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This paper aims to explore the impact of metaverse technology on the hospitality and tourism industry. The introduction of metaverse technology has revolutionised the way the hospitality and tourism industry works. In the present study, the authors have investigated the role of social media marketing in the adoption of metaverse technology in hotel booking in India.

An extended technology acceptance model was proposed for an empirical investigation in the Indian context. Sample of 344 respondents was collected across India using a purposive sampling technique for the purpose of data analysis. The structural model analysis is used to analyse the data collected from the respondents using the SmartPLS software to check the structural and the measurement fit of the model.

The adoption intentions were largely influenced by the utility, attitude (ATT) and ease of use of the technology, and social media marketing plays a major role in influencing the perceived usefulness (PU) and ease of use (PEU). The study finds positive ATTs of the customers for using metaverse technology for booking their hotels. PU and PEU significantly influence the ATT of the consumer indicating the traveller’s perception of the usefulness and ease of metaverse technology influence their ATTs towards adoption.

Influence of metaverse technology is at a nascent stage in India specifically for hotel booking and tourism. The authors have used discriminant validity by using the criteria for both the square root of the average variance extracted and heterotrait–monotrait ratio tests, and the results suggest that the constructs in the research are distinct from other.

In online exchange platforms' sponsored search advertising, the array of product quality signals within a keyword search results list plays a crucial role in shaping buyers' purchasing decisions. This research seeks to explore the impact of various quality signals – namely, ranking position, seller reputation and product price – on ad clicks. Additionally, it examines the role of keyword attributes, such as specificity and popularity, in modulating the effects of these quality signals on advertising clicks.

A total of 5,763 effective data points were collected from a leading B2B electronic platform company, and we employed negative binomial regression with Heckman correction methods to test the hypotheses.

The results indicate that in online exchange platforms, search ad clicks are significantly and positively affected by displayed signals such as ranking position, seller reputation and product price information. Notably, a U-shaped relationship emerges between product price and ad clicks. Furthermore, keyword specificity and popularity distinctly moderate the impact of these displayed signals on ad clicks within online exchange platforms.

This paper addresses the gap in existing research on search advertising by methodically analyzing the impact of various signals displayed in search results and how keyword attributes moderate ad clicks, all through a signaling theory lens.