sh.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • harvard-anglia-ruskin-university
  • apa-old-doi-prefix.csl
  • sodertorns-hogskola-harvard.csl
  • sodertorns-hogskola-oxford.csl
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Digital Content Marketing på sociala medier: En kvantitativ studie om hur Digital Content Marketing kan optimeras och påverka köpintentionen hos konsumenter i Genration Z
Södertörn University, School of Social Sciences, Business Studies.
Södertörn University, School of Social Sciences, Business Studies.
2023 (Swedish)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

Purpose: Due to the rapidly increasing use of Digital Content Marketing (DCM) on social media and the lagging empirical research in the field, this study aims to determine how marketers can optimize DCM on social media and influence the purchase intention of Generation Z consumers. 

Methodology: Since the study is based on a consumer perspective, a quantitative method with a deductive approach has been conducted. The empirical data consisted of a digital survey with responses from 141 Generation Z consumers. 

Findings: Results of the survey reveals that it is possible to optimize the existing characteristics of DCM, as the most preferred traits were valuable, reliable, and entertaining. Furthermore, DCM has a strong impact on the target audience’s purchase intention and can be most advantageously conveyed through video and image formats on Instagram. 

Research limitations: This study contributes to an increased understanding of how to use DCM on social media. However, more empirical research is still needed in the field that can be generalized to the entire Generation Z population. 

Practical implications: Findings provide an optimized and up-to-date version of DCM that provides marketers with guidelines and opportunities for how DCM on social media can increase consumer engagement and purchase intention. 

Originality/value: This study is one of the first to optimize DCM on social media based on consumer preferences, thus demonstrating how DCM can be designed to increase consumer purchase intention. 

Keywords: Digital Content Marketing, Content Marketing, purchase intention, social media, digital platforms, digital formats

Place, publisher, year, edition, pages
2023. , p. 61
Keywords [sv]
Digital Content Marketing, Content Marketing, köpintention, sociala medier, digitala plattformar, digitala format
National Category
Business Administration
Identifiers
URN: urn:nbn:se:sh:diva-51802OAI: oai:DiVA.org:sh-51802DiVA, id: diva2:1773484
Subject / course
Business Studies
Supervisors
Available from: 2023-06-26 Created: 2023-06-22 Last updated: 2023-06-26Bibliographically approved

Open Access in DiVA

fulltext(3547 kB)87 downloads
File information
File name FULLTEXT01.pdfFile size 3547 kBChecksum SHA-512
43cacd91b7cf4dfda5169edfb15e1324854808e4c9a04718483baa2bb2ab2ffe78cbc24daf3b570958a843c26598043160416fd169d57e8e38ce9a3e8e713e40
Type fulltextMimetype application/pdf

By organisation
Business Studies
Business Administration

Search outside of DiVA

GoogleGoogle Scholar
Total: 87 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 273 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • harvard-anglia-ruskin-university
  • apa-old-doi-prefix.csl
  • sodertorns-hogskola-harvard.csl
  • sodertorns-hogskola-oxford.csl
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf