Management Research in Iran

Abstract Recently, with the penetration of artificial intelligence, the marketing environment of small and medium enterprises has experienced significant developments. The aim of this research is to identify the most influential contributors, current trends, and future research directions in the field of artificial intelligence in digital marketing in small and medium enterprises. For this purpose, bibliometric data of 100 documents between 2000 and 2025 in the field of artificial intelligence in marketing research were extracted from the Scopus database. VOSviewer version 1.6.20.0 software was used for the analysis. The results and publication trends indicate the annual growth in artificial intelligence in marketing research. In addition, keyword co-occurrence analysis uncovered four main thematic clusters: Cluster 1 - Digitalization of SMEs, Cluster 2 - Marketing Opportunities of AI in Industry, Cluster 3 - Data Analytics and Advanced Decision Making, and Cluster 4 - Marketing Strategies and Social Media. By identifying current thematic clusters, this study identifies future research areas. It also has practical implications for marketers in SMEs and shows how AI can be used to improve business operations.

Abstract The digital world provides many opportunities for marketers to reach customers. However, in the fast-paced world, finding new and innovative ways to market products and services is very important. Due to the advancement of artificial intelligence and its development in the field of international marketing, professionals now have the tools to completely redefine the current understanding of branding, marketing and advertising. The growing popularity of the Internet and the increased use of mobile devices are generating massive amounts of consumer data that feed artificial intelligence-based systems. This research is a type of mixed research with a qualitative and quantitative approach, which is a survey study in terms of its purpose, application, and in terms of data collection. The statistical population of the research was managers and experts specializing in the field of digital marketing and IT in the international field, who were selected using the snowball sampling method. In the qualitative part, the tools for collecting information were library and articles review, interviews, and in the quantitative part, questionnaires. In the qualitative part of the data analysis method, using the theme analysis that was compiled with MAXQDA software and using the coding method, and in the quantitative part, the analysis method was based on Kendall's correlation test. According to the results of the research, 9 main themes, 20 sub-themes and 50 codes were discovered, which included the consequences of using artificial intelligence in international marketing. The research findings can have important results for exporters and international marketers

Abstract The emergence of Web 3, characterized by the integration of digital technologies such as artificial intelligence, machine learning, big data, and blockchain, has the potential to revolutionize traditional business practices. This transformative phase, referred to as Web 3 entrepreneurship, is disrupting established industries and creating new markets, thereby driving economic growth and generating employment opportunities. However, the rapid pace of technological advancement presents complex challenges that necessitate exceptional adaptability and continuous learning within the evolving entrepreneurial landscape. This study aims to identify the critical factors for growth and success, as well as to explore the implications of this modern form of entrepreneurship. To achieve this, a Delphi study was conducted involving 30 industry experts, leading to the identification of four categories of key success factors: technological, individual, environmental, and organizational. The findings of this research revealed that while there are potential adverse environmental, social, and economic consequences, such as the risk of creating a digital divide and increased energy consumption, there are also opportunities inherent in this technology. These opportunities include the potential to mitigate these consequences by fostering greater transparency and trust in transactions, creating new decentralized ecosystem-based opportunities, and developing sustainable solutions to address environmental challenges.

Abstract All of the financial institutions for gaining the best profit of their investment are always looking for the best investors, consulters, and borrowers. Besides, different sciences attempt to represent accurate methods for the separation of the customers. For that reason, sciences such as psychology, management sciences, mathematics, financial and etc…seek to achieve this aim. The subject that comes into consideration in this paper is the necessity of using the new methods in data mining in mixture with artificial intelligence techniques in order to deal with the sophisticated issue and answer to this question that do the usage of combined approach predict the customer rating well? If we want this process occurs, another dimension must not be forgotten that is the select measurement criteria and in this regard, the researcher has used judging journalist and non-parametric analysis in order to rank criteria thatfinally, select the number of indicatorsin order to implement the hybrid model will lead the researcher to answer this question: do the journalist’s ideas selection criteria result in a good prediction of the credit status of customers? The three indicators “age”, “previous relationship with the bank”, and “credit”to implement a fuzzy neural hybrid model are chosen. The model has been implemented in three layers and results suggest that 89.67% times the system can accurately estimate the proportion of customers provide ratings.To optimize the fuzzy neural network, the ant colony algorithm was used which results in improved performance of the model was 90.5%.