Analysis Of Australian Airlines Services Dataset For Improving Airport Services

Overview Of The Assignment

a)

The field of statistics has many applications in business setting. Owing to technological innovations, large quantities of data are produced by business nowadays. These data are nowadays being applied by companies to make strategic decisions. The collection and analysis of quantitative data shoves some of the most critical decisions and conclusions that are drawn in the contemporary business world, for example the quality of produced products, the preferences of a customer base, the marketing , supplies and distribution of products, and the accessibility of financial resources (Bell et al. 2018, pg. 69). Accordingly, it is indispensable for persons working in this setting to have relevant skills and knowledge to be able to interpret and use the obtained statistical inferences to inform various real life scenarios.

The task in question involves the use of the various statistical techniques learnt during statics classes, collection and analysis of quantitative data, to analyze real life scenarios and generate useful insights that can be applied to improve Airport services to airline in Australia. In an increasingly competitive and commercial business setting, airports should able to generate sufficient returns to finance their investments in airport operations and infrastructure. This is very crucial as it permits airports to uphold great service levels to travelers and airlines (Braithwaite 2017, pg. 24). As a consultant in the aviation industry, the underlying task is meant to generate insights that will address the growing demand at Australia’s major airports i.e. Sydney, Brisbane and Melbourne.

b)

The given data is mainly secondary data since it has been obtained from the online Australian Government Open Data site (Dougan 2016, pg.107). Secondary data implies second-hand data that has already been collected and recorded by any researcher save for the user for a particular purpose and not relating to the present research problem. It is the readily accessible form of data obtained from several sources like government publications, censuses, company’s internal records and reports, journal articles, books, websites etc. (Leech, N.L. and Onwuegbuzie 2011, pg 56). Secondary data is beneficial in some ways as it is easily obtainable, saves cost and time of the investigator. Nonetheless, secondary data is faulted for many reason such as the data is collected for the purposes instead of the problem in mind, so the practicality of the data may be restricted in several ways like accuracy and relevance.

There are many variables in statistics among them categorical and numerical variables, independent and dependent variables and discrete and continuous variables (Lewis 2015, pg. 435). The given dataset 1 contains fourteen variables which are presented below.

Categorical Variables: In and Out, Australian City, International City, Airline, Route, Port Country, Port Region , Service Country, Service Region

Numerical or Quantitative Variables:  Stops, All Flights, Maximum Seats, Year, Month

Cases are the objects or subjects that the research obtain information about. There are many cases in the provided data set. For instance, airports we have Brisbane, Melbourne and Sydney among others, airline we have Qantas Airways, Air Niugini, Virgin Atlantic Airways, Air New Zealand and so on

Task Description

c)

The dataset 2 is mainly primary data. Primary data is data obtained by the researcher for the first time through direct experience and efforts, specifically for the aim of addressing a given research problem ( Leech and Onwuegbuzie 2011, pg. 67)  . Primary data collection is to a certain extent expensive, as the research is piloted by the agency or organization itself, which necessitates resources like manpower and investment (Nardi 2018, pg. 104). The collection of data is under supervision and direct control of the researcher. The various techniques that are commonly used to collect primary data included surveys, physical testing, observations, questionnaire (mainlined or online), interviews (personal or telephonic), case studies, focus groups, etc (Palinkas 2015, pg. 544).

The objective of the survey was to examine the satisfaction levels of KOI students in three major airports that is Melbourne, Brisbane, and Sydney. The two variables that the researcher focused on in dataset 2 were the location of individual airports and the flying experience of KOI students. Due to the scope of the study, only 20 KOI students were interviewed. In terms of variables, dataset 2 contained two variables which can be categorized as shown below.

KOI student flying experience – a numeric variable (continuous).

The researcher used simple random non-probability sampling to gather data that later formed dataset 2. Simple random sampling is technique all items in any particular sample have an equal chance of being selected (Neuman 2013, pg. 47). Even though the researcher used simple random sampling method to collect data for dataset2, it had several shortcomings including being a time-consuming and complicated sampling technique which required the researcher among other things having sufficient research experience and a high skill level. As a result, the quality of the data was being gathered was heavily dependent on the skills and quality of the researcher. Thus, the results of dataset 2 could be highly biased and inaccurate to some extent.

a)

Table 1: Summary statistics: All Flights

The shape of the histogram is skewed to the right. Otherwise, interpreted, most of flights in different airports in Australia and which were made between September 2003 and September 2018 were 30.

b)

Hypothesis Statement

The hypothesis of this part are stated as:

Ho: μ>30

H1: μ ≤ 30

Where Ho: – Average number of flights came in and flew out to Australia in a month between September 2003 and September 2018 is equal more than 30

H1: The average number of flights came in and flew out to Australia in a month between September 2003 and September 2018 is less than or equal to 30

Table 2: t-Test: Two-Sample Assuming Unequal Variances

Since P (T<=t) , that is, 0.066199, one-tail>0.05, we fail to reject the null hypothesis. We thus conclude that there the average number of flights came in and flew out to Australia in a month between September 2003 and September 2018 more than 30.

a)

The graph and chart below compares the variables Australian city for only for three main cities namely Brisbane, Melbourne and Sydney and Airlines by considering main three Airlines namely Singapore Airlines, Air New Zealand and Cathy Pacific Airways.

Answer

Table 3: Airport Performance

It is clear from Table 2 and Figure 2 above that Sydney was outperformed by its counterparts that is Melbourne and Brisbane between September 2003 and September 2018. In total Sydney Sydney recorded only 20 flights by airlines the three airlines , that is, Singapore Airlines, Air New Zealand and Cathy Pacific Airway, Brisbane recorded 25 (one less than Melbourne) whereas Melbourne lead have recorded 26 air flights by the three airline. Surprisingly, Sydney recorded highest number of flights by Air New Zealand than the other two cities that is 17 to 16 in Melbourne and 15 to Brisbane. However, Sydney recorded zero flight Singapore Airlines between September 2003 and September 2018.

b)

Ho: μ=0

H1: ≠ μ30

Ho: There is a significant relationship between Australian City and Airlines

H1: There is no significant relationship between Australian City and Airlines

Table 4: Correlation of Airports and Airlines

It is clear from the results above, that there is not only a correlation between Australian City and Airlines but a very strong positive correlation since the p-values are positive and close to 1. Thus we fail to reject null hypothesis and conclude that there is a significant relationship between Australian City and Airlines.

c)

Sydney performed dismally compared to its counterparts Brisbane and Melbourne airports recording only 20 flights in total by Singapore Airlines, Air New Zealand and Cathy Pacific Airway, Brisbane recorded 25 (one less than Melbourne) whereas Melbourne lead recorded the largest number at 26 air flights. Notwithstanding, Sydney recorded highest number of flights by Air New Zealand than the other two cities that is 17 to 16 in Melbourne and 15 to Brisbane. However, Sydney recorded zero flight Singapore Airlines between September 2003 and September 2018. We can thus conclude that the Australian Government needs to market her aviation industry and its services to the Singapore Airlines to increase the number of flights coming in and going out of Sydney.

The flying experience of KOI students in Sydney Airport was scored the least, at 66%, compared to their experience in the other two airports with Melbourne Airport experience being scored at 78% while Brisbane Airport was ranked the highest at 85%.

a)

The main objective of this paper was to examine the performance and flying experience in three major airports in Australia that is, Melbourne, Brisbane, and Sydney.  As per the analysis, the average number of flights that came in and flew out to Australia in a month between September 2003 and September 2018 was more than 30. Sydney performed dismally compared to its counterparts Brisbane and Melbourne airports recording only 20 flights in total by Singapore Airlines, Air New Zealand and Cathy Pacific Airway, Brisbane recorded 25 (one less than Melbourne) whereas Melbourne lead recorded the largest number at 26 air flights. Notwithstanding, Sydney recorded highest number of flights by Air New Zealand than the other two cities that is 17 to 16 in Melbourne and 15 to Brisbane. However, Sydney recorded zero flight Singapore Airlines between September 2003 and September 2018.  In terms of Airport experience, Sydney also fell behind its key competitor’s only scoring 66% compared to Melbourne (78%) and Brisbane (85%). Irrespective of these ratings by the 20 KOI students that were surveyed to form dataset 2, it can be concluded that all the three airports offer a fairly good Flying experience, in or out in Australia as they have been rated above 66% in terms of satisfaction that comes with Flying in or out in Australia.

b) Conclusion and Suggestion for Other Future Studies

From the analysis above, this study established that the flying experience heavily influenced the traffic of travelers in Australia’s Airports with Sydney recording the list number of travelers which is largely explained by the nature of the Airport services that are offered to clients. Thus, there is a need for the Australian Government to invest highly on Airport infrastructures on Sydney to improve on the customers’ flying experience in this particular airport.  In addition, this study established that there is not only a correlation between Australian City and Airlines but a very strong positive correlation. This was signified in one particular case where Sydney recorded no recorded zero flight Singapore Airlines between September 2003 and September 2018.  We can thus conclude that the Australian Government needs to market her aviation industry and its services to the Singapore Airlines to increase the number of flights coming in and going out of Sydney.

Besides this observations and conclusions, this study recommends the following areas, as the possible topics of future studies:

• A study to identify the effect of efficiency airport capacity on airport performance.
• A study to establish Airplanes types influence air freight market of Australia.
• A study to establish Airplanes capacity influence air freight market of Australia.

References

Bell, E., Bryman, A. and Harley, B., 2018. Business research methods. Oxford university press.

Braithwaite, G.R., 2017. Attitude or latitude?: Australian aviation safety. Routledge.

Dougan, M., 2016. A Political Economy Analysis of China’s Civil Aviation Industry. Routledge.

Fleischhacker, S.E., Evenson, K.R., Sharkey, J., Pitts, S.B.J. and Rodriguez, D.A., 2013. Validity of secondary retail food outlet data: a systematic review. American journal of preventive medicine, 45(4), pp.462-473.

Neuman, W.L., 2013. Social research methods: Qualitative and quantitative approaches. Pearson education.

Leech, N.L. and Onwuegbuzie, A.J., 2011. Beyond constant comparison qualitative data analysis: Using NVivo. School Psychology Quarterly, 26(1), p.70.

Lewis, S., 2015. Qualitative inquiry and research design: Choosing among five approaches. Health promotion practice, 16(4), pp.473-475.

Nardi, P.M., 2018. Doing survey research: A guide to quantitative methods. Routledge.

Palinkas, L.A., Horwitz, S.M., Green, C.A., Wisdom, J.P., Duan, N. and Hoagwood, K., 2015. Purposeful sampling for qualitative data collection and analysis in mixed method implementation research. Administration and Policy in Mental Health and Mental Health Services Research, 42(5), pp.533-544.

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