Gaming Tasks as a Method for Studying the Impact of Warning Messages on Information Behavior

2020 ◽  
Vol 68 (4) ◽  
pp. 576-598
Author(s):  
Alexandra Haddad ◽  
James Sauer ◽  
Jeremy Prichard ◽  
Caroline Spiranovic ◽  
Karen Gelb
Keyword(s):  
Information Behavior ◽  
Warning Messages ◽  
The Impact

An improved car-following model considering the impact of safety messages

2018 ◽  
Vol 32 (32) ◽  
pp. 1850398 ◽  
Author(s):  
Tenglong Li ◽  
Fei Hui ◽  
Xiangmo Zhao
Keyword(s):  
Traffic Congestion ◽  
Dominant Factor ◽  
Velocity Difference ◽  
Car Following ◽  
Safety Message ◽  
Warning Messages ◽  
Gray Correlation ◽  
Car Following Model ◽  
The Stability ◽  
The Impact

The existing car-following models of connected vehicles commonly lack experimental data as evidence. In this paper, a Gray correlation analysis is conducted to explore the change in driving behavior with safety messages. The data mining analysis shows that the dominant factor of car-following behavior is headway with no safety message, whereas the velocity difference between the leading and following vehicle becomes the dominant factor when warning messages are received. According to this result, an extended car-following model considering the impact of safety messages (IOSM) is proposed based on the full velocity difference (FVD) model. The stability criterion of this new model is then obtained through a linear stability analysis. Finally, numerical simulations are performed to verify the theoretical analysis results. Both analytical and simulation results show that traffic congestion can be suppressed by safety messages. However, the IOSM model is slightly less stable than the FVD model if the average headway in traffic flow is approximately 14–20 m.

scholarly journals Are Information Disclosures Effective? Evidence from the Credit Card Market

2017 ◽  
Vol 9 (1) ◽  
pp. 277-307 ◽  
Author(s):  
Enrique Seira ◽  
Alan Elizondo ◽  
Eduardo Laguna-Müggenburg
Keyword(s):  
Financial Markets ◽  
Information Disclosure ◽  
Credit Card ◽  
Large Population ◽  
Warning Messages ◽  
Credit Card Market ◽  
Credit Scores ◽  
Randomized Control ◽  
The Impact ◽  
Actual Policy

Consumer protection in financial markets in the form of information disclosure is high on government agendas, even though there is little evidence of its effectiveness. We implement a randomized control trial in the credit card market for a large population of indebted cardholders and measure the impact of Truth-in-Lending-Act-type disclosures, de-biasing warning messages and social comparison information on default, indebtedness, account closings, and credit scores. We conduct extensive external validity exercises in several banks, with different disclosures, and with actual policy mandates. We find that providing salient interest rate disclosures had no effects, while comparisons and de-biasing messages had only modest effects at best. (JEL D14, D83, G21, G28, O16)

Milling and Public Warnings

2017 ◽  
Vol 50 (5) ◽  
pp. 535-566 ◽  
Author(s):  
Michele M. Wood ◽  
Dennis S. Mileti ◽  
Hamilton Bean ◽  
Brooke F. Liu ◽  
Jeannette Sutton ◽  
...  
Keyword(s):  
Qualitative Methods ◽  
Mobile Devices ◽  
Protective Action ◽  
Response Delay ◽  
Warning Messages ◽  
Norm Theory ◽  
Context Specific ◽  
The Impact ◽  
Quantitative And Qualitative Methods ◽  
Warning Response

Given the potential of modern warning technology to save lives, discovering whether it is possible to craft mobile alerts for imminent events in a way that reduces people’s tendency to seek and confirm information before initiating protective action is essential. The purpose of this study was to examine the possibility of designing messages for mobile devices, such as Wireless Emergency Alert (WEA) messages, to minimize action delay. The impact of messages with varied amounts of information on respondents’ understanding, believing, personalizing, deciding, and intended milling was used to test Emergent Norm Theory, using quantitative and qualitative methods. Relative to shorter messages, longer public warning messages reduced people’s inclination to search for and confirm information, thereby shortening warning response delay. The Emergent Norm Theory used herein is broader in application than the context-specific models provided by leading warning scholars to date and yields deeper understanding about how people respond to warnings.

Gambling warning messages: The impact of winning and losing on message reception across a gambling session.

2016 ◽  
Vol 30 (8) ◽  
pp. 931-938 ◽  
Author(s):  
Meredith K. Ginley ◽  
James P. Whelan ◽  
Holly A. Keating ◽  
Andrew W. Meyers
Keyword(s):  
Warning Messages ◽  
Message Reception ◽  
The Impact

scholarly journals A Walk in the Park? Examining the Impact of App-Based Weather Warnings on Affective Reactions and the Search for Information in a Virtual City

2021 ◽  
Vol 18 (16) ◽  
pp. 8353
Author(s):  
Samuel Tomczyk ◽  
Maxi Rahn ◽  
Henriette Markwart ◽  
Silke Schmidt
Keyword(s):  
Information Seeking ◽  
Behavioral Intentions ◽  
Affective Reactions ◽  
Online Experiment ◽  
Warning Messages ◽  
Warning Message ◽  
Virtual City ◽  
Search For Information ◽  
The Impact

Background: Warning apps can provide personalized public warnings, but research on their appraisal and impact on compliance is scarce. This study introduces a virtual city framework to examine affective reactions when receiving an app-based warning, and subsequent behavioral intentions. Methods: In an online experiment, 276 participants (M = 41.07, SD = 16.44, 62.0% female) were randomly allocated to one of eight groups (warning vs. no warning, thunderstorm vs. no thunderstorm, video vs. vignette). Participants were guided through a virtual city by a mock-up touristic app (t1). Then, the app issued a warning about an impending thunderstorm (t2), followed by a virtual thunderstorm (t3). The virtual city tour was presented via vignettes or videos. ANCOVAs were used to investigate trajectories of momentary anxiety, hierarchical regressions analyzed the impact of momentary anxiety on information seeking. Results: Participants who received a warning message and were confronted with a thunderstorm showed the highest increase in momentary anxiety, which predicted information seeking intentions. Conclusions: The findings underscore the importance of affective appraisal in processing warning messages. The virtual city framework is able to differentiate the impact of warning versus event in an online context, and thus promising for future warning research in virtual settings.

scholarly journals Warning Messages in Crisis Communication: Risk Appraisal and Warning Compliance in Severe Weather, Violent Acts, and the COVID-19 Pandemic

2021 ◽  
Vol 12 ◽  
Author(s):  
Maxi Rahn ◽  
Samuel Tomczyk ◽  
Nathalie Schopp ◽  
Silke Schmidt
Keyword(s):  
Crisis Communication ◽  
Individual Characteristics ◽  
Severe Weather ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Risk Appraisal ◽  
Warning Messages ◽  
Warning Message ◽  
Violent Acts ◽  
The Impact

BackgroundIn crisis communication, warning messages are key to informing and galvanizing the public to prevent or mitigate damage. Therefore, this study examines how risk appraisal and individual characteristics influence the intention to comply with behavioral recommendations of a warning message regarding three hazard types: the COVID-19 pandemic, violent acts, and severe weather.MethodsA cross-sectional survey examined 403 German participants from 18 to 89 years (M = 29.24; 72% female). Participants were allocated to one of three hazard types (COVID-19 pandemic, violent acts, severe weather) and presented with warning messages that were previously issued via an official warning app. Four components of risk appraisal—perceived severity (PS), anticipated negative emotions (AE), anticipatory worry (AW), and risk perception (RP)—were assessed before and after presenting the warning message. Path models were calculated to predict the intention to comply with the warning message, controlling for age, gender, and previous hazard experience.ResultsFor the COVID-19 pandemic, higher age (β = 0.18) predicted warning compliance (R2 = 0.05). AE (β = 0.20) predicted compliance in the case of violent acts (R2 = 0.09). For severe weather, PS (β = 0.28), age (β = 0.29), and female gender (β = 0.34) lead to higher compliance (R2 = 0.27). Changes across risk appraisal components were not consistent, as some facets decreased after the receipt of a warning message.DiscussionRisk appraisal has shown a marginal yet differential influence on warning message compliance in different types of hazards. Regarding the COVID-19 pandemic, the impact of sociodemographic factors on compliance should be studied more intensively. Moreover, integrating intermediary variables, such as self-efficacy, is necessary.

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