Next Article in Journal
Agile Leadership from the Perspective of Dynamic Capabilities and Creating Value
Next Article in Special Issue
Crisis Management and Sustainability in Tourism Industry: Obstacles and Recovery Strategies after the COVID-19 Crisis in Antalya, Türkiye
Previous Article in Journal
The Mitigation of Phytopathogens in Wheat under Current and Future Climate Change Scenarios: Next-Generation Microbial Inoculants
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Servicescape Effects on Hotel Guests’ Willingness to Pay Premiums at Different Stages of Pandemic: A Multi-Phase Study

1
White Lodging-J.W. Marriot, Jr. School of Hospitality and Tourism Management, College of Health and Human Sciences, Purdue University, 900 Mitch Daniels Blvd, West Lafayette, IN 47907, USA
2
Department of Hospitality and Sport Business Management, Alfred Lerner College of Business and Economics, University of Delaware, 303 Alfred Lerner Hall, Newark, DE 19716, USA
*
Author to whom correspondence should be addressed.
Sustainability 2023, 15(21), 15252; https://doi.org/10.3390/su152115252
Submission received: 17 September 2023 / Revised: 17 October 2023 / Accepted: 23 October 2023 / Published: 25 October 2023
(This article belongs to the Special Issue Tourism Industry Recovery after COVID-19)

Abstract

:
Drawing on servicescape theory, this research investigates guests’ perceptions of and responses to the protection and prevention practices launched by hotels at different stages of the pandemic. The research finds that hotel guests’ general response-efficacy beliefs positively influence their perception of the effectiveness of the protection and prevention practices adopted in hotels’ physical and social servicescapes, and such positive relationships also show a significant increase from 2020 to 2021. The servicescape effects’ downstream results show that hotel guests are willing to pay premium prices for safety servicescapes manifested as protection and prevention practices implemented at the private space or related to employees. This research sheds light on servicescape theory by deconstructing the overall hotel servicescape concept into multiple dimensions, particularly in a health threat situation such as the pandemic, and empirically examining each dimension’s effects on guests’ monetary response at different timepoints. From a practical perspective, this study provides managerial insights into which servicescape dimensions warrant operational investments by hotels.

1. Introduction

Although the upheaval COVID-19 caused in the hotel industry is well-documented [1,2], the virus has persisted, with concerns about new variants and outbreaks occurring in the years since it first burst onto the scene in late 2019. Thus, it is necessary for the industry to prepare for possible pandemics in the future by understanding how to co-exist with the virus while continually evaluating strategies to protect guests’ health [3]. From the early stage of the pandemic, industry practitioners have recognized the need to implement new health-related protection and prevention practices to secure guests’ health and safety and reduce the virus spread. Guidance and best practices were developed by the American Hotel and Lodging Association [2] and major hotel chains. Due to the persisting status of the pandemic, health and safety have become key motivations and considerations for travelers when making their hotel decisions [2]. As a result, many health-related protection and prevention practices have been kept as a necessary and important part of hotels’ servicescape design [4].
Servicescape theory suggests that customers’ cognitions, emotions, and behaviors can be affected and shaped by the service environment [5]. While servicescape theory originally only recognized the physical environment design and element (e.g., space/function, ambiance, and facilitation decor), it has been extended to the social environment (e.g., purchase occasion, social density, and emotions displayed by others in the environment) [6]. Line and Hanks [7] further delineate hotels’ social servicescape into employee-related and guest-related services. Similarly, hotels’ physical environments can be categorized as public spaces (e.g., common areas such as hotel lobby and workout areas) and private spaces (e.g., guestrooms). Coincidently, the recommended COVID-19 protection and prevention practices for hotels also cover these physical and social servicescape categories: conducting frequent cleaning and sanitation of the lobby area and re-arranging furniture layout to promote social distancing (public spaces); using contactless mobile keys to enter guestrooms and placing a seal on the guestroom door to indicate that there has been no use of the room since the last cleaning (private spaces); hotel employees wearing masks/gloves and engaging in regular health screenings (employee-related); requiring guests to wear masks and keep socially distancing (guest-related). These protection and prevention practices have now become many of the hotels’ service routines as part of the hotel servicescape design regarding the health of both employees and guests.
Recent qualitative interview research shows that hotel managers report servicescape reorganization to be a key component of a safe customer experience design in response to the pandemic’s impact [4]. From the hotel managers’ perspective, a reorganization of servicescape regarding the four aspects of customer experience design (physical environment, social environment, customer journey, and customer–employee touchpoints) is expected to alter the intended safe customer experience to cope with the pandemic health threat [4]. To further validate previous research findings from the customers’ perspective and conduct a comprehensive investigation, this study aims to consolidate the major protection and prevention practices manifested as different servicescape categories and examines whether and which servicescape reorganization solutions can help enhance guests’ experience at hotels and consequent behavioral intentions (i.e., willingness to pay a premium for safe hotel stays) during the pandemic. The current research findings provide insights and guidelines to hotel managers about how to invest efficiently and effectively in capitalizing pandemic protection and prevention practices for enhanced customer experience and improved revenue performance.
Hotel guests’ perceptions and behavioral responses likely changed during different stages of the pandemic. For example, the number of cases, hospitalizations, and deaths fluctuated throughout the pandemic, accompanied by the simultaneous updating of guidance and regulations by professional associations (e.g., the American Hotel and Lodging Association (AH&LA)) and federal/state/local agencies (e.g., Centers for Disease Control and Prevention (CDC)). In addition, as the pandemic waned, people began to experience pandemic fatigue, reflected as demotivation to follow the recommended protection and prevention behavior guidelines [8], causing declines in people’s adherence to the COVID-19 protection and prevention practices [9]. At the same time, the availability of COVID-19 vaccines since December 2020 provided hope that an end to the pandemic was near. All these pandemic-related changes may have collectively affected people’s evaluation of the general protection and prevention solutions established to cope with this health threat (i.e., response efficacy) [2,10,11]. Therefore, it is possible that, at different timepoints during the pandemic (starting/early to middle/end stages), guests’ belief in hotels’ response efficacy may have fluctuated due to the external macro-environment as a whole, which further affects their perception of the importance of specific protection and prevention practices at hotels, and their consequent willingness to pay extra for such practices to ensure a safe hotel stay.
With all of these considerations, the current study aims to systematically investigate how hotel guests perceive and react to the reorganized servicescape elements (i.e., public and private spaces in the physical environment and employee-related and guest-related actions in the social environment) adopted as various protection and prevention practices in response to the pandemic health threat [4] and, particularly, the premiums they might be willing to pay for these practices. Furthermore, data collected over two different timeframes (November 2020 and March 2021) are compared to explore whether any temporal variations existed among hotel guests as the pandemic evolved. The current study sheds light on servicescape theory by deconstructing the overall hotel servicescape concept into multiple dimensions, particularly in a health threat situation (i.e., a pandemic), and empirically examining each dimension’s effects on guests’ monetary response. From a practical perspective, this study provides managerial insights into servicescape dimensions that warrant operational investments by hotels.

2. Theoretical Backgrounds and Hypothesis Development

2.1. Servicescape Theory

This research draws on servicescape theory [5,12] as the theoretical framework to examine the impacts of the protection and prevention practices implemented by the hotel industry since the pandemic. Originally, a servicescape is defined as “the environment in which the service is assembled and in which the seller and customer interact, combined with tangible commodities that facilitate performance or communication of the service” [12] (p. 36). Servicescape theory is frequently used to explain and explore how a designed service environment may influence the behavior of people in that environment [5,6]. After decades of development, this classic theoretical framework expanded to multiple dimensions and was applied in various contexts.
Physical servicescape—The term servicescape traditionally refers to the physical elements of the service environment in which a service encounter happens [5,12]. The three major physical elements are space/function, ambience, and facilitating décor [5]. Space/function refers to spatial layout, furniture and furnishing, navigation and location; ambience encompasses elements such as scent, sound, lighting, and temperature; facilitating décor includes signs/signages, decorations, and artifacts and objects particular to the service company or destination [5]. These physical environment elements can influence customers’ cognitions and perceptions, and their emotional and behavioral responses to their service experience [5,13,14].
Social servicescape—Following the original servicescape concept developed by Bitner [5], Tombs and McColl-Kennedy [6] propose the term “social servicescape” and extend the framework to the social aspects of the service environment. The notion of social servicescape implies that social factors due to other customers and service employees also influence people’s service experiences in the shared environment [6,15]. The social servicescape elements include purchase occasion, social density, and the emotions displayed by others, which affect the focal customers’ affective and cognitive responses to the service experience [6]. Recent research indicates that the mere presence of other customers and employees should be viewed as an important part of the overall social servicescape, which can affect the focal customers’ service experience [16]. Line and Hanks [7] further delineate social presence into three dimensions: appearance, behavior, and similarity.

2.2. Hotel Protection and Prevention Practices

Since the outbreak of the pandemic, the hotel industry has launched a series of protection and prevention practices, adding to the existing servicescapes at hotels. The American Hotel and Lodging Association [2] developed the “Safe Stay” program as an industry-wide response to the threat of the COVID-19 virus, and this program was updated throughout the progress of the pandemic. The “Safe Stay” program provides comprehensive guidelines for hotel cleaning and disinfecting practices, and guidance for signage, personal protective equipment, social distancing, and specialized employee training. Additionally, all the major hotel chains launched their own protection and prevention practices in response to the pandemic, including new cleaning programs and disinfecting protocols, social-distancing-related practices, and increased usage of various contactless practices and technologies [17,18].
To investigate how hotel guests perceive and respond to the protection and prevention practices implemented by the hotel industry, we applied the servicescape framework for a systematic examination. Following the servicescape theoretical framework, hotels’ protection and prevention practices can be categorized as physical and social servicescapes [5,6]. Specifically, the physical servicescapes include practices in the hotel’s public spaces (e.g., frequent cleaning and sanitation in public areas, partitions, and social distancing set-up for public facilities) and the private spaces of hotel guestrooms (e.g., contactless room service, mobile apps to open the guestroom, certified cleaning and disinfection procedures for guestrooms). The social servicescapes are further specified as employee-related (e.g., service employees wearing masks and gloves, temperature measuring, and health screens for employees) and guest-related (e.g., guests wearing masks, signages reminding guests to maintain social distancing). The detailed protection and prevention practices of each servicescape type tested in the current study are provided in Appendix A.

2.3. Hypothesis Development

The extant pandemic-related research widely utilized the protection motivation theory [19] to explore how customers evaluate the available coping strategies to protect them from the potential risks caused by the pandemic in various hospitality and tourism sectors (e.g., restaurant, hotel, and travel) [10,20,21]. The protection motivation theory posits that people’s self-protective behaviors when facing threats or risks result from a set of cognitive processes: threat appraisals of threat susceptibility and severity, and coping appraisals of self-efficacy and response-efficacy [22]. Prior research finds that guests’ perception of hotels’ protection and prevention practices mediates the relationship between their perceived threats/individual response-efficacy and hotel stay intention during the pandemic [10]. In other words, guests may have varying levels of belief that hotels’ coping responses (manifested as the protection and prevention practices implemented by hotels) can effectively reduce the risk caused by the pandemic, which in turn influences their behavioral intentions regarding hotel stays. In definition, response-efficacy refers to people’s general perception regarding whether any behavioral changes are useful to reduce risk [22]. Such a perception relates to how much people believe that any recommended responses are effective in coping with a health threat [10].
At the time of the two rounds of data collection for this research (November 2020, eight months after the World Health Organization declared COVID-19 a pandemic, and March 2021, one year after the announcement of the pandemic; CDC, n.d.), the general population in the U.S. had already acknowledged the pandemic threat and established their own perceived ability to cope with the risk, presented as their individual response efficacy belief [10]. Such an individual response-efficacy belief could directly impact the degree to which a hotel guest perceives the effectiveness of the protection and prevention practices added to the hotel servicescapes [10]—the higher the level of response-efficacy guests have, the more they believe that these pandemic-related practices would be effective to protect them from contracting the virus. Specifically, we propose the following hypotheses for testing.
Hypothesis 1 (H1).
Guests’ response-efficacy beliefs positively affect the perceived effectiveness of the protection and prevention practices adopted in the physical servicescape at (a) hotel public spaces, and (b) guests’ private spaces at hotels.
Hypothesis 2 (H2).
Guests’ response-efficacy beliefs positively affect the perceived effectiveness of the protection and prevention practices adopted in the social servicescape related to (a) hotel employees, and (b) hotel guests.
The extant servicescape studies investigated various hospitality and tourism contexts (e.g., restaurant, hotel, event, theme park) [7,14,16,21,23,24] and found that customers respond to physical and social servicescape cues in many ways, ranging from affective to cognitive responses [6]. Positive customer responses align with customer goals (e.g., feeling satisfied, happy, welcome, comfortable, and belonging; enhanced quality of life) and, in turn, help service companies to achieve organizational goals such as customers’ desire to stay, return intentions, positive word-of-mouth, loyalty, attachment to the service establishment, and propensity to spend [7,14,16,21,23,24,25].
Previous servicescape research has investigated how servicescape cues lead to various downstream effects, particularly those benefiting service companies, such as consumption intentions and loyalty behaviors (e.g., [7,21,23,26]). Other than Lockwood and Pyun’s [14] findings that the aesthetic qualities of hotel servicescapes can make guests spend more than originally planned, there is a paucity of research regarding how much extra people may want to pay for certain servicescapes. In the recent pandemic-related literature, Fan et al. [27] discovered that guests’ response efficacy may positively impact their willingness to pay more for a safe hotel stay amid the COVID-19 pandemic through the enhanced protection motivation.
Established on previous research, this study aims to examine the downstream outcome of willingness to pay premiums in the current context of pandemic-related servicescapes. Willingness to pay premiums or willingness to pay more/extra refers to people’s expression of market demand, determined by the level of perceived benefits and values [28]. This indicates a service company’s competitive advantages in the market [29]. In this study, willingness to pay premiums is defined as to what extent guests would be willing to pay increased prices for a safe hotel stay to reduce the risk of contracting the virus, particularly willingness to pay premium prices for hotels adopting protection and prevention practices in their servicescapes. Following prior research suggesting that response-efficacy may influence guests’ willingness to pay premiums through the enhanced protection motivation [27], the current study tests whether guests’ general response-efficacy beliefs, formed since the burst of the pandemic, have a direct positive impact on their willingness to pay premiums for a safe hotel stay. Moreover, this study proposes that the protection and prevention practices adopted by the hotel servicescapes significantly enhance guests’ willingness to pay premiums for the hotel. Accordingly, the following hypotheses are posited:
Hypothesis 3 (H3).
Guests’ response-efficacy beliefs positively influence their willingness to pay premiums to hotels for a safe stay.
Hypothesis 4 (H4).
Protection and prevention practices adopted by the physical servicescape at (a) hotel public spaces, and (b) guests’ private spaces at hotels positively influence guests’ willingness to pay premiums to hotels for a safe stay.
Hypothesis 5 (H5).
Protection and prevention practices adopted by the social servicescape related to (a) hotel employees, and (b) hotel guests positively influence guests’ willingness to pay premiums to hotels for a safe stay.
Figure 1 demonstrates the overall conceptual model.
Another goal of the current research is to investigate whether guests’ perceptions and responses may change as the pandemic progresses. Since the declaration of the COVID-19 pandemic on 11 March 2020 (CDC, n.d.), the entire world and all walks of life have witnessed and experienced dramatic changes, particularly in the hospitality and tourism industry [30,31,32]. As the pandemic moves from the peak to fluctuation stages, people’s general perceptions of the pandemic threat and their response-efficacy may have changed as well.
More states have ended their stay-at-home orders, and nationwide recommendations regarding travel and indoor gathering were loosened by the Centers for Disease Control and Prevention (CDC). For example, 1 November 2020 marked the end of “no sail” orders for cruise ship companies, and from 8 March 2021, fully vaccinated people were allowed to gather indoors without masks. At the same time, the hotel associations (e.g., AH&LA) and hotel companies continually updated their protection and prevention programs and protocols to improve their practices to protect against the pandemic. These changes, along with the progress of different pandemic stages, may have significantly affected hotel guests’ perceptions and responses. Therefore, we chose a multi-phase approach for this research, exploring any differences by comparing two timeframes, and proposed the following research question:
Research Question: Are there any differences regarding guests’ perceptions of the protection and prevention practices and willingness to pay premiums between the following two timestamps: early and middle stages of the pandemic (November 2020) vs. late/end stage (March 2021)?

3. Methodology and Results

3.1. Data Collection

The convenience sample method was used to collect the data with a survey questionnaire distributed via the online crowdsourcing platform of Amazon Mechanical Turk. Participants living in the U.S. were targeted over two timeframes during the pandemic. Data were collected in November 2020 and March 2021, immediately after a major CDC announcement regarding the progressive loosening of pandemic policies and recommendations. The first timestamp marked the end of the no-sail order for cruise ship companies, and the second was the declaration that fully vaccinated people could gather indoors without masks (CDC, n.d.). Relevant screening questions (acknowledgment of the ongoing pandemic and previous lodging experience) and attention check questions (e.g., “for this question, please select Disagree as the answer”; “for attention check, please select Agree for this question”) were asked to ensure sample quality. After removing unqualified respondents, the final data for analysis included 324 qualified responses for the November 2020 dataset and 346 qualified responses for the March 2021 dataset.
These two samples were similar in their demographic characteristics. For the November 2020 and March 2021 datasets, the average age for participants was 37.6 and 37.5, respectively; gender split was 59.3% male/40.7% female and 56.9% male/43.1% female, respectively; 95.1% had college or above education for both timeframe datasets; 63.9% and 64.4%, respectively, reported an annual household income of more than USD 50,000; less than 1% participants indicated a poor health status during both survey timeframes.

3.2. Measurement

Participants were asked a series of questions about the following variables tested in this study. Three measurement items regarding response-efficacy belief were asked about (adapted from [33]). Then, participants were asked about the perceived effectiveness of a range of protection and prevention practices adopted by the hotel industry, including items adapted from relevant research [34,35,36] and industry practices since the outbreak of COVID-19 in the U.S. (AH&LA Opening Procedures April 2020; Cleaning Council Program by Marriott; Global Care and Cleanliness Commitment by Hyatt; CleanStay Program by Hilton). Based on the nature of these protection and prevention practices, they were grouped into public-space-related and private-space-related practices in the physical servicescape and employee-related and guest-related practices in the social servicescape. Lastly, participants were asked about their willingness to pay premiums for hotels implementing protection and prevention practices to minimize the risk of contracting the virus and ensure a safe stay. Three items were asked to measure participants’ willingness to pay premiums (adapted from the scale by [37]). All items were measured using the 7-point Likert scale. The measurement item details are available in Appendix A.

3.3. Results

The partial least square structural equation model (PLS-SEM) was employed to test the proposed hypotheses (H1 to H5). In contrast to the covariance-based SEM, PLS-SEM is component-based and provides parameter estimates that maximize the explained variance for prediction-oriented goals [38]. The main advantages of PLS-SEM are that it relies on less stringent assumptions like the normal distribution of the variables, and can estimate such complex models with many latent variables, such as the variables proposed in the current model [38]. In this study, PLS-SEM was used to calculate the influence of participants’ response-efficacy belief regarding their perception of the hotel’s protection and prevention practices and the confluence of these practices on their willingness to pay premiums for a safe hotel stay. This model also included demographic variables as control variables, including age, gender, education level, household income, and health status. The sample size of the two collected datasets met the requirement of PLS-SEM—10 times the largest number of structural paths directed at a particular latent construct [38].
Following the suggested benchmarks [38], the measurement model showed good reliability, with reliability ratings over 0.7 and indicator loadings higher than 0.7, and a good convergent validity with AVEs of latent constructs above 0.5 (Table 1). A good discriminant validity is reflected in the heterotrait–monotrait ratio of correlations (HTMT) based on a benchmark of values below 0.9 [39], and through the cross-loading results (Appendix A).
The bootstrapping procedure was conducted to determine the significance of path coefficients for the structural model. The variance inflated factor (VIF) test indicated no potential multicollinearity issues. Furthermore, multi-group analysis (PLS-MGA) was used to compare the model differences between the two collected datasets. Following the procedures delineated by [40], the permutation algorithm was used to assess the measurement invariance of composite models (MICOM). The requirements of configural invariance (Step 1), compositional invariance (Step 2), and the equality of the composites’ mean values and variances across groups (Step 3) were met, indicating the appropriateness of comparing the path coefficients with the PLS-MGA [41]. The SmartPLS 3.0 [42] was used for the above analyses.
The PLS-SEM results are provided in Table 2. For both timeframes (2020 and 2021), participants’ response-efficacy belief had a significant, positive impact on the perceived effectiveness of hotels’ protection and prevention practices, manifested as a physical servicescape (public space and private space) and social servicescape (employee and guest). Thus, H1a, H1b, H2a, and H2b were all supported. However, participants’ response-efficacy belief did not significantly influence their willingness to pay premiums for hotels; therefore, H3 was not supported.
In terms of how participants’ perceived effectiveness of various prevention and protection servicescape cues affected their willingness to pay premiums (H4 and H5), the results were mixed. The public-space-related practices did not show any significant effects for both timeframes, thereby failing to support H4a. On the other hand, the private-space-related practices significantly positively influenced willingness to pay premiums; therefore, H4b was supported. For the social servicescape cues, results reflected that both the employee-related and guest-related practices were not found to influence willingness to pay premiums for the November 2020 dataset, but evidence in the March 2021 dataset indicated a significant positive relationship. Hence, H5a and H5b were partially supported.
For the group comparison between the two timeframes (November 2020 vs. March 2021), the PLS-MGA results showed differences in the relationships between response-efficacy belief and the perceived effectiveness of various protection and prevention practices, reflecting the increased influence of response-efficacy belief from the year 2020 to 2021. However, no group differences were found in any hypothesized relationships regarding willingness to pay premiums for a safe stay at hotels.

4. General Discussion

4.1. Conclusions

Drawing on the servicescape theory, this research investigated the servicescape effects in the hotel context during the recent pandemic. The research categorized the major protection and prevention practices implemented by the hotel industry to cope with the pandemic into physical servicescape cues (public space and private space) and social ones (employee-related and guest-related), and systematically examined each of their effects. The research found that hotel guests’ general response-efficacy belief positively influenced the perceived effectiveness of the protection and prevention practices adopted in hotels’ physical and social servicescapes, and such positive relationships also increased between the two timeframes from November 2020 to March 2021 (H1 and H2), although such general response-efficacy beliefs did not directly influence guests’ willingness to pay premiums for hotels (H3). In terms of the downstream outcome of the servicescape effect, the results showed that, in general, although guests may have perceived the protection and prevention practices adopted in the public space or applied to guests to be effective, they did not want to pay premium prices for these practices; in contrast, hotel guests were willing to pay premiums for servicescapes manifested as the protection and prevention practices implemented in the private space or related to employees for a safe hotel stay (H4 and H5).

4.2. Theoretical Implications

The current research sheds new light on the long-standing servicescape literature. This research further deconstructs the servicescape concept into multiple dimensions that are directly related to the hotel context and empirically examines each dimension’s effects on hotel guests’ monetary response. Specifically, the research investigates whether guests would pay premium prices for each dimension of the hotel servicescapes (i.e., public- and private-space physical servicescapes and employee- and guest-related social servicescapes) in a health-threatening situation (i.e., the pandemic).
Since it was first proposed [5,12], the servicescape framework has evolved from only including physical elements [5] to also including social aspects [6]. In the hotel context, recent research further categorizes the social servicescape into customer- and employee-related servicescapes [7]. Expanding the extant literature, our research further specifies the hotel physical servicescapes into public space and private space categories, and thoroughly examines the servicescapes’ effects on hotel guests. Following this categorization, the research finds that guests respond differently in the two types of hotel space: guests are willing to pay more for the protection and prevention servicescape cues that are available at guests’ private spaces, at the hotel or in their own domain (e.g., hotel guestroom and guests’ own mobile phone), rather than for similar practices in public spaces that are shared with others. Such findings imply that different servicescape categories could have varying impacts on customer responses. Specifically, private (vs. public) physical servicescapes might matter more to customers in the hotel context. Consistent with previous social servicescape studies, the current research shows that employee-related social servicescapes significantly enhanced customer responses (customer satisfaction [7] and willingness to pay premiums in this study), but the effects of customer-related social servicescapes are situational, such as crowding levels [7] or pandemic timing (2020 vs. 2021), as in the present study.
This research makes another contribution by extending the extensive servicescape framework to a health-threatening context (i.e., pandemic) that has been largely under-researched in the extant servicescape literature. The pandemic has dramatically changed many aspects of hospitality and tourism activities, as reflected and documented in recent scholarly works [10,15,20]. The current research integrates the long-standing servicescape theory with recent pandemic inquiries to systematically examine what kind of servicescape may significantly affect customers’ intentions to spend extra money to protect themselves from a health-threatening virus. The research findings not only contribute to the recent pandemic literature but also present the implications of the crisis management and resilience research by identifying which coping practices matter most to customers and what strategies and tactics could help hotels to maintain their competitiveness when facing critical times or difficult situations [27,31].
In addition to examining the downstream effects of hotel servicescapes, our research also investigates antecedent conditions that may affect how guests perceive the effectiveness of various types of servicescape. The research confirms that guests’ individual response efficacy beliefs positively influence their perceptions of the protection and prevention practices reflected in various hotel servicescapes [10]. Furthermore, a comparison in two different years (2020 vs. 2021) indicates that the more people know about the coping mechanisms that can be used to prevent or reduce risk, the more confidence they have in the coping strategies adopted by hotels. Nevertheless, unlike previous research indicating a positive relationship between hotel guests’ individual response efficacy and their intention to stay during the pandemic [10], the current research finds that guests’ response efficacy belief does not directly affect their willingness to pay more. Such results imply that a belief in the coping strategies may not be strong enough to motivate people to go beyond intention to stay to further monetary intention. Rather, to prompt people to spend more, concrete, materialized, and tangible servicescape cues (e.g., specific protection and prevention practices) are needed to facilitate guests’ monetary decisions [14].

4.3. Managerial Implications

The study results provide practical operating guidelines and capitalization effort insights to hotel operators managing a health-threatening crisis. Guests appreciate that hotels reorganize their physical and social servicescape design to counter the health threat, reflected in their willingness to pay extra for the protection and prevention practices implemented since the outbreak of the pandemic. However, there are nuances regarding the specific pandemic-related servicescape elements for which guests are willing to pay premiums. The reorganization and extra servicescape elements adopted in response to the pandemic threat require both financial and operational investments, and this research helps pinpoint the most efficient investment area. The study finds that hotel guests are willing to pay more to ensure the cleanliness and safety of their own private spaces than that of public areas. Hence, housekeeping may prioritize the cleaning and hygiene of guests’ private spaces, as hotel guests perceive the cleanliness in public versus private spaces differently, and the protection and prevention practices implemented in guestroom areas directly affect guests’ impression of the hotel’s cleanliness and safety [36,43]. Because of this prolonged pandemic, many of the originally temporary solutions to the virus outbreak may be implemented in the long-term and become part of hotels’ operation routines. The research clearly indicates that investments in private space servicescapes might generate better financial returns, and hence could be emphasized (e.g., contactless technology and services, cleaning and sanitization programs for guestrooms).
The research findings underscore the importance of hotel employee training in responding to the pandemic and obtaining positive guest responses. The trainings are twofold: general protection and prevention training for all employees and professional cleaning and sanitation training for housekeeping staff. The current study indicates that guests are willing to pay extra for two aspects of pandemic-related servicescape cues: employee-related social cues and physical cues in guests’ own private spaces. Correspondingly, training all hotel employees to enforce pandemic operation protocols (e.g., wearing masks and gloves, regular temperature measurements and health screenings) helps to create salient social servicescape cues (employees’ professional appearances and responsible behavior) to impress guests with a safe social interaction environment. Specialized housekeeping training should aim to enhance guest experience and ensure safety, particularly focusing on properly and effectively cleaning and sanitizing the guestrooms. Additionally, it is important for hotel companies to invest in research and education programs related to housekeeping, cleaning procedures, and best practices, as guests perceive a cleaned and sanitized guestroom as a safe place to stay during the pandemic, and they are willing to pay premiums for such a safe room due to concerns regarding protection and virus-prevention.
This research also implies that marketing campaigns and awareness programs aiming to promote protection and prevention practices for safe hotel stays (e.g., Safe Stay Program by AH&LA, Cleaning Council Program by Marriott) are effective tactics that can help both hotels and guests in the pandemic crisis. The research findings demonstrate that the more guests are aware of hotels’ determination and ability to prevent or reduce the virus risk (response efficacy), the more confidence they may have in the various coping practices implemented by hotels. Guests’ confidence in hotels’ coping effectiveness not only enhanced their perceived safety and experience at hotels but also transformed into monetary returns to hotels (willingness to pay premiums), which can manifest into improvements in hotels’ revenue performance. Therefore, hotel companies may consider including relevant customer awareness campaigns and education programs in the companies’ crisis management strategy, helping hotels to better prepare for and cope with future crises.

5. Limitations and Future Research

Although this study provides important insights, the results should be viewed in the context of potential limitations. The current study only collected and analyzed data from two timepoints during the ongoing pandemic in the U.S. People’s perceptions and behavioral intentions might have evolved at different stages of the pandemic and across various regions/countries. As the pandemic continued, longitudinal data collection and analysis could have provided more comprehensive findings. Another limitation is that this study employed a convenience sample. Future studies may utilize a more purposeful sample, reflective of various traveler segments (e.g., business, leisure, and/or (in)frequent travelers). While this study only considered coping appraisal as an antecedent factor, other impactful factors related to hotel guests’ servicescape perceptions and willingness to pay more need to be evaluated. Future research may explore any variances related to health-related servicescape designs and settings among different lodging types (e.g., traditional hotels vs. peer-to-peer accommodation such as Airbnb; different tiers of hotels), as the amount of social interaction (employee–guest interaction or guest–guest interaction) and the public versus private space allocation vary across various lodging facilities.

Author Contributions

A.F.: Project administration, conceptualization, methodology, investigation, writing—original draft preparation, writing—review and editing, supervision. S.F.K.: Conceptualization, funding acquisition, writing—original draft preparation, writing—review and editing. Y.L.: Conceptualization, formal analysis, writing—original draft preparation, writing—review and editing. K.B.: Conceptualization, writing—original draft preparation, writing—review and editing. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Delaware Data Innovation Lab (100 W. 10th Street, Suite 915, Wilmington, DE 19801, USA).

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Board of University of Delaware (protocol code of 1617037-1 and approval date of 26 June 2020).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Data is unavailable due to the Institutional Review Board restrictions.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A

Table A1. Measurement items and cross-loadings for constructs (2020/2021).
Table A1. Measurement items and cross-loadings for constructs (2020/2021).
Response-Efficacy BeliefPhysical ServicescapeSocial ServicescapeWillingness to Pay Premiums
Response-efficacy belief
I believe that there are effective ways to protect myself from contracting COVID-19 when staying at hotels.0.745/
0.784
0.271/
0.483
0.189/
0.393
0.088/
0.352
I believe that the hotels’ protection and prevention practices can decrease my chance of contracting COVID-19 during stay.0.880/
0.842
0.347/
0.452
0.281/
0.397
0.194/
0.376
I believe that the hotels’ protection and prevention practices can reduce my risk to contract COVID-19 during stay.0.863/
0.826
0.323/
0.407
0.239/
0.359
0.220/
0.322
Physical servicescape
Hand sanitizer stations are available in public areas.0.347/
0.479
0.738/
0.823
0.578/
0.671
0.424/
0.552
Public areas are frequently cleaned.0.350/
0.438
0.737/
0.721
0.518/
0.561
0.414/
0.494
Contactless mobile apps for service are provided by using the guest’s own mobile phone.0.180/
0.412
0.726/
0.772
0.571/
0.604
0.476/
0.540
Contactless mobile key is provided to enter the guestroom by using apps on the guest’s mobile phone.0.204/
0.445
0.766/
0.794
0.577/
0.667
0.441/
0.561
No service staff enter the guestroom during guests’ stay.0.269/
0.326
0.660/
0.684
0.532/
0.520
0.399/
0.479
A seal is attached on the guestroom door to indicate the room has not been used since last cleaned/disinfected.0.302/
0.341
0.787/
0.741
0.622/
0.619
0.499/
0.566
The cleaning certificate program or procedures are followed at the guestroom (e.g., Marriott Cleaning Council program).0.285/
0.454
0.721/
0.753
0.548/
0.541
0.446/
0.529
Social servicescape
Service staff wear masks.0.234/
0.397
0.655/
0.689
0.760/
0.814
0.397/
0.563
Service staff wear gloves.0.196/
0.345
0.579/
0.607
0.703/
0.757
0.413/
0.548
Temperatures are taken for service staff upon arrival.0.218/
0.398
0.555/
0.626
0.800/
0.825
0.451/
0.629
Health screenings are regularly conducted for service staff.0.244/
0.385
0.561/
0.629
0.792/
0.824
0.422/
0.594
Guests are required to wear masks.0.234/
0.442
0.692/
0.684
0.784/
0.821
0.416/
0.576
Temperatures are taken for guests upon arrival.0.188/
0.310
0.465/
0.609
0.717/
0.809
0.440/
0.642
Willingness to pay premiums
I am willing to pay extra to stay at hotels implementing special protection and prevention practices to avoid contracting COVID-19.0.200/
0.375
0.538/
0.582
0.520/
0.667
0.879/
0.884
I am willing to pay premium prices for hotels implementing special protection and prevention practices to avoid contracting COVID-19.0.227/
0.429
0.554/
0.646
0.502/
0.656
0.885/
0.893
I plan to upgrade to better hotels (e.g., from an economy hotel to a midscale hotel, or from an upscale hotel to a luxury hotel) to minimize my risk of contracting COVID-19.0.111/
0.318
0.478/
0.617
0.425/
0.596
0.843/
0.845

References

  1. Aharon, D.Y.; Jacobi, A.; Cohen, E.; Tzur, J.; Qadan, M. COVID-19, government measures and hospitality industry performance. PLoS ONE 2021, 16, e0255819. [Google Scholar] [CrossRef] [PubMed]
  2. American Hotel and Lodging Association (AH&LA). Available online: https://www.ahla.com/safestay (accessed on 11 September 2023).
  3. Marani, M.; Katul, G.; Pan, W.; Parolari, A. Intensity and frequency of extreme novel epidemics. Proc. Natl. Acad. Sci. USA 2021, 118, e2105482118. [Google Scholar] [CrossRef] [PubMed]
  4. Bonfanti, A.; Vigolo, V.; Yfantidou, G. The impact of the COVID-19 pandemic on Customer Experience Design: The Hotel Managers’ Perspective. Int. J. Hosp. Manag. 2021, 94, 102871. [Google Scholar] [CrossRef] [PubMed]
  5. Bitner, M.J. Servicescapes: The impact of physical surroundings on customers and employees. J. Mark. 1992, 56, 57. [Google Scholar] [CrossRef]
  6. Tombs, A.; McColl-Kennedy, J.R. Social-servicescape conceptual model. Mark. Theory 2003, 3, 447–475. [Google Scholar] [CrossRef]
  7. Line, N.D.; Hanks, L. The social servicescape: Understanding the effects in the full-service hotel industry. Int. J. Contemp. Hosp. Manag. 2019, 31, 753–770. [Google Scholar] [CrossRef]
  8. WHO Pandemic Fatigue: Reinvigorating the Public to Prevent COVID-19. Available online: https://apps.who.int/iris/bitstream/handle/10665/335820/WHO-EURO-2020-1160-40906-55390-eng.pdf (accessed on 12 September 2023).
  9. Petherick, A.; Goldszmidt, R.; Andrade, E.B.; Furst, R.; Hale, T.; Pott, A.; Wood, A. A worldwide assessment of changes in adherence to COVID-19 protective behaviours and hypothesized pandemic fatigue. Nat. Hum. Behav. 2021, 5, 1145–1160. [Google Scholar] [CrossRef]
  10. Hsieh, Y.; Chen, Y.-L.; Wang, Y.-C. Government and Social Trust vs. hotel response efficacy: A protection motivation perspective on hotel stay intention during the COVID-19 pandemic. Int. J. Hosp. Manag. 2021, 97, 102991. [Google Scholar] [CrossRef]
  11. Milne, S.; Sheeran, P.; Orbell, S. Prediction and intervention in health-related behavior: A meta-analytic review of Protection Motivation Theory. J. Appl. Soc. Psychol. 2000, 30, 106–143. [Google Scholar] [CrossRef]
  12. Booms, B.H.; Bitner, M.J. Marketing strategies and organization structures for service firms in (Eds). In Marketing Services; Donnelly, J., George, W.R., Eds.; American Marketing Association: Chicago, IL, USA, 1981. [Google Scholar]
  13. Lin, I.Y. Evaluating a servicescape: The effect of cognition and Emotion. Int. J. Hosp. Manag. 2004, 23, 163–178. [Google Scholar] [CrossRef]
  14. Lockwood, A.; Pyun, K. How do customers respond to the hotel servicescape? Int. J. Hosp. Manag. 2019, 82, 231–241. [Google Scholar] [CrossRef]
  15. Zheng, D.; Luo, Q.; Ritchie, B.W. Afraid to travel after COVID-19? self-protection, coping and resilience against pandemic ‘travel fear. Tour. Manag. 2021, 83, 104261. [Google Scholar] [CrossRef]
  16. Hanks, L.; Line, N.; Yang, W. Status seeking and perceived similarity: A consideration of homophily in the social servicescape. Int. J. Hosp. Manag. 2017, 60, 123–132. [Google Scholar] [CrossRef]
  17. HVS Report—Hotel Cleanliness Policies in the Time of COVID-19. Available online: https://www.hotelnewsresource.com/article112645.html (accessed on 12 September 2023).
  18. Running on Empty: Protecting People and Business during the COVID-19 Crisis. Available online: https://bluetoad.com/publication/?m=16012&i=657476&p=0&+ver=html5 (accessed on 12 September 2023).
  19. Rogers, R.W. A protection motivation theory of fear appeals and Attitude change. J. Psychol. 1975, 91, 93–114. [Google Scholar] [CrossRef] [PubMed]
  20. Byrd, K.; Her, E.; Fan, A.; Almanza, B.; Liu, Y.; Leitch, S. Restaurants and COVID-19: What are consumers’ risk perceptions about restaurant food and its packaging during the pandemic? Int. J. Hosp. Manag. 2021, 94, 102821. [Google Scholar] [CrossRef] [PubMed]
  21. Zheng, Y.; Wei, W.; Line, N.; Zhang, L. Integrating the tourist gaze with the social servicescape: Implications for creating memorable theme park experiences. Int. J. Hosp. Manag. 2021, 93, 102782. [Google Scholar] [CrossRef]
  22. Floyd, D.L.; Prentice-Dunn, S.; ROGERS, R.W. A meta-analysis of research on Protection Motivation theory. J. Appl. Soc. Psychol. 2000, 30, 407–429. [Google Scholar] [CrossRef]
  23. Lee, S.; Chuang, N.-K. Applying expanded Servicescape to the hotel industry. J. Hosp. Tour. Res. 2021, 46, 771–796. [Google Scholar] [CrossRef]
  24. Siu, N.Y.-M.; Wan, P.Y.; Dong, P. The impact of the servicescape on the desire to stay in Convention and Exhibition Centers: The case of Macao. Int. J. Hosp. Manag. 2012, 31, 236–246. [Google Scholar] [CrossRef]
  25. Line, N.D.; Hanks, D.; Kim, W.G. An expanded Servicescape framework as the driver of place attachment and word of mouth. J. Hosp. Tour. Res. 2018, 42, 476–499. [Google Scholar] [CrossRef]
  26. Hanks, L.; Zhang, L.; Line, N. Perceived similarity in third places: Understanding the effect of place attachment. Int. J. Hosp. Manag. 2020, 86, 102455. [Google Scholar] [CrossRef]
  27. Fan, A.; Kline, S.F.; Liu, Y.; Byrd, K. Consumers’ lodging intentions during a pandemic: Empirical insights for crisis management practices based on protection motivation theory and expectancy theory. Int. J. Contemp. Hosp. Manag. 2022, 34, 1290–1311. [Google Scholar] [CrossRef]
  28. Enrique Bigné, J.; Mattila, A.S.; Andreu, L. The impact of experiential consumption cognitions and emotions on behavioral intentions. J. Serv. Mark. 2008, 22, 303–315. [Google Scholar] [CrossRef]
  29. He, Z.; Wu, L.; Li, X. When art meets tech: The role of augmented reality in enhancing museum experiences and purchase intentions. Tour. Manag. 2018, 68, 127–139. [Google Scholar] [CrossRef]
  30. Chan, J.; Gao, Y.; McGinley, S. Updates in service standards in hotels: How COVID-19 changed operations. Int. J. Contemp. Hosp. Manag. 2021, 33, 1668–1687. [Google Scholar] [CrossRef]
  31. Shi, F.; Shi, D.; Weaver, D.; Samaniego Chavez, C.E. Adapt to not just survive but thrive: Resilience strategies of five-star hotels at Difficult Times. Int. J. Contemp. Hosp. Manag. 2021, 33, 2886–2906. [Google Scholar] [CrossRef]
  32. Zhu, R.; Zhang, J. Rebounding through the pandemic: Towards the digitized and digitalized small hospitality business in China. Int. J. Contemp. Hosp. Manag. 2021, 33, 2676–2694. [Google Scholar] [CrossRef]
  33. Fisher, J.J.; Almanza, B.A.; Behnke, C.; Nelson, D.C.; Neal, J. Norovirus on cruise ships: Motivation for handwashing? Int. J. Hosp. Manag. 2018, 75, 10–17. [Google Scholar] [CrossRef]
  34. COVID-19 Study 2 Report—Restaurant and Hotel Industry. Available online: https://uwi.edu/covid19/sites/covid19/files/Covid-19%20Summary%20Report%20-%20Restaurant%20and%20hotel%20customers%E2%80%99%20sentiment%20analysis.pdf (accessed on 15 September 2023).
  35. Kline, S.; Neal, J.; Almanza, B. Hotel guest room cleaning: A systematic approach. Food Saf. Res. Hazard Hazard. Foods 2014, 303–322. [Google Scholar]
  36. Park, H.; Kline, S.F.; Kim, J.; Almanza, B.; Ma, J. Does hotel cleanliness correlate with surfaces guests contact? Int. J. Contemp. Hosp. Manag. 2019, 31, 2933–2950. [Google Scholar] [CrossRef]
  37. Xu, X.; Gursoy, D. Influence of sustainable hospitality supply chain management on customers’ attitudes and behaviors. Int. J. Hosp. Manag. 2015, 49, 105–116. [Google Scholar] [CrossRef]
  38. Hair, J.F.; Ringle, C.M.; Sarstedt, M. PLS-SEM: Indeed a silver bullet. J. Mark. Theory Pract. 2011, 19, 139–152. [Google Scholar] [CrossRef]
  39. Henseler, J.; Ringle, C.M.; Sarstedt, M. A new criterion for assessing discriminant validity in variance-based structural equation modeling. J. Acad. Mark. Sci. 2015, 43, 115–135. [Google Scholar] [CrossRef]
  40. Matthews, L. Applying multigroup analysis in PLS-SEM: A step-by-step process. In Partial Least Squares Path Modeling; Springer: Cham, Switzerland, 2017; pp. 219–243. [Google Scholar]
  41. Henseler, J.; Ringle, C.M.; Sinkovics, R.R. The use of partial least squares path modeling in International Marketing. Adv. Int. Mark. 2009, 20, 277–319. [Google Scholar]
  42. SmartPLS 3.0 Boenningstedt: SmartPLS. Available online: https://www.researchgate.net/publication/270883448_SmartPLS_3 (accessed on 15 September 2023).
  43. Lockyer, T. Hotel cleanliness—How do guests view it? let us get specific. A New Zealand study. Int. J. Hosp. Manag. 2003, 22, 297–305. [Google Scholar] [CrossRef]
Figure 1. Conceptual model.
Figure 1. Conceptual model.
Sustainability 15 15252 g001
Table 1. Reliability, validity, and inter-construct correlation (2020/2021).
Table 1. Reliability, validity, and inter-construct correlation (2020/2021).
Cronbach’s αCRAVE1234
1.
Response-efficacy belief
0.778/
0.752
0.870/
0.858
0.692/
0.669
2.
Physical servicescape
0.857/
0.875
0.891/
0.903
0.539/
0.572
0.458/
0.672
3.
Social servicescape
0.853/
0.894
0.891/
0.919
0.578/
0.654
0.349/
0.570
0.899/
0.895
4.
Willingness to pay premiums
0.838/
0.846
0.902/
0.907
0.755/
0.765
0.246/
0.534
0.710/
0.818
0.657/
0.841
Note: HTMT criterion for discriminant validity.
Table 2. PLS-SEM and PLS-MGA results.
Table 2. PLS-SEM and PLS-MGA results.
Hypothesisβ
(2020)
β
(2021)
Group Difference
(2020 vs. 2021)
H1a. Response-efficacy belief → Perceived effectiveness of protection/prevention practices (public space)0.397 ***0.523 ***0.126
H1b. Response-efficacy belief → Perceived effectiveness of protection/prevention practices (private space)0.328 ***0.517 ***0.189 *
H2a. Response-efficacy belief → Perceived effectiveness of protection/prevention practices (employee)0.284 ***0.463 ***0.179 *
H2b. Response-efficacy belief → Perceived effectiveness of protection/prevention practices (guest)0.254 ***0.425 ***0.171 *
H3. Response-efficacy belief → Willingness to pay premiums−0.0130.0280.042
H4a. Perceived effectiveness of protection/prevention practices (public space) → Willingness to pay premiums0.0910.0520.040
H4b. Perceived effectiveness of protection/prevention practices (private space) → Willingness to pay premiums0.363 ***0.293 ***0.070
H5a. Perceived effectiveness of protection/prevention practices (employee) → Willingness to pay premiums0.1290.273 **0.144
H5b. Perceived effectiveness of protection/prevention practices (guest) → Willingness to pay premiums0.1210.192 **0.071
Notes: 1. Control variables: age, gender, education, income, health status. 2. *** < 0.001, ** < 0.01, * < 0.05. 3. Model fit metric (SRMR): 0.060 for timeframe 2020, 0.049 for timeframe 2021. 4. R2 adjusted: 0.142 (physical servicescape), 0.080 (social servicescape), 0.386 (willingness to pay premiums) for timeframe 2020; 0.300 (physical servicescape), 0.218 (social servicescape), 0.587 (willingness to pay premiums) for timeframe 2021. 5. Q2: 0.124 (physical servicescape), 0.066 (social servicescape), 0.016 (willingness to pay premiums) for the 2020 timeframe; 0.292 (physical servicescape), 0.209 (social servicescape), 0.180 (willingness to pay premiums) for the 2021 timeframe.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Fan, A.; Kline, S.F.; Liu, Y.; Byrd, K. Servicescape Effects on Hotel Guests’ Willingness to Pay Premiums at Different Stages of Pandemic: A Multi-Phase Study. Sustainability 2023, 15, 15252. https://doi.org/10.3390/su152115252

AMA Style

Fan A, Kline SF, Liu Y, Byrd K. Servicescape Effects on Hotel Guests’ Willingness to Pay Premiums at Different Stages of Pandemic: A Multi-Phase Study. Sustainability. 2023; 15(21):15252. https://doi.org/10.3390/su152115252

Chicago/Turabian Style

Fan, Alei, Sheryl F. Kline, Yiran Liu, and Karen Byrd. 2023. "Servicescape Effects on Hotel Guests’ Willingness to Pay Premiums at Different Stages of Pandemic: A Multi-Phase Study" Sustainability 15, no. 21: 15252. https://doi.org/10.3390/su152115252

APA Style

Fan, A., Kline, S. F., Liu, Y., & Byrd, K. (2023). Servicescape Effects on Hotel Guests’ Willingness to Pay Premiums at Different Stages of Pandemic: A Multi-Phase Study. Sustainability, 15(21), 15252. https://doi.org/10.3390/su152115252

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop