scholarly journals Local interactions and homophily effects in actor collaboration networks for urban resilience governance

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Qingchun Li ◽  
Ali Mostafavi
Keyword(s):  
Network Formation ◽  
Urban Systems ◽  
Collaboration Network ◽  
Bipartite Network ◽  
Network Motifs ◽  
Collaboration Networks ◽  
Local Interactions ◽  
Infrastructure Systems ◽  
Planning And Management ◽  
Interdependent Infrastructure

AbstractUnderstanding actor collaboration networks and their evolution is essential to promoting collective action in resilience planning and management of interdependent infrastructure systems. Local interactions and choice homophily are two important network evolution mechanisms. Network motifs encode the information of network formation, configuration, and the local structure. Homophily effects, on the other hand, capture whether the network configurations have significant correlations with node properties. The objective of this paper is to explore the extent to which local interactions and homophily effects influence actor collaboration in resilience planning and management of interdependent infrastructure systems. We mapped bipartite actor collaboration network based on a post-Hurricane Harvey stakeholder survey that revealed actor collaborations for hazard mitigation. We examined seven bipartite network motifs for the mapped collaboration network and compared the mapped network to simulated random models with same degree distributions. Then we examined whether the network configurations had significant statistics for node properties using exponential random graph models. The results provide insights about the two mechanisms—local interactions and homophily effect—influencing the formation of actor collaboration in resilience planning and management of interdependent urban systems. The findings have implications for improving network cohesion and actor collaborations from diverse urban sectors.

Risk Adjusting Health Care Provider Collaboration Networks

2019 ◽  
Vol 58 (02/03) ◽  
pp. 071-078
Author(s):  
Ariel E. Chandler ◽  
R. Kannan Mutharasan ◽  
Lia Amelia ◽  
Matthew B. Carson ◽  
Denise M. Scholtens ◽  
...  
Keyword(s):  
Health Care ◽  
Health Care Providers ◽  
Collaboration Network ◽  
Bipartite Network ◽  
Collaboration Networks ◽  
Care Providers ◽  
Readmission Rates ◽  
Patient Factors ◽  
Adjusted Model ◽  
The Impact

Abstract Objectives The quality of hospital discharge care and patient factors (health and sociodemographic) impact the rates of unplanned readmissions. This study aims to measure the effects of controlling for the patient factors when using readmission rates to quantify the weighted edges between health care providers in a collaboration network. This improved understanding may inform strategies to reduce hospital readmissions, and facilitate quality-improvement initiatives. Methods We extracted 4 years of patient, provider, and activity data related to cardiology discharge workflow. A Weibull model was developed to predict the risk of unplanned 30-day readmission. A provider–patient bipartite network was used to connect providers by shared patient encounters. We built collaboration networks and calculated the Shared Positive Outcome Ratio (SPOR) to quantify the relationship between providers by the relative rate of patient outcomes, using both risk-adjusted readmission rates and unadjusted readmission rates. The effect of risk adjustment on the calculation of the SPOR metric was quantified using a permutation test and descriptive statistics. Results Comparing the collaboration networks consisting of 2,359 provider pairs, we found that SPOR values with risk-adjusted outcomes are significantly different than unadjusted readmission as an outcome measure (p-value = 0.025). The two networks classified the same provider pairs as high-scoring 51.5% of the time, and the same low scoring provider pairs 85.6% of the time. The observed differences in patient demographics and disease characteristics between high-scoring and low-scoring provider pairs were reduced by applying the risk-adjusted model. The risk-adjusted model reduced the average variation across each individual's SPOR scored provider connections. Conclusions Risk adjusting unplanned readmission in a collaboration network has an effect on SPOR-weighted edges, especially on classifying high-scoring SPOR provider pairs. The risk-adjusted model reduces the variance of providers' connections and balances shared patient characteristics between low- and high-scoring provider pairs. This indicates that the risk-adjusted SPOR edges better measure the impact of collaboration on readmissions by accounting for patients' risk of readmission.

Institutional Connectedness in Resilience Planning and Management of Interdependent Infrastructure Systems

2020 ◽  
Vol 36 (6) ◽  
pp. 04020075 ◽  
Author(s):  
Shangjia Dong ◽  
Qingchun Li ◽  
Hamed Farahmand ◽  
Ali Mostafavi ◽  
Philip R. Berke ◽  
...  
Keyword(s):  
Infrastructure Systems ◽  
Planning And Management ◽  
Interdependent Infrastructure

scholarly journals Power Quality: Scientific Collaboration Networks and Research Trends

Energies ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 2067 ◽  
Author(s):  
Francisco Montoya ◽  
Raul Baños ◽  
Alfredo Alcayde ◽  
Maria Montoya ◽  
Francisco Manzano-Agugliaro
Keyword(s):  
Power Quality ◽  
Scientific Collaboration ◽  
Research Field ◽  
Research Trends ◽  
Collaboration Network ◽  
Collaboration Networks ◽  
Different Types ◽  
Voltage Frequency ◽  
Advanced Model ◽  
Proper Operation

Power quality is a research field related to the proper operation of devices and technological equipment in industry, service, and domestic activities. The level of power quality is determined by variations in voltage, frequency, and waveforms with respect to reference values. These variations correspond to different types of disturbances, including power fluctuations, interruptions, and transients. Several studies have been focused on analysing power quality issues. However, there is a lack of studies on the analysis of both the trending topics and the scientific collaboration network underlying the field of power quality. To address these aspects, an advanced model is used to retrieve data from publications related to power quality and analyse this information using a graph visualisation software and statistical tools. The results suggest that research interests are mainly focused on the analysis of power quality problems and mitigation techniques. Furthermore, they are observed important collaboration networks between researchers within and across countries.

Infrastructure Decay Modeling With the Input-Output Inoperability Model

2015 ◽  
Vol 1 (1) ◽  
Author(s):  
Vhance V. Valencia ◽  
Alfred E. Thal ◽  
John M. Colombi ◽  
William E. Sitzabee
Keyword(s):  
Asset Management ◽  
Input Output ◽  
Infrastructure Systems ◽  
Cascading Effects ◽  
Multiple Networks ◽  
Infrastructure Network ◽  
Asset Managers ◽  
Infrastructure Interdependency ◽  
Interdependent Infrastructure

Asset management and infrastructure interdependency concepts are found to be useful in the study of infrastructure decay. As such, infrastructure decay is modeled with the input-output inoperability model (IIM), which is a method of analysis that captures cascading effects of a disturbance in interdependent infrastructure systems. This paper presents an extension to the IIM that simplifies the construction of the interdependency matrix central to the model and integrates the use of component decay curves for each component in the system. The revised model results in the ability of infrastructure asset managers to recognize the effect of decay across an entire infrastructure network or multiple networks.

A Comparison between International Trade and R&D Collaboration Networks in the European Aerospace Sector

2016 ◽  
pp. 141-171
Author(s):  
Pier Paolo Angelini ◽  
Lucio Biggiero
Keyword(s):  
International Trade ◽  
Wide Spectrum ◽  
Collaboration Network ◽  
Final Conclusion ◽  
Collaboration Networks ◽  
Aerospace Sector ◽  
Problems And Solutions ◽  
Methodological Problems ◽  
The Common ◽  
International Trade Network

Do trading countries also collaborate in R&D? This is the question that, facing with a number of methodological problems, here it is dealt with. Studying and comparing the international trade network and the R&D collaboration network of European countries in the aerospace sector, social network analysis offers a wide spectrum of methods and criteria either to make them comparable or to evaluate its similarity. International trade is a 1-mode directed and valued network, while the EU-subsidized R&D collaboration is an affiliation (2-mode) undirected and unvalued network, and the elementary units of this latter are organizations and not countries. Therefore, to the aim to make these two networks comparable, this paper shows and discusses a number of methodological problems and solutions offered to solve them, and provides a multi-faceted comparison in terms of various statistical and topological indicators. A comparative analysis of the two networks structures is made at aggregate and disaggregate level, and it is shown that the common centralization index is definitively inappropriate and misleading when applied to multi-centered networks like these, and especially to the R&D collaboration network. The final conclusion is that the two networks resemble in some important aspects, but differ in some minor traits. In particular, they are both shaped in a core-periphery structure, and in both cases important countries tend to exchange or collaborate more with marginal countries than between themselves.

Management Education Collaboration Networks

2014 ◽  
Vol 4 (4) ◽  
pp. 1-16 ◽  
Author(s):  
Owen P. Hall ◽  
Kenneth D. Ko
Keyword(s):  
Performance Management ◽  
Business Education ◽  
Management Education ◽  
Implementation Strategies ◽  
Learning Technologies ◽  
Collaboration Network ◽  
Collaboration Networks ◽  
Curriculum Innovation ◽  
Educational Approach ◽  
And Performance

Management education has come a long way since Sir Isaac Pitman initiated the first correspondence course in the early 1840s. Today the demands from a globalized economy are causing a sea change in the way business education is being delivered. The traditional one-size-fits-all educational approach of the past is being replaced with a customized and flexible learning paradigm that focuses on student outcomes and performance. Management education collaboration networks can assist in this transformation. A primary function of a collaboration network is to provide the management education community with access to curriculum innovation, databases, cloud computing resources, mobile learning technologies and implementation strategies. The network design should be based on stakeholder attitudes, new learning technologies, globalization, changing demographics and sustainability. The purpose of this article is to highlight the results of a global survey on collaboration networks and to outline the role of cloud-based collaboration in the future of business education.

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