AI Washing: The Framing Effect of Labels on Algorithmic Advice Utilization

2023 | International Conference on Information Systems | Citations: 0

Authors: Leffrang, Dirk; Mueller, Oliver

Abstract: Many researchers and practitioners see artificial intelligence as a game change ... Expand

Abstract: Many researchers and practitioners see artificial intelligence as a game changer compared to classical statistical models. However, some software providers engage in "AI washing", relabeling solutions that use simple statistical models as AI systems. By contrast, research on algorithm aversion unsystematically varied the labels for advisors and treated labels such as "artificial intelligence" and "statistical model" synonymously. This study investigates the effect of individual labels on users' actual advice utilization behavior. Through two incentivized online within-subjects experiments on regression tasks, we find that labeling human advisors with labels that suggest higher expertise leads to an increase in advice-taking, even though the content of the advice remains the same. In contrast, our results do not suggest such an expert effect for advice-taking from algorithms, despite differences in self-reported perception. These findings challenge the effectiveness of framing intelligent systems as AI-based systems and have important implications for both research and practice. Collapse

Topics: artificial intelligence decision making individual characteristic user experience user behavior

Methods: computational algorithm experiment survey longitudinal research within subject experiment

Powerlessness Also Corrupts: Lower Power Increases Self-Promotional Lying

2023 | Organization Science | Citations: 0

Authors: Li, Huisi (Jessica); Chen, Ya-Ru; Hildreth, John Angus D.

Abstract: The popular maxim holds that power corrupts, and research to date supports the v ... Expand

Abstract: The popular maxim holds that power corrupts, and research to date supports the view that power increases self-interested unethical behavior. However, we predict the opposite effect when unethical behavior, specifically lying, helps an individual self-promote: lower rather than higher power increases self-promotional lying. Drawing from compensatory consumption theory, we propose that this effect occurs because lower power people feel less esteemed in their organizations than do higher power people. To compensate for this need to view themselves as esteemed members of their organizations, lower power individuals are more likely to inflate their accomplishments. Evidence from four studies supports our predictions: compared with those with higher power, executives with lower power in their organizations were more likely to lie about their work achievements (Study 1, n = 230); graduate students with lower power in their Ph.D. studies were more likely to lie about their publication records (Study 2, n = 164); and employees with lower power were more likely to lie about having signed a business contract (Studies 3 and 4). Mediation analyses suggest that lower power increased lying because lower power individuals feel lower esteem in their organizations (Study 3, n = 562). Further supporting this mechanism, a self-affirmation intervention reduced the effect of lower power on self-promotional lying (Study 4, n = 536). These converging findings show that, when lies are self-promotional, lower power can be more corruptive than higher power. Collapse

Topics: anonymity consumer behavior missing data electronic mail website

Methods: survey mediation analysis parametric test chi squared test survey design

Theories: self construal theory

The puzzle of experience vs. memory: Peak-end theory and strategic gamification design in M-commerce

2023 | Information & Management | Citations: 0

Authors: Li, Manning; Jiang, Zhenhui (Jack); Ma, Guanghui

Abstract: As businesses increasingly use gamified mobile marketing campaign (GMMC) systems ... Expand

Abstract: As businesses increasingly use gamified mobile marketing campaign (GMMC) systems to engage mobile shop­ pers, gamification in m-commerce systems warrants more attention in both IS research and design practices. Inspired by peak-end theory, this study focused on the puzzling differences between user experience vs. memory and empirically examined the impact of different experience orders of cognitive load on user perceptions and behavioral intentions. Overall, the outcomes of this research suggest that appropriate applications of the peakend effect, moderated via users’ regulatory focus styles, can alleviate the negative mental utility imagery of users, reducing their perceived uncertainties and opt-out intentions from the GMMC. Important implications for research and practice are then discussed. Collapse

Topics: electronic data interchange marketing management user experience gamification systems design

Methods: experiment electroencephalography survey multivariate analysis of variance survey design

Theories: technology acceptance model flow theory self determination theory theory of planned behavior

Between Attention and Portfolio Adjustment: Insights from Machine Learning-based Risk Preference Assessment

2023 | International Conference on Information Systems | Citations: 0

Authors: Li, Xin; Rai, Arun; Song, Qingping; Xu, Sean Xin

Abstract: Financial firms recommend products to customers, intending to gain their attent ... Expand

Abstract: Financial firms recommend products to customers, intending to gain their attention and change their portfolios. Based on behavioral decision-making theory, we argue attention's effect on portfolio adjustment is through the risk deviation between portfolio risk and their risk preference. Thus, to fully understand the adjustment process, it is necessary to assess customers' risk preferences. In this study, we use machine learning methods to measure customers' risk preferences. Then, we build a dynamic adjustment model and find that attention's impact on portfolio adjustment speed is stronger when customers' risk preference is higher than portfolio risk (which needs an upward adjustment) and when customers' risk preference is within historical portfolio risk experience. We conducted a field experiment and found that directing customers' attention to products addressing the risk deviation would lead to more portfolio adjustment activities. Our study illustrates the role of machine learning in enhancing our understanding of financial decision-making. Collapse

Topics: decision making analytical information system electronic finance web page online banking

Methods: field experiment experimental group machine learning XGBoost digital trace data

Beyond the First Offer: Decoding Negotiation Openings and Their Impact on Economic and Subjective Outcomes

2023 | Group Decision and Negotiation | Citations: 0

Authors: Lipp, Wolfram E.; Smolinski, Remigiusz; Kesting, Peter

Abstract: First offers play a significant role in negotiations as they anchor negotiators’ ... Expand

Abstract: First offers play a significant role in negotiations as they anchor negotiators’ perceptions and influence negotiation outcomes in favor of the first-offer proposer. However, negotiation is a joint decision-making process in which a first offer is typically succeeded by a counteroffer. The impact of a counteroffer has not yet been systematically researched. We propose that a counteroffer influences negotiation outcomes like a first offer. In addition, we conceptualize the “anchor zone” as the distance between the first offer and the counteroffer. We theorize that the anchor zone influences negotiation outcomes because it captures additional information compared to a single offer. To test our hypotheses, we conducted two studies: Study 1 was a vignette study (n = 190) in which participants reacted to a counteroffer that they received based on their first offer as part of a simulated negotiation. Study 2 was an online experiment (n = 212) in which participants negotiated by exchanging offers with no further communication. Our analysis suggests that the counteroffer is a significant predictor of economic outcomes. Thus, it works like a first offer, but with a lower impact. In addition, the anchor zone predicted how far the final agreement was from the first offer. Furthermore, we found that the third offer, the average concessions, and the number of offers mediated the effects of the counteroffer and anchor zone on economic outcomes. Finally, we discovered that a more aggressive counteroffer reduced the subjective value of both negotiators. Collapse

Topics: Apple iPhone decision making data quality

Methods: experiment statistical hypothesis test simulation statistical power analysis regression analysis method

Theories: behavioral economics

The Negative Spillover Effect of Electronic Prescribing for Controlled Substances (EPCS) on Opioid Epidemic

2023 | International Conference on Information Systems | Citations: 0

Authors: Liu, Xiaoyu; Kyung, Nakyung

Abstract: ... Expand

Abstract: Collapse

Topics: electronic prescription pandemic health information system

Methods: experimental group longitudinal research difference in differences quantitative observational study propensity score matching

When and Why Consumers Respond to Online Privacy Violations

2023 | HICSS | Citations: 1

Authors: Tran, Chi; Reich, Brandon; Yuan, Hong

Abstract: As consumer privacy concerns become paramount, it is increasingly critical to un ... Expand

Abstract: As consumer privacy concerns become paramount, it is increasingly critical to understand what constitutes a privacy violation and how consumers respond. Using a multi-method approach, this research shows that consumers perceive three privacy violation types with increasing levels of severity, explaining when and why consumers exhibit seemingly paradoxical responses to different violation types. Our theorizing and findings suggest that resource control is the predominant mechanism driving privacy behavior, and that situation controllability (operationalized as level of variability of privacy practices within the industry) may moderate its effects. ***Disclosure: An earlier version of this work was submitted and accepted to HICSS last year but was later withdrawn as the authors were unable to attend the conference due to extenuating circumstances. Thanks to the reviews provided by the conference committee last year, we were able to revise and update new analyses and studies in our empirical package in this submission. Collapse

Topics: privacy Twitter Facebook data breach privacy behavior

Methods: qualitative content analysis theory development mixed method experiment parametric test

Theories: self determination theory

Using blockchain to signal quality in the food supply chain: The impact on consumer purchase intentions and the moderating effect of brand familiarity

2023 | International Journal of Information Management | Citations: 0

Authors: Treiblmaier, Horst; Garaus, Marion

Abstract: Food safety is a public health issue of paramount importance. In this regard, bl ... Expand

Abstract: Food safety is a public health issue of paramount importance. In this regard, blockchain has emerged as a promising technology that allows users to effectively and efficiently record the origin and flow of products and eliminate or reduce harmful food fraud. Consumers can benefit from this development by receiving up-to-date and verifiable information about the origins and delivery routes of their purchases. Drawing on signaling the­ ory and the results of two experimental studies with 151 and 152 participants, respectively, we investigate how the use of blockchain to trace food products impacts consumers’ perception of product quality as a mediating variable and subsequently their purchase intention. Our framework further considers brand familiarity as a moderating variable. The findings from the two experiments show that blockchain labels as a signaling mech­ anism in food supply chains help to strengthen consumers’ perceived quality of food products, which, in turn, increases their purchase intention. This effect is more pronounced for less familiar brands, which is valuable information for managers who want to build a brand’s reputation. From an academic perspective, we highlight the applicability of signaling theory to identify blockchain-based traceability systems as important drivers of perceived product quality and consequently purchase intention. Collapse

Topics: blockchain supply chain management marketing management supply chain management system systems design

Methods: experiment survey mediation analysis chi squared test experimental group

Theories: signaling theory

How product review voting is influenced by existing votes, consumer involvement, review valence, and review diagnosticity

2023 | Decision Support Systems | Citations: 0

Authors: Tseng, Shih-Lun; Lu, Shuya; Weathers, Danny; Grover, Varun

Abstract: Websites that allow consumers to post online reviews often allow others to signa ... Expand

Abstract: Websites that allow consumers to post online reviews often allow others to signal the value of the reviews by voting for them as being helpful (i.e., an upvote) or unhelpful (i.e., a downvote). Although a review's content should drive votes, herd behavior may also be operative if consumers discount their own judgments of the review based on signals others provide. Using a field study of online product reviews from Amazon, a longitudinal experiment, and two cross-sectional experiments, we find evidence for herd behavior: consumers' voting de­ cisions and intentions are influenced by others' votes. However, this effect is complex with multiple moderating factors, including consumer involvement, review valence, and review diagnosticity. We discuss the theoretical and practical implications of these findings for reducing the potential negative effects of herd behavior in the context of online reviews. Collapse

Topics: online review Reddit Twitter electronic commerce user-generated content

Methods: computational algorithm longitudinal research longitudinal experiment statistical hypothesis test parametric test

Theories: signaling theory

CATCHM: A novel network-based credit card fraud detection method using node representation learning

2023 | Decision Support Systems | Citations: 0

Authors: Van Belle, Rafaël; Baesens, Bart; De Weerdt, Jochen

Abstract: Advanced fraud detection systems leverage the digital traces from (credit-card) ... Expand

Abstract: Advanced fraud detection systems leverage the digital traces from (credit-card) transactions to detect fraudulent activity in future transactions. Recent research in fraud detection has focused primarily on data analytics combined with manual feature engineering, which is tedious, expensive and requires considerable domain expertise. Furthermore, transactions are often examined in isolation, disregarding the interconnection that exists between them. Collapse

Topics: fraud detection credit card fraud privacy business process management electronic mail

Methods: computational algorithm experiment machine learning feature engineering literature study