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Author: Nasir Hussain

Affiliation: College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics (NUAA), Jiangjun Road no.29, Jiangning District, Jiangsu Province, Nanjing and China

Keyword(s): Knowledge Management, Software Crowdsourcing, Success and Failure Factors, Quantitative Research.

Related Ontology Subjects/Areas/Topics: Service-Oriented Software Engineering and Management ; Software Engineering ; Software Process Improvement

Abstract: Within Software Crowdsourcing, Knowledge Management has a great significance in both academia and industry as a valuable tool used to manage knowledge from the crowd. The aim of this research is to ascertain which success are and which are failure factors of Knowledge Management in Software Crowdsourcing. Literature review techniques and Quantitative Research techniques were applied in order to establish the success and failure factors. By utilizing the literature review method a total of twelve success factors were established of which seven is supported. Eight failure factures were established out of which six are supported. Subsequent to the analysis, a framework is presented in which the factors are further linked to the implementation of Knowledge Management in Software Crowdsourcing. This research and its suggested framework will also prove useful for academics to further gain a comprehensive view of Knowledge Management factors in Software Crowdsourcing for use in future studi es. (More)

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Paper citation in several formats:
Hussain, N. (2019). Categorical Classification of Factors Effecting Knowledge Management in Software Crowdsourcing: Hypothetical Framework. In Proceedings of the 14th International Conference on Evaluation of Novel Approaches to Software Engineering - ENASE; ISBN 978-989-758-375-9; ISSN 2184-4895, SciTePress, pages 578-585. DOI: 10.5220/0007811005780585

@conference{enase19,
author={Nasir Hussain.},
title={Categorical Classification of Factors Effecting Knowledge Management in Software Crowdsourcing: Hypothetical Framework},
booktitle={Proceedings of the 14th International Conference on Evaluation of Novel Approaches to Software Engineering - ENASE},
year={2019},
pages={578-585},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007811005780585},
isbn={978-989-758-375-9},
issn={2184-4895},
}

TY - CONF

JO - Proceedings of the 14th International Conference on Evaluation of Novel Approaches to Software Engineering - ENASE
TI - Categorical Classification of Factors Effecting Knowledge Management in Software Crowdsourcing: Hypothetical Framework
SN - 978-989-758-375-9
IS - 2184-4895
AU - Hussain, N.
PY - 2019
SP - 578
EP - 585
DO - 10.5220/0007811005780585
PB - SciTePress