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By mobilizing the empirical setting of a megaproject, this study problematizes public budgeting as participatory practice. The authors suggest that megaprojects are prone to democratic legitimacy challenges due to a long history of cost overruns, which provides stakeholders with a chance to dramatize a budgetary controversy.

Through article and document data, the authors reconstructed a controversy that emerged around the budget of Stockholm/Åre’s candidature for the Olympic Winter Games 2026. The authors used Boltanski and Thévenot's (2006) orders of worth to systematically analyze the justification work of key stakeholder groups involved in the controversy.

This study illustrates that a budgetary controversy was actively maintained by stakeholder groups, which resulted in a lack of public support and the eventual demise of the Olympic candidature. As such, the authors provide a more nuanced understanding of public budgeting as a controversy-based process vis-à-vis a wider public with regard to the broken institution of megaprojects.

This study suggests more attention to the disruptive power of public scrutiny and the dramatization of budgeting in megaprojects. In this empirical case, the authors show how stakeholders tend to take their technical concerns too far in order to challenge a budget, even though megaprojects generally provide an ill-suited setting for accurate forecasts.

While studies around the financial legacies of megaprojects have somewhat matured, very few have looked at pitching them. However, the authors argue that megaprojects are increasingly faced with financial skepticism upon their approval upfront.

This study aims to discuss the state-of-the-art digital factory (DF) development combining digital twins (DTs), sensing devices, laser additive manufacturing (LAM) and subtractive manufacturing (SM) processes. The current shortcomings and outlook of the DF also have been highlighted. A DF is a state-of-the-art manufacturing facility that uses innovative technologies, including automation, artificial intelligence (AI), the Internet of Things, additive manufacturing (AM), SM, hybrid manufacturing (HM), sensors for real-time feedback and control, and a DT, to streamline and improve manufacturing operations.

This study presents a novel perspective on DF development using laser-based AM, SM, sensors and DTs. Recent developments in laser-based AM, SM, sensors and DTs have been compiled. This study has been developed using systematic reviews and meta-analyses (PRISMA) guidelines, discussing literature on the DTs for laser-based AM, particularly laser powder bed fusion and direct energy deposition, in-situ monitoring and control equipment, SM and HM. The principal goal of this study is to highlight the aspects of DF and its development using existing techniques.

A comprehensive literature review finds a substantial lack of complete techniques that incorporate cyber-physical systems, advanced data analytics, AI, standardized interoperability, human–machine cooperation and scalable adaptability. The suggested DF effectively fills this void by integrating cyber-physical system components, including DT, AM, SM and sensors into the manufacturing process. Using sophisticated data analytics and AI algorithms, the DF facilitates real-time data analysis, predictive maintenance, quality control and optimal resource allocation. In addition, the suggested DF ensures interoperability between diverse devices and systems by emphasizing standardized communication protocols and interfaces. The modular and adaptable architecture of the DF enables scalability and adaptation, allowing for rapid reaction to market conditions.

Based on the need of DF, this review presents a comprehensive approach to DF development using DTs, sensing devices, LAM and SM processes and provides current progress in this domain.