نشریه مدیریت بازاریابی هوشمند
سال پنجم شماره 2 (پیاپی 24، تابستان 1403)

In the future world, where self-sustaining artificial ecosystems are designed and developed as sustainable habitats for humans and other creatures, marketing has also undergone fundamental changes. These ecosystems, which are managed using advanced technologies and artificial intelligence, require innovative and intelligent marketing approaches that can adapt to their complex and independent environments. In this short article, we take a deep look at smart marketing strategies in these new ecosystems. From using environmental data to personalize customer experiences to designing campaigns that are synchronized with self-learning algorithms and self-adjusting systems, we will show how marketers can meet the changing and complex needs of the inhabitants of these ecosystems by using advanced technologies and predictive analytics. Also, the ethical and social challenges related to marketing in these self-sufficient environments have been examined and solutions are provided to create a balance between profitability and social responsibility. Finally, we will draw a vision of the future of marketing in a world that moves towards sustainability and self-sufficiency. And the importance of innovation and adaptability will be addressed in this direction.

Currently, the expansion of information technology and the explosion of information has led to an increasing attention to neuromarketing. Therefore, the continuous analysis of the internal and external environment of the organization and the continuous interpretation of the information received from the environment will have a great impact on the future decisions of the managers for the greater success of the organization. One of the important resources of the organizations to achieve this goal is the development of the competitive advantage of sustainable production. Therefore, the current research prioritizes the effective factors of neural marketing techniques in sustainable production in Iran's food industry using the fuzzy DANP method.

The current research is considered to be applied in terms of purpose and descriptive survey in terms of data collection. Using the purposeful sampling method, 15 experts were selected as sample members. Fuzzy Delphi, Fuzzy Dematel and Fuzzy DANP techniques were used to analyze the data. In this research, in the first stage, the effective factors of neuromarketing techniques in the sustainable production of Iran's food industry were identified. And then, in the second stage, the importance of the factors was determined, and in the third stage, the alternatives were ranked.

The findings showed that the effective factors in choosing neuromarketing techniques in sustainable production include: cost, accuracy, usefulness, time saving, information quality, biases, memory search and emotions, and the alternatives are: advertising, product development, pricing , branding, product design, customer decision-making, investment in capacity building, growth and development strategy, implementation of green strategy, environmental strategies, more energy saving. The four most important criteria include: information quality (0.155), usefulness (0.148), memory search and emotions (0.145) and biases (0.143). Also, four high priority options include: customer decision-making (0.116), implementation of green strategy (0.108), investment in capacity building (0.107) and branding (0.103). Therefore, it can be said that nowadays consumers are more interested in buying sustainable products and are willing to pay for sustainable products because of their benefits in reducing socio-ecological problems.

Exporting can bring in new resources and income from foreign markets and these resources can help to invest in research and development, develop new technologies, grow and improve business. By entering the global markets, the products and services of international companies are improved and grow day by day. Successful companies in the international arena are said to be companies that use successful export strategies. For this reason, exporting through the mediation of the competitive advantage of intelligent services can expand international businesses in terms of size and technical knowledge. The aim of this research is the impact of exports on the performance of international businesses by mediating the competitive advantage of smart services.

The current research method is based on the purpose, applied and based on the nature of the data, descriptive survey. The statistical population of the research included 110 managers and employees of international Iranian start-up companies and international businesses. Standard questionnaires have formed the data collection tool in this research. Also, the software used to analyze the research data was SPSS and structural equation modeling using the PLS approach.

The findings indicate the positive and important role of export, market intelligence, product innovation and pricing on improving the competitive advantage of intelligent services and the performance of international businesses. It was also concluded that the competitive advantage of intelligent services plays the role of mediating the effectiveness of this relationship.

Many businesses use new technologies to be more present and gain more market share. According to the results of the research, it can be said that when companies enter the field of export by mediating the competitive advantage of intelligent services, they witness an increase in their productivity and performance. Therefore, exporting to foreign markets allows the business to reach new markets, the amount of demand and market opportunities are different in different countries, and the company's competitive advantage can help the company to grow in foreign markets.

The proliferation of generative artificial intelligence, from healthcare to finance, underscores its transformative potential in addressing real-world challenges. The generative AI model is trained to act almost like a human. The conversational format allows the AI to answer follow-up questions, admit mistakes, challenge false premises, and reject inappropriate requests. Also, generative artificial intelligence provides huge opportunities for organizations that use this advanced technology strategically. Therefore, the current research was conducted with the aim of identifying the antecedents and consequences of the productive artificial intelligence tool using the fuzzy FCM method. The statistical population of the research is the experts in the field of information technology and artificial intelligence, among whom 10 people were selected as sample members using the purposeful sampling method and based on the principle of theoretical saturation. The tool for collecting information is an interview in the qualitative part and a questionnaire in the quantitative part. In this research, the content analysis method and coding with Atlas software were used to analyze the data in the qualitative part, and the content method and theoretical validity and intra-coder inter-coder reliability were used to check the validity and reliability of the data collection tool in the qualitative part. Its reliability was confirmed with a coefficient of 0.84. Also, the validity and reliability of the data collection tool in the quantitative part, content validity and retest reliability showed the confirmation of the reliability of the questionnaires. Also, the validity and reliability of the research questionnaire was measured by content and retest validity. The findings of the research show that the most important antecedent factors for the development of productive artificial intelligence are keeping pace with the fundamental changes in technology, the possibility of correcting organizational gaps, and facilitating the learning of employees. Also, the most important consequences of the formation of productive artificial intelligence are speeding up the implementation of processes, increasing efficiency and productivity, and the risk of privacy violations.

This research is to investigate the effect of efficient human resource management practices on readiness for change, emotional commitment and employee performance with the moderating role of hierarchical culture in Tejarat Bank branches in North Tehran. The research is descriptive and survey in terms of practical purpose and in terms of how to collect information. Research data has been collected through five-choice Likert questions included in the research questionnaire. In this research, in order to analyze the data obtained from the questionnaire, in accordance with the statistical needs, SPSS.V24 statistical software and pls.V3 structural equation software were used in the form of descriptive and inferential statistics in the form of linear and multiple regression. The statistical population of this research is the employees of Tejarat Bank in the northern branches of Tehran, which totals 440 people. In order to calculate the required sample size for the research, using Cochran's formula, 5% confidence level equal to 205 people was obtained. The studied sample was collected by the available method. The results of the research show that effective human resource management methods affect employees' emotional commitment (0.269), effective human resource management methods affect employees' readiness for change (0.355), emotional commitment affects employees' readiness for change (0.523), readiness To change the performance of employees (0.479), efficient human resources management methods have a significant effect on the emotional commitment of employees with the role of adjusting the hierarchical culture (0.089) in Tejarat Bank branches in the north of Tehran.