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Technological innovation has been changing the tourism industry precipitously and making the holiday experience more enjoyable and easier than before. The purpose of this study is to identify the current and future changes by the machine learning (ML) system as artificial intelligence in the hospitality industry.

This study has a descriptive research approach because building knowledge on technology and applying this knowledge to a tourism research are still new extensions in social studies, especially in tourism.

This research shows the value of using ML in the quality of data, features and algorithms besides stating the difficulties of data analysis in hospitality. This research also provides a comparison of automated ML techniques and the use of a robot for customer services in the hotel.

This research contributes to the tourism and technology literature by shedding light on the use of ML in tourism advancement to predict future business conditions, revenue, challenges and also to identify the current trend of tourist demand.

The hospitality industry in developed countries is under pressure due to labor shortages and it is likely more food and beverage operations will have to be automated in the future. This research investigates the public’s perceptions of the use of robots in food and beverage operations to learn about how the public perceives automation in food and beverage.

Data were collected from a survey disseminated online in 12 languages, resulting in a sample of 1,579 respondents. The data were analyzed using factor analysis and OLS regressions.

The data also reveal that generally positive attitudes toward the use of robots in tourism and hospitality is a strong indicator of positive attitudes toward the use of robots in an F&B setting. The data also illustrate that the public’s perception of appropriateness of the use of robots in F&B operations is positively related to robots’ perceived reliability, functionality and advantages compared to human employees.

The implications illustrate that the public seems to be generally accepting robots in food and beverage operations, even considering the public’s understanding and acceptance of the limitations of such technologies.

The research suggests that a critical element in terms of incorporating automation into future food and beverage operations is encouraging consumers to have generally positive attitudes toward the use of robots in hospitality and tourism industries.

This survey is based upon the data gathered in multiple countries to learn about how individuals perceive the use of robots in food and beverage operations, illustrating the attitudes that will assist or hinder the automation of this service industry.

For the supply chain to be responsive in the age of globalization, the firm needs to adopt strategies to enable them to meet the changing market needs. Thus, it is essential to adopt automatic replenishment programmes such as vendor-managed inventory (VMI). This study sought to examine the relationship between VMI and operational performance (OP) and the moderation roles of leadership and digitization in the mining sector.

A quantitative approach was used, including primary data collected from industry players in the mining sector in Ghana. A total of 97 industry players were included in the study. Data gathered was analysed using SPSS and LISREL (8.5).

The results indicate that VMI significantly affects OP. However, both digitization and leadership failed to moderate the relationship between VMI and OP.

The study offers mining companies an understanding of VMI applications in their industry. The knowledge will stimulate and improve inventory management practices in the mining industry.

This study is among the first few attempts to understand VMI in the mining industry, especially in the Sub-Saharan Africa context. It presents a detailed understanding of VMI and opportunities for future research.