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Factor analysis of the growth of startups
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.
2022 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesisAlternative title
Faktoranalys av tillväxten av start-ups (Swedish)
Abstract [en]

The task of predicting start-up growth has been an item of institutional as wellas widespread individual research and acclaim of those successful. This workis an attempt to distill the alleged factors of prediction in the large body ofwork that has already been documented, as well as investigating reasonable butyet untested variables. Conclusions are built with a multiple regression model,exploring 7 regressors with data spanning 2014-2019 to avoid the potentiallyabnormal impact of the Covid-19 crisis.Due to the choice of non-predictive regressors, the final result is an explanatorymodel, highlighting the importance of rigorousness in the process of model-building and outlining of data collection in regression analysis. Most regres-sors had a non-significant or weak relationship with the response variable, butconcludes an explanatory degree of 51%. Even if it can not be utilised as apredictive model, it may provide some interesting insight. In the final model,every regressor except one had an unexpected beta value, contradicting earlierresearch.

Abstract [sv]

Åtagandet att förutsäga 'start-up' tillväxt har varit ämne för institutionellsåväl som utbredd individuell undersökning och följaktligen hyllning för de som varit framgångsrika. Denna studieär ett försök att destillera de påstådda faktorerna för förutsägelse utifrån den redan dokumenterade litteraturen, samt utreda rimliga men ännu outforskade variabler. Slutsatser byggs med en multipel regressionsmodell,som utforskar 7 regressorer med data som sträcker sig 2014-2019 för att undvika de potentiellt atypiska effekterna av covid-19-krisen.På grund av valet av vissa icke-prediktiva regressorer är slutresultatet en förklarandemodell, som belyser vikten av noggrannhet i processen för modell-uppbyggnad och planeringen av datainsamling i regressionsanalys. De flesta regressorer hade ett icke-signifikant eller svagt samband med svarsvariabeln, men den slutgiltiga modellen påvisar en förklaringsgrad på 51 %. Även om den inte kan användas som en prediktiv modell, så bidrar den med betydande insikter. Alla regressorer utom en visade ett oväntat beta-värde, vilket motsäger tidigare forskning.

Place, publisher, year, edition, pages
2022.
Series
TRITA-SCI-GRU ; 2022:286
Keywords [en]
Start-up, Growth, Prediction, Regressor, CAGR, Venture Capital, Unicorn, SaaS
Keywords [sv]
Start-up, Tillväxt, Prediktion, Regressor, Riskkapital, CAGR, Enhörning, SaaS
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:kth:diva-326711OAI: oai:DiVA.org:kth-326711DiVA, id: diva2:1757006
Subject / course
Applied Mathematics and Industrial Economics
Educational program
Master of Science in Engineering - Industrial Engineering and Management
Supervisors
Examiners
Available from: 2023-05-15 Created: 2023-05-15 Last updated: 2023-05-15Bibliographically approved

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CiteExportLink to record
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