Investigating Critical Success Factors for Software Projects:An InterpretiveStructural Modeling Approach
Publish place: Management,Culture & Economical Development
Publish Year: 1394
Type: Conference paper
Language: English
View: 644
This Paper With 8 Page And PDF Format Ready To Download
- Certificate
- I'm the author of the paper
Export:
Document National Code:
MCED01_362
Index date: 14 February 2016
Investigating Critical Success Factors for Software Projects:An InterpretiveStructural Modeling Approach abstract
Software project management is the art and science of planning and leading software projects. It is asub-discipline of project management in which software projects are planned, implemented,monitored and controlled. These projects takes a considerable time and resources from theorganization. Therefore, it is essential that critical success factors (CSFs) of software projects areidentified. The objective of this paper is to develop the relationships among the identified CSFs insmall and medium-sized enterprises (SMEs) in Iran. According to this objective, two steps areprovided: in the first step the author initially uses a related topic of CSFs in software projectimplementation, which aims at identifying and investigating factors that result in more successfulsoftware project implementation that generate higher levels of value for organizations. By integratinginsights drawn from these studies, the author proposed a set of 9 CSFs which is believed to be moresuitable for SMEs. Then, in the second step, the interpretive structural modeling (ISM) methodologyis used to evolve mutual relationships among these factors.
Investigating Critical Success Factors for Software Projects:An InterpretiveStructural Modeling Approach Keywords:
Investigating Critical Success Factors for Software Projects:An InterpretiveStructural Modeling Approach authors
Farnaz Zeidi
Payame Noor University of Khorasgan
مراجع و منابع این Paper:
لیست زیر مراجع و منابع استفاده شده در این Paper را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود Paper لینک شده اند :