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A regression analysis of the factors affecting the ticket price in thetravel industry
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.
2017 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesisAlternative title
En regressionsanalys påde faktorer som påverkar biljettpriset inom resebranschen (Swedish)
Abstract [en]

This bachelor thesis in applied mathematics and industrial engineering and management investigates which factors that affect the price of tickets in the travel industry. This has been done by performing different multiple linear regression analyses based on the theory from mathematical statistics and econometrics. The analyses has been made with data that has been provided by MTR Express, containing data of departures of 2016 for the main operators in the railway and airline industry. The route that has been analysed is Stockholm - Gothenburg since this is the route where MTR Express has established its business in the railway market in Sweden. The results of the linear regression analysis show that the variables "Days before departure" and the weekday of travel have the most significant impact on the prices for both train and flight tickets. The final models have an explanation

degree of 50% for the railway and 51% for the airline industry. The results show many similarities and correlations between the railway and airline industries. Furthermore, some interesting differences between these subindustries appeared in the final regression models and these have been one of the aspects in the discussion. The conclusion of the thesis is that there are several different aspects affecting the price in the travel industry

Abstract [sv]

Detta kandidatexamensarbete inom tillämpad matematik och industriell ekonomi undersöker vilka faktorer som påverkar priset på biljetter i resebranschen. Detta har gjorts genom linjära regressionsanalyser som har baserats på teorier inom matematisk statistik och ekonometri. Dessa analyser har gjorts möjliga med hjälp av data från MTR Express som innehåller information om avgångar under 2016 för de största aktörerna inom tåg- och flygbranschen i Sverige. Den sträcka som analyserats är Stockholm - Göteborg då detta är den rutt som MTR Express har etablerat sig på. Resultatet av de regressionsmodeller som beräknats fram visar att faktorerna "dagar före avresa" och veckodag för avresa har stor påverkan på priset för såväl flyg som tåg. De slutgiltiga modellerna visar en förklaringsgrad på 50 % och 51 % för tåg- respektive flygindustrin.

Resultaten visar likheter och korrelation mellan tåg- och flygindustrin. Utöver likheter mellan branscherna har även intressanta skillnader gått att identifiera från resultaten som diskuteras i rapporten. De slutsatser som går att dra från detta kandidatexamensarbete är att det finns många faktorer som påverkar priset på resor men att vissa har större påverkan och bör tas i beaktning när man ska köpa biljetter.

Place, publisher, year, edition, pages
2017.
Series
TRITA-MAT-K ; 2017:02
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:kth:diva-209234OAI: oai:DiVA.org:kth-209234DiVA, id: diva2:1114111
External cooperation
MTR Express
Subject / course
Applied Mathematics and Industrial Economics
Educational program
Master of Science in Engineering - Industrial Engineering and Management
Supervisors
Examiners
Available from: 2017-06-22 Created: 2017-06-22 Last updated: 2017-08-04Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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More styles
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