This paper aims to establish the motivation factors behind the accommodation choices made by millennials for stays at short-term rental properties and small hotels amidst the COVID-19 pandemic, a topic that remains under-represented in the hospitality and tourism literature. Using data from a survey of 145 millennials who stayed at an Airbnb property and a small hotel in the past year, a non-parametric test was utilized to compare six motivation factors that affect millennials' accommodation choices, guided by the push-pull motivational framework. The Wilcoxon signed-rank test results showed that the millennials significantly considered price and reviews as their common pull motivations when making accommodation choices. Interestingly, motivation factors such as location, service quality, facilities and amenities, safety, and security do not appear to significantly influence the millennials' choices for either accommodation. This paper contributes to the limited pool of empirical research on short-term rental properties and addresses the challenges faced by the small hotel industry by focusing on millennials' accommodation choices.

Data analytics is currently the buzzword for the hospitality industry to stay ahead of their competitors. Service providers use data analytics to ensure their brand remains relevant for customers. Using data analytics in customer relationship management is a relatively novel initiative for the hospitality industry to enhance the efforts of customer relationship management. Obtaining customers’ data (i.e. customers’ hotel stay and preferences) provides both opportunity and challenges for the hospitality industry. Data analytics helps the hospitality industry to quickly, effectively, and efficiently pursue data-driven decision-making. At the same time, acquiring relevant customers’ data is a challenge, for example, data privacy and confidentiality. This case study is based on Alpen Hotel (pseudonym), a luxury hotel in Singapore with a good standing in the hospitality industry. This case is focused on the issues they experienced in implementing data analytics as part of the hotel’s customer relationship management efforts. This case study aims to highlight data analytics dilemma at the hotel and may create an opportunity for hospitality educators to work interdisciplinary with faculties from an information systems or technology discipline. Finally, the case study may enhance knowledge and minimise the practice gap between industry and academia.

This research project focussed on the topic of superstitions which is widely prevalent but under-explored. Specifically, this study examined the effects of demographical variables (namely, gender, age, education, income, and religion) on 18 superstitious behaviours. An online survey was distributed using two non-probability sampling techniques: snowballing and voluntary response sampling. The data collection was done through known contacts and on a social media platform within online communities. The survey was open to participants who were at least 18 years old and fitted the other criterion of being guests at hotels, hostels, Airbnb, etc. A total of 126 usable responses was collected and analysed. Descriptive statistics and MANOVA results indicated that demographical variables did not have much effect on superstitious behaviours. Furthermore, the extent of superstitious behavioural displays was also not varied among respondents with different demographical profiles. In a challenging business landscape, it is relevant and important for the accommodation industry to have heightened awareness about guests’ superstitions. Such knowledge can aid the operators in exhibiting extra cultural sensitivity and gracious respect towards their guests, generating more satisfaction and building loyalty.