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2019 | OriginalPaper | Chapter

Learning the required entrepreneurial best practices using data mining algorithms

Authors : Waseem Ahmad, Shuaib K. Memon, Kashif Nisar, Gurpreet Singh

Published in: Computational Science and Technology

Publisher: Springer Singapore

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In this research, our focus is to establish a relationship between some of the entrepreneurial best practices such as good networking skills, developing a clear vision, perseverance and ability to take risks with the business success in the field of kiwifruit contractors. Failures at the initial stage of this business is a common occurrence in the Bay of Plenty region of New Zealand. For aspiring kiwifruit contractors achieving success is a herculean but a possible task. The success factor in this research is calculated based on the number of hectares cultivated land and the number of employees hired by the contractors. The research design adopted in this study is the quantitative research approach, the instrument of a well-structured questionnaire was devised, which was based on the 5 point Likert scale format. Weka, a well known data mining toolbox was used for the analysis of primary data collected from the respondents. In this research, rule based and decision tree algorithms were used to extract useful and actionable information from the data. The study concluded that clear vision and risk taking capabilities are two most important features required to become successful in this business.

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Metadata
Title
Learning the required entrepreneurial best practices using data mining algorithms
Authors
Waseem Ahmad
Shuaib K. Memon
Kashif Nisar
Gurpreet Singh
Copyright Year
2019
Publisher
Springer Singapore
DOI
https://doi.org/10.1007/978-981-13-2622-6_45