I Tell You What You Want, What You Really Really Want: Digital Information Nudging as a Bridge towards a Sustainable Purchase Decision

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Peters, Leonore; Wieland, Désirée

Abstract: The importance of sustainability seems to be ingrained in most consumers' minds ... Expand

Abstract: The importance of sustainability seems to be ingrained in most consumers' minds by now, yet this is not always reflected in consumers' consumption behavior. We suggest nudging as an instrument to close the gap between green consciousness and purchase decision in an environment influenced by technostress. The results, based on an experimental study with 201 participants, show that information nudging in ecommerce is a useful tool to close this gap, but that the effect is significantly weakened with increasing levels of technostress, especially in combination with an already existing high green purchase intention, suggesting cognitive strain, e.g. due to information overload. Our study contributes to the e-commerce and consumer psychology literature and extends the research by showing how digital information nudging in combination with perceived technostress in online shopping situations influence consumers' purchase decisions with respect to sustainable products. Collapse

Topics: technostress electronic commerce website design information overload decision making

Methods: survey factor analysis regression analysis method experiment SEM tool

Theories: theory of reasoned action

Impact of Open-Source Community on Cryptocurrency Market Price: An Empirical Investigation

2023 | Journal of Management Information Systems | Citations: 0

Authors: Petryk, Mariia; Qiu, Liangfei; Pathak, Praveen

Abstract: Although the prices of cryptocurrencies remained volatile for the past decade, t ... Expand

Abstract: Although the prices of cryptocurrencies remained volatile for the past decade, the factors that impact the price dynamics of the new type of investment instrument have not been fully identified yet. In this study, we recognize the dual nature of cryptocurrencies, that is, being a software program and a financial instrument, and examine the impact of software advancement on the price dynamics of cryptocurrencies. The open-source software (OSS) platform functionality enables social behaviors that we use as signals. Using data from the largest OSS platform, we establish the connection between open-source activities and the price movement of cryptocurrency. In particular, as project popularity (forks and watches) and users' feedback (issues) increase, the market price increases by 4.3 percent, 2.4 percent, and 4.4 percent per annum, respectively. On the contrary, the number of code corrections (pull requests) is negatively related to prices leading to a 5 percent annual price decrease. Our results suggest that OSS contributions create a perfect selection mechanism, where higher quality projects receive more developers' attention and user feedback, whereas lower quality projects do not, thus creating the separating equilibrium. Collapse

Topics: cryptocurrency open source IT project systems development system quality

Methods: instrumental variables estimation longitudinal research computational algorithm theory development autocorrelation analysis

Theories: lemon market theory signaling theory

Is it Your Fault? Framing Social Media Inclusion and Exclusion Using Just World Theory

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

Authors: Petter, Stacie; Giddens, Laurie

Abstract: Individuals who have experienced harm (also known as victims) by people, organi ... Expand

Abstract: Individuals who have experienced harm (also known as victims) by people, organizations, or adverse events sometimes use social media to share their experiences with others, search for information, and find social support. While some observers offer support and engage in inclusion toward victims on social media, other observers blame victims for their plight and participate in revictimization and exclusion. Victim blaming, which can lead to social exclusion, disproportionately impacts those in society who are already at risk for exclusion and may perpetuate existing racial, ethnic, gender, and economic inequalities. This research provides a theoretical framework to identify reasons why observers engage in such wide-ranging responses to victims on social media. Specifically, we consider social inclusion and exclusion at the confluence of a social phenomenon (victim blaming), a theory (just world theory), and an information technology artifact (social media) among a specific type of actor (observers). Our theoretical framework of social media inclusion and exclusion is informed by just world theory and considers how social media functionalities can promote social media inclusion or exclusion. We also offer research questions to stimulate future research related to social media inclusion, social media exclusion, and just world theory.Stacie Petter is the Citibank/Calloway Fellow and a professor of management information systems at the Wake Forest University School of Business. Much of her research focuses on the impacts of information systems on individuals, organizations, and society, including how information technology can be used to counter human trafficking, how gamification can provide value in organizational settings, and how and why individuals use information technology for their personal or professional needs. Her work has appeared in outlets such as MIS Quarterly, Collapse

Topics: social media affordance Facebook cyberbullying

Methods: theory development design artifact conceptual modelling survey

Theories: social sciences theory

Algorithmic Fairness in AI

2023 | Business & Information Systems Engineering | Citations: 0

Authors: Pfeiffer, Jella; Gutschow, Julia; Haas, Christian; Möslein, Florian; Maspfuhl, Oliver; Borgers, Frederik; Alpsancar, Suzana

Abstract: ... Expand

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Topics: artificial intelligence decision making IT security digital service price management

Methods: machine learning generalized linear model

Explanatory Interactive Machine Learning

2023 | Business & Information Systems Engineering | Citations: 1

Authors: Pfeuffer, Nicolas; Baum, Lorenz; Stammer, Wolfgang; Abdel-Karim, Benjamin M.; Schramowski, Patrick; Bucher, Andreas M.; Hügel, Christian; Rohde, Gernot; Kersting, Kristian; Hinz, Oliver

Abstract: The most promising standard machine learning methods can deliver highly accurate ... Expand

Abstract: The most promising standard machine learning methods can deliver highly accurate classification results, often outperforming standard white-box methods. However, it is hardly possible for humans to fully understand the rationale behind the black-box results, and thus, these powerful methods hamper the creation of new knowledge on the part of humans and the broader acceptance of this technology. Explainable Artificial Intelligence attempts to overcome this problem by making the results more interpretable, while Interactive Machine Learning integrates humans into the process of insight discovery. The paper builds on recent successes in combining these two cutting-edge technologies and proposes how Explanatory Interactive Machine Learning (XIL) is embedded in a generalizable Action Design Research (ADR) process – called XIL-ADR. This approach can be used to analyze data, inspect models, and iteratively improve them. The paper shows the application of this process using the diagnosis of viral pneumonia, e.g., Covid-19, as an illustrative example. By these means, the paper also illustrates how XIL-ADR can help identify shortcomings of standard machine learning projects, gain new insights on the part of the human user, and thereby can help to unlock the full potential of AI-based systems for organizations and research. Collapse

Topics: explainable artificial intelligence database system crowdsourcing artificial intelligence cloud computing

Methods: machine learning action design research case study computational algorithm design science

A decision support framework to incorporate textual data for early student dropout prediction in higher education

2023 | Decision Support Systems | Citations: 0

Authors: Phan, Minh; De Caigny, Arno; Coussement, Kristof

Abstract: Managing student dropout in higher education is critical, considering its substa ... Expand

Abstract: Managing student dropout in higher education is critical, considering its substantial impacts on students’ lives, academic institutions, and society as a whole. Using predictive modeling can be instrumental for this task, as a means to identify dropouts proactively on the basis of student characteristics and their academic performance. To enhance these predictions, textual student feedback also might be relevant; this article proposes a hybrid decision support framework that combines predictive modeling with student segmentation efforts. A real-life data set from a French higher education institution, containing information of 14,391 students and 62,545 feedback documents, confirms the superior performance of the proposed framework, in terms of the area under the curve and top decile lift, compared with various benchmarks. In contributing to decision support system research, this study (1) proposes a new framework for automatic, data-driven segmentation of students based on textual data; (2) compares multiple text representation methods and confirms that incorporating student textual feedback data improves the predictive performance of student dropout models; and (3) establishes useful insights to help decision-makers anticipate and manage student dropout behaviors. Collapse

Topics: decision support decision support system electronic mail

Methods: machine learning doc2vec data transformation BERT computational algorithm

The Effectiveness of Highlighting Different Communication Orientations in Promoting Mobile Communication Technology at Work vs. at Home: Evidence from a Field Experiment

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

Authors: Phang, Chee Wei; Fang, Zheng; Liao, Chengcheng

Abstract: With the development of mobile communication technologies, people can now engag ... Expand

Abstract: With the development of mobile communication technologies, people can now engage in seamless communications with family members and coworkers at both home and work. When promoting a new mobile communication technology (e.g., the 5G network), firms may be tempted to emphasize how the technology can strengthen communication both within and across the two domains with the hope of improving purchase rates. Yet research has suggested that people may perceive mobile communication differently depending on whether those they are communicating with others who belong to the same domain. Thus, the promotion of the technology to potential users should perhaps consider users' location domain and their communication targets. Through a field experiment, we show that when promoting mobile communication technology in the home domain, highlighting prevention-focused communication promotes greater purchase rates. However, at work, when coworkers are the target of communication, highlighting promotion-focused communication works better. These findings can not only help practitioners design more effective promotional messages in promoting mobile communication technologies but also contribute to the understanding of nuanced differences in the nature of mobile communication that make it more appealing to users in different within-and cross-domain communication scenarios. Collapse

Topics: communication service infrastructure mobile system broadband cellular network technology adoption global navigation satellite system

Methods: survey field experiment experiment statistical hypothesis test randomized field experiment

Theories: regulatory focus theory work family border theory

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

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

Become a Lifesaver - How to Design Conversational Agents to Increase Users’ Intention to Donate Blood

2023 | International Conference on Information Systems | Citations: 0

Authors: Pietrantoni, Nico; Lichtenberg, Sascha; Morana, Stefan

Abstract: Donating blood is a selfless act that impacts public welfare, potentially savin ... Expand

Abstract: Donating blood is a selfless act that impacts public welfare, potentially saving human lives. However, blood shortage is a rising worldwide issue due to increased demand. Thus, finding ways to animate and motivate potential donors to donate blood is paramount. In this context, conversational agents (CAs) offer a promising approach to educating, promoting, and achieving desired behaviors. In this paper, we conducted an online experimental study (N=303) and investigated the effect of a human-like designed CA and fear-inducing communication on users' intention to donate. Our results show that users' intention is driven by perceived persuasiveness rather than perceived humanness and that fear-inducing communication does not significantly affect the intention to donate. Against this background, we provide numerous theoretical and practical implications, contributing to information system literature by enhancing our understanding of how fear-inducing communication is used in CA interactions. Collapse

Topics: Facebook Messenger health information system social media online chat Google+

Methods: experiment experimental group chatbot descriptive statistic partial least squares regression

Theories: protection motivation theory social response theory social identity theory

The Dual Function of Organizational Structure: Aggregating and Shaping Individuals’ Votes

2023 | Organization Science | Citations: 0

Authors: Piezunka, Henning; Schilke, Oliver

Abstract: How do organizational structures influence organizational decision making? This ... Expand

Abstract: How do organizational structures influence organizational decision making? This article reveals organizational structures’ dual function: they both (1) aggregate and (2) shape individuals’ decisions. What makes this dual function so remarkable is that the two effects are diametrically opposed to one another. Ceteris paribus, a less stringent decision-making structure reduces the amount of support required for a given project to be greenlit at the organizational level, which should result in more investments getting approved. However, we find that this ceteris paribus assumption does not hold, because a less stringent decision-making structure also reduces individuals’ tendency to provide their support for an investment. Our experimental investigation of organizational voting provides evidence for our position that organizational structure plays an important role beyond mere aggregation: voting thresholds also affect individuals’ voting behavior. The combination of both effects explains why the organizational adoption of a new voting threshold may not yield the intended outcome. Funding: This work was supported by a National Science Foundation CAREER Award from the Directorate for Social, Behavioral and Economic Sciences [Grant 1943688] granted to O. Schilke. Supplemental Material: The online appendices are available at https://doi.org/10.1287/orsc.2023.1653. Collapse

Topics: organization structure decision making privacy entrepreneurship organizational context

Methods: Poisson regression experiment survey experimental task regression analysis method

Theories: organizational theory dynamic capabilities theory organizational behavior theory