Analyzing the impact of social capital on US based Kickstarter projects outcome

Joseph Ochieng Onginjo, Dong Mei Zhou, Tesema Fiseha Berhanu, Sime Welde Gebrile Belihu

Research output: Journal PublicationArticlepeer-review


The essence of this paper is to analyse the ripple effects caused from the intertwining and complex relationship between the relational and structural dimensions of social capital on the US based Kick starter projects’ outcomes. This will be measured based on real time data collected from the Kick starter. com in form of 1157 projects organised in the structure of the number of backers, amount of time taken to fund the projects and the converted amount pledged towards the projects, as classified according to various project categories and geographical locations. This research applies qualitative and quantitative statistical analysis methods as well as data mining techniques; k-Nearest Neighbour, Naive Bayes and Decision Tree Algorithms. The results from this research confirm that relational social capital i.e. the number of backers involved in the projects, has significantly strong and positive impact on the converted amount pledged towards a project and the project outcome. This paper also offers a feasible decision-making model that will be used by the entrepreneurs in the future to determine which type of project categories an entrepreneur can choose to host and the project outcome.

Original languageEnglish
Article numbere07425
Issue number7
Publication statusPublished - Jul 2021
Externally publishedYes


  • Crowdfunding
  • Decision tree algorithm
  • Naive Bayes
  • Social capital theory dimensions
  • k-nearest neighbor

ASJC Scopus subject areas

  • General


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