Journal of value creating in Business Management

Abstract Abstract The aim of this research is to sociologically explain the bottlenecks and challenges affecting the economic development of small and medium-sized enterprises with a data-based approach. The research method is applicable developmental in terms of purpose, descriptive exploratory in terms of strategy, and qualitative in terms of implementation method, with a grounded theory approach. The statistical population of the research includes 14 experts and academic scholars in the economic-sociological field. The sample size was selected using the snowball sampling method. A semi-structured interview was used to collect information. A grounded theory approach was used to analyze the data. The validity of the interview questions was confirmed by the content method; and its reliability by implementing the test-retest method (0.897). Based on data-based theorizing; causal conditions (including interactional/identity conditions and generational gap conditions), the central category (the process of lack of economic development and growth), the context makers (including weak cultural capital and lack of competitiveness), contextual factors (including lack of development thinking and low investment rates), strategies (including lack of purpose-centeredness and lack of value-centeredness), and consequences (including continued underdevelopment and business collapse) were explained in the paradigmatic model, and finally the relationships between them were identified in the selected model. Introduction Sociological components and factors cause differences among humans in ethics, responsibility, spirituality, dynamic management, entrepreneurial initiatives, risk-taking, and many other behaviors that are likely to affect the economic success of individuals (Throsby, 2001). Iran's economy is currently facing bottlenecks in various areas, for which a solution must be found for each of them. Perhaps one of the most important challenges is in the field of production. Although production and how to make it flourish is itself an important challenge, we will also face other challenges to make production flourish. The fragile recession caused the closure of many economic enterprises in the country; so much so that the government's 16 trillion rial financial assistance could not seriously solve the problems of small and medium-sized enterprises (Rezaei & Safa, 2016). The interest of economists and sociologists in the institutional manifestations of small enterprise development and their role in economic development has recently increased. This socio-economic concern is well reflected in the fact that all theories of entrepreneurship tend to trace the sources of economic change to the activities exerted by certain types of individual or collective agents (Gruzina et al, 2021). Unlike economics, sociology has been interested in analyzing companies as social institutions or social organizations from the very beginning, and a sophisticated analysis of this tradition remains today. Max Weber initiated this tradition, which has continued in the field of industrial sociology and today in the sociology of organizations, and is still alive in the field of industrial sociology and related fields, namely the sociology of work (Swedenborg, 2012). The most important influential factor is the marketing power of these companies to sell their products; therefore, the lack of sufficient information of companies in Arak city about the needs of the market at home and abroad is weak, which has faced these companies with the problem of lack of demand for their products, and this has an impact on sales and profitability. The results of comparisons of the implementation performance of the regulations on quick-turnover enterprises in Markazi province during the period under review also show that, in general, the industry and mining sector has had a negligible contribution to most of the indicators examined in this study. Due to the industrial nature of this city, it is desirable that by implementing effective support policies, the effectiveness of industry in the province’s GDP and employment can be realized. Therefore, serious support for early-stage industrial projects, removing existing obstacles in small and medium-sized enterprises, using the effective model of priority industries in Arak city, and providing the grounds and preparations for more investment in this city can be effective in increasing the share of small and medium-sized enterprises and their role in the development of the province. Accordingly, the present study seeks to answer this question: What are the sociological bottlenecks and challenges affecting the economic development of small and medium-sized enterprises with a data-based approach? Theoretical Framework Economic Development Economic development is economic growth accompanied by fundamental changes in the economy and an increase in production capacities, including physical, human, and social capacities. In economic development, a small growth in production will be achieved, but along with it, social institutions will also change. Economic development has goals that include: increasing the wealth and welfare of the people of society, reducing poverty, and creating employment, which are goals for achieving social justice. The view of economic development in developed and underdeveloped countries is different. In underdeveloped countries, the main goal is to increase the welfare and opportunities of the people, while in underdeveloped countries, the main goal is to eradicate poverty and increase social justice (Vahed Moghadam & Kaykha, 2015). Small and Medium Enterprises Small and medium enterprises are considered the backbone of an economy because they play an important role in poverty reduction, employment generation, promotion of foreign trade and technical innovation, and also significantly contribute to the growth of developing economies (Elahi Shirvan et al, 2023). Taromi (2024) studied the impact of small and medium enterprises and their role in economic development. The results showed that what is effective in the efficiency of these units in the economy of any country is that these units provide their goods or services to consumers in a competitive environment with the lowest cost and time, while complying with various standards of transportation - storage - sale. Rostamian et al, (2023) studied the effects of small and medium enterprise credit on economic growth and employment (a dynamic computable general equilibrium model). The results of the analysis of the employment rate in small, medium (and large) enterprises showed that the employment rate increased during the period from 2005 to 2012), considering the credit ceilings of 20, 30, 40 and 50 percent made by the government. Therefore, it can be said that the amount of credit allocation has a direct relationship with the production rate of small, medium (and large) enterprises and consequently the amount of employment. The amount of employment in large enterprises was higher compared to small and medium enterprises, which is due to the centralization of the integrated management system and the greater type of support that the government provides to these types of enterprises. Research Methodology The research method is applicable developmental in terms of purpose, descriptive exploratory in terms of strategy, and qualitative in terms of implementation method, with a grounded theory approach. The statistical population of the research includes 14 experts and academic scholars in the economic-sociological field. The sample size was selected using the snowball sampling method. A semi-structured interview was used to collect information. Research findings A grounded theory approach was used to analyze the data. The validity of the interview questions was confirmed by the content method; and its reliability by implementing the test-retest method (0.897). Based on data-based theorizing; causal conditions (including interactional/identity conditions and generational gap conditions), the central category (the process of lack of economic development and growth), the context makers (including weak cultural capital and lack of competitiveness), contextual factors (including lack of development thinking and low investment rates), strategies (including lack of purpose-centeredness and lack of value-centeredness), and consequences (including continued underdevelopment and business collapse) were explained in the paradigmatic model, and finally the relationships between them were identified in the selected model. Conclusion The present study was conducted with the aim of sociologically explaining the bottlenecks and challenges affecting the economic development of small and medium-sized enterprises using a grounded theory approach. The results of this study are consistent with the results of Taromi (2024), Rostamian et al, (2023), Muthuraman et al, (2021), Pedraza (2021), Nazari et al, (2021), Kushins et al, (2020), Kawaguchi (2019), and Bani Fatemeh et al, (2017). Nazari et al, (2021) showed that business cultural components have a positive effect on the production-commercial performance of industrial units. The research findings also indicate that the components of low power distance, individualism, low uncertainty avoidance, long-term orientation, and masculinity have a positive effect on the production-commercial performance of industrial units. One of the causal conditions affecting the bottlenecks and challenges affecting the economic development of small and medium-sized enterprises from a sociological perspective is the interaction/identity conditions. Maintaining power is highly valued in collectivist societies; therefore, there is no desire to delegate authority and involve colleagues in decision-making. In this regard, industrial managers are suggested to place the types of management on a bipolar scale according to the amount of authority delegated to subordinate colleagues. If these types of economic enterprises want to develop and continue in generations, they must first remove the obstacles and problems within the organization in terms of realizing meritocracy, prioritizing expertise, training members, etc. by observing organizational principles and management hierarchy. They should try to provide easier generational transition areas by using non-family specialist managers and by separating ownership from management.

Abstract Abstract
The main goal of this research is to design the maturity model of the fourth industrial revolution in the supply chain of banking services and the development of digital banking with the data-based approach. The current research is, qualitative type based on strategy, and it is in the basic research categories in terms of goal. The data collection method is field research, and the data collection tool is a semi-structured interview. The participants of the current research are the senior managers of the country's banks, experts and activists in the field of digital banking, and using the sampling method, 10 people were selected as participants in the research. It should be noted that the interview has progressed to theoretical saturation. Qualitative data obtained through interviews were analyzed using the data-based theorizing method. Qualitative data analysis was done using Max Kyoda software version 2020. According to the results obtained, the categories identified in this research include ten categories in the causal conditions section, seven categories as components of the central phenomenon, four categories related to contextual conditions, eleven categories in the strategies section, and seven categories for intervening conditions. And finally, there are eight categories for the consequent part of the model.
Introduction
In the last few years, technology has been developing rapidly and big data or mega data, computing or cloud computing, smartphones and high bandwidth are now commonplace. Examining and comparing the effects of technology in other industries shows that digital has created great changes in the status and value of the industry (Barazideh et al., 2024). There is much pressure to change and transform the banking industry. Customer experiences and expectations, technological capabilities, legal requirements, demographic and lifestyle issues, and economics all create an inevitable necessity for change. It is obvious that the digital age has had a pervasive impact on every industry and organization (Ramzanpour Osmavandani et al., 2024). Digital transformation management is the determining factor of the survival or destruction of organizations in this era, and now it is the era of transition from traditional models to technology-oriented and value-creating business models. In recent years, the new generation of banking under the name of digital banking has been operationalized in the world and the main attention of leading banks has been focused around the axis of digital transformation (Karimi et al., 2023. (
Over the years, the development of new services in the banking and financial sector has been driven by telephone banking, online banking and other forms of fintech (Hasan et al., 2020). These developments enabled the banking sector to overcome the global challenges associated with facilitating transactions across industries, thanks to improvements in accessibility, speed, efficiency, effectiveness and transparency. However, the introduction of digital banking, focusing on technologies such as blockchain, has been announced as the next evolutionary step that will transform not only the banking and financial industry, but also the nature and execution of corporate transactions (Osmain et al., 2021).
Therefore, the use of new mechanisms such as blockchain with all kinds of monetary services brings the possibility of causing widespread disruption in the banking industry. As a result, it includes activities such as facilitating international money transfers, smart contracts, digital banking, office automation and digital assets. Thus, it provides an opportunity for relevant stakeholders to contribute to the improvement of openness, trust and privacy issues. However, although blockchain technology has provided many opportunities for businesses, it is necessary to realize that there will be many problems and complexities in the areas of adoption as well as in the areas of technology and regulation. For example, the numerous risks caused by the loss of digital money and cyber security breaches are examples of recent incidents that have revealed a high level of risks associated with the use of blockchain technologies in banking and finance (Demirhan et al., 2021). According to the items mentioned above, the main question of the current research is:
How to fully recognize, evaluate and design the maturity dimensions of the fourth industrial revolution in the supply chain of banking services and the development of digital banking using a data-base approach, so that banks can use modern optimizing technologies to provide their services, improve financial performance and customer experience?
Theoretical framework
In the fourth industrial revolution, the emergence of major technologies such as artificial intelligence and the Internet of Objects has led to extensive changes in business models, among which banks have had a greater share of these developments. Despite the research conducted in the field of business model change in the fourth industrial revolution, the issue of transformation in the supply chain of banking services in the fourth industrial revolution has been almost neglected (Shahabi et al., 2021). The competition between banks and financial institutions, the emergence of digital technologies, the problems caused by sanctions, the continuous change of customer requests and the needs of society have made planning for the development of digital banking an undeniable necessity for banks. Digital technologies (such as social media, mobile, cloud computing, Internet of Objects and other digital technologies) offer great opportunities for organizations to provide new value propositions, especially by combining their existing capabilities with new digital capabilities. In addition, digital technologies will increase user experience and create new revenue streams (Asqari et al., 2018).
Chaidar et al., (2023) in their paper investigated the dynamic relationship between fintech investments and financial performance and showed whether the size of the bank can affect its performance in the field of digital transformation (digitalization) or not. The fully modified ordinary least squares model is estimated for 23 European banks in the whole period from 2010 to 2019 and for two sub-periods from 2010 to 2014 and from 2015 to 2019. Econometric results show that fintech is positively and significantly related to bank profitability, in the sense that the more digital interaction banks have, the higher the profitability.
 In their research, Avianto et al., (2024) analyzed the differences in book prices of banks based on the level of digitalization and investigated the effect of digitization and financial factors on the value of book prices of banks with digital services. The analysis of the results of this study shows that higher levels of digitalization are associated with improvements in the share of fee income, return on equity and price to book value of the bank. Additionally, the level of digitization enhances equity returns, improves non-performing loans and increases capital utilization, all of which significantly impact book value.
Zhao et al., (2024) in their study investigate the effects of corporate digitization on green transformation in listed resource-based companies in China from 2009 to 2021. The data analysis of this research shows that digital transformation significantly increases the sustainability of these companies.
Ayinaddis et al., (2024) in their study analyzed the perceived effects of digital transformation in the banking industry and identified the factors that most affect banking performance and business volume. Based on the obtained results, the strengthening of the impact of digital transformation in banking and the vital importance of employees' skills and the digital experience of shareholders have been highlighted.
Research methodology
Based on the type of data, this research is considered as a qualitative research and according to the purpose of the research, it is considered as a basic and exploratory research, which seeks to design a model for the maturity of the fourth industrial revolution in the supply chain of banking services and the development of digital banking.. The participants of the research are senior managers of the country's banks and experts and activists in the field of digital banking, 10 of whom were selected by theoretical sampling and interviewed. In selecting the samples, an effort was made to select the most knowledgeable and well-known managers. The interviews have been repeated in order to share the preliminary findings, complete, correct, revise and adjust the data.
Research findings
In the current research, according to the purpose of the research to design a model for the maturity dimensions of the fourth industrial revolution in the supply chain of banking services and the development of digital banking, the researcher has used the data-based theorizing method in the style of Strauss and Corbin. In this research, the researcher started the interviews with targeted sampling of the desired samples and questions about the maturity dimensions of the fourth industrial revolution in the supply chain of banking services and the development of digital banking. In the central coding step, while the interviews were progressing, the relationship of the categories in the relative sampling of the codes of the interviews was determined to some extent. In the last step of selective coding, a selective sampling of the categories was carried out and according to the causal conditions raised in connection with the maturity of the fourth industrial revolution in the supply chain of banking services and the development of digital banking from the samples in connection with Phenomenon-oriented, strategies, contextual conditions, intervening conditions, and finally, the consequences of questions were asked and finally, in the supplementary stage, according to the literature of this field and theoretical foundations, the final form of the model was completed.
Conclusion
In the era of technological advancement and innovative disruption, digital banking with artificial intelligence has emerged as an alternative technology for channel management, services and online banking solutions. Although the emergence of artificial intelligence in digital banking has enriched digital banking services, the adoption of digital banking with artificial intelligence and meeting the expectations of digital banking users is still an important issue. According to the results obtained from the model presented in this article, and according to the strategies identified in this model, the country's banks can create value for customers and improve their financial performance. Also, other consequences include personalized services, structural improvement, creation of new institutions and organizations, re-engineering of processes, creation of a suitable banking business model and finally improvement of customer performance.

Abstract Abstract The purpose of this research is to investigate the impact of environmental stimuli on the implementation of the agility policy in logistics villages of Tehran province. The current research is applicable-developmental in terms of purpose. The statistical population of the research includes managing directors and members of the board of directors, deputies, managers and heads and supervisors of different departments of logistics villages in Tehran province, whose number is 99 and the sampling method is total number. The information collecting tool was the questionnaire of environmental stimuli made by the researcher, taken from the qualitative section. The reliability of the research was checked and confirmed using Cronbach's alpha criterion in SPSS software. SPSS software was also used for data analysis, and PLS software was used for structural equation modeling. The findings of the research showed that the acceptance percentage of the language term "very high pressure and impact" is confirmed for the category of the impact of environmental stimuli on the implementation of the agility policy of the administrative system of logistics villages in Tehran province, and also the model has a good fit. Extended Abstract Introduction One of the most important policies included in the policies of the administrative system announced by the Supreme Leader is the issue of making administrative structures agile and flexible (paragraphs 10 and 11 of the mentioned document) (Office of Preservation and Publishing of Her Holiness's Works, 2009). And the reason for this importance and emphasis on it is the scientific and research propositions of great scientists and researchers such as Goldman (1995) and SE Lootah et al, (2020) that tie the issue of agility of administrative systems to their survival and organizational life. Evaluation is part of the most important requirements for the perfection of public policies, including the agility of administrative systems, which guarantees their thought-oriented, accurate implementation, and continuous improvement (Vaezi & MOhammadi, 2017). According to many experts, evaluation of implementation is a legal requirement, but in principle, evaluation is a way for effectiveness, policy improvement, policy development, service delivery, ensuring the fulfillment of needs, and using existing potentials. The main core of the new policy is the evaluation that can lead to the effectiveness and efficiency of the service (Equality and Human Rights Commission (EHRC)); this proposition is obviously imaginable and generalized for evaluation of agility policy in logistic villages. Determining suitable areas for the construction of logistics villages and determining its functions in the "Document for the preparation of logistics centers of the country" as an upstream document in 2017 was approved by the Ministry of Roads and Urban Development of IRI., and "Public Warehouses and Customs Services Company of Iran" to as the only example of logistics centers in the country, whose nationalization was approved by the Revolutionary Council of IRI. in the meeting dated 2/20/1359, will be studied as the target community. Logistics centers in different countries not only act as connecting points of different types of transportation, but have appeared as links connecting trade and transportation (Uyanik et al, 2018), which shows the importance of these institutions in the formation and development of logistics in the country.  Therefore, the researcher is trying to answer the question: what is the effect of environmental stimuli on the implementation of the agility policy in logistics villages of Tehran province? Theoretical Framework Policy The measures necessary for the effectiveness or execution of the selected policies are concentrated, which is called policy implementation. Enforcement of public policies refers to the enforcement of a specific policy decision in accordance with the law, the court, or the directives of any administrator. In the process of managing policies, they are often developed or added in their details. One of the main stages of policy making is its implementation stage. Establishing a logical and appropriate communication between policy makers and implementers is considered one way to develop countries and it will cause the opinions of employees at the level of organizations and the views of people at the level of society to be somehow involved in policy making and drafting of laws. Paying attention to implementation in the policy-making process accelerates the realization of the goals of the system and leads to the realization of bureaucracy in society (Parsanasab et al, 2022). Organizational Agility Organizational agility can be considered an organizational competency and ability to effectively engage with the ecosystem and help organizations to keep up with technological, economic, social and cultural challenges in a changing environment (Dupont, 2019). Research background  Rahimi et al, (2023) discussed the effect of using knowledge management on organizational agility with the mediating role of innovation in defense project-oriented organizations. The findings of this research showed that the application of knowledge management had a direct, positive and significant effect on the agility of defense project-oriented organizations with a coefficient of 0.498, and it can also increase organizational agility through organizational innovation with an indirect effect and a coefficient of 0.363. Therefore, defense project-oriented organizations should focus more on the effective implementation of knowledge management, so that through strengthening innovation and improving the level of organizational agility, they can respond to the rapid changes in the defense environment and create a suitable level of defense deterrence. Parsanasab et al, (2022) examined the presentation of a model for the acceptance of public policies in the field of personnel by the target community. The relevant results showed that the value of the GOF index for the numerical model is equal to 0.495, which is a strong index and shows the overall high quality of the model. Based on this index and other indicators of the model, it was proved that the 22 identified criteria can, in general and in the form of a model, well measure the acceptance of the public policy, and the effects of each of the criteria present a suitable predictability. The impact of the identified variables in the model showed that all the identified factors have a significant effect in explaining the acceptance of the policies. The factor of interference and policy dependence, the methods of implementing the interference policy and the culture of the target society, and the environment of the target society have the greatest effect in explaining the acceptance of policies, and organization has the least effect.   Research methodology The current research is applicable-developmental in terms of purpose. The statistical population of the research includes managing directors and members of the board of directors, deputies, managers and heads and supervisors of different departments of logistics villages in Tehran province, whose number is 99 and the sampling method is a total number. The tool for collecting information was the questionnaire of environmental stimuli made by the researcher and taken from the qualitative section. The reliability of the research was checked and confirmed using Cronbach's alpha criterion in SPSS software. Research findings SPSS software was used for data analysis, and PLS software for structural equation modeling. The findings of the research showed that the acceptance percentage of the language term "very high pressure and impact" is confirmed for the category of the impact of environmental stimuli on the implementation of the agility policy of the administrative system of logistics villages in Tehran province, and also the model has a good fit. Conclusion The present study was conducted with the aim of investigating the impact of environmental stimuli on the implementation of the agility policy in logistics villages of Tehran province. The results of this research are consistent with the results of Rahimi et al, (2023), Jamaluddin Ahmad (2020), Jae Moon (2020), Jamaluddin, Ahmad (2020), and Tavakoli Rudi et al, (2019). Jamaluddin Ahmad (2020) showed in a research that the use of management information systems based on information and communication technology had a significant impact on the quality of local government financial reports and accountability and transparency of local government. According to him, these results are strengthened by using the principles of government agility in the form of government agencies that use skill, accountability, flexibility agility, and competence agility. According to the research results, it is suggested: - Involving stakeholders: make maximum use of the network of stakeholders in their work agenda. For this reason, there will be no discrimination, bias and personal interests in the conclusions, and it makes the model objective. - Comprehensive rooting in the ruling paradigms in policy effectiveness: Unlike many public policy evaluation models, categories such as the implementation process, environmental drivers, organizational framework makers, outputs and effects of policy implementation, and implementation have been considered. - Making decisions and defining actions as a result of the evaluation - Use of uncertainty: in the real world, programs and policies are implemented in an environment where uncertainty is one of the main characteristics of it, and decision-making and management, which is an integral part of the evaluation process, also takes place in the light of culture, perceptions, beliefs and values, attitudes, personality, knowledge and human insight, whose main essence is uncertainty. - Emphasis on learning and dissemination of knowledge: learning is the ultimate goal of policy evaluation, which can be facilitated by knowing the activation mechanisms and possible obstacles.  - The comprehensiveness of evaluation values: by considering the environmental conditions, organizational frameworks, policy implementation outputs, policy implementation consequences, implementation process and procedures, learning, etc., it has covered different angles of evaluation with a metaphor from the systems theory approach.

Abstract The purpose of this research is to identify the dimensions and components of the maturity model of the open innovation ecosystem in Iran's defense industries based on the purposeful use of knowledge flows, in the form of ideas, science or technology in order to create value that can bring significant benefits to the individuals and organizations, including accelerating the main processes inside the organization (internal innovation) or expanding the market (external innovation) outside the organization. This research is an applied-basic one. In order to do so, 485 papers in the field of open innovation were collected using the meta-synthesis method. Based on the algorithm for selecting the final articles, the data of 80 articles were analyzed, and the maturity model of open innovation ecosystem was designed using the coding method and Maxqda Analytics Pro Software. To check the quality or reliability of the indicators, Kappa coefficient was used in SPSS software, which is equal to 0.86 in the current research, that indicates the appropriate reliability of the indicators. The analysis of the concluding model and the findings of this research showed that the open innovation ecosystem has several components in forms of 13 categories and 23 concepts, including collaborations and joint ventures, investment in ideas and research, and crowdsourcing. Also, the results showed that participating in investment, making mutual contracts with companies active in the field of business, and acquiring small and knowledge-based companies can accelerate the main processes of innovation within the organization. Extended Abstract Introduction The open innovation approach is a paradigm that assumes, in line with its technological development in sales, a company should also exploit external ideas (including customers, competitors, industry, suppliers and so on) as easily as the internal ideas it uses for its activities. (Podmetina et al, 2019). In recent years, we have seen an increase in the efforts of the defense industries of countries with high military power to improve their innovation process through open innovation, because problems such as reducing the defense budget of countries and increasing the dispersion of knowledge in society for the development of new products, has made research-based innovation domestic development difficult or low productivity. On the other hand, open innovation success factors such as external networking, technological intelligence innovation means, absorption capacity, market business model and human factors such as culture and motivation should be taken into consideration (Spender et al, 201 7). By implementing the open innovation plan and creating a dynamic and two-way interaction between the owners of innovation and the country's military organizations, especially the defense industries, employees, owners of the best ideas and innovative entrepreneurs should be placed at the service of solving the problems of the defense industries. The use of open innovation in the defense industry, which is considered one of the sources of innovation, in order to collect pure data from the internal and external environment and transform it into knowledge in order to survive in a very changing environment, is of particular importance. In such a situation, the tools that can help the defense industry in achieving its goals is the use of the innovation ecosystem based on the open innovation approach.   Theoretical Framework The term ecosystem, which originated from the word ecology, was proposed for the first time by an Italian ecologist named Tanzelli in 1935. It is the basic functional unit of the bio-environment, which is formed by biotic communities interacting with their non-living or unnatural environment. A living community and its environment together represent a ecosystem. Therefore, ecosystem includes living organisms (living community) and non-living environment (non-living community) that are separately related and interact (Granstrand and Holgersson, 2020). Open innovation is defined as: Targeted use of knowledge inflows and outflows to accelerate internal innovation and then develop markets for external use of innovation. Open innovation is a new approach that states that when seeking to improve technology and knowledge derived from their research, organizations should, in addition to internal ideas, apply external ideas from internal and external paths to the market (Boger et al, 2018).   Research methodology This research is fundamental in terms of its purpose and exploratory in terms of nature because it is done with the intention of practical application of knowledge and application of findings to answer the questions raised in Iran's defense industry. The qualitative method used in this research is the meta-synthesis of Sandelowski and Barroso (2007). Because in this research, a general sentence is deduced by using detailed information and establishing a relationship between them, and observations are made on specific events in a sample of the industry (Iran's defense industries) and then the inference is made about all the members of the industry based on the observation of incidents or events, the research approach is inductive type (that is, reaching from the part to the whole). The strategy of this research is qualitative. Because this research aims to create a new theory and develop knowledge about the open innovation ecosystem, the purpose of the research is exploration. Also, meta-composite method is used in this research and the approach of this research is qualitative (data collection, documentary-meta-composite). Kappa coefficient was used in SPSS software to check the quality or reliability of indicators.   Research findings First step: Setting research questions. Proposing the research questions in meta-composite analysis before starting the next steps of the research determines its general framework: what? According to the background study, what are the main concepts and key categories of the open innovation ecosystem? And what should be the appropriate framework for explaining the open innovation ecosystem? Study community (who)? Second step: systematic review of texts. In this step, the most relevant studies were identified and the less relevant studies were separated. The articles are taken from several sites, including the Journal of Corporate and Industrial Changes, the Quarterly Journal of Technology Development Management, the Quarterly Journal of Innovation and Value Creation, the California Journal of Management, the MIT University Policy and Innovation Science Lab, the Journal of Information and Management, the Journal of Management Improvement, technology forecasting and social change magazine, innovation management magazine, research and development management magazine, innovation management magazine in defense organizations, international innovation management magazine, government information quarterly, technology development quarterly and so on. The period of extraction of Iranian articles is between 1394 and 1400 (2015 to 2021) and foreign articles between 2006 and 2022. The total number of Iranian articles was 240 and foreign articles were 245, and a total of 485 articles were reviewed. The third step: searching and choosing suitable articles; Glynn's (2006) tool "Basic Evaluation Skills Program" was used to evaluate the quality of researches (Glynn, 2006). To select suitable articles, various parameters such as title, abstract, content, access, and research method quality have been evaluated. Fourth step: extracting the results; The information of the articles based on the reference of each article, including the title of the article, the name of the authors, the year of article publication, research method, theoretical concepts, open innovation ecosystem methods, challenges of the open innovation ecosystem, and the application of the open innovation ecosystem in each article was classified. Fifth step: analysis and consolidation of findings. At this stage, a three-stage coding approach was used through which, all the remaining studies were studied and coded in three stages. Based on the analysis and content analysis of the articles, 80 final articles were selected and a total of 13 categories, 23 concepts and 85 final codes for the components of the open innovation ecosystem were discovered and labeled in this research. Sixth step: quality control of extracted codes. Reliability of the research focusing on how much the research results can be repeated by other researchers, step-by-step documentation of the stages has been used. In this research, Kappa coefficient was used in SPSS software to check the quality or reliability of indicators. Seventh step: presentation of findings; By analyzing the content of the final selected articles, thirteen main categories including collaborations and joint investments, investment in ideas and research, utilization of knowledge and crowdsourcing, creating strategic alliances, purchasing new products and services. use of new business models, cooperation with partners and networking, use of domestic and foreign technology, use of new market capacities, establishing relationships with stakeholders, cooperation with research organizations, startups and competitors, participation in events and holding events, and protection of inventions and intellectual property were presented.   Conclusion The present article has presented an integrated framework in the field of open innovation ecosystem research by organizing scattered studies in the field of "open innovation ecosystem" in a meta-combination method. Based on the results, the open innovation ecosystem framework is set in thirteen categories and twenty three concepts. The resulting categories of this article are collaborations and joint investments, investment in ideas and research, exploitation of knowledge and crowdsourcing, creation of strategic alliances, purchase of new products and services, use of models New business opportunities, cooperation with partners and networking, use of domestic and foreign technology, use of new market capacities, establishing relationships with stakeholders, cooperation with research organizations, start-ups and Competitors, participating in and holding events, and protecting inventions and intellectual property. According to the stated contents and the results of this research, suggestions and solutions based on open innovation ecosystem models are presented: 1) Providing the license to use the company's brand to other companies in order to carry out activities, and receiving the license to use the brand of other companies in return. 2) Participation in investment with active and generally small companies or individuals in the field of business, concluding joint investment contracts with companies active in the field of business, acquisition of small and knowledge-based companies and use their knowledge in the field of business, supporting and using the knowledge of startups that operate in the field of business, and buying the intellectual property of reputable brands. 3) Cooperating with suppliers and negotiating payment in the field of business. 4) Carrying out research-oriented activities, including: supporting research in the field of business, applying business ideas using the "crowd sourcing" method, cooperating with research centers of universities and science and technology parks to obtain up-to-date knowledge in the field of business, and outsourcing research and development activities to obtain capabilities, skills, and innovation opportunities. 5) Carrying out knowledge-oriented activities, including the internal discovery of knowledge through holding an idea contest within the company, exploiting the internal knowledge discovered in the company, and setting up knowledge management systems in the organization with the aim of establishing communication between experts and experienced people of the organization and the combined use of knowledge and experience. 6) Use of intermediaries and types of networks in promoting business processes: social networks, internal networks, external networks, customer networks and the like. 7) Empowerment and localization of competitors' findings in business areas, such as business model localization, and conducting joint research with competitors in a joint study center.

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 aim of the current research is to identify the dimensions (layers) of a framework for applying business intelligence to improve the relationship between academia and industry. According to its purpose, the research method is applicable; and in terms of implementation, it is qualitative, descriptive and thematic analysis. Fuzzy Delphi method was used to collect information. The statistical population of this research included 12 professors and specialists in the field of communication with industry, selected by the available method, and interviews were conducted with them. According to the analysis that was carried out using thematic analysis method to identify the layers of applying business intelligence to improve the relationship between university and industry, 7 dimensions and 57 indicators were identified and confirmed. Data analysis was done using MAXQDA 2018 software. The results showed that the dimensions of using business intelligence to improve the relationship between university and industry include the first layer/preparation of the environment, the second layer/data collection, the third layer/ETL (extraction, transfer, loading of data), the fourth layer/warehousing Data, and the fifth layer/user interface (UI), metadata management and change management.
Extended Abstract
Introduction
For business intelligence to be useful in a company, it should be promoted from top management and the necessary resources should be provided and decisions should be made based on information. Business intelligence monitoring addresses various issues including investment, project prioritization, project management, and data quality. If monitored, business intelligence can be a powerful driver of business strategy. In fact, business intelligence can have a direct impact on the financial aspects of the organization. The best actions taken in business intelligence can be presented based on laws and regulations as well as suggestions to control the value of business intelligence actions, and this factor leads to more income than capitalization. The Business Intelligence Competence Center is a group of information technology business and analysts who work together to provide business intelligence solutions and organizational needs in the organization (Hoseinloo et al, 2021).
The success of countries in the future will depend on the extent and manner of their growth and influence in their scientific, research and strategic products. With continuous progress in science, technology and culture, countries have been able to continuously improve the level of standards, to the extent that they have brought vast global markets under control of themselves and their new knowledge and technologies in the national and transnational arenas. Applying knowledge and excelling in technology is one of the main indicators of the development of societies (Hamed et al, 2022).
Therefore, the researcher asked the main question: what are the dimensions (layers) of the framework for applying business intelligence to improve the relationship between academia and industry?
Theoretical framework
Many organizations today have adopted business intelligence as a catalyst to meet specific business needs and improve effectiveness. Business intelligence is about how to capture, access, understand, analyze and change one of the most valuable assets of a company to actionable information to improve business performance (Hoseinloo et al, 2021). Business intelligence systems have a great impact on the quality of strategic decisions in order to reduce decision time.
BIS promotes the management quality in organization through new type of technology and techniques of extraction, change, process, and offer data in order to provide strategic information. Therefore, it must be ensured that the organization follows a good BI architecture plan in its implementation process so that BI success is achieved. Business intelligence architecture is a framework consisting of various BI components (for example, data, people, processes, technology and management) and how these components should come together to ensure the smooth operation of a BI system (Ankrah & Tabbaa, 2015).
Zhang et al, (2022) in a research entitled "The effects of the depth and breadth of university-industry alliance portfolio on the growth of new technology-based firms": states evidences from China that in emerging economies, new technology-based firms (NTBF) are often at the same time, make multiple alliances with universities and research institutes to access knowledge and external resources critical to their survival and growth, thus forming University-Industry Alliance Portfolios (UIAP). However, little attention has been paid to this phenomenon. The results show the negative effects of UIAP depth on company growth and the positive effects of UIAP breadth on company growth. Furthermore, the results show that government subsidies weaken the negative relationship between UIAP depth and NTBF growth, along with the positive relationship between UIAP breadth and NTBF growth. By contributing to previous research on alliance portfolios, university–industry collaborations, and firm growth; this study provides some practical implications for both industry practitioners and policymakers in emerging economies.
Zeraatkar & Moghaddasi (2022) investigated the mediation model of business intelligence in the relationship between process innovation and organizational performance. According to the studies carried out, it shows the fact that hotel management must have strong points such as having specialized and specialized human resources, having specialized medical facilities, having natural resources and attractions, tourism infrastructure, transportation, etc. and the results indicate that process innovation has an impact on business intelligence, and also business intelligence through process innovation has an impact on organizational performance.
Research Methodology
This research is applicable in terms of purpose, quantitative in terms of data collection, and thematic analysis research in terms of research implementation method. To collect information, the fuzzy Delphi method was used in three rounds to find the use of business intelligence to improve the relationship between the university and the industry. The statistical population of this research consists of 12 professors and specialists in the field of communication with industry and, selected using the available method; and primary dimensions, components and indicators were compiled by using the field method and semi-structured interview tool. After analyzing the interviews, a total of 5 dimensions and 57 indicators were identified in line with the research objectives.
Research Findings
Data analysis was done using MAXQDA 2018 software. Based on the obtained results and according to the qualitative analysis, a total of 7 dimensions and 57 indicators have been identified and confirmed. The results showed that the dimensions of using business intelligence to improve the relationship between university and industry include the first layer/preparation of the environment, the second layer/data collection, the third layer/ETL (extraction, transfer, loading of data), the fourth layer/warehousing, and the fifth layer/user interface (UI), metadata management and change management.
Conclusion
The current research has been carried out with the aim of identifying the dimensions (layers) of a framework for applying business intelligence to improve the relationship between university and industry. The results of this research are in agreement with the results of Zhang et al, (2020), Zhang et al, (2022), Basile et al, (2021), Paradza & Daramola (2021), Caloghirou et al, (2021) and Hoseinloo et al, (2021). Zhang et al, (2020) states that BI readiness makes it possible for the organization to recognize its current situation and prepare to make changes. In this layer, along with reviewing and analyzing the current situation, designing and planning is done for the process of technology transfer from university to industry, which is a basis for establishing intelligent business communication between university and industry. Also, the factors affecting the said transfer process are examined. At this stage, proper management of processes, budget allocation, hardware and software resources, skill requirements, and training of employees are provided in order to prepare the conditions for the implementation of BI architecture.
Based on the obtained results, it is suggested for business intelligence to improve communication between university and industry by providing groups with extensive databases to transfer information faster and more accurately.
Based on the obtained results, it is suggested for business intelligence to improve the communication between the university and the information by information verification and refining the complete compatibility of software and hardware by applying a strong filter so that more accurate information is available.