This study explores the impact of artificial intelligence (AI) on customer perceptions and behavior in restaurants, airline companies, and hotel sectors within the hospitality industry of Iran. The primary objective is to analyze how AI affects customer trust, brand engagement, electronic word-of-mouth (eWOM), and tourists’ readiness to use AI technologies. Using a comparative analysis approach and surveys, this research tests hypotheses about the effects of artificial intelligence on various dimensions of customer interaction. The findings highlight significant relationships between the quality of artificial intelligence and customer engagement metrics, such as trust and brand loyalty, which are crucial for understanding and predicting customer behavior in response to technological advancements. This study lays the groundwork for theoretical assumptions about sustainability in these sectors in developing countries, providing a basis for future empirical research that could validate these assumptions and explore broader implications of AI integration in enhancing sustainable practices within the hospitality industry.

This study investigates the perceptions of employees in the hotel industry of the Republic of Serbia regarding the acceptance and importance of artificial intelligence (AI). Through a modified UTAUT model and the application of structural equation analysis (SEM), we investigated the key factors shaping AI acceptance. Research results show that behavioral intention and habit show a significant positive impact on AI usage behavior, while facilitating conditions have a limited but measurable impact on behavioral intention. Other factors, including social influence, hedonic motivation, performance expectancy, and effort expectancy, have minimal influence on the examined variables. The analysis reveals the crucial mediating role of behavioral intention, effectively bridging the gap between various predictors and AI usage behavior, thereby highlighting its significance in the broader context of technology adoption in the hotel industry. The primary goal of the study, which closes significant research gaps, as well as the manner in which it uses a specific model and statistical analysis to accomplish this goal, shows how innovative the work is. This method not only broadens the field’s understanding but also offers valuable insights for shaping sustainable development practices in the hospitality sector in the Republic of Serbia.

The primary goal of this paper was to investigate the strength of the influence of different types of risk on the travelers’ intention to visit destinations in future, that are, prejudiced due to COVID-19, marked as “stigmatized”, “isolated”, or “risky destinations”. Field interview research was conducted at the “Belgrade Nikola Tesla Airport” (Serbia). The results obtained by multiple regression analysis showed that all types of risks influenced the intention of travelers, with financial risk showing a more significant impact. Canonical discriminant analysis indicated that men were most afraid of human induced risk, service quality risk, natural disaster and COVID-19 risk, and they chose safer destinations. Among the women, the biggest fear was financial risk, socio-psychological risk, and food safety risk. Older respondents and those under the influence of external factors decided on safer destinations, while financial status did not play a significant role in predicting the choice of destination. The selection of the destination according to the degree of security was determined by the ordinal regression methodology. The entire research presents a certain novelty, because so far in the numerous studies on the topic of the negative consequences of COVID-19 on tourism, there has been no discussion of stigmatized or risky destinations that received that epithet, and were therefore negatively and unfairly marked in the minds of tourists for future visits.

This study investigates the perception of the implementation of the Farm to Table (F2T) concept on the sustainability of agritourism households in the Republic of Serbia. The main objective of the study is to determine how this concept affects the environmental, economic, and social sustainability of these households according to the participants. Data were collected through surveys of agritourism homestead owners in the regions of Vojvodina, Western Serbia, Southern Serbia, and Eastern Serbia. The research findings, obtained using quantitative (SEM) analyses, indicate that the F2T concept significantly contributes to the sustainable development of agritourism homesteads by increasing economic profitability, reducing environmental impact, and strengthening the social community. Moderators such as seasonal product availability, employee education, and the local community support have a significant impact on the effectiveness of F2T activities. The innovation of this study lies in the application of quantitative methods to analyze the specific impacts of the F2T concept on the sustainability of agritourism households, an area that has been poorly explored in the literature. The study has a number of implications, including providing empirical data that can help farmers, tourism operators, and policymakers to promote sustainable agritourism businesses.

Contemporary digital technologies have become key instruments in enhancing the security and sustainability of tourist destinations. This study explores the role of digital solutions such as smart surveillance systems, mobile applications, artificial intelligence, and the Internet of Things (IoT) in strengthening tourist safety and supporting long-term sustainable development. The theoretical framework is based on the Norm Activation Model (NAM), employing the constructs of Awareness of Consequences, Ascription of Responsibility, Personal Norms, and Behavioral Intention, expanded by the construct of Sustainability Outcomes. This research was conducted as a comparative case study of Almaty (Kazakhstan) and Belgrade (Serbia), using a structured questionnaire and quantitative analysis. The findings indicate that tourists’ perceptions of security, mediated by digital technologies, significantly shape their behavioural intentions and contribute to sustainable destination outcomes. The study provides theoretical implications for the advancement of the NAM in tourism, as well as practical guidelines for destination managers in developing a safe and sustainable environment.

Gastronomic tourism heritage represents a significant segment of intangible cultural heritage, reflecting traditional knowledge, local identity, and long-standing culinary practices. The contemporary development of digital technologies, particularly artificial intelligence (AI), opens new possibilities for its preservation, documentation, and sustainable interpretation within cultural tourism. The aim of this research is to examine the role of artificial intelligence as a tool for preserving gastronomic tourism heritage from the perspective of local community members in Bosnia and Herzegovina, Serbia, and North Macedonia, regions characterised by shared gastronomic and cultural traditions. The study was conducted using a quantitative research design based on a structured questionnaire administered to 571 respondents. A convenience sampling approach was applied, targeting individuals involved in the preparation, transmission, or promotion of traditional gastronomy. Data were collected through a combination of field-based and online survey distribution. The analysis focuses on respondents’ perceptions of AI applications in documenting traditional recipes, interpreting gastronomic heritage, and promoting it within tourism, as well as on attitudes related to authenticity and cultural identity preservation. The findings indicate that, within the surveyed sample, artificial intelligence is generally perceived as a useful tool for safeguarding gastronomic heritage. At the same time, respondents emphasise the importance of transparent governance, community participation, and culturally sensitive implementation in order to minimise risks of commodification and loss of authenticity.