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Principles Of Behavioral Economics And The Effect Of Artificial Intelligence

Author

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  • NICULESCU GEORGE

    (CONSTANTIN BRANCUSI UNIVERSITY OF TARGU JIU)

Abstract

This article analyzes and concretizes several important principles of behavioral economics, such as "welldefined preferences", "goal proximity", "loss aversion" and the "endowment effect". The article provides examples of the application of these behavioral economic principles, emphasizing the complexity and diversity of factors that can influence preferences in the fields of management and marketing. Behavioral economics recognizes that human decisions are not always rational, and these subtle influences can significantly impact how individuals choose products, services, or adopt certain management aspects. The implementation of artificial intelligence in the field of behavioral economics can bring significant benefits in personalizing experiences, increasing operational efficiency, and creating a stronger connection with customers and employees. Understanding these influences allows companies and creators to approach the target audience more effectively and better understand consumer or community motivations. The importance of ethical and privacy considerations in the implementation of these technologies is highlighted to ensure that preference influencing is done transparently and respects individual rights. Behavioral economics and artificial intelligence (AI) represent two closely interconnected fields capable of collaborating to better understand and influence human behavior in the economic and social context. Through their collaboration, behavioral economics and AI aim to make significant improvements in understanding and shaping human behavior in various aspects of economic and social life.

Suggested Citation

  • Niculescu George, 2023. "Principles Of Behavioral Economics And The Effect Of Artificial Intelligence," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 6, pages 139-149, December.
  • Handle: RePEc:cbu:jrnlec:y:2023:v:6:p:139-149
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    References listed on IDEAS

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