بازاریابی

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.

Introducion: Policy-making is the basic function of the government and the process of intervention in order to achieve results and realize its political vision. The study of public policy seeks to describe and explain government policy and how to influence and change it. The current research has been carried out with the aim of designing a model for the marketing policy of cultural and creative goods and services in the Ministry of Culture and Islamic Guidance, using the theory derived from the data.  The research method is of descriptive-applied type, in terms of orientation, it is of fundamental type, and in terms of research goal, it is also of exploratory-qualitative studies type. The statistical population of the participants of this research included academic experts and people specializing in the field of marketing and industries active in the field of cultural and creative goods and services, the number of samples was selected based on the snowball sampling method in the number of 30 people. Data collection has been done in the form of a semi-structured interview. In the data analysis, first, the codes and components of the design model of the policy model of the marketing of cultural and creative goods and services were extracted from the interviews and compiled in the form of the foundation’s data conceptual model. The central category and causal, background, intervening conditions, strategies and results, formulation and final model were presented. Then, using the Delphi analysis method, a preliminary model design questionnaire was presented by experts to modify, confirm and model the marketing policy of cultural and creative goods and services in the Ministry of Culture and Islamic Guidance.  According to the results of this research, the main categories of the compiled model have included policy factors of marketing of cultural and creative goods and services. Therefore, based on it, the expected consequences of the policy model of marketing of cultural and creative goods and services in the Ministry of Culture and Islamic Guidance can be achieved. Hence, this research investigates the conceptual foundations and practical implications of creativity and innovation within the realm of creative industries. It begins by outlining how novel and original thinking serves as a driving force behind economic transformation and the production of new services and products. Drawing upon a diverse array of theoretical perspectives - including international frameworks provided by organizations such as the United Nations Conference on Trade and Development and insights from the British Department for Digital, Culture, Media & Sport- the study positions creativity not merely as an aesthetic or cultural phenomenon, but as a strategic economic asset that influences market competitiveness and national development. The theoretical section of the paper reviews seminal literature on the emergence of creative thinking and its evolution over time. It discusses how creativity has been conceptualized as both an individual and collective process, underpinning innovation in various sectors. The review further examines the interplay between governmental policies, cultural influences, and technological advancements in shaping the dynamics of creative industries. In doing so, the article highlights how contemporary economic models increasingly rely on innovative practices that blend cultural capital with market-driven strategies. Methodologically, the study employs a mixed-methods approach that integrates qualitative content analysis and grounded theory. Through a series of in-depth interviews and surveys with experts and practitioners, the research captures a wide spectrum of perspectives on the integration of creative processes in business and public policy. Data analysis was facilitated by specialized software, allowing for systematic coding and identification of key themes such as the strategic application of creative thinking, the role of interdisciplinary collaboration, and the impact of evolving cultural and regulatory environments. The findings indicate that creativity is a multifaceted construct, one that is essential not only for the development of new products and services but also for fostering organizational resilience and competitive advantage. The study reveals that successful innovation in creative industries hinges on a complex mix of factors, including the effective translation of abstract creative ideas into concrete economic outcomes, the supportive role of policy frameworks, and the capacity for adaptive learning in rapidly changing market conditions. In conclusion, the research presents a comprehensive model that bridges the gap between creative ideation and strategic execution. It calls for managers and policymakers to adopt an integrated approach that combines adaptive leadership, strategic alignment, and continuous improvement to fully leverage the potential of creativity in driving economic success. By fostering environments that support innovation and by implementing robust measurement and evaluation systems, organizations can transform creative insights into sustainable competitive advantages. Future research is encouraged to explore how emerging technologies and evolving market conditions further impact the role of creativity in strategic management, thus providing ongoing guidance for practitioners seeking to navigate the complexities of modern business environments.

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.

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.

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.

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.

Considering the importance of marketing and public relations in libraries and the lack of an official position on the one hand and the compilation of the new standard of public libraries in Iran on the other hand, the aim of this research was to investigate the view of public library managers of Isfahan province about the feasibility of implementing the Standard of Marketing and Public Relations of Iranian Public Libraries (2020).

This research was applied in terms of purpose and descriptive-survey in terms of method. The statistical population consisted of 196 public library managers of Isfahan province. 127 managers were selected as a statistical sample by the Krejcie and Morgan table and stratified random sampling method. The data collection tool was a researcher-made questionnaire, and SPSS V.26 statistical software was used to analyze the data.

The results showed that the average feasibility of implementing the Standard from the view of public library managers of Isfahan province is lower than the average (x=3) and the observed average difference is also significant. The average of the components of planning, evaluation and support were all lower than the hypothetical average, which shows the poor condition of the feasibility of these components in the public libraries of Isfahan province. There was also no significant difference between the view of the public library managers based on the demographic variables of gender, age, education degree, discipline, city and work experience regarding the feasibility of implementing the Standard.

Conclusions: 

So far, there has been no research on the Standard of Marketing and Public Relations of Iranian Public Libraries (2020). The results of the present research can achieve the desired situation in the field of marketing and public relations in order to attract the audience and facilitate relations with the actual and potential audience community.

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.

Political marketing, as an interdisciplinary science, seeks new ways to understand and manage modern policies, emphasizing the analysis of voter behavior, political organizations, and governments to guide public opinion in influencing people's votes and maximizing political participation in political competitions, especially elections. This research employs a qualitative method based on grounded theory, conducting semi-structured in-depth interviews with 21 political elites and experts based in Tehran using snowball sampling until theoretical saturation is reached. The study initially seeks to answer the question of how individuals, parties, and political movements can maximize their vote share and consistently succeed in electoral competitions, emphasizing which components. The findings indicate that the research model comprises 14 dimensions, 31 components, and 81 effective indicators, structured within a paradigmatic model that includes two causal condition variables, three contextual condition variables, two core category variables, three strategic variables, two intervening variables, and two outcome variables.

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

This research is applied from the perspective of purpose and descriptive-survey research from the perspective of data collection method. The statistical population included customers of sports complexes in Tehran. The samples were determined based on Cochran's formula of 384 people using cluster random sampling method. For data collection, the Internet Advertising Assessment Questionnaire, Chang and Wang (2019), respectively. Chang and Wang Electronic Word of Mouth Advertising Questionnaire (2019). Questionnaire of disapproval of the expectation of the judge and colleagues (2017). Behavioral Tendency Questionnaire from Hyun, Kim and Lee Questionnaire (2011). used. SPSS and Smart pls software were used to analyze the data. Based on the results of electronic advertising and word of mouth, it has an effect on the behavioral tendencies of customers (0.712) and (203), respectively, which is significant according to the rate of T (9.550) and (2.483). And disapproval of expectation as a mediator affects the relationship between electronic advertising and behavioral tendencies of customers, so disapproval of expectation as a mediator affects the relationship between word of mouth and customer behavioral tendencies. Therefore, with the increase of advertising, customers' behavioral inclinations will also increase and the tendency to prefer and use products and services will also increase. Therefore, it is suggested that in presenting advertisements, points such as increasing the quality of services at the time of submitting the request and need, awarding prizes, facilities and price discounts, and using new and non-repetitive techniques to advertise services should be considered.

The purpose of this study is to design a marketing development model for the Iranian Wrestling Federation. The statistical population of this study includes specialized faculty members (marketing, sports management, wrestling experts of the Islamic Republic of Iran), senior managers of the Wrestling Federation of the Islamic Republic of Iran, national and provincial coaches Higher education in sports management, wrestling experts and journalists, senior managers of the National Olympic Committee and the Ministry of Sports. Purposeful sampling was performed by snowball method. Then the primary, axial and selective codes were assigned. Findings showed that the reported regression coefficients, causal factors, contextual factors and intervening factors had the greatest impact on marketing development, respectively. In addition, the impact of interfering factors is negative. This means that as it increases, the amount of marketing development decreases. In this study, data collection and analysis were performed based on variable sequences and with multiple revisions of the same. The research in general showed that in causal conditions (managerial and technical category), intervening results, legal and legal requirements), underlying factors, (efficient manpower) and marketing development (causal conditions) are very effective. And the rest of the categories are in the next priorities.

The current research was designed and implemented with the aim of designing a marketing model for the services of women's sports clubs. The current research was mixed in terms of practical purpose, in terms of descriptive-survey data collection method and based on the research approach. The statistical population of the present research in the qualitative part includes professors who had conducted research (books, translations, research projects, conference and research articles and at least two cases) in the field of sports marketing, as well as managers of women's sports teams. Be Purposive sampling method was used to select the interviewees. This sampling continued until theoretical saturation was reached and finally 30 people were selected as a sample. Also, the statistical population in the quantitative part of the research included the same group in the qualitative part in order to participate in the Delphi process (30 people). The tools of the current research included semi-structured interviews and a Deli questionnaire (59 items and 5 dimensions) in a 9-point Likert scale. Open, axial and selective coding was used to examine the data in the qualitative part, and the fuzzy Delphi method was used in the quantitative part. The results of the present research showed that the 4 factors of operation, cultural, social, infrastructure and economic are among the most important factors affecting the marketing of women's sports club services. Considering the effect of the service marketing model on the development and improvement of Batawan sports clubs,

This study aimed to identify and analyze the factors affecting themarketing of sports equipment manufacturing companies in social networks.

This study was a mixed-methods research with a sequential explanatory design. The participants of this research consisted of 18 experts who were selected using snowball sampling method. The content analysis method proposed by King et al. (2018) was used to identify the influential factors, and the Dematel technique was used for internal analysis. In the qualitative section, research auditing strategies such as researcher sensitivity, methodological coherence, sample adequacy, simultaneous data collection and analysis, and theoretical thinking were used. In the quantitative study, for validation purposes, formal and content validity were confirmed by 8 marketing experts in the sports field, and questionnaire reliability was obtained through Cronbach's alpha coefficient of 0.896. 

The qualitative study identified 77 sub-themes and 16 main themes affecting the marketing of sports equipment manufacturing companies in social networks. In a quantitative analysis, it was determined that the themes of hard threat, soft threat, and the expansion of social networks have the greatest effect on the mentioned marketing, and contrast to the themes of legislation, value creation, and determining content production strategy, respectively, they have the least effect on marketing. It was also found that the themes of determining content production strategies, tactics and policy, and the platform have the highest effectiveness. And the theme of determining tactics and approaches has the most interaction with other relevant themes. Finally, the variables of severe threat, soft threat, expanding the influence of social networks, the growth of the digital environment, customer recognition and financing are causal themes, and other themes are invalid variables.

It can be concluded that the factors influencing the marketing of sports equipment manufacturing companies on social media platforms are diverse. Among them, these companies should pay special attention to the most influential threats, both hard and soft, and plan to address these threats and leverage available opportunities.

A successful marketing strategy is essential for driving economic dynamism within the steel and iron industry, particularly during times of economic instability and fluctuating prices. The objective of this article is to identify and prioritize the key factors influencing the marketing of the iron and steel industry amid exchange rate volatility. To achieve this, a mixed-methods approach (qualitative-quantitative) was employed. Initially, a comprehensive analysis of existing literature and documents was conducted to identify the primary factors affecting marketing in the iron and steel sector. In the subsequent quantitative phase, a survey was administered to 100 marketing experts to further explore and prioritize these factors using stepwise regression analysis. The qualitative phase involved a review of relevant articles, research reports, and theses related to industrial marketing, while the quantitative phase targeted experts and specialists in the field of marketing. A purposive sampling technique, specifically snowball sampling, was used for both phases. Data collection tools included content analysis for the qualitative phase and a researcher-developed questionnaire for the quantitative phase. Data analysis was conducted using SPSS version 23, complemented by manual analysis as needed.The results of the study revealed that the most important criteria affecting the marketing of the iron and steel industry during exchange rate fluctuations, in order of priority, are: economic factors (such as reducing production costs, utilizing up-to-date production technologies, and aligning production with supply and demand), social factors (including strategic management and identifying customers and their needs), and environmental factors (with a focus on reducing production energy consumption).

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