What Drives Commuters to Pay for Autonomous Vehicles?

2021 ◽  
pp. 036119812110580
Author(s):  
Alireza Rahimi ◽  
Ghazaleh Azimi ◽  
Xia Jin
Keyword(s):  
Autonomous Vehicles ◽  
Latent Variable ◽  
Data Privacy ◽  
Choice Behavior ◽  
The United States ◽  
Marketing Strategies ◽  
Robust Performance ◽  
Early Adopters ◽  
Using Data ◽  
Demographic Attributes

Although commuters have been identified as potential early adopters of autonomous vehicles (AVs) that can boost the adoption rate of this technology, there is a lack of knowledge on their willingness to pay (WTP) for this technology and the attitude that influences this decision. Using data from a consumer survey conducted in the United States, this study presents a comprehensive analysis of the decision to pay for AVs among commuters. An integrated choice and latent variable (ICLV) model was applied in this study, considering its robust performance in modeling choice behavior for integrating users’ attitudes. The results showed that commuters with a favorable view toward multitasking tended to put a higher value on driverless cars. On the other hand, although a favorable view toward technology motivated commuters to pay more for AVs, data privacy and trust issues with the technology could outweigh this factor and discourage commuters from adopting and paying for AVs. This study also provides in-depth insights and comprehensive views on the impacts of commuters’ socioeconomic and demographic attributes on the decision to pay for AVs. Notably, although age and educational attainment did not directly affect WTP behavior, they played important roles in this decision, with significant effects mediated through latent attitudes. These in-depth analyses provide useful insights that can help develop customized marketing strategies for different market segments according to their specific and unique preferences and concerns.

Time and money volunteering among older adults: the relationship between past and current volunteering and correlates of change and stability

2010 ◽  
Vol 30 (4) ◽  
pp. 559-581 ◽  
Author(s):  
NAMKEE G. CHOI ◽  
RITA JING-ANN CHOU
Keyword(s):  
Social Connectedness ◽  
The United States ◽  
Network Size ◽  
Older Volunteers ◽  
Religious Identification ◽  
Social Network Size ◽  
The Hours ◽  
Using Data ◽  
Demographic Attributes ◽  
The Relationship

ABSTRACTUsing data from the first and second waves of the Survey of Midlife Development in the United States – MIDUS1 1995–1996 and MIDUS2 2004–2006, this paper examines the relationship between the extent of time and money volunteering among people aged 55 or more years at baseline and those of the same age nine years later. Following an analysis of the changes and stability in volunteering status, the paper examines the relationships between change or stability in volunteering and various socio-demographic attributes of the respondents and measures of their human capital, cultural capital and social capital. A majority of older volunteers of time and/or money were repeat volunteers, and the extent of volunteering at the start of the studied period was one of the most significant predictors of the extent of volunteering nine years later. The level of education was a consistent predictor of the extent of both time and money volunteering and of new engagement and stability in volunteering. Social network size, or social connectedness, represented by the number of various meetings attended, was a significant predictor not only of the hours of time volunteering, but also of new engagement and stability in both time and money volunteering. A high degree of religious identification also appeared to be a motivation for money volunteering and to affect the value of donations. The paper concludes by discussing the implications of the findings for the recruitment and retention of volunteers.

Migration and the Internet

2017 ◽  
Vol 14 (3) ◽  
pp. 331-342 ◽  
Author(s):  
Thomas John Cooke ◽  
Ian Shuttleworth
Keyword(s):  
United States ◽  
Information And Communication Technologies ◽  
Unobserved Heterogeneity ◽  
Panel Study ◽  
The United States ◽  
Negative Effect ◽  
Information And Communication ◽  
Using Data ◽  
And Migration ◽  
Dynamics Models

It is widely presumed that information and communication technologies, or ICTs, enable migration in several ways; primarily by reducing the costs of migration. However, a reconsideration of the relationship between ICTs and migration suggests that ICTs may just as well hinder migration; primarily by reducing the costs of not moving.  Using data from the US Panel Study of Income Dynamics, models that control for sources of observed and unobserved heterogeneity indicate a strong negative effect of ICT use on inter-state migration within the United States. These results help to explain the long-term decline in internal migration within the United States.

Data Envelopment Analysis (DEA) in the Psychological Sciences

2019 ◽  
Author(s):  
Jeffrey A. Shero ◽  
Sara Ann Hart
Keyword(s):  
Data Envelopment Analysis ◽  
Aggressive Behavior ◽  
Personality Traits ◽  
Educational Administration ◽  
Latent Variable ◽  
Organizational Management ◽  
Data Envelopment ◽  
Targeted Interventions ◽  
Component Skills ◽  
Using Data

Using methods like linear regression or latent variable models, researchers are often interested in maximizing explained variance and identifying the importance of specific variables within their models. These models are useful for understanding general ideas and trends, but often give limited insight into the individuals within said models. Data envelopment analysis (DEA), is a method with roots in organizational management that make such insights possible. Unlike models mentioned above, DEA does not explain variance. Instead, it explains how efficiently an individual utilizes their inputs to produce outputs, and identifies which input is not being utilized optimally. This paper provides readers with a brief history and past usages of DEA from organizational management, public health, and educational administration fields, while also describing the underlying math and processes behind said model. This paper then extends the usage of this method into the psychology field using two separate studies. First, using data from the Project KIDS dataset, DEA is demonstrated using a simple view of reading framework identifying individual efficiency levels in using reading-based skills to achieve reading comprehension, determining which skills are being underutilized, and classifying and comparing new subsets of readers. Three new subsets of readers were identified using this method, with direct implications leading to more targeted interventions. Second, DEA was used to measure individuals’ efficiency in regulating aggressive behavior given specific personality traits or related skills. This study found that despite comparable levels of component skills and personality traits, significant differences were found in efficiency to regulate aggressive behavior on the basis of gender and feelings of provocation.

Student Privacy and the Law in the Internet Age

2019 ◽  
Author(s):  
Leah Plunkett ◽  
Urs Gasser ◽  
Sandra Cortesi
Keyword(s):  
Learning Environments ◽  
School Environment ◽  
Privacy Protection ◽  
Data Privacy ◽  
Digital Technologies ◽  
The United States ◽  
Legal Framework ◽  
Privacy Law ◽  
Student Privacy ◽  
High Level

New types of digital technologies and new ways of using them are heavily impacting young people’s learning environments and creating intense pressure points on the “pre-digital” framework of student privacy. This chapter offers a high-level mapping of the federal legal landscape in the United States created by the “big three” federal privacy statutes—the Family Educational Rights and Privacy Act (FERPA), the Children’s Online Privacy Protection Act (COPPA), and the Protection of Pupil Rights Amendment (PPRA)—in the context of student privacy and the ongoing digital transformation of formal learning environments (“schools”). Fissures are emerging around key student privacy issues such as: what are the key data privacy risk factors as digital technologies are adopted in learning environments; which decision makers are best positioned to determine whether, when, why, and with whom students’ data should be shared outside the school environment; what types of data may be unregulated by privacy law and what additional safeguards might be required; and what role privacy law and ethics serve as we seek to bolster related values, such as equity, agency, and autonomy, to support youth and their pathways. These and similar intersections at which the current federal legal framework is ambiguous or inadequate pose challenges for key stakeholders. This chapter proposes that a “blended” governance approach, which draws from technology-based, market-based, and human-centered privacy protection and empowerment mechanisms and seeks to bolster legal safeguards that need to be strengthen in parallel, offers an essential toolkit to find creative, nimble, and effective multistakeholder solutions.

scholarly journals Challenges in Bridge Health Monitoring: A Review

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4336
Author(s):  
Piervincenzo Rizzo ◽  
Alireza Enshaeian
Keyword(s):  
United States ◽  
Health Monitoring ◽  
Highway Bridges ◽  
The United States ◽  
Anomalous Behavior ◽  
Existing Structures ◽  
Bridge Health Monitoring ◽  
Using Data ◽  
The Many ◽  
Major Factors

Bridge health monitoring is increasingly relevant for the maintenance of existing structures or new structures with innovative concepts that require validation of design predictions. In the United States there are more than 600,000 highway bridges. Nearly half of them (46.4%) are rated as fair while about 1 out of 13 (7.6%) is rated in poor condition. As such, the United States is one of those countries in which bridge health monitoring systems are installed in order to complement conventional periodic nondestructive inspections. This paper reviews the challenges associated with bridge health monitoring related to the detection of specific bridge characteristics that may be indicators of anomalous behavior. The methods used to detect loss of stiffness, time-dependent and temperature-dependent deformations, fatigue, corrosion, and scour are discussed. Owing to the extent of the existing scientific literature, this review focuses on systems installed in U.S. bridges over the last 20 years. These are all major factors that contribute to long-term degradation of bridges. Issues related to wireless sensor drifts are discussed as well. The scope of the paper is to help newcomers, practitioners, and researchers at navigating the many methodologies that have been proposed and developed in order to identify damage using data collected from sensors installed in real structures.

scholarly journals Assessing the Relationships Between COVID-19 Stay-at-Home Orders and Opioid Overdoses in the State of Pennsylvania

2021 ◽  
pp. 002204262110063
Author(s):  
Brian King ◽  
Ruchi Patel ◽  
Andrea Rishworth
Keyword(s):  
Age Groups ◽  
The United States ◽  
Opioid Use Disorder ◽  
Opioid Overdose ◽  
Policy Recommendations ◽  
Opioid Use ◽  
Fentanyl Analogs ◽  
Measure Change ◽  
Using Data ◽  
At Home

COVID-19 is compounding opioid use disorder throughout the United States. While recent commentaries provide useful policy recommendations, few studies examine the intersection of COVID-19 policy responses and patterns of opioid overdose. We examine opioid overdoses prior to and following the Pennsylvania stay-at-home order implemented on April 1, 2020. Using data from the Pennsylvania Overdose Information Network, we measure change in monthly incidents of opioid-related overdose pre- versus post-April 1, and the significance of change by gender, age, race, drug class, and naloxone doses administered. Findings demonstrate statistically significant increases in overdose incidents among both men and women, White and Black groups, and several age groups, most notably the 30–39 and 40–49 ranges, following April 1. Significant increases were observed for overdoses involving heroin, fentanyl, fentanyl analogs or other synthetic opioids, pharmaceutical opioids, and carfentanil. The study emphasizes the need for opioid use to be addressed alongside efforts to mitigate and manage COVID-19 infection.

A Behavioral-Analytic Model for Assessing Stress in Firefighters

2021 ◽  
pp. 014544552098613
Author(s):  
Bailee B. Schuhmann ◽  
Sarah N. Henderson ◽  
Ryan A. Black ◽  
Vincent B. Van Hasselt ◽  
Kristin Klimley Margres ◽  
...  
Keyword(s):  
Stress Reduction ◽  
Discriminant Validity ◽  
Stress Test ◽  
The United States ◽  
Fire Service ◽  
Analytic Model ◽  
Negative Effects ◽  
Internal Reliability ◽  
Convergent And Discriminant Validity ◽  
Using Data

Research has documented a number of acute and chronic stressors unique to the fire service. Due to the rise in mental health concerns in firefighters, there has been increased awareness of the negative effects of unmanaged stress. The present study employed a behavioral-analytic model to construct a brief screening measure of stress for this population: the Firefighter Assessment of Stress Test (FAST). Psychometric properties of the FAST were evaluated using data from active-duty firefighters throughout the United States. Results indicated the FAST has good internal reliability ( α = 0.89), as well as good convergent and discriminant validity. Also, the factor structure of the FAST revealed three significant subscales reflective of stress associated with responding to calls, administrative difficulties, and being overworked. Scoring and interpretation guidelines were established to suggest when further assessment is warranted. The FAST offers a brief and valid method of self-assessment of current stress levels in firefighters. Information obtained from the FAST (i.e., overall stress level and domains) has the potential to facilitate more immediate identification and recognition of stress in firefighters than what has been possible to date. Moreover, heightened awareness of stress and its effects will hopefully culminate in expanded efforts directed toward stress reduction and intervention for firefighters and their families.

Role Stress and Sense of Control Predict Using Food to Cope With Stress in Midlife Women

2021 ◽  
pp. 089826432110110
Author(s):  
Dana R. Riedy ◽  
Ashley MacPherson ◽  
Natalie D. Dautovich
Keyword(s):  
Work Stress ◽  
Underlying Mechanism ◽  
The United States ◽  
Role Stress ◽  
Work And Family ◽  
Midlife Women ◽  
Sense Of Control ◽  
Study Results ◽  
Using Data ◽  
Significant Mediator

Objective: The current study examined the association between role stress and using food to cope with stress in midlife women and examined sense of control as a potential underlying mechanism. Methods: An archival analysis was performed using data from 638 midlife women from the Midlife in the United States II study. Results: Hierarchical linear regression analyses demonstrated that work stress (β = .180, p < .001) and family stress (β = .138, p < .05) significantly predicted using food to cope with stress. Sense of control was a significant mediator between work stress and using food to cope with stress ( b = 0.02, 95% CI [.0014, .0314]). Discussion: Midlife women with higher role stress related to work and family are more likely to use food to cope with stress, and sense of control seems to be the link between work stress and using food to cope.

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