THE IMPACT OF SOCIAL SERVICESCAPE ON RESTAURANT IMAGE AND CUSTOMER SATISFACTION
EL IMPACTO DEL PANORAMA DE SERVICIOS SOCIALES EN LA IMAGEN DEL RESTAURANTE Y LA SATISFACCIÓN DEL CLIENTE
Savaş Artuğer
Doctor en Gestión del Turismo del Instituto de Ciencias Sociales de la Universidad de Adnan Menderes
Universidad Muğla Sitki Koçman
Turquía
[savasartuger@mu.edu.tr]
Fatih Ercan
Doctor en Gestión del Turismo de Adnan Menderes University
Universidad de Zonguldak Bulent Ecevit
Turquía
[fatih.ercan@beun.edu.tr]
Aziz Gökhan Özkoç
Doctor en Gestión y Organización de la Universidad Ciencias Aplicadas de Sakarya
Universidad de Ciencias Aplicadas de Sakarya
Turquía
[azizozkoc@subu.edu.tr]
Taner Dalgin
Doctor en Administración de Empresas del Instituto de Ciencias Sociales
Universidad Muğla Sitki Koçman
Universidad Muğla Sitki Koçman
Turquía
[tanerdalgin@mu.edu.tr]
Para citar el artículo: Artuğer, S.; Ercan, F.; Gökhan, A., & Dalgin, T. (2025). The Impact of Social Servicescape on Restaurant Image and Customer Satisfaction. Turismo y Sociedad, Vol. XXXVI, pp. 313-326. DOI: https://doi.org/10.18601/01207555.n36.13
Fecha de recepción: 5 de mayo de 2024. Fecha de modificación: 8 de agosto de 2024. Fecha de aceptación: 14 de agosto de 2024.
Resumen
Este estudio busca determinar cómo el panorama de servicios sociales influye en la imagen y satisfacción de los clientes de restaurantes. Se analizó a los restaurantes en el distrito de Bahçelievler en Estambul con el Certificado de Gestión Turística del Ministerio de Cultura y Turismo de Türkiye. Se recopilaron datos de 360 visitantes de los restaurantes. Se utilizaron los Modelos de Ecuaciones Estructurales (MES) para examinar las relaciones entre las variables. Los resultados muestran que las dimensiones del panorama de servicios sociales, como empleados, otros clientes y relaciones, impactan positivamente en la imagen del restaurante. Sin embargo, la aglomeración social tiene un efecto negativo en la imagen. Además, se encontró que la imagen del restaurante influye positivamente en la satisfacción del cliente.
Palabras clave: Panorama de servicios, Panorama de servicios sociales, Imagen, Satisfacción del cliente.
Abstract
The purpose of this study is to determine the effect of the social servicescape on restaurant image and customer satisfaction. The population of the study consists of restaurants operating in the Bahçelievler district of Istanbul province that have obtained a Tourism Management Certificate from the Ministry of Culture and Tourism of the Republic of Turkey. The study collected data from 360 people who visited these restaurants. Structural Equation Modeling (SEM) was employed to analyze the relationships between the variables. As a result of the research, it was revealed that the social servicescape dimensions of employees, other customers and rapport have a positive impact on restaurant image. On the other hand, the social crowding aspect was found to have a negative effect on restaurant image. It was also found that restaurant image has a positive effect on customer satisfaction.
Keywords: Servicescape, Social Servicescape, Image, Customer Satisfaction.
1. Introduction
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; Dedeoğlu 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.
2. Literature review and hypotheses
2.1. Social servicescape and restaurant image
Servicescape literature began to emerge after Kotler (1973) introduced the term "atmosphere". The author referred to the servicescape as "service atmosphere" and defined it as "the organization of service environments to create emotional effects in order to increase the sense of purchase in customers". According to the source, atmospheric elements consist of four dimensions: visual (e.g. color, brightness, size and shapes), auditory (e.g. sound), olfactory (e.g. smell and freshness) and tactile (softness, smoothness, and warmth) (Kandampullly et al. 2023).
According to Bitner (1992), servicescape is defined as "the physical environment or surroundings of a service business in which services are provided". Servicescape was classified into three dimensions by Bitner (1992): ambient conditions, spatial layout and functionality, and signs, which are symbols and artworks. Ambient conditions are factors such as noise, odor, and temperature. Spatial layout and functionality refer to the arrangement of furnishings and appliances in the service environment. Signs, symbols, and artworks are wayfinding signs, symbols and artworks that provide orientation and information to people in the setting.
The servicescape can be divided into two categories. These are defined as the physical servicescape and the social servicescape. The social servicescape was first conceptualized by Tombs and McColl-Kennedy (2003). The authors drew attention to the importance of human or social elements in the servicescape (Andaji Garmaroudi et al. 2021). While the physical servicescape emphasizes the tangible aspects of the service experience (Asghar et al. 2023), the social servicescape emphasizes the societal aspects of the consumption environment, such as employees and other customers sharing the consumption space (Discepoli et al. 2020). The social servicescape involves social elements such as emotional and behavioral displays, employees' service performance and compliance, social respect, and perceived crowding (Andaji Garmaroudi et al. 2021). Jang et al. (2015) identified four dimensions of social servicescapes consisting of employees, other customers, social crowding, and rapport.
Upon analysis of the relevant literature, it is evident that there are very few studies examining the impact of social servicescape on restaurant image (Jang et al. 2015; Uzuncan and Artuğer 2022). The majority of research regarding how the servicescape affects perception is centered around the physical aspect of the servicescape (Ali et al. 2013; Dedeoğlu et al. 2015; Durna et al. 2015; In et al. 2017). These studies conducted with hotels have concluded that the physical servicescape has an impact on the hotel's image. Jang et al. (2015) investigated the impact of social servicescape dimensions (employees, other customers, social crowding and rapport) on restaurant image. As a result of the research, it was revealed that all social servicescape dimensions were influential on restaurant image. In their study, Uzuncan and Artuğer (2022) reported that the social servicescape dimensions of employees, other customers and relationship had a positive effect on restaurant image, while the social crowding dimension did not have an apparent effect. Abdel-Aal and Abbas (2016), in their study, found that the social servicescape dimensions of employees, other customers and rapport had a positive effect on restaurant image. In this regard, the data from earlier literature was taken into consideration when developing the following hypotheses:
H1: Employees have a positive impact on restaurant image.
H2: Other customers have a positive impact on restaurant image.
H3: Social crowding has a negative impact on restaurant image.
H4: Rapport has a positive impact on restaurant image.
2.2. Restaurant image and customer satisfaction
Literature defines image in a variety of ways. According to common definitions, an individual's views, opinions, and perceptions regarding an item, service, place, person, business, or brand (Lee et al. 2010). According to Aaker (1996), image is "all the experiences, impressions, beliefs, feelings and knowledge that consumers have about a business". Image has a powerful impact on how people view the products and services provided due to its appeal to their emotions (Şahin and Yiğitoğlu 2022). Restaurant image is defined as the sum of perceptions, thoughts, prejudices, and symbolic attitudes that consumers develop about the restaurant. In other words, restaurant image is the result of consumers' cognitive and emotional subjective evaluations and feelings about a restaurant, regarding its attributes (Özdemir and Şahin, 2021).
Fulfilling the needs and desires of customers has turned into a motto for businesses looking to keep and grow their clientele. Increasing customer satisfaction is the ultimate goal of hotel and restaurant businesses in the highly competitive global hospitality market (Lee et al. 2020). Long-term competitiveness and business success are frequently linked to customer satisfaction. Customer satisfaction can be thought of as an evaluation based on a comparison between performance and expectations. Customer satisfaction occurs when a product or service meets or surpasses the expectations of the client (Ullah Khan et al. 2022). Customer satisfaction can be defined as the combined evaluation of customers' purchase and consumption experiences. As a result, another typical definition of customer satisfaction is the post-purchase assessment of the quality of the product or service in comparison to pre-purchase expectations (Yi et al. 2021). Studies examining the effect of restaurant image on customer satisfaction can be found in the literature (da Costa Oliveira et al. 2020; Erkmen and Hançer, 2019; Espinosa et al. 2018; Jeon, 2017; Ryu et al. 2008). These studies concluded that restaurant image has a positive effect on customer satisfaction. Based on these findings, the following hypothesis can be proposed:
H5: Restaurant image has a positive effect on customer satisfaction.
3. Methodology
3.1. Research instrument
The questionnaire technique was utilized as a data collection method in this present study. The questionnaire consists of three sections. In the first section, the demographic characteristics of the participants (gender, age, and education level) and the frequency of visits to the restaurant are presented. In the second part, there is a scale measuring the social servicescape area consisting of 19 items and 4 main dimensions (employees, other customers, rapport, and social crowding). In the third section, restaurant image and customer satisfaction were measured with three statements each. The scale measuring the social servicescape and the statements related to restaurant image were adopted from the study conducted by Jang et al. (2015). Statements related to customer satisfaction were adopted from the study conducted by Ryu and Han (2011). The level of agreement of the participants for each statement on all three scales was rated on a 5-point Likert scale as "Strongly disagree=1", "Disagree=2", "Neutral=3", "Agree=4" and "Strongly agree=5".
3.2. Sampling and Data Collection
The population of the present study, which aims to determine the effect of social servicescape on restaurant image and customer satisfaction, consists of restaurants operating in Bahçelievler district of Istanbul province, which have received a Tourism Management Certificate from the Ministry of Culture and Tourism of the Republic of Türkiye. According to the data of the Istanbul Provincial Directorate of Culture and Tourism in September 2023, there are 10 restaurants in Bahçelievler district. Restaurant owners and managers were interviewed and 5 of them agreed to be surveyed, while 5 refused. The surveys were collected from Turkish customers who visited these restaurants between September 1 and September 30, 2023.
Convenience sampling, one of the non-probability sampling techniques, was applied in the present study. There are various opinions on the appropriate number of samples to use when employing structural equation modeling. Hair et al. (2014) emphasize that 200 people would be sufficient for the sample size if structural equation modeling is utilized. According to Schumacker and Lomax (2010), this number can range between 250-500. However, this research targeted to reach 400 participants. Accordingly, 400 questionnaires were distributed equally (80) among 5 restaurants that agreed to conduct the survey. Out of the distributed questionnaires, 375 were returned. Ten of these returned questionnaires were excluded due to incomplete and incorrect completion, and 365 questionnaires were taken into evaluation.
3.3. Data Analysis
Firstly, frequency and percentage distributions regarding the demographic characteristics of the participants (gender, age, and education) and the frequency of their visits to the restaurant are presented. The relationships between the variables in the study were analyzed using the Structural Equation Modeling (SEM) technique. Structural Equation Modeling was performed using the Maximum Likelihood Estimation method. This present study applied the two-stage approach suggested by Anderson and Gerbing (1988) for Structural Equation Modeling. Therefore, first, Confirmatory Factor Analysis (CFA) was applied to test the validity and reliability of the measurement model. Then, SEM was conducted to test the model proposed in the study.
Before applying SEM, the data was examined for outliers, missing data, and the presence of a normal distribution (multivariate normality) (Evangelista and Dioko 2010; Woo et al. 2015). No missing values were found in the data. When the Mahalanobis Distance values were checked for irregularities utilizing the Amos program, several outliers were identified. The questionnaires with outliers (five) were removed from the dataset, leaving 360 questionnaires for analysis. The skewness and kurtosis values were evaluated to determine if the data fit the normal distribution. According to Shiel and Cartwright (2015), skewness and kurtosis values between -1 and +1 are considered to be quite good for the normal distribution of data, while values between -2 and +2 are acceptable. As a result of the analysis, it was determined that the skewness value of only one item was between -2 and +2, while the skewness and kurtosis values of the other items were between -1 and +1.
4. Results
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.
When the goodness-of-fit index of the model in table 2 is examined; χ2=521.521, df=217, χ2/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.
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 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 χ2=529.637, df=221, χ2/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).
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 (β) 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.
5. Conclusion
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; Dedeoğlu 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.
6. Limitations and suggestions for future research
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.
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