Intelligent Decision-Making System Frameworks for a Digital Plan of Work: A Theoretical Investigation for the Construction Industry

The construction industry is characterised by fragmentation and suffers from lack of collaboration, often adopting adversarial working practices to achieve deliverables. For the UK Government and construction industry, BIM is a game changer aiming to rectify this fragmentation and promote collaboration. However it has become clear that there is an essential need to have better controls and definitions of both data deliverables and data classification. Traditional methods and techniques for collating and inputting data have shown to be time consuming and provide little to improve or add value to the overall task of improving deliverables. Hence arose the need in the industry to develop a Digital Plan of Work (DPoW) toolkit that would aid the decision making process, providing the required control over the project workflows and data deliverables, and enabling better collaboration through transparency of need and delivery. The specification for the existing Digital Plan of Work (DPoW) was to be, an industry standard method of describing geometric, requirements and data deliveries at key stages of the project cycle, with the addition of a structured and standardised information classification system. However surveys and interviews conducted within this research indicate that the current DPoW resembles a digitised version of the pre-existing plans of work and does not push towards the data enriched decision-making abilities that advancements in technology now offer. A Digital Framework is not simply the digitisation of current or historic standard methods and procedures, it is a new intelligent driven digital system that uses new tools, processes, procedures and work flows to eradicate waste and increase efficiency. In addition to reporting on conducted surveys above, this research paper will present a theoretical investigation into usage of Intelligent Decision Support Systems within a digital plan of work framework. Furthermore this paper will present findings on the suitability to utilise advancements in intelligent decision-making system frameworks and Artificial Intelligence for a UK BIM Framework. This should form the foundations of decision-making for projects implemented at BIM level 2. The gap identified in this paper is that the current digital toolkit does not incorporate the intelligent characteristics available in other industries through advancements in technology and collation of vast amounts of data that a digital plan of work framework could have access to and begin to develop, learn and adapt for decision-making through the live interaction of project stakeholders.

The Impact of Education and Socioeconomic and Occupational Conditions on Self-Perceived and Mental Health Inequalities Among Immigrants and Native Workers in Spain

There is limited evidence on the influence of social determinants on the self-perceived and mental health of immigrants settled at least 8 years in Spain. The aim of this study was to examine differences between workers related to migrant-status, self-perceived and mental health, and to assess their relationship to occupational conditions, educational level and occupational social class, stratified by sex. Using data from the Spanish National Health Survey of 2011/12, we computed prevalence, odds ratios and explicative fractions. Mental (OR 2.02; CI 1.39–2.93) and self-perceived health (OR 2.64; CI 1.77–3.93) were poorer for immigrant women compared to natives. Occupational social class variable contributes 25 % to self-perceived health OR in immigrant women. Settled immigrant women workers are a vulnerable group in Spain.