Abstract
Purpose
This paper aims to explore the factors influencing customers' attitudes and behaviours, specifically in terms of affective satisfaction, participation behaviour, and word-of-mouth, within the restaurant industry, with a focus on both tangible and intangible elements. Additionally, the study seeks to identify the dual mediating role of customer affective satisfaction in this relationship.
Design/methodology/approach
In this exploratory study, SEM-VB was utilized to examine data from 312 valid respondents who completed a face-to-face questionnaire using a quantitative methodology. The respondents were targeted at restaurants that serve comparable food and beverages for a similar socioeconomic class.
Findings
The findings reveal that perceived value, physical appearance, and standardization significantly contribute to customer affective satisfaction, which, in turn, positively influences their participation behaviour and word-of-mouth.
Practical implications
Practically, restaurant managers can enhance customer experiences and boost positive word-of-mouth by fostering affective satisfaction and encouraging interactive customer participation.
Originality/value
The novel concept of “affective satisfaction” contributes to restaurant management literature by identifying its tangible and intangible drivers and uncovering its outcomes in participation behaviour and word of mouth. By combining numerous factors and investigating the mediating function of affective satisfaction and based on the theory of Expectancy-Disconfirmation, this study adds to the theoretical understanding of what drives the affective satisfaction and word-of-mouth of casual dining restaurants’ customers.
Keywords
Citation
Khalifa, G.S.A., Elshaer, A.M., Hussain, K. and Elnagar, A.K. (2024), "What drives customers’ participation behaviour? Unveiling the drivers of affective satisfaction and its impacts in the restaurant industry", Journal of Hospitality and Tourism Insights, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/JHTI-01-2024-0100
Publisher
:Emerald Publishing Limited
Copyright © 2024, Emerald Publishing Limited
1. Introduction
The food service industry is now recognized as a major component of the global economy. In Egypt, the current state of the Egyptian economy has increased the workforce employed in the restaurant industry (Elshaer, 2022). A surge in the popularity of eating out has made consumers more aware of the quality of the food, service, and atmosphere at food service establishments (Rajput and Gahfoor, 2020). Therefore, restaurants strive to deliver a memorable eating experience by mixing both tangible and intangible elements. At the restaurant, the decisive goal is to achieve effective customer satisfaction (ACS), customer participation behaviour (CPB), and word of mouth (WOM) (Ribeiro et al., 2024).
In terms of assessing restaurants, food, and service are considered the most vital factors for customers in determining their satisfaction (Wang et al., 2010; Stribbell and Duangekanong, 2022). Academics are actively studying the consequences and antecedents of affective customer satisfaction, advocating for further research in this domain (Elshaer, 2020; Güvenç et al., 2023; Khalifa et al., 2023). Affective satisfaction in restaurant management is patrons' emotional response during and after dining, closely tied to enhancing value and enjoyment – a feeling of satisfaction (Hwang and Lee, 2019; Ribeiro et al., 2024), influencing emotional fulfilment and purchasing decisions (Hwang and Lee, 2019). It differs from servicescape, which encompasses the physical environment’s ambiance – evaluation of physical attributes (Kim and Park, 2019), with elements evoking specific emotional responses (Kim and Lee, 2022). This study intends to investigate the aspects that affect affective satisfaction, customer participation behaviour, and WOM in the setting of Egyptian restaurants, including perceived value, physical appearance, standardization, ambient condition, and food hygiene. However, according to Malik et al. (2013), there is little empirical research on customer satisfaction’s antecedents and outcomes concerning restaurant service quality. While there have been numerous studies investigating perceived value and customer satisfaction in general (Chen et al., 2014), limited and insufficient research has specifically focused on affective satisfaction and its impact on customer participation behaviour in the context of the restaurant industry.
The food quality, the service level, and the physical environment of restaurants – which constitute the restaurant domain – are increasingly influencing the attitudes and behaviours of customers – see Figure 1. According to Rajput and Gahfoor (2020), in the case of just one evasive encounter, customers swiftly transfer their allegiance. Elshaer (2020) therefore states that restaurants should concentrate on offering a memorable eating experience by fusing tangible and intangible necessities. Given the pivotal role of customer satisfaction in restaurant success, word-of-mouth (WOM) activities, proven more impactful than promotions, demand careful consideration (Güvenç et al., 2023). The integration of local culinary resources into WOM marketing strategies is underscored as crucial (Okumus and Cetin, 2018), especially with customer participation behaviour aimed at crafting memorable dining experiences, which enhances perceived benefits and performance, and potentially generates positive WOM (Ngoma et al., 2019). This suggests that establishing positive customer participation behaviour and capitalizing on their WOM can significantly contribute to achieving a competitive edge in highly competitive markets (Ngoma et al., 2019). Furthermore, Ryu et al. (2021) discovered that factors affecting consumer satisfaction in the restaurant industry need further research, including service standardization (Wang et al., 2010), physical environment (Yeh et al., 2020), restaurant ambiance (Nusairat et al., 2020), and food hygiene (Kubde et al., 2016). In addition, the affective basis of satisfaction justifying this relationship has not been adequately explored (Fauza et al., 2022).
This study delves into the exploration of affective satisfaction and customer participation behaviour (Ida, 2017) within the context of customer co-creation value (Pantoja-Diaz et al., 2023), potentially bolstering positive WOM in competitive market environments. In particular, the scholarly focus has primarily cantered on developed and/or Western nations. Yet, understanding this construct within an African context is imperative for both industry success and the nation’s overall development (Ukeje et al., 2021). Notably, Elshaer (2022) noted significant challenges and changes in Egypt’s food service industry, particularly in Greater Cairo, leading to intensified competition. The competitive climate in Cairo, known for its cultural diversity and culinary heritage, attracts culinary tourism (Rafaqat, 2024), with a substantial number of casual-dining restaurants (726 classified by the Ministry of Tourism and Antiquities) (Chamber of Tourism Establishments, 2024; Rafaqat, 2024). The study addressed the dearth of research on affective satisfaction and customer participation behaviour in the Egyptian restaurant industry by examining 73 restaurants in Greater Cairo, chosen for their proximity to the elite clientele known for restaurant commuting. The study uncovers fresh insights into Egyptian dining experiences, revealing how certain factors significantly impact customer satisfaction. By understanding these dynamics, restaurant owners can cultivate stronger customer participation and positive word-of-mouth through improved affective satisfaction.
2. Theoretical framework and relevant literature
2.1 Expectancy-disconfirmation theory
The impact of expectancy disconfirmation on customer satisfaction has been widely recognized and implemented in the satisfaction literature in the retail and service sectors (Piqueras-Fiszman and Spence, 2015). Based on the Expectancy-Disconfirmation Theory (EDT), individuals form expectations regarding a service or product based on their prior experiences, information, and personal beliefs. These anticipations function as a benchmark by which individuals assess their real experiences or perceived performance (Oliver, 1999). Positive disconfirmations are linked to positive actions, positive attitudes, and satisfied customers (Cai and Chi, 2021).
In the competitive realm of restaurants, prioritizing customer attraction is vital, followed by ensuring satisfaction (Güvenç et al., 2023). Research suggests that factors like perceived value, physical appearance, standardization, ambient conditions, and food hygiene significantly influence satisfaction (Agbenyegah et al., 2022; Khalifa et al., 2023; Kim et al., 2021; Sengel et al., 2015). Affective satisfaction acts as a mediator between these factors, and dependent variables, including customer participation behaviour and word-of-mouth (WOM). Customers experiencing affective satisfaction are more likely to engage in positive guest participation behaviours, such as active involvement in the service process and providing feedback (Teng and Chang, 2013; Yeh et al., 2020). This behaviour can be seen as a confirmation of their positive expectations and a desire to maintain or enhance their satisfying experience. Additionally, affective satisfied customers are more likely to engage in positive WOM, sharing their positive experiences with others and recommending the restaurant to friends and family.
By applying ED theory, this study can assess the degree to which customers’ expectations are met or exceeded by the independent variables and how this influences their affective satisfaction, guest participation behaviour, and WOM. It helps to understand the process through which expectations, perceived performance, and affective satisfaction shape customers’ behaviours and attitudes, providing valuable insights into customer satisfaction and engagement in the restaurant industry.
2.2 Customer affective satisfaction
Affective satisfaction can be defined as the subjective measure of the emotions and feelings experienced while interacting and engaging with a service or product (Park et al., 2019). The concept of affective satisfaction aims to capture the subjective impressions and emotional responses elicited during the consumption of services and products, providing valuable insights to designers regarding how guests can be affective satisfied in various situations (Cho et al., 2011).
While there have been numerous studies measuring affective satisfaction across different disciplines, only a few have specifically examined its relationship within the restaurant industry and its interaction with other constructs (Elshaer, 2022). In this essence, Palací et al. (2019) mentioned that affective satisfaction encompasses various dimensions including simplicity, luxury, attractiveness, texture, colourfulness, delicacy, salience, and overall satisfaction – see Table 1.
2.3 Customer-perceived value, affective satisfaction, and participation behaviour
In the last decades, there has been a great deal of scholarly attention on customers’ perceived value within the service industry (Ukeje et al., 2021), as customers have become more value-driven (Elshaer, 2020). This concept has been linked to various outcomes, including loyalty, satisfaction, patronage, retention, purchase intention, revisit intention, and behavioural intention (El-Adly, 2019). Understanding customers' perceived value in the restaurant context necessitates acknowledging its subjective and multidimensional nature, which goes beyond price and quality considerations (Hossain et al., 2023). Perceived value has been found to have a significant and positive direct effect on customers’ satisfaction and loyalty across various services, particularly within the restaurant industry (e.g. Paulose and Shakeel, 2022).
In Egypt’s competitive restaurant industry, customer-perceived value is crucial for enhancing satisfaction (Rafaqat, 2024). Perceived value, as described by Prayag et al. (2015), encompasses affective or psychological reactions stemming from the consumption experience, encompassing both functional (e.g. food quality) and hedonic (e.g. staff politeness) aspects. Nitiwanakul (2014) found that 40% of the variance in perceived value can be attributed to its influence on customer satisfaction. According to the ED theory, satisfaction occurs when perceived performance aligns with or exceeds expectations. Therefore, when customers perceive value in their dining experience, such as high-quality food at reasonable prices, it promotes customer affective satisfaction, encouraging customers’ participation in the restaurant (Teng and Chang, 2013). Consequently, affective satisfaction can act as a mediating factor between perceived value and participation behaviour, contributing to customers’ attitudes and the mutual understanding necessary to improve restaurant service and overall reputation. Hence, the following hypothesis is developed:
There is a significant and positive relationship between perceived value and customer affective satisfaction.
2.4 Physical appearance, affective satisfaction, and customer participation behaviour
Physical appearance holds a significant influence on various aspects of life, including interpersonal relationships, personal well-being, facial attractiveness, employment opportunities, financial incentives, and reputations (Yeh et al., 2020). Extensive research has been conducted in different sectors to explore the measurements and relationships associated with physical appearance (e.g. Choi et al., 2020). According to Khalifa et al. (2023), physical appearance is a vital aspect of the restaurant experience and exhibits dimensional relationships with attractiveness, competence, trustworthiness, likeability, and happiness. Yeh et al. (2020) added that customers focus on various aspects of overall service, including server style when serving food, how they inquire about food preferences, offering additional food, and a good demeanour and appearance. Following the ED theory, individuals' expectations, shaped by factors such as physical appearance’s impact on mental and health conditions in restaurant settings (Peat et al., 2008), influence affective satisfaction and customer participation in restaurant services. Therefore, the following hypothesis is established:
There is a significant relationship between physical appearance and customer affective satisfaction.
2.5 Standardization, customer affective satisfaction, and customer participation behaviour
Standardization, initially introduced in the European market by Elinder (1961), aims to achieve desirable and feasible uniformity. In the service context, it involves establishing consistent characteristics for products or services, aiding in forecasting, control, and failure minimization (Weyers and Louw, 2017). Standardization in restaurant operations enhances consistency, optimizes service time, ensures quality service, increases competition, reduces costs, protects brand image, and fosters innovation (Weyers and Louw, 2017). According to Wang et al. (2010), standardization is vital in the service context of restaurants, ensuring that customers receive consistent and distinctive food and service experiences. In particular, inconsistency in quality and service is a common issue for Egyptians dining out, encompassing variations in food taste, portion sizes, and service standards like wait times and staff attentiveness (Abdelaal and Elshaer, 2020; Elshaer, 2020).
Standardization in restaurant operations, encompassing food preparation and service delivery, ensures consistent high-quality service and food, leading to cost reduction and improved efficiency (Kwol et al., 2020; Weyers and Louw, 2017). This adherence to service quality principles prompts consumer investment in service improvement, aligning with the ED theory (Oliver, 1999) to maintain high service standards while also leaving an emotional image that impacts consumer affective satisfaction (Dong and Sivakumar, 2017), supporting the hypothesis.
There is a significant and positive relationship between standardization and customer participation behaviour.
2.6 Ambient condition, customer affective satisfaction, and customer participation behaviour
The ambient condition, including decor, ambiance, seating comfort, equipment, design, cleanliness, safety, view, and food ingredients, provides cues to first-time customers regarding the nature of the expected service offerings (Ngah et al., 2022). In the service industry, where intangible experiences pose evaluation challenges (Elshaer and Marzouk, 2019), the ED theory underscores the importance of surpassing expectations for satisfaction (Oliver, 1980). Consequently, researchers and hospitality managers prioritize crafting appealing ambient conditions in restaurants (Kim et al., 2021) to exceed guest expectations and foster satisfaction.
According to Kim et al. (2021), ambient condition plays a crucial role in influencing customers through providing an enjoyable dining atmosphere. Similarly, Moon et al. (2021) emphasized the significant impact of facility interiors on customers’ dining experience and participation behaviour. The mediating role of affective satisfaction between ambient conditions and customer participation behaviour captures the influence of the restaurant’s structure, features, and overall design on customer affective satisfaction (Ryu et al., 2021). While previous research has suggested that ambient condition strongly influences satisfaction (Agbenyegah et al., 2022), there has been limited investigation into the relationship between ambient conditions and customer participation behaviour after achieving affective satisfaction. Therefore, this study suggests the following hypothesis:
There is a significant and positive relationship between ambient conditions and customer participation behaviour.
2.7 Perceived food hygiene, affective satisfaction, and customer participation behaviour
In the restaurant industry, concerns over cleaning methods and compliance with COVID-19 protocols heighten customer anxieties (Siddiqi et al., 2022). Prioritizing food hygiene instils confidence in customer safety and enhances affective satisfaction, fostering positive perceptions and participation (Elshaer et al., 2022). Similarly, Soonsan et al. (2023) highlight the impact of hygiene measures on customer satisfaction. Additionally, Elshaer (2022) and Fatimah et al. (2011) argued that customers form their overall impressions based on the sanitary conditions of the locations they frequent, the spaces utilized by service providers, and the personal cleanliness of the service providers themselves, echoing the principles of the ED theory.
Research in service management has highlighted that customers' experiences with restaurant services directly influence their attitudes toward the products and services provided (Rajput and Gahfoor, 2020). Therefore, restaurant hygiene plays a crucial role in predicting customers' behavioural responses, including their overall satisfaction and their desire to return (Lim et al., 2022). According to Buccheri et al. (2010), a hygienic environment makes customers feel satisfied and encourages them to participate in different activities within the restaurant. So, we contend that sanitary behaviour affects consumer participation through customer satisfaction, leading to the following hypothesis:
There is a significant and positive relationship between food hygiene and customer participation behaviour.
2.8 Affective satisfaction and customer participation behaviour
Customer satisfaction is the degree to which a customer’s experience leaves them feeling comfortable (Rust and Oliver, 1994). It has been demonstrated that customer satisfaction, which is primarily a cognitive activity, acts as a mediating variable between perceived quality of service and behavioural intentions (Hartono and Raharjo, 2015). This study defines customer satisfaction from a cumulative standpoint – see Figure 2 emphasizing overall assessments rather than any purchasing experience (Oliver, 1999).
Customer participation is a well-established idea in the service business and is particularly prominent in the restaurant context (Chen et al., 2014). Participation behaviour involves informational, emotional, and responsible engagement (Yi and Gong, 2013), and the inseparability of service consumption and production implies that customers become active participants in the service processes (Elshaer and Marzouk, 2019). Therefore, participation behaviour is closely intertwined with affective satisfaction, as it involves seeking benefits through interactions and service provision. In this vein, Delpechitre et al. (2018) revealed that customer participation behaviour positively impacts their emotional understanding and promotes agreement among customers to participate. Thus, assessing affective satisfaction levels during the service process, from sharing information to smiles and lenience, facilitates understanding customer participation. Hence, the following hypothesis is developed:
There is a significant and positive relationship between affective satisfaction and customer participation behaviour.
There is a significant and positive mediation effect of affective satisfaction between (perceived value, physical appearance, standardization, ambient condition, food hygiene) and customer participation behaviour.
2.9 Customer affective satisfaction and WOM
Customer affective satisfaction reflects guests' emotional experiences and overall satisfaction with a service or product (Ehimen et al., 2021), while word-of-mouth (WOM) refers to informal communication and recommendations about experiences with a service or product (Chao et al., 2021). Studies consistently show that affective satisfaction significantly influences WOM behaviour, as satisfied customers are more likely to engage in positive recommendations and share their experiences (Chao et al., 2021; Khoo, 2020).
Perceived value is a key determinant of affective satisfaction, as it encompasses the assessment of the advantages and costs associated with a service or product (Elshaer and Huang, 2023). When customers perceive that they have received high value for their money, they are more likely to feel satisfied and inclined to share positive WOM. In the context of the restaurant industry, the value that customers receive entails different elements that contribute to their satisfaction and positive WOM, such as physical appearance (Yeh et al., 2020), standardization of service quality (Stribbell and Duangekanong, 2022), ambient condition (Agbenyegah et al., 2022), and food hygiene (Elshaer, 2022). In summary, understanding and managing customer affective satisfaction is crucial for fostering positive WOM. Consequently, we hypothesize that:
Affective satisfaction is positively influencing WOM.
There is a significant and positive mediation effect of affective satisfaction between (perceived value, physical appearance, standardization, ambient condition, food hygiene) and WOM.
2.10 Customer participation behaviour and WOM
The connection between customer participation behaviour and WOM holds significant importance in the service industry. When customers actively participate in the service process and have a positive engagement with the service providers, they are more likely to have memorable and enjoyable experiences (Elshaer and Marzouk, 2022), leading to positive WOM (Elshaer and Marzouk, 2019). Customers actively engaged in the service process, experiencing a sense of co-creation, are more likely to become brand advocates and engage in positive word-of-mouth (WOM) (Delpechitre et al., 2018). Their involvement reflects satisfaction and enthusiasm, influencing others to try the service and spread positive recommendations. Additionally, customer participation behaviour enhances the authenticity and credibility of WOM, as their first-hand experiences demonstrate higher involvement and commitment (Ida, 2017). As a result (see Figure 3), we hypothesize:
Customer participation behaviour is positively influencing WOM.
3. Method
3.1 The study design
The study focused on 73 restaurants located in diverse geographical locations within Greater Cairo, chosen for their proximity to the population elite renowned for commuting to restaurants. Residents who reside in areas with a higher density of restaurants tend to exhibit a heightened inclination toward dining out, as observed by Bell et al. (2020). Additionally, Haddad et al. (2023) found that individuals residing in neighbourhoods abundant in restaurants tend to engage in dining-out activities more frequently. This approach facilitated the acquisition of a diverse and representative sample of respondents for the study by strategically targeting locations renowned for their substantial restaurant presence, such as Zamalek, Madinet Naser, Maadi, and Heliopolis, as depicted in Figure 4. The selected restaurants varied in location and ambiance, yet provided similar food and beverages tailored to a consistent socioeconomic demographic.
The survey comprised three parts: the first explored the restaurant domain (PV, PA, ST, AC, and FH), the second focused on customer affective satisfaction, participation behaviour, and WOM, and the third identified participant demographics and dining preferences.
To assess the model’s constructs and increase the study’s content validity, 37 items in all were developed from the body of research. The first part of the study focused on the features of restaurants, including perceived value, physical appearance, standardization, ambient condition, and food hygiene, which were based on previously validated scales including Hyun et al. (2011), etc. (see Table 2). While, affective satisfaction was measured through a 5-point Likert scale, assessing feelings of happiness, pleasantness, joyfulness, and delight, as outlined by Ladhari et al. (2017). Delpechitre et al. (2018) scale items were employed to measure customer participation behaviour, consisting of information sharing (3 items) and responsible behaviour (3 items). Also, items from the scale used by Jalilvand et al. (2012) were recognized to measure WOM. Likert scales with a range of 1 (strongly disagree) to 5 (strongly agree) were used for assessing every item.
3.2 Data gathering and sample characteristics
The study included frequent diners aged 18 and above who had visited different types of restaurants in Egypt within the past six months. A random sampling approach, guided by Sekaran’s (2011) recommendations for the specific area, involved selecting participants randomly from lists of registered diners who had visited restaurants within the defined timeframe. The questionnaire employed an unrestricted or simple random sampling procedure, for which Hoelter (1983) recommends a minimum sample size of 200. Based on this, a total of 350 questionnaires were delivered to the target population, resulting in 312 valid responses, representing 89.1% of the population.
3.3 Data analysis
This study utilized Smart-PLS 3.0 software and applied the Partial Least Squares (PLS) approach within Structural Equation Modelling-Variance Based (SEM-VB) (Ringle et al., 2015). Following a descriptive analysis, a two-stage analytical approach recommended by Hair et al. (2017) was employed. This approach involves evaluating the validity and reliability of the measurement model, followed by examining the hypothesized correlations in the structural model. PLS offers advantages over a one-step procedure by simultaneously examining both models, resulting in more accurate estimates (Ringle et al., 2015).
3.4 Descriptive analysis
For the study’s sample, males make up 52.9% of restaurant customers while females make up 47.1%. The category of age under 30 years represents 40.4% of restaurants’ customers, while the category between 30–39 years represents 39.4% of restaurant customers. The nationalities of respondents include 92.6% Egyptian, and 7.4% are foreigners. Customers regularly eat in the same restaurant for more than 4 times/month (49%), 4/month (40.7%), and 3/month (10.3%) (see Table 3).
4. Results
4.1 Measurement model assessment
Convergent and discriminant validity, along with construct reliability, were assessed in the measurement model. Each core variable’s Cronbach’s alpha coefficient was examined separately, with all individual items' factor loadings being statistically significant (p < 0.01), indicating reliability. Table 4 details the mean, standard deviation, factor loading, Cronbach’s alpha, composite reliability (CR), and average variance extracted (AVE) for each construct (Kline, 2010). Cronbach’s alpha values and CR scores for all constructs exceeded the recommended 0.7 thresholds, indicating strong internal consistency and reliability (Kannana and Tan, 2005). AVE values, above 0.5, demonstrated convergent validity. High factor loadings, exceeding the 0.5 threshold, were observed for every item in Table 4, confirming indicator reliability. Convergent validity for each construct was well-established, reinforcing confidence in utilizing these constructs for analysing relationships and achieving research objectives (Hair et al., 2017).
The discriminant validity of the measurement model was evaluated using three metrics: cross-loadings, the Fornell-Larcker criterion, and the heterotrait-monotrait ratio (HTMT). Cross-loadings in Table 5 indicate that items are more closely associated with their intended construct than with others, confirming their ability to measure the intended concepts. This underscores the distinctiveness of the constructs, affirming their capability to capture unique aspects of the investigated phenomenon (Hair et al., 2017).
Table 6, utilizing the Fornell-Larcker criteria, displays discriminant validity results where the square root of the average variance extracted (AVE) for each construct exceeds correlations with other constructs, meeting the criterion (Hair et al., 2017). This supports the distinctiveness of the constructs, showcasing greater variance within their items compared to items from other constructs (Awang, 2014). The same table also presents Heterotrait-Monotrait (HTMT) ratio results for discriminant validity, assessing the strength of correlations between different constructs (Henseler et al., 2015). As per the HTMT criterion, values below 0.90 are indicative of discriminant validity. Table 7 confirms discriminant validity among constructs, with most HTMT ratios below 0.90, emphasizing the distinctiveness of the constructs and stronger internal correlations compared to correlations with other constructs.
4.2 Assessment of structural model and hypothesis testing
Hair et al. (2017) recommend assessing the structural model by analysing beta (β), R2, and associated t-values through a bootstrapping process with a 5,000 resample. They also advise disclosing both predictive relevance (Q2) and effect sizes (f2). Sullivan and Feinn (2012) argue that although the p-value indicates the occurrence of an impact, it does not reveal its magnitude (see Figure 5).
Table 7 presents findings from the structural path analysis, featuring standardized beta coefficients, standard errors, t-values, p-values, hypothesis support decisions, effect sizes (f2), predictive relevance (Q2), and VIF values. The results confirm positive and significant relationships between Perceived Value (PV), Physical Appearance (PA), Standardization (ST), Ambient Condition (AC), Food Hygiene (FH), and Affective Satisfaction (AS), supporting hypotheses H1 to H5. Additionally, hypotheses H6 (AS and Customer Participation Behaviour) and H7 (AS and WOM) are supported. However, H8, suggesting a relationship between Customer Participation Behaviour (CPB) and WOM, is not supported. Effect sizes (f2) range from 0.007 to 0.559, indicating the percentage of variance explained, and predictive relevance (Q2) values range from 0.270 to 0.495, assessing model prediction quality. VIF values (1.000–1.600) suggest no multicollinearity issues. These results support the proposed theoretical framework, highlighting significant relationships among variables.
For that mediation effect, Kenny (2019) regarded that casual variables have a relationship with outcomes and mediator for the model and mentioned (total effect = direct effect + indirect effect, c = c'+ ab) as the mediator equation (Kenny, 2019).
Table 8 shows that the affective satisfaction (As) as a mediator between ambient condition (AC) and customer participation behaviour (CPB) is not supported with β = 0.063, t-value = 1.958, p-value = 0.051. As a result, the restaurant’s ambient condition and design do not entice customers to participate in voluntary activities in terms of improving the environment/conditions. Likewise, the affective satisfaction (As) as a mediator between ambient condition (AC) and WOM is not supported with β = 0.060, t-value = 1.951, p-value = 0.052. However, the indirect effects on CPB and WOM through AS were supported for the other independent variables (PV, PA, ST, and FH). For PV, PA, ST, and FH, the indirect effects through AS on CPB were significant, with standardized beta coefficients of 0.161, 0.129, 0.110, and 0.134, respectively. The p-values for these relationships were all below 0.001, indicating strong support for the indirect effects. Also, for PV, PA, ST, and FH, the indirect effects through AS on WOM were significant, with standardized beta coefficients of 0.153, 0.124, 0.105, and 0.128, respectively. The p-values for these relationships were all below 0.005, indicating good support for the indirect effects.
4.3 Importance-performance map analysis (IPMA)
In the post-hoc analysis of this study, an Importance-Performance Matrix Analysis (IPMA) was conducted within Partial Least Squares (PLS), with affective satisfaction as the outcome construct. Latent construct scores were rescaled to a 100 to 0 range for performance score calculation. This allowed the IPMA to assess total effects, representing the importance of precursor constructs in shaping affective satisfaction (Hair et al., 2017). Ringle et al. (2015) emphasize that IPMA enhances PLS analysis by considering both latent constructs' average values (performance aspect) and path coefficient analysis (importance aspect). The results, comprising performance (index values) and importance (total effects), are presented in Table 9.
Figure 6 displays a priority map presenting index values and overall effects scores. Physical appearance (PA) emerges as notably important in determining affective satisfaction, although its performance lags behind perceived value (PV). Following Hair et al. (2017), IPMA aims to identify predecessors with low performance but high importance for the target construct. In the Egyptian restaurant setting, elevating affective satisfaction hinges on enhancing standardization, food hygiene, and appearance—a triad of factors that intertwine tangible and intangible elements.
5. Discussion and conclusion
5.1 Conclusions
This study examines how various factors in the restaurant sector, including perceived value, physical appearance, standardization, ambient conditions, and food hygiene, impact customer satisfaction and behaviours. The study’s findings contribute to our knowledge of the elements that impact customers’ affective satisfaction and subsequent behaviours. The study’s findings confirm the assumptions and show that numerous elements have a substantial influence on customers’ affective satisfaction.
The study identified significant relationships supporting hypotheses related to the impact of various factors on affective satisfaction. Firstly, the association between perceived value and affective satisfaction (H1: PV → AS) was found to be significant. This implies that customers' perceptions of the value and service concerning the cost and food portion and choices significantly influence their affective satisfaction. Our study aligns with Elshaer and Huang (2023), Nitiwanakul (2014), and Paulose and Shakeel (2022), highlighting the key role of high perceived value in driving satisfaction and positive emotions, thereby advancing existing literature. Similarly, a significant connection was identified between physical appearance and affective satisfaction (H2: PA → AS). Our study supports the notion that the restaurant’s physical attributes influence customer satisfaction, in line with Yeh et al. (2020). Emphasizing the need for an appealing environment, it underscores the importance of factors such as proximity to amenities, efficient layout, and high-quality furnishings (Khalifa et al., 2023).
Furthermore, the study found a significant connection between standardization and affective satisfaction (H3: ST → AS). The findings suggest that customers' perceptions of consistent and standardized service delivery contribute positively to their affective satisfaction. This observation resonates with the assertions made by Dong and Sivakumar (2017), Wang et al. (2010), and Weyers and Louw (2017) who argued that consistent service meeting expectations promotes reliability and trust, thereby enhancing satisfaction. The relationship between ambient condition and affective satisfaction (H4: AC → AS) was also found to be significant. This implies that the physical attributes of the restaurant, including lighting, music, and overall atmosphere, play a role in shaping customers' affective satisfaction. This finding aligns with previous studies (e.g. Agbenyegah et al., 2022; Kim et al., 2021; Moon et al., 2021), emphasizing the importance of establishing a pleasant and comfortable environment to enhance customer satisfaction. Additionally, the connection between food hygiene and affective satisfaction (H5: FH → AS) was found to be significant. This suggests that customers' perceptions of cleanliness and hygiene standards significantly influence their affective satisfaction. Elshaer (2022) and Soonsan et al. (2023) emphasize the importance of maintaining high food safety and hygiene standards to meet customer expectations and enhance overall satisfaction. This highlights the crucial role of food handlers' safety knowledge, as suggested by Kwol et al. (2020), in ensuring the success of food hygiene practices.
Furthermore, the study investigated the relationship between affective satisfaction and customer participation behaviour (H6: AS → CPB). Our results uncover an interesting finding: satisfied customers not only enjoy their restaurant visit but actively contribute to its improvement. It’s like a harmonious symphony, with each satisfied customer adding their melody to the ambiance. This idea echoes previous studies such as Delpechitre et al. (2018), which emphasized how satisfaction drives customer engagement. However, our study introduces a new aspect by showing how engaged customers, play a role in enhancing the dining atmosphere. This dynamic illustrates that satisfaction isn’t just an outcome but a force that turns customers from passive observers into active participants (sharing his/her information and showing responsible behaviour, ultimately enriching the restaurant experience for everyone (Yi and Gong, 2013).
Moreover, the study explored the link between affective satisfaction and WOM communication (H7: AS → WOM). The study finds a significant positive relationship: highly satisfied customers are more likely to engage in positive word-of-mouth. This is supported by scholars like Khoo (2020), indicating that satisfied customers contribute to a business’s reputation and success. However, the study did not identify a significant connection between customer participation behaviour and WOM (H8: CPB → WOM). This suggests that while customer participation behaviour may contribute to their own experiences and interactions in the restaurant, it may not directly translate into WOM recommendations. As outlined by Ferguson et al. (2010), such behaviour may manifest more in repeat purchase behaviour and customer loyalty rather than in WOM recommendations. This finding underscores the complexity of the relationship between customer behaviour and WOM communication, suggesting that factors beyond participation alone may shape customers' inclination to recommend the restaurant.
Up to this point, these findings underscore the importance of factors such as ambient condition, food hygiene, standardization, perceived value, and physical appearance in shaping customers' affective satisfaction (Agbenyegah et al., 2022; Elshaer, 2022; Stribbell and Duangekanong, 2022; Yeh et al., 2020). Moreover, these results highlight the mediating role of affective satisfaction in influencing customer participation behaviour and WOM (Chao et al., 2021; Khoo, 2020; Hwang and Lee, 2019).
Beyond exploring direct relationships between independent and dependent variables, the study delved into indirect effects mediated by affective satisfaction. The results of the bootstrapping analysis yielded intriguing findings regarding the indirect relationships between independent variables (perceived value, physical appearance, standardization, ambient condition, and food hygiene) and dependent variables (customer participation behaviour and WOM communication) through affective satisfaction.
In examining the indirect impact of ambient conditions, the results indicate no statistically significant connection between ambient conditions and customer participation behaviour (AC → AS → CPB). This implies that the influence of ambient conditions on customer participation behaviour is not entirely mediated by affective satisfaction. This insight resonates with existing literature (Luo, 2021), highlighting the multifaceted nature of customer participation in service environments.
On the contrary, significant indirect effects of affective satisfaction were observed in the relationships between food hygiene and customer participation behaviour (FH → AS → CPB), physical appearance and customer participation behaviour (PA → AS → CPB), standardization and customer participation behaviour (ST → AS → CPB), ambient condition and WOM communication (AC → AS → WOM), food hygiene and WOM communication (FH → AS → WOM), physical appearance and WOM communication (PA → AS → WOM), and perceived value and WOM communication (PV → AS → WOM). These findings suggest that the positive impact of these independent variables on customer participation behaviour and WOM communication is partially mediated by affective satisfaction (Liu and Jang, 2009). These significant indirect effects underscore the crucial role of affective satisfaction in transmitting the influence of certain factors on customer behaviours and communication. Positive affective experiences lead customers to engage in participatory behaviours, such as interacting with restaurant staff, providing feedback, and contributing to the overall restaurant experience. Similarly, satisfied customers are more likely to engage in positive WOM, sharing their positive experiences and recommendations.
5.2 Theoretical implications
This study contributes theoretically to the field of food service management and customer behaviour in several ways. Firstly, it enhances the understanding of the Expectancy-Disconfirmation Theory (EDT) by exploring its applicability within the restaurant industry context. The findings validate the relationships among perceived value, physical appearance, standardization, ambient condition, perceived food hygiene, affective satisfaction, customer participation behaviour, and WOM, aligning with the fundamental principles of ED theory. This reaffirms the concept that customers formulate expectations regarding service attributes and their satisfaction is influenced by the extent to which these expectations are met or exceeded. Secondly, the study advances understanding of affective satisfaction’s mediating role between key variables and customer behaviours (participation behaviour and WOM communication), with a unique focus on the Egyptian restaurant industry, contributing to theoretical advancements in this area.
5.3 Practical implications
The study’s practical implications provide valuable insights for restaurant managers in enhancing customer experiences and achieving positive outcomes by understanding the factors influencing affective satisfaction and subsequent behaviours. Firstly, by acknowledging the indirect effects mediated by affective satisfaction, restaurant managers can understand the underlying processes driving guest behaviour’s and communication, allowing them to promote positive customer behaviour’s and stimulate positive word-of-mouth communication. Secondly, the study highlights the significance of customer participation behaviour in driving positive word-of-mouth (WOM). To leverage this, managers can foster customer engagement by offering opportunities for contribution and interaction during service delivery. Incorporating interactive elements like open kitchens, DIY options, or feedback mechanisms can encourage customer involvement. Such active participation not only boosts satisfaction but also cultivates their inclination to share positive experiences, amplifying WOM communication and yielding favourable business outcomes.
5.4 Limitations and future research
Despite valuable insights, it’s important to acknowledge limitations. Firstly, the study’s context specificity warrants caution in generalizing findings. Data collected from a specific region may not reflect broader cultural and contextual variations. Future research should replicate the study in diverse contexts to assess the findings' robustness and generalizability. Secondly, the study’s reliance on self-reported measures introduces the potential for common method bias, despite efforts to mitigate it. Future research could employ a multi-method approach, integrating objective measures or observational data, to enhance validity. Thirdly, the study’s focus on a specific set of variables may limit the scope of findings. Future research should explore additional factors like service quality, trust, or customer loyalty to provide a more comprehensive understanding of customer behaviour in the restaurant industry.
Given the identified limitations, several avenues for further research emerge. Firstly, longitudinal studies could explore the temporal dynamics of the relationships investigated in this study, offering insights into stability and changes over time. Secondly, qualitative methods like focus groups or interviews could delve deeper into underlying mechanisms and processes. Lastly, future research might investigate organizational factors' role, such as service provider training or organizational culture, in shaping customer experiences and behaviour’s, contributing to a comprehensive understanding of satisfaction, participation, and WOM communication.
Figures
Figure 1
Relations between restaurant domain and customers attitudes and behaviours
Figure 2
Affective customer satisfaction examined in the hospitality, leisure, and tourism industry
Figure 3
The research’s conceptual framework
Figure 4
Geographical distribution of selected restaurants
Figure 5
The research’s conceptual framework
Figure 6
IPMA (Priority Map) for affective satisfaction
Dimensions of the affective satisfaction
| Definitions | Dimension |
|---|---|
| Neat and simple products or services process | Simplicity |
| Products and services are elaborate, delicate, skilful and finely made | Delicacy |
| Luxurious or looking superior in quality and exclusive | Luxuriousness |
| Arousing interest, pleasing and attractive with extra features and quality | Attractiveness |
| Matching of inventing colour with the combination | Colour |
| Making user overall satisfaction with effective service and providing quality product | Overall satisfaction |
Source(s): Cho et al. (2011)
Previous literature review and theoretical identification constructs
| Constructs | Authors/previous literature |
|---|---|
| Perceived value | Hyun et al. (2011) |
| Physical appearance | Tuzunkan and Albayrak (2016) |
| Standardization | Wang et al. (2010) |
| Ambient condition | Ryu and Jang (2008) |
| Food hygiene | Fatimah et al. (2011) |
| Customer affective satisfaction | Ladhari et al. (2017) |
| Customer participation behaviour | Delpechitre et al. (2018) and Yi and Gong (2013) |
| Word of mouth | Jalilvand et al. (2012) |
Source(s): Authors own work
Respondents' profile
| Demography of respondents | Variables | (n = 312)% |
|---|---|---|
| Gender | Male | 52.9 |
| Female | 47.1 | |
| Age | Under 30 years | 40.4 |
| 30–39 years | 39.4 | |
| 40–49 years | 17.9 | |
| 50–59 years | 2.2 | |
| 60 and above | 0 | |
| Nationality | Egyptian | 92.6 |
| Foreigners | 7.4 | |
| Regulatory of eating out in restaurant | First time | 0 |
| Two per month | 0 | |
| Three per month | 10.3 | |
| Four per month | 40.7 | |
| More than four times | 49 |
Source(s): Authors own work
Mean, standard deviation, loading, Cronbach’s Alpha, CR and AVE
| Constructs | Item | Loading (>0.5) | M | SD | α (>0.7) | CR (>0.7) | AVE (>0.5) |
|---|---|---|---|---|---|---|---|
| Ambient condition (AC) | AC1 | 0.816 | 4.182 | 0.3069 | 0.901 | 0.921 | 0.627 |
| AC2 | 0.730 | ||||||
| AC3 | 0.678 | ||||||
| AC4 | 0.749 | ||||||
| AC5 | 0.776 | ||||||
| AC6 | 0.811 | ||||||
| AC7 | 0.956 | ||||||
| Food hygiene (FH) | FH1 | 0.833 | 4.197 | 0.0383 | 0.889 | 0.912 | 0.677 |
| FH2 | 0.744 | ||||||
| FH3 | 0.753 | ||||||
| FH4 | 0.778 | ||||||
| FH5 | 0.982 | ||||||
| Standardization (ST) | ST1 | 0.611 | 4.234 | 0.0358 | 0.827 | 0.865 | 0.566 |
| ST2 | 0.875 | ||||||
| ST3 | 0.853 | ||||||
| ST4 | 0.699 | ||||||
| ST5 | 0.690 | ||||||
| Perceived value (PV) | PV1 | 0.921 | 4.423 | 0.0393 | 0.803 | 0.876 | 0.705 |
| PV2 | 0.867 | ||||||
| PV3 | 0.716 | ||||||
| Physical appearance (PA) | PA1 | 0.850 | 4.292 | 0.0350 | 0.795 | 0.863 | 0.612 |
| PA2 | 0.802 | ||||||
| PA3 | 0.705 | ||||||
| PA4 | 0.766 | ||||||
| Affective satisfaction (AS) | AS1 | 0.696 | 4.338 | 0.0328 | 0.749 | 0.836 | 0.562 |
| AS2 | 0.835 | ||||||
| AS3 | 0.752 | ||||||
| AS4 | 0.706 | ||||||
| Customer participation behaviour (CPB) | CPB1 | 0.921 | 4.234 | 0.0363 | 0.837 | 0.879 | 0.557 |
| CPB2 | 0.586 | ||||||
| CPB3 | 0.634 | ||||||
| CPB4 | 0.930 | ||||||
| CPB5 | 0.613 | ||||||
| CPB6 | 0.712 | ||||||
| Word-of-mouth (WOM) | WOM1 | 0.641 | 4.289 | 0.0288 | 0.738 | 0.826 | 0.616 |
| WO M2 | 0.800 | ||||||
| WOM3 | 0.893 |
Note(s): M = Mean; SD=Standard Deviation, α = Cronbach’s alpha; CR = Composite Reliability, AVE = Average Variance Extracted
• A five-point scale, ranging from 1 to 5 (strongly disagree to strongly agree, respectively), is employed for measuring
• All the factor loadings of the individual items are statistically significant (p < 0.01)
Source(s): Authors own work
Discriminant validity results using cross loading
| AC | AS | FH | GPB | PA | PV | ST | WOM | |
|---|---|---|---|---|---|---|---|---|
| AC1 | 0.816 | 0.406 | 0.318 | 0.470 | 0.145 | 0.490 | 0.389 | 0.311 |
| AC2 | 0.730 | 0.159 | 0.092 | 0.148 | 0.199 | 0.194 | 0.137 | 0.122 |
| AC3 | 0.678 | 0.182 | 0.324 | 0.147 | 0.295 | 0.141 | 0.117 | 0.123 |
| AC4 | 0.749 | 0.305 | 0.251 | 0.256 | 0.386 | 0.123 | 0.113 | 0.213 |
| AC5 | 0.776 | 0.296 | 0.229 | 0.209 | 0.365 | 0.168 | 0.125 | 0.214 |
| AC6 | 0.811 | 0.397 | 0.311 | 0.513 | 0.118 | 0.505 | 0.435 | 0.322 |
| AC7 | 0.956 | 0.422 | 0.374 | 0.421 | 0.325 | 0.380 | 0.331 | 0.303 |
| AS1 | 0.300 | 0.696 | 0.395 | 0.305 | 0.383 | 0.160 | 0.202 | 0.421 |
| AS2 | 0.415 | 0.835 | 0.421 | 0.756 | 0.106 | 0.663 | 0.553 | 0.528 |
| AS3 | 0.300 | 0.752 | 0.268 | 0.285 | 0.286 | 0.224 | 0.190 | 0.440 |
| AS4 | 0.186 | 0.706 | 0.215 | 0.238 | 0.219 | 0.148 | 0.248 | 0.459 |
| FH1 | 0.374 | 0.481 | 0.833 | 0.561 | 0.083 | 0.506 | 0.426 | 0.331 |
| FH2 | 0.192 | 0.123 | 0.744 | 0.175 | 0.145 | 0.130 | 0.102 | 0.116 |
| FH3 | 0.273 | 0.170 | 0.753 | 0.109 | 0.184 | 0.057 | 0.092 | 0.130 |
| FH4 | 0.224 | 0.419 | 0.778 | 0.278 | 0.259 | 0.123 | 0.204 | 0.328 |
| FH5 | 0.339 | 0.376 | 0.982 | 0.362 | 0.206 | 0.269 | 0.266 | 0.284 |
| CPB1 | 0.389 | 0.564 | 0.400 | 0.921 | 0.069 | 0.648 | 0.544 | 0.401 |
| CPB2 | 0.207 | 0.223 | 0.227 | 0.586 | 0.181 | 0.237 | 0.264 | 0.151 |
| CPB3 | 0.183 | 0.331 | 0.249 | 0.634 | 0.087 | 0.259 | 0.307 | 0.262 |
| CPB4 | 0.421 | 0.614 | 0.410 | 0.930 | 0.073 | 0.678 | 0.541 | 0.439 |
| CPB5 | 0.268 | 0.356 | 0.282 | 0.613 | 0.248 | 0.217 | 0.124 | 0.161 |
| CPB6 | 0.393 | 0.440 | 0.295 | 0.712 | −0.035 | 0.993 | 0.506 | 0.343 |
| PA1 | 0.284 | 0.297 | 0.245 | 0.109 | 0.850 | −0.082 | 0.018 | 0.156 |
| PA2 | 0.274 | 0.257 | 0.136 | 0.051 | 0.802 | −0.017 | 0.033 | 0.148 |
| PA3 | 0.152 | 0.136 | 0.103 | 0.115 | 0.705 | 0.013 | 0.059 | 0.074 |
| PA4 | 0.240 | 0.192 | 0.129 | 0.084 | 0.766 | 0.013 | 0.127 | 0.159 |
| PV1 | 0.387 | 0.514 | 0.349 | 0.747 | −0.016 | 0.921 | 0.535 | 0.363 |
| PV2 | 0.335 | 0.374 | 0.271 | 0.599 | −0.058 | 0.867 | 0.461 | 0.325 |
| PV3 | 0.263 | 0.193 | 0.098 | 0.432 | −0.011 | 0.716 | 0.258 | 0.159 |
| ST1 | 0.087 | 0.105 | 0.074 | 0.189 | −0.018 | 0.217 | 0.611 | 0.425 |
| ST2 | 0.348 | 0.500 | 0.360 | 0.624 | 0.071 | 0.586 | 0.875 | 0.568 |
| ST3 | 0.332 | 0.386 | 0.281 | 0.484 | 0.027 | 0.504 | 0.853 | 0.547 |
| ST4 | 0.138 | 0.232 | 0.107 | 0.226 | 0.068 | 0.210 | 0.699 | 0.523 |
| ST5 | 0.169 | 0.199 | 0.196 | 0.249 | 0.073 | 0.209 | 0.690 | 0.516 |
| WOM1 | 0.103 | 0.188 | 0.167 | 0.145 | 0.006 | 0.133 | 0.624 | 0.641 |
| WOM2 | 0.239 | 0.360 | 0.190 | 0.403 | 0.014 | 0.404 | 0.745 | 0.800 |
| WOM3 | 0.316 | 0.689 | 0.355 | 0.377 | 0.262 | 0.286 | 0.435 | 0.893 |
Note(s): Key: AC: Ambient Condition, AS: Affective Satisfaction, FH: Food Hygiene, GPB: Guest Participation Behaviour; PA: Physical Appearance; PV: Perceived Value; ST: Standardization; WOW: Word of Mouth
Source(s): Authors own work
Discriminant validity
| Fornell-Larcker | HTMT | |||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| AC | AS | FH | GPB | PA | PV | ST | WOM | AC | AS | FH | GPB | PA | PV | ST | WOM | |
| AC | 0.792 | |||||||||||||||
| AS | 0.421 | 0.749 | 0.451 | |||||||||||||
| FH | 0.358 | 0.450 | 0.823 | 0.366 | 0.445 | |||||||||||
| CPB | 0.435 | 0.599 | 0.428 | 0.746 | 0.433 | 0.633 | 0.407 | |||||||||
| PA | 0.316 | 0.299 | 0.209 | 0.110 | 0.783 | 0.374 | 0.398 | 0.236 | 0.199 | |||||||
| PV | 0.401 | 0.471 | 0.320 | 0.718 | 0.135 | 0.839 | 0.413 | 0.458 | 0.278 | 0.786 | 0.566 | |||||
| ST | 0.333 | 0.446 | 0.318 | 0.549 | 0.066 | 0.531 | 0.753 | 0.292 | 0.431 | 0.259 | 0.533 | 0.101 | 0.513 | |||
| WOM | 0.315 | 0.620 | 0.334 | 0.423 | 0.178 | 0.362 | 0.676 | 0.785 | 0.307 | 0.670 | 0.310 | 0.451 | 0.181 | 0.405 | 0.765 | |
Note(s): Diagonals represent the square root of the average variance extracted while the other entries represent the correlations
Key: AC: Ambient Condition, AS:Affective Satisfaction, FH: Food Hygiene, GPB: Guest Participation Behaviour; PA: Physical Appearance; PV: Perceived Value; ST: Standardization; WOW: Word of Mouth
Source(s): Authors own work
Results of the structural path analysis
| H | Relationship | Std beta | Std error | t-value | p-value | Decision | f2 | Q2 | VIF |
|---|---|---|---|---|---|---|---|---|---|
| H1 | PV → AS | 0.268 | 0.273 | 4.928 | 0.000 | Supported | 0.077 | 0.406 | 1.600 |
| H2 | PA → AS | 0.216 | 0.219 | 4.943 | 0.000 | Supported | 0.068 | 0.358 | 1.178 |
| H3 | ST → AS | 0.183 | 0.188 | 3.385 | 0.001 | Supported | 0.039 | 0.368 | 1.461 |
| H4 | AC → AS | 0.105 | 0.101 | 1.998 | 0.046 | Supported | 0.023 | 0.495 | 1.440 |
| H5 | FH → AS | 0.224 | 0.222 | 4.736 | 0.000 | Supported | 0.068 | 0.501 | 1.253 |
| H6 | AS → CPB | 0.599 | 0.606 | 15.365 | 0.000 | Supported | 0.559 | 0.288 | 1.000 |
| H7 | AS → WOM | 0.572 | 0.575 | 11.363 | 0.000 | Supported | 0.343 | 0.400 | 1.559 |
| H8 | CPB → WOM | 0.080 | 0.079 | 1.335 | 0.182 | Not-Supported | 0.007 | 0.270 | 1.559 |
Note(s): Key: AC: Ambient Condition, AS:Affective Satisfaction, FH: Food Hygiene, CPB: Customer Participation Behaviour; PA: Physical Appearance; PV: Perceived Value; ST: Standardization; WOW: Word of Mouth
Source(s): Authors own work
Bootstrapping the indirect effect of organizational excellence
| Relationship | Std beta | Std error | t-value | p-value | Decision |
|---|---|---|---|---|---|
| PV → AS → CPB | 0.161 | 0.166 | 4.266 | 0.000 | Supported |
| PA → AS → CPB | 0.129 | 0.132 | 4.723 | 0.000 | Supported |
| ST → AS → CPB | 0.110 | 0.114 | 3.304 | 0.001 | Supported |
| AC → AS → CPB | 0.063 | 0.061 | 1.958 | 0.051 | Not- Supported |
| FH → AS → CPB | 0.134 | 0.134 | 4.559 | 0.000 | Supported |
| PV → AS → WOM | 0.153 | 0.156 | 4.868 | 0.000 | Supported |
| PA → AS → WOM | 0.124 | 0.125 | 4.773 | 0.000 | Supported |
| ST → AS → WOM | 0.105 | 0.109 | 2.974 | 0.003 | Supported |
| AC → AS → WOM | 0.060 | 0.058 | 1.951 | 0.052 | Not-Supported |
| FH → AS → WOM | 0.128 | 0.127 | 4.360 | 0.000 | Supported |
Note(s): Key: AC: Ambient Condition, AS: Affective Satisfaction, FH: Food Hygiene, GPB: Guest Participation Behaviour; PA: Physical Appearance; PV: Perceived Value; ST: Standardization; WOW: Word of Mouth
Source(s): Authors own work
IPMA for affective satisfaction
| Latent constructs | Total effect of the construct affective satisfaction (Importance) | Index values (Performance) |
|---|---|---|
| Ambient condition (AC) | 0.106 | 63.592 |
| Food hygiene (FH) | 0.205 | 63.510 |
| Physical appearance (PA) | 0.231 | 66.613 |
| Perceived value (PV) | 0.218 | 72.162 |
| Standardization (ST) | 0.171 | 64.341 |
Note(s): Key: AC: Ambient Condition, AS: Affective Satisfaction, FH: Food Hygiene, GPB: Guest Participation Behaviour; PA: Physical Appearance; PV: Perceived Value; ST: Standardization; WOW: Word of Mouth
Source(s): Authors own work
References
Abdelaal, E. and Elshaer, A. (2020), “Investigating the effect of VSM on the performance of quick-service restaurants”, Journal of Association of Arab Universities for Tourism and Hospitality, Vol. 19 No. 3, pp. 228-250, doi: 10.21608/jaauth.2021.52594.1097.
Agbenyegah, A.T., Zogli, L.-K.J., Dlamini, B., Mofokeng, N.E.M. and Kabange, M.M. (2022), “Ambient situation and customer satisfaction in restaurant businesses: a management perspective”, African Journal of Hospitality, Tourism and Leisure, Vol. 11 No. 2, pp. 394-408, doi: 10.46222/ajhtl.19770720.232.
Awang, Z. (2014), Structural Equation Modeling Using AMOS, Penerbit Universiti Teknologi MARA, Shah Alam.
Bell, C.N., Sacks, T.K., Tobin, C.S.T. and Thorpe, R.J. Jr (2020), “Racial non-equivalence of socioeconomic status and self-rated health among African Americans and Whites”, SSM-Population Health, Vol. 10, pp. 1-9, doi: 10.1016/j.ssmph.2020.100561.
Buccheri, C., Mammina, C., Giammanco, S., Giammanco, M., Guardia, M.L. and Casuccio, A. (2010), “Knowledge, attitudes and self-reported practices of food service staff in nursing homes and long-term care facilities”, Food Control, Vol. 21 No. 10, pp. 1367-1373, doi: 10.1016/j.foodcont.2010.04.010.
Cai, R. and Chi, C.G.Q. (2021), “Pictures vs reality: roles of disconfirmation magnitude, disconfirmation sensitivity, and branding”, International Journal of Hospitality Management, Vol. 98, pp. 1-10, doi: 10.1016/j.ijhm.2021.103040.
Chamber of Tourism Establishments (2024), available at: http://www.egyptianhotels.org/ (accessed 20 March 2024).
Chao, R.F., Fu, Y. and Liang, C.H. (2021), “Influence of service scape stimuli on word-of-mouth intentions: an integrated model to indigenous restaurants”, International Journal of Hospitality Management, Vol. 96, pp. 1-11, doi: 10.1016/j.ijhm.2021.102978.
Chen, S.C., Raab, C. and Tanford, S. (2014), “Construction and validation of the customer participation scale”, Journal of Hospitality Tourism Research, Vol. 46 No. 1, pp. 65-75, doi: 10.1016/j.ijhm.2015.01.012.
Cho, Y., Park, J., Han, S.H. and Kang, S. (2011), “Development of a web-based survey system for evaluating affective satisfaction”, International Journal of Industrial Ergonomics, Vol. 41 No. 3, pp. 247-254, doi: 10.1016/j.ergon.2011.01.009.
Choi, H.C., Huang, S., Choi, H. and Chang, H. (2020), “The effect of flight attendants' physical attractiveness on satisfaction, positive emotion, perceived value, and behavioral intention”, Journal of Hospitality and Tourism Management, Vol. 44 No. 2, pp. 19-29, doi: 10.1016/j.jhtm.2020.05.001.
Delpechitre, D., Connelly, L.K. and Chaker, N.N. (2018), “Customer value co-creation behavior: a dyadic exploration of the influence of salesperson emotional intelligence on customer participation and citizenship behaviour”, Journal of Business Research, Vol. 92 No. 3, pp. 9-24, doi: 10.1016/j.jbusres.2018.05.007.
Dong, B. and Sivakumar, K. (2017), “Customer participation in services: domain, scope, and boundaries”, Journal of the Academy of Marketing Science, Vol. 45 No. 6, pp. 944-965, doi: 10.1007/s11747-017-0524-y.
Ehimen, S., Uduji, J.I. and Ugwuanyi, C.C. (2021), “Hotel guests' experience, satisfaction and revisit intentions: an emerging market perspective”, African Journal of Hospitality Tourism and Leisure, Vol. 10 No. 2, pp. 406-424, doi: 10.46222/ajhtl.19770720-108.
El-Adly, M.I. (2019), “Modelling the relationship between hotel perceived value, customer satisfaction, and customer loyalty”, Journal of Retailing and Consumer Services, Vol. 50 No. July 2018, pp. 322-332, doi: 10.1016/j.jretconser.2018.07.007.
Elinder, E. (1961), “How international can advertising be?”, International Advertiser, Vol. 29 No. 2, pp. 12-16, doi: 10.2307/1249253.
Elshaer, A.M. (2020), “Restaurants' response to COVID-19 pandemic: the realm of Egyptian independent restaurants”, Journal of Quality Assurance in Hospitality and Tourism, Vol. 23 No. 3, pp. 716-747, doi: 10.1080/1528008X.2021.1911732.
Elshaer, A.M. (2022), “Analysis of restaurants’ operations using time-driven activity-based costing (TDABC): case study”, Journal of Quality Assurance in Hospitality and Tourism, Vol. 23 No. 1, pp. 32-55.
Elshaer, A. and Huang, R. (2023), “Perceived value within an international hospitality learning environment: antecedents and outcomes”, Journal of Hospitality, Leisure, Sport and Tourism Education, Vol. 32 C, pp. 1-12, doi: 10.1016/j.jhlste.2023.100429.
Elshaer, A. and Marzouk, A. (2019), Labor in Tourism and Hospitality Industry: Skills, Ethics, Issues, and Rights, Apple Academic Press, New York.
Elshaer, A.M. and Marzouk, A.M. (2022), “Memorable tourist experiences: the role of smart tourism technologies and hotel innovations”, Tourism Recreation Research, Vol. 49 No. 3, pp. 1-13, doi: 10.1080/02508281.2022.2027203.
Elshaer, A.M., Marzouk, A.M. and Khalifa, G.S. (2022), “Antecedents of employees' perception and attitude to risks: the experience of Egyptian tourism and hospitality industry”, Journal of Quality Assurance in Hospitality and Tourism, Vol. 24 No. 3, pp. 1-29, doi: 10.1080/1528008X.2022.2050877.
Fatimah, U.Z.A.U., Boo, H.C., Sambasivan, M. and Salleh, R. (2011), “Foodservice hygiene factors—the consumer perspective”, International Journal of Hospitality Management, Vol. 30 No. 1, pp. 38-45, doi: 10.1016/j.ijhm.2010.04.001.
Fauza, G., Nurasyiah, A., Nursiwi, A. and Ariviani, S. (2022), “Investigating the customer satisfaction on food quality, service and environment facility of restaurant X using food hygiene perspectives”, Proceedings of the First Australian International Conference on Industrial Engineering and Operations Management, Sydney, December 20-21.
Ferguson, R.J., Paulin, M. and Bergeron, J. (2010), “Customer sociability and the total service experience: antecedents of positive word‐of‐mouth intentions”, Journal of Service Management, Vol. 21 No. 1, pp. 25-44, doi: 10.1108/09564231011025100.
Güvenç, N.Y., Köz, E.N. and Evren, S. (2023), “Analysis of customer reviews on Korean restaurant experience: the case of Zomato Istanbul”, Journal of Tourismology, Vol. 9 No. 1, pp. 41-49, doi: 10.26650/jot.2023.9.1.1153011.
Haddad, A.J., Mondal, A. and Bhat, C.R. (2023), “Eat-in or eat-out? A joint model to analyze the new landscape of dinner meal preferences”, Transportation Research Part C: Emerging Technologies, Vol. 147, pp. 1-25, doi: 10.1016/j.trc.2023.104016.
Hair, J.F., Hult, G.T.M., Ringle, C. and Sarstedt, M. (2017), A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM), 2nd ed., SAGE, Thousand Oaks.
Hartono, M. and Raharjo, H. (2015), “Exploring the mediating role of affective and cognitive satisfaction on the effect of service quality on loyalty”, Total Quality Management and Business Excellence, Vol. 26 No. 9, pp. 971-985, doi: 10.1080/14783363.2015.1068595.
Henseler, J., Ringle, C.M. and Sarstedt, M. (2015), “A new criterion for assessing discriminant validity in variance-based structural equation modeling”, Journal of the Academy of Marketing Science, Vol. 34 No. 1, pp. 115-135, doi: 10.1007/s11747-014-0403-8.
Hoelter, J.W. (1983), “The analysis of covariance structures: goodness-of-fit indices”, Sociological Methods and Research, Vol. 11 No. 3, pp. 325-344, doi: 10.1177/0049124183011003003.
Hossain, M.S., Sambasivan, M., Abuelhassan, A.E. and Khalifa, G.S.A. (2023), “Factors influencing customer citizenship behaviour in the hospitality industry”, Annals of Leisure Research, Vol. 26 No. 1, pp. 65-88, doi: 10.1080/11745398.2020.1850302.
Hwang, K. and Lee, B. (2019), “Pride, mindfulness, public self-awareness, affective satisfaction, and customer citizenship behaviour among green restaurant customers”, International Journal of Hospitality Management, Vol. 83, pp. 169-179, doi: 10.1016/j.ijhm.2019.05.009.
Hyun, S.S., Kim, W. and Lee, M.J. (2011), “The impact of advertising on patrons' emotional responses, perceived value, and behavioral intentions in the chain restaurant industry: the moderating role of advertising-induced arousal”, International Journal of Hospitality Management, Vol. 30 No. 3, pp. 689-700, doi: 10.1016/j.ijhm.2010.10.008.
Ida, E. (2017), “The role of customers' involvement in value co-creation behaviour is value cocreation the source of competitive advantage?”, Journal of Competitiveness, Vol. 9 No. 3, pp. 51-66, doi: 10.7441/joc.2017.03.04.
Jalilvand, M.R., Samiei, N., Dini, B. and Yaghoubi, P. (2012), “Examining the structural relationships of electronic word of mouth, destination image, tourist attitude toward destination and travel intention: an integrated approach”, Journal of Destination Marketing Management, Vol. 1 Nos 1-2, pp. 134-143, doi: 10.1016/j.jdmm.2012.10.001.
Kannana, V.R. and Tan, K.C. (2005), “Just in time, total quality management, and supply chain management: understanding their linkages and impact on business performance”, Omega: The International Journal of Management Science, Vol. 33 No. 2, pp. 153-162, doi: 10.1016/j.omega.2004.03.012.
Kenny, D.A. (2019), “Enhancing validity in psychological research”, American Psychologist, Vol. 74 No. 9, pp. 1018-1028, doi: 10.1037/amp0000531.
Khalifa, G.S.A., Abuelhassan, A.E., Khreis, S.H.A., Soliman, M. and Hossain, M.S. (2023), “Innovation mechanism in hospitality industry: a mediated-moderated model”, Journal of Tourism and Services, Vol. 26 No. 14, pp. 173-196, doi: 10.29036/jots.v14i26.492.
Khoo, K.L. (2020), “A study of service quality, corporate image, customer satisfaction, revisit intention and word-of-mouth: evidence from the KTV industry”, PSU Research Review, Vol. 6 No. 2, pp. 105-119, doi: 10.1108/PRR-08-2019-0029.
Kim, M. and Lee, G. (2022), “The effect of servicescape on place attachment and experience evaluation: the importance of exoticism and authenticity in an ethnic restaurant”, International Journal of Contemporary Hospitality Management, Vol. 34 No. 7, pp. 2664-2683, doi: 10.1108/ijchm-07-2021-0929.
Kim, M.J. and Park, C.J. (2019), “Does customer delight matter in the customer satisfaction-loyalty linkage?”, The Journal of Asian Finance, Economics and Business, Vol. 6 No. 3, pp. 235-245, doi: 10.13106/jafeb.2019.vol6.no3.235.
Kim, J.J., Han, H. and Ariza-Montes, A. (2021), “The impact of hotel attributes, well-being perception, and attitudes on brand loyalty: examining the moderating role of COVID-19 pandemic”, Journal of Retailing and Consumer Services, Vol. 62, pp. 1-10, doi: 10.1016/j.jretconser.2021.102634.
Kline, R.B. (2010), Principles and Practice of Structural Equation Modeling, 3rd ed., The Guilford Press, New York.
Kubde, S.R., Pattankar, J. and Kokiwar, P.R. (2016), “Knowledge and food hygiene practices among food handlers in food establishments”, International Journal of Community Medicine and Public Health, Vol. 3 No. 1, pp. 251-256, doi: 10.18203/2394-6040.ijcmph20151572.
Kwol, V.S., Eluwole, K.K., Avci, T. and Lasisi, T.T. (2020), “Another look into the Knowledge Attitude Practice (KAP) model for food control: an investigation of the mediating role of food handlers' attitudes”, Food Control, Vol. 110, pp. 1-8, doi: 10.1016/j.foodcont.2019.107025.
Ladhari, R., Souiden, N. and Dufour, B. (2017), “The role of emotions in utilitarian service settings: the effects of emotional satisfaction on product perception and behavioral intentions”, Journal of Retailing and Consumer Services, Vol. 34, pp. 10-18, doi: 10.1016/j.jretconser.2016.09.005.
Lim, W.M., Aggarwal, A. and Dandotiya, R. (2022), “Marketing luxury services beyond affluence in the new normal: insights from fine dining during the coronavirus pandemic”, Journal of Retailing and Consumer Services, Vol. 66 No. 1, 102936, doi: 10.1016/j.jretconser.2022.102936.
Liu, Y. and Jang, S.S. (2009), “Perceptions of Chinese restaurants in the US: what affects customer satisfaction and behavioral intentions?”, International Journal of Hospitality Management, Vol. 28 No. 3, pp. 338-348, doi: 10.1016/j.ijhm.2008.10.008.
Luo, X. (2021), “The effect of online community interaction on customer participation in value co-creation based on stimulus-organism-response model”, available at: https://repository.nida.ac.th/handle/662723737/6197
Malik, S.A., Jaswal, L.H., Malik, S.A. and Awan, T.M. (2013), “Measuring service quality perceptions of the customers of restaurants in Pakistan”, International Journal of Quality Research, Vol. 7 No. 2, pp. 187-200.
Moon, H., Lho, H. and Han, H. (2021), “Self-check-in Kisok quality and airline non-contact service maximization: how to win air traveler satisfaction and loyalty in the post-pandemic world”, Journal of Travel and Tourism Marketing, Vol. 38 No. 4, pp. 383-398, doi: 10.1080/10548408.2021.1921096.
Ngah, H.C., Rosli, N.F.M., Lotpi, M.H.M., Samsudin, A. and Anuar, J. (2022), “A review on the elements of restaurant physical environment towards customer satisfaction”, International Journal of Academic Research in Business and Social Sciences, Vol. 12 No. 11, pp. 818-828, doi: 10.6007/IJARBSS/v12-i11/15621.
Ngoma, M., Ntale, P.D. and Wright, L.T. (2019), “Word of mouth communication: a mediator of relationship marketing and customer loyalty”, Cogent Business and Management, Vol. 6 No. 1, doi: 10.1080/23311975.2019.1580123.
Nitiwanakul, W. (2014), “A comparative study of customer perceived value as a driver for fine dining restaurant selection: a case of Thai consumers and expatriates”, AU Journal of Management, Vol. 2 No. 1, pp. 1-13.
Nusairat, M.N., Hammouri, Q., Al-Ghadir, H., Ahmad, A.M. and Eid, M.A. (2020), “The effect of design of restaurant on customer behavioral intentions”, Management Science Letters, Vol. 10, pp. 1-11, doi: 10.5267/j.msl.2020.2.021.
Okumus, B. and Cetin, G. (2018), “Marketing Istanbul as a culinary destination”, Journal of Destination Marketing and Management, Vol. 9, pp. 340-346, doi: 10.1016/j.jdmm.2018.03.008.
Oliver, R.L. (1980), “A cognitive model of the antecedents and consequences of satisfaction decisions”, Journal of Marketing Research, Vol. 17 No. 4, pp. 460-469, doi: 10.1177/002224378001700405.
Oliver, R.L. (1999), “Whence consumer loyalty?”, The Journal of Marketing, Vol. 63 No. 4_suppl1, pp. 33-44, doi: 10.1177/00222429990634s105.
Palací, F., Salcedo, A. and Topa, G. (2019), “Cognitive and affective antecedents of consumers' satisfaction: a systematic review of two research approaches”, Sustainability, Vol. 11 No. 431, pp. 1-35, doi: 10.3390/su11020431.
Pantoja-Diaz, O., Tulcán, A.L. and Ramos-Alvarez, A. (2023), “The impact of affective behavior on Co-creation and customer satisfaction”, International Conference in Information Technology and Education, Springer Nature Singapore, Singapore, pp. 235-244.
Park, E., Jang, Y., Kim, J., Jeong, N.J., Bae, K. and del Pobil, A.P. (2019), “Determinants of customer satisfaction with airline services: an analysis of customer feedback big data”, Journal of Retailing and Consumer Services, Vol. 51 No. 1, pp. 186-190, doi: 10.1016/j.jretconser.2019.06.009.
Paulose, D. and Shakeel, A. (2022), “Perceived experience, perceived value and customer satisfaction as antecedents to loyalty among hotel guests”, Journal of Quality Assurance in Hospitality and Tourism, Vol. 23 No. 2, pp. 447-481, doi: 10.1080/1528008X.2021.1884930.
Peat, C.M., Peyerl, N.L. and Muehlenkamp, J.J. (2008), “Body image and eating disorders in older adults: a review”, The Journal of General Psychology, Vol. 135 No. 4, pp. 343-358, doi: 10.3200/GENP.135.4.343-358.
Piqueras-Fiszman, B. and Spence, C. (2015), “Sensory expectations based on product-extrinsic food cues: an interdisciplinary review of the empirical evidence and theoretical accounts”, Food Quality and Preference, Vol. 40, pp. 165-179, doi: 10.1016/j.foodqual.2014.09.013.
Prayag, G., Khoo-Lattimore, C. and Sitruk, J. (2015), “Casual dining on the French Riviera: examining the relationship between visitors' perceived quality, positive emotions, and behavioral intentions”, Journal of Hospitality Marketing and Management, Vol. 24 No. 1, pp. 24-46, doi: 10.1080/19368623.2014.859114.
Rafaqat, A. (2024), “Egypt restaurants, cafes, and bakeries in 2024: insights for F&B and FMCG industries”, available at: https://www.xmap.ai/blog/egypt-restaurants-cafes-and-bakeries-in-2024-insights-for-f-b-and-fmcg-industries (accessed 20 March 2024).
Rajput, A. and Gahfoor, R.Z. (2020), “Satisfaction and revisit intentions at fast food restaurants”, Future Business Journal, Vol. 6 No. 1, pp. 1-12, doi: 10.1186/s43093-020-00021-0.
Ribeiro, P., Ramos, R.F. and Moro, S. (2024), “Restaurant containment measures and perceived service quality: implications for future pandemics”, Consumer Behavior in Tourism and Hospitality, Vol. 19 No. 1, pp. 116-130, doi: 10.1108/CBTH-06-2023-0081.
Ringle, C.M., Wende, S. and Becker, J.-M. (2015), SmartPLS 3, SmartPLS, Bonningstedt.
Rust, R.T. and Oliver, R.L. (1994), “Service quality: insight and managerial implications from the frontiers”, in Rust, R.T. and Oliver, R.L. (Eds), Service Quality: New Directions in Theory and Practice, Sage, London, pp. 1-19.
Ryu, K. and Jang, S. (2008), “DINESCAPE: a scale for customers’ perception of dining environments”, Journal of Foodservice Business Research, Vol. 11 No. 1, pp. 2-22.
Ryu, K., Kim, H.J., Lee, H. and Kwon, B. (2021), “Relative effects of physical environment and employee performance on customers' emotions, satisfaction, and behavioral intentions in upscale restaurants”, Sustainability, Vol. 13 No. 17, p. 9549, doi: 10.3390/su13179549.
Sekaran, U. (2011), Research Methods for Business: A Skill Building Approach, John Wiley & Sons, Hoboken.
Sengel, T., Karagoz, A., Cetin, G., Dincer, F.I., Ertugral, S.M. and Balık, M. (2015), “Tourists' approach to local food”, Procedia-Social and Behavioral Sciences, Vol. 195, pp. 429-437, doi: 10.1016/j.sbspro.2015.06.485.
Siddiqi, U.I., Akhtar, N. and Islam, T. (2022), “Restaurant hygiene attributes and consumers' fear of COVID-19: does psychological distress matter?”, Journal of Retailing and Consumer Services, Vol. 67 No. 2020, 102972, pp. 1-11, doi: 10.1016/j.jretconser.2022.102972
Soonsan, N., Phakdee-auksorn, P. and Suksirisopon, P. (2023), “Determining food attributes for measuring and evaluating a gastronomic destination's appeal to visitors”, Journal of Hospitality and Tourism Insights, Vol. 6 No. 5, pp. 1755-1775, doi: 10.1108/JHTI-02-2022-0048.
Stribbell, H. and Duangekanong, S. (2022), “Satisfaction as a key antecedent for word of mouth and an essential mediator for service quality and brand trust in international education”, Humanities and Social Sciences Communications, Vol. 9 No. 438, pp. 1-11, doi: 10.1057/s41599-022-01459-z.
Sullivan, G.M. and Feinn, R. (2012), “Using effect size - or why the p value is not enough”, Journal of Graduate Medical Education, Vol. 4 No. 3, pp. 279-282, doi: 10.4300/jgme-d-12-00156.1.
Teng, C. and Chang, J.H. (2013), “Mechanism of customer value in restaurant consumption: employee hospitality and entertainment cues as boundary conditions”, International Journal of Hospitality Management, Vol. 32, pp. 169-178, doi: 10.1016/j.ijhm.2012.05.008.
Tuzunkan, D. and Albayrak, A. (2016), “The importance of restaurant physical environment for Turkish customers”, Journal of Tourism Research and Hospitality, Vol. 5 No. 2, pp. 1-7.
Ukeje, U.E., Lasisi, T.T., Eluwole, K.K., Titov, E. and Ozturen, A. (2021), “Organizational level antecedents of value co-destruction in hospitality industry: an investigation of the moderating role of employee attribution”, Current Issues in Tourism, Vol. 24 No. 6, pp. 842-856, doi: 10.1080/13683500.2020.1763928.
Wang, G., Wang, J., Ma, X. and Qiu, R.G. (2010), “The effect of standardization and customization on service satisfaction”, Journal of Service Science, Vol. 2, pp. 1-23, doi: 10.1007/s12927-010-0001-3.
Weyers, M. and Louw, L. (2017), “Framework for the classification of service standardisation”, The Service Industries Journal, Vol. 37 No. 7, pp. 409-425, doi: 10.1080/02642069.2017.1329419.
Yeh, W.C., Lee, C.C., Yu, C., Wu, P.S., Chang, J.Y. and Huang, J.H. (2020), “The impact of the physical attractiveness and intellectual competence on loyalty”, Sustainability, Vol. 12 No. 10, pp. 1-23, doi: 10.3390/su12103970.
Yi, Y. and Gong, T. (2013), “Customer value co-creation behavior: scale development and validation”, Journal of Business Research, Vol. 66 No. 9, pp. 1279-1284, doi: 10.1016/j.jbusres.2012.02.026.