Index

• Introduction
• Literature Review
• Method
• Results
• Discussion
• Conclusion
• References

Abstract

Studies on service quality have gained significant attention from practitioners, managers, and researchers in the tourism industry. Malaysia is experiencing an unstable and declining pattern in the rate of international tourists’ expenditure on services they receive in this country, highlighting a severe challenge in planning the right services to offer tourists since they refuse to spend on the services provided. Therefore, this research investigated the dimensions of service quality at the destination level to improve the quality of a destination. Self-administered questionnaires were distributed to international tourists from the United Kingdom and Australia at Kuala Lumpur International Airport. The pilot study’s data, involving 100 respondents, were tested using Exploratory Factor Analysis (EFA) and reliability analysis. Subsequently, 337 usable questionnaires were collected from fieldwork and analyzed using Confirmatory Factor Analysis (CFA). The study findings identified four dimensions of destination service quality: health and hygiene, accommodation, shopping, and information facilities. In addition, it suggested that tourism management and local citizens (Malaysians) should focus on these four dimensions to enhance the overall quality of service in Malaysia, thereby enhancing tourist satisfaction and spending on the services provided in the country. The limitation of this research was that the data were collected solely at Kuala Lumpur International Airport (KLIA). Future research may include other Malaysian international airports to strengthen the generalizability of the results.

Keywords: Confirmatory factor analysis, Destination service quality, Exploratory factor analysis, Malaysia, SERVPERF.

Received: 12 September 2022 / Revised: 4 November 2022 / Accepted: 25 November 2022 / Published: 12 December 2022

Contribution/ Originality

A limited number of previous studies have evaluated the performance of service quality at the destination level. Many prior studies measured service quality using the SERVQUAL rather than the SERVPERF model. Hence, the present study focused on the SERVPERF model to measure the service quality at a destination.

1. INTRODUCTION

Mulec (2010) argued that even if a location has the finest goods and experiences, it may not be able to persuade travelers to come unless it can create the impression in their minds that it provides something distinct, better, and more desirable than other places. Nevertheless, to stimulate return intention and recommendation behaviors, destinations must design, construct, promote, and coordinate satisfying experiences for visitors that maximize their economic contribution (Abdulla et al., 2020; Ahmad Puad, Fathilah, Siti Falindah, & Wan Mariam, 2018; Shariffuddin, Azinuddin, Hanafiah, & Zain, 2022).

Vassiliadis, Bista, and Fotiadis (2008) noted that tourists often travel far for their holidays to see new places, relax, and have new experiences. Since tourist expectations are constantly rising, it is necessary to emphasize service quality to improve growth strategies in the tourism industry and attain a competitive advantage (Muhamad Nasir, Mohamad, & Ab Ghani, 2021; Tosun, Dedeoğlu, & Fyall, 2015). Service quality at the destination level is based on service delivery processes (such as employees’ competence, efficiency, friendliness, and reliability) and the results of the service (such as food, accommodation, and recreational facilities) (Žabkar, Brenčič, & Dmitrović, 2010). Tosun et al. (2015) stated that destination service quality comprises the services provided at the destination, including accommodation, transportation, airport, hospitality, activities, cleanliness, and language. Hence, one of the indicators to evaluate the quality of service delivery is tourists’ expenditure on services they use at the destination. 

In the context of Malaysia, tourists normally spend on accommodation, shopping, food and beverages, local transportation, entertainment, international airfares using local carriers, domestic airfares, medical needs, fuel, and sports (Žabkar et al., 2010). However, the percentage change in international tourist expenditure in Malaysia has displayed an unstable and declining pattern, as illustrated in Figure 1. This indicates a severe challenge in terms of determining the right services to offer the tourists since they refuse to spend on the services currently provided in this country.

Figure 1. International tourists’ expenditure.

Source: Tourism Malaysia (2022).

It is essential to understand the service components in Malaysia to increase tourists’ expenditure. Hence, this research attempts to determine the definition and dimensions of service quality at the destination level, which could benefit scholars and tourism management to improve Malaysia’s quality as a destination.

2. LITERATURE REVIEW

2.1. Definition of Service Quality

To achieve the highest degree of visitor satisfaction, service quality must be better understood. Offering excellent service quality to tourists is crucial to achieving long-term business success (Abd Halim & Alsheikh, 2018; Muhamad Nasir et al., 2021). Hence, different scholars have provided different definitions of service quality, as illustrated in Table 1.

No.	Researchers	Definitions
1	Chen and Tsai (2007)	The visitor’s assessment of the standard of the service delivery process in association with the trip experience
2	Chen and Chen (2010)	Destination service quality is described as service performance at the attribute level
3	Kayat and Abdul Hai (2014)	The perceptions held by tourists towards tourism facilities and services that they observe and experience at the time of their visit
4	Tosun et al. (2015)	Tourists’ valuation of the performance of services consumed in a given tourist destination
5	Cong (2016)	A visitor’s quality experience, feelings, and overall evaluation of a destination
6	Yolal, Chi, and Pesämaa (2017)	A tourist’s quality perception of the service provided by the destination that they have stayed at
7	Mohamad, Ab Ghani, and Nasir (2019a)	Tourists’ overall assessment of the services and facilities at a destination based on their experiences and internal feelings

As shown in Table 1, Chen and Chen (2010) considered destination service quality to be service performance at the attribute level. The key feature of this definition is “attribute level,” which refers both to human-made (hotel, restaurant, and transportation) and natural-made (sea, mountains, and animals) facilities. Hence, service providers that can fully utilize the destination attributes, such as by providing sufficient logistics, comfortable hotels, and delicious food at restaurants, as well as exciting activities like hiking in beautiful mountains and diving in the open sea, would be considered by tourists to be service providers with the highest quality of service during their trip to a particular destination. On the other hand, Tosun et al. (2015) described service quality as visitors' evaluations of the performance of services consumed in a certain tourist location. Similarly, Yolal et al. (2017) defined service quality as tourists’ quality perception of the services provided at their destination. These two definitions focus on tourists’ perceptions, which relate to tourists’ cognitive evaluation of the services offered at the destination level, instead of solely evaluating the services themselves. Kayat and Abdul Hai (2014) extended their definition by including tourists’ perceptions of the facilities (public toilets and gyms) they experience during their trip. Similarly, Cong (2016) included tourists’ emotional responses to the services provided at the destination.
Hence, this study defines service quality as tourists' thoughts and views of the amenities and service performance they receive during their stay.

2.2. The Dimension of Service Quality

The SERVQUAL paradigm consists of five dimensions: tangible assets, reliability, empathy, responsiveness, and assurance. The term "tangible assets" refers to equipment, physical facilities, and personnel appearance, while "reliability" refers to a service provider's ability to execute the promised service consistently and properly. "Empathy" reflects the staff's ability to comprehend and attend to customers' needs, while "responsiveness" refers to the staff's eagerness to serve clients and provide prompt service. Finally, "assurance" relates to the competence and civility of personnel, as well as their capacity to gain customers' trust and confidence. Today, much research is aimed at evaluating tourist experiences at a destination, rather than evaluating the quality of the services provided by service providers such as tour operators, restaurants, and hotels, which suggests several disadvantages in the application of the SERVQUAL model (Žabkar et al., 2010). These disadvantages can be attributed to the assessment of the five service dimensions of the SERVQUAL model, namely assurance, reliability, tangible assets, empathy, and responsiveness. When depending on these dimensions for quality assessment, several essential factors of service encounters at the destination level, such as entertainment, attractions, and cultural experiences, may be omitted from the assessment (Žabkar et al., 2010). Furthermore, tourists travel far for their holidays to see new places, relax, and gain new experiences. At the same time, a destination offers various types of services, such as accommodation services of various qualities and prices, food and restaurant services, entertainment services, and transportation facilities (Vassiliadis et al., 2008). Tosun et al. (2015) argued that service quality encompasses both physical products and services.

No.	Author	Dimension
1	Narayan, Rajendran, Sai, and Gopalan (2009)	10 dimensions: Core-tourism experience Information Hospitality Fairness of price Hygiene Amenities Value for money Logistics Food Security
2	Lopez-Toro, Diaz-Munoz, and Perez-Moreno (2010)	7 dimensions: Hotels and apartments Accessibility and small businesses items Image of the destination Tangible elements of retail outlets Services outside hotels Overcrowding Beaches
3	Moutinho, Albayrak, and Caber (2012)	5 dimensions: Shopping Health and hygiene Information and facilities Transportation Accommodation
4	Kim, Holland, and Han (2013)	2 dimensions: Performance-based quality Product-based quality
5	Kayat and Abdul Hai (2014)	2 dimensions: Perceived tour service quality Perceived hospitality service quality
6	Rajaratnam, Nair, Sharif, and Munikrishnan (2015)	7 dimensions: Accessibility and logistics Core tourism experience Hygiene Information Security Value for money Hospitality
7	Tosun et al. (2015)	7 dimensions: Accommodation Local transport Cleanliness Hospitality Activities Language communication Airport services
8	Cong (2016)	5 dimensions: Transport Destination brand Attraction Hospitality Entertainment

Žabkar et al. (2010) claimed that most tourism studies use destination attributes as a way to evaluate the quality of tourism destinations as these attributes are strongly related and that a quality assessment should articulate the relevancy of the features of a specific destination. Table 2 demonstrates the diversity of the service quality dimensions used by previous researchers to evaluate destination-level service quality.

As shown in Table 2, Narayan et al. (2009) assessed service quality using 10 dimensions. In the context of the tourist sector, the term "core-tourism experience" refers to its wholeness. Information relates to general knowledge about the tourist site. Hospitality relates to the tourist's expectation that others will be cordial and pleasant, beginning with immigration officials at the port of entry and extending to the tour operator, hotel staff (Burns, Graefe, & Absher, 2003; Tribe & Snaith, 1998), and locals (Yüksel & YuÈksel, 2001). The fairness of prices refers to the tourist’s expectation of a fair payment system between them and residents. For instance, taxi drivers are expected to charge tourists and residents the same rate. Hygiene implies that tourists expect cleanliness at airports, places of stay (Yüksel & YuÈksel, 2001), tourist destinations (Tribe & Snaith, 1998; Yüksel & YuÈksel, 2001), and restaurants (Yüksel & YuÈksel, 2001), as well as the overall cleanliness of food available at the destination. Amenities relate to how the destination provides comfort and convenience to tourists, such as money exchange facilities for tourists to convert their money into local currency and easy access to medical help in case of emergency. Value for money means that tourists feel the money spent is worth the accommodation, tour packages, domestic flights, and food provided. Logistics is associated with frequent transport services, covering a wide range of transport types, from cars and buses to boats, for the logistics of transporting passengers (Mohamad, Nasir, Ab Ghani, & Afthanorhan, 2019c). Meanwhile, tourists expect food to be available in the places they intend to consume it, whether local cuisine or foods they eat in their home country. Security is concerned with the expectation of a safe and pleasant destination during their trip.

Rajaratnam et al. (2015) measured service quality similarly to Narayan et al. (2009). The seven dimensions used are identical, except that these authors exclude fairness of price, amenities, and food. In contrast, Kim et al. (2013) assessed tourist destinations in terms of performance-based quality as well as product-based quality. In other words, the authors evaluated both the “process” and the “outcome” of service delivery. Cong (2016) included one vital dimension to evaluate service quality in Vietnam, namely destination brand. This dimension refers to people’s personalities when they offer services, including their friendliness, elegance, and empathy, which could instill in tourists the perception that the Vietnamese possess positive attributes when delivering services. Nevertheless, the most prevalent dimensions that the majority of destinations utilize to demonstrate the quality of their services are those suggested by Moutinho et al. (2012),comprising the dimensions of shopping, health and hygiene, information, facilities, transportation, and accommodation.

2.3. The Measurement Approach to Service Quality

Markovic and Raspor (2010) highlighted that the specific nature of services makes it difficult to provide, measure, and maintain quality. Santos (2003) established two primary conceptualizations of service quality based on the literature. The first is based on the approach of disconfirmation, while the second is based on performance. In addition, Brady and Cronin Jr (2001) asserted that the cornerstone of service quality theory is found in the literature on product quality and customer satisfaction. Brady and Cronin Jr (2001) and Tian-Cole and Cromption (2003) noted that research on service quality based on the disconfirmation paradigm was pioneered between 1982 and 1984 and 1985 and 1988, respectively. Earlier, Grönroos (1984) had argued that the evaluation process begins when consumers compare their expectations to the services they believe they experienced. This process is known as perceived quality of service and highlights that service quality is based on two factors, namely anticipated service, and perceived service. Therefore, Grönroos (1984) proposed two primary aspects of service quality: technical quality and functional quality. Technical quality relates to what the client experiences, while functional quality pertains to how they perceive it.

Parasuraman, Zeithaml, and Berry (1985) also established a model for assessing service quality. According to the gap theory proposed by Parasuraman et al. (1985), the concept of service quality is based on the incompatibility between customers' expectations regarding the performance of a broad category of service providers and their evaluations of the actual performance of service providers within the category. In other words, according to Park and Yi (2016), SERVQUAL measures the discrepancy between expectation and performance in service quality. SERVQUAL, or the performance-expectation measure of service quality, has become a widely used instrument and has been used in a variety of service sectors, such as retail, dental services, hotels, travel and tourism, vehicle maintenance, business schools, and hospitality (Markovic & Raspor, 2010; Park & Yi, 2016). The instruments of SERVQUAL have been modified to suit the features of specific services (Markovic & Raspor, 2010). Even though many studies have applied the SERVQUAL model, the conceptual and operational basis of the model has been criticized by several academicians, particularly its validity, reliability, operationalization of expectations, and dimensional structure (Markovic & Raspor, 2010). This was reinforced by Cronin and Taylor (1992), who found that the impression of service quality is better described by the performance measure than by expectations.

The SERVPERF model was pioneered by Cronin and Taylor (1992) and Jain and Gupta (2004). Cronin and Taylor created SERVPERF because, according to them, Parasuraman et al.’s (1985) conceptualization and characterization of service quality (SERVQUAL) were insufficient. The SERVPERF model is recognized as a performance-only measure of service quality, often known as customer perception of performance (Park & Yi, 2016). According to Jain and Gupta (2004), the SERVPERF scale is an essential alternative to SERVQUAL that contains a conceptually and methodologically better scale than the SERVQUAL scale. This is supported by Jo Bitner, Faranda, Hubbert, and Zeithaml (1997), who stated that service encompasses quality attributes of the experience that can only be recognized during and/or after the consumption phase; however, goods contain several search quality attributes, which are suitable for SERVQUAL measures. In contrast, the SERVPERF model gathers opinions on service quality based on the perceptions of tourists after experiencing or using the services or products (Yusof & Rahman, 2011).

Moutinho et al. (2012) argued that the quality of service at a destination should be measured using a performance-only approach achieved by separate means that depend on performance at the consumption stage (at the destination). This is because the use of a performance-only approach offers more consistent results than the performance-expectation approach (Moutinho et al., 2012).

Based on the reviewed literature, this study aims to measure the service quality of a destination using a performance-only approach with destination attributes developed by Moutinho et al. (2012), which comprise five dimensions: 1) shopping, 2) health and hygiene, 3) information and facilities, 4) transportation, and 5) accommodation, as most previous studies have applied a performance-only approach. Additionally, it was argued by Cronin and Taylor (1992)  that perceived service quality should be conceptualized and studied as an attitude, and the performance-only approach should be used to adequately comprehend consumers' perceptions of the service quality offered by service providers. In their study of service quality at a destination in Manavgat, Turkey, Moutinho et al. (2012) measured destination service quality based solely on customer perception of the destination, as opposed to measuring the importance of service features or the gap between customer expectations and service quality attributes. Furthermore, the five mentioned dimensions are among the service components that international tourists spend the most on during their vacations in Malaysia, as suggested by Tourism Malaysia (2022). Consequently, the primary objective of this research is to evaluate the aspects of service quality at the destination level to improve Malaysia's standing as a tourism destination and thereby increase tourists’ expenditure on the services they consume in Malaysia.

3. METHOD

3.1. Survey Instruments

A closed-ended questionnaire was employed in this study to gather primary data on service quality. The questionnaire adapted 14 items from Moutinho et al. (2012) to measure service quality. Once the pilot study had been completed, 10 items were utilized in the final survey, while 4 items were removed from the questionnaire.  Participants were asked to rate the perceived service quality of the items on a scale ranging from 1 for "extremely bad" to 10 for "very excellent."

3.2. Pilot Study

A pilot study was conducted at Kuala Lumpur International Airport (KLIA), using respondents with comparable backgrounds to the real participants. During this pilot project, information was collected from 100 participants from the United Kingdom and Australia. The data were analyzed using two statistical methods: exploratory factor analysis (EFA) and a reliability test. EFA was used to minimize and summarize the aspects of the destination service quality dimension, while the reliability test assessed the instrument's validity and dependability.

3.3. Exploratory Factor Analysis (EFA)

EFA was used to characterize and summarize the data by grouping associated variables together (Zikmund & Babib, 2010). After gathering the pilot test data, EFA was used to determine the underlying aspects of destination service quality. Table 3 displays the results of the Kaiser–Meyer–Olkin (KMO) and Bartlett spherical tests for service quality. As indicated by Hair, Black, Babin, and Anderson (2014), the KMO value was more than 0.5, and the result of Bartlett's test of sphericity was significant (p < 0.001). Hence, the destination service quality variable was suitable for EFA.

Construct	KMO (> 0.50)	Bartlett’s Test of Sphericity
Service Quality	0.680	0.00

Table 4 presents the number of items for each variable after EFA was conducted. The number of items for each construct was reduced through the extraction process. The items with factor loadings of more than 0.60 were retained and included in the actual survey. The first dimension of service quality was health and hygiene (QF1). This dimension included the items of general environmental cleanliness (Q5), cleanliness of food and drink (Q6), and cleanliness of public toilets (Q7). Another dimension of service quality was accommodation (QF2). This dimension was measured using three items, namely the overall cleanliness of the hotel (Q12), the quality of food and drink at the hotel (Q14), and the manners of the hotel staff (Q13). The third dimension of service quality was shopping (QF3). This dimension included the items of shopkeepers’ manners towards tourists (Q1) and shopkeepers’ honesty (Q2). The fourth dimension of service quality was information content (FQ4), which included opportunities to obtain maps, brochures, etc. about the region (Q9), as well as information signs and symbols (Q10).

3.4. Reliability Analysis

Reliability analysis was used to ensure the research instrument was free of random error and without bias (Sekaran & Bougie, 2016) . The test revealed a Cronbach's alpha value of 0.79 for destination service quality after EFA. As the value of 0.79 was greater than 0.7, the study’s measure of destination service quality was error-free, reliable, and fit for use in the actual survey.

Items in destination service quality	Factor Loadings	Eigen Value	Variance Explained (%)
Service Quality:
QF1: Health and Hygiene		4.050	25.006
General environmental cleanliness (Q5)	0.878
Cleanliness of food and drink (Q6)	0.868
Cleanliness of public toilets (Q7)	0.765
QF2: Accommodation		1.702	22.206
Overall cleanliness of the hotel (Q12)	0.790
The quality of food and drink at the hotel (Q14)	0.863
Manners of the hotel staff (Q13)	0.844
QF3: Shopping		1.381	19.269
Shopkeepers’ manners towards tourists (Q1)	0.933
Shopkeepers’ honesty (Q2)	0.886
QF4: Information Content		1.188	16.739
Opportunities to obtain maps, brochures, etc. about the region (Q9)	0.902
Information signs and symbols (Q10)	0.837
Total Variance Explained (%)			83.221

3.5. Method of Data Collection

The questionnaire was finalized after the analysis of the pilot study data had been completed. Since the target respondents were from the United Kingdom and Australia, an international airport was selected as the location for data collection. This approach has been used by other researchers in the same area to reach their target population, including Mohamad, Afthanorhan, Awang, and Mohammad (2019b), Hapsari, Clemes, and Dean (2016), Leong, Yeh, Hsiao, and Huan (2015), Kim et al. (2013), Sun, Chi, and Xu (2013), Lee, Lee, and Choi (2011), Wang, Zhang, Gu, and Zhen (2009), and Kozak (2001). Kuala Lumpur International Airport (KLIA) was therefore chosen as the location to conduct the actual study as the airport is the primary point of departure and entry for many foreign travelers to Malaysia. 

3.6. Analysis Description

The data were analyzed using the programs Statistical Package for Social Science (SPSS version 22) and Analysis of Moment Structure (AMOS version 23). Utilizing SPSS, descriptive analysis, reliability analysis, and exploratory factor analysis were conducted. AMOS software was applied to assess the validity of the measurement model by determining uni-dimensionality, evaluating model goodness of fit, and establishing construct validity using confirmatory factor analysis.

4. RESULTS

4.1. Profile of Respondents

In this study, a total of 337 tourists provided valid responses for the descriptive analysis. The data revealed that 51.9 percent (n=175) of the tourists were from the United Kingdom, whereas 48.1 percent (n=162) were from Australia. Among the tourists who participated in this survey, female tourists represented 56.7 percent (n=191), and male tourists represented 43.3 percent (n=146). The majority of the tourists were between the ages of 25 and 34, representing 27.3 percent (n=92) of the total sample. Most of the tourists claimed that it was their first time visiting Malaysia (57.3% or n=193). Another 42.7 percent (n=144) claimed that they were repeat tourists (second to more than fifth visit).

 4.2. Confirmatory Factor Analysis (CFA)

Confirmatory factor analysis can be used to confirm the measurement model derived from the exploratory factor analysis (Hair et al., 2014). Figure 2 depicts the 10 items that made up the measurement approach to the quality of destination service.

To assess the fit of the measurement model, several goodness-of-fit indicators were used as a guideline in this study. Table 5 displays the goodness-of-fit for the destination service quality measurement model. Root Mean Square Error Approximation (RMSEA) was used as a guideline in this investigation. The model produced an RMSEA score of 0.074, which indicates a good fit. According to Hair, Black, Babin, Anderson, and Tatham (2010), the suggested cut-off limit for RMSEA should be less than 0.08. In addition to RMSEA, the fit of the measurement model was evaluated using the Comparative Fit Index (CFI), Goodness of Fit Index (GFI), Tucker-Lewis Index (TLI), and p-value.

At 0.974, the CFI score revealed a strong fit. In addition, the GFI and TLI values indicated a good fit with values of 0.95 and 0.960, respectively, in line with the model fit indices given by Hair et al. (2010), which demanded values larger than 0.90. The p-value for the destination service quality model was statistically significant (p < 0.05). A chi-square (ratio) with a normal distribution was used to determine the model's fit. The normed chi-square (ratio) value was less than 3, indicating a better-fitting model (Hair et al., 2010). After reviewing the measurement model's goodness of fit, it was necessary to analyze the model's uni-dimensionality, reliability, and validity.

Table 6 provides the construct's standardized factor loading Composite Reliability (CR) and Average Variance Extracted (AVE) values. The standardized factor loadings were greater than 0.6, indicating that the service quality constructs had attained uni-dimensionality. The data also revealed that the dependability condition was met since the construct's CR values were above 0.60. The AVE values of more than 0.5 suggested that the model had acceptable convergent validity.

Index	Level of acceptance	Measurement Model 2	Remarks
Absolute fit:
Chi-Square	P-value > 0.05	0.00	Not applicable if sample size is more than 200
Root Mean Square Error Approximation (RMSEA)	< 0.08	0.074	Achieved
Goodness of Fit Index (GFI)	> 0.90	0.954	Achieved
Incremental fit:
Comparative Fit Index (CFI)	> 0.90	0.974	Achieved
Tucker-Lewis Index (TLI)	> 0.90	0.960	Achieved
Parsimonious fit:
Chi-square/df	< 3.00	2.833	Achieved

Construct/Items	Factor Loading	CR	AVE
Service Quality:		0.815	0.527
Shopping (QF1)	0.82
Health and Hygiene (QF2)	0.74
Accommodation (QF3)	0.71
Information and Facilities (QF4)	0.62
Shopping (QF1):
Shopkeepers’ manners towards tourists (Q1)	0.90	0.884	0.792
Shopkeepers’ honesty (Q2)	0.88
Health and Hygiene (QF2):		0.864	0.681
Cleanliness of food and drink (Q4)	0.90
Cleanliness of public toilets (Q5)	0.77
General environmental cleanliness (Q3)	0.80
Accommodation (QF3):		0.895	0.740
Overall cleanliness of the hotel (Q8)	0.87
The quality of food and drink at the hotel (Q10)	0.88
Manners of the hotel staff (Q9)	0.83
Information Content (QF4):		0.856	0.748
Opportunities to obtain maps, brochures, etc. about the region (Q6)	0.85
Information signs and symbols (Q7)	0.88

Factors	Shopping (QF1)	Health and Hygiene (QF2)	Accommodation (QF3)	Information Content (QF4)
Shopping (QF1)	0.88
Health and Hygiene (QF2)	0.58	0.82
Accommodation (QF3)	0.59	0.53	0.86
Information Content (QF4)	0.48	0.57	0.37	0.86

The last stage in verifying the validity of a measuring model is to assess the discriminant validity. To prevent multi-collinearity issues, the constructs in a model must be distinguishable from one another (Mohamad et al., 2019b). It is important to compare the values of the square root of AVE of the construct with the values of the correlation between the relevant constructs to demonstrate discriminant validity. In this case, discriminant validity is attained when the square root of AVE for each construct is greater than the correlation value between the corresponding constructs (Mohamad et al., 2019b). The value of the correlations between the constructs should not exceed 0.85 (Mohamad et al., 2019b). Table 7 illustrates the results of discriminant validity for the pooled model. The results show that all these requirements were met, with none of the correlations surpassing the diagonal values (square root AVE).

5. DISCUSSION

Park. and Jeong (2019) claimed that studies on service quality at tourism destinations are vital to achieving a competitive advantage and increasing tourist organizations’ profit. Hence, this research aimed to investigate the dimensions of service quality at the destination level to improve a destination’s quality. Furthermore, Malaysia is experiencing an unstable and declining pattern in the rate of international tourists’ expenditure on services they consume, indicating a serious challenge in deciding the right services to provide to tourists since they refuse to spend on the services provided. Hence, the present study adopted the dimensions suggested by Moutinho et al. (2012), comprising the dimensions of shopping, health and hygiene, information facilities, transportation, and accommodation. The findings revealed that the factors contributing to service quality included shopping, health and cleanliness, accommodation, and information content and that these factors influenced the experiences of tourists from the United Kingdom and Australia in Malaysia. This study’s finding concurs with the study of Moutinho et al. (2012), in which the four dimensions used were similar to the ones suggested in our study. In the present study, tourists who visited Malaysia were mostly first-time tourists. They evaluated service quality based on shopping, health and hygiene, accommodation, and information facilities as the components of service quality that most contributed to their satisfaction during their visit to Malaysia. By concentrating on these dimensions of service quality, tourists’ expenditure on services they consume within this country could be increased.

5.1. Managerial Implications

Several Malaysian entities, such as Tourism Malaysia (Malaysia Tourism Promotion Board) and other tourism-related agencies and businesses, could benefit from this study by encouraging related parties, especially hoteliers, restaurant owners, and local people (Malaysians) to practice conducive manners and embrace good hygiene practices to ensure the cleanliness of the environment, facilities, and public amenities, including public toilets, food at restaurants, and the hotel environment. By providing excellent cleanliness, foreign tourists who visit Malaysia will be impressed with the cleanliness and hygiene of Malaysians. Other related service providers, such as shopping areas and hotels, need to ensure that their staff can deliver high-quality products and great services with a positive attitude.

In addition, the tourism management board should upgrade access to information facilities in the form of brochures, maps, and informative signs and symbols to provide correct facts and additional information, which will ensure tourists’ satisfaction with the services, thus improving profitability in the future. These practices will also create loyal visitors who are pleased to select Malaysia as their travel destination and will continue to visit Malaysia in the future, in addition to recommending Malaysia as a travel destination to others.

6. CONCLUSION

Malaysia's tourist industry is one of the most significant contributors to the country's economy. The concept of service quality is important to enhance tourists’ expenditure on the services they consume at their destination. Therefore, this study investigated the concept of service quality by assessing its dimensions among international tourists visiting Malaysia from the United Kingdom and Australia. The data from the pilot study were subjected to Exploratory Factor Analysis (EFA) and reliability analysis. EFA was conducted to simplify and summarize the quality aspects of the destination’s services. Meanwhile, Cronbach’s alpha was used to analyze the instrument's internal dependability as part of the reliability analysis. Next, confirmatory factor analysis was conducted to validate the study’s measurement model using the field study data (Nasir, Mohamad, Ghani, & Afthanorhan, 2020). Four dimensions (shopping, health and cleanliness, accommodation, and information content) of service quality were observed to be crucial to increasing tourists’ expenditure during their visits to this country. However, there were limits to this research, since the sole data collection location was Kuala Lumpur International Airport (KLIA). Therefore, the study's applicability in the context of research techniques may be restricted. To strengthen the generalizability of these results, data collection should include more Malaysian international airports, such as Penang International Airport, Langkawi International Airport, Kota Kinabalu International Airport, and Kuching International Airport.

Funding: This study received no specific financial support.

Competing Interests: The authors declare that they have no competing interests.

Authors’ Contributions: All authors contributed equally to the conception and design of the study.

REFERENCES

Abd Halim, M. S. B., & Alsheikh, G. A. A. (2018). The impact E-commerce service quality to loyalty evidence study in Malaysian hotel industry. International Journal of Academic Research in Business and Social Sciences, 8(12), 1-11.Available at: https://doi.org/10.6007/ijarbss/v8-i12/5071.

Abdulla, S. A. M., Khalifa, G. S., Abuelhassan, A. E., Nordin, B. B., Ghosh, A., & Bhaumik, A. (2020). Advancement of destination service quality management technology in tourism industry. Journal of Critical Reviews, 7(11), 2317-2324.

Ahmad Puad, M. S., Fathilah, I., Siti Falindah, P., & Wan Mariam, W. A. (2018). Host-guest expectations of service quality at small Island settings: A cross-cultural approach. International Journal of Engineering & Technology, 7(4), 374-376.Available at: https://doi.org/10.14419/ijet.v7i4.34.26876.

Brady, M. K., & Cronin Jr, J. J. (2001). Some new thoughts on conceptualizing perceived service quality: A hierarchical approach. Journal of Marketing, 65(3), 34-49.Available at: https://doi.org/10.1509/jmkg.65.3.34.18334.

Burns, R. C., Graefe, A. R., & Absher, J. D. (2003). Alternate measurement approaches to recreational customer satisfaction: Satisfaction-only versus gap scores. Leisure Sciences, 25(4), 363-380.Available at: https://doi.org/10.1080/714044496.

Chen, C. F., & Chen, F. S. (2010). Experience quality perceived value satisfaction and behavioral intentions for heritage tourists. Tourism Management, 31(1), 29-35.Available at: https://doi.org/10.1016/j.tourman.2009.02.008.

Chen, C. F., & Tsai, D. (2007). How destination image and evaluative factors affect behavioral intentions? Tourism Management, 28(4), 1115-1122.Available at: https://doi.org/10.1016/j.tourman.2006.07.007.

Cong, L. C. (2016). A formative model of the relationship between destination quality tourist satisfaction and intentional loyalty: An empirical test in Vietnam. Journal of Hospitality and Tourism Management, 26, 50-62.Available at: https://doi.org/10.1016/j.jhtm.2015.12.002.

Cronin, J., J. J., & Taylor, S. A. (1992). Measuring service quality: A reexamination and extension. Journal of Marketing, 56(3), 55-68.Available at: https://doi.org/10.2307/1252296.

Grönroos. (1984). A service quality model and its marketing implications. European Journal of Marketing, 18(4), 36-44.Available at: https://doi.org/10.1108/eum0000000004784.

Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2014). Multivariate data analysis (7th ed.). United States: Pearson Education Limited.

Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2010). Multivariate data analysis (7th ed.). New Jersey: Pearson Prentice Hall.

Hapsari, R., Clemes, M., & Dean, D. (2016). The mediating role of perceived value on the relationship between service quality and customer satisfaction: Evidence from Indonesian airline passengers. Procedia Economics and Finance, 100(35), 388-395.Available at: https://doi.org/10.1016/s2212-5671(16)00048-4.

Jain, S. K., & Gupta, G. (2004). Measuring service quality: Servqual Vs. Servperf scales. Option, 29(2), 25-38.Available at: https://doi.org/10.1177/0256090920040203.

Jo Bitner, M., Faranda, W. T., Hubbert, A. R., & Zeithaml, V. A. (1997). Customer contributions and roles in service delivery. International Journal of Service Industry Management, 8(3), 193-205.Available at: https://doi.org/10.1108/09564239710185398.

Kayat, K., & Abdul Hai, M. (2014). Perceived service quality and tourists' cognitive image of a destination. Anatolia, 25(1), 1-12.Available at: https://doi.org/10.1080/13032917.2013.814580.

Kim, S. H., Holland, S., & Han, H. S. (2013). A structural model for examining how destination image perceived value and service quality affect destination loyalty: A case study of Orlando. International Journal of Tourism Research, 15(4), 313-328.Available at: https://doi.org/10.1002/jtr.1877.

Kozak, M. (2001). Repeaters' behavior at two distinct destinations. Annals of Tourism Research, 28(3), 784-807.Available at: https://doi.org/10.1016/s0160-7383(00)00078-5.

Lee, J. S., Lee, C. K., & Choi, Y. (2011). Examining the role of emotional and functional values in festival evaluation. Journal of Travel Research, 50(6), 685-696.Available at: https://doi.org/10.1177/0047287510385465.

Leong, A. M. W., Yeh, S. S., Hsiao, Y. C., & Huan, T. C. T. (2015). Nostalgia as travel motivation and its impact on tourists' loyalty. Journal of Business Research, 68(1), 81-86.Available at: https://doi.org/10.1016/j.jbusres.2014.05.003.

Lopez-Toro, A. A., Diaz-Munoz, R., & Perez-Moreno, S. (2010). An assessment of the quality of a tourist destination: The case of Nerja Spain. Total Quality Management, 21(3), 269-289.Available at: https://doi.org/10.1080/14783360903553164.

Markovic, S., & Raspor, S. (2010). Measuring perceived service quality using SERVQUAL: A case study of the croatian hotel industry. Management, 5(3), 195-209.

Mohamad, M., Ab Ghani, N. I., & Nasir, M. M. (2019a). The impact of perceived value destination service quality and tourist satisfaction on destination loyalty among international tourists visiting Malaysia. Journal of Tourism, 4(16), 10-26.Available at: https://doi.org/10.35631/jthem.416002.

Mohamad, M., Afthanorhan, A., Awang, Z., & Mohammad, M. (2019b). Comparison between CB-SEM and PLS-SEM: Testing and confirming the maqasid syariah quality of life measurement model. The Journal of Social Sciences Research, 5(3), 608-614.Available at: https://doi.org/10.32861/jssr.53.608.614.

Mohamad, M., Nasir, M. N. M., Ab Ghani, N. I., & Afthanorhan, A. (2019c). Parallel mediators of place attachment and tourist satisfaction in destination attractiveness destination loyalty and service quality. International Journal of Innovation Creativity and Change, 7(7), 228-256.

Moutinho, L., Albayrak, T., & Caber, M. (2012). How far does overall service quality of a destination affect customers' post-purchase behaviours? International Journal of Tourism Research, 14(4), 307-322.Available at: https://doi.org/10.1002/jtr.856.

Muhamad Nasir, M. N., Mohamad, M., & Ab Ghani, N. I. (2021). Modelling the relationships between destination attractiveness service quality tourist satisfaction and destination loyalty. Asia-Pacific Journal of Innovation in Hospitality and Tourism, 10(2), 1-19.

Mulec, I. (2010). Promotion as a tool in sustaining the destination marketing activities. Tourism, 14(1), 13-21.Available at: https://doi.org/10.5937/turizam1001013m.

Narayan, B., Rajendran, C., Sai, L. P., & Gopalan, R. (2009). Dimensions of service quality in tourism–an Indian perspective. Total Quality Management, 20(1), 61-89.Available at: https://doi.org/10.1080/14783360802614299.

Nasir, M., Mohamad, M., Ghani, N., & Afthanorhan, A. (2020). Testing mediation roles of place attachment and tourist satisfaction on destination attractiveness and destination loyalty relationship using phantom approach. Management Science Letters, 10(2), 443-454.Available at: https://doi.org/10.5267/j.msl.2019.8.026.

Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1985). A conceptual model of service quality and its implications for future research. Journal of Marketing, 49(4), 41-50.Available at: https://doi.org/10.2307/1251430.

Park, S. J., & Yi, Y. (2016). Performance-only measures vs performance-expectation measures of service quality. The Service Industries Journal, 36(15-16), 741-756.Available at: https://doi.org/10.1080/02642069.2016.1275579.

Park., J., & Jeong, E. (2019). Service quality in tourism: A systematic literature review and keyword network analysis. Sustainability, 11(13), 3665.Available at: https://doi.org/10.3390/su11133665

Rajaratnam, S. D., Nair, V., Sharif, S. P., & Munikrishnan, U. T. (2015). Destination quality and tourists’ behavioural intentions: Rural tourist destinations in Malaysia. Worldwide Hospitality and Tourism Themes, 7(5), 463-472.Available at: https://doi.org/10.1108/whatt-06-2015-0026.

Santos, J. (2003). E-service quality: A model of virtual service quality dimensions. Managing Service Quality, 13(3), 233-246.Available at: https://doi.org/10.1108/09604520310476490.

Sekaran, U., & Bougie, R. (2016). Research methods for business: A skill building approach (6th ed.). United Kingdom: John Wiley and Sons Ltd.

Shariffuddin, N. S. M., Azinuddin, M., Hanafiah, M. H., & Zain, W. M. A. W. M. (2022). A comprehensive review on tourism destination competitiveness literature. Competitiveness Review: An International Business Journal.Available at: https://doi.org/10.1108/cr-04-2021-0054.

Sun, X., Chi, G., & Xu, H. (2013). Developing destination loyalty: The case of Hainan Island. Annals of Tourism Research, 43, 547-577.Available at: https://doi.org/10.1016/j.annals.2013.04.006.

Tian-Cole, S., & Cromption, J. (2003). A conceptualization of the relationships between service quality and visitor satisfaction and their links to destination selection. Leisure Studies, 22(1), 65-80.Available at: https://doi.org/10.1080/02614360306572.

Tosun, C., Dedeoğlu, B. B., & Fyall, A. (2015). Destination service quality affective image and revisit intention: The moderating role of past experience. Journal of Destination Marketing & Management, 4(4), 222-234.Available at: https://doi.org/10.1016/j.jdmm.2015.08.002.

Tourism Malaysia. (2022). International tourists expenditure in Malaysia. Retrieved from: https://tourism.gov.my/statistics.

Tribe, J., & Snaith, T. (1998). From servqual to holsat: Holiday satisfaction in varadero Cuba. Tourism Management, 19(1), 25–34.

Vassiliadis, C., Bista, R., & Fotiadis, A. (2008). Basic service quality dimensions in tourist destination planning. Journal of Tourism Challenges and Trends, 1(2), 33-44.

Wang, X., Zhang, J., Gu, C., & Zhen, F. (2009). Examining antecedents and consequences of tourist satisfaction: A structural modeling approach. Tsinghua Science and Technology, 14(3), 397-406.Available at: https://doi.org/10.1016/s1007-0214(09)70057-4.

Yolal, M., Chi, C. G.-Q., & Pesämaa, O. (2017). Examine destination loyalty of first-time and repeat visitors at all-inclusive resorts. International Journal of Contemporary Hospitality Management, 29(7), 1834-1853.Available at: https://doi.org/10.1108/ijchm-06-2015-0293.

Yüksel, A., & YuÈksel, F. (2001). Comparative performance analysis: Tourists’ perceptions of Turkey relative to other tourist destinations. Journal of Vacation Marketing, 7(4), 333-355.Available at: https://doi.org/10.1177/135676670100700404.

Yusof, N. A., & Rahman, F. A. (2011). Tourists perceptions of service quality in a lake-based tourism area. Paper presented at the In International Conference on Business and Economics Research.

Žabkar, V., Brenčič, M. M., & Dmitrović, T. (2010). Modelling perceived quality visitor satisfaction and behavioural intentions at the destination level. Tourism Management, 31(4), 537-546.Available at: https://doi.org/10.1016/j.tourman.2009.06.005.

Zikmund, W. G., & Babib, B. J. (2010). Essentials of marketing research (4th ed.). USA: South-Western Cengage Learning.

Views and opinions expressed in this article are the views and opinions of the author(s), Journal of Tourism Management Research shall not be responsible or answerable for any loss, damage or liability etc. caused in relation to/arising out of the use of the content.