Received: 30th October 2022 Review: 12th December 2022 Accepted: 16th January 2023
http://doi.org/10.53908/NMMR.310103
Abstract
Purpose – The study examines the impact of customer experience on revisit intention and further studies the moderating influence of the purpose of travel on the relationship between customer experience and revisit intentions.
Design/Methodology/Approach – The data were collected, using a convenient sampling method, from 230 customers/guests from three major chain hotels, Radisson, Taj, and Oberoi, located in two different tourist regions of Jammu and Kashmir, and Delhi. After reliability and validity analysis, the data were analyzed using exploratory factor analysis, confirmatory factor analysis, and structural equation modelling using SPSS and AMOS.
Findings – The findings suggest that customer experience influences revisit intentions. The study establishes positive and significant relationships among the education, entertainment, and esthetic experience, but the escapist customer experience dimension does not have a substantial impact on revisit intention, the study also reveals that the relationship between customer experience and revisit intention is contingent upon the purpose of travel.
Practical Implications – This study extended the role of customer experience and provided directions to hospitality service providers in creating and enhancing customer experience to sustain competitive advantage. Hence, managers should focus on customer experience dimensions to improve customers’ revisit intention.
Originality/Value – Unlike previous studies, the present study expands their understanding of the experience economy by examining customers’ experiences operating together with multiple dimensions of their experience at hotels to develop their loyal behavior by taking into consideration the moderating role of the purpose of travel.Keywords: Customer Experience, Education Experience, Entertainment Experience, Escapist Experience, Esthetic Experience, Purpose of Travel, Revisit Intention.
http://doi.org/10.53908/NMMR.310103
1. Introduction
The Indian hospitality industry is one of the significant segments of the services sector. The Indian hotel market, including domestic, inbound, and outbound, was estimated at US$ 32 billion in FY20 and is expected to reach US$ 52 billion by FY27, driven by increased travel demand. The hotel industry in India is expected to reach a value of INR 1,210 billion by the end of 2023, expanding at a compound annual growth rate of 13% during the 2018-2023 period, owing to the higher level of the arrival of foreign tourists.
Indian hotels are innovating to survive the competition from domestic and international chains. The Indian hotel chains have diversified from exclusive chains to serving the middle and lower-budget markets. Thus, Indian hotels have become competitive, innovative, and highly customer-centric, successfully establishing their place in global markets. Indian hotels have established world-class brands through superior service and guest experience. Hotels like ITC, Taj, Oberoi, and Radisson other hotel chains have not only been awarded consistently by international agencies for providing superior services and guest satisfaction.
The hospitality industry needs to deliver a fascinating customer experience to make a mark among customers, and this fascinating customer experience is the key driver of their satisfaction. The concept started gaining increasing interest among academicians and practitioners, mainly because of the shift from a service-based economy to an experience-based economy (Kim et al., 2008; Pine & Gilmore, 1999; Verhoef et al., 2009). Experiences create a unique value for customers, are hard to imitate by competitors, and strongly affect customers’ satisfaction, loyalty, and recommendation behaviors (Berry et al., 2002; Pine & Gilmore, 1999). Even though customer experiences have attracted considerable attention in recent years, creating and managing memorable experiences are still among the significant challenges for the hospitality industry (Walls et al., 2011).
Therefore, the primary objective of this study is to offer a more comprehensive model of customer experience management and validate it through research conducted in the hotel industry. This study aims to assess customer experience dimensions at a hotel and its effects on their post-consumption evaluations. The present study expands their understanding of the experience economy by examining customers’ memories operating together with multiple dimensions of their hotel experience to develop their loyal behaviour.
2. Objectives of Study
- To examine the impact of customer experience on revisit intention in the hospitality sector.
- To examine the moderating effect of the purpose of travel on the relationship between customer experience and revisit intention.
3. Significance of the Study
Even though there are many conceptual studies on experiences, customer experience theories have only been verified by a few empirical studies. This explains insufficient clarification about factors influencing customer experiences. Previous literature on customer experiences might be considered complex, and subjective. Hence fails to develop on previous studies and bridge the gap between literature and practice. Different views exist on the definition, antecedents, variables, measurement, and impacts of customer experiences. Without a clear direction on experience items and their contribution to organizational performance, strategies established to create desired customer experiences might be ineffective (Kim & Brown, 2012). This study attempts to fill this gap and examine customer experiences regarding customers’ behavioral outcomes in the hospitality industry. Although previous studies in the context of hospitality and tourism have been instrumental in advancing our understanding of the different aspects of customer experience management, more research is required because the prior studies were either conceptual (Adhikari & Bhattacharya, 2016; Tung & Ritchie, 2011; Walls et al., 2011) or qualitative (Huang et al., 2014; Klaus & Maklan, 2013; Lindberg & Østergaard, 2015; Stein & Ramaseshan, 2016; Walls et al., 2011), making it significant to further research on customer experience, particularly in a hospitality sector.
4. Review of Literature
4.1 Customer Experience Management in the Hospitality sector
Hospitality sector research is drawn from marketing and management studies; therefore, in the analysis of experience, both service marketing and hospitality management literature are refereed. In examining the customer experience process across different sectors, Johnston and Kong (2011) found that experience is significant to customers and results in cost reductions, improved efficiency, and a better experience for staff. In the hospitality industry, customer experience design is considered a strategic means to obtain differentiation and long-term competitive advantage (Bergs et al., 2020).
The hospitality industry is shifting its focus from a product-centric, physical-asset- intensive firm to a customer-centred, experience-centred firm (Knutson et al., 2006). Researchers and managers have determined that customer experience management is vital for the hospitality sector, and hotel managers consider customer experiment management a prime goal (Bharwani & Jauhari, 2013). Customer experience
management is even more significant in hospitality and tourism research due to the experiential nature of the hospitality and tourism industry.
4.2 Customer Experience and Revisit Intention
The hospitality and tourism literature has increasingly emphasized the significance of the customer experience in creating strong customer loyalty rather than merely providing an experience to customers (Prebensen & Rosengren, 2016). A holistic view of customer experience is highly valued in hospitality and tourism research because most experiences comprise multiple stages: pre-experience, during the experience, and post-experience. Larsen (2007) listed the dynamic method of the tourism experience, which includes visitors’ expectations before, during, and after the trip, impacting their revisit intentions for the consecutive trip. Organizations usually manage customer experience by delineating and striving for the customer journey (Lemon & Verhoef, 2016; McColl-Kennedy et al., 2019; Voorhees et al., 2017). Palmer (2010) confirms that by employing customer experience management strategies, an organization gains a sustainable competitive advantage and becomes successful. Exceptional customer experiences lead to positive outcomes like higher customer satisfaction, frequent shopping, and higher profits (Grewal et al., 2009; Klaus & Maklan, 2013; Sharma & Chaubey, 2014). The main consequences of customer experience management are customer satisfaction, customer value, and revisit intention (Luturlean & Anggadwita, 2015). Therefore, the following assumption was proposed:
H1: Customer experience impacts revisit intention positively.
Revisit intention has been recognized as the essential component for the survival and growth of business in the hospitality sector. According to Gronholdt et al. (2000) and Baker and Crompton (2000), revisit intention is demonstrated as the willingness of tourists to revisit a destination; this behavior is considered an expression of customer loyalty. Revisit intention is a significant marketing concept to assess travellers’ loyalty behaviors (Hu, 2003). Thus, this research describes revisit intention as the likelihood and willingness of tourists to revisit the hotel. Revisit intention originates from guests’ travel experience (Guest, 1995) and intentions to return to the experienced tourist attraction (Baker & Crompton, 2000). Chang et al. (2014) asserted that the quality of the customer experience is the most significant antecedent of revisit intention. Besides, customers exposed to a memorable experience display a favorable behavioral intention and become loyal customers, ultimately leading to revisit intention (Boulding et al., 1993; Reichheld & Sasser, 1990). Qu (2017) posited a significant relationship between education, entertainment, esthetic, escapism experience, and revisit intention. Radder and Han (2015) revealed that edutainment is the experience between education and entertainment, and is the most critical experience dimension in determining customers’ revisit intention.
Quadri (2012) demonstrated that esthetic and escapism experiences are crucial for building revisit intention in a setting wine trail. In addition, Baker (2016) found that the vital customer experience elements for increasing return intention are esthetic and educational experiences. The pleasant education, entertainment, esthetic and escapism environments make the hotel industry an attractive realm to explore experiences. Customers who experience a beautiful atmosphere and participate in exciting shows and activities increase their revisit intention. Hence, the following hypotheses are proposed:
H1 a: Education experience is positively related to revisit intention.
H1 b: Entertainment experience is positively related to revisit intention.
H1 c: Esthetic experience is positively related to revisit intention.
H1 d: Escapist experience is positively related to revisit intention.
4.3 The Role of Purpose of Travel as Moderator
The influence of customer characteristics on the significance of customer experience has been well established in adopting this view for our study of the hotel industry, among the many factors that potentially moderate the relationship, this study expects the purpose of travel (i.e., business and leisure) to be exclusively influential (Ringle et al., 2011). Rajaguru and Hassanli, (2018) suggest that hotels generally meet guests’ needs with different travel purposes. Furthermore, Liu et al. (2013); Radder and Wang (2006) added that leisure and business guests’ expectations of hotel attributes are more likely to differ.
The customer experience is intrinsically personal and biased (Pine & Gilmore, 1998). The customer experience is influenced by various factors, including those directly controlled by the service provider (Huang & Hsu, 2010). Previous studies revealed that trip-related factors like the purpose of travel also influence the customer experience (Barros & Machado, 2010; Huang & Hsu, 2010; Light, 1996; Wong & Kwong, 2004). The guest’s evaluation of hotel selection and service quality exhibit differences in the purpose of travel (Chu & Choi, 2000; Kashyap & Bojanic, 2000; Lewis, 1985). Walls et al. (2011) demonstrate that different travellers often introduce the predictions of their hotel experience by mentioning it to be situational. Previous literature appears to lack a combined and proven set of trip-related factors like the purpose of travel that influence the hotel stay experience, trip-related factors were found to play a significant role in affecting the identified dimensions and customers’ experience in this study. The previous research identified the purpose of travel as one of the critical determinants of how guests interpret their hotel stay experiences. Depending on the purpose of the travel, such as business or leisure, their expectations of experiences
vary. Pine and Gilmore (1999); Schmitt (1999) argue that the economy is transforming into an experience-based economy, several researchers stated that they sometimes want different degrees of experiences during their hotel stays.
It is evident from different research findings that, depending on customers’ characteristics, such as trip-related factors, guests have different experience sensitivities and needs (Walls et al., 2011). The trip-related factors influence an individual’s response to an environment, such as the reason for being in the particular environment (Russell & Snodgrass, 1987). These plans and purposes frequently change regardless of an individual’s personality traits (Bitner, 1992). Further, because of these unique differences, guests may have differing levels of interest in experiences while staying in hotels. These results have demonstrated that the purpose of travel plays a significant role in shaping hotel guests’ customer experiences. In the hospitality sector, Kim et al. (2012) explored the impact of memorable experience components on loyalty intention. Their results reveal that memorable experience components influence guests’ revisit intention strongly. Xu & Chan (2010) pointed out that the quality of customer experiences depends on hotel loyalty. Furthermore, Hosany and Witham (2010) assert that experience positively relates to customers’ intention to recommend. Hence, concluded studies agree that experience influences revisit intention Zhang et al. (2017), which is contingent upon the purpose of travel. Therefore, the following assumption was proposed:
H2: The relationship between customer experience and revisit intention is contingent upon the purpose of travel.
5. Proposed Model
By integrating the hypotheses, this study has developed a conceptual model (Figure 1) that demonstrates the effects of customer experience on the revisit intention of three chain hotels.
(Figure 1: Conceptual framework)
6. Methodology
6.1 Research Instrument
To ensure validity, all the measurement items were taken from previous studies; however, minor modifications to the statements were made to make them adequate for the present study. The customer experience scale contains 16 items related to four dimensions viz., education experience (4 statements), entertainment experience (4 statements), esthetic experience (4 statements), escapism experience (4 statements) based on the scale of previous researchers (Hosany & Witham, 2010). Four items adapted from (Kim et al., 2009; 2020) were used to measure revisit intentions, and the moderator purpose of travel was measured as a categorical variable, all of these measurement items are shown in table 1. This study used a 5-point Likert-type where 1 = strongly disagree, and 5 = strongly agree.
6.2 Data analysis
The population approach for this study was the hotel guests who visited the hotel. These hotel guests were the sample representatives. They were selected using convenience sampling. The scope of this study was limited mainly to three chain hotels, namely Radisson, Taj, and Oberoi, in Jammu & Kashmir and Delhi. This empirical research comprised two stages. A pilot study was conducted to test the survey questionnaire in the first stage. In the second stage, data was collected from 230 respondents, out of which 200 questionnaires completed in all aspects were used for further analysis. A standardized three-step process was employed to test the proposed conceptual model. The study first applied SPSS version 26 to process the descriptive statistics and reliability analysis on the collected data and assess the internal consistency of the constructs. As proposed by Anderson and Gerbing (1988), this study investigated the properties of measurement scales for convergent validity and discriminant validity and constructed composite reliability by confirmatory factor analysis (CFA), followed by the application of structural equation modelling (SEM) to verify the path relationships of dimensions of customer experience and revisit intentions, and hierarchical regression analysis was employed to examine the moderating effect of the purpose of travel. The software used for CFA and SEM was AMOS version 24.
6.3 Measurement model
This study followed a two-step factor analysis followed by structural equation modelling. Exploratory factor analysis (EFA) was performed with the principal component analysis (PCA) method and the varimax rotation for extracting factors. To assess the appropriateness of the data for factor analysis, this study used Bartlett’s sphericity test and the Kaiser–Mayer–Olkin (KMO) measure of sampling adequacy. The Bartlett’s sphericity test achieved statistical significance (p = 0.000 < 0.05) Bartlett (1954), and the KMO value was .942, which suggested significant sampling adequacy (Kaiser, 1974). The value of the Kaiser-Meyer-Olkin (KMO) statistic must be at least 0.60 (Tabachnick & Fidell, 2001). The two dimensions explained 70.58% of the total variance, which exceeded the commonly accepted value of 60% in social science research (Hair et al., 2006). After the exploratory factor analysis, confirmatory factor analysis was conducted, and five items, EDU4, ENT2, EST4, ESC1, and RI3, were deleted based on standardized residual covariances to improve the model fit and the validity analysis.
Table 1 and 2 appear at the end of the article
Table 1 reveals that the chi-square value (χ2 = 241.132) is significant, and the ratio of the value to degrees of freedom (χ2 /df = 2.043) is less than the cut-off value is 3, as suggested by (Bagozzi & Yi, 1988). Furthermore, the comparative- fit index (CFI = .946) and tucker-lewis index (TLI = .934) are more significant than the recommended value of 0.9. The root-mean-square error of approximation (RMSEA = 0.072) is, which is less than .08 (Hair et al., 2006). Therefore, the model fits the data quite well. The results showed that all indicators had relatively high standardized factor loadings on their constructs (values ranged from .62 to .87). They were all significant at the level of p < .05, recommending that the specified indicators were sufficient in their representation of the constructs. The average variance extracted (AVE) for the customer experience construct was 0.603, and revisit intention was 0.674 exceeding the minimum criterion of .50, indicating that the variance was explained reasonably by the constructs (Hair et al., 2006). These results suggested that the measurement items had moderate to high reliability and validity. Nunnally and Bernstein (1994) stated that cronbach’s alpha should be higher than 0.7 for adequate internal consistency. These factor loadings values exceed the recommended threshold of 0.70 (Hair et al., 2006). Table 2 shows the AVE values of each construct and the squared correlation coefficients between constructs. Finally, the convergent validity analysis results reveal that the average variance extracted (AVE) value has to be higher than 0.5 according to (Fornell & Larcker, 1981), but when composite reliability is above 0.6. AVE must be greater than MSV, and the square root of AVE should be greater than inter-construct correlations. MaxR(H) should be greater than > 0.8. To analyze the discriminant validity, the square root of the AVE was compared to all inter-construct correlations. The AVE’s square root, shown on the diagonals, is greater than the other inter-construct correlations. The above-stated aspects met the reliability and validity, making the “model fit”.
6.4 Structural Model
A structural model was estimated to evaluate the hypothesis. Firstly, the goodness- of-fit statistics of the proposed model were estimated. The chi-square value of the
model (χ2 /df = 2.07, p = 0.00) and other goodness of fit indices (RMSEA = 0.065; CFI =0.912; TLI = 0.904) revealed that the model fit the data reasonably well hence, this model was kept for further analysis. The results of hypothesis testing indicate that customer experience (β = 0.132, P < 0.01), educational experience (β = 0.154, P < 0.01), entertainment experience (β = 0.265, P < 0.05), and esthetic experience (β = 0.171, P < 0.01) has a significant and positive relation with revisit intention. Hence, H1, H1a, H1b, and H1c are accepted. Escapist experience has no significant relationship with revisit intention (β = 0.075, P < 0.05). Hence, H1d is not supported, and the results are consistent (Paisri et al., 2022). Furthermore, H2 tests the relationship between the customer experience and revisit intention with the purpose of travel as the moderator with (β = 0.202, P < 0.01) therefore, H2 is supported.
Note: ** = p < 0.01, * = p < 0.05
CE: Customer Experience; EDU; Education Experience; ENT: Entertainment Experience; EST: Esthetic Experience; ESC: Escapist Experience; RI: Revisit Intention.
(Figure 2: Structural Model for Hypothesis Testing)
The study aimed to determine whether the relationship between the customer experience and revisit intention was affected by the purpose of travel. To make this observation, hierarchical regression analysis was used. The method recommended by Baron and Kenny (1986) was used for the analysis. According to Holmbeck (2002), moderation can be seen when the interaction between the independent and moderating variables significantly impacts the dependent variable. According to Kim et al. (2003), the moderator variable strengthens, weakens, or modifies the relationship between the independent and dependent variables. The effects of the customer experience on revisit intention were analyzed in the first stage. The variable customer experience is taken as the summation of education experience, entertainment experience, esthetic experience and escapist experience. The first step involved observing how customer experience affected revisit intention. The impact of the purpose of travel on revisit intention was investigated in the following stage. An interaction variable was added to the model in the last phase. The customer experience and purpose of travel variables were standardized before being computed in SPSS to create this interaction variable. As shown in Table 4, the purpose of travel modifies the association between customer experience and revisit intention. The increasing R2 value from model 1 to model 4 suggests the same. Indicating moderation is the fact that both the moderating and the interacting variables have a sizable impact on revisit intention (Aiken, West, and Reno 1991).
Table 4: Moderation effect of Purpose of Travel
|
Steps |
IV |
DV |
Beta Value |
p Value |
R2 Value |
|
Model 1 |
EDU |
RI |
0.358 |
.002 |
0.480 |
|
ENT |
0.686 |
.000 |
|||
|
EST |
0.596 |
.000 |
|||
|
ESC |
.456 |
.027 |
|||
|
Model 2 |
EDU |
RI |
0.267 |
.001 |
0.532 |
|
ENT |
0.473 |
.010 |
|||
|
EST |
0.394 |
.017 |
|||
|
ESC |
0.359 |
.005 |
|||
|
PT |
-0.377 |
.009 |
|||
|
Model 3 |
EDU |
RI |
0.259 |
.001 |
0.578 |
|
ENT |
0.462 |
.000 |
|||
|
EST |
0.368 |
.000 |
|||
|
ESC |
0.343 |
.001 |
|||
|
PT |
-0.345 |
.004 |
|||
|
Model 4 |
EDU |
RI |
0.299 |
.002 |
0.597 |
|
ENT |
0.332 |
.003 |
|||
|
EST |
0.465 |
.010 |
|||
|
ESC |
0.379 |
.015 |
|||
|
PT |
-0.336 |
.001 |
|||
|
Moderator (EDU*ENT*EST*ESC*PT) -0.202 .009 |
|||||
IV: Independent Variable; DV: Dependent Variable; EDU = Education experience; ENT= Entertainment Experience; EST= Esthetic Experience; ESC = Escapist Experience; PT: Purpose of Travel; RI = Revisit Intention.
7. Discussions and Conclusions
This study attempts to bridge the research gap by investigating the effects of customer experience on revisit intention. Previous research examined the impact of customer experience, which affects behavioral intentions through emotions and memories in the tourism context. In contrast, this study proposes a new framework to explain the relationships between customer experience and revisit intention from the customer perspective. The study investigates the generalizability of customer experience, and the revisit intention constructs in the hospitality industry. This study contributes to academic research by expanding the concepts of customer experience dimensions and revisit intention. Moreover, the purpose of travel was found to act as a moderator in the relationship between the dimension of customer experience, and revisit intention. The purpose of travel moderates the impact of the four dimensions of the customer experience. In other words, it controls the relationship. This outcome supports H2, and the relationship between the customer experience and revisit intention is moderated by the purpose of travel. As shown in Table 4, it actually reduces the influence of customer experience on revisit intention. This suggests that if the customers do not have a good experience at the hotel, their intention of revisiting would be reduced.
7.1 Theoretical implications
The study reveals that the dimension of customer experience generates positive revisit intention. The study’s findings regarding the role of customer experience dimensions and revisit intention provide meaningful theoretical implications. First, the esthetic experience appears to be a crucial attraction for guests. A more substantial esthetic dimension impacts the intention to recommend (Alegre & Cladera, 2009; Chi & Qu, 2008; Yoon & Uysal, 2005). Second, the results show that esthetic and education experiences significantly relate to revisit intention. These dimensions of customer experience reflect the community’s way of living, making guests feel satisfied. Previous research has shown that the environment significantly influences guests’ behaviors, increasing the likelihood of the customers revisiting the destination (Wright et al., 2006). Guests participate in a learning experience in the unique culture of hotels, which affects their revisit intention. Hence, esthetic and education experiences should be designed to create memorable experiences, resulting in guests revisiting the hotel. Tung and Ritchie (2011) proposed that customers’ memorable experiences significantly influence their revisit intention. This study addresses the existing gap in research by investigating various dimensions of customer experiences that influence revisit intention in the hospitality industry by considering the moderating role of the purpose of travel.
7.2 Managerial implications
This study contributes to the hospitality industry by helping create memorable customer experiences that stimulate revisit intention. This study provides some recommendations. Firstly, hotel managers should focus on creating educational and esthetic experiences directly influencing revisit intention. The hotels should support cultural learning by promoting the unique local culture and community identity through a learning centre. These activities support creating an educational experience that may affect the spread of public stories via several social media platforms. These aspects should be presented to guests, creating or improving the market landscape. The unique identity and community’s way of life would help guests fully experience the local atmosphere. As a result, the guests want to revisit the destination. The hotel managers should focus on education and esthetic experiences and consider the creation of entertainment and escapist experiences as well. Thus, hotel managers should provide local performing arts, dancing, music, and other activities that allow guests to participate in a different lifestyle. These unique performances and activities would help guests to fully enjoy their experience, inducing feelings of worthwhileness. Secondly, the hotel managers should organize tourism activities in their hotel to allow guests to post pictures, and share or send messages that reflect the cultural identity, beautiful landscape, and unique performances and activities. All these elements can stimulate the customer’s desire to revisit the same hotel and recommend the same to their acquaintances.
7.3 Limitation and Future Research
First, the extant literature on customer experience and its dimension is primarily addressed in the context of developed countries. The study of customer experience, and revisit intention in those countries may yield different results due to the effect of cultural factors. However, this study suffered some limitations. In addition, future studies should address the firm perspectives to obtain comprehensive results and further contribute to customer experience management. Second, this study only addressed the relationship between customer experience and revisit intention other variables of loyalty behavior could be analyzed in future studies. Finally, this study was conducted in the context of two states, Jammu & Kashmir and Delhi, and only three chain hotels therefore, the results thereof may lack generalization. Future research should test the proposed conceptual framework in other hospitality and tourism industries or other industrial sectors related to experience creation.
Surbhi Choudhary, Research Scholar, University of Jammu, The Business School, Jammu, India 0000-0002-9665-3641
Vinay Chauhan, Professor, University of Jammu, The Business School, Jammu, India 0000-0002-5252-9550
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Table 1: Exploratory and Confirmatory Factor Analysis (N=200)
|
Constructs |
Statements |
Factor Load- ings |
Regression Weights |
Cronbachα |
|
Customer Experience |
Education Experience |
|
|
.877 |
|
EDU1 The experience has made me more knowl- edgeable about this hotel |
.794 |
.77 |
||
|
EDU2 I learned a lot during my experience visit- ing this hotel |
.762 |
.74 |
||
|
EDU3 It stimulated my curiosity to learn new things here |
.830 |
.83 |
||
|
EDU4 It was a real learning experience here |
.872 |
—- |
||
|
Entertainment Experience |
|
|
.863 |
|
|
ENT1 Activities at the hotel were amusing to watch and perform |
.735 |
.72 |
||
|
ENT2 Activities at the hotel were captivating to watch and perform |
.808 |
—- |
||
|
ENT3 Activities at the hotel were entertaining to watch and perform |
.699 |
.87 |
||
|
ENT4 Activities at the hotel were fun to watch and perform |
.790 |
.77 |
||
|
Esthetic Experience |
|
|
.881 |
|
|
EST1 I felt a real sense of harmony in this hotel |
.793 |
.76 |
||
|
EST2 Just being here was very pleasant |
.788 |
.71 |
||
|
EST3 The setting was very attractive in this hotel |
.793 |
.77 |
||
|
EST4 The setting really showed attention to de- sign detail |
.862 |
—- |
||
|
Escapism Experience |
|
|
.880 |
|
|
ESC1 I felt I played a different character here |
.836 |
—- |
||
|
ESC2 I felt like I was living in a different time or place |
.772 |
.76 |
||
|
ESC3 The experience here let me imagine being someone else |
.785 |
.77 |
||
|
ESC4 I totally forgot about my daily routine |
.832 |
.62 |
|
Revisit In- tention |
RI1 I consider this hotel as my first choice com- pared to other hotels. |
.871 |
.81 |
.864 |
|
RI2 I have a strong intention to visit this hotel again |
.824 |
.79 |
||
|
RI3 I will continue to use this hotel even if the price goes up |
.834 |
— |
||
|
RI4 I will positively recommend this hotel to my acquaintances |
.855 |
.80 |
EDU = Education experience; ENT= Entertainment Experience; EST= Esthetic Experience; ESC = Escapist Experience; RI: Revisit Intention.
Table 2: Validity Analysis
|
|
CR |
AVE |
MSV |
MaxR(H) |
Cus- tomer Experi- ence |
Revisit Intention |
|
Customer Experience |
0.958 |
0.603 |
0.003 |
0.960 |
0.777 |
0.055 |
|
Revisit Intention |
0.802 |
0.674 |
0.003 |
0.876 |
*** |
0.821 |
CR = composite reliability; AVE = average variance extracted; MSV = maximum shared variance: MaxR(H) = maximum reliability.
