Introduction to the Minitrack on Explainable Artificial Intelligence (XAI)

2023 | HICSS | Citations: 0

Authors: Abedin, B.; Meske, C.; Rabhi, F.; Klier, M.

Abstract: Artificial Intelligence (AI) already reached or even surpassed the task perform ... Expand

Abstract: Artificial Intelligence (AI) already reached or even surpassed the task performance of humans in various domains. However, most AI systems are still "black boxes" that are difficult to comprehend -not only for developers, but also for users and decision-makers. Explainable Artificial Intelligence (XAI) is aimed at intelligent systems that are highly performant to enable their users to understand, appropriately trust, and scrutinize them. Collapse

Topics: explainable artificial intelligence artificial intelligence

Methods: experiment structured literature research

Input control and its signalling effects for complementors' intention to join digital platforms

2023 | Information Systems Journal | Citations: 2

Authors: Adam, Martin; Croitor, Evgheni; Werner, Dominick; Benlian, Alexander; Wiener, Martin

Abstract: Existing information systems (IS) research on platform control has largely focus ... Expand

Abstract: Existing information systems (IS) research on platform control has largely focused on examining how input control (i.e., the mechanisms used to control platform access) affects complementors' intentions and behaviours after their decision to join a digital platform. Yet, our understanding of how input control is perceived before this decision and how such perceptions influence prospective complementors' intention to join a platform is still nascent. In this regard, our study views input control as a salient signal that shapes prospective complementors' expected benefits and costs (i.e., their performance and effort expectancy), and ultimately their decision to join a digital platform. Drawing on signalling theory and the antecedent-benefit-cost (ABC) framework, we conducted a randomized online experiment in the context of donation-based crowdfunding. The experiment results offer empirical support for this view by showing that input control has distinct and complex signalling effects for prospective complementors. In particular, our findings reveal curvilinear and competing signalling effects, with perceived input control increasing both performance expectancy (at a decreasing rate) and effort expectancy (at an increasing rate). Also, we find that performance expectancy linearly increases prospective complementors' intention to join a platform, whereas effort expectancy linearly decreases their intention to do so. These findings imply that the overall relationship between perceived input control and intention to join follows an inverted U-shape curve, which means that neither a low nor a high, but a moderate degree of perceived input control maximizes prospective complementors' intention to join. In sum, the results of our study provide novel and important insights into the signalling role that perceived input control plays in shaping prospective complementors' decision to join a digital platform. Collapse

Topics: digital platform crowdsourcing crowdfunding behavioral intention digital ecosystem

Methods: experiment mediation analysis survey survey design theory development

Theories: signaling theory

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

Differential Impact of Content in Online Communication on Heterogeneous Candidates: A Field Study in Technical Recruitment

2023 | Information Systems Research | Citations: 0

Authors: Aggarwal, Rohit; Lee, Michael J.; Midha, Vishal

Abstract: Recruitment is a critical activity for companies, and the research community has ... Expand

Abstract: Recruitment is a critical activity for companies, and the research community has also shown significant interest in examining technology recruitment. Companies often communicate how they value their employees along with job requirements to potential candidates in a bid to attract them. However, there is an overall lack of understanding of how candidates react to such information and how their motivation toward the job changes with such online communication. Although there is substantial work that examines the decision-making process of managers who do technical hiring, to the best of our knowledge, there is a paucity of work that investigates the decision-making process of technical candidates. The broad research question studied is how including certain content in online communication about a technical job opportunity may (de)motivate heterogeneous candidates differently in applying for the job. We theorize the underlying process of how including certain content in online job communication may influence candidates’ propensity to apply and their minimum acceptable salary increase if they were to join the company. Additionally, we capture mediating variables that influence the effect of different online content on candidates’ propensity to apply and on candidates’ minimum acceptable salary increase. By testing actual job application behavior in a field study, we confirmed the content that can attract high performers while discouraging low performers from applying.History: Yong Tan, Senior Editor; Yan Huang, Associate Editor.Supplemental Material: The online appendices are available at https://doi.org/10.1287/isre.2022.1120. Collapse

Topics: social media electronic mail IS economics economic surplus IT workforce

Methods: experimental group survey field study factor analysis descriptive statistic

Theories: motivation theory

An Investigation of Domain-based Social Influence on ChatGPT-Related Twitter Data

2023 | International Conference on Information Systems | Citations: 0

Authors: Ahangama, Supunmali

Abstract: ... Expand

Abstract: Collapse

Topics: Twitter social influence social media social identity robotic

Methods: chatGPT sentiment analysis multiple linear regression term frequency–inverse document frequency NLTK

Design Science Research: Progression, Schools of Thought and Research Themes

2023 | DESRIST | Citations: 0

Authors: Akoka, Jacky; Comyn-Wattiau, Isabelle; Storey, Veda C.

Abstract: Design science research, a well-established research approach to solving complex ... Expand

Abstract: Design science research, a well-established research approach to solving complex real-world problems, has evolved over time. This research characterizes design science research in information systems. By performing a bibliometric analysis, we show that design science research has progressed in the information systems field through three main phases, which we call periods of inquiry. A co-citation analysis shows that the progression has been largely influenced by a few main pioneering studies, leading to three schools of thought. Bibliographic coupling analysis suggests that research in design science can be classified into several distinct intellectual areas corresponding to different research themes. This bibliometric analysis proposes a broad viewpoint of design science and design research, serving as a basis for shaping further research. Collapse

Topics: blockchain database system

Methods: design science co-citation analysis literature sample bibliometric analysis cluster analysis

THE IMPACT OF ONLINE ADVERTISMENT PERSONALIZATION AND TRANSPARENCY ON INDIVIDUAL DEFENSIVE RESPONSES AND ENGAGMENT

2023 | European Conference On Information Systems | Citations: 0

Authors: Al Helaly, Yasser; Dhillon, Gurpreet; Oliviera, Tiago

Abstract: This study identifies the different individual defensive responses that are tri ... Expand

Abstract: This study identifies the different individual defensive responses that are triggered by ad personalization. We investigate how these responses impact user engagement behavior on social media. The study also examines the role of transparency in advertising and the perceived benefits of personalization on user engagement in Europe. To conduct our study, we are theoretically grounded in the defensive response model. A multi-step quantitative approach constituting two experiments and a survey is used. With 154 and 199 participants each, the experiments allowed us to define the theoretical model. The experiment identified paradoxical findings. We indent surveying online ads-users to examine the impact of personalization on individual defensive responses and the role transparency plays in predicting user engagement. Our research contributes to the theory by identifying defensive responses that explain the engagement behavior, and the impact of transparency on personalized advertising. Collapse

Topics: personalization usability Facebook social media privacy

Methods: experiment survey Student's t-test statistical hypothesis test parametric test

Self-Building Artificial Intelligence and Machine Learning to Empower Big Data Analytics in Smart Cities

2023 | Information Systems Frontiers | Citations: 0

Authors: Alahakoon, Damminda; Nawaratne, Rashmika; Xu, Yan; De Silva, Daswin; Sivarajah, Uthayasankar; Gupta, Bhumika

Abstract: The emerging information revolution makes it necessary to manage vast amounts of ... Expand

Abstract: The emerging information revolution makes it necessary to manage vast amounts of unstructured data rapidly. As the world is increasingly populated by IoT devices and sensors that can sense their surroundings and communicate with each other, a digital environment has been created with vast volumes of volatile and diverse data. Traditional AI and machine learning techniques designed for deterministic situations are not suitable for such environments. With a large number of parameters required by each device in this digital environment, it is desirable that the AI is able to be adaptive and self-build (i.e. self-structure, self-configure, self-learn), rather than be structurally and parameter-wise pre-defined. This study explores the benefits of self-building AI and machine learning with unsupervised learning for empowering big data analytics for smart city environments. By using the growing self-organizing map, a new suite of self-building AI is proposed. The self-building AI overcomes the limitations of traditional AI and enables data processing in dynamic smart city environments. With cloud computing platforms, the self-building AI can integrate the data analytics applications that currently work in silos. The new paradigm of the self-building AI and its value are demonstrated using the IoT, video surveillance, and action recognition applications. Collapse

Topics: artificial intelligence smart city big data cloud computing distributed system

Methods: computational algorithm experiment unsupervised learning machine learning longitudinal research

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

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

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

Accepting the Familiar: The Effect of Perceived Similarity with AI Agents on Intention to Use and the Mediating Effect of IT Identity

2023 | HICSS | Citations: 0

Authors: Alawi, N.; De Vreede, T.; De Vreede, G.

Abstract: With the rise and integration of AI technologies within organizations, our unde ... Expand

Abstract: With the rise and integration of AI technologies within organizations, our understanding of the impact of this technology on individuals remains limited. Although the IS use literature provides important guidance for organization to increase employees' willingness to work with new technology, the utilitarian view of prior IS use research limits its application considering the new evolving social interaction between humans and AI agents. We contribute to the IS use literature by implementing a social view to understand the impact of AI agents on an individual's perception and behavior. By focusing on the main design dimensions of AI agents, we propose a framework that utilizes social psychology theories to explain the impact of those design dimensions on individuals. Specifically, we build on Similarity Attraction Theory to propose an AI similarity-continuance model that aims to explain how similarity with AI agents influence individuals' IT identity and intention to continue working with it. Through an online brainstorming experiment, we found that similarity with AI agents indeed has a positive impact on IT identity and on the intention to continue working with the AI agent. Collapse

Topics: artificial intelligence usage intention behavioral intention brainstorming usability

Methods: chatbot experiment survey descriptive statistic statistical hypothesis test

Theories: social psychology theory