Survey data and case study data for From Cradle to Value: A Life Cycle-Informed Value Management Framework for Sustainable Steel Manufacturing: An Australian Case Study

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Steel plays an integral role in Australian manufacturing, construction, and infrastructure. The steel industry continues to experience increased economic, environmental, and operational pressures threatening its long-term viability. Examples include energy costs, labour costs, environmental regulation, supply chain disruption and access, and global market forces. Value Management (VM) enables stakeholders to systematically improve functional performance, resource utilisation, and create value while supporting environmental, economic and social sustainability. VM has a well-established evidence base supporting its use across numerous industry sectors; however, its uptake within the Australian steel industry has been limited.

The current research aimed to design and validate a sustainable Value Management framework to support Overall Sustainability Success (OSS) within the Australian steel industry by examining the impact of removing VM implementation barriers, VM Critical Success Factors (CSFs), and VM implementation applied through a digital decision-support platform. The key outcome of this research was the development and validation of an integrated Value Management (VM) framework that brings together VM implementation barriers, VM implementation practices, VM CSFs, OSS, and the online decision-support tool (PowerVM). Using a combination of empirical modelling and practical validation methods, this VM framework offers guidelines for facilitating sustainable decision-making practices and improving value generation specifically for the Australian steel industry and steel-intensive infrastructure projects. Five hypotheses were tested using five separate but related structural models. Four structural models explored relationships between the constructs of removing VM implementation barriers, VM implementation, and OSS. The fifth model focused on the relationship between VM CSFs and OSS.

A two-stage mixed-approach was used in this study. Stage 1 consisted of a systematic literature review and a questionnaire survey sent to 120 industry professionals working within the Australian steel industry. Of these questionnaires sent out, 81 were usable responses (67.5%). These quantitative data collected from the survey were analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM) techniques to test five hypotheses and provide development of the proposed VM framework. Stage 2 was a case study used to practically verify the use of the proposed framework and PowerVM decision-support tool within a steel-intensive bridge infrastructure project. This two-phased approach allowed for the framework to be empirically tested and practically verified.

A digital VM desktop application was developed using Microsoft Power Apps to operationalise the research framework. PowerVM embeds the full VM Job Plan, including function analysis, TRIZ-informed creativity tools, Life Cycle Cost Analysis (LCCA), the Analytical Hierarchy Process (AHP), automated Value Index (VI) calculations, and creates a structured and transparent decision-making framework.

The research framework was validated using a bridge design case study located in Queensland, Australia. The case study described the use of the proposed framework by undertaking an OSS evaluation of nine bridge design alternatives supported by PowerVM. Results determined that the prestressed concrete girder bridge with a geopolymer concrete deck alternative was preferred, having the highest Value Index, and could provide an estimated 20.2% life-cycle cost savings compared to the reference design. The case study findings demonstrate that the proposed framework and digital tool enable a systematic, transparent, and data-driven approach for assessing design alternatives and can support more sustainable decision-making practices within steel-intensive infrastructure projects.

This research has provided the steel industry with a validated VM framework to support sustainable decision-making, empirical evidence to support the importance of minimising implementation barriers and maximising CSFs, and a practical digital decision-support tool that contributes towards sustainable value management theory and its application to infrastructure. Theoretically, this study contributes to the Value Management literature by empirically examining the role of implementation barriers and CSFs affecting VM adoption and sustainability performance outcomes in an industry in which VM has been rarely researched, the steel industry. Additionally, the study contributes to sustainability literature by creating a linkage between VM practices and environmental, economic and social sustainability goals.