Hotel attributes and overall customer satisfaction: What did COVID-19 change?

Customer satisfaction with Restaurants Service Quality during COVID-19 outbreak: A two-stage methodology

Online reviews have been used effectively to understand customers' satisfaction and preferences. COVID-19 crisis has significantly impacted customers' satisfaction in several sectors such as tourism and hospitality. Although several research studies have been carried out to analyze consumers' satisfaction using survey-based methodologies, consumers' satisfaction has not been well explored in the event of the COVID-19 crisis, especially using available data in social network sites. In this research, we aim to explore consumers' satisfaction and preferences of restaurants' services during the COVID-19 crisis. Furthermore, we investigate the moderating impact of COVID-19 safety precautions on restaurants' quality dimensions and satisfaction. We applied a new approach to achieve the objectives of this research. We first developed a hybrid approach using clustering, supervised learning, and text mining techniques. Learning Vector Quantization (LVQ) was used to cluster customers' preferences. To predict travelers' preferences, decision trees were applied to each segment of LVQ. We used a text mining technique; Latent Dirichlet Allocation (LDA), for textual data analysis to discover the satisfaction criteria from online customers' reviews. After analyzing the data using machine learning techniques, a theoretical model was developed to inspect the relationships between the restaurants' quality factors and customers' satisfaction. In this stage, Partial Least Squares (PLS) technique was employed. We evaluated the proposed approach using a dataset collected from the TripAdvisor platform. The outcomes of the two-stage methodology were discussed and future research directions were suggested according to the limitations of this study.

Service Quality and Customer Satisfaction in the Post Pandemic World: A Study of Saudi Auto Care Industry

The aim of this research is to examine the impact of service quality on customer satisfaction in the post pandemic world in auto care industry. The car care vendor in the study made effective use of social media to provide responsive updates to the customers in the post pandemic world; such use of social media provides bases for service quality and customer satisfaction. The study examined the relationship between service quality and customer satisfaction using the SERVQUAL framework. According to the findings, empathy, reliability, assurance, responsiveness, and tangibles have a significant positive relationship with customer satisfaction. Our findings suggest that it is critical for workshops to recognize the service quality factors that contribute to customer satisfaction. Findings also suggest that empathy, assurance, reliability, responsiveness, and tangibles contribute to customer satisfaction. Auto repair industry must regularly provide personal attention, greet customers in a friendly manner, deliver cars after services, notify customers when additional repairs are required, and take the time to clarify problems to customers. Furthermore, workshops must screen and hire courteous staff who can clearly communicate the services required to customers both in-person and online and effectively communicate the risks associated with repairs. Service quality seems to be aided by prompt services.

COVID-19 prevention in hotels: Ritualized host-guest interactions

As COVID-19 prevention efforts have become normalized, conflicts between guests and hotel staff, who must adhere to government protocols, can have a serious impact on host-guest interactions. Drawing on interaction ritual chain theory, this research explores the ritualized mechanism of host-guest interactions during the pandemic from the perspectives of staff and guests. By combining video ethnography and interviews, this study identifies the ritual ingredients, processes, outcomes, and collective symbols of COVID-19 prevention measures. Based on the attitudes and performance paths of staff and guests, the interaction chain may become longer or shorter, and result in guests becoming "insiders" or "outsiders" and leaving the interaction space. An integrated model of host-guest interactions based on interaction ritual theory is proposed.

Net Promoter Score (NPS) and Customer Satisfaction: Relationship and Efficient Management

The NPS index is used in the hotel industry to measure customer loyalty and, by extension, customer satisfaction. Many hotel companies set their annual budget based on this index and include it, together with annual economic results, for evaluation when deciding on a potential management bonus. For managers in some companies, achieving a high NPS becomes nearly as important as achieving strong economic results. The purpose of this research is to deepen the study of the NPS index by analysing the existing relationship that the model has with customer satisfaction, focusing on the following main areas of a hotel: reception, cleanliness and room comfort, and gastronomy. To do so, this study uses fuzzy set qualitative comparative analysis (fsQCA). New evidence of value is offered based on the analysis of a sample of six hotels (4 and 5*) located in the Balearic Islands, Spain (Mallorca, Minorca, and Ibiza). In total, 557 surveys were completed in August 2021 and 571 surveys were completed in August 2020, and therefore both sample groups were impacted by a Black Swan (BS) event, the COVID-19 pandemic, in two different stages of its trajectory. The results suggest that in the study sample, the key factor in achieving a high NPS was (1) gastronomy in 2021 (after more than one year of the COVID-19 pandemic), and (2) cleanliness and room comfort in 2020 (at the beginning of the COVID-19 pandemic). These results offer insights for hotel managers, as well as for academics who can develop new lines of research on the subject.