The Construction 2025 Industrial Strategy has set a vision for the UK construction to be technologically advanced and efficient . A reduction of 50% in the time to complete projects and 33% in initial construction costs are targets set up by the government to ensure Britain has a competitive edge. These targets are to be achieved by the construction sector by taking advantage of new technology global trends. Machine learning (ML) is a technology already impacting the global economy and has the potential to transform the construction industry with the use of data-based solutions to improve the way projects are delivered by (1) better managing its workforce and (2) increasing construction productivity.
a) What can you draw from the academic and industry literature that offers ways of affecting change in construction with the use of ML on (2) of the above goals?
b) From this review, what would you recommend is done at the construction firm to improve (1) of the above goals? Consider the geographic focus and limits of your answer (your recommendations only apply to UK)
c) Provide reflective conclusions on the key learning you have obtained from answering this brief and identify no more than three recommendations for scholars to research and practitioners to consider implementing.
Reference: 30 reference required(I have uploaded 20). You should use Harvard referencing and base your reasoning on peer-reviewed literature in academic journals and books primarily based on such literature. Where you are required to use real world examples you may refer to trade literature and newspaper articles.
Analysis: Logical and appropriate analytical structure used to develop a coherent and to some degree original/independent argument. Argument grounded in observations of specific industry conditions. In addition, the paper shows ability to understand and solve problems, and work with and connect both theoretical and empirical content.
Conclusion: the last part of the essay will be for you to reflect on the major learning that has been achieved in the way.