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The Impact of Servicescape and Employee Service Quality in the KTV Industry.


Karaoke is an activity in which people sing their favourite songs over a pre-recorded music track and is a very popular form of entertainment in Asia. The amateur singer's tempo is guided by moving symbols or changing colours of the lyrics displayed on a large video screen (Fung, 2009). Karaoke establishments, also known as KTVs, typically have multiple lavishly-furnished rooms with karaoke equipment that are available for rental. China's karaoke-booth market alone is currently worth about $600 million and is expected to reach $1.2 billion by the end of 2018 (The Wall Street Journal, 2018). The increasing number of KTVs emerging in Malaysia indicates the rising demand for karaoke entertainment among Malaysians. Some of the popular karaoke chains in Malaysia include RedBox, Loudspeaker, Neway, and Superstar Family KTV (Tan, 2016).

As customers entertain themselves in these rooms for a paid duration of time, the servicescape of KTVs plays a vital role in facilitating customer service, satisfaction, and re-patronisation (Lam, 2005). Servicescape refers to the environment in which the organisation provides services for customers (Bitner, 1992; Zeithaml & Bitner, 1996). Physical assets such as the interior design, decor, and signage help to communicate a favourable impression and to bolster enjoyment and satisfaction of customers (Booms & Bitner, 1982; Ali et al., 2018). Specifically, for service entertainment establishments such as KTVs, servicescape is an extrinsic cue that conveys the image of the establishment and has a huge impact on customer satisfaction and their willingness to recommend the KTV outlet to their friends (Bitner, 1992; Wakefield & Blodgett, 1996). Many empirical studies have consistently reported that customers respond positively both emotionally and cognitively to a pleasant physical environment (Lin, 2004; Kim & Moon, 2009; Lockwood & Pyun, 2019). In fact, for travellers, servicescape and its associated psychological benefits have been reported to outweigh the utilitarian need for comfortable accommodation (Ritchie and Crouch, 2003).

The influence of servicecape has been widely examined in various contexts such as in the hotel industry (Wu & Ko, 2013), food festivals (Wu et al., 2014b), the hot spring industry (Wu et al., 2015), Taiwan tourist night markets (Wu et al., 2014a), Museums (Wu & Li, 2015) and theme parks (Wu et al., 2018). Despite the wide interest in these physical environments, there has been very little research dealing with this subject in the context of the KTV industry, where customers spend a significant amount of time to sing in the service environment. Our understanding of how the KTV servicescape affects human emotions and behaviours remains incomplete. To fill the gap, this study aims to examine the influence of servicescape and employee service quality on customer satisfaction and how customer satisfaction affects corporate image, revisit intention, and word-of-mouth. Apart from that, the analysis of the importance and performance of each factor in relation to customer satisfaction will be carried out so that the discussion on the managerial and practical implications are more meaningful.

Literature Review

Stimulus-Organism-Response Model (SOR)

Guided by the Mehrabian and Russell (1974) stimulus-organism-response model (SOR), this study utilises a theoretical framework that explains how servicescape affects customer satisfaction, which in turn influences the image of the establishment, revisit intention, and word-of-mouth in the karaoke context. The stimuli in the SOR model are external to the customer and consist of both marketing mixed variables and other environmental inputs. In this study, the 'stimuli' refers to servicescape of KTVs (e.g., ambience, design, and social factors) and employee service quality. The 'organism' refers to "internal processes and structures intervening between stimuli external to the person and the final actions, reactions, or responses emitted" (Chang et al., 2011, p, 235). In this study, customer satisfaction is used to represent the organism. Instead of measuring pleasure, arousal, and dominance, the concept of customer satisfaction was selected to characterise the organism because customer satisfaction can be a reflection of pleasant or disappointed feelings derived from the performance of a product or service in meeting or surpassing customers' expectations (Kotler & Keller, 2006). The 'responses' in the S-O-R paradigm represent the reactions of consumers, which can be approach and avoidance behaviours (Donovan & Rossiter, 1982; Sherman et al., 1997). For this study, the responses are corporate image, revisit intention, and word-of-mouth.


The physical environment of an organisation providing services is referred to as a servicescape (Bitner, 1992). Leisure service establishments such as hotels, cruise lines, cinemas and karaoke lounges typically involve customers spending time within the physical environments of the service provider. Hence for the leisure and entertainment industry, servicescape plays a crucial role in influencing customer satisfaction, corporate image, revisit intention, and word-of-mouth (Bitner, 1992; Sherman et al., 1997). Servicescape has the power to not only create a positive impression but also influence customer engagement. In this paper, we examine the impact of ambience, cleanliness, functionality, spatial layout, signs, symbols, and employee service quality on customer satisfaction. In addition, customer satisfaction is also hypothesised to impact corporate image, revisit intention, and word-of-mouth.

Customer Satisfaction

Customer satisfaction is a measure of how products and services provided meet or surpass customer expectations (Kotler et al., 2018). Maintaining high levels of customer satisfaction is crucial for corporate survival and profitability. Past studies consistently conclude that satisfied customers are more likely to be loyal, to repeat purchases, and to endorse the products and services (Bojanic, 1996; Lam et al., 2011). Customer satisfaction has been reported to be affected by the physical environment in which services are rendered (Chen et al., 2011; Wu & Cheng, 2013; Wu, 2013).


Ambience refers to the feeling and mood associated with a place and is enhanced by the character, decoration, atmosphere (of the place) through lighting, temperature, noise, music, and scent (Lam et al., 2011). Ambience affects human perception and responses through the five human senses (Bitner, 1992; Hirsch, 1995; Johnson, Mayer & Champaner, 2004; Morin, Dube & Chebat, 2007). For example, Yuksel and Yuksel (2003) reported that some customers value the atmosphere of restaurants more than the quality and prices of the food served. For retail shops, the tempo of the music has been found to affect the pace of shopping, length of stay, and amount of money spent (Milliman 1982, 1986). Lockwood and Pyun (2019) found that atmosphere plays a significant role in affecting the emotional responses as well as behaviour of customers in a hotel context. In fact, atmosphere was found to be an important driver for behavioural intention in various contexts (Wu et al., 2015; Wu et al., 2018). This is because satisfied customers are likely to experience positive emotions, which lead to favourable behaviours towards the company such as recommending the services to others and repurchasing the services in the future. Similarly, having a pleasant ambience in a karaoke establishment can lead to customer satisfaction. As such, we postulate that:

H1 Ambience (air and noise) has a significant positive influence on customer satisfaction.

H2 Ambience (lighting and temperature) has a significant positive influence on customer satisfaction.


Cleanliness is a key aspect of servicescape (Wakefield & Blodgett, 1996). The absence of dirt (including dust, stains, and bad smells) is defined as cleanliness. There are two aspects of cleanliness, firstly, the state of being clean and free from dirt and secondly, the continuous cleaning-up process (Wakefield & Blodgett, 1996). The place needs to be cleaned before customers arrive and constantly cleaned throughout the operational hours. Cleanliness influences pleasant feelings and endears trust; its importance has been highlighted extensively in the literature (see Fitzsimmons, 2003; Berta, 2005). Vos et al., (2018) conducted a systematic review of the influence of cleanliness on customer responses and found that cleanliness is an important factor of customer satisfaction in various contexts. Furthermore, cleanliness positively influences customer behavioural outcomes such as the intention to pay more and the intention to revisit (Lee & Kim, 2014). A clean and tidy place visually creates an image of professionalism and superior service (Gary & Sansolo, 1993). For conference delegates, cleanliness is the most decisive factor for customer satisfaction. Similarly, cleanliness has been determined to be a significant factor for the revisit intention of hotel customers (Hoffman et al., 2003). In the leisure and entertainment establishments where clients spend several hours in the premises, cleanliness is paramount for customer satisfaction (Wakefield & Blodgett, 1996). Hence, we postulate that:

H3 Cleanliness has a significant positive influence on customer satisfaction.


Functionality refers to the ability of the servicescape to facilitate the performance of services. The effects of functionality have been amply documented in organisational behaviour and psychology research. Functionality as an attribute of servicescape is conceptualised as "the ability of arranged machinery, equipment, and furnishings to facilitate and the accomplishment of goals" (Bitner, 1992, p. 66). For example, appropriate equipment is a key element of functionality for conference delegates (Wu & Weber, 2005). For airports, equipment and electronic displays that report flight schedules and provide entertainment, these all contribute positively to the experience and perception of satisfaction by customers (Wakefield & Blodgett, 1996). Similarly, electronic equipment in exhibition centres has also been reported to influence customer satisfaction and the desire for customers to linger longer (Siu et al., 2012). With regard to a self-service entertainment environment like KTVs, where the customers need to self-service themselves and not depend on employees to serve them, functionality is critical. In this research, functionality refers to the user-friendly feature of the karaoke equipment in selecting the songs, in adjusting the sound effects, and providing guidance on when and what to sing. The importance of the role of functionality increases when the tasks to be carried out are highly complex or when customers are under pressure to perform the tasks, such as in a karaoke setting where customers need to sing in the presence of clients, colleagues, and friends. Hence, we postulate that:

H4 Functionality has a significant positive influence on customer satisfaction.

Spatial Layout

Spatial layout refers to the arrangement and relationship of furniture, equipment, and service areas to facilitate customer services (Bitner, 1992; Nguyen & Leblanc, 2002). A well-designed layout that facilitates intuitive guidance and provides convenience enhances customer comfort and increases the likelihood of repeat business (Liu & Jang, 2009). Spatial layout has been documented to affect customer seating comfort and forms a crucial component of servicescape (Bitner, 1992). Seating comfort has been found to be critical for places where customers sit for a considerable amount of time such as in casinos (Lucas, 2003) as well as airports (Zheng, 2014). Thus, we postulate that:

H5 Spatial layout has a significant positive influence on customer satisfaction.

Signs and Symbols

Signs and symbols refer to physical signs that may serve a symbolic role as well as provide cues for direction, and information about appropriate behaviour within the servicescape (Bitner, 1992). Example of signs are insignias, labels (such as the company name, department name), direction indicators (e.g., exit, entrance), and permitted/non-permitted behaviour signs (no smoking, children must be accompanied by an adult). Reportedly, signs could decrease perceived over-crowding even in a prison environment as well as reduce stress in a jail lobby room (Wener & Kaminoff, 1982). Elements in the physical environment not only serve a functional role, but often communicate symbolism via subtle messages (Siu et al., 2012). Artwork, certificates, photographs, and carpets signify symbolism and create a positive aesthetic impression. Hence, symbols are used to create aesthetic impressions in order to help people understand the significance of the place and/or to convey instructions (Zeithaml et al., 1996) such as the corporate logo located at the entrance of the building and directional signs. Signs and symbols help to encourage appropriate behaviour of people, for example, signs in a library discouraging people from talking loudly enable more people to enjoy the library facilities. Hence, we hypothesise that:

H6 Signs and symbols have a significant positive influence on customer satisfaction.

Employee Service Quality

The nature of employee service is intangible, inseparable, heterogeneous, and perishable. Parasuraman et al. (1985, 1988) were the first researchers to conceptualise and operationalise service quality. Service quality influences the experience of consumers, particularly their emotions (Debra & O'Cass, 2004). Service quality is significantly related to the image of the establishment and actuates customer expectations and behavioural intentions (Jang et al., 2015). Studies suggest that the service encounter experienced by a customer directly impacts customer satisfaction (Parasuraman et al., 1985). A business that creates a good social impression can generate positive emotions in customers if supported by superior service quality (Baker et al., 1994). Furthermore, service staff and their performance influence consumer emotions and determine their perception of service quality (Lin & Lin, 2011). Olorunniwo et al. (2006) reported that good service quality is positively related to customer satisfaction, which in turn leads to behavioural intention. They surmised that the behaviour of employees and contact with customers form a critical determinant of customer satisfaction, whether positive or negative. Similarly, Dong and Siu (2013) documented that service quality plays an important role in customer evaluation of the service experience. Hence, we postulate that:

H7 Employee service quality has a significant relationship with customer satisfaction.

The Impact of Customer Satisfaction on Corporate Image, Revisit Intention and Word-Of-Mouth

Many studies have consistently reported that customer satisfaction or dissatisfaction influences behavioural intentions. Satisfied customers are more likely to have the intention to purchase more, repurchase, become loyal and recommend others to purchase (Rust & Williams, 1994; Cronin et al., 2000). In addition, satisfied customers also enhance their desire to remain in the service area and spend more in the establishment (Bitner, 1992; Wakefield & Blodgett, 1996; Lucas, 2003). Similarly, satisfied customers are less likely to seek competing products/services, (Anderson & Srinivasan, 2003). In addition, customer satisfaction has been found to have a positive influence on the corporate image and customer loyalty in the hotel industry (Liat et al. 2014). Similarly, Ihtiyar et al., (2018) found that customer satisfaction has a significant positive influence on intention to pay more, revisit intention, and word-of-mouth on a sample of 660 customers who enjoy visiting wellknown coffee shops. Furthermore, satisfied customers are less likely to spread negative word-of-mouth reviews (Szymanski & Henard, 2001). Therefore, we propose:

H8 Customer satisfaction has a significant positive influence on corporate image.

H9 Customer satisfaction has a significant positive influence on revisit intention.

H10 Customer satisfaction has a significant positive influence on word-of-mouth.

The research model is shown in Figure 1.


Data Collection and Subjects

The research objectives are achieved through a quantitative research approach by means of the survey questionnaire method. The questionnaire was pre-tested on a senior manager, two academic experts, and also three regular karaoke customers. Based on their feedback, we modified the questionnaire to suit the context of this research. The questionnaire consisted of three main sections. Section one inquired about servicescape and service quality of the KTV company. Section two sought the feedback of customers regarding satisfaction, corporate image, revisit intention, and word-of-mouth. Section three requested their personal information.

To accurately capture customer perceptions concerning certain subjects (e.g., servicescape, customer satisfaction), the target respondents were required to have visited a KTV recently. As such, we obtained permission from a major KTV establishment in Malaysia to distribute questionnaires to their customers 30 minutes before their karaoke session ended. Each questionnaire was attached with a RM 10 voucher sponsored by the KTV company to motivate customers to complete the questionnaire and to reduce common method bias. This data collection method was deemed suitable because while the KTV experiences are still fresh in the minds of the customers, they can relate better to the questions asked in the questionnaire. This study refers to the KTV company as "Company X" in order to conceal the identity of the company. Out of 300 distributed questionnaires in six different branches (of the same company) with each given 50 survey forms, 270 completed questionnaires were received. After removing straight lining and suspicious data, 253 usable sets of data were retained for further analysis. The sample size (N=253) is sufficient as G*power analysis indicates that the minimum sample size required in this research is 103.

The respondents mostly comprised young people aged below 25 years old (70 %) and almost 90 % of them were Chinese (Table 1). KTVs appear not to be a popular choice of entertainment amongst the other races (Indians and Malays). Females constituted 65 % of the population and the majority of respondents (65 %) earned RM4,000 and below.


To measure servicescape, we adapted the scale from Lam (2005), which consisted of six different dimensions: ambience (Lighting and Temperature, 4 items), ambience (Air and Noise, 3 items), cleanliness (3 items), functionality (6 items), spatial layout (6 items), and signs and symbols (2 items). These dimensions were validated by two academic experts and the top management of the surveyed KTV company. A fouritem scale developed by Wu et al. (2013) was used to measure employee service quality. An example item was "service employees are friendly and polite". Customer satisfaction was measured using a three-item scale adapted from Oliver (1980). Items included "Overall, I am satisfied with my experience at this KTV". The scale to measure corporate image was adapted from Aydin and Ozer (2005), which consisted of five items. An example item was "This KTV is stable and firmly established". Revisit intention was assessed using a two-item scale adapted from Lam et al. (2011).

An example item was "I will visit the Company X in the future". Lastly, a four-item scale by Line et al. (2018) was used to measure word-of-mouth. An example item was "I would say positive things about the Company X to other people". All items were measured on a standard 5-point Likert scale (1- strongly disagree to 5- strongly agree).


This study employed Partial Least Squares (PLS) structural equation modelling (PLSSEM) using Smart PLS 3.0 software (Ringle et al., 2015). The rationale of using PLSSEM instead of co-variance based structural equation modelling (CB-SEM) was 1) the research objective focuses more on prediction rather than theory confirmation, 2) PLS-SEM can handle non-normal data due to its bootstrapping procedure and 3) PLSSEM achieves higher levels of statistical power compared to CB-SEM with small sample sizes (Hair et al., 2017). On top of that, a recent article by Hair et al. (2019) stated that PLS-SEM outperforms regression analysis when assessing mediation and this was one main reason to justify the use of PLS-SEM. As suggested by Anderson and Gerbing (1998), a two-step approach was used. We first assessed the measurement model and then the structural model.

Common Method Variance

The common method variance (CMV) was assessed using Harman's one-factor test in this study. The one-factor solution accounted for 36.08 % of the total variance, which was less than 50%, indicating that the model passed the one-factor test (Podsakoff & Organ, 1986). Furthermore, the construct correlation matrix (Table 3) showed that each of the inter-construct correlations was less than 0.9, indicating that CMV was not a serious issue (Bagozzi et al., 1991). A full collinearity test was also conducted and the results showed that the majority of VIF values were lower than the recommended value of 3.3 (Kock, 2015). Only one construct in all the regressions had a value of above 3.3 but below 5, which was acceptable (Hair et al., 2017). Hence, CMV should not be a major concern in this research.

Measurement Model

In assessing the measurement model, we first examined the internal consistency of measures by checking the values of the Cronbach alpha and composite reliability. In Table 2, the values of the Cronbach alpha and composite reliability for all constructs were above the recommended value of 0.7, indicating good internal consistency. Next, the convergent validity was examined by checking the factor loadings and average variance extracted (AVE). Items with a factor loading below 0.4 should be removed and the AVE should be above 0.5. As long as the AVE value for the construct exceeds 0.5, any indicator with low loading values, but not less than 0.4, could be kept to maintain the content validity. Table 2 showed that all constructs passed the threshold values for factor loading and AVE. Hence, we conclude that convergent validity was not an issue of concern for this research.

Discriminant validity was assessed via the Fornell-Larcker criterion and HeterotraitMonotrait (HTMT) ratio. To pass the Fornell-Larcker test, the square root of AVE (diagonal elements) should be significantly greater than correlations (off-diagonal elements) in the corresponding rows and columns. Another confirmation of this validity comes from satisfying the HTMT test (Henseler et al., 2015). If the HTMT value is greater than 0.85, there would be a problem of discriminant validity. Table 3 confirmed that discriminant validity was not a problem. The saturated model and the estimated model obtained a Standardised Root Mean Square Residual (SRMR) value of 0.067 and 0.074 respectively, which were lower than the guideline value of 0.08 implying that data fitted the model (Hair et al., 2019; Henseler et al., 2016).

Structural Model

A non-parametric bootstrapping procedure with 5,000 re-samples was performed to examine the statistical significance of the path coefficients (Hair et al., 2017). In Table 4, the results showed that ambience (A&N), ambience (L&T), and cleanliness do not have a significant influence on customer satisfaction. Hence, H1, H2, and H3 are not supported. However, it was found that functionality, spatial layout, signs and symbols, and employee service quality have a significant influence on customer satisfaction, supporting H4, H5, H6, and H7. In addition, satisfaction was found to have a significant influence on corporate image, revisit intention, and word-of-mouth, thus supporting H8, H9, and H10. The adjusted R2 value of customer satisfaction was 0.501 which means that the proposed model could explain 50.1 % variation of customer satisfaction. The adjusted R2 values for corporate image, revisit intention, and word-of-mouth were 0.586, 0.559, and 0.576 respectively. These figures indicated that customer satisfaction alone can explain 58.6 % of the variance of corporate image, 55.9 % of the variance of revisit intention, and 57.6 % of the variance of wordof-mouth respectively.

The SOR model states that environment will produce an emotional state in an individual, consequently resulting in certain behaviour in response to the environment (Mehrabian & Russell, 1974). Based on this theoretical reasoning, a post-hoc test was conducted to determine whether customer satisfaction mediates the relationships as shown in the research model although no hypotheses were developed in advance. A bootstrapping procedure was performed to determine the significance of the indirect effect and bias-corrected confidence intervals (BCCI). If the BCCI confidence value intervals contain a zero value, this means there is no mediation effect for that construct (Niltz et al., 2016). As shown in Table 5, customer satisfaction mediates 12 relationships out of the 21 relationships.

A blindfolding procedure with an omission distance of 7 was conducted to examine the predictive relevance of the model (Geisser, 1974; Stone, 1974). A Q2 value greater than zero indicates the model has predictive relevance. The Q2 values for customer satisfaction, corporate image, revisit intention, and word-of-mouth were 0.403, 0.393, 0.504, and 0.403 respectively. This paper also conducted a PLS prediction analysis developed by Shmueli et al. (2016) to determine the predictive power of the model. The PLS prediction uses training and holdout samples to generate and evaluate predictions from PLS path model estimations. As shown in Table 6, the Q2 value was positive indicating the prediction error of the PLS-SEM results was smaller than the prediction error of simply using the mean values. Given that the Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) values for the PLS model are lower than for the LM and that the Q2 values for the indicators of the PLS model are larger than those generated for the LM model, it can be concluded that the model has strong predictive relevance (Shmueli et al., 2019).

IPMA Analysis

We conducted an importance-performance map analysis (IPMA) which was built on the PLS estimates for the relationships in the research model (importance of each latent variable) and the average values (performance) of the latent variables. The results are shown in Table 7 and Figure 2. The indicators and unstandardized latent variable scores were rescaled to range from 0 to 100 (Hair et al., 2017). In brief, the results of the IPMA analysis suggested that the most significant predictors of customer satisfaction in the order of their importance are employee service quality, followed by functionality, and spatial layout. However, it was found that the performance of employee service quality and functionality are relatively low as compared to the other predictors. Hence, this suggested that the KTV company should spend more resources on improving these two most significant, yet underperforming predictors, namely employee service quality and functionality.

Discussion and Managerial Implications

The findings of this study have significant contextual contributions to the stimulusorganism-response model (SOR) by investigating how servicescape influences customer reactions and responses in a karaoke establishment. Specifically, it was found that not all of the dimensions of the servicescape have a significant influence on customer satisfaction. Significant predictors of customer satisfaction in order of their importance were employee service quality, functionality, spatial layout, and signs and symbols. Consistent with previous studies in other leisure contexts (Siu et al., 2012), functionality was found to be an important predictor of customer satisfaction given the fact that the core business of KTV establishments involves the high usage of selfservice electronic equipment such as microphones, speakers, screens, and computers. KTV companies need to ensure that the karaoke system they employ is user friendly, the speakers produce high-quality sound, and the latest songs are made available promptly.

Wakefield and Blodgett (1996) stated that a comfortable seating environment is crucial to make the service experience of customers pleasurable, especially for customers who spend long hours in the same room. Consistent with those findings, this study found that spatial layout is another salient factor of customer satisfaction in a KTV establishment as customers typically spend three hours or more singing in the same room. Customers need to feel comfortable and at ease with the decor and room in which they sing songs (Ariffin et al., 2012). KTV companies should allocate the appropriate room size according to the number of customers. Furthermore, the significant relationship of signs and symbols with customer satisfaction is consistent with previous studies (Lam et al., 2011). Appropriately designed signs and symbols can increase customers' sense of control and ease, particularly for new customers unfamiliar with the place. In addition, customers might feel safer with emergency signs being properly displayed.

Lastly, employee service quality is a crucial factor that affects the feeling of satisfaction of the customers (Abu El Samen, Akroush, Al-Sayed & Hasan, 2012). Employees need to be pleasant, polite, helpful, and responsive to customers especially within the karaoke setting. In addition to enjoying singing songs in the privacy of a room without the presence of strangers (such as KTV's employees), the customers would also like to order food and drinks easily and get served promptly and courteously as befitting an upscale entertainment environment. Since service quality is an important indicator for customer satisfaction, managers should spend more resources to develop the service process and dedicate resources in order to at least meet customers' needs satisfactorily. This also implies that KTV companies should train their front-line service personnel to provide pleasant professional services befitting an upscale entertainment venue and allocate sufficient manpower during peak hours.

Surprisingly, the two dimensions of ambience were found to be insignificant to customer satisfaction suggesting that customers are not concerned so much about ambience. One possible reason is that the room in which customers sit is usually kept dark when they sing, and air conditioners are usually centralised making it difficult for customers to adjust the temperature. Another possible explanation for the insignificant relationship between ambience (air and noise) and customer satisfaction is that the music produced in the room during the karaoke session can be so loud that noise from other rooms is not an issue. Furthermore, cleanliness was also found insignificant to customer satisfaction probably because as customers tend to dim the lights in the KTV room when they sing, cleanliness often gets ignored. Hence, cleanliness has no effect on customer satisfaction.

Customer satisfaction was found to have a significant influence on corporate image, consistent with past studies (Kant et al., 2017; Cheng et al., 2014). This result suggests that improving customer satisfaction could increase the positive image of karaoke establishments. In addition, customer satisfaction was found to have a significant influence on revisit intention and word-of-mouth, consistent with past studies (Kuo & Tang, 2013; Cheng et al., 2014; Lee, 2019). The results indicate the importance of customer satisfaction in encouraging customers to revisit the karaoke house on a long-term basis and spreading positive messages about the organisation to friends, colleagues, and corporate clients.

Theoretical Contributions

This study has contributed to the servicescape literature in several ways. Predicated on the SOR model, this study examined the influence of various dimensions of servicescape on customer satisfaction in the KTV context, which has not been done previously. Second, supported by the SOR model and previous studies, a post-hoc mediation test to examine the mediating role of customer satisfaction was also conducted. The results revealed how servicescape and employee service quality act as stimuli that influence customer satisfaction (emotional states), which subsequently trigger various responses such as revisit intention, word-of-mouth, and positive corporate image. Third, the results of importance-performance map analysis (IPMA) demonstrated that employee service quality, functionality, and spatial layout were the most important stimuli which organisations must emphasise if the aim is to increase customer satisfaction.

Conclusion and Future Recommendations

Overall, the findings of this study support the importance of servicescape and employee service quality in affecting customer satisfaction, which in turn influences corporate image, revisit intention, and word-of-mouth. The top management has to realise that the physical environment is an important element not only in order to attract customers but also to build customer satisfaction, which can result in higher revisits and profitability. Apart from that, the top management also needs to continually focus on providing quality service to customers as this is the most important factor impacting customer satisfaction. Although this research context focused on KTV establishments, the findings could also be extended to other similar industries. However, there are several limitations in this study. First, we used customer satisfaction to represent the organism in the stimulus-organism-response model but customer satisfaction may not accurately measure the emotional state of customers. Hence, future research should include pleasure, arousal, and dominance in the model. Second, while the findings could be useful for similar entertainment industries which focus heavily on self-consumption services, it may not be directly applicable to other industries. Lastly, qualitative research such as interviews or observations could be employed for future research to gain a greater in-depth understanding of the issues.

Implications for Asian Business Context

Karaoke is a popular leisure activity for many people in Asia. People usually go to a karaoke establishment to sing whenever they have free time. Given that the KTV industry is prospering and growing, the aim of this study is to investigate factors influencing customer satisfaction and to examine how customer satisfaction could lead to various positive consumer outcomes. The findings of this study suggest that in order to make karaoke customers happy and satisfied, KTV companies need to ensure that the karaoke equipment is well-maintained and easy to use, the rooms are spacious and large enough for movements, the signage (e.g. toilet and exit signs) is provided, and the employees are friendly and competent. Hence, KTV companies should spend more resources in maintaining the standard of these areas in order to effectively keep their customers satisfied. These recommendations are generally applicable to the majority of KTV companies operating in Asia, especially in Hong Kong, Japan and China as these countries have many major karaoke chains which are similar in terms of the nature of business. When customers are well taken care of by the KTV company, they will reciprocate by spreading positive word-of-mouth about the company and revisiting the karaoke establishment in the future. When the existing customers recommend the KTV company to their friends, they are likely to get influenced by the positive reviews and visit the KTV company. If the KTV company is able to please their new customers, they will eventually spread good things about the KTV company to others as well, which can attract more potential customers and the cycle continues. Furthermore, repeat patronage is critical for the survival and success of any company. KTV companies should value their loyal customers because these customers will revisit the karaoke establishment to sing regardless of the KTV companies' promotions. In conclusion, as the positioning of each KTV company varies, it is important to understand the needs and wants of their customers in order to better satisfy them.


Ali, F., Kim, W. G., Li, J., & Jeon, H. M., (2018), "Make it delightful: Customers' experience, satisfaction and loyalty in Malaysian theme parks", Journal of Destination Marketing & Management, vol. 7, pp. 1-11.

Abu El Samen, A., Akroush, M. N., Al-Sayed, A. L., & Hasan, H. J., (2012), "An empirical model of customer service quality and customer loyalty in an international electronics company", International Journal of Electronic Business, vol. 10, no. 1, pp. 39-63.

Anderson, R. E., & Srinivasan, S. S., (2003), "E-satisfaction and e-loyalty: A contingency framework", Psychology & Marketing, vol. 20, no. 2, pp. 123-138.

Anderson, J. C., & Gerbing, D. W., (1988), "Structural equation modelling in practice: A review and recommended two-step approach", Psychological Bulletin, vol. 103, no. 3, pp. 411-423.

Ariffin, H. F., Bibon, M. F., & Abdullah, R. P. S. R., (2012), "Restaurant's atmospheric elements: What customer wants", Procedia-Social and Behavioural Sciences, vol. 38, pp. 380-387.

Aydin, S., & Ozer, G., (2005), "The analysis of antecedents of customer loyalty in the Turkish mobile telecommunication market", European Journal of Marketing, vol. 39, no. 7/8, pp. 910-925.

Bagozzi, R. P., Yi, Y., & Phillips, L. W., (1991), "Assessing construct validity in organizational research", Administrative Science Quarterly, vol. 36, no. 3, pp. 421-458.

Baker, J., Grewal, D., & Parasuraman, A., (1994), "The influence of store environment on quality inferences and store image", Journal of the Academy of Marketing Science, vol. 22, no. 4, pp. 328-339.

Berta, D., (2005), "Focus on restaurant cleanliness may spruce up sales figures", Nation's Restaurant News, vol. 39, no. 30, p. 122.

Bitner, M. J., (1992), "Servicescape: The impact of physical surroundings on customers and employees", Journal of Marketing, vol. 56, no. 2, pp. 57-71.

Bojanic, D. C., (1996), "Consumer perceptions of price, value and satisfaction in the hotel industry: An exploratory study", Journal of Hospitality and Leisure Marketing, vol. 14, no. 1, pp. 5-22.

Booms, B. H., & Bitner, M. J., (1982), "Marketing services by managing the environment", Cornell Hotel and Restaurant Administration Quarterly, vol. 23, no. 1, pp. 35-40.

Chang, H. J., Eckman, M., & Yan, R. N., (2011), "Application of the Stimulus-OrganismResponse model to the retail environment: The role of hedonic motivation in impulse buying behaviour," The International Review of Retail, Distribution and Consumer Research, vol. 21, no. 3, pp. 233-249.

Chen, C. M., Lee, H. T., Chen, S. H., & Huang, T. H., (2011), "Tourist behavioural intentions in relation to service quality and customer satisfaction in Kinmen National Park, Taiwan", International Journal of Tourism Research, vol. 13, no. 5, pp. 416-432.

Cheng, B. L., Mansori, S., & Huei, C. T., (2014), "The associations between service quality, corporate image, customer satisfaction, and loyalty: Evidence from the Malaysian hotel industry", Journal of Hospitality Marketing & Management, vol. 23, no. 3, pp. 314-326.

Cronin, J. J., Brady, M. K., & Hult, T. M., (2000), "Assessing the effects of quality, value, customer satisfaction on consumer behavioural intentions in service environment", Journal of Retailing, vol. 76, no. 2, pp. 193-216.

Debra, G., & O'Cass, A., (2004), "Examining service experiences and post-consumption evaluations", Journal of Services Marketing, vol. 18, no. 6, pp. 450-461.

Dong, P., Siu, N. Y. M., (2013), "Servicescape elements, customer predispositions and service experience: The case of theme park visitors", Tourism Management, vol. 36, pp. 541-551.

Donovan, R. J., & Rossiter, J. R., (1982), "Store atmosphere: An environmental psychology approach", Journal of Retailing, vol. 70, no. 3, pp. 34-57.

Fitzsimmons, B., (2003), "Restroom cleanliness: The last detail", Restaurant Hospitality, vol. 87, no. 10, pp. 100-102.

Fornell, C. G., & Larcker, D. F., (1981), "Evaluating structural equation models with unobservable variables and measurement error", Journal of Marketing Research, vol. 18, no. 1, pp. 39-50.

Fung, A., (2009), "Consuming karaoke in China modernities and cultural contradiction", Chinese Sociology and Anthropology, vol. 42, no. 2, pp. 39-55.

Gary, M., & Sansolo, M., (1993), "60th annual report of the grocery industry: Consumers show cautious optimism", Progressive Grocer, vol. 72, no. 4, pp. 88-94.

Geisser, S., (1974), "A predictive approach to the random effects model", Biometrika, vol. 61, no. 1, pp. 101-107.

Hair, J. F. J., Hult, G. T. M., Ringle, C. M., & Sarstedt, M., (2017), A primer on Partial Least Squares Structural Equation Modelling (PLS-SEM), Sage Publications, Thousand Oaks.

Hair, J. F., Sarstedt, M., & Ringle, C. M., (2019), "Rethinking some of the rethinking of partial least squares", European Journal of Marketing, vol. 53, no. 4, pp. 566-584.

Hoffman, K. D., Kelly, S. W., & Chung, B. C., (2003), "A CIT investigation of servicescape failures and associated recovery strategies", Journal of Service Marketing, vol. 17, no. 4, pp. 322-340.

Henseler, J., Hubona, G. S., & Pauline, A. R., (2016), "Using PLS path modeling in new technology research: Updated guidelines", Industrial Management & Data Systems, vol. 116, no. 1, pp. 2-20.

Henseler, J., Ringle, C. M., & Sarstedt, M., (2015), "A new criterion for assessing discriminant validity in variance-based structural equation modelling", Journal of the Academy of Marketing Science, vol. 43, no. 1, pp. 115-135.

Ihtiyar, A., Ihtiyar, H. G., & Galay, Y., (2018), "Exploration of the antecedents and consequences of customers' service experiences", Journal of Hospitality and Tourism Insights, vol. 1, no. 4, pp. 367-386.

Jang, S. S., & Namkung, Y., (2009), "Perceived quality, emotions, and behavioural intentions: Application of an extended Mehrabian-Russell model to restaurants", Journal of Business Research, vol. 62, no. 4, pp. 451-460.

Jang, Y., Ro, H., & Kim, T. H., (2015), "Social servicescape: The impact of social factors on restaurant image and behavioural intentions", International Journal of Hospitality & Tourism Administration, vol. 3, no. 16, pp. 290-309.

Johnson, L., Mayer, K. J., & Champaner, E., (2004), "Casino atmospherics from a customer's perspective: A re-examination", UNLV Gaming Research and Review Journal, vol. 8, no. 2, pp. 1-10.

Kant, R., Jaiswal, D., & Mishra, S., (2017), "The investigation of service quality dimensions, customer satisfaction and corporate image in Indian public sector banks: An application of structural equation model (SEM)", Vision-The Journal of Business Perspective, vol. 21, no.1, pp. 76-85.

Kim, W. G., & Moon, Y. J., (2009), "Customers' cognitive, emotional, and actionable response to the servicescape: A test of the moderating effect of the restaurant type", International Journal of Hospitality Management, vol. 28, no. 3, pp. 144-156.

Kock, N., (2015), "Common method bias in PLS-SEM: A full collinearity assessment approach", International Journal of e-Collaboration, vol. 11, no. 4, pp. 1-10.

Kotler, P., & Keller, K., (2006), Marketing management: Customer value, customer satisfaction and customer loyalty, Prentice Hall, New Jersey.

Kotler, P., Keller, K. L., Ang, S. H., Tan, C. T., & Leong, S. M., (2018), Marketing management: An Asian perspective, Pearson Education Limited, Harlow.

Kuo, C. W., & Tang, M. L., (2013), "Relationships among service quality, corporate image, customer satisfaction, and behavioural intention for the elderly in high speed rail services", Journal of Advanced Transportation, vol. 47, no. 5, pp. 512-525.

Lam, A. T. P., (2005), "The role of karaoke box servicescape play in customer satisfaction", Thesis of Hong Kong Baptist University, Hong Kong, China, 2005.

Lam, L. W., Chan, K. W., Fong, D., & Lo, F., (2011), "Does the look matter? The impact of casino servicescape on gaming customer satisfaction, intention to revisit, and desire to stay", International Journal of Hospitality Management, vol. 30, no. 3, pp. 558-567.

Lee, C. Y., (2019), "Does corporate social responsibility influence customer loyalty in the Taiwan insurance sector? The role of corporate image and customer satisfaction", Journal of Promotion Management, vol. 25, no. 1, pp. 1-22.

Lee, S. Y., & Kim, J. H., (2014), "Effects of servicescape on perceived service quality, satisfaction and behavioural outcomes in public service facilities," Journal of Asian Architecture and Building Engineering, vol. 13, no. 1, pp. 125-131.

Lin, I. Y., (2004), "Evaluating a servicescape: The effect of cognition and emotion", International Journal of Hospitality Management, vol. 23, no. 2, pp. 163-178.

Lin, J. S. C., & Lin, C. Y., (2011), "What makes service employees & customers smile: Antecedents consequences of the employees' affective delivery in the service encounter", Journal of Service Management, vol. 22, no. 2, pp. 183-201.

Line, N. D., Hanks, L., & Kim, W. G., (2018), "An expanded servicescape framework as the driver of place attachment and word of mouth", Journal of Hospitality & Tourism Research, vol. 42, no. 3, pp. 476-499.

Liu, Y., & Jang, S., (2009). "The effects of dining atmospherics: An extended MehrabianRussell model", International Journal of Hospitality Management, vol. 28, no. 4, pp. 494-503.

Lockwood, A., & Pyun, K., (2019), "How do customers respond to the hotel servicescape?", International Journal of Hospitality Management, vol. 82, pp. 231-241.

Lucas, A. F., (2003), "The determinants and effects of slot servicescape satisfaction in a Las Vegas hotel casino", UNLV Gaming Research and Review Journal, vol. 7, no. 1, pp. 1-19.

Mehrabian, A., & Russell, J. A., (1974), An approach to environmental psychology, The MIT Press, Cambridge.

Morin, S., Dube, L., & Chebat, J. C., (2007), "The role of pleasant music in servicescape: A test of the dual model of environmental perception", Journal of Retailing, vol. 83, no. 1, pp. 115-130.

Nguyen, N., & Leblanc, G., (2002), "Contact personnel, physical environment and the perceived corporate image of intangible services by new clients", International Journal of Service Industry Management, vol. 13, no 3, pp. 242-262.

Nitzl, C., Roldan, J. L., & Cepeda, G., (2016), "Mediation analysis in partial least squares path modeling: Helping researchers discuss more sophisticated models", Industrial Management & Data Systems, vol. 116, no. 9, pp. 1849-1864.

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.

Olorunniwo, F., Hsu, M. K., & Udo, G. J., (2006), "Service quality, customer satisfaction, and behavioural intentions in the service factory", Journal of Services Marketing, vol. 1, no. 20, pp. 59-72.

Parasuraman, A., Zeithaml, V. A., & Berry, L. L., (1985), "A conceptual model of service quality and its implications for future research", Journal of Marketing, vol. 49, no. 4, pp. 41-50.

Parasuraman, A., Zeithaml, V. A., & Berry, L. L., (1988), "SERVQUAL: A multiple-item scale of measuring consumer perceptions of service quality", Journal of Retailing, vol. 64, no. 1, pp. 12-37.

Podsakoff, P. M., & Organ, D. W., (1986), "Self-reports in organizational research: Problems and prospects", Journal of Management, vol. 12, no. 4, pp. 531-544.

Ringle, C. M., Wende, S., & Becker, J. M., (2015), "SmartPLS 3", Retrieved from:

Ritchie, J. R. B., & Crouch, G. I., (2003), The competitive destination: A sustainable tourism perspective, CABI Publishing, Oxon.

Rust, R. T., & Williams, D. C., (1994), "How length of patronage affects the impact of customer satisfaction on repurchase intention?", Journal of Consumer Satisfaction, Dissatisfaction, and Complaining Behaviour, vol. 7, pp. 107-113.

Sherman, F., Mathur, A., & Belk, S. R., (1997), "Store environment and consumer purchase behavior: Mediating role of consumer emotions", Psychology and Marketing, vol. 14, no. 4, pp. 361-378.

Shmueli, G., Ray, S., Velasquez Estrada, J. M., & Chatla, S. B., (2016). "The elephant in the room: Evaluating the predictive performance of PLS models", Journal of Business Research, vol. 69, no. 10, pp. 4552-4564.

Shmueli, G., Sarstedt, M., Hair, J., Cheah, J., Ting, H., Vaithilingam, S., & Ringle, C., (2019), "Predictive model assessment in PLS-SEM: Guidelines for using PLSpredict", European Journal of Marketing, vol. 53, no. 11, pp. 2322-2347.

Siu, N. Y. M., Wan, P. Y. K., & Dong, P., (2012), "The impact of the servicescape on the desire to stay in convention and exhibition centres: The case of Macao", International Journal of Hospitality Management, vol. 31, no. 1, pp. 236-246.

Stone, M., (1974), "Cross-validatory choice and assessment of statistical predictions", Journal of the Royal Statistical Society, vol. 36, no. 2, pp. 111-147.

Szymanski, D. M., & Henard, D. H., (2001), "Customer satisfaction: A meta-analysis of the empirical evidence", Journal of the Academy of Marketing Science, vol. 20, no. 1, pp. 16-35.

Tan, C., (2016), "10 best karaoke lounges for under rm80 for you to sing your heart out", Retrieved from

The Wall Street Journal, (2018), "Like karaoke but can't sing? Introducing the booth for one, Retrieved from

Vos, M. C., Galetzka, M., Mobach, M. P., Hagen, M. V., & Pruyn, A. T. H., (2018), "Cleanliness unravelled: A review and integration of literature", Journal of Facilities Management, vol. 16, no .4, pp. 429-451.

Wakefield, K. L., & Blodgett, J. G., (1996), "The effect of the servicescape on customers' behavioural intentions in leisure service settings", Journal of Services Marketing, vol. 10, no. 6, pp. 45-61.

Wener, R. E., & Kaminoff, R., (1982), "Improving environmental information: Effects of signs on perceived crowding and behaviour", Environment and Behaviour, vol. 14, no. 6, pp. 671-694.

Wu, A., & Weber, K., (2005), "Convention center facilities, attributes and services: The delegates' perspective", Asia Pacific Journal of Tourism Research, vol. 10, no. 4, pp. 399-410.

Wu, H. C., (2013), "An empirical study of the effects of service quality, perceived value, corporate image and customer satisfaction on behavioural intentions in the Taiwan quick service restaurant industry", Journal of Quality Assurance in Hospitality & Tourism, vol. 14, no. 4, pp. 364-390.

Wu, H. C., & Cheng, C. C., (2013), "A hierarchical model of service quality in the airline industry", Journal of Hospitality and Tourism Management, vol. 20, pp. 13-22.

Wu, H. C., Cheng, C. C., & Hsu, F. S., (2014a), "An assessment of visitors' behavioural intentions in the Taiwan tourist night market using a multilevel and hierarchical model", Tourism Analysis, vol. 19, no. 2, pp.185-197.

Wu, H. C., & Ko, Y. J., (2013), "Assessment of service quality in the hotel industry", Journal of Quality Assurance in Hospitality & Tourism, vol. 14, no. 3, pp. 218-244.

Wu, H. C., Li, M.-Y., & Li, T., (2018), "A study of experiential quality, experiential value, experiential satisfaction, theme park image, and revisit intention", Journal of Hospitality & Tourism Research, vol. 42, no. 1, pp. 26-73.

Wu, H. C., Wong, W. C. J., & Cheng, C. C., (2014b), "An empirical study of behavioural intentions in the food festival: The case of Macau", Asia Pacific Journal of Tourism Research, vol. 19, no. 11, pp. 1278-1305.

Yuksel, A., & Yuksel, F., (2003), "Measurement of tourist satisfaction with restaurant services: A segment-based approach", Journal of Vacation Marketing, vol. 9, no. 1, pp. 52-68.

Zeithaml, V. A., Berry, L. L., & Parasuramam, A., (1996), "The behavioural consequences of service quality", Journal of Marketing, vol. 60, no. 2, pp. 31-46.

Zeithaml, V. A., & Bitner, M. J., (1996), Services marketing, McGraw-Hill, New York.

Zheng, M. C., (2014), "How airport users luggage affects their perception of seat design at airports", Journal of Asian Architecture and Building Engineering, vol. 13, no. 1, pp. 141-148.

Kian Yeik Koay

Department of Management, Monash University Malaysia, Malaysia

Kim Leng Khoo

Department of Marketing, Sunway University, Malaysia

Patrick Chin-Hooi Soh

Department of Management, Multimedia University, Malaysia

DOI: 10.14707/ajbr.190067
Table 1: Demographics

Item               Count  Percentage

Younger than 21     92    36.4
21 to 25            86    34.0
26 to 30            43    17.0
31 to 35            14     5.5
36 to 40             7     2.8
Older than 40        4     1.6
Missing Gender       7     2.8
Male                81    32.0
Female             165    65.2
Missing Ethnicity    7     2.8
Malay               24     9.5
Chinese            216    85.4
Indian               1     0.4
Others               4     1.6
Missing              8     3.2

Table 2: Measurement Model

Constructs        Items

                  AC1: Sufficient lighting in lobby
Ambience          AC2: Sufficient lighting in rooms
(L&T)             AC3: The switch for adjusting lighting in rooms
                  helps to enhance the atmosphere
                  AC4: Temperature inside the rooms is appropriate
Ambience          AM1: Rooms are always full of tobacco smell (r)
(A&N)             AM2: Air quality is bad in rooms (r)
                  AM3: Insufficient sound arrester (noise barriers)
                  among rooms (r)
                  CL1: Lobby is clean
Cleanliness       CL2: Facilities inside the rooms are clean
                  CL3: Toilet is clean
                  WOM1: I would say positive things about company X to
                  other people.
Word-of-          WOM2: If a friend were to seek my advice about
Mouth             Karaoke, I would recommend company X.
                  WOM3: I would post positive things online about
                  company X.
                  WOM4: I would write a positive review online about
                  company X.
                  ESQ1: Service employees are friendly and polite
Employee Service  ESQ2: Service employees provide prompt services
Quality           ESQ3: Service employees are competent
                  ESQ4: Service employees are never too busy to help me
                  FC1: Many new songs
Functionality     FC2: New songs are available quickly
                  FC3: Variety of songs for me to choose
                  FC4: The karaoke system is user-friendly
                  FC5: The speakers produce high-quality sound
                  FC6: Tone quality of microphones is good
                  IM1: Company X is stable and firmly established
Corporate         IM2: Company X is innovative and forward-looking
Image             IM3: Company X has a social contribution for society
                  IM4: Company X is a leading firm in the KTV sector
                  IM5: Company X has a positive image
Revisit           RV1: I will visit company X in the future
Intention         RV2: I will continue singing at company X in the
                  SL1: Sufficient seats inside the rooms
                  SL2: Layout of rooms is convenient to customers
Spatial           SL3: Size of room assigned is large enough for the
Layout            numbers of customers
                  SL4: Size of television screen inside the rooms is
                  SL5: Table size and height inside the rooms is
                  SL6: Seats in rooms are very comfortable
Signs and         SS1: Sufficient signs / route signs (e.g. Toilet and
                  exit signs)
Symbols           SS2: Signs / route signs can be easily understood
Customer          SAT1: Overall, I am satisfied with my experience at
                  company X
Satisfaction      SAT2: My decision to visit company X was a wise one
                  SAT3: As a whole, I have really enjoyed myself at
                  company X

                            Cronbach's  Composite    Variance
Constructs        Loadings  Alpha       Reliability  Extracted (AVE)

Ambience          0.863                              0.641
(L&T)             0.798     0.798       0.834
Ambience          0.928                              0.631
(A&N)             0.907     0.803       0.872
                  0.841                              0.680
Cleanliness       0.861     0.763       0.864
Word-of-          0.888                              0.758
Mouth                       0.895       0.926
                  0.874                              0.788
Employee Service  0.927     0.909       0.937
Quality           0.925
                  0.682                              0.521
Functionality     0.744     0.819       0.867
Corporate         0.860                              0.715
Image             0.843     0.900       0.926
                  0.823                              0.942
Revisit           0.970     0.938       0.970
Intention         0.971
Spatial           0.803                              0.627
Layout                      0.881       0.910
                  0.812                              0.903
Signs and         0.927     0.898       0.949
Symbols           0.972
Customer          0.904                              0.846
Satisfaction      0.925     0.909       0.943

Table 3: Discriminant Validity

Fornell-Larcker Criterion
Constructs                   Mean   STD    1       2      3      4

1. Ambience (A&N)            3.117  1.177   0.801
2. Ambience (L&T)            3.893  0.673   0.018  0.794
3. Employee Service Quality  3.614  0.841   0.077  0.375  0.888
4. Functionality             3.577  0.703   0.137  0.440  0.539  0.722
5. Corporate Image           3.738  0.621   0.061  0.348  0.500  0.564
6. Word-of-Mouth             3.837  0.684   0.113  0.383  0.545  0.558
7. Revisit intention         4.101  0.765   0.143  0.388  0.456  0.499
8. Satisfaction              3.863  0.725   0.066  0.426  0.586  0.604
9. Signs and symbols         3.835  0.784  -0.028  0.353  0.235  0.258
10. Spatial Layout           3.825  0.693   0.172  0.553  0.439  0.560
11. Cleanliness              3.859  0.730   0.176  0.500  0.500  0.583

Fornell-Larcker Criterion
Constructs                   5      6      7      8      9      10

1. Ambience (A&N)
2. Ambience (L&T)
3. Employee Service Quality
4. Functionality
5. Corporate Image           0.845
6. Word-of-Mouth             0.666  0.871
7. Revisit intention         0.599  0.671  0.970
8. Satisfaction              0.767  0.760  0.749  0.920
9. Signs and symbols         0.237  0.244  0.300  0.304  0.950
10. Spatial Layout           0.528  0.526  0.509  0.556  0.224  0.792
11. Cleanliness              0.462  0.463  0.415  0.467  0.176  0.584

Fornell-Larcker Criterion
Constructs                   11

1. Ambience (A&N)
2. Ambience (L&T)
3. Employee Service Quality
4. Functionality
5. Corporate Image
6. Word-of-Mouth
7. Revisit intention
8. Satisfaction
9. Signs and symbols
10. Spatial Layout
11. Cleanliness              0.824

Note: Values on the diagonal represent the square root of the AVE
while the off-diagonals are correlations.

HTMT Criterion
Constructs                   1      2      3      4      5      6

1. Ambience (A&N)
2. Ambience (L&T)            0.076
3. Employee Service Quality  0.104  0.440
4. Functionality             0.152  0.548  0.613
5. Corporate Image           0.064  0.404  0.552  0.630
6. Word-of-Mouth             0.109  0.441  0.598  0.619  0.729
7. Revisit intention         0.176  0.443  0.494  0.540  0.650  0.714
8. Customer Satisfaction     0.068  0.495  0.644  0.684  0.845  0.827
9. Signs and Symbols         0.067  0.393  0.252  0.280  0.253  0.254
10. Spatial Layout           0.164  0.663  0.490  0.642  0.590  0.583
11. Cleanliness              0.183  0.631  0.597  0.725  0.556  0.551

HTMT Criterion
Constructs                   7      8      9      10     11

1. Ambience (A&N)
2. Ambience (L&T)
3. Employee Service Quality
4. Functionality
5. Corporate Image
6. Word-of-Mouth
7. Revisit intention
8. Customer Satisfaction     0.810
9. Signs and Symbols         0.309  0.320
10. Spatial Layout           0.556  0.617  0.244
11. Cleanliness              0.486  0.557  0.197  0.707

Table 4: Effects on Endogenous Variables

     Relationships                                      Beta    Std

 H1  Ambience (L&T) -> Customer Satisfaction             0.028  0.068
 H2  Ambience (A&N) -> Customer Satisfaction            -0.033  0.057
 H3  Cleanliness -> Customer Satisfaction               -0.016  0.071
 H4  Functionality -> Customer Satisfaction              0.279  0.060
 H5  Spatial Layout -> Customer Satisfaction             0.243  0.059
 H6  Signs and Symbols -> Customer Satisfaction          0.097  0.051
 H7  Employee Service Quality -> Customer Satisfaction   0.306  0.059
 H8  Customer Satisfaction -> Corporate Image            0.767  0.028
 H9  Customer Satisfaction -> Revisit Intention          0.749  0.033
H10  Customer Satisfaction -> Word-of-Mouth              0.760  0.029

     t values    BCCI 5.0%    p values  Decision       [f.sup.2]

 H1   0.419    -0.088  0.132  0.338     Not Supported  0.001
 H2   0.586    -0.149  0.042  0.279     Not Supported  0.002
 H3   0.217    -0.123  0.112  0.414     Not Supported  0.000
 H4   4.670     0.168  0.369  0.000     Supported      0.084
 H5   4.086     0.147  0.339  0.000     Supported      0.063
 H6   1.900     0.014  0.184  0.029     Supported      0.017
 H7   5.155     0.212  0.406  0.000     Supported      0.123
 H8  27.223     0.716  0.809  0.000     Supported
 H9  22.807     0.689  0.798  0.000     Supported
H10  26.069     0.706  0.803  0.000     Supported

Table 5: A Post-Hoc Mediation Analysis

                                   Indirect  Std    t-value
                                   Effect    Error

Ambience (A&N)-> Customer
Satisfaction -> Corporate Image    -0.025    0.043  0.587
Ambience (L&T)-> Customer
Satisfaction -> Corporate Image     0.022    0.052  0.422
Employee Service Quality ->
Customer Satisfaction ->
Corporate Image                     0.234    0.047  5.012
Functionality -> Customer
Satisfaction -> Corporate Image     0.214    0.047  4.531
Signs and Symbols -> Customer
Satisfaction -> Corporate Image     0.075    0.040  1.881
Spatial Layout -> Customer
Satisfaction -> Corporate Image     0.186    0.046  4.062
Cleanliness -> Customer
Satisfaction -> Corporate Image    -0.012    0.056  0.212
Ambience (A&N)-> Customer
Satisfaction -> WOM                -0.025    0.043  0.589
Ambience (L&T)-> Customer
Satisfaction -> WOM                 0.022    0.051  0.420
Employee Service Quality ->
Customer Satisfaction -> WOM        0.232    0.048  4.853
Functionality -> Customer
Satisfaction -> WOM                 0.212    0.048  4.464
Signs and Symbols ->
Customer Satisfaction -> WOM        0.074    0.039  1.884
Spatial Layout -> Customer
Satisfaction -> WOM                 0.185    0.045  4.064
Cleanliness -> Customer
Satisfaction -> WOM                -0.012    0.056  0.211
Ambience (A&N)-> Customer
Satisfaction -> Revisit Intention  -0.025    0.042  0.591
Ambience (L&T)-> Customer
Satisfaction -> Revisit Intention   0.021    0.050  0.423
Employee Service Quality ->
Customer Satisfaction ->
Revisit Intention                   0.229    0.047  4.879
Functionality -> Customer
Satisfaction -> Revisit Intention   0.209    0.046  4.520
Signs and Symbols -> Customer
Satisfaction -> Revisit Intention   0.073    0.039  1.887
Spatial Layout -> Customer
Satisfaction -> Revisit Intention   0.182    0.045  4.041
Cleanliness -> Customer
Satisfaction -> Revisit Intention  -0.012    0.055  0.212

                                   95% Bootstrap  Mediation
                                   BCI            effect?

Ambience (A&N)-> Customer
Satisfaction -> Corporate Image    -0.128  0.044  No
Ambience (L&T)-> Customer
Satisfaction -> Corporate Image    -0.088  0.115  No
Employee Service Quality ->
Customer Satisfaction ->
Corporate Image                     0.147  0.328  Yes
Functionality -> Customer
Satisfaction -> Corporate Image     0.117  0.301  Yes
Signs and Symbols -> Customer
Satisfaction -> Corporate Image     0.000  0.157  Yes
Spatial Layout -> Customer
Satisfaction -> Corporate Image     0.103  0.283  Yes
Cleanliness -> Customer
Satisfaction -> Corporate Image    -0.112  0.110  No
Ambience (A&N)-> Customer
Satisfaction -> WOM                -0.123  0.044  No
Ambience (L&T)-> Customer
Satisfaction -> WOM                -0.087  0.115  No
Employee Service Quality ->
Customer Satisfaction -> WOM        0.143  0.331  Yes
Functionality -> Customer
Satisfaction -> WOM                 0.114  0.301  Yes
Signs and Symbols ->
Customer Satisfaction -> WOM        0.000  0.155  Yes
Spatial Layout -> Customer
Satisfaction -> WOM                 0.102  0.284  Yes
Cleanliness -> Customer
Satisfaction -> WOM                -0.112  0.107  No
Ambience (A&N)-> Customer
Satisfaction -> Revisit Intention  -0.121  0.044  No
Ambience (L&T)-> Customer
Satisfaction -> Revisit Intention  -0.086  0.111  No
Employee Service Quality ->
Customer Satisfaction ->
Revisit Intention                   0.142  0.327  Yes
Functionality -> Customer
Satisfaction -> Revisit Intention   0.114  0.296  Yes
Signs and Symbols -> Customer
Satisfaction -> Revisit Intention   0.000  0.152  Yes
Spatial Layout -> Customer
Satisfaction -> Revisit Intention   0.100  0.276  Yes
Cleanliness -> Customer
Satisfaction -> Revisit Intention  -0.109  0.106  No

Table 6: PLS Prediction Assessment

Construct Prediction Summary
              RMSE   MAE    [Q.sup.2]

Corporate     0.481  0.364  0.306
Word-of-      0.467  0.358  0.337
Revisit       0.493  0.377  0.225
Customer      0.570  0.432  0.434
                     PLS                      LM
              RMSE   MAE    [Q.sup.2]  RMSE   MAE    [Q.sup.2]
IM2           0.632  0.517  0.261      0.669  0.539  0.173
IM5           0.611  0.477  0.272      0.646  0.491  0.186
IM1           0.611  0.479  0.302      0.650  0.511  0.210
IM4           0.641  0.506  0.259      0.687  0.527  0.149
IM3           0.642  0.517  0.269      0.667  0.529  0.211
WOM4          0.725  0.577  0.242      0.776  0.588  0.132
WOM1          0.604  0.474  0.351      0.631  0.486  0.291
WOM2          0.600  0.460  0.362      0.639  0.478  0.276
WOM3          0.732  0.584  0.236      0.787  0.620  0.118
RV1           0.662  0.517  0.318      0.676  0.516  0.288
RV2           0.645  0.504  0.314      0.671  0.514  0.258
Sat3          0.618  0.480  0.399      0.646  0.495  0.344
Sat2          0.641  0.492  0.392      0.681  0.518  0.315
Sat1          0.572  0.447  0.419      0.621  0.487  0.315

Construct Prediction Summary

              RMSE    MAE     [Q.sup.2]
IM2           -0.037  -0.022  0.088
IM5           -0.035  -0.014  0.086
IM1           -0.039  -0.032  0.092
IM4           -0.046  -0.021  0.110
IM3           -0.025  -0.012  0.058
WOM4          -0.051  -0.011  0.110
WOM1          -0.027  -0.012  0.060
WOM2          -0.039  -0.018  0.086
WOM3          -0.055  -0.036  0.118
RV1           -0.014   0.001  0.030
RV2           -0.026  -0.010  0.056
Sat3          -0.028  -0.015  0.055
Sat2          -0.040  -0.026  0.077
Sat1          -0.049  -0.040  0.104

IM, corporate image; WOM: word-of-mouth; RV, revisit intention: CS,
customer satisfaction; RMSE, root mean square error; MAE, mean
absolute error; PLS, partial least squares path model; LM, linear
regression model

Table 7: IPMA Analysis

Constructs                Importance  Performance

Ambience L&T               0.028      72.319
Ambience A&N              -0.033      52.923
Employee Service Quality   0.306      65.350
Functionality              0.279      64.430
Signs and symbols          0.097      70.872
Spatial Layout             0.243      70.634
Cleanliness               -0.016      71.465
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Author:Koay, Kian Yeik; Khoo, Kim Leng; Soh, Patrick Chin-Hooi
Publication:Asian Journal of Business Research
Geographic Code:9MALA
Date:Dec 1, 2019
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