An integrated model of BIM return on investment for Australian small- and medium-sized enterprises (SMEs)

Abstract

PurposeThe business benefits envisaged for BIM represent the main criteria for decision-making about BIM implementation – or shy away from BIM. Despite the significance, traditional evaluation techniques have difficulty to capture “the true value” of BIM from multiple levels and dimensions – as an effective evaluation method is supposed to. This study aims to identify the significant factors that affect BIM return on investment (ROI), develop an integrated model for companies and examine the influence of intangible returning factors of BIM on the rate of BIM implementation.Design/methodology/approachA cluster sampling technique was used; 92 questionnaires completed by Australian architecture, engineering and construction small- and medium-sized enterprises (SMEs) provided the basis to identify and analyse the key measurable returning factors, value drivers and strategic benefits associated with BIM ROI.FindingsApplying the PLS-SEM technique, findings reveal that a lack of reliable quantification methods for the ROI factors associated with BIM significantly affects the organisation's commitments to implement BIM. In essence, the failure to adequately identify and assess these benefits could result in the system not being appropriately implemented and supported by executive sponsors, who give priority to hard and tangible ROI measurements.Practical implicationsThe outcome of this study would be of direct appeal to policymakers, industry professionals and the academic community alike, in providing data-informed insight into the intersection between the implementation of BIM and the concept of ROI. Findings would provide a springboard for further research into using ROI factors to increase BIM implementation. Though the findings are directly applicable and contextualised for Australia, they provide lessons and offer a blueprint for similar studies in other countries and settings. That is, regardless of the context, findings raise awareness and provide a point of reference for the quantification of intangible returning factors rather than the tangible returning factors, as one of the first studies in its kind.Originality/valueThe study provides original insight in drawing attention to an untapped area for research in BIM implementation, namely BIM ROI. Apart from raising awareness around BIM ROI, the study is novel in providing a quantified model that establishes the links and level of impacts of various factors associated with BIM ROI. Findings of this study, particularly add value to the body of knowledge related to the business implications associated with BIM implementation in the context of Australian SMEs, while providing lessons for other countries and settings.

Quantifying BIM investment value: a systematic review

“…To maintain consistency and ensure a high standard of review, we followed the customary practice of including only journal articles in our literature review, as recommended by Sompolgrunk et al (2022). Journal articles, which typically present comprehensive and self-contained research findings, undergo multiple rounds of rigorous peer review.…”

The co-movement effect of managers' psychological factors on the BIM adoption decision in SMEs: a study based on fsQCA

“…PR is related to the uncertainty of ROI and refers to the Managers' perceptions of putting in a lot of resources and not gaining a return. For SMEs with limited resources (Sompolgrunk et al, 2022), they may have no intention to adopt BIM if there is no direct evidence of its ROI. Resource availability is the driving force for organizations to adopt innovation (Sharma and Rai, 2015).…”

“…, 2021) dictates that such decisions are not only influenced by the net effect of single psychological factors but also by the combined effect of multiple psychological factors. Managers need to make BIM adoption decisions by considering both costs and benefits as well as the resources available to the organization under the risk of uncertain return on investment (ROI) (Sompolgrunk et al. , 2022).…”

“…However, the complexity of BIM adoption decisions (Brito et al, 2021) dictates that such decisions are not only influenced by the net effect of single psychological factors but also by the combined effect of multiple psychological factors. Managers need to make BIM adoption decisions by considering both costs and benefits as well as the resources available to the organization under the risk of uncertain return on investment (ROI) (Sompolgrunk et al, 2022). Complexity theory suggests that linear analysis cannot provide true outcomes of behavior due to the complexity of the decision-making process (Chuah et al, 2021).…”

Automated 4D BIM development: the resource specification and optimization approach

“…The main reason why human errors happen is the lack of organized and formulized approach in calculating time and cost of projects and applying existing approaches of manual estimations, despite the advances in technology (Ma et al., 2013; Sompolgrunk et al., 2021). Furthermore, the lack of a clear system on managing and recording the time and cost of elements, and difficulties in collaborating between different members of a construction project in transferring the information of time and cost can escalate the problem (Shourangiz et al., 2011; Sompolgrunk et al., 2022). This is mainly prominent in developing countries like Iran in which the time and cost of materials have strong fluctuations, and the economy suffers from huge inflation and time delays for each project (Hosseini et al., 2017; Khanzadi et al., 2018; Hosseini et al., 2019).…”