نشریه مدیریت بازاریابی هوشمند
سال پنجم شماره 1 (پیاپی 23، بهار 1403)

In the modern world of marketing, the use of emerging technologies plays a vital role in shaping marketing strategies. In this regard, ChatGPT, as a tool based on artificial intelligence, has provided new possibilities for marketers that can create great changes in interacting with customers and personalizing marketing communications. This article examines and analyzes the applications of ChatGPT in marketing and through a case study and data analysis, shows how this technology can help optimize customer-related processes. In this article, a comprehensive review and analysis of scientific articles published in 2023 and 2024 has been done to show what new developments have been experienced in marketing research. The main focus is on the role and importance of using artificial intelligence tools such as GPT chat in this research. The findings show that the use of these technologies in marketing studies has not only helped to form a better understanding of consumer behavior, but has also been effective in improving the level of interaction and responding to their needs. In particular, GPT chat has emerged as a powerful tool for personalizing the customer experience, and significant benefits have been achieved in improving communication and increasing customer loyalty. This research confirms that the integration of advanced technologies in marketing strategies can have positive effects on the overall performance of companies. In addition, this paper addresses the main challenges arising from the implementation of AI-based technologies in the marketing industry, including concerns about customer privacy and data management. Finally, it provides recommendations for overcoming these challenges and optimally exploiting ChatGPT in marketing. This research provides a platform for a better understanding of the uses and potentials of ChatGPT in the field of marketing and can serve as a guide for marketers to use more effective strategies.

This research is designing and explaining the intelligence model of new businesses (startups) for the purpose of organizational resilience in the conditions of inflationary stagnation. This research is fundamental (first stage) with applied approach (second stage). In terms of its nature, it is also included in mixed methods (exploratory-descriptive). In this research, in order to analyze the data obtained from the questionnaire, the coding procedure, according to the statistical needs, is from the statistical software SPSS.V24 and from the structural equation software pls.V3 in the format Two parts of descriptive and inferential statistics have been used in the form of linear and multiple regression. The statistical population of this research in the qualitative stage is 15 experts in the field of organizational behavior, including university professors and managers of active startups in Tehran province. The statistical sample in the qualitative part will be based on the snowball technique. Quantitative statistics of all active startup employees in Tehran province, whose number is 1500. The sampling method in this research is accessible. which are 306 people using Cochran's formula. whose number will be 384 people. The results of the research show that the causal conditions of the research on the central phenomenon in the intelligence model of start-up businesses (0.737), the intelligence of start-up businesses on research strategies in the intelligence model of start-up businesses (0.700) 0) interventional factors of research on research strategies in the intelligence model of start-up businesses (0.003) contextual factors of research on research strategies in the intelligence model of start-up businesses (0.999) research strategies on the consequences of research in the intelligence model of start-up businesses (0.700) has a significant effect in the conditions of inflation stagnation.

In this research study, which was conducted in 1402 in the information technology department of the National Bank of Tehran, an attempt was made to explain and formulate a new phenomenon in the form of a causal model of organizational social responsibility, based on the decisive role of organizational commitment. Using the present approach, the researcher has searched for a correct and deep understanding of the related concepts, while the case study includes providing a sample of 200 employees in the relevant unit, who were selected through available sampling method. The precise design of measurement tools includes questionnaires specialized, including the questionnaire of professional ethics of innovative management by Karam Dokht (2010), organizational performance indicators extracted from the Achio model, by Rahmani and Rajab Dari (2015), the social responsibility scale by Gio Hyomin and Chris Ryan (2011), the organizational culture tool from Denison (2000) and the structure of organizational commitment was compiled by Mir and Allen (1997). The skillful use of IBM AMOS software version 24 in data analysis can indicate the accuracy and complexity of the statistical analysis of this research. The findings of the model fit confirmed the hypothesis that organizational commitment affects social responsibility and placed this relationship at a significant level with a P value of 0.003. In addition, it was found that the variables of organizational culture, organizational performance and management ethics also have significant effects on social responsibility, which is also confirmed with a valuable P value of 0.001. These data decisively express the importance of organizational commitment in strengthening the principles and values related to social responsibility among employees. In addition, the obtained results indicate that an effective organizational culture acts as a supportive platform for increasing organizational performance and creating a context for ethical behavior among managers. Research hypotheses and models were prepared using advanced structural equation modeling methods, where Path analysis and direct and indirect effects between variables were explored. This approach has described the dialectic between organizational commitment and the components affecting organizational social responsibility in a scientific and practical way and revealed meaningful links between them.​

The current research aims to investigate the characteristics of platforms based on augmented reality technology on the behavioral and cognitive responses of customers of interior design products and furniture in Tehran. The current research is quantitative in terms of practical purpose and research method. In terms of data collection, due to the use of library study methods and field methods such as electronic questionnaires, it is a descriptive-survey type. In this research, the customers of the interior design products of buildings and furniture in Tehran have been selected as the statistical population. Therefore, the size of the unlimited population and the sample size were calculated using G*power software 257 people. After checking and verifying the reliability and validity, the questionnaire was distributed electronically. After pre-processing,257 collected questionnaires were finally used. Demographic data was analyzed with SPSS version 23 software, and due to the non-normality of data distribution, Smart PLS version3software was used for model testing. Finally based on the hypothesis test, the increase in the number of interaction variables, system quality,ability to provide information about the product, and agreement with reality, which are considered as features of platforms based on augmented reality,on the reactions Emotional,cognitive and behavioral of customers has a positive and significant effect.According to research findings,augmented reality technology has a significant impact on customers' decisions.When customers use platforms based on augmented reality,the sense of immersion, enjoyment, and interest in the product increases,and as a result, the trust in the choice,the level of usefulness of the platform,and generally positive attitude also increases,which ultimately leads to an increase in intention.The re-use of the platform and the intention to buy in the customers.The proposal that is made to managers active in the field of production of devices related to the interior design of buildings and furniture,is to initially design and test their business in an augmented reality environment with the help of professional groups.Of course,because this technology is new in Iran,one must be very careful in the design of the platform.It is necessary to design the desired platform in such a way that the customer,despite being unfamiliar,can easily communicate with it.

With the expansion of the use of the Internet of Things and its role in the cheaper and faster use of physical and digital sensors and the possibility of collecting data on a large scale, the use of these tools in marketing is becoming more and more ready and the study of the emotional behavior of buyers is becoming more widespread. Artificial intelligence and machine learning as a processor of collected data can help us in analyzing consumer behavior, especially in emotional purchases that have a wider complexity. This article was written with the aim of finding a model for using the Internet of Things and artificial intelligence in the analysis of emotional purchases. This article was written as a systematic review of SLR and by examining review articles in the three dimensions of Internet of Things, artificial intelligence and emotional purchases from 2020 onwards. Finally, the model proposed by the researchers has been presented.

The main purpose of this research was to investigate the impact of customer hostility on business. Due to the exploratory nature of the research topic, it was not possible to provide an initial answer or a hypothesis plan suitable to the main question above, and the final answer was obtained by using the theme analysis method. To collect data and extract experts' opinions, interviews A semi-structured interview was conducted with 15 managers and professionals with experience in business who were selected by a purposeful method and as a snowball chain reference. Then, with a round-trip process based on theme analysis of key concepts related to the impact of hostility. Finally, 186 key concepts, 43 selective codes, and 22 sub-themes were identified and in the form of 8 main themes including: 1-increase in unbalanced behavior of customers 2-increase in the number of complaining customers 3-increase in business costs 4-increase in negative advertisements by customers 5- Decrease in brand popularity and position 6- Decrease in sales 7- Decrease in business profit 8- Decrease in market share

This research was done with the Strategies and measures related to competitive advantage with the mediation of environmental factors and operational capabilities of the organization in the clothing industry. The statistical population includes 15 experts and managers of clothing manufacturing companies who were selected in a non-random way. The main tool of data collection is semi-structured in-depth interview. After confirming the reliability and validity of the interviews, a qualitative analysis method with a data base approach was used using MAXQDA software, and then, based on the findings of this stage, the research model was developed. Next, in order to explain the model based on the findings of the qualitative method, the initial questionnaire in the quantitative part of the design, validity and reliability of this tool was reviewed by referring to the opinions of experts and managers and approved after the corrections. The statistical population in the quantitative section, the customers of clothing products in Tehran and the statistical sample, according to Morgan's table, a sample consisting of 384 people was selected and distributed and collected by available sampling method. Analysis and processing of quantitative data was done with the help of PLS software. Coding has been done in three stages: open, central and selective coding. Based on the obtained paradigm model, the research in the apparel industry in three categories of central phenomenon (competitive advantage), strategies (company planning), intervening conditions (competition management factors) were identified.