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.
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 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 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.
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).
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).
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.
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.
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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
Table 1: Demographics Item Count Percentage Age 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 future 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 appropriate SL5: Table size and height inside the rooms is appropriate 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 Average Cronbach's Composite Variance Constructs Loadings Alpha Reliability Extracted (AVE) 0.812 Ambience 0.863 0.641 (L&T) 0.798 0.798 0.834 0.694 Ambience 0.928 0.631 (A&N) 0.907 0.803 0.872 0.489 0.841 0.680 Cleanliness 0.861 0.763 0.864 0.768 0.898 Word-of- 0.888 0.758 Mouth 0.895 0.926 0.870 0.824 0.874 0.788 Employee Service 0.927 0.909 0.937 Quality 0.925 0.821 0.682 0.521 Functionality 0.744 0.819 0.867 0.711 0.679 0.759 0.750 0.871 Corporate 0.860 0.715 Image 0.843 0.900 0.926 0.830 0.823 0.942 Revisit 0.970 0.938 0.970 Intention 0.971 0.839 0.810 Spatial 0.803 0.627 Layout 0.881 0.910 0.744 0.741 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 0.931 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 Error 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 Image Word-of- 0.467 0.358 0.337 mouth Revisit 0.493 0.377 0.225 Intention Customer 0.570 0.432 0.434 Satisfaction 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 Corporate Image Word-of- mouth Revisit Intention Customer Satisfaction PLS-LM 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|
|Date:||Dec 1, 2019|
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