Search results

Background: Commodity-driven deforestation is a major driver of forest loss worldwide, and globalisation has increased the disconnect between producer and consumer countries. Recent due-diligence legislation aiming to improve supply chain sustainability covers major forest-risk commodities. However, the evidence base for specific commodities included within policy needs assessing to ensure effective reduction of embedded deforestation.

Methods: We conducted a rapid evidence synthesis in October 2020 using three databases; Google Scholar, Web of Science, and Scopus, to assess the literature and identify commodities with the highest deforestation risk linked to UK imports. Inclusion criteria include publication in the past 10 years and studies that didn't link commodity consumption to impacts or to the UK were excluded. The development of a review protocol was used to minimise bias and critical appraisal of underlying data and methods in studies was conducted in order to assess the uncertainties around results.

Results: From a total of 318 results, 17 studies were included in the final synthesis. These studies used various methodologies and input data, yet there is broad alignment on commodities, confirming that those included in due diligence legislation have a high deforestation risk. Soy, palm oil, and beef were identified as critical, with their production being concentrated in just a few global locations. However, there are also emerging commodities that have a high deforestation risk but are not included in legislation, such as sugar and coffee. These commodities are much less extensively studied in the literature and may warrant further research and consideration.

Conclusion: Policy recommendations in the selected studies suggests further strengthening of the UK due diligence legislation is needed. In particular, the provision of incentives for uptake of policies and wider stakeholder engagement, as well as continual review of commodities included to ensure a reduction in the UK's overseas deforestation footprint.

Industry 4.0 is a promising concept that allows industries to meet customers’ demands with flexible and resilient processes, and highly personalised products. This concept is made up of different dimensions. For a long time, innovative digital technology has been thought of as the only dimension to succeed in digital transformation projects. Other dimensions have been identified such as organisation, strategy, and human resources as key while rolling out digital technology in factories. From these findings, researchers have designed industry 4.0 theoretical models and then built readiness models that allow for analysing the gap between the company initial situation and the theoretical model. Nevertheless, this purely deductive approach does not take into consideration a company’s background and context, and eventually favours one single digital transformation model. This article aims at analysing four actual digital transformation projects and demonstrating that the digital transformation’s success or failure depends on the combination of two variables related to a company’s background and context. This research is based on a double approach: deductive and inductive. First, a literature review has been carried out to define industry 4.0 concept and its main dimensions and digital transformation success factors, as well as barriers, have been investigated. Second, a qualitative survey has been designed to study in-depth four actual industry digital transformation projects, their genesis as well as their execution, to analyse the key variables in succeeding or failing. 46 semi-structured interviews were carried out with projects’ members; interviews have been analysed with thematic content analysis. Then, each digital transformation project has been modelled regarding the key variables and analysed with regards to succeeding or failing. Investigated projects have consolidated the models of digital transformation. Finally, nine digital transformation types have been identified.

The purpose of this study is to review literature on the relationship between leadership and workplace learning, to critically analyze and discuss findings and to suggest future research paths based on the synthesis.

This study applied a refined literature review process leading to a selection of 40 articles, which originated from 14 internationally acclaimed journals.

When explaining leadership influence regarding individual and team learning, the concepts of role modeling behavior, relational support and negotiation of meaning is significant. If leaders provide support, show exemplary behavior and negotiate individual arrangements with employees, workplace learning development is positively affected.

Future studies should focus on empirical cases further illustrating how the leader–employee relationship is formed in practice, to further understand differences in leadership influence on employee workplace learning.

The gathered knowledge implicates that carefully designed leadership training programs and personalized work arrangements between leader and employees are beneficial for leader’s ability to influence employee workplace learning.

The reviewed studies were solely published in top management journals, which resulted in an original literature selection. This study also discusses implicit or articulated assumptions about the view of learning in the selected studies, offering additional understanding about the underlying learning views in leadership–workplace learning research.

The purpose of this study is to review evidence on the nature of effective leadership in interprofessional health and social care teams.

A critical review and thematic synthesis of research literature conducted using systematic methods to identify and construct a framework to explain the available evidence about leadership in interprofessional health and social care teams.

Twenty-eight papers were reviewed and contributed to the framework for interprofessional leadership. Twelve themes emerged from the literature, the themes were: facilitate shared leadership; transformation and change; personal qualities; goal alignment; creativity and innovation; communication; team-building; leadership clarity; direction setting; external liaison; skill mix and diversity; clinical and contextual expertise. The discussion includes some comparative analysis with theories and themes in team management and team leadership.

This research identifies some of the characteristics of effective leadership of interprofessional health and social care teams. By capturing and synthesising the literature, it is clear that effective interprofessional health and social care team leadership requires a unique blend of knowledge and skills that support innovation and improvement. Further research is required to deepen the understanding of the degree to which team leadership results in better outcomes for both patients and teams.

In order to mitigate the effects of climate change, the UK government has set a target of achieving net zero greenhouse gas (GHG) emissions by 2050. Agricultural GHG emissions in 2017 were 45.6 million tonnes of carbon dioxide equivalent (CO₂e; 10% of UK total GHG emissions). Farmland hedgerows are a carbon sink, storing carbon in the vegetation and soils beneath them, and thus increasing hedgerow length by 40% has been proposed in the UK to help meet net zero targets. However, the full impact of this expansion on farm biodiversity is yet to be evaluated in a net zero context. This paper critically synthesises the literature on the biodiversity implications of hedgerow planting and management on arable farms in the UK as a rapid review with policy recommendations. Eight peer-reviewed articles were reviewed, with the overall scientific evidence suggesting a positive influence of hedgerow management on farmland biodiversity, particularly coppicing and hedgelaying, although other boundary features, e.g. field margins and green lanes, may be additive to net zero hedgerow policy as they often supported higher abundances and richness of species. Only one paper found hedgerow age effects on biodiversity, with no significant effects found. Key policy implications are that further research is required, particularly on the effect of hedgerow age on biodiversity, as well as mammalian and avian responses to hedgerow planting and management, in order to fully evaluate hedgerow expansion impacts on biodiversity.

The purpose of this two-part study is to systematically review, analyze and critically synthesize the current state of empirical research on knowledge loss induced by organizational member turnover (KLT).

A systematic literature review was conducted based on 91 empirical studies on KLT.

Part I of the study contributes to the advancement of KLT scholarship by mapping key developments in empirical research on KLT (publication trends, methodological and theoretical foci, heterogeneity of geographical, industrial and organizational contexts); encapsulating KLT antecedents associated with both voluntary and involuntary turnover; and revealing a broad scope of KLT effects at organizational and unit level.

This study has limitations related to inclusion/exclusion criteria used for creating the review sample and the “Antecedents–Phenomenon–Outcomes” logic used to synthesize the findings.

Part I of the study offers a systematic synthesis of KLT empirical research with respect to KLT antecedents, outcomes and factors affecting them.

This paper aims to synthesize health-care leaders’ experiences of the competencies required for crisis management.

The systematic review followed the joanna briggs institute (JBI) guidance for systematic reviews of qualitative evidence. The search strategy included free text words and medical subject headings and peer-reviewed qualitative studies published in English, Finnish and Swedish and was not limited by year or country of publication. The databases searched in March 2022 were Scopus, PubMed, CINAHL, ABI/INFORM and the Finnish database Medic. Gray literature was searched using MedNar and EBSCO Open Dissertations. Studies were screened by title and abstract (n = 9,014) and full text (n = 43), and their quality was assessed by two independent reviewers. Eight studies were included. The data was analyzed using meta-aggregation.

Fifty-one findings (themes and subthemes) were extracted, and 11 categories were created based on their similarities. Five synthesized findings were developed: the competence to comprehend the operational environment; the competence to stay resilient amidst change; the competence to adapt to and manage change; the competence to manage and take care of staff; and the competence to co-operate and communicate with diverse stakeholders.

This systematic review produced novel information about health-care leaders’ experiences of the competencies required for crisis management during COVID-19. This study complements the field of research into crisis management in health care by introducing five original and unique competency clusters required for crisis management during the acute phase of COVID-19.

This review aimed to identify and map published studies on self-care practices to manage common acute health conditions in the Philippines.

The authors conducted a scoping review in PubMed, Scopus, Cumulative Index of Nursing and Allied Health Literature (CINAHL), ProQuest Central, Journal Storage (JSTOR) and the Philippine Council for Health Research and Development – Health Research and Development Information Network (HERDIN). The authors included all studies on self-care practices to manage common acute conditions, namely low back pain, allergic rhinitis, general acute pain, cough, cold, diarrhea, constipation and stress, published up to 2021 in the Philippines. Information on the article type, aim of the study, study design and setting, population characteristics and size, and self-practices employed for the conditions were extracted and synthesized.

The authors identified various self-care practices for acute conditions among the general population and indigenous peoples in the Philippines from 26 studies included in the review: the use of medicines with and without a prescription, appropriate and inappropriate antibiotic use, use of medicinal plants and other traditional and alternative therapies and products, recreational activities and healthy habits and behaviors, and self-management or seeking care from traditional healers (albularyo or manggagamot) or health professionals. A number of considerations influenced their decision on how to manage symptoms, including perceived severity of the condition, availability and perceived effectiveness of treatment, cost, and advice from trusted sources of health information.

The authors searched five major databases and a local research database, but some studies may still have been missed in the review. The review also excluded intervention studies on the outcomes of self-care, which limits the authors' ability to make conclusions on the effectiveness of the different modalities of self-care.

Filipinos engage in a variety of “safe” (or evidence-informed) and “unsafe” (or harmful) self-care practices. While the term “self-care” is not routinely used by the general population and health providers, it is widely enculturated and practiced in the Philippines. Self-care benefits individuals and the health system, but there are also practices that increase risk of adverse outcomes and death including inappropriate antibiotic use, prescription sharing and reuse, and delays in seeking adequate treatment from a health professional. To leverage on self-care in advancing Universal Health Coverage (UHC) goals, the authors recommend a national strategy that provides guidance on how to practice responsible self-care, further research on the effectiveness and safety of alternative medicine and other priority areas, and better integration of self-care in the formal education and health systems. The authors also propose that the research agenda on self-care include acute health conditions, given their impact and burden on health and the economy.

This is the first published review of self-care practices for managing common acute health conditions, which captured practices of various groups and populations including indigenous peoples.

With the progress of new technologies of information and communication, more and more producers of data exist. On the other hand, the web forms a huge support of all these kinds of data. Unfortunately, existing data is not proper due to the existence of the same information in different sources, as well as erroneous and incomplete data. The aim of data integration systems is to offer to a user a unique interface to query a number of sources. A key challenge of such systems is to deal with conflicting information from the same source or from different sources. We present, in this paper, the resolution of conflict at the instance level into two stages: references reconciliation and data fusion. The reference reconciliation methods seek to decide if two data descriptions are references to the same entity in reality. We define the principles of reconciliation method then we distinguish the methods of reference reconciliation, first on how to use the descriptions of references, then the way to acquire knowledge. We finish this section by discussing some current data reconciliation issues that are the subject of current research. Data fusion in turn, has the objective to merge duplicates into a single representation while resolving conflicts between the data. We define first the conflicts classification, the strategies for dealing with conflicts and the implementing conflict management strategies. We present then, the relational operators and data fusion techniques. Likewise, we finish this section by discussing some current data fusion issues that are the subject of current research.

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.