This study explores the evolution of institutional collaborations in articles published in the
Strategic Management Journal
between 1980 and 2014 via descriptive analysis and social network analysis. ...These analyses show that, in each sub-period, the number of institutions involved, as measured by papers published, increased significantly and a significant number of new institutions participated in the strategic management community via the
SMJ
. However, a few institutions from the US dominated the field. The collaboration network was weakly clustered, fragmented, and scattered, and the relationship among institutions was not close. International collaborations have been growing based on center-periphery, international trade, and social factors, instead of geographic proximity. An inclusive evaluation of the results, limitations, and suggestions for future research is provided.
Quantifying the dynamical linkage, co‐evolution, and propagation of regional heatwaves is essential to minimize socio‐economic losses. Here, we investigate such network structure and propagation ...characteristics for warm period (May–September) heatwaves over Conterminous United States using a complex network approach based on daily maximum temperature. The concept of Event Synchronization (ES) is applied to identify the source and sink regions primarily responsible for heatwave propagations and the strength of association between these regions. The network coefficients are derived to evaluate the extremal dependence, co‐evolution, and spatial propagation of large scale heatwavc events. The topology and propagation of heatwaves are influenced by the spatial distribution of the zonal and meridional air mass transport. Furthermore, we demonstrated the application of ES metrics and the network coefficients for heatwave days prediction between source and sink regions with true positive rate of 63% at a lead time of 2 days.
Plain Language Summary
The large scale heatwave events have become very common over the Conterminous United States. The examples include heatwave events in Chicago and the Gulf coastal plains (2019 and 2020) and the recent ongoing extreme heat event in California (August 2020). The United States incurs significant socio‐economic losses and health problems due to exposure to heatwaves. Under climate change, such heatwaves are likely to increase in different parts of the world, leading to increased socio‐economic impacts. We apply complex network analysis to understand the USA heatwaves’ regional connectivity and the underlying physical mechanisms. The derived information is essential in the forecasting of heatwaves.
Key Points
Dominant air mass transport and topographic characteristics influence the synchronization structure and propagation patterns of heatwaves
Event Synchronization metrics can identify the source and sink regions primarily responsible for heatwave propagations
Network coefficients able to capture the spatial dependency between warm‐period heatwave events occurring at different locations
A NETWORK ANALYSIS OF TOURISM RESEARCH Benckendorff, Pierre; Zehrer, Anita
Annals of tourism research,
October 2013, 2013-10-00, Letnik:
43
Journal Article
Recenzirano
•Identifies classic scholars and works influencing tourism research over 15years.•Uses co-citation analysis to explore relationships between scholars and works.•Presents networks of influential ...scholars and works.•Identifies disciplinary clusters and interdisciplinary contributions.•Reveals networks, tribes and territories in tourism research.
This paper uses network analysis to identify the pioneering scholars and seminal works which have influenced recent papers in leading journals. The analysis extends beyond rankings of scholars by using co-citation networks to visualize the relationships between the most influential scholars and works and to uncover the disciplinary contributions which have supported the emergence of tourism as a field of academic study. The networks of scholars and works illuminate invisible colleges, tribes and territories in tourism research and indicate that while the social sciences have been most influential, business-related citations are increasing. The findings contribute to the discourse about the epistemology of tourism research by using bibliometric techniques to offer insights into the interdisciplinary structure of tourism research.
Recently, the role of personal ties in migration decisions has received considerable attention. However, this aspect has seldom been studied in the context of retirement. This paper addresses this ...gap by shedding light on the composition of personal networks, types of mobility patterns and retirement locations for four groups of older adults. To this end, two methodological approaches are employed: (1) a qualitative Social Network Analysis to examine the composition of older adults' personal networks and (2) thematic coding to analyse the relational aspects of migration decisions. This paper draws on 29 semi‐structured interviews conducted in Spain and Switzerland in 2020 and 2021. The findings demonstrate that pre‐retirement migration trajectories shape personal network composition. Moreover, personal ties play a critical role in older adults' mobility patterns and choices of retirement location. Overall, this study provides valuable insights into the impact of personal networks on migration decisions of older adults.
Community detection is a central problem of network data analysis. Given a network, the goal of community detection is to partition the network nodes into a small number of clusters, which could ...often help reveal interesting structures. The present paper studies community detection in Degree-Corrected Block Models (DCBMs). We first derive asymptotic minimax risks of the problem for a misclassification proportion loss under appropriate conditions. The minimax risks are shown to depend on degree-correction parameters, community sizes and average within and between community connectivities in an intuitive and interpretable way. In addition, we propose a polynomial time algorithm to adaptively perform consistent and even asymptotically optimal community detection in DCBMs.
The objective of this paper is to depict a landscape of the scientific literature on the concept of the 'Smart Factory', which in recent years is gaining more and more attention from academics and ...practitioners because of significant innovations in the production systems within the manufacturing sector. To achieve this objective, a dynamic methodology called 'Systematic Literature Network Analysis (SLNA)' has been applied. This methodology combines the Systematic Literature Review approach with the analysis of bibliographic networks. The adopted methodology allows complementing traditional content-based literature reviews by extracting quantitative information from bibliographic networks to detect emerging topics, and by revealing the dynamic evolution of the scientific production of a discipline. This dynamic analysis allowed highlighting research directions and critical areas for the development of the 'Smart Factory'. At the same time, it offers insights on the fields on which companies, associations, politicians and technology providers need to focus in order to allow a real transition towards the implementation of large-scale Smart Factory.
•Loneliness, sadness, self-hatred fatigue, self-deprecation and crying most central symptoms in depression network.•Loneliness most contributing factor to suicide ideation.•Suicide ideation seems ...indicative of depression symptom severity during adolescence.
According to the network perspective, psychopathology is the result of interactions between symptoms. A previous study used network analysis to identify central symptoms of adolescent depression. The aim of the current study was replicate and extend this study by including suicide ideation as a symptom of depression and evaluating which depression symptoms are contributing factors to suicide ideation in adolescents.
A large community sample (N = 5,888) of adolescents aged 11–16 years completed the Children's Depression Inventory (CDI-2). Network analysis was used to identify the network structure of the CDI-2 and which symptoms were directly related to suicide ideation in the network. Additionally, the network structure of adolescents who did and did not experience suicide ideation were compared.
Results pertaining the depression network were highly similar to the study we aimed to replicate. The most central symptoms in the depression network were loneliness, sadness, self-hatred, fatigue, self-deprecation and crying. Loneliness explained most variance of suicide ideation. Adolescents who experience suicide ideation had a similar network structure as those who do not. Adolescents with suicide ideation scored higher on all depression symptoms.
The use of cross-sectional data indicates that only undirected networks and results based on between-subject data could be estimated.
Loneliness was a central factor for depression networks and also the most contributing factor of suicide ideation. Preventative efforts should consider taking experiences of loneliness into account as these are especially prevalent in adolescents. Suicide ideation seems more representative of depression symptom severity in adolescents.
We study how to assess the potential benefit of diversifying an equity portfolio by investing within and across equity sectors. We analyse 20 years of US stock price data, which includes the global ...financial crisis (GFC) and the COVID-19 market crash, as well as periods of financial stability, to determine the ‘all weather’ nature of equity portfolios. We establish that one may use the leading eigenvalue of the cross-correlation matrix of log returns as well as graph-theoretic diagnostics such as modularity to quantify the collective behaviour of the market or a subset of it. We confirm that financial crises are characterised by a high degree of collective behaviour of equities, whereas periods of financial stability exhibit less collective behaviour. We argue that during times of increased collective behaviour, risk reduction via sector-based portfolio diversification is ineffective. Using the degree of collectivity as a proxy for the benefit of diversification, we perform an extensive sampling of equity portfolios to confirm the old financial adage that 30–40 stocks provide sufficient diversification. Using hierarchical clustering, we discover a ‘best value’ equity portfolio for diversification consisting of 36 equities sampled uniformly from 9 sectors. We further show that it is typically more beneficial to diversify across sectors rather than within. Our findings have implications for cost-conscious retail investors seeking broad diversification across equity markets.
•We analyse 20 years of US daily stock price data.•PCA and graph theoretic diagnostics quantify the degree of financial market collectivity.•A new sampling procedure compares diversification within and across equity sectors.•A best-value portfolio consisting of 36 equities from 9 sectors is found.•Our portfolio diversification findings may provide cheap diversification for retail investors.
Heavy metal pollution in soil around abandoned mine sites is one of the most critical environmental issues worldwide. Soil microbes form complex communities and perform ecological functions ...individually or in cooperation with other organisms to adapt to harsh environments. In this study, we investigated the distribution patterns of bacterial and fungal communities in non-contaminated and heavy metal-contaminated soil of the abandoned Samkwang mine in Korea to explore microbial interaction mechanisms and their modular structures. As expected, the bacterial and fungal community structures showed large differences depending on the degree of heavy metal contamination. The microbial network was divided into three modules based on the levels of heavy metal pollution: heavy metal-tolerant (HM-Tol), heavy metal-mid-tolerant (HM-mTol), and heavy metal-sensitive (HM-Sens) modules. Taxonomically, microbes assigned to Vicinamibacterales, Pedosphaeraceae, Nitrosomonadaceae, and Gemmatimonadales were the major groups constituting the HM-Tol module. Among the detected heavy metals (As, Pb, Cd, Cu, and Zn), copper concentrations played a key role in the formation of the HM-Tol module. In addition, filamentous fungi (Fusarium and Mortierella) showed potential interactions with bacteria (Nitrosomonadaceae) that could contribute to module stability in heavy metal-contaminated areas. Overall, heavy metal contamination was accompanied by distinct microbial communities, which could participate in the bioremediation of heavy metals. Analysis of the microbial interactions among bacteria and fungi in the presence of heavy metals could provide fundamental information for developing bioremediation mechanisms for the recovery of heavy metal-contaminated soil.
Display omitted
•Heavy metals (HMs) alter the composition and structure of microbial community.•Distinct modular units based on the levels of heavy metal pollution were obtained.•Copper plays a key role in the formation of the HM-tolerant module.•Fusarium and Mortierella showed interactions with bacteria in soil.
Foreign-born scholars can accumulate and/or utilise their intellectual capital (IC) through intellectual migration. IC is a combination of transferrable human, cultural, and social capital. While IC ...has been conceptualised, no known studies have measured it. As foreign-born scholars often develop academic networks that transcend geographical and ethnic boundaries, their IC should not be simplified as a single scale. Adopting the ego-centric network analysis method, this study proposes an approach to quantify foreign-born scholars' IC based on their co-author network. This approach includes a group of measures to capture IC within and between different geographic and ethnic contexts. Based on the co-authorship data collected among China-born scholars at a public research university in the U.S., this study examines how their IC levels evolve over time, differ between younger- and older-generation scholars, and whether they are influenced by where one receives a PhD degree.
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