1.Introduction
Consumers and staff interactions are inevitable in the hospitality industry, although technology allows non contact staff services. There are various foodservice establishments with different concepts since consumers have different purposes for visiting foodservice establishments. For example, eating out has evolved from diminishing hunger and now fulfills consumers’ needs per eating out occasion. To meet various consumers’ demands, foodservice establishments offer services and concepts, affecting consumers’ purpose of the visit. Services at foodservice establishments include table services, counter services, buffet services, etc. These service types affect the designs of the place and significantly impact consumer behaviors. In addition, consumers’ reactions to physical environments are various (Bitner, 1990, 1992). Service environment has been an important subject in the hospitality industry; however, there has been little consideration of the social context of the dining environment affecting consumers’ overall perception of the services (Kim & Baker, 2017).
Variability is the most common service characteristic and significantly impacts consumer behavior. In service delivery, less variability in services is an important element to securing consumer satisfaction. The distribution of service delivery can be considered as the appropriate allocation of services to consumers. Hence, this study defined the distribution of service delivery as described above. Service is an interaction between consumers and service providers, and during the service process, consumers value the functional and emotional or experiential aspects (Bellos & Kavadias, 2019).
Communication is one of the elements that consumers use to measure staff behaviors. In other words, there is an association between communication and consumer behavior (Jacob, Guéguen, & Boulbry, 2014). Rapport, known as pleasant interactions between consumers and service employees (Gremler & Gwinner, 2000), is established through communication (Azab & Clark, 2017). Human communication comprises physical movement 55%, vocal behavior 38%, and verbal 7%. (Mehrabian, 1981). Verbal communication (VC) can be through non-verbal communication (NVC), which can be a tool to enhance the VC.
Sundram and Webster (2000) claimed that spoken language and body language are elements of communication that convey one’s behavior intention. Thus, spoken language is a cue of VC (Baker & Kim, 2018), and body language, such as smiling, is a cue of NVC (Magnini, Miller, & Kim, 2011; Wang, Miao, & Mattila, 2015). For example, making suggestions to consumers leads to choosing menu items (Guéguen & Jacob, 2005), and an open-mouth smile increases tips (Tidd & Lockard, 1978). However, VC should incorporate a proper tone with emotion for the situation and attitudes towards consumers when recovery is needed (Gabbott & Hogg, 2001). In addition, NVC can play essential roles to emphasize and give accuracy to the VC (Gabbott & Hogg, 2001). Hence, measuring staff performance should include a combination of VC and NVC in the distribution of service delivery.
Consumer behaviors have been at the center of research in the hospitality industry. Of the factors influencing consumer satisfaction, service staff’s behaviors (Guéguen & Jacob, 2005; Kathryn Frazer, 2000; Tidd & Lockard, 1978) and the service environment (Babin, Hardesty, & Suter, 2003; Bitner, 1990, 1992)showed a significant impact on consumer behaviors. The recent pandemic brought new waves in the foodservice industry. As consumers became more concerned about food safety, food handling hygiene became crucial in offering safe food. Therefore, consumers want to know how food is prepared and cooked by the staff. In a traditional restaurant design, consumers cannot look inside the kitchen where staff prepare and handle food. As open kitchen-style restaurants gained popularity during the 2000s, we can now see that design applied to counter service-style restaurants. The cleanliness of the restaurant, including the kitchen, is an essential factor for consumers to visit a restaurant (Aksoydan, 2007). Consumers can see the kitchen’s cleanliness and the staff’s performance through an open kitchen. In a counter service, restaurants can boost the consumers’ dining experiences through an entertainment component such as watching food preparation (Alonso & O'Neill, 2010). Employee behavior is an attractive factor related to signal processing in the distribution of service delivery. Staff encounter with consumers is important in terms of service quality (Guéguen & Jacob, 2005; Tidd & Lockard, 1978; Tsaur, Luoh, & Syue, 2015).
Numerous studies exist on consumer behaviors, including closed kitchen restaurants, or the studies did not specify the type of kitchen. However, measuring consumers’ service experiences in a counter service restaurant is limited. In addition, there are limited empirical studies examining consumers’ preferences of VC (spoken language) and NVC (body language) in service encounters (Holmqvist, Van Vaerenbergh, & Grönroos, 2017). Facial expressions and language can influence consumers’ perceptions in service settings; however, studies regarding employee appearance are limited (Kim & Baker, 2017).
Therefore, this study investigated consumers’ perceptions of kitchen staff’s performance at a counter kitchen. The study used the kitchen staff’s VC and NVC to measure their performance in the distribution of service delivery. Along with perceptions of VC and NVC, we also measured consumer satisfaction and revisit intention.
2. Literature Review
2.1. Verbal Communication
VC is the most basic method of communication and is the center of human communication. Of linguistic communication, over 75% is VC (Mansfield, 1987), and it improves social intimacy and credibility. When it comes to communication, communication needs to consider the audiences' attitude, which leads to the acceptance of the communication (Riggio, Salinas, Riggio, & Cole, 2003). A previous study found that lead time (the total time needed from taking an order to serving the food) contributes to work pressure and creates more employee burden than tasks such as food delivery and cleaning. Therefore, improving lead time can improve employees’ behaviors. Communication itself is important for delivering information regarding food, services, or any area of interest or questions from consumers or vice versa. In food allergies, the lack of proper communication between employees and customers might cause food allergy reactions (Leftwich et al., 2011).
2.2. Non-verbal Communication
Each moment people interact with others, NVC occurs as a part of communication (Gabbott & Hogg, 2001). NVC regulates and mediates social relationships (Gabbott & Hogg, 2001)and consumer behavior (Jacob et al., 2014). In addition, researchers found that NVC was associated with both positive evaluation of the server and the restaurant (Hornik, 1992). For example, smiles can help boost rapport when communicating where different languages are spoken (Van Vaerenbergh & Holmqvist, 2014). Furthermore, smiles impact sincerity when communicating (Sundar, Dinsmore, Paik, & Kardes, 2017). Overall, NVC is emotional communication through stimulus and reactions (Gabbott & Hogg, 2001).
Jung and Yoon (2011) found that NVC affected consumers’ emotional responses. In a social relationship, message delivery can include NVC and NVC is a means of delivery of a combination of emotion and attitudes. In addition, emotion and accuracy affect the quality of service (Wong, 2013). Staff behaviors themselves can be a medium to deliver feelings or experiences to consumers. For example, customers notice smiling facial expressions and interpret them as happiness, which is a positive indication of NVC (Gabbott & Hogg, 2001; Tidd & Lockard, 1978).
Also, touching consumers tends to increase tips in foodservice establishments (Guéguen & Jacob, 2005). Gabbott and Hogg (2001) categorized NVC as 1) body postures, 2) personal spaces, 3) communicative aspects of eye behaviors, and 4) vocal tones and intonation. According to Gabbott and Hogg (2001), NVC can establish the authority to control interactions hence, NVC is essential for the staff who works in the counter service kitchen and needs to control the service encounters.
Jung and Yoon (2011) found that NVC affected satisfaction through emotional responses. NVC impacts rapport, leading to consumer satisfaction and revisit intention (Baker & Kim, 2018). The volume of communication between consumers and staff affected consumer satisfaction (Cynthia & Sundaram, 2009). In addition, when staff made mistakes, their appropriate and sincere attitudes can remedy the situation (Sundar et al., 2017) which may decrease negativity towards total satisfaction.
Hence, in counter services, staff needs communication skills with VC with sincere NVC. However, there are differences in perceptions of NVC by culture, gender, and religion. Interestingly, women considered staff in open kitchen-style restaurants more engaged with consumers (attentiveness) since they can observe the staff’s activities in the kitchen (Alonso & O'Neill, 2010). Therefore, this study postulates hypotheses as follows.
H1: Communications will be perceived significantly differently by demographic characteristics.
H1-1: VC will be perceived significantly differently by consumers’ demographic and eating out characteristics
H1-2:NVC will be perceived significantly differently by consumers’ demographic and eating out characteristics
H2: VC will significantly influence consumers’satisfaction and revisit intention
H2-1: VC will significantly influence consumers’ satisfaction
H2-2: ‘VC will significantly influence consumers’revisit intention
H3: NVS will significantly influence consumers’ satisfaction and revisit intention
H3-1: NVS will significantly influence consumers’ satisfaction
H3-2: NVS will significantly influence consumers’ revisit intention
H4: The satisfaction will significantly influence consumers’ revisit intention
3. Research Methodsand Materials
3.1. Participants
This study used a quantitative method to gather data. A survey was conducted for two weeks, from November 20 to December 3, 2017, in Daejeon, Republic of Korea. Survey respondents, chosen randomly by this study’s researchers, were briefed on the survey and asked if they had visited a counter service restaurant before. If so, they were then asked for their consent to participate in the survey. Upon receiving their consent, respondents’ answers were self-administered. After screening the responses, we had 245 questionnaires for further analysis.
3.2. Measures
The questionnaire was composed of consumers’ experiences with VC and NVC at a counter service restaurant, satisfaction, and revisit intention. Participants responded to the questions on a five-point Likert scale from 1 (not at all) to 5 (very much). We adopted the questions regarding consumers’ experiences with VC and NVC from previous studies (Gabbott & Hogg, 2001; Islam & Kirillova, 2020; Jacob et al., 2014). Satisfaction statements included five items rated on a five-point Likert scale from 1 (not at all) to 5 (very much) adopted from (Jung & Yoon, 2011). The statements included: ‘I am satisfied with staff service at the counter kitchen, ’ ‘I received pleasant service, ’ ‘I thought I made a good choice to select this restaurant to eat, ’ ‘I had a good dining experience, ’ and ‘I am satisfied with overall service at the restaurant.’ We measured the revisit intention with three statements: ‘I will visit this restaurant again to dine out, ’ ‘I will visit this restaurant regularly in the future, ’ and ‘I will consider this restaurant first of all other restaurants to dine out.’ We used the same five-point Liker scale from 1 (not at all) to 5 (very much) to measure revisit intention. In addition, we also asked questions about participant demographic characteristics and eating out frequency and budget.
3.2. Data Analysis
We coded gathered data using Excel and then analyzed it with the Statistical Package for the Social Sciences (SPSS, version 25, IBM Cor, 2018). First, we ran an exploratory analysis on items measuring communication using the maximum likelihood method with varimax rotation. We then conducted correlations and Cronbach’s alphas of the extracted variables and variables of satisfaction and revisit intention to determine the validity and internal consistency of the measurements.
Next, we ran descriptive analyseson the demographic and dining out characteristics of the respondents. We also ran analyses of variance, Scheffe and Games and Howell to compare each factor in the respondents' demographic and dining out characteristics. Then we conducted multiple regression analyses to determine the effect of VC and NVC on satisfaction and revisit intention. Lastly, we ran a regression to measure the impact of satisfaction on revisit intention. Figure 1 represents a framework for this study.
Figure 1: A proposed conceptual framework
4. Results and Discussion
4.1. Profile of Participants
Table 1 represents the demographic and dining out characteristics of the respondents. The majority of the respondents were male (68.6%), aged between 20 and 29 (29.8%), followed by 40-49 (26.1%) and 50-59 (25.3%). More than half of the respondents had a Bachelor’s degree (52.7%), followed by high school and less (21.2%), attended college (18.8%), and master’s degree and above (7.3%). Monthly income ranged from ≤ 2, 000, 000 and > 3, 000, 000 won (26.1%) to ≤ 3, 000, 000 and > 4, 000, 000 won (23.7%). Average spending on dining per person was as follows: ≤ 10, 000 and > 20, 000 won (30.2%), > 10, 000 won (21.6%), ≤ 20, 000 and > 30, 000 won (17.6%). The remainder (30.6%) reported other spending. The frequency of dining out was 2- 3 times per week (51%), 1 time or less per week (31.4%), 4- 5times per week (13.95%) and 6 times or more per week (3.7%).
Table 1: Profiles of the respondents Results
We ran an exploratory factor analysis on communication items. First, we ran13 items using principlerotation with the maximum likelihood method (Table 2). We excluded one item (“The staff had a cheerful look when providing service”) after factor analysis since it represented NVC, but we categorized it into VC. After excluding the item, we ran an exploratory factor analysis on 12 items. We loaded seven items on VC with Cronbach’s alpha .920 and five items on NVC with Cronbach’s alpha .842. We measured satisfaction with five statements resulting in Cronbach’s alpha .911. The result of the three revisit intention statements resulted in Cronbach’s alpha .865. Table 3 shows the correlations of the variables.
Table 2: Results of exploratory factor analysis
Table 3: Correlations between variables
Note: *** p < 0.001
Significance at 0.01 at two tails
4.2. Comparisons of VC and NVC by Demographic Characteristics
We compared the perception of VC and NVC by gender using an independent t-test (Table 4). There were no significant differences between men (M = 4.073, SD = 0.614) and women (M = 3.994, SD = 0.643) on VC (t = .904, p > 0.5). We also found no significance differences on NVC (t = 1.907, p > 0.05) between men (M = 4.069, SD = 0.690) and women (M = 3.897, SD = 0.740). We ran ANOVAs on demographic characteristics on VC and NVC. Age did not have any significant differences on VC (F = .919, p > 0.05) and NVC (F = .985, p > 0.05). Education did not have any significant differences on VC (F = .086, p > 0.05) and NVC (F = .335, p > 0.05). Average monthly income showed significance on VC (F = 4.332, p = 0.001) but not on NVC (F = 2.016, p > 0.05).
Table 4: Comparisons of VC and NVC by demographic characteristics
Note: Different subscripts show significant differences by column in each category
Results of Scheffeshowed that per VC, average monthly income less than 1, 000, 000 won was significantly different from between 2, 000, 000-2, 999, 999 won and from between 3, 000, 000-3, 999, 999 won at p < 0.05. Average budget for eating out was significantly different on both VC (F = 2.414, p < 0.05) and NVC (F = 4.776, p < 0.001). Results of Games–Howell showed that per VC, average eating out budget 10, 000-19, 999 won was significantly different from budget 40, 000-49, 999 won at p < 0.05. For NVC, a budget less than 10, 000 won was significantly different from a budget of 10, 000-19, 999 won, 30, 000-39, 999 won and more than 50, 000 won at p < 0.05. Frequency of eating out did not show any differences on VC and NVC. Therefore, these results partially support H-1-1 and H1-2.
4.3. Impact of VC and NVC on Satisfaction and Revisit Intention
Both VC and NVC were regressed on satisfaction (Table 5). VC (B = .426, SE = .049. t = 8.684 p < 0.001) and NVC (B = .420, SE = .056. t = 7.504, p < 0.001) significantly influenced satisfaction (F = 243.69, p = 0.000). Hence, the results support H2-1 and H3-1.
Table 5:Results of regression of VC and NVC on satisfaction
Note: F = 243.694, p = 0.000, R = .817, R2 = .668, Adjusted R2 = .665 *** p < 0.001
In addition, both VC and NVC were regressed on revisit intention (Table 6). VC (B = .500, SE = .067, t = 7.471, p < 0.001) and NVC (B = .344, SE = .076, t = 4.518, p < 0.001) showed significant effect on revisit intention supporting H2- 2 and H3-2. In addition, satisfaction was regressed on revisit intention. Satisfaction significantly affected revisit intention (B = .874, SE =.047, t = 18.614, p < 0.001) (Table 7). Hence, the results support H4.
Table 6:Results of regression of VC and NVC on revisit intention
Note: F = 134.806, p = 0.000, R = .726, R2 = .527, Adjusted R2 = .523 * p < 0.05 *** p < 0.001
This study measured consumers’ VC and NVC experiences and impact on satisfaction and revisit intention regarding the distribution of service delivery. Unlike previous studies (Gabbott & Hogg, 2001), which found that women were moreaffected by NVC, this study did not find gender differences. Monthly income affected VC but not NVC. Individuals with higher income more positively perceived VC than lower-income; however, the highest income group did not differ from the lowest income group. It could be that they consider issues other than VC in services provided by staff. In addition, differences in average budget per person when dining out perceived staff communications differently. Both VC and NVC were showing similar patterns as the trends of monthly income on VC. However, age, education, and frequency of dining out did not significantly affect the reception of both VC and NVC.
Table 7: Results of regression of satisfaction on revisit intention
Note: F = 346.496, p = 0.000, R = .767, R2 = .588, Adjusted R2 = .586 *** p < 0.001
The results give us two different messages. In this regard, one message conveys that consumer consider the distribution of service deliveries and their expenditure on dining at the restaurant. Therefore, consumers with lower spending may have less expectation of services regarding communications than consumers with higher spending, except for the highest spending consumers. The other is that the consumers with the highest spending do not pay attention to the communications when dining at a restaurant. They might have some other purposes for special occasions such as business meetings, special events, etc. Therefore, consumers visiting for these reasons might not want to be bothered with narrative communication from staff in the distribution of service deliveries.
Both VC and NVC affected satisfaction and revisit intention. Previously a study found that NVC had more significance than VC. However, in this study, VC had more power than NVC on satisfaction and revisit intention, which may explain why Baker and Kim (2018) measured VC as language itself, whether Korean or English, and not descriptive verbal dialogue. Descriptive dialogue can be more effective stimuli to consumers than appearance when dining at a counter restaurant. This finding may explain why VC is delivered to consumers more effectively; VC elicits a feeling of satisfaction in the distribution of service delivery. Another reason is that respondents have a greater recall of their VC service experience at a counter service restaurant than NVC services since studies found that VC encourages better memory recall (Icht, Ben-David, & Mama, 2021). Hence, VC remains in long-term memory and affects consumers’ satisfaction and revisit intention more than NVC. However, NVC also positively impacts satisfaction and revisit intention. Previously, Jung and Yoon (2011) found that NVC affected satisfaction through emotional responses, indicating NVC is another stimulus affecting consumers’ responses. Consumers may pay attention to NVC, but the experience with NVC does not stay with consumerslonger than VC. In addition, NVC can be a part of the restaurant environment, but VC can be a part of a consumer’s direct experiences in distributing services. Therefore, a counter service kitchen should be less noisy so that consumers can pay attention to VC. Also, the restaurant should maintain an appropriate sound level for music and kitchen noise for better communication with consumers.
Moreover, this study’s findings suggest that servers should notice consumers’ characteristics to offer satisfactory services. For example, previous studies showed restaurant kitchen style, whether open or closed, did not influence consumers’ satisfaction. However, studies showed that consumers highly valued grooming, cleanliness, and care in preparing food. This finding is despite researchers conducting the study in a college town where counter service with open kitchen style was limited (Alonso & O’Neill, 2010). Kitchen style matters when it comes to facilitating VC and NVC to increase consumers’ overall satisfaction. A counter service kitchen may magnify the chance of communication to build rapport between consumers and staff, which brings a pleasant interaction followed by satisfactory service. Knowing consumers’ expectations before providing service is essential. Staff at a counter service restaurant should notice consumers’ expectations from their communication or the price of menu items they choose and then engage communication accordingly.
5. Conclusions
This study hypothesized that VC and NVC affect consumers’ satisfaction and revisit intention. Positively perceived VC and NVC influenced not only consumers’ satisfaction positively but also their revisit intention. This study confirmed that staff communication with consumers during the distribution of service delivery is important to attain consumer satisfaction and other factors previously known in the hospitality industry. In addition, this study’s results suggest that communication is composed of verbal and non-verbal affecting consumers’ behaviors. Consumers’ perceived VC and NVC differed by consumers’ demographic and eating out characteristics related to monetary value. The study found that monetary value impacted consumers’ choice of restaurant and that consumers visiting a restaurant for a particular purpose might be less concerned by staff communication. Although there are some differences between consumers’ demographics and eating out characteristics, consumers were still affected by staff communication skills in the distribution of service deliveries.
Our study also has some limitations for consideration in future studies. Firstly, this study used respondents’ answers within a limited geographical area: the Republic of Korea. Hence, this study's results might show the characteristics of Korean consumers in the distribution ofservice deliveries at counter service restaurants. This study did not measure the purpose of the visit to the counter service restaurant. Consumers might have specific reasons for visiting a restaurant with a different concept or environment from another. This study focused on the effect of VC and NVC on consumer satisfaction and revisit intention. Hence, some other factors that might influence consumer satisfaction need to be included in a future study. In addition, this study depended on respondents’ memory of when they visited a counter service restaurant; therefore, an investigation at an actual restaurant should follow. Moreover, we recommend researching communication’s interaction effect with other factors which influence consumers’ behavior. Lastly, this study asked questions based on respondents’ previous experiences at a counter service restaurant, so further research needs to measure actual consumer behavior in the distribution of service delivery
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