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Bew, M D (2017) Engineering better social outcomes through requirements management & integrated asset data processing, Unpublished PhD Thesis, School of the Built Environment, University of Salford.
- Type: Thesis
- Keywords: building information modelling; feedback; infrastructure; measurement; migration; motivation; owner; performance improvement; population; productivity; skills
- URL: http://usir.salford.ac.uk/id/eprint/42341/
The needs of society are no longer serviceable using the traditional methods of infrastructure providers and operators. Urbanisation, pressure on global resources, population growth and migration across borders is placing new demands which traditional methods can no longer adequately serve. The emergence of data and digital technology has enabled new skills to emerge and offer new possibilities as well as set much higher expectations for the younger generation who have only known lives in the digital age. The data describing the physical properties of built assets have been well understood and digital methods such as Building Information Modelling are providing levels of access and quality historically unknown. The concepts of human perception are not so well understood with research only being documented over the last forty years or so, but the understanding of human needs and the impact of poor infrastructure and services has now been linked to poor perception and social outcomes. This research has developed and instantiated a methodology which uses data from the delivery and operational phases of a built asset and with the aid of understanding the user community’s perceptions creates intelligence that can optimise the assets performance for the benefit of its users. The instantiation was accomplished by experiment in an educational environment using the “Test Bench” to gather physical asset data and social perception data and using analytics to implement comparative measurements and double loop feedback to identify actionable interventions. The scientific contributions of this research are the identification of methods which provide valuable and effective relationships between physical and social data to provide ‘’actionable’’ interventions for performance improvement and the instantiation of this discovery through the development and application of the ‘’Test Bench’’. The major implication has been to develop a testable relationship between social outcomes and physical assets, which with further development could provide a valid challenge to the least cost build option that is taken by the vast number of asset owners, by better understanding the full implications on people’s perceptions and social outcomes. The cost of operational staff and resources rapidly outweighs the cost of assets, and the effective motivation and productivity the right environment can provide improved or inhibited performance and social outcomes.