Consumer behavior and service experiences are greatly influenced by the servicescape. (Furrer et al. 2023). Kotler (1973) coined the term "atmosphere" to describe the environmental cues that influence customers to develop specific emotions and thus increase their likelihood to make a purchase, and since then the influence of the servicescape on customer responses has increased substantially. Bitner (1992) proposed the term "servicescape" to describe the physical environment in which a business provides services to customers (Li and Wei 2021).

Servicescape can be divided into two categories. These are defined as the physical servicescape and the social servicescape. The physical servicescape consists of elements like ambience, décor, layout, facilities, and architecture (Bitner, 1992); the social servicescape consists of elements like employees, other customers, social crowding, and rapport in a servicescape (Jang et al. 2015). A well-thought-out servicescape increases customer satisfaction and makes them feel good. Service quality is often difficult to assess. This is why customers often perceive the servicescape as an important quality indicator. As a result of this, the servicescape plays an essential role in determining how consumers view the image and positioning of a business (Wirtz et al. 2017). A favorable perception of the servicescape has a positive effect on the image of the business (Ali et al. 2013). Accordingly, customer satisfaction is also impacted by a positive perception of a company's image (Ryu et al. 2008).

Several studies on the impact of physical servicescape on business image have been conducted (e.g., Ali et al. 2013; Dedeoglu et al. 2015; Durna et al. 2015; Erkmen and Hançer, 2019; Han 2019; In et al. 2017). However, studies on the impact of social servicescape on business image are rather limited (Abdel-Aal and Abbas, 2016; Jang et al., 2015; Uzuncan and Artuğer 2022). There are only two studies that specifically focus on restaurants (Jang et al. 2015; Uzuncan and Artuğer 2022). Furthermore, research has also indicated that a favorable customer perception of a business positively affects customer satisfaction (da Costa Oliveira et al. 2020; Erkmen and Hançer, 2019; Espinosa et al. 2018; Jeon, 2017; Ryu et al. 2008).

The aim of this study is to identify the influence of social servicescape on restaurant image and customer satisfaction, in accordance with the data collected from literature. In line with this objective, the research was conducted in restaurants operating in the Bahçelievler district of Istanbul province, which have received a Tourism Management Certificate from the Ministry of Culture and Tourism of the Republic of Turkey. Determining the impact of social servicescape on restaurant image is a crucial aspect of this study, as it has not been extensively explored by many scholars in previous research. In this regard, it is believed that this study will close a gap in the field and add significantly to the relevant literature.

According to the data in table 1, 50.8% of the participants were male and 49.2% were female. The majority of the participants (79.7%) ranged from 21 to 50 years of age. Regarding the educational level of the participants, the majority (83.4%) held associate, undergraduate, and postgraduate degrees. 44.7% of participants visited the restaurant for the first time, 18.1% for the second time, 11.9% for the third time, and 25.3% for the fourth or more times.

Table 1

Characteristics	Frequency	%
Gender
Male	183	50.8
Female	177	49.2
Age
20 and under	17	4.7
21-30	120	33.3
31-40	100	27.8
41-50	67	18.6
51-60	33	9.2
61 and over	23	6.4
Education Status
Primary School	12	3.3
High School	48	13.3
Associate	42	11.7
Bachelor's Degree	191	53.1
Master's Degree	67	18.6
Frequency of visit to the restaurant
First time	161	44.7
Second time	65	18.1
Third time	43	11.9
Fourth time and over	91	25.3

When the goodness-of-fit index of the model in table 2 is examined; X²=521.521, df=217, X²/df=2.40, p<0.001, RMSA=0.06, AGFI=0.86, GFI=0.90, CFI=0.95, NFI=0.92. These numbers indicate that the fit values in the measurement model are acceptable (Hoe, 2008; Schermelleh-Engel et al. 2003).

In order to determine the construct validity of the scale, convergent validity and discriminant validity were evaluated. Three methods were used to assess convergent validity: Factor loadings show, CR (composite reliability) and AVE (average variance explained) values (Hair et al 2014).

According to Hair et al. (2014), factor loadings in confirmatory factor analysis must be 0.70 or above, but 0.50 or above remains acceptable. As a result of the confirmatory factor analysis, two statements from the social crowding dimension in the scale measuring social servicescape were excluded from the factor analysis since their factor loadings were below 0.50. Upon closer inspection, the factor loadings of other statements in table 2 are found to be above 0.70. Existing research literature suggests that the CR value should be 0.70 and above and the AVE value should be 0.50 and above (Hair et al 2014). Analysis of the data in Table 2 indicates that the AVE values of all dimensions are above 0.50 and their CR values are above 0.70.

Table 2

Factor/Items	Factor loading	Cronbach's Alpha	CR	AVE
Employees		0.92	0.92	0.65
The staff make an effort for the customers.	0.80
The staff are competent.	0.85
The staff seem confident.	0.81
Staff show empathy towards customers.	0.81
Staff make eye contact with customers.	0.76
Staff communicate well with customers.	0.84
The staff are friendly.	0.76
Other customers		0.91	0.92	0.74
Other customers seem happy.	0.85
Other customers seem satisfied.	0.86
Other customers seem cheerful.	0.86
The other customers seem peaceful.	0.87
Social crowding		0.86	0.87	0.69
This restaurant seems a little too busy.	0.81
There are a lot of customers in this restaurant.	0.90
This restaurant looks very crowded.	0.78
Rapport		0.84	0.86	0.69
The interaction between staff and customers seems harmonious.	0.86
The interaction between staff and customers seems to be good.	0.93
The staff seem to have a close relationship with the customers.	0.68
Restaurant Image		0.87	0.87	0.70
This restaurant has a pleasant atmosphere.	0.78
This restaurant is a convenient place to eat.	0.86
This restaurant is attractive.	0.87
Customer Satisfaction		0.92	0.92	0.80
Overall, I was pleased with this restaurant.	0.87
Overall, I was pleased with the service I received from this restaurant.	0.93
I really enjoyed this restaurant.	0.88

Goodness-of-fit statistics: p:0.000 X²:521.521 df:217, X²/df =2.40, CFI:0.95, GFI: 0.90, NFI:0.92, RMSEA:0.06, AGFI:0.86

In discriminant validity, the square roots of AVE values are compared with the correlation coefficients between constructs. Correlation values between constructs should be lower than the square roots of AVE values (Fornell & Larcker, 1981). When the data in table 3 are analyzed, it is seen that the correlation coefficients between the constructs are lower than the square root of AVE values. Upon assessing all the results collectively, it can be concluded that the construct validity of the scale was achieved.

Table 3

	Employees	Other customers	Social crowding	Rapport	Restaurant image	Customer satisfaction
Employees	0.806
Other customers	0.717	0.860
Social crowding	0.347	0.311	0.830
Rapport	0.752	0.647	0.375	0.830
Restaurant image	0.743	0.670	0.211	0.721	0.836
Customer satisfaction	0.568	0.544	0.312	0.653	0.525	0.894

Note: The diagonals (in bold) represent the square root of the AVE

Table 4 presents the fit values and hypothesis test results of the structural equation model. When the goodness-of-fit index of the model in table 4 is examined, it is seen that x²=529.637, df=221, x²/df=2.39 p<0.000, RMSEA=0.07, AGFI=0.85, GFI=0.90, CFI=0.95, NFI=0.91. These values show that the fit values of the measurement model are at an acceptable level (Hoe, 2008; Schermelleh-Engel et al, 2003).

Table 4

Note: x²=529.637 df=221, x²/df=2.39 p<0.000, RMSEA=0.07, AGFI=0.85, GFI=0.90, CFI=0.95, NFI=0.91

When the data in table 4 is examined, it is seen that the social servicescape dimensions of employees (β=0.386, p<0.05), other customers (β=0.191, p<0.05), and rapport (β=0.406, p<0.05) have a positive effect on restaurant image. Whereas, social crowding (β=-0.123, p<0.05) has a negative effect on restaurant image. Therefore, hypotheses H₁, H₂, H₃ and H₄ are all supported. According to the standardized regression coefficients (P) in table 4, the most significant factor influencing restaurant image is rapport (β=0.406, p<0.05). Additionally, restaurant image (β=0.281, p<0.05) was found to have a positive effect on customer satisfaction. Therefore, hypothesis H₅ is also supported.

This present study aims to determine the effect of social servicescape on restaurant image and customer satisfaction. It was determined that the social servicescape dimensions of employees, other customers and rapport have a positive effect on restaurant image. Research results revealed that the most influential factor affecting restaurant image is the rapport (interaction/relationship between customer and employee) dimension. To put it differently, it was concluded that the interaction between employees and customers has a greater impact on restaurant image. These results are similar to the results of the studies conducted by Jang et al. (2015) and Uzuncan and Artuğer (2022). Accordingly, the results of these studies revealed that the most important factor affecting restaurant image is the rapport dimension. Kaminakis et al. (2019) concluded that rapport has an impact on relationship quality. Abdel-Aal and Abbas (2016) found that social servicescape affects hotel image more than physical servicescape. This finding suggests that social servicescape, as opposed to physical servicescape, has a greater impact on hotel image in tourism businesses.

In the present study, it was determined that the social crowding dimension, one of the social servicescape dimensions, has a negative effect on restaurant image. To put it differently, as social crowding increases in restaurants, the image perception of the business is negatively affected. This finding aligns with the result attained by Jang et al., (2015). However, in the research conducted by Uzuncan and Artuğer (2022) in restaurants, it was revealed that the social crowding dimension did not have any effect regarding restaurant image.

The number of studies on the impact of social servicescape on image is rather limited (Jang et al., 2015; Uzuncan and Artuğer, 2022). The focus has mostly been on the physical servicescape in tourism businesses. Nevertheless, when these studies (Ali et al. 2013; Dedeoglu et al. 2015; Durna et al, 2015; In et al, 2017) are analyzed, it is observed that physical servicescape has a positive effect on image as well.

Another conclusion obtained from this present study is that restaurant image influences customer satisfaction in a positive way. Positive restaurant image perceptions are positively correlated with increased customer satisfaction. Several studies in previous literature support this conclusion (da Costa Oliveira et al., 2020; Erkmen and Hançer, 2019; Espinosa et al, 2018; Jeon, 2017; Ryu et al, 2008).

Taking into account the findings of this study, restaurant owners and managers can consider the following suggestions for further improvement. In restaurants, especially the rapport (interaction between customers and employees) dimension has a significant impact on restaurant image. Therefore, restaurant managers should pay more attention to rapport and train their employees in effective communication and oratory. Furthermore, the fact that other customers in the restaurant are happy and satisfied also contributes significantly to the image perception of the restaurant. Therefore, providing good service only to a certain group of customers in the restaurant will not be enough. Providing the same level of service quality to all customers is crucial for the image of the establishment. Positive image perception among customers will also positively affect their satisfaction.

Since the present study was carried out in restaurants, it cannot be applied to other tourism-related businesses. While a considerable amount of research has been conducted regarding the impact of physical servicescape on image, very little has been conducted regarding the influence of social servicescape on image. The purpose of this study is to close this gap in the literature. Further research can be carried out in other tourism establishments (such as hotels, bars, etc.) in order to benefit the literature and tourism industry professionals.