Airasias service quality marketing essay

AirAsia is the largest low cost carrier in the region, and amongst the largest in the world. The liberalisation of the domestic airline industry in Malaysia has seen an increase in the intensity of the competition between AirAsia and Malaysia Airlines. Therefore, this study was conducted to identify the level of AirAsia’s service quality, by using SERVQUAL to see if their performance met customers’ expectations, and whether these expectations vary from customer to customer, based on demographics and experience with the organisation.

INTRODUCTION

Statement of the Problem

While AirAsia has faced competition since its inception, the liberalisation of the domestic airline industry in Malaysia has seen an increase in the intensity of the competition between AirAsia and Malaysia Airlines (Ong and Tan, 2009; Bernama, 2009). Recently, Malaysia Airlines launched its ” Everyday Low Fares” programme which sees it offering zero-fare or low-fare seats (Wong, 2008; Yeow, 2008). This was implemented in an effort to see empty seats on Malaysia Airline flights filled up, while attempting to create new demand among consumers that would not normally fly with Malaysia Airlines (Yeow, 2008; TheStar Online, 2008). AirAsia saw this scheme as a move by Malaysia Airlines to compete directly with AirAsia, and claimed that this was a form of unfair competition (Ng, 2008; Daily Express, 2008).

On other fronts, AirAsia is also seeing intense competition from other low cost carriers in the region (Ricart and Wang, 2005; Chong, 2008). Since the start up of AirAsia in 2001, dozens of low cost carriers have been started with in the region and around Asia (Ortolani, 2005). With such competition only set to increase, low cost carriers need to look at strategies that go beyond price and look more towards marketing (Mulchand, 2006). AirAsia needs to add an element of creativity into their strategies if they want to remain profitable (Ortolani, 2005). An analysis of AirAsia’s service quality is an important step in beginning to understand how AirAsia might better fulfill the needs of their passengers, and thus further differentiate itself.

Purpose of the Study

The purpose of this study is to identify whether AirAsia performs their services in a manner that meet customers’ expectations. It also seeks to identify whether customers have differences in expectations, based on their variables such as age, income, and nationality. Finally, this study seeks to indentify if customers that fly more or less frequently than others have differences in expectations.

Importance of the Study

This research is especially important to AirAsia. This study will help AirAsia to identify if there are gaps between the level of service quality that they provide, and the level of service quality that customers expect. By knowing this information, AirAsia will be able to understand where they are doing things right, and they will be able to identify areas where they need to improve. If areas where they do not meet customers’ expectations are acted upon, this will help them to better meet the expectations of their customers through their current service offerings. The study will also be important for AirAsia when they formulate future strategies, as it will help them to formulate strategies in accordance with customers’ expectations.

Besides its importance to AirAsia, an analysis of the literature has identified the gaps in the research, which this study can help contribute to. There are three main gaps that this study will contribute to. This study will contribute to research because it is conducted on a low cost carrier, in Malaysia, and specifically on AirAsia.

While much research has been done in applying SERVQUAL to the airline industry, most of this research has been conducted on full service carriers. This study will contribute to research as it is conducted solely on a low cost carrier. Instruments will be designed in light of the service that low cost carriers provide; therefore everything tested will provide information specifically on low cost carriers.

Although there has been research done on low cost carriers, very little research has been done in Malaysia, especially in terms of the SERVQUAL instrument. A significant piece of literature that we reviewed concerning low cost carriers was conducted in India (Khan, Vippan, and Bansal, 2007). This study will help to fill in the gaps in the literature by providing research from a Malaysian perspective. This will be helpful as Malaysia is host to the region’s most significant low cost carrier, and is fast becoming a hub for low cost carriers.

Finally, this research makes relevant contributions as it specifically measures the service quality of AirAsia. AirAsia is the largest low cost carrier in the region, and amongst the largest in the world. Very little research has been done on the service quality of AirAsia, therefore this study will help to contribute in that area.

Research Objectives

In light of the literature reviewed, and the gaps that exist in the literature, the three objectives of this study are as follows:

To determine if AirAsia’s performance meets customers’ expectations

To establish if customers’ opinions vary between demographics.

To ascertain if customers’ opinions vary based on their experience with AirAsia.

LITERATURE REVIEW

Critical Analysis of Past Research

SERVQUAL

According to Lewis and Booms (1983), service quality is measured by comparing customer’s expectations with the service delivered, and then seeing whether the service delivered matches those expectations. SERVQUAL is an instrument developed by Parasuraman, Zeithaml, and Berry (1988), which attempts to measure the service quality of an organisation. It uses a 22 item scale that measures a customer’s pre-purchase expectations of a service, and the post-purchase perceptions of an organisation’s performance (Parasuraman, Zeithaml, and Berry, 1988; Oh, 1999). Customer’s expectations and perceptions are then compared against each other, by identifying the arithmetic difference (Oh, 1999). Parasuraman, Zeithaml, and Berry (1985) called this difference ” the gap”. These 22 items are further reduced into the five dimensions of tangibles, reliability, responsiveness, assurance, and empathy (Pakdil and Aydin, 2007).

Shahin (2004), states that SERVQUAL is statistically valid instrument that is the predominant method of measuring quality throughout the service industry. It can be conducted repeatedly, therefore allowing for yearly comparisons, and time analyses (Shahin, 2004). This also makes it a useful instrument when it comes to benchmarking purposes (Kang and Bradley, 2002).

However, while there are advantages to the instrument, there are also criticisms. Peter, Churchill and Brown (1993) and Brown, Churchill and Peter (1993) claim that using the difference score (the gap) causes poor reliability. Furthermore, Teas (1993) claims that in the measurement of expectations, the scale may omit certain unexpressed expectations.

Independent Variables

Various studies have been conducted using SERVQUAL to assess the service quality of airlines. This literature shows how the individual variables rank according to importance to customers. Waguespack, Rhoades, and Tiernan (2007) state that reliability is the most important SERVQUAL dimension among air passengers. Young, Cunningham, and Lee (1994), Park, Robertson, and Wu (2006), Kien-Quoc, and Simpson (2006), and Sultan, and Simpson (2000) concur with that finding. However, while reliability remains the most important dimension to customers, Khan, Vippan, and Bansal (2007) found that the gap between customer expectations and perception for reliability was high, even more so for low cost carriers than for full service carriers.

Responsiveness was found to follow reliability in terms of importance (Robertson, and Wu, 2006; Kien-Quoc, and Simpson, 2006). However, Young, Cunningham, and Lee (1994), found that empathy followed reliability in terms of significance to customers. It was found that the gap for reliability was also significant, as low cost carriers are unable to provide the prompt service expected by customers, due to a low staff to passenger ratio (Khan, Vippan, and Bansal, 2007).

The remaining variables: tangibles and assurance, are not as much a concern as the former variables. Park, Robertson, and Wu (2006), find that customers do not place high expectations on tangibles, due to the fact that they know that financial constraints do not allow for extravagant tangibles. The literature regarding assurance contrast each other in that Natalisa, and Subroto (2003) found assurance to have the strongest effect on customer satisfaction, while Park, Robertson, and Wu (2006) found it to be of least importance among the five dimensions. Table 26 shows the measurable individual attributes of each variable that have been derived from Gilbert and Wong (2003), and Fatma and Aydin (2007).

Demographics.

There are various demographic variables that may influence the expectations of customers (Kien-Quoc, and Simpson, 2006; O’Connell, and Williams, 2005; Gagliano, and Hathcote, 1994; Sultan, and Simpson, 2000). Kien-Quoc, and Simpson (2006) found that age, ethnicity, and income may be factors that influence expectations. In a study conducted on full service carriers and low cost carriers, which included AirAsia, age was found to be a factor that affected service quality results (O’Connell, and Williams, 2005). The study found that younger people from the major segments of the passengers of low cost carriers. Older people preferred the full service carriers. Younger people tend to have lower expectations, lower income, and demand for less; therefore, it is easier for them to accept the service quality of a low cost carrier.

In their study on retail apparel stores, Gagliano and Hathcote (1994) found that Caucasians tend to have higher gaps. Sultan and Simpson (2000) found that expectations differ by nationality. They found that European passengers tend to be more critical in their service quality ratings that Americans. The same was found for those with higher incomes; the higher the income, the higher the discrepancies between expectations and perceptions. Therefore service quality does tend to vary between demographics.

Experience.

In Webster (1991) research, past experience significantly influences one’s expectations of a service. Kien-Quoc, and Simpson (2006) found that expectations vary between frequency of flight travel. Therefore it is important to consider experience when analysing the service quality of an organisation. One who has more experience with an organisation or a service would expect something different compared to one who has never had an experience with that organisation or service.

Key Hypotheses

In order to achieve the research objectives of this study, the following hypotheses have been formulated. The first five test the dimensions of SERVQUAL. The following three test how demographics affect the service quality gaps. The final hypothesis tests whether a customer’s experience with AirAsia will affect the service quality gaps.

H1: AirAsia’s performance meets customers’ reliability expectations

H2: AirAsia’s performance meets customers’ tangibility expectations

H3: AirAsia’s performance meets customers’ responsiveness expectations

H4: AirAsia’s performance meets customers’ assurance expectations

H5: AirAsia’s performance meets customers’ empathy expectations

H6: AirAsia’s service quality gaps vary by age

H7: AirAsia’s service quality gaps vary by income

H8: AirAsia’s service quality gaps vary by nationality

H9: AirAsia’s service quality gaps vary by experience

RESEARCH METHOD

Subjects

As this research study was conducted to evaluate the service quality of AirAsia’s, the population of this study has to be all of the AirAsia’s customers. Out of this population, a sample of 89 respondents who have flown by AirAsia before and are above 18 years old were taken to represent the population.

Research Instruments

Questionnaires are used as the research instrument in this survey. Only close-ended questions were used in this questionnaire in order to simplify data collection and analysing. A mixture of nominal and ordinal scales were used to determine the demographics of respondents such as age, nationality, income, and purpose of travel at the beginning of the survey. This was followed by questions using an interval scale, namely Likert scale, regarding the five dimensions of SERVQUAL which includes reliability, tangibility, responsiveness, assurance and empathy in terms of expectations and the actual performance.

Data Collection Method

Data was collected through random sampling method where AirAsia’s customers were approached randomly at the Low Cost Carrier Terminal (LCCT). Personal administered interviews were then conducted with the respondent in order to sort out difficulties in the questionnaire provided and also to clarify unclear terms. In total, there were 89 respondents with an 89% response rate for statistical analysis.

Research Hypothesis and Statistical Analysis

The research hypotheses were all tested using Bivariate statistical analysis. The two analysis used to test the hypotheses were Paired Samples t-test and One-way Anova. Both these tests were suitable as they were used to test for differences in means. The results are shown and explained in the next section.

Assumptions

A few assumptions are made during the selection of respondents for this study. The first was that all respondents are AirAsia’s customers. The next was all respondents are above 18 years old.

Limitations

There are several limitations in this study of AirAsia’s service quality. The first is that there is a significantly large amount of Malaysians as compared to the other nationalities. Thus is mainly due to the fact that the research was carried out in Malaysia and there were definitely more Malaysians in the LCCT while the research was being conducted. In addition, most of the questions are measured using Likert scale. There is a chance that this may cause order bias as some of the respondents might answer the questions blindly without reading beforehand. Lastly, as performed in the Multiple Regression test which can be seen in the next section, the service quality variables only explains 53% of the dependent variable. Thus, another limitation would be that this study had not taken into account other service quality variables.

RESULTS OF THE STUDY

Profile of the Respondents

The findings were collected based on a total of 89 respondents. A descriptive analysis is used to illustrate the demographics and the characteristic of the respondents. Tables 1 to Table 6 in the Appendix represent the respondent’s profile. The demographic variables used in this case were age, nationality, occupation, income, travel purpose, and flying frequency.

Among the 89 respondents, 12 were below 21 years old, 26 were 21-30 years old, 20 were 31-40 years old, 21 were 41-50 years old and 10 were above 50 years old. The majority of the respondents were Malaysians and they comprise of 42. 7% of the total respondents. The other nationalities include Filipino (16. 9%), Australian (15. 7%), American (7%), Chinese (3%) and others. Next, the most popular occupation is to be an employee (57. 3%), followed by being a student (22. 5%). The rest are either self-employed, unemployed or have retired. In terms of income, 46. 1% makes less than RM 2000 a month, 33. 7% makes more than RM5000 a month and 20. 2% makes between RM 2000-5000 a month. About 40 respondents have travelled around two to five times with AirAsia, 33 of them only once and 16 had travelled more than five times with AirAsia. Lastly, the majority of the respondents were travelling for leisure purposes (75. 3%). Only 16. 9% were travelling for business and 4. 5 % were travelling for the purpose of studying.

Reliability Test

The reliability analysis will determine the internal consistency of the scale using Cronbach’s alpha (Coakes, Steed and Dzidic, 2006). The Cronbach Reliability Analysis was produced by the Statistical Package for the Social Sciences (SPSS) programme to test the reliability of the scale used. As can be seen in Table 7 in the Appendix, the Cronbach alpha for the overall scale is 0. 943. Thus, there is evidence that the reliability of the scale used is very high.

Factor Analysis

When used to construct a reliable test, Factor Analysis is an additional means of determining whether items are tapping into the same construct (Coakes et. al., 2006). In other words, factor analysis can be used to check the validity of the questions. In this case, the assumptions of normality have been satisfied before analysis. In Table 8 of the Appendix, it can be seen that the Bartlett test of sphericity is significant and that the Kaiser-Meyer-Olkin measure of sampling adequacy is greater than 0. 6 that is 0. 764. Thus, the scale used can be said to be valid.

Relationship between the Dependent Variable and Independent Variables in the Conceptual Framework

The conceptual framework derived from the literature review had five independent variables that lead to service quality, namely tangibility, responsiveness, reliability, assurance and empathy. The Multiple Regression test was used to determine whether there is a relationship between the independent variables (tangibility, responsiveness, reliability, assurance and empathy) and dependent variable (overall service quality). The assumptions that the dependent variable has a linear relationship with the independent variable and that there is normal distribution were satisfied. This can be seen in Figures 1 to 10 and Figure 12 in the Appendix.

From Table 19, it can be seen that the R-square is 0. 529 or 0. 53. The F statistics of 18. 636 in Table 20 indicates a considerably large amount of explained variation due to regression. The low sig-value of 0. 000 is evidence that this F-statistics had not happened by chance. In other words, this means that there the combined effects of tangibility, responsiveness, reliability, assurance and empathy can explain about 53% of service quality. The remaining 47% of variation is due to random fluctuations service quality and to other factors that have not been measured and included in the model.

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Hypotheses Testing

Evaluation of AirAsia’s Service Quality

Paired samples t-test was employed to examine the differences between respondents’ expectations of respondents and their evaluation of AirAsia’s service quality. The assumptions that there are two interval scaled variables measured on the same scale for comparison and that the variables were normally distributed, were fulfilled. The normality of the variables can be seen in Figures 1 till 10 in the Appendix. In this case, each of the service quality variables (tangibility, responsiveness, reliability, assurance and empathy) was measured using five questions in the questionnaire. The questions were answered using a Likert scale where ‘1’ was highly disagree and ‘5’ was highly agree. Prior to carrying out t-test, the questions had been computed in order to derive the mean for each service quality variables.

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Table 9 illustrates that there is a difference in mean between respondents’ expectations of tangibility with the AirAsia’s service quality in terms of tangibility. Table 10 shows that the difference in mean between the two is 0. 6135. The sig-value for the difference in mean between the expectations and service quality in terms of tangibility is 0. 000. As p < 0. 05, there is a very high significance level. In other words, there is 0% chance that the difference in means had occurred by chance. Thus, as the mean for respondents' expectation is 4. 016, and the mean for AirAsia's service quality in terms of tangibility is 3. 402, it can be concluded that AirAsia's service quality has not met the respondents' expectations in terms of tangibility.

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From Table 11, it can be seen that there is a difference in mean between respondents’ expectations of tangibility with the AirAsia’s service quality in terms of responsiveness. Table 12 shows that the difference in mean between the two is 0. 7056. The sig-value for the difference in mean between the expectations and service quality in terms of responsiveness is lower than 0. 05 as it is 0. 000. This means that the differences in means are highly significant and had not occurred by chance. Thus, as the mean for respondents’ expectation is 4. 090, and the mean for AirAsia’s service quality in terms of tangibility is 3. 384, it can be concluded that AirAsia’s service quality has not met the respondents’ expectations in terms of responsiveness.

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Table 13 shows the mean of the total respondents’ expectations of reliability to be 4. 472 and the mean of the AirAsia’s total service quality for reliability to be 3. 575. So, as illustrated in Table 14, the difference in mean between the two is 0. 8966. With a sig-value of 0. 000 which is lower than 0. 05, this difference is highly significant. This means that there is 0% likelihood that this difference in means had not occurred by chance. Thus, as the mean for respondents’ expectation is higher than the mean for AirAsia’s service quality in terms of relaibitlity, it can be concluded that AirAsia’s service quality has not met the respondents’ expectations in terms of reliability.

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Table 15 and 16 illustrate the difference in mean to be 0. 6854 with the mean for expectations of assurance and service quality in terms of assurance being 4. 189 and 3. 503 respectively. The sig-value is 0. 000 and so p < 0. 05. So, this difference is highly significant and it is unlikely that this difference in means had occurred by chance. Thus, as the mean for respondents' expectation is higher than the mean for AirAsia's service quality in terms of assurance, it can be concluded that AirAsia's service quality has not met the respondents' expectations in terms of assurance

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In Table 18, it can be seen that the difference in mean is 0. 5034. The p < 0. 05 as the sig-value is 0. 000. Similarly, this shows that this difference is unlikely to have occurred by chance. Thus, as the mean for respondents' expectation (4. 099) is higher than the mean for AirAsia's service quality in terms of empathy (3. 596), it can be concluded that AirAsia's service quality has not met the respondents' expectations in terms of empathy.

From the findings, it is clear that AirAsia’s service quality had not met the respondents’ expectations in all five of the service quality variables, that is tangibility, responsiveness, reliability, assurance and empathy. Therefore, all the five hypotheses are rejected. While a majority of the respondents had expected a high level of service quality from a budget airline, they have found AirAsia’s service quality to be only moderately high. The hypotheses are:

H1: Customer expectations meet AirAsia’s service quality in terms of tangibility

H2: Customer expectations meet AirAsia’s service quality in terms of responsiveness

H3: Customer expectations meet AirAsia’s service quality in terms of reliability

H4: Customer expectations meet AirAsia’s service quality in terms of assurance

H5: Customer expectations meet AirAsia’s service quality in terms of empathy

Differences between Respondents based on Demographic

As the independent variables (tangibility, responsiveness, reliability, assurance, and empathy) have been found to adequately explain the dependent variable (service quality), testing the differences between respondents against the dependent variable alone seems sufficient. Only the relevant demographic variables were chosen to be examined. These demographic variables are age, income level and nationality. As discussed in the literature review, there is likely to be a difference between respondents based on these demographic variables and their expectations and performance evaluation. One-way Anova test was carried out as it is the most suitable test to determine if groups differ from one another. The assumptions of an interval scaled dependent variable (overall service quality), a grouping variable of three or more groups and the normality of the dependent variable were satisfied. The normality of the dependent variable can be seen in Figure 1 to 10 while the linearity can be seen in Figure 11 in the Appendix.

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From the findings in Table 21 and Table 22, it can be seen that there is a low significance level (p > 0. 05) when differences in customers are tested with age and income level.

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However, when tested with nationality, as can be seen in Table 23, the sig-value is 0. 02 which is lower than 0. 05. This suggests that there is a very small probability that the differences in respondents had occurred by chance. Thus, there is evidence to suggest that respondents’ rating towards the overall service quality differs between nationalities. Table 24 shows the Levene’s statistics. As the sig-value is high, 0. 860, there is a low significance level. Thus, this shows that there is no variances between groups and the assumption of homogeneity of variances are met.

While both the hypotheses that AirAsia’s service quality varies by age and AirAsia’s service quality varies by income level are rejected, the hypothesis that AirAsia’s service quality varies by nationality is accepted.

Differences between Respondents based on Experience with AirAsia

The differences between respondents were tested against the dependent variable alone since the independent variables (tangibility, responsiveness, reliability, assurance, and empathy) have been found to adequately explain the dependent variable (service quality). The respondents’ experience with AirAsia was depicted by the number of flights they have flown with AirAsia. Once again, One-way Anova test was carried out as it is the most suitable test to determine if groups differ from one another. The assumptions of an interval scaled dependent variable (overall service quality), a grouping variable of three or more groups and the normality of the dependent variable were satisfied. The normality of the dependent variable can be seen in Figure 1 to 10 in the Appendix while the linearity of the variables can be seen in Figure 11 of the Appendix.

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Based on Table 25, the sig-value is 0. 078 which is slightly higher than 0. 05. This means that there is a low significance level of differences between respondents in terms of experience. Thus, it can be concluded that respondents do not differ in terms of experience the hypothesis that AirAsia’s service quality vary by experience is rejected.

Discussion and Recommendations

Based on the evaluation of AirAsia’s service quality, it can be seen from the mean score that most of the respondents’ had rather high expectations of a budget airline. This is surprising as research has shown that expectations of a low costs carriers are normally presumed to be relatively lower (O’Connell and Williams, 2005). A possible reason to this change in customer expectations could be the increasing intensity of the competition in the airline industry (Ong and Tan, 2009; Bernama, 2009). As mentioned earlier, AirAsia is no longer the only airline offering low rates as Malaysian Airlines is performing the same strategy while still offering a five-star service quality (Wong, 2008; Yeow, 2008). Thus, as cheap flights are so readily available, customers might expect more out of a low cost carrier. Anyhow, this research implies that AirAsia should look into improving its service quality. Improving their service quality will allow AirAsia to stay competitive in the market and sustain long-term success in terms of reputation, brand equity and profitability.

Next, it is also clear that the service quality evaluation done had not differed between age and income but had differed between nationalities of the respondents. This goes against our findings in our literature review. However, the researches in the literature review were examining the difference in expectations of age and income between a low cost carrier and a full service carrier. The difference in nationality, on the other hand, could possibly be due to the differences in culture between nationalities as some nations’ norms allow them to be more critical than other nations (Sultan and Simpson, 2000). Since AirAsia has customers from various nations, this finding indicates that the marketing strategies that AirAsia implements should take into account the different expectations and perceptions that exist based on nationality. Besides that, this research is also important in order for AirAsia to successfully gain market share internationally.

There are some managerial implications that can be applied with the understanding of these findings. Firstly, AirAsia could look into it to determine how marketing strategies can be altered for the greatest effect of improving their service quality. One of the most important steps that can be taken is investing in proper training and development of their staff so that they can effectively respond to the expectations of customers. Also, research indicates, it should not be assumed that a high service quality in one country would mean that the particular service quality will be perceived to be high in another country too. Thus, it is important for AirAsia to continuously evaluate their service quality periodically. This will ensure that their quality of service will meet the changing expectations of customers.

CONCLUSION

The research at hand was conducted on 89 participants, of various ages, nationalities, income levels, and experience levels. This sample met all the assumptions needed to test the hypotheses. The first five hypotheses tested the five independent variables of SERVQUAL (reliability, responsiveness, tangibility, assurance and empathy), by testing whether o