A case study on graphically modelling and detecting knowledge mobility risks

As the world continues to increasingly depend on a knowledge economy, companies are realising that their most valuable asset is knowledge held by their employees. This asset is hard to track, manage and retain especially in a situation where employees are free to job-hop for better pay after providing a few weeks’ notice to their employers. In previous work we have defined the concept of knowledge risk, and presented a graph-based approach for detecting it. In this paper, we present the results of a case study which employs knowledge graphs in the context of four software development teams.peer-reviewe

A Case Study on Graphically Modelling and Detecting Knowledge Mobility Risks

As the world continues to increasingly depend on a knowledge economy, companies are realising that their most valuable asset is knowledge held by their employees. This asset is hard to track, manage and retain especially in a situation where employees are free to job-hop for better pay after providing a few weeks’ notice to their employers. In previous work we have defined the concept of knowledge risk, and presented a graph-based approach for detecting it. In this paper, we present the results of a case study which employs knowledge graphs in the context of four software development teams

Change in outbreak epicentre and its impact on the importation risks of COVID-19 progression: A modelling study

Background The outbreak of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) that was first detected in the city of Wuhan, China has now spread to every inhabitable continent, but now the attention has shifted from China to other epicentres. This study explored early assessment of the influence of spatial proximities and travel patterns from Italy on the further spread of SARS-CoV-2 worldwide. Methods Using data on the number of confirmed cases of COVID-19 and air travel data between countries, we applied a stochastic meta-population model to estimate the global spread of COVID-19. Pearson's correlation, semi-variogram, and Moran's Index were used to examine the association and spatial autocorrelation between the number of COVID-19 cases and travel influx (and arrival time) from the source country. Results We found significant negative association between disease arrival time and number of cases imported from Italy (r = −0.43, p = 0.004) and significant positive association between the number of COVID-19 cases and daily travel influx from Italy (r = 0.39, p = 0.011). Using bivariate Moran's Index analysis, we found evidence of spatial interaction between COVID-19 cases and travel influx (Moran's I = 0.340). Asia-Pacific region is at higher/extreme risk of disease importation from the Chinese epicentre, whereas the rest of Europe, South-America and Africa are more at risk from the Italian epicentre. Conclusion We showed that as the epicentre changes, the dynamics of SARS-CoV-2 spread change to reflect spatial proximities

A content and comparative analysis of strategic management research in the Baltic area

Purpose – The purpose of this paper is to provide a research agenda for qualitative studies in the field of strategic management (SM) in the Baltic area. Design/methodology/approach – A total of 167 SM-related articles in this area between 2000 and 2013 were found. The content within title, abstract and authors’ keywords was analysed by means of a multiple correspondence analysis based on the HOMALS technique. Findings – The intellectual structure of SM in the Baltic area is to some extent similar to the global structure of the field. Hence research on this topic in the Baltic area is well integrated in the field. Three topics of interest have been identified while the fourth seems to offer more limited opportunities for qualitative studies. These are: entry and competition; strategic behaviour and the micro-foundations of strategy; the growth-performance relationship; and global strategies. Research limitations/implications – Despite the modest number of articles in our sample, the findings are consistent with past research on the structure of the SM field. The classification of articles into qualitative- and quantitative-based methods helped provide a research agenda. Practical implications – SM scholars in the Baltic area may find this paper as an interesting input to their quest for finding and justifying their own research path. Originality/value – This is an original literature review. The use of a quantitative method in the literature review and the suggested matrix is a second original contribution to evolving methodologies for content analysis. The method allows the inclusion of large samples while limiting the use of scholars’ intuition. </jats:sec

Improved dredge material management for the Great Barrier Reef Region: Synthesis report

The Department of Sustainability, Environment, Water, Population and Communities and the Great Barrier Reef Marine Park Authority commissioned Sinclair Knight Merz Pty Ltd and Asia-Pacific Applied Science Associates to undertake a study on Improved Dredge Material Management for the Great Barrier Reef Region. The study provides analysis and information to inform future dredge material management for the five major ports (Ports of Cairns, Townsville, Gladstone, Abbot Point, Hay Point) and one marina (Rosslyn Bay) in the Great Barrier Reef World Heritage Area. The study examines differences in sediment migration patterns from placing dredge material at hypothetical alternative and currently used placement sites. It is the first study to both incorporate the effects of regional oceanic currents in modelling dredge material migration and model dredge material migration over a period of 12 months, providing insight into the behaviour and potential risks of dredge material over time. The information generated by this study is high level and is not intended to replace the detail required as part of an environmental impact assessment process for any future dredge material placement operations

Mapping the Evolution of "Clusters": A Meta-analysis

This paper presents a meta-analysis of the “cluster literature” contained in scientific journals from 1969 to 2007. Thanks to an original database we study the evolution of a stream of literature which focuses on a research object which is both a theoretical puzzle and an empirical widespread evidence. We identify different growth stages, from take-off to development and maturity. We test the existence of a life-cycle within the authorships and we discover the existence of a substitutability relation between different collaborative behaviours. We study the relationships between a “spatial” and an “industrial” approach within the textual corpus of cluster literature and we show the existence of a “predatory” interaction. We detect the relevance of clustering behaviours in the location of authors working on clusters and in measuring the influence of geographical distance in co-authorship. We measure the extent of a convergence process of the vocabulary of scientists working on clusters.Cluster, Life-Cycle, Cluster Literature, Textual Analysis, Agglomeration, Co-Authorship

Cyber resilience meta-modelling: The railway communication case study

Recent times have demonstrated how much the modern critical infrastructures (e.g., energy, essential services, people and goods transportation) depend from the global communication networks. However, in the current Cyber-Physical World convergence, sophisticated attacks to the cyber layer can provoke severe damages to both physical structures and the operations of infrastructure affecting not only its functionality and safety, but also triggering cascade effects in other systems because of the tight interdependence of the systems that characterises the modern society. Hence, critical infrastructure must integrate the current cyber-security approach based on risk avoidance with a broader perspective provided by the emerging cyber-resilience paradigm. Cyber resilience is aimed as a way absorb the consequences of these attacks and to recover the functionality quickly and safely through adaptation. Several high-level frameworks and conceptualisations have been proposed but a formal definition capable of translating cyber resilience into an operational tool for decision makers considering all aspects of such a multifaceted concept is still missing. To this end, the present paper aims at providing an operational formalisation for cyber resilience starting from the Cyber Resilience Ontology presented in a previous work using model-driven principles. A domain model is defined to cope with the different aspects and “resilience-assurance” processes that it can be valid in various application domains. In this respect, an application case based on critical transportation communications systems, namely the railway communication system, is provided to prove the feasibility of the proposed approach and to identify future improvements

A systematic review of the data, methods and environmental covariates used to map Aedes-borne arbovirus transmission risk

BACKGROUND: Aedes (Stegomyia)-borne diseases are an expanding global threat, but gaps in surveillance make comprehensive and comparable risk assessments challenging. Geostatistical models combine data from multiple locations and use links with environmental and socioeconomic factors to make predictive risk maps. Here we systematically review past approaches to map risk for different Aedes-borne arboviruses from local to global scales, identifying differences and similarities in the data types, covariates, and modelling approaches used. METHODS: We searched on-line databases for predictive risk mapping studies for dengue, Zika, chikungunya, and yellow fever with no geographical or date restrictions. We included studies that needed to parameterise or fit their model to real-world epidemiological data and make predictions to new spatial locations of some measure of population-level risk of viral transmission (e.g. incidence, occurrence, suitability, etc.). RESULTS: We found a growing number of arbovirus risk mapping studies across all endemic regions and arboviral diseases, with a total of 176 papers published 2002-2022 with the largest increases shortly following major epidemics. Three dominant use cases emerged: (i) global maps to identify limits of transmission, estimate burden and assess impacts of future global change, (ii) regional models used to predict the spread of major epidemics between countries and (iii) national and sub-national models that use local datasets to better understand transmission dynamics to improve outbreak detection and response. Temperature and rainfall were the most popular choice of covariates (included in 50% and 40% of studies respectively) but variables such as human mobility are increasingly being included. Surprisingly, few studies (22%, 31/144) robustly tested combinations of covariates from different domains (e.g. climatic, sociodemographic, ecological, etc.) and only 49% of studies assessed predictive performance via out-of-sample validation procedures. CONCLUSIONS: Here we show that approaches to map risk for different arboviruses have diversified in response to changing use cases, epidemiology and data availability. We identify key differences in mapping approaches between different arboviral diseases, discuss future research needs and outline specific recommendations for future arbovirus mapping