Developing Tourism Service Customization Indicators: Establishing the Application of Artificial Intelligence to Enhance Satisfaction Levels: A case study of Sanandaj

A B S T R A C T
The tourism industry is increasingly oriented toward service customization as a key strategy for enhancing tourist satisfaction. In this context, artificial intelligence (AI) plays an important role by enabling data analysis, predicting tourist needs, and supporting the delivery of personalized services. Sanandaj, with its distinctive cultural and historical attractions, has considerable potential for the development of customized tourism services. However, the capabilities of artificial intelligence have not yet been fully utilized to attract tourists and enhance their retention in this city. This study aims to develop indicators for service customization in tourism and to provide a practical framework for the application of artificial intelligence in this field, using the city of Sanandaj as a case study. The research adopts a mixed-methods approach integrating quantitative and qualitative techniques. In the quantitative phase, a questionnaire comprising 24 items measured on a Likert scale was administered to tourists during the Nowruz holiday in 2025. A total of 325 valid questionnaires were collected through convenience sampling and analyzed using SPSS software and Pearson correlation analysis. In addition, semi-structured interviews were conducted with experts in the fields of information technology and artificial intelligence to identify key challenges and opportunities related to the use of AI in tourism services. The findings indicate that the quality of online information and the accessibility of digital services have a significant and positive influence on tourist satisfaction. Furthermore, the absence of effective systems for service customization and inadequate information infrastructure were identified as the main challenges. Accordingly, the study recommends that urban managers and tourism industry stakeholders improve digital infrastructure and implement AI-based customized services to enhance tourist experience and satisfaction.
Extended Abstract
Introduction
The tourism industry, as one of the largest and most influential sectors of the global economy, is currently undergoing a fundamental transition toward digitalization. This transformation has been driven by the rapid advancement of digital technologies, with artificial intelligence and information and communication systems playing a central role in reshaping tourism service delivery and tourist–destination interactions. In the contemporary digital environment, tourists are no longer passive recipients of standardized services; instead, they actively seek accurate, up-to-date, and personalized information that enables them to plan their trips independently and efficiently. Artificial intelligence has emerged as a core enabling technology in this transformation. By analyzing large volumes of data and identifying behavioral patterns, AI allows tourism businesses and destination managers to automatically tailor their services at scale. This process, commonly referred to as service customization, aims to enhance tourist satisfaction by offering experiences that correspond closely to individual preferences, needs, and expectations. A growing body of empirical research confirms that customized services significantly increase customer satisfaction, strengthen destination loyalty, and improve the overall perceived value of the travel experience.
At the center of this digital evolution are intelligent recommender systems, which play a critical role in reducing the complexity of choice for tourists. These systems assist users in navigating a vast array of destinations, attractions, accommodations, and services by providing targeted and personalized recommendations. Through the integration of AI and machine learning techniques, recommender systems can analyze user behavior, preferences, and feedback, thereby generating more relevant and accurate suggestions. As a result, tourists are better equipped to make informed and optimal decisions, while destinations benefit from improved visitor engagement and satisfaction. Despite the recognized importance of service customization in tourism, objectively measuring the degree of customization and accurately assessing its impact on tourist satisfaction remain challenging. These challenges highlight the need for the development and application of specific quantitative and qualitative indicators capable of capturing both the technical and experiential dimensions of customized online tourism services. This need is particularly evident in destinations with high tourism potential that have not yet fully capitalized on digital opportunities.
The city of Sanandaj, the capital of Kurdistan Province in Iran, represents a clear example of such a destination. Sanandaj possesses rich cultural, historical, and natural attractions; however, despite these advantages, it has struggled to effectively attract and retain tourists. Limited utilization of digital technologies and insufficient development of online tourism services have constrained the city’s competitiveness in an increasingly digital tourism market. Given the central role of digital technologies and the proven impact of service customization on tourist satisfaction and loyalty, the present study investigates opportunities for customizing tourism services through online information platforms in Sanandaj. The research focuses on the Kurdistan Provincial Tourism Website (KurdTourism.com), specifically its sections related to Sanandaj. The main research question guiding this study is: How can the development of indicators for measuring the level of tourism service customization help evaluate its impact on tourist satisfaction in the city of Sanandaj? The ultimate objectives of this research are to analyze existing challenges and opportunities, propose strategies for optimizing online tourism services, and contribute to improving tourist experiences and increasing visitor retention in Sanandaj. By addressing these issues, the study seeks to provide a foundation for evidence-based digital transformation in emerging tourism destinations.
 
Methodology
This study examines the impact of digital technologies on tourism service customization and tourist satisfaction in Sanandaj, with the aim of proposing practical solutions for enhancing online services and improving visitor satisfaction. A mixed-methods research design, combining quantitative and qualitative approaches, was adopted to ensure a comprehensive understanding of the research problem. The study population consisted of tourists who visited Sanandaj during the period from March 2025 to mid-April 2025. A total of 325 questionnaires were distributed among visitors, of which 300 were completed fully and deemed suitable for analysis. The quantitative data were collected using a structured questionnaire containing 24 items designed to measure various dimensions of online tourism services, service customization, and tourist satisfaction. These data were analyzed using SPSS software, and Pearson correlation analysis was employed to examine the relationships between service-related variables and tourist satisfaction. This statistical approach allowed for the identification of significant associations and the relative strength of different service dimensions. In addition to the quantitative component, 20 semi-structured interviews were conducted with experts in information technology, artificial intelligence, and tourism development. These interviews aimed to capture in-depth insights into the strengths and weaknesses of the tourism website, the current state of digital infrastructure, and the feasibility of implementing intelligent and customized tourism services. By integrating quantitative findings with qualitative expert perspectives, the study identifies key factors influencing tourism service customization and tourist satisfaction, and formulates practical recommendations for improving online tourism services in Sanandaj.
 
Results and discussion
Tourist satisfaction was evaluated through the integration of quantitative analysis (Pearson correlation test) and qualitative analysis (semi-structured expert interviews), focusing on five key dimensions of online tourism services provided by the Sanandaj tourism website. The first dimension, access to online information, revealed clear priorities among tourists. Quantitative results showed that the quality and quantity of information resources had the strongest positive correlation with tourist satisfaction (r = 0.468). Other critical components, such as information diversity (r = 0.389) and information clarity (r = 0.375), also demonstrated significant positive relationships with satisfaction. These findings underscore the importance of rich, multidimensional, and well-presented content from the users’ perspective. However, qualitative insights obtained from expert interviews revealed a substantial practical gap. Experts emphasized that much of the website’s information is outdated and lacks regular updates. They also noted that the content focuses primarily on well-known attractions while neglecting lesser-known sites with significant tourism potential. Additionally, experts highlighted the presence of vague and insufficient information in several sections. These qualitative findings explain why, despite high statistical significance, considerable room for improvement remains in this dimension.
The second dimension, service customization, yielded particularly revealing results. Quantitative analysis indicated that none of the measured components, such as user data analysis, personalized recommendations, feedback mechanisms, responsiveness to specific needs, or awareness of changing user preferences, showed a statistically significant relationship with tourist satisfaction. These results clearly indicate that service customization does not currently play a meaningful role in the user experience. The qualitative findings provide essential context for interpreting these results. Experts unanimously agreed that the website lacks any active intelligent mechanisms or personalized interaction features. The absence of data analytics systems, feedback sections, and personalized response capabilities confirms that service customization components are not merely ineffective but largely nonexistent in practice.
The third dimension, user experience, demonstrated relative success in the quantitative analysis. Support for multiple devices exhibited the strongest positive correlation with tourist satisfaction across the entire study (r = 0.528). Website design, user interface, and the influence of content on tourists’ perceptions also showed strong and positive correlations. These results highlight the importance of accessibility, visual appeal, and impactful content. Nevertheless, expert assessments painted a more critical picture. The website’s design was described as outdated and visually unengaging, and the mobile version was identified as poorly optimized. Technical issues, such as slow loading speeds, and service shortcomings, including the absence of online support, user guides, and instructional videos, were also noted. Thus, while multi-platform accessibility is highly valued by users, the quality of its implementation remains suboptimal.
The fourth dimension, social and cultural impacts, revealed that tourists value cultural awareness and the preservation of local values, both of which showed significant positive correlations with satisfaction. In contrast, experts argued that the website’s influence in this area is superficial and limited. They emphasized the lack of features facilitating social interaction between tourists and the host community, as well as the complete absence of content related to sustainable tourism. This discrepancy suggests that the website has not fully realized its potential as a cultural bridge or a promoter of social responsibility.
Finally, the fifth dimension, trust in technology, showed that only trust in the website itself had a significant relationship with tourist satisfaction, while more structural components, such as privacy transparency, brand credibility, and perceptions of security risks, had no significant effect. This may indicate that users primarily rely on visible content and surface-level impressions. However, experts issued serious warnings regarding the fragility of this trust. They pointed to the lack of credible information sources, the absence of an SSL security certificate, and unclear privacy policies. These qualitative findings suggest that the foundation of trust is weak and that user satisfaction could quickly deteriorate as awareness of these infrastructural deficiencies increases.
 
Conclusion
The findings of this study clearly demonstrate that the quality of online tourism services plays a decisive role in shaping service customization and tourist satisfaction in the city of Sanandaj. Multi-platform support and the quality of information resources emerged as the most influential factors, exhibiting the strongest positive correlations with tourist satisfaction. These results align with previous research emphasizing the critical importance of reliable and accessible online content in contemporary tourism. However, qualitative evidence from expert interviews reveals two major structural challenges: the absence of intelligent and effective systems for delivering customized services, and the lack of accurate, up-to-date, and comprehensive information about tourist attractions. These shortcomings not only diminish the quality of the tourist experience but also reflect broader weaknesses in the city’s information and communication technology (ICT) infrastructure.
Comparative insights suggest that Sanandaj has underperformed in adopting digital technologies and developing related infrastructure compared to similar destinations. Insufficient investment in digital tourism has contributed to feelings of insecurity, dissatisfaction, and uncertainty among visitors regarding the destination’s efficiency and attractiveness. Consequently, transforming digital infrastructure and enhancing online service quality should be considered a prerequisite for increasing tourist retention. Moving toward sustainable tourism development in Sanandaj requires immediate focus on the implementation of intelligent service customization systems based on artificial intelligence, substantial improvement in the quality, quantity, and interactivity of tourism information, and the facilitation of inclusive access to services and attractions through digital channels. Future research may further advance this agenda by conducting comparative studies with successful destinations, analyzing the economic impacts of intelligent tourism services, and exploring the role of social media in destination marketing.
From a broader perspective, the implications of this study extend beyond Sanandaj and contribute directly to tourism development strategies. By demonstrating the critical role of service customization in enhancing tourist satisfaction, this research provides a practical framework for emerging destinations seeking to improve competitiveness in the digital tourism market. Moreover, the findings highlight how investment in intelligent online services can support sustainable tourism growth, strengthen destination branding, and increase visitor loyalty. Ultimately, the adoption of data-driven and customized tourism services can foster more inclusive, resilient, and experience-oriented tourism development.
Funding
In this research, there is no funding support.
 
Funding
In this research, there is no funding support.
 
Authors’ Contribution
The authors were equally involved in the conception and writing of the work. The authors confirmed the content of the manuscript and agreed on all aspects of the work.
 
Conflict of Interest
The authors declare that there was no conflict of interest in this study.
 
Acknowledgements
The authors are grateful to those who have contributed to the improvement of this article through their scientific recommendations.