Travelers’ Risk-Taking Behaviors in Day-to-Day Dynamic Evolution Model

2016 ◽  
Vol 2565 (1) ◽  
pp. 27-36 ◽  
Author(s):  
Xiaoming Lou ◽  
Lin Cheng
Keyword(s):  
Risk Taking ◽  
Evolution Model ◽  
Dynamic Evolution ◽  
Risk Taking Behaviors

Risk-Taking Behaviors in Adolescents

1999 ◽  
Author(s):  
Kristin M. von Ranson ◽  
Susan L. Rosenthal
Keyword(s):  
Risk Taking ◽  
Risk Taking Behaviors

Adolescents’ Future Negative Time Perspective and Risk-Taking Behaviors: The Roles of Coping Styles and Self-Control

2020 ◽  
Author(s):  
Kai Dou ◽  
Ming-Chen Zhang ◽  
Yue Liang
Keyword(s):  
Risk Taking ◽  
Time Perspective ◽  
Longitudinal Design ◽  
Coping Styles ◽  
Future Time Perspective ◽  
Self Control ◽  
Total N ◽  
Negative Coping ◽  
Risk Taking Behaviors ◽  
Negative Time

The association between future time perspective and risk-taking behaviors has received extensive empirical attention. However, the underlying mechanism that links future negative time perspective to risk-taking behaviors are complex and not well-understood. To address this gap, we adopted a longitudinal design examined the association between FNTP and risk-taking behaviors, and the roles of coping styles and self-control in this association among Chinese adolescents (total N = 581, 46.3% females). Results showed that FNTP at wave 1 predicted risk-taking behavior at wave 3 via positive and negative coping styles at wave 2. Furthermore, adolescents with low self-control and used negative coping strategies prefer to engage in risk-taking behaviors as compared to their high self-control counterparts. Taken together, these research findings underscore the importance of considering influence of the future negative time perspective on adolescents’ risk-taking behaviors, and provided important implications for developing the preventions and interventions for reducing adolescents’ risk-taking behaviors.

scholarly journals Dynamic Evolution Model of a Collaborative Innovation Network from the Resource Perspective and an Application Considering Different Government Behaviors

Information ◽  
2019 ◽  
Vol 10 (4) ◽  
pp. 138 ◽  
Author(s):  
Wu ◽  
Shao ◽  
Feng
Keyword(s):  
Network Evolution ◽  
Evolution Model ◽  
Dynamic Evolution ◽  
Innovation Network ◽  
Transfer Policy ◽  
Collaborative Innovation ◽  
Innovation Output ◽  
The Government ◽  
Small Change ◽  
Innovative Behaviors

The evolution of a collaborative innovation network depends on the interrelationships among the innovation subjects. Every single small change affects the network topology, which leads to different evolution results. A logical relationship exists between network evolution and innovative behaviors. An accurate understanding of the characteristics of the network structure can help the innovative subjects to adopt appropriate innovative behaviors. This paper summarizes the three characteristics of collaborative innovation networks, knowledge transfer, policy environment, and periodic cooperation, and it establishes a dynamic evolution model for a resource-priority connection mechanism based on innovation resource theory. The network subjects are not randomly testing all of the potential partners, but have a strong tendency to, which is, innovation resource. The evolution process of a collaborative innovation network is simulated with three different government behaviors as experimental objects. The evolution results show that the government should adopt the policy of supporting the enterprises that recently entered the network, which can maintain the innovation vitality of the network and benefit the innovation output. The results of this study also provide a reference for decision-making by the government and enterprises.

Risk Factors for a Positive Hepatitis C Status in Fishermen in Kuantan Malaysia

2019 ◽  
Vol 31 (3) ◽  
pp. 227-237
Author(s):  
Priya Lall ◽  
Rumana Saifi ◽  
Diva Baggio ◽  
Samantha Fitzsimmons Schoenberger ◽  
Martin Choo ◽  
...  
Keyword(s):  
Hepatitis C ◽  
Confidence Interval ◽  
Risk Taking ◽  
Odds Ratio ◽  
Large Scale ◽  
Adjusted Odds Ratio ◽  
Environmental Drivers ◽  
Negative Effects ◽  
Risk Taking Behaviors ◽  
Risk Communities

Malaysia currently has an estimated hepatitis C virus (HCV) prevalence of 1.3% with an infected population of 384,000. Fishermen in Malaysia are at risk of HCV infection due to injection drug use and disproportionately high rates of incarceration. This study used quantitative data from Project WAVES, a large-scale mixed methods project charting environmental drivers of risk-taking behaviors among a respondent-driven sample of 406 fishermen in Malaysia. Over a quarter of participants (27.9%) reported injecting drugs in the past month; 49.8% of the sample tested positive for HCV. Respondents who had previously been arrested displayed increased odds of being HCV-positive (adjusted odds ratio = 4.79, confidence Interval = 2.46-9.35). Participants who reported being in lock-up displayed close to 6-fold odds of being HCV-infected (adjusted odds ratio = 5.49, confidence interval = 2.77-10.90, P < .001). These findings underscore the need for policies and structural interventions targeting the negative effects of aggressive incarceration contributing to the burden of HCV among high-risk communities.

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