Korea Tourism Research Association

Current issue

International Journal of Tourism and Hospitality Research - Vol. 31 , No. 10

[ Article ]
International Journal of Tourism and Hospitality Research - Vol. 31, No. 10, pp.73-83
ISSN: 1738-3005 (Print)
Print publication date 31 Oct 2017
Received 23 Aug 2017 Revised 10 Sep 2017 Accepted 15 Sep 2017
DOI: https://doi.org/10.21298/IJTHR.2017.10.31.10.73

Aging society
: A study on the role of philanthropic corporate social responsibility in the quick service restaurant industry
Jinsoo Hwang** ; Jung-Kyu Choi
**Associate professor, College of Hospitality and Tourism Management, Sejong University, Seoul 05000, Republic of Korea (jhwang@sejong.ac.kr)

Correspondence to : Assistant professor, Department of International Logistics, Dongseo University, e-mail: jkchoi@gdsu.dongseo.ac.kr

Funding Information ▼

Abstract

In recent years, the issue of poverty among the elderly has become an issue that the Korean government has made great efforts to solve. For example, the Korean government planned to create about 430,000 new jobs for the elderly by 2017. At this point, finding a role of the elderly in the food service industry is very important. Thus, this study examined the important role of philanthropic corporate social responsibility (PCSR), focusing on restaurants where people aged 65 and over provide services. For this, a theoretical model was developed in order to find the impact of PCSR on customer citizenship behavior (CCB). In addition, based on the existing theoretical background, it was proposed that brand preference moderates the relationship between PCSR and CCB. Data were collected from 259 customers who had visited a McDonald’s restaurant where those aged 65 and over had provided services in the past three months in Korea. The data analysis results indicated that PCSR has a positive influence on all four dimensions of CCB including tolerance, advocacy, helping, and feedback. Lastly, this study found the moderating role of brand preference in the relationships between (1) PCSR and advocacy and (2) PCSR and feedback. The important theoretical/managerial implications that were derived from the data analysis are presented and discussed in the last part of the paper.


Keywords: Philanthropic corporate social responsibility, Brand preference, Customer citizenship behavior, Restaurant industry

Ⅰ. Introduction

Recently, the aging of Korean society is emerging as an important, growing issue (The Korea Herald, 2014). In 2013, the population over 65 is 12.7% of the total population (Statistics Korea, 2014). In addition, the proportion of the 65-year-old population will increase to 24.3% in 2030 and 40.1% in 2060, respectively (Statistics Korea, 2014). This increase in the elderly population leads to various problems including the poverty of the elderly. To solve these problems, the Korean government had made efforts to create 43,000 new jobs for the elderly by 2017 (The Korea Herald, 2013).

Along with the efforts of the government, the restaurant industry is also trying to solve problems caused by the increase of the elderly. For example, since 2011, McDonald’s has provided seniors with the opportunity to work part-time through the ‘senior internship program.’ Such a program has helped solve the problem of aging and has received recognition from the Ministry of Health and Welfare for this achievement. From an organizational standpoint, the senior internship program played a major role in shaping customers’ positive attitudes toward the McDonald’s brand. This phenomenon needs to be examined in relation to the concept of philanthropic corporate social responsibility (hereafter PCSR). The PCSR refers to voluntary actions taken by a company for social development such as donations and the environment campaign (Carroll, 1979). In particular, PCSR activities play an important role in positively changing the attitudes of customers for companies (Servaes & Tamayo, 2013).

Furthermore, this study tried to explore how PCSR affects customer citizenship behavior (hereafter CCB) with the moderating role of brand preference. CCB refers to voluntary participation by customers to act in a way that helps the company (Groth, 2005; Yi & Gong, 2013). CCB is attracting attention in recent years because it has a big impact on corporate performance (e.g., Curth, Uhrich, & Benkenstein, 2014; Nguyen et al. 2014; Revilla-Camacho, Vega-Vázquez, & Cossío-Silva, 2015). Unlike in previous studies, PCSR is applied as a predictor variable of CCB in this study because the perception of PCSR leads to positive emotions or future behavior intentions (Carroll & Shabana, 2010; Choi & La, 2013). In addition, brand preference is an integral part of a competitive business, so many researchers have long studied its antecedents and consequences in the diverse industries (e.g., Kim, Ok, & Canter, 2010; Roberts & Lattin, 1991; Rundle-Thiele & Mackay, 2001). This study focused on the moderating role of brand preference for the first time in the restaurant industry as consumers tend to behave differently depending on brand preference level (Mathur, Moschis, & Lee, 2003; Mowday, Porter, & Steers, 1982).

Despite the importance of PCSR, research in this area has not yet been conducted in the food service industry. At this point, finding the role of the elderly in the food service industry is very important. Thus, this study examined the important role of philanthropic corporate social responsibility (PCSR), focusing on the restaurants where people aged 65 and over provide services. For this, a theoretical model was developed in order to find the impact of PCSR on CCB. In addition, based on the existing theoretical background, it was proposed that brand preference moderates the relationship between PCSR and CCB.


Ⅱ. Literature review
1. Philanthropic corporate social responsibility (PCSR)

In the last few decades, the concept of corporate social responsibility (CSR) has been investigated by many researchers in various fields (e.g., Ha, 2017; Sen & Bhattacharya, 2001; Sohn, 2016). Although there are many definitions of CSR, the definition of CSR proposed by Carroll (1979) is the most known and cited. According to the author, CSR refers to “the social responsibility of business encompasses the economic, legal, ethical, and discretionary (philanthropic) expectations that society has of organizations.” (p. 500). That is, CSR is an activity undertaken by the company to meet the social duties that society expects and demand from the company (Lindgreen & Swaen, 2010; McWilliams, 2000). CSR consists of the four dimensions including economic, legal, ethnical, and philanthropic, and this study focused on PCSR. It is widely accepted that the concept of PCSR constitutes the essence of CSR due to its high correlation with cause-related marketing that plays a critical role in shaping the consumer attitude toward the brand (Berger & Kanetkar, 1995; Carroll & Shabana, 2010). For this reason, many studies have recently focused on PCSR (Choi & La, 2013). PCSR is defined as “corporate actions that are in response to society’s expectation that business be a good corporate citizen” (Carroll & Shabana, 2010, p. 96). These PCSR activities play an important role in improving the overall image of the company, enhancing corporate performance (Menon & Kahn, 2003). Bruch and Walter (2005) also suggested that if companies focus more on PCSR activities, they can attract more customers and result in greater revenues. Recently, PCSR activities are attracting attention as society emphasizes corporate transparency and ethics, so it is accepted as an obligation, not an option of the company (Iwannanda & Adiputra, 2017; Lins, Servaes, & Tamayo, 2017).

2. Customer citizenship behavior (CCB)

Customer citizenship behavior refers to “voluntary and discretionary behaviors that are not required for the successful production and/or delivery of the service but that, in the aggregate, help the service organization overall” (Groth, 2005, p. 11). From a company standpoint, customers with high levels of CCB are known as a second employee because they are enthusiastic about helping the company, which is enough to replace the employee’s role (Gruen, Summers, & Acito, 2000; Halbesleben, Becker, & Buckley, 2003). In particular, such customers play an important role in company development because they voluntarily help the company. According to Yi and Gong (2013), CCB consists of four theoretical sub-dimensions as follows. Feedback is a message that customers leave after using the service. Such feedback is formed through the comparison of other services, so it is a key information in order to improve the overall service quality (Voss et al., 2004). Advocacy is defined as introducing products to close people (also known as word-of-mouth) (Groth, Mertens, & Murphy, 2004). People are easily influenced by the information given by others around them, so advocacy is more influential than commercial advertising (Söderlund, 1998). Helping is the extent to which customers voluntarily help others who want to use the service (Yi & Gong, 2013). Customers who had a specific problem at a service facility try to help other customers who have the same problem (Groth et al., 2004; Rosenbaum & Massiah, 2007). Tolerance is defined as “customer willingness to put up with or to be patient of service encounters that are not delivered as expected” (Keh & Teo, 2001, p. 374). There is a high correlation between tolerance and attitude toward a service provider (Lengnick-Hall, Claycomb, & Inks, 2000). From recipient to contributor, examining customer roles and experienced outcomes. For instance, customers with a high level of tolerance are less likely to complain about service failures.

As mentioned earlier, many companies try to focus on PCSR activities such as free education and donations for local development which helps to enhance customer loyalty (Ailawadi et al., 2014; Chung et al., 2015). Previous studies also supported this argument. For instance, Yi and Gong (2008) examined the predictors of CCB. They indicated that when people perceive high levels of justice (i.e. distributive, procedural, and interactional) which enhance positive emotions, they are more likely to show CCB. Vlachos et al. (2009) explored how PCSR positively affects behavioral intentions using 830 customers. They suggested that CSR plays an important role in predicting positive customers’ future behavioral intentions. In addition, Martínez, Pérez, and del Bosque (2014) tried to investigate the relationship between CSR and loyalty in the hotel industry and found that CSR has a positive influence on loyalty. For instance, Kim et al. (2017) developed a theoretical model in order to explore the important role of charitable responsibility (same as PCSR) using data collected from 426 customers who had visited the franchised chain hotel in Seoul, Korea. They found that charitable responsibility positively affects SNS citizenship behavior. In addition, Luu (2017) tried to find the relationship between CSR and customer value co-creation behavioral and showed that CSR has a major influence on customer value co-creation behavioral. Therefore, it can be inferred that if the restaurant participates in a variety of volunteer activities, customers show voluntary and discretionary behaviors for the restaurant. Based on the theoretical and empirical backgrounds, the following hypotheses were therefore proposed:

H1: PCSR has a positive influence on tolerance.
H2: PCSR has a positive influence on advocacy.
H3: PCSR has a positive influence on helping.
H4: PCSR has a positive influence on feedback.

3. Brand preference

Hellier et al. (2003, p. 1765) defined brand preference as “the extent to which the customer favors the designated service provided by a certain company, in comparison to the designated service provided by other companies in his or her consideration set.” Brand preference helps to reduce the complexity when making buying decisions about products (Gensch, 1987). The process of forming brand preference is as follows. Consumers are exposed to various brands when purchasing their products. They easily recall some of the distinctive brands. In particular, if consumers are satisfied after using a certain brand, they prefer the brand. That is, preferring a certain brand means that the overall attitude toward the brand is good (Hwang & Ok, 2013). It is widely known that brand preference is very important for companies because it has a significant influence on brand loyalty (Rundle-Thiele & Mackay, 2001). In particular, since brand preference is directly related to the company’s profits, many companies are making a lot of efforts to make customers prefer their own brands (Mathur, Moschis, & Lee, 2003). Empirical studies have also shown the importance of brand preference in the formation of positive customers’ future behavioral intentions. For instance, Kim, Ok, and Canter (2010) developed a theoretical model in order to explore the effect of brand preference on customer share of visits using data collected from 270 restaurant patrons. They suggested that brand preference is a critical predictor of customer share of visits. More recently, Hwang and Han (2016) explored the relationship between brand preference and revisit intentions in the casino industry. They found that brand preference plays an important role in the formation of revisit intentions.

This study proposed the moderating role of brand preference in the relationship between PCSR and CCB based on the following theoretical background. Brand preference is created by customers’ past experiences (Keiningham et al., 2005; Kim et al., 2010). In other words, when customers have had a good experience with a particular brand, they prefer that brand. More importantly, customers with high levels of brand preference are committed to a certain brand (Mathur et al., 2003; Mowday et al., 1982), suggesting that depending on the level of brand preference, customers have different future behavioral intentions. That is, the higher the brand preference, the better the future behavioral intentions. On the contrary, the lower the brand preference, the worse the future behavioral intentions. This theoretical argument can be applied to this study as follows. For example, if customers who prefer a certain brand perceive that the brand makes efforts for social development, they would show a more positive CCB for the brand. On the other hand, even though customers with low levels of brand preference perceive PCSR activities of a certain brand, they are less likely to show CCB for the brand because the brand is not in his or her consideration set. Thus, it can be inferred that if customers have high levels of brand preference, they are more enthusiastic about helping the brand. On the other hand, if customers do not prefer a particular brand, they are less likely to show voluntary and discretionary behaviors for the brand. In accordance with this logic, the author proposes the following hypotheses.

H5a: Brand preference moderates the relationship between PCSR and tolerance, such that the positive effect of PCSR on tolerance is stronger with a high level of brand preference.
H5b: Brand preference moderates the relationship between PCSR and advocacy, such that the positive effect of PCSR on advocacy is stronger with a high level of brand preference.
H5c: Brand preference moderates the relationship between PCSR and helping, such that the positive effect of PCSR on helping is stronger with a high level of brand preference.
H5d: Brand preference moderates the relationship between PCSR and feedback, such that the positive effect of PCSR on feedback is stronger with a high level of brand preference.


Ⅲ. Methodology
1. Measurement

Six constructs were employed in this study. PCSR was measured using four items adapted from Carroll (1979) and Lee et al. (2013). CCB consisted of four sub-dimensions, including feedback, advocacy, helping, and tolerance, and was measured with 14 items borrowed from Yi and Gong (2013). Lastly, brand preference was measured with three items adapted from Hellier et al. (2003) and Kim et al. (2010). The questionnaire used a five-point Likert-type scale, anchored from strongly disagree (1) to strongly agree (5).

2. Data collection

The questionnaire was distributed to people who have made purchases at a McDonald’s restaurant in which those aged 65 and over provide services in the last three months in Seoul, Korea. Data were collected for 1 month from May 2016, and five interviewers who were trained in order to understand how to collect data. The questionnaire was conducted face-to-face. Prior to the start of the questionnaire the interviewers obtained consent and gave the first question as follows. Have you visited a McDonald’s restaurant where people aged 65 and over provide services/a McDonald’s restaurant where people younger than 65 provide services in the past three months? If the respondent answered no, the questionnaire ended. Furthermore, if there is something unknown in the middle of the questionnaire, the surveyor answered. When the survey was completed, questionnaires were returned on-site in order to increase the usable high response rates. 300 surveys were conducted. Among them, 41 responses were excluded because of incomplete questionnaires and multivariate outliers. Consequently, 259 surveys were used for further analysis.


Ⅳ. Data analysis
1. Descriptive statistics

As for gender, 45.6% were male and 54.4% were female. The respondents’ average age was 38.81 years old (standard deviation = 11.39). In terms of annual household income, the majority of the respondents belonged to KRW 80,000,000 or over and KRW 60,000,000 - 79,999,999 (n = 101, 39.0%). In addition, 62.9% (n = 163) were married respondents and 69.5% (n = 180) possessed a bachelor’s degree. The highest percentage category of respondents were white collar (n = 140, 54.1%).

2. Principal components analysis for philanthropic corporate social responsibility

A principal components analysis with varimax rotation was conducted for philanthropic corporate social responsibility. The results of the principal components analysis showed that the appropriateness of the extracted factor structure was assessed by using the Kaiser-Meyer- Olkin (KMO) measure of sampling adequacy (.848) and Bartlett’s test of sphericity (p < .001). All the items’ factor loadings were greater than .871, suggesting that the convergent validity was acceptable. In addition, the extracted variance was 77.031%. Lastly, the value of Cronbach’s alpha was .900, thus surpassing the criterion of .70 recommended by Nunnally (1978). That is, the internal consistency of item was confirmed.

3. Principal components analysis for customer citizenship behavior

To examine the underlying dimensions of customer citizenship behavior, a principal components analysis with varimax rotation was also used. The results of the principal components analysis showed a four-factor structure which had eigenvalues exceeding 1.0. Validity of the extracted factor structure was evaluated by the KMO measure of sampling adequacy (.921) and Bartlett’s test of sphericity (p<.001) respectively. All the items’ factor loadings were higher than .742, suggesting satisfactory convergent validity. The generated domains were labeled ‘tolerance’ (Domain 1), ‘advocacy’ (Domain 2), ‘helping’ (Domain 3), and ‘feedback’ (Domain 4). The total extracted variance was 78.864%, consisting of 21.635% in tolerance, 20.591% in advocacy, 20.318% in helping, and 16.320% in feedback. Lastly, the value of Cronbach’s alpha for all four domains ranged from .738 to .823, suggesting acceptable reliability.

Table 1. 
Principal components analysis for philanthropic corporate social responsibility
Variables SFL E EV CA
Philanthropic corporate social responsibility (mean=3.44, SD=.855) 3.081 77.031 .900
The restaurant participates in a variety of volunteer activities. .890
The restaurant provides variety of donations. .887
The restaurant is committed to build a better community. .873
The restaurant develops a campaign for helping the needy. .871
Notes: KMO measure of sampling adequacy = .848, Bartlett’s test of sphericity (p<.001), SD=Standard deviation, SFL=Standardized factor loadings, E=Eigenvalue, EV=Extracted variance, CA=Cronbach’s alpha

4. Principal components analysis for brand preference

The results of principal components analysis for brand preference indicated that the appropriateness of the extracted factor structure was evaluated by employing the Kaiser- Meyer-Olkin (KMO) measure of sampling adequacy (.828) and Bartlett’s test of sphericity (p < .001). All the items’ factor loadings were greater than .866, suggesting that the convergent validity was satisfactory. In addition, the extracted variance was 78.537%. Lastly, the value of Cronbach’s alpha was .863, suggesting appropriate reliability (Nunnally, 1978).

5. Effects of philanthropic corporate social responsibility (PCSR) on customer citizenship behavior (CCB)

Table 5 shows the results for the regression. The data analysis results showed that PCSR had a statistically significant influence on all four dimensions of CCB. According to beta coefficients (β), PCSR has had the greatest impact on advocacy (β=.456, p<.05, R2=.208), followed by feedback (β=.426, p<.05, R2=.181), tolerance (β=.366, p<.05, R2=134), and helping (β=.325, p<.05, R2 =.106).

6. Moderating role of brand preference

Table 7 provides the results of the hierarchical regression analyses of the moderating role of brand preference in the relationship between PCSR and CCB. First, in the case of tolerance, model 3 indicated the effect of brand preference along with PCSR on tolerance. Although PCSR and brand preference together explained additional 1% of variance in tolerance, the interaction effect (PCSR × brand preference) was not significant (p = .055), indicating that brand preference did not significantly moderate the relationship between PCSR and CCB. Therefore, Hypothesis 5a was not supported. Second, the results of the hierarchical regression analyses showed that the interaction variable (PCSR×brand preference) had a significant influence on advocacy adding 4% (p<.05) to the extracted variance. Therefore, Hypothesis 5b was supported. Third, regarding helping, model 3 showed the effect of brand preference along with PCSR on tolerance was not significantly supported (p=.911), suggesting that Hypothesis 5c was rejected. Lastly, the data analysis results that the interaction term (PCSR×brand preference) had a significant impact on feedback (p<.05) adding 2.8% to the extracted variance. Thus, Hypothesis 5d was supported.

Table 2. 
Principal components analysis for customer citizenship behavior
Variables SFL E EV CA
Customer citizenship behavior
Tolerance (mean=3.40, SD=.875) 2.164 21.635 .823
If service is not delivered as expected in this restaurant .828
If an employee makes a mistake during service delivery in this restaurant .782
If I have to wait longer than normal to receive service in this restaurant .742
Advocacy (mean=3.61, SD=.785) 2.059 20.591 .811
I recommend this restaurant brand to others. .787
I encourage friends and relatives to visit this restaurant brand. .760
Helping (mean=3.47, SD=.761) 2.032 20.318 .821
I give advice to other customers in this restaurant if I think it’s necessary. .836
I teach other customers to use the service correctly in this restaurant. .768
I assist other customers at this restaurant if they need my help. .750
Feedback (mean=3.50, SD=.781) 1.632 16.320 .738
If I have a useful idea on how to improve their service at this restaurant, I will let the employee know. .783
When I experience a problem, I will let the employee know about it. .757
Notes: Total extracted variance=78.864%, KMO measure of sampling adequacy=.921, Bartlett’s test of sphericity (p<.001), SD=Standard deviation, SF=Standardized factor loadings, E=Eigenvalue, EV=Extracted variance, CA=Cronbach’s alpha

Table 3. 
Principal components analysis for brand preference
Variables SFL E EV CA
Brand preference (mean=3.54, SD=.791) 2.356 78.537 .863
This restaurant brand meets my needs better than other comparable restaurant brands. .906
When I am deciding on a restaurant to visit, this brand is frequently a viable choice. .887
I am interested in trying various menu items in this restaurant brand more than other comparable restaurant brands. .866

Table 4. 
Results of regression: PCSR with customer citizenship behavior
Standardized Estimate t-value F-value R2 Hypothesis
H1 PCSR à Tolerance .366 6.297* 39.658 .134 Supported
H2 PCSR à Advocacy .456 8.206* 67.343 .208 Supported
H3 PCSR à Helping .325 5.508* 30.333 .106 Supported
H4 PCSR à Feedback .426 7.539* 56.838 .181 Supported
Notes: *p<.05, PCSR = Philanthropic corporate social responsibility

Table 5. 
Results of hierarchical regression analysis: The moderating role of brand preference
Predictor
Variable:
PCSR
Model R R2 SE Statistical variation Durbin-
Watson
ΔR2 ΔF df1 df2 p-value
H5a
Tolerance
1 .366 .134 .932 .134 39.658 1 257 .000* 1.468
2 .569 .324 .825 .190 71.839 1 256 .000*
3 .577 .333 .821 .010 3.731 1 255 .055
H5b
Advocacy
1 .456 .208 .891 .208 67.343 1 257 .000* 1.807
2 .460 .212 .891 .004 1.339 1 256 .248
3 .502 .252 .869 .040 13.807 1 255 .000*
H5c
Helping
1 .325 .106 .947 .106 30.333 1 257 .000* 1.646
2 .347 .120 .941 .015 4.263 1 256 .040*
3 .347 .120 .943 .000 .012 1 255 .911
H5d
Feedback
1 .426 .181 .906 .181 56.838 1 257 .000* 1.410
2 .426 .181 .908 .000 .006 1 256 .940
3 .458 .209 .894 .028 9.131 1 255 .003*
Notes: *p<.05, PCSR = Philanthropic corporate social responsibility


Ⅴ. Discussion and implications

Based on the existing theoretical background, it was hypothesized that PCSR positively affects CCB. In addition, it was proposed that brand preference plays an important role in the relationship between PCSR and CCB. Integrating the proposed theoretical relationships, a research model was developed and analyzed using empirical data collected from 259 customers who have used a McDonald’s restaurant in which those aged 65 and over provide services. The results of data analysis provide the following important theoretical and managerial implications.

1. Theoretical implications

First, the data analysis results indicated that PCSR has a positive influence on all four dimensions of CCB including tolerance (.366, p<.05), advocacy (.456, p<.05), helping (.325, p<.05), and feedback (.426, p<.05). It can be interpreted that when the restaurant is committed to build a better community (1) if service is not delivered as expected in this restaurant, customers are willing to tolerate it; (2) customers encourage friends and relatives to visit this restaurant brand; (3) customers give advice to other customers in this restaurant if they think it’s necessary; and (4) if customers have a useful idea on how to improve their service at this restaurant, they will let the employee know. The results of this study are similar with previous studies (e.g., Kim et al., 2017; Luu, 2017), suggesting that PCSR plays an important role in the formation of CCB. From this point of view, this study confirmed and extended the existing theoretical backgrounds by finding the relationship between PCSR and CCB.

Second, the results showed that brand preference moderates the relationship between (1) PCSR and advocacy and (2) PCSR and feedback. That is, customers holding strong brand preference feel higher levels of advocacy and feedback when the restaurant participates in a variety of volunteer activities. However, unlike our expectations, brand preference did not moderate the relationship between (1) PCSR and tolerance and (2) PCSR and helping. It can be interpret that even though customers holding strong brand preference perceive PCSR, they are less likely to have high levels of tolerance and helping. These results can be interpreted as follows. Advocacy and feedback are frequently seen in everyday life and are considered to be acceptable to general customers. However, it is somewhat difficult for general customers to accept tolerance and help because they are somewhat larger at the cost of their sacrifice. From an academic point of view, this study tried to investigate the moderating role of brand preference with PCSR and CCB for the first time in the restaurant and this is the important theoretical contribution.

2. Managerial implications

These findings also have managerial implications. First, it is recommended that hiring the elderly is of great significance because it makes restaurant patrons perceive high levels of PCSR, which in turn positively affects CCB. As described above, the increase in the elderly population causes various problems such as the elderly poverty, so it is good for social development to provide jobs for seniors in restaurants. The restaurant should pay attention to employment of the elderly as well as other PCSR activities. A typical example of PCSR activity is ‘green restaurant.’ Green restaurant is a way of providing services to customers through an eco-friendly way in operating restaurants. Green restaurants make customers perceive high levels of PCSR, so they are more likely to show voluntary and discretionary behaviors for the restaurant. In addition, PCSR activities include free education and donations for local development. For example, Home Depot Inc. helps tornado victims by giving them knowledge of restoration of homes in the United States. Such PCSR activities play an important role in the formation of consumers’ voluntary and discretionary behaviors. Therefore, restaurants should pay more attention to PCSR activities because it leads to increased CCB. Especially, customers with high CCB can substitute the roles of the employees, which is a big profit for the company. Lastly, government policy on PCSR activities should also be supported. For example, it is recommended that the government could provide tax relief and other benefits to companies that are actively engaged in PCSR activities.

Second, the data analysis results showed the moderating role of brand preference in the relationship between (1) PCSR and advocacy and (2) PCSR and feedback. These results indicated the need for customer segmentation strategies. For this, restaurants categorize customers according to their brand preference level. And then, it is expected that the marketing effect will be significant if advertisements emphasizing the PCSR activities of the restaurant is given to the customers with high levels of brand preference. Thus, if restaurants focus on promoting PCSR activities to customers with high brand preference, the customers would have high levels of CCB.

3. Limitations

Despite important theoretical and managerial implications, the following limitations exist. This study focused on the restaurant industry, so the results of this study may not be suitable for other industries. In addition, since the data used in this study was collected in Korea, it is also not easy to apply the results of this study to other cultures. Therefore, future research needs to collect data from other industries in order to enhance the external validity of the findings of this study. Lastly, it would be meaningful to apply the proposed model of this study to other cultures.


Acknowledgments

This work was supported by the National Research Foundation of Korea Grant funded by the Korean Government(2015S1A5A 8013828).


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