(A337) State Failure as a Factor in International Global Medical Operations: Network Modeling

IntroductionIn order to counteract disasters and emergencies, it is necessary to build cooperation and collaboration among all entities and actors. Field teams of rescuers require support from the State experiencing a disaster. The responses to the earthquake in Haiti demonstrated a lack of cooperation and collaboration and the rescuers encountered concomitant difficulties. Thus, the problems in the field are not only related to natural and technological aspects, but also social and political contexts. It is time to explore the role of the impact of State power on national and international disasters and emergencies. One modern and fruitful instrument for analysis of these complicated social and group processes is Complex Network modeling. Complex Network tools have been applied successfully to understanding and counteracting such threats as they relate to the spread of infectious diseases and/or to terrorist activities. Another significant utilization of the Complex Network approach is to develop good governance, management, and organizational processes in national and corporate landscapes.MethodsBased on a Complex Network Scope, a novel, three-layer network model of public connections for diverse State regimes for further simulation is proposed. Quantitative assessments and practical processes should be implemented for countering global disasters using international and interdisciplinary teams. Contrary to the known hierarchical layer approach for knowledge acquisition, this new model describes an overall national Society Network by dividing the approach into the three layers: (1) Formal (State), as hierarchical governments structures; (2) Informal (presented by different long-term sustainable link groups); and (3) Informal (aquatinters with short term links (“weak ties”).ResultsAccording to each of these layers, one of three types of network topologies exist: (1) hierarchical; (2) scale-free; and (3) random, respectively.

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Antitakeover Provisions and Shareholder Wealth: A Survey of the Literature

Journal of Financial and Quantitative Analysis ◽

10.1017/s0022109014000532 ◽

2014 ◽

Vol 49 (4) ◽

pp. 933-956 ◽

Cited By ~ 32

Author(s):

Miroslava Straska ◽

H. Gregory Waller

Keyword(s):

Good Governance ◽

Empirical Studies ◽

Shareholder Wealth ◽

Current Debate ◽

Firm Characteristics ◽

Policy Changes ◽

Governance Practices ◽

The Impact ◽

Long Term Studies

AbstractWe survey theoretical and empirical research on antitakeover provisions, focusing on the relation between antitakeover provisions and shareholder value. We divide the empirical studies based upon the evidence that they provide: short-term event studies, studies on performance and policy changes around adopting antitakeover provisions or passing state antitakeover laws, studies on the impact of antitakeover provisions on takeovers, studies on the relation between antitakeover provisions and firm characteristics, and long-term studies on the relation between antitakeover provisions and firm performance or policies. We also discuss the place of antitakeover provisions in the current debate about “good governance” practices.

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Dual-class firms and governance: an acquisition perspective

Managerial Finance ◽

10.1108/mf-05-2014-0141 ◽

2015 ◽

Vol 41 (11) ◽

pp. 1221-1235 ◽

Cited By ~ 6

Author(s):

Ashrafee Tanvir Hossain

Keyword(s):

Good Governance ◽

Positive Impact ◽

Content Type ◽

Corporate Takeovers ◽

Governance Quality ◽

Return On Sales ◽

Dual Class ◽

Term Performance ◽

The Impact

Purpose – The purpose of this paper is to examine the impact of governance quality on firms with multiple voting structures. Design/methodology/approach – The sample includes 487 acquisitions undertaken by dual-class firms from 1996 to 2009. The author used event studies (Patell, 1976) for short-term performance analysis around merger announcement dates; Berkovitch and Narayanan (1993) methods to identify the motive behind these transactions; and standard benchmark adjusted return on assets (and return on sales) (Barber and Lyon, 1996) and BHAR (Mitchell and Stafford, 2000) to analyze long-term post-acquisition performance. Findings – First, dual-class acquirers with better governance quality show stronger performance around takeovers which indicates that these firms make better acquisition decisions. These results hold even after controlling for different firm and deal characteristics. Second, transactions undertaken by acquirers with good governance show little or no sign of agency motive. This reinforces the findings in first. Third, the author reports that acquirers with above-median governance quality display stronger long-term post-acquisition operating as well as stock performances. These results are robust to different benchmarks used for this study. Originality/value – This paper expands the literature on dual-class firms by showing the impact of governance quality on acquisition activities undertaken by these firms. This is the first study to show that despite agency issues inherent in the dual-class structure, improving governance quality would have a positive impact, at least in the case of corporate takeovers.

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Vaccination strategies against COVID-19 and the diffusion of anti-vaccination views

Scientific Reports ◽

10.1038/s41598-021-85555-1 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Rafael Prieto Curiel ◽

Humberto González Ramírez

Keyword(s):

Diffusion Model ◽

Large Population ◽

Vaccination Strategy ◽

Small World ◽

Years Of Life Lost ◽

Scale Free ◽

Vaccination Strategies ◽

Network Topologies ◽

Network Disruptions ◽

The Impact

AbstractMisinformation is usually adjusted to fit distinct narratives and propagates rapidly through social networks. False beliefs, once adopted, are rarely corrected. Amidst the COVID-19 crisis, pandemic-deniers and people who oppose wearing face masks or quarantine have already been a substantial aspect of the development of the pandemic. With the vaccine for COVID-19, different anti-vaccine narratives are being created and are probably being adopted by large population groups with critical consequences. Assuming full adherence to vaccine administration, we use a diffusion model to analyse epidemic spreading and the impact of different vaccination strategies, measured with the average years of life lost, in three network topologies (a proximity, a scale-free and a small-world network). Then, using a similar diffusion model, we consider the spread of anti-vaccine views in the network, which are adopted based on a persuasiveness parameter of anti-vaccine views. Results show that even if anti-vaccine narratives have a small persuasiveness, a large part of the population will be rapidly exposed to them. Assuming that all individuals are equally likely to adopt anti-vaccine views after being exposed, more central nodes in the network, which are more exposed to these views, are more likely to adopt them. Comparing years of life lost, anti-vaccine views could have a significant cost not only on those who share them, since the core social benefits of a limited vaccination strategy (reduction of susceptible hosts, network disruptions and slowing the spread of the disease) are substantially shortened.

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CONGESTION AND EFFICIENCY IN COMPLEX TRAFFIC NETWORKS

International Journal of Modern Physics C ◽

10.1142/s0129183113500721 ◽

2013 ◽

Vol 24 (10) ◽

pp. 1350072 ◽

Cited By ~ 4

Author(s):

JIAN-FENG ZHENG ◽

ZHI-HONG ZHU ◽

HAO-MING DU ◽

ZI-YOU GAO

Keyword(s):

Complex Networks ◽

Small World ◽

Traffic Networks ◽

Flow State ◽

Traffic Demand ◽

Scale Free ◽

Link Cost ◽

Network Topologies ◽

The Impact ◽

The Relationship

This paper investigates the degree of congestion and efficiency in complex traffic networks, by introducing congestion effects, which can be described by flow-based link cost functions. Different network topologies including random networks, small-world networks and scale-free networks are explored. The impact of different distributions of capacity and origin-destination traffic demand on the degree of congestion and efficiency in complex networks is mainly studied. A phase transition from free flow state to traffic jams can be uncovered. The relationship between congestion and efficiency in complex networks is also discussed.

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Ripple-Spreading Network Model Optimization by Genetic Algorithm

Mathematical Problems in Engineering ◽

10.1155/2013/176206 ◽

2013 ◽

Vol 2013 ◽

pp. 1-15 ◽

Cited By ~ 2

Author(s):

Xiao-Bing Hu ◽

Ming Wang ◽

Mark S. Leeson

Keyword(s):

Genetic Algorithm ◽

Complex Network ◽

Network Model ◽

Real World ◽

Network Models ◽

Small World ◽

Network Systems ◽

Scale Free ◽

Apply Genetic ◽

Network Topologies

Small-world and scale-free properties are widely acknowledged in many real-world complex network systems, and many network models have been developed to capture these network properties. The ripple-spreading network model (RSNM) is a newly reported complex network model, which is inspired by the natural ripple-spreading phenomenon on clam water surface. The RSNM exhibits good potential for describing both spatial and temporal features in the development of many real-world networks where the influence of a few local events spreads out through nodes and then largely determines the final network topology. However, the relationships between ripple-spreading related parameters (RSRPs) of RSNM and small-world and scale-free topologies are not as obvious or straightforward as in many other network models. This paper attempts to apply genetic algorithm (GA) to tune the values of RSRPs, so that the RSNM may generate these two most important network topologies. The study demonstrates that, once RSRPs are properly tuned by GA, the RSNM is capable of generating both network topologies and therefore has a great flexibility to study many real-world complex network systems.

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Suppressed, but Not Forgotten

Swiss Journal of Psychology ◽

10.1024/1421-0185/a000033 ◽

2011 ◽

Vol 70 (1) ◽

pp. 5-11 ◽

Cited By ~ 8

Author(s):

Beat Meier ◽

Anja König ◽

Samuel Parak ◽

Katharina Henke

Keyword(s):

Memory Trace ◽

Thought Suppression ◽

Test Phase ◽

Indirect Test ◽

Final Test ◽

Test Experiment ◽

And Control ◽

Cue Words ◽

The Impact

This study investigates the impact of thought suppression over a 1-week interval. In two experiments with 80 university students each, we used the think/no-think paradigm in which participants initially learn a list of word pairs (cue-target associations). Then they were presented with some of the cue words again and should either respond with the target word or avoid thinking about it. In the final test phase, their memory for the initially learned cue-target pairs was tested. In Experiment 1, type of memory test was manipulated (i.e., direct vs. indirect). In Experiment 2, type of no-think instructions was manipulated (i.e., suppress vs. substitute). Overall, our results showed poorer memory for no-think and control items compared to think items across all experiments and conditions. Critically, however, more no-think than control items were remembered after the 1-week interval in the direct, but not in the indirect test (Experiment 1) and with thought suppression, but not thought substitution instructions (Experiment 2). We suggest that during thought suppression a brief reactivation of the learned association may lead to reconsolidation of the memory trace and hence to better retrieval of suppressed than control items in the long term.

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