فهرست مطالب ebrahim chirani

Social media in companies helps facilitate the flow of information, share knowledge within the company, strengthen the company's interaction with customers, and improve the company's internal and external cooperation. Therefore, relying on the development of media and social media, businesses and companies have gained unique opportunities to communicate easily with their customers in a dynamic manner. Considering the developments in the field of digital technology and the development of social media, the competences and capabilities of marketers in order to optimally use these tools and keep pace with these developments in the insurance industry are vague and unclear. In the last two decades, Iran's insurance industry has faced major structural changes such as privatization, liberalization and changes in regulatory frameworks. Despite such developments, the country's insurance industry is still facing a low penetration rate and inappropriate development indicators compared to global and regional statistics. The low level of these indicators can be attributed to the weak performance of companies in formulating and implementing strategies suitable for the insurance industry and market in Iran. The emergence of insurance technology has provided an opportunity to increase the sales position of insurance services by gaining the trust of people and industries, and by relying on these services, individuals, businesses and entrepreneurs can increase the security of business and economic activities. Therefore, the main purpose of the research is Identifying the factors affecting the competencyies of future marketing specialists for the development of the insurance industry.

In terms of purpose, this research is in the category of applied-developmental research. This study has two statistical populations. The first statistical population includes previous researches related to the subject of the present study and the second statistical population includes managers, sales representatives and marketers active in different insurance companies who have at least 5 years of work experience in sectors related to the insurance industry. The selection of samples was done with the purposeful sampling method and out of 36 articles, only 28 articles related to concepts such as competencies and skills of the future of marketing were selected. Also, semi-structured interviews with 6 questions were continued until theoretical saturation was achieved in the 12th interview. Using the qualitative method of theme analysis, the dimensions, components and indicators of the competence model of the future marketing specialists in the insurance industry will be identified. After identifying the themes, three-stage open, central and selective coding was done manually and it was shown in the theme grid. The statistical population of the research consists of managers and active marketers in different insurance companies of the country. Non-probability methods are often used in qualitative research to select samples. With this attitude, the selection of experts in the qualitative stage is done according to two criteria: having at least 5 years of work experience in the sectors related to the insurance industry and having a master's degree or higher (business management and insurance) and the number of will be determined based on reaching theoretical saturation in the interviews. Therefore, the interviews and data collection will continue until the interviewees mention new things about the factors affecting the competences of future marketing specialists for the development of the insurance industry. Otherwise, the interviews will be stopped and theoretical saturation will be achieved.

Based on the findings, 7 organizing themes and 68 basic themes have been identified, which are: the emergence of dynamic business models with 2 sub-organizing themes and 6 basic themes, entering the era of artificial intelligence with 2 themes Sub-organizer and 6 basic themes, environmental factors with 2 sub-organizer themes and 5 basic themes, development of insurance marketers' capabilities with 4 sub-organizer themes and 12 basic themes, insurance industry development with 2 sub-organizer themes and 6 basic topics that were included under new general and specialized competencies comprehensive topics and were shown in the topic network. Then, the conceptual model was presented. Then, according to the basic themes and the identified organizing themes, a model in the form of a theme network was presented to show the competencies of future marketing specialists.

This research responded to the previous deficiencies and gaps in studies related to the competences of insurance marketers by examining various factors and emphasizing the changes in the business environment. Therefore, strengthening the dimensions and components of the model through planning and using it in attracting and training insurance marketers, evaluating their competences, and creating a database of competencies marketers as a part of the administrative system's memory. It can be a facilitator for the better implementation of the research model framework and the realization of transformation and development of the insurance industry in the country.

This article aims to forecast Iran Cooperative Development Bank's profit/loss using a two-stage collective learning method. Employing machine learning for profit and loss prediction is a novel approach to numerical computations, aligning with the article's goal of leveraging big data. Hence, we employ a two-stage collective learning method utilizing Support Vector Machines, Decision Trees, and Weighted Averaging models for learning, testing, and predicting the profit/loss of the Cooperative Development Bank.

In the initial stage of machine learning, Support Vector Machines, and Decision Trees serve as the base models, while the second stage employs a weighted averaging approach. The combination of base learning models was utilized to initially test the prediction process on the performance of 35 branches of the Cooperative Development Bank nationwide from 2012 to 2021. The two-stage machine learning method relies on the utilization of 12 variables grouped into 5 factors for the task. These variables encompass interest-free loans and short-term deposits, deposit interest expenses, total customer deposits, income from facilities and investments, common income, cash balances, administrative expenses, long-term deposits, non-common income, asset depreciation expenses, and the bank's size. Relevant data for the study was obtained from the financial statements of 35 branches of the Cooperative Development Bank spanning the years 2012 to 2021. To minimize prediction errors and facilitate ratio comparisons, all indicators mentioned were adjusted relative to the total value of the bank's assets. Furthermore, to minimize prediction errors and enhance the comparability of ratios, all the mentioned indicators were adjusted in proportion to the total value of the bank's assets. In the initial stage of applying this method, two machine learning models - Support Vector Machines and Decision Trees - were employed, followed by a weighted averaging approach in the second stage.

This article contrasts linear regression with machine learning approaches for predicting the Cooperative Development Bank's actual profit/loss. The results reveal notably high-performance accuracy, evidenced by an MAE metric of 5.66 and an MSE metric of 620.34. Additionally, the correlation between training data and predictions from the two-stage collective machine learning stands at 0.9977. Following this method's performance assessment, it is subsequently employed to predict the Cooperative Development Bank's profit/loss for the years 2022 to 2027.

The results, showcasing the high efficiency of the two-stage collective machine learning method, suggest that managers can employ these approaches for profit/loss prediction in banks. Based on this method, and under normal conditions without abnormal or non-normal circumstances, the obtained results indicate a prospective decrease in the accumulated losses of the Cooperative Development Bank in future years, leading to an ultimate increase in profits by the year 1405. The results of data analysis reveal that the average ratio of the net profit or loss of the bank to its total assets has been computed in a manner that reflects the average profitability of the bank branches over the research period.

Predicting time series of financial markets is a challenging issue in the field of specialized studies of time series and has attracted the attention of many researchers. Due to the presence of big data, this issue has led to the growth of developments in the field of machine learning models. Due to the importance of this issue, in this study, by using the comparison of different machine learning models such as random forest approaches, support vector machine, artificial neural network and deep learning-based recurrent neural networks to investigate the ability of different machine learning models in prediction. The total index of Tehran Stock Exchange during the period 2013 to 2020 has been discussed. The prediction results of 1, 3 and 6 day courses for the out-of-sample period show that the machine learning method based on the long short-term memory (LSTM) network, a recurrent neural networks, has a better result compared to other models.

The present study investigates the relationship between acquired factors and monetary disorders for the first time in Iran. The statistical population of the banks are members of the Tehran Stock Exchange. The sample size is based on new methods based on experiments and using sample power software and according to the type of research relationship hypothesis which is a combination of two scale variables but abnormal, Spearman test has been used. The first hypothesis of the research based on the relationship between the two variables of financial knowledge and monetary disorders showed that there is no significant relationship between these two variables and the first hypothesis of the research was not accepted. However, based on the results, the second hypothesis has a significant relationship between the variables of attitude to planning and monetary disorders, which shows a negative relationship between the variables. The second hypothesis was accepted as research. Therefore, based on the acquired origin of variables has monetary disorders.

Today, the insurance industry plays a significant role in the prosperity of the economy, so paying attention to the creation of knowledge can play a significant role in increasing the penetration rate of insurance. Therefore, the main question of the current research is how to design and explain the model of the elements of customer knowledge co-creation in the insurance industry? In order to answer this question, the present research aims to identify the elements of the customer knowledge co-creation model in the insurance industry in the first stage, and in the next stage to test the relationship model of the elements of customer knowledge co-creation in the insurance industry, and based on the results of Data analysis will provide solutions to the managers of this industry in order to make decisions and policies related to knowledge creation and as a result promote and improve insurance products and services and increase the penetration rate of insurance in the society.

Literature Review:

Knowledge Co-Creation has been described as an act of collective creativity, with applications ranging from product and service design to more abstract spheres of value creation taking place between two or more individuals who may or may not belong to the same actor group (Amann & Rubinelli, 2017). “Customer knowledge Co-creation is defined as the collective ability of group members to analyze, interpret, reconfigure customer-related knowledge, and it means that knowledge is co-created by group members” (Menguc et al, 2013). In the following, we discuss some of the researches conducted in the field of customer knowledge co-creation.Itani et al. (2022) conducted a study with the aim of investigating the effects of using social media and customer relationship management technology on the customer knowledge co-creation and sales performance in B2B companies. Based on the theories of task-technology fit and self-determination, the findings show that social media, customer relationship management technology, and their interaction, support salespeople in joint value-creation efforts through the mediating role of knowledge enriched by these tools. The results indicated a significant moderating effect of the salesperson's job independence and the ease of the sales quota in increasing the relationship between knowledge and value co-creation.Xie et al. (2020), in a study titled "Using Customer Knowledge for Service Innovation in Travel Agency Industry", investigated the influencing factors and the effects of service team access and the combination of customer knowledge on tourist service companies. The results showed that both factors of customer orientation and intensity of interaction are effective on customer knowledge co-creation teams, which can promote service innovation. Also, the results indicated that customer knowledge co-creation moderates the relationship between interaction intensity and service innovation.

The current research was done in two stages using a mixed method. In this research, in order to identify the components of the customer knowledge co-creation model, first the qualitative approach of grounded theory was used. For this purpose, semi-structured interviews were conducted with a selection of insurance industry experts, including a number of university professors and insurance company managers, as a result of which the components of the research and their dimensions were identified. Then, in order to present the relationship model of the main components of the research, the opinions of experts were evaluated through the matrix of pairwise comparisons, and based on this, the conceptual model of the research was explained. Then, in order to test the research model and hypotheses, the partial least squares quantitative method was used. The statistical population in the quantitative stage consists of managers and experts of three active insurance companies in Iran, including Alborz, Iran, and Asia. The statistical sample was obtained from the random cluster sampling method, based on which 310 people were selected as a statistical sample. The data collection tool in the quantitative stage is a researcher-made questionnaire. Cronbach's alpha method was used to check the reliability of the measurement tool, and its value was greater than 0.7 for all variables. Therefore, all variables were confirmed in terms of reliability.

In the first stage of the current research, the qualitative method of grounded theory was used to identify the components and dimensions of customer knowledge co-creation. As a result of this stage, 7 main aspects were identified for customer knowledge co-creation. After identifying the research components and developing the model, 9 hypotheses were formulated in the quantitative stage. Based on the findings of data analysis using the partial least squares method, all 9 research hypotheses were confirmed. The results showed that the infrastructure of information and communication technology has an effect on being knowledge-oriented. Also, being knowledge-oriented has an impact on internal marketing and customer relationship management. In addition, the effect of internal marketing and customer relationship management on customer orientation was confirmed. Also, the effect of customer orientation on creating motivation and trust building was confirmed, and finally, the effect of creating motivation and trust building on customer knowledge co-creation was confirmed.

Customer knowledge co-creation is a process by which organizations acquire competencies and knowledge of customers, so that they can use this information to create an experience for customers and reach new markets for themselves.

According to the confirmation of all 9 research hypotheses and with emphasis on the structures (sub-indices) that have the highest factor load obtained from the partial least squares method, the following practical suggestions are presented:In order to develop the component of “information and communication technology infrastructures” in insurance companies, considering the importance of "the company's presence in social media and producing up-to-date content", it is suggested that managers of insurance companies use experts who have enough expertise in the field of content production to manage social media pages. Also, through social pages, they can establish a two-way relationship with customers, especially special customers, and encourage them to share their insurance knowledge and experiences.In line with the development of “internal marketing”, the managers of insurance companies should continuously strive to hold brainstorming sessions with the employees in order to update their knowledge and skills. In these meetings, in addition to presenting technical matters such as informing about possible changes in insurance policies, new insurance laws, etc., experts in fields such as marketing, psychology, and negotiation can also be invited so that the employees and the sales network, in addition to mastering the technical skills, also master the communication skills of the day.In order to ensure customer satisfaction and as a result of complying with customer-oriented principles, insurance companies must first observe and understand the needs of their customers. For this purpose, they should listen to the expectations and criticisms of the customers, and by establishing a friendly relationship with them, in addition to getting to know the customers more and knowing their level of satisfaction, they should have a positive effect on their perception.In order to increase the “trust of customers”, insurance companies should adopt strategies that lead to improving the mental image of customers towards the company's brand. Since the main mission of insurance companies is to issue perfect insurance policies as well as timely and adequate payment of damages, if this is done correctly, it can play an effective role in attracting customers’ trust.Finally, in order to develop the customers' knowledge co-creation, insurance companies should use the experiences and knowledge gained from customers to produce and create new knowledge and improve and develop the organization's products and services.

The main purpose of this study is to level the indicators of extreme events affecting the behavior of investors and capital market risk using a structural-interpretive modeling approach.This research is based on purpose, is practical and descriptive in terms of data collection. The statistical population of this study is 15 professors and PhD students in accounting, financial management, economics and business management, who were selected as experts through purposive sampling, and these, and these experts, through an interpretive structural questionnaire, identified 15 indicators of extreme events that had previously been identified in another study by the authors of this article, through 3 stages of fuzzy Delphi and among 72 indicators,in 5 categories, they were graded and prioritized. The validity of the questionnaire was confirmed by respected professors, advisors and financial experts. Also, Cronbach's alpha coefficient was used for the reliability of the questionnaire, which was more than 0.7 for all variables,and MIC MAC software was also used to analyze the data.Findings from the structural-interpretive method in this study show that the extreme events indices are ranked at five levels. So that, inflation and sanctions indices in the fifth level, have the greatest impact and air pollution index in the first level, have the least impact on investor behavior and capital market risk.

The present study is about the effect of financial risk Impulses (based on Enterprise Risk Management-ERM) and dividend policy on the efficiency of capital allocation by PVAR method. The implementation of this research is in terms of the need to move from the traditional style of risk management to the new style (ERM); In order to manage financial risks in the form of a portfolio, the need to improve the quality of capital allocation and exploit the functions of dividend policy is important.The research method is analytical-descriptive.Data analysis of114 companies during2009-2017 using PVAR method, which is a combination of self-explanatory vector and panel data, was performed with Stata15 software.Efficiency models of capital allocation were estimated based on two indicators: "investment inefficiency - the first model" and "investment elasticity to value-added market - the second model". According to the (IRF), the "reaction intensity" and "damping period" of the individual impulse effect of the variables in the second model are more intense and earlier than the first model and about 4 periods.According (Fevd), the most changes in both measures of capital allocation efficiency are due to these criteria and only in the first model, the share of financial risk explanation at the end of the period reaches10% to16% and the share of dividend policy to19%.As a result, in the process of capital allocation and financial risk management, firms should focus on the autoregressive process of capital allocation efficiency indicators and financial risks in the first place and in the short run.

Innovation, which is the result of the joint work of university and industry, is an initiative that improves the efficiency of innovation. This type of cooperation, i.e. collaborative innovation between university and industry, is called collaborative innovation. Collaborative innovation brings dynamism and vitality to companies and causes economic growth and expansion. (1). In fact, one of the important factors in innovation, and one of the important factors in economic growth and development, is the transfer of knowledge that takes place between universities and industry because this cooperation makes commercialization in companies easier (2).On the other hand, one of the things that has always been very important in knowledge-based companies is the commercialization process. This process has three separate phases, the ideation phase, the technology/product development phase, and the commercialization phase. First, an idea that has a demand in the market is created and cultivated. In the development stage, this idea becomes a product or technology, and commercialization is technological knowledge that has entered the market (9).In our beloved country of Iran, knowledge-based companies active in the field of medical products have succeeded in reaching self-sufficiency in the field of medical products to almost 40% in the past few years, but they have been very unsuccessful in the discussion of commercializing medical products for export to other countries. . Now, according to the capacity of our country, we can earn up to two billion dollars a year from the commercialization of these types of goods, which has a positive impact on the national economy. Therefore, the researcher seeks to solve these problems by presenting a model for commercialization. Therefore, the main research question is, what is the commercialization model of medical products for knowledge-based companies?

The current research is of an exploratory and expansion type, which was conducted using a qualitative method. The statistical population of this research is experts with practical experience in the field of commercialization of products of knowledge-based companies in the science and technology park of Mazandaran province, and professors of the University of Medical Sciences and management professors of management faculties of universities of Mazandaran province, who are aware of the subject of the research. 12 people were selected as samples from among them by snowball method until full saturation. Then a semi-structured interview was conducted to collect data from them.Interviews were held one by one with each expert. After conducting the interviews (audio recording), the texts of the interviews recorded from the experts, on the same day of the interview, were transcribed word by word on paper and typed as research data. , was used. The research data are analyzed on two levels, the textual level and the conceptual level.The textual level includes the coding of the data, the conceptual level emphasizes the construction of the research model including establishing a relationship between the codes based on the Strauss and Corbin model. Also, in order to ensure the validity of the model, the strategy of analysis and review by knowledgeable people (multi-view) has been used.

To design the model using the foundation data method in the first step; Initial coding was done using the text of the interviews. In this step, one hundred and nine primary codes were extracted. In the second step; Axial coding was done. In this step, thirty-two axial codings were obtained from a total of one hundred and nine initial codes. In the third step; Selective coding Selective coding was done based on the results of open coding and axial coding in this step, which is the main step of theorizing. Thirteen codes were obtained.Also, the validity of the research model was done by using the analysis and review method by knowledgeable people, in this method, to check the validity of the research model, all the data and primary extracted codes were sent to other experts who are familiar with the issue of commercialization of medical products in knowledge-based companies. They were informed and experts were given and they were asked to modify and approve the designed codes, and all the codes were approved, thus the validity of this research was proved. Also, the reliability of the research was checked with Kreppendorf's alpha method, and the agreement of five experts on the codes was equal to 89%. Considering that this amount is more than 60%, the reliability of the codings of this research is confirmed.

In this research, the causal conditions for the commercialization of medical products, four factors of human capital, technology, digital transformability of the company and environmental factors have been stated. (Shirvani, Tulai and Delavi, 2019 limited the causal conditions to digital technology. Considering these factors by the companies residing in the science and technology park, they can take into account all the effective factors in creating a successful business for their products and Don't just focus on technology.The strategies of this research have been identified in three dimensions; Financial strategies, market orientation and attracting cooperation of the University of Medical Sciences. Every business unit needs capital in order to set up and start its activity, and in order to develop and continue its activity, it needs new investment, which must be provided through financial resources (24). Access to financial resources is one of the important factors in the success of companies and one of the important concerns of companies at different stages of their life (25). Market orientation can be defined as a stage of organizational growth or as a level that reflects organizational maturity (26). Kotler has looked at market orientation as the final stage of the development of a business organization and believes that the market orientation is created along the development of different business orientations. Market orientation is based on marketing thinking and marketing thinking forms its philosophical foundation. (26). However, marketing thinking as a foundation and philosophical foundation is not enough. Because market orientation focuses not only on customers, but also on competitors, different organizational issues and many external factors that affect the needs and preferences of customers.

Due to the developments in the field of digital technology and the expansion of social media, the competences and capabilities of marketers in order to use these tools and keep pace with these developments in the insurance industry are vague and unclear. Therefore, the main objective of this research is to provide a model for the competences of marketing specialists in the country’s insurance industry.

This research, relying on qualitative data, has been collected and seeks to provide an acceptable framework in relation to the indicators for determining the competences of marketing professionals in the insurance industry, and finally to fill the current gap in the insurance marketing literature . This research in terms of its goal is a developmental research. The implementation method of this research is to apply foundation grounded theory using a systematic approach. The statistical population of this research includes managers and marketers active in different insurance companies in Iran and they were selected using the purposive sampling method. With this attitude, the selection of experts was done based on two criteria: having at least five years of work experience in the sectors related to the insurance industry and having a master’s degree or higher in the fields of business management and insurance. The semi-structured interviews continued by phone and face-to-face, with six general questions, until theoretical saturation was realized in the ninth interview.

In this research, the systematic data approach of the grounded theory was used. In the systematic approach, theorizing was done in three main steps: open coding, axial coding, and selective coding. In this way, in order to identify the constituent factors of the competency model of marketing specialists in the insurance industry, data analysis in the open coding stage led to the extraction of 77 primary open codes, 17 sub-themes and finally 7 main fields.In the phase of axial coding, 7 main topics in the form of core phenomena (general and specialized competence); causal conditions (including individual capabilities); strategies (including the development of the capabilities of insurance marketers); intervening conditions (including environmental factors); contextual conditions (including policies of the insurance company); and the consequences (including the development of the insurance industry) were identified and then a paradigm model was drawn. Finally, in selective coding, the previous findings were refined and through this process, a theoretical framework was obtained. According to the obtained model, the general and specialized competence of marketers in the country’s insurance industry are influenced by factors related to individual capabilities. In addition, the development of the capabilities of insurance marketers with the aim of strengthening their competences are influenced by environmental factors and the policies of the insurance company. In the end, it was found that the development of the capabilities of insurance marketers could lead to the expansion of the country’s insurance industry.

Based on the investigation of various factors and by emphasizing the necessary developments in the business environment, this research will be able to respond to the deficiencies and gaps in the past-related studies to the competence of insurance marketers. Therefore, strengthening and developing all dimensions and components of this model through planning and using it in attracting and cultivating insurance marketers, evaluating their competences and creating a database of qualified marketers will be able to act as a facilitator for Realization of transformation and development of the insurance industry in the country

The transmission of financial crises between different markets in an economy indicates the existence of channels of transmission of this crisis. Today, parallel currency markets are closely related to other markets such as gold, coins, stocks and oil. Channels that transmit shocks and fluctuations of the foreign exchange market to other markets can include information, macroeconomic variables, investment behaviors, and so on. In this study, using daily data from 2009 to 2017, the explanation of overflow fluctuations and shocks in the foreign exchange market and how to transfer these shocks to other markets has been examined. The results indicate the existence of fluctuations overflow as well as structural fractures due to the presence of this overflow. The research model and determination of interruptions is based on the VAR model. Yields and fluctuations as well as the presence of the Arch effect in the model are determined based on the VAR model. The MV-GARCH model is used to determine the returns in the foreign exchange market. Fluctuations and shocks of the foreign exchange market and its impact on other markets as well as future prices in different markets are determined based on the VAR model. The results of this study indicate the effect of shock in the foreign exchange market on the trend of future prices in this market as well as the impact on other markets.

The purpose of this research is to design a model of conflict dimensions from the point of view of tourists entering Gilan province and local natives. This research is descriptive and exploratory based on the nature and method of data collection. The statistical population of this research is tourists and residents, and the participation of university experts and cultural heritage and tourism experts with a number of 18 people is also included. The data of the qualitative part was collected using the approach based on classical grounded theory and using semi-structured interviews through purposeful snowball sampling. In the quantitative part, the relationship and significance of the categories were determined with the interpretive structural modeling approach. Based on the obtained results, inflation in the real estate sector, disruption in the transportation system, and cultural differences are the cornerstones of the pattern of tourism conflict dimensions and have a high effect on it. This model can be used to investigate the tourism conflict phenomenon according to the views of different stakeholders, as a reference for tourism development and guidance for managing tourism operations. Also, the problems and shortcomings of tourism development in Gilan province can be changed by increasing or decreasing each of the variables and using the results as a basis for tourism development.

Profit forecasting is an important criterion for companies and companies listed on the Tehran Stock Exchange must be very careful in forecasting their profits. This study aims to provide a neural network model to predict the profits of companies listed on the Tehran Stock Exchange and compare its accuracy with ARIMA and HDZ models. The research method is an applied research in terms of purpose, an inductive research in terms of logic and a quantitative research in terms of data nature. In order to collect data, the basic financial statements of companies in the period 1398-1393 were used. In this study, neural network method was used to predict corporate profits and two models, ARIMA and HDZ, were evaluated. The results show that the rate of data convergence and regression in the first phase and in the HDZ method equal to 0.79087, in the second phase, in the ARIMA method, it is equal to 0.79184, and in the artificial neural network method, it is equal to 0.79464, which has a higher degree of convergence and regression coefficient. Based on the results, it can be seen that the designed neural network has the ability to predict stock price trends using general and industry indicators, and this, in addition to confirming the neural network's ability to predict financial areas and profitability it also confirms strategy of the price forecast on the Tehran Stock Exchange.‏ ‏‏

Predicting crises and price jumps in the stock market and based on different models has been growing over the last decade. Due to the presence of big data, this issue has led to the growth of developments in the field of machine learning and deep learning models. Due to the importance of this issue, This study examined the ability of different machine learning models to predict the jumps in the total index of the Tehran Stock Exchange during the period 2013 to 2020. For this purpose, first stock market jumps were extracted based on the ARJI-GARCH approach and then these jumps were predicted by considering the possible effective variables including global and domestic markets. The prediction results of 1-, 3-, and 6-day periods for the out-of-sample period show that the machine learning method based on the long short-term memory (LSTM) network, a recurrent neural network, has a better result than other models.

Global catastrophic risks are classified into 62 categories, 34 of which have been recorded in Iran. Such risks are major threats to the Iranian economy. Using the capacity of the alternative risk transfer instruments, as one of the recommended ex-ante risk management strategies, creates financial protection in the macro frameworks of the domestic catastrophe risk management via incorporating the financial instruments of the Iranian capital market as well as the Islamic financial market. Transferring such catastrophic risks requires appropriate financial instruments. The purpose of this study is to provide, explain and design the domestic catastrophic risk management framework by alternative risk transfer instruments.

The present study has been conducted based on a systematic literature review method. For this purpose, the related literature was systematically reviewed over a period of eight months. Firstly, after specifying the subject of study, the research question was developed. Then, the research protocol was designed and an appropriate mental model was designed accordingly. Subsequently, inclusion and exclusion criteria were determined. The researchers next began the comprehensive and systematic research through which 112 papers were examined. After classifying, screening, and measuring their quality, 73 studies were selected for the final in-depth analysis. In the next step, through the purposive and snowball sampling method, 18 experts were interviewed. The Delphi method was used to obtain the opinion of experts until data saturation was achieved. Their viewpoint was embedded in the final proposed framework. In the last step, the obtained data were classified, codified (using the open coding method through MAXQDA 2020   software) synthesized, and finally summarized. The trustworthiness and authenticity of the current research was measured according to the four-stage model of Lincoln and Guba.

In general, all the factors that affect the catastrophic risk management framework can be classified into four main categories of “necessity, implementation of infrastructure, risk measurement, and designing appropriate financial instruments”. Each category includes several subcategories and codes. The proposed framework in the present study is made up of 4 categories, 10 sub-categories, and 415. Also, 37 risks were collected and classified out of 62 catastrophic risks to obtain the “Iran Disaster Risks Diversity Table”. Finally, the appropriate financial instruments for risk transferring based on the capacity of the domestic capital market, i.e. “Insurance Sukuk Vekala” and “Cat Takaful (CT) Sukuk” (for the international Islamic Capital Market), were designed and proposed by this research.

Finally, a schematic model was proposed to establish Iran’s catastrophic risk management framework through alternative risk transfer instruments, according to the diversity of detected factors. As a multi-dimensional concept, the framework should be considered in the implementation process.

Knowledge is a key element in fostering product and service innovation. One of the newest concepts proposed for using knowledge resources outside the organization is the concept of knowledge co-creation. Knowledge co-creation means the processes of voluntary collaboration between customers, researchers and organizational managers to create knowledge about products and services. The most important actor that plays a role in the co-creation of knowledge is the customer. The issue of customer knowledge co-creation is not yet well known in our country's insurance industry, so identifying its components and determining the influence of each of them is one of the challenges of current insurance companies. Therefore, the purpose of this study is to identify the components of customer knowledge co-creation and provide a model of relationships between customer knowledge co-creation components in the country's insurance industry.The present study is a fundamental research based on the purpose and based on the data collection method is a descriptive-survey approach. In order to identify the components of the research, interviews were conducted with 14 experts including insurance industry managers and faculty members who are experts in this field. In order to present the model of component relationships, the standard questionnaire of interpretive structural modelling approach, which is based on pairwise comparisons, was completed by 10 experts. Based on the results of semi-structured interviews with experts, 51 primary codes and 7 categories were extracted, which were classified into 5 levels by interpretive structural modeling approach. In this model, the component of "ICT infrastructure" is at the lowest level, which indicates the highest penetration among other components, which means that the change and development of this component, causes a change and development of other components of the model. Also, the components of "motivating customers" and "building trust", which are at the first level of the model, are the most influential components of the model. Therefore, in order to optimally implement the process of customer knowledge co-creation in insurance companies, strengthening the components of lower levels of the model, which have more influence, should be a priority in management decisions.

In today's growing, saturated and competitive markets, the insurance industry, like other industries, is suffering from customer churn. Recent advances in communications and technology have led to increased awareness and ease of comparison of insurance policies and services. Thus, insurers are constantly confronted with new offers from competing companies and easily turn to competitors; in other words, they churn. The aims of this research are actually pursued through the following research question. What are the main factors of churn in the Iranian insurance industry? This study is conducted in two phases: qualitative and quantitative. First, in the qualitative phase, 15 experts in the insurance industry are interviewed to identify the factors affecting churn. Then, based on the identified factors in the research literature and comparing them with the results of the interview, 8 main influential factors are identified and finalized. In the quantitative phase, these indices are first weighted by hierarchical analysis technique. Then, the statistical population is determined in the quantitative phase; they included the insurers of the Iranian insurance company, and by selecting a sample of 120, neural network technique is applied to fit the model. The calculated R = 0.74 proves that the eight identified factors (type of insurance, premium, final result of claims, duration of cooperation, payment method, number of installments, number of policies, and number of claims) can best explain the reasons of churn of policyholders.

Macroeconomic policies are an important tool for governments to achieve financial commitments andtheir social and economic goals. Macroeconomic policies have different types and their implementationcan effects different markets in various ways which can cause change and turbulence in them. With thisapproach, in the present study by using the Bayesian Causal Map (BCM) and seemingly unrelatedregression equations (SURE) model, a model is designed to explain the effect of macroeconomic policieson money and capital markets. It should be noted that the time period of the present study was 1989 to2019. The results of the present study showed that money and capital markets are affected by variablesand policies applied in different markets in both direct and indirect ways. If the amount of savings in thesociety changes as a result of government policies or other economic and non-economic components,the facilities granted by the banking system will change as well. This directly affects the money market.Given that changes in the money market affect the capital market, the capital market is also affected bychanges made in the money market. At the same time, changes in the money market also affect othermacroeconomic variables such as................

In this study, the identification of factors affecting the attitudes and behavioral intentions of consumers in the selection of Iranian products has been considered by the researcher. Considering the importance of customer behavior, the purpose of this study is to present a native-Iranian model with emphasis on the attitude and intention of consumers to buy Iranian products in order to implement the policies of the resistance economy in the country. In this regard, the mixed research method was used, which in the qualitative stage the grounded theory method is the basis theory and in the quantitative stage the descriptive-survey method is used. In the present study, priority was given to qualitative findings and the role of research and quantitative data was only to test the hypothetical model designed in the qualitative part of the research and to generalize the findings. Qualitative data analysis was performed in three stages of open, axial and selective coding. At the end of the qualitative stage, a conceptual model was designed to explain the attitude and intention of consumers to buy Iranian products. The conceptual model of the research has been studied by modeling structural equations and the least squares approach and based on the measurement results, structural indicators and fit have been judged. Model fit indices indicate the optimal fit of the data with the concept model. In other words, the quantitative data fits well with the conceptual model of the research and confirms the qualitative data.

The present study aimed to design a target market segmentation model for foreign tourists, qualitatively and using data theory and based on the proposed steps of Glaser and Strauss. The statistical population includes all senior managers of Guilan Cultural Heritage, Tourism and Handicrafts Organization, as well as experts in the fields of business and tourism management and senior managers of municipal, governorate and governorate organizations, 15 of whom are qualified to have at least a master's degree. And at least 15 years of experience in the tourism industry and the use of the snowball method as a targeted method in the form of a statistical sample for interview has been used through a semi-structured questionnaire and has reached theoretical adequacy. Max QDE software is used and the three stages of open coding, selective coding and axial coding are used. The research findings have led to the presentation of a model that includes the historical attractions of the destination, the cultural attractions of the destination, the recreational attractions of the destination, the commercial attractions of the destination, the educational attractions of the destination, and the income attractions of the destination. Classification of causal conditions of service factors (destination facilities), health factors (capacities), supportive factors and underlying conditions is predominant and motivational factors / perceptual factors / cognitive factors / competitive factors / economic factors / financial factors / political factors (government) They play a moderating role. Play. The cultural and economic development of Gilan is one of the marketing consequences of the cultural-historical capabilities of Gilan tourism. Finance is one of the main reasons for the development of medical tourism. In Iran, due to the creation of additional capacities in the health sector, especially at the medical level, the expansion of medical tourism can be a fundamental strategy to solve problems such as excess capacity. The purpose of this study was to classify foreign clients of four hospitals in Iran based on their expected benefits from medical services. Conclusion In this study, people gave the highest percentage of importance to providing respectful care. Therefore, hospitals should focus on the quality of communication with their customers in their marketing efforts. In the present study, in the qualitative part, the data theory of the foundation has been used, which has been implemented based on the proposed steps of Glaser and Strauss. The statistical population includes experts in the field of tourism, including all senior managers of the Cultural Heritage, Tourism and Handicrafts Organization of Guilan Province, as well as faculty members in the fields of business and tourism management and senior managers of the municipality, governorate and governorate. Organizations, including 15 considering the requirements of having at least a master's degree and at least 15 years of experience in the tourism industry and using the snowball method as a targeted method in sampling qualitative research as a statistical sample for interviews, for interviews Specialized used. Taken and reached theoretical adequacy. The interview was conducted through a semi-structured questionnaire in the form of 5 years, so that questions were asked similar to the experts, but they were free to provide their answers in any way they wished, the questionnaire questions based on the identification variables in the literature The research has been compiled and their content validity has been examined by university professors in terms of indicators of validity or reliability, transferability or transferability, verification or verification and reliability. Finally, the researcher was responsible for encrypting the answers and classifying them. All 2 and 4 are used by Max QDE software, so they have been "assisted In the third coding method, the coding is optional. At this stage, the researcher has proposed a theory among the categories obtained in the axial coding model, which has led to the presentation of the model. Research findings show that behavioral segmentation is one of the central conditions in target market segmentation for foreign tourists. In explaining it, it can be stated that the behavior of tourists includes the search for leisure experiences, the interaction between the features and characteristics of the places they have chosen and visited. According to Lepper, it can be argued that understanding consumer consumer behavior in tourism is not just an academic aspect; nevertheless, academic analysis contributes to effective tourism planning and marketing. Kane believes the world is not yet global; Therefore, tourism consumer behavior in each country is still different and needs to be recognized in terms of many determinants that affect the supply and demand of tourism. It is very key to develop, promote and sell tourism products. Clearly, if we are to optimize the efficiency and effectiveness of marketing activities, we need to understand how consumers decide to buy or use tourism products. If we know their patterns of behavior, we know when we need to intervene in the process to get the results we want. In this case, we know what tourism product to develop for the target market at a particular time. Most importantly, we know how to get them to buy a particular product that we have designed to be more effective in meeting their specific needs and wants. Therefore, market segmentation based on behavior patterns is essential for success in marketing activities.

 Today, due to the rapid growth of technology in the world and the tendency of companies towards startup companies, the category of valuation is of particular importance. If we want to divide startup companies into two general categories (1- Startup companies in the idea stage 2- Startup companies in the post-idea stage), Net assets value (NAV), book value (BV), present value of cash flows (DDM), etc., but these methods are not applicable to the first category, which is in the early stages and lacks cash flows and physical assets. To valuate the first type of companies, methods such as valuation of Bill Payne scorecard, valuation of Dave Brexes, aggregation of risk factors are used, so researchers according to the conditions and in accordance with existing financial, tax, administrative, jurisprudential and religious laws, etc. In the country, experts, forensic experts, stock valuation experts, etc. have been researched and the dimensions, criteria and valuation indicators of startup companies in the idea stage, which lack cash flows and physical assets, have been identified through mathematical methods. AHP are ranked, as a model in the future Suitable for evaluating such companies to be used by users who currently have no model in Iran. Researchers, after identifying the valuation indicators of startup companies in the idea stage and compatible with the Iranian environment, have proceeded to rank these indicators, the results of which are given at the end of the article.

Today, companies are well aware of the significance of sales and attempt to stabilize and/or improve their status in the competitive climate of the markets by increasing their sales. The present qualitative research aims to enumerate the factors influencing sales effectiveness using grounded theory to identify the categories underpinning the sales effectiveness of companies. The research data were collected from 10 experts in the food industry in Guilan province, Iran. The collected data were analyzed by coding in the MAXQDA software. Results show that 287 concepts (in terms of repetition) were extracted from the interviews at the first step (open coding). By considering the relationship of the concepts at the axial coding level (the second step), they were narrowed to 26 categories, and finally, six themes were identified at the third step (selective coding). These themes, i.e., the factors underpinning organizational sales effectiveness, include the firms' strategic orientations, marketing capabilities, sales control management, salesforce performance, and environmental factors. As well, sales effectiveness was decomposed into the categories of investment, profitability, market share, and customer satisfaction.

The financial statements are the result of negotiations between the auditor and the client. Therefore, auditors need to be able to negotiate well with their owners and resolve existing disputes. This article examines how the social identities of the auditor and the client affect their performance in the negotiation process. The identity of the auditors shapes their motivational orientation towards the negotiations. Therefore, understanding the impact of gender on negotiation behaviors, trends, and outcomes, and thus the quality of financial statements, is increasingly important. Data were collected in the form of a questionnaire from 42 official auditors, members of the Iranian Society of Certified Public Accountants and professors in this field. The present study shows that male and female auditors approach negotiation of audit settings differently. Therefore, creating gender diversity in the audit team to resolve existing disputes can be very helpful. Findings also show that bargaining power and critical power are the main components of the success of female auditors, employers have more flexibility than female auditors and female auditors in the negotiating position can perform the same performance in terms of skills and competitive behavior compared to male auditors. .

The increasing spread of financial crimes and the irreparable economic, and even social and cultural damage they cause, clearly illuminates the necessity of research and analysis in this area and to investigate the causes of such crimes. Therefore, the main issue in this research is the spread of financial crime and its concerns in Iranian society. The researcher seeks to understand financial crime economically and not from a sociological or criminological perspective. Therefore, the overall purpose of the present study is to design and test a model to explain and predict the causes of financial crime to prevent financial deviations. In this regard, a hybrid research approach was used which used the qualitative stage of the theory of grounded theory or the grounded theory and in the quantitative stage the descriptive-survey method. The qualitative findings were analyzed by MAXQDA software and at the end of the qualitative phase the conceptual model of financial crime was extracted. In the quantitative phase, the model was validated using partial least squares structural equation modeling with PLS software. Model fit indices indicate that the data fits well with the conceptual model. In other words, quantitative data fits well with the conceptual model of research and confirms the qualitative data.

This research is an attempt to introduce a desirable pattern for Dynamic Modeling of the Estimated Optimal Ratio of Gold Coin Risk Coverage. Given the unique nature of Iran in producing and supplying saffron and weakness in the commercial sector of this product, it was necessary to supply this product through the Iranian Stock Exchange. Following the presentation of the Saffron Deposit Certificate in the Iranian Commodity Exchange in 2017, the futures contracts for saffron in the Iranian Commodity Exchange were defined in 2018. On the other hand, the gold coin futures market was halted in 2018 due to the volatility of the gold coin market. Therefore, considering the importance of estimating the risk coverage in financial markets, in this study, we modeled the estimation of the optimal ratio of daily gold coin risk with respect to the future contracts of saffron from May 22, 2018 to October 22, 2019, through the Coppola functions and wavelet analysis. And the combination of these two models is discussed. The results of the study show that the saffron futures market is able to estimate the risk coefficient of gold coin cash market risk and that investors can use this market to cover their risk. In addition, in terms of structural dependence on the basis of the Coppola functions and wavelet decomposition, it results in an optimal estimation of the coverage over the medium and long time periods.