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.

The construction industry has a lamentable reputation for having a high prevalence of suicides and mental health (MH) problems. Several government and academic reports have identified that construction workers are at a far higher risk of MH disorders than workers in other industrial sectors. While studies on construction workers’ MH have significantly increased in recent years, a systematic review of the potential causes of MH problems in the industry has hitherto eluded construction researchers. This study fills this ominous knowledge gap by conducting a realist systematic review of the literature published since 2003. The review conducted adopts the psychological safety climate model of PSC-12 to create a comprehensive list of MH causation (sourced from a rich literature synthesis) as a precursor to developing a theoretical model that identifies MH causations affecting distinct psychological safety climates within the industry. Emergent findings identify 43 MH causation factors with high job demand as the most significant contributor, followed by interpersonal relationships, low job control, low job support and physical status. In addition, it is found that organisation participation factors have been the major areas of focus, while management commitment and management priority are under-researched areas. Moreover, research gaps within the four dimensions of the PCS-12 model were explored to distinguish new potential research areas to address the knowledge gaps observed. In practical terms, the study collates and presents a comprehensive theoretical model of MH causations, providing a concise source of practical knowledge for practitioners.

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.

With the aim of developing a new theoretical insight which will augment the promulgation of leading indicators’ use, this present research studies pertinent literature. Associated study objectives are to: 1) generate insight into potential challenges, use and benefits of adopting leading indicators in safety management from pertinent literature; and 2) elucidate upon existing abstruseness between safety leading and lagging indicators. For an extensive and thorough literature analysis, two consecutive data analysis methods are adopted (viz., thematic and content analyses). Through thematic analysis, 13 clusters (each representing different uses of leading indicators) emerged, from which the ‘health and safety’ cluster was selected for a deeper analysis in content analysis. In addition, by reviewing the compendium of leading indicator examples collected from extant safety leading indicator literature, novel types of dichotomous leading indicators were identified, viz., generic and specific leading indicators. Subsequently, a synthesis of challenges and benefits of safety leading indicator adoption was generated through deductive content analysis. Furthermore, a new theoretical explanation into the relationship of safety leading and lagging indicators is proffered which also incorporates safety management dynamics representing different levels of safety maturity. This study constitutes a first attempt to: provide a structured synthesis of safety leading indicators’ functions along with their challenges in development, implementation and adoption stages; shed a new light into the theoretical explication of safety lagging and leading indicators’ relationship; and introduce safety management dynamics that establish different levels of safety maturity.

This research implements the steps of developing or identifying leading indicators (LIs) delineated in a previously published conceptual model to test its practicality on case study data. Concomitant objectives are (a) to systematically review extant literature of 'LIs development and identification' to develop an analytical framework for identifying LIs; and to identify LIs from case study incident reports and normative documents using the framework. To empirically validate the conceptual model, a two staged data analysis process was adopted: (1) a theoretical work stage, where pertinent literature was studied through systematic literature review using Scopus and Web of Science databases and a detailed framework analysis; and (2) practical work stage, where an inductively developed analytical framework and insights gained from the theoretical work stage were applied to real-life case study data and their apposite normative documents. Random sampling was used to select 12 different case studies of accidents from a private database of 97 case studies. In total, 2,423 LIs were identified from extant literature and through framework analysis using the bespoke analytical framework generated, a total of 484 LIs were identified from a combination of selected case study materials and their relevant normative documents. All these 484 newly developed LIs were contrasted with a compilation of the previously published 2,423 LIs in the literature. Consequently, a total of 232 LIs out of 484 were recognized as entirely new and novel. These LIs were then thematically grouped into 19 clusters for brevity. A novel analytical framework for identifying new LIs was inductively developed. The framework enables identification of LIs from a qualitative dataset and classify them into eight types of LIs. This novel research constitutes the first attempt to identify and validate LIs via the use of an analytical framework and real-life case study data.

A lack of processual guidance on selecting research methodology elements that align to a phenomenon under investigation (notably from a state of tabula rasa ) convolutes the process of creating a bespoke, cogent and scientifically grounded narrative that engenders higher scientific validity. Therefore, this study reviews research methodology literature to delineate current guidance and provide taxonomic synthesis of research methodology elements and their use in a research process. Associated objectives are to: (1) describe research methodology layers of choices in a compendious manner; and (2) generate a novel decision support framework as processual guidance for scholars to select the optimal research methodology elements for a given phenomenon being studied. This systematic literature review study adopts interpretivism and inductive reasoning in a two-step qualitative sequential analyses process that encompasses a preliminary literature review and subsequent, content analysis. First, a preliminary literature review scrutinises prominent research publications on research methodology (via Google Scholar), which leads to the emergence of research focus, namely ‘the role of objectivity and subjectivity in research methodology’. Second, 138 research publications sourced from Scopus are studied by manual thematic clustering, followed by a content analysis of 59 most relevant-to-research-focus items using the qualitative data analysis tool NVivo. Common research methodology elements are tabulated and their componential features are cross-compared against prevalent-in-the-literature research attributes or research classifications. These research methodology elements (that are differentiated as involving either implicit or explicit decision-making) are modelled into an infographic depiction which describes these elements on the spectrum of objectivity to subjectivity and their convergence point. Such a summary model differentiates research designs and studies that are gravitating towards objectivity, falling towards subjectivity or levitating between the two. These findings are subsequently transformed into a guidance model (entitled ‘magnetic field of research methodology’) which introduces inputs into and outcomes from the process of research methodology elements selection. The model emphasises the role of ‘external forces’ (i.e. research inputs/materials) in the choice of research methodology elements and their impact on research outcome type. This study is the first attempt in extant literature to: collate and organise research methodology elements on the level of objectivity and subjectivity; and provide a decision-making framework which incorporates decisions, research stages, steps and research item progress which elucidates the process of constructing a scientifically robust methodology.