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This study aims to aid theory building, the use of decision theory (DT) concepts in sustainable supply chain management (SSCM) research is examined.

An abductive approach considers two DT concepts, Snowden’s Cynefin framework for sense-making and Keeney’s value-focussed decision analysis, in a systematic literature review of 160 peer-reviewed papers in English.

Around 60 per cent of the papers on decision-making in SSCM come from operational research (OR), which makes explicit use of DT. These are almost all normative and rationalist and focussed on structured decision contexts. Some exceptions seek to address unstructured decision contexts via Complex Adaptive Systems or Soft Systems Methodology. Meanwhile, a second set, around 16 per cent, comes from business ethics and are empirical, behavioural decision research. Although this set does not explicitly refer to DT, the empirical evidence here supports Keeney’s value-focussed analysis.

There is potential for theory building in SSCM using DT, but the research only addresses SSCM research (including corporate responsibility and ethics) and not DT in SCM or wider sustainable development research.

Use of particular decision analysis methods for SSCM may be improved by better understanding different decision contexts.

The research shows potential synthesis with ethical DT absent from DT and SCM research.

Empirical behavioural decision analysis for SSCM is considered alongside normative, rational analysis for the first time. Value-focussed DT appears useful for unstructured decision contexts found in SSCM.

Empirical, behavioural decision analysis for SSCM is considered alongside normative rational analysis for the first time. Value-focussed DT appears useful for unstructured decision contexts found in SSCM.

This study demonstrates how artificial intelligence (AI) shapes the strategic planning process in volatile, uncertain, complex and ambiguous (VUCA) business environments. Having adopted various domains of the Cynefin framework, the research explores AI's transformative potential and provide insights regarding how organisations can harness AI-driven solutions for strategic planning.

This conceptual paper theorises the role of AI in strategic planning process in a VUCA world by integrating extant knowledge across multiple literature streams. The “model paper” approach was adopted to provide a theoretical framework predicting relationships among considered concepts.

The paper highlights potential application of the Cynefin framework to manage complexities in strategic decision-making process, the transformative impact of AI at different stages of strategic planning, the required strategic planning characteristics within VUCA to be supported by AI and the attendant challenges posed by AI integration in the uncertain business landscape.

This study pioneers a theoretical exploration of AI's role in strategic planning within the VUCA business landscape, guided by the Cynefin framework. Thus, it enriches scholarly discourse and expands knowledge frontiers.

Using a complexity-informed approach, we aim to understand why introduction of a mobile service delivery model for osteoporosis across diverse organisational and country contexts in the UK National Health Service (NHS) met with variable success.

Six comparative case studies; three prospectively in Scotland using an action research-informed approach; and three retrospectively in England with variable degrees of success. The Non-adoption, Abandonment, Scale-up, Spread and Sustainability framework explored interactions between multi-level contextual factors and their influence on efforts to introduce and sustain services.

Cross-boundary service development was a continuous process of adaptation and evolution in rapidly shifting healthcare context. Whilst the outer healthcare policy context differed significantly across cases, inner contextual features predominated in shaping the success or otherwise of service innovations. Technical and logistical issues, organisational resources, patient and staff actions combined in unpredictable ways to shape the lifecycle of service change. Patient and staff thoughts about place and access to services actively shaped service development. The use of tacit “soft intelligence” and a sense of “chronic unease” emerged as important in successfully navigating around awkward people and places.

“Chronic unease” and “soft intelligence” can be used to help individuals and organisations “tame” complexity, identify hidden threats and opportunities to achieving change in a particular context, and anticipate how these may change over time. Understanding how patients think and feel about where, when and how care is delivered provides unique insights into previously unseen aspects of context, and can usefully inform development and sustainability of patient-centred healthcare services.

This study has uniquely traced the fortunes of a single service innovation across diverse organisational and country contexts. Novel application of the NASSS framework enabled comparative analysis across real-time service change and historical failures. This study also adds to theories of context and complexity by surfacing the neglected role of patients in shaping healthcare context.

The purpose of this paper is to apply the aspects of decision theory (DT) to performance measurement and management (PMM), thereby enabling the theoretical elaboration of volatility, uncertainty, complexity and ambiguity in the business environment, which are identified as barriers to effective PMM.

A review of decision theory and PMM literature establishes the Cynefin framework as the basis for extending the performance alignment matrix. Case research with seven companies explores the relationship between two concepts under-examined in the performance alignment matrix – internal dominant logic (DL) as the attribute of organisational culture affecting decision making, and the external environment – in line with the concept of alignment or fit in PMM. A focus area is PMM related to sustainable operations and sustainable supply chain management.

Alignment between DL, external environment and PMM is found, as are instances of misalignment. The Cynefin framework offers a deeper theoretical explanation about the nature of this alignment. Other findings consider the nature of organisational ownership on DL.

The cases are exploratory not exhaustive, and limited in number. Organisations showing contested logic were excluded.

Some organisations have cultures of predictability and control; others have cultures that recognise their external environment as fundamentally unpredictable, and hence there is a need for responsive, decentralised PMM. Some have sought to change their culture and PMM. Being attentive to how cultural logic affects decision making can help reduce the misalignment in PMM.

A novel contribution is made by applying decision theory to PMM, extending the theoretical depth of the subject.

Quality management (QM) can support organisations in contributing to sustainable development. As a result of an expanding focus from customers towards stakeholders within QM, the perspectives to consider multiply. Understanding how practices and tools for process management are specifically affected by this increase in perspectives is key to creating the right conditions for improvement initiatives that support sustainable development.

This paper constructs a typology wherein the use of process management practices and tools is described in nine distinguished system contexts. Inductive discrimination is used to differentiate the system contexts and different use cases for process practices and tools.

Using the system of systems grid (SOSG), mainstream business process management (BPM) practices are positioned in a simple unitary context, whilst sustainability challenges also involve more complex contexts. Addressing these challenges requires integrating new tools and methods from paradigms outside of traditional functionalist business process management practices.

This paper highlights the necessity to consider system contexts when developing feasible practices and tools for effective process management.

Practical implications are that quality practitioners aiming to exploit the potential in process management to support sustainability get support for planning and conducting process improvement initiatives aiming to consider several stakeholder perspectives.

This paper presents a new typology for understanding the context of QM process initiatives and BPM in light of a contemporary sustainability focus.

Experiments are the backbone of the development process of data-driven predictive models for scientific applications. The quality of the experiments directly impacts the model performance. Uncertainty inherently affects experiment measurements and is often missing in the available data sets due to its estimation cost. For similar reasons, experiments are very few compared to other data sources. Discarding experiments based on the missing uncertainty values would preclude the development of predictive models. Data profiling techniques are fundamental to assess data quality, but some data quality dimensions are challenging to evaluate without knowing the uncertainty. In this context, this paper aims to predict the missing uncertainty of the experiments.

This work presents a methodology to forecast the experiments’ missing uncertainty, given a data set and its ontological description. The approach is based on knowledge graph embeddings and leverages the task of link prediction over a knowledge graph representation of the experiments database. The validity of the methodology is first tested in multiple conditions using synthetic data and then applied to a large data set of experiments in the chemical kinetic domain as a case study.

The analysis results of different test case scenarios suggest that knowledge graph embedding can be used to predict the missing uncertainty of the experiments when there is a hidden relationship between the experiment metadata and the uncertainty values. The link prediction task is also resilient to random noise in the relationship. The knowledge graph embedding outperforms the baseline results if the uncertainty depends upon multiple metadata.

The employment of knowledge graph embedding to predict the missing experimental uncertainty is a novel alternative to the current and more costly techniques in the literature. Such contribution permits a better data quality profiling of scientific repositories and improves the development process of data-driven models based on scientific experiments.

This corpus-based study provides a descriptive account of the distribution of the polysemous noun nafs in two Arabic varieties, Modern Standard Arabic (MSA) and Classical Arabic (CA). The research objective is to survey the use of nafs as a reflexive marker in local binding domains and as a self-intensifier in NP-adjoined positions.

The consulted corpora are Timespamped JSI Web corpus for MSA and Quran corpus for CA. While attending to corpora size differences, MSA and CA exhibit a pattern of difference and similarity in nafs diffusion.

In the modern variety, nafs is pervasively used as reflexive marker in canonical binding domains, along with a less frequent, yet notable, intensifier user, and these uses are partially and cautiously attributed to the specific genre in which they occur. In CA, nafs is mainly recurrent as a polysemous noun, along with extensive use as a reflexive marker in local binding settings. As an intensifier, nafs is totally non-existent in the CA corpus, in the same way as it is in absentia in VP-constituent extraction in MSA.

Examining whether nafs, as a reflexive marker, deviates from canonical binding in Arabic the way English reflexive pronouns do. Building a general account of this distribution is relevant in understanding the explicit (syntactic) and implicit (discourse-based) dimensions of reflexive marker and self-intensifier processing and interpretation in Arabic as a first and second language.

Developing cybersecurity awareness (CSA) is becoming a more and more important goal for modern organizations. CSA is a complex sociotechnical system where social, technical and organizational aspects affect each other in an intertwined way. With the goal of providing a holistic representation of CSA, this paper aims to develop a taxonomy of factors that contribute to organizational CSA.

The research used a design science approach including a literature review and practitioner interviews. A taxonomy was drafted based on 71 previous research publications. It was then updated and refined in two iterations of interviews with domain experts.

The result of this research is a taxonomy which outline six domains for importance for organization CSA. Each domain includes several activities which can be undertaken to increase CSA within an organization. As such, it provides a holistic overview of the CSA field.

Organizations can adopt the taxonomy to create a roadmap for internal CSA practices. For example, an organization could assess how well it performs in the six main themes and use the subthemes as inspiration when deciding on CSA activities.

The output of this research provides an overview of CSA based on information extracted from existing literature and then reviewed by practitioners. It also outlines how different aspects of CSA are interdependent on each other.

Distinguishing between autism characteristics and trauma-related symptoms may be clinically challenging, particularly in individuals who have experienced early traumatisation. Previous studies have described a risk that trauma-related symptoms are misinterpreted and/or misattributed to autism. This study aims to describe and explore assessment strategies to distinguish autism and early traumatisation in the case of a young woman with mild intellectual disability.

A clinical case study outlining assessment strategies, diagnostic decision-making and initial intervention.

A multi-informant interdisciplinary assessment using multiple assessment tools, together with a comprehensive review of records from previous assessments and contacts with various services, was helpful in distinguishing between autism and trauma. This included specific assessment tools for autism and trauma. Autism characteristics and trauma-related symptoms appeared to interact, not merely co-occur.

The current case demonstrates that diagnostic overshadowing may occur for autism in the context of early trauma. The case further highlights the importance of not ascribing trauma-related symptoms to autism, as service provision and treatment need to take account of both. Overlooking autism in individuals who have experienced early traumatisation may result in a risk that intervention and care are not appropriately adapted, which may involve a risk of exacerbating trauma symptoms.

This study aims to analyse the non-linear losses of a porous media (stack) composed by parallel plates and inserted in a resonator tube in oscillatory flows by proposing numerical correlations between pressure gradient and velocity.

The numerical correlations origin from computational fluid dynamics simulations, conducted at the microscopic scale, in which three fluid channels representing the porous media are taken into account. More specifically, for a specific frequency and stack porosity, the oscillating pressure input is varied, and the velocity and the pressure-drop are post-processed in the frequency domain (Fast Fourier Transform analysis).

It emerges that the viscous component of pressure drop follows a quadratic trend with respect to velocity inside the stack, while the inertial component is linear also at high-velocity regimes. Furthermore, the non-linear coefficient b of the correlation ax + bx² (related to the Forchheimer coefficient) is discovered to be dependent on frequency. The largest value of the b is found at low frequencies as the fluid particle displacement is comparable to the stack length. Furthermore, the lower the porosity the higher the Forchheimer term because the velocity gradients at the stack geometrical discontinuities are more pronounced.

The main novelty of this work is that, for the first time, non-linear losses of a parallel plate stack are investigated from a macroscopic point of view and summarised into a non-linear correlation, similar to the steady-state and well-known Darcy–Forchheimer law. The main difference is that it considers the frequency dependence of both Darcy and Forchheimer terms. The results can be used to enhance the analysis and design of thermoacoustic devices, which use the kind of stacks studied in the present work.