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From project risk to complexity analysis: a systematic classification

From project risk to complexity analysis: a systematic classification The purpose of this paper is to provide a systematic classification for frameworks, methods, and models of in-project quantitative risk analysis (IQRA) for the last 30 years.Design/methodology/approachAn extensive literature review is conducted to identify pertinent IQRA works. Identified IQRA frameworks/methods/models are then classified on the basis of commonalities in key attributes and assumptions. Linkages between each category of IQRAs and dimensions of complexity are also observed.FindingsAround 70 key publications on IQRAs are identified. Major attributes for each work are described. Five distinct categories of IQRAs emerge with unique linkages to complexity dimensions. An analytical framework in the form of a matrix is presented to illuminate evolution on modeling characteristics and to indicate a relationship between respective category and dimensions of project complexity.Research limitations/implicationsThe research coverage is intended to be comprehensive but it is by no means exhaustive. This study highlights research opportunities in IQRAs and the possible extension toward in-project quantitative complexity analysis (IQCA).Practical implicationsThe proposed matrix provides guidance to practitioners to select the appropriate category of IQRAs for a specific project complexity type in a contingency fashion. The study highlights lessons from development and utilization of IQRAs. Outstanding issues from IQRAs are discussed to avoid similar drawbacks for IQCAs.Originality/valueThis study provides an original framework/matrix to classify extant works in IQRAs. It also establishes an association between IQRAs and the emerging conceptual works of complexity. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Managing Projects in Business Emerald Publishing

From project risk to complexity analysis: a systematic classification

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References (130)

Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
1753-8378
DOI
10.1108/ijmpb-09-2017-0108
Publisher site
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Abstract

The purpose of this paper is to provide a systematic classification for frameworks, methods, and models of in-project quantitative risk analysis (IQRA) for the last 30 years.Design/methodology/approachAn extensive literature review is conducted to identify pertinent IQRA works. Identified IQRA frameworks/methods/models are then classified on the basis of commonalities in key attributes and assumptions. Linkages between each category of IQRAs and dimensions of complexity are also observed.FindingsAround 70 key publications on IQRAs are identified. Major attributes for each work are described. Five distinct categories of IQRAs emerge with unique linkages to complexity dimensions. An analytical framework in the form of a matrix is presented to illuminate evolution on modeling characteristics and to indicate a relationship between respective category and dimensions of project complexity.Research limitations/implicationsThe research coverage is intended to be comprehensive but it is by no means exhaustive. This study highlights research opportunities in IQRAs and the possible extension toward in-project quantitative complexity analysis (IQCA).Practical implicationsThe proposed matrix provides guidance to practitioners to select the appropriate category of IQRAs for a specific project complexity type in a contingency fashion. The study highlights lessons from development and utilization of IQRAs. Outstanding issues from IQRAs are discussed to avoid similar drawbacks for IQCAs.Originality/valueThis study provides an original framework/matrix to classify extant works in IQRAs. It also establishes an association between IQRAs and the emerging conceptual works of complexity.

Journal

International Journal of Managing Projects in Business – Emerald Publishing

Published: May 17, 2018

Keywords: Complexity; Review; Project risk; Quantitative risk analysis; Risk analysis classification

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