Journal of value creating in Business Management

Abstract Abstract The purpose of this study was to provide a basic and strategic innovation model in petrochemical design and construction companies. The research method was mixed, and the statistical population in the qualitative part was 10 academic experts; and in the quantitative part 145 managers, assistants and senior experts of Petro Niro Saba Company. The sampling method was purposeful in the qualitative part, and simple random in the quantitative part. Delphi questionnaire (qualitative part) and researcher-made questionnaire (quantitative part) were used to collect data. The validity of the questionnaire was confirmed using Cronbach's alpha coefficient, convergent and divergent validity. In order to qualitatively analyze and validate the fundamental and strategic innovation model, the Delphi technique was used, and confirmatory factor analysis was used for quantitative validation. The results showed that the basic and strategic innovation model includes 7 components in the order of importance: the component of revolutionary technologies with a standard coefficient of 0.93 in the first place, the component of innovation in the market with a standard coefficient of 0.86 in the second place, the component of innovation in the development and planning of manpower with the standard coefficient of 0.85 is in the third place, the component of the birth of new industries with a standard coefficient of 0.83 is in the fourth place, the component of innovation in organizational processes and organizational structure is in the fifth place with a standard coefficient of 0.82, the component of product innovation with the standard coefficient of 78 0.75 is in the sixth rank, and finally the operational capability component with the standard coefficient of 0.75 in the seventh rank and 45 indicators. Extended Abstract Introduction By creating growth strategies, new classes of products; services and various business models change the game and create new values ​​for customers and the company (Binai Bash et al, 2015). Since strategic innovation as a systematic concept is faced with the overall change of an organization's map, companies need to identify the extent of implementing strategic innovation in the organization and measure it, and find the dimensions of these changes and find components that can help them to implement strategic innovation in their organizations and companies (Chen et al, 2018). Large organizations, including petrochemical designing and manufacturing companies, are facing political obstacles, internal conflicts, oil prices, geopolitics, and economic tension; fundamental and technological innovation is one of the needs of these large organizations. Non-aligned motivations, organizational structures that focus on existing operations, or personal motivations can affect innovation decision-making (Mirza et al, 2022). Executive managers also invest too much on their popular projects or spend a lot of resources on ideas that they have created themselves. Depending on the gradual or fundamental innovation, there might exist differences regarding how to be applied and which one is more important. So far, current research has not provided specific factors regarding the difference in criteria depending on innovation (Kranz, 2021). Therefore, in this research, the researcher intends to answer the basic question that what the important factors of fundamental and strategic innovation in petrochemical design and construction companies are and how these factors are ranked. Theoretical framework Fundamental innovation is the creation of new products and services, which are generally technology-oriented. The vision of fundamental innovation is always moving ahead of time and the market. Usually, this model of innovation is technology-oriented, and in it, first the new production technology is defined, then its market is defined. Fundamental innovation changes the method and the realization of problems and the performance of phenomena in general. (Shahtahmasbi et al, 2017) Strategic innovation is a clear goal of achieving competitive advantage by creating new customer and market value. However, this concept oscillates between two extremes; creating customer value in existing markets or for new markets. One of the key characteristics of strategic innovation is that it is stimulated in an organization where the creation of competitive advantage is rooted in its culture (Watson, 2022). Strategic innovation aims to re-conceptualize the business model, create a hassle-free market environment and jump in customer value. The learning process perspective of absorptive capacity (exploratory, homogeneous, changeable and exploitative learning processes) shows that the transformational learning process in particular plays a key role in strategic innovation (Carvalho et al, 2016). Brink (2022) conducted a research entitled "Organizing to enable strategic innovation in the sense of horizontal leadership for the duality of stability and change". The statistical population is service companies in Paris. The research method was descriptive-analytical and purposeful sampling. The results of the research showed that while being creative and creating ideas seems very easy, being innovative and implementing these ideas and accomplishing them in a regular way is very difficult. Baregheh et al, (2022) conducted a research entitled "The role of government and strategic innovation in organizational learning". The statistical population includes industrial companies in England. Research method is correlative, and sampling method is simple random. The research results showed that the level of industrial governance and organizational strategic innovation can play an effective role in improving people's learning and organizational performance. Methodology This research is a descriptive-analytical approach that is applicable in terms of purpose, and based on the type of mixed data (qualitative and quantitative). The statistical population in the qualitative part was 10 university experts and in the quantitative part 145 managers, deputies and senior experts of Petro Niro Saba Company. The sampling method was purposeful in the qualitative part and simple random in the quantitative part. Delphi questionnaire (qualitative part) and researcher-made questionnaire (quantitative part) were used to collect data. The validity of the questionnaire was confirmed using Cronbach's alpha coefficient, convergent and divergent validity. In order to qualitatively analyze and validate the fundamental and strategic innovation model, the Delphi technique was used; and confirmatory factor analysis was used for quantitative validation. A researcher-made questionnaire was used to collect data related to fundamental and strategic innovation variables. Discussion and Results In order to qualitatively analyze and validate the fundamental and strategic innovation model, the Delphi technique was used, and confirmatory factor analysis was used for quantitative validation. The results showed that the basic and strategic innovation model includes 7 components in the order of importance: the component of revolutionary technologies with a standard coefficient of 0.93 in the first place, the component of innovation in the market with a standard coefficient of 0.86 in the second place, the component of innovation in the development and planning of manpower with The standard coefficient of 0.85 is in the third place, the component of the birth of new industries with a standard coefficient of 0.83 is in the fourth place, the component of innovation in organizational processes and organizational structure is in the fifth place with a standard coefficient of 0.82, the component of product innovation with the standard coefficient of 78 0.75 is in the sixth rank, and finally the operational capability component with standard coefficient of 0.75 in the seventh rank and 45 indicators. Conclusion The present research was conducted with the aim of providing a basic and strategic innovation model in petrochemical design and construction companies. The results of this research are consistent with the findings of researchers such as Baregheh et al, (2022), Hübel et al, (2022), Tayebi Abolhasani & et al, (2020) and Taherpour Kalantari & Hosseini (2020). Regarding the results obtained from this study, Tayebi Abolhasani et al, (2020) announced in their research that the capacity to absorb knowledge is effective on strategic innovation. Also, competitiveness and strategic flexibility play a moderating role in the relationship between knowledge absorption capacity and strategic innovation and increase the intensity of the relationship. From the perspective of Baregheh et al, (2022), the level of industrial governance and organizational strategic innovation can play an effective role in improving people's learning and organizational performance. Management systems with the support of ideation (through dispatchihg employees to exhibitions and conducting visits) and operational making ideas (through team building, establishing a system of proposals, and creating mechanisms of creativity and innovation) have an effect on technological innovation. The organizational structure shapes the activities of employees to achieve common organizational goals (Dinesh, 2021). By creating cooperation and respect in the organization, which provides a cooperative and reliable environment between employees and managers, as well as increasing the willingness to take risks and the willingness to innovate among employees in the organization, the organization can be synchronized with technological innovations. Absence of any obstacle in intra-organizational communication, creating a cooperative environment in the organization, flexibility and readiness of employees to accept changes and pay attention to the ideas of new employees are more important in this dimension (Ghanbari, 2019). According to the results of the research, it is suggested that the determination of the mission of the organization should be realistic, explicit, motivating, differentiating and meaningful, and be a response to the needs of the organization. It should also be clear and obvious enough so that all members of the organization can understand it. It is better to express the vision of the organization as quantitatively, clearly and objectively as possible so that its achievement is understandable for the members of the organization. In this regard, the value statement in the organization should be clear and the same for everyone and visible in the organization. It should be the basis for the growth of people in the organization and should be related and aligned with the organizational goals. Also, these values ​​should be aligned with each other and synergistic.

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.  

Abstract The purpose of this research is to compile a model of digital marketing strategies in successful Iranian startups. According to its purpose, the research method is practical, and in terms of its implementation, it is mixed (qualitative-quantitative). The statistical population of the research in the qualitative part includes 13 academic and executive experts in the field of startups in the country, who were selected using the purposeful judgment method and the snowball method, and the statistical population in the quantitative part includes the marketing unit of active successful startups. There are 250 people in the country (5 companies) and marketing professors of 5 top universities in Tehran, and the statistical sample was 148 people, 180 distributed and 163 analytical questionnaires were selected using Morgan's table. A semi-structured interview and a researcher-made questionnaire taken from the qualitative section were used to collect information. In the qualitative part, the data theory method of the foundation was used, and the data obtained from the interviews were coded and analyzed in the three main stages of open coding, central coding, and selective coding, and in the quantitative part, the factor analysis of the indicators was done. The results of the qualitative part indicated that 241 primary codes, 46 central codes and 14 selective codes were identified and extracted. The results of the research showed that the causal conditions with 4 variables of network capability, use of artificial intelligence, marketing capability and customer knowledge have an effect on digital marketing strategies, and the results of confirmatory factor analysis showed that the fit indices of the model were confirmed.
Extended Abstract
Introduction
With the growth of ECT technologies including artificial intelligence, GPS, Bluetooth, QR code and other mobile and Internet connected technologies, marketers can offer micro-experiences/activities/services at an ultra-local level and adjust their messaging to effectively target small consumer segments locally (Singh & Keating, 2018). In this regard, digital marketing activities including mobile marketing, search engine based marketing, institutional marketing, email marketing, social network based marketing, etc. have been proposed. (Dwivedi et al, 2020). On the other hand, social networks have also created new challenges and advantages. It is important for companies to act in the field of specialized social networks so that digital marketing is not used by inexperienced experts and companies are safe from adverse effects by paying special attention to aligning their organizational goals with digital marketing solutions (Aswani et al., 2019).
Internet technology and the increase in the number of Internet startups have fundamentally affected the world economy. The Internet provides companies with the opportunity to offer their products and services internationally 24 hours a day (Kohler, 2016). Experience shows that in the future, all organizations must operate online in order to remain competitive. The cost of advertising and marketing products and services on the Internet is very low compared to advertising and distribution costs related to traditional methods. Small and medium businesses are an important part of the economy in all countries, but they are heavily influenced by rapid changes in the external environment, especially demographic and economic. These rapid changes affect the marketing department of these businesses to meet the needs and expectations of customers in order to maintain a competitive position in the market (Sedaghati & Seiedin, 2023).
Based on this, the current research is looking for an answer to this question: How is the formulation of digital marketing strategies model in successful Iranian startups?
Theoretical Framework
Digital marketing
The term digital marketing has been referred to as a subset of marketing management and advertising management since two decades ago (Kannan, 2017). Digital marketing includes the set of all tools and activities that are used to market products and services on a digital platform (web, mobile internet or other (digital) tools) (Vaziri Gohar & Abdolhosani, 2020).Digital marketing strategiesIn this changing world, there is an urgent need for a strategic vision and a clear strategy map to sustain business growth. As a result, organizations cannot implement digital marketing without a clear definition of the strategy.Create a good quality customer experience.In defining the digital marketing strategy, management should determine the transition plan to identify the ability of human resources to cope with the change. The company must help, accompany its employees during this transformation, and invest in their retention and competitive advantage (Erdmann & Ponzoa, 2021).
Javid et al, (2023) investigated the quality of customer relationship management for the development of digital marketing strategies in Bank-e Shahr. The results of the research showed that the variables of infrastructure, organizational environment, customer orientation, human resources, communication management, service quality, management and planning, strategic management, marketing and performance are in a favorable condition in Bank-e Shahr. The use of up-to-date technologies and the implementation of a suitable organizational structure for managing relationships with customers were identified as reasons for this favorability.
Hamdi et al, (2023) investigated the identification of dimensions and components of acceptance of customer relationship management social systems by professional users using Web 2.0 technology. 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, including three dimensions; organizational, customer, and technological; which organizational dimension has three components (manpower, organizational culture, organizational structure), customer dimension includes three components (value creation, performance expectation, customer satisfaction), and technological has been identified as having two components (social networks, content production).
Research methodology
According to its purpose, the research method is applicable, and in terms of its implementation, it is mixed (qualitative-quantitative). The statistical population of the research in the qualitative part includes 13 academic and executive experts in the field of startups in the country, who were selected using the purposeful judgment method and the snowball method; and the statistical population in the quantitative part includes the marketing unit of active successful startups in the country (5 companies) and marketing professors of 5 top universities in Tehran; as many as 250 people, and the statistical sample was 148 people, 180 analytical questionnaires distributed and 163 were selected using Morgan's table. A semi-structured interview and a researcher-made questionnaire taken from the qualitative section were used to collect information.
Research findings
In the qualitative part, the data-based theory method was used, and the data obtained from the interviews were coded and analyzed in the three main stages of open coding, central coding, and selective coding; and in the quantitative part, factor analysis of the indicators was done. The results of the qualitative part indicated that 241 primary codes, 46 central codes and 14 selective codes were identified and extracted. The results of the research showed that causal conditions with 4 variables of network capability, use of artificial intelligence, marketing capability and customer knowledge have an effect on digital marketing strategies; and the results of confirmatory factor analysis showed that the fit indices of the model were confirmed.
Conclusion
The current research has been conducted with the aim of developing a model of digital marketing strategies in successful Iranian startups. The results of the present study are in agreement with the results of Javid et al, (2023), Saeidi & Hoseinzadeh Naer (2022), Gholipur (2022), Boban et al, (2020), Bozkut & Gligor (2021), Musavirad & Ahmadi (2022), Dehghan (2018). Malek Akhlagh et al, (2021) showed that electronic customer relationship management means the development of traditional customer relationship management with the help of Internet technologies and an attempt to improve and fill the communication gap in which companies' marketing performance helps through examining the created development. Digitalization blurs the boundaries between technology and management and facilitates new business models based on the concepts, methods and tools of the digital environment.
According to the results obtained from the research, it is suggested:
Strengthening business practices with the aim of increasing competitiveness based on artificial intelligence should be considered, which leads to a major transformation in business. By using artificial intelligence, startups are able to identify, consider and understand their target buyers, and understand which type of product may be most needed at a specific time. With the evolution of big data and technologies, startups will be able to estimate buyer activity and monitor data-driven companies in any catastrophic situation and will obtain significant results that will improve their marketing decisions. Based on marketing capabilities, startups can meet the needs of current and new customers both through the development of new products and through the development of features and applications of existing products in order to ensure stability and survival, and to avoid shocks caused by new waves of competition based on new technologies.

Abstract The purpose of this research was to design a distribution channel selection system in the supply chain of the oil industry using the combination of adaptive neural-fuzzy network and meta-heuristic algorithms (Case study: National Oil Products Distribution Company of the dual regions of West Azerbaijan). This research was based on the purpose of the research, developmental-applicative and based on the descriptive-modeling research method. The statistical population of this research was 185 axis sales, Sekodar and fuel supply stations in the two regions of North and South of West Azarbaijan province. In this research, questionnaires and documents were used to collect data. In order to analyze the data, confirmatory factor analysis, adaptive neural-fuzzy network in basic mode and adaptive neural-fuzzy network combined with genetic meta-heuristic algorithms and particle swarm have been used. In this research, first, the combined distribution channel selection system was designed, and then using the system designed based on the least error, the traditional distribution channel and the branding plan of the fuel stations were evaluated based on the input scores. The results show that the best system for selecting the distribution channel was the adaptive neural-fuzzy network combined with the particle swarm algorithm. By comparing the performance of the branding plan and the traditional method, it was determined that the branding plan has a better performance and is a suitable distribution channel for the National Oil Products Distribution Company of the dual regions of West Azerbaijan.
Extended Abstract
Introduction
Rapid changes in consumer purchasing behavior, along with supply chain redesign, have caused both existing and new retailers to implement a variety of new inventory management strategies (Zhang et al., 2017; Melis et al., 2015). According to Forbes magazine, companies like Wal-Mart are known as the biggest companies in terms of sales (Forbes, 2014). The success of these companies is strongly related to the strategy and proper operations of the supply chain (Bogenrief, 2012). Some companies around the world (such as Amazon, Apple, Coca-Cola, Dell and Nike) attribute at least part of their success to supply chain management. At the same time, the results of the survey conducted in 2012 show that less than half of company managers recognize supply chain management as a strategic asset. In general, companies that recognize supply chain management as a strategic asset and use it in their daily processes, on average, achieve 70% higher financial performance (Kozlenkova et al., 2015). Since one of the main concerns of marketing is providing value to the consumer and the final user, an efficient supply chain is perhaps the most essential marketing function. Any mistake anywhere in the supply chain can have two-way effects for the company and its customers (Ellis, 2011). On the other hand, an effective and efficient supply chain allows companies to deliver higher value to final customers and improve results for the company.
Marketing distribution channels are where the process of creating customer value in the supply chain is more prominent (Kozlenkova et al., 2015). Distribution channels and their proper use can help to increase the competitiveness of companies (Gong et al., 2023); therefore, distribution channel management is considered as an important task (Berling et al., 2023; Chen et al., 2014; Chiang, et al., 2003).
Based on the above discussions, the approach of paying attention to the distribution channels in the supply chain is a problem that has led the researcher to conduct this research. This issue originated from two main areas. On one hand, the researcher's studies show that there is a lack of research in the field of choosing distribution channels in supply chain management, and the knowledge gap in this field is clearly visible. On the other hand, due to the fact that the National Oil Products Distribution Company of Iran, in a new approach, is looking for branding and creation of oil products distribution chain companies, which is the first of its kind in Iran; in such a situation, the need to design a supply chain distribution channel selection system in distribution companies can make it possible for managers of oil products distribution companies to choose appropriate distribution channels, develop appropriate cooperation, and understand priorities in relation to the members of the channel and identify the desired channel. In such a situation, methods such as artificial intelligence can be helpful. One of the methods of artificial intelligence is adaptive neural-fuzzy networks.
Research methodology
This research is applicable in terms of purpose, and descriptive-modeling in terms of the research method. Based on the nature of research variables, the statistical population of this research has been investigated in two parts. In the first part, the main statistical population of this research was axis sales, Sekodar and fuel supply stations in the two regions of North and South of West Azarbaijan Province.
To determine the validity of the questionnaire, two relative coefficients of content validity and content validity index were used. The results of these two coefficients indicate the elimination of some measures and confirm the validity of the questionnaire. The final parameters of the research based on inputs and outputs are shown in table (3).
Cronbach's alpha coefficient has been used to determine reliability. Reliability was determined based on the original sample, and the results showed that the value of Cronbach's alpha coefficient for all the main components was greater than 0.7, and based on this, the reliability of the questionnaire was confirmed.
In order to analyze the data in this research, the ANFIS method and its combination with genetic meta-heuristic algorithm and particle swarm were used to design the supply chain distribution channel selection system in the National Oil Products Distribution Company.
Findings
Confirmatory factor analysis
In order to verify the main components through the measured reagents, confirmatory factor analysis was used in Lisrel software. For confirmatory factor analysis, two categories of fit indices of the confirmatory model and factor loadings indicating the relationship between the main component and the indicators have been used. For the fit of the confirmatory model, the root mean square error of estimation (RMSEA) index, root mean square residual (RMR) index, goodness of fit index (GFI), adjusted goodness of fit index (AGFI), comparative fit index (CFI) and the normalized fit index (NFI) was used. The root mean square index of the estimation error should be less than 0.09, the residual mean square root index should be less than 0.05, and the values ​​of the goodness of fit, adjusted goodness of fit, comparative fit and normalized fit indices should be greater than 0.9; to be able to claim that the verification model correctly verifies the main component. In the second part, factor loadings and t values ​​have been used to investigate the relationship between the main component and the variables. From an empirical point of view, the value of each factor load should be greater than 0.5, and from a statistical point of view, the corresponding t value of each factor load should be greater than 1.96. The results are shown in table (4).
The results of the suitability indices of the verification models in Table (4) show that the value of RMSEA is smaller than 0.09, the value of the RMR index is smaller than 0.05, the value of the goodness of fit indices, the adjusted goodness of fit, Adaptive fit and normalized fit are greater than 0.9. Also, the relative chi-square value was calculated smaller than 3, which indicated the appropriateness of all the verification models and the verification of the main input and output components in the model. Examining the relationship between the main component and the determinants through factor loadings also shows that all factor loadings are greater than 0.5. The statistical analysis of factor loadings through t values ​​also shows that the t value obtained for all factor loadings is greater than 1.96 and is significant. Therefore, the results obtained for the reagents and the main components can be confirmed in general. As an example, the output of the software for operating loads and t values ​​of the main component of channel tasks are shown in figures (3) and (4).
Discussion and conclusion
This article was formed based on this main question: how is the appropriate system for choosing distribution channels in the supply chain of the oil industry using the combination of adaptive neural-fuzzy network and meta-heuristic algorithms in the National Oil Products Distribution Company of the dual regions of West Azerbaijan? To answer, first the literature and theoretical foundations of the research were reviewed; and in line with that, the variables and indicators affecting the selection of distribution channels in the supply chain of the distribution companies of the National Oil Products Distribution Company were extracted. In the next step, confirmatory factor analysis was used to confirm the main components through the measured indicators in the studied statistical population. After confirming the main components and specifying the inputs and outputs of the supply chain distribution channel selection system in distribution companies, first the adaptive neuro-fuzzy system in the basic state was implemented, and the error of each system using the indices of mean square error and root mean square error were calculated to determine the performance of each of them. After identifying the best adaptive neural-fuzzy system in the base state, in the second stage, the adaptive neural-fuzzy system is combined with meta-heuristic algorithms and finally the best distribution channel selection system in the supply chain of the National Oil Products Distribution Company in two regions of West Azarbaijan was determined based on the designed hybrid system.
Based on the results obtained, it is suggested to the executives to increase the quality of the distribution channel in the supply chain by factors such as creating mutual trust, attention should be paid to the infrastructure and facilities of the place when granting representation, the quality of the human resources of the placeholders and the level of capital submitted by the placeholders, and, evaluate each of these cases with a detailed investigation. In the branding method, in order to promote the brand, it is necessary to establish mutual trust between the main brand and the established brand, and the established brand defines its identity based on the original brand. The use of specialized and trained manpower in the branding method to increase the quality of distribution is one of the main requirements in the issue of distribution in the branding method, which needs to be addressed by providing multiple trainings to the existing employees. Also, the main brand can help the incumbents in accessing financial resources and new investments in the form of low interest loans.

Abstract This article aims to design a structural, behavioral and background model for talent management in the specialized parent company of thermal power generation. Since the phenomenon of organization and management can be studied and analyzed in the form of three categories of structural, behavioral and contextual factors, the basic basis of the conceptual framework of the research is the use of the three-pronged model. To achieve the purpose of the research, a mixed exploratory design (qualitative-quantitative) was used. became Based on the findings of the qualitative section, a questionnaire was compiled and distributed among 237 employees of thermal electricity subsidiaries. The final model was validated by the structural equation modeling method and the appropriateness of the model was confirmed in fitting the collected data. The results showed that the structural dimensions of talent management include six dimensions of organizational structure, recruitment system, training system, service compensation system, management and performance evaluation system, and organizational strategy. Behavioral dimensions include the three dimensions of organizational culture, leadership style and meeting high-level needs, and contextual dimensions include the atmosphere and environment of the organization and the external environment. The proposed three-dimensional model can be effective in line with the policies and decisions of managers in the process of attracting, developing and maintaining talents. Extended Abstract Introduction Organizations have well understood that they need to have the best talents in order to succeed in the complex global economy and survive in the competitive business environment. Also, organizations have realized that these intellectual capitals are vital resources that require management in order to achieve the best results (Mahmudi et al, 2022). In the past, talent management was assigned to the human resources unit as a side responsibility, while today talent management is considered as an organizational task, which is the responsibility of all organizational units. Talent management is so important that it alone can be considered the heart of human resources (McDonnell et al, 2019). Due to their high contribution and influence in the country's economy, state-owned companies are among the organizations that need to be specially addressed in the talent management process (Dehghaniyan et al, 2018). During the past few years, the country's electricity industry has faced problems in attracting, developing and maintaining organizational elites and talents, and also leaving a number of them for various reasons. This issue has; therefore, not only caused problems for the companies through the lack of human resources in these positions, but also, each of these people have carried their explicit and implicit knowledge out of the company, and damaged the organization from this point of view as well. Also, some talents want to have special privileges compared to other employees of the organization, for example, to receive more and better training, to have more flexible working hours (floating), and to enjoy more benefits (Shateri et al., 2016). Based on this, the current research is looking for an answer to this question: What is the model of talent management in the specialized mother company of thermal power? Theoretical Framework Talent management is a continuous process that includes attracting and maintaining qualitative employees and developing their skills. This program is aimed at providing human capital to improve organizational performance through employee empowerment (King et al, 2021). Its purpose is to ensure the availability of talent and to place the right people in the right job at the right time based on the strategic goals of the business. Talent management includes all human resources, administrative and technological processes. It usually refers to things like choosing recruitment options, selection, recruitment, socialization, retention, development and deployment, which is accompanied by planning and analysis. In other words, talent management is related to the recruitment, development of employees and management processes, and can be described as "talent optimization" (Froese et al, 2020). Montero Guerra et al, (2023) investigated the impact of digital transformation on talent management processes. Their results showed that organizational changes caused by digital transformation affect talent management and attracting and retaining talents. Mahmudi et al, (2022) investigated the role of talent management in organizational succession among physical education managers in Tehran. The results of the research findings showed that there is a positive and significant relationship between talent management and its dimensions of attracting and identifying talents, selecting and hiring talents, developing talents, employing talents, retaining and maintaining talents, the attitude and approach of talent management with the performance of succession planning, and the results of the research model showed that the use of talent was a stronger predictor than the succession. The results state that for the flourishing of talents and the formation of a unified Islamic-Iranian identity, the education organization requires the existence of talented and high-quality people and the training of suitable replacement forces based on the philosophy of Islamic-Iranian education. Research methodology According to its purpose, the research method is developmental-applicable, and in terms of execution method, it is mixed (qualitative-quantitative), and in terms of the data collection method, the qualitative part is exploratory-inductive and the quantitative part is descriptive-analytical. The statistical population of the research in the qualitative part includes 15 academic and industrial experts, and the dimensions of talent management in the form of structure, behavior and context, selected for the interview using purposeful sampling and in the form of snowball. The statistical population in the quantitative part includes 237 employees of thermal power subsidiaries who were selected using simple random sampling. Semi-structured interviews were used to collect information in the qualitative part, and a researcher-made questionnaire taken from the qualitative part was used in the quantitative part. Research findings In the qualitative part of the comparative approach and content analysis, the final categories were identified using previous studies; and in the quantitative part, SPSS software was used for analysis and AMOS was used for structural equations. The results showed that the structural dimensions of talent management include six dimensions of organizational structure, recruitment system, training system, service compensation system, management system, performance evaluation, and organizational strategy. Behavioral dimensions include the three dimensions of organizational culture, leadership style, and meeting high-level needs; and contextual dimensions include the atmosphere and environment of the organization and the external environment. The results in the quantitative section showed that the model has a good fit.   Conclusion The current research was conducted with the aim of designing a model of talent management in the specialized mother company of thermal power. The results of the present study are in agreement with the results of Montero Guerra et al, (2023), Mahmudi et al, (2022), Sotudeh arani et al, (2021), Haghghani (2021), Mahfozi et al, (2019), Moradi et al, (2022), and Won Yon (2020). Mahmudi et al, (2022) showed that a positive and significant relationship exists between talent management and its dimensions of attracting and identifying talents, selecting and hiring talents, developing talents, employing talents, retaining and maintaining talents, the attitude and approach of talent management on one side, and succession planning on the other, and based on the results of the research model, it was observed that the use of talent was a stronger predictor than succession planning. They also showed that for the flourishing of talents and the formation of a unified Islamic-Iranian identity in the education organization, it is necessary to have talented and high-quality people and to train suitable replacement forces based on the philosophy of Islamic-Iranian education. According to the results obtained from the research, it is suggested: To attract talent from within the organization through evaluation centers in the organization that periodically evaluate employees in terms of work and behavior and guide them in the field of performance management and career development. To recruit from outside the organization, the selection and recruitment process should be focused on identifying talented graduates and applying the law of recruiting elites and preventing the entry of people who do not have the necessary qualifications. The use of prominent professors to provide educational content; professors who, while having theoretical literacy, also have the required practical and applicable experience and have good abilities.

Abstract Abstract The present study aims to provide a recurring marketing strategy with a customer credibility determination approach using neural network data mining. The method of this research is applicable in terms of purpose, and is of a mixed type (qualitative-quantitative) in terms of implementation. First, by using the content analysis method, the key components of recurring marketing were identified and the initial optimization framework was designed. Then, the Delphi method and structured interviews with experts in the field of marketing and customer management were used to validate the indicators. In this study, a combination of the K-Means++ clustering algorithm and the RFM model was used to segment customers and identify groups in need of marketing interventions. Also, by using decision trees and artificial neural networks, the rules for validating customers and the accuracy of predicting their behavior have been improved. The research findings show that this combined framework not only improves the accuracy of clustering, but also allows designing personalized strategies for each group of customers. The results indicate that the recency index has the greatest impact in determining customer value, and the integration of transactional data with demographic and behavioral characteristics provides more comprehensive insights for marketing decisions. By filling the gaps in previous research, especially in the area of ​​interpretability and generalizability of models, this research has taken an effective step towards developing theoretical and applicable knowledge of return marketing. Introduction Customer value is defined as the perception of what a product or service can be useful to the customer, compared to possible alternatives. By benefit, we mean whether the customer feels that he or she receives certain benefits by purchasing a product in exchange for a certain amount of money. Lifetime value shows the profit from the customer relationship for the entire period from the moment he saw the first advertisement or registered on the site to the last purchase. Lifetime value affects the amount of revenue: the more regular customers a company has, the higher its revenue. How can you calculate lifetime value? To calculate lifetime value, you can multiply the average purchase size by the number of purchases and the retention period. Or divide the total revenue by the total number of users for a given period. In this regard, customer credit is one of the crucial issues and is very important for maintaining the financial security and sustainability of the organization. One of the fundamental challenges in this area is identifying the appropriate indicators for crediting and scoring customers. Therefore, determining correct and reliable indicators is very challenging. Segmenting customers into different prominent groups and designing personalized activities for each cluster is a vital technique for determining marketing tactics (Rajesh et al., 2024). Also, to score customers, there must be an appropriate and fair scoring system. This system must be able to place customers in different categories by considering credit and behavioral criteria and assign them appropriate points based on their performance (Wulansari & Heikal, 2024). In addition, there is a need to develop methods to evaluate and monitor customers over time. The aim of this research is to present a return marketing strategy with a customer credit determination approach using data mining. However, so far, the inability to discover valuable information contained in the collected data has prevented this data from being converted into valuable and usable knowledge in the organization, and data mining tools can help organizations discover hidden knowledge in a large amount of data (Calisir et al., 2016). Therefore, this research seeks to answer the question: what does a return marketing strategy with a customer credit determination approach using data mining look like? Theoretical Framework Return Marketing Return marketing is a suitable method for retaining current customers and increasing their loyalty. Using retention marketing techniques, customers can be encouraged to buy again and even share the brand with others (East et al., 2006). Customer Loyalty Loyalty is defined as an emotional and attractive connection to a brand and a practical action over time. In this definition, an individual prefers a particular brand to other brands and makes decisions as a psychological commitment to it. (Cardinale et al., 2016). Moula et al. (2024) in a study on customer type discovery and its impact on increasing hotel revenue: a data mining approach, reached the following results. Demand estimation is a fundamental component of revenue management systems. The demand for a product can be determined from the customers who purchase it. Identifying customer types in this field is a challenging endeavor that has recently been solved using metaheuristic and mathematical techniques. The metaheuristic method takes advantage of the lack of data in the business ecosystem, starts with random samples, and uses a fit function as a guide throughout the operation. The approach proposed in this study builds the ecosystem by combining complementary data to identify valuable customer types. The researchers use a new periodic table with additional data to achieve this goal. Subsequently, the relevant data is reduced through a data mining clustering method, and finally an algorithm and fit function are used to identify valuable customer types. To validate this approach, the proposed solution was compared with the latest research in the field, including genetic, memetic, and mathematical approaches. The researchers’ results showed that the model has lower error, with a maximum reduction of 34% and an improvement in value of up to 7%. Singh et al. (2024) examined customer churn in banking: A machine learning approach and a coherent program leveraging data science and management. According to this paper, customer churn in the banking industry occurs when consumers stop using the goods and services offered by the bank for a period of time and then discontinue their relationship with the bank. Therefore, customer retention is essential in today’s highly competitive banking market. In addition, having a strong customer club helps in attracting new consumers by strengthening the trust and referrals of existing customers. These factors make reducing customer churn an important step that banks should follow. In their study, Singh et al. examined banking data and predicted which users were most likely to stop using bank services. The researchers used various machine learning algorithms to analyze the data and show a comparative analysis on different evaluation criteria. Research Methodology The method of this study is applicable in terms of purpose, and mixed (qualitative-quantitative) in terms of implementation. First, by using the content analysis method, the key components of remarketing were identified and the initial optimization framework was designed. Then, the Delphi method and structured interviews with experts in the field of marketing and customer management were used to validate the indicators. Research Findings In this study, a combination of the K-Means++ clustering algorithm and the RFM model was used to segment customers and identify groups in need of marketing interventions. Also, by using decision trees and artificial neural networks, the rules for validating customers and the accuracy of predicting their behavior were improved. The findings of the study show that this combined framework not only improves the accuracy of clustering, but also allows designing personalized strategies for each group of customers. The results indicate that the recency index has the greatest impact in determining customer value, and the integration of transactional data with demographic and behavioral characteristics provides more comprehensive insights for marketing decisions. By filling the gaps in previous research, especially in the area of ​​interpretability and generalizability of models, this study has taken an effective step towards developing theoretical and practical knowledge of return marketing. Conclusion The present study was conducted with the aim of presenting a return marketing strategy with the approach of determining customer credibility using neural network data mining. The results of this study are in line with the results of Moula et al. (2024), Singh et al. (2024), Egorenkov (2024), Dwivedi et al. (2024), Haghi & Hamidi (2024), Khadivar & Mehmannavazan (2023), and Sharifi Esfahani et al. (2023). Dwivedi et al. (2024) showed that service quality and employee behavior have a positive and significant effect on customer satisfaction. To satisfy customers and retain them, customer relationship management must be strong and reliable. Therefore, customer relationship management plays a vital role in increasing market share, productivity, improving in-depth knowledge of the customer and his satisfaction to increase loyalty to the organization. Based on the research results, the following recommendations were made: Offering products tailored to age, occupation, or geographic region (e.g., student facilities for young customers). Offering digital services (e.g., e-wallets) to customers who transact online.  

Abstract Abstract The aim of this research is to design and explain a model of marketing processes with data-driven innovation capabilities in B2B companies. The research is of a mixed type (qualitative-quantitative). In the qualitative part, the main categories and components of the model were identified by using in-depth semi-structured interviews with 10 of experts in the field of marketing and data technology, using purposive sampling. In the quantitative part, the statistical population included managers, directors, and employees active in the marketing units of B2B companies located in Tehran. Considering the size of the statistical population of 530 people, based on the Morgan table, 219 people were selected as the sample size and were examined using the relative cluster sampling method. The findings were tested using a questionnaire and confirmatory factor analysis. The results showed that causal conditions such as data-driven culture and technological infrastructure have a significant effect on the formation of data-driven marketing processes. These processes also lead to outcomes such as increased marketing innovation, improved business performance, and improved customer satisfaction through data-driven strategies. The relationships between conditions, processes, strategies, and outcomes were statistically significant. As a result, the presented model can be used as a framework for developing innovative data-driven approaches in B2B companies. The findings emphasize that by strengthening a data-driven culture and using predictive analytics, companies will be able to make more effective marketing decisions and gain a more sustainable competitive advantage. Introduction In today's world, data-driven marketing is considered one of the key approaches to optimizing marketing processes in B2B companies. This approach is especially important in complex and dynamic competitive conditions, as it is able to improve strategic decision-making based on the analysis of customer data, market trends, and collected information (Rosário et al., 2023). Data-driven marketing allows companies to more accurately identify their customers’ needs and design their marketing strategies based on reliable information and predictive analytics (Akter, 2021; cao et al., 2021). In this regard, B2B companies, especially in complex industries requiring customized solutions, should improve their marketing processes using data-driven innovation (Ghayour baghbani et al., 2024). One of the biggest challenges in this area is implementing data-driven innovation models that not only make optimal use of existing data but also exploit new technologies such as artificial intelligence (AI) and machine learning (De Luca, 2020). Specifically, these models must provide a deep understanding of customers and accurate predictions of their future needs so that marketing processes can be designed effectively and optimally (Länsipuro, 2020). In order for B2B companies to benefit from this approach, they need comprehensive models that include processes such as data collection, data analysis, and strategy development (Mohaisen et al., 2024). These models should be designed in a way that not only helps optimize marketing processes but also improves customer experience and increases overall company efficiency (Johnson et al., 2019). In this regard, Big Data analysis and the use of advanced analytical tools allow companies to adjust their marketing strategies based on more accurate predictions and continuously improve them (Becha et al., 2021). On the other hand, the exploitation of data-driven innovations in B2B companies should be implemented considering the specific characteristics of this type of business and the more complex relationships they have with customers (Bagheri et al., 2024). These characteristics require companies to design their marketing processes based on accurate and reliable analyses of customer and market data to create a sustainable competitive advantage in addition to improving the customer experience (Alghamdi & Agag, 2024). Data-driven marketing models should also consider that data is regularly updated and that they have the ability to respond quickly to customer needs in conditions of rapid market changes (De Luca, 2020). Considering the above, the present study seeks to present a data-driven and innovative model for optimizing marketing processes in B2B companies; a model based on advanced technologies that both responds to the specific needs of this environment, is simple for companies to implement, and allows for continuous updating and adaptation to rapid market changes. Accordingly, and in accordance with the research objective, this study seeks to answer the main question: How can a comprehensive and implementable model be designed that, by relying on data and technological innovation, significantly increases the effectiveness of B2B marketing processes while reducing costs and remaining flexible to environmental changes?  Theoretical foundations In this study, data-driven marketing refers to the use of customer data collected from various sources (including online interactions, CRM systems, social media data, and market research) to formulate marketing strategies and implement advertising campaigns in B2B companies (Al-Khatib, 2025), and data-driven innovation refers to the use of data and their analysis to create new and improved products, services, and marketing processes in B2B companies (Mirzaei and Thompson, 2024). Paying attention to the capacities of data-driven innovation as one of the most important factors in improving marketing performance can directly affect the promotion of companies' competitive advantage (Mahmoudi, 2024). On the other hand, using data as one of the key resources in marketing decision-making processes can create new opportunities and reduce risks associated with undocumented decisions (Kardani Maliki nejad et al., 2024). In addition, this trend allows marketing strategies to be planned more carefully and allows businesses to gain significant competitive advantages in competition with other companies (Al-Khatib, 2025; lamminparras, 2022). Al-Khatib et al. (2025) examined “How do big data-based organizational capabilities shape innovation performance?”, empirically found that data-driven organizational capabilities have a positive and significant relationship with intellectual property and play a moderating role in internal and external supply chain integration. This relationship, in addition to the indirect effect of supply chain innovation capabilities, improves firms’ innovation performance. Torabi et al. (2024) examined “A Critical Review of Intelligent Marketing Strategies: Challenges Between Data-Driven Marketing and Human Experience in the Age of "Encompassing Technologies" used document analysis to find that using data alone without considering the psychological complexities of customers leads to superficial decision-making. Combining data and human insight increases the effectiveness of campaigns and customer satisfaction. Challenges include privacy protection and analyzing customer behavior. Research Methodology Research Methodology of this study is based on a mixed approach (qualitative-quantitative) and aims to design a model of marketing processes with data-driven innovation capabilities in B2B companies. In order to achieve this goal, the research was conducted in two consecutive and complementary stages. In the first stage, a qualitative and exploratory approach was used to identify the main dimensions and components of the model. Therefore, the grounded theory method was used. The statistical population in this section included academic experts and senior managers of B2B companies who had significant experience and knowledge in the field of data-driven marketing and organizational innovation. Purposive and snowball sampling was used to select individuals with the most knowledge and insight into the subject. After conducting semi-structured interviews with 10 of these experts, the data were analyzed through open, axial, and selective coding and key concepts were extracted. In the second stage, to verify and test the model obtained from the qualitative section, the research entered the quantitative phase. The statistical population in this section included managers, directors, and employees active in the marketing units of B2B companies located in Tehran. Considering the size of the statistical population (530 people), based on the Morgan table, 219 people were selected as the sample size and the relative cluster sampling method was used. The data collection tool in this stage was a researcher-made questionnaire designed based on the findings of the qualitative stage and was provided to the respondents after confirming the content and construct validity. Cronbach's alpha coefficient was used to measure the reliability of the questionnaire, and the structural equation modeling method in Smart PLS software was used to analyze the data.  Research findings The research findings show that effective networking and building ongoing relationships in marketing between companies is a key factor for sustainable success, and that stakeholder identification, a culture of collaboration, and data analytics play a vital role. Also, data-driven innovation capabilities and big data analytics increase organizational efficiency by enhancing marketing agility and competitive advantage, and the convergence of data-driven with human experience makes marketing decision-making more comprehensive and intelligent. Data-driven strategic orientations and the development of organizational capabilities enhance innovation performance and sustainable value creation, and intelligent human resource management and big data provide the necessary infrastructure for the operationalization of innovations. Overall, the integration of networking, data-driven innovation, and a customer-centric approach provides an integrated and effective framework for improving marketing performance and achieving sustainable competitive advantage. Discussion and Conclusion The results of this study show that data-driven marketing and data-driven innovation capabilities, as a multidimensional phenomenon, are influenced by a set of causal, contextual, and intervention factors that ultimately lead to improved marketing performance and sustainable competitive advantage through scientific and creative strategies. In the causal dimension, the results indicate that the existence of technological infrastructure, data-driven culture, and top management support are key prerequisites for the formation of data-driven marketing. This result is consistent with the findings of Al-Khatib et al. (2025) who emphasized that organizational capabilities based on big data are the foundation for the development of intellectual property and innovation in manufacturing companies. In comparison with the research of Koivuniemi (2020), both emphasize the role of human resources and technology as the main resources in applying the data-driven approach. The main focus of the research is on data-driven marketing innovation, which shows how to transform data into actionable insights. The findings indicate that combining data and human creativity takes marketing from the level of mere numerical analysis to the level of intelligent decision-making. This finding is consistent with the study of Torabi et al. (2024), which emphasized that relying solely on quantitative data without considering human experience leads to superficial decisions. In the contextual dimension, the findings showed that organizational structure, learning culture, digital maturity, and management policies play an important role in the success of data-driven marketing. Organizations that have an open culture and flexible structure reach data maturity faster. This result is consistent with the research of Länsipuro (2020), who identified structural and cultural barriers as the most important challenges of data-driven marketing. It is also consistent with the findings of Aljumah et al. (2024). In the intervention conditions, barriers such as resistance to change, weak analytical skills, and lack of technology budget were identified. However, the results showed that targeted training, employee empowerment, and knowledge management can greatly reduce these barriers. This result is similar to the findings of Kardani Maliki Nejad et al. (2024) who emphasized the role of expert validation and training in the implementation of data-driven innovation. It is also in line with the research of Lamminparras (2022) who pointed out the need to develop dynamic capabilities in data-driven decision-making. The strategies identified in this study include data analysis for service personalization, designing value propositions, and creating targeted communications with customers. Implementing these strategies allows companies to use data not only to describe the past, but also to predict the future.

Abstract Abstract The purpose of this research is to provide a model to identify the role of social communication capital and the ability to take advantage of international business opportunities. The research method is applicable in terms of purpose, mixed (qualitative-quantitative) in terms of execution method, and descriptive-survey in terms of nature and method. The statistical population of the research in the qualitative part includes 17 experts from the country's petrochemical industry, and in the quantitative part, it includes 108 experts from the international trade department of the petrochemical industry; selected by a simple random sampling method. Data collection in the qualitative part was carried out by semi-structured interviews; and in the quantitative part by the questionnaire. Qualitative data analysis was done using the method of theme analysis and coding and MAXQDA software, and in the quantitative part, it was done using SPSS and Smart PLS software. In the qualitative section, 90 open codes and 14 categories were identified. In the quantitative part, confirmatory factor analysis was used to examine the validity of the identified elements and components of the model of the role of social communication capital in the ability to take advantage of international business opportunities in the petrochemical industry. The results of the research showed that the model of the role of social communication capital in the ability to take advantage of international business opportunities in the petrochemical industry has two main factors and their indicators. This model consists of indicators that are the core and heart of this model. Also, the GOF index was obtained 0.44, which indicates the good fit of the model. Introduction The variety of needs and demands, and the change in the pattern of production and consumption and, as therefore, life as a result of significant advances in technology have made it impossible to live within the borders of a country, so that internal border relations have turned into international relations in a very broad sense, and even the  disappearance of these borders is also expectable. Different nations with different cultures, policies and economic and social conditions need to exchange goods and services to meet their diverse needs. Due to these new conditions and new needs, different societies have started trading with other countries and at this time opportunities have been created to increase commercial activities. Among these opportunities, we can mention export, non-oil export, and joint cooperation (Ahoei, 2019). International business opportunities are the possible opportunities that organizations face due to their presence in foreign markets (Muzychenko, 2008). Various factors can contribute to its non-development. In this research, social communication capital is one of the factors whose role is investigated in using international business opportunities. Social capital or social bonds that are placed in different cultural contexts are important and valuable resources that bring the meaning of identity to people's minds. This type of identity concept will give them a positive emotional experience (Shan & Tian, ​​2022). Social capital is a comprehensive concept that takes into account the social aspect of human interaction and enables access to the resources of members of the association or network due to their membership in the association (Christy et al, 2022). Social capital refers to the characteristics of social organization such as trust, norms, and networks that can improve the efficiency of society by facilitating coordinated actions (Salisua et al, 2019). Therefore, this research aims to take an effective step in the direction of improving social communication capital and consequently empowering the performance of the country's petrochemical industry. As mentioned, today's organizations are under the influence of factors such as increased global competition, sudden transformations, the need for quality and after-sales services, and the existence of limited resources and under a lot of pressure. After years of experience, the world has come to the conclusion that if an organization wants to be a leader in its economy and business affairs and not lag behind in the field of competition, organizations must be empowered and be able to use this empowerment in line with practical action. Therefore, in this research, we are looking for an answer to this question: how to identify the role of social communication capital and the ability to take advantage of international business opportunities? Theoretical Framework Social capital Social capital refers to features of social organization such as trust, norms, and networks that are able to improve the efficiency of society by facilitating cooperative actions. It is stated that social capital can be simply defined as the existence of a certain set of norms with informal values ​​that the members of a group with cooperation among them, share in it (Alwani, 2015). International marketing opportunities Internationalization is a step-by-step process of international business development, whereby a company is increasingly involved in international business operations through specific products in selected markets. To adapt the organization to the needs and preferences of customers, marketing knowledge is required to be created and disseminated among functional departments within an organization (Muzychenko, 2008). The export company must acquire the necessary and complete knowledge of the international marketing environment in order to increase the possibility of its success. The marketing environment includes forces that directly and indirectly affect the performance of the organization. For an organization, changes in the marketing environment create uncertainty, threats, and opportunities (Alaghehmand Shandi & Joybari, 2023). Mahmoudi & Pourshahabi (2023) investigated the effect of the value of financial intelligence on the risk-taking of Zahedan National Bank employees with the mediating role of social capital. Analyzing the model and carrying out structural equations showed that financial intelligence with the mediating role of social capital cannot affect employees' risk taking. Also, the results showed that financial intelligence has a separate effect on the two variables of risk-taking and social capital. Alaghehmand Shandi & Joybari (2023) investigated ethical challenges and opportunities in international business: a look at ethical values ​​as the most important assets of international businesses. The results show how ethical values ​​can be considered as the most important assets of international businesses. Some of the main ethical barriers in international business include corruption, unfavorable working conditions, and lack of respect for human rights. Also, some of the opportunities in international business include strengthening cultural connections, observing ethical principles in business relationships, and promoting transparency and accountability. Finally, this paper concludes that adherence to ethical values ​​can serve as a competitive advantage for international businesses and help local and global communities to improve. Research methodology The research method is applicable in terms of purpose, mixed (qualitative-quantitative) in terms of execution method, and descriptive-survey in terms of nature and method. The statistical population of the research in the qualitative part includes 17 experts from the country's petrochemical industry, and in the quantitative part, it includes 108 experts from the international trade department of the petrochemical industry; selected by a simple random sampling method. Data collection in the qualitative part was carried out by semi-structured interviews; and in the quantitative part by the questionnaire. Research findings Qualitative data analysis was done using the method of theme analysis and coding and MAXQDA software, and in the quantitative part, it was done using SPSS and Smart PLS software. In the qualitative section, 90 open codes and 14 categories were identified. In the quantitative part, confirmatory factor analysis was used to examine the validity of the identified elements and components of the model of the role of social communication capital in the ability to take advantage of international business opportunities in the petrochemical industry. The results of the research showed that the model of the role of social communication capital in the ability to take advantage of international business opportunities in the petrochemical industry has two main factors and their indicators. This model consists of indicators that are the core and heart of this model. Also, the GOF index was obtained 0.44, which indicates the good fit of the model. Conclusion The current research was conducted with the aim of providing a model to identify the role of social communication capital and the ability to take advantage of international business opportunities. The results of this research are in agreement with the results of Mahmoudi & Pourshahabi (2023), Alaghehmand Shandi & Joybari (2023), Shariatnejad et al, (2023), Tajpor et al, (2022), Troise et al, (2020), Noruzi et al, (2019), and Pinho (2016). Noruzi et al, (2019) showed that social capital in a specific market and social capital at the international level have a direct and positive effect on taking advantage of business opportunities; on the other hand, social capital at the international level has a positive and meaningful effect on social capital in a specific market. According to the results of the research, the following suggestions were presented: Based on the research findings and confirmation of the effectiveness of inter-organizational cooperation, it is suggested that the training of human resources and empowerment in the field of inter-organizational cooperation in the organization should be included in the organization's programs, and increase employees' knowledge of different cultures through training courses and holding scientific meetings and scientific journals and... so that employees believe in it and respect it in the work environment.

Abstract Abstract
The present study aims to measure and scale the trans-Industrial technological model in the Iranian packaging industry (case study: saffron packaging). The method of this research is applicable in terms of purpose, and is of a mixed type (qualitative-quantitative) and descriptive-analytical type in terms of implementation. The statistical population in the interpretative structural section includes university experts and managers of saffron packaging companies, the number of statistical samples was selected purposefully as 15 people, and the number of statistical samples in the confirmatory factor analysis section was estimated to be 384 people based on random stratified sampling using the Cochran formula. The research tools in the qualitative section are semi-structured interviews, and in the quantitative section include the ISM questionnaire and a researcher-made questionnaire taken from the qualitative section. The analysis method in the qualitative section is an interpretative structural approach with the Miqmac software, and in the quantitative section, confirmatory factor analysis was carried out with the IMOS software. The findings of the interpretive structural section showed that the identified factors were categorized into seven levels, with the factor of “new technologies and smart packaging” being identified as the most important factor, and the results of the confirmatory factor analysis section showed that the causal paths and relationships between external and internal constructs in the structural model were confirmed by the confirmatory factor analysis method.
Introduction
During several decades of rapid and extraordinary growth of some economies around the world, especially in East Asia, a concept called technological leapfrogging was formed in the economic development literature. (Ponomarev & Gareev, 2025) The concept of leapfrogging has been defined as reducing the gap between countries in productivity and income with leading countries and, in general, convergence and reducing the difference in productivity and income in the whole world. Leapfrogging can be measured by different indicators such as income, productivity, and technological capability. The measurement method should be selected based on the research objective and the levels of study at the firm, industry, and national levels (Li et al., 2022). In addition, the similarity of production methods, technologies and institutions of developed countries helps developing countries. In research, different reasons such as geographical advantages, human capital, development of science and technology, cultural or political institutions, trade and international blocs have been proposed for convergence (Li et al., 2025).
The packaging industry, as one of the main pillars of the supply chain and marketing of products, plays a key role in maintaining quality, increasing shelf life, safety and attracting customers (Yao et al, 2024). Appropriate packaging not only prevents damage to products during transportation and storage, but also creates added value for producers and increases competitiveness in domestic and international markets (Wang et al., 2024). Saffron, as one of the main export products of Iran, despite its competitive advantage, still faces packaging problems and requires special attention in this area. Saffron has been used in fields such as cooking, medicine, cosmetics and dyeing since ancient times due to its special aroma and color. Iran has long been one of the most important producers and exporters of saffron in the world, and proper packaging of this product is of great importance for maintaining its quality and increasing its export value. Packaging plays a decisive role in protecting the aroma, flavor and color of saffron and preventing its contamination; while improper packaging can reduce quality and damage the reputation of the manufacturer. Considering the importance of the packaging industry in Iran, considering the weaknesses in this industry, and considering the technological trans-Arabic solution, this study seeks to answer the question: how to measure and scale the technological trans-Arabic model in the Iranian packaging industry?
Theoretical Framework
Technological trans-Arabic
Technological trans-Arabic means filling the gap in technological capabilities that are measured qualitatively or quantitatively, for example, the number of patents and the ratio of research and development to GDP. The policy of trans-Asianization says that we should not necessarily follow the path that others have taken; rather, we should use the experiences of others along the shortest development path. Although developing countries are technologically behind developed countries, they can take advantage of their new arrival advantages to develop technology (Liu et al., 2025).
Shi et al. (2025) conducted a study on China's technological catch-up through foreign intellectual property acquisition: disentangling the effects of international distance. The results show that: (1) different sub-dimensions of distance have different direct effects on foreign intellectual property acquisition, (2) the positive effect of knowledge distance on intellectual property acquisition interacts with the other three forms of distance, (3) the most aggressive foreign intellectual property acquisition strategies are associated with only three forms of distance, and (4) the effect of disentangling distance depends on the type of intellectual property asset and whether the buyer is in the manufacturing or service sector.
Karbasi et al. (2025) examined the role of innovation in the development of saffron processing and transformation industries. They acknowledged that product innovation and process innovation have a positive effect on the development of saffron processing and transformation industries. Accordingly, strengthening smart packaging infrastructure and digital marketing can pave the way for sustainable and export-oriented development of these businesses.
Research Methodology
The method of this research is applicable in terms of purpose and is of mixed type (qualitative-quantitative), and descriptive-analytical type. The statistical population in the interpretative structural section includes university experts and managers of saffron packaging companies, the number of statistical samples was selected purposefully as 15 people, and the number of statistical samples in the confirmatory factor analysis section was estimated to be 384 people based on random stratified sampling using the Cochran formula. The research tools in the qualitative section are semi-structured interviews, and in the quantitative section include the ISM questionnaire and a researcher-made questionnaire taken from the qualitative section.
Research findings
The analytical method in the qualitative section is an interpretative structural approach with the MICMAC software; and in the quantitative section, confirmatory factor analysis was carried out with the Imus software. The findings of the interpretive structural section showed that the identified factors were categorized into seven levels, with the factor of "new technologies and smart packaging" being identified as the most important factor, and the results of the confirmatory factor analysis section showed that the paths and causal relationships between external and internal constructs in the structural model were confirmed by the confirmatory factor analysis method.
 Conclusion
The present study was conducted with the aim of measuring and scaling the technological trans-Arabic model in the Iranian packaging industry (case study: saffron packaging). The results of this study are consistent with the results of Shi et al. (2025), Nayyerhoda et al. (2025), Karbasi et al. (2025), Jafari Toye & Noruzi (2024), Soltanzadeh et al. (2024), Matsuo et al. (2024), Yun et al (2023), Alizadeh et al. (2023), and Safdari Ranjbar (2022). Karbasi et al. (2025) showed that product innovation and process innovation have a positive effect on the development of saffron processing and transformation industries. Accordingly, strengthening smart packaging infrastructure and digital marketing can pave the way for sustainable and export-oriented development of these businesses.
According to the results of the study, the following suggestion was made:
 Launching advanced and automatic production lines in line with global standards; especially in export packaging according to the requirements of target market customers.
 Continuous monitoring and analysis of market developments and international competitors to predict new trends and demands using data mining tools.