Relationship of Customer Engagement, Perceived Quality and Brand Image on Purchase Intention of Premium Hotel ’ s Room

Brand image is a key factor for online hotel industry since the hotel offers experience and service that has intangible features, some tangible cues are more essential in shaping the brand image, which may generate travellers’ purchase intention. The traditional hotel industry is facing very serious problems. Because there are many new types of accommodation emerged based on the internet, such as homestay. Due to the change, it is necessary to unde rstand the key factors that influence travellers’ online purchase intention in hotel booking sector. This study summarized the development of the brand image, customer engagement, and perceived quality of online purchase intention in the existing literature. This research aims to develop a theoretical model to examine the direct effect of the variables in the online hotel booking area, which helps the further investigation of online hotel brand image, customer engagement, perceived quality and travellers’ o nline purchase intention. Additionally, this paper generates and discusses contributing to the research. A respectable sample of 81 was collected through a survey and the data were further analysed using Smart-PLS. It proposed that brand image, perceived quality and customer engagement has a positive influence on online purchase intention. This study assisted hotels to build a strong online brand image that results in the travellers’ online purchase intention.


Introduction
Online business and online services are becoming essential for tourist and hotel industry. According to the CNNIC report, China's online travel booking users reached 4.18 million, with a utilization rate of 48.9% in 2019 (CNNIC, 2020).. The transaction scale of China's online tourism market has increased year by year. In 2019, the annual transaction scale of China's online tourism market will reach RMB 1086.65 billion, with a year-on-year increase of 11.4%, and the growth rate is 2.1% higher than that of last year (Analysys, 2020). Moreover, the scale of China's online accommodation booking market continues to rise as well. In 2019, the online accommodation booking market transactions reached RMB 210.929 billion, a year-on-year increase of 12.1%, accounting for 19.4% of online travel (Analysys, 2020).
According to the 2019 Q1 China online hotel booking data, the transaction of OTA occupied 58.3% ranked No.1, the following channel is hotel official webpage or app occupied 18.6% (BigData Research, 2019). Many hotels are focusing on increasing their market share through cooperating with OTAs, which shows how important such cooperative ventures are for hotels to leverage their sales (Laise et al., 2019).
However, OTA dominated the online hotel market generates many issues. Firstly, increasingly high commissions (15-25%) decrease profitability of hotels (Liu, 2019;Paper, 2017). Secondly, damage hotel membership system and reduce loyalty users (Analysys, 2020). OTA has become a double-edged sword for hotels, which may help hotels but at the same time brings competition to them (Xue et al., 2020). This relationship is now both competitive and cooperative. What is more, the serious problem for the hotel industry is that OTAs start to invest and built hotels in order to control resources. Since 2016, OTA has taken more frequent actions to invest in hotels, establish hotel groups or establish joint ventures with hotel groups (LI, 2021). If they continue to develop in this way, it will be a big threat for other hotels because of the low online marketing cost, better integration and cooperation, and internal technology system in OTAs' hotels.
To solve the above issues, hotels need to develop and utilize the online official channel to its full potential and fight for the initiative (Baloglu & Pekcan, 2006;Teng et al., 2020). It is urgent to study OHR online booking behavior, especially in online purchase intention, in order to increase competitive advantage of official booking.
Since not many study had been done in the China's market, the need to fill in this gap was important. The goal of this study is to evaluate the direct effect of factors in the online hotel booking area, by examination of online hotel brand image, customer engagement, perceived quality, and travellers' online purchase intent. Thus the following research objectives were formulated. Research Objective 1: To examine the relationship between Brand Image and Purchase Intention. Research Objective 2: To examine the relationship between Perceived Quality and Purchase Intention. Research Objective 1: To examine the relationship between Customer Engagement and Purchase Intention.

Literature Review Brand Image
Brand image was proposed in 1950s, and has become a popular research objective in customer buying behavior studies since consumer seek products or service for something more than their physical feature and functions (Dobni & Zinkhan, 1990). Additionally, industry managers and marketers appreciate brand image as well because it is a key factor to create greater benefit and value (Wang and Tsai, 2014). Due to the increasing understanding of brand image, a more comprehensive definition was proposed by Keller, Parameswaran and Jacob. They point out brand image is reflected by the associations that customers hold for it (Keller et al., 2011).
It is important and beneficial to industry manger distinguishing between two different levels of customers, in terms of basic level customers that consider brand image relating to specific performance, imagery attributes and benefits, and higher level of customers that realize it relating to overall judgments, attitude and feelings. In other words, customers' overall reaction and connection with a brand based on perception of specific attributes and advantages of the brand that demonstrate strong relationship between basic level and higher level customers (Melisa, 2018;Keller et al., 2011, p.379).

Perceived Quality
Product or service quality is a key determinant that influences customers' purchase decisions. In order to compete in the fierce market, firms are making efforts to offer better quality products in a good environment (Soriano et al., 2002). Perceived Quality may generate continuous purchase or satisfaction since the value of product exceeds the expectation of customers (Shaharudin et al., 2011).
Some researchers suggested that product or service should be made available in different forms or unique and personalized, since under the changing demands, lifestyles and customer preference situation (Badruldin et al., 2012;Wong, 2016).

Customer Engagement
Customer engagement is a hot topic in a decade and has been widely discussed in marketing researches. Some researches defined customer engagement as a psychological process generating customer loyalty (Bowden, 2009). Van Doorn et al (2010) argue customer engagement refers to customer behaviors that relate to the specific types or patterns of focal engagement activities. They indicate that engagement is derive from motivational drivers and can be described as customer behavior based or centered on a brand or company, beyond purchase. Similar perspectives have been claimed in the studies of Jaakkola and Alexander (2014); Pham and Avnet (2009), who described engagement as customer activity types or patterns.
Additionally, Gummerus et al (2012) point out customers engage in a series of behaviors that enhance their relationship with a product, company or brand that exceed mere purchasing behavior. Moreover, engaged customers are expected to have a stronger preference for premium products and lower price sensitivity, demonstrating to become profitable than their non-engaged counterparts (Rishika et al., 2013).
Customer engagement is a better predictor referring to loyalty related outcomes beyond purchase than other traditional marketing constructs such as quality and price, since other constructs cannot capture the depth of relationships customers form with what they purchase (Bowden, 2009;Hollebeek, 2011). Thus, customer engagement is expected to contribute to the core relationship marketing principle of consumer repeat purchases, retention and loyalty . Bowden (2009) deeply investigate that engagement is helpful for the understanding of consumers' behavior or outcomes, in terms of loyalty related outcomes.

Purchase Intention
Intention refers to the specific behavior that the individual is willing to perform (Ajzen & Driver, 1991). The higher the individual's willingness, the higher the likelihood of behavior (Alamoudi, 2016). Purchase intention has been defined as an intervening psychological variable influencing the relationship between customer attitude and customer actual buying behavior (Miniard et al., 1983). Additionally, Kim and Ko (2012) support the opinion, and indicate purchase intention as a variable that related to customers' preference may evaluate the attraction of brand to customers.
Purchase intention can be seen as one part of customer cognitive behavior that refers to how a customer intends to purchase a brand or product (Choon Ling, Teck Chai, & Hoi Piew, 2010). Bojei and Wong (2012) researched on repeat purchase or repurchase intention of smartphones in their study as the dependent variable. There are many researches investigate online purchase intention on hotel booking, which indicate information quality, website quality, perceived price, brand and trust factors are the key factors toward purchase intention (Bai et al., 2008;Chen & Chang, 2012;Chiang & Jang, 2006;Kim et al., 2009;Lien et al., 2015;Wong & Law, 2005;Wu et al., 2014). In online room reservation, purchase intention indicates the wants that consumer willing to book a room by online website (Lien et al., 2015).

Research Methodology
Based on the literature, this study constructs a framework. The contribution of the following framework is to investigate the mediator effect of customer engagement and perceived quality on the relationship between brand image and online purchase intention. This study use quantitative survey method and conducted by distributing the questionnaires in China. Close-ended questions with 7-point Likert type scale were used throughout the study. Then, the data was interpreted using analytical tool Smart PLS3. The underpinning theory in this research is Theory of Planned Behavior (TPB) and Theory of Reasoned Action (TRA).
This research proposed a research framework as per below:  Table below shows a list of all the proposed hypothesizes of this study.
Proposed Hypotheses H1: Brand image will positively affect online purchase intention. H2: Perceived quality will positively affect online purchase intention. H3: Customer engagement will positively affect online purchase intention

Analysis and Findings Pilot Study
Prior to questionnaire distribution, a pilot test for pre-testing purpose was conducted and distributed in China target group that Chinese or live in China who have booked a premium hotel (4-5 stars) before but not on hotel official channel. The pilot test took about 3 weeks and got back 81 successful respondents. From the pilot study, all four variables (Brand Image, Perceived Quality, Customer Engagement and Online Purchase Intention ) have all above the good level of 0.80 as according to (Yang et al., 2020).

Reliability and Validity
Internal Consistency Reliability: A measurement model said to have satisfactory internal consistency reliability when the composite reliability (CR) of each construct exceeds the threshold value of 0.7 (Cham, Cheng, Low, & Cheok, 2020). Table 4-1 shows the CR of each construct for this dissertation ranges from 0.957 to 0.976. These results indicate that the items used to represent the constructs poses satisfactory internal consistency reliability.
Additionally, Cronbach Alpha's value fall between 0.944 and 0.973, there are no items have been deleted as the values have fulfilled the requirement of over 0.70 .
Indicator reliability: The indicator reliability of the measurement model is measured by examining the items loadings. A measurement model is said to have a satisfactory indicator reliability when each item's loading estimates is higher between 0.5 -0.7 (Hair et al., 2010). Based on the analysis, all items in the measurement model exhibited loadings exceeding 0.5, ranging from 0.658 to 0.927. Thus, all items used for this research demonstrate satisfactory indicator reliability.
Convergent Validity: In this dissertation, the measurement model's convergent validity is assessed by examining its average variance extracted (AVE) value. Convergent validity is said to be adequate when constructs have an average variance extracted (AVE) value close to 0.5 or higher (Yang et al., 2020).  Overall, the reliability and validity tests conducted on the measurement model are satisfactory, suggesting that items used to measure constructs in this paper are valid and fit to be used to estimate parameters in the structural model.

Hypothesis Testing Result
The explanation of the direct hypothesized result shows on table 4-2. When T value was more than 1.96, P value less than 0.05, then the relationship is significant . There are 6 direct hypothesis that all supported (H1-H6).  .

Conclusion and Recommendation
The findings of the pilot test showed satisfactory reliability and validity and all the hypotheses were supported. This study had managed to achieve all three research objectives set out earlier namely to examine the relationship between Brand Image and Purchase Intention, to examine the relationship between Perceived Quality and Purchase Intention and lastly to examine the relationship between Customer Engagement and Purchase Intention. All the hypotheses were significantly positive between the independent variables with the dependent variable.
Brand Image has the highest effect with the beta value of 0.364 followed by Customer Engagement(beta=.0337) and Perceived Quality(beta=0.285). This finding adds to the existing body of knowledge specially in the context of tourism marketing in China. Thus, aiding the hotel marketers in deciding their marketing resources accordingly to this rank.
A further full test will expand the scope of research in order to get a better final result. For future research, it is necessary to focus on customer engagement in the online hotel booking. Perhaps a study on the relationship of new variables and purchase intention with involvement of other third variables would be interesting in filling up the knowledge gaps.