درخت حوزه‌های تخصصی

Subject and purpose: The intelligent sales management system in Metaverse is the concept of performing sales operations, using smart contracts, machine learning, intelligent process automation and direct monitoring of all network members in Metaverse.The aim of the current research is to provide a model of intelligent sales management system in Metavers. Methodology: In the qualitative research, the statistical population includes experts in the fields of business management and information management, and the sample size was calculated and carried out according to the theoretical saturation point of 14 people using the snowball sampling method. Data collection was done through semi-structured interviews with experts and analysis. Data were collected using open, central and selective coding method. Findings:The findings obtained in the qualitative research showed 112 codes, 29 concepts and 9 categories, which led to the presentation of an intelligent sales management system model in Metaverse. Conclusion:This research led to the presentation of a new model of intelligent sales management system. Keywords: Intelligent management system, Metaverse, Foundation data.

Introduction: Within marketing literature, a widely accepted notion indicates that strategies in marketing significantly differ between business-to-business (B2B) and business-to-consumer (B2C) models. This study thoroughly investigates brand loyalty, examining the nuanced differences in methodologies for building brand loyalty specifically within B2B frameworks, aiming to develop a model tailored for B2B enterprises. Methodology: The research utilizes a sequential exploratory mixed-methods approach. The initial qualitative phase involves systematic reviews and meta-synthesis to identify factors influencing brand loyalty. The subsequent quantitative phase employs techniques such as structural equation modeling (SEM) to analyze the impact of various factors on brand loyalty across different business models. Finally, interviews are conducted to gain insights into tailored strategies that enhance loyalty in B2B contexts. Data for the literature review will come from reputable domestic channels, including academic portals, alongside foreign databases like Scopus and Web of Science. The second phase will gather information from diverse companies in the insurance industry, utilizing convenience sampling for analysis. The third phase targets business experts in B2B settings, selected through purposive judgment sampling to ensure relevant insights are gained. Findings: The initial phase reveals ten critical factors that contribute to brand loyalty in B2B markets. These factors encompass customer satisfaction, perceived value, switching costs, trust, perceived quality, personalized interactions, perceived support, brand image, and commitment. Analysis indicates significant differences in factors influencing brand loyalty between B2B and B2C models. The study concludes with a collection of tailored strategies essential for fostering customer loyalty in B2B operations, including developing strategic frameworks and adopting stringent quality standards. Conclusion: This research expands the understanding of loyalty-building strategies across diverse business models, offering insights that enhance the existing body of knowledge. By proposing a specialized loyalty model for the insurance industry, the study equips practitioners with practical tools to improve operational efficiency and competitive advantage.

Purpose: The primary objective of this research was to integrate ChatGPT, an advanced artificial intelligence language model, into distance science education. By addressing the specific challenges inherent in online learning environments, this study aims to investigate how technological advancements, such as ChatGPT, can effectively enhance the management and overall quality of distance education experiences. Method: This qualitative, exploratory study aimed to provide a comprehensive understanding of the potential applications of ChatGPT in distance science education. This study identifies the various interactions that can occur in distance education and describes and evaluates the input and output instructions associated with each interaction. The chat bot used is https://chatbot.theb.ai and A biology tutoring platform uses ChatGPT to provide personalized support to students working on biology issues or concepts. Findings: Based on the results, the artificial intelligence can play an important role in improving distance science education. Furthermore, this study highlights the importance of developing metacognitive skills among learners and encourages educators to seek professional development opportunities to enhance the quality and engagement of distance science education. This study emphasizes the need for careful planning, research, design, evaluation, management, and responsible application of AI technology in distance education. Conclusion: This study was concluded that ChatGPT could be very useful for both learners and educators in distance education. This research showcases the innovative results facilitated by ChatGPT and provides valuable insights and practical guidance for educators, researchers, and policy makers on the effective use of AI technologies in distance science education.

Purpose: The purpose of the current research is to extract the components and dimensions of digital transformation and determine the levels and sequence of dimensions in Iran's education and upbringing, for the planning and implementation roadmap.Method: This research has a mixed approach (qualitative-quantitative). The qualitative section was able to extract the components of digital transformation by searching for authentic Persian and English articles published in the last ten years. With the help of seven experts, the digital transformation components were classified into eight dimensions in the form of 109 identified sub-components using the ISM method. Dimension levels were determined by SSIM matrix calculations in the quantitative part. MICMAC software version 5.3.0 was used to calculate the impact of relationships.Findings: Based on the opinion of experts and the results of ISM calculations, the identified dimensions including: institutional, education, technology, infrastructural, social, cultural and economic were placed in four levels.Conclusion: According to experts, the institutional dimension, being placed at the fourth level, has the greatest impact on digital transformation in Iran's education. Therefore, it is one of the key dimensions to achieve digital educational transformation that is placed at the first level of the model. According to the results of ISM, the economic and cultural dimensions were placed at the third level. Also, in analyzing the impact of relationships between dimensions using MICMAC software, the results indicate that the institutional dimension has a significant impact on infrastructure development.

Exploratory studies in understanding the impact of decisions on the sustainability of small and medium businesses during the corona disease crisis in line with the research objectives and based on the non-linear and dynamic conditions caused by the high speed of prevailing environmental changes compared to the development of a dynamic model of the decision making. These businesses, on the one hand, are fragile against crises due to their limited financial ability, and on the other hand, with high flexibility and quick decision-making power, they have the ability to adapt to the existing conditions. In order to create this model, it is necessary to identify the problem, and in order to answer the research questions therefor it is necessary to develop a theory based on the opinions of experts and available data. This theory is due to the special conditions and the lack of previous experience result of the Grounded Theory’s methodology, that it should indicate all the effective factors in the field of decision-making in these businesses in Iran and the causal relationships between them and affected by the existing background conditions and it is an environmental interferes. background factors and identifying the impact of environmental interferes on the decision-making process in SME under the conditions of the Corona crisis. This theory states that the decision-making process for the sustainability of the business should be based on strategies. These strategies include creating opportunities, applying a new attitude in the continuation of business life, changing in business processes, creating organization agility, and re-engineering the structure . Considering the mathematical ability of the dynamic method to analyze the results of the dynamic model as scenarios that are applied to the business in the form of decisions made and by controlling their feedback, its effects on the organization's pillars and resources can be shown as quantities. The measurement of these quantities and the way of changes and their impact enables the quantitative proof of the mentioned theory. By this method the managers will have the ability to evaluate and prospect their decision results in the conditions of the Corona crisis.

Purpose: Neurotransmitters, emotional intelligence, and personality traits are the key factors that affect the behavior and decisions of individual investors. This study aimed to investigate the effects of neurotransmitters, emotional intelligence, and personality traits on the behavior and decisions of individual investors simultaneously, in the Tehran stock exchange. Design/methodology/approach: In terms of purpose, the current research was practical. In terms of method, it was a descriptive survey research. In terms of time, it was a cross-sectional research. The research data were collected through a questionnaire and convenience sampling method. The sample size was 212 individual investors. Composite reliability, average variance extracted, convergent validity and divergent validity were used to measure the validity and reliability of the questionnaire. Data were analyzed using structural equation modeling. Findings: This study includes 19 constructs (variables). These constructs include dopamine, serotonin, norepinephrine, and epinephrine (neurotransmitters); Self-appraisal of emotions, other’s emotion appraisal, use of emotion and regulation of emotion (emotional intelligence); extraversion, neuroticism, openness, conscientiousness, and agreeableness (personality traits); investment horizon, risk attitude, personalization of loss, confidence, and control (investors' behavior); and investors' decisions. The current study includes six main hypotheses and 78 sub-hypotheses. The research findings showed that neurotransmitters, emotional intelligence, and personality traits affect the investors' behavior and decisions. Originality/value: The findings of this study showed that the neurofinance and behavioral finance have a key role in decision making of policymakers and investors. Finally, the findings of this study would provide new horizons in neurofinance and behavioral finance.