Enhancing Consumer Confidence and Response Efficacy in Tourism: Typology and Effectiveness of the Hotel Industry’s Responses to COVID-19

Abstract

Although the tourism industry, including hotels, has been ravaged by the COVID-19 pandemic, few empirical studies have systematically examined the typology and effectiveness of their responses. To capture common response strategies within the hotel industry and assess their effectiveness, two studies were conducted. Study 1 adopted a hybrid approach involving deductive and inductive thematic analyses to evaluate 4,211 news articles. Five broad themes emerged: (1) revenue management, (2) crisis communication, (3) alternative approaches to service delivery, (4) human resource management, and (5) corporate social responsibility. Drawing upon protection motivation theory, Study 2 included a pre-test, pilot study, and main experimental study to examine the effectiveness of several common response strategies. Results showed that reassuring crisis communication and contactless services can foster consumer confidence and response efficacy, leading to positive consumers’ attitudes and booking intentions. Crisis communication and price discount were found to influence consumers’ attitudes and booking intentions directly.

Keywords

COVID-19 response strategies hybrid thematic analysis protection motivation theory

Introduction

COVID-19, as an unprecedented global crisis, has had a devastating impact on the global travel and tourism industry, with the hotel sector among the hardest hit (Jones 2020): as of August 2020, the hotel industry was on the brink of collapse, with nearly two-thirds of hotels at or below 50% occupancy (American Hotel and Lodging Association AHLA 2020a). In the United States, hotels have lost more than $13 billion in room revenue since public health anxieties escalated in February 2020; daily room revenue is expected to decline by more than $500 million ($3.5 billion per week) on the basis of reported occupancy rates (AHLA 2020a). As a key sector of the travel and tourism domain, the hotel industry is especially vulnerable to disasters or crises, the consequences of which can be socially and economically detrimental to hotel operations (Möller, Wang, and Nguyen 2018).

In cases of crisis, the news media disseminate nearly real-time details about the situation along with information about strategic preparedness and responses (Li and Pennington-Gray 2015). Many tourism firms have seized this avenue to rebuild consumer confidence and convey their response efficacy. Amid the COVID-19 outbreak, media outlets also act as transmitters and coordinators of critical crisis messages (Hall and Li 2020). As these channels enable organizations to share messages promptly, many tourism service providers (including hotels) have turned to the media to describe their response strategies in coping with the pandemic (Harrison 2020). For example, through media outlets, hotels stated that they have adopted stringent hygiene protocols to protect guests’ and staff members’ safety; health risks now constitute a major concern among patrons staying at hotels (Perez and Paranhos 2020). The wide distribution of such information is intended to restore guests’ safety-related confidence and to promote positive attitudes and behavioral intentions (Wang et al. 2019).

In terms of addressing pressing COVID-19-related questions, the literature (e.g., Hao, Xiao, and Chon 2020; Shin and Kang 2020) has suggested crisis response strategies in line with hotels’ proactive response initiatives. To date, Ritchie’s (2004) strategic implementation framework and typology have been widely applied to crisis response strategies in tourism settings (e.g., Hystad and Keller 2008; Paraskevas and Quek 2019). However, existing typologies have primarily focused on general response processes in the macro tourism ecosystem (i.e., on the destination level) (e.g., Hystad and Keller 2008; Paraskevas and Arendell 2007). Typology building has been used to minimize the complexity of observed phenomena by capturing and categorizing relevant terms (Fiss 2011). For example, scholars (e.g., Sparks and Bradley 2017) have developed a typology of management responses to negative online reviews to capture the ideal construction and classification of this empirical phenomenon. Little attention has been given to the development of a typology of response strategies amid a pandemic of this scope, apart from a handful of seminal conceptual efforts such as the COVID-19 management framework (e.g., Hao, Xiao, and Chon 2020). The relative lack of empirical research involving hotels and global health crises has led to limited coherence among scholars and practitioners in categorizing the industry’s response strategies. Considering the severe impacts of COVID-19 and the growing situational complexity facing the hotel industry, such knowledge is theoretically and practically vital. Study 1 was thus conducted to address this gap by systematically examining the typology of crisis response strategies in the hotel industry.

Furthermore, although recent tourism research has advocated for a system approach to avoid a tsunami of COVID-19 studies (Bausch, Gartner, and Ortanderl 2021), the current literature lacks empirical exploration of the effectiveness of key industry response strategies. According to UNWTO (2020a), consumer confidence and response efficacy are paramount to the tourism industry’s recovery from COVID-19. Therefore, understanding how to improve consumers’ confidence and the perceived response efficacy of firms during the pandemic poses a critical strategic challenge for hotels. With that in mind, Study 2 empirically investigated the effectiveness of key response strategies to generate consumer confidence, demonstrate response efficacy, and engender positive attitudes and booking intentions among potential tourists. Taken together, these two studies generated empirical findings that enrich the theoretical understanding of hotels’ crisis response strategies and provide useful recommendations regarding how the tourism industry should implement response strategies during challenging times.

Overview of the Studies

Two sequential studies were conducted to address this paper’s research objectives. Followed by the suggested guidelines for conducting multistage, multimethod research (Venkatesh et al. 2013), Study 1 was designed to identify major crisis response strategies in the global hotel industry by adopting a hybrid approach involving deductive and inductive thematic analyses (Fereday and Muir-Cochrane 2006). Five major themes of crisis response strategies emerged from the data: (1) revenue management, (2) crisis communication, (3) alternative approaches to service delivery, (4) human resource management, and (5) corporate social responsibility (CSR). To cross-validate the adequacy of this typology, an expert panel review was conducted with 22 managerial experts from the hotel industry. This process reinforced our findings and reflected the robustness of the response strategy typology.

Combining the findings of Study 1 with the theoretical framework of protection motivation theory, Study 2 also examined the impacts of three customer-oriented response strategies (i.e., crisis communication, service delivery, and a price discount) on two general outcome variables (i.e., customers’ attitudes and booking intentions). In light of our overarching aim to uncover effective ways to build consumer confidence and response efficacy in the face of COVID-19, Study 2 investigated the effects of two preventive measures (i.e., crisis communication and alternative service delivery) on two COVID-19-related coping appraisals (i.e., consumer confidence and response efficacy), which in turn influenced consumers’ attitudes and booking intentions. Findings revealed that providing crisis communication can promote consumer confidence and response efficacy, thereby engendering positive consumer attitudes and booking intentions toward a hotel. Similarly, alternative service delivery can facilitate consumer confidence, which in turn affects positive consumer attitudes and booking intentions. Thus, this study identified that consumer confidence and response efficacy served as mediating mechanisms, linking hotels’ response strategies with consumers’ attitudes and booking intentions. Furthermore, a hotel price discount and crisis communication were also found to directly affect consumers’ attitudes and booking intentions.

Literature Review

Crisis Management

A “crisis” is defined as “disruption that physically affects a system as a whole and threatens its basic assumptions, its subjective sense of self, its existential core” (Pauchant and Mitroff 1992, p. 15). Crises such as the 2009 swine flu pandemic (Page, Song, and Wu 2012) and the current COVID-19 pandemic (Hao, Xiao, and Chon 2020) have resulted in a significant body of work focused on devising tourism crisis management plans (e.g., Hystad and Keller 2008; Liu, Pennington-Gray, and Krieger 2016; Ritchie 2004). Ritchie and Jiang’s (2019) extensive review of the literature on crisis and disaster management highlighted the importance of tourism response and recovery, although relevant research involved case studies pertaining to differential impacts and effective/ineffective strategies. Among the studies reviewed, Ritchie’s (2004) framework and typology conceptually described the strategic implementation of crisis response strategies in several categories (see Table 1): (1) strategy evaluation and strategic control, (2) crisis communication and control, (3) resource management, and (4) understanding and collaborating with stakeholders. All these classifications have been frequently adopted in the tourism literature (e.g., Hystad and Keller 2008; Paraskevas and Quek 2019).

Table 1.

Response Strategies from Ritchie (2004).

Category	Summary
Strategy evaluation and strategic control	Identify strategic alternatives, evaluate alternatives, choose appropriate strategies, control over the crisis
Crisis communication and control	Develop crisis communication tactics, control over crisis communication, engage in crisis communication
Resource management	Implement responsive organizational structures, redistribute financial resources, change leadership styles
Understanding and collaborating with stakeholders	Communicate with internal and external stakeholders, collaborate with different organizations to resolve the crisis

Put simply, scholars have contended that crises are inevitable and must therefore be managed (e.g., Liu, Pennington-Gray, and Krieger 2016; Ritchie 2004)—yet tourism organizations often lack response plans for global pandemics such as COVID-19. Many countries have issued travel restrictions to stem the virus’s spread (Aljazeera 2020). These policies have limited tourists’ mobility and reduced individuals’ willingness to travel (Zhang, Hou, and Li 2020). The number of global tourist arrivals is projected to fall by 20%–30% in 2020 because of COVID-19, putting millions of jobs at risk (Unwto 2020b). The industry is expected to recover gradually and to require research-based guidance to navigate the COVID-19 landscape. Given its focus on response strategies, this study refers to Ritchie’s (2004) widely accepted crisis response typology as the primary coding scheme.

Study 1

Research Design

Study 1 aimed to capture common crisis response strategies in the hotel industry using a hybrid approach of deductive and inductive thematic analyses (Fereday and Muir-Cochrane 2006). To ensure methodological rigor, this study adopted a hybrid method of qualitative techniques of thematic analysis, integrating both deductive a priori template of codes method delineated by Ritchie (2004) and the data-driven inductive method of Moeller et al. (2013). After reviewing research on response strategies in tourism (e.g., Faulkner 2001; Ritchie and Jiang 2019), a deductive approach was adopted to guide the categorization process. The deductive method is often used when the structure of the analysis is operationalized on the basis of previous knowledge, thus moving from general to specific concepts (Elo and Kyngäs 2008). This study took the crisis response typology suggested by Ritchie (2004) as an initial categorization matrix for data coding.

Next, an inductive thematic analysis was conducted to identify and refine the typology of crisis response strategies in the hotel industry. This step allowed for the expansion of our initial deductive thematic analysis, which was limited to an existing typology that may not capture new information in different areas (Matthes and Kohring 2008). Researchers (e.g., Le and Phi 2021) have acknowledged that media plays an important role in the tourism industry by conveying information to shape destination evaluations and guide the selection of tourism products in times of crisis (Liu and Pennington-Gray 2015). The analysis of news media can also produce important insight into contemporary issues because media outlets deliver timely reports of actors’ responses to evolving situations across the globe (Le and Phi 2021). Amid COVID-19, the media is a primary information source for the public and regularly covers health-related issues (Liu and Pennington-Gray 2015). Thus, a media analysis is deemed as an adequate method to capture the crisis management function of the tourism industry.

For the purposes of this study, data were drawn from COVID-19 news articles published via LexisNexis and AHLA using the keywords “COVID-19,” “Coronavirus,” and “hotel”; these terms could appear anywhere in the documents. LexisNexis, an academic database, is one of the world’s biggest news databases (Stepchenkova and Eales 2011). AHLA (2020b) is the national association standing for all segments of the U.S. lodging industry, such as major hotel chains, independent hotels, management companies, and industry partners. Our data triangulation was intended to promote a comprehensive understanding of the phenomena of interest and to test the credibility of data through different sources, thereby enhancing the validity of identified outcomes and the representativeness of information (Rolfe 2006).

Source documents were published between April 16, 2020, when the CDC announced a phased approach to reopening the economy and social activities, and August 13, 2020, when most governments had moved into a response and recovery phase. Our full dataset contained 16,872 articles. We employed iteration and refutation operational approaches (Spiggle 1994). To identify inclusion criteria, we referred to predetermined coding categories from Ritchie’s (2004) strategic implementation typology. These criteria included strategy, evaluation, control, communication, management, resource, collaboration, and response. While examining articles across the two data sources, we found two new strategy themes—CSR and alternative approaches to service delivery—which were not captured by previous crisis frameworks. After investigating 4,211 articles, no new information emerged, indicating data saturation (Glaser and Strauss 1967). Thus, we analyzed 24.96% of all articles collected, in line with Kim, Rahman, and Bernard’s (2020) suggested qualitative content analysis approach.

Data Analysis

Following Moeller et al. (2013), our analysis involved five steps: (1) familiarizing ourselves with the news articles, (2) coding the articles’ content, (3) classifying the codes, (4) contrasting the categorizations/codes, and (5) resolving all inconsistencies. After excluding duplicate news articles, a total of 832 articles were imported into NVivo. A member of the research team familiarized himself with the articles by reviewing them in chronological order and developing descriptions of the chosen sources in Step 1. The data were analyzed to extract various meanings in Step 2 (Matthes and Kohring 2008). We used NVivo 12 to facilitate coding organization and management. NVivo makes use of the term node to refer to a code, which is a group of references related to a certain theme, synthesized from several sources into a central point. We classified these nodes into a “tree node” in a hierarchical manner (Bazeley and Richards 2000). Where we agreed to do so, we also separated and collapsed certain tree nodes into new nodes based on the code association; nodes were renamed as needed during this process. NVivo enabled flexibility between the researchers by allowing for code modification and comparison. After coding all elements of hotels’ response strategies (first-order codes) in NVivo, Step 3 involved two of the researchers grouping strategy components into categories. We followed Creswell (2000) in establishing the reliability and credibility of our methodology in Step 4. Specifically, several virtual meetings were held with all researchers to discuss categorizations and codes and thus substantiate all-encompassing themes (Creswell 2000). This procedure met the researchers’ lens perspective standards. Inconsistencies were resolved through discussion during Step 5. After grouping first-order codes into more abstract second-order categories, five primary response strategies emerged (see Table 2): (1) revenue management, (2) crisis communication, (3) alternative approaches to service delivery, (4) human resource management, and (5) CSR.

Table 2.

A Typology of Response Strategies in the Hotel Industry.

Second-order Category	First-order Codes	Representative Examples	Applicability
Revenue management	Price discount	• Offering a discount on hotel room rates	6.1
	Flexible policy	• Extending members’ loyalty program status and pausing points expiration	6.0
	Alternative uses (leasing)	• Temporarily converting rooms or space into workstations, including a spacious desk and enhanced WiFi, for remote working	4.5
Crisis communication	Internal communication	• Using consistent communication systems (e.g., hotel intranet) to communicate with employees	4.9
	External communication	• Communicating with guests using multiple channels (e.g., official website and social media)	5.9
	Lobbying for governmental assistance	• Lobbying for an extension of aid packages (e.g., tax relief); seeking additional relief to support operations	5.2
Alternative approaches to service delivery	Contactless service	• Providing contactless service, such as self check-in/out and 24/7 e-concierge service accessible via hotels’ apps	5.8
	Third-party technology partners	• Partnering with delivery companies (e.g., Uber Eats and DoorDash) to offer food and beverage delivery from local restaurants	5.4
	Protocols and certification	• Following updated safety and sanitation protocols (e.g., sanitizing hands and wearing face masks) for service delivery	6.6
Human resource management	Laying off employees to reduce labor force	• Implementing temporary layoffs to reduce capital expenditure	5.9
Human resource management	Supporting employees and unemployed	• Providing current staff members and unemployed members with short-term relief	4.5
Corporate social responsibility	Funding and donations to local communities	• Forming partnerships with food banks and other food provision charities to help those most in need	4.7
	Alternative uses (good causes)	• Offering free rooms to doctors, nurses, and other first responders helping in the fight against COVID-19	4.5

Note: Each applicability indicates the average score on a single response strategy measured on a 7-point Likert-type scale (1 = highly inappropriate, 7 = highly appropriate) from 22 managerial experts in the hotel industry.

Results

Revenue Management

The first theme was revenue management, which entails optimizing product availability and price to maximize revenue growth. First, the sample articles (35%) outlined various revenue management strategies, including pricing strategies, flexible policies, and alternative uses. During the COVID-19 pandemic, many hotels have used revenue management as a customer-oriented response strategy. For example, several articles highlighted pricing strategies, including price discounts and bundling, as ways to increase hotel occupancy and revenue. Hotels have also proposed multiple pricing strategies, ranging from discounted hotel rates to up-selling (e.g., offering consumers an opportunity to upgrade to a better room or a better view for an additional cost) and cross-selling (e.g., encouraging guests to eat at the hotel’s restaurant or to book a spa package).

Second, the selected articles generally emphasized flexible hotel policies, such as waiving cancelation fees and maintaining consumers’ membership and points. Many hotels have also implemented more flexible cancelation policies amid COVID-19 to provide guests with full refunds. Certain hotels, such as the Intercontinental Hotels Group, Hilton, and Marriott International, have also offered membership tier and point status extensions; for instance, loyalty program members have been allowed to maintain their current membership tier during these challenging times.

Third, the articles summarized alternative uses of hotels. As remote work has skyrocketed during the pandemic, some hotels have converted unused space into sanitary remote workstations for homebound workers. In other cases, by providing housing to first responders and essential workers, hotels have offered much-needed services while generating additional cash. Given growing COVID-19 cases, state and local governments have also sought to use hotel properties as operating spaces to quarantine individuals. Collectively, hotels have been repurposed as hospitals, quarantine centers, and business offices during the pandemic.

Crisis Communication

The second theme that emerged from our data was crisis communication, which is designed to protect an organization’s reputation in the face of the crisis. Sample articles (32%) discussed diverse crisis communication strategies, including internal/external communication and lobbying for governmental assistance. First, some large hotel chains have offered guests 24/7 medical care and presented guests with insurance services and agreements to foster trust and confidence. Hotels have also used multiple communication channels to target consumers and to ensure guests can remain well-informed. For instance, through email databases, websites, and social media channels, hotels have kept their guests up to date regarding COVID-19 response efforts. Accordingly, external communication represents a common customer-oriented response strategy in the hotel industry.

In addition to consumer communication, some articles highlighted the importance of effective communication with hotel staff. Unified messaging is essential to helping hotels alleviate employees’ confusion, promote ongoing productivity, and establish trust among staff. Thus, hotels have generally enacted internal communication plans via reliable internal communication tools on a digital hub. Hotels have also communicated with governments to seek pandemic-related assistance, although such measures appear less common than consumer- and staff-centric initiatives. The present pandemic has compelled personnel at all levels of government to focus on monetary and fiscal policy, enabling the hotel industry to remain operational and even enhance its liquidity. Many players in the hotel industry have sought a much-needed financial life raft to survive the next few months until a vaccine is in mass production.

Alternative Approaches to Service Delivery

Alternative approaches to service delivery represent a major response strategy for hotels. About 17% of the chosen articles reported new findings that previous crisis typologies did not capture. In addition to revenue management and crisis communication, alternative approaches to service delivery have often been implemented as innovative customer-oriented response strategies. First, people have been required to increase their physical distance because COVID-19 is highly transmissible via person-to-person contact (WHO 2020). Thus, service robotics and technology-enabled services are expected to become popular throughout the tourism industry during the pandemic. Hotels have already adopted robots and unmanned machines to deliver contactless service; examples include facial scanning at check-in and check-out, robot concierge assistants and receptionists, and 24/7 e-concierge service accessible via hotels’ apps.

Second, some hotels have begun cooperating with delivery companies such as Uber Eats and DoorDash to modify food and beverage delivery. In addition to offering an alternative approach to service delivery, such collaboration has partially addressed hotels’ cash flow problems by minimizing food waste. Other hotels have implemented pick-up services, where local consumers can order food online and then safely retrieve their meals.

Third, our dataset reflected the importance of hotel hygiene and cleanliness. Hotels are now adhering to particular safety protocols: hotel staff must meticulously sanitize their hands and wear disposable gloves and face masks while working. Daily thermal checks are generally conducted for all employees before beginning a shift. Guests must also submit a temperature check before entering the hotel premises. Additionally, staff members have received training on sanitation and physical distancing in accordance with guidance from the CDC and WHO.

Human Resource Management

The theme of human resource management relates to strategic approaches to the effective management of individuals within an organization. Sample articles (16%) reported several human resource management strategies, including layoffs and support for employees and the unemployed. First, hotels have called for a substantial reduction in their workforce due to extreme business-related effects from COVID-19. Multiple industry positions have been pruned, such as room attendants, cooks and kitchen staff, maintenance workers, and security personnel.

Although workers under many hotel brands have found themselves unemployed during the pandemic, several chains, such as MGM Resorts and the InterContinental Hotel Group, have provided staff and their immediate families with short-term financial relief. Some hotels have also notified the creation of job centers and affiliations with retailers in other industries to help employees find temporary jobs. Other hotels have agreed to supply unemployed workers with health insurance and their base wage for an extended period; for instance, Hilton has financially supported unemployed staff and their families. Furthermore, certain hotels have partnered with leading companies (e.g., Amazon and Walgreens) to support staff suspended from their hotel positions through hundreds of thousands of temporary jobs.

Corporate Social Responsibility

Another theme identified from our data was CSR, defined as a firm’s commitment to maximizing long-term societal, economic, and environmental well-being through business resources and practices (Du, Bhattacharya, and Sen 2011). About 18% of articles mentioned hotels implementing social responsibility initiatives, motivated by a potential return on investment and a genuine desire to positively influence society. From a philanthropic perspective (Tsai et al. 2010), several hotels sacrificed their own profits to benefit social stakeholders based on the industry’s unique resources during the pandemic. For example, hotels have recently leveraged their core competencies when creating opportunities for shared value to demonstrate CSR by providing free hotel rooms and food to frontline workers (e.g., health care and police) and other vulnerable groups. Furthermore, some hotels have donated to charity partner relief efforts in local communities during the pandemic. Thus, CSR activities have been used to build a favorable reputation, which contributes to a company’s competitive advantage and sustainability.

Cross-Validation

An expert panel review was conducted to cross-validate the empirical applicability of our typology. The project team sent an email to hotel managerial experts that included a link to a Qualtrics survey. Twenty-two experts (10 general managers, eight directors, three vice presidents of operations, and one owner) with an average of 19 years of relevant work experience in the industry participated in the expert panel. Among respondents, 50% (n = 11) were from full-service hotels, 45% (n = 10) were from limited-service hotels, and 5% (n = 1) reported working at a boutique hotel. The sample size was in line with prior expert panel review exercises (e.g., Gallarza et al. 2017; Sparks and Bradley 2017). We adopted a 7-point Likert-type scale (1 = highly inappropriate, 7 = highly appropriate) to evaluate the applicability of our typology. Ratings on all response strategies far exceeded the scale mid-point of 4, indicating a high degree of convergence (Sparks and Bradley 2017). The most applicable strategy was protocols and certification (6.6), followed by price discount (6.1), flexible policy (6.0), laying off employees to reduce the labor force (5.9), external communication (5.9), and contactless service (5.8). Table 2 presents the typology of response strategies as well as its applicability scores in the hotel industry.

Discussion

Study 1 established the typology of crisis response through a hybrid approach of deductive and inductive thematic analyses. Five key response strategy themes were observed. Specifically, our findings suggest that revenue management, crisis communication, and alternative approaches to service delivery have been widely used from a consumer perspective. In line with the results of Study 1, which underscored revenue management as the predominant theme of hotels’ response strategies, recent studies (e.g., Guillet and Chu 2021) demonstrate that pricing strategy, demand modeling and forecasting, and business analysis are the most significant revenue management processes in the context of COVID-19. A price discount, which is one type of pricing strategy, is particularly widely used as a customer-oriented response to speed up crisis recovery by increasing cash flow and maximizing total profitabilit. However, the actual impact of a price discount under low-demand and low-supply conditions owing to the pandemic remains surprisingly uncertain. Thus, a price discount was further examined as a key customer-oriented response strategy, along with crisis communication and alternative approaches, in Study 2.

Study 2 explored the impacts of hotels’ customer-oriented response strategies (i.e., crisis communication, service delivery, and a price discount) on two general outcome variables (i.e., customers’ attitudes and booking intentions). Furthermore, considering our overarching aim to uncover effective ways to build consumer confidence and response efficacy in the face of crisis, Study 2 was intended to extend the findings of Study 1 by investigating the effects of two preventive measures (i.e., crisis communication and service delivery) on coping appraisal (i.e., consumer confidence and response efficacy), which in turn affected consumers’ attitudes and booking intentions.

Study 2

Theoretical Background

Protection Motivation Theory

To evaluate consumer confidence and response efficacy during the current pandemic, protection motivation theory (Roger 1975) was adopted as the conceptual framework in Study 2. This framework has been used to identify the psychological processes underlying various aspects of human behavior during global pandemics. Protection motivation theory posits that, when contemplating information sources in terms of response measures to diminish the consequences of crises, consumers execute one of two cognitive mediating processes—threat appraisal and coping appraisal—that inspire behavioral intentions (Milne, Sheeran, and Orbell 2000). When engaging in threat appraisal, an individual evaluates the severity of a crisis and considers how threatened they feel by the event (Floyd, Prentice-Dunn, and Rogers 2000). This process informs the degree to which the person engages in health-protective behavior (Floyd, Prentice-Dunn, and Rogers 2000).

By contrast, individuals involved in coping appraisal assess their perceptions and belief about the appropriateness and effectiveness of coping strategies in managing a threat (Floyd, Prentice-Dunn, and Rogers 2000). The literature suggests that coping appraisal tends to be more strongly related to outcome variables (e.g., people’s intentions and actual behavior) compared with threat appraisal (Wang et al. 2019). Coping appraisal also involves evaluations of consumer confidence and response efficacy. Consumer confidence is defined as an individual’s cognition-based evaluation, reflecting their degree of certainty about the appropriateness of coping strategies; response efficacy refers to an individual’s belief about the effectiveness of coping strategies in reducing a perceived threat (Rimal and Real 2003).

Crisis Communication

Crisis communication refers to strategic messages employed to diminish the consequences of a crisis (Coombs 2007). Crisis communication is derived from public relations; it is intended to address the public’s perceptions of crises and to lessen these events’ adverse impacts on affected organizations (Benoit 1997). Providing accurate and relevant information can also decrease the distress associated with a crisis while boosting optimism amid a high degree of uncertainty (Cahyanto et al. 2016). Implementing effective crisis communication strategies can thus limit negative public perceptions both during a crisis and in the crisis response stage (Ritchie 2004). Thus, hotels strive to communicate response strategies to consumers effectively in order to protect patrons from various crises, thereby enhancing consumer confidence and response efficacy (Liu-Lastres, Schroeder, and Pennington-Gray 2019; Möller, Wang, and Nguyen 2018). Although it remains unclear whether such effects pertain to a pandemic of the magnitude of COVID-19, strategic crisis communication has been found to help tourists perceive hotels as safe during crises and thus boost their booking intentions (Ritchie and Jiang 2019). As such, we hypothesize that:

Hypothesis 1: During a global pandemic, (a) consumer confidence, (b) response efficacy, (c) attitudes, and (d) booking intentions are higher when a hotel clearly communicates its COVID-19 preventive measures than when it provides limited information about its COVID-19 measures.

Service Delivery

The COVID-19 outbreak has compelled hotels to confirm they are safe by employing alternative approaches to service delivery, such as innovative automated technologies for physical distancing (Shin and Kang 2020). Hotels are now especially likely to adopt “unmanned” devices, including digital key systems for check-in and check-out, face recognition technologies, and robot cleaning systems, to increase consumer confidence and response efficacy. One of the most well-known methods is self-service technologies (SSTs) (Rust and Espinoza 2006). SSTs are technological interfaces which allow consumers to make use of a service without interacting with employees (Wang, Harris, and Patterson 2013). By adopting a threat appraisal, a recent study demonstrated that technology-mediated systems (e.g., kiosk check-in and mobile systems) can alleviate guests’ perceived health risks (Shin and Kang 2020). Given that social distancing is important to curb the spread of COVID-19, new technologies such as self-service kiosks can presumably enhance coping appraisals (i.e., consumers’ confidence and response efficacy) vis-à-vis the hotel industry and hence improve their attitudes and booking intentions (Wang et al. 2013). Therefore, we propose the following hypotheses:

Hypothesis 2: During a global pandemic, (a) consumer confidence, (b) response efficacy, (c) attitudes, and (d) booking intentions are higher when a hotel provides contactless services than when it provides human services.

Price Discounts

The nature of hotels involves earning revenue through price changes based on demand (Cross, Higbie, and Cross 2009). Price discounts, a common revenue-boosting strategy among service-oriented companies with perishable inventory (Cross 2011), can raise hotels’ revenue: discounting services and/or products during challenging times, such as periods of low demand, can appeal to consumers (Narasimhan 1984). Although consumers tend to calculate the potential value of products by evaluating the trade-off between perceived benefits and costs (Zeithaml 1988), the actual impact of price discounts during a pandemic of such magnitude is unclear. While some marketing studies have suggested that price discounts could diminish consumers’ brand preferences and quality perceptions as well as compromise brand equity by leading consumers to focus on cost (Aaker 1996), short-term price reductions have been adopted to encourage travel following an epidemic, such as SARS in Southeast Asia (Wang 2009). Thus, hotels adjust their room prices in an attempt to sell more rooms at substantially discounted rates during low- demand periods (Guillet and Chu 2021). While research on the effects of price discounts on consumers during a global pandemic is limited, on the basis of the literature, we hypothesize that:

Hypothesis 3: During a global pandemic, consumers’ (a) attitudes and (b) booking intentions are higher when a hotel offers a price discount than when it does not.

Coping Appraisal

Protection motivation theory (Roger 1975) holds that coping appraisal (i.e., consumer confidence and response efficacy) mediates the effects of information sources on behavioral outcomes. Coping appraisal processes can emerge from consumers’ assessment of coping mechanisms’ effectiveness, thus offering critical decision-making guidance (Wang et al. 2019). Therefore, the interplay of coping appraisals (i.e., consumer confidence and response efficacy) ultimately inspires consumers’ decisions (i.e., attitudes and booking intentions). Consistent with this theorization, the literature has shown that consumer confidence and response efficacy can mediate the relationships between usage or purchase intention and their antecedents in contexts such as workplace safety (Basil et al. 2013). Consumers’ confidence in hotel safety during the pandemic depends on their perceptions of a hotel’s competence in performing protective tasks and the hotel’s fiduciary responsibility to protect its guests (Storopoli, Braga da Silva Neto, and Mesch 2020). According to recreancy theory, consumer confidence in organizations (i.e., hotels) is a critical factor predicting the adoption of protective behavior and in turn, affects behavioral intention (Sapp and Downing-Matibag 2009). In addition, response efficacy represents an individual’s expectation of adopting a behavior, which increases one’s possibility of engaging in protective behavior (Bandura 1997). Accordingly, in this study, crisis communication and alternative service delivery are responses that hotels can implement to communicate with and protect their guests; price discounts contribute to a hotel’s revenue management. Thus, these two response strategies are assumed to influence consumers’ attitudes and booking intentions directly as well as indirectly (i.e., through consumer confidence and response efficacy). We, therefore, postulate the following:

Hypothesis 4: During a global pandemic, consumer confidence mediates the effects of a hotel’s crisis communication on consumers’ (a) attitudes and (b) booking intentions.

Hypothesis 5: During a global pandemic, consumer confidence mediates the effects of a hotel’s service delivery on consumers’ (a) attitudes and (b) booking intentions.

Hypothesis 6: During a global pandemic, response efficacy mediates the effects of a hotel’s crisis communication on consumers’ (a) attitudes and (b) booking intentions.

Hypothesis 7: During a global pandemic, response efficacy mediates the effects of a hotel’s service delivery on consumers’ (a) attitudes and (b) booking intentions.

Figure 1 presents the proposed conceptual model guiding this study.

Figure 1.

Conceptual model.

Methodology

An experimental design was adopted to investigate the effects of two preventive measures (i.e., crisis communication and service delivery) on two COVID-19-related coping strategies (i.e., consumer confidence and response efficacy) and to further examine the impacts of three customer-oriented response strategies (i.e., crisis communication, service delivery, and a price discount) on two general outcome variables (i.e., customers’ attitudes and booking intentions). Specifically, a 2 (a price discount: no discount vs. 20% discount) ×2 (crisis communication: no vs. yes) ×2 (service delivery: human service vs. contactless service) between-subjects scenario-based experimental design was used, containing eight experimental conditions. To account for the effects of individual differences on the results and focus on the causal relationships, we controlled for pandemic-related variables (i.e., underlying medical conditions, vulnerability, and severity) and sociodemographic variables (i.e., age, gender, and education level), which were measured as covariates.

Perdue and Summers (1986) suggested that the choice to measure dependent variables before or after assessing manipulation checks can lead to potential issues. If dependent variables are measured first, subjects’ responses to these variables may bias reactions to the manipulation checks (Kidd 1976). As such, to minimize potential bias, we assessed manipulation checks before presenting the main dependent variables. Guided by Perdue and Summers (1986), we also conducted a pre-test and pilot study to assess the designed manipulations before conducting our main study to further lessen response bias.

Pre-test

A pre-test was conducted in October 2020 with 117 respondents (78 men; M_age = 34.85 years) recruited from Amazon Mechanical Turk (MTurk) to assess preliminary manipulation of the three independent variables. Participants were randomly assigned to one of the eight scenarios. The scenarios first asked participants to imagine that they were currently planning a family trip for an upcoming long weekend and needed to book a hotel room. A hypothetical hotel named Joy Hotel was mentioned, and the price discount was manipulated. In the discount condition, participants were told that Joy Hotel was offering 20% off its regular room rate; in the no discount condition, participants were told that Joy Hotel was not offering a discount off its regular room rate (see Supplemental Material). The two levels of crisis communication were manipulated such that Joy Hotel either clearly communicated its COVID-19 preventive measures or provided little information about such measures. Service delivery was manipulated based on either human service or contactless service. The two levels of service delivery were represented by two conditions: either “checking in to the hotel by interacting with a front desk clerk,” or “checking in to the hotel via a self-service kiosk.”

A chi-square test and two independent t-tests were performed to assess the manipulation. As intended, manipulations of the three independent variables were successful. Specifically, in the no discount condition, 63.2% of respondents correctly indicated that Joy Hotel did not provide any discount; in the 20% discount condition, 93.3% correctly recognized the discount (χ²[2] = 44.79, p < .001). Respondents also accurately perceived the distinctions between different levels of crisis communication (M_yes = 5.86, M_no = 4.72, t = 3.79, p = .000) and touch (vs. tech) service (M_{human service} = 3.97, M_{contactless service} = 6.25, t = −6.82, p = .000). Based on the pre-test results, the survey was refined by adding an item to manipulate the hotel’s price discount. To verify the clarity of the stimuli and manipulations, the survey was further tested through a pilot study.

Pilot Study

Following a similar data collection procedure to that in the pre-test, a pilot study was conducted in October 2020 with 230 respondents from MTurk. The number of responses to each scenario ranged from 26 to 30. Again, as expected, results of the manipulation check for a price discount (M_{no discount} = 4.28, M_{20% discount} = 5.66, t = −6.18, p = .000), crisis communication (M_yes = 5.79, M_no = 5.05, t = 3.86, p = .000), and touch–tech service (M_{human service} = 4.53, M_{contactless service} = 5.86, t = −5.48, p = .000) indicated that the manipulations were successful. Both Joy Hotel scenarios were perceived as realistic (M = 5.62, SD = 0.91) and believable (M = 5.74, SD = 0.95). Additionally, respondents indicated they could see themselves assuming the role described in the scenario (M = 5.83, SD = 1.05). Minor modifications to items’ wording, the clarity of stimuli, and manipulation checks were made before carrying out the main study.

Main Study

Data Collection

After the pre-test and pilot study, the main study was performed in November 2020. MTurk was again used to recruit 240 respondents. After reviewing the consent form, participants were asked to read the stimuli carefully and answer manipulation check questions. Subsequently, participants were asked to respond to a series of questions about their assigned scenario. An attention check question was included to assess respondents’ concentration. All questions were presented in a forced-choice format to prevent missing values. Lastly, participants’ demographic information (e.g., gender, age, educational level, and income) was collected.

Measures

All items intended to evaluate the dependent variables were adapted from prior studies and modified slightly to suit the current research context. In particular, four items were adapted from Liu, Pennington-Gray, and Krieger (2016) to assess response efficacy. To measure consumer confidence, three modified items were drawn from De Jonge et al. (2008) and Lassoued and Hobbs (2015). Consumers’ attitudes toward staying at Joy Hotel were assessed using four items from Collier, Moore. A. Horkey, and Moore (2012); consumers’ booking intentions were measured based on three items from Grewal, Monroe, and Krishnan (1998). Given the current COVID-19 situation, underlying medical conditions were taken as a control variable in this study. The CDC (2020) defines underlying medical conditions as those that could increase an individual’s risk of experiencing severe illness upon contracting COVID-19. Furthermore, vulnerability and severity were adopted from Murdock and Rajagopal (2017) as control variables. The realism of each scenario was checked based on three items adapted from Willson and McNamara (1982) and Bradley and Sparks (2009). All constructs were scored on either a semantic differential scale or a 7-point Likert-type scale.

The price discount manipulation was checked by asking participants to respond to two items: “In the scenario, Joy Hotel provides a discount off its regular room rate,” scored on a 7-point Likert-type scale (1 = strongly disagree, 7 = strongly agree); and “How would you describe the price discount described in the scenario?” based on two choices (i.e., no discount or 20% discount). Crisis communication was checked by asking participants to rate the extent to which Joy Hotel clearly communicated its COVID-19 preventive measures, using a 7-point Likert-type scale (1 = strongly disagree, 7 = strongly agree). Similarly, service delivery was checked by asking participants to rate the item “How would you describe your service interaction described in the scenario?” on a 7-point semantic differential scale (1 = interacting with the hotel’s front desk clerk, 7 = interacting with the self-service kiosk).

Results

Surveys from 21 participants were omitted due to incomplete responses or failure to answer the attention check question correctly; 219 responses were retained. Among the sample, 53.7% of participants were men and 46.3% were women. About half (45.8%) were between 20 and 35 years old, followed by 30.9% aged between 36 and 50 and 21% above 50 years old. Nearly all respondents (92.6%) held an associate degree or higher. Roughly three-quarters of respondents (75.9%) earned between $20,000 and $80,000 annually.

Randomization and Manipulation Checks

The number of responses to each scenario ranged from 22 to 29. As Cohen (1988) suggested, a sample requires at least 25 participants per scenario at a power of 0.80 and a significance level of 0.05 with a small-medium effect size (Cohen’s f²: 0.04) (Cohen 1988). All eight scenarios had a sample size of 29, except for one scenario with a sample size of 22. The pre-test and pilot studies established an experimental foundation for the main study; the sample sizes for individual scenarios were therefore deemed to meet requirements. Participants were randomly assigned to one of the eight scenarios and were then asked a series of questions to check whether the scenarios were realistic and whether the manipulation of each treatment was effective. Again, as expected, all three constructs were manipulated effectively. Respondents perceived the hotel’s price discount (M_{no discount} = 3.08, M_{20% discount} = 6.10, t = −12.95, p = .000), crisis communication (M_yes = 6.23, M_no = 3.41, t = 12.67, p = .000), and service delivery (M_{human service} = 2.99, M_{contactless service} = 6.22, t = −12.24, p = .000) as expected. Furthermore, participants found the scenarios realistic (M = 5.71, SD = 1.01) and believable (M = 5.86, SD = 0.95). They could also imagine themselves fulfilling these roles (M = 5.93, SD = 0.98).

Hypothesis Testing

To test our hypotheses, a series of three-way analyses of covariance (ANCOVAs) were conducted to examine the main effect and interaction effect with respondents’ underlying medical conditions, vulnerability, and severity as covariates. The primary purpose of the two- and three-way ANCOVAs was to determine if a significant interaction existed between the two or three independent variables (i.e., crisis communication, service delivery, and a price discount) on each dependent variable (i.e., attitudes or booking intentions). ANCOVA assumptions were verified per Hair et al. (2006). The normality of dependent variables was assessed based on skewness and kurtosis. As shown in Table 3, the values of skewness (Min = −1.20, Max = −0.63) and kurtosis (Min = −0.19, Max = 1.56) showed that the data were normally distributed (Kim 2013). All constructs were reliable with a Cronbach’s α greater than 0.70 (Hair et al. 2006). Next, Levene’s test for homogeneity of variance was conducted; the results revealed a violation of this assumption for consumers’ attitudes (F = 6.01, p < .01) and booking intentions (F = 4.16, p < .01). Residuals were normally distributed as indicated by Q-Q plots. Thus, the ANCOVAs were considered robust to moderate deviation from the assumptions in equal samples (Dattalo 2013).

Table 3.

Measurement Items and Descriptive Statistics of Constructs.

Construct/Item	Mean^a	SD	Skewness	Kurtosis	Cronbach’s α
Response efficacy (Liu, Pennington-Gray, and Krieger 2016)					0.77
There are effective ways to prevent a COVID-19 outbreak at Joy Hotel.	5.32	1.25	−1.08	1.10
There are effective ways to eradicate a COVID-19 outbreak at Joy Hotel.	5.03	1.42	−0.78	0.25
If I take recommended measures, I am less likely to get a COVID-19 infection.	5.51	1.25	−1.16	1.56
Consumer confidence (De Jonge et al. 2008; Lassoued and Hobbs 2015)					0.89
How certain are you about the safety of the Joy Hotel?	4.90	1.53	−0.81	0.06
How optimistic are you with the overall safety of the Joy Hotel you will book in the future?	4.96	1.62	−0.89	0.09
How knowledgeable do you consider yourself about the overall safety of the Joy Hotel?	4.91	1.55	−0.63	−0.18
Attitudes (Collier, Moore. A. Horkey, and Moore 2012)					0.95
Unfavorable/favorable	5.35	1.53	−1.18	−1.18
Unappealing/appealing	5.33	1.52	−0.92	−0.92
Unpleasant/pleasant	5.47	1.50	−1.17	−1.17
Bad/good	5.59	1.52	−1.20	−1.20
Booking intentions (Grewal, Monroe, and Krishnan 1998)					0.95
If I were going to book a hotel, the probability of booking Joy Hotel is. . .	4.83	1.55	−0.87	0.31
The probability that I would consider booking Joy Hotel is. . .	4.86	1.63	−.81	0.16
The likelihood that I would book Joy Hotel is. . .	4.95	1.63	−0.79	0.06
Underlying medical conditions					0.75
I have underlying medical conditions that would increase my risk for severe illness from COVID-19.	3.94	2.15	−0.16	−1.55
My family member(s) has underlying medical conditions that would increase the risk for severe illness from COVID-19.	4.55	2.05	−0.55	−1.12
Vulnerability (Murdock and Rajagopal 2017)					0.76
How concerned are you about getting COVID-19?	4.94	1.86	−0.77	−0.51
How likely do you think it is that you will get COVID-19?	4.31	1.80	−0.21	−0.85
How likely do you think it is that staying at hotels will give you COVID-19?	4.42	1.78	−0.33	−0.85
Severity (Murdock and Rajagopal 2017)					0.93
I believe that COVID-19 is severe.	5.48	1.51	−1.08	0.62
I believe that COVID-19 is serious.	5.71	1.41	−1.41	2.00
I believe that COVID-19 is significant.	5.67	1.39	−1.23	1.43

Note. ^aMeasured on a 7-point Likert-type scale (either 1 = strongly disagree, 7 = strongly agree; or 1 = very low, 7 = very high).

In addition, to control the effects of pandemic-related variables on consumers’ attitudes and booking intentions, we tested the hypothesized model with pandemic-related control variables (i.e., underlying health conditions, vulnerability, and severity). Results showed that the covariates of severity (F = 0.12, p > .05), underlying health conditions (F = 0.08, p > .05), and vulnerability (F = 0.09, p > .05) were not significant in predicting consumers’ attitudes. Similarly, when predicting consumers’ booking intentions, the covariates of severity (F = 2.14, p > .05), underlying health conditions (F = 1.03, p > .05), and vulnerability (F = 0.87, p > .05) were not significant.

We also controlled the effects of sociodemographic variables on the general outcome variables of consumers’ attitudes and booking intentions. Accordingly, we tested the hypothesized model with control variables including age, gender, and education level. The covariates of age (F = 0.56, p > .05), gender (F = 0.08, p > .05), and education level (F = 0.45, p > .05) were not significant in predicting consumers’ attitudes. In the same vein, when predicting consumers’ booking intentions, the covariates of age (F = 1.91, p > .05), gender (F = 2.62, p > .05), and education level (F = 1.42, p > .05) were not significant.

Effects of Hotel’s Crisis Communication and Service Delivery on Consumer Confidence and Response Efficacy

Results revealed that consumer confidence [M_yes = 5.43, M_no = 4.39, F(1, 211) = 33.61, p = .00] was significantly higher in the crisis communication condition than in the no crisis communication condition, supporting H1a (see Table 4). Consumer confidence [M_{human service} = 5.14, M_{contactless service} = 4.73, F(1, 211) = 5.14, p = .02] was found to be significantly higher in the contactless service delivery condition compared with the human service condition, providing support for H2a. In addition, response efficacy [M_yes = 5.51, M_no = 5.05, F(1, 211) = 9.95, p = .00] was significantly higher in the crisis communication condition than in the no crisis communication condition, substantiating H1b. However, response efficacy was not significantly different between the two crisis communication conditions [F(1,211) = 2.43, p = .12]; H2b was therefore not supported.

Table 4.

Results of ANCOVA.

Hypothesis	Response Strategy	Dependent Variable	Type III SS	df	F	p	Conclusion
H1a	Crisis communication	Consumer confidence	57.27	1	33.61	.00	Supported
H1b		Response efficacy	11.1	1	9.95	.00	Supported
H1c		Attitudes	52.77	1	29.97	.00	Supported
H1d		Booking intentions	52.87	1	25.95	.00	Supported
H2a	Service delivery	Consumer confidence	8.75	1	5.14	.02	Supported
H2b		Response efficacy	2.71	1	2.43	.12	Rejected
H2c		Attitudes	1.07	1	0.61	.43	Rejected
H2d		Booking intentions	6.71	1	3.29	.07	Rejected
H3a	Price discount	Attitudes	8.06	1	4.57	.03	Supported
H3b		Booking intentions	9.44	1	4.63	.03	Supported

Effects of Hotel’s Responses on Consumers’ Attitudes

The ANCOVAs showed significant main effects of a price discount [M_{no discount} = 5.65, M_{20% discount} = 5.25, F(1,211) = 4.57, p = .03] and crisis communication [M_yes = 5.95, M_no = 4.93, F(1,211) = 29.97, p = .00] on customers’ attitudes. Specifically, attitude scores were higher in the 20% discount condition than in the no discount condition. These scores were also higher in the crisis-communication condition compared with the no crisis communication condition. As such, H1c and H3a were supported. However, no main effect was identified for service delivery (p = .43) on attitudes, leading H2c to be rejected. Furthermore, a follow-up simple main effect analysis was conducted to decompose significant two- and three-way interactions. However, no two-way interaction (F_{discount*communication} = 0.11, p = .74; F_{discount*service} = 0.02, p = .90; F_{communication*service} = 2.51, p = .12) or three-way interaction (F_{discount*communication*service} = 0.46, p = .50) was observed. Thus, univariate tests revealed insignificant effects of interactions between the two and three independent variables on consumers’ attitudes.

Effects of Hotel’s Responses on Consumers’ Booking Intentions

A significant main effect was associated with a price discount [M_{no discount} = 4.68, M_{20% discount} = 5.09, F(1,211) = 4.63, p = .03] and crisis communication [M_yes = 5.37, M_no = 4.36, F(1,211) = 25.95, p = .00] on booking intentions. In particular, scores on booking intention were higher in the 20% discount and crisis communication conditions than in the no discount and no crisis communication conditions. H1d and H3b were accordingly supported. No main effect was observed for service delivery (p = .07), failing to support H2d. No two-way interaction (F_{discount*communication} = 0.03, p = .86; F_{discount*service} = 0.67, p = .41; F_{communication*service} = 1.72, p = .19) or three-way interaction (F_{discount*communication*service} = 0.29, p = .59) was identified either. Accordingly, univariate tests demonstrated insignificant effects of interactions between the two or three independent variables on consumers’ booking intentions.

Mediation Analysis

To test the mediation role of consumer confidence, Hayes (2013) PROCESS Model 4 with bootstrapping with 5,000 samples was used. Bootstrapping results indicated that consumer confidence fully mediated the effect of crisis communication on attitudes (b = 0.75, 95% bootstrap interval: 0.35, 0.71) and booking intention (b = 0.96, 95% bootstrap interval: 0.43, 0.84), lending support to H4. Following the same analysis procedure, bootstrapping results revealed that consumer confidence fully mediated the effect of service delivery on attitudes (b = 0.31, 95% bootstrap interval: 0.05, 0.61) and booking intention (b = 0.38, 95% bootstrap interval: 0.04, 0.73), supporting H5.

The mediation role of response efficacy was also examined using PROCESS Model 4. Bootstrapping results showed that response efficacy partially mediated the effect of crisis communication on attitudes (b = 0.33, 95% bootstrap interval: 0.12, 0.57) and on booking intention (b = 0.38, 95% bootstrap interval: 0.15, 0.64), providing support for H6. In addition, response efficacy did not mediate the effect of service delivery on attitudes (b = 0.18, 95% bootstrap interval: −0.04, 0.42) or booking intention (b = 0.20, 95% bootstrap interval: −0.04, 0.47), causing H7 to be rejected. In sum, Hypotheses 1, 2a, 3, 4, 5, and 6 were supported whereas Hypotheses 2b, 2c, 2d, and 7 were not.

Discussion

The purpose of Study 2 was to empirically test the impacts of hotels’ COVID-19 response strategies on consumer confidence and response efficacy, which can in turn affect consumers’ attitudes and booking intentions. Our findings demonstrated that delivering effective crisis communication and providing contactless service can enhance consumers’ confidence in a hotel, leading to more positive attitudes and booking intentions. This study indicated that consumer confidence mediated the effects of crisis communication and service delivery on consumers’ attitudes and booking intentions. The mediation role of response efficacy between crisis communication and consumers’ attitudes as well as booking intentions was also supported. Furthermore, a price discount and crisis communication were found to influence consumers’ attitudes and booking intentions directly.

General Discussion

The COVID-19 outbreak has had unprecedented impacts on the tourism ecosystem, and it will likely take the hotel industry several years to mitigate the pandemic’s disastrous consequences. In the face of this crisis, hotels have proactively launched a range of initiatives intended to minimize adverse effects on their businesses. Although COVID-19-related studies have focused on the pandemic’s impacts on the tourism industry from multiple perspectives, such as those of employees (Shin et al. 2021) and consumers (Zhang, Hou, and Li 2020), little attention has been paid to the typology of the hotel industry’s response strategies. Furthermore, empirical investigations regarding the effectiveness of holistic industry response strategies on consumer confidence, response efficacy, and resultant positive attitudes and booking intentions among consumers remain scant.

Our multistage, multi-method approach, guided by the work of Venkatesh et al. (2013), is unique from previous research in comprehensively addressing an urgent concern in tourism. Using a hybrid approach (Fereday and Muir-Cochrane 2006) coupled with cross-validation from 22 managerial experts, Study 1 suggested five dominant response strategies: (1) revenue management, (2) crisis communication, (3) alternative approaches to service delivery, (4) human resource management, and (5) CSR. More importantly, the findings from Study 1 highlighted revenue management, crisis communication, and alternative approaches to service delivery as common customer-oriented response strategies in the hotel industry. Specifically, during the pandemic, some hotels transformed their rooms into quarantine spaces to raise cash flow and boost total revenue. Additionally, to cope with this challenging time, some hotels have continued communicating with guests about their COVID-19 response efforts via multiple online channels. Given the highly contagious nature of COVID-19, some hotels have implemented contactless service from check-in to check-out, providing a seamless and safe experience. Such findings on these measures are consistent with previous studies (e.g., Möller, Wang, and Nguyen 2018; Ritchie and Jiang 2019), thus reinforcing the roles of pricing strategies, external communication with consumers, and contactless service delivery in bolstering business during the pandemic.

In addition to the three aforementioned customer-oriented strategies, some hotels have adopted CSR and human resource management strategies as part of their operations to ensure quality service provision. Despite devastating economic losses in the tourism industry, some hotels have donated and offered free hotel rooms to essential frontline workers with the aim of giving back to the community. CSR initiatives can boost firm value and business performance from a resource-based perspective. However, prior research (e.g., Shin et al. 2021) has also suggested potentially negative impacts of hotel CSR on firms’ market value and consumers’ booking behavior during COVID-19; hotel guests are likely to be highly sensitive to safety issues and less apt to visit a hotel if they perceive notable health-related risks (Shin and Kang 2020). In addition to CSR, human resource management has surfaced as a way to effectively adjust a hotel’s organizational structure and human resource capacity from an operational standpoint. In sum, our thorough typology of response strategies can decrease the perceived complexity of this phenomenon and clarify coherence between the literature and industry practices.

In Study 2, we expanded upon the findings from Study 1 and protection motivation theory (Roger 1975) by conducting an experiment that empirically examined the effectiveness of the customer-orientated response strategies. The findings from Study 2 suggested that reassuring crisis communications and price discounts directly affect consumers’ attitudes and booking intentions. The classical economy theories (e.g., Marshall 1920) explained the law of demand by suggesting that a lower price is associated with a higher quantity of demand; however, some research has shown that price discounts do not encourage booking intentions and may even negatively affect hotels through low overall evaluations (Aaker 1996; Nusair et al. 2010), and that excessive price discounts can diminish consumers’ brand preferences and quality perceptions because deeper price cuts are tied to lower overall hotel quality (e.g., Nusair et al. 2010). Therefore, this study expands our current understanding of price discounts and consumer responses when both demand and supply are low during a public health crisis, suggesting that an appropriate level of price discounts can elicit positive consumer attitudes and behavioral intentions during the current pandemic.

Additionally, Study 2 suggested that strategic crisis communication can generate consumer confidence and response efficacy, whereas contactless service only influences consumer confidence. Contactless service enables physical distancing, which appears crucial to limiting the spread of COVID-19. However, the method of service delivery (i.e., contactless or human-delivered service) did not appear to alter potential travelers’ response efficacy, attitudes, or booking intentions regarding hotels in this study. Our findings are largely consistent with previous research (e.g., Shin and Kang 2020) in that there was no significant direct effect of high interactions with technological tools (e.g., mobile or kisosk check-in systems) on hotel booking intentions. Considering the transmissibility of COVID-19, staying at a hotel is no longer simply an accommodation decision but a health concern. Contactless service can reduce viral spread by limiting social interaction and enabling social distancing. A global pandemic poses a severe threat to people’s health, triggering a protection motivation likely to change individuals’ consumption and health behavior. Although scholars have emphasized the role of contactless service in enhancing consumers’ positive attitudes (Shin and Kang 2020) along with response efficacy and purchase intentions (Wang et al. 2013), researchers did not previously consider a pandemic that would prevent many potential guests from staying at hotels. We included key covariates, such as sociodemographic variables (i.e., age, gender, and education level) and pandemic-related variables (i.e., underlying health conditions, vulnerability, and severity), to minimize individual differences and focus on the causal relationships. As such, our findings demonstrated the impact of contactless service on consumer confidence.

Theoretical contributions

Ritchie’s (2004) crisis response typology and adopting a sequential research design, our research offers several theoretical contributions. First, we contribute to devising a typology of crisis response strategies for the hotel industry based on deductive and inductive thematic analyses of 4,211 news articles, cross-validated by managerial experts. Findings have extended the body of knowledge on crisis response strategies (Faulkner 2001; Hystad and Keller 2008; Ritchie 2004) by investigating a global health crisis and uncovering themes, including alternative approaches to service delivery and CSR, that exemplify the hotel industry’s preferred pandemic response strategies. These results could bridge the gap between academic insight and industry practices with respect to effective response strategies. The established typology can also be applied in similar circumstances to examine hotels’ and consumers’ responses, shedding light on how to enhance hotel management decisions in times of crisis.

Second, combining data from three sources (i.e., news articles, an expert panel review, and online consumer panel data), this study is one of the first empirical attempts to systematically examine the hotel industry’s responses to COVID-19. Specifically, the effects of price discounts on attitudes and booking intentions were examined amid a pandemic during which travel poses substantial risks. Our work expands current understanding of price discounts and consumer responses when demand and supply are both low during a health crisis; in essence, an appropriate level of price discounts could elicit positive consumers’ attitudes and behavioral intentions during COVID-19. The impacts of price discounts have been widely studied in general. However, this study provides a theoretical foundation from which to extend knowledge of the use of this tactic for crisis management in the tourism industry.

In addition, this study provides a deeper understanding of coping strategies (i.e., consumer confidence and response efficacy) by examining the roles of crisis communication and coping strategies in underlying psychological processes of human behavior during a global pandemic. Furthermore, this study has pointed out the need for tourism service providers to offer thorough information about their COVID-19 preventive measures along with clear instructions for consumers to ensure a safe experience. These findings align with earlier research (Cahyanto et al. 2016; Ritchie and Jiang 2019), reflecting and validating the importance of crisis communication during a global pandemic.

Lastly, consistent with protection motivation theory (Roger 1975), this study’s findings provide meaningful insight into the psychological processes underlying human behavior amid a pandemic. In line with previous literature (e.g., Wang et al. 2019), coping appraisal can influence positive consumers’ attitudes and behavioral intentions. Our results demonstrate that response efficacy can partially mediate the effects of hotels’ crisis communication on consumers’ attitudes and booking intentions, respectively. Additionally, consumer confidence appears to partially mediate the impacts of crisis communication and service delivery on consumer outcomes. Specifically, in addition to direct effects, crisis communication and service delivery have indirect effects on outcome variables through consumer confidence. Thus, our study contributes to the literature by showcasing consumer confidence as a mediator and emphasizing its importance during pandemics. Given the highly contagious and unprecedented nature of COVID-19, the findings of this study contribute to the tourism literature by highlighting the significance of providing reassuring communication, adopting contactless service, and offering prices discounts during the pandemic.

Managerial contributions

To survive the COVID-19 pandemic, tourism operators such as hotels must adopt new strategies and practices to maintain their businesses. Thus, our findings have practical implications for the hotel industry. The conceptual framework applied in this research provides a useful response typology during a pandemic by highlighting five main response strategy themes that hotels can follow during and after COVID-19. Based on the findings of Study 1, hotels should follow stringent safety and sanitation protocols and obtain hygiene certifications from the government as evidence of their ability to protect consumers. Notably, CSR has emerged as an important initiative which previous crisis management frameworks (e.g., Hystad and Keller 2008; Ritchie 2004) did not fully capture. The hotel industry is often considered at the forefront of implementing CSR practices to increase its positive influences on society while minimizing its negative impacts. Amid COVID-19, CSR initiatives are particularly appreciated by consumers, helping a hotel brand to further enhance its reputation and gain publicity. Thus, hotels should support the local community. In the long term, CSR may help hotels construct a positive image and promote firm–consumer emotional attachment.

The results of Studies 1 and 2 consistently point to price discounts as a primary survival strategy for hotels. The breakdown of tourism across the globe in the wake of COVID-19 has pushed the tourism industry to implement price adjustments, with the hotel sector being the most fervent adopter of this trend. Although larger hotels can implement better revenue management with lower costs compared to smaller hotels due to economies of scale (Xu et al. 2019), small- and mid-sized hotels also use discounts. Higher dynamic price variability contributes to greater cash flows and revenue for relatively smaller hotels in times of crisis (Abrate, Nicolau, and Viglia 2019; Guizzardi, Pons, and Ranieri 2017). According to data from the National Statistics Institute (CaixaBank Research, 2021), hotels’ price per room per day in the summer of 2020 was 16% lower than in the prior year. However, the actual effects of price discounts during the pandemic remain unclear because historical demand patterns are no longer relevant. The expert panel review in Study 1 validated the importance of price discounts, showing high applicability during the pandemic regardless of hotel sizes (e.g., large, medium, or small) and service types (e.g., full or limited service). More importantly, 2020 was a year during which both demand and supply were low. On one hand, tourist demand fell sharply; on the other hand, severe restrictions were imposed on hotel capacity, which severely constrained the number of available rooms. Our findings mirror the response phase in that several hotels have recently striven to adjust room rates to reflect real-time market conditions and maximize revenue.

This study also provides compelling evidence of the effectiveness of hotels’ crisis communication in fostering consumers’ safety perceptions amid COVID-19. Messages distributed through multiple channels can include normative appeals and meanings that can positively shape consumers’ beliefs about the appropriateness and effectiveness of coping strategies to manage threats, ultimately influencing consumers’ decisions. Therefore, in addition to following CDC safety guidelines, hotels could leverage channels such as social media, hotel’s own websites, and other third-party websites to publicize their preventative measures against COVID-19. In particular, with the growing usage of social media platforms, hotel managers could proactively utilize different types of social media—live streams (e.g., Instagram Live and Facebook Live), video social media (e.g., YouTube and Vimeo), and social audio providers (e.g., Clubhouse and Spotify)—to expedite the seamless exchange of information and reframe their crisis management by positioning themselves as safe, secure, and reliable accommodations. Hoteliers should also communicate with guests before and during stays to keep consumers apprised of the hotel’s prevention plans.

Moreover, our study found that self-service kiosks (vs. employee-delivered services) can greatly affect consumer confidence during a crisis. Contactless service delivery is highly recommended in the service sector to maintain physical distancing and promote consumer confidence. While contactless service delivery has been implemented by many hotels, restaurants, and even grocery stores, it is unclear how such response strategies may affect consumer confidence. The findings from this study provide empirical evidence for the important role of contactless service delivery in promoting consumer confidence during the COVID-19 pandemic. Based on such findings, hotels managers could arrange “zero-touch” floors. On these floors, consumers are encouraged to use self-service such as requesting service robot for room service, using mobile applications to control doors, lights, televisions, and air conditioning. Such practices would enhance consumers’ confidence toward the hotel safety during the pandemic. However, hotels must be cautious when allocating contactless service across service touch points: these allocations may shape consumers’ attitudes and booking intentions during pandemics and other crises. Furthermore, this study has pointed out the need for tourism service providers to offer thorough information about their COVID-19 preventive measures along with clear instructions for consumers to ensure a safe experience.

Limitations and Future Research

Despite its meaningful findings, several limitations of this study provide opportunities for future research. First, based on the various revenue management strategies observed in Study 1, future research should explore whether other strategies (e.g., extending consumers’ membership status and points) affect consumers’ subsequent behavior. Furthermore, CSR was noted as a key response strategy category in Study 1. Implementing CSR initiatives is more crucial for the hotel industry than the other industries that deliver tangible goods as hotel service quality is more difficult to assess due to its nature of intangibility. Scholars could thus explore the effects of CSR on consumers’ loyalty, perceived value, and attitudes toward tourism firms depending on specific CSR practices (e.g., donations and providing free hotel rooms to frontline workers) from a long-term perspective.

In addition, this work was conducted using a scenario-based survey, which may limit the generalizability of our findings to the real world. Thus, future research could involve field studies to investigate consumers’ real-time feelings and attitudes toward hotels amid a pandemic. Research has suggested that service robots and artificial intelligence play important roles in the tourism sector’s responses to the pandemic (Gursoy and Chi 2020; Jiang and Wen 2020). Although this study provides evidence that contactless service contributes to consumer confidence, subsequent research should investigate whether different technological innovations (e.g., service robots and artificial intelligence) or service encounters (e.g., front desk, concierge, and room service) influence the relationships between service delivery and response efficacy relative to consumers’ attitudes and booking intentions. Lastly, we took behavioral intentions as a proxy of travel behavior; future studies should investigate actual travel behavior to supplement our findings.

Supplemental Material

sj-pdf-1-jtr-10.1177_00472875221095211 – Supplemental material for Enhancing Consumer Confidence and Response Efficacy in Tourism: Typology and Effectiveness of the Hotel Industry’s Responses to COVID-19

Supplemental material, sj-pdf-1-jtr-10.1177_00472875221095211 for Enhancing Consumer Confidence and Response Efficacy in Tourism: Typology and Effectiveness of the Hotel Industry’s Responses to COVID-19 by Hyunsu Kim, Jing Li and Kevin Kam Fung So in Journal of Travel Research

Footnotes

Acknowledgements

This research was conducted when the first author was a Ph.D. Candidate at the College of Hospitality, Retail and Sport Management, University of South Carolina.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs

Hyunsu Kim

Jing Li

Kevin Kam Fung So

Supplemental Material

Supplemental material for this article is available online.

Author Biographies

Hyunsu Kim, Ph.D., is Assistant Professor in the Department of Management, Mihaylo College of Business and Economics, California State University, Fullerton, USA. His research interests focus on service management and services marketing, with an emphasis on customer experience, customer engagement, and service and technological innovations in hospitality and tourism.

Jing Li, Ph.D., is Assistant Professor in the Department of Hospitality and Retail Management at Texas Tech University. She earned her Ph.D. from the University of South Carolina. Her research focuses on customer experience, sharing economy, and service marketing.

Kevin Kam Fung So, Ph.D., is William E. Davis Professor and Associate Professor at the School of Hospitality and Tourism Management, Spears School of Business, Oklahoma State University, USA. His research interests focus on services marketing, service management, and applications of advanced quantitative methods and analytical techniques. The majority of his research articles have appeared in the discipline’s top-tier journals. He serves on the editorial boards for 10 journals including Journal of Travel Research, Tourism Management, International Journal of Hospitality Management, Journal of Hospitality & Tourism Research, Cornell Hospitality Quarterly, and International Journal of Contemporary Hospitality Management.

References

Aaker

D. A.

1996. Building Strong Brands. New York: The Free Press.

Abrate

Nicolau

J. L.

Viglia

2019. ‘The Impact of Dynamic Price Variability on Revenue Maximization.” Tourism Management 74:224–33.

AHLA. 2020a. “COVID-19’s Impact on the Hotel Industry.” Last modified January 30. https://www.ahla.com/covid-19s-impact-hotel-industry.

AHLA. 2020b. “Who We Are.” Last modified January 30. https://www.ahla.com/who-we-are.

Aljazeera. 2020. “Coronavirus: Travel Restrictions, Border Shutdowns by Country.” Last modified January 30. https://www.aljazeera.com/news/2020/6/3/coronavirus-travel-restrictions-border-shutdowns-by-country.

Basil

Deshpande

Lavack

A. M.

2013. “Applying the Extended Parallel Process Model to Workplace Safety Messages.” Health Communication 28 (1): 29–39.

Bausch

Gartner

W. C.

Ortanderl

2021. “How to Avoid a COVID-19 Research Paper Tsunami? A Tourism System Approach.” Journal of Travel Research 60 (3): 467–85. doi:10.1177/0047287520972805

Benoit

W. L.

1997. “Image Repair Discourse and Crisis Communication.” Public Relations Review 23 (2): 177–86.

Bradley

G. L.

Sparks

B. A.

2009. “Dealing With Service Failures: The Use of Explanations.” Journal of Travel & Tourism Marketing 26 (2): 129–43.

10.

Bazeley

Richards

2000. The NVivo Qualitative Project Book. Thousand Oaks: Sage Publications.

11.

Bandura

1997. Self-efficacy: The Exercise of Control. New York: W. H. Freeman and Company.

12.

Cohen

1988. Statistical Power Analysis for the Behavioral Sciences. Hillsdale: Lawrence Erlbaum Associates.

13.

CaixaBank Research (2021). “Cut-price Tourism: The Role Played by Hotel Rate Adjustments in the Recovery.” Last modified January 30. https://www.caixabankresearch.com/en/sector-analysis/tourism/cut-price-tourism-role-played-hotel-rate-adjustments-recovery#:~:text=According%20to%20data%20from%20the,reviving%20demand%20in%20some%20regions.

14.

Cahyanto

Pennington-Gray

Thapa

Srinivasan

Villegas

Matyas

Kiousis

2016. “Predicting Information Seeking Regarding Hurricane Evacuation in the Destination” Tourism Management 52:264–75.

15.

Collier

J. E.

Moore

Horkey

Moore

2012. “Situational Variables and Attitudes Toward Self-Service Technology Choice: A Qualitative–Quantitative Approach.” Society for Marketing Advances 50:150–1.

16.

Coombs

W. T.

2007. “Protecting Organization Reputations During a Crisis: The Development and Application of Situational Crisis Communication Theory.” Corporate Reputation Review 10 (3): 163–76.

17.

Cross

R. G.

2011. Revenue Management: Hard-Core Tactics for Market Domination. New York, NY: Currency.

18.

Cross

R. G.

Higbie

J. A.

Cross

D. Q.

2009. “Revenue Management's Renaissance: A Rebirth of the Art and Science of Profitable Revenue Generation.” Cornell Hospitality Quarterly 50 (1): 56–81.

19.

Creswell

J. W.

Miller

D. L.

. 2000. “Determining Validity in Qualitative Inquiry.” Theory into Practice 39 (3): 124–30.

20.

CDC. 2020. Underlying Medical Conditions Associated with Higher Risk for Severe COVID-19: Information for Healthcare Professionals. Last modified January 30. https://www.cdc.gov/coronavirus/2019-ncov/hcp/clinical-care/underlyingconditions.html.

21.

Dattalo

2013. Analysis of Multiple Dependent Variables. New York, NY: Oxford University Press.

22.

De Jonge

Van Trijp

Goddard

Frewer

2008. “Consumer Confidence in the Safety of Food in Canada and the Netherlands: The Validation of a Generic Framework.” Food Quality and Preference 19 (5): 439–51.

23.

Bhattacharya

C. B.

Sen

2011. “Corporate Social Responsibility and Competitive Advantage: Overcoming the Trust Barrier.” 57 (9): 1528–45.

24.

Elo

Kyngäs

2008. “The Qualitative Content Analysis Process.” Journal of Advanced Nursing 62 (1): 107–15.

25.

Faulkner

2001. “Towards a Framework for Tourism Disaster Management.” Tourism Management 22 (2): 135–47.

26.

Fiss

P. C.

2011. “Building Better Causal Theories: A Fuzzy Set Approach to Typologies in Organization Research.” Academy of Management Journal 54 (2): 393–420.

27.

Fereday

Muir-Cochrane

2006. “Demonstrating Rigor Using Thematic Analysis: A Hybrid Approach of Inductive and Deductive Coding and Theme Development.” International Journal of Qualitative Methods 5 (1): 80–92.

28.

Floyd

D. L.

Prentice-Dunn

Rogers

R. W.

2000. “A Meta-Analysis of Research on Protection Motivation Theory.” Journal of Applied Social Psychology 30 (2): 407–29.

29.

Guizzardi

Pons

F. M. E.

Ranieri

2017. “Advance Booking and Hotel Price Variability Online: Any Opportunity for Business Customers?” International Journal of Hospitality Management 64:85–93.

30.

Gallarza

M. G.

Arteaga

Del Chiappa

Gil-Saura

Holbrook

M. B.

2017. “A Multidimensional Service-Value Scale Based on Holbrook’s Typology of Customer Value: Bridging the Gap Between the Concept and Its Measurement” Journal of Service Management 28 (4): 724–62.

31.

Glaser

B. G.

Strauss

A. L.

1967. The Discovery of Grounded Theory: Strategies for Qualitative Research. New Brunswick: Aldine Transaction.

32.

Grewal

Monroe

K. B.

Krishnan

1998. “The Effects of Price-Comparison Advertising on Buyers’ Perceptions of Acquisition Value, Transaction Value, and Behavioral Intentions.” Journal of Marketing 62 (2): 46–59.

33.

Guillet

Chu

A. M. C.

2021. “Managing Hotel Revenue Amid the COVID-19 Crisis.” International Journal of Contemporary Hospitality Management 33 (2): 604–27. Published online January, 6. doi:10.1108/IJCHM-06-2020-0623

34.

Gursoy

Chi

C. G.

2020. “Effects of COVID-19 Pandemic on Hospitality Industry: Review of the Current Situations and a Research Agenda.” Journal of Hospitality Marketing & Management 20 (5): 527–9.

35.

Hair

J. F.

Black

W. C.

Babin

B. K.

Anderson

R. E.

Tatham

R. L.

2006. Multivariate Data Analysis. vol. 6. Upper Saddle River, NJ: Pearson Prentice Hall.

36.

Hall

2020. “What COVID-19 Reveals about the Value of Media Globally.” Last modified January 30. https://www.weforum.org/agenda/2020/04/covid-19-media-value/.

37.

Hao

Xiao

Chon

2020. “COVID-19 and China’s Hotel Industry: Impacts, a Disaster Management Framework, and Post-Pandemic Agenda.” International Journal of Hospitality Management 20:102636. Published online August, 5. doi:10.1016/j.ijhm.2020.102636

38.

Harrison

2020. “Council Post: Five Ways Hotels Can Build Guest Relationships during the Global Crisis.” Last modified January 30. https://www.forbes.com/sites/forbesagencycouncil/2020/05/08/five-ways-hotels-can-build-guest-relationships-during-the-global-crisis/.

39.

Hystad

P. W.

Keller

P. C.

2008. “Towards a Destination Tourism Disaster Management Framework: Long-Term Lessons From a Forest Fire Disaster.” Tourism Management 29 (1): 151–62.

40.

Jiang

Wen

2020. “Effects of COVID-19 on Hotel Marketing and Management: A Perspective Article.” International Journal of Contemporary Hospitality Management 32 (8): 2563–73.

41.

Jones

2020. “Three Industries that are Being Decimated by the Coronavirus.” Last modified January 30. https://www.forbes.com/sites/chuckjones/2020/03/28/three-industries-that-are-being-decimated-by-the-coronavirus/.

42.

Kim

H. Y.

2013. “Statistical Notes for Clinical Researchers: Assessing Normal Distribution (2) Using Skewness and Kurtosis.” Restorative Dentistry & Endodontics 38 (1): 52–4.

43.

Kim

Rahman

Bernard

2020. “Comparing Online Reviews of Hyper-Local Restaurants Using Deductive Content Analysis.” International Journal of Hospitality Management 86. Published online December 19. doi:10.1016/j.ijhm.2019.102445

44.

Kidd

R. F.

1976. “Manipulation Checks: Advantage or Disadvantage?” Representative Research in Social Psychology 7 (2): 160–65.

45.

Lassoued

Hobbs

J. E.

2015. “Consumer Confidence in Credence Attributes: The Role of Brand Trust.” Food Policy 52:99–107.

46.

Phi

2021. “Strategic Responses of the Hotel Sector to COVID-19: Toward a Refined Pandemic Crisis Management Framework.” International Journal of Hospitality Management 94: 102808. doi: 10.1016/j.ijhm.2020.102808.

47.

Liu

Pennington-Gray

Krieger

2016. “Tourism Crisis Management: Can the Extended Parallel Process Model Be Used to Understand Crisis Responses in the Cruise Industry?” Tourism Management 55:310–21.

48.

Liu-Lastres

Schroeder

Pennington-Gray

2019. “Cruise Line Customers’ Responses to Risk and Crisis Communication Messages: An Application of the Risk Perception Attitude Framework.” Journal of Travel Research 58 (5): 849–65.

49.

Liu

Pennington-Gray

2015. “Bed Bugs Bite the Hospitality Industry? A Framing Analysis of Bed Bug News Coverage.” Tourism Management 48:33–42.

50.

Marshall

1920. Principles of Economics. 8th ed. London: Macmillan.

51.

Matthes

Kohring

2008. “The Content Analysis of Media Frames: Toward Improving Reliability and Validity.” Journal of Communication 58 (2): 258–79.

52.

Milne

Sheeran

Orbell

2000. “Prediction and Intervention in Health-Related Behavior: A Meta-Analytic Review of Protection Motivation Theory.” Journal of Applied Social Psychology 30 (1): 106–43.

53.

Moeller

Ciuchita

Mahr

Odekerken-Schröder

Fassnacht

2013. “Uncovering Collaborative Value Creation Patterns and Establishing Corresponding Customer Roles.” Journal of Service Research 16 (4): 471–87.

54.

Möller

Wang

Nguyen

H. T.

2018. “# Strongerthanwinston: Tourism and Crisis Communication Through Facebook Following Tropical Cyclones in Fiji.” Tourism Management 69:272–84.

55.

Murdock

M. R.

Rajagopal

2017. “The Sting of Social: How Emphasizing Social Consequences in Warning Messages Influences Perceptions of Risk.” Journal of Marketing 81 (2): 83–98.

56.

Narasimhan

1984. “A Price Discrimination Theory of Coupons.” Marketing Science 3 (2): 128–47.

57.

Nusair

Yoon

H. J.

Naipaul

Parsa

H. G.

2010. “Effect of Price Discount Frames and Levels on Consumers’ Perceptions in Low End Service Industries.” International Journal of Contemporary Hospitality Management 22 (6): 814–35.

58.

Page

Song

D. C.

2012. “Assessing the Impacts of the Global Economic Crisis and Swine Flu on Inbound Tourism Demand in the United Kingdom.” Journal of Travel Research 51 (2): 142–53.

59.

Paraskevas

Arendell

2007. “A Strategic Framework for Terrorism Prevention and Mitigation in Tourism Destinations.” Tourism Management 28 (6): 1560–73.

60.

Paraskevas

Quek

2019. “When Castro Seized the Hilton: Risk and Crisis Management Lessons From the Past.” Tourism Management 70:419–29.

61.

Pauchant

T. C.

Mitroff

1992. Transforming the Crisis-Prone Organization: Preventing Individual, Organizational, and Environmental Tragedies. San Francisco: Jossey-Bass Inc.

62.

Perez

Paranhos

2020. “Hotels Enhance Cleaning Protocols in Light of COVID-19.” Last modified January 30. https://www.hotelnewsnow.com/articles/302702/Hotels-enhance-cleaning-protocols-in-light-of-COVID-19.

63.

Perdue

B. C.

J. O. Summers . 1986. “Checking the Success of Manipulations in Marketing Experiments.” Journal of Marketing Research 23 (4): 317–326.

64.

Rimal

R. N.

Real

2003. “Perceived Risk and Efficacy Beliefs as Motivators of Change: Use of the Risk Perception Attitude (RPA) Framework to Understand Health Behaviors.” Human Communication Research 29 (3): 370–99.

65.

Ritchie

B. W.

2004. “Chaos, Crises and Disasters: A Strategic Approach to Crisis Management in the Tourism Industry.” Tourism Management 25 (6): 669–83.

66.

Ritchie

B. W.

Jiang

2019. “A Review of Research on Tourism Risk, Crisis and Disaster Management: Launching the Annals of Tourism Research Curated Collection on Tourism Risk, Crisis and Disaster Management.” Annals of Tourism Research 79. Published online November 1. doi:10.1016/j.annals.2019.102812

67.

Rolfe

2006. “Validity, Trustworthiness and Rigour: Quality and the Idea of Qualitative Research.” Journal of Advanced Nursing 53:304–10.

68.

Rogers

R. W.

1975. “A Protection Motivation Theory of Fear Appeals and Attitude change1.” The Journal of Psychology 91 (1): 93–114.

69.

Rust

R. T.

Espinoza

2006. “How Technology Advances Influence Business Research and Marketing Strategy.” Journal of Business Research 59 (10–11): 1072–78.

70.

Sapp

S. G.

Downing-Matibag

2009. “Consumer Acceptance of Food Irradiation: A Test of the Recreancy Theorem.” International Journal of Consumer Studies 33 (4): 417–24.

71.

Shin

Kang

2020. “Reducing Perceived Health Risk to Attract Hotel Customers in the COVID-19 Pandemic Era: Focused on Technology Innovation for Social Distancing and Cleanliness.” International Journal of Hospitality Management 91:102664. Published online September 7. doi:10.1016/j.ijhm.2020.102664

72.

Shin

Sharma

Nicolau

J. L.

Kang

2021. “The Impact of Hotel CSR for Strategic Philanthropy on Booking Behavior and Hotel Performance During the COVID-19 Pandemic.” Tourism Management 85:104322. Published online March 21. doi:10.1016/j.tourman.2021.104322

73.

Spiggle

1994. “Analysis and Interpretation of Qualitative Data in Consumer Research.” Journal of Consumer Research 21 (3): 491–503.

74.

Sparks

B. A.

Bradley

G. L

. 2017. “A “Triple A” Typology of Responding to Negative Consumer-Generated Online Reviews.” Journal of Hospitality & Tourism Research 41 (6): 719–45.

75.

Stepchenkova

Eales

J. S.

2011. “Destination Image as Quantified Media Messages: The Effect of News on Tourism Demand.” Journal of Travel Research 50 (2): 198–212.

76.

Storopoli

Braga da Silva Neto

W. L.

Mesch

G. S.

2020. “Confidence in Social Institutions, Perceived Vulnerability and the Adoption of Recommended Protective Behaviors in Brazil During the COVID-19 Pandemic.” Social Science & Medicine 265:113477. Published online October 27. doi:10.1016/j.socscimed.2020.113477

77.

Tsai

W. H.

Hsu

J. L.

Chen

C. H.

Lin

W. R.

Chen

S. P.

2010. “An Integrated Approach for Selecting Corporate Social Responsibility Programs and Costs Evaluation in the International Tourist Hotel.” International Journal of Hospitality Management 29 (3): 385–96.

78.

UNWTO. 2020a. “100% of Global Destination Now Have COVID-19 Travel Restrictions, UNWTO Reports.” Last modified January 30. https://www.unwto.org/news/covid-19-travel-restrictions.

79.

UNWTO. 2020b. “International Tourist Arrivals Could Fall by 20-30% in 2020.” Last modified January 30. https://www.unwto.org/news/international-tourism-arrivals-could-fall-in-2020.

80.

Venkatesh

Brown

S. A.

Bala

2013. “Bridging the Qualitative-quantitative Divide: Guidelines for Conducting Mixed Methods Research in Information Systems.” MIS Quarterly 21–54.

81.

Zhang

Baker

Harrington

R. J.

Marlowe

2019. “Drivers of Degree of Sophistication in Hotel Revenue Management Decision Support Systems.” International Journal of Hospitality Management 79:123–39.

82.

Wang

Harris

Patterson

2013. “The Roles of Habit, Self-Efficacy, and Satisfaction in Driving Continued Use of Self-Service Technologies: A Longitudinal Study.” Journal of Service Research 16 (3): 400–14.

83.

Wang

Liu-Lastres

Ritchie

B. W.

Mills

D. J.

2019. “Travellers' Self-Protections Against Health Risks: An Application of the Full Protection Motivation Theory.” Annals of Tourism Research 78. Published online June 29. doi:10.1016/j.annals.2019.102743

84.

Wang

Y. S.

2009. “The Impact of Crisis Events and Macroeconomic Activity on Taiwan's International Inbound Tourism Demand.” Tourism Management 30 (1): 75–82.

85.

WHO. 2020. “WHO Director-General's Opening Remarks at the Media Briefing on COVID-19 - 11 March 2020.” Last modified January 30. https://www.who.int/dg/speeches/detail/who-director-general-s-opening-remarks-at-the-media-briefing-on-covid-19—11-march-2020.

86.

Willson

McNamara

J. R.

1982. “How Perceptions of a Simulated Physician-Patient Interaction Influence Intended Satisfaction and Compliance.” Social Science & Medicine 16:1699–704.

87.

Zeithaml

V. A.

1988. “Consumer Perceptions of Price, Quality, and Value: A Means-End Model and Synthesis of Evidence.” Journal of Marketing 52 (3): 2–22.

88.

Zhang

Hou

2020. “Threat of Infectious Disease During an Outbreak: Influence on Tourists' Emotional Responses to Disadvantaged Price Inequality.” Annals of Tourism Research 84:102993. Published online July 16. doi:10.1016/j.annals.2020.102993

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