Developing a framework for statistical process control approaches in project management

Colin, Jeroen; Vanhoucke, Mario

doi:10.1016/j.ijproman.2015.03.014

Cited by 29 publications

(13 citation statements)

References 34 publications

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“…4(b) shows the SPC procedure proposed by Leu and Lin (2008). A recent study (Colin and Vanhoucke 2015) shows that this approach outperforms the other SPC procedures that were proposed in the literature for project control. For details on the calculation of the control limits (and consequently, the zones A, B, and C) and the simulation from which these can be calculated, the reader is referred to the original article and the comparative study.…”

Section: Statistical Process Control (Spc) Application For Project Mamentioning

confidence: 92%

“…4(c) shows a grey area of actual cost curves for fictitious executions of project C2014-06 that would belong to the Lowm=Low class. The simulation that was used to produce these fictitious project executions was described in Colin and Vanhoucke (2015). The probability of these actual cost curves is indicated by the dotted lines that are superimposed onto the grey area.…”

Section: Management Reserve Planning Application For Project Managementmentioning

confidence: 99%

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Empirical Perspective on Activity Durations for Project-Management Simulation Studies

Colin

Vanhoucke

2016

J. Constr. Eng. Manage.

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Simulation has played an important role in project-management studies of the last decades, but in order for them to produce practical results, a realistic distribution model for activity durations is indispensable. The construction industry often has needed historical records of project executions, to serve as inputs to the distribution models, but a clearly outlined calibration procedure is not always readily available, nor are their results readily interpretable. This study seeks to illustrate how data from the construction industry can be used to derive realistic input distributions. Therefore, the Parkinson simulation model with a lognormal core is applied to a large empirical dataset from the literature and the results are described. From a discussion of these results, an empirical classification of project executions is presented. Three possible uses are presented for the calibration procedure and the classification in project management simulation studies. These were validated using a case study of a construction company.

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Section: Statistical Process Control (Spc) Application For Project Mamentioning

confidence: 92%

Section: Management Reserve Planning Application For Project Managementmentioning

confidence: 99%

Empirical Perspective on Activity Durations for Project-Management Simulation Studies

Colin

Vanhoucke

2016

J. Constr. Eng. Manage.

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“…Organizations have paid attention to the capability of planning, resource allocation, and control functions to ensure project objectives are achieved [19][20][21][22]. This approach to project management assumes all the organizations work as a whole and has neglected the interorganizational relationship of participants in overall project success.…”

Section: Interorganization Controlmentioning

confidence: 99%

(Dis)Trust, Control, and Project Success: From a Chinese Project Owner’s Perspective

2017

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Abstract:This research aims to investigate the relationship between interorganizational trust and control and their effects on the project success from the perspective of project owners. Based on relevant literature and the actual situation in the Chinese construction industry, trust was classified as calculative trust and relational trust, and control was classified as outcome control, behavior control, and social control. Results show that project owners' distrust of contractors is independent of project owners' trust of contractors. Calculative trust has a positive influence on all kinds of control. Relational trust has negative impacts on outcome control and behavior control and positive impacts on social control. Of the three kinds of control, outcome and behavior control have negative impacts on social control. All constructs have positive impacts on project success. Project managers should be aware that distrust has a positive influence on project success through the mediation effects of control. Similarly, social control is the most influential type of control, influencing the controller to internalize norms to complete project tasks.

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“…A framework to develop and test such statistical project control methods and to interpret the produced warning signals was presented by [16]. Furthermore, a comparison between four statistical project control methodologies has been presented in [21] and a similar comparison between various general versions of top-down project control has been published in [15].…”

Section: Top-downmentioning

confidence: 99%

On the use of multivariate regression methods for longest path calculations from earned value management observations

Vanhoucke

Colin

2016

Omega

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Developing a framework for statistical process control approaches in project management

Cited by 29 publications

References 34 publications

Empirical Perspective on Activity Durations for Project-Management Simulation Studies

Empirical Perspective on Activity Durations for Project-Management Simulation Studies

(Dis)Trust, Control, and Project Success: From a Chinese Project Owner’s Perspective

On the use of multivariate regression methods for longest path calculations from earned value management observations

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