Examining the Differential Effectiveness of Fear Appeals in Information Security Management Using Two-Stage Meta-Analysis

2023 | Journal of Management Information Systems | Citations: 0

Authors: Lowry, Paul Benjamin; Moody, Gregory D.; Parameswaran, Srikanth; Brown, Nicholas James

Abstract: Most of the information security management research involving fear appeals is g ... Expand

Abstract: Most of the information security management research involving fear appeals is guided by either protection motivation theory or the extended parallel processing model. Over time, extant research has extended these theories, as well as their derivative theories, in a variety of ways, leading to several theoretical and empirical inconsistencies. The large body of fragmented, and sometimes conflicting, research has muddied the broader understanding of what drives protection- and defensive motivation. We provide guidance to the security discourse by offering the first study in the literature to employ two-stage meta-analytic structural equation modeling (TSSEM), which combines covariance-based structural equation modeling and meta-analysis. Information systems (IS) researchers have traditionally used meta-analysis for structural equation modeling for such purposes—an approach that has several serious statistical flaws. Using 341 systematically selected empirical security articles (representing 383 unique studies) and TSSEM, we pool a large series of five datasets to test six models, from which we examine the effects of constructs and paths in the security fear-appeals literature. We compare and test six versions of models inspired by issues in the broader fear-appeals literature. We confirm the importance of both the threat- and coping-appraisal processes; establish the central role of fear and that it has greater importance than threat; show that efficacy is a stronger predictor of protection motivation than is threat; demonstrate that response costs as currently measured are ineffective but that maladaptive rewards have a strong negative effect on protection motivation and a positive effect on defensive motivation; and provide evidence that dual models of danger control and fear control should be used. Collapse

Topics: H1N1 flu self efficacy Python data quality information security management

Methods: structural equation modeling meta analysis statistical hypothesis test hierarchical linear modeling statistical power analysis

Theories: fear appeal theory extended parallel process model protection motivation theory

Coping and Regulatory Responses on Social Media during Health Crisis: a Large-scale Analysis

2022 | HICSS | Citations: 0

Authors: Abramova, Olga; Batzel, Katharina; Modesti, Daniela

Abstract: During a crisis event, social media enables two-way communication and many-to-ma ... Expand

Abstract: During a crisis event, social media enables two-way communication and many-to-many information broadcasting, browsing others’ posts, publishing own content, and public commenting. These records can deliver valuable insights to approach problematic situations effectively. Our study explores how social media communication can be analyzed to understand the responses to health crises better. Results based on nearly 800 K tweets indicate that the coping and regulation foci framework holds good explanatory power, with four clusters salient in public reactions: 1) “Understanding” (problem-promotion); 2) “Action planning” (problem-prevention); 3) “Hope” (emotion-promotion) and 4) “Reassurance” (emotionprevention). Second, the inter-temporal analysis shows high volatility of topic proportions and a shift from self-centered to community-centered topics during the course of the event. The insights are beneficial for research on crisis management and practicians who are interested in large-scale monitoring of their audience for well-informed decision-making. Collapse

Topics: Twitter social media pandemic fake news terrorist incident

Methods: topic model psychometrics survey natural language processing machine learning

Theories: regulatory focus theory terror management theory

Retweets of officials’ alarming vs reassuring messages during the COVID-19 pandemic: Implications for crisis management

2020 | International Journal of Information Management | Citations: 0

Authors: Rao, H. Raghav; Vemprala, Naga; Akello, Patricia; Valecha, Rohit

Abstract: Coronavirus related discussions have spiraled at an exponential rate since its i ... Expand

Abstract: Coronavirus related discussions have spiraled at an exponential rate since its initial outbreak. By the end of May, more than 6 million people were diagnosed with this infection. Twitter witnessed an outpouring of anxious tweets through messages associated with the spread of the virus. Government and health officials replied to the troubling tweets, reassuring the public with regular alerts on the virus's progress and information to defend against the virus. We observe that social media users are worried about Covid 19-related crisis and we identify three separate conversations on virus contagion, prevention, and the economy. We analyze the tone of officials’ tweet text as alarming and reassuring and capture the response of Twitter users to official communications. Such studies can provide insights to health officials and government agencies for crisis management, specifically regarding communicating emergency information to the public via social media for establishing reassurance. Collapse

Topics: Twitter social media pandemic covid 19 emergency management

Methods: word2vec topic model word embedding latent dirichlet allocation computational algorithm

Weakly Supervised and Online Learning of Word Models for Classification to Detect Disaster Reporting Tweets

2018 | Information Systems Frontiers | Citations: 7

Authors: Palshikar, Girish Keshav; Apte, Manoj; Pandita, Deepak

Abstract: Social media has quickly established itself as an important means that people, N ... Expand

Abstract: Social media has quickly established itself as an important means that people, NGOs and governments use to spread information during natural or man-made disasters, mass emergencies and crisis situations. Given this important role, real-time analysis of social media contents to locate, organize and use valuable information for disaster management is crucial. In this paper, we propose self-learning algorithms that, with minimal supervision, construct a simple bag-of-words model of information expressed in the news about various natural disasters. Such a model is human-understandable, human-modifiable and usable in a real-time scenario. Since tweets are a different category of documents than news, we next propose a model transfer algorithm, which essentially refines the model learned from news by analyzing a large unlabeled corpus of tweets. We show empirically that model transfer improves the predictive accuracy of the model. We demonstrate empirically that our model learning algorithm is better than several state of the art semi-supervised learning algorithms. Finally, we present an online algorithm that learns the weights for words in the model and demonstrate the efficacy of the model with word weights. Collapse

Topics: Twitter criminality knowledge representation natural hazard earthquake

Methods: computational algorithm WordNet semi-supervised learning support vector machine part of speech tagging

Exploring the Effects of Source Credibility on Information Adoption on YouTube

2016 | European Conference On Information Systems | Citations: 0

Authors: Coursaris, Constantinos K.; Van Osch, Wietske

Abstract: This research-in-progress paper explores the effects of information source credi ... Expand

Abstract: This research-in-progress paper explores the effects of information source credibility (brands versus vloggers), information type (how-to tutorial versus product demonstration), and viewer characteristics on perceptions of information quality, information usefulness, information satisfaction, and information adoption in the context of YouTube makeup videos. The primary goal of this study is to understand how users process information provided through YouTube videos by brands and vloggers, as well as extend existing models of information adoption that solely focus on information and source characteristics without considering characteristics of the user or viewer. Envisioned future steps in this project are discussed as well as implications for research and practice. Collapse

Topics: data quality YouTube data relevance user satisfaction communication service infrastructure

Methods: experiment

Simulation modeling for pandemic decision making: A case study with bi-criteria analysis on school closures

2013 | Decision Support Systems | Citations: 0

Authors: Araz, Ozgur M.; Lant, Tim; Fowler, John W.; Jehn, Megan

Abstract: Pandemic influenza continues to be a national and international public health co ... Expand

Abstract: Pandemic influenza continues to be a national and international public health concern, and has received significant attention worldwide with the A/H1N1 influenza outbreak in 2009. Many countries, including the United States, have developed preparedness plans for an influenza pandemic. Preparedness plans are falling under renewed scrutiny as decision-makers apply new findings and seek key leverage points for more effective preparedness and response. School closure has been recommended by the World Health Organization as one of the best ways to protect children and other susceptible individuals at the early stages of the pandemic. However, school closure is a difficult mitigation policy to implement from both strategic and operational points of view. Challenges include impacts on alternative education delivery services, such as student meals and after-school oversight, as well as direct and indirect economic outfalls. To help public health decision makers address these issues, we developed an epidemiological simulation tool for pandemic influenza which enables users to make decisions during a simulated pandemic. We then designed a school closure tabletop exercise using our simulation model as a decision-support tool for evaluating the effectiveness of school closure as a community mitigation strategy for pandemic influenza. We conducted two exercises in February 2009 for the Arizona Department of Health and Human Services including high-ranking health and education administrators from across the state. The purpose of these exercises was to test the state's pandemic preparedness plans with respect to school closure timing and impact. The exercises required participants to make (hypothetical) strategic and operational decisions to mitigate the impacts of pandemic influenza at the state and local levels. Our simulation and decision analysis tool was used to assess the impact of key decisions in the exercises. This paper presents the technical details involved in the design and evaluation of this pandemic decision-support tool. Based on the decisions made in the exercises, we present a bi-criteria decision analysis framework to evaluate analytical results obtained from the simulation model. Our analyses show that sequential school closure and re-opening strategy with a specific decision rule gives the best compromised solution in terms of minimizing the total number of infections and providing minimal educational discontinuity. Collapse

Topics: pandemic decision support system decision making database system H1N1 flu

Methods: simulation case study archival research cross sectional research mathematical model

An Information Diffusion-Based Recommendation Framework for Micro-Blogging

2011 | Journal of the Association for Information Systems | Citations: 0

Authors: Jiesi Cheng; Sun, Aaron; Hu, Daning; Zeng, Daniel

Abstract: Micro-blogging is increasingly evolving from a daily chatting tool into a critic ... Expand

Abstract: Micro-blogging is increasingly evolving from a daily chatting tool into a critical platform for individuals and organizations to seek and share real-time news updates during emergencies. However, seeking and extracting useful information from micro-blogging sites poses significant challenges due to the volume of the traffic and the presence of a large body of irrelevant personal messages and spam. In this paper, we propose a novel recommendation framework to overcome this problem. By analyzing information diffusion patterns among a large set of micro-blogs that play the role of emergency news providers, our approach selects a small subset as recommended emergency news feeds for regular users. We evaluate our diffusion-based recommendation framework on Twitter during the early outbreak of H1N1 Flu. The evaluation results show that our method results in more balanced and comprehensive recommendations compared to benchmark approaches. Collapse

Topics: blog Twitter H1N1 flu recommender system Google+

Methods: computational algorithm cluster analysis machine learning k-means clustering NLTK

Research Commentary—Virtual Worlds: A Performative Perspective on Globally Distributed, Immersive Work

2010 | Information Systems Research | Citations: 10

Authors: Schultze, Ulrike; Orlikowski, Wanda J.

Abstract: Virtual worlds are immersive, simulated, persistent, and dynamic environments th ... Expand

Abstract: Virtual worlds are immersive, simulated, persistent, and dynamic environments that include rich graphical three dimensional spaces, high fidelity audio, motion, viewpoint, and interactivity. Initially dismissed as environments of play, virtual worlds have gained legitimacy in business and educational settings for their application in globally distributed work, project management, online learning, and real-time simulation. Understanding the emergent aspects of these virtual worlds and their implications for organizations will require both new theories and new methods. We propose that a performative perspective may be particularly useful as it challenges the existence of independent objects with fixed or given properties and boundaries, and focuses instead on situated and relational practices that enact entangled and contingent boundaries, entities, identities, and effects. Collapse

Topics: virtual world Second Life H1N1 flu

Methods: qualitative interview