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Är du motiverad till att älska ditt arbete?: En kvantitativ studie som analyserar inre motivationspredicerande förmåga på arbetstillfredsställelse
Karlstad University, Faculty of Arts and Social Sciences (starting 2013), Karlstad Business School (from 2013).
2023 (Swedish)Independent thesis Advanced level (degree of Master (One Year)), 10 credits / 15 HE creditsStudent thesisAlternative title
Are motivated to love your work? : A quantitative study that analyses intrinsic motivation’s predictive ability on jobsatisfaction (English)
Abstract [sv]

Studiens syfte var att undersöka om inre motivation hos projektmedlemmar inomIT/mjukvarubranchen kan predicera upplevd arbetstillfredsställelse. Därför sågenomfördes en kvantitativ enkätstudie som skickades ut till respondenter inomstudiens valda urvalsgrupp. Det som undersöktes var inre motivation baserat på detre behovsområdena inom självbestämmandeteorin. Det resulterade i att studiensoberoende variabler blev självbestämmande, kompetens och tillhörighet och hur dekan predicera arbetstillfredsställelse. Insamlad data från 84 respondenteranalyserades genom en multipel regression. Där visade sig att i modellen så kundeoberoende variablerna med statistisk signifikans predicera 69% av variansen i denberoende variabeln. Den oberoende variabeln som visade sig ha störst uniktsignifikant predicerande förmåga var självbestämmande. Studien visar att deanalyserade oberoende variablerna har en stark förmåga att prediceraarbetstillfredsställelse.

Abstract [en]

The aim of the study was to examine whether intrinsic motivation among projectmembers in the IT/software industry can predict perceived job satisfaction.Therefore, a quantitative questionnaire study was conducted and sent out torespondents within the study's selected sample group. What was examined wasintrinsic motivation based on the three psychological need areas in the selfdetermination theory. This resulted in the study's independent variables beingautonomy, competence and belonging and how they can predict job satisfaction. Collected data from 84 respondents was analysed through a multiple regression. This showed that in the model, the independent variables could predict 69% of thevariance in the dependent variable with statistical significance. The independentvariable that proved to have the greatest uniquely significant predictive power wasautonomy. The study shows that the analysed independent variables have a strongability to predict job satisfaction. 

Place, publisher, year, edition, pages
2023. , p. 40
Keywords [en]
Project management, project members, intrinsic motivation, job satisfaction, software development industry
Keywords [sv]
Projektledning, projektmedlemmar, inre motivation, arbetstillfredsställelse, mjukvaruutveckling
National Category
Social Sciences
Identifiers
URN: urn:nbn:se:kau:diva-95190OAI: oai:DiVA.org:kau-95190DiVA, id: diva2:1765833
Subject / course
Project Leadership
Educational program
Master's Degree Programme (one year) in Project Management, 60 hp
Supervisors
Examiners
Available from: 2023-06-12 Created: 2023-06-12 Last updated: 2023-06-12Bibliographically approved

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CiteExportLink to record
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Citation style
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