Keywords

Sentiment Analysis; Netnography; Thematic Analysis; Guests Service Experiences/ Expectations.

Introduction

Providing superior customer service is widely acclaimed as an essential parameter for the chief segment of hospitality businesses (Gaur, Afaq, Singh, et al., 2021). High customer satisfaction can result in customer retention and loyalty, bringing an absolute competitive advantage (Ieva and Ziliani, 2018; Sahu et al., 2023). How a hotel is perceived is of utmost importance, and every hotel works hard to create one unparalleled virtue that becomes the basis of why guests choose a particular hotel (Jones and Comfort, 2020; Quan et al., 2022). This exceptional virtue is pivotal in creating guests' experiences and expectations from the tourism and hospitality management perspective (Afaq et al., 2023a).

The outbreak of the latest pandemic, i.e., COVID-19, has created tremendous uncertainty and disruptions in the hospitality industry (Beck and Hensher, 2020). The sudden travel collapse adversely affected the hospitality business (Neuburger and Egger, 2021). According to (Bureau, 2020), there was also a massive job loss in the hospitality and tourism industry due to COVID-19, and the fear of getting infected was stopping guests from visiting hotels. This sector was, therefore, fighting to survive, let alone thrive (Guevara, 2020). Now, health and safety are the prime concerns of the customers. Even in the pre-COVID-19 era, hotels continuously reinvented themselves to meet guests' expectations, which was only possible by constantly understanding them (Gaur, Afaq, Solanki, et al., 2021).

As the ramifications of the pandemic gradually recede, there has been a significant shift in the challenges faced by service providers in the hospitality industry. Notably, guests' expectations are no longer confined to the standards of the pre-COVID-19 era. Instead, they now encompass a new set of criteria that reflect the altered perceptions and habits resulting from the pandemic (Afaq et al., 2021). These evolving expectations are prominently centered around 'safety and sanitisation.' However, the landscape has extended beyond mere hygiene concerns; there is now a psychological apprehension related to travel and potential exposure to infections (Afaq et al., 2022). In this altered scenario, guests require more than the reassurance of traditional hospitality; they seek assurance that their health and well-being will be safeguarded amidst the extraordinary circumstances generated by the pandemic(Flavián and Casaló, 2021). It's worth noting that as individuals become accustomed to the presence of sanitisers and other preventive measures in their daily lives, these practices have begun to integrate into their psyche. Furthermore it can be said that the incorporation of technologies like artificial intelligence can also tailor customer experiences and foster the digital landscape (Gaur and Sahoo, 2022; Sahu et al., 2023).

Consequently, their expectations from hotels and hospitality experiences have broadened. They now seek a comprehensive approach to wellness and health, where their stay offers comfort and contributes positively to their physical and mental well-being (Hu et al., 2021). This expectation shift is also reflected in the preference for contactless services, where technological advancements are harnessed to minimise direct physical interaction (Gaur and Garg, 2023).

In response to these changing dynamics, it has been suggested by experts in tourism and hospitality management that the analysis of user-generated content (UGC) available on the Internet is essential (Monmousseau et al., 2020). This approach aids in understanding the nuanced desires of hotel guests, enabling the industry to cater to their refined expectations and deliver an experience that aligns with the current context (Yu et al., 2021).

We have identified the four main gaps centered on the review of the prior extended literature. These gaps are (1) a lack of Twitter-based studies (including other social media platforms) identifying the alterations in expectations/experiences of hotel guests due to the outbreak of the COVID-19 pandemic. (2) limited studies that have applied thematic analysis to identify the emerging themes based on online reviews in the hospitality industry after the outbreak of the COVID-19 pandemic. (3) Dearth of studies that combine quantitative and qualitative techniques (sentiment analysis and thematic analysis) to provide better insights into hotel guests' changing experiences/expectations after the spurt of the COVID-19 pandemic. (4) Most of the studies conducted after the outburst of the COVID-19 pandemic in tourism and hospitality management are based on surveys of a small sample size. The current study aims to bridge these gaps with the application of sentiment and thematic analysis on the data set extracted from Twitter using web scraping to analyse guests' experiences/expectations towards the services and hospitality provided by the hotels. Therefore, this study examines two research questions

(RQ1) What sentiments do hotel guests harbour regarding the effectiveness of hospitality services provided by the hotel?

(RQ2) How have hotel guests' experiences and expectations undergone transformation in the wake of the COVID-19 pandemic outbreak?

The authors conducted two analyses to address the research questions. Initially, SA assesses the sentiment-based viewpoint of guests' encounters and anticipations concerning international chain hotels. Next, TA was undertaken to comprehend guests' experiences/expectations qualitatively. Different themes were identified wherein the guests shared their perceptions after COVID-19.

This study uses tweets from the social media platform Twitter to measure guests' sentiments towards fifteen global chain hotels in South Asia and critically analyse their service experiences with them.

Twitter is a preferred channel for our study because its massive data set assisted in getting customers' insights and helped answer the research questions. As Twitter is widely used, it helps reflect guests' sentiments expressed in the tweets. The hospitality service providers extensively use Twitter to enhance engagement and build strong brand loyalty (Ibrahim et al., 2017), and customers prefer Twitter because of the speedy response from the hospitality companies.

The study's novelty comes from the following: (1) It is a pioneer study that combines SA and TA to depict guests' sentiments and expectations after the flare-up of COVID-19. (2) This study develops a theoretical model by embracing (Hau and Kim, 2011) version of the Social Capital Theory.

The flow of the remaining paper is as follows: The background literature depicts the main aspects of social media platforms (Twitter) and customers' experiences/expectations. Further, the theoretical framework for the study is discussed, abided by the methodology section. Next is the results section, followed by the conclusion and limitations of the study.

Background Literature

Overview of Twitter

Consumers engage with brands on social media (Mogaji et al., 2021) because social media platforms offer an engaging path for customers to interact with brands. This brand engagement allows the companies to ascertain customers' expectations and experiences about them and their competitors (Buhalis and Sinarta, 2019). Previous research has indicated that social media platforms produce plentiful content for the tourism and hospitality management sectors, assisting businesses in decision-making (Ahuja and Alavi, 2018).

Every social media platform has uniqueness, given what it provides to the audience. For example, Twitter is a microblogging platform that establishes engagement through short messages (Walker et al., 2017). Twitter provides a platform for individuals to express their happy and sad sentiments, and this information can be viewed by both passive and active users (Ibrahim and Wang, 2019). Furthermore, Twitter can be regarded as a helpful customer engagement tool. It allows people to explicit diverse opinions compared to other social media platforms, where conversations take place in a slightly controlled way (Mueller, 2019).

Twitter has drawn public attention (Walasek et al., 2018) and has evolved into a formidable tool brands use to engage with customers. Compared to other social media platforms, one distinctive quality of Twitter is its concise text layout that helps individuals express their views clearly and concisely.

Customers' Experience and Expectations in the Hospitality Industry

The competitive environment in the hospitality industry triggers companies to not only attract customers but also inspect customers' experiences for optimising service performance (Mehta et al., 2021; Gaur et al., 2020), as quality service will lead to an enhanced hospitality experience. Service quality is an essential factor for improving customer experience, which holds correct in the case of the hospitality industry as well. Poor service quality leads to a poor hospitality experience, which leads to a loss in the market share of the companies (Tosun et al., 2022). This negative experience can further result in negative WOM on social media (Quynh et al., 2021). Whereas effective hospitality leads to satisfied customers, they become better advocates for the hotels (Gómez-Suárez and Veloso, 2020)

Previous research on guests' experience/expectations has primarily discussed the importance of service quality of hospitality companies (Gaur and Afaq, 2020). For instance, (Li and Wei, 2021) examined the attributes that motivate the customers to recommend the hotel to others. The results showed that prompt service recovery actions enhance guest experiences and increase guests' chances of recommending the hotel on social media. Furthermore, (Afaq and Gaur, 2021; Punel et al., 2019) stated that while hospitality in terms of service quality is perhaps the most crucial attribute for enhancing guests' experience, there can be variations in guests' expectations regarding service quality depending upon the geographical regions (Gaur et al., 2023; Naved et al., 2023). Also, advancements in technology like augmented reality are giving wings to new expectations to the customers (Orús et al., 2021).

Theoretical Framework

The social capital theory (SST) postulates that social networks have virtues, which individuals derive through their social communities (Putnam, 2000). The knowledge-giving attitude of an individual depends upon the resources enclosed within the social networks (Blau, 2017). (Nahapiet and Ghoshal, 1998) proffered three interconnected dimensions of social capital: basic (the general type of association between individuals), relational (the recognition and connection individuals have created through collaborating), and cognitive (those assets giving shared portrayal, explanations, and frameworks of importance among parties). Further, this model was created by (Hau and Kim, 2011), who plot the structural attributes as the social ties through the network onto which mutual trust (relationship dimension) progresses. Moreover, all individuals in the group have similar pursuits (cognitive dimension).

Social capital impels knowledge-giving in online communities (Zhang et al., 2019). Social capital theory assists in connecting resources using social networking and helps understand consumer behaviour in the social media sphere (Yan et al., 2019). The present study uses the social capital theory to examine how guests engage and express their experiences/expectations on Twitter.

The present study develops a theoretical model, as shown in Figure 1, as a foundation for the research process by embracing (Hau and Kim, 2011) version of the Social Capital Theory. The framework encompasses three interlinked aspects of social capital, with sentiment analysis providing insights into the social connections within the network. This analysis can illustrate the extent of the relationship between hotels and guests, which plays a pivotal role in shaping a positive perception of the community (Ukpabi et al., 2019). Then, this is fed into TA to explore social trust in knowledge-giving.

Methodology

The study integrated both SA and TA to address the research questions. SA is "the automatic method to extract and analyse the subjective judgments on different aspects of an item or entity" (Soleymani et al., 2017). It uses a machine learning technique involving NLP to identify authors' opinions and perspectives regarding entities (Li and Hovy, 2017). Figure 2 depicts the research process for the study. The research process comprehends the intrinsic insights of the exchange of tweets between hotels and guests in the study.

In this study, conducting thematic analysis alongside sentiment analysis was crucial, as sentiment analysis alone cannot fully capture guests' experiences and overall viewpoints. Also, the factors that made them form a positive or negative view of the services must be addressed. The flowchart of the methodology used for the study is delineated in Figure 3.

The thematic analysis presents a qualitative aspect and identifies the reasons for shaping guests' experiences on Twitter. TA extensively applies to marketing studies employing netnography (Heinonen and Medberg, 2018). It is preferred because it identifies critical points by identifying repeated patterns and emerging themes (Kosciejew, 2021). Netnography, an evolution of ethnography, serves as a tool to examine consumers' online behavioral patterns (Tavakoli and Wijesinghe, 2019). The methodology workflow is divided into three parts, as presented below.

Data Collection

For the present study, guests, tweets were gathered as a direct impression of their experiences and expectations with the hotels. Python language assisted in text mining and SA, particularly 'GetOldTweets,' which was utilised for text mining. Comprehensive word documentation is included in the sentiment analysis software Textblob, which can handle all opinion-related tasks. It adopts NLP and machine learning principles to examine the terms present in a sentence; this study analyses tweets and determines whether tweets are positive or negative (Mogaji and Erkan, 2019). The input data comprises tweets sourced from the fifteen international chain hotels. The Twitter handles of these hotels were employed as keywords, and the data collection period spanned from January 1, 2022, to January 31, 2023.

Challenges in Collecting the Vast Dataset

The biggest challenge was accessing Twitter's restricted tweets, for which authors used the package 'GetOldTweets' in Python to bypass this limitation of Twitter's official API. In GetOldTweets, three parameters are passed, which are: "hotel names as the keywords," "From Date," and "To Date." As we had to fetch a massive data set, we did our search at a minimal level. The data set for two years could not be extracted in one go. Therefore, we extracted data on a per-day basis.

Data Preprocessing

The next step was the data pre-processing. This step was required to remove the unnecessary clutter from the unstructured Twitter data. In the pre-processed phase of extracting tweets, all irrelevant tweets were discarded to ensure that they did not impact the analyser interpreting the polarity.

Data Analysis

In the data analysis stage, sentiment analysis and thematic analysis were performed to analyse guests' sentiments and their experiences and expectations while engaging with the hotels on Twitter post-outbreak of COVID-19. The themes were identified through consequent examination of tweets in a netnographic setting. A portion of the tweets extracted using text mining was chosen for the thematic analysis. A total of twenty thousand tweets were chosen for analysis, and these tweets were subject to thematic analysis. These tweets were saved as a PDF and were transferred into NVivo12, a qualitative research tool used for thematic analysis.

Results and Discussion

Sentiment Analysis

In total, 324,194 tweets from the hotels were gathered. Nonetheless, only 271,077 of these tweets were employed for sentiment analysis, as the remaining tweets were attributed to the hotel companies and were predominantly neutral in nature. Of the tweets utilised for analysis, those reflecting positive sentiments comprised 41.34% (n=112,042). Meanwhile, tweets conveying negative sentiments accounted for 21.83% (n=59,206), and tweets with neutral sentiments made up 36.82% (n=99,840). The collective findings depict an overall positive sentiment associated with the hospitality industry.

The sentiments of the hotel guests towards the services offered by the hotels assist the companies in analysing the perception of their service in the minds of the guests. The results portray that the hotels are striving hard to cater to the needs of their guests. Despite the outbreak of COVID-19, the overall sentiments towards the hotels depict a positive trend. The results also portray that the negative sentiments towards the services generally revolve around the words like delayed, poor, slow, etc. The lack of on-time services can be one of the major reasons for the negative sentiments of the guests. Figure 4 depicts the hotel guests' positive, neutral, and negative sentiments towards the service providers.

Thematic Analysis

The global pandemic has affected customers in many ways. The most prominent themes visible during this period are depicted below.

Hotel Sanitization and Fumigation

A prominent trend in the dataset demonstrated guests' apprehensions regarding the fumigation efforts within the hotels. Questions were raised about the guest safety policies and whether rooms were properly sanitised following each check-out. Some guests stated grievances regarding perceived insensitivity among certain staff members. They highlighted situations where guests were allowed to check in without proper sanitisation, posing potential risks to guests and infants. Conversely, there were positive tweets commending certain hotels for their adequate adherence to stringent cleaning protocols.

Face-covering Policies for Fully Vaccinated Guests

The pandemic has left many anxious and scared about their safety, with an unwavering commitment to preventive measures. This sentiment is evident in our dataset, where guests depict dissatisfaction with hotel authorities for not enforcing mask-wearing among individuals. Some guests highlighted instances where hotels made promises on social media regarding a safe environment but allegedly failed to deliver. Additionally, there were reports of hotel staff verbally stating that fully vaccinated guests were exempt from wearing masks. However, this raised concerns about potential health risks to others, particularly as such information was not prominently displayed on the hotel's official website. Guests took to Twitter to voice their anger at the presence of individuals roaming without masks, reflecting their strong commitment to safety measures.

Food Safety Concerns

Guests have expressed their reservations regarding food safety and the overall hygiene in food preparation. Their doubts revolve around whether hotels are strictly following the guidelines for ensuring food safety. Many tweets stated the guests' desire for transparency regarding the disinfection and hygiene protocols employed during meal preparation. Many raised concerns about the efficacy of hotel buffet systems, with some customers proposing the promotion of in-room dining as a safer alternative to prevent the potential spread of infections.

Innovative Safety Measures in Hotels

The prevailing apprehension surrounding COVID-19 has presented fresh challenges for all stakeholders. Amid the various safety protocols implemented at hotels for screening visitors, guests have expressed a mix of satisfaction and uncertainty. Many guests commended hotels for their use of thermal scanners and sanitiser stations at various points within the hotel premises. Nevertheless, many guests suggested and urged hotels to adopt cutting-edge safety methods, such as the use of robots for cleaning and disinfection procedures. Some tweets even recommended that hotels use virtual reality technology to offer guests a virtual tour, showcasing the safety practices. This approach instils confidence in guests, ensuring a safe environment during their hotel visits.

Contactless Amenities in Hotels

The data set reveals the guests' safety-related worries. Customers' appreciation for contactless customer experiences, such as using hotel applications for check-in and check-out and keyless admission to rooms, is a crucial pattern frequently observed in the dataset. Virtual client assistance was commonly cited in tweets as safe consumer services. However, some consumers complained that they didn't receive personalised customer service when employing technology and were unsatisfied with virtual customer assistance.

Comparing Different Hotels

Customers frequently watch out for one another and recommend various service providers. In their tweets, they discuss the better offers offered by each hotel during COVID-19 and contrast their services. They demonstrate to other customers how to get better services at a lower cost by switching service providers and promoting one hotel's offers and advantages.

Observation in the Event of a Service Failure

Digital consumers of today don't take poor service in silence. The incorrect billing, unclean bathrooms despite the hygienic stay labels, and subpar Wi-Fi services were all complaints from the visitors of the hotels. However, numerous tweets also emphasised how the employees handled the service issue attentively. Customers enjoyed the staff's follow-up to see if they were happy or unsatisfied with the recovery procedure.

Value for Money

After the lockdowns, low hotel room rates and other loyalty programs encouraged visitors to resume their regular lives. The affordable hotel packages that included numerous extras, such as virtual health and fitness programs, pleased the guests. To reserve rooms at five-star hotels at a discount, guests cited the hotels' names and tagged friends. Guest repurchase intentions were reflected in value for money. Many visitors claimed that the hotel's more affordable rate, compared to other options, was the only factor in their decision.

Employee Courtesy: Setting Grievances and Imparting Praises

By recognising the staff members by name in their tweets, many visitors have expressed gratitude to the friendly staff for replying to their questions promptly and with a welcoming attitude. Many visitors posted about how the employees went above and beyond to help them. However, numerous tweets also emphasised the poor quality of the hotel's room service.

Table 1 illustrates the themes identified post-COVID-19 pandemic and portrays the hotel guests' experience/expectations.

Table 1 Themes Identified Post-Covid-19 Pandemic
S. No.	Themes
Theme-1	Hotel Sanitization and Fumigation
Theme-2	Face-covering policies for fully vaccinated Guests
Theme-3	Food Safety Concerns
Theme-4	Innovative safety measures in hotels
Theme-5	Contactless amenities in hotels
Theme-6	Comparing different hotels
Theme-7	Observation in the event of a service failure
Theme-8	Value for money
Theme-9	Employee Courtesy: Setting grievances and imparting praises

Conclusion, Implications, Limitations, and Future Research Areas

This study strengthens existing research on hotel visitors' experiences and expectations following COVID-19. The study is significant from the standpoint of the hotel and tourist sector, given its online setting. Scholars have argued that it is crucial to understand the varied aspects of customer expectations/experiences on Twitter, as Twitter feeds are plentiful with insights about guests' service experiences. The study invoked the SCT to develop a theoretical model as a foundation for the research process and aid in answering the two research questions. We undertook sentiment analysis using Python to address the RQ1, which is related to evaluating the guests' experiences/expectations from a sentiment point of view towards the hotels. This helped us to identify the polarity among the sentiments of the customers. The findings portrayed an overall positive sentiment towards the hotel service providers.

To address the RQ2, we undertook the thematic analysis to qualitatively understand guests' experiences/expectations. Sentiment analysis gives an understanding of the polarity of sentiments; however, it cannot provide an overall sense of guests' experiences/expectations. Therefore, the thematic analysis delivered qualitative insight and identified the themes after the outbreak of COVID-19 that shaped guests' experiences and expectations of the hotels. This study thus offers various functional implications for theory and practice.

Implications

Theoretical Implications

The three critical theoretical contributions of this work are as follows:

First, this work's primary contribution is identifying the themes illustrating the evolving experiences and expectations of hotel guests post-COVID-19 pandemic. These themes highlight the mutable and unstable character of interactions with guests enhanced by interpersonal and relational interactions.

By incorporating hotel and guest conversations on Twitter, this study also developed a theoretical framework that strengthens the application of social capital theory. This framework highlights the potential outcomes for the community and offers a current, crucial, and interconnected understanding of customers' service experiences. The study demonstrates how keen guests are to tweet their issues and demand a prompt hotel reaction.

Thirdly, this study enhances the field of sentiment analysis and makes a methodological contribution to the study of social media. A useful data production and analysis method that varies from conventional interviews and surveys is provided by this strategy. Furthermore, by utilising NLP and big data methodologies used in management research, this study offers insights into customers' feelings and behaviour in an online arena. Additionally, the readiness and desire of the customers to tweet about their interactions with the service providers enhances the validity of the data and offers actual insights into how they view the service providers. Guests might not often be asked questions or convinced to complete a questionnaire.

Practical Implications

From a practical perspective, this study offers the following implications.

First, providing food safety guarantees, taking precautions like vacuum-packaging food, utilising virtual reality to demonstrate cooking, and adopting other safety measures like sterilising utensils can help build customers' faith in the hotels' adherence to safety and hygiene standards.

Second, it's clear from the tweets that customers are motivated to switch service providers suggested by other guests. These modest efforts suggest that consumers occasionally view them as important influences and persuade others to switch service providers (Afaq et al., 2023b). It has consequences for hotels regarding how they might actively interact with the visitors to attract additional visitors. In a nutshell, electronic word of mouth is increasingly being used by customers to promote hotels.

Third, customer engagement is yet another crucial factor. Hotels should make an effort to develop relationships with their guests in addition to handling inquiries and complaints from guests. The brand's Twitter behaviour should reflect humility, consideration, good humour, and assistance. It is important to spread messages that are both educational and entertaining.

Social Implications

The unprecedented challenges of fear in guests' minds can be reduced if hotels handle it better by sharing information regarding the implementation of changes that hotels are planning, like a shift to touchless travel and an amended safety health management sustained by digital tools.

Research Limitations and Future Research Areas

Although this study has contributed significantly, it is vital to recognise its limitations and consider potential future research directions.

First, no demographic data from the visitors whose tweets were examined was extracted for this study. Additionally, only tweets on hotels in South Asia were included in the analysis therefore they might not be easily generalised to other sectors or geographical areas. Nevertheless, our research has shed light on essential correlations and patterns that can be a starting point for more investigation. Future studies can compare the shifts in consumer preferences and expectations due to COVID-19 to examine service experiences and expectations across different industries.

Second, most tweets chosen for thematic analysis came from months with few travel restrictions. The experiences and expectations of visitors may change over time due to the COVID-19 pandemic's evolving nature and changing governmental regulations everywhere. Therefore, future studies should capture the changing themes and patterns in visitors' experiences and expectations as travel alerts and guidelines change.

Thirdly, the rationale for choosing Twitter data as this study's sole source of analysis was presented. Future studies, however, can broaden their focus by comparing UGC from other social media sites like Facebook and Instagram to support and enhance the conclusions of this study. Future research can also explore whether customer demographics, such as gender and nationality, impact the themes connected to guest service experiences. Such a strategy might offer more nuanced perceptions of the diversification within the hotel sector. To further our understanding of guests' experiences, future research projects might include a more comprehensive array of qualitative and quantitative methodologies.

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Received: 13-Sep-2023, Manuscript No. AMSJ-23-14007; Editor assigned: 14-Sep-2023, PreQC No. AMSJ-23-14007(PQ); Reviewed: 30-Oct-2023, QC No. AMSJ-23-14007; Revised: 29-Dec-2023, Manuscript No. AMSJ-23-14007(R); Published: 24-Jan-2024