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DOI: 10.14569/IJACSA.2020.0110739
PDF

How Entrepreneurs Utilize Accelerators: A Demographic Factor Analysis in Turkey using Regression

Author 1: Ceren Cubukcu
Author 2: Sevinc Gulsecen

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 11 Issue 7, 2020.

  • Abstract and Keywords
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Abstract: This study examines entrepreneurs participating into eight accelerator programs located in Istanbul, Turkey. Business accelerators are a new kind of incubation program built in particular to help technology entrepreneurs and assist them reach to the next level. In total eight accelerator programs are researched in this study. A survey is developed for this study and applied to entrepreneurs attending these eight accelerator programs. In this survey, the effectiveness of these programs are measured according to the demographics of entrepreneurs. The aim of this research is to analyze how entrepreneurs use the services given by the accelerator program. In relation to entrepreneurs’ age, gender, work experience, educational status and family background, several hypotheses have been identified for assessing the value of supports given in these accelerator programs. The data of this research have been examined via SPSS using Mann-Whitney and Kruskal-Wallis methods. According to the results of these tests, a regression model called Generalized Linear Mixed Model (GLMM) has been developed. This study adds to the literature by examining accelerator supports and facilities so that accelerators can set apart their programs in line with the requests of the entrepreneurs.

Keywords: Accelerators; e-business; startups; regression

Ceren Cubukcu and Sevinc Gulsecen, “How Entrepreneurs Utilize Accelerators: A Demographic Factor Analysis in Turkey using Regression” International Journal of Advanced Computer Science and Applications(IJACSA), 11(7), 2020. http://dx.doi.org/10.14569/IJACSA.2020.0110739

@article{Cubukcu2020,
title = {How Entrepreneurs Utilize Accelerators: A Demographic Factor Analysis in Turkey using Regression},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2020.0110739},
url = {http://dx.doi.org/10.14569/IJACSA.2020.0110739},
year = {2020},
publisher = {The Science and Information Organization},
volume = {11},
number = {7},
author = {Ceren Cubukcu and Sevinc Gulsecen}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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