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With the increasing development of technologies and communication methods, the use of digital marketing to advertise and promote services and products has become very important. One of the industries that benefit from these methods is the medical tourism industry. Also, considering the ever-increasing growth of technology and the widespread use of the Internet in different societies, the use of artificial intelligence and related technologies is very important. Therefore, the aim of the current research is to identify the effective factors on digital marketing in medical tourism with an emphasis on artificial intelligence (case study: Tehran). This research is a survey in terms of practical purpose and in terms of data collection. The statistical population of the research included 53 medical tourists from Tehran, who were selected to participate in building the model. For this purpose, the conceptual framework of the specific model and the data were analyzed using tools and techniques of fuzzy cognitive mapping and social network analysis. The results showed that several factors are involved in digital marketing in medical tourism with an emphasis on artificial intelligence (case study: Tehran city), including site optimization and branding factors in search engines, marketing targeting, better evaluation of marketing campaigns and better feedback from Audiences were the most important in order; Because they were more central.

The purpose of this research is to investigate the identification of effective factors on the distribution strategy in the food industry from the point of view of marketing and online sales. This research is in terms of applied-developmental purpose, in terms of the method of collecting data in a qualitative form, and in terms of the research implementation method, it is a meta-composite approach. The statistical population of the research includes 12 university professors who are experts in the field of marketing management and distribution channels and have books or articles in this field, as well as theorists and researchers who have specialized studies in this field. This research was analyzed using the scientific method of metasynthesis (metasynthesis) and by reviewing the published articles, and based on 23 selected articles, 85 indicators were extracted. Finally, 16 components were evaluated and identified, and finally the final framework was created by applying the total opinions of experts on the components of human factors, creating value for the customer, paying attention to the competence of managers, internal factors, external factors, management factors, opinion mining, digital marketing, Environmental factors, content marketing, business strategies, complete knowledge of the internal and external environment, direct marketing, visual features, optimization, competitive performance were confirmed and identified.

 The purpose of this research is to analyze the impact of effectiveness of media (Seda-va-Sima) advertisement on the extent of consumers’ urge to consume national commodities. In case of its goal, this research is an applied research, and is a descriptive-survey research, which has been conducted as a field work. Statistical population of the research is the population of Mashhad city. Using Cochran formula, 384 people were selected as the statistical sample. In order to gather data, a researcher-made questionnaire with 61 questions was used. Content validity of the questionnaire was approved by 15 academic and practitioner experts in the field of advertisement and media. The reliability of the questionnaire according to Cronbach's alpha was 0.824. Also, SPSS and SPLS applications were used to analyze data. Results of the research indicate that effectiveness of media advertisement positively and in a meaningful manner affects consumers’ urge to consume national commodities.

Persuading customers to buy or use a service requires providing a valuable proposition from the customer's point of view. Therefore, marketing programs try to increase the value of the desired service or product by using scientific solutions. This research was conducted with the aim of investigating the influence of influencers' characteristics on the intention to use services according to the mediating role of customers' perceived value. This research is applied in terms of purpose and descriptive-correlative in nature. The statistical population in this research is all the followers of Mithaq School page, whose number was 3748 at the end of 1402. In this research, the sample size was determined according to Cochran's formula of 350 people who were selected by non-probability method. In this research, the data collection tool was a standard questionnaire. The validity of the content has been confirmed by the opinion of the professors and the validity of the construct using the method of factor analysis. The reliability of the questionnaire was checked and confirmed by Cronbach's alpha method and composite reliability coefficient. Structural equation modeling by SmartPLS3 software was used to check the hypotheses. Based on the obtained results, the characteristics of influencers have an effect on perceived value and intention to use services. Also, perceived value affects the intention to use services. In this research, the mediating role of perceived value has been confirmed.

Green influencer marketing is considered one of the new approaches in today's world in purchasing tourism services. Influencers, people with a large number of followers in social networks, play an important role in promoting products and services by influencing the attitudes and behaviors of customers. The tourism industry has also used this potential. The purpose of this research is to design a green influencer marketing model in purchasing tourism services. The research method is qualitative and the research strategy is based on foundational data theorizing. The participants include university professors, researchers and experts active in the field of tourism and marketing, 12 people have been selected by the judgmental sampling method of the snowball type according to theoretical saturation. To collect data, in-depth interviews and A semi-structured interview was used. To calculate the reliability of the model, the method of percentage agreement coefficient or Cohen's kappa coefficient was used, the value of which was calculated to be 0.85. The research findings included 6 categories. Causal conditions include social media developments and technological developments. The core category of the core category (green influencer marketing) includes the sharing of experience from the tourist destination and the mental representation of the destination brand. The strategies include the strategy of creating a mental road map, the strategy of creating unique content, and the strategy of online tourism services. Consequences include improving tourist performance, improving tourism industry performance. Intervenors include individual characteristics of influencers, macro environmental factors. Areas include personal branding and infrastructure.

The‏ aim‏ of‏ this‏ research‏ is‏ to‏ design‏ a‏ digital‏ marketing‏ model‏ in‏ small‏ and‏ medium-sized‏ industries‏ in‏ Iran‏ using‏ the‏ meta-synthesis‏ method.‏ The‏ present‏ research‏ was‏ conducted‏ as‏ a‏ qualitative‏ research.‏ Accordingly,‏ in‏ order‏ to‏ design‏ a‏ comprehensive‏ model‏ of‏ digital‏ marketing,‏ the‏ meta-synthesis‏ qualitative‏ research‏ method‏ of‏ Sandelowski‏ and‏ Barroso‏ (2007)‏ was‏ used.‏ Thus,‏ after‏ identifying‏ the‏ categories,‏ concepts‏ and‏ codes‏ of‏ digital‏ marketing‏ and‏ evaluating‏ its‏ validity‏ and‏ reliability,‏ the‏ conceptual‏ model‏ of‏ the‏ research‏ was‏ formed. Finally,‏ the‏ present‏ research‏ model‏ consists‏ of‏ 6‏ categories,‏ 18‏ components‏ and‏ 54‏ indicators‏ that‏ can‏ represent‏ the‏ digital‏ marketing‏ model‏ in‏ small‏ and‏ medium-sized‏ industries‏ in‏ Iran.‏ The‏ results‏ of‏ the‏ research‏ show‏ that‏ all‏ six‏ categories;‏ 1.‏ Marketing‏ strategy,‏ 2.‏ Reaching‏ and‏ interacting‏ with‏ target‏ customers,‏ 3.‏ Converting‏ visitors‏ into‏ customers,‏ 4.‏ Engaging‏ customers,‏ 5.‏ Appropriate‏ digital‏ tools,‏ and‏ 6.‏ Digital‏ content‏ marketing‏ play‏ a‏ significant‏ role‏ in‏ the‏ "digital‏ marketing"‏ model‏ for‏ Iranian‏ small‏ and‏ medium-sized‏ industries,‏ and‏ the‏ designed‏ model‏ is‏ the‏ most‏ appropriate‏ digital‏ marketing‏ model‏ in‏ terms‏ of‏ the‏ cultural,‏ organizational,‏ and‏ structural‏ conditions‏ existing‏ in‏ Iranian‏ small‏ and‏ medium-sized‏ industries.

This research was conducted with the aim of analyzing the gap in the deployment of artificial intelligence in advertising and marketing companies in Iran.

the multi-criteria decision-making study method was chosen using Super Decision. The methods of information collection, according to the background of the research, library methods were used, and the field method was used to collect information to answer the research questions. The tool used to collect information in this research is through a questionnaire designed by the researcher in order to identify challenges. In the next step, using experts' opinions, they were modified and then analyzed using the combined approach of ANP and DEMATEL.

The findings of the research showed that in the technical subject of security factor, in the subject of culture the leadership and organizational support factor, in the organizational-human factor of organizational strategy and in the social-environmental topic organizational culture had the most importance from the experts' point of view.

The research results also stated that artificial intelligence will transform the business world, increase innovation and productivity, and help advertising and marketing companies to think bigger. Lack of current knowledge and experience in using this technology is definitely one of the main obstacles that prevent organizations from using artificial intelligence in marketing. But the way and the only answer to this is education. It is worth noting that another factor investigated in the research was the constantly changing trends, which is another major obstacle that we see in the field of artificial intelligence. This is inevitable as the technology is still developing. However, there is no way to solve this problem except for it to constantly present itself. Organizations can use artificial intelligence to improve their products, processes and decision making. The impact of artificial intelligence is felt in all industries, especially marketing. With the help of AI, companies are better equipped to combat crisis by using AI decision-making algorithms, identifying anomalies and predicting future behavior.

Personalized Digital Marketing is one of the key and thriving trends in the world of digital marketing, developed with the aim of delivering unique and tailored experiences to each customer. In this approach, marketers strive to understand the needs, preferences, and behaviors of users by collecting and analyzing their data. Based on these insights, they design marketing content, advertisements, and offers that align specifically with each individual. The goal of this research is to identify the dimensions and components of personalized digital marketing through a recommendation engine using a thematic analysis approach. To achieve this, after reviewing the literature and research background, basic and organizing themes were identified. Then, through surveys and interviews with 25 experts and university professors familiar with the concepts of personalized digital marketing, a conceptual model of the research was introduced. In conclusion, practical suggestions were provided to IT and marketing managers in online stores, including Digikala.

Artificial intelligence has become one of the key tools for enhancing advertising strategies. By leveraging capabilities such as data analysis, machine learning, and natural language processing, AI enables transformative advancements in advertising and marketing processes. Exploring the role of AI in fostering advertising innovation, increasing audience engagement, and optimizing advertising strategies is of significant importance.The primary aim of this study is to map the knowledge structure of research on the application of AI in advertising using co-word analysis. To achieve this, 3,577 scientific articles published between 1994 and 2024 were retrieved from the Scopus database. The titles and abstracts of these articles were analyzed using VOSviewer software to generate a comprehensive map of the most frequent terms and key topics. The results revealed that the keyword “advertising” had the highest frequency, serving as a focal point for numerous studies in this field.The co-word analysis identified five main clusters: (1) prediction and optimization of advertising performance, (2) AI-driven content generation, (3) precise targeting and audience identification, (4) personalization of advertisements for enhanced engagement, and (5) the development of recommender systems to improve advertising efficiency. These clusters reflect the key trends in AI applications in advertising and marketing.This analysis provides a comprehensive and structured map of the existing knowledge on AI applications in advertising and serves as a reference for future research in this area. It also offers guidance for developing policies and strategies in the advertising industry.

This study aims to design a ritual marketing mix model based on interpretive structural modeling.

The research is exploratory in terms of its objective and qualitative in approach. In this study, 15 experts were interviewed for analysis. The snowball sampling method was used to collect data, which was then categorized and analyzed using thematic analysis. Semi-structured interviews and document analysis based on thematic analysis were employed to gather data in line with the research objectives.

Ultimately, one overarching theme, four organized themes, 11 basic themes, and 63 initial codes were identified. The organized themes included: religious advertising and promotional strategies, distribution channels and religious sales locations, religious products, and religious pricing. Based on interpretive structural modeling, the final model was developed.

The results suggest that integrating cultural and religious values into marketing strategies provides a comprehensive approach for engaging audiences in religious communities. This model can not only strengthen deeper connections with customers but also enhance social responsibility and help achieve the economic objectives of organizations. By adopting this approach, a balance is achieved between economic benefits and ethical principles.

The present study is a mixed method and a type of exploratory mixed research design, which is carried out in two consecutive qualitative-quantitative stages. In the first phase (qualitative phase), the present research conducted a qualitative study, and in this phase, by reviewing and evaluating the studies conducted in the field of the topic raised in the current research, as well as in-depth interviews with knowledgeable experts in the field of brand repositioning, the necessary information was collected. And by using the grounded theory analysis method, it has been coding and categorizing and presenting a conceptual model. The second phase (quantitative phase) of the study was quantitative and by the method of structural equation modeling, for this purpose, the data collected from the researcher-made questionnaire based on the proposed model (resulting from the qualitative phase of the study) was evaluated using Smart PLS software. Results In the qualitative part, the grounded theory results showed that the brand repositioning pattern of companies active in the electricity industry includes 71 open codes, 8 core codes, and 1 selective code. In the quantitative part, the results of structural equation modeling showed that 8 components including financial power, quality, price, delivery, service, marketing, customer satisfaction and human resource management were identified for the brand repositioning model of companies active in the electricity industry, and all 8 The component affects the repositioning of the brand of companies active in the electricity industry

Pricing of goods and services is one of the important topics of Islamic economics, which has long been the focus of the thinkers of the Islamic Society. The lack of government oversight of prices is a clear violation of social rights that has detrimental consequences. Therefore, in some cases, pricing should be considered. Pricing strategies differ for each stage of the product life cycle. Although each stage of product life has its own peculiarities and challenges, the most difficult and challenging stage is setting prices for new products .

This paper is prioritized new product pricing strategies and offered appropriate solutions using multidisciplinary decision-making. In this research, to evaluate and select appropriate solutions is used a hybrid MCDM approach based on FANP-DEMATEL-FCOPRAS approaches due to a multiplicity of quantitative evaluation criteria and fuzzy nature of qualitative criteria. The statistical sample consists of 15experts and specialists of Shokouh Cellulose Materials and Paperback firm. Findings,

According to studies, the main criteria in this research are innovation, marketing, organization, customer, product, and technology, each of which in turn includes sub-criteria. The results show that the free product as if zero price in priority, combining multiple products into a single package and selling them for one price in the second priority have been.

In today’s world, the rapid development of information technology has led to the creation of vast amounts of data. Approximately 2.5 quintillion bytes of data are generated daily, and this figure is expected to rise with the advent of the Internet of Things (IoT) (Seranmadevi & Kumar, 2019). The availability of reliable data is crucial for producing and utilizing information that enables quick and accurate business decisions. The rapid technological advancements and their widespread distribution globally have created opportunities to gain a competitive advantage through new methods based on data and artificial intelligence (AI) in marketing management. This study aims to enhance the marketing process by providing a systematic and precise approach toidentifying research gaps, thereby connecting practical and research actions in the field of marketing and AI. Consequently, the primary objective of this research is to develop a marketing plan based on AI using a hybrid approach and strategy.Artificial intelligence finds applications in various business contexts. Experts and academics consider AI to be the future of our society. With technological advancements, the world has become a network of interconnected systems (Jeric et al., 2019). The implementation of technology has led to investments in AI to analyze big data and create market intelligence (Stone et al., 2020).A marketing plan primarily consists of the marketing mix, which is a combination of marketing elements. The marketing mix comprises controllable marketing tools that a company uses to implement its marketing strategy, designed to satisfy consumers (Jerk & Mazurk, 2019). It is divided into four general groups known as the 4Ps. Subsequently, the 4Cs plan was introduced to emphasize the importance of the customer’s position and the formation of effective marketing communications (Tangyananakit & Samasat, 2022).Shirmohammadi and Mohammadi (2023) conducted a study titled “Using Artificial Intelligence and Internet of Things Based on Big Data to Create Knowledge and Rational Decision Making in B2B Marketing to Improve the Performance of Smart Travel Service Offices.” Their research demonstrated that AI and IoT positively and significantly impact the creation of customer and user knowledge. Additionally, the creation of customer knowledge and user knowledge of foreign markets positively andsignificantly affects rational marketing decision-making.Shah Nazari and Sharifi (2023) conducted a study titled “Artificial Intelligence-Based Systems for Consumption in Structural Marketing: Historical Reminder, Current and Future Views.” Their research highlighted the development of conscious systems and special power points to support decision-making situations for companies, especially those with a strategic identity, where good strategic data is essential.Shaik (2023) conducted a study titled “The Effect of Artificial Intelligence on Marketing,” which demonstrated that artificial intelligence significantly impacts marketing. Nalbant and Aydin (2023) conducted research titled “Development and Transformation in Digital Marketing and Artificial Intelligence Branding: The Dynamics of Digital Technologies in the Metaverse World,” showing that artificial intelligence is effective in digital marketing. Torres et al. (2022) conducted a study titled “Artificial Intelligence and Its Impact on Brand Loyalty: Relationships and Combinations with Satisfaction and Brand Name.” They used Fuzzy Qualitative Comparative Analysis (FS/QCA) along with Structural Equation Modeling (SEM). These methods reveal subtle differences that help understand the effects of different value dimensions. While SEM results emphasize the mediating role of brand love, FS/QCA results show that brand love is a major condition for brand loyalty. Different paths can be sufficient to produce beneficial results. These findings enhance our understanding of AI performance and can guide practitioners in using game experiences to influence consumer behavior.

The primary objective of this research is to identify the antecedents, dimensions, and consequences of an AI-based marketing program. It is developmental in nature and, since the data were collected without direction and manipulation, it is classified as non-experimental (descriptive) research. This study was conducted within the pragmatism paradigm using a mixed-method approach, incorporating both quantitative and qualitative methods. The bibliometric analysis method and the four-step approach proposed by Costa et al. (2017) were used to review the systematic research background. In the qualitative approach, metacomposition and the seven-step method of Sandlowski and Barroso (2007) were employed.Bibliometric Analysis As stated, this study utilized a four-step method proposed by Costa et al. (2017) for bibliometric analysis, which includes: Selection of bibliometric databases. Defining keywords (search strategy). Refining the initial results (entry and exit criteria).  Data analysis plan.

Data were collected from the Scopus database and saved in CSV format for further analysis. A total of 115 documents related to this particular issue have been published up to the mentioned date. The authors have used 789 keywords for the mentioned period. The chart illustrates the number of articles published over different years. As shown, only one article was published in 1985 in the field of artificial intelligence and marketing. From 2010 onwards, this issue gradually gained attention from researchers, and the trend of publishing articles has been on the rise from 2010 to 2022. In 2021, 50 articles were published, and in 2022, 21 articles have been published to date.

Existing studies, such as those by Avari (2018), Decamp (2020), Antons and Breidbach (2018), Chang et al. (2009), Chang et al. (2016), Liebman et al. (2019), and Gu et al. (2019), indicate that marketers can use mechanical artificial intelligence for standardization to prepare marketing plans. Intellectual artificial intelligence has a high potential for creating advertising content and personalization. For instance, authors of advertising content, websites, and social networks can facilitate the production of advertisements or post content using artificial intelligence. AI technologies enable the personalization and optimization of customer profiles in different locations and times. Content analysis can assist advertisers in creating more effective content.Based on the obtained results, the following practical suggestions can be made:Using AI for customer interaction (e.g., conversational bots to gather data related to customers’ moods and emotions).Employing AI to create music and write short stories to make advertisements more creative and memorable for customers.Utilizing mechanical AI to automate adjustments and price changes.Implementing automation by mechanical AI in the advertising media planning department.Using AI writers to produce content.Future research should consider conducting studies using experimental and longitudinal methods, as well as mixed methods. It is also suggested that future researchers address the limitation of excluding non-English language studies

Augmented reality technology has emerged as one of the main trends in the digital market in recent years. This innovative technology, due to its appeal and potential, has been repeatedly applied in innovative businesses. The aim of this study is to conduct a systematic and comprehensive review using a bibliometric approach on the citation data of literature related to purchase decision-making based on augmented reality technology. A pragmatic paradigm allowed the researcher to systematically collect citation data from the Scopus database and preprocess it following the standard PRISMA protocol. Ultimately, 239 studies were included in the bibliometric analysis using R Studio and Vosviewer software. The final results identified the most influential documents, authors, journals, organizations, and countries, and highlighted key points regarding buyer behavior and purchase decision-making with augmented reality in virtual businesses through interactive patterns between elements and content analysis of the data. Additionally, it is noteworthy that this concept mainly revolves around five primary areas: virtual and psychological experiences of buyers in online shopping with augmented reality; the impact of artificial intelligence on new technologies in buyer behavior; interactions of technology, perceived value, and cognition on buyer experience in retail using mobile augmented reality; the role of augmented reality technology in purchase decision-making and smart shopping in the virtual space. The influential school of thought on augmented reality technology in buyer decision-making is associated with the stimulus-organism-response theory, which forms the intellectual foundation of this field.

The purpose of this research is to provide a development model for the effectiveness of persuasive advertising in social networks. The research method is applicable in terms of its purpose and qualitative in terms of implementation. The statistical population of the research includes 15 experts, university professors, and managers and specialists in the field of marketing; selected through the maximum diversity sampling method. A semi-structured interview was used to collect information. Data-based and coding method was used for data analysis. In open coding, the researcher found 146 concepts, which were classified into 31 categories. Persuasive advertising in social networks can have significant effects on the behavior and attitude of consumers. These effects include changes in consumer behavior, intensification of competition, formation of values ​​and beliefs, influence on decision making, change in social behavior, influence on brand trust, change in brand attitude, and influence on social networks. However, these effects depend on various factors such as technological changes, social and cultural changes, economic changes, legal and political changes, changes in competition, and changes in the content and format of advertisements. As a result, to increase the effectiveness of persuasive advertising in social networks, it is recommended to pay special attention to these factors.

The purpose of the current research is to present an entrepreneurial marketing model based on teamwork with an emphasis on start-up companies. The research method is applicable according to its purpose, and qualitative in terms of its implementation. The statistical population consists of 15 experts who are academic professors in the field of marketing management, and managers in the marketing and sales industry, who were selected by targeted non-probability sampling. Thematic analysis method and MAXQDA software were used for data analysis, and MICMAC software was used for effective and effected between variables. The results showed that 5 comprehensive themes and 13 organized themes and 87 basic codes were identified and extracted from the theme analysis method, and then using interpretative structural modeling, the identified indicators were leveled; and the results showed that the fourth level includes marketing strategy (C04) is the most effective one that acts as the cornerstone of the model and directly affects the third level criteria (content and marketing tools (C03), and marketing performance evaluation (C02)). The first level includes the development of teamwork (C04) as the most effective level. The dimensions of the second level (networking and marketing public relations (C01)) act as interfaces.

Today, knowledge-based companies play an important role in creating innovation, enhancing employment, and increasing the competitive advantage of countries. Marketing in contemporary knowledge-based companies is an essential challenge for them as it plays a critical role in their business development, so the use of marketing knowledge is considered a key factor for their activity in the market. Businesses should use a variety of marketing activities to reach multiple customers. The rapid development of information and communication technology has provided knowledge-based companies with a wide range of marketing and advertising tools in the digital world to be more competitive in the market, create an innovative approach to exploiting market opportunities, and adopt effective marketing strategies. A marketing strategy that can be used by these companies is the newsjacking technique. The current research aimed to design a model for newsjacking in the marketing of knowledge-based businesses located in the Science and Technology Park of Khuzestan province.

The research was conducted with a qualitative approach, using the grounded theory method. The participants in the qualitative phase included marketing professors, experts, and elites in Khuzestan province, eight of whom were selected using purposive and theoretical sampling. The data collection instrument was an in-depth personal interview. A three-step coding method was used in data analysis.

Based on the results, the speed and breadth of notification, competition in grasping opportunities, and economic benefits were detected as causal factors. People's tendency towards digital media, up-to-dateness, technological progress, strategic position of the country, promotional flexibility, and innovative tendency were detected as contextual factors. Infrastructure status and government support policies were detected as intervening factors. Product introduction and marketing, low-cost advertising, digital advertising, and competitive and opportunistic advertising were detected as the axial categories. Speed of action, up-to-dateness, scientific innovation, and creative content were detected as strategies. Finally, in-advance advertising, strengthening the scientific and cultural prestige of the country, and effective communication with market and economic components were identified as consequences.

Conclusion/ Implications:

 Based on the results, it is suggested that knowledge-based businesses, while participating in various festivals, diversify the content of their advertisements, use honesty, humor, and flexibility, and recruit media consultants to choose the most suitable news that is of interest to the domestic and foreign communities, thereby compiling advertising content for their products as soon as possible. Also, they need to introduce their products to the audience by using new and creative ideas and employing all the available facilities to put their advertisements in a suitable and flexible form in social media and news.

The research was conducted with the aim of designing a neuromarketing model in the electronic services of Saderat Bank of Iran.Research method is Qualitative type of foundational data theorizing. Participants are decision-making managers and policymakers in the field of marketing in electronic services. The sampling method is purposeful and snowball with the number of 12 people. Data analysis is done through coding using Max quda software.Research findings includes 6 categories, 13 components and 144 primary codes or indicators in the form of causal conditions, central categories, strategies, consequences, contexts and interveners. Findings have shown that conditions such as organizational and customer self-conscious expectations cause neuromarketing to be formed in Saderat Bank's electronic services. On the other hand, these factors affect strategies. The mentioned factors make strategies such as new banking service strategy, digital marketing, metaverse, artificial intelligence and social media to be formed. These strategies have consequences for improving customer performance and improving bank performance. The background of these strategies, i.e. economic factors and cultural factors, should also be provided. In the meantime, interventionists such as facilitators and limiters should not be ignored.Due to the increasing growth of new technologies, the use of neural marketing strategies can help Saderat Bank to compete successfully in the digital world and provide its electronic services to customers in the best possible way.

The aim of this research is to design a pattern of drawing attention to commercial advertisements on websites, which was done in a mixed method and of the exploratory type in two consecutive qualitative-quantitative stages. In the first stage, the researcher collects the necessary information by examining studies related to the research topic and also in-depth interviews with experts in the field of marketing, and by using the method of grounded theory analysis with Glaser's approach, coding, categorizing and presenting a concept model. In the quantitative stage, the study was conducted using the structural equation modeling method. For this purpose, the data collected from a researcher-made questionnaire based on the proposed model was evaluated using Smart PLS software. After reviewing the previous studies, using exploratory and semi-structured interview tools, qualitative questions were asked from the statistical population of 14 experts and theoretical saturation was achieved. The results of grounded theory showed that the pattern of factors attracting attention to internet advertising includes 19 open codes, 5 central codes and 1 selective code. In the quantitative part, a questionnaire consisting of 19 items was provided to 217 marketing-advertising experts. Based on the results of the structural equation modeling, the value of the significance coefficient t is related to the relationship between the main variables with attracting attention to the forms of advertisements on websites at the 95% confidence level and indicates the significance of their effect on attracting attention to advertisements on websites. Therefore, all variables are identified as main variables.

The main goal of this research is to provide a model for promoting creativity theories in marketing and artificial intelligence using metacombination method. The current research is developmental in terms of its purpose, qualitative in terms of the nature of the data, and meta-composite in terms of documental data collection. Critical Assessment Skills Program (CASP) can be used to evaluate articles. Based on 52 articles selected from reliable scientific databases, the process of extracting information from the results and analyzes of these articles was done, and after evaluating each of them, 25 articles were finally approved and screened. Then, by examining the backgrounds and models of approved articles, a new conceptual model design was obtained. for the category of creativity theories from three indicators of individual creativity (personal creativity, creative advertising insight, creative performance, creativity in sales); organizational creativity (collective creativity, advertising creativity, strategic innovation, creative self-efficacy); Product creativity (product innovation, creative production, new product innovation) was extracted. Also, for the marketing category, three indicators of marketing strategy (creative marketing strategy, marketing activities, marketing channels); B2B marketing capability (information management, planning, implementation); Integrated digital marketing (experiential marketing, content marketing, digital marketing, real-time marketing) was extracted, and finally, for the category of artificial intelligence, an index of artificial intelligence capabilities was extracted (artificial intelligence strategy for leading smart technologies, artificial intelligence-based marketing).