using AMOS 24 was employed to test and validate the conceptual model derived from the qualitative analysis. The data for this phase were collected from a sample of 250 managers and experts working in knowledge-based IT companies. The results of the confirmatory factor analysis (CFA) indicated that all measurement models demonstrated satisfactory levels of construct validity and reliability. Key fit indices, including CFI, TLI, RMSEA, and χ²/df, were within acceptable thresholds, confirming the adequacy of the measurement model. Subsequent analysis of the structural model showed that all hypothesized paths were statistically significant at the 0.05 level. Specifically, intervening conditions exhibited a strong and positive effect on strategies (β=0.914), while strategies demonstrated a significant positive impact on branding-related outcomes (β=0.912). The coefficient of determination (R²) further indicated that the proposed model possesses strong explanatory power for the main constructs. Overall, the quantitative findings provide empirical support for the conceptual model developed in the qualitative phase and reinforce the theoretical coherence of relationships among causal conditions, contextual factors, intervening conditions, strategies, and outcomes within knowledge-based IT companies. 4.Conclusion The present study was an attempt to develop a model for marketing knowledge-based companies in the IT field through branding in the northwest region. Conducted qualitatively with a data-based research method, the study extracted over 331 open codes, 72 concepts, and 17 categories to identify characteristics essential for successful branding in the IT sector. The main category explored is knowledge-based companies in the IT field based on branding, highlighting the importance of understanding environmental threats, growth, and competitive strategies for effective marketing and branding. The research emphasizes the significance of considering both external environmental factors and internal organizational capacities in developing marketing strategies. Additionally, the study distinguishes between controllable and uncontrollable factors that impact marketing and branding strategies, emphasizing the need for a detailed analysis to shape effective marketing plans for knowledge-based companies in the dynamic IT environment. In summary, experts recommend investing in knowledge-based companies, establishing relationships with customers, building culture, training and utilizing human resources, and implementing targeted marketing and branding strategies to drive success in the IT field. By focusing on these key areas, businesses can increase their competitive edge, improve customer relationships, foster a positive internal culture, enhance employee skills, and strengthen their brand position in the market. Implementing these strategies can lead to increased investment, improved risk management, expanded product offerings, international market growth, and enhanced brand recognition, ultimately driving growth and success for knowledge-based companies in the IT industry. Implementing smart customer management strategies can lead to increased customer satisfaction, loyalty, and market share for companies. In the realm of human resource development, focusing on culture-building, training, and talent acquisition can enhance team efficiency and performance. Market positioning and competition management are crucial for boosting brand recognition and implementing effective marketing strategies, ultimately increasing a company's competitive edge and ensuring sustainable success in the market. By prioritizing improvement and excellence, companies can mitigate risks and optimize their resources to meet the evolving needs and challenges of the IT market. Conflict of interest: none

Successful organizational managers recognize that optimal job performance depends not only on the employees’ physical health but also on their mental health. Numerous psychological studies have emphasized that the quality of a desirable life, in terms of psychological dimensions, is closely linked to the important concept of psychological well-being. Nevertheless, so far, relatively few studies have been conducted on this topic. Hence, the present study aimed to provide a comprehensive model that identifies and classifies the variables affecting employees’ psychological well-being and examines its consequences. To this end, at first, a systematic search and review of scientific databases were conducted to retrieve and screen all related studies. In total, out of 2528 studies, 243 were selected for the review process. These studies were analyzed using a thematic analysis approach, employing Maxqda software in a two-step coding process. Through this process, the main themes and sub themes emerged, forming the model of employees’ psychological well-being. This model consists of four main themes including occupational and organizational factors, individual characteristics, actions, and consequences of psychological well-being. To ensure quality control and validation of these findings, the researchers’ evaluations were compared with some expert opinions, and inter-rater agreement was assessed using the Kappa coefficient. Based on the findings, it can be concluded that psychological well-being is a complex and multidimensional indicator that is influenced by various factors, leading to different consequences. Applying these factors can help improve employees’ psychological well-being within organizations. Key Words: psychological well-being, mental health, job performance, employees 1.Introduction In the modern era, successful organizational managers have acknowledged that optimal job performance depends not only on the employees’ physical health but also on their mental health. Numerous psychological studies have emphasized that the quality of a desirable life, in terms of psychological dimensions, is closely linked to the important concept of psychological well-being. This factor plays a fundamental role in employees' performance and has the power to influence individuals' behavior beyond rules, norms, incentives, and punishments. The characteristics of this psychological variable can determine the desirability or undesirability of individuals' behavior. Ryff (2022) studied individuals who demonstrated desirable performance in both personal and social contexts, and based on her findings, she identified these individuals as having psychological health and balance across a set of components that later became known as the defining dimensions of psychological well-being. Given the limited amount of research in this field, the aim of the present study is to propose a model regarding employees’ psychological well-being. 2.Literature review Psychological well-being has been defined in various ways. This diversity stems from differences in psychological perspectives and the theoretical beliefs regarding the elements associated with psychological well-being, or in some cases, from the findings of some empirical studies (Ruggeri et al., 2020). Discussions about happiness, ideal life and factors that contribute to achieving them have a long history dating back to the time of Aristotle. From his point of view, human beings strive to develop their potential in pursuit of excellence and flourishing (Intellisano et al., 2019). This reflective lifestyle is considered one of the criteria of the indicators of psychological well-being. Effective living does not only mean more positive emotions than negative emotions, but also pays attention to human lifestyle and good and effective living (Xin Kai, 2020). Moving from the initial path towards higher goals, along with engaging in meaningful activities, is the meaning of true well-being (Warren et al., 2018). In psychological well-being, both the content and the way of life are considered. For this reason, psychological well-being, in addition to the criteria of life satisfaction, happiness and the absence of negative emotions, also includes criteria such as mindfulness, the search for inner goals, self-following, and the satisfaction of psychological needs (Yousefi Afrashteh & Hosni, 2022). 3.Methodology The present research is applied in terms of its objectives and uses a systematic review approach in data collection. In the research process, after determining the research objectives and protocol, a comprehensive literature review was conducted to identify studies as the research population in reputable international databases. The criteria for including studies were the relevance of their content to the research topic, studies written in English, studies published between 1978 and July 2023, and accessibility to their full text. The criteria for excluding studies were the lack of relevance of their content to the research topic, studies written in languages other than English, studies published outside the timeframe of 1978 to July 2023, and the unavailability of the full text. After searching in databases and reviewing the references of identified studies, a total of 2528 studies were identified. Through screening and qualitative evaluation of these studies, ultimately 243 studies entered the final review process for information extraction. At this stage, the concepts that reflected the influential factors or consequences of employees' psychological well-being were extracted and recorded, resulting in a total of 404 base codes or concepts. 4.Result Based on the data analyzed, and the results of the systematic literature review as well as the thematic analysis, the psychological well-being model for employees includes four main themes as occupational and organizational factors, individual characteristics, actions, and consequences, along with 49 sub themes as outlined below. Occupational and organizational factors: job and organizational stress, job satisfaction, job and organizational commitment, organizational changes, leadership style, job burnout, work autonomy, customers (clients), organizational culture, job attachment, safety in the work environment, collaborative decision-making, human resource management, and Organizational trust. Conflict of interests: none

Todays, even impressive and continuous innovations in services or products are quickly obsolete due to dynamic markets. Therefore, to overcome the problems of competitive markets, a concept called organizational ambidexterity has been used to describe two conflicting and apparently incompatible processes of exploitation and exploration; Exploitation means improving, expanding, or modifying existing services, markets, and technologies, and exploration means testing or acting on emerging technologies and markets. The present research has been conducted in order to identify the consequences of organizational ambidexterity in Alborz Insurance Company, one of the leading companies in the insurance industry, as a solution to adapt to the complex environment of the insurance industry and improve its short-term and long-term performance. In this research, which is considered practical in terms of its purpose, semi-structured interviews were used to collect information and thematic analysis method was used to analyze the information. The qualitative part was implemented with judgmental sampling and snowball method and interviews with 13 experts and specialists in this field (including managers and academic staff members with education, relevant experience and familiarity with the subject); In the quantitative part, a questionnaire was designed based on the pattern obtained in the qualitative part for ambidextrous outcomes and was completed by the managers of Alborz insurance branches in the country. Quantitative data analysis was done with structural equation model method and with the help of Smart PLS software. Based on the results, the development of organizational ambidexterity will lead to organizational and supra-organizational consequences; At the organizational level, it will lead to financial results, operational effectiveness, stakeholders satisfaction, and competitive ability, and at the supra-organizational level, it affects two social and economic dimensions, which are suggested to managers in this regard, considering the wide range and the important consequences of organizational ambidexterity, put it in priority and at the same time emphasize exploitative and exploratory actions and create coordination and compatibility between these two approaches. Keywords: Organizational Ambidexterity, Exploration, Exploitation and Alborz Insurance Company. Introduction In recent years, the paradigm of organizational ambidexterity (i.e., the ability of a firm to simultaneously pursue exploitation and exploration) has received much attention in management research as a dynamic capability that emphasizes the role of management in adapting, integrating, and reconfiguring organizational skills and resources. (Kasutaki, 2022: 2). At the same time, it is one of the most difficult management challenges, because it requires the ability to simultaneously pursue gradual and discontinuous changes to the extent that the challenge of becoming an ambidextrous organization has been described as "the central paradox of management" (He and Wang, 2004: 481). The idea of ambidexterity creates a relatively complex challenge for organizations; Because it leads to the problem of allocating resources to different and conflicting conditions. Therefore, the current research has been conducted with the aim of knowing the consequences of organizational ambidexterity in the branches of Alborz Insurance Company, which is an important step in persuading and encouraging the managers of this group to spend time and money in order to achieve organizational ambidexterity. Literature Review Duncan used the term organizational ambidexterity for the first time in 1976; However, March's outstanding paper published in 1991 is often credited as the catalyst for interest in the topic of organizational ambidexterity (Georger, 2022: 72). Ambidexterity is considered the organization's ability to be aligned and efficient in managing today's business needs; while simultaneously adapting to environmental changes (Reich and Birkinshaw, 2008: 379). There are three approaches, structural, sequential and contextual, to achieve the right balance in organizational ambidexterity, which often occur in a mixed form (Scholz and Castro, 2022: 7). To implement organizational ambidexterity, four groups of contradictions have been identified in studies; 1. Contradictions resulting from conflicting interests of stakeholders, 2. Contradictions resulting from the desire to maintain control, 3. Contradictions resulting from resource limitations, and 4. Contradictions resulting from the inefficiency of the innovation system (Sahat et al., 1401: 43). The consequences of organizational ambidexterity identified in past studies have indicated significant differences and contradictions; A group of studies considers ambidexterity to be beneficial for the organization and a group has documented the negative effect of ambidexterity for the organization (Dranoff, Izusimova and Meisner, 2018: 677). Methodology The current research is a mixed research (qualitative and quantitative) with a sequential exploratory approach; In terms of purpose, it is considered practical. The statistical community of the research consists of experts and managers of Alborz insurance branches. The tool of the qualitative part is a semi-structured interview and thematic analysis method was used to identify the consequences of organizational ambidexterity. Then, based on the results of the qualitative part, the conceptual model of the research has been tested using a 5-point Likert scale questionnaire. Result Figure 1 shows the conceptual model of the research based on the results of the qualitative part. The extracted model of the qualitative part was tested in the quantitative part. The reliability and validity of the questionnaire was confirmed and checked using the structural model. Table No. 1 shows two hypotheses designed based on the results of the qualitative section at a significance level of 0.95. hypothesis Standard estimate quantity t Test result organizational ambidexterity→ organizational level 0.66 9.33 confirmed organizational ambidexterity→ supra-organizational level 0.53 6.40 confirmed Discussion The term organizational ambidexterity in management is defined as the ability of a company to exploit existing opportunities and at the same time the ability to explore future possibilities for long-term benefits (Priyanka et al., 2022: 1). In the qualitative part, thematic analysis method was used to identify the consequences, which the results were placed at two organizational and supra-organizational levels, then hypotheses were designed based on the results of the qualitative section and confirmed by structural equation modeling. The organizational level includes four organizational themes of financial results, operational effectiveness, customer satisfaction and competitive ability. The supra-organizational level includes two organizing themes of the social and economic dimension. In line with the results of the present research, it is recommended to the managers of the collection to prioritize it, considering the wide and important consequences of organizational ambidexterity; For this reason, the ambidextrous leadership style should be used and at the same time, exploitative and exploratory actions by managers and creating coordination and compatibility between these two opposing approaches should be emphasized; At the same time, managers should play the role of their model in relation to ambidexterity for employees. This research is supported by the Postdoc grant of the Semnan University (number 23276). Conflict of interest: none

industries. The Industrial Internet of Things (IIoT) is considered as a new technology for industries in the fourth industrial revolution, and its acceptance by the workforce has become vitally important. Therefore, it is necessary to identify and prioritize the workforce attributes to increase performance in the Industry 4.0 and implement the industrial internet of things. The aim of this study is to identify the effective factors in improving the efficiency of workforce and to rank them in terms of the components of the industrial internet of thing in the automotive industry. Based on the systematical review of the pertinent literature, key features in the field of workforce were extracted. These key workforce attributes were evaluated according to the criteria of analysis, using the results of the survey done by selected industry experts. In the first step, the options (workforce attributes) and criteria were localized using a survey of experts and the degree of importance of the criteria was calculated using one of the structural models. Next, the workforce components in the studied area were ranked and analyzed employing MATLAB software. According to the results, leadership criteria, communication skills, employee performance level, and management support, respectively, were known as the most important criteria, and network and server familiarity skills, responsibility, proficiency in using data and technologies, and the ability to understand their security as the most key attributes Manpower was introduced. Key Words: CFCS defuzzification method, Edas method, Internet of Things, Iranian automobile industry, workforce 1.Introduction Industrial Internet of Things (IIoT), as an important event in the fourth industrial revolution, can create major changes for industries, and workforce, as the key success factor in the industry, needs to accept these developments and adapt new roles, technologies and responsibilities (Jerona et al., 2017).The workforce plays a fundamental role in the success of industrial innovations and implementation of the Industrial Internet of Things to ensure the realization of the Industry 4.0, which leads to increased competition among industries (Kanan & Garrad, 2020). Therefore, it is necessary to analyze the attributes of the workforce in the Industry 4.0 to adopt this skill-based technology and to increase employee performance (Liao, 2017). Hence, the purpose of the current research is to identify and rank the effective factors in improving the efficiency of workforce in the automobile industry with the components of the Industrial Internet of Things. Literature Review In this study, using the experts’ opinions and the information gained from the Scopus database, the articles published in the last seven years were surveyed. The data from Scopus indicates that the subject of Industrial Internet of Things has been investigated over the years and more than 300 articles have been published in this regard, however, the field of human resources has received less attention compared to other subjects. Therefore, in this database, with the keywords of Industry 4.0, Internet of Things, Industrial Internet of Things, and workforce, the studies that were closely related to the subject of the present study were extracted. Methodology In the first step of this investigation, previous researches related to the components of workforce and the Industrial Internet of Things first were identified using valid databases. Then, from among these studies, 20 attributes of the workforce in the field of IIoT (research options) and 13 criteria were extracted and provided to the experts in the form of a questionnaire with linguistic spectrum ​​to collect the data. The experts expressed their opinions in the form of triangular fuzzy numbers, and then, their answers were localized using the fuzzy Delphi method, and the criteria and options with Values ​​above the limit of 0.7 were accepted. Next, in order to determine the degree of importance of the accepted criteria, the revised Dimetal technique was used. In this method, the criteria in the form of the revised Dimtel questionnaire were provided to the experts, and the experts made pairwise comparisons based on the spectrum of no effect (0), low effect (1), medium effect (2), high effect (3), and very effect (4). After the expert survey, the weight of the accepted criteria was obtained with the revised Dimtel technique and used as an input in the Idas method. Subsequently, the prioritization of workforce attributes as research options was implemented with the IDAS technique. In this way, the fourteen accepted attributes based on ten criteria were provided to the experts of the previous stages in the form of a questionnaire with the relevant linguistic spectrum. Based on the answers of the experts, the fuzzy decision matrix with the fuzzy spectrum was formed. Due to the fuzzyness of the initial matrix in IDAS technique, first de-fuzzification was done by CFCS method and the difuzzy decision matrix was ​​obtained. Result Based on the results of revised Dimetal, the criteria of leadership and communication skills were the most important with weights of 0.1056 and 0.1048, respectively. The criteria of employee performance level, management support were placed in the next level of importance with a slight difference. Their weights were 0.1034 and 0.103, respectively. The next criterion with a weight of 0.1019 was flexibility and adaptability to changing conditions. The criteria of risk and crisis management, relevant work experience, coordination and integration of technology, use of digital technology, value and belief of work culture were less important. According to the ranking results, the attributes of familiarity with the network and servers, responsibility, the skill of using data and technologies, and the ability to understand their security, were among the top three attributes of employees in the field of IIoT in the automotive industry. The attributes of readiness to learn and accept new skills, ability to participate, creative and innovative thinking and spirit, alignment of goals and incentives with desired performance, were in the next priorities, respectively. Additionally, planning skills, high enthusiasm and motivation, decision-making skills, technical skills, time management, coordination ability, analytical and logical thinking, respectively, were among the characteristics of the workforce with lower priority. Discussion In recent years, with the emergence of the fourth industrial revolution, due to the vast advances in technology, we witness a great number of changes. Subsequently, the importance of the Internet of Things, which is considered as an important event in the 4th generation industry, is increasingly growing, which has a major impact on industries. Considering the rapid growth of knowledge and technology, an important part of competitive advantage should be done in the field of technology. It is clear that the expansion of Internet of Things increases attention to the importance of Internet of Things services in the industry. Therefore, the implementation of this technology seems necessary in the industry. Considering this, with the introduction of the Internet of Things in the industry, due to the importance of the role of employees and their acceptance of this development and new responsibilities, we need to strengthen and improve the attributes of workforce in the industry. Therefore, the current research investigates the attributes of workforce, which helps to implement the Internet of Industrial Things, and to improve the effectiveness of the workforce and productivity in the automobile industry. This study can help the automotive industry actors to better understand the role of workforce components and provide the necessary guidance to make decisions about how to manage workforce and implement technologies. Based on the findings of the present study, organizations should pay special attention to the activities and skills of their workforce in order to achieve greater productivity from the 4th generation industry technologies, which are considered important factors of economic growth in countries. They should allocate the necessary investment and provide the factors for the growth of the organization, industry and country. Furthermore, automotive companies can use the findings of this research as a reference in implementing the Internet of Things and in evaluating and improving their performance as well as formulating appropriate policies to achieve excellence. Conflict of interest: none

Productivity is regarded as one of the fundamental drivers of development and progress in the field of sports services. The present study was conducted with the aim of identifying the most influential authors, articles, journals, countries, and universities in the domain of productivity in sports services, using a systematic review approach combined with content analysis. This research employed a mixed-methods design. In the quantitative phase, a scientometric method with a bibliometric analysis approach was used to map and analyze the scientific structure of this field. To achieve this, the data were retrieved and cleaned from the Scopus database using the Publish or Perish software. The data were then processed with Excel for descriptive and preliminary classification purposes. VOSviewer was used to visualize collaboration networks among countries, journals, and co-occurring keywords. Furthermore, advanced bibliometric analyses-including identifying influential authors and articles, publication trends, and thematic clustering-were conducted using R programming language and related packages in RStudio. In the qualitative phase, MAXQDA 2020 software was used to perform content analysis on the top ten articles. The statistical population of this study consisted of all English-language articles indexed in Scopus related to productivity in sports services. The findings revealed that Smith D.D. and Smith D.A., with four publications, were the most influential authors in this field. The article by Green and Oakley (2001) received the highest number of citations and was recognized as the most influential publication. The journal Sustainability (Switzerland), the Netherlands, and Robert Morris University were also identified as leading entities in their respective categories. Content analysis further identified ten key components of productivity in sports services: operational management, service quality, technology utilization, staff empowerment, equipment efficiency, facility management, marketing and promotion, continuous improvement, financial management, and customer relationship management. Based on the results of this study, it is argued that gaining a deeper understanding of productivity components and their relationship with sports services can contribute to improving service quality and increasing productivity in this domain. This research provides practical implications for organizations and decision-makers seeking to enhance performance and optimize service delivery in the sports sector. Key Words: efficiency, scientific analysis, content analysis, sports services 1.Introduction One of the main priorities of sports managers in the current era is related to the issues of productivity and efficiency in sports services, which is considered a vital and prominent issue. In today's world, productivity and its development are among the main goals of organizations and institutions in active life. This issue is especially important in institutions such as physical education organizations, sports federations and other executive organizations that interact with sports facilities, in particular, those related to different groups of population at various levels. It can be clearly stated that productivity, in addition to the effective effects in creating wealth for a nation or organization, allows the organization to pay higher wages to its employees. In fact, it enables managers to provide higher wages and better benefits for employees while maintaining capital efficiency. Generally, salaries and wages paid to employees along with capital return are two key factors in creating national wealth. The countries that have increased their wealth and become increasingly wealthy and developed are the countries that have improved their productivity quickly and timely. Considering the importance of improving productivity in sports organizations, it should be noted that the sports services provided by these organizations and institutions are among the issues that should always be emphasized and that we should be diligent in increasing the productivity of these services. In the last two decades, the quality of sports services has increasingly gained attention even in sports industry, and currently, the quality of providing sports services is considered one of the most important elements in sports marketing. Given the significance of productivity in sports services, this study aims to comprehensively address this issue by employing a mixed-methods research approach (quantitative and qualitative). We strive to identify the components of productivity in sports services and develop a model in this regard. To this end, in the quantitative part of the research, we will use the systematic review method to answer the following questions: Who are the most influential authors? What are the most influential articles? Which are the most influential countries, journals, organizations, and universities in the field of productivity in sports services? Additionally, in the qualitative part of the research, we will use content analysis to identify the components of productivity in sports services. Literature Review Ye et al. (2023), in a similar study, revealed that the performance of inputs and outputs of combined sports resources has not yet been fully effective, and that in some cases, there are significant unreasonable losses. Assessing the improvement in the efficiency of allocating resources to group sports while maximizing the effectiveness of investment in limited resources can significantly accelerate the development of group sports. In another performance-related research, Wang (2022) found that establishing a scientific system for managing sports equipment can lead to improved performance of the equipment management process and enable managers to better focus on their tasks by reducing the difficulties associated with the practice. Azizi et al. (2017), in the research conducted in relation to the quality of sports services, also concluded that there is a positive meaningful relationship between the quality and different dimensions of sport services and the satisfaction of women. Methodology The present study employed a mixed method (quantitative and qualitative) design. This research, in terms of method, is qualitative due to a review of the related English articles published in the fields of productivity and sports services using documentary (library) methods, and regarding the purpose it is applied research since it was conducted using a scientific approach and bibliometric techniques. The statistical community in this research includes 138 English articles in the field of productivity and sports services in sports, published in the Scopus reference database during 1981 to 2023. In the qualitative phase of the study, content analysis was used to identify the dimensions of the productivity of sports services. Hence, the top ten articles in the field of productivity and services in sports, after performing the necessary analyzes and using Rstudio software, were used as the statistical sample of this research. Results The number of articles that deal with the issue of service efficiency in sports has continuously increased significantly over the past few decades. This growth shows the importance and need for extensive and diverse research in this field. Green and Oakley's study, entitled "Elite Sports Development Systems and Playing to Win: Uniformity and Diversity in International Approaches", in 2001 has been introduced as the most influential article in this field, which is the main topic of this research in relation to improving elite sports. The superiority of this article in elite sports is its high number of citations (176) indicates its high importance in terms of scientific productivity. The findings of this research show that Smith D. D. and Smith D. A., with four studies in this field, are among the active leaders in the field and are introduced as the most influential authors. Also, in this research, ten institutions and universities that have played the most important role in the field of sports service productivity were identified and introduced. Additionally, Robert Morris University in the United States, with eight articles in this field, was found to have a great impact in the relevant field and is known as the most influential institution and university. Furthermore, based on the analysis of 83 articles, five countries—the Netherlands, America, Portugal, Great Britain, and Canada—had the most upward trend in this field. Switzerland Sustainability Magazine, which is one of the best magazines in the world today, holds the title of the most influential magazine in the field of sports services by publishing seven scientific research articles on the efficiency of sports services. This journal is one of the few journals indexed in both JCR and Scopus. Moreover, following the content analysis of the top ten articles in the field of sports services which were cited in the Scopus database, the components of operational management, service quality, technology use, personnel empowerment, equipment efficiency, facility management, marketing and advertising, continuous improvement, financial management, and customer relationship management were identified as the key components of this field. Discussion The research on the productivity of sports services shows that increasing productivity in this industry can lead to improving operational management, customer satisfaction, revenue and profitability for organizations, and economic development. Also, proper planning, use of technology, provision of diverse and high-quality services, development of sports platforms, optimal human resource management and promotion of sports culture in society are among the most important factors that can increase productivity in this field. In general, it should be said that productivity in sports services not only helps individuals but also communities to experience a healthier life and achieve higher economic productivity. In a nutshell, it can be said that all organizations, especially sports organizations, can increase the efficiency of their sports services by considering the findings of this research and paying attention to the components of the proposed model which can ultimately guarantee the economic efficiency of their organizations and help them survive in the dynamic environment of today's world. Conflict of interest: none

The present study was conducted to develop a competency model focused on the performance dimensions of employees. This research was applied in terms of orientation and was conducted using a mixed-exploratory method. The qualitative part was conducted with an inductive approach, using the thematic analysis strategy. The statistical sample of this part were 14 human resource management experts, including managers of the human resource management unit of the National Iranian Drilling Company and university professors, who were selected using a non-random, purposeful method and snowball technique. Semi-structured interviews were used to collect the data. Qualitative data analysis was conducted with the thematic analysis approach using the Atread-Stirling coding method. The quantitative part was conducted using a survey strategy in order to validate the proposed model. The statistical sample of this part included 154 employees with superior performance in the National Iranian Drilling Company in the last 5 years, who were selected using the convenience sampling procedure. Quantitative data analysis was conducted using Smart PLS3 software and confirmatory factor analysis method. The findings from the data coding showed that the competency development model, focused on employee performance dimensions, includes 80 basic themes that are categorized into 22 organizing themes and five overarching themes. The overarching themes include task competencies (i.e., knowledge, technical skills, appropriate behavior, work commitment, coaching, and leadership); attitudinal competencies (including engagement in work, career calling, psychological competence, collectivism, and job commitment); contextual competencies (i.e., organizational citizenship behavior, helping colleagues, selflessness, and enthusiasm); innovativeness (encompassing proactivity, creativity, problem-solving ability, and idea presentation); and finally adaptive competencies (i.e., adaptability, emotional intelligence, resilience, and job stress management). The quantitative data analysis confirmed the validity and fit of the model. Key Words: job performance, task performance, contextual performance, employee competence 1.Introduction Competence is considered as one of the main elements in determining the overall productivity of the organization. For any business to succeed, ensuring that its team members have the necessary skills and qualities for their assigned roles is critical. It is common for businesses to define specific areas of competency that ensure success in specific situations or roles. An important part of employee competence is related to performance, which is referred to as performance-oriented competence. A primary goal of any professional, whether a manager or an employee, is to achieve high performance at work while supporting the success of colleagues and teams. Consequently, the concept of employee performance (sometimes called job performance) is an important element in management. However, although the term job performance is a widely used tool in management, organizations rarely address what job performance actually is, what dimensions it includes, and in which areas of organizational performance it is important. Given this description, it seems more logical, it seems more logical to prioritize competencies related to performance dimensions rather than focusing solely on job performance. This study is an attempt to develop a model of competencies aimed at the functional dimensions of employees. The main goal of this research is to answer the following research question: What are the characteristics of a competency development model aimed at the functional dimensions of employees.? Literature Review There is a broad consensus in the scientific community that job performance consists of two interacting components: task performance and contextual performance. According to Putra et al. (2024), task performance describes the main job responsibilities of an employee. It is also called "role prescribed behavior" and is reflected in specific work results and outcomes as well as their quality and quantity. Contextual performance goes beyond formal job responsibilities. Also known as "optional extra-role behavior", contextual performance is reflected in activities such as coaching colleagues, strengthening social networks in the organization, and doing more for the organization (Potra et al., 2024). A part of the employees' functional competencies is related to the issue of compatibility and adaptability. Previous studies have shown that when employees achieve a certain amount of perfection in their assigned tasks, they try to adapt their attitude and behavior to the different requirements of their job roles (Soni et al., 2022). In their study, Putra et al. (2024) showed that the attitudinal preparation of employees - for example, through empowerment - plays an effective role in improving performance in both task and extra-role dimensions. Sharma et al. (2024) investigated the effect of workplace stress on employees' job performance. While emphasizing the negative impact of stress on performance, this study revealed that people who have the power to manage workplace stress show better job performance. Mazzetti et al. (2023) in a meta-analysis study showed that job involvement has a negative relationship with turnover intention among employees. Gunawan et al. (2023) conducted a study titled the effect of leadership style on the contextual performance of employees. The results of this survey study showed that leadership style has a significant effect on the contextual performance of employees. Methodology This research was applied in terms of orientation and was conducted using a mixed-exploratory method. The qualitative part was conducted with an inductive approach, using the thematic analysis strategy. The statistical sample of this part were 14 human resource management experts, including managers of the human resource management unit of the National Iranian Drilling Company and university professors, who were selected using a non-random, purposeful method and snowball technique. Semi-structured interviews were used to collect the data. Qualitative data analysis was conducted with the thematic analysis approach using the Atread-Stirling coding method. The quantitative part was conducted using a survey strategy, in order to validate the proposed model. The statistical sample of this part included 154 employees with superior performance in the National Iranian Drilling Company in the last 5 years, who were selected using the convenience sampling procedure. Quantitative data analysis was conducted using Smart PLS3 software and confirmatory factor analysis method. Result In the first stage of the analyses (open coding), the data were examined at the sentence and phrase level for each of the interviews. A total of 80 primary codes were extracted from the transcripts. In the next step, we convert these open codes into basic themes. In this way, the 80 counted codes were categorized into 21 basic themes. Based on the analysis of the qualitative data, obtained from in-depth and exploratory interviews and subsequent coding, the dimensions and components of the competences related to the functional dimensions of employees were identified according to the participants’ insights. Task competencies emerged as the first category of themes identified in the competency development model aimed at the functional dimensions of employees. Based on the data analysis, it was found that part of the performance-oriented competencies is related to the attitudinal competencies of the employees. Contextual competencies represent the third theme in the competency development model aimed at the functional dimensions of employees. Moreover, innovation emerged as another key theme identified in the competency development model. Lastly, adaptive competencies were identified as the last organizational theme identified in the competency development model focused on the functional dimensions of employees. Discussion The model presented in this research is one of the first models developed in the country that specifically addresses the competencies contributing the performance of employees. The knowledge-enhancing contribution of this research lies in advancing beyond the well-known model of task performance/contextual performance by offering a more sophisticated and comprehensive model. This model, developed through an exploratory approach, encompasses five main components and 22 subcategories. Conflict of interests: none

People's travel behavior is reflected in their choice of transportation modes and is influenced by various factors. Travelling by private car often leads to numerous problems. Therefore, policymaking to shift citizens’ travel behavior from private car use to public bus transportation is important. Hence, the purpose of this research is to examine the travel behavior of Tehran’s residents using a system dynamics simulation model. Accordingly, after identifying the main variables affecting travel behavior through library studies and expert interviews, the hypotheses of the model were formulated. Subsequently, by drawing the cause-and-effect diagram and the stock and flow model, the relevant mathematical equations were derived and validated, and the model was then tested for accuracy and reliability. Subsequently, policies related to the three variables of the number of BRT buses, access to BRT buses and parking capacity were implemented through several scenarios. The results revealed that increasing the rate of parking construction does not lead to favorable results. Moreover, the increase in the number of BRT bus fleet alone cannot have an effective role either under current conditions or when combined with the scenarios involving reducing or increasing parking construction rates. Reducing the rate of parking alone has favorable results. Similarly, increasing the number of BRT stations yields positive results. Moreover, implementing both scenarios simultaneously- reducing the rate of parking development and expanding BRT stations- represents the most effective scenario among those analyzed. Key Words: public transportation, car-oriented, travel behavior, system dynamics model 1.Introduction The use of private cars has become a major challenge for cities worldwide due to its negative externalities, such as traffic congestion and environmental pollution. Achieving sustainability in transportation and continuing economic development requires reducing the use of private cars and increasing dependence on public transportation. In Tehran, according to the obtained statistics, the demand for daily trips, the share of rides, the demand for daily car trips and the number of private cars used per day are all increasing. The current statistical situation indicates the important role of planners and policy makers in this area. In fact, travel planning seeks to create a balance between travel supply and demand, where the first depends on the capacity of the transportation network and the second on the amount of travel needs of users. Knowing the travel demand helps the planners of this area to develop the necessary infrastructure according to the actual demand or to use the maximum capacity of the existing transportation network. Understanding the factors affecting the choice of public transport travel method is very necessary for the purpose of transport planning. Therefore, this article specifically examines the long-term effect of travel supply policies (i.e., parking capacity, access to BRT stations and fleet) on the competitive behavior between choosing private cars and BRT buses in Tehran. Literature review In recent years, numerous studies have been conducted to investigate the factors influencing on the decision-making regarding the choice of travel method. Zhou and his colleagues (2023) investigated the necessary policies to reduce the use of private vehicles in an urban area in the Netherlands using an activity-based travel demand model. The results indicate that the improvement of public transportation services and small transportation network increase the potential of displacement hubs in terms of stabilizing travel displacement patterns. Also, limiting parking capacity and increasing parking costs in city centers are especially useful strategies for reducing car use. McSlan and Sperry (2023) investigated the relationship between parking requirements and car ownership in Swedish municipalities. The results of this study showed that reducing parking minimums can be an effective policy to reduce car ownership. Khosravi et al. (2020) used system dynamics modeling to evaluate transportation demand management policies in the center of Isfahan. In this research, incentive and restriction policies were investigated in the central commercial area of ​​Isfahan. Effective transportation policies were implemented for ten years and were ranked based on three indicators of air pollution, energy consumption and traffic flow. The results revealed that completing the metro network, developing the BRT network, improving bicycle facilities, implementing road pricing, increasing parking fees, improving bus and taxi services, enforcing the even and odd policy, and encouraging car sharing are among the most effective policies in the center of Isfahan. Method The present study aims to provide a dynamic simulation model of Tehran residents’ travel behavior using advanced modeling tools, in order to conduct a more detailed analysis of the residents' travel mode choices and their consequences, thereby helping policymakers improve the behavioral anomalies in the transportation sector. In this research, the method used was descriptive and modeling in its purpose. Additionally, the variables influencing travel mode choice were identified through a review of the research literature and experts' opinions. These variables were then incorporated into a system dynamics model, enabling simulation and examination of different policies over time. This research was conducted in Tehran, using the data collected from the Tehran City Transportation Organization on the share of Tehran residents’ trips made by private cars and BRT buses between 2011 to 2021. Since the system dynamics method consists of five steps, the model presented in this research was structured accordingly. The first step in this process was to identify the problem and its boundaries. In this step, the reference variable and its past behavior were also examined. Based on this analysis, the number of private cars was identified as the main issue that this research aims to reduce. The second step focused onformulating dynamic hypotheses. In this step, the main variables affecting the problem were examined and the boundaries of the model were determined. In this regard, after reviewing the research literature and examining previous studies, a semi-structured questionnaire was used to get the experts' opinions. The experts were first asked the main questions, and during the interview, additional questions were posed as needed, based on the flow of the discussion. Through this process and using the opinions of subject matter experts, the research variables were identified and refined for use in the next stages. Drawing on the theoretical foundations of research and experts' opinions, and based on a clear understanding of the problem, cause-and-effect loops were designed and gradually a complete diagram of cause-and-effect loops was created, ultimately providing a simplified representation of the real-world system. In this regard, one of the influential factors contributing to the undesirable behavior of choosing a private car is its high level of attractiveness. After formulating the hypotheses, the key variables were identified including parking capacity, number of BRT buses and number of BRT stations as the independent variables and the number of private cars used per day as the dependent variable. Then, how these variables affect each other were investigated and the cause-and-effect loops were drawn. The next step was to simulate the model in the relevant software. Once the main hypotheses and the system boundaries were formed, the model could be implemented. By entering the mathematical equations and identifying the stock, flow and auxiliary variables, the stock-flow diagram was then developed. Finally, the model was simulated and implemented. By analyzing the changes in the behavior of the model over time and comparing it with what actually happened in the past, the validation of the model was done to validate its ability to predict future behavior. In this research, the status of the error index and the coefficient of determination of 97% confirmed the validity of the model for predicting the future behavior of the model. Also, another required measure to validate the model was to analyze its sensitivity in the implementation of different scenarios. Other validation tests, including the structural evaluation test, system boundary adequacy test, dimensional consistency test, equation logic test, and model behavior prediction test were also performed and had acceptable results. Result After simulating and examining the behavior of the model components over the desired thirty-year period, the values ​​of the different variables of the model were adjusted and their effects were analyzed on the main variable, that is, the number of private cars used per day. In addition, the time step of model 1 and the time unit of the year were defined. By changing the values ​​of parking construction rate, BRT bus purchase rate and the number of BRT stations, eight scenarios were compiled. The outputs of Vensim software regarding the first scenario or the increase in the rate of parking construction showed that the number of private cars has increased significantly with the increase in the rate of parking construction. In the second scenario which involves the reduction of the parking construction rate, the results indicated that the number of private cars will increase at a slower rate compared to the current situation. In the third scenario, that is, increasing the parking rate and increasing the BRT bus purchase rate at the same time, it was observed that the simultaneous application of increasing the parking rate and increasing the BRT bus purchase rate leads to an increase in the number of private car use. Notably, the increasing slope of the number of private cars in case of simultaneous application of the changes did not change significantly compared to the scenario in which only the parking construction rate was increased. In relation to the fourth scenario, addressing the increase in the purchase rate of BRT buses, the simulation results showed that the number of private cars after increasing the purchase rate of BRT buses was not different from the existing conditions, which means that with the increase in the purchase rate of BRT buses, the number of private cars will still be increasing with the same slope of the existing conditions. Regarding the fifth scenario, that is, reducing the parking rate and increasing the BRT bus purchase rate at the same time, it was observed that the simultaneous application of reducing the parking rate and increasing the BRT bus purchase rate led to an increase in the number of private cars but at a slower rate than under the existing conditions. In the sixth scenario regarding the increase in the number of BRT stations, the results also showed that with the increase in the number of BRT stations, the number of private cars increased but at a slower rate. Moreover, as regards to the seventh scenario, or increasing the rate of parking construction and the number of BRT bus stations at the same time, after performing the simulation, it was observed that simultaneous increase in the rate of parking construction as well as the number of BRT stations leads to an increase in the use of private cars. In this case, the increasing trend in the number of private cars, compared to the situation where only the rate of parking construction was increased, did not change significantly, showing a slight improvement. In the eighth scenario, the simulation results after reducing the rate of parking construction and increasing the number of BRT bus stations at the same time indicated a lower slope than under the existing conditions, leading to the best performance compared to the other seven scenarios. Discussion The practical findings of the current research show that, under current situation, improving access to the BRT bus stations is more critical than expanding the BRT bus fleet. Additionally, simultaneously purchasing BRT buses and building new parking facilities cannot contribute to the reduction of private car use. This finding is important for urban planners as the simultaneous implementation of these two policies fails to encourage a shift toward BRT use. As long as the time of searching for parking decreases due to the construction of new parking construction and private cars remain attractive, merely buying BRT buses will not significantly change travel behavior toward public transportation. Finally, the practical findings reveal that choosing the BRT bus travel mode compared to a private car is only possible when, in addition to strengthening the BRT bus infrastructure, we overlook expanding car infrastructure. Helping the managers of different areas of the municipality to observe the effects of independent policies is another practical finding of this research since the results showed that contradictory decisions can lead to the loss of desirable results and the imposition of heavy costs. Conflict of interests: none

The purpose of the present research is to conceptualize and apply the silent cries of organizational talents trapped in the glass barriers of promotion. This work is guided by a fundamentally applicative goal and is examined through a pragmatic, parasitological lens during the exploratory phase of model development. In the testing phase, interpretive type is positivist. |This study employs a thematic analysis strategy to analyze the qualitative data, using Clark's method, supported by Maxqda. In the qualitative part of the research, targeted sampling was conducted with the cooperation of senior managers of government organizations and interviews were held with fifteen senior managers. The quantitative statistical population included managers and experts of the Ministry of Interior. In the qualitative stage, the main items and components were identified using SPSS software and exploratory factor analysis. In the quantitative part, simple random sampling was carried out and the sample size was determined using GPower software at a significance level of 0.05 and a test power of 0.95, resulting in a final sample of 140 participants. The content validity was confirmed by experts and the construct validity of the measurement model structure was assessed through Average Variance Extraction, the Fornell and Larcker criterion, and the multitrait - multimethod matrix. The reliability of the model was checked and confirmed using Cronbach's alpha coefficient. The path analysis of the proposed model was conducted using SPSS and SmartPLS software. According to the research results, 20 indicators (items), 6 subcategories, and 3 main categories were identified and validated. Key Words: internal talents, thematic analysis, Structural Equation Model 1.Introduction In today’s changing world, life is marked by constant changes and transformations. Organizations, as part of this dynamic environment, must keep pace with these changes, otherwise, they risk falling behind in global competition. Preparing organizations is not limited to upgrading equipment and technology; Rather, they must carefully and prudently retain their employees, who are their most valuable assets. Modern organizations, playing an active role in driving change, strive to direct the talents of their employees toward organizational success. In this situation, talent management is of particular importance to senior managers since using skilled and motivated labor is the key to achieving a competitive advantage. However, this issue, despite its importance, has not been adequately studied in theoretical and practical fields. Talented human resources are the pride of any organization and are considered the driving force of efficiency and creativity. Yet, are the voices of these talents always heard? Is there a way for them to grow and flourish in the organization? Many of these talents are trapped within the glass walls of organizational dead ends. Despite all their abilities and potential, there is no way for them to grow and flourish. Their silent voices are not heard by anyone. It is as if they are screaming in a vacuum and their voices are not heard. 2.Literature Review A review of the research literature reveals that most studies have focused on human resources as organizational talents and their management. Numerous researchers have examined the effects of talent management and adherence to meritocracy principles, making them the basis of their work. However, no research has been conducted on the silent cries of organizational talents and how to promote them in organizations. Related researches include the study of Kaliannan et al. (2023), titled "Inclusive Talent Development: A Systematic Literature Review", which identifies the research gaps in talent management and highlights the need for organizations to effectively manage and promote talents to grow and gain a sustainable competitive advantage. Aljbou and French (2022), in their article "A Multi-Level Talent Management Framework: A Systematic Review", examine different perspectives and approaches to talent management, demonstrating that a combination of these perspectives leads to improved organizational performance. Angas et al. (2022), in "A Review of Meritocracy in the Chinese Political System," analyze the strengths and weaknesses of the meritocratic system compared to dictatorship and attribute the progress of societies to the attention to meritocracy and the right choice of managers. Kast (2021), in his doctoral dissertation "Organizational Structure and the Logic of Merit," states that holding sensitive positions requires experience and expertise. He criticizes that appointing managers based on political relations leads to organizational problems. Methodology The current research adopted a pragmatic philosophical stance and employed a combined inductive-deductive approach. The inductive method was initially utilized in the exploratory phase, followed by the deductive method in the validation phase. This combination of research strategies provides a qualitative-quantitative integration with an exploratory and sequential approach to the topic. The primary objective of this research was to conceptualize and identify the dimensions and indicators associated with the silent cry of organizational talents trapped in the glass ceiling of advancement. Qualitative Phase: In the qualitative phase of the research, thematic analysis was employed to identify the main- and sub-themes. Clark's method and MAXQDA 2023 software were utilized for the analysis of the qualitative data. Purposive sampling was conducted in collaboration with senior managers of public sector organizations, and interviews were held with fifteen senior managers. In the qualitative phase, the main statements and components were identified using exploratory factor analysis using SPSS software. Quantitative Phase: In the quantitative phase, structural equation modeling was performed using the partial least squares (PLS) approach. Random sampling was employed for the quantitative phase, and the sample size was determined using G*Power software at a significance level of 0.05 and a test power of 0.95, resulting in a final sample of 140 participants. Content validity was confirmed by experts, and the construct validity of the measurement model (divergent validity and convergent validity) was assessed using the Average Variance Extracted (AVE), Fornell-Larcker, and multitrait-multimethod matrices. The reliability of the model was examined and confirmed using Cronbach's alpha coefficient Result Given the mixed-methods nature of this research, SPSS software and exploratory factor analysis were employed in the qualitative phase to identify the primary and secondary categories and components (as an innovation in this study). Twenty initial indicators or codes were extracted and conceptualized into six sub-dimensions using exploratory factor analysis and MAXQDA software.These six factors or sub-dimensions were categorized into three main components or factors: 1)Deviation from organizational ideals due to complex relationships in manager selection; 2)Erosion of commitment and expertise under the shadow of informal political relationships; and 3)Managerial appointments based on illogical criteria, leading to stagnation, inactivity and despair. Additionally, the research findings in the quantitative phase indicate that the significance coefficients for all relational components of the model are below 0.05. Therefore, the research model is confirmed with 95% confidence. Discussion Previous research has focused on various aspects of human resources and employees’ motivation techniques. By emphasizing the importance of transparency, commitment, and meritocracy in the manager selection process, this study offers a fresh perspective on talent management and highlights the crucial role of managers in leveraging internal organizational talents. It is proposed that two fundamental factors be considered when selecting and appointing managers, particularly those who have a significant impact on organizational decisions. These two factors are: 1- Religious commitment to the principles of the Islamic Republic of Iran and belief in the principle of absolute guardianship of the Islamic jurist (Velayate Faqih) 2-Technical and scientific expertise, adhering to the principle of meritocracy These two conditions, as essential and complementary elements in the selection of managers, especially those who have a significant impact on important organizational decisions, must be taken into account. The absence of either of these conditions in managers can lead to demotivation among talented individuals and create obstacles to advancement, with negative consequences for both the organization and society. Conflict of interests: none

The emergence of the Fourth Industrial Revolution (Industry 4.0) and its tremendous impact on industries and production systems have introduced new challenges in the field of quality management. These technological advancements compel quality specialists to revise the traditional methods of quality management. Quality 4.0 represents an updated version of the traditional quality management that seeks to improve traditional quality control methods using digital tools of Industry 4.0. Design of experiment is also an important tool in the statistical data analysis in the quality management area. This research attempts to provide customer satisfaction focusing on developing the quality 4 in the context of Fourth Industrial Revolution. Therefore, developing tools that can effectively respond to the diverse demands and needs of customers seems to be a key factor for industries seeking to strengthen their economic position, reduce vulnerability to external factors and enhance organizational sustainability. This paper, firstly, focuses on the design of experiment field and describes the existing opportunities and challenges. Then, after introducing the pillars of the Fourth Industrial Revolution, the study outlines the concept of Quality 4.0 along with its structure and requirements. Additionally, it presents a method for designing experiments within the Quality 4.0 environment and explains its algorithm step by step. Overall, this research introduces a systematic approach for identifying and extracting the key parameters required for the design of experiment. It introduces a model for design of experiment within the Industry 4.0 environment. The research method is based on the review of published literature, in which the methodologies of the references are validated using relevant case studies. This research is organized in three main components: 1) Identifying Industry 4.0 requirements; 2) Extracting key parameters for designing experiments focused on product development and customer satisfaction; and 3) Implementing the design of experiments in the context of the Fourth Industrial Revolution. Key Words: customer satisfaction, design of experiment, Fourth (4.0) Industrial Revolution, Quality 4.0, product design 1.Introduction The design of experiments is a quantitative tool, a subset of quality, which is used for the statistical optimization of system performance, which is used to manage the value of the input variables to reach the optimal values ​​of the test sample and the goals of the tests. The Fourth Industrial Revolution has led to fundamental changes in production methods and the emergence of new tools and concepts such as the Internet of Things, smart products, smart factories and cyber security. The industrial revolution rests on two basic pillars of flexibility: one involves adapting to extensive economic and social changes through decentralization and organizational flexibility, and the other involves responding to technological pressures in industry, such as the emergence of smart phones and 3D printers. Quality 4. is a developed approach that is a combination of traditional quality methods with new technologies. Relying on artificial intelligence, Quality 4.0 seeks to respond the diverse needs of industries undergoing fundamental changes with the emergence of the Fourth Industrial Revolution. Hence, this research aims to propose an effective model grounded in the literature and informed by Design of experiments, with the aim of: 1) keeping pace with the developments of the Fourth Industrial Revolution; and 2) enabling product design based on customer experiences to increase customer satisfaction. Literature Review Fractional factorial designs, Taguchi design of experiments, composite central design, Box-Benken design, robust parameter designs, computer-aided designs, design of experiments using response surface methodology (Winer, 1962; Paulo Davim, 2012; Antony et al., 2006) are among the most important methods of designing experiments. The modular, smart-factory model of the Fourth Industrial Revolution-built on cyber-physical systems that monitor physical processes-creates a virtual representation of the physical world that enables decentralized decision-making. The requirements of the Fourth Industrial Revolution, derived from the research of Ustundag and Cevikcan (2018) on the Internet of Things, cyber-physical system, robotic developments, the role of augmented reality, and the roadmap of technology and intelligent development, are introduced as the defining characteristics of this new industrial era. Quality 4 can be considered as the improved approach of the previous quality models, emerging in parallel with the technological advancements of the Fourth Industrial Revolution. Targeting the satisfaction of customers and continuous improvement, it has a direct relationship with lean production and 6 sigma and comprehensive quality management (Chiarini & Kumar, 2021). The need to advance toward Quality 4. Has been driven by the Fourth Industrial Revolution, the emergence of new digital concepts and the ineffectiveness of the traditional management approaches in addressing these needs. Previous studies, including those by Hong et al. (2022), Al-Zahrani et al. (2021) and Nikolajan et al. (2019), consider the basic components of Quality 4.0 as a requirement for the successful implementation within the context if Industry 4.0. Methodology The main goal of this research is to develop an accurate algorithm capable of determining product designs according to the experiences and desires of customers. Quality 4.0 serves as a powerful tool that can keep up with the developments of the Fourth Industrial Revolution. It achieves this, on the one hand, by monitoring the production process, and on the other hand, by connecting to the marketing process and feedback to customers' needs, to ensure customer satisfaction and achievement of production goals and of stakeholders’ objectives. The key requirements of Quality Management 4.0 can be summarized as follows: identifying the primary stakeholders, defining strategic business goals, assessing available resources, analyzing competitors, recognizing key drivers such as customer satisfaction. Additionally, the architecture of the Fourth Industrial Revolution and its implementation within business planning necessitate attention to elements such as big data, cyber-physical systems, Internet of Things service, digitalization, and artificial intelligence. The increasing intensity of data flows and the size of the analyzed data set require a review of the traditional methods of designing experiments in the context of Industry 4.0. In this research, a new seventy- step experimental design method tailored to the requirements of the Fourth Industrial Revolution is proposed. The key stages include: understanding the requirements of Industry 4.0; making a list of iterative optimization and artificial intelligence methods; combining one optimization method with an artificial intelligence method (according to the characteristics of the process); matching the Industry 4.0 architecture with the selected case study; defining the purpose of the research (design of experiments); and determining the most effective tools for recording data in Quality Management 4.0. The procedure further involves understanding the process, specifying the factors, determining the levels of the factors/response variables, establishing the relationship among Quality 4.0 tools through artificial intelligence. Additional steps include developing a predictive model, finding machine parameters, ranking and training data using artificial intelligence, applying different machine learning models to predict part quality, utilizing inspection methods for components of complex 3D designs, and selecting and specifying high-tech equipment. To achieve the objectives above, this method was employed to convert the classification result of the factor levels into a continuous model, specify the experimental design method, and compare the results with the design goals. This experiment-based method is structured into five stages: 1) defining the problem, 2) identifying factors and response variables, 3) designing experimental tests, 4) conducting the experiments, and 5) analyzing and interpreting the results. Result In this research, by examining traditional methods of production and aligning them with digitalization, technological integration, and globalization, striving to get a major share of the market, we defined the Fourth Industrial Revolution and its requirements in various industries. The study showed that, just as traditional quality management has been a suitable tool to strengthen traditional production, Quality 4.0 also plays this role in the context of Industry 4.0. In order to establish it, we need to implement quality components and dimensions. The experimental design methods with the approach of customer satisfaction within the Fourth Industrial Revolution, demonstrate clear advantages over traditional customer satisfaction tests. This approach is evaluated based on parameters such as flexibility, distance between the designer and customers, the level of customer satisfaction, the possibility of involvement in the design process, the speed of design, the quality level of risk management, reliability, and the final price of the product. Compared to the traditional design and testing methods, this approach not only enhances these parameters but also increases the capability and competitiveness of industries in today's challenging world. Discussion In fact, this research is based on four principles: Developing a model for experimental design in the Fourth Industrial Revolution as a robust statistical and quantitative quality analysis tool that effectively reduces costs and increases the efficiency of intelligent industry. Providing optimal indicators for experimenters in order to select the most suitable method among the various methods of designing experiments. Offering a suitable algorithm to find the optimal criterion of customer satisfaction. Using experimental design as a quantitative tool to determine factors which increase customer satisfaction in the context of Industry 4.0 as a vital element for the sustainability of industries in today’s challenging competitive market. Conflict of interests: none