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This study investigates the service quality dimensions of hotel resorts in renowned beach destinations of Thailand. It also explores the relationship between review text sentiment expressed in online platforms and the satisfaction ratings provided for those reviews.

The study employs a two-step analysis approach: first, supervised and unsupervised machine learning via support vector machine (SVM) and latent Dirichlet allocation (LDA) are used to identify service quality dimensions, and second, SmartPLS with PROCESS macro is applied to analyze the moderating roles of quality signals and reviewer’s experience on the relationship between sentiment and satisfaction rating. The dataset comprises 102,179 online reviews from TripAdvisor, focusing on 187 selected hotels rated from 3 to 5 stars.

Eight service quality dimensions were identified, including leisure activities, tangibles and surroundings, reliability, responsiveness, service process, food, empathy and ambience. The study underscores that the service process stands as the sole dimension exhibiting negative sentiment. Furthermore, the analysis revealed a robust positive association between sentiment of review texts and satisfaction, and reviewers’ experience and brand affiliation influenced the relationship between customer sentiment and satisfaction.

Hotel managers should focus efforts on maintaining tangible aspects while enhancing existing service quality level of other dimensions, particularly those related to intangible elements. Independent hotels might implement quality audit to ensure that service quality gaps are monitored.

This study contributes an examination of the moderating roles of quality signals and reviewer’s experience on the relationship between review sentiment and satisfaction rating in online reviews.

Provisions for the minimisation of human error are essential through governance structures such as recruitment, human resource allocation and education/training. As predictors of safety attitudes/behaviours, employees’ personality traits (e.g. conscientiousness, sensation-seeking, agreeableness, etc.) have been examined in relation to human error and safety education.

This review aimed to explore research activity on the safety attitudes of healthcare staff and their relationship with the different types of personalities, compared to other complex and highly regulated industries. A scoping review was conducted on five electronic databases on all industrial/work areas from 2001 to July 2023. A total of 60 studies were included in this review.

Studies were categorised as driving/traffic and industrial to draw useful comparisons between healthcare. Certain employees’ personality traits were matched to positive and negative relationships with safety attitudes/behaviours. Results are proposed to be used as a baseline when conducting further relevant research in healthcare.

Only two studies were identified in the healthcare sector.

The necessity for additional research in healthcare and for comparisons to other complex and highly regulated industries has been established. Safety will be enhanced through healthcare governance through personality-based recruitment, human resource allocation and education/training.