The Innovative Construction Research Centre (ICRC) is dedicated to socio-technical systems research within the built environment, with particular emphasis on through-life performance in support of the client's business operations. Our vision is for a research centre that not only supports the competitiveness of the architectural, engineering, construction and facilities management sectors, but also supports societal needs for built infrastructure and the broader competitiveness of the UK economy. The domain of enquiry lies at the crucial interface between human and technical systems, thereby requiring an inter-disciplinary approach that combines engineering research methods with those derived from the social sciences. The ICRC's research portfolio is organised into six themes: (1) Integration of design, construction and facilities management. Concerns the through-life management of socio-technical systems within the built environment. Topics of consideration include: integrated logistic support, design for reliability and systems integration for building services. Of particular concern is the way that firms within the supply chain are integrated to provide solutions that add value to the client's business. (2) Knowledge management and organisational learning. Addresses the means of supporting knowledge flows across extended supply chains and the extent to which procurement systems learn across projects. Of particular importance is the design of learning mechanisms that extend across organisational boundaries. Also investigates the degree to which the construction sector can learn from other sectors, i.e. aerospace, automotive, retail, defence. (3) Human resource management and the culture of the industry. The construction sector is too often characterised by regressive approaches to human resource management (HRM) with little emphasis on developmental to support innovation. Of particular importance is the concept of 'high commitment management' that has emerged as a central component in the quest to link people management to business performance. Any attempt to improve HRM practices in the construction sector must also recognise cultural barriers to the implementation of new ways of working.(4) Innovative procurement. Includes legal, economic and organisational aspects of procurement systems. The last twenty years has seen a plethora of new procurement methods seeking to encourage different behaviours and allocations of risk. Many such initiatives experienced significant reality gaps between technological intent and resultant behaviours. Of particular importance in the current context is the notion of performance-based contracting which seeks to reward parties on the basis of building performance.(5) Innovation in through-life service provision. Most innovation in facilities management (FM) is concerned with service provision rather than the design and construction of the built asset. The inclusion of FM-service provision reflects the ICRC's strategic focus on through-life issues. The shift towards service provision is reflected in practice through procurement approaches such as PFI/PPP. But the issue has a wider significance as construction contractors increasingly embrace service philosophy. (6) Competitiveness, productivity and performance. Focuses on techniques for performance improvement, coupled with a broader emphasis on competitiveness and profitability within the marketplace. Techniques for performance improvement include: process mapping, benchmarking, value management, risk management and life-cycle costing. Also seeks to assess the competitiveness of the construction sector in comparison to other countries, and to achieve a broader understanding of the economic context within which firms operate.

This proposal is for the creation of Samples of Anonymised Records (SARs) from British censuses 1961 to 1981 and reconstruction of a 2001 SAR using record-level data recovered from archive tapes by the Office for National Statistics (ONS). Current changes to ONS IT infrastructure and some benefits from contemporary census processing present a unique moment of opportunity to recover these historical data and to create a rich new research resource for the analysis of social change over the last 50 years. The insights likely to be revealed from these data directly address ESRC's current priorities of 'Influencing behaviour and informing interventions' (e.g. 'How does the interplay of childhood, family, community and wider society influence inequalities in wellbeing?') and 'A vibrant and fair society' (e.g.,'How mobile is our society?'). In relation to both of these objectives ESRC has articulated a clear intention to make better use of existing data and to deepen the capacity of the UK research community.

Productivity growth has been slowing down in the last decade in major economies as well as in emerging markets despite the prevalence of digital technologies. This phenomenon is widely known as the productivity paradox. The productivity growth slowdown is particularly acute in the UK compared to other major economies. Moreover, industries that are the most intensive users of Information and Communication Technologies (ICT) appear to have contributed most to the slowdown in productivity. One of the main reasons for this productivity slowdown could be due to the limited redesign of business processes and business models following the adoption of new digital technologies by firms. Through the research programme Dr. Velu will provide a better understanding the relationship between business model innovation and productivity improvements following the adoption of intelligent automation technologies. Dr. Velu will build a digital tool for management information and decision support systems for assessment of productivity of business models in order to enable rapid and sustained improvements in productivity within firms following the adoption of digital technologies. In doing so, the Dr Velu aims to propose a new framework for productivity reporting for national income accounting. Dr. Velu will conduct historical analysis of firms that have implemented intelligent automation technologies in order to learn and develop the criteria for productivity measurement of business models. This will include analysis from historical publically available data as well as within firm analysis of a number of selected sectors such as manufacturing, distribution and the sharing economy. In addition, the research will conduct longitudinal in depth analysis of firms in similar sectors as the historical analysis in order to build a digital tool that will identify business model innovation opportunities following the adoption of intelligent automation technologies. This will involve working with the senior management team of a selected number of firms in these sectors in order to define the data requirements, draw-up the technology specification, develop the software programme, populate and test the digital tool with data and propose ways to embed the digital productivity tool within existing management reporting systems. The research will benefit firms as it will provide the basis for a systematic evaluation of the need for business model innovation opportunities following the implementation of intelligent automation technologies. The research will also benefit policymakers by defining good quality and appropriate data in addressing the challenges of measuring productivity in the digital economy.

177 million tonnes of virgin aggregates, 15 million tonnes of cement and 2 billion bricks were used to build houses, civic and commercial buildings, roads and railways, etc, in the UK in 2016. Meanwhile, 64 million tonnes of waste arose from construction and demolition. Materials from construction and demolition are mainly managed by down-cycling with loss of the value imparted to them by energy-intensive and polluting manufacturing processes; for example, high value concrete is broken down into low value aggregate. Environmental damage is associated with the whole linear life cycles of mineral-based construction materials, and includes scarring of the landscape and habitat destruction when minerals are extracted from the earth; depletion of mineral and energy resources; and water use and emission of greenhouse gases and other pollutants to air, land and water, during extraction, processing, use and demolition. It is important to take action now, to return materials to the resource loop in a Circular Economy, and reduce the amount of extraction from the earth, as the amount we build increases each year. For example, the UK plans spend £600 billion to build infrastructure in the next decade. The UKRI National Interdisciplinary Circular Economy Research Centre for Mineral-based Construction Materials therefore aims to do more with less mineral-based construction materials, to reduce costs to industry, reduce waste and pollution, and benefit the natural environment that we depend on. There is potential for mineral-based construction materials to be reused and recycled at higher value, for example, by refurbishing rather than demolishing, or by building using reusable modules that can be taken apart rather than demolished, so all the energy that went into making them isn't wasted. It may also be possible to substitute minerals from natural sources by other types of mineral wastes, such as the 76 million tonnes of waste arising from excavation and quarrying, 14 million tonnes of mineral wastes that come from other industries, or 4 billion tonnes of historical mining wastes. We can also be more frugal in our use of mineral-based construction materials, by designing materials, products and structures to use less primary raw materials, last longer, and be suitable for repurposing rather than demolition, and using new manufacturing techniques. First, our research will try to better understand how mineral-based construction materials flow through the economy, over all the stages of their life cycle, including extraction, processing, manufacture, and end-of-life. The Centre will work to support the National Materials Database planned by the Office of National Statistics, which will capture how, where and when materials are used and waste arises, so that we have the information to improve this system. We will also study how any changes we might make to practices around minerals use would affect the environment and the economy, such as greenhouse gas emissions, costs to businesses, or jobs. Second, we will work on technical improvements that we can make in design of mineral-based products and structures, and in all the life-cycle stages of mineral-based construction materials. Third, we will look at how changes in current business models and practices could support use of less mineral-based construction materials, such as how they might be able to move more quickly to new technologies, or how they might use digital technologies to keep track of materials. We will explore how the government can support these changes, and how we can provide education so that everyone working in this system understands what they need to do. In the first 4 years of our Centre, 15 postdoctoral researchers will gain research experience working in the universities for 2y and will then work with an industrial collaborator for a year, to implement the results of their research. More than 20 PhD and 30 MSc students will also be trained in the Centre.

We live in the age of data. Technology is transforming our ability to collect and store data on unprecedented scales. From the use of Oyster card data to improve London's transport network, to the Square Kilometre Array astrophysics project that has the potential to transform our understanding of the universe, Big Data can inform and enrich many aspects of our lives. Due to the widespread use of sensor-based systems in everyday life, with even smartphones having sensors that can monitor location and activity level, much of the explosion of data is in the form of data streams: data from one or more related sources that arrive over time. It has even been estimates that there will be over 30 billion devices collecting data streams by 2020. The important role of Statistics within "Big Data" and data streams has been clear for some time. However the current tendency has been to focus purely on algorithmic scalability, such as how to develop versions of existing statistical algorithms that scale better with the amount of data. Such an approach, however, ignores the fact that fundamentally new issues often arise when dealing with data sets of this magnitude, and highly innovative solutions are required. Model error is one such issue. Many statistical approaches are based on the use of mathematical models for data. These models are only approximations of the real data-generating mechanisms. In traditional applications, this model error is usually small compared with the inherent sampling variability of the data, and can be overlooked. However, there is an increasing realisation that model error can dominate in Big Data applications. Understanding the impact of model error, and developing robust methods that have excellent statistical properties even in the presence of model error, are major challenges. A second issue is that many current statistical approaches are not computationally feasible for Big Data. In practice we will often need to use less efficient statistical methods that are computationally faster, or require less computer memory. This introduces a statistical-computational trade-off that is unique to Big Data, leading to many open theoretical questions, and important practical problems. The strategic vision for this programme grant is to investigate and develop an integrated approach to tackling these and other fundamental statistical challenges. In order to do this we will focus in particular on analysing data streams. An important issue with this type of data is detecting changes in the structure of the data over time. This will be an early area of focus for the programme, as it has been identified as one of seven key problem areas for Big Data. Moreover it is an area in which our research will lead to practically important breakthroughs. Our philosophy is to tackle methodological, theoretical and computational aspects of these statistical problems together, an approach that is only possible through the programme grant scheme. Such a broad perspective is essential to achieve the substantive fundamental advances in statistics envisaged, and to ensure our new methods are sufficiently robust and efficient to be widely adopted by academics, industry and society more generally.