Validation of the Effective Indicators of Artificial Intelligence with Emphasis on ConValidation Consumer Behavioral Patterns in Tourism Institutionssumer Institutions

Shareef Naser, Wahhab; Rahimi Kolour, Hossein; Seifollahi Anar, Naser; Bashokouh Ajirlou, Mohammad

doi:10.22034/ijumes.2024.737189

Validation of the Effective Indicators of Artificial Intelligence with Emphasis on ConValidation Consumer Behavioral Patterns in Tourism Institutionssumer Institutions

Document Type : Case Study

Authors

Wahhab Shareef Naser ¹

Hossein Rahimi Kolour ²

Naser Seifollahi Anar ³

Mohammad Bashokouh Ajirlou ³

¹ Ph.D. Student, Department of Business Management, Faculty of Social Sciences, University of Mohaghegh Ardabili, Ardabili, Iran

² Associate Professor, Department of Business Management, Faculty of Social Sciences, University of Mohaghegh Ardabili, Ardabili, Iran

³ Professor, Department of Business Management, Faculty of Social Sciences, University of Mohaghegh Ardabili, Ardabili, Iran

10.22034/ijumes.2024.737189

Abstract

The present study was conducted with the aim of validating the effective indicators of artificial intelligence with emphasis on consumer behavioral patterns in tourism institutions. Methodologically, the study adopted a mixed approach and was pursued quantitatively in its final stage. In the qualitative phase, the statistical population comprised 18 professors, specialists, and experts in the fields of information technology, management, and tourism marketing, who were selected purposively and contributed to the design of the initial model. In the quantitative phase, based on the variables extracted from the qualitative phase, a semi-open questionnaire was designed and distributed among 100 respondents. The data were analyzed using SPSS and LISREL software through descriptive statistics, confirmatory factor analysis, and structural equation modelling. The descriptive results showed that the majority of respondents were men, held bachelor’s and master’s degrees, and were mainly in the 31–35 age range. The inferential findings indicated an appropriate fit of the study’s measurement and structural models: the goodness-of-fit indices (GFI and AGFI) were at a desirable level, and the factor loadings of all indicators were significant. The convergent validity and composite reliability of the constructs were also confirmed. The results showed that components such as digital-sales development, prediction of customer purchase behavior, analysis of customer data, the use of data mining, the development of customer-relationship-management systems, and the improvement of service quality play a significant role in the effectiveness of AI in tourism institutions. Overall, the findings indicate that AI can be used as a strategic instrument for improving marketing decisions, personalizing services, and enhancing customer engagement in the tourism industry.

Keywords

AI effectiveness

Artificial intelligence

consumer behavior

consumer behavioral patterns

tourism institutions

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