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1 

        MULTIDISCIPLINARY SCIENTIFIC RESEARCH 
          BJMSR VOL 9 NO 6 (2024) P-ISSN 2687-850X E-ISSN 2687-8518 

         Available online at https://www.cribfb.com 

     Journal homepage: https://www.cribfb.com/journal/index.php/BJMSR 

                                                                                                                                                                                                    Published by CRIBFB, USA 
                                                                                                                                     

MARKETING MAGIC: UNCOVERING THE KEY DRIVERS OF 

LOYALTY AMONG LUXURY HOTEL GUESTS     
 

Yu Liang (a)1   
 

(a) PhD Candidate, UCSI Graduate Business School, UCSI University, Kuala Lumpur, Malaysia and Lecturer, Taiyuan Tourism College, Shanxi 

Province, China; E-mail: liangyu6806@gmail.com 
                     

 
A R T I C L E I N F O 

 
 

Article History: 

 

Received: 24th July 2024 

Reviewed & Revised: 24th July 
to 12th November 2024 

Accepted: 18th November 2024 

Published: 26th November 2024  

 
Keywords: 

 

Price Fairness, Social Media Marketing, 
Service Quality, Consumer Behaviour, 

Customer Loyalty. 

 
JEL Classification Codes: 

 

M31, M37, L83, L84, Z32 

 

       

      Peer-Review Model:  

 
      External peer review was done through  

      double-blind method. 

        

 
A B S T R A C T      

 
Over the past decade, the tourism industry in China has grown significantly, boosting both the size and 

revenue of the hotel sector across the nation. To stay competitive and relevant to the demand of the 

market, hospitality firms, particularly the hotels, must deliver excellent services and employ innovative 

and creative marketing strategies to attract new customers while retaining existing ones. As competition 

intensifies, research suggests that hotel brand image and customer awareness towards the brand have 

become crucial catalysts in driving customer loyalty and word-of-mouth, both of which are key to 

business success in the long term. Given the importance of a sustainable business model for hotels, this 

study explores and examines the interrelationships between marketing factors, hotel brand image and 

awareness, service quality, customer satisfaction, loyalty, and word-of-mouth. Using a survey 

questionnaire, we collected data from 396 luxury hotel guests in mainland China. The collected data 

were subsequently analysed using SPSS and SmartPLS statistical software. The results reveal that hotel 

brand image and awareness significantly impact guests' perceived service quality, and all hypotheses 

regarding the interrelationships between service quality, satisfaction, and loyalty were supported. 

Furthermore, the findings suggest that hotel managers should prioritise brand image and customer 

awareness towards the brand as part of their key strategies to improve perceived service quality and, 

ultimately, drive loyalty among hotel guests. Lastly, this study offers various strategic methods that hotels 

can consider to attract both domestic and international guests, providing valuable insights to advance 

the hospitality industry in mainland China. 

 
 

© 2024 by the authors. Licensee CRIBFB, USA. This open-access article is distributed under the 
terms and conditions of the Creative Commons Attribution (CC BY) license 
(http://creativecommons.org/licenses/by/4.0).  

            

 

INTRODUCTION 

According to Global Hospitality Group (2020), the luxury hotel market was valued at USD 93 billion in 2019 and is 

projected to grow at a compound annual growth rate (CAGR) of 4.3% from 2020 to 2027. It is anticipated that about 4,300 

luxury hotels worldwide have demonstrated the sector's encouraging expansion since 2020 (Smith Travel Research, 2020). 

Despite its initial impact, this growth illustrates how the pandemic has driven the hotel industry towards greater resilience 

and innovation. The spread of COVID-19 a few years ago has led to greater resilience in the hotel industry, significantly 

impacting its dynamics and accelerating growth in certain regions. The pandemic forced hotels to adopt stringent health 

protocols and adapt to new customer preferences, such as increased demand for hygiene and contactless services (Lin & 

Chen, 2022). In China, the hotel industry recovered significantly post-COVID-19, with international luxury hotels surging 

to over 3,000 by 2020, driven by a robust domestic travel market and support from both the national and provincial 

governments. The luxury hotel segment in China generated approximately $16 billion in revenue in 2021, up from $5 billion 

in 2010, highlighting the sector's resilience (Mordor Intelligence, 2022). Occupancy rates in major cities like Beijing and 

Shanghai often exceeded 70%, underscoring the industry's adaptation to new market demands (EHL Insights, 2021). 

In addition, China's rapid economic growth over the past few decades has led to a sizable and affluent middle and 

upper class with increasing disposable income and a growing appetite for luxury goods and services. This demographic shift 

has positioned China as a lucrative market for the luxury hotel industry, as more Chinese consumers are willing to pay a 

premium for high-quality hospitality experiences that signify status and prestige (Peng & Chen, 2019; Wu et al., 2023). 

Despite the rapid growth of the hotel industry in China, this high-credence industry still faces significant challenges. One 

major issue is increased competition, which pressures hotels to innovate and improve their services to remain competitive 

continuously (Hao et al., 2020). Additionally, engaging current customers is crucial for hotels, as acquiring new customers 

                                                      
1Corresponding author: ORCID ID: 0009-0005-7311-2278 

© 2024 by the authors. Hosting by CRIBFB. Peer review is the responsibility of CRIBFB, USA.  

https://doi.org/10.46281/bjmsr.v9i6.2256 

 

To cite this article: Liang, Y. (2024). MARKETING MAGIC: UNCOVERING THE KEY DRIVERS OF LOYALTY AMONG LUXURY HOTEL 

GUESTS. Bangladesh Journal of Multidisciplinary Scientific Research, 9(6), 1-16. https://doi.org/10.46281/bjmsr.v9i6.2256 

http://creativecommons.org/licenses/by/4.0/)
http://creativecommons.org/licenses/by/4.0/)
https://www.openaccess.nl/en
https://doi.org/10.46281/bjmsr.v9i6.2256
https://orcid.org/0009-0005-7311-2278


Liang, Bangladesh Journal of Multidisciplinary Scientific Research 9(6) (2024), 1-16

 

2 

requires five times more time and money than retaining existing ones. That makes meeting the evolving expectations of 

post-pandemic travellers more challenging, including prioritising hygiene, safety, contactless services, etc. (Bonfanti et al., 

2021). 

However, prior research mainly focused on the individual effects of marketing factors in the business world. For 

instance, Abeza et al. (2020) focus on how social media marketing enhances brand visibility and engagement, fostering 

customer community and encouraging positive word-of-mouth. Rather et al. (2024) investigated how personalised services 

cater to individual customers' needs, increasing satisfaction and loyalty by making guests feel valued and understood. 

Natarajan and Veera Raghavan (2024) explored the idea that loyalty programmes reward repeat customers, incentivise 

ongoing patronage, foster a deeper connection with the brand, etc. Limited research focuses on the aligned effects of crucial 

marketing factors that can foster solid and enduring relationships with guests, ultimately driving long-term business success. 

Additionally, prior studies have proved that guanxi plays an important role in customer relationship management in the 

Chinese context (Liu et al., 2024). In the online marketplace, swift guanxi, grounded in the theoretical lens of guanxi, is 

vital in facilitating online transactions (Ou et al., 2014) since online shopping has become increasingly common. For 

example, the higher the level of swift guanxi perceived by customers, the stronger their intention to make a favourable 

decision in the online marketplace (Zhang et al., 2021). Therefore, luxury hotels' swift guanxi is essential to customer loyalty 

and positive word-of-mouth communication. Thus, this study is focused on integrating crucial marketing factors that can 

improve customer loyalty and positive word-of-mouth in the post-pandemic era in mainland China. This study aims to assist 

hotels in navigating the competitive landscape and building a loyal customer base that drives positive word-of-mouth and 

repeat business. 

The remainder of this paper is arranged as follows: Section 2 provides a detailed review of previous literature and 

the development of research hypotheses. Section 3 discusses the research methodology. Sections 4 and 5 present the research 

findings, implications, and suggestions for future research. 

 

LITERATURE REVIEW 

Underpinning Theory: Relationship Marketing Theory 

The evolution of relationship marketing theory has been marked by significant developments since its inception in the 1980s, 

when it initially recognised the critical importance of cultivating customer relationships. This theory has broadened from 

mere transactional exchanges to a focus on fostering long-term relationships and reciprocal benefits between businesses and 

their stakeholders (Palmatier & Steinhoff, 2019). The advent and proliferation of digital technology and social media have 

further revolutionised relationship marketing by facilitating more personalised and interactive engagements with customers 

(Rooney et al., 2021). Moreover, relationship marketing theory has significantly impacted the hotel sector by applying across 

various industries. This theory underlines the essence of nurturing enduring relationships with customers, an aspect that 

becomes indispensable in industries where the quality of customer experience is a primary concern (Rather et al., 2024). 

The competitive landscape of the hotel industry, coupled with the paramount importance of customer loyalty and retention, 

underscores the need for employing relationship marketing theory. By establishing robust relationships with guests, hotels 

can improve guest satisfaction, foster loyalty, and encourage positive word-of-mouth, which is critical for a hotel's success 

(Wu & Chang, 2024). 

In addition, marketing factors like price, social media marketing, and service innovation emerge as essential 

elements of relationship marketing theory in luxury hotel research. Price fairness significantly influences guests' value 

perceptions, affecting their loyalty and satisfaction (Benetti Corrêa da Silva et al., 2021). Meanwhile, social media marketing 

is instrumental in engaging customers and bolstering brand awareness and loyalty (Nalluri et al., 2023). It was also reported 

that service innovation is crucial for setting luxury hotels apart by offering unique and memorable experiences, thereby 

driving customer satisfaction and loyalty (Liu et al., 2024). Moreover, relationship marketing theory within luxury hotel 

research encompasses several vital facets, including brand image, perceived service quality, customer satisfaction, loyalty, 

and word-of-mouth communication. Brand image and awareness lay the foundation for attracting guests and setting 

expectations. Perceived service quality influences guest satisfaction, affecting their loyalty and propensity to recommend 

the hotel to others. These interlinked components are instrumental in a hotel's success, facilitating the cultivation of solid 

and enduring relationships with guests (Rather et al., 2024). In Chinese luxury hotel research, guanxi is argued to be a 

pivotal aspect of relationship marketing theory. Guanxi, denoting the network of social and influential relationships that aid 

in business and other transactions, is relevant in China due to its cultural significance (Lee et al., 2018). It is anticipated that 

integrating guanxi into relationship marketing theory acknowledges the critical role of these social dynamics in augmenting 

customer loyalty and satisfaction, as well as the success of luxury hotels in China (Rather et al., 2024). 

 

Hypotheses Development 

The Significance of Branding: Brand Image and Brand Awareness  

Brand image is the perception and beliefs held by customers and the public regarding a brand. It encompasses the values, 

characteristics, and attributes consumers associate with a brand based on their experiences, beliefs, feelings, and knowledge 

(El-Said, 2020; Ryu et al., 2019). Brand image is not solely dictated by what the brand professes to be; it is predominantly 

shaped by customers' experiences and the broader societal interpretation of the brand's actions and communications (Bashir 

et al., 2020). Brand image is pivotal in the hotel industry, where the quality of experiences and services significantly impacts 

customer perceptions. Within the relationship marketing theory framework, brand image's significance in fostering long-

term customer relationships is paramount. It directly influences customer loyalty, trust, and satisfaction—elements at the 

heart of relationship marketing's aim to develop solid and lasting customer bonds (Nelson et al., 2024; Rather et al., 2024). 

A positive brand image increases consumers' likelihood of choosing a brand over its competitors and engaging in repeat 



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3 

patronage. A robust brand image is instrumental in attracting new customers, retaining current ones, and cultivating loyalty 

and trust—critical factors in an industry marked by intense competition and the necessity for exceptional customer service 

and satisfaction (Foroudi, 2019; Šerić & Gil-Saura, 2019). 

Brand awareness, in contrast, is about more than just recognition; it is about how familiar consumers are with the 

unique qualities or images of a specific brand of goods or services (Foroudi, 2019). It is about a brand's recognisability to 

its target audience and ability to influence consumer decision-making (Matikiti-Manyevere et al., 2020). Beyond simply 

recognising the brand name, brand awareness entails understanding the qualities that make the brand unique and superior to 

competitors. This strategic understanding of brand awareness as the initial phase of the marketing funnel, leading to brand 

preference and, eventually, customer loyalty and advocacy, highlights its importance in customer decision-making (Foroudi, 

2019; Matikiti-Manyevere et al., 2020; Šerić & Gil-Saura, 2019). In the relationship marketing theoretical lens, brand 

awareness is critical because it establishes the foundation for nurturing long-term relationships between the brand and its 

customers. Brand awareness is paramount in the hotel industry, where the services offered are intangible, and experiential 

hotels with significant brand awareness remain at the top of potential guests' minds, considerably influencing their lodging 

decisions. Such visibility is beneficial for attracting first-time guests and vital for customer retention and loyalty cultivation 

(Şanlıöz-Özgen & Kozak, 2023; Wu et al., 2023). In an intense competition and elevated customer expectations landscape, 

brand awareness emerges as a crucial differentiator, empowering hotels to discover a unique identity, capture a larger market 

share, and forge enduring relationships with their guests (Polo-Peña et al., 2023; Shanti & Joshi, 2022). 

 

Price Fairness (PF)  

Price fairness refers to the customers' perception of whether the price is reasonable, considering the value received from the 

service (Lu et al., 2020). The relationship between price fairness and brand image is crucial, as price fairness can 

significantly influence a hotel's brand image (Alderighi et al., 2022; Gironda, 2016). If customers perceive the pricing as 

fair, this can enhance the hotel's reputation, suggesting a positive impact (Bashir et al., 2020; Jin et al., 2019). Due to the 

apparent importance of this relationship, more research needs to be done to focus on how price fairness affects brand image, 

specifically within the hotel industry (Sohaib et al., 2022). This scarcity of studies underlines the need to investigate how 

customers' perceptions of price fairness can shape a hotel's brand image. 

In addition, price fairness has also been reported to impact brand awareness significantly. When customers perceive 

prices as fair, they are more likely to engage positively with the brand, enhancing recognition and recall (Jin et al., 2019). 

Therefore, fair pricing strategies can benefit customer satisfaction and loyalty and strengthen brand awareness in the 

competitive hotel industry (Liu et al., 2024; Polo-Peña et al., 2023). Despite the logical connection between these concepts, 

research exploring price fairness's direct impact on brand awareness is sparse in the hotel industry (Sohaib et al., 2022). 

Besides, the interplay between how consumers perceive price fairness and its subsequent effect on brand awareness still 

needs to be explored, highlighting a gap in the existing literature. Based on the evidence presented above, this study proposes 

the following hypothesis: 

 

H1a: Price fairness positively impacts the brand image. 

H2a: Price fairness positively impacts brand awareness. 

 

Social Media Marketing (SMM) 

In the hotel industry, social media marketing encompasses strategies to promote hotels and their services across various 

social media platforms, aiming to engage potential and current customers through content that resonates with their interests 

and preferences. The impact of social media marketing on a hotel's brand image is significant, providing a direct channel 

for hotels to craft and disseminate their desired brand narratives, engage in real-time with customers, and manage their 

reputation online (Barreda et al., 2020). Hotels can enhance their brand image through strategic social media marketing, 

making it more appealing and relatable to their target audience (Barreda et al., 2020; Kim & Han, 2022). An effective social 

media strategy can significantly improve how customers perceive and emotionally connect with a hotel brand (Nusair et al., 

2024). However, despite the intuitive link between social media marketing and brand image enhancement, most existing 

studies focus on broader aspects without delving into its specific effects on brand image within the hotel sector (Jiang & 

Wen, 2020; Liu et al., 2022). 

Apart from the above, the influence of social media marketing on brand awareness within the hotel industry 

represents a significant area of interest, underlined by the pervasive adoption of social media platforms for hospitality 

marketing endeavours (Kim et al., 2020; Nalluri et al., 2023). Effective implementation of social media marketing gives 

hotels a dynamic medium to amplify their brand's visibility and recognition, engaging directly with potential and current 

customers, thus markedly elevating hotel brand awareness. This direct engagement facilitates a broader reach and more 

profound, personalised interaction with the target audience (Nalluri et al., 2023; Sürücü et al., 2019). Moreover, it is 

premised on the notion that strategically curated social media campaigns can effectively captivate a wider audience, thereby 

bolstering the visibility and recognition of hotel brands (González-Padilla & Lacárcel, 2023; Polo-Peña et al., 2023). Despite 

the evident relevance of social media marketing to enhancing brand awareness in hotels, there is a notable scarcity of focused 

research delving into the specifics of this impact within the hotel sector. Given the above, this study postulated that: 

 

H1b: Social media marketing positively impacts the brand image. 

H2b: Social media marketing positively impacts brand awareness. 

 

 



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Service Innovation (SI) 

In the hotel industry, service innovation refers to introducing new or significantly improved services or processes to enhance 

customer experiences, operational efficiency, or competitive advantage (Ziyae et al., 2021). This can include anything from 

implementing cutting-edge technology for seamless check-ins to offering personalised guest experiences that cater to the 

unique preferences of each visitor (Ishizaka et al., 2019; Tomašević, 2018). The impact of such innovations on a hotel's 

brand image is profound; by delivering novel and improved services, hotels can significantly enhance their brand perception, 

setting themselves apart as leaders in customer satisfaction and technological advancement (Bashir et al., 2020; Ryu et al., 

2019). Despite the intuitive connection between service innovation and enhanced brand image within the hospitality sector, 

there is a noticeable scarcity of focused research exploring this relationship in depth. 

In the hotel industry, service innovation significantly influences brand awareness by introducing novel or greatly 

improved services tailored to guests' evolving preferences (Ziyae et al., 2021). These innovations, which range from digital 

check-ins to personalised guest experiences, not only fulfil but exceed customer expectations, acting as critical 

differentiators in a fiercely competitive market and markedly boosting a hotel's visibility and brand awareness (Ishizaka et 

al., 2019; Tomašević, 2018). Studies on service innovation typically span across various industries, with less emphasis on 

its direct effects on brand awareness in the hotel industry (Foroudi, 2019; Sürücü et al., 2019). Addressing this gap, this 

study asserts that service innovation positively influences brand awareness in the hotel sector. It suggests that hotels 

leveraging innovative services can significantly enhance their brand's visibility, attract more guests and establish a more 

pronounced market presence. Therefore, this study proposes: 

 

H1c: Service innovation positively impacts the brand image. 

H2c: Service innovation positively impacts brand awareness. 

 

Perceived Service Quality (PSQ) 

Perceived service quality in the hotel industry is defined as guests' evaluation of the overall excellence and value of the 

service provided, incorporating dimensions such as responsiveness, reliability, and personalisation (Palazzo et al., 2021; 

Polyakova & Ramchandani, 2023). This subjective assessment is crucial in shaping guests' experiences and satisfaction. 

Brand image, representing consumers' overall impressions of a hotel's brand, significantly impacts perceived service quality 

(Wai Lai, 2019). A strong and positive brand image can elevate guests' service quality perceptions by communicating a 

promise of consistency and excellence (Bashir et al., 2020; Ryu et al., 2019). Moreover, a hotel with a solid and favourable 

brand image will likely be perceived as providing higher-quality services, enhancing guest satisfaction and loyalty. 

However, studies often discuss brand image's broader impacts without focussing on its specific implications for perceived 

service quality in hospitality (Foroudi, 2019; Sürücü et al., 2019). 

In addition to the aforementioned, brand awareness, which reflects how customers recognise and are familiar with 

a hotel brand, can shape and often heighten their expectations regarding service quality in the hotel industry (Foroudi, 2019; 

Sürücü et al., 2019). When a well-known hotel brand is present, customers will likely have heightened perceptions of service 

quality, associating the brand's visibility with reliability and excellence (Wai Lai, 2019). This connection suggests that brand 

awareness can be a precursor to perceived service quality, reinforcing that a prominent brand is synonymous with superior 

service. Therefore, this study hypothesises that: 

 

H3a: Brand image positively impacts perceived service quality. 

H3b: Brand awareness positively impacts perceived service quality. 

 

Customer Satisfaction (CS) 

Customer satisfaction in the hotel industry is understood as guests' perceptions of how a hotel's services align with or surpass 

their expectations. It is a critical performance metric for hospitality businesses (Malik et al., 2020). Perceived service quality, 

or guests' assessment of the service's excellence and value, significantly influences this satisfaction by setting the standard 

against which services are judged (Palazzo et al., 2021; Polyakova & Ramchandani, 2023). While the link between perceived 

service quality and customer satisfaction is widely acknowledged (Nowlin, 2024), focused investigations within the hotel 

sector could be more comprehensive. Therefore, this study asserts that: 

 

H4: Perceived service quality positively impacts customer satisfaction. 

 

Customer Loyalty (CL) 

Customer loyalty in the hotel industry is characterised by a guest's continued preference for a particular hotel brand, 

evidenced by repeat bookings, reluctance to switch to competitors, and positive referrals (Närvänen et al., 2020). This loyalty 

indicates a pattern of repeat patronage and a deep-seated trust and emotional bond with the brand (El-Adly, 2019; Närvänen 

et al., 2020). Moreover, the link between customer satisfaction and loyalty is evident, with satisfied customers more inclined 

to remain loyal due to positive experiences that meet or surpass expectations, fostering trust and attachment to the hotel 

(Khan et al., 2022; Molinillo et al., 2022). By considering narrowing down the broad overview of customer satisfaction 

across various sectors (Alam et al., 2021; Hohenberg & Taylor, 2022) to the hotel industry, this study posits that: 

 

H5a: Customer satisfaction positively impacts customer loyalty. 

 

 



Liang, Bangladesh Journal of Multidisciplinary Scientific Research 9(6) (2024), 1-16

 

5 

Word-of-Mouth Communication (WOM) 

Word-of-mouth communication in the hotel industry refers to the informal exchange of information and opinions about a 

hotel's services or experiences between potential and past guests (Donthu et al., 2021). This form of communication is highly 

valued for its authenticity and significant influence on consumer behaviour, acting as a powerful tool for attracting new 

customers and building a hotel's reputation (El-Adly, 2019; Khan et al., 2022). Customer satisfaction plays a pivotal role in 

fuelling word-of-mouth communication, as satisfied guests are likelier to share positive experiences and recommendations 

with others, enhancing the hotel's image and attracting future business (Gajewska et al., 2019; Otto et al., 2020). However, 

most studies generally focus on the dynamics of customer satisfaction and its results without specifically examining its 

direct influence on word-of-mouth communication within the hospitality industry. Therefore, this study proposed the 

following hypothesis: 

 

H5b: Customer satisfaction positively impacts word-of-mouth communication. 

 

The Moderating role of Swift Guanxi (SGX)  

Swift guanxi is a concept that adapts the traditional Chinese notion of guanxi, emphasising interpersonal relationships and 

networks, to the fast-paced and transient interactions typical of modern business and social exchanges. Different from 

conventional guanxi, built over long periods through personal interactions and mutual obligations, swift guanxi refers to the 

rapid development of trust and cooperative relationships between parties who may not have a long history of personal 

connections (Ou et al., 2014). This concept is particularly relevant when quick decision-making and immediate trust are 

essential, leveraging modern communication technologies to establish connections swiftly (Liu et al., 2024). Besides, swift 

guanxi is important because it highlights businesses' ability to quickly forge meaningful relationships with customers, 

partners, and other stakeholders. This rapid relationship-building is crucial for attracting and retaining customers, navigating 

business negotiations, and entering new markets (Nelson et al., 2024). Specifically, in the hotel industry, swift guanxi can 

be a pivotal factor in customer satisfaction and loyalty. Given the industry's emphasis on service excellence and guest 

experiences, the ability of hotel staff to quickly establish a rapport with guests—making them feel valued and understood 

from the moment of their first interaction—can enhance guest satisfaction and encourage repeat business (Davari et al., 

2022; Kim & Han, 2022). 

In a highly competitive market, hotels implementing swift guanxi strategies can differentiate themselves by 

creating a more personalised and memorable experience for their guests, fostering positive word-of-mouth, and building a 

loyal customer base. For instance, swift guanxi can soften potential adverse reactions to price decisions by reinforcing the 

hotel's commitment to personalised care and value, positively affecting the brand's perception among guests (Lu et al., 

2020). Moreover, in the hotel industry, swift guanxi suggests that when hotels effectively use social media marketing to 

connect with and engage their audience, the presence of swift guanxi can amplify the positive impact on the hotel's brand 

image (Kim & Han, 2022; Liao et al., 2020). Swift guanxi can enhance guests' trust and connection towards the hotel, 

making social media marketing efforts more effective and directly influencing guests' perceptions and loyalty (Barreda et 

al., 2020; Nalluri et al., 2023). Besides, swift guanxi could also amplify the positive impact of service innovations on the 

brand image by strengthening the bond between the hotel and its guests, reinforcing the hotel's reputation for innovation, 

and valuing guest relationships (Bashir et al., 2020; Ryu et al., 2019). 

Furthermore, it was reported that establishing robust and swift guanxi may improve guests' perceptions of price 

fairness, increasing brand awareness, as guests are likelier to share their positive experiences and perceptions (Jin et al., 

2019; Konuk, 2018). Specifically, swift guanxi can intensify the positive effects of social media marketing on brand 

awareness by fostering a sense of familiarity and trust among guests, making them more likely to engage with and spread 

word-of-mouth recommendations about the hotel (Barreda et al., 2020; Nalluri et al., 2023). Moreover, the strength of swift 

guanxi can amplify the positive effects of service innovations on brand awareness, as guests are more likely to perceive the 

hotel as attentive and committed to providing exceptional experiences (Zhang et al., 2021). Therefore, this study proposes 

that: 

 

H6a: Swift Guanxi moderates the relationship between price fairness and brand image. 

H6b: Swift Guanxi moderates the relationship between social media marketing and brand image. 

H6c: Swift Guanxi moderates the relationship between service innovation and brand image. 

H7a: Swift Guanxi moderates the relationship between price fairness and brand awareness. 

H7b: Swift Guanxi moderates the relationship between social media marketing and brand awareness. 

H7c: Swift Guanxi moderates the relationship between service innovation and brand awareness. 

 

 

 



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6 

H4 

 

 

 

 

 

 

 

 

 

 

Figure 1. Research framework 

 

MATERIALS AND METHODS 

The target sample of this study is consumers who have stayed at least one night in a luxury hotel in mainland China for the 

last six months. A purposive combined with a snowball sampling method was used to collect data to ensure the responses 

were reliable and justifiable. The data collection process involved using two screening questions: those at least 18 years of 

age and those who have stayed at least one night in a luxury hotel for the past six months. The survey was conducted online 

using a digital questionnaire created on the SoJump platform, which is well-known and widely used in China for surveys. 

The questionnaire was then shared across social media channels like WeChat and Xiaohongshu. Qualified participants in 

this study were urged to share the survey questionnaire with their peers and family. Only 396 eligible responses were 

received for this investigation, which is more than the minimal sample size of 153 needed according to the G*Power 

software. There are 44.2% male and 55.8% female participants in the sample. Of these respondents, 56.8% are in the 18–25 

age group, and 18.7% fall into the 36–45 age bracket. 

As for the measurement instruments, with a few modest modifications to suit the context of the hotel sector in 

mainland China, the survey questions were adapted from previously published literature. Appendix A presents a detailed 

list of measurement items and their sources. Using a 6-point Likert scale with one denoting "strongly disagree" and six 

denoting "strongly agree," respondents were asked to rate their opinion for all the questions asked in the questionnaire. 

Moreover, qualified translators carried out a comprehensive back-to-back translation procedure to ensure accurate 

translation of the content from English to Chinese, as the Chinese people are the study's primary target audience. Moreover, 

a panel of seven native speakers with expertise in tourism-related studies validated the face validity of these items during 

the pre-testing stage. Furthermore, a pilot test with eighty respondents demonstrated good internal reliability and convergent 

validity. 

 

RESULTS 

This work uses PLS-SEM (partial least squares structural equation modelling) and SmartPLS 4 software for data analysis. 

According to Hair et al. (2019), PLS-SEM is particularly well-suited for predictive research using intricate models with 

several components, indicators, and pathways. PLS-SEM was chosen over covariance-based structural equation modelling 

(CB-SEM) for this investigation due to its suitability for extending the theory. This study uses statistical and procedural 

techniques to avoid conventional method bias because exogenous and endogenous variables data were collected from the 

same respondents (Podsakoff et al., 2003). It protected respondent confidentiality and avoided using technical terms and 

complicated jargon in the survey design to allay procedural worries. Two widely accepted approaches were used to reduce 

common method variance (CMV). First, Hair et al.'s (2019) full collinearity approach was adopted. As shown in Table 3, 

all constructs' variance inflation factor (VIF) values were between 3.718 and 4.913, indicating that CMV had a negligible 

effect on the dataset. Second, we applied the Liang et al. (2007) described unmeasured common latent component technique. 

Appendix B shows that the substantial substantive-to-method variance ratio was 14.275:1, with all substantive factor 

loadings (R1) significantly more significant than the method factor loadings (R2). This suggests that the typical procedure 

variance in this study will likely be delicate. 

 

Assessment of Measurement Model 

Table 1 shows that all constructs readily exceeded the minimum standards for convergent validity and composite reliability, 

with all average variance extracted (AVE) values greater than 0.50 and all factor loadings above 0.70 (Hair et al., 2019). As 

a result, convergent validity and internal consistency are proven. Next, as shown in Table 2, the study validates discriminant 

validity following the Fornell-Larcker criterion. All indicator intercorrelations are less than the square roots of the AVE 

values (Hair et al., 2019). 

 

 

 

Perceived Price 

Fairness 

Social Media 

Marketing 

Perceived Service 

Innovation 

Brand Image 

Brand Awareness 

Perceived  

Service Quality 

Customer 

Satisfaction 

Customer Loyalty 

Swift Guanxi 

Word-of-Mouth 

Communication 

  Marketing Factors 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

H7a 



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7 

Table 1. Assessment of loading, reliability and convergent validity 

 
Construct Items Loading Cronbach's 

alpha 

Composite 

reliability 

(rho_a) 

Composite 

reliability 

(rho_c) 

Average 

variance 

extracted 

(AVE) 

BA BA1 

BA2 

BA3 

0.964 

0.958 

0.950 

0.955 0.955 0.971 0.917 

BI BI1 

BI2 

BI3 

0.914 

0.948 

0.923 

0.920 0.921 0.949 0.862 

CL CL1 
CL2 

CL3 

0.921 
0.928 

0.913 

0.910 0.910 0.944 0.848 

CS CS1 
CS2 

CS3 

0.922 
0.932 

0.933 

0.921 0.921 0.950 0.863 

PF PF1 

PF2 
PF3 

PF4 

0.889 

0.880 
0.894 

0.919 

0.918 0.919 0.942 0.802 

PSQ PSQ1 
PSQ2 

PSQ3 

PSQ4 
PSQ5 

PSQ6 

PSQ7 

0.879 
0.886 

0.911 

0.916 
0.907 

0.919 

0.887 

0.961 0.963 0.968 0.812 

SGX SGX1 

SGX2 

SGX3 
SGX4 

SGX5 

SGX6 
SGX7 

SGX8 

SGX9 

0.925 

0.943 

0.937 
0.932 

0.907 

0.911 
0.937 

0.921 

0.910 

0.979 0.979 0.982 0.855 

SI SI1 
SI2 

SI3 

SI4 

0.914 
0.950 

0.938 

0.845 

0.932 0.936 0.952 0.833 

SMM SMM1 

SMM2 

SMM3 
SMM4 

SMM5 

0.873 

0.922 

0.916 
0.921 

0.909 

0.947 0.949 0.959 0.825 

WOM WOM1 

WOM2 

WOM3 

WOM4 
WOM5 

0.857 

0.919 

0.917 

0.935 
0.871 

0.941 0.945 0.955 0.811 

Notes: BA= Brand Awareness; BI = Brand Image; CL = Customer Loyalty; CS = Customer Satisfaction; PF = Price Fairness; PSQ = Perceived Service 

Quality; SGX = Swift Guanxi; SI = Service Innovation; SMM = Social Media Marketing; WOM= Word-of-Mouth Communication. 

 

Table 2. Discriminant validity analysis (Fornell-Larcker criterion) 

  
BA BI CL CS PF PSQ SGX SI SMM WOM 

BA 0.957 
         

BI 0.865 0.928 
        

CL 0.721 0.696 0.921 
       

CS 0.718 0.705 0.818 0.929 
      

PF 0.768 0.757 0.579 0.619 0.896 
     

PSQ 0.823 0.803 0.758 0.74 0.682 0.901 
    

SGX 0.873 0.852 0.717 0.735 0.787 0.817 0.925 
   

SI 0.786 0.806 0.677 0.693 0.704 0.777 0.808 0.912 
  

SMM 0.864 0.887 0.678 0.664 0.752 0.797 0.846 0.806 0.908 
 

WOM 0.886 0.848 0.725 0.743 0.766 0.826 0.885 0.848 0.872 0.9 

Notes: BA= Brand Awareness; BI = Brand Image; CL = Customer Loyalty; CS = Customer Satisfaction; PF = Price Fairness; PSQ = Perceived Service 
Quality; SGX = Swift Guanxi; SI = Service Innovation; SMM = Social Media Marketing; WOM= Word-of-Mouth Communication. 

 

 



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8 

Assessment of Structural Model 

According to Hair et al. (2019), multicollinearity was determined by analysing the VIF (variance inflation factor) (Table 3) 

at a threshold of 5. This confirms that multicollinearity is not a cause for concern. The structural model was then investigated 

using 5,000 subsamples with a bootstrapping technique. 

 

Table 3. Collinearity statistics (VIF) 

  
BA BI CL CS PF PSQ SGX SI SMM WOM 

BA 
     

3.976 
    

BI 
     

3.976 
    

CS 
  

1 
      

1 

PF 4.083 4.083 
        

PSQ 
   

1 
      

SGX 4.913 4.913 
        

SI 3.718 3.718 
        

SMM 4.504 4.504 
        

Notes: BA= Brand Awareness; BI = Brand Image; CS = Customer Satisfaction; PF = Price Fairness; PSQ = Perceived Service Quality; SGX = Swift 

Guanxi; SI = Service Innovation; SMM = Social Media Marketing. 

 

The supported hypotheses are listed in Table 4, and all the critical pathways are depicted in Figure 1. P-values less 

than 0.05 indicate empirical solid support for each of the hypothesised relationships. PF (H1a: β = 0.103, p < 0.05; H2a: β 

= 0.108 p < 0.01), SMM (H1b:β = 0.487, p < 0.001; H2b:β = 0.381, p < 0.001)) and SI (H1c:β = 0.19, p < 0.001; H2c:β = 

0.097, p < 0.05)) reported a positive impact on both BI and BA. Moreover, PSQ is positively affected by BI (H3a:β = 0.36, 

p < 0.001) and BA (H3b:β = 0.512, p < 0.001) and positively impacted on CS (H4: β = 0.74, p < 0.001). Finally, CS reported 

a positive impact on CL (H5a:β = 0.818, p < 0.001) and WOM (H5b: β = 0.743, p < 0.001). 

 

Table 4. Hypothesis testing (direct effect) 

 
Relationship Path Coefficients T statistics P values Results 

H1a PF -> BI 0.103* 2.328 0.02 Supported 

H2a PF -> BA 0.108* 2.552 0.011 Supported 

H1b SMM -> BI 0.487*** 11.358 0 Supported 

H2b SMM -> BA 0.381*** 7.444 0 Supported 

H1c SI -> BI 0.19*** 4.464 0 Supported 

H2c SI -> BA 0.097* 2 0.046 Supported 

H3a BI -> PSQ 0.36*** 6.213 0 Supported 

H3b BA -> PSQ 0.512*** 8.602 0 Supported 

           H4 PSQ -> CS 0.74*** 26.003 0 Supported 

H5a CS -> CL 0.818*** 30.555 0 Supported 

H5b CS -> WOM 0.743*** 26.695 0 Supported 

Notes: 1.*p < 0.05; ***p < 0.001; 2. BA= Brand Awareness; BI = Brand Image; CL = Customer Loyalty; CS = Customer Satisfaction; PF = Price Fairness; 

PSQ = Perceived Service Quality; SI = Service Innovation; SMM = Social Media Marketing; WOM= Word-of-Mouth Communication. 

 

Table 5 displays the values for the Q² (cross-validated redundancy) and R² (coefficient of determination) to help 

assess the structural model's validity further (Hair et al., 2019). Hair et al. (2019) state that R2 values of 0.75, 0.5, and 0.25 

for endogenous latent variables in marketing research suggest strong, moderate, or weak explanatory power. Apart from 

providing a very slight explanation for WOM (R2 = 0.552), CL (R2 = 0.668), CS (R2 = 0.548), and PSQ (R2 = 0.711), the 

structural model demonstrates significant explanatory power in forecasting BA (R2 = 0.828) and BI (R2 = 0.847) results. 

Additionally, Q2 values significantly greater than zero imply that the structural model displays appropriate predictive 

accuracy for all internal constructs (Hair et al., 2019).  

 

Table 5. Model evaluation 

 
Construct R2 Q² (=1-SSE/SSO) 

BA 0.828 0.751 

BI 0.847 0.722 

CL 0.668 0.563 

CS 0.548 0.47 

PSQ 0.711 0.573 

WOM 0.552 0.445 

Notes: BA= Brand Awareness; BI = Brand Image; CL = Customer Loyalty; CS = Customer Satisfaction; PSQ = Perceived Service Quality; WOM= Word-

of-Mouth Communication. 

 

In terms of relative influence (f2), Table 6 shows that there are significant effects of CS on CL (f2 = 2.016), WOM 

(f2 = 1.23), and PSQ on CS (f2 = 1.211), all of which surpass the 0.35 threshold (Cohen, 2016). Furthermore, there are 

notable moderating effect sizes for both BA (f2 = 0.188) and BI (f2 = 0.345) and SMM (f2 = 0.228) on PSQ, each of which 



Liang, Bangladesh Journal of Multidisciplinary Scientific Research 9(6) (2024), 1-16

 

9 

exceeds the 0.15 threshold (Cohen, 2016). Lastly, BI on PSQ (f2=0.113), PF on BA (f2=0.009) and BI (f2=0.013), SI on BA 

(f2=0.016), and BI (f2=0.063) all reported small effect size (Cohen, 2016). 

 

Table 6. Effect size analysis (f2) 

 
Construct BA BI CL CS PSQ WOM 

BA 
    

0.228 
 

BI 
    

0.113 
 

CS 
  

2.016 
  

1.23 

PF 0.017 0.017 
    

PSQ 
   

1.211 
  

SI 0.015 0.063 
    

SMM 0.188 0.345 
    

Notes: BA= Brand Awareness; BI = Brand Image; CS = Customer Satisfaction; PF = Price Fairness; PSQ = Perceived Service Quality; SI = Service 
Innovation; SMM = Social Media Marketing. 

 

Moderation Effect 

A two-stage latent interaction strategy was used to investigate the moderating effect of rapid guanxi. It (Table 7) indicated 

that swift guanxi does not affect the link between PF and BA (β = −0.023; p-value = 0.613) and BI (β = −0.070; p-value = 

0.173), SMM and BA (β = 0.107; p-value = 0.059); SI and BA (β = −0.051; p-value = 0.286), thus, H6a, H7a, H7b, H7c, 

are rejected. In contrast, swift guanxi significantly impacted the relationship between SI and BI (β = −0.152; p-value = 0.00), 

SMM and BI (β = 0.249; p-value = 0.00), supporting H6c and H6b. 

 

Table 7. Hypothesis testing (Moderation effect) 

 
Hypotheses Path Original sample (O) P values Decisions f2 

H6a SGX x PF -> BI -0.07NS 0.173 Not supported 0.008 

H6b SGX x SMM -> BI 0.249*** 0 Supported 0.087 

H6c SGX x SI -> BI -0.152*** 0 Supported 0.040 

H7a SGX x PF -> BA -0.023NS 0.613 Not supported 0.001 

H7b SGX x SMM -> BA 0.107NS 0.059 Not supported 0.014 

H7c SGX x SI -> BA -0.051NS 0.286 Not supported 0.004 

Notes: 1.NSp>0.5; *p < 0.05; **p < 0.01; ***p < 0.001; 2.BA= Brand Awareness; PF = Price Fairness; SGX = Swift Guanxi; SI = Service Innovation; 

SMM = Social Media Marketing. 

 

Before SGX was introduced as a moderator, the R2 value for BI was 0.821. This indicated that SMM and SI 

explained 82.1% of BI's variance, underlining their significant effect on hotel brand images. Adding the SGX interaction 

term raised the R2 to 0.847, a statistically significant increase of 2.6%, showing that SGX notably enhances the effectiveness 

of marketing strategies on BI. An interaction plot was used to illustrate SGX's moderating effects on SI's impact on BI 

(Dawson, 2014). Figure 1 shows a steeper line at lower SGX levels, indicating a more substantial impact of SI on BI, while 

at higher SGX levels, the line flattens, suggesting a reduced impact. This demonstrates that higher SGX levels weaken SI's 

influence on BI. The f2 effect size of 0.040 indicates a sizeable negative moderation effect, confirming that SGX significantly 

diminishes the relationship between SI and BI (Hair et al., 2021). Moreover, Figure 2 demonstrates that at high SGX levels, 

the impact of SMM on BI is notably more substantial, as shown by a steeper line.  In contrast, at lower SGX levels, the line 

flattens, indicating a weaker effect. Thus, higher SGX enhances the influence of SM on BI. The f2 effect size of 0.087 

indicates a significant positive moderation effect, confirming that SGX significantly strengthens the relationship between 

SMM and BI. 

 

 
Figure 2. SGX dampens the positive relationship between SI and BI 



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10 

 
Figure 3. SGX strengthens the positive relationship between SMM and BI 

 

DISCUSSIONS 

The primary aim of this study was to use the relationship marketing model to examine how experiential marketing factors—

such as price fairness, social media marketing, and service innovation—influence hotel brand image and awareness. The 

findings confirm that these factors significantly impact both aspects, supporting Hypotheses H1a-c and H2a-c. Price fairness 

ensures customers perceive value for their money, fostering a positive brand image (Jin et al., 2019). Effective social media 

marketing broadens brand reach and enhances customer engagement, boosting brand awareness (Dedeoğlu et al., 2020). 

Additionally, service innovations differentiate the hotel from competitors and improve customer perceptions of the brand 

(Foroudi, 2019). Collectively, these elements strengthen the hotel's market position by improving how customers perceive 

and recognise the brand, reinforcing insights (Nelson et al., 2024; Rather et al., 2024). The study's second objective 

conclusively demonstrates the impact of hotel brand influence (e.g., brand image and awareness) on customers' perceived 

service quality, thereby supporting Hypotheses H3a and H3b. These hypotheses explore the nuanced dynamics between 

hotel brand image, brand awareness, and customer perceptions of service quality. Hypothesis H3a posits that a favourable 

hotel brand image—characterised by the hotel's distinguished reputation, intrinsic values, and recognised attributes—

significantly enhances perceived service quality (Bashir et al., 2020; Ryu et al., 2019). This suggests that positive perceptions 

of a hotel's brand image are closely linked to superior evaluations of its service quality, driven by anticipatory positive 

associations with the brand. Similarly, Hypothesis H3b asserts that increased brand awareness—evidenced by customer 

familiarity and recall of a hotel brand—positively impacts perceived service quality (Foroudi, 2019; Sürücü et al., 2019). A 

hotel brand that achieves high recognition and remains top-of-mind for customers creates a halo effect, enhancing 

perceptions of service quality before any actual service interaction. These findings underscore the significant role of brand 

image and awareness in shaping customer expectations and improving their perceptions of service quality within the hotel 

industry. 

The third objective of this study concludes that customer satisfaction is the crucial intermediary linking perceived 

service quality with outcomes such as customer loyalty and word-of-mouth communication, affirming Hypotheses H4, H5a, 

and H5b. Anchored in relationship marketing principles, this sequence begins with the customer's perception of the hotel's 

service quality, significantly impacting their satisfaction level (El-Adly, 2019; Slack et al., 2020). Consequently, satisfied 

customers with service quality are more inclined to exhibit loyalty towards the hotel and recommend it to others (Khan et 

al., 2022; Lin et al., 2020). This underscores the critical need for hotels to consistently deliver high-quality service to foster 

customer loyalty and encourage positive recommendations by actively enhancing and sustaining service quality to align 

with customer expectations. In addressing the final objective of this study, it was found that swift guanxi dampens the 

positive relationship between service innovation and brand image and strengthens the positive relationship between social 

media marketing and brand image (H6c and H6b); others are not supported (H6a and H7a-c are rejected). This may be due 

to swift guanxi involving mutual understanding, reciprocal favours, and relationship harmony in the online marketplace (Ou 

et al., 2014). These elements can reinforce shaping and refining brand perceptions and sculpting a positive brand image 

through targeted content and interactive engagement strategies in social media marketing (Dwivedi et al., 2021). 

Furthermore, a brand image includes functional, symbolic, or experiential aspects (Iglesias et al., 2019). The 

concept of swift guanxi can influence these aspects of innovative services. In digital platforms, trust is fundamental; 

however, innovation introduces change and uncertainty. Thus, swift guanxi can moderate the impact of innovative services 

on brand image, highlighting the uncertainty associated with change. 

 

CONCLUSIONS 

This study examines the relationships between marketing factors, hotel brand image and awareness, service quality, 

customer satisfaction, loyalty, and word-of-mouth, with Swift Guanxi as a moderator. The results indicate that hotel brand 

image and awareness significantly positively affect guests' perceived service quality. All hypothesised relationships between 

service quality, customer satisfaction, and loyalty were confirmed. However, not all moderating effects of swift guanxi on 

the relationships between brand image, awareness, and marketing factors were supported. These findings provide practical 

guidance and valuable insights for advancing the hotel industry in mainland China. By understanding the complex 

interactions between these variables, hotel managers can tailor their strategies more effectively to enhance service quality, 

increase customer satisfaction and loyalty, and encourage positive word-of-mouth. 



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11 

This study adds a few noteworthy new pieces to the body of literature. First, this study embarks on an in-depth 

exploration of the theoretical limits within relationship marketing theory, with a particular focus on understanding how 

various marketing factors—such as price fairness, service innovation, and social media marketing—shape the perception 

and effectiveness of hotel brands (e.g., brand image and awareness) in the hospitality sector. This research delves into the 

marketing and branding elements that significantly influence customers' perceived service quality. Prior research has only 

touched on the diverse marketing factors that impact hotel branding (Lee et al., 2018). This study seeks to bridge this gap 

by meticulously identifying and examining marketing-related elements that are pivotal in shaping perceived service quality. 

In doing so, the study addresses the shortcomings of previous investigations. It unfolds a detailed understanding of the 

crucial marketing factors that underpin the perception of quality in the hotel industry. This contribution enriches the 

discourse on relationship marketing and brand management within the hospitality context, offering valuable insights and 

guiding future research. 

Second, this study investigates how hotels' brand image and awareness positively influence guests' perceptions of 

service quality, boosting their satisfaction, loyalty, and likelihood to recommend the hotel to others. Despite the significance 

of these relationships within the hotel industry, comprehensive explorations in this area still need to be made available 

(Rather et al., 2024; Wu & Chang, 2024). This research bridges the gap by demonstrating the direct pathway from brand 

perception to increased customer loyalty and word-of-mouth recommendations, offering valuable insights for hotel 

management on leveraging brand strategies to enhance guest satisfaction and loyalty. This study further emphasises the 

importance of brand management in improving guest experiences and behaviours, paving the way for future scholarly 

investigations in the field. Third, this study significantly enriches relationship marketing theory by spotlighting the 

moderating role of swift guanxi in the interaction between marketing strategies—like price fairness, social media marketing, 

and service innovation—and hotel brand attributes, such as brand image and awareness. Despite the acknowledged 

importance of swift guanxi, research on its specific moderating effects within these relationships has been scant (Chen et 

al., 2022; Cheng et al., 2020). By addressing this gap, this study highlights the significance of incorporating swift guanxi 

into marketing strategies to enhance customer outcomes more effectively in the hospitality industry. It calls for deeper 

exploration into the nuanced interplay between marketing strategies and relational dynamics, proposing a path for more 

personalised and effective marketing tactics. 

This study has significant management ramifications as well. Instead of thinking only from the business 

perspective, hoteliers should concentrate on creating marketing strategies that align with the tastes of their target market. 

Hoteliers can amplify their brand image and awareness by seamlessly blending price fairness, social media marketing, and 

service innovation into their marketing arsenal. Price fairness establishes a foundation of trust and loyalty through 

transparent pricing that reflects the actual value of the stay. Social media marketing extends the hotel's reach, engaging 

potential and current guests with compelling content that showcases the hotel's unique offerings and fosters a vibrant 

community. Service innovation keeps the hotel at the forefront of the industry by introducing novel or improved services 

that enhance guest experiences. This triad strategy attracts a diverse audience and cultivates a strong, positive brand 

perception. For practical application, hoteliers should conduct detailed market research to align their offerings with guest 

expectations, using this insight to inform pricing and service development. Clear communication about the value behind 

their pricing should be disseminated across all marketing channels, particularly on social media, where engaging content 

can highlight the hotel's distinct features and encourage community engagement. Additionally, leveraging guest feedback 

and social media analytics can guide service innovation and content strategy, ensuring the hotel's offerings resonate with 

current trends and guest preferences. By adopting this holistic approach, hoteliers can ensure their brand stands out in a 

competitive landscape and remains dynamically aligned with guest desires, driving satisfaction and loyalty. 

Swift guanxi is another essential factor that may impact marketing factors (e.g., price fairness, social media 

marketing, and service innovation) and hotel brands (e.g., brand image and brand awareness). Hotels can use swift guanxi 

to ensure timely, personalised interactions with guests, use CRM systems to customise experiences, train staff in effective 

relationship-building techniques, and keep communication channels open. Prioritising swift guanxi can strengthen a hotel's 

competitive edge. For instance, sending personalised welcome messages via email or SMS immediately after booking can 

establish a direct line of communication, providing guests with valuable stay information and a personal touch. Using a 

CRM system to remember guest preferences for room types or dietary needs allows for customised experiences, such as 

greeting returning guests with their favourite wine or ensuring their preferred room is available, demonstrating meticulous 

attention to detail. Rapid response teams or social media platforms should be poised to address guest inquiries, complaints, 

or feedback promptly, underscoring the hotel's commitment to guest satisfaction. Designing loyalty programmes with clear, 

appealing rewards for repeat visits or referrals, like discounts or room upgrades, ensures guests feel appreciated and valued. 

Following up with a personalised thank-you message and feedback survey post-stay helps acknowledge guest contributions 

to service improvement and inform them about implemented changes based on their suggestions, reinforcing the 

relationship. Engaging with guests through social media marketing and creating a community around the hotel encourages 

sharing positive experiences, further enhancing the hotel's reputation and appeal. 

This study primarily targets guests who have stayed in luxury hotels in mainland China, which presents a limitation 

regarding generalizability. While offering valuable insights, this particular demographic may only partially represent the 

broader spectrum of hotel guests. As a result, the findings may be skewed toward the preferences and behaviours of a more 

affluent, luxury-oriented clientele. Additionally, by focusing on guests who actively engage with hotel services, the research 

may overlook the perspectives of those with varying levels of engagement. This selective focus could lead to an incomplete 

understanding of the effectiveness of relationship marketing strategies, thus limiting the study's comprehensiveness across 

the entire range of guests. Moreover, mainland China's unique cultural, economic, and social context heavily influences the 

study's results. While this provides detailed insights into the Chinese market, it also restricts the applicability of these 



Liang, Bangladesh Journal of Multidisciplinary Scientific Research 9(6) (2024), 1-16

 

12 

findings to other cultural or regional contexts, where different dynamics may exist, thereby limiting the study’s broader 

relevance. 

The hotel marketing industry is becoming increasingly dynamic and competitive. Many hotels use different 

marketing components to create plans that work, guaranteeing their future profitability and expansion. This study adds to 

the body of knowledge by developing and validating a model for customer loyalty and word-of-mouth recommendations 

amongst guests at luxury hotels, utilising relationship marketing theory. This study's findings acknowledge that combining 

marketing factors positively influences a hotel's brand image and awareness. This study further demonstrated that customer-

perceived service quality is critical to improving customer satisfaction outcomes. At the same time, swift guanxi acts as the 

boundary condition that may enhance consumers' loyalty and recommendation. Because of the investigation of various 

crucial marketing elements, this research has broadened the use of the relationship marketing model in the setting of luxury 

hotels. However, this study has many limitations that must be examined further. Data gathering was initially limited to 

China. Subsequent research endeavours may delve into luxury hotels across multiple nations to scrutinise disparities among 

cultural and national contexts. This study also uses a quantitative methodology. Future research on this topic should involve 

a comprehensive qualitative analysis of the context of luxury hotels. 

 

 
Author Contributions: Conceptualization, Y.L.; Methodology, Y.L.; Software, Y.L.; Validation, Y.L.; Formal Analysis, Y.L.; Investigation, Y.L.; 

Resources, Y.L.; Data Curation, Y.L.; Writing –Original Draft Preparation, Y.L.; Writing –Review & Editing, Y.L.; Visualization, Y.L., Supervision, 
Y.L.; Project Administration, Y.L.; Funding Acquisition, Y.L. Authors have read and agreed to the published version of the manuscript.  

Institutional Review Board Statement: Ethical review and approval were waived for this study because the research does not involve vulnerable groups 

or sensitive issues. 
Funding: The authors received no funding for this research. 

Acknowledgments: This research is part of the first author’s Ph.D. work at the UCSI University, Kuala Lumpur, Malaysia.  
Informed Consent Statement: Informed consent was obtained from all subjects involved in the study. 

Data Availability Statement: The data presented in this study are available on request from the corresponding author. The data are not publicly available 

due to restrictions.  
Conflicts of Interest: The authors declare no conflict of interest.      

 

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APPENDICES 

Appendix A: Measurement items and respective sources 

 
NO. Modified Scale Items Used in this Study Source 

Word-of-mouth 

Communication 

My family/friends influenced my attitude towards this hotel. 

My family/friends mentioned things I had not considered about this hotel. 
My family/friends provided some different ideas about this hotel. 

My family/friends influenced my evaluation of this hotel. 

My family/friends helped me decide on selecting this hotel. 

O'Cass and Grace (2004). 

Perceived 

Price Fairness 

I think the price I paid for this hotel is fair. 

I think the price I paid for this hotel is reasonable. 

I think the price I paid for this hotel is appropriate. 
I think the price I paid for this hotel is acceptable. 

Darke and Dahl (2003). 

Social Media 

Marketing 

This hotel's social media site shares enjoyable content. 

This hotel's social media site is up to date. 

This hotel's social media site facilitates two-way interaction with others. 

This hotel's social media site allows users to search for customized information. 

This hotel's social media site makes me want to share my opinions on brands, items, or 

services I have acquired with others. 

Kim and Ko (2010). 

Service Innovation I feel this hotel's products are innovative. 

I feel this hotel's staff is well-trained. 

I feel this hotel's operations are well-managed. 
I feel this hotel's strategic marketing activities are well-planned. 

Cheng et al. (2014). 

Swift Guanxi This hotel's staff and I understand each other's point of view. 

This hotel's staff and I can follow the flow of the conversation. 
This hotel's staff and I show interest in each other's opinions. 

This hotel's staff and I help each other. 

This hotel's staff and I establish a lasting friendship. 
This hotel's staff and I offer positive ratings or comments to each other. 

This hotel's staff and I tend to avoid conflicts. 

This hotel's staff and I respect each other. 
This hotel's staff and I maintain harmony. 

Ou et al. (2014) 

Brand Image This hotel's brand possesses complete practical functions (hotel services and adequate hotel 

facilities). 

This hotel's brand possesses a positive symbolic meaning (good reputation, credibility, and 
positive image). 

This hotel's brand provides me with a pleasant service experience. 

Hsieh and Li (2008). 

Brand Awareness I easily recognize the brand of this hotel. 
I easily recall the logo of this hotel. 

I pay attention to what other members share about this hotel. 

Chahal et al. (2020).   

Perceived Service 

Quality 

I feel this hotel's equipment is up to date. 

I feel this hotel's equipment is attractive. 
I feel this hotel's staff provides quality service. 

I feel this hotel's staff provide dependable service. 

I feel this hotel's staff is always willing to help. 

Parasuraman et al. (1988) 



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16 

I feel this hotel's staff is trustworthy. 

I feel this hotel's staff understands my specific requirements. 

Customer 

Satisfaction 

Overall, I am satisfied with the services and amenities provided by this hotel. 

Overall, this hotel meets my expectations. 

Overall, my decision to book this hotel was a wise one. 

Panjakakornsak (2008) 

Customer Loyalty In the future, I would like to revisit this hotel. 

I would like to recommend this hotel to my friends and family. 

I would like to speak positively about this hotel. 

Ndubisi's (2014) 

 

Appendix B: Common method factor analysis 

 
Construct Item Substantive Factor 

Loading (R1) 

R12 Method Factor 

Loading (R2) 

R22 

BA BA1 1.077*** 1.159929 -0.121** 0.014641  
BA2 1.087*** 1.181569 -0.138* 0.019044  
BA3 0.71*** 0.5041 0.257*** 0.066049 

BI BI1 1.006*** 1.012036 -0.099 NS 0.009801  
BI2 1.108*** 1.227664 -0.173*** 0.029929  
BI3 0.673*** 0.452929 0.269*** 0.072361 

CL CL1 0.88*** 0.7744 0.05 NS 0.0025  
CL2 0.895*** 0.801025 0.043 NS 0.001849  
CL3 0.988*** 0.976144 -0.094* 0.008836 

CS CS1 0.859*** 0.737881 0.078* 0.006084  
CS2 0.957*** 0.915849 -0.03 NS 0.0009  
CS3 0.521*** 0.271441 0.278*** 0.077284 

PF PF1 0.778*** 0.605284 0.131** 0.017161  
PF2 0.938*** 0.879844 -0.069 NS 0.004761  
PF3 0.991*** 0.982081 -0.114** 0.012996  
PF4 0.879*** 0.772641 0.049 NS 0.002401 

PSQ PSQ1 1.024*** 1.048576 -0.156* 0.024336  
PSQ2 1.009*** 1.018081 -0.132* 0.017424  
PSQ3 1.17*** 1.3689 -0.282*** 0.079524  
PSQ4 0.729*** 0.531441 0.204*** 0.041616  
PSQ5 0.73*** 0.5329 0.192** 0.036864  
PSQ6 1.025*** 1.050625 -0.116* 0.013456  
PSQ7 0.629*** 0.395641 0.279*** 0.077841 

SGX SGX1 0.865*** 0.748225 0.064 NS 0.004096  
SGX2 0.939*** 0.881721 0.005 NS 0.000025  
SGX3 1.046*** 1.094116 -0.114* 0.012996  
SGX4 0.961*** 0.923521 -0.03 NS 0.0009  
SGX5 0.898*** 0.806404 0.01 NS 0.0001  
SGX6 0.876*** 0.767376 0.037 NS 0.001369  
SGX7 0.928*** 0.861184 0.009 NS 0.000081  
SGX8 0.919*** 0.844561 0.001 NS 0.000001  
SGX9 0.889*** 0.790321 0.021 NS 0.000441 

SI SI1 0.823*** 0.677329 0.103* 0.010609  
SI2 1.066*** 1.136356 -0.131*** 0.017161  
SI3 0.945*** 0.893025 -0.009 NS 0.000081  
SI4 0.806*** 0.649636 0.044 NS 0.001936 

SMM SMM1 1.221*** 1.490841 -0.376*** 0.141376  
SMM2 1.002*** 1.004004 -0.086 NS 0.007396  
SMM3 0.836*** 0.698896 0.088 NS 0.007744  
SMM4 0.748*** 0.559504 0.187*** 0.034969  
SMM5 0.756*** 0.571536 0.164** 0.026896 

WOM WOM1 0.934*** 0.872356 -0.079 NS 0.006241  
WOM2 0.929*** 0.863041 -0.012 NS 0.000144  
WOM3 0.941*** 0.885481 -0.027 NS 0.000729  
WOM4 0.85*** 0.7225 0.089 NS 0.007921  
WOM5 0.853*** 0.727609 0.023 NS 0.000529 

Average 
 

0.9063913 
 

0.00623913 
 

Notes: NS p > 0.05; *p < 0.05; **p < 0.01; ***p < 0.001 
BA= Brand Awareness; BI = Brand Image; CL = Customer Loyalty; CS = Customer Satisfaction; PF = Price Fairness; PSQ = Perceived Service Quality; 

SGX = Swift Guanxi; SI = Service Innovation; SMM = Social Media Marketing; WOM= Word-of-Mouth Communication. 

 

 

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