Using a systematic review of literature, this study identifies the potential impact of blockchain solutions for augmenting supply chain resilience (SCR) to cybercrime. This rich literature synthesis forms the basis of a novel theoretical framework that provides guidance and insight for blockchain adopters and vendors as well as delineate palpable benefits of this novel technology. An interpretivist philosophical design and inductive reasoning are adopted to conduct the systematic review of literature. A total of 867 papers were retrieved from Scopus database between the years of 2016 and 2020 and subsequently analysed via abductive reasoning, grounded theory and a thematic meta-analysis; where the latter was achieved using a scientometric approach and software tools such as VOS viewer and NVivo. Scientometric analysis revealed the most prolific countries, sources, publications and authors who reside at the vanguard of blockchain developments and adoption. Subsequent grounded theory analysis identified six main clusters of research endeavour viz: “case study”, “challenges and opportunity”, “traceability”, “smart contract” “blockchain and IoT” and “data security”. From 28 SCR metrics identified within literature, five were found to have been positively impacted by blockchain technology solutions, namely: “visibility”, “collaboration”, “integration”, “risk management” and “information sharing.” Prominent applications of blockchain technology in practice were “traceability systems” and “smart contracts” which are often implemented separately or in combination and primarily in food supply chains. This research constitutes the first study to critically synthesise extant literature for evaluation of blockchain solutions’ implication on SCR metrics. New perspectives obtained provided a basis for the novel theoretical framework for implementation that will be valued by software developers and adopting organizations, whilst creating new direction for researchers interested in blockchain technology.

Buildings inevitably deteriorate with time. Schools buildings are no exception and require refurbishment at times. Despite the UK Government announcing the £1 billion funding for rebuilding 50 schools over 10 years starting 2010–2021, it is common practice for builders and designers to, upon completion of a building project, move on to the next development without considering how the completed building performs. This research undertakes a post occupancy evaluation (POE) of three schools in the West Midlands, UK with specific focus on building services, viz., heating, lighting, and air conditioning and ventilation. The research adopted a mixed philosophical approach of interpretivism and post-positivism to conduct inductive reasoning. A questionnaire that collected both quantitative and qualitative primary data was distributed to the end-users of the schools. Data was analysed using the Cronbach’s alpha, one sample t-test and Kruskal–Wallis test to identify any differences between the questionnaire responses. Findings revealed that building users demanded greater control of the internal environment thus contradicting the current trend for automated ‘intelligent systems’ approaches. This research represents the first work to consider the contractor’s perspective towards developing a better understanding of client satisfaction with the school buildings. Moreover, the POE result represents a notable pragmatic advancement to knowledge that will influence the contractor’s knowledge and understanding of client satisfaction, and where to improve upon these.

Leading indicators represent an invaluable tool that offer organizations the capability to: track health and safety performance, not just failures and accidents; measure effectiveness of safety efforts adopted; and focus on undesired precursors, rather than undesired occurred events. Despite these palpable advantages associated with their adoption, leading indicator's definition, application, and function are mostly ambiguous and inconsistent within literature. Therefore, this study systematically reviews pertinent literature to identify the constructs of leading indicators and generates guidance for leading indicator implementation (as a conceptual model). The overarching epistemological design adopted interpretivism and critical realism philosophical stances together with inductive reasoning to analyze 80 articles retrieved from the Scopus database, plus 13 more publications supplemented by the snowballing technique. Analysis of the safety discourse within literature (as secondary data) was undertaken in two stages, namely: (1) a cross-componential analysis identified the main features of leading indicators in comparison to lagging indicators; and (2) content analysis revealed prominent constructs of leading indicators. Analysis results identify that the definition, types, and development methods represent the main constructs for understanding the concept of leading indicators. The study identifies that ambiguity around the definition and function of leading indicators is due to the lack of differentiation of its types, namely passive leading indicators and active leading indicators. As a practical contribution, the conceptual model, which introduces continuous learning through a perpetual loop of development and application of leading indicators, will help adopters create a knowledge repository of leading indicators and to continuously learn and improve their safety and safety performance. Specifically, the work clarifies their difference in terms of the timeframe passive leading indicators and active leading indicators take to measure different safety aspects, the functions they serve, the target they measure and their stage of development.

This study conducts a systematic review of safety risk models and theories by summarizing and comparing them to identify the best strategies that can be adopted in a digital ‘conceptual’ safety risk model for highway workers’ safety. A mixed philosophical paradigm was adopted (that used both interpretivism and post-positivism couched within inductive reasoning) for a systematic review and comparative analysis of existing risk models and theories. The underlying research question formulated was: can existing models and theories of safety risk be used to develop this proposed digital risk model? In total, 607 papers (where each constituted a unit of analysis and secondary data source) were retrieved from Scopus and analysed through colour coding, classification and scientometric analysis using VOSViewer and Microsoft Excel software. The reviewed models were built on earlier safety risk models with minor upgrades. However, human elements (human errors, human risky behaviour and untrained staff) remained a constant characteristic, which contributed to safety risk occurrences in current and future trends of safety risk. Therefore, more proactive indicators such as risk perception, safety climate, and safety culture have been included in contemporary safety risk models and theories to address the human contribution to safety risk events. Highway construction safety risk literature is scant, and consequently, comprehensive risk prevention models have not been well examined in this area. Premised upon a rich synthesis of secondary data, a conceptual model was recommended, which proposes infusing machine learning predictive models (augmented with inherent resilient capabilities) to enable models to adapt and recover in an event of inevitable predicted risk incident (referred to as the resilient predictive model). This paper presents a novel resilient predictive safety risk conceptual model that employs machine learning algorithms to enhance the prevention of safety risk in the highway construction industry. Such a digital model contains adaptability and recovery mechanisms to adjust and bounce back when predicted safety risks are unavoidable. This will help prevent unfortunate events in time and control the impact of predicted safety risks that cannot be prevented.

A scientometric analysis of extant literature is conducted to elucidate upon the practicality of teleworking throughout industry as a prelude to prescribing a bespoke conceptual adoption model that embeds innovative digital technologies to facilitate teleworking for construction professionals. The model is premised upon the Royal Institute of British Architects (RIBA) work stages and illustrates how technologies are being used at each incremental stage. An interpretivist philosophy and inductive reasoning were adopted using a sample of longitudinal secondary data contained within pertinent extant literature, where each publication constitutes a unit of analysis. The qualitative scientometric software VOSviewer and Voyant Tools were utilised to examine emergent research trends, with further manual review of prominent papers contained within the sample dataset. Four distinct historical advances are delineated in a timeline that describes the evolution of home working from the 1970s through to the present day (and during the global COVID-19 pandemic). Key milestones delineated indicate how technological advances have created new opportunities for teleworking. The research indicates that an acceleration of digital advances has engendered modernity in contemporary work location patterns and that these offer potentials to reduce the environmental impact of anthropogenic activities. This unique study highlights how COVID-19 and available digital technologies have shaped the future of teleworking from home and the potential environmental impact of such. This concludes by signposting directions for future research into the adoption of teleworking at the organisational level and establishing the cost and environmental savings to businesses from abandoning the traditional model of employer-based working.

The construction industry has endured high incident rates for many decades. Although multiple safety measures in the form of Safety I- and II-enabled safe systems of working (SSoWs) have been implemented, statistics reveal that a significant prevalence of incidents prevails worldwide. However, there is limited information available about the actual factors that are impeding these SSoWs. This study investigates and evaluates the barriers, bottlenecks and challenges (BB&Cs) that hinder the implementation of Safety I- and II-enabled SSoWs in the construction industry. Using a scoping review methodology, a thorough search of articles documenting the BB&Cs of implementing Safety I- and II-enabled SSoWs was carried out using Google Scholar, Scopus, and Web of Science databases. An initiative model was employed for categorising BB&C to implement Safety I and II, which includes micro- (site), meso- (organisation), and macro (environment)-thematic groupings, as a guiding framework for the mapping and analysis of results. The search yielded 98 articles that discussed the implementation of Safety I and II, with 54 of them specifically related to BB&Cs. Emergent results emphasised how there is scant literature on the BB&Cs of implementation Safety I- and II-enabled SSoWs across site, organisation and environment levels. Extensive global research is necessary to comprehensively understand the obstacles to implementing Safety I and II in practice as a first step towards reducing incidents and accidents on site. Cumulatively, the findings suggest that implementing Safety I- and II-enabled SSoWs should be based on removing BB&Cs and evaluating how they affect safety performance.