Choosing suitable project control modes to improve the knowledge integration under different uncertainties

Lin, Lin; Müller, Ralf; Zhu, Fei; Liu, Hanwen

doi:10.1016/j.ijproman.2019.07.002

Cited by 27 publications

(33 citation statements)

References 87 publications

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“…We assume that "innovative projects are projects managed on the basis of new methods, while innovation projects bring new products and new services" (Spalek 2016). In such circumstances, we ought to refer to tools enabling uncertainty modeling (Lin et al 2019;Midler et al 2016;Narayanan et al 2019;Oehmen et al 2020;Pich et al 2002;Singh and Rani 2019;Vats et al 2019). Uncertainty may be defined in many ways (Gaspars-Wieloch 2018); however, in this paper, we assume that it occurs when at least one parameter of the decision problem is not deterministic (Gaspars-Wieloch 2019a, 2019b, 2020b, 2021.…”

Section: From Deterministic Ap To Ap Under Uncertainty-motivation Ofmentioning

confidence: 99%

The Assignment Problem in Human Resource Project Management under Uncertainty

Gaspars-Wieloch

2021

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The assignment problem (AP) is a discrete and combinatorial problem where agents are assigned to perform tasks for efficiency maximization or cost (time) minimization. AP is a part of human resource project management (HRPM). The AP optimization model, with deterministic parameters describing agent–task performance, can be easily solved, but it is characteristic of standard, well-known projects realized in a quiet environment. When considering new (innovation or innovative) projects or projects performed in very turbulent times, the parameter estimation becomes more complex (in extreme cases, even the use of the probability calculus is not recommended). Therefore, we suggest an algorithm combining binary programming with scenario planning and applying the optimism coefficient, which describes the manager’s nature (attitude towards risk). The procedure is designed for one-shot decisions (i.e., for situations where the selected alternative is performed only once) and pure strategies (the execution of a weighted combination of several decision variants is not possible).

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Section: From Deterministic Ap To Ap Under Uncertainty-motivation Ofmentioning

confidence: 99%

The Assignment Problem in Human Resource Project Management under Uncertainty

Gaspars-Wieloch

2021

Risks

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“…Cognitive load, defined as one's ability to process and apply knowledge (Paas, Tuovinen, Tabbers, & Van Gerven, 2003), or knowledge-based attributes may span tacit and explicit issues which include knowledge management, transfer, coordination, sharing, access, and intelligence attrition throughout the project lifecycle. These play a part in the overall process of projects and portfolio management (Lin, Müller, Zhu, & Liu, 2019;Wei & Miraglia, 2017 for project organisations to best leverage these for project excellence (Sirisomboonsuk, Gu, Cao, & Burns, 2018).…”

Section: A Backdrop Of Dynamic Complex Projectificationmentioning

confidence: 99%

Transient Information Adaptation of Artificial Intelligence: Towards Sustainable Data Processes in Complex Projects

Dacre

Kockum

Senyo

2021

Preprint

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Large scale projects increasingly operate in complicated settings whilst drawing on an array of complex data-points, which require precise analysis for accurate control and interventions to mitigate possible project failure. Coupled with a growing tendency to rely on new information systems and processes in change projects, 90% of megaprojects globally fail to achieve their planned objectives. Renewed interest in the concept of Artificial Intelligence (AI) against a backdrop of disruptive technological innovations, seeks to enhance project managers’ cognitive capacity through the project lifecycle and enhance project excellence. However, despite growing interest there remains limited empirical insights on project managers’ ability to leverage AI for cognitive load enhancement in complex settings. As such this research adopts an exploratory sequential linear mixed methods approach to address unresolved empirical issues on transient adaptations of AI in complex projects, and the impact on cognitive load enhancement. Initial thematic findings from semi-structured interviews with domain experts, suggest that in order to leverage AI technologies and processes for sustainable cognitive load enhancement with complex data over time, project managers require improved knowledge and access to relevant technologies that mediate data processes in complex projects, but equally reflect application across different project phases. These initial findings support further hypothesis testing through a larger quantitative study incorporating structural equation modelling to examine the relationship between artificial intelligence and project managers’ cognitive load with project data in complex contexts.

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“…To enhance the credibility of the mid-range theory developed, the case selection approach was informed by replication logic, when each case is treated as a distinct experiment representing a unit of analysis: that is, selected cases replace a set of experiments enabling the researcher to draw theoretical inferences and generalisations (Lin et al, 2019;Lehtinen and Aaltonen, 2020;Qiu et al, 2019). Further, the selected cases comply with the principle of typicality (Lin et al, 2019). Purposive sampling is used in qualitative research to identify and select information-rich cases for the most proper utilization of available resources (Etikan et al, 2016).…”

Section: Case Selectionmentioning

confidence: 99%

Integrating hierarchical and network centric management approaches in construction megaprojects using a holonic methodology

Gorod

Hallo

Statsenko

et al. 2020

ECAM

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PurposeTraditional “hierarchical” and “network-centric management” approaches often associated with the management of well-defined construction projects lack the adaptability to cope with uncertainty, standardised practices and the required conformance to industry standards. The purpose of this paper is to propose an integrative “holonic” methodology for the management of megaprojects in the construction industry, which incorporates both adaptability and conformance to standards, and to illustrate the associated benefits of such a methodology.Design/methodology/approachA multi-case study comprising three cases delivered in the USA and Australia, namely the Adelaide Desalination Plant (ADP), the Seattle–Tacoma International Airport, and the Olmsted Locks and Dam Replacement project were utilized to demonstrate the key features of the hierarchical, network-centric and holonic approaches to managing megaprojects.FindingsThe case studies demonstrate incorporating the holonic approach into the management of complex construction projects results in increased management effectiveness and project success. The proposed “holonic” methodology provides the potential to efficiently manage megaprojects navigating through high degrees of uncertainty.Practical implicationsThe adoption of the holonic view by project management (PM) practitioners will help them manage megaprojects that are characterised by greater complexity. Second, the proposed methodology enables the discipline of PM to evolve in alignment with rapidly unfolding global transformation trends.Originality/valueThis paper demonstrates the application of the “holonic” methodology to the domain of the management of construction megaprojects. Such an approach is needed as construction projects become increasingly more complex across the world due to technological, political and social uncertainties, larger scale, changing environmental and safety regulations, and the growing involvement of human factors germane to this research.

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Choosing suitable project control modes to improve the knowledge integration under different uncertainties

Cited by 27 publications

References 87 publications

The Assignment Problem in Human Resource Project Management under Uncertainty

The Assignment Problem in Human Resource Project Management under Uncertainty

Transient Information Adaptation of Artificial Intelligence: Towards Sustainable Data Processes in Complex Projects

Integrating hierarchical and network centric management approaches in construction megaprojects using a holonic methodology

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