For decades construction labour productivity has been stagnated or declining. Changing this issue requires new knowledge on the labour-intensive construction production system. The work sampling method was applied to collect data from 3 renovation construction production systems. It quantifies observations of on-site work and enables deep analyses of how time is used. The analysis revealed that the renovation projects had a baseline of value-adding-work (VAW) time on 29.5%. It further identified 5 system behaviours outlining how VAW and Non-Value-Adding work (NVAW) time behaves. The new knowledge of how both VAW and NVAW time behaves advances knowledge on how time is wasted in construction projects and opens new branches of future research. The findings are furthermore of potential use to industry professionals who work with process improvement in renovation projects because they provide, among others, answers to how targets can be defined for both VAW and NVAW.

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Labor productivity in construction has fallen behind other industries in most of the world and has declined continuously for decades in the US. To change this, the construction industry needs to know where to focus. This research aims to show how important craftsmen efficiency is for national construction labor productivity (CLP) development. Statistical analysis was used to compare craftsmen efficiency and CLP data from North America (NA) in the period 1972-2010. Craftsmen efficiency data were extracted from published work that measured direct work (DW) through work sampling, and CLP data were extracted from national databases. A statistically significant relationship between DW and CLP was established. This revealed that adding 36 seconds of DW to every work hour could yield a yearly return of 5.4 billion USD to the NA gross domestic product (GDP). Results show that more focus on activity and project level efficiency is crucial for changing the trends of national CLP. Industry leaders and policy makers now have a solid foundation for taking corrective actions for an industry plagued by low productivity.

The elimination of waste is a core focus of lean construction. Reducing waste will increase work efficiency. For several years it has been debated how flow and the efficiency of processes can be measured. Kalsaas, Koskela, and others conclude that in order to operationalize workflow measures, it must be disconnected from productivity and throughput measures and instead focus on work efficiency. However, an extensive and valid baseline of work time efficiency is missing in the community. The establishment of such becomes the objective of this research.The method is an extensive litterateur review that identified 474 case studies of time waste measures from the 1970s until today. This sample is analyzed in different ways, among others showing that the average direct work time is 43.6%.The results show that the sample contains considerable uncertainty, which is mainly due to an inconsistent understanding of direct work, indirect work, and waste work in the many different studies. Besides, the results show no statistically significant difference between the performance of varying trades or between countries.The construction industry can use this research as a baseline for the current direct work level and apply this as a benchmark in a continuous improvement process.

The construction industry has experienced stagnation and perhaps even a decline in construction labor productivity for decades. This is problematic as labour costs in construction constitute up to 60% of the total project costs.This research aimed to investigate further how much complimentary lean construction tools could impact Construction Labor Efficiency (CLE). CLE is a key element in the denominator when calculating Construction Labor Productivity (CLP) because CLP focuses on maximizing value-adding-work time (numerator) and minimizing nonvalueadding-work time (denominator).A case study research approach with four renovation projects was used to collect Lean Implementation Degree (LID) and CLE data. The research findings showed a strong positive correlation between LID and CLE in the four renovation projects.The findings have implications for both academia and industry professionals. Academia now has initial results on which future research can be built. Industry professionals now have a better understanding of how lean improves efficiency and hereby better arguments for why lean construction methods must be implemented in future renovation projects.The research was limited by a small sample size of only four renovation projects. Thus, further research is needed to validate the effects in renovation projects and other types of construction projects as well.

The European Green Deal's Renovation Wave aims to renovate 35 million energy-inefficient buildings to reduce carbon dioxide (CO2) emissions by at least 55% by 2030. Historically, efforts to reduce CO2 emissions focused on Operational Energy (OE) of the finished buildings. However, in recent years the Embodied Energy (EE) of the building’s construction process has gained attention because of its essential role in construction renovations projects. In this context, construction efficiency, and more precisely, workers’ efficiency, is a vital catalyst to achieve the European Union (EU) targets. To identify the impact of Construction Labour Productivity (CLP) on the renovation wave an exploratory case study was adopted as a research strategy. Data from four domestic housing renovation projects were gathered. Three specific research goals are outlined. The first is to demonstrate the effect of the adoption of Lean tools and methods to increase CLP. The second is to quantify the correlation between improved productivity and the EE emissions saved during the construction phase. The third goal is to estimate the effect the higher productivity has on OE emissions. The results show that the adoption of several Lean tools and methods has a potential to improve CLP to 45%.  This rate of improvement for the 35 million housing units to be renovated could save 6.9 million tonnes CO2e from EE and 386 million tonnes CO2e from OE. This novelty link between process improvements and reduced energy consumption and emissions can support politicians and infrastructural developers in decision-making for a more sustainable construction industry.

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Construction can be considered a socio-technical system, which is challenging to model due to the many agents interacting either in a managed way or autonomously. Therefore, cause and effect models are hard to validate, and a traditional correlation approach is insufficient. In this study, the method of robustness testing was applied to test the effect stability when assumptions of a model are changed. The research objective is to apply robustness testing on WS data to assess the robustness and validity of the WS method. An actual refurbishment project was the case for this study, where data was acquired through nine days of continuous WS application. Time-series data were grouped into Direct Work (DW), Indirect Work, and Waste Work. Several different robustness tests were applied. It can be concluded that the WS method is robust, i.e., the effect (DW) is stable even if the assumptions are changed severely. Deleting 90% of the sample does, for instance, almost not change the effect. Likewise, if errors are infused into the sample, the effect is stable. Also, if certain structural parts are excluded from the sample, e.g., observations during morning startup, etc., the effect is still stable.