Identifying factors affecting artificial intelligence-based digital transformation in e-business (Case study: Digikala)
The present study was conducted using the meta-synthesis method with the aim of identifying factors affecting digital transformation in e-businesses based on artificial intelligence. In this regard, 50 selected articles that were selected by researchers over the past two months were carefully examined and data related to the research objective were extracted. Qualitative analysis of the findings and integration of expert opinions led to the identification of 7 main dimensions including: digital infrastructure, AI enabling technologies, customer experience, data-driven management and decision-making, digital leadership, data privacy, and smart supply chain. These dimensions have been classified into 34 subcategories. Based on the research findings, to realize digital transformation based on artificial intelligence, businesses must strengthen their technological infrastructure and develop capacities such as cloud computing, cybersecurity, and advanced communications. Also, the use of technologies such as machine learning, natural language processing and predictive analytics in key processes play a decisive role in digital success. Personalizing the customer experience, designing analytical dashboards and using business intelligence facilitate data-driven decision-making at different levels of the organization. Empowering organizational leaders, formulating detailed policies in the field of data privacy and utilizing the Internet of Things and intelligent automation in the supply chain are other requirements of this transformation. The findings of this research can be used as a strategic framework for managers, decision-makers and policymakers in the field of designing and implementing digital transformation programs based on artificial intelligence.
-
Using Gamification along with Recommender Models in Learning of Data Science
Amir Haji Ali Beigi, Mohammadreza Sanaei *, Ali Bozorgi-Amiri
Journal of Industrial and Systems Engineering, Autumn 2024 -
Insulin-resistant control under uncertainty using a hybrid framework of fuzzy logic and metaheuristic algorithms
Farshad Jafarieh, Mohammadreza Sanaei *
Journal of Intelligent Strategic Management, Spring 2024