Symbols, Sublimes, Solutions, and Problems: A Garbage Can Model of Megaprojects

Steen, John; Ford, Jerad A.; Verreynne, Martie‐Louise

doi:10.1177/875697281704800609

Cited by 20 publications

(12 citation statements)

References 53 publications

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“…Indeed, aspirations for improved performance have been shown to motivate firms to search more broadly for ideas and technology (Alexy et al, 2016). Although there may be limits to the size of the network that a project firm can effectively use for innovation (Ford et al, 2018;Laursen & Salter, 2014;Steen et al, 2017), we propose that the ability to quickly locate and leverage information and intellectual property from multiple sources within the interorganizational project amplifies the relationship between adaptive problem-solving and new product innovation. This represents a positive interaction effect between sensing and seizing within the Teece ( 2007) model in dynamic capability terms.…”

Section: Adaptive Problem-solving and The Interrelationships Between Sensing And Seizing Activitiesmentioning

confidence: 97%

“…First, large projects have inherent uncertainties stemming from the complex interaction of the many interrelated subsystems (Baccarini, 1996;Nightingale, 2000) and numerous participant firms (Kardes et al, 2013;Perminova et al, 2008;van Marrewijk et al, 2008). Interactions between these elements give rise to unforeseen events and problems, which need to be resolved (Ahola & Davies, 2012;Atkinson et al, 2006;Jaafari, 2001;Steen et al, 2017;Stinchcombe & Heimer, 1985). Such uncertainties may induce firms to adopt broader search patterns within interorganizational projects, because the resulting diversity of information increases the probability that a solution can be found (Alexy et al, 2016;Leiponen & Helfat, 2010).…”

Section: Sensing Activities: Sourcing and Revealing Informationmentioning

confidence: 99%

“…Importantly, problem emergence is not exclusive to the design phase of projects. Technical and organizational challenges occur throughout any large engineering project (Jaafari, 2001;Miller & Lessard, 2000;Nachbagauer & Schirl-Boeck, 2019;Steen et al, 2017).…”

Section: Adaptive Problem-solving and The Interrelationships Between Sensing And Seizing Activitiesmentioning

confidence: 99%

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A Dynamic Capabilities Model of Innovation in Large Interfirm Projects

Steen

Ford

Verreynne

2021

Project Management Journal

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Large-scale projects often involve hundreds or even thousands of businesses. There are opportunities for these firms to produce innovations to solve problems and improve the project’s outcomes, but the time-bounded nature of the project and technical interdependencies also constrains innovation. Using quantitative analysis of data from firms in large oil and gas projects, we show that Teece’s sensing, seizing, and reconfiguring model of dynamic capabilities theorizes innovation in this interfirm project context. We also identify connections between these microfoundations that are not captured in Teece’s linear model, where sensing activities moderate the relationship between seizing activities and innovation.

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Section: Adaptive Problem-solving and The Interrelationships Between Sensing And Seizing Activitiesmentioning

confidence: 97%

Section: Sensing Activities: Sourcing and Revealing Informationmentioning

confidence: 99%

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A Dynamic Capabilities Model of Innovation in Large Interfirm Projects

Steen

Ford

Verreynne

2021

Project Management Journal

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“…• Pertinent O&G project performance literature, for example, Merrow (2011Merrow ( & 2012, EY (2014), Rui et al (2017), andSteen et al (2017); • Cross-case and within-case analysis of our project dataset; • Theory mapping; and • Questionnaire feedback.…”

Section: Project Performancementioning

confidence: 99%

Reference Class Forecasting and Machine Learning for Improved Offshore Oil and Gas Megaproject Planning: Methods and Application

Natarajan¹

2022

Project Management Journal

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This article develops and describes rigorous oil and gas project forecasting methods. First, it builds a theoretical foundation by mapping megaproject performance literature to these projects. Second, it draws on heuristics and biases literature, using a questionnaire to demonstrate forecasting-related biases and principal-agent issues among industry project professionals. Third, it uses methodically collected project performance data to demonstrate that overrun distributions are non-normal and fat-tailed. Fourth, reference-class forecasting is demonstrated for cost and schedule uplifts. Finally, a predictive approach using machine learning (ML) considers project-specific factors to forecast the most likely cost and schedule overruns in a project.

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“…Megaprojects are often marked by limited knowledge, imperfect technologies, and inconsistent goals and preferences of the changing participants (Steen et al , 2017). Cohen et al .…”

Section: Challenges In Megaprojectsmentioning

confidence: 99%

Managing the unexpected in megaprojects: riding the waves of resilience

Nachbagauer

Schirl-Boeck

2019

IJMPB

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Purpose Risk management and uncertainty in megaprojects is a flourishing topic in project management, while the unexpected is still a neglected matter. The purpose of this paper is to offer conceptual clarifications of the unexpected based on second-order-cybernetics and systems theory. While transferring findings from organisation theory to project management, the article provides fresh insights into managing the unexpected in megaprojects. Design/methodology/approach Being grounded on constructionism and systems theory, the conceptual paper explores selected research approaches from organisation theory: research on high-reliability organising, organisational resilience and organisational improvising, on contributions to managing the unexpected in megaprojects. Using the framework of meaning i.e. the factual, social and temporal dimensions, challenges of handling the unexpected are analysed and (effects of) decision-making structures for such projects are defined. Findings This paper argues that classic project management, while neglecting the fundamental distinction between risk, uncertainty and the unexpected, sticks to a planning-and-controlling approach. But the unexpected cannot be planned; however, organisations and managers can prepare for the unexpected. This requests a balance between structure and self-organisation in planning, communication, hierarchy and organisational culture. Understanding the contradictions inherent in managing megaprojects allows for smart decision-making when riding the waves of resilience. Originality/value The study adds to the literature on complexity and uncertainty in project management by enhancing the view to include the unexpected. While rejecting the universal applicability of rationality-based risk and controlling conceptions, shifting to second-order cybernetics and integrating elements of resilient organising increases the understanding of handling the unexpected in megaprojects.

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Symbols, Sublimes, Solutions, and Problems: A Garbage Can Model of Megaprojects

Cited by 20 publications

References 53 publications

A Dynamic Capabilities Model of Innovation in Large Interfirm Projects

A Dynamic Capabilities Model of Innovation in Large Interfirm Projects

Reference Class Forecasting and Machine Learning for Improved Offshore Oil and Gas Megaproject Planning: Methods and Application

Managing the unexpected in megaprojects: riding the waves of resilience

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