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Bayesian approaches have been widely applied in construction management (CM) research due to their capacity to deal with uncertain and complicated problems. However, to date, there has been no systematic review of applications of Bayesian approaches in existing CM studies. This paper systematically reviews applications of Bayesian approaches in CM research and provides insights into potential benefits of this technique for driving innovation and productivity in the construction industry.

A total of 148 articles were retrieved for systematic review through two literature selection rounds.

Bayesian approaches have been widely applied to safety management and risk management. The Bayesian network (BN) was the most frequently employed Bayesian method. Elicitation from expert knowledge and case studies were the primary methods for BN development and validation, respectively. Prediction was the most popular type of reasoning with BNs. Research limitations in existing studies mainly related to not fully realizing the potential of Bayesian approaches in CM functional areas, over-reliance on expert knowledge for BN model development and lacking guides on BN model validation, together with pertinent recommendations for future research.

This systematic review contributes to providing a comprehensive understanding of the application of Bayesian approaches in CM research and highlights implications for future research and practice.

A configurable reference model can be used to assist in the development and management of business processes in complex, multi-stakeholder environments. The purpose of this paper is to demonstrate a process design in such environments via configurable process reference modelling, using airports as an example.

Existing reference modelling methods around process modelling, merging and configuration are extended to include contextual and spatial factors using the design science methodology. The approach is empirically based on a set of business process management notation (BPMN) models for international passenger departures, consolidated from five Australian airport case studies via document analysis, interviews and observation.

The use of contextual factors and operational scenarios, structured using the proposed approach, facilitated efficient cross-organisational comparison for configuring processes to suit the needs of a target organisation. The resulting configurable model integrates the perspectives of organisational stakeholder groups with that of the customer in a transparent and unambiguous graphical representation. It is a reusable tool with low data collection needs for each use.

Future research should include: version management; how to keep the model current; configurability via modelling objects other than gateways; and cross-discipline application (e.g. as a foundation for quantitative decision-making models).

This is the first reported application of configurable reference modelling to airport passenger facilitation. Methodological contributions include the addition of space-sensitive process elements and notation to BPMN; guidelines for systematically deriving contextual factors associated with process variants across similar organisations; and overall normative guidelines for inductively developing a configurable process reference model.