Augmenting safe system of working: a systems thinking approach with leading indicators embedded within

Bayramova, Ashyrgul (2025) Augmenting safe system of working: a systems thinking approach with leading indicators embedded within. Doctoral thesis, Birmingham City University.

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Abstract

Complex and evasive phenomenon such as safety requires a holistic, multifaceted and intricately monitored and managed approach as opposed to current fragmented and reductionistic methods predominating in safety management. Such gestaltism of combining componential elements of complexly integrated systems can be achieved through the adoption of systems thinking and via the use of weak but early signals known as leading indicators. Therefore, this current doctoral study seeks to engender a novel theoretical basis in the form of conceptual model for the promulgation of proactive and holistic safety management, which is founded on continual and iterative learning from past and current safety activities. Such a conceptual model is inductively developed through analysis of existing knowledge in the literature and is tested with real life case study data.

To achieve the research aim, the research philosophies of interpretivism and critical realism were adopted to study the phenomenon under investigation and develop new theoretical insights. Within this overarching epistemology, the research strategy of sequential mixed methods was employed by combining a systematic literature review and case study using combination of data analysis methods such as thematic analysis, content analysis, cross-comparison analysis and framework analysis. The research process follows two phases viz., in phase 1 pertinent literature is systematically reviewed with inductive reasoning and in phase 2 the research outcome from the preceding phase is tested with real case data using abductive and deductive reasoning. Consequently, the phase 1 of the study engenders a novel conceptual model for leading indicators’ development and implementation. To test this research outcome, a proof-of-concept is designed at phase 2 by adopting the development step of the conceptual model viz., by seeking to develop leading indicators from a combination of case study data and their relevant normative documents. In addition to testing the conceptual model, this step engenders a novel analytical framework which provides the systematic development of leading indicators from the qualitative dataset. As a result, a total of 484 new leading indicators were identified by using the analytical framework. Subsequently, all these three research outcomes (i.e. proof-of-concept model, analytical framework and examples of leading indicators) are validated through focus group interview of experts.

Consequently, the study has developed multiple research outcomes, viz., main contributions such as proof-of-concept model in Figure 7.9; analytical framework in Figure 8.3; as well as other research contributions such as guidance note for training efficacy assessment in Figure 7.4; Safety-in-cohesion model in Figure 7.7; and Dynamic theory of incident evolution in Figure 8.5. These research findings generated create the groundwork for: proliferation of systems thinking in understanding safety, its management and maintenance; propagation of proactive and pre-emptive stance in development of safety countermeasures; and promulgation of a dynamic and adaptable approach in the generation of safety intelligence for continuous improvement. Therefore, these emergent theoretical and practical contributions stemming from this current doctoral work will become instrumental in mitigating asset and personal risks related to frontline workers’ interaction with operating vehicles and construction machinery on highway work sites as well as in other safety critical industries and sectors. Moreover, the work will be influential in continuously monitoring safety status of complex systems and simultaneously preventing unfavourable events from taking place and learning from both failures and successes.

Item Type:	Thesis (Doctoral)
Dates:	Date Event 26 February 2025 UNSPECIFIED
Uncontrolled Keywords:	Leading indicators; systems thinking; lagging indicators; safety analytics; proactive safety management; continuous learning organisation.
Subjects:	CAH10 - engineering and technology > CAH10-01 - engineering > CAH10-01-07 - civil engineering CAH13 - architecture, building and planning > CAH13-01 - architecture, building and planning > CAH13-01-04 - planning (urban, rural and regional)
Divisions:	Doctoral Research College > Doctoral Theses Collection Faculty of Computing, Engineering and the Built Environment > College of Built Environment
Depositing User:	Louise Muldowney
Date Deposited:	03 Mar 2025 09:27
Last Modified:	03 Mar 2025 09:27
URI:	https://www.open-access.bcu.ac.uk/id/eprint/16188

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