American Journal of Theoretical and Applied Statistics
Volume 4, Issue 1-1, January 2015, Pages: 9-14
Received: Dec. 4, 2014;
Accepted: Dec. 8, 2014;
Published: Dec. 27, 2014
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Teejan T. El-Khazendar, Information Technology, Islamic University of Gaza, Gaza, Palestine
Rifa J. El-Khozondar, Physics department, Al-Aqsa University, Gaza, Palestine
Entrepreneurship became an important sector in the Arab world. A lot of young entrepreneurs have ambitious projects and creative ideas, which they hope to get fund and incubation to implement these ideas. There are three incubators in Gaza which provide the required incubation, training and fund. Entrepreneurs personality characters have a big effect on the success of their startup companies; moreover, the startup companies category plays a big role on the success of their startup companies especially in small markets such as in Gaza. So we have to find a way to discover which is the most successful ideas and under which category can be classified with paying tight attention for the characters of the team members for each idea. They should have some traits which qualify this team seems to be successful. In the present paper, we are using computing approach based on data mining techniques to study one of the business fields to produce a business technique that helps in extraction the association rules for the incubated startup companies in Gaza. Moreover, we will study these association rules to understand and help the incubators in Gaza to avoid the failed ideas and teams as possible as it could be. Therefore, the incubators will be able to improve the incubation and entrepreneurship sector and increase the number of successful startup companies in Gaza and reduce the wasted fund and time on failed startups.
Teejan T. El-Khazendar,
Rifa J. El-Khozondar,
Towards a Successful Startup Company: Best Successful Team Components, American Journal of Theoretical and Applied Statistics. Special Issue: Computational Statistics.
Vol. 4, No. 1-1,
2015, pp. 9-14.
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