2011
DOI: 10.1080/01446193.2011.611152
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Identification and evaluation of success factors for public construction projects

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Cited by 117 publications
(67 citation statements)
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References 54 publications
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“…This involves an algorithmic selection process, and is therefore arbitrary to some extent as it proceeds by entering/ eliminating one IV at a time. This extracts more significant variables for inclusion in the model @ao and Proverbs, 2003; Lowe et al, 2006;Tabish and Jha, 2011). On the other hand, it can be regarded as a form of data dredging (Smith and Ebrahim, 2002), involving the 'torture' of data into a high model fit.…”
Section: Identification Of Contractor Satisfaction Predictorsmentioning
confidence: 99%
“…This involves an algorithmic selection process, and is therefore arbitrary to some extent as it proceeds by entering/ eliminating one IV at a time. This extracts more significant variables for inclusion in the model @ao and Proverbs, 2003; Lowe et al, 2006;Tabish and Jha, 2011). On the other hand, it can be regarded as a form of data dredging (Smith and Ebrahim, 2002), involving the 'torture' of data into a high model fit.…”
Section: Identification Of Contractor Satisfaction Predictorsmentioning
confidence: 99%
“…The selected case study was chosen on the basis that it engineers, architects, project management firms and government agencies who work together to 381 deliver the required outcomes. Achieving success in public projects is difficult because it requires 382 economy, efficiency, quality, fairness and transparency (Tabish and Jha, 2011). 383…”
Section: Case Study 327mentioning
confidence: 99%
“…The differences in many ways between public and private sector projects are pointed out by several studies [21,22]. It is clear that diverse demands and perceptions exist in the private and public sectors.…”
Section: Public Funded Projectsmentioning
confidence: 99%