Risks and uncertainties are inevitable in construction projects and can drastically change the expected outcome, negatively impacting the project’s success. However, risk management (RM) is still conducted in a manual, largely ineffective, and experience-based fashion, hindering automation and knowledge transfer in projects. The construction industry is benefitting from the recent Industry 4.0 revolution and the advancements in data science branches, such as artificial intelligence (AI), for the digitalization and optimization of processes. Data-driven methods, e.g., AI and machine learning algorithms, Bayesian inference, and fuzzy logic, are being widely explored as possible solutions to RM domain shortcomings. These methods use deterministic or probabilistic risk reasoning approaches, the first of which proposes a fixed predicted value, and the latter embraces the notion of uncertainty, causal dependencies, and inferences between variables affecting projects’ risk in the predicted value. This research used a systematic literature review method with the objective of investigating and comparatively analyzing the main deterministic and probabilistic methods applied to construction RM in respect of scope, primary applications, advantages, disadvantages, limitations, and proven accuracy. The findings established recommendations for optimum AI-based frameworks for different management levels—enterprise, project, and operational—for large or small data sets.

A significant body of literature addresses the application of lean thinking to improving the interface between detailed design and construction production, yet none specifically focuses on remote site projects. These projects range from tourism and scientific investigation to resource exploration developments. The challenges confronting the project teams tend to fit within a sociologically oriented world where designers respond to functional, aesthetic and environmental concerns, or within a production oriented world, where strategic decisions made during the early stages of a project impact markedly upon construction, logistics and sustainability. The research aimed to establish how the integration of lean design and design management thinking influenced the development of a conceptual design management model for remote site projects, and the level of rigour achieved ‘in the field’ when tested. A postdoctoral reflective review is made of a selection of the reviewed literature, the methodology/process undertaken in the model development and testing stages, and the findings from two case studies used when testing the developed model. Semi-structured interviews were conducted with selected ‘working-in-the-field’ participants across a diverse range of remote site projects; the model was found to be robust and portable.

The next 20 years will see inward investment of up to £100 billion in construction (and energy) projects in northern Scotland, particularly in the Highlands and Islands. The majority of these projects will take place in locations which are, to a greater or lesser extent, remote. However the performance of many remotely-sited projects across the world highlight the need for more effective management strategies and models. The multi-stakeholder management framework for remote site projects, developed by Kestle (2009), synthesised production and sociological design and management approaches, and has already been tested and validated on Antarctic, humanitarian aid and post-disaster reconstruction projects globally. Participants for this research were designers, construction, and project managers involved on a commercial scale marine infrastructure project in the Scottish Highlands. Semi-structured interviews were conducted and the findings analysed to establish and reflect on whether the framework modelled the realities on this remote site project, and actually provided the value-added sought by the multi-stakeholders involved. The findings suggested that the stakeholders’ value criteria expectations were indeed met, and that the management framework did reflect the realities of designing and managing this particular remote site project.