Journal of value creating in Business Management

Abstract Abstract
The aim of this research is to identify the dimensions and components of acceptance of social systems of customer relationship management by professional users using Web 2.0 technology. The current research is applicable in terms of nature, qualitative in terms of implementation method, and of descriptive and thematic kind. The statistical population of this research was made up of 15 university professors in the fields of management, business and IT along with managers of digital business companies, selected by non-random sampling method.
The criteria for selecting people are having a doctorate degree with more than 10 years of experience in digital businesses, having time, interest and ability to take part in interviews (a semi-structured) and fill the questionnaires. Also, MAXQDA 2020 software was used in data analysis. The identified factors were extracted in the form of 40 indicators, 8 components and 3 dimensions. Components and indicators of dimensions and components of acceptance of customer relationship management social systems included three dimensions; organizational, customer, and technological; which organizational dimension has three components (manpower, organizational culture, organizational structure), customer dimension includes three components (value creation, customer satisfaction, expectation of performance), and technologically has two components (social networks, content production).
Extended Abstract
Introduction
In the approval of customer relationship management, organizational changes and organizational developments are always expected. However, there is little knowledge about the effects of these changes on customer relations, employees and the quality of the effect of their activities and behavior on the success of customer relationship management. Factors affecting the acceptance of traditional customer relationship management have been supported by numerous studies in developed countries. Due to this, in developing countries, with significant costs, research studies investigating traditional customer relationship management systems and factors affecting the acceptance of customer relationship management from Companies and their customer prospects are facing infrastructure restrictions (Sana Azeem et al, 2020).
The application of social media is the latest development and innovation in information and communication technology in online business. The popularity of social media technology has contributed greatly to this development, as it engages individuals as part of an online social community and fosters peer-to-peer interaction. And it has created a new opportunity for organizations to use social networking platforms to do business, called social commerce. Social business creates prosperity in Electronics transaction through making relationship and sharing the evaluation of experiences of the social media website members in using the various products or services. (Fahadyar et al, 2021).
Therefore, the researcher asked the main question, what are the dimensions and components of acceptance of customer relationship management social systems by professional users using Web 2.0 technology?
Theoretical Framework
Social networking technologies introduced social customer relationship management as a new version of social customer relationship management strategy (Malthouse et al, 2013). Based on the literature, this research defines social customer relationship management as a type of social network technology for customer relationship management. Today, organizations around the world have more and more adopted social media for their different business purposes, such as labor collaboration, intelligent business, and social customer relationship management (Abedin, 2016).
Web 2.0 is a term that is often used in relation to the ever-increasing evolution seen in the World Wide Web. This transformation and transition has taken place from a set of websites towards computer bases that serve the final users of web applications. Finally, it is expected that Web 2.0 services will replace everyday computer software in many ways. Of course, it should not be assumed that Web 2.0 means a completely new and different version of Web 1. Rather, Web 2.0 is actually a symbol of the evolution and combination of complementary characteristics of Web 2.0. It is a set of new approaches in the Internet space towards open, flexible and collaborative development models for content production systems that can lead to reducing the costs of information production and processing, increasing public awareness, and increasing the efficiency of systems (Nobre & Silva, 2014).
Rabieh & Rezaeiyan (2022) discussed the effect of social customer relationship management on financial performance with the mediating role of customer commitment and customer satisfaction (case study: private banks in Khuzestan province). The results showed that social customer relationship management with the mediating role of customer commitment and customer satisfaction has a positive and significant effect on the financial performance of the private bank of Khuzestan province.
Mehrabi et al, (2022) discussed in their article entitled the explanation of the optimization model of marketing success and customer relationship management in electronic services and businesses. The results of the analysis of the findings showed that; Price, sales promotion, branding, perceptual/emotional features, hardware facilities, software facilities, social media, technological features, networking, innovation, customer orientation, digital marketing, inter-organization factors, marketing, and customer relationship management have a significant impact on marketing and e-commerce success. Following are some suggestions.
Research Methodology
The current research is applied in terms of nature, and qualitative in terms of execution method. The statistical population of this research was formed by 15 university professors in the fields of management, business and IT, and managers of digital business companies; and the sampling method is non-random purposeful to determine a group of experts. The criteria for selecting people were having a doctorate degree with more than 10 years of experience in digital businesses, having time, interest and ability to conduct interviews and questionnaires. The method of data collection was done by a library method. The study tools are literature and research texts.
 Research FindingsIn order to analyze the data, open and axial coding of MAXQDA 2020 software was used, and the results showed that the dimensions and components of acceptance of customer relationship management social systems extracted by professional users using Web 2.0 technology included in total 40 indicators and 8 components and 3 dimensions. Components and indicators of dimensions and components of acceptance of customer relationship management social systems, including three dimensions: organizational, customer, and technological; which organizational dimension has three components (manpower, organizational culture, organizational structure), customer dimension includes three components (expectation of performance, value creation, customer satisfaction), and technological has two components (social networks, content production).
Conclusion
The current research was conducted with the aim of identifying the dimensions and components of acceptance of customer relationship management social systems by professional users using Web 2.0 technology. The results of this research are consistent with the results of Rabieh & Rezaeiyan (2022), Mehrabi et al, (2022), Farsadfar (2021), Fahadyar et al, (2021), Fang (2021), Li (2020), and Jameel et al, (2019). Fang, (2021) has conducted a research under the title of the analytical effect of the e-commerce customer relationship management system based on smart network communication. In this research, he examines the analysis of e-commerce frequencies and the efficiency of customer relationship management. In this way, the existing limitations in the interference of e-commerce links and the construction of matrices of these links have been investigated in order to analyze the performance of the smart network communication system and technology to create a model for the productivity of customer communication. The results indicate that the optimization of e-commerce methods and communication with the smart network improves customer relationship management.
According to the obtained results, it is suggested that organizations pay special attention to the customer dimension, which has three components: customer satisfaction, value creation, and performance expectation. For this purpose, organizations through examining cases such as providing support and services to customers in the social networks they use, interacting and communicating with customers in real time, monitoring and quickly solving problems by monitoring and following up social networks, searching and rewarding brand supporters and customers who help others, help make the brand more visible in the places where the audience spends their time, increase interaction and deep relationships with customers, and etc. improve customer satisfaction.
In the organizational dimension, due to the importance of human resources, organizational culture, and organizational structure; organizations can address issues such as job satisfaction (salaries and benefits, rewards, employee relations, etc.), job security, secure environment, job hierarchy, delegation of authority, superior and subordinate relationships, and etc., influence the behavior of employees and institutionalize organizational culture among them.
Also, in the technological dimension, according to the results obtained and the importance of social networks and content production, organizations can give importance to things such as the content of the work produced according to the conditions and time (so that it can be republished by others), producing targeted content, excellent and attention-grabbing headlines, proper timing, high quality images and videos, avoiding repetition, etc. can achieve better success in the technological field.

Abstract Abstract
The purpose of this research is to design a model of artificial intelligence competencies on organizational performance, taking into account business-to-business marketing capabilities. The research method is exploratory (qualitative-quantitative). In the qualitative part, it is considered with the Shannon entropy approach, and in the quantitative part, it is descriptive-survey. The participants of the present research in the qualitative part are faculty members and elites of artificial intelligence and marketing and management, which was conducted with 14 people based on the theoretical saturation rule, and in the quantitative part, the 540number of executive directors of industrial towns in northern Iran, of which 190 were selected as statistics sample. The data collection tool was semi-structured interview in the qualitative part, and researcher made questionnaire in the quantitative part. The method of data analysis was selected in the quantitative part of confirmatory factor analysis tests using SmartPLS software. The results showed that the mechanisms of artificial intelligence competencies have an effect on business-to-business marketing capabilities and organizational performance, and also the model of artificial intelligence competencies on organizational performance is confirmed considering the aspect of business-to-business marketing capabilities.
Extended Abstract
Introduction
The huge increase in the amount of data along with access to processing power capabilities and storage space on digital devices, have attracted new attention in the last few years to artificial intelligence in several fields and scientific courses (Enholm et al., 2021). The intense competition among organizations around the world has also accelerated the need to use artificial intelligence to achieve a competitive advantage over competitors (Ransbotham et al., 2018). Most C-level executives do not see AI as a core competency that organizations must employ to remain competitive in the long term (Kietzmann & Pitt, 2020). One of the key areas of using artificial intelligence in organizational activities has been business-to-business marketing (Mikalef et al., 2021). Smart solutions are needed to enhance business-to-business marketing capabilities in a complex business environment, because business-to-business operations are often associated with enormous information complexity and the need to make quick decisions. In this sense, artificial intelligence has the potential to revolutionize the way of performing common activities due to the ability to process increasing amounts of data and provide rich insights about key business partners and customers (Bag et al., 2021). In addition, it has been stated that artificial intelligence applications enable the automation of many manual processes, and this can help eliminate bottlenecks and increase operational efficiency in business-to-business activities (Paschen et al., 2020). In fact, a recent survey study on corporate executives conducted by Garner showed that the majority believe that artificial intelligence is likely to become a key development in their organization in the next few years (Shin & Kang, 2022).
Therefore, the main questions of this research are: What effect does artificial intelligence competencies have on organizational performance considering the B2B variable? Through what mechanism, the effects of artificial intelligence competencies on organizational performance are realized? And finally, what is the model of artificial intelligence competencies on organizational performance considering the aspect of B2B marketing capabilities?
Theoretical framework
Until now, there is not a complete understanding of how organizations should plan the development of artificial intelligence and turn it into a strategic asset applicable to achieve a competitive advantage. This issue is very evident and prominent in the field of business-to-business marketing, because there is still very little knowledge about the impact of artificial intelligence and the potential mechanisms of value generation from such technologies (Huang et al., 2019). Understanding the value of AI in business-to-business marketing and how to achieve it is critical to reducing the number of failed initiatives within organizations, as well as accelerating the development of AI in these types of operations. Similarly, recent survey studies of industry professionals show that there are still a number of significant bottlenecks preventing the adoption and use of AI that go beyond technical challenges. In addition, from the point of view of many managers, the value of adopting artificial intelligence is still not clear and certain, which prevents its further application in key organizational operations (Bhalerao et al., 2022). A recent study by McKinsey noted that the most popular use cases for AI in organizations relate to optimizing business-to-business marketing and service processes, and this is where respondents placed the most value. However, there are still several challenges associated with realizing such value by investing in AI and specifically with creating an AI competency that can always support business needs (McKinsey, 2022). To address this gap, this study uses the core competence theory (Prahalad, 1993) and provides a definition of the use of artificial intelligence within organizational boundaries, following the key followers of this theory. Especially, we express the concept of artificial intelligence competence as a central competence of organizations, which indicates the need for creative and coordinated use of artificial intelligence. The stated theories explain that organizations able to develop an artificial intelligence competency are organizations that are able to realize a competitive advantage over their competitors; because the application of artificial intelligence is unique in nature and requires comprehensive efforts from various organizational entities to produce artificial intelligence applications difficult to imitate and add value.
Methodology
In the current research, a systematic approach is used. This approach inductively uses a systematic set of procedures to formulate a theory in relation to a phenomenon. Content analysis is one of the documentary methods that deal with the systematic, objective, quantitative and generalizable examination of communication messages. This method is considered a concealer in the classification of methods, and it is used to check the obvious content of the messages in a text, and as a result, it does not enter into the interpretation and semiotics of the message content. The Delphi method is a structured communication method or technique that was originally invented and developed for the purpose of systematic and interactive forecasting by relying on the deliberation of experts. This method used in future research mainly pursues goals such as discovering innovative and reliable ideas or providing appropriate information for decision making. The Delphi method is a structured process for collecting and classifying the knowledge available to a group of experts, which is done through the distribution of questionnaires among these people and the controlled feedback of the answers and opinions received. Research method is fundamental-applied according to the goal; mixed (qualitative-quantitative) of sequential exploratory type according to the type of data; cross-sectional according to the time of data collection; and descriptive-survey according to the method of data collection or the nature and method of the research.
Discussion and Results
According to the results of Shannon's entropy technique for evaluating the capabilities of artificial intelligence, it can be seen that all the dimensions and indicators were higher than the average level of the group's weight, and remain in the model. Therefore, using the results of semi-structured interviews and inspired by the theoretical and empirical literature of the research, the identified categories will be categorized as described in the table below. As mentioned in the previous discussions, the sample size in the qualitative part of the research follows the principle of theoretical saturation, which is reflected in the next table on how to reach theoretical saturation.
Conclusion
The main goal of this research was to design a model of artificial intelligence competencies on organizational performance, considering the aspect of business-to-business marketing capabilities. The research method was exploratory (qualitative-quantitative). It was taken into account with the Delphi technique approach in the qualitative part, and descriptive-survey in the quantitative part. The participants of the present research in the qualitative part were academic faculty members and elites of artificial intelligence and marketing and management, which was conducted with 14 people based on the theoretical saturation rule; and in the quantitative part, 540 people of the industrial managers of the industrial towns in northern Iran, of which 190 people were selected a statistical sample. The data collection tool was a semi-structured interview in the qualitative part, and a researcher-made questionnaire in the quantitative part. The method of data analysis was carried out in the quantitative part of confirmatory factor analysis tests using SmartPLS software. One of the goals of this research was to try to understand whether, and under what conditions, artificial intelligence can lead to organizational value for companies. In order to answer this question, we grounded artificial intelligence based on the theory of core competencies. Therefore, the competencies of artificial intelligence were considered from the aspect of one of the key organizational capabilities that has the potential to create a competitive advantage for organizations. Therefore, the competencies of artificial intelligence are not only understood from the technical aspect, but also include management's ability to creatively anticipate applications that add value to the organization and include the ability to experience and test new methods of using artificial intelligence. Also, based on this approach, AI competency is considered as a core competency that organizations should strive to enhance, rather than just an ancillary and auxiliary set of capabilities that can support certain operations.
 

Abstract Abstract
The purpose of this study is to examine how electronic customer relationship management affects marketing performance, with a particular focus on the mediating influence of product innovation and the significance of customer knowledge. The research method is a descriptive survey and applicable in terms of purpose. The statistical population of the study includes managers and supervisors of Dana Insurance's central office, branches, and representatives in Mashhad. Based on Morgan's table, 165 samples were simple-randomly selected. Data were collected through a standard questionnaire and then analyzed using structural equation modeling (SEM) through Smart PLS 3 software. The findings demonstrate that electronic customer relationship management significantly and positively influences product innovation development. Furthermore, product innovation development has a positive and significant effect on marketing performance. Additionally, customer knowledge positively and significantly affects both marketing performance and product innovation development. In conclusion, both electronic customer relationship management and customer knowledge play a vital role in positively and significantly influencing marketing performance through the development of product innovation.
Extended Abstract
Introduction
The condition of survival and durability of any organization depends on trying to improve its performance in the form of growth and profitability indicators. Organizations utilize various mechanisms to enhance their performance (Hilton et al., 2021). Companies that demonstrate outstanding performance can successfully attain their objectives, boost profits, enhance product quality, and expand their market share (Jannopat et al., 2022). Marketing performance comprises two components: customer satisfaction and trust (Yasa et al., 2020). Customer trust develops through repeated customer interactions over time (Rahman et al., 2020). Organizations seek success and promote their marketing performance by paying attention to customers as their reserves in competitive markets and identifying their needs, getting their satisfaction and creating long-term relationships (Mohammadi & Sohrabi, 2016). On the other hand, organizations aim to improve their marketing performance by establishing long-term relationships with customers (Mohammadi & Sohrabi, 2016). Conversely, seeking customer satisfaction is achieved by swiftly and accurately understanding customer needs (Herman et al., 2020). Organizations regard customer relationship management as a crucial element that reinforces effective marketing and sales endeavors (Alshourideh, 2022). Also, the rapid development of technology has led to the emergence of the concept of electronic customer relationship management, which actually maintains implementing the principles of traditional customer relationship management with the aid of Internet technology (Hanif et al., 2020). Nowadays, electronic customer relationship management creates strong customer relationships by understanding customer needs and monitoring their behavior (Al-Ghasawneh et al., 2021). It is a tool that assists organizations in strengthening their marketing communications to enhance marketing performance (Salameh et al., 2020). By doing so, companies can improve the quality of services provided, leading to customer loyalty, trust, and satisfaction, ultimately increasing marketing performance (Asli Beigi et al., 2016). On the other hand, one of the secure steps to gain and maintain a competitive advantage is constant innovation based on customers' tastes in the supply of services and products (Ata, et al., 2018). Product innovation can have a crucial impact on a company's marketing performance (Erlangga, 2022), representing a significant process that aids companies in their survival and continuous improvement (Bidgholi et al., 2019).
Establishing close and continuous communication with customers stands as a fundamental activity within the realm of electronic customer relationship management (Salameh et al., 2020). Product innovation, by updating and offering better product quality that meets customer expectations, can directly and positively impact marketing performance. The better the quality of electronic customer relationship management and the greater the capacity for customer knowledge sharing, the better the product development will be, ultimately positively affecting marketing performance (Herman et al., 2020). Considering the importance of the aforementioned issues and the fact that insurance is one of the essential and critical needs of families, insurance companies must be able to influence product innovation by improving the quality of electronic customer relationship management and increasing customer knowledge, and transfer these effects to customer-oriented marketing performance (Herman et al., 2020). Given the above explanations, the main question in this research is: "How does electronic customer relationship management and customer knowledge impact marketing performance in insurance companies through product innovation?"
 
Theoretical Literature
Asgarnezhad et al. (2022) conducted a study titled "The Role of Social Networks in Electronic Customer Relationship Management and Marketing Performance," which revealed a noteworthy and positive influence of electronic customer relationship management on marketing performance. Similarly, in their research titled "The Impact of Product Development and Innovation on Marketing Performance", Erlamgga et al. (2022) demonstrated a substantial relationship between product innovation and marketing performance. Hosseini (2020) also found significant effects of product innovation on marketing performance in their study. Setini et al. (2021), in their research titled "The Impact of Innovation on Marketing Performance in Sports Businesses," identified various forms of innovation with significant and positive effects on marketing performance in sports businesses. Additionally, Setini et al. (2021) observed in another study titled "The Effects of Knowledge Sharing, Social Capital, and Innovation on Marketing Performance" that knowledge sharing had a positive and significant impact on both innovation and marketing performance.
Research Methodology
The present study is applied in terms of purpose, and descriptive-correlative in terms of nature. It is field research using a questionnaire-based survey and based on structural equation modeling. The statistical population of the study consists of all managers and supervisors present in the central office, branches, and representatives of Dana Insurance in Mashhad, with a total of 286 individuals. Based on Morgan's table, a sample size of 165 participants was randomly selected. The data collection tool was a questionnaire containing 16 questions related to the main variables of the research. The questionnaire was validated and distributed after its primary distribution. It underwent Cronbach's alpha and composite reliability tests for assessing its reliability, both of which confirmed its reliability. To assess its validity, formal validity, and construct validity (through confirmatory factor analysis) were used and validated. Smart PLS version 3 software was used for data analysis in this study.
Research Findings
For examining and testing the research hypotheses or conceptual model, Smart PLS 3 software was utilized, and the findings indicated a favorable impact with a calculated strength of 0.46 for electronic customer relationship management on product innovation. The t-test statistic obtained (89.3) was greater than the critical t-value at a 5% level of significance (1.96), indicating a significant observed effect. The strength of the impact of product innovation on marketing performance was calculated as 0.67, indicating a desirable effect. The t-test statistic obtained (95.6) was greater than the critical t-value at a 5% level of significance (1.96), indicating a significant observed effect. The strength of the impact of customer knowledge on product innovation was calculated as 0.68, indicating a desirable effect. The t-test statistic obtained (95.7) was greater than the critical t-value at a 5% level of significance (1.96), indicating a significant observed effect. The strength of the impact of customer knowledge on marketing performance was calculated as 0.35, indicating a desirable effect. The t-test statistic obtained (42.2) was greater than the critical t-value at a 5% level of significance (1.96), indicating a significant observed effect. The strength of the impact of electronic customer relationship management on marketing performance through product innovation was calculated as 0.31, indicating a desirable effect. The t-test statistic obtained (5.43) was greater than the critical t-value at a 5% level of significance (1.96), indicating a significant observed effect. The strength of the impact of customer knowledge on marketing performance through product innovation was calculated as 0.46, indicating a desirable effect. The t-test statistic obtained (35.5) was greater than the critical t-value at a 5% level of significance (1.96), indicating a significant observed effect. The mediating role in recent hypotheses is confirmed.
Conclusion
The primary objective of this study was to explore the influence of electronic customer relationship management on marketing performance, with a focus on the mediating roles of product innovation and customer knowledge (Case Study: Insurance Company). The test results are consistent with the findings of previous research (ElFarmawi (2020), Herman et al. (2020), Pedron et al. (2018), Nazari (2018), Garanti et al. (2019), Asgari & Baghestani (2020), Tarabashkina et al. (2020), Hoseini (2020), Ghaderi & Rahimnia (2020), Ghahremanpour et al. (2019), Pramuki & Kusumawati (2021), Rahman et al. (2021), Soekotjo et al. (2021)).
Marketing performance consists of two components: customer satisfaction and trust. The ability of any company to gain customer satisfaction and loyalty justifies the organization's performance. Organizations, considering customers as their assets in competitive markets and aim to identify their needs, gain their satisfaction, and establish long-term relationships, striving for success and improvement in marketing performance. Since the most crucial key for success in businesses is establishing strong relationships with customers, the electronic customer relationship management system, through understanding customer needs and monitoring their behavior, achieves a sustainable competitive advantage. Product innovation and aligning products with customer expectations directly and positively influence marketing performance. Moreover, the greater the quality of electronic customer relationship management and the capacity for customer knowledge sharing, the more it contributes to product development, resulting in a favorable impact on marketing performance.

Abstract Abstract This article aims to compare RW and PW models in profit forecasting for small and medium-sized companies. The research method is applicable in terms of its purpose, and it is an inductive and quantitative research in terms of the implementation logic and the nature of the data. Financial statements in the period of 2011 to 2021 have been used to collect data. In order to select the appropriate statistical sample, the systematic elimination sampling method was used. In this method, firstly, the small and medium-sized companies are identified, according to the number of employees and the nominal value of the capital, and conditions are defined for the selection of the sample, and those that do not have the mentioned conditions are removed from the sample. These conditions are determined according to the hypothesis test model and research variables. Also, in this article, the panel model and Eviuse software have been used to extract the proposed model from the principal component analysis approach and to fit the model to the observations. According to the results obtained from the analysis presented in this research, it can be seen that the new model provided for profit forecasting is more effective than the profit forecasting of RW and PW models, and this issue confirms the ability of regression models to forecast profit in the field of financial and profitability strategies for small and medium-sized companies. Extended Abstract Introduction Financial analysts have grown in number and importance over the decades. The first societies of investment analysts can be traced back to 1925 in Chicago, 1937 in New York, and 1962 in Europe (Graham, 2004). The profession became formalized due to its ever-increasing presence and application in capital markets around the world. Analysts provide useful information in the form of stock releases, price targets, and earnings forecasts as a link between management and investors. Much research has been done on sell-side analysts and their earnings forecasts, as these forecasts increasingly influence investors as well as management (Azevedo, 2020). Without information about firms and their projects, financial markets cannot perform their function of capital allocation. Some information is freely available to investors, but most information is expensive and must be produced by trained professionals. The profession of financial analysts has evolved to perform this economic function and has provided investors with detailed and specialized public information that would be very difficult to do without them. Financial analysts have the necessary combination of technical expertise, industry knowledge, and financial activity needed to understand the future prospects of companies. By publishing analyst reports, they bring stock prices closer to intrinsic values, making the market more efficient in terms of information and directing capital flows to promising investments (Higashikata, 2020). Traditionally, analyst reports contain three separate pieces of information: 1) earnings forecasts, 2) price forecasts, and 3) recommendations on whether to buy, hold, or sell. These forecasts and recommendations can publish private information or create new information from public information, and the change in information has a significant impact on the stock market price. Previous research has shown that revisions to buy or sell recommendations change investor responses. Specifically, recommendation reductions and negative forecast revisions are considered to convey bad information, while recommendation updates and positive forecast revisions are considered to convey good information (Higashikata, 2020). Takamusto and Akono (2019) show that specific factors of countries' information environment can influence the importance of information disclosed by firms, such as accounting standards and governance quality. These characteristics affect the user's understanding of the information and thus the stock price. In addition, uncertainty in countries' information environment can also affect the quality of analysts' forecasts (Hou, 2019). This is reinforced for emerging markets, because the accuracy of analysts' forecasts is strongly associated with the characteristics of each country's environment (Han, 2020). However, Han (2020) stated that analysts have a better ability to understand the different accounting options of firms as well as issues related to countries' information environment. Therefore, according to the above, in this research, we are looking for whether the profit forecasting model presented in small and medium companies is more effective compared to the RW and PW models. Literature benefit predict Profit forecasting has always been an important topic in accounting research because of its proven relationship with market returns. Profit forecasting not only reflects the development of accounting research but also uses the development of statistics and computer science topics. Early research relies on random step and time series models to predict future profits. Some researches also included basic data in the prediction model based on linear regression or logistic regression (Harris and Wang, 2018).   Research background In an article, Ansari (2023) discussed life cycle forecasting and financial performance evaluation of companies using decision tree algorithm and multi-criteria decision making techniques. The purpose of this research is to provide methods for decision-making that can be implemented with minimal specialized financial knowledge. For this purpose, a sample consisting of 172 companies admitted to the Tehran Stock Exchange by company-year was examined. First, financial ratios were prioritized using decision tree regression analysis for life cycle forecasting. Financial ratios have been analyzed as an independent variable and cash flow statement data as a dependent variable. In order to accurately implement the presented models, MATLAB software coding environment was used. The results showed that cash adequacy ratio and debt-to-equity ratio are the most and least important, respectively. Then, using hierarchical analysis, financial ratios were prioritized to evaluate the financial performance of companies, and leverage ratios and profitability ratios were assigned the highest and lowest ranks, respectively. The results of this research can be considered by all investors in the stock exchange to create a clear picture of the financial performance of companies. Melkian. et al (2023) in an article investigated the liquidity shock, financial flexibility and speed of dividend adjustment in Tehran Stock Exchange. To measure the speed of dividend adjustment, which is a measure of profit smoothing, Gholtan regression was used according to the Lintner model; and also the method of De Jong et al and Falkander and Wang have been used to measure the unused debt capacity and the final value of cash, which is an index to measure financial flexibility. According to the limitations of the research, 105 companies admitted to the Tehran Stock Exchange during the period of 2010-2019 have been examined. The findings of the research show that the final value of cash and unused debt capacity do not have a significant effect on the speed of dividend adjustment. Also, the liquidity shock has no effect on the relationship between the final value of cash and unused debt capacity on the speed of dividend adjustment. Based on the obtained results, in justifying the positive relationship between the final value of cash and the speed of dividend adjustment, it can be said that any company that has higher financial flexibility, faces less risk overall and improves the performance of managers when using growth and invested opportunities, and finally smoothing their dividend is higher. Also, in justifying the negative relationship between unused debt capacity and dividend adjustment speed, it can be said that any company that has a higher unused debt capacity, their dividend adjustment is lower. Research methodology In this research, in order to extract the proposed model from the principal component analysis approach, and to fit the model to the observations, the panel model and Eviuse software are used. The difference between the actual and predicted profit is used to measure the efficiency of the models. The central and dispersion indices for the research variables are determined for descriptive analysis of the variables before testing the hypotheses. In order to determine the average level of the variables, the average index is used. The dispersion of observations is measured by the standard deviation. Also, the difference of the variables from the normal distribution is measured using skewness and kurtosis indices. In the present research, it has been used to test the hypotheses in the companies admitted to the Tehran Stock Exchange  Discussion and results: The adjusted coefficient of determination in the first regression model is equal to 0.65 and in the case of RW model 58% and PW model 0.52; this shows that our regression model has been able to provide a more accurate relationship than the other two regression models with the components of profit forecasting, thus, model-based profit forecasting is more efficient than the other two profit forecasting models. Therefore, these results are consistent with the stated claim and at the confidence level of 95, it can be claimed that our profit forecasting model is more efficient than the RW and PW models. Conclusion: In this research, first, the statistical population and the companies included in this population were examined. Then the volume and sampling method were determined. After that, research hypotheses were stated. In the following, the research method and the method of data collection were discussed; Also, the variables examined in the research were introduced and how they were calculated was explained. After the definition of the research variables, the statistical methods necessary to check the statistical hypotheses and their analysis were discussed. Based on this, the present research for the first time compares model-based forecasting and profit forecasting based on RW and PW models in small and medium-sized companies, and according to the results obtained from the analysis presented in this research, it can be found that the proposed model for profit forecasting is more efficient than profit forecasting based on the other two models, and this is a confirmation of the ability of regression models to forecast profit in financial fields and the profitability of stock price forecasting strategy in the Tehran stock exchange also confirms.  

Abstract Abstract The purpose of this research was to investigate the role of Flow theory in viral promotional advergames with an emphasis on sharing personal data and forwarding the games. Using a viral marketing campaign, 393 out of 765 participants clicked on the game link sent via email, But 288 people participated in the game, 141 people answered the questions, invited their friends to the game, or shared their personal data. Poisson regression was used to investigate the role of Flow theory on game forwarding, and logistic regression was used on sharing personal data through Eviews software. Players with intrinsic enjoyment and psychological Flow (dimensions of Flow) tend to invite more people to the game and share more personal data about themselves. Perceived reward value is also positively related to game forwarding behaviors, although not related to sharing personal data. That is, players seem to communicate more about the game when they have extrinsic motivation (rewards), but are less likely to share personal data with the brand. On the other hand, extrinsically motivated players still have significant privacy concerns. In contrast, Flow is positively related to sharing personal data, suggesting that fully immersed players tend to "lose themselves" and forget about their more conscious concerns and thus appear more likely to share personal data with the brand. Companies that want to capture customers' personal data should focus more on designing game elements than rewards in such a way as to stimulate the psychological Flow of the players. Extended Abstract Introduction The implementation of viral marketing in the framework of launching a viral campaign in the form of a video or an attractive content in the form of a game is produced and then advertised online to the target audience. Basically, users are quickly attracted to this ad and share it widely. The virality of an advertisement or message in the form of a game is done randomly and is suddenly welcomed by many people, but the design and implementation of viral campaigns requires a lot of planning and creativity to be able to manage it during the campaign activity, so that it moves on the right track. In this regard, games are an important part of advertising campaigns and have attracted a lot of attention from academics and experts in this field. Previous research has been mostly about in-game advertising or advertising games and the distinction between them (Castiblanco Jimenez, I.A. et al.,2023). Viral Promotional Advergames combine a prize advertising game with an advertising game in a viral marketing campaign aimed at encouraging word of mouth to drive immediate responses and behavioral reactions from players towards goals such as; sharing personal data; forwarding the Game to friends lead to increase consumer knowledge of the brand and improve their attitude towards that brand. In this regard, Mihaly Csikszentmihalyi's Flow Theory (1975) is used, which considers Flow as a special mental state that appears when performing an action, in which the actor focuses on a task in such a way that he has a sense of adherence to, and completely Flows/immerses himself in the work and the satisfaction of the process of doing the work. In fact, he is so engrossed in doing it that he doesn't feel time, place, tiredness, hunger or unhappiness and concentrates on pursuing his work. But when they did the work, they lost that attachment and focus (Lavoie, R., & Main, K. 2019). In fact, the result of the work is not so important for these people, but it is the nature of the work they are doing is important to them. In the current research, it is investigated what factors will lead to such behavior, such as the mental state that these people experience while engaging in their profession and skills, and which is called the Flow state. It is a state in which a person is so engrossed in a task that nothing else matters to him, and this experience is so enjoyable that it is done only for its own sake. No studies have addressed the Flow experience in the context of viral advergames. Flow in the game, including enjoying and disappearing in the game, directs the responses and immediate behavioral reactions of the players towards actions such as forwarding the game and sharing personal data, and in the marketing process it plays as an important strategy for advertising or comprehensive advertising of a brand, product or service(Kim, Yoon Jeon & Ifenthaler, Dirk. 2019). Finally, the main question is how the Flow theory in Viral Promotional Advergames can lead players to forwarding games to friends and others and sharing personal data?. Theoretical framework Games have evolved over time and with the advancement of technology. An emerging form of gamification is designed as part of viral marketing campaigns, where consumers play the gambit to win sales promotions. The target consumers of such games are mostly adults rather than children. During the game, players can increase their chances of winning if they share their personal data or if they invite their friends to play the game. To distinguish this type of game, which is a combination of a promotional game for the purpose of a prize with an advertising game for the purpose of advertising in a viral marketing campaign, the term Viral Promotional Advergames is used. Due to the nature of advertising games, Viral Promotional Advergames often contain advertising messages of a brand and try to increase one's perception of the brand's status and attract positive consumer opinion (Zhao, Z., & Renard, D. 2018). Also, viral advergames are often designed as contests that allow consumers to win prizes due to luck or skill, and are intended to elicit immediate behavioral responses, with the promise of an increased chance of winning if those behaviors are performed. Previous literature describes consumers' cognitive and affective perceptions of different types of games, although it mainly focuses on children as participants. The current research examines adult gamers' behavioral reactions to Viral Promotional Advergames: namely, sharing personal data and Forwarding games. In addition, it examines how the internal and external values of adult players motivate such behaviors. Extensive empirical research confirms that Flow theory influences consumers' cognitive, emotional, and behavioral responses such as attitudes, behavioral intentions, and actual behaviors (Sarkar, J.G., Sarkar, A. and Sreejesh, S. 2023). A few researchers have applied Flow theory to advergames, but no studies have addressed experiences of Flow theory in the context of viral advergames or examined specific consumer behavioral outcomes of sharing personal data and game Forwarding. For the measurement of drowning, the existing approaches are either unidimensional or multidimensional. Multidimensionality typically includes attributes such as challenge, mastery, control, focus, enjoyment, curiosity, arousal, involvement, playfulness, telepresence, and time distortion. One popular unidimensional measure relies on perceived playfulness, as with more immersive games, enjoyment and concentration have stronger effects on player perception and behavior. Playfulness exists to some extent in any activity in which one freely engages. This structure is reflected in the two dimensions of pleasure and intellectual freedom (disappearing into work). Both dimensions indicate a state of psychological Flow. Both intrinsic and extrinsic benefits can stimulate social sharing behaviors. With regard to intrinsic benefits, emotional diffusion theory suggests that social sharing occurs when people need to share their evoked emotional experience with others (Lavoie, Raymond & Main, Kelley & Stuart-Edwards, Anastasia. 2022). According to the existing literature, intrinsic enjoyment leads to a stronger intention to participate in online word-of-mouth advertising. Perceived playfulness implies a sense of engagement that is inherently pleasurable, creating a positive emotional state. In the context of Viral Promotional Advergames, players' enjoyment of the game should lead to more positive evaluations, which increases the value of sharing personal data and Forwarding the game. Methodology This research is applicable in terms of purpose, cross-sectional survey method in terms of method, and purposeful and accessible in terms of selection of the research sample. In this study, data was collected using a pre-test-post-test method with a real viral marketing campaign. An advertising game was created for a weekly cultural magazine (at the request of magazine officials, magazine details are not reported) and data was collected during the campaign. Subscribers are people who provide their email address in exchange for promotional offers. In the pre-test stage, subject to the respondents' agreement to participate in the survey, in the first step, they received an email with a self-administered questionnaire about their attitude towards the weekly brand. In the post-test phase, participants received another email asking them to participate in a viral advertising game and to allow their behavioral data to be collected during the game for research purposes. At last, 393 out of the 765 participants clicked on the game link sent via email, but 288 participated in the game; and 141 people answered the questions, invited their friends to the game, or shared their personal data. Finally, Poisson regression was used to investigate the role of Flow theory on game forwarding and logistic regression was used on sharing personal data through Eviews software. Discussion and Results  Flow is positively related to game Forwarding and personal data sharing behaviors, such that if games elicit higher levels of enjoyment and concentration, the players may also be more willing to share personal data and Forward games. While the perceived value of prizes has a positive and significant effect on Forwarding games by players, it will not have a significant effect on sharing personal data. Also, prior attitudes towards the brand moderate the effect of perceived value of rewards on game Forwarding behavior. Also, players with inner pleasure and psychological Flow (dimensions of Flow) are more inclined to invite more people to the game and share more personal data about themselves. Perceived reward value is also positively related to game Forwarding behaviors, although not related to sharing personal data. That is, players appear to communicate more about the game when extrinsically motivated, but are less likely to share personal data with the brand. On the other hand, extrinsically motivated players still have significant privacy concerns. In contrast, perceived playfulness is positively related to personal data sharing, suggesting that fully immersed players tend to "lose themselves" and forget their more conscious concerns. As a result, they seem more likely to share personal data with the brand. Another interesting result comes from the absence of a reciprocal relationship between intrinsic and extrinsic motivation with regard to both behaviors. The reason can be the complexity of external rewards in this study. Conclusion Players with intrinsic enjoyment and psychological Flow (dimensions of Flow) tend to invite more people to the game and share more personal data about themselves, and perceived reward value is also positively related to game forwarding behaviors, although not related to sharing personal data. That is, players seem to communicate more about the game when they have extrinsic motivation (rewards), but are less likely to share personal data with the brand. Therefore, it is suggested; Companies that want to obtain customers' personal data should focus more on the design of game elements rather than prizes because the perceived value of prizes does not seem to have a significant and meaningful effect on the sharing of personal data. Games should also be designed in such a way as to induce psychological Flow/immersion in players; that is, game design elements should optimize the Flow or peak situation. On the other hand, companies that want to encourage players to submit their game should focus on both game design and prize placement, and prizes should be offered at different value levels to bias players' evaluations of more prizes. Previous research shows the importance of Flow for predicting learning, control, exploratory behaviors, positive subjective experiences, and other behavioral intentions (Lavoie & Main, 2019). Whereas, no previous studies have addressed the experience of Flowing/peaking in the context of Viral Promotional Advergames or examining Sharing Personal Data and game forwarding behaviors. With a field study of a real campaign of Viral Promotional Advergames, real data on player behavior is collected and how the intrinsic Flow/peak and extrinsic value of rewards are related to player behavior is measured. To measure intrinsic Flow/peak, players' perception of game playfulness was assessed (Chen, L.; Zhou, P.; Xiao, H. 2023). The results show that immersion in the game (enjoyment and immersion in the game) is positively related to game forwarding and Sharing Personal Data behaviors, while the external criterion related to the perceived value of rewards is positively related to game forwarding, but not to Sharing Personal Data. Furthermore, prior brand attitudes (prior to playing viral promotional games) moderate the effect of perceived value of rewards on game forwarding behavior.

Abstract Abstract The aim of this research is to present a model for the development of the tourism industry with an emphasis on the role of media management using a mixed approach. A mixed (qualitative-quantitative) approach has been used in this research. The statistical sample in the qualitative part included 15 professors and specialists and experts in communication, media and tourism: and in the quantitative part of the research, it included 200 managers and senior tourism experts in Mazandaran. In the first step of the research, the coding of the specialized research interviews was done using the qualitative analysis of the theme with MAXQDA v10.R150410 software. In the next step, the results of confirmatory factor analysis with Smart PLS software are presented. Then, the existing categories were leveled with the structural-interpretive method with MicMac software and the initial research model was designed. Based on the results obtained in this research, advertising, service quality, policy making, participation of local people, tourism culture, proper use of the environment, income generation in tourism destination and infrastructure facilities were identified as the main components that have an impact on the tourism industry. The results of the quantitative part of the research showed that the proposed model has a good fit and credibility for the impact of mass media on the development of the tourism industry. Extended Abstract Introduction Undoubtedly, tourism is one of the most prosperous service industries worldwide. Tourism is vital to the economic success of many countries around the world. Over the past two decades, some countries have been able to achieve very high incomes despite the shortage of natural resources by investing in the tourism industry (Qiu et al., 2020). There are numerous benefits of tourism in host destinations. Tourism increases economic income, creates thousands of jobs, develops a country's infrastructure, and creates a sense of cultural exchange between foreigners and citizens. The number of jobs created by tourism in many different regions is significant. These jobs are not only part of the tourism industry, but may also include the agricultural, communication, health, and educational sectors. Many tourists travel to experience the culture, different traditions, and cuisine of the host destination. This is very profitable for local restaurants, shopping centers, and shops. For instance, in Melbourne, Australia, with a population of about 4 million, approximately 22,000 citizens are employed only in the tourism sector (Fjelldal et al., 2022). With the recognition of the economic importance of tourism, many governments and tourism companies have started extensive advertising campaigns to brand their destinations and attract tourists. As a result, there is now intense competition among tourism organizations (as well as different governments) to introduce domestic tourism destinations and attract as many tourists as possible. Therefore, marketing has essentially become a key component for success in the tourism industry (Yung et al., 2021). Considering these marketing efforts, marketing is essentially a type of messaging to customers (both potential and existing). The important role of the media in introducing tourism destinations and creating a destination brand can be understood (Alsalami & Al-Zaman, 2021). Although the use of media, including radio and television advertising, billboards, and more, has a very long history in the tourism industry, the advent of technology-based media has caused a great transformation in tourism advertising. Information is a vital lifeline for the tourism industry; therefore, effective use of information technology and modern mass media is crucial for competitive advantage and success. As a result, many companies involved in the tourism industry have chosen to use modern media as their most important marketing and customer interaction tool (van Nuenen & Scarles, 2021). Therefore, there is a need for research that focuses on providing a native approach to developing a model for the tourism industry with an emphasis on the role of media management. The main issue of this study is the neglect of the capacity of media as a key tool for successful tourism marketing within the country. In this study, a model for the development of the tourism industry with an emphasis on the role of media management using a mixed approach is presented. This research seeks to find an answer to the question of what components make up a model for developing the tourism industry based on media management. Theoretical framework Tourism is the act and process of spending time away from home in pursuit of leisure, relaxation, and enjoyment while also utilizing commercial services. Thus, tourism is a product of modern social arrangements that began in Western Europe in the 17th century, although it has roots in classical antiquity. Tourism differs from exploration in that tourists follow a "well-established path," utilize established supply systems, and, as befits pleasure-seekers, are generally immune to difficulty, danger, and embarrassment (Rasulov, Madjitova & Islomova, 2022). However, tourism overlaps with other activities, interests, and processes, such as pilgrimage, for example. This has led to the creation of common categories such as "business tourism," "sports tourism," and "medical tourism" (international travel for the purpose of receiving medical care) (Palacios-Florencio, Santos-Roldán, Berbel-Pineda & Castillo-Canalejo, 2021). In the past few decades, the trend of tourism has grown significantly worldwide, as the concept of travel has changed in people's lives. In the past, traveling was often a cumbersome and sometimes frustrating experience that required constant planning. However, today, thanks to technology and changes in lifestyle, this concept has become an incredibly enjoyable and effortless experience. People travel for business, holidays, leisure, adventure, or even medical treatments. These issues have led to the emergence of a booming tourism industry, with successful countries earning substantial incomes from this sector (Zhu, Airey & Siriphon, 2021). Tourism marketing is a term used to refer to the commercial field that attracts visitors to a particular location, which can be a state, a city, a specific heritage site or tourist destination, a hotel, or a convention center. The location can be anything that has the potential to attract tourism, as people visit a new place for tourism purposes. Tourism marketing is often associated with marketing strategies in the tourism industry. Nowadays, many countries in the world have a significant role for tourism in increasing their gross domestic product (GDP), making tourism marketing an essential factor. Many places are often tourist hotspots, such as the Taj Mahal in India, and are now the best areas to strengthen tourism marketing. Places that are likely to be the main attraction for tourists are the places where tourism marketing has the most significant impact. Currently, tourism marketing is all about using multiple marketing techniques and strategies to enhance the tourism industry of a particular place (Liu, et.al, 2022). Research methodology The present study is aimed at the field of developmental research, and in terms of approach, it falls under exploratory studies. Based on the type of data, this research is categorized as a mixed-methods study (qualitative-quantitative). In the qualitative stage, the sample included 15 professors, experts, and specialists in communication, media, and tourism at universities in Mazandaran. The sample size is determined based on theoretical saturation. Given the research topic and objectives, a semi-structured interview method was used to collect data. In the quantitative stage, the statistical population included managers and senior experts in tourism throughout Mazandaran province (N=412), from which a sample of 200 people was selected. To determine the validity and reliability of the interviews, the retest and inter-coder agreement methods were used. In this research, the content analysis method was used to analyze qualitative data. In the next stage, the results of confirmatory factor analysis are presented. Then, the existing issues are classified using the structural-interpretive method, and the initial model of the research is designed. Finally, the partial least squares method is used for model validation. Qualitative analysis was performed using MAXQDA software, structural-interpretive analysis using MicMac software, and partial least squares method using Smart PLS software. Research findings Given that the retest reliability rate is 85%, which is higher than 60%, the coding reliability is acceptable. Additionally, considering that the intercoder reliability rate is 79%, which is also higher than 60%, the coding reliability is acceptable. Based on the results of the qualitative data analysis; advertising, service quality, policy-making, local community participation, tourism culture, appropriate environmental management, tourism income generation, and infrastructural facilities were identified as the main components that impact the tourism industry. The results of the quantitative section showed that the proposed model has a good fit and validity for the impact of mass media on the development of the tourism industry. Conclusion
Numerous research studies have been conducted on the components and indicators of media management in the tourism industry, with an emphasis on media management perspectives. However, there are still various concepts and different measures for these perspectives that need to be investigated and standardized to achieve a comprehensive view. Generally, the most important components include advertising, service quality, policy-making, participation of local people, tourism culture, proper environmental management, income generation at the tourist destination, and infrastructure facilities. In conclusion, media has a significant role in creating a platform for the expansion or recession of activities related to this sector, given its capabilities. By careful and controlled planning, media can shape the thoughts and behaviors of a community and expand their desired perspectives. Today, through modern forms and audience-friendly media, they are the largest and most effective tool for producing concepts, social relations, and cultural messages in societies. Radio, television, newspapers, the internet, and modern media are indirect communication tools that have the power to influence, apply taste, and shape mentality. Media and its quantitative and qualitative advances are leading recent movements in all dimensions of life and development of communication. Visualization, needs assessment, persuasion, awareness, effective communication, and the use of new technologies in the field of media have placed many countries among the top tourist destinations in the world. With the development of communication technologies and the formulation of work and safety laws, tourism has reached such a position in the current global conditions that one cannot ignore its countless benefits.