Prediction Modeling of Software Startup Success By PLS-SEM Approach

 
 
 
  • Abstract
  • Keywords
  • References
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  • Abstract


    With the fact that the tendency of startup business fail, it is necessary to understand factor influencing the startup success. It is understood that the lack of knowledge of how to start business creates uncertainty. The uncertainty may increase the likelihood of  startup failure, which leads to economic loss. This paper aims to develop a predictive model of startup success in identifying factors and variables influencing startup success. This study also explores ways to compile and validate predefined startup prediction models in the startup business environment. Furthermore, the significance of factors and variables have also been identified to predict software startup success. The results showed that there were 18 significant factors influencing software startup success. These include the characteristics of the founders, quality of the startup organizations, support of resources, environmental conditions, performance of value creation processes, and  effectiveness of competitive strategies. The result also showed that six variables contributed significantly (74.8%) in the prediction of software startup success.

     

     

     

  • Keywords


    prediction modeling; startup; software startup; startup success; structural equation model; pls-sem approach

  • References


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Article ID: 24421
 
DOI: 10.14419/ijet.v7i4.40.24421




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