Marketing research report conclusion PDF

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Scott Graves (22004469) Joshua Brown (21980795) Jian Ming P’Ng (21698649)

Contents Executive Summary......................................................................................................................................2 Introduction.................................................................................................................................................3 Question 1....................................................................................................................................................4 Question 2....................................................................................................................................................6 Qantas’ Service Quality Dimensions.............................................................................................................6 All Airlines Service Quality Dimensions........................................................................................................7 Service Quality Significance..........................................................................................................................8 Question 3....................................................................................................................................................9 The effect of gender on service quality evaluations.....................................................................................9 The effect of age on service quality evaluations...........................................................................................9 The effect of experience on service quality evaluations.............................................................................10 Question 4..................................................................................................................................................12 Part A..........................................................................................................................................................12 Part B..........................................................................................................................................................12 Part C.....................................................................................................................................................13 Recommendations......................................................................................................................................13 Appendices.................................................................................................................................................15

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Executive Summary This report was created to provide analysis, evaluation, and insight into customer satisfaction of airline customers. 222 airline customers completed a survey where they would evaluate the airline service quality, give their demographic information, and their overall satisfaction. The variables were all measured on 5-point scales ranging from 1=strongly disagree to 5=strongly agree. The information was analysed using IBM SPSS Statistics Data Editor to conduct crossairline comparisons, to find areas that need improvement, to determine any demographic influences, and to find influences that service quality dimensions may have on behavioural outcomes. The usable output tables will be found in the appendices of the report. The findings to the four research questions are the following: Qantas customer evaluations did not have significant differences to Air New Zealand customer evaluations. The order of service quality dimensions, ranked by summed mean from highest to lowest, is safety, helpfulness, convenience, knowledge, timeliness, meals, and comfort. All dimensions are closely ranked and there is not a stand-out area that needs immediate improvement. Gender, age, and experience all influenced service ratings. Males and females rated safety and timeliness differently to one another. People over 50 rate safety higher than people between the ages of 18-29 and 40-49. People with high experience rate convenience lower than people with medium experience. People with medium and high experience rate helpfulness higher than people with low experience. People with low experience rate meals higher than people with high experience. Helpfulness of staff is the biggest influence on overall rating, while safety is the biggest influence on recommending an airline to a friend and re-patronage. Our recommendations to airlines are: 

Try and achieve higher summed scores by focusing upon improving elements from all the dimensions

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Due to recent events people are scared. Airlines need to emphasise safety to increase patronage.

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Increase comfort with free blankets, pillows, and travel packs.

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Increase the range of meals and include vegetarian and allergy specific food. Provide passengers complimentary snacks.

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Educate staff on the importance of customer service

The major limitation in this market research process was the sample size. Some variables had to be grouped together or removed as they did not have a large enough sample. Without a large enough sample, the results cannot be used to accurately represent their respective populations. A much larger sample of people would greatly improve the accuracy of our calculations and analysis and would have provided many more areas that could have been explored more thoroughly.

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Introduction

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Question 1 Qantas airline service quality dimensions are rated differently to Air New Zealand, in all areas. Figure 1.1 shows the comparison in means for service quality dimensions between the airlines. The graph shows that there is not a large difference between the airlines, however they’re not perfectly the same. We can accurately determine whether there is a significant difference in each of the service quality dimensions by performing an independent sample T Test for each of the service quality dimensions.

Fi gure 1.1 An independent-samples t-test (Figure 1.2) was conducted to compare the average knowledge of airline staff for Qantas and Air New Zealand. There was an insignificant difference in the scores for Air New Zealand (M= 3.6667, SD= 0.78755) and Qantas (M= 3.6447, SD= 0.77045) conditions; t (142) =0.169, p = 0.771. These results suggest that there is not a significant difference in the quality dimension of airline staff knowledge between the two airlines (We fail to reject the null hypotheses at 5% level of significance).

An independent-samples t-test (Figure 1.3) was conducted to compare the average safety score for Qantas and Air New Zealand. There was an insignificant difference in the scores for Air New Zealand (M= 3.9372, SD= 0.78127) and Qantas (M= 3.9872, SD= 0.63210) 5

conditions; t (145) = -0.428, p = 0.107. These results suggest that there is not a significant difference in the quality dimension of safety between the two airlines as 0.107>0.05 (We fail to reject the null hypotheses at 5% level of significance).

An independent-samples t-test (Figure 1.4) was conducted to compare the average score for the convenience of travel experience for Qantas and Air New Zealand. There was an insignificant difference in the scores for Air New Zealand (M= 3.7206, SD= 0.73440) and Qantas (M= 3.7230, SD= 0.81452) conditions; t (137) = -0.018, p = 0.319. These results suggest that there is not a significant difference in the quality dimension of convenience between the two airlines as 0.319>0.05 (We fail to reject the null hypotheses at 5% level of significance).

An independent-samples t-test (Figure 1.5) was conducted to compare the average score for comfort for Qantas and Air New Zealand. There was an insignificant difference in the scores for Air New Zealand (M= 3.1408, SD= 0.89432) and Qantas (M= 3.2711, SD= 0.77586) conditions; t (145) = -0.946, p = 0.319. These results suggest that there is not a significant difference in the quality dimension of comfort between the two airlines as 0.319>0.05 (We fail to reject the null hypotheses at 5% level of significance).

An independent-samples t-test (Figure 1.6) was conducted to compare the average score for helpfulness of the airline staff for Qantas and Air New Zealand. There was an insignificant difference in the scores for Air New Zealand (M= 3.8588, SD= 0.78117) and Qantas (M= 3.8500, SD= 0.76811) conditions; t (142) = 0.068, p = 0.557. These results suggest that there is not a significant difference in the quality dimension of helpfulness of staff between the two airlines as 0.557>0.05 (We fail to reject the null hypotheses at 5% level of significance).

An independent-samples t-test (Figure 1.7) was conducted to compare the average score for the timeliness for Qantas and Air New Zealand. There was an insignificant difference in the scores for Air New Zealand (M= 3.5145, SD= 0.10179) and Qantas (M= 3.5779, SD= 0.75575) conditions; t (144) = -0.479, p = 0.304. These results suggest that there is 6

not a significant difference in the quality dimension of timeliness between the two airlines as 0.304>0.05 (We fail to reject the null hypotheses at 5% level of significance).

An independent-samples t-test (Figure 1.8) was conducted to compare the average score for the quality of meals for Qantas and Air New Zealand. There was an insignificant difference in the scores for Air New Zealand (M= 3.2717, SD= 1.01708) and Qantas (M= 3.2760, SD= 0.94554) conditions; t (144) = -0.026, p = 0.675. These results suggest that there is not a significant difference in the quality dimension of meals between the two airlines as 0.675>0.05 (We fail to reject the null hypotheses at 5% level of significance).

Question 2 The service quality dimensions that Qantas are interested in assessing are the knowledge of staff, safety, convenience, comfort, helpfulness of staff, timeliness and the quality of meals on board. These aspects have been recorded in the data set as summed scores per airline in terms of service quality. These scores are represented on a scale of 1-5 with 1=strongly disagree and 5=strongly agree. Testing the means of the service quality dimensions with the summed scores as the dependent variable and the airline as the independent variable we can analyse and rank these dimensions for Qantas and compare to the other airline.

Qantas’ Service Quality Dimensions Purely focusing on Qantas, the data revealed that the service quality dimensions are all similar. The 7 different dimensions only range from means of 3.2711-3.9872 (Figure 2.1). This means that Qantas customers rate the service quality dimensions similar with no real big issues. The highest ranked score was safety (3.9872), one of the most critical dimensions when travelling via aircraft. With the recent scare of aircraft MH370, missing since March 2014 it is assumed that consumers are still nervous to travel, making safety a priority. The lowest rank score was comfort (3.2711). With comfort one of the less important dimensions, this score is not a surprise and is probably expected. The score isn’t low on the 1-5 scale and is still an acceptable score considering it is the lowest ranked. The official ranking in order from highest to lowest was safety (3.9872), helpfulness (3.85), convenience (3.7230), knowledge (3.6447), timeliness (3.5779), meals (3.2760) and comfort (3.2711). 7

All Airlines Service Quality Dimensions On a general level, the service quality results were like Qantas’ scores (Figure 2.2). By conducting a one sample t-test we gathered the average scores of the service quality dimensions. The results concluded that the safety score was ranked the highest, the same as Qantas. This mean across all airlines was only slightly smaller (3.9895) in comparison to Qantas (3.9872). The lowest ranked factor was the quality of meals with an average of 3.1159. This is different to Qantas who achieved a higher average (3.2760). On average across all airlines the knowledge (3.6820) and helpfulness (3.9388) were also ranked higher than Qantas’ averages for those scores. Qantas did although achieve higher results in the convenience, comfort, timeliness and meals. In comparison to other airlines, Qantas has very similar ranked service quality dimensions to Air New Zealand. Singapore Airlines has a much higher rating with 4 of 7 dimensions ranked above 4.0. This is an inaccurate representation in comparison to Qantas and Air New Zealand due to the difference in participants. Only 12 people participated in the evaluation for Singapore in comparison to an average of 68.5714 for Air New Zealand and 76.1429 for Qantas. These findings are demonstrated by the graph, showing the means of the summary scores. The bar chart shows the minimal differences between Air New Zealand and Qantas as well as Singapore Airlines’ higher means.

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Service Quality Significance The t-test also revealed whether any significance occurred between the means of the service quality dimensions (Figure 2.3). The results concluded that all 7 dimensions had a p-value of 0.00. This means that the summed scores are perfectly significant and we reject the null hypothesis as all p-values are 0.00 and are less than the significant mark of 0.05. This means that there is a perfect relationship between the 7 dimensions as we can see by the means of the service quality dimensions being very similar. We can gather from this that all 7 factors are critical and should be accounted for rather than focusing upon a certain dimension or a group. This is a very important statistic for Qantas to consider. Qantas must continue to improve all their criteria and not just one. It is evident by these results that travellers rank the dimensions very closely and do not have any dimensions that are outstanding and dimensions that are strongly concerning.

Question 3 Qantas are interested in whether there are any differences in service quality evaluation among males and females, different age groups and traveller experience. To determine if there are any differences between these groups we will run a series of tests on SPSS. The output of these tests will tell us whether there is a significant difference in service quality evaluations among groups in different demographics.

The effect of gender on service quality evaluations The survey had 222 respondents, 118 being female and 104 being male. An independent samples T-test was conducted on all quality evaluation variables to determine which variables had a significant relationship with the respondent’s gender. It was found that safety and timeliness had a significance level of .05. Thus, we can conclude that gender only has a significant effect on timeliness and safety ratings.

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An independent-samples t-test was conducted to compare safety rating in males and females (Figure 3.1). There was a significant difference between the safety rating for males (Mean = 4.1) and females (Mean = 3.89) with the p- value being 0.019. This result suggests that gender really does influence safety ratings. Specifically, our results suggest that females rated the airline safety lower than males. Another independent-samples t-test was conducted to compare timeliness rating in males and females (figure 3.2). There was a significant difference between the timeliness rating for males (Mean=3.67) and females (Mean=3.44) with a p-value of 0.042. This result suggests that gender influences timeliness ratings. Specifically, our results suggest that females rated timeliness lower than males.

The effect of age on service quality evaluations Age is split up into 6 groups: Group 1 – 18-29 (92 respondents) Group 2 – 30-39 (31 respondents) Group 3 – 40-49 (41 respondents) Group 4 – 50-59 (30 respondents) Group 5 – 60-69 (17 respondents) Group 6 - 70+ (11 respondents) However, group 5 and group 6 did not have at least 20 respondents, meaning their results are not a good indicator of their complete population’s feedback. As a result, we combined group 5 and group 6 and created a new group that consisted of people 60+ years of age. This new group was defined as group 5 for our tests. We ran a one-way ANOVA test to determine if different age groups rated any service quality dimensions differently. The only dimension that was significantly differently across age groups was safety. A one-way ANOVA was conducted to compare the effect of age on safety rating among the five different age groups (Figure 3.3). Post hoc comparisons using the LSD (least significant differences) test indicated that there is a significant difference between 18-29-yearold’s (Mean=3.877) and 50-59-yearold’s(Mean=4.244) with a p-value of .008. There is also significant difference between 18-29-yearold’s (Mean=3.877) and 60+ year old’s (Mean=4.196) with a p10

value of .024. There is also significant difference between 40-49-yearold’s (Mean=3.931) and 5059-yearold’s (Mean=4.244) with a p-value of .046. These results suggest that age does influence safety rating. Specifically, our results suggest that people aged 18-29 rate safety significantly lower than people aged 50-59 and people aged 60+. Our results also suggest that people aged 40-49 rate safety significantly lower than people aged 50-59. However, there is no significant difference in rating between any other age groups.

The effect of experience on service quality evaluations. The experience variable split respondents into three groups, judging experience by the number of times flown internationally in the last year. Group 1 is people who have flown 1 to 2 times internationally in the last year. Group 2 is people who have flown 3 to 5 times internationally in the last year. Group 3 is people who have flown more than 5 times internationally in the last year. A one-way ANOVA was conducted to determine if people with different levels of flying experience rated any service quality dimensions differently. The results of this ANOVA tell us that there was a significant difference between groups when evaluating convenience, helpfulness, and meals. A one-way ANOVA was conducted to compare the effect of experience on convenience rating among the three different experience groups (Figure 3.4). There was a significant effect of experience on convenience rating at the p...