Gamified monetary reward designs: Offering certain versus chance-based rewards

2023 | Information Systems Journal | Citations: 0

Authors: Adam, Martin; Reinelt, Annika; Roethke, Konstantin

Abstract: To motivate visitors to engage with websites, e-tailers widely employ monetary r ... Expand

Abstract: To motivate visitors to engage with websites, e-tailers widely employ monetary rewards (e.g., vouchers, discounts) in their website designs. With advances in user interface technologies, many e-tailers have started to offer gamified monetary reward designs (MRDs), which require visitors to earn the monetary reward by playing a game, rather than simply claiming the reward. However, little is known about whether and why gamified MRDs engage visitors compared to their non-gamified counterpart. Even less is known about the effectiveness of gamified MRDs when providing certain or chance-based rewards, in that visitors do or do not know what reward they will gain for successfully performing in the game. Drawing on cognitive evaluation theory, we investigate gamified MRDs with certain or chance-based rewards and contrast them to non-gamified MRDs with certain rewards in user registration systems. Our results from a multi-method approach encompassing the complementary features of a randomised field experiment (N = 651) and a randomised online experiment (N = 330) demonstrate differential effects of the three investigated MRDs on user registration. Visitors encountering either type of gamified MRD are more likely to register than those encountering a non-gamified MRD. Moreover, gamified MRDs with chance-based rewards have the highest likelihood of user registrations. We also show that MRDs have distinct indirect effects on user registration via anticipated experiences of competence and sensation. Overall, the paper offers theoretical insights and practical guidance on how and why gamified MRDs are effective for e-tailers. Collapse

Topics: website electronic mail electronic commerce gamification website design

Methods: experiment randomized field experiment survey experimental task mixed method

Theories: cognitive evaluation theory self determination theory

D&L: A Natural Language Processing Based Approach for Protecting Sensitive Information from Shoulder Surfing Attacks

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Aldossari, Marran; Zhang, Dongsong

Abstract: Despite the increasing attention and research effort, how to protect sensitive ... Expand

Abstract: Despite the increasing attention and research effort, how to protect sensitive information from shoulder surfing attacks is still under studied. Existing methods for protecting sensitive textual content on users' screens from shoulder surfing attacks have various limitations, including ineffectiveness, insufficient protection of sensitive information, low usability, and high cognitive workload. To address those limitations, this paper proposes, develops, and evaluates a new solution called "detection and labeling" (D&L), which uses NLP techniques to automatically detect and label sensitive information in the textual content. The labeled and hidden sensitive information is then read to users through their headphones upon their clicking a label. Evaluation results demonstrate that D&L improves protection, enhances usability, reduces users' cognitive workload, and allows faster browsing speed compared to the baseline methods. Collapse

Topics: electronic mail laptop computer usability privacy perceived ease of use

Methods: survey parametric test experiment Tukey HSD for post poc analysis ANOVA

Towards a thematic dimensional framework of online fraud: An exploration of fraudulent email attack tactics and intentions

2023 | Decision Support Systems | Citations: 1

Authors: Bera, Debalina; Ogbanufe, Obi; Kim, Dan J.

Abstract: Despite anti-phishing filters, social engineering-based cyber-attacks still resu ... Expand

Abstract: Despite anti-phishing filters, social engineering-based cyber-attacks still result in billions of dollars lost annually, significant personal identity theft, loss of corporate secrets, and espionage. We review the phishing literature on psychological attacks and design tactics employed for deception by attackers. The result reveals the need to continuously identify tactics embedded in fraudulent email content to understand why users still fall prey to phishing attacks. Using the literature as a backdrop, we identify and conceptualize a thematic dimensional framework of fraudulent phishing attacks. This study uses benchmark datasets of fraudulent email to empirically validate the proposed dimensional framework. Specifically, a combination of machine learning-based content analysis and topic modeling found a majority of the discovered topics were labeled against the proposed di­ mensions. Statistical analysis was employed to provide empirical evidence of the thematic dimensions of fraudulent email attacks. This study thus, not only extends the cybersecurity literature by identifying and vali­ dating eight dimensions that enrich our understanding of phishing and attack identification but stimulates cu­ mulative research endeavors to develop yet more comprehensive dimensional frameworks of phishing email attacks. Collapse

Topics: phishing email phishing electronic mail email spam personalization

Methods: term frequency–inverse document frequency natural language processing topic model discriminant analysis literature study

The “holiday effect” in consumer satisfaction: Evidence from review ratings

2023 | Information & Management | Citations: 0

Authors: Deng, Lingfei; Ye, Qiang; Xu, DaPeng; Sun, Fangfang

Abstract: This study explores whether and how a holiday effect exists in consumers’ review ... Expand

Abstract: This study explores whether and how a holiday effect exists in consumers’ review rating behavior, which is well explained by expectancy-disconfirmation theory (EDT). After utilizing the secondary data of online restaurant reviews and conducting an online experiment, we find that consumers have the tendency to form high expec­ tations before holidays, thus leading to more negative disconfirmation and bad moods, which finally induce their negative review rating behavior on holidays. The consumer heterogeneity analyses provide evidence that con­ sumers who are tourists, tourists with less travel experience, and male natives are more likely to post lower review ratings on holidays. Collapse

Topics: online review service quality user-generated content consumer behavior website

Methods: experiment experimental group regression analysis method product review survey

Rising Above vs. Falling Below: When and Why Status Change Affects Interpersonal Helping in Workgroups

2023 | Organization Science | Citations: 0

Authors: Doyle, Sarah P.; Lount, Robert B.

Abstract: The current research sheds new light on how and why status hierarchies impact in ... Expand

Abstract: The current research sheds new light on how and why status hierarchies impact interpersonal helping by examining people’s reactions to recently experienced status change. Specifically, we incorporate findings from research on the self-serving attributional bias to theorize about how the direction of status change (i.e., a gain or a loss) can shape the extent to which people accept or deflect personal responsibility for their change in status, which we argue will then impact other-concern and, thus, their willingness to help. Further, we identify status change legitimacy as a key contingency that will strengthen or weaken the psychological and behavioral effects of status change. Among firefighter teams (Study 1), participants in the laboratory (Studies 2 and 3), and student teams (Study 4), we show that (1) status change impacts interpersonal helping through its impact on changes in other-concern and (2) status change legitimacy moderates the effect of status change on both other-concern and interpersonal helping. Additionally, we document an asymmetry with regards to the effects of status change on both other-concern and helping behavior (i.e., with the negative impact of a status loss being stronger than the positive impact of a status gain). Theoretical and practical implications are discussed. Collapse

Topics: team productivity missing data accounting

Methods: survey polynomial regression parametric test survey design two-way ANOVA

Promoting Learning Through Explainable Artificial Intelligence: An Experimental Study in Radiology

2023 | International Conference on Information Systems | Citations: 0

Authors: Ellenrieder, Sara; Kallina, Emma; Pumplun, Luisa; Gawlitza, Joshua Felix; Ziegelmayer, Sebastian; Buxmann, Peter

Abstract: The deployment of machine learning (ML)-based decision support systems (DSSs) i ... Expand

Abstract: The deployment of machine learning (ML)-based decision support systems (DSSs) in high-risk environments such as radiology is increasing. Despite having achieved high decision accuracy, they are prone to errors. Thus, they are primarily used to assist radiologists in their decision making. However, collaborative decision making poses risks to the decision maker, e.g. automation bias and long-term performance degradation. To address these issues, we propose combining findings of the research streams of explainable artificial intelligence and education to promote human learning through interaction with ML-based DSSs. We provided radiologists with explainable vs nonexplainable decision support that was high-vs low-performing in a between-subject experimental study to support manual segmentation of 690 brain tumor scans. Our results show that explainable ML-based DSSs improved human learning outcomes and prevented false learning triggered by incorrect decision support. In fact, radiologists were able to learn from errors made by the low-performing explainable ML-based DSS. Collapse

Topics: decision support system decision support explainable artificial intelligence decision making artificial intelligence

Methods: experiment qualitative interview magnetic resonance imaging parametric test ANOVA

Collateral Damage: The Relationship Between High-Salience Events and Variation in Racial Discrimination

2023 | Organization Science | Citations: 0

Authors: Gorbatai, Andreea; Younkin, Peter; Burtch, Gordon

Abstract: To what extent are individual or organizational biases affected by racially sali ... Expand

Abstract: To what extent are individual or organizational biases affected by racially salient events? We propose that acts of discrimination and the individual biases that undergird them are sensitive to high-salience events and will oscillate with the salience of the focal attribute. In short, that the propensity to discriminate reflects both individual and environmental differences, and therefore a given person may become more prone to discriminate in the aftermath of a high-salience event. We test our hypothesis in three online experiments that examine how varying the salience of race affects the evaluation of in-group or out-group founders. We find that respondents evaluate their in-group members more favorably, and out-group members less favorably, when exposed to a high-salience event, which translates into a significant disadvantage for the minority (African American) group. We complement these studies with an assessment of how police shootings affect fundraising outcomes on Kickstarter to confirm the external validity of our findings. Together, these studies indicate that racially salient events depress the quality evaluations and success odds of African American entrepreneurs relative to others. Hence, discrimination levels can be affected by salient yet unrelated events, and such events are consequential for the economic fortunes of individuals belonging to minority and disadvantaged groups.History: This paper has been accepted for the Organization Science Special Issue on Experiments in Organizational Theory.Supplemental Material: The online appendices are available at https://doi.org/10.1287/orsc.2021.1527. Collapse

Topics: crowdfunding crowdsourcing website criminality application programming interface

Methods: experiment parametric test statistical hypothesis test survey facial recognition system

CONVERSATIONAL AGENTS WITH VOICE: HOW SOCIAL PRESENCE INFLUENCES THE USER BEHAVIOR IN MICROLENDING DECISIONS

2023 | European Conference On Information Systems | Citations: 0

Authors: Heßler, Pascal; Pfeiffer, Jella; Unfried, Matthias

Abstract: This paper investigates how social cues, used to anthropomorphize assistance sy ... Expand

Abstract: This paper investigates how social cues, used to anthropomorphize assistance systems (ASs), like conversational agents, influences the behavior of users. We find that anthropomorphizing, in our case by giving them a voice, increases social presence, and, in turn, empathy and trust. Yet, we argue that social presence also has negative impacts. We propose-and empirically proof-that a higher social presence also leads to a stronger feeling of being observed. This, in contrary to our hypothesis, results in lower investments. In addition, we found a trend of higher enjoyment with increasing feeling of being observed. This result emphasis the complexity of creating and designing ASs. Through the invocation of social presence anthropomorphizing might have negative and positive effects on outcome variables. Collapse

Topics: social presence user behavior conversational agent website web page

Methods: experiment partial least squares path modeling parametric test survey descriptive statistic

Can Conversations on Reddit Forecast Future Economic Uncertainty? An Interpretable Machine Learning Approach

2023 | International Conference on Information Systems | Citations: 0

Authors: Jiang, Jinhang; Feng, Mei; Srinivasan, Karthik

Abstract: In recent years, social media has become an indispensable source of information ... Expand

Abstract: In recent years, social media has become an indispensable source of information through which public attitudes, opinions, and concerns can be studied and quantified. This paper proposes an interpretable machine learning framework for predicting the Equity Market-related Economic Uncertainty Index using features generated from a popular discussion forum on Reddit. Our framework consists of a series of custom preprocessing and analytics methods, including BERTopic for latent topic identification and regularized linear models. Using our framework, we evaluate explanatory models with different configurations over a large corpus of Reddit posts belonging to the personal finance category. Our analysis generates valuable insights about discussion topics on Reddit and their efficacy in accurately predicting future economic uncertainty. The study demonstrates the potential of using social media data and interpretable machine learning to inform economic forecasting research. Collapse

Topics: Reddit social media explainable artificial intelligence Python permutation feature importance

Methods: descriptive statistic time series analysis longitudinal research topic model experiment

Seeking Information Using Search Engines: The Impact of Negation on Judgments

2023 | Communications of the Association for Information Systems | Citations: 0

Authors: Kayhan, Varol; Warkentin, Merrill

Abstract: We examine how online searches lead to judgment formation in two contexts where ... Expand

Abstract: We examine how online searches lead to judgment formation in two contexts where statements are negated differently. In one context, a statement (of the form "if P then Q") is negated using "not" (as in "if P then not Q"), while in the other context, it is negated using a different term or phrase (as in "if P then R"). We show that online searches to find information about the validity of this statement generate different results in these contexts. Our findings contribute to extant work on online searches by suggesting that when individuals test the validity of a statement using search engines, their searches lead to categorically different results contingent on the search context. From a practical standpoint, we make recommendations to search engine developers and content providers so online searches generate more inclusive results. Collapse

Topics: search engine Google+ web page decision making accounting

Methods: experiment blood pressure experimental task statistical hypothesis test analysis of covariance