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Article

Exploring How Consumers’ Perceptions of Corporate Social Responsibility Impact Dining Intentions in Times of Crisis: An Application of the Social Identity Theory and Theory of Perceived Risk

by
Yooin Noh
and
Pei Liu
*
Department of Hospitality Management, University of Missouri, Columbia, MO 65211, USA
*
Author to whom correspondence should be addressed.
J. Risk Financial Manag. 2024, 17(2), 44; https://doi.org/10.3390/jrfm17020044
Submission received: 1 November 2023 / Revised: 6 January 2024 / Accepted: 22 January 2024 / Published: 25 January 2024
(This article belongs to the Section Business and Entrepreneurship)
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Abstract

:
During the pandemic, the restaurant industry placed greater emphasis on corporate social responsibility (CSR) initiatives. However, there seems to be a dearth of comprehension regarding how customers’ perceived risks impacted their dining intentions. This challenges the industry to devise an effective crisis response strategy. Thus, this study investigates the relationship between perceived CSR, restaurant image, and dining intentions during the crisis. In addition, this study examines how perceived CSR influences three types of perceived risks associated with restaurants (quality, health, and environment) and how these types of risks influence restaurant image and dining intentions during this period. The results demonstrate that perceived CSR positively impacted a restaurant’s image and concurrently reduced perceived risks among consumers during the coronavirus disease 2019 (COVID-19) pandemic. Furthermore, perceived health risks had a negative influence on customers’ dining intentions. This study offers valuable insight into the theoretical foundations and managerial implications of CSR’s effects and risk management, particularly in the context of future pandemics within the restaurant industry.

1. Introduction

The unprecedented coronavirus disease 2019 (COVID-19) pandemic afflicted tens of thousands and caused thousands of deaths worldwide since 2020 (Manuel and Herron 2020). Among various industries, the restaurant sector has suffered a significant impact from the coronavirus’s outbreak, resulting in customer decline due to virus-related fears and rumors (Yu et al. 2021). Furthermore, this impact has the potential to intensify rapidly, posing a greater threat to the survival of businesses in the restaurant industry compared with other sectors (Song et al. 2021). Consequently, timely strategies have become imperative to reduce the harm and ensure swift responses during crises for restaurants.
In the restaurant industry, the concept of corporate social responsibility (CSR) gains heightened significance during crises (Lee and Ham 2021). CSR entails a business’s ethical and responsible practices that consider not only profit but also the well-being of employees, customers, and the larger community (Atzori et al. 2018). A restaurant that harbors a strong commitment to health and safety measures, supports its staff, and engages in initiatives to aid the community is likely to hold a positive image (Liu et al. 2022). This positive image can alleviate customers’ fears and uncertainties, leading to improved patronage and loyalty (Simakhajornboon and Sirichodnisakorn 2022). Similarly, understanding customer perceptions and decision-making factors during crises is vital to proactively prepare for unforeseen events, such as the outbreak of diseases like severe acute respiratory syndrome (SARS) (Pine and McKercher 2004) and the COVID-19 pandemic. By understanding how consumers respond to crises and what influences their decisions, restaurant businesses can tailor their strategies to align with customer expectations, including the importance of CSR values (Liu et al. 2022).
Traditionally, CSR has been recognized as a significant factor within the restaurant industry in enhancing customer retention (Chen et al. 2021). Moreover, CSR serves as a means to cultivate a favorable company image while attracting and retaining loyal customers, which aligns with the principles of the social identity theory (Ali et al. 2021; Reich et al. 2010). It also effectively distinguishes and elevates brand equity by contributing to environmental preservation and resource conservation (Liu et al. 2014). Given the inherent value of CSR, marketers regard CSR practices as a source of competitive advantage and a strategic avenue for overcoming business challenges, especially during a crisis (Harnrungchalotorn and Phayonlerd 2018).
Customers’ perception of risk plays a crucial role in changing their attitudes and behaviors within the restaurant industry (Rather 2021). The perceived risk among customers employs a substantial influence on their decision-making process, as consumers tend to be more attentive to potential negative consequences (Crespo et al. 2009). Chen and Chang (2012) also highlighted that perceived risk incorporates concerns regarding unfavorable environmental impacts related to consumer purchasing choices. Research has demonstrated a strong connection between a restaurant’s reputation and perceived risk, suggesting that reducing perceived risk can lead to increased customer loyalty and a higher likelihood of repeat visits (Lacey et al. 2009). Given the circumstances of the pandemic, it is likely that restaurant consumers may have exhibited caution in visiting dining establishments due to various risks, including health and environmental concerns. Consequently, the perceived risk experienced by customers during the COVID-19 pandemic could potentially weaken the relationship between perceived CSR and customer perceptions and behaviors within the restaurant industry.
Given the highly unprecedented effects of COVID-19, it is reasonable to assume that the connection between perceived CSR and customers’ attitudes and behaviors, such as their perceptions of a restaurant, brand loyalty, and dining intentions, may have been significantly influenced by various subfactors of perceived risk during this pandemic (Liu et al. 2022). Therefore, gaining a comprehensive understanding of how customers’ perceived risks impact their dining intentions is crucial for effective crisis response. However, previous studies have primarily focused on the financial performance resulting from CSR rather than on customers’ dining intentions (Lee et al. 2013). Furthermore, there is a lack of empirical evidence regarding how customers’ perceptions of CSR in restaurants contribute to such scenarios.
To address the research gap, this study aims to explore how consumers’ perceptions of CSR impact dining intentions by applying the theory of perceived risk. Specifically, this study seeks to (1) identify the types of perceived risks associated with restaurants during the crisis, (2) demonstrate the influence of consumers’ perceived CSR on restaurant image and their dining intentions, and (3) examine the relationships among perceived CSR, perceived risk, restaurant image, and dining intentions.

2. Literature Review

2.1. CSR Activities in the Hospitality Industry

CSR is not a new concept; in fact, it has gained increasing attention in the business world over the past decade (Albus and Ro 2017). This shift in focus is attributed to the fact that customers no longer judge a company solely based on its profit-making capabilities; they now expect companies to act as responsible corporate citizens, prioritizing more than just profits (Albus and Ro 2017). CSR incorporates a company’s obligations and responsibilities regarding its social impact. Caroll (1991) proposed a four-dimensional pyramid model to describe CSR, including economic, legal, ethical, and philanthropic dimensions. CSR practices are widely recognized as a source of competitive advantage and a means of generating long-term revenue for marketers in the hospitality industry (Chen et al. 2021).
Among the diverse range of hospitality and restaurant firms, Starbucks stands out as a company that places a strong emphasis on CSR in its management strategy. This is evident through initiatives like price discounts for tumbler users, efforts to reduce water consumption, and the employment of disabled baristas. Starbucks’ commitment to this management philosophy has not only allowed it to build lasting relationships with customers but has also positioned it as a more competitive brand compared with others (Harnrungchalotorn and Phayonlerd 2018). During the COVID-19 pandemic, numerous hospitality corporations embraced various CSR practices as part of their marketing strategies to navigate the business crisis (Tong et al. 2021). Furthermore, CSR has been viewed as an opportunity for firms to demonstrate their authenticity in times of crisis. For example, several branded hotels (Marriott, InterContinental, Hilton, etc.) provided complimentary accommodation or food to healthcare workers combating the COVID-19 pandemic as part of their strategic philanthropic activities during this challenging period (Rhou and Singal 2020).
Although many studies over several decades have aimed to demonstrate the impact of CSR in the hospitality and restaurant industries, only a few hospitality scholars have explored the effects of CSR activities during a pandemic. For instance, Shin et al. (2021) investigated how CSR philanthropic activities by hotels during COVID-19 influenced their financial performance and customer booking behavior. Similarly, Huang and Liu (2020) examined the effectiveness of CSR donation appeals in hospitality marketing during the pandemic. However, the impact of CSR activities in crisis circumstances has received relatively less attention in current hospitality research when compared with general CSR studies.

2.2. Social Identity Theory

The social identity theory, developed originally through early research in social psychology by Tajfel (1978), forms the foundation of this study. According to the social identity theory, customers tend to identify themselves with businesses they perceive as highly socially responsible. Consequently, they attribute a higher value to these businesses and exhibit a greater degree of commitment, often leading to increased loyalty (Ali et al. 2021). Numerous studies have demonstrated that hotels and restaurants actively engaged in CSR practices can help consumers develop a meaningful social identity (e.g., Srivastava and Singh 2021). This, in turn, has a significant impact on consumer behavior and their support for the corporation (Ghaderi et al. 2019).
In light of these insights, this study is grounded in the assumption that the relationship between customer-perceived CSR and a restaurant’s image and dining intention can be effectively explained by the social identity theory. To elaborate, when a restaurant actively participates in CSR initiatives, it can create a positive image in the minds of consumers. This positive image, established in shared values and beliefs, may encourage consumers to choose the restaurant for their dining experiences.
Impact of Perceived CSR on Restaurant Image: Brand image refers to the general perceptions and beliefs of customers about a particular brand (Adeniji et al. 2015). It plays a crucial role in building brand value and enhancing a company’s competitiveness in the market (Chen et al. 2021). A brand’s image is shaped by various attributes, and in the highly competitive hotel and restaurant industry, establishing a strong brand is essential for business success (Sheth and Parvatiyar 2000). Notably, CSR promotes a positive company image while attracting and retaining new and loyal customers (Reich et al. 2010).
Previous research has consistently demonstrated a positive association between perceived CSR and restaurant image. For instance, Martínez et al. (2014) found that enhancing CSR practices can lead to an improved brand image and reputation, highlighting CSR’s significant contribution to brand image. In addition, Mohammed and Rashid (2018) explored the mediating role of brand image between CSR initiatives and customer satisfaction. Furthermore, Lho et al. (2019) provided evidence that the four dimensions of CSR (economic, philanthropic, ethical, and legal) positively influence a hotel’s brand image. On the basis of the aforementioned prior research, our study anticipates a positive impact of customers’ perceived CSR on a restaurant’s image. Thus, we hypothesize:
H1. 
The perceived CSR has a positive impact on the restaurant’s image.
Impact of Perceived CSR on Dining Intention: Dining intention toward socially responsible restaurants reflects the likelihood of customers recommending a restaurant to others, returning to it, or spreading positive word of mouth due to the restaurant’s socially responsible practices (Jeong and Jang 2010). This intention is a commonly used outcome variable to examine the effects of restaurants’ CSR practices on customer perceptions and responses (Xu and Jeong 2019). With an increasing number of restaurant customers becoming more conscious of socially responsible actions, such as environmental and social initiatives, CSR practices have gained importance in influencing customers’ dining intentions (Tong and Wong 2014).
To encourage restaurants to be more proactive in implementing CSR initiatives during the pandemic, it is crucial for them to understand the relationship between customers’ perceptions of CSR initiatives taken by restaurants during this crisis and their dining intentions. Previous research has shown that consumers’ perceived importance of CSR positively influences their intentions to revisit restaurants (Liu and Tse 2021). Similarly, Xu and Jeong (2019) found that green messages in restaurants positively impact dining intentions. Hwang et al. (2020) also demonstrated that Starbucks’ philanthropic CSR initiatives positively affect customers’ behavioral intentions, including the intention to use the service, word-of-mouth intentions, and willingness to pay more. Thus, we hypothesize:
H2. 
The perceived CSR has a positive impact on dining intention.

2.3. Perceived Risk Theory

The concept of perceived risk theory originates from the fields of marketing and consumer behavior literature, as established by Bauer (1960). It is defined as an individual’s subjective evaluation of uncertainty regarding the potential financial, physical, and social outcomes associated with a consumption experience, as articulated by Liebermann and Stashevsky (2002). These perceptions tend to yield significant behavioral implications, particularly influencing consumer purchasing decisions, given that individuals tend to focus more on the potential negative consequences of their actions, as emphasized by Kim et al. (2008). A previous study highlighted that an increased perception of risk among customers can have a negative influence on their future intentions of dining out (Wei et al. 2021).
Impact of Perceived CSR on Perceived Risk: The perceived CSR in the restaurant industry may have influenced the perceived risks that customers associate with dining out during the COVID-19 pandemic (Yu et al. 2021). Potential customers may have hesitated to visit restaurants due to their heightened perception of risk (Shin et al. 2021). Consequently, even if customers held a positive image of a restaurant and possessed dining intentions toward establishments implementing CSR initiatives, they might have found these options less appealing during this crisis because of increased perceived risks. Accordingly, the following hypothesis is proposed:
H3. 
The perceived CSR has a negative impact on perceived risk.
H3a. 
The perceived CSR has a negative impact on quality risk.
H3b. 
The perceived CSR has a negative impact on health risk.
H3c. 
The perceived CSR has a negative impact on environmental risk.
Impact of Perceived Risk on Restaurant Image: Only a limited number of studies have investigated the influence of perceived risk on restaurant image in the hospitality industry, particularly when examining perceived risk from a multidimensional perspective. For example, Hwang and Choe (2020) examined the impact of seven dimensions of perceived risk in the image of edible insect restaurants. The results of their study identified that five dimensions of perceived risk (i.e., quality, psychological, health, financial, and social) negatively affected the image of edible insect restaurants. In addition, Yoon and Chung (2018) demonstrated that hygienic and environmental risks toward food truck dining have a negative impact on consumers’ image of it. In accordance with the special circumstances of the pandemic, this study only adopts three dimensions of perceived risk. These dimensions encompass (1) quality risk, referring to concerns about a product’s falling short of expectations; (2) health risk, associated with the possibility of a product or service posing health hazards; and (3) environmental risk, covering concerns regarding a product or service’s environmental impact (Al-Ansi et al. 2019; Featherman and Pavlou 2003; Garner 1986; Grewal et al. 1994).
Following the traditional research framework within the hospitality research literature (e.g., Hwang and Choe 2020) and considering the unique nature of this pandemic, the following hypothesis is proposed:
H4. 
The perceived risks have a negative impact on a restaurant’s image.
H4a. 
The quality risk has a negative impact on a restaurant’s image.
H4b. 
The health risk has a negative impact on a restaurant’s image.
H4c: 
The environmental risk has a negative impact on a restaurant’s image.
Impact of Perceived Risk on Dining Intention: Several studies have demonstrated the impact of perceived risk on dining intentions in the restaurant industry. For instance, Yu et al. (2021) illustrated how four types of perceived COVID-19 risk impacted post-traumatic stress disorder and customers’ intention to revisit restaurants, including physical, psychological, financial, and performance risks. Huifeng et al. (2020) revealed that two risk factors (performance and financial risks) negatively affected customers’ intentions to visit restaurants. Choi et al. (2013) found that risk perception of street food consumption is highly associated with health and environmental risks regarding food safety. Consumers aware of these risks were more likely to have a negative attitude toward street food and were less likely to repurchase or recommend street food to others. Similarly, the COVID-19 crisis led consumers to avoid eating foods that are unsafe for their health and the environment and pose a high risk of exposure to the virus at restaurants (Yost and Cheng 2021). Therefore, the following hypothesis is proposed:
H5. 
The perceived risks have a negative impact on dining intention.
H5a. 
The quality risk has a negative impact on dining intention.
H5b. 
The health risk has a negative impact on dining intention.
H5c. 
The environmental risk has a negative impact on dining intention.

2.4. Relationship between Restaurant Image and Dining Intention

The existing literature has consistently demonstrated the substantial influence of restaurant image on customers’ dining intentions (Espinosa et al. 2018). Within the restaurant industry, a favorable restaurant image is widely recognized as a robust predictor of customers’ dining intentions and their likelihood to share positive feedback with others (Chen et al. 2014). Building upon these established findings, we suggest that a restaurant’s image will likely have a substantial and meaningful influence on customers’ dining intentions. Thus, we hypothesize:
H6. 
A restaurant’s image has a positive influence on dining intention.

2.5. Proposed Research Model

We suggested the proposed research model of this study in Figure 1, including the perceived CSR, perceived risk, restaurant image, and dining intention. Perceived risk has three subfactors: quality risk, health risk, and environmental risk. The six hypotheses are presented in the proposed theoretical framework.

3. Methods

3.1. Participants and Data Collection

The participants for this study were recruited via Qualtrics “www.qualtrics.com (accessed from 1 to 14 May 2020)”. Initially, we collected a total of 573 completed surveys. Our target participants were individuals over 18 years old who had dined at a restaurant after the onset of COVID-19. Following the exclusion of unusable data, which included responses with significant missing values, failed attention checks, rapidly completed surveys and similar or identical responses, we retained 526 responses for the subsequent analysis.

3.2. Measures and Instrument Development

Before responding to the survey questions, the participants were provided with the definition of CSR. They were then instructed to specify the name of the restaurant they had most recently visited in person. On the basis of their recent dining experience at that restaurant, the participants proceeded to answer the remaining questionnaires. All variables were assessed using multiple items adapted from existing literature and tailored to the context of this study. Specifically, perceived CSR was measured using nine items adapted from Brown and Dacin (1997) and Wong (2019), whereas perceived risks were assessed with nine items selected from Al-Ansi et al. (2019), Baker et al. (2016), and Klerck and Sweeney (2007). Restaurant image was evaluated using six items from Hwang and Choe (2019), and dining intention was gauged with three items sourced from Zeithaml and Bitner (1996). All measurement items were rated on a seven-point Likert scale, ranging from 1 (strongly disagree) to 7 (strongly agree). Demographic questions for the participants were included at the end of the survey.

3.3. Data Analysis

Data were analyzed using SPSS v. 23.0 and AMOS. First, using SPSS 23.0 software, this study performed descriptive statistics (e.g., frequency and percentages) and exploratory factor analysis (EFA) to extract the perceived risks of the restaurants during COVID-19. Second, using AMOS 23 software, reliability, and validity were measured through confirmatory factor analysis (CFA), and to verify the conceptual framework and validate the suggested hypotheses, this structured equation model (SEM) was performed.

3.4. Declaration of Generative AI and AI-Assisted Technologies in the Writing Process

During the preparation of this work, the authors used the Google Translate tool to check grammar errors and sentence structures. After using this tool/service, the authors reviewed and edited the content as needed and took full responsibility for the publication’s content.

4. Results

4.1. Participant Profiles

A summary of the demographic characteristics of the 526 responses is provided in Table 1. Among the respondents, 42.2% were male and 57.8% were female. The largest age group among the respondents was under 30 (31%), followed by those above 60 (24.7%). In terms of ethnicity, 392 (74.5%) respondents identified as Caucasian. Regarding the highest level of education, the majority of the respondents achieved a bachelor’s degree (27.0%). In terms of household income, 31.4% of the respondents reported an income of under USD 40,000, whereas 20.5% reported an income of USD 100,000 and above. The most common response for the average daily accommodation cost was in the range of USD 50–99, accounting for 46.8% of all responses. Approximately 33.3% of the respondents mentioned that they dined out at restaurants a few times per week before the COVID-19 pandemic, whereas nearly 28.1% reported dining out once a week prior to the outbreak. However, this percentage decreased following the onset of COVID-19, with only 21.5% of the respondents indicating that they dined out at restaurants a few times per week.

4.2. Principal Component Analysis

We conducted a principal component analysis to identify the perceived risks associated with restaurants during the crisis. Following a comprehensive literature review, we adhered to the suggestion that three subgroups of perceived risk should be analyzed collectively. These subgroups were categorized as quality, health, and environmental risks. The results of the principal component analysis confirmed the validity of the factor model, with a Kaiser–Meyer–Olkin (KMO) measure of sampling adequacy at 0.910. Furthermore, the factor model accounted for 85.183% of the variance. Notably, all items exhibited factor loadings exceeding 0.761. In addition, the Cronbach’s alpha values fell within the range of 0.890 to 0.921, indicating a high level of reliability exceeding 0.7 (refer to Table 2).

4.3. Confirmatory Factor Analysis (CFA)

CFA was employed to verify the reliability and validity of the scales (Anderson and Gerbing 1988). The results are presented in Table 3. The CFA results were all above the acceptable level (χ2 = 1230.635, df = 301, χ2/df = 4.088, p < 0.001, IFI = 0.925, CFI = 0.925, TLI = 0.913, and RESEA = 0.077). The factor loadings using standardized regression weights ranged from 0.59 to 0.951, and all factor loadings were significant at p < 0.001. Consequently, it was confirmed that all the measurement items in this study were reliable. In addition, average variance extracted (AVE) and composite reliability (CR) were examined to identify internal consistency and convergent validity. The AVE values ranged from 0.593 to 0.8, whereas the CR values ranged from 0.9 to 0.928. Given that the AVE values were higher than 0.5 and the CR values were higher than 0.7, the internal consistency and convergent validity of the measurement variables were acceptable (Fornell and Larcker 1981). Lastly, we investigated discriminant validity to assess differentiation among the constructs. According to Fornell and Larcker (1981), discriminant validity is confirmed when the AVE value is greater than the squared correlation coefficients of the constructs (see Table 4).
In addition, average variance extracted (AVE) and composite reliability (CR) were examined to identify internal consistency and convergent validity. The AVE values ranged from 0.593 to 0.8, whereas the CR values ranged from 0.9 to 0.928. Given that the AVE values were higher than 0.5 and the CR values were higher than 0.7, the internal consistency and convergent validity of the measurement variables were acceptable (Fornell and Larcker 1981). Lastly, we investigated discriminant validity to assess differentiation among the constructs. According to Fornell and Larcker (1981), discriminant validity is confirmed when the AVE value is greater than the squared correlation coefficients of the constructs (see Table 4).

4.4. Structural Equation Modeling (SEM)

To validate the suggested hypotheses, we adopted SEM. The goodness of fit of this model was appropriate (χ2 = 1161.5, df = 297, χ2/df = 3.910, p < 0.001, NFI = 0.909, IFI = 0.931, CFI = 0.930, TLI = 0.918, and RMSEA = 0.074). The SEM results with standardized coefficients are presented in Figure 2. Specifically, perceived CSR (β = 0.397, p < 0.001) positively affected a restaurant’s image, thus supporting H1. Perceived CSR was significantly associated with quality risk (β = −0.116, p < 0.01), health risk (β = −0.121, p < 0.01), and environmental risk (β = −0.157, p < 0.05); thus, H3a, H3b, and H3c were statistically supported. Quality risk (β = −0.114, p < 0.05) and environmental risk (β = −0.099, p < 0.05) were found to be significantly associated with restaurant image; thus, H4a and H4c were supported. In addition, quality risk (β = −0.059, p < 0.05) and health risk (β = −0.152, p < 0.05) were found to be significantly associated with dining intention; thus, H5a and H5b were supported. Moreover, the data analysis revealed that restaurant image positively affected dining intention (β = 0.993, p < 0.001); therefore, H6 was supported. We summarized the hypothesis testing results in Table 5.

5. Discussion and Implications

5.1. Summary of the Findings

Although previous research has primarily focused on the relationship between CSR and financial performance in the restaurant industry, less attention has been given to understanding how customers’ perceptions of CSR impact their dining intentions, especially during a crisis. There has been a lack of theoretical evidence that explores the role of perceived risk in these dynamics. This study aimed to bridge this gap by investigating whether the CSR initiatives implemented by restaurants influence their overall image and, subsequently, customers’ dining intentions. In addition, we examined the influence of three specific types of perceived risk, namely, quality, health, and environmental risks, on the relationships among these variables. The results of this study could provide valuable insight into the practical strategies that the restaurant industry can apply in times of crisis.

5.2. Theoretical Implications

This research can provide several theoretical implications for the restaurant industry. First, our study added to the literature related to the effect of CSR initiatives during the pandemic in the restaurant industry. Our results show that perceived CSR was a strong predictor of restaurant image compared with dining intention during the crisis. Specifically, we demonstrate that the more customers were aware of a restaurant’s CSR, the higher was the restaurant’s image. Similar to previous research showing that customers’ perceived CSR positively impacts brand image (e.g., Martínez et al. 2014), our study confirmed that customers’ perceived CSR positively impacts restaurant image even during the COVID-19 pandemic. However, the lack of a significant association between perceived CSR and dining intention may have been due to various factors. For instance, consumers may perceive CSR initiatives positively, which would enhance a restaurant’s image as socially responsible. However, this positive image might not necessarily translate directly into their dining intentions during a crisis, where other factors like health and safety risks play a more dominant role (Yost and Cheng 2021). The relationship between CSR and dining intention could be mediated or influenced by other variables not considered in the study, such as trust in the CSR initiatives or the severity of the crisis (Kim and Ham 2016; Kim et al. 2021).
Second, we confirmed three types of perceived risk at restaurants during the pandemic. We extracted three factors of perceived risk (i.e., quality, health, and environmental risks) through principal component analysis. Furthermore, CFA was performed to determine the adequacy of the measurement structure, and the results showed high levels of validity and reliability. Prior research has demonstrated that four dimensions of the perceived risk of COVID-19 (i.e., psychological, financial, performance, and physical risks) are predictors of post-traumatic stress disorder (PTSD) and revisit intention at hotels (Yu et al. 2021). Thus, the results of the current study contribute to important theoretical implications by investigating three types of perceived risk in times of crisis in the restaurant industry.
Third, our research enriched the understanding of CSR in times of crisis. In particular, our results contribute to the existing COVID-19 hospitality literature indicating that customers’ perceived risk should be taken into consideration to strengthen the effects of CSR practices during the pandemic. This study reinforces the theoretical support that perceived CSR reduces three aspects of perceived risk (i.e., quality, health, and environmental risks). Given that diverse hospitality corporations were involved in various CSR initiatives as one of the risk management strategies to respond to the COVID-19 pandemic, this study can contribute to the hospitality literature by understanding that perceived CSR decreased three types of perceived risk (i.e., quality, health, and environmental) during the pandemic. Furthermore, this research can provide a body of hospitality literature on how people perceive and interpret CSR during crises in the restaurant industry. Our results demonstrate that quality and environmental risks were not significant indicators of consumers’ dining intention. This finding is not surprising because consumers may prioritize other factors, such as health and safety concerns, over quality and environmental concerns during a pandemic (Yost and Cheng 2021), confirming our study’s results that health risks significantly impacted consumers’ intention to dine out at a restaurant other than the mediating effect of restaurant image. During a pandemic, consumers prioritize their immediate safety and health, often placing these concerns above other factors, such as a restaurant’s image.
Fourth, the results of this study confirmed the positive relationship between restaurant image and dining intention, which is consistent with the results of previous research (Hwang and Choe 2020; Namkung and Jang 2017). Specifically, when consumers have a positive image of a restaurant, they are more willing to eat out at restaurants. On a related note, we identified the important role of a restaurant’s image by examining its impact on dining intentions during the pandemic, which can contribute to theoretical implications.

5.3. Managerial Implications

On the basis of the findings above, the authors present a series of practical implications, particularly for the restaurant industry. First, one finding provides significant guidance for restaurants to understand the role of CSR on restaurant image during the pandemic. In times of crisis, implementing CSR initiatives can be traditionally viewed as a great opportunity to show authenticity and reduce customers’ skepticism toward those initiatives. Thus, restaurant companies should perform a variety of CSR initiatives to enhance restaurant image and visit intention during the uncommon golden period by supporting local communities, donating food, ensuring employees’ well-being, and reducing environmental issues. For instance, restaurants can demonstrate their commitment to the well-being of the local community by engaging in initiatives such as food drives, partnering with local charities, or even offering free meals to those in need. Meanwhile, restaurants can prioritize the health, safety, and overall welfare of their staff. This may involve implementing stringent health and safety protocols, offering mental health support, or providing flexible work arrangements to accommodate employees’ needs. Furthermore, there has been an increasing trend of the importance of CSR initiatives in the food service industry. These CSR marketing practices were not only highlighted during the pandemic’s phases. Thus, restaurants can harness the benefits of CSR initiatives for future advertising plans to accelerate postcrisis recovery. For example, restaurants can create advertisements that showcase their sustainability efforts, which may include using ecofriendly packaging, sourcing ingredients from local farms, or implementing energy-saving practices.
Second, our findings identified that perceived health risks negatively affect customers’ dining intentions. This result is plausible because customers may fear being infected with the virus while eating out during this period. Hence, restaurant practitioners should lead initiatives that prove the capacity of the industry to help their customers reduce their perceived health risks. For example, it would be crucial for restaurants to adopt various cleaning technology systems (e.g., contactless ordering kiosks and cleaning robot systems) to minimize perceived risks in the health aspect. In addition, restaurant managers need to provide strict employee hygiene training by mandatorily letting the staff wear masks and asking them to frequently wash their hands before and after serving customers.
Furthermore, our results indicate a negative association between perceived quality and environmental risks with a restaurant’s image. Thus, reducing perceived quality and environmental risks is crucial for enhancing a restaurant’s image. To reduce perceived quality risks, restaurants could emphasize providing quality food, ensuring food safety practices, and implementing standardized cooking procedures and staff training. To reduce perceived environmental risks, restaurants could implement sustainable practices, such as recycling, composting, and reducing single-use plastics. They can also enhance energy efficiency by using LED lighting, energy-efficient appliances, and smart thermostats. By addressing quality and environmental risks and making these efforts visible to customers, restaurants can positively influence their image, attract more consumers, and build long-term loyalty.

5.4. Limitations and Future Research

Although the current study identified interesting findings and implications, there are some limitations of this study that are recommended to be addressed in future studies.
First, this study concentrated on the effects of CSR only in the food service industry. Therefore, the validity of the research results should be expanded through comparison with other service industries (e.g., hotels) in future studies. For example, during the pandemic, large-scale hotel corporations were also involved in CSR activities, such as free accommodation for healthcare workers and food donations. Hence, we expect that diverse types of perceived risk can weaken the relationship between perceived CSR and visit intention in other service businesses.
Second, this study did not classify consumers according to personality traits or individual characteristics. Accordingly, we may have overlooked the potential effects of various individualistic features on customers’ dining intentions. Consumers’ personal characteristics, such as environmental consciousness, skepticism, or personal value, can be crucial in their attitudes toward CSR activities. Thus, future research should include how consumer knowledge or characteristics may influence the effects of CSR on individuals’ dining intentions.
Third, this study had a cross-sectional design, so the data were gathered during the COVID-19 period. However, it is important for the restaurant industry to mitigate customers’ perceived risks even in the post-pandemic era. In addition, the types of customer-perceived risks may differ after the post-pandemic phase because the impact and the types of perceived risks may have changed over time compared with those during the pandemic. Therefore, follow-up studies should consider how the impact and the type of risk perceived by customers differed in the post-pandemic period compared with during the pandemic in the restaurant industry.

Author Contributions

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

Funding

This research was funded by USDA-NIFA grant number 1025308.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest.

References

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Jrfm 17 00044 g001
Figure 1. Proposed research model.
Figure 1. Proposed research model.
Jrfm 17 00044 g001
Jrfm 17 00044 g002
Figure 2. Standardized theoretical path coefficients.
Figure 2. Standardized theoretical path coefficients.
Jrfm 17 00044 g002
Table 1. Demographic profile (n = 526).
Table 1. Demographic profile (n = 526).
Demographic CharacteristicsDescriptiveFrequency
(n = 526)		Percentage
(%)
GenderMale22242.2
Female30457.8
AgeUnder 3016831.0
31–408215.6
41–507514.3
51–607614.4
Over 6013024.7
EthnicityCaucasian39274.5
African American7313.9
Native American81.5
Hispanic/Latino315.9
Asian/Pacific Islander214.0
Others10.2
Highest Education LevelLess than a high school diploma91.7
High school diploma/GED10620.2
Some college13726.0
Associate degree6312.0
Bachelor’s degree14227.0
Graduate Degree6913.1
Household IncomeLess than USD 40,000 16531.4
USD 40,000–59,999 10319.6
USD 60,000–79,9998916.9
USD 80,000–99,9996111.6
USD 100,000 and above10820.5
The frequency of dining out at restaurants before the COVID-19 virusOnce a day224.2
A few times per week17533.3
Once a week14828.1
2–3 times per month12624.0
Once a month5510.5
The frequency of ordering restaurant foods after COVID-19Once a day152.9
A few times per week11321.5
Once a week17733.7
2–3 times per month12323.4
Once a month8816.7
None101.9
Table 2. Exploratory factor analysis for the three types of perceived risk.
Table 2. Exploratory factor analysis for the three types of perceived risk.
VariablesStandardized Factor LoadingsEigenvalueExplained Variance (%)Cronbach’s Alpha
Health risk 6.40271.1350.890
I worry that ordering food from this restaurant is harmful.0.835
I worry about my health after ordering food from this restaurant.0.904
I worry that ordering food from this restaurant is unhealthy.0.794
Quality risk 0.7328.1340.912
I worry about the lower quality of this restaurant than before.0.761
I worry because of the low quality of this restaurant.0.912
I am concerned about the quality of this restaurant.0.865
Environmental risk 0.5325.9140.921
I am concerned about the cleanliness of this restaurant.0.899
I am concerned about the environmental conditions of this restaurant.0.867
I am concerned about the hygiene standards of this restaurant.0.829
Total explained variance = 85.183%; KMO measure of sampling adequacy = 0.910; Bartlett’s test of sphericity, p < 0.001.
Table 3. Confirmatory factor analysis with items and loadings.
Table 3. Confirmatory factor analysis with items and loadings.
Construct and Scale ItemStandardized Factor Loadings
Perceived CSR
This restaurant protects the environment. 0.725
This restaurant shows it is committed toward society by improving the welfare of the communities in which it operates. 0.823
This restaurant directs part of its budget to donations to social causes. 0.782
This restaurant provides a safe and relaxed dining environment for customers. 0.621
This restaurant offers good working conditions for its employees. 0.691
This restaurant is very involved with the local community. 0.805
This restaurant commits to using a substantial portion of its profits to help communities where it does its business. 0.875
This restaurant includes charity work in its business activities. 0.791
This restaurant shows concern over environmental degradation. 0.789
Quality risk
I worry about the lower quality of this restaurant than before. 0.870
I worry because of the low quality of this restaurant. 0.951
I am concerned about the quality of this restaurant. 0.840
Health risk
I worry that ordering food from this restaurant is harmful. 0.802
I worry about my health after ordering food from this restaurant. 0.930
I worry that ordering food from this restaurant is unhealthy. 0.861
Environmental risk
I am concerned about the cleanliness of this restaurant. 0.920
I am concerned about the environmental conditions of this restaurant. 0.919
I am concerned about the hygiene standards of this restaurant. 0.843
Restaurant image
This restaurant has a distinctive character. 0.589
I often say positive things about this restaurant. 0.841
I hear positive feedback about this restaurant. 0.780
The overall image for dining out at this restaurant is good. 0.821
The overall image of this restaurant is great. 0.873
Overall, I have a good image of this restaurant. 0.887
Dining intention
I would order food (dining-in or dining-out) from this restaurant again. 0.835
I am willing to order food (dining-in or dining-out) from this restaurant again. 0.892
I plan to return to order food (dining-in or dining-out) from this restaurant. 0.884
Goodness-of-fit statistics: χ 2 = 1230.635, df = 301, χ 2/df = 4.088, p < 0.001, IFI = 0.925, CFI = 0.925, TLI = 0.913, and RESEA = 0.077. All factor loadings are significant at p < 0.001.
Table 4. Discriminant validity and means of variables.
Table 4. Discriminant validity and means of variables.
ConstructPCSRQRHRERRIDIAVECRMean
(SD)
PCSR1 0.5930.9294.89
(1.01)
QR−0.118
(0.01)		1 0.7890.9183.03
(1.57)
HR−0.129
(0.01)		0.731
(0.53)		1 0.7450.92.73
(1.65)
ER−0.126
(0.01)		0.766
(0.59)		0.785
(0.62)		1 0.80.9232.98
(1.69)
RI0.569
(0.32)		−0.363
(0.13)		−0.331
(0.11)		−0.361
(0.13)		1 0.6470.9165.27
(1.13)
DI0.424
(0.18)		−0.439
(0.19)		−0.453
(0.21)		−0.44
(0.19)		0.716
(0.51)		10.7580.9035.85
(1.18)
PCSR: perceived corporate social responsibility; QR: quality risk; HR: health risk; ER: environmental risk; RI: restaurant image; DI: dining intention.
Table 5. Standardized parameter estimates for the structural model.
Table 5. Standardized parameter estimates for the structural model.
Standardized Estimatet-ValueHypothesis
H1PCSRJrfm 17 00044 i001RI0.397 ***10.273Supported
H2PCSRJrfm 17 00044 i001DI−0.028−0.644Not supported
H3aPCSRJrfm 17 00044 i001QR−0.116 *−1.779Supported
H3bPCSRJrfm 17 00044 i001HR−0.121 *−1.884Supported
H3cPCSRJrfm 17 00044 i001ER−0.157 **−2.081Supported
H4aQRJrfm 17 00044 i001RI−0.114 **−3.100Supported
H4bHRJrfm 17 00044 i001RI0.0110.263Not supported
H4cERJrfm 17 00044 i001RI−0.099 **−2.424Supported
H5aQRJrfm 17 00044 i001DI−0.028−0.627Not supported
H5bHRJrfm 17 00044 i001DI−0.152 **−2.817Supported
H5cERJrfm 17 00044 i001DI−0.0040.076Not supported
H6RIJrfm 17 00044 i001DI0.933 ***10.683Supported
PCSR = perceived corporate social responsibility; QR = quality risk; HR = health risk; ER = environmental risk; RI = restaurant image; DI = dining intention. * p < 0.01, ** p < 0.05, *** p < 0.001.
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Noh, Y.; Liu, P. Exploring How Consumers’ Perceptions of Corporate Social Responsibility Impact Dining Intentions in Times of Crisis: An Application of the Social Identity Theory and Theory of Perceived Risk. J. Risk Financial Manag. 2024, 17, 44. https://doi.org/10.3390/jrfm17020044

AMA Style

Noh Y, Liu P. Exploring How Consumers’ Perceptions of Corporate Social Responsibility Impact Dining Intentions in Times of Crisis: An Application of the Social Identity Theory and Theory of Perceived Risk. Journal of Risk and Financial Management. 2024; 17(2):44. https://doi.org/10.3390/jrfm17020044

Chicago/Turabian Style

Noh, Yooin, and Pei Liu. 2024. "Exploring How Consumers’ Perceptions of Corporate Social Responsibility Impact Dining Intentions in Times of Crisis: An Application of the Social Identity Theory and Theory of Perceived Risk" Journal of Risk and Financial Management 17, no. 2: 44. https://doi.org/10.3390/jrfm17020044

APA Style

Noh, Y., & Liu, P. (2024). Exploring How Consumers’ Perceptions of Corporate Social Responsibility Impact Dining Intentions in Times of Crisis: An Application of the Social Identity Theory and Theory of Perceived Risk. Journal of Risk and Financial Management, 17(2), 44. https://doi.org/10.3390/jrfm17020044

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