Traveling to heritage sites represents a growing sector with great potential in the context of heritage tourism, which is a relevant topic but has received little scholarly attention. The present study tries to bridge this gap by investigating the mediating role of heritage image and attitudes toward a heritage site in the relationship between user-generated content (UGC) and travel intention toward a heritage site. In particular, we applied partial least squares structural equation modeling (PLS-SEM), which is a relatively popular new method, instead of the traditionally used covariance-based structural equation modeling (CB-SEM) method. The rise in popularity of PLS-SEM has been particularly noticeable since 2013, but in the area of heritage tourism, research is still in an early stage of development because the heritage discipline has hardly exploited the benefits of this approach. We proposed a multimediation model for heritage tourism to address this relatively new research avenue. It was discovered that exogenous variables directly and indirectly influenced travel intentions toward a heritage site through their mediators (i.e., heritage image and attitudes toward a heritage site). The findings provide an appropriate empirical and theoretical conclusion as well as valuable insights for heritage management organizations (HMOs) into the performance of heritage tourism, both for local professionals and the host communities that assist in increasing the development of heritage tourism.

Research background: Generative Artificial Intelligence (GenAI) is a disruptive technology with great promise for the FinTech industry. The current study focuses on the drivers of GenAI adoption and its consequences for both exploratory and exploitative innovation in FinTech companies. Purpose of the article: Based on a conceptual model that extends the Technology-Organization-Environment (TOE) framework, this study also explores the moderating effect of ethical dilemmas in the relationship between GenAI adoption and innovation, as well as the role of Environmental, Social, and Governance (ESG) factors in shaping the broader impact of GenAI on organizational practices. Methods: Data were collected and analyzed using Structural Equation Modeling (SEM) from participants in the Chinese FinTech industry. Findings & value added: Our empirical findings show that GenAI improves both kinds of innovations and, subsequently, leads to improved organizational performance. However, ethical dilemmas do not significantly affect either of these effects. Moreover, the study suggests that aligning GenAI adoption with ESG goals, such as promoting sustainable practices and ensuring ethical governance, can further enhance long-term performance and stakeholder trust. This study underlines the strategic role of GenAI adoption in driving innovation, advancing ESG objectives, and improving performance in the fast-evolving landscape of FinTech.

Festivals are the most viable source of tourism promotion and provide recognition to different cultures and communities. This paper proposed and examined a holistic model of festival word of mouth (WOM), which is influenced by authenticity, promotion, loyalty, quality, and satisfaction. Accordingly, the current paper investigated the effect of the proposed model with reference to Lok Virsa handicrafts, the most famous festival of the Islamabad region in Pakistan. The findings revealed that the festival quality has direct impact on WOM and promotion. Promotion has a positive influence on loyalty, satisfaction, and WOM. Festival authenticity strongly influences promotion, quality, satisfaction, and WOM. Festival satisfaction is positively related to WOM and loyalty. Whereas, festival loyalty and WOM are significantly associated. The results suggest that festival organizers should deliver the claims and promises in the festival that they have made with tourists. This technique will harvest positive WOM and increase tourist re-visitation to upcoming festivals.

Purpose: Robots have been adopted in numerous tourism and hospitality sectors, including restaurants. This study aims to investigate fast-food employees' use of service robots (SRs) in Pakistan.Design/methodology/approach: This study used a conceptual model based on innovation resistance theory (IRT). By employing structural equation modeling (SEM) in Smart-PLS 3.2.8, we evaluated data from 247 valid respondents.Findings: The findings demonstrated that drivers of robot adaptation significantly influenced image barriers, risk barriers, traditional barriers, usage barriers and value barriers. The results also revealed that usage, image and traditional barriers significantly affect usage intention.Originality/value: This study enhances the research on robotics acceptance in tourism and hospitality and subsequently aids in the planning for post-COVID-19 resumption. This study offers several practical and theoretical insights for further investigation.