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How Review Quality and Source Credibility Interacts to Affect Review Usefulness: An Expansion of the Elaboration Likelihood Model
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2023 | Information Systems Frontiers | Citations: 0
Authors: Aghakhani, Navid; Oh, Onook; Gregg, Dawn; Jain, Hemant

Abstract: This study extends our understanding of what makes an online review useful by ex ... Expand

Abstract: This study extends our understanding of what makes an online review useful by examining the effects of review quality (i.e., as a composite variable of review comprehensiveness and review topic consistency) on review usefulness, and the moderating effects of source credibility on the relationship between review quality and review usefulness. The Elaboration Likelihood Model, convergence theory, and cueing effect literature are used to define the variables of review comprehensiveness and review topic consistency. Analyses of 27,517 restaurant reviews from Yelp show that review topic consistency has a positive effect on review usefulness, but, contrary to our hypothesis, review comprehensiveness has a negative effect on review usefulness. We also found source credibility positively moderates the effect of review comprehensiveness on review usefulness, but negatively moderates the effect of review topic consistency on review usefulness. Theoretical and practical implications are discussed. Collapse

Semantic filters: elaboration likelihood model

Topics: online review user-generated content Python website data breach

Methods: topic model term frequency–inverse document frequency NLTK statistical hypothesis test robustness check

Theories: elaboration likelihood model
Too Tired and in Too Good of a Mood to Worry About Privacy: Explaining the Privacy Paradox Through the Lens of Effort Level in Information Processing
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2023 | Information Systems Research | Citations: 0
Authors: Alashoor, Tawfiq; Keil, Mark; Smith, H. Jeff; McConnell, Allen R.

Abstract: The confluence of digital transactions, growing cybersecurity threats, and the i ... Expand

Abstract: The confluence of digital transactions, growing cybersecurity threats, and the internet of the future (e.g., web 3.0 and the metaverse) have made information privacy increasingly important to consumers and companies that rely on consumers willingly sharing their personal information. Although information privacy has been of interest to researchers for decades and much has been learned, one thing that perplexes scholars is the privacy paradox, which we define as a mismatch between stated privacy concerns and actual disclosure behaviors. In this paper, we shed light on this phenomenon and show that low-effort information processing triggered by cognitive depletion (Experiment 1), positive mood (Experiment 2), or both (Experiment 3) significantly attenuates the association between stated privacy concerns and disclosure behaviors. These findings do not indicate that individuals do not care about privacy because we find consistent evidence in the three experiments for a significant negative association between stated privacy concerns and disclosure behaviors when individuals have sufficient cognitive capacity (Experiment 1), experience a negative (or neutral) mood (Experiment 2), or have sufficient cognitive capacity coupled with a negative mood state (Experiment 3). Our findings reveal that the paradox is neither an absolute phenomenon nor a myth, but its existence is conditional on contextual factors, including psychological factors related to information processing. We discuss our contribution to privacy theory and provide implications for consumers, companies, and policymakers. History: Alessandro Acquisti, Senior Editor; Idris Adjerid, Associate Editor. Supplemental Material: The online appendix is available at https://doi.org/10.1287/isre.2022.1182. Collapse

Semantic filters: elaboration likelihood model

Topics: information privacy concern privacy decision making mobile application task productivity

Methods: experiment descriptive statistic statistical hypothesis test theory development Student's t-test

Theories: elaboration likelihood model
Explainable artificial intelligence in information systems: A review of the status quo and future research directions
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2023 | Electronic Markets | Citations: 4
Authors: Brasse, Julia; Broder, Hanna Rebecca; Förster, Maximilian; Klier, Mathias; Sigler, Irina

Abstract: The quest to open black box artificial intelligence (AI) systems evolved into an ... Expand

Abstract: The quest to open black box artificial intelligence (AI) systems evolved into an emerging phenomenon of global interest for academia, business, and society and brought about the rise of the research field of explainable artificial intelligence (XAI). With its pluralistic view, information systems (IS) research is predestined to contribute to this emerging field; thus, it is not surprising that the number of publications on XAI has been rising significantly in IS research. This paper aims to provide a comprehensive overview of XAI research in IS in general and electronic markets in particular using a structured literature review. Based on a literature search resulting in 180 research papers, this work provides an overview of the most receptive outlets, the development of the academic discussion, and the most relevant underlying concepts and methodologies. Furthermore, eight research areas with varying maturity in electronic markets are carved out. Finally, directions for a research agenda of XAI in IS are presented. Collapse

Semantic filters: elaboration likelihood model

Topics: explainable artificial intelligence artificial intelligence user requirement electronic market user experience

Methods: literature study literature sample cluster analysis synthesis machine learning

Theories: information systems theory activity theory agency theory attribution theory cognitive fit theory
Influence of Twitter on Hydroxychloroquine Medication Prescriptions for COVID-19 Patients

2023 | International Conference on Information Systems | Citations: 0
Authors: Gorthi, Sai Soundarya; Ganju, Kartik; Pinsonneault, Alain

Abstract: Social media is proposed to play a crucial role in healthcare providers' care d ... Expand

Abstract: Social media is proposed to play a crucial role in healthcare providers' care decisions. However, social media information may not always be reliable as false information is prone to virality, and emotional cues may drive information sharing. Hence, in our study, we strive to understand the influence of social media on healthcare providers' care decisions by empirically examining the influence of Twitter discourse regarding Hydroxychloroquine (HCQ) on the actual prescribing rates of the drug in the USA for treating Collapse

Semantic filters: elaboration likelihood model

Topics: Twitter social media application programming interface Python missing data

Methods: longitudinal research machine learning qualitative coding autocorrelation analysis mixed method

Theories: elaboration likelihood model
Disasters Information-Seeking Behavior via Social Networking Sites

2023 | Americas Conference on Information Systems | Citations: 0
Authors: Khalil, Omar; Alajmi, Bibi

Abstract: Disasters bring uncertainties and substantial health, economic, social, and psy ... Expand

Abstract: Disasters bring uncertainties and substantial health, economic, social, and psychological challenges. Effective management of disasters requires thorough understanding of their causes, nature, and consequences. Affected individuals may, therefore, seek instant, trustworthy information from different sources including social networking sites (SNSs). This study investigates what leads individuals to seek disaster information on SNSs. The investigated potential drivers are source credibility (SC), argument quality (AQ), self-efficacy (SEF), perceived usefulness of information (OUI), and behavioral intention (INT). The results confirm the newly emerged source & argument quality (SAQ) construct, SEF, and PUI are significant antecedents of INT, which in turn influences disaster information seeking behavior (ISB) via SNSs. Keywordsdisaster information seeking behavior, social networking sites, disaster. Collapse

Semantic filters: elaboration likelihood model

Topics: emergency management self efficacy perceived usefulness behavioral intention

Methods: structural equation modeling cross sectional research survey theory development factor analysis

Theories: technology acceptance model social cognitive theory elaboration likelihood model cognitive theory theory of planned behavior
Augmenting Password Strength Meter Design Using the Elaboration Likelihood Model: Evidence from Randomized Experiments
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2023 | Information Systems Research | Citations: 0
Authors: Khern-am-nuai, Warut; Hashim, Matthew J.; Pinsonneault, Alain; Yang, Weining; Li, Ninghui

Abstract: Password-based authentication is the most commonly used method for gaining acces ... Expand

Abstract: Password-based authentication is the most commonly used method for gaining access to secured systems. Unfortunately, empirical evidence highlights the fact that most passwords are significantly weak, and encouraging users to create stronger passwords is a significant challenge. In this research, we propose a theoretically augmented password strength meter design that is guided by the elaboration likelihood model of persuasion (ELM). We evaluate our design by leveraging three independent and complementary methods: a survey-based experiment using students to evaluate the saliency of our conceptual design (proof of concept), a controlled laboratory experiment conducted on Amazon Mechanical Turk to test the effectiveness of the proposed design (proof of value), and a randomized field experiment conducted in collaboration with an online forum in Asia to establish proof of use. In each study, we observe the changes in users’ behavior in response to our proposed password strength meter. We find that the ELM-augmented password strength meter is significantly effective at addressing the challenges of password-based authentication. Users exposed to this strength meter are more likely to change their passwords, leading to a new password that is significantly stronger. Our findings suggest that the proposed design of augmented password strength meters is an effective method for promoting secure password behavior among end users.History: Alessandro Acquisti, Senior Editor; Pallab Sanyal, Associate Editor.Funding: The authors gratefully acknowledge financial support from the Social Science and Humanities Research Council of Canada (SSHRC) [Grant 435-2018-0605].Supplemental Material: The online appendix is available at https://doi.org/10.1287/isre.2022.1125. Collapse

Semantic filters: elaboration likelihood model

Topics: password website data security electronic authentication application programming interface

Methods: experiment survey laboratory experiment experimental group field experiment

Theories: elaboration likelihood model
How to attract low prosocial funders in crowdfunding? Matching among funders, project descriptions, and platform types
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2023 | Information & Management | Citations: 0
Authors: Li, Yuanqing; Cabano, Frank; Li, Pingshu

Abstract: The amount of crowdfunding research that investigates funding success factors ha ... Expand

Abstract: The amount of crowdfunding research that investigates funding success factors has been increasing. The existing research shows inconsistent evidence regarding how a prosocial project description affects funding success and largely ignores the issue of alignment/misalignment among different factors in affecting funding success. We suggest that funders’ prosocial motivation can be an important factor for this inconsistent evidence. We integrate the elaboration likelihood model and language expectancy theory and demonstrate distinct decision-making patterns from high and low prosocial motivation funders. Through three experiments, we provide evidence for alignment/misalignment effects among funders’ prosocial motivation, prosocial project descriptions, and platform types (donation-based vs. reward-based). While there are no differences for participants with high prosocial motivation across conditions, we find that participants with low prosocial motivation are more willing to contribute to a project that has alignment between the different factors, namely to a project that has a high prosocial description on a donation-based platform, or to a project that has a low prosocial description on a reward-based platform. This research sheds light on the crowdfunding and prosocial motivation literature. Collapse

Semantic filters: elaboration likelihood model

Topics: crowdfunding crowdsourcing decision making cost benefit analysis cross cultural research

Methods: experiment parametric test descriptive statistic ANOVA one-way ANOVA

Theories: expectancy theory of motivation elaboration likelihood model organizational behavior theory
A Design Theory for Certification Presentations
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2023 | ACM SIGMIS Database | Citations: 0
Authors: Lins, Sebastian; Becker, Jan-Michael; Lyytinen, Kalle; Sunyaev, Ali

Abstract: Prior information system research remains inconsistent of the effects of system ... Expand

Abstract: Prior information system research remains inconsistent of the effects of system certifications. In their current use, certifications are often reduced to graphical seals. This approach fails to incorporate detailed assurance information emanating from the certification process. To address this gap, we adopt a design science approach and deploy a four-phase research design to clarify how to design impactful IS certification presentations. First, we identify sources of users' limited understanding of seals and formulate a design proposal for a certification presentation by drawing upon the elaboration likelihood model. In the second phase, we formulate and validate a set of design meta-requirements and guidelines to improve certification presentation, using cognitive load theory and Toulmin's model of argumentation as kernel theories. In the third phase, new certification presentations that comply with the proposed guidelines are developed and evaluated for their effectiveness. We show that presentations that augment seal-based certification presentations with richer assurance information improve certification effectiveness. This increases users' assurance and trust perceptions when the presentations align with the users' cognitive information processing needs in ways that reduce their cognitive load and enhance argument quality of assurance information. Collapse

Semantic filters: elaboration likelihood model

Topics: cloud computing website information privacy concern cloud storage data quality

Methods: experiment design guideline experimental group survey design artifact

Theories: argumentation theory dual-system theory cognitive load theory elaboration likelihood model
Be a Miracle - Designing Conversational Agents to Influence Users’ Intention Regarding Organ Donation

2023 | International Conference on Information Systems | Citations: 0
Authors: Pietrantoni, Nico; Greulich, Stefan; Morana, Stefan

Abstract: The increasing need for organ donations remains a worldwide challenge as transp ... Expand

Abstract: The increasing need for organ donations remains a worldwide challenge as transplant waiting lists grow and donation rates persist at constant levels. The increasing popularity of conversational agents (CAs) has prompted new strategies for educating and persuading individuals to adjust their cognitive and behavioral beliefs and become donors. However, how CAs should be designed to modify uninformed users' intention to donate remains unclear. Against this background, we conducted an online experiment (N=134) to examine the impact of a human-like CA design on users' intention to become organ donors. Based on the three-factor theory of anthropomorphism and the elaboration likelihood model, we derive three theoretical mechanisms to understand the influence of a CAs human-like design on users' intention to donate. The findings show that perceived anthropomorphism does not directly impact persuasion and empathy but is mediated via perceived usefulness to influence the intention to donate. Collapse

Semantic filters: elaboration likelihood model

Topics: perceived usefulness health information system crowdsourcing Facebook Google+

Methods: experiment partial least squares regression statistical power analysis structural equation modeling parametric test

Theories: elaboration likelihood model
Stimulating Feedback Contributions Using Digital Nudges: A Field Experiment in a Real-time Mobile Feedback Platform

2023 | International Conference on Information Systems | Citations: 0
Authors: Rivera, Michael; Guo, Xue; Shan, Guohou; Qiu, Liangfei

Abstract: In the contemporary remote work environment, the demand for effective and timel ... Expand

Abstract: In the contemporary remote work environment, the demand for effective and timely feedback has significantly grown. Despite the adoption of feedback systems, many employees still find these platforms lacking in delivering meaningful insights. This study delves into the potential of digital nudges-reminder notifications sent to users-as a strategy to enhance feedback contributions on mobile platforms. A randomized field experiment was conducted in collaboration with a prominent organization, exploring variations in nudge send times and the emphasis on task significance. Spanning five weeks, the experiment evaluated the efficacy of these nudges in fostering feedback engagement among employees. Our findings indicate that the timing, content of nudges (i.e., task significance message), and a combination of these two, can significantly influence feedback behavior. The study's findings have potential implications for organizations aiming to bolster their feedback systems, making them more responsive and effective in the digital age. Collapse

Semantic filters: elaboration likelihood model

Topics: decision making smartphone IS effectiveness individual impact marketing management

Methods: experimental group experiment randomized field experiment qualitative interview Student's t-test

Theories: elaboration likelihood model prisoner's dilemma

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Found 183 articles

How Review Quality and Source Credibility Interacts to Affect Review Usefulness: An Expansion of the Elaboration Likelihood Model

Too Tired and in Too Good of a Mood to Worry About Privacy: Explaining the Privacy Paradox Through the Lens of Effort Level in Information Processing

Explainable artificial intelligence in information systems: A review of the status quo and future research directions

Influence of Twitter on Hydroxychloroquine Medication Prescriptions for COVID-19 Patients

Disasters Information-Seeking Behavior via Social Networking Sites

Augmenting Password Strength Meter Design Using the Elaboration Likelihood Model: Evidence from Randomized Experiments

How to attract low prosocial funders in crowdfunding? Matching among funders, project descriptions, and platform types

A Design Theory for Certification Presentations

Be a Miracle - Designing Conversational Agents to Influence Users’ Intention Regarding Organ Donation

Stimulating Feedback Contributions Using Digital Nudges: A Field Experiment in a Real-time Mobile Feedback Platform