Online Guest Research Articles

Determining Training Need Analysis of a 4-Star Hotel in Mumbai through Online Guest Feedback Review: A Case Study

Determining Training Need Analysis of a 4-Star Hotel in Mumbai through Online Guest Feedback Review: A Case Study

Evaluation of the use of Robotics in Hotels in terms of Customer Satisfaction

Purpose:This study aims to evaluate the online guest comments made for all of the hotel businesses in the world that use robotic technology in the tourism industry and serve on the TripAdvisor website by content analysis methodDesign/methodology/approach –Content analysis model, one of the qualitative research methods, was used in this study. Accordingly, the comments made by customers on Tripadvisor were analyzed and examined under the main theme and sub-themes. Thus, it was determined on which subjects there were more complaintsResults –According to the research findings, it was understood that most of the complaints were about price/performance. Additionally, it was seen that the limited responses of the robotic technologies and autonomous systems used to solve the guest's problems were another critical reason for complaintsDiscussion–The increase in the use of robotic services, which is developing in the tourism sector, as in other sectors, and how this situation affects the consumers of the tourism sector, which shows the service feature based on human relations, have been investigated. In this way, it is revealed how the field of robotics accelerated by the development of technology and the reflections of this field on the tourism industry are welcomed by the visitors, and inferences is made about the future of robotic applications in the tourism sector. In the study, consumer expectations about the future of the tourism sector and the effects of technological developments on the sector in terms of competitive conditions were evaluated. This study will be the first post-pandemic study and aims to guide future research and the industry thanks to its comparison with pre-pandemic findings.

Peer-to-Peer Accommodation User Experience: Evidence From Sri Lanka

With the emergence of the sharing economy, Airbnb has become the poster child for the digital peer-to-peer accommodation market in the hospitality industry. The study explores the attributes influencing Airbnb user experiences in Sri Lanka by analyzing online guest reviews. The study uses an exploratory research design to examine a large data set of Airbnb user reviews utilizing text mining and sentiment analysis. According to the analysis, five key themes emerged from the review comments: “recommend,”“host,”“experience,”“room,” and “location.” Furthermore, the relationship between the host and the guest greatly impacts the Airbnb user experience in Sri Lanka. Most Airbnb user reviews are positive and primarily focus on the host, while negative ones typically focus on the property’s indoor environmental quality. The study contributes to the literature on the sharing economy by offering a structured and extensive analysis of actual online reviews from Airbnb customers to understand their experiences better while providing valuable insights for various stakeholders in the industry.

CUSTOMER SATISFACTION AND SENTIMENT REVIEWS ON SELECTED BOOKING SITES OF MANILA MANOR HOTEL 2019-2021

One approach to significantly enhance hotel products, services, and marketing strategies is through online guest evaluations. However, few research has examined online reviews utilizing a SERVQUAL model for sentiment analysis, therefore addressing this gap, notably in the Philippine hotel industry. The SERVQUAL model, which was modified in accordance with the purpose of the study, served as the foundation for the framework. Customers who had stayed at and evaluated the establishment on Agoda, Kayak, and Booking Web Portal served as subjects, and Qualitative Sentiment Analysis Research design was used. The results were divided into positive and negative sentiments and categorized using the five RATER (Reliability, Assurance, Tangibles, Empathy, and Responsiveness) dimensions of service quality. The validity and reliability of the instruments used can be attributed to the literature utilizing and validating them as a measurement scale of customer satisfaction. Finally, the study revealed that the overall satisfaction of guests at the hotel establishment was heavily influenced by physical hotel features rather than intangible factors. The researchers were then able to provide specific suggestions for improving the hotel service and product quality, as well as prospective program improvements which can also be used by other accommodation.

Ecological hotels' customer satisfaction through text mining of online reviews: a case of Ecuador hotels

PurposeThis research aims to analyze the customer satisfaction associated with experiences from 14 ecological hotels in Ecuador by exploring online guest reviews and classifying the most influential factors.Design/methodology/approachThis study applied big data exploration, semantic network analysis, EFA and linear regression. It processed 22,629 online reviews from Google/travel, extracting 100 words with the highest frequency. In addition, CONCOR analysis built a comprehensive structural model gathering essential keywords. Furthermore, exploratory factor analysis and regression were conducted to explore the elements that best express customer satisfaction in ecological hotels.FindingsThe words such as green, sustainable, recycle, environment and ecological were not found among the main attributes extracted. Nonetheless, the keywords obtained reflect customer satisfaction, revealing that green practices do not affect comfort and the guests' experience. CONCOR analysis displayed four categories associated with satisfaction: tangibles, experience, location and empathy. Then, EFA restructured and revealed the factors: facilities feature, assurance, reliability, location and experience. Lastly, the regression disclosed location, assurance and facilities features as the most significant factors for customer satisfaction in the 14 ecological hotels. The terms related to the hotel area, staff care and hotel amenities were decisive for guests.Practical implicationsThis study demonstrated that employee courtesy and location are the keys to enhancing customer experience and satisfaction. Hotel managers must promote green attributes and practices to increase customer awareness through constant staff training and information disclosure in common areas.Originality/valueThese findings provide insight and empirical evidence for hoteliers to understand how and what guest perceive to be green practices. By identifying the main features or concepts associated with satisfaction in Ecuador's green hotels, hoteliers could address new strategies to respond to expectations, effectively satisfy customers and provide a superior experience.

The Effects on Neighborhood Environments during Lockdowns: Being Comfortable in Residences

Cities around the world have been hit by the COVID-19 crisis. The worst consequences of the pandemic are closely related to urban areas. Many studies investigated the impact of COVID-19 on people but there are few studies that have investigated the satisfaction level of university students during the COVID-19 lockdown at the neighborhood level. Therefore, the aim of this study is to investigate the satisfaction of university students at the neighborhood level during the COVID-19 lockdown and investigate the experience of online education during that period—if they received any. An online survey was conducted involving university students of different countries, and a total of 427 responses (n = 427) were received and analyzed using the CHAID model. Results show that comfort at residences during the COVID-19 lockdown was affected by the neighborhood environment (viz., greenery, pleasant views, independent housing with gardening facilities), transportation (i.e., saving 1–2 commuting hours on a daily basis and safety from traffic hazards), and the provision of online education (i.e., effectiveness, such as traditional methods of education and the opportunity to connect with field experts). Thus, it can be concluded that providing green neighborhoods, detached or terraced houses (townhouses) with visual connection, and gardening facilities for the residents should be encouraged in the future because these types of neighborhoods are not only comfortable in ordinary situations but also provide comfort during critical periods such as COVID-19 lockdowns. It can also be concluded that a hybrid style of education should be encouraged for universities, as it can save travel time, provide safety from traffic, and provide more opportunities to become connected with international experts through online guest lectures, seminars, and workshops.

Rancang Bangun Wedding Organizer Menggunakan Metode Pendekatan User Centered Design

Marriage is a sacred thing and when the newlyweds wait for it, a new family will be formed. To carry out these activities, a wedding reception is needed as a form of happiness. In this case, sometimes the bride and groom experience problems in managing their wedding reception, due to lack of information and limited time. Seeing from this phenomenon, one of the wedding organizers or who is familiar with wedding organizers (WO) took the initiative to expand their business to be wider. One of the wedding organizers is the Baba Family. Where the current system used by the Baba wedding organizer family is still using a manual system, the process must come directly to the place. Of course, this is one of the obstacles for the Baba Wedding Organizer family to share information and existing processes, because it cannot be done by businesses all the time. From this, the Baba Family, in overcoming their business problems, built an information system for ordering wedding organizers. The purpose of the research is to build a wedding organizer system in searching for information on wedding services consisting of wedding package prices, aisle and dress simulations, buildings, catering, and online guest books. By building the information system, it is necessary to do an approach method so that it is better and measurable. One approach method is using the User Centered Design (UCD) approach, a method in a design design that focuses on user needs. In relation to Information Systems, User Centered Design is part of the SDLC (System Development Life Cycle), so that application designs developed through UCD will be optimized and focused on end-user needs. The information system built by the researcher is able to provide future business value for the Baba Family on their wedding organizer. So that the system used can provide the right information and according to the needs of its users, as well as the transaction process for ordering wedding organizers to be easier and more helpful.

A Smart Tourism Case Study: Classification of Accommodation Using Machine Learning Models Based on Accommodation Characteristics and Online Guest Reviews

This paper deals with the analysis of data retrieved from a web page for booking accommodation. The main idea of the research is to analyze the relationship between accommodation factors and customer reviews in order to determine the factors that have the greatest influence on customer reviews. Machine learning methods are applied to the collected data and models that can predict the review category for those accommodations that are not evaluated by users are trained. The relationship between certain accommodation factors and classification accuracy of the models is examined in order to get detailed insight into the data used for model training, as well as to make the models more interpretable. The classification accuracy of each model is tested and the precision and recall of the models are examined and compared.

Paradigm shift in teaching-learning from classroom to virtual mode – Challenges and opportunities

Since the unprecedented declaration of lockdown there has been a paradigm shift in medical education from chalk and board to virtual mode imposing both challenges and opportunities to faculty and students alike. As guest lecture is an innovative way of pedagogy we addressed them through an online talk to analyse the preferences towards sudden change in medical education. Students and faculty were addressed about the paradigm shift in teaching learning methods through an online guest lecture and the attendees answered a feedback questionnaire on different Teaching Learning methods. Based on responses to the questions results were plotted in Microsoft Excel and completed questionnaires were analyzed for statistics. : 90% of students and 100% of faculty found online guest lecture interesting and opined positively about having more online lectures in academic year. As far as teaching learning method is concerned both faculty and as students preferred offline/ traditional/ classroom teaching. : Online guest lecture offers more opportunities than challenges for both faculty and students. Arranging online guest lectures is economical, cost effective, has ease of attending from place of convenience provided robust internet connection is ensured, eliminates travel time as well as reduces the programme budget. Hence more number of virtual guest lectures can be arranged in an academic year for benefit of medical undergraduates. It is a novel platform for student teacher interaction and arrangement of more and more online guest lectures from eminent speakers excelling in various superspecialities should be encouraged.

The Role of Online Guest Review Sites in the Hospitality Industry: Evidences from Managers’ Perspectives

The Role of Online Guest Review Sites in the Hospitality Industry: Evidences from Managers’ Perspectives

Examining the direct and interaction effects of picture color cues and textual cues related to color on accommodation-sharing platform rental purchase

Given the increasing popularity of peer-to-peer (P2P) accommodation-sharing platforms (i.e., Airbnb), this paper aims to explore the effects of both picture color cues and textual cues related to color (TCC) on rental decisions made on these platforms in China. Based on cue utilization theory, this paper distinguishes picture color cues signaled from photos listed by hosts and TCC signaled from online guest reviews. The paper conducts an empirical study using data crawled from Xiaozhu.com. The research model is tested with poisson regression using 2520 valid listings collected in Guangzhou and is verified with additional data collected in Shanghai. Results show that both picture color cues and TCC affect rental transactions. Properties displayed with warm-colored pictures are more likely to be rented than those with cold-colored pictures. In addition, the consistency of picture color cues and TCC is found to have a significant impact on rental decisions. Interestingly, we also found an invert-U effect of brightness on rental purchase. • Based on cue utilization theory, this paper defined picture color cues and textual cues related to color (TCC). • Results show that both picture color cues and TCC affect rental transactions. • Properties displayed with warm-colored pictures are more likely to be rented than those with cold-colored pictures. • The consistency of picture color cues and TCC is found to have a significant impact on rental decisions. • We also found an invert-U effect of brightness on rental purchase.

Education Reform as a Platform to Improve Interactions of the Engineering Students During Online Teaching and Learning at Higher Education Amidst Covid-19 Pandemic

The objective of this study was to outline the education reform approaches which could implement during online teaching and learning activities. The approaches consisted with online teaching, online mentoring /student induction programmes, online examinations and online guest lectures/webinars. The approaches practiced, were discussed in activity 1 to 7 in the methodology section. In addition, the outcome assessed using 4Rs model for reflection and PDCA cycle at the results and discussion section. In conclusion, this study showed that the approaches implemented assist to improve the interaction of the students.

The Influence of Sustainable Initiatives on Hotel Guest Experience

This study investigates the relationship between sustainable initiatives in hotels and their guest experiences by using big data from online guest reviews. Hotel review data of 1 018 938 hotel guest reviews from 23 international destinations were used. Word recognition software was utilised to filter reviews containing comments about sustainable initiatives resulting in a usable database of 903 reviews. Sentiment analysis was then performed to enable the transformation of the variables into 5-point Likert type scales. Using chi-squared tests and Cramer’s V for statistical and practical significance respectively, sustainable initiatives were found to have a statistical significant relationship with each of the eight hotel experience dimensions as well as overall hotel experience. The eight hotel experience dimensions are value, service, location, rooms, food, ambience, facilities and cleanliness. The hypothesis was accepted as there was a statistically significant relationship between sustainable initiatives and the hotel experience dimensions. The results from the comments, provide hotel management and academics with new insight into the relationship between sustainable initiatives in hotels and the hotel guest experience. Sustainable initiatives should be considered as another important dimension of the hotel experience, and big data analysis is effective to analyse guest reviews.

The Effects of Language Errors in Service Recovery Communication on Customers’ Hotel Perceptions and Booking Intentions

ABSTRACT Research in the field of marketing and crisis communication has shown that language errors negatively affect consumers’ image of a company and their buying intentions. We extended this line of research to the hospitality industry. Using a between-subjects design, we tested whether language errors in a hotel response to a negative online guest review affect customers’ perceptions of the hotel and their booking intentions in two service recovery contexts: a customer complaint regarding a service failure and a customer complaint which the hotel could not be held responsible for. The results show that language errors negatively influence customers’ perceptions of the hotel’s expertise, its reputation, and its trustworthiness and affect their booking intentions, irrespective of the type of complaint. Therefore, hotels should pay significant attention to avoid language errors in their online service recovery communication.

A fine-grained sentiment analysis of online guest reviews of economy hotels in China

ABSTRACT This study aims to investigate the experiences of Chinese economy hotel guests by applying deep learning fine-grained sentiment analysis on 363,723 Chinese-text online reviews. Findings reveal that location is the domain that most of the positive sentiments are associated, followed by facilities, service, price, image, and reservation experience. Prominent features with negative sentiments include sound insulation, air conditioning, beddings, windows, toilets, TV sets, WiFi signals, towels, elevators, hair dryers, slippers, toilet bowls, return cash, invoices. Positive and negative sentiments are compared. This research offers an alternative approach and a more comprehensive understanding of the experiences and sentiments of Chinese economy hotel guests. Theoretical contributions and practical implications regarding economy hotel management are discussed.

A 2020 perspective on “Online guest profiling and hotel recommendation”: Reliability, Scalability, Traceability and Transparency

Tourism crowdsourcing platforms accumulate and use large volumes of feedback data on tourism-related services to provide personalized recommendations with high impact on future tourist behavior. Typically, these recommendation engines build individual tourist profiles and suggest hotels, restaurants, attractions or routes based on the shared ratings, reviews, photos, videos or likes. Due to the dynamic nature of this scenario, where the crowd produces a continuous stream of events, we have been exploring stream-based recommendation methods, using stochastic gradient descent (SGD), to incrementally update the prediction models and post-filters to reduce the search space and improve the recommendation accuracy. In this context, we offer an update and comment on our previous article (Veloso et al., 2019a) by providing a recent literature review and identifying the challenges laying ahead concerning the online recommendation of tourism resources supported by crowdsourced data.

Comparison of online customer ratings between the eco-labelled and non-eco-labelled hotels of Oslo

Online guest reviews are now playing an increasingly important role in consumer purchase decisions. Online booking websites are considered excellent sources of information, thanks to their millions of reviews. This paper contributes to research into eco-labels in the hospitality industry by discussing the online ratings of hotels with reference to different attributes, such as average daily rate, number of rooms, number of detailed reviews, and overall customer rating, as well as specific ratings for staff, value for money, location, facilities, comfort, cleanliness and free Wi-Fi. The results of this study indicate that there was a statistically significant difference between eco-labelled and non-eco-labelled hotels in terms of average daily rates and number of rooms. Eco-labelled hotels were found to have significantly better scores than non-eco-labelled hotels. However, there was no statistically significant difference between eco-labelled and non-eco-labelled hotels in terms of the number of detailed reviews and the customer ratings regarding the different attributes that measure customer satisfaction.

The impact of online reputation on hotel profitability

PurposeThe purpose of this study is to quantify the impact of online customer reputation on financial profitability.Design/methodology/approachOnline reputation is captured by extracting the most recurring textual themes associated with customer satisfaction and dissatisfaction, expressed within positive vs negative online guest reviews on Booking.com. Latent semantic analysis is used for textual analysis. Proxies of overall financial performance are manually constructed for the sample hotels, using financial data from the Financial Analysis Made Easy (FAME) database. Ordinary least squares is used to gauge the effect of online customer reputation on financial profitability.FindingsEmpirical findings indicate that recurring textual themes from positive online reviews (in contrast to negative reviews) exhibit a higher degree of homogeneity and consensus. The themes repeated in positive, but not in negative reviews, are found to significantly associate with hotel financial performance. Results contribute to the discussion about the measurable effect of online reputation on financial performance.Originality/valueContemporary quantitative methods are used to extract online reputation for a sample of UK hotels and associate this reputation with bottom-line financial profitability. The relationship between online reputation, as manifested within hotel guest reviews, and the financial performance of hotels is examined. Financial profitability is the result of revenues, reduced by the costs incurred in order to be able to offer a given level of service. Previous studies have mainly focused on basic measures of performance, i.e. revenue generation, rather than bottom-line profitability. By combining online guest reviews from travel websites (Booking.com) with financial measures of enterprise performance (FAME), this study makes a meaningful contribution to the strategic management of hotel businesses.

On-line guest profiling and hotel recommendation

Abstract Information and Communication Technologies (ICT) have revolutionised the tourism domain, providing a wide set of new services for tourists and tourism businesses. Both tourists and tourism businesses use dedicated tourism platforms to search and share information generating, constantly, new tourism crowdsourced data. This crowdsourced information has a huge influence in tourist decisions. In this context, the paper proposes a stream recommendation engine supported by crowdsourced information, adopting Stochastic Gradient Descent (SGD) matrix factorisation algorithm for rating prediction. Additionally, we explore different: (i) profiling approaches (hotel-based and theme-based) using hotel multi-criteria ratings, location, value for money (VfM) and sentiment value (StV); and (ii) post-recommendation filters based on hotel location, VfM and StV. The main contribution focusses on the application of post-recommendation filters to the prediction of hotel guest ratings with both hotel and theme multi-criteria rating profiles, using crowdsourced data streams. The results show considerable accuracy and classification improvement with both hotel-based and theme-based multi-criteria profiling together with location and StV post-recommendation filtering. While the most promising results occur with the hotel-based version, the best theme-based version shows a remarkable memory conciseness when compared with its hotel-based counterpart. This makes this theme-based approach particularly appropriate for data streams.

Business Analytics in Tourism: Uncovering Knowledge from Crowds

Abstract Business Analytics leverages value from data, thus being an important tool for the decision-making process. However, the presence of data in different formats is a new challenge for analysis. Textual data has been drawing organizational attention as thousands of people express themselves daily in text, like the description of customer perceptions in the tourism and hospitality area. Despite the relevance of customer data in textual format to support decision making of hotel managers, its use is still modest, given the difficulty of analyzing and interpreting the large amounts of data. Our objective is to identify the main evaluation topics presented in online guest reviews and reveal changes throughout the years. We worked with 23,229 hotel reviews collected from TripAdvisor website through WebScrapping packages in R, and used a text mining approach (Latent Semantic Analysis) to analyze the data. This contributes with practical implications to hotel managers by demonstrating the applicability of text data and tools based on open-source solutions and by providing insights about the data and assisting in the decision-making process. This article also contributes in presenting a stepwise text analysis, including capturing, cleaning and formatting publicly available data for organizational specialists.