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Article

Patrons Reaction to Fear in Different Dining Contexts: A Cognitive-Experiential Self-Theory Exploration

by
Robert Paul Jones
1,* and
Mohammad Alimohammadirokni
2
1
Department of Hospitality and Retail Management, College of Health and Human Sciences, Texas Tech University, Lubbock, TX 79409, USA
2
Sales and Marketing, and Hospitality and Tourism, Department of Entrepreneurship, College of Business, Western Carolina University, Cullowhee, NC 28723, USA
*
Author to whom correspondence should be addressed.
Tour. Hosp. 2024, 5(3), 689-712; https://doi.org/10.3390/tourhosp5030041
Submission received: 2 July 2024 / Revised: 5 August 2024 / Accepted: 11 August 2024 / Published: 17 August 2024

Abstract

:
Cognitive-experiential self-theory is a unique model for exploring restaurant patrons’ decision making. Fear and its impact on diners’ decision making, particularly related to specific dining contexts (dine-in, takeout, and delivery), are limited in their representation in the literature. The COVID-19 pandemic provided an instance where a single fear could be explored universally for dining patrons. This study explores how fear influences diners’ perception of risk, antipathy, and avoidance toward restaurant dining and how these factors impact their intention to dine in a restaurant. Furthermore, it investigates how those constructs influence diner decision making regarding the selection of one of the identified dining contexts. Online survey data (n = 1225) of diners were analyzed using SEM. The research finds that fear impacts dining contexts differentially. Additionally, environmental control is identified as a valuable tool in the mitigation of diners’ fear. The pandemic had devastating impacts on the restaurant industry, partly due to the lack of research into fear, particularly in dining contexts. This research helps to fill the important research gap through the findings and theoretical and managerial implications provided.

1. Introduction

Fear can be crucial in dining decision making. Fear can shape preferences, dining schedules, and specific menu selections [1,2]. The disruptions caused by the pandemic, leading to the closure of hospitality establishments, triggered a universal fear rooted in health and safety concerns. Although the pandemic’s immediate threat has subsided, new scenarios continue to evoke similar fears [3]. The recent pandemic is not the first coronavirus that could have impacted the restaurant industry. In 2003, severe acute respiratory syndrome (SARS) and, again, in 2012, the Middle East respiratory syndrome (MERS) threatened to be as devastating as COVID-19 [4,5]. While it never impacted the U.S., it did impact the Middle and Far East, leading to the implementation of tactics such as mask wearing, sanitizing, and social distancing [6]. The lack of preparation the industry follows can lead us to have similar fear-driven impacts again. For example, the emergence of new virus variants, occasional infection spikes, and lingering concerns about public health have sustained anxiety among diners [7]. Currently under scrutiny is the outbreak of H5N1 avian flu. While extremely rare in humans, 14 cases have been identified since 2022 [8]. While there is plenty of research regarding these diseases, there remains little by way of research on the restaurant industry and how to respond.
Other health-related concerns such as foodborne illnesses, contamination scares [9], and broader issues like climate change and its impact on food safety contribute to a persistent sense of fear for diners [10]. Cultural backgrounds and unique circumstances influence this fear [11,12]. Empirical evidence highlights that fear significantly alters consumers’ risk assessments [13] when choosing dining establishments, fostering risk aversion and preferences for safer alternatives [9,14,15]. Recognizing that fear shapes emotional responses, attitudes, and behaviors during crises [16,17,18,19], this study explores fear’s role in diners’ decision making during crises.
The pandemic provides a unique opportunity to explore a common fear among the entire population yet may manifest in differing intensities, influencing patrons’ dine-in, takeout, and delivery choices. Understanding fear’s impact on dining behaviors is crucial for the restaurant industry, which has faced significant challenges and transformations both during and after the pandemic [19]. This knowledge is essential for developing strategies that address diner fear and enhance dining experiences regardless of the fear present in the diners’ environment. As a result, this study provides valuable information on how to predict and respond to future fear-related changes in dining preferences and behavior.
While this study’s context is related to the pandemic, the insights remain highly relevant due to the ongoing nature of fear-inducing events in the public health domain. The residual effects of the pandemic continue to influence consumer behavior, as does the emergence of new variants and other health scares [7]. Additionally, the enduring psychological impact and behavioral shifts initially triggered by COVID-19 provide a valuable context for understanding current and future consumer responses to similar crises.
Despite the variety of fear-inducing events for patrons, rendering fear pervasive, its impact within specific dining contexts remains understudied. The significant pandemic and post-pandemic repercussions on the restaurant industry highlight the urgent need for research into fear, particularly in dining contexts. Investigating fear during such crises enables a deeper understanding of how businesses can adapt and innovate in the face of unforeseen circumstances. This study aims to bridge the emotional and rational landscapes that diners navigate during decision making. It seeks to explore fear’s role in shaping dining choices during crises, providing insights and practical applications for academia and restaurateurs. Exploring the role of fear in dining choices highlights the importance of emotional and psychological well-being in consumer behavior [20]. This focus can lead to more holistic approaches to managing customer experiences. It can also offer strategies for mitigating fear and enhancing customer confidence, ultimately contributing to the resilience and recovery of the hospitality sector.

2. Materials and Methods

2.1. Theoretical Framework

The study adopts the cognitive-experiential self-theory (CEST) [21] to explore the sequential relationships among fear, risk, antipathy, avoidance, and dining intention across the three contexts: dine-in, takeout, and delivery. CEST provides a comprehensive framework that integrates cognitive and experiential dimensions of decision making [22,23]. In the context of dining experiences during a pandemic, where emotions and rational considerations interplay, CEST is well suited to capture the intricate dynamics of decision making. CEST’s dual-system approach provides a theoretical lens to explore how rational decision making coexists and interacts with experiential and emotional processes.
The application of cognitive-experiential self-theory (CEST) to dining contexts to this point has been limited. Many studies in the extant literature have explored various aspects of consumer decision making in the presence of fear. However, this is the first study to explore the interplay of fear, risk, antipathy, and avoidance on dining choice intention utilizing the systematic approach of CEST. Additionally, this study explores the interplay of those elements and intentions across all three dining contexts: dine-in, takeout, and delivery. This study expands the application of CEST within the dining literature and offers novel insights into the intricate dynamics of fear’s influence across diverse dining contexts.
CEST [21] posits that individuals possess two distinct systems: rational and experiential. The rational system (conscious, deliberate, and analytical) functions via a person’s understanding of the conventional rules of logic, while the experiential system is driven by intuition, emotions, and experiences [22,23]. This dual-system framework becomes particularly relevant for the current study as individuals must navigate complex dining decisions in the face of fear, social pressures, and uncertainty during a pandemic. The CEST theoretical model can be found in Figure 1.
While CEST has been applied in various contexts, such as consumer responses to sales promotions [24], food choices [25], moral behaviors [26], self-service technology adoption [27], and customers’ authenticity perceptions [28], its specific application to dining decisions during a pandemic is less explored. The unique fear associated with a global health crisis adds complexity to cognitive and experiential processes. In addition, dining decisions are influenced by many factors beyond fear and risk, such as subjective norms [29], cultural influences, and individual preferences [30]. While CEST focuses primarily on rational and experiential systems, it might oversimplify the multifaceted nature of dining choices. However, CEST provides a robust framework for understanding these processes even in such unprecedented situations as it provides a structured way to understand how diners process fear and make decisions under uncertainty, a scenario heightened during a pandemic. The framework’s ability to explain both intuitive and rational responses provides a robust basis for analyzing dining behaviors during the pandemic.
While alternative theories, such as the theory of planned behavior [31] and protection motivation theory [32], could be considered, CEST is more appropriate for this study due to its dual-system approach. CEST uniquely integrates both emotional and rational processes, which is crucial for capturing the full spectrum of diners’ decision making during a pandemic. Additionally, CEST’s sequential model outlines how emotional responses to fear can trigger rational avoidance behaviors [33], aligning well with observed behaviors during the pandemic [34]. Its focus on the experiential system’s role in risk perception and emotional responses like antipathy directly applies to the study’s context.

2.2. Literature Review and Hypothesis Development

Existing research has concentrated on the broad impact of fear on consumer behavior but has not sufficiently addressed its influence within specific dining contexts. While studies such as those conducted by Baek and Lee (2023) [19] and Liu-Lastres and Wen (2023) [15] highlight general shifts in dining preferences due to fear, they often lack specificity in exploring how fear affects specific dining scenarios, such as dine-in versus takeout and delivery options. Previous research (e.g., Harris et al., 2018; Jeon et al., 2024) [9,14] also tends to generalize the impact of fear on consumer risk aversion without delving into how fear influences diverse dining contexts. This gap in the literature underscores the need for a more detailed examination of how fear affects specific dining behaviors and choices, which this study aims to address. This study focuses on how pandemic-induced fear contributes to changes in patrons’ dining activities and the role environmental control may play in mitigating fear. It provides a unique contribution to the field, offering practical strategies for restaurant management during crises.
In dining experiences, fear can come in many present forms: food-born illnesses such as norovirus, salmonella (non-typhoidal), clostridium perfringens, campylobacter, and staphylococcus aureus; cross-contamination; food poisoning [9]; price-gouging [35]; poor service; or service refusal [36], among others. These factors influence diners’ decision making toward restaurant preferences, dining times, and specific menu selections [1,2]. Unexpected events, such as salmonella outbreaks, can evoke fear in many individuals [37]. This fear is driven by the uncertainty surrounding the illness, its transmission, and its potential impacts on health and well-being [38].
While universally experienced, pandemic fears are uniquely expressed by individuals based on personal histories, cultural backgrounds, and circumstances [11]. This personalized expression adds complexity to the overarching theme of fear within dining experiences. Concerns among restaurant patrons about indoor dining sparked significant changes in consumer behavior, profoundly impacting restaurant operations amid the pandemic [39,40]. The fear of COVID-19 transmission caused consumers to distrust shared facilities and spaces [38]. Even after lockdowns were lifted, many consumers remained hesitant to return to indoor dining environments, indicating a lasting impact of pandemic-induced fear on dining preferences [41].
The pandemic had a significant impact on fear as well as risk perception in dining contexts. Fear and risk are multifaceted, involving concerns about personal and food safety [42], hygiene, and overall well-being [38]. Fear resulting from foodborne illness outbreaks or publicized health violations can significantly influence consumers’ risk assessments in choosing where to dine. Fear-induced risk aversion may lead individuals to modify their dining behaviors, such as avoiding certain establishments or preferring familiar and perceived safer options [9]. The fear of contracting the coronavirus has altered dining norms, leading risk-averse customers to view services as less safe and prefer takeout, which minimizes human contact compared to dine-in options [43]. The widespread unpleasant feelings experienced during the pandemic highlight the need to investigate perceived risks within dining experiences. Yildirim and Guler (2022) [44] emphasize the profound influence of the COVID-19 pandemic on perceived risks, propelled by psychological factors like fear and worry. The emotional aspects of perceived risks and individual concerns about potential threats are significant predictors of individuals’ overall risk perception [45,46]. Synthesizing these insights, the following hypothesis is proposed:
H1. 
Fear experienced by individuals as a result of the pandemic has a significant positive influence on the perceived risks associated with dining choice decisions, including dine-in, takeout, and delivery.
Fear can also influence antipathy in the context of dining conditions. For instance, heightened concerns about food safety or contamination can lead individuals to develop a strong aversion toward certain dining establishments or culinary practices [47]. During crises, such as the pandemic, fear extends beyond the immediate worry of contracting the virus, instigating a sense of unease and reluctance among individuals when confronted with decisions about dining out [17]. Scholars have studied fear’s emotional responses and psychological implications, ranging from heightened anxiety to adaptive behavioral adjustments [48]. This study introduces a novel perspective exploring the relationship between fear and antipathy toward dining behaviors. Scant literature links fear to antipathy by dining context, yet existing research indicates fear substantially impacts emotional states and behavioral tendencies [49]. For example, COVID-19-related dread and anxiety can result in psychological distress and various negative emotional disorders in consumers [38]. The enjoyment derived from dining out can gradually be overshadowed by negative emotions such as stress and concern, driven by fears of infection [50]. Building upon this literature, this study hypothesizes that fear, such as contracting COVID-19, may contribute to a general sense of emotional aversion or antipathy toward engaging in various dining activities. As individuals perceive increasing risk associated with each dining context, from delivery to takeout to dine-in, their intuitive emotional response will manifest stronger negative feelings and aversions [51]. Therefore, this study posits the following:
H2. 
Fear experienced by individuals as a result of the pandemic has a significant positive influence on the antipathy associated with dining choice decisions, including dine-in, takeout, and delivery.
Fear is generally suggested to drive individuals to engage in avoidance behaviors in an effort to reduce or mitigate fear [15]. Fear resulting from worries about food safety, hygiene, or widely publicized contamination incidents prompts individuals to avoid certain dining establishments [9]. Moreover, avoidance driven by fear can alter consumer preferences, guide individuals toward familiar and perceived safer choices, and ultimately mold the dynamics of the dining industry [52]. Within the behavioral responses to the pandemic, fear substantially impacts avoidance behaviors in shared facilities [53]. Exploring the intricate dynamics between fear and preventive behaviors reveals a compelling connection [54], especially amid lockdowns, resulting in a discernible avoidance of dining at restaurants [17]. Health concerns and the fear of illness lead to behaviors that involve avoiding restaurants [43]. In the face of an uncertain and fearful scenario brought about by crises, like the pandemic, avoidance emerges as an integral individual defense mechanism [38,55]. Therefore, it is hypothesized that:
H3. 
Fear experienced by individuals as a result of the pandemic has a significant positive influence on avoidance associated with dining choice decisions, including dine-in, takeout, and delivery.
Fear has been demonstrated in the extant literature to have significant negative correlations with purchase intentions, such as crime at shopping sites [56] and fraudulent use of electronic information during online shopping [57]. Studies in tourism on the effects of fear induced by crises further emphasize the role of fear. Fear has been shown to add significant stress to tourists’ decision making regarding whether or not to travel to specific destinations [58]. Understanding intentions is vital because they serve as predictors of consumer behavior [59]. Intentions toward dining at a restaurant during the pandemic were influenced substantially by fear, shaping dining behavior [19]. Fear generated from individuals’ cognitive evaluations of the threat and their ability to engage in risk-preventative actions is a significant indicator of observed customer behaviors related to restaurant visits [60]. Additionally, Chi et al. (2022) [43] argue that the fear of contracting COVID-19 and transmitting it to loved ones may cause individuals to become more hesitant and alter their travel and dining intentions. COVID-19 outbreaks intensify feelings of altruistic fear as individuals worry about the potential death of family or friends due to the virus, leading them to prefer staying at home and shift their intentions from dining to opting for online delivery [61]. In light of these considerations, the following hypothesis was formulated:
H4. 
Fear experienced by individuals as a result of the pandemic has a significant positive influence on intentions associated with dining choice decisions, including dine-in, takeout, and delivery.
Fear, as has been previously noted, has a significant impact on diners’ risk perception and developing antipathy toward engaging with restaurants in traditional ways. The concept of antipathy, as influenced by perceived risks, remains underexplored in dining research. Antipathy, a general aversion or dislike [62], is a significant emotional response shaped by perceived risks associated with dining-related conditions. Drawing on existing literature highlighting fear’s impact on emotional states and behavioral tendencies [18,49], this study theorizes that the fear experienced during the pandemic contributes to an emotional aversion or antipathy toward engaging in various dining activities.
Negative emotions arising from perceived psychological risks can diminish consumers’ desire to dine out, as the enjoyment previously associated with dining out is gradually replaced by stress and concerns related to the fear of infection [50]. As individuals perceive increased risk associated with dining activities, their intuitive, emotional response will likely manifest as stronger aversions and negative feelings [51]. Under these circumstances, antipathy becomes an intuitive expression of discomfort and aversion in response to perceived risks. Risk perception positively correlates with negative emotions [63]. Antipathy, characterized as a general aversion or dislike [62], emerges as a relevant emotional response influenced by the perceived risks associated with dining contexts. For instance, individuals may develop antipathy toward dining in a restaurant due to concerns about crowded spaces, inadequate sanitation, or uncertainties about the health status of others within the dining environment [46,51]. In light of the connections between perceived risks and emotional aversions, we propose the following hypothesis:
H5. 
Perceived risks experienced by individuals as a result of the pandemic have a significant positive influence on antipathy associated with dining choice decisions, including dine-in, takeout, and delivery.
In response to fear engendered by the pandemic, individuals exhibited a pronounced inclination to avoid public spaces and interpersonal interactions. During the pandemic, individuals may avoid or postpone purchasing hospitality products due to the perceived or actual risk of exposure to the coronavirus [43]. The pandemic has significantly increased uncertainty in the restaurant industry due to decreased consumer demand for food and avoidance of dining out. With these risk concerns, consumers may perceive less enjoyment from dining out than they did previously and may even choose to avoid it altogether. The perceived physical risk of contracting COVID-19 reduces consumers’ desire to dine out as they seek to avoid exposure to potential health threats [50]. Yenerall et al. (2022) [64] suggest that the most effective strategy to mitigate risks associated with dining establishments during the pandemic is the outright avoidance of restaurants. Building on this, a series of studies, including those conducted by Oh et al. (2021) [54] and De Zwart et al. (2009) [65], have shed light on the intricate relationship between perceived personal risk and engagement in preventive behaviors. This inclination toward risk aversion aligns with the innate tendency of individuals to avoid risky situations, as observed by Liu-Lastres et al. (2021) [66]. Significantly, this instinctive avoidance extends to restaurant dining contexts, as individuals opt to protect themselves by avoiding public dining spaces [15]. Therefore, the following hypothesis was formulated:
H6. 
Perceived risks experienced by individuals as a result of the pandemic have a significant positive influence on avoidance associated with dining choice decisions, including dine-in, takeout, and delivery.
Heightened perceptions of perceived risk driven by fear can exacerbate anxiety, exerting a negative effect on behavioral intentions [67]. In the context of the pandemic, heightened perceptions of risks associated with infection may negatively impact consumers’ intentions to engage in dining in or from a restaurant. Zhong et al. (2021) [50] state that perceived risk is closely linked to factors that can lead to negative outcomes or losses. The perceived physical risk of contracting COVID-19 decreases consumers’ desire to dine out as they aim to avoid exposure to health threats. Restaurants, as public venues with high foot traffic, can heighten the risk of human contact and infection, thereby fostering negative perceptions of dining out. In other words, high perceived risks of coronavirus infection, both physically and mentally, can adversely affect consumers’ intentions to dine outside. The stringent dining restrictions have further diminished the appeal of restaurant visits, resulting in a substantial decline in the number of visits despite an increase in food delivery orders [68]. Several studies illustrate that escalating levels of risk perception correlate with reduced intentions for restaurant utilization and an increased preference for private dining options (e.g., Kim & Lee, 2020; Foroudi et al., 2021) [52,69]. Radic et al. (2021) [29] also found that the perceived health risk from COVID-19 strongly discourages female passengers from intending to dine on cruise ships during the pandemic. Consequently, higher levels of risk perception may lead individuals to curtail activities like food consumption from public options such as restaurants. Having considered this discussion, the following hypothesis was proposed:
H7. 
Perceived risks experienced by individuals as a result of the pandemic have a significant negative influence on intentions associated with dining choice decisions, including dine-in, takeout, and delivery.
During the pandemic, individuals’ emotional responses to well-founded fear led to antipathy to various dining-related conditions [70]. While direct studies on antipathy in dining contexts are limited, existing research on emotional responses includes aversion or antipathy toward specific situations or conditions, such as dining during crises [71]. Emotional antipathy is hypothesized to play a significant role in avoidance, often considered a protective mechanism triggered by perceived threats [51]. If individuals experience antipathy toward various dining-related contexts during the pandemic, it is plausible that they would adopt avoidance as a means of self-protection. This aligns with the broader literature on fear-driven avoidance and emphasizes the emotional dimensions intertwined with rational decision making in response. Observations of changes in consumer behavior during the pandemic provide additional support for the hypothesis. Despite increased food delivery, the documented decrease in restaurant visits [68] suggests a shift in preferences and choices driven by negative emotional sentiments. If individuals harbor antipathy toward specific dining conditions, it is reasonable to infer that they would opt for avoidance strategies. Therefore, the following hypothesis was developed:
H8. 
Antipathy experienced by individuals as a result of the pandemic has a significant positive influence on avoidance associated with dining choice decisions, including dine-in, takeout, and delivery.
Costa (2013) [72] posited that a sense of moral obligation can instigate negative evaluations of convenience-oriented food, fostering antipathy that diminishes consumers’ intention to purchase. Though Costa’s focus is primarily on home meal replacement, the underlying concept of antipathy serves as a foundation for its potential extension to dining choices amid the pandemic. In a broader context, Antonetti et al.’s (2019) [73] review illuminates the widespread ramifications of consumer animosity, demonstrating that consumer animosity is linked to perceptions of poor product quality, diminished trust, negative attitudes, negative word-of-mouth, reduced purchase intention, product avoidance, and even brand boycotts. Crucially, the antipathy discussed by Antonetti et al. (2019) [73] transcends restaurant contexts, encompassing various consumer engagements. This broader understanding of consumer antipathy as a negative emotional attitude becomes an invaluable lens to explore individuals’ sentiments within the dining landscape. Furthermore, the definition of consumer animosity as residual antipathy stemming from events such as military, political, or economic occurrences [74] introduces a cross-contextual dimension. While initially applied in international relations, this definition underscores the pervasive nature of antipathy as a potent emotional response. Applying this insight to dining-related conditions during the pandemic reveals that individuals may harbor antipathy toward specific dining options based on perceptions of safety, hygiene, and convenience, all of which are influenced by the fear of contracting the disease. Drawing upon Costa’s (2013) [72] insights into moral obligations, Antonetti et al.’s (2019) [73] review of consumer animosity, and the broader definition provided by Harmeling et al. (2015) [73], this study proposes the following:
H9. 
Antipathy experienced by individuals as a result of the pandemic has a significant negative influence on intentions associated with dining choice decisions, including dine-in, takeout, and delivery.
The existing literature has explored avoidance in different contexts, such as retail and public spaces, emphasizing its role in shaping consumer choices and intentions [75]. The pandemic engendered significant consumer-related fear, thereby introducing significant uncertainty into the restaurant industry due to reduced consumer demand for food and a tendency to avoid dining out [50]. Radic et al. (2021) [29] found that once fear of the perceived health risk from COVID-19 becomes the dominant emotion for travelers, they are likely to avoid certain behaviors. Within the realm of dining, avoidance manifests in various forms. Some individuals may avoid crowded dine-in settings due to concerns about maintaining social distancing, while others may shy away from food delivery or takeout services due to uncertainties surrounding the handling and delivery of their orders [76]. Avoiding different dining contexts during the pandemic is a strategic adaptation to the prevailing circumstances [77]. Avoidance acts as a coping mechanism, allowing individuals to navigate the dining landscape while prioritizing health and safety. Against this backdrop, the following hypothesis is developed:
H10. 
Avoidance experienced by individuals as a result of the pandemic has a significant negative influence on intentions associated with dining choice decisions, including dine-in, takeout, and delivery.
Figure 2 displays the research model of the study. As can be seen, it reflects the same relationships as found in the theoretical model in Figure 1. Further, it specifies that the constructs of risk and antipathy reflect the intuitive/experiential elements of CEST. The analytical/rational construct of CEST is represented by avoidance. Intention represents the behavior aspect of CEST. CEST is expanded in Figure 2 by the inclusion of fear as an external force that has direct impacts on risk, antipathy, avoidance, and intention. Further, we can see the systematic process of the model as fear impacts the intuitive/experiential elements of risk and antipathy, which then impact the analytical/rational element of avoidance and then impact the behavior element, intention. We also can see the specified influence of the model in which the environment element of fear and intuitive/experiential elements can also directly influence behavior.

2.3. Methodology

2.3.1. Data Collection

The data were collected in the midst of the pandemic in July 2021 by a group of researchers representing several U.S. institutions in the southwest, southeast, and midwest. The research explored many elements of hospitality impacted by the pandemic both for companies and individuals. Many manuscripts have been completed thus far. This research, however, is the first manuscript from that research that explores fear’s impact on the consumer.
The data were gathered using an online survey design using an online consumer panel. Respondents demonstrated sufficient dining experience during the pandemic. The sample was representative of the U.S. population, particularly regarding key demographics such as gender, age, and race.
Respondents read an introductory statement:
“For the following questions, please think back to the first year of the COVID-19 pandemic (March to December 2020). The pandemic was at its initial peak. Mask wearing in public and social distancing was enforced. Your attitudes regarding restaurants during that time should frame how you respond to the following questions.”
Participants used a slider marker to answer three restaurant context questions about the likelihood they would select (1) dine-in, (2) takeout, or (3) delivery. The responses placed them into one of the three dining cases. Once in their groups, participants were asked to answer a series of questions from scales that were either operationalized using methods described by Churchill and Iaccabucci (2009) [78], including fear and environmental control, or previously operationalized, including perceived risk [79], antipathy [80], avoidance [81], and intention [79]. A list of the scale items and their loadings can be found in Appendix A, Table A1.
Screening tools to eliminate respondents who were not providing usable responses included the following: a slide marker consistently over or under 50% for all conditions; completed surveys in under 50% of the average completion time; and/or “straight line” answer patterns. This process yielded 441 dine-in, 378 takeout, and 406 delivery observations.
Steps to reduce common method variance (CMV), in accordance with Podsakoff et al. (2003) [82], included a priori survey structure using blocks of questions, different answer schemes, and leaving the dependent variable for last [82]. Post hoc, Harman’s single-factor test indicated that under 50% of the variance (32.6%) was explained when modeling the observed items as a single variable. Ranges for skewness (range: −0.38: 0.57) and kurtosis (range: −1.35: −0.53) indicate the data were appropriately distributed for the specification of structural equation models.

2.3.2. Sample

A total of 1225 responses were retained for analysis. Based on analysis of the number of parameters in the models (nmeasurement = 58; nstructural = 54; nnested = 162), the data support an appropriate ratio of free parameters to observations for use in structural equation modeling [83]. The sample was found to be a representative sample of the U.S. dining population. The gender split was relatively even, with men at 49.1% and women at 50.0%. Income for 70% was below USD 70,000, over 60% were below 55 years of age, and 34% worked full-time. Sample demographics can be found in Table 1. No significant biases were found to need mitigation in the sample data.

3. Results

3.1. Measurement Model

The measurement model and the structural models to follow were specified using AMOS version 29 software. The fit of the measurement model, including all data and disaggregated data from all three dining conditions, can be seen in Table 2. All constructs and indicators, along with the associated estimates, Cronbach’s alphas, error terms, and average variance extracted (AVE), are reported in Appendix A, Table A1.
The convergent and discriminant validity were assessed using the results of the measurement model [84]. The validity assessment and correlation matrix are reported in Table 3. The AVE is greater than 0.5 for all constructs, and the CR for all constructs is greater than the AVE, indicating convergent validity [85]. For each construct pair, the shared variance was less than the corresponding value for the AVE square root, suggesting that all constructs are also discriminately valid [85].

3.2. Structural Models

The first structural model was specified using the aggregated data (i.e., all dining contexts). The specified model (corresponding to Figure 2) was a good fit to the data (χ2 = 454.27, df = 119; Normed χ2 = 3.82; RMSEA = 0.05; CFI = 0.98; NFI = 0.97; TLI = 0.97), and all parameters were significant in the hypothesized direction. However, this research aims to establish the impact fear plays in the differing dining contexts. As a result, we need another model to be specified for further analyses. Therefore, a three-group nested model was fit utilizing dining context (e.g., dine-in, takeout, delivery) as the group-level moderator. The multi-group nested model fit statistics (χ2 = 1238.44, df = 476; Normed χ2 = 2.60; RMSEA = 0.03; CFI = 0.97; NFI = 0.96; TLI = 0.97) were a significantly better fit to the data than the aggregated specification (Δχ2 = 784; Δdf = 357; p < 0.001). For these reasons, the three-group model was accepted over the aggregated model. Nested model fit specifications and path estimates can be found in Table 4. Having accepted the nested model, estimates could be compared across the three dining conditions.

4. Discussion

As can be seen in Table 5, fear’s impact on antipathy and avoidance was positive in all dining contexts. Fear’s relationship was not significant for intention in the takeout and dine-in conditions. This relationship is most likely bound to avoidance, which is founded on fear. Therefore, the diner with the greatest fear can be seen opting for delivery and not engaging in either riskier options of dine-in or takeout. Fear was significant and positive for risk in the dine-in condition and delivery conditions while not significant for takeout. Takeout was a more common method of obtaining restaurant food prior to the pandemic. Therefore, risk assessment is associated in this case with dine-in, the highest risk, and delivery, which for many would be a newer form and less familiar method of obtaining restaurant food. Fear’s only negative and significant relationship was with risk in the delivery condition. This negative relationship indicates that as individuals’ fear increased, their risk assessment of delivery decreased. As such, individuals who sought out delivery would feel they decreased their risk in the face of fear. The only unexpected result was the non-significant relationship between antipathy and intention in all contexts except delivery, thereby partially accepting hypothesis nine. Antipathy and avoidance were similarly non-significant in all cases, thereby rejecting hypothesis eight. This is surprising as both fear and risk had very strong relationships (p < 0.001) with antipathy, as well as avoidance and intention. The lack of significance for the path from antipathy to avoidance and intention may be due to the strong relationship between fear and risk with antipathy. The fear felt by the diner along with their risk assessment may have overridden their feelings of antipathy by already moving toward avoidance. Finally, it is not completely surprising that the path from avoidance to intention for takeout and delivery is non-significant. The diner seeking to resolve the best option to engage with restaurants finds that it is unavoidable to use takeout or delivery methods.
The authors find substantial evidence for the hypothesized effects of fear within the social experiential context as it pertains to dining behavior. The results identify consistent positive relationships as hypothesized of fear with antipathy and avoidance as well as risk with antipathy and avoidance in all dining contexts (see Appendix B, Table A2 and Table A3), supporting hypotheses two, three, five, and six. The relationship between risk and intention was significantly negative in all dining contexts, supporting hypothesis seven.
Based on these findings, it is clear the authors should have hypothesized that antipathy would have little to no impact on avoidance or intention. From an emotional perspective, avoidance is a stronger emotion, often resulting from antipathy. Therefore, avoidance is the emotion that would have a significant relationship. Further, it is possible that one year into the pandemic when these data were gathered, the diner had already shifted to delivery, which is why perhaps we see such mixed results for takeout.

5. Moderation

Finding support or partial support for each hypothesis raises another question. What if the dining patron had some ability to exert some level of control over their environment? Would this moderate any of the relationships within the model? In particular, would environmental control moderate the relationship fear had with the other constructs in the model? For this answer, we conducted further analysis of the data.
In the context of a pandemic, environmental control refers to measures implemented to manage and mitigate the spread of the disease. These measures may involve encouraging and enforcing good hygiene practices, such as regular handwashing, sanitizing surfaces, maintaining cleanliness in shared spaces, ensuring proper ventilation in indoor spaces to reduce the concentration of airborne particles that may contain infectious agents, implementing measures to maintain physical distance between individuals, and encouraging or mandating the use of appropriate personal protective equipment, such as masks or face coverings. Gudi et al. (2020) [86] emphasized that implementing universal safety precautions—such as maintaining personal hygiene, handwashing, following social-distancing guidelines, practicing self-isolation, and using face masks and hand sanitizers—is the sole method to control the widespread transmission of COVID-19 globally. Consequently, most governments have enforced these preventive measures to mitigate the pandemic’s impact on populations [53].
During times of heightened fear, individuals naturally perceive higher risks across various activities [44], including dining choices. Environments characterized by a high degree of control over safety measures, encompassing strict adherence to health protocols, visible sanitation practices, and effective crowd management, often result in lower levels of fear [87]. This perceived control can act as a barrier against pandemic-induced anxiety, moderating the relationship between fear and perceived risks in dining choices. Conversely, in settings where environmental control is perceived as lacking or insufficient, the fear experienced by individuals may intensify, amplifying the perception of risks. In addition, environmental control and preventive behaviors become indispensable in mitigating negative emotions evoked by the pandemic [88] by providing a sense of order, safety, and predictability [89]. Environments with strict safety protocols enforced empower individuals with higher perceived control over their surroundings. This heightened control can then moderate the relationship between fear and antipathy.
Kim et al. (2023) [90] state that environmental control is crucial in reducing avoidance related to dining decisions. A well-controlled setting, such as a dine-in environment with high environmental control, may encourage individuals to overcome their fears [91] and engage in the activity, relying on established safety measures to reduce the perceived risk of exposure. In contrast, avoidance may increase if environmental control is lacking or insufficient [92]. In the broader context of a pandemic, the confidence instilled by a well-controlled environment moderates the impact of fear, rendering individuals more willing to follow through with their dining intentions despite concerns related to the pandemic [43]. Therefore, the following hypotheses were proposed:
H11a. 
Environmental control will moderate the relationship between fear experienced by individuals as a result of the pandemic and perceived risks associated with dining choice decisions, including dine-in, takeout, and delivery.
H11b. 
Environmental control will moderate the relationship between fear experienced by individuals as a result of the pandemic and antipathy associated with dining choice decisions, including dine-in, takeout, and delivery.
H11c. 
Environmental control will moderate the relationship between fear experienced by individuals as a result of the pandemic and avoidance associated with dining choice decisions, including dine-in, takeout, and delivery.
H11d. 
Environmental control will moderate the relationship between fear experienced by individuals as a result of the pandemic and intentions associated with dining choice decisions, including dine-in, takeout, and delivery.
Figure 3 displays the moderation model of the study.
The variables in this model used to explore moderation were standardized before analysis. The assessment of moderation uses an interaction term created by multiplying the standardized Fear variable with the standardized Environmental Control variable. The analysis balance follows the methodology suggested by Baron and Kenny (1986) [93]. The outcome of the analysis provides insight into where diners felt that establishing some control over their environment was beneficial. In Table 6, the hypotheses are tested. Only the paths between fear with avoidance and intention showed any signs of moderation, thereby rejecting hypotheses H11a and b. Hypotheses H11c and d are partially accepted, as can be found in Table 6.
This moderation analysis provides powerful evidence that when a dining patron has the opportunity to exercise some amount of control over their environment, they can reduce their level of fear as it relates to avoidance of dine-in and takeout. It also demonstrates a reduction in fear with intention toward delivery. In total, we have seen how fear and perhaps some forms of mitigation, such as environmental control, can influence diners’ decision making regarding dining in an establishment, takeout, or delivery.
The slope analyses can be found in Appendix C Figure A1 and Figure A2, demonstrating these outcomes. In Appendix C, Figure A1, we can see that the exercise of environmental control by the diner decreased avoidance in the dine-in and takeout conditions. This is a valuable finding as it provides evidence that the diners’ fear can be at least mitigated to some degree, coaxing them into a more pre-fear engagement with the restaurant. Further, in Appendix C, Figure A2, we see that environmental control dampens the positive relationship between fear and intention to use delivery. This is very reinforcing of the information in Appendix C, Figure A1, further demonstrating that diners, given some level of environmental control, can be coaxed into returning to in-restaurant dining.

6. Conclusions

6.1. Fear and Its Influence on Restaurant Patronage

This research aims to explore how fear influences restaurant patronage behavior. We utilized CEST because of its dualistic nature to explore a diner’s intuitive/emotional/experiential responses coupled with their analytical/rational responses. We extended the CEST theory through the introduction of fear. Additionally, we explored the diners’ responses related to several dining contexts. The following reviews some of the key findings.
The extant literature on context-specific changes in restaurant patron behavior is limited to nonexistent, which leaves a research gap laid bare by the pandemic. The fear of contracting COVID-19, particularly through in-restaurant dining, proved to be a particularly negative outcome for patrons and restaurants alike. Further, there is little guidance on how to mitigate patrons’ fear within the confines of the restaurant and how to address other dining contexts, such as takeout and delivery. Therefore, this research provides great value to future researchers and industry practitioners through the exploration of the differential impact of fear on the dining contexts of dine-in, takeout, and delivery.

6.2. Cognitive-Experiential Self-Theory; Fear and Its Influence on Restaurant Patronage Decisions

This research demonstrates that CEST is useful for exploring restaurant patronage behavior. The findings indicate that fear had a positive relationship with antipathy and avoidance (H2 and H3) across all dining contexts. Additionally, fear had a significant relationship with risk, antipathy, avoidance, and intention for the delivery context. This indicates that fear of contamination from other dining contexts led patrons to use delivery for continued restaurant patronage. This is particularly evident in the negative fear-to-risk relationship in the delivery context. As fear increases, the risk assessment of delivery declines relative to dine-in or takeout. Risk was also demonstrated to be positively related to antipathy and avoidance (H5 and H6) and negatively related to intention (H7) in all dining contexts. These findings are particularly important as they demonstrate that increases in risk assessment led to increases in antipathy and avoidance, which also led to decreases in intention to engage in any restaurant dining context.
Further, only one hypothesis, antipathy to avoidance (H8), was rejected. Therefore, the remaining hypotheses, H1, H4, H9, and H10, all demonstrated significant relationships differentially among the restaurant dining contexts. Significantly, in H10, the only significant relationship was the dine-in context. In this case, as avoidance increases, the intention to engage in the dine-in experience by patrons decreases. As a result of this study, we see that during states of heightened fear, patrons will first and foremost disengage from the dine-in context and, most preferably, turn to delivery. Takeout receives a mixed message. While not as preferred as delivery, it is perceived to be a better option than dine-in. What is most striking is that the results are so uniform among the contexts. Hypotheses 2, 3, 5, 6, and 7 are accepted across all contexts. Takeout, as noted, is a mixed result from its position in the middle of the options and had the most rejections. Delivery, on the other hand, as the preferred option, had the least. Critically, environmental control was shown to help moderate avoidance for dine-in and takeout as well as fear with the intent to dine in.

6.3. Other Restaurant Patron Fears and Impact on Behavioral Change

While the pandemic served as the context to explore fear, the pandemic is hardly a singular fear-inducing event for diners. Diners have many fears, including cross-contamination, listeria, salmonella, norovirus, and other foodborne illnesses. These fears may cause temporary or permanent changes in diners’ habits. Diners who have a single negative cross-contamination event may choose to stop frequenting an establishment. Diners who have multiple negative cross-contamination events may choose to avoid restaurants altogether. However, it is more likely that we are going to see replications of our findings when there is a more common cause of the fear-inducing event. Outbreaks of new pandemic-like events, such as the avian flu and/or mass salmonella incidents, will likely return diners to an outlook similar to that during the pandemic where patrons will attempt to minimize their risk. Restauranteurs and the industry at large should be concerned that continued negative health events could lead to permanent changes in diner behavior, which would be a net negative to the industry.

6.4. Behavioral Changes and the Influence of Environmental Control

In fact, we see that the diner has indeed engaged in prolonged changes in behavior post-pandemic. Spending at full-service restaurants by dine-in patrons has declined approximately 35% in comparison with pre-pandemic levels [94], while delivery is more than double pre-pandemic levels [94,95]. This trend for in-restaurant dining appears to have stabilized. However, delivery continues to increase, growing 8% year on post-pandemic year [95]. All of this indicates that the lack of planning and preparation to mitigate pandemic fear by restaurants early on has led to a prolonged and potentially permanent change in diner habits. Unfortunately, the continued increase in delivery is not enough to offset the decline in on-premises dining. This should serve as yet another call to action for restauranteurs to be mindful of and prepared to address diner fears regardless of the cause. Failure in this preparation can lead to further declines in on-premises dining, which will not be made up through takeout or delivery.
This research further explored the moderating effect that environmental control may have on the model’s existing relationships, particularly related to fear. Environmental control was demonstrated to weaken the relationship between fear and avoidance in the dine-in and takeout contexts while having no effect on the delivery context. This indicates that restaurants can offer patrons options that allow them to feel more in control of their environment, which may stimulate a return to patronage. However, delivery appears to be a high form of environmental control that patrons are already practicing. Takeout also demonstrated that environmental control moderation weakens the relationship between fear and intention. Again, this is a positive sign for restaurateurs looking to enhance diner patronage. However, restaurants need to develop plans that provide comfort to diners who would otherwise dine in. The results of this study indicate that in-restaurant dining is perceived as the highest-risk and most fear-inducing restaurant channel to engage with from a health risk perspective. We have seen that the building of outside pods, significant internal spacing, outdoor seating, and more may help. These are, unfortunately, all post hoc solutions, many of which are expensive to implement. Restaurants need to consider as part of their everyday business how they could more effectively provide environmental control for their diners to encourage continued patronage.
Theoretically, this research extends CEST into the dining literature in two significant ways. First, the inclusion of fear as an independent variable was demonstrated to have significant effects throughout the model. Further, this research demonstrates that the impacts of fear on the model elements are differential based on the dining context. Both findings provide significant new areas for research and unique insight into the literature. Additionally, we demonstrated that environmental control can be a valuable tool in providing restaurant patrons with a means to help them mitigate their fear. These findings demonstrate that the dining context is important when fear is involved in the patronage decision.

6.5. Managerial Implications

The gap in the literature regarding fear and the various contexts in which restaurant patrons can engage in dining is significant. This became all too clear during the pandemic as the industry struggled to respond to a universal fear. Had the industry been more aware of the impact fear can have on dining patrons, particularly in-restaurant diners, changes to utilize delivery and, to a lesser degree, takeout could have been more rapid. Further, plans to help make the in-dining experience more comfortable for patrons during the pandemic climate would have been greatly beneficial. Managers could have also responded with more robust measures to ensure patrons were engaging in a safe environment. Providing assurances of cleanliness, social distancing, mask-wearing, etc., could all have been deployed rapidly to reassure diners that it was safe to continue to engage in restaurant dining. Particularly important are messages regarding cleanliness. This is a message that resonates at all times. Knowing that a restaurant adheres to the highest standards of cleanliness helps to provide significant comfort to patrons. Messaging that reflects how food is cooked in individual vessels not only reinforces the cleanliness message but also minimizes concern over cross-contamination. These types of messages have no event or time-based limitations. They can be utilized regardless of the current conditions.
Providing managers with messaging that identifies areas in which the restaurant is taking specific actions to limit risk and, therefore, fear for patrons is essential. This includes targeting those messages by dining context. As mentioned, ventilation, social distancing, mask-wearing, etc., is well suited to the in-restaurant context. Delivery and takeout can both focus on contactless service. While these examples are relevant for a pandemic, restaurant patrons have many fears that may influence dining behavior beyond the next pandemic. Consider the case of food allergies. Patrons with this fear may be more inclined toward in-restaurant dining as they can have a face-to-face discussion with their server about their food allergies. Having a perceived advocate in the kitchen for their safety can be a significant benefit for in-restaurant dining. Providing patrons with opportunities to include food allergen notes in an ordering app for takeout or delivery [96], including notifications in the order review highlighting the allergy, may help lower concern, provide a positive experience for the diner, and reduce fear over ordering takeout or delivery.
Providing elements of environmental control for patrons is another element that may benefit restaurants. Providing masks, hand sanitizer, secluded seating, open-air environments, etc., that the patron can select provides them a sense of control over their environment, encouraging participation. The ability for patrons to see mitigation efforts from the restaurant plus the ability to engage with additional elements helps lower risk and, thereby, fear. Beyond the pandemic, messaging about food preparation, cleanliness, food sourcing, and more demonstrates control elements being exercised by the restaurant. Providing patrons with options in food preparation may also help. Again, from a cross-contamination perspective, patrons could be offered the option to have fried elements of their meal pan-fried in a single pan as opposed to the communal fryer, minimizing risk. This provides the patron with environmental control they value in risk mitigation.
A key insight from this study is that fear drives behavior in restaurant patrons, which can result in channel changes as well as decisions to not engage with restaurants at all. The study can inform risk communication strategies, helping businesses effectively convey safety measures and reduce customer fears. This is particularly relevant in ensuring customer confidence and trust in dining establishments. Further, fear can come from various places and is present in the everyday environment, not just during a pandemic. Restaurants are encouraged to have an active outreach through in-restaurant signage, menu verbiage, email, loyalty programs, website, and social media to inform patrons about ongoing efforts to mitigate a variety of fear triggers. Highlighting how food is prepared, where it is sourced, value for the cost of the menu items, cleanliness programs, and more can all help reduce fear in patrons. These ultimately encourage diners to frequent those establishments that acknowledge their fear and have demonstrated an effort to mitigate it.

7. Limitations and Future Research

There are some limitations associated with this study. This study utilized the recent pandemic as its foci for fear, which devastatingly impacted the restaurant industry. Understanding how to mitigate this and other fears in the future is essential to continued success for restaurateurs. Chief among those limitations is the cross-sectional nature of the study, including its sample of U.S.-only participants. The study explored a snapshot of restaurant patrons roughly one year into the pandemic. It is not clear whether diners’ perceptions of restaurant engagement had changed from the beginning of the pandemic and would change more since we explored a single instance.
Further, the sample was U.S. only. As has been noted, culture plays a key role in fear response. While the pandemic had a global impact, it cannot be said that all other cultures feared the pandemic in the same way. In fact, it can be noted that certain cultures, Sweden, for example, opted to not enforce any pandemic restrictions [97]. Therefore, without additional cultural research, extending these findings to dissimilar cultures would be ill-advised. Further, the literature would benefit from exploring other societal elements such as government actions, media coverage, cultural norms, and more, which might also have impacted diners’ decision making. Additionally, to address the cross-sectional concerns, future research should consider exploring other cultures as well as more longitudinal studies to better understand how time and culture influence outcomes.
A limitation of this research is the generalizability to a variety of fears that restaurant patrons may manifest. It is not clear that all fears would result in the same responses. Individual fears, such as food allergies and cross-contamination, may differ in response to broad-scale fears, such as a salmonella outbreak, or another pandemic fear, such as H5N1. Therefore, future research should consider exploring these different forms of fear and how they impact restaurant patronage. Further, future research would also do well to perform a longitudinal research study of fear and restaurant patronage to better understand how these elements complete their cycle in CEST. As noted in the model, each element can influence the other. In the case of this research, the elements only influence in a forward direction. It would be interesting to see how intention influences the intuitive/experiential and the analytical/rational elements.
The pandemic provided a platform that allowed the study of diner behavior universally across the U.S. While pandemics are rare, fear is not. Restauranteurs would do well to implement as many fear-reducing strategies as possible for their everyday business to provide it with the maximum opportunity to gain and/or maintain patronage.

Author Contributions

Conceptualization, R.P.J. and M.A.; methodology, R.P.J.; software, R.P.J.; validation, R.P.J. formal analysis, R.P.J.; investigation, M.A.; resources, R.P.J.; data curation, R.P.J.; writing—original draft preparation, M.A.; writing—review and editing, M.A. and R.P.J.; visualization, M.A.; supervision, R.P.J.; project administration, R.P.J.; funding acquisition, R.P.J. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Texas Tech University and the Office of Research, the Provost’s Office, and College of Health and Human Sciences.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki, and approved by Human Research of Texas Tech University (IRB2023-1082 and 11 September 2023).

Informed Consent Statement

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

Data Availability Statement

The data presented in this study are available on request from the corresponding author due to the requirements of the university, which funded the research.

Acknowledgments

The authors wish to thank the Office of Research, the Provost’s Office, and the College of Health and Human Sciences at Texas Tech University for their funding support of this research.

Conflicts of Interest

The authors declare no conflicts of interest.

Appendix A

Table A1. Scale properties.
Table A1. Scale properties.
Constructs and IndicatorsStd. Est.Std. Err.
Fear of [Dining Context] (α = 0.94)0.80 a
Anxious0.78 ***0.052
Panicked0.95 ***0.047
Frightened0.90 ***0.047
Afraid0.94 ***0.047
Perceived Risk (α = 0.85)0.53 a
I think shopping [dining context] does not imply a waste of my money0.72 ***0.051
I think shopping [dining context] won’t provide the promised benefits0.6 ***0.047
I think shopping in-store is less productive0.80 ***0.044
I think shopping [dining context] will result in wasted time0.87 ***0.047
I doubt the functional performance of [dining context]0.56 *0.047
Shopping Antipathy (α = 0.83)0.63 a
During the Pandemic, I find [dining context] frustrating.0.79 ***0.049
During the Pandemic, I find [dining context] is mostly a pain.0.94 ***0.047
During the Pandemic, I find [dining context] boredom in any store.0.61 ***0.046
Shopper Avoidance (α = 0.79)0.65 a
I worry about catching COVID-19 from [dining context]0.88 ***0.058
I often went without, so that I could avoid [dining context]0.73 ***0.057
Dining Intention (α = 0.88)0.71 a
I often [dining context].0.89 ***0.048
I recommended [dining context] at restaurants.0.79 ***0.049
I tried to [dining context].0.84 ***0.049
Note: α = Cronbach’s alpha; Std. Est. = standardized estimate; Std. Err. = standard error; a = AVE; * = p < 0.001. *** = p < 0.001.

Appendix B

Table A2. Hypothesis recap for H2-H3, and H5- H7.
Table A2. Hypothesis recap for H2-H3, and H5- H7.
Dine-InTakeoutDelivery
βp<βp<βp<
H20.2550.0010.1180.050.1650.001
H30.7010.0010.6770.0010.6590.001
H50.2850.0010.4620.0010.4920.001
H60.2290.0010.2210.0010.1450.05
H7−0.1810.001−02830.001−0.4250.001
Table A3. Hypothesis recap H1, H4, and H10.
Table A3. Hypothesis recap H1, H4, and H10.
Dine-InTakeoutDelivery
βp<βp<βp<
H10.5980.0010.0370.509−0.1460.010
H40.0470.6260.0720.4110.2870.001
H10−0.6830.001−0.1180.2310.0600.436

Appendix C

Figure A1. Moderation slope analysis for fear and avoidance path.
Figure A1. Moderation slope analysis for fear and avoidance path.
Tourismhosp 05 00041 g0a1
Figure A2. Moderation slope analysis for fear and intention path in the delivery condition.
Figure A2. Moderation slope analysis for fear and intention path in the delivery condition.
Tourismhosp 05 00041 g0a2
The slope analyses can be found in Appendix C, Figure A1 and Figure A2, demonstrating these outcomes. In Appendix C, Figure A1, we can see that the exercise of environmental control by the diner decreased the avoidance in the dine-in and takeout conditions. This is a valuable finding as it provides evidence that the diners’ fear can be at least mitigated to some degree coaxing them into a more pre-fear engagement with the restaurant. Further, in Appendix C Figure A2, we see that environmental control dampens the positive relationship between fear and intention to use delivery. This is very reinforcing to the information in Appendix C, Figure A1, further demonstrating that diners, given some level of environmental control, can be coaxed into returning to in-restaurant dining.

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Figure 1. Cognitive experiential self-theory model.
Figure 1. Cognitive experiential self-theory model.
Tourismhosp 05 00041 g001
Figure 2. Research study model.
Figure 2. Research study model.
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Figure 3. Moderation model.
Figure 3. Moderation model.
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Table 1. Demographics.
Table 1. Demographics.
AgeIncEmployment
N% N% N%
18–2414111.5%Less than USD 10,000867.0%Full-Time41734.0%
25–3421917.9%USD 10,000–USD 29,99926821.9%Part-Time16913.8%
35–4419515.9%USD 30,000–USD 49,99930524.9%Unemployed—Looking957.8%
45–5419115.6%USD 50,000–USD 69,99920616.8%Unemployed—Not Looking846.9%
55–6412810.4%USD 70,000–USD 89,9991189.6%Retired33827.6%
65–7425520.8%USD 90,000–USD 99,999756.1%Student443.6%
75–84937.6%USD 100,000–USD 149,9991209.8%Disabled786.4%
85+30.2%USD 150,000+473.8%
Living in the HomeChildren in the HomeGender
N% N% N%
130224.7%088672.3%Male60249.1%
261450.1%119015.5%Female61350.0%
318915.4%2907.3%Non-Binary60.5%
4786.4%3322.6%Prefer Not to Say40.3%
5312.5%4171.4%
6 +110.9%560.5%
6+40.3%
Table 2. Measurement model fit statistics.
Table 2. Measurement model fit statistics.
χ2dfNormed χ2RMSEACFINFITLI
Aggregate568.4051374.1490.050.970.960.96
Dine-In325.551661.960.050.980.950.97
Takeout335.211662.020.050.960.930.95
Delivery428.951662.580.060.950.920.94
Note: χ2 = chi-square, df = degrees of freedom, Normed χ2 = normed chi-square, RMSEA = root mean square of approximation, CFI = comparative fit index, NFI = normed fit index, TLI = Tucker–Lewis Index.
Table 3. Validity assessment and correlation matrix.
Table 3. Validity assessment and correlation matrix.
CRAVEMSVASVFearAvoidAntip.IntentRisk
Fear0.9400.7970.5040.1490.893 *
Avoid0.7840.6470.5040.2210.7100.805 *
Antipathy0.8310.6270.2030.1080.2170.3560.792 *
Intention0.9100.7170.2350.103−0.114−0.328−0.2370.847 *
Risk0.8470.5310.2350.1540.1790.3810.450−0.4850.729 *
Note: Avoid = avoidance; Antip. = antipathy; Intent = intention; AVE = average variance extracted; CR = critical ratio; MSV = maximum shared squared variance; and ASV = average shared squared variance (ASV). * = square root of AVE.
Table 4. Nested model fit specifications and path estimates.
Table 4. Nested model fit specifications and path estimates.
Path EstimatesAllDine-InTakeoutDelivery
βS.E.βS.E.βS.E.βS.E.
H1Fear toRisk0.179 ***0.040.598 ***0.070.037 NS0.07−0.146 **0.08
H2Fear toAntipathy0.141 ***0.040.255 ***0.090.118 *0.060.165 ***0.07
H3Fear toAvoid0.645 ***0.050.701 ***0.090.677 ***0.090.659 ***0.09
H4Fear toIntention0.165 ***0.080.047 NS0.190.072 NS0.120.287 ***0.12
H5Risk ToAntipathy0.425 ***0.040.285 ***0.070.462 ***0.060.492 ***0.06
H6Risk ToAvoid0.211 ***0.030.229 ***0.060.221 ***0.060.145 *0.05
H7Risk ToIntention−0.409 ***0.05−0.181 **0.09−0.283 ***0.07−0.425 ***0.07
H8Antipathy toAvoid0.121 ***0.03−0.001 NS0.040.051 NS0.060.131 NS0.05
H9Antipathy toIntention0.017 NS0.040.072 NS0.06−0.064 NS0.06−0.026 *0.06
H10Avoid toIntention−0.296 ***0.06−0.683 ***0.14−0.118 NS0.090.060 NS0.10
Fit: χ2 = 1238.44, df = 476; RMSEA = 0.03; CFI0 = 0.97; NFI = 0.96; TLI = 0.97. Note: *** p < 0.001; ** p < 0.01; * p < 0.05; NS = non-significant.
Table 5. Hypothesis support recap.
Table 5. Hypothesis support recap.
Dining Context
HypothesisAll DataDine-InTakeoutDelivery
Path EstimatesOutcomeβββΒ
H1Fear toRiskPartial SupportAcceptAcceptRejectAccept
H2Fear toAntipathySupportedAcceptAcceptAcceptAccept
H3Fear toAvoidSupportedAcceptAcceptAcceptAccept
H4Fear toIntentionPartial SupportAcceptRejectRejectAccept
H5Risk ToAntipathySupportedAcceptAcceptAcceptAccept
H6Risk ToAvoidSupportedAcceptAcceptAcceptAccept
H7Risk ToIntentionSupportedAcceptAcceptAcceptAccept
H8Antipathy toAvoidPartial SupportAcceptRejectRejectAccept
H9Antipathy toIntentionRejectRejectRejectRejectReject
H10Avoid toIntentionPartial Support AcceptAcceptRejectReject
Table 6. Moderation analysis.
Table 6. Moderation analysis.
Dining ContextBaseDine-inTakeoutDelivery
HypothesesPathModerationEstimateS.E.EstimateS.E.EstimateS.E.EstimateS.E.
Hyp. 11aFear to RiskFear0.237 ***0.0320.587 ***0.0450.089 NS0.056−0.030 NS0.058
Fear_EnvCtrl_Inter−0.042 NS0.029−0.052 NS0.037−0.114 NS0.0520.077 NS0.053
EnvCtrl−0.090 ***0.032−0.018 NS0.043−0.037 NS0.057−0.163 ***0.059
Hyp. 11bFear to AntipathyFear0.241 ***0.0320.421 ***0.0490.171 ***0.0550.133 *0.057
Fear_EnvCtrl_Inter0.009 NS0.0280.066 NS0.041−0.035 NS0.051−0.001 NS0.052
EnvCtrl−0.016 NS0.0320.043 NS0.048−0.026 NS0.056−0.057 NS0.058
Hyp. 11cFear to IntentFear−0.168 ***0.033−0.551 ***0.047−0.065 NS0.0510.229 ***0.051
Fear_EnvCtrl_Inter0.014 NS0.0290.086 *0.0390.030 NS0.047−0.149 ***0.047
EnvCtrl0.106 *0.033−0.047 NS0.0460.068 NS0.0520.244 ***0.052
Hyp. 11dFear to AvoidFear0.697 ***0.020.770 ***0.0280.704 ***0.0360.633 ***0.033
Fear_EnvCtrl_Inter−0.058 ***0.018−0.100 ***0.023−0.071 ***0.0330.046 NS0.031
EnvCtrl0.147 ***0.020.180 ***0.0270.112 ***0.0360.188 ***0.034
Note: *** = p < 0.001, * = p < 0.05, NS = Not Significant.
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Jones, R.P.; Alimohammadirokni, M. Patrons Reaction to Fear in Different Dining Contexts: A Cognitive-Experiential Self-Theory Exploration. Tour. Hosp. 2024, 5, 689-712. https://doi.org/10.3390/tourhosp5030041

AMA Style

Jones RP, Alimohammadirokni M. Patrons Reaction to Fear in Different Dining Contexts: A Cognitive-Experiential Self-Theory Exploration. Tourism and Hospitality. 2024; 5(3):689-712. https://doi.org/10.3390/tourhosp5030041

Chicago/Turabian Style

Jones, Robert Paul, and Mohammad Alimohammadirokni. 2024. "Patrons Reaction to Fear in Different Dining Contexts: A Cognitive-Experiential Self-Theory Exploration" Tourism and Hospitality 5, no. 3: 689-712. https://doi.org/10.3390/tourhosp5030041

APA Style

Jones, R. P., & Alimohammadirokni, M. (2024). Patrons Reaction to Fear in Different Dining Contexts: A Cognitive-Experiential Self-Theory Exploration. Tourism and Hospitality, 5(3), 689-712. https://doi.org/10.3390/tourhosp5030041

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