The mediating effect of artificial intelligence marketing strategy on the relationship between value co-creation and business performance of travel agencies Cover Image

The mediating effect of artificial intelligence marketing strategy on the relationship between value co-creation and business performance of travel agencies
The mediating effect of artificial intelligence marketing strategy on the relationship between value co-creation and business performance of travel agencies

Author(s): Jelena Jevtić, Dražen Marić, Ksenija Leković
Subject(s): Tourism
Published by: Факултет за хотелијерство и туризам у Врњачкој Бањи
Keywords: travel agency; co-creators; marketing strategies; business performance; artificial intelligence

Summary/Abstract: Purpose - This study delves into the relationship between value co-creation and business performance in travel agencies. Furthermore, the study examines the mediating role of artificial intelligence (AI) marketing strategies in travel agencies. Methodology – The study used questionnaires to collect primary data from the respondents, which were subsequently analyzed using the Smart-PLS software. Data collection focused on individuals employed in travel agencies within the Republic of Serbia, aiming to empirically test the study’s hypotheses. Findings – The findings highlight the importance of value co-creation in achieving superior business performance. They also suggest that implementing artificial intelligence marketing strategies positively correlates with the business performance of travel agencies in the Republic of Serbia. Finally, the findings illustrate a significantly positive relationship between AI-based marketing strategies, value co-creation, and business performance of travel agencies in the Republic of Serbia. Implications – Artificial intelligence has become a key topic for tourism organizations. A marketing strategy based on artificial intelligence, combined with feedback from service users, is likely to enhance the performance of service organizations.

  • Issue Year: 13/2025
  • Issue No: 1
  • Page Range: 59-79
  • Page Count: 21
  • Language: English
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