Introduction to the Minitrack on Design and Appropriation of Knowledge and AI Systems

2023 | HICSS | Citations: 0

Authors: Smolnik, Stefan; Hadaya, Pierre; Holford, W. David

Abstract: The objective of this minitrack is to contribute to the body of knowledge that ... Expand

Abstract: The objective of this minitrack is to contribute to the body of knowledge that helps scholars and practitioners increase their collective understanding of (1) how knowledge and artificial intelligence (AI) systems are planned, designed, built, implemented, used, evaluated, supported, upgraded, and evolved; (2) how knowledge and AI systems impact the context in which they are embedded; and (3) the human behaviors reflected within and induced through both (1) and (2). By knowledge and AI systems, we mean systems in which human participants and/or machines perform work (processes and activities) related to the creation, retention, transfer and/or application of knowledge using information, technology, and other resources to produce informational products and/or services for internal or external customers (adapted from Alter 2008). Such systems may include, but are not limited to, knowledge management systems, decision systems, social media, expert systems, machine learning systems, and other AI systems as well as any other ITenabled knowledge processes.It is the eleventh year of the minitrack. We received six papers this year and after a rigorous review process, we accepted three for publication in the proceedings and online presentation at the conference.The first paper is titled Knowledge Transfer between Humans and Conversational Agents: A Review, Organizing Framework, and Future Directions. Authored by Prakash Chandra Sukhwal, Wei Cui, and Atreyi Kankanhalli, this paper presents a systematic literature review of empirical information system and human-computer interaction studies on the knowledge transfer between humans and conversational agents. After analyzing gathered papers, the authors provide a summary of the current state of empirical research, propose an organizing framework for synthesizing the prior research, identify gaps in understanding, and lay out future research directions on this topic.The second paper is titled Context-Aware Knowledge-based Systems: A Literature Review.Authored by Thi-My-Hang Vu, Thang Le Dinh, Nguyen Anh Khoa Dam, and Cuong Pham-Nguyen, this paper aims to stimulate future works on contextaware knowledge-based systems, by providing an overall synthesis of how to conceptualize and implement context-aware systems, which leverage knowledge-based approaches to provide smart services to users. The authors focus on behavioral (i.e., processes or steps/activities to design and implement a system) and structural aspects (i.e., components of a system), which must be considered in any system conception and design. They arrive at the conclusion that facilitates the conception and design of contextaware knowledge-based systems, a systematic framework, which considers both knowledge management and context-aware design aspects, needs to be further investigated.The third and last paper is titled No ground truth at sea -developing high-accuracy AI decision support for complex environments. Authored by Adrian Bumann, this paper aims to answer the following research questions: What are the challenges in designing a highaccuracy AI-based decision-support tool for a complex context subject to external physical sources of inaccuracy? And how do innovators mitigate these challenges? Drawing upon a rich longitudinal singlecase study on the development of AI decision support for maritime navigation, the author shows that (1) the goal of achieving high output accuracy is complicated by the physical environment hindering training data creation; and (2) developers chose to reduce the output accuracy to successfully situate the AI application in an existing sociotechnical context.We wish to thank all of the authors who submitted work for consideration in this minitrack. We also thank the dedicated reviewers for the time and effort they invested in reviewing the papers. We believe that the accepted papers contribute to furthering our understanding on the creation and appropriation of knowledge and AI systems. We look forward to discussing these further during our sessions in January 2023. Collapse

Topics: artificial intelligence knowledge sharing expert system decision support human computer interaction

Methods: chatbot structured literature research longitudinal research literature sample literature study

Does Technology Matter? How Digital Self-Efficacy Affects the Relationship between ICT Exposure and Job Dissatisfaction

2022 | HICSS | Citations: 0

Authors: Busse, Julian; Busse, Robin; Schumann, Matthias

Abstract: Despite multiple potentials of information and communication technologies (ICT), ... Expand

Abstract: Despite multiple potentials of information and communication technologies (ICT), their increasing diffusion at today’s workplaces may lead to psychological issues for employees, unveiling a dark side of ICT use. Our study aims to examine the association between work-related ICT exposure (i.e. ICT use and digital work intensification) and job dissatisfaction. We further look at the role of digital self-efficacy as a moderator of the effect of digital work intensification. Cross-sectional data from a nationally representative study of 1,145 employees were used in multiple regression analysis. Our results show that higher levels of digital work intensification are associated with higher levels of job dissatisfaction. Further, digital self-efficacy buffers the effect of digital work intensification on job dissatisfaction. Thus, our findings imply that fostering employees’ confidence in their abilities in dealing with the challenges of digitalization promotes employees’ job satisfaction and coping with the negative effects of work-related ICT exposure. Collapse

Topics: IT work self efficacy information system use technostress accounting

Methods: regression analysis method cross sectional research likelihood-ratio test survey self reported survey

The interaction of dark traits with the perceptions of apprehension

2022 | HICSS | Citations: 0

Authors: Gaia, Joana; Murray, David; Sanders, George; Sanders, Sean; Upadhyaya, Shambhu; Wang, Xunyi; Yoo, Chul

Abstract: This paper integrates dark personality traits with the economics of crime and ra ... Expand

Abstract: This paper integrates dark personality traits with the economics of crime and rational choice theories to identify the role that the Dark Triad and thrill-seeking have on the perceptions of being caught engaging in violating privacy laws. Collapse

Topics: criminality Health Insurance Portability and Accountability Act personality information privacy law computer crime

Methods: survey partial least squares regression PLS tool

Theories: rational choice theory

When is enough, enough? An Examination of Student Engagement when Watching Online Group Project Presentations

2022 | HICSS | Citations: 0

Authors: Kumar, Manasvi; Valacich, Joseph; Jenkins, Jeff; Kim, David

Abstract: In traditional face-to-face classes, conventional wisdom suggests that deliverin ... Expand

Abstract: In traditional face-to-face classes, conventional wisdom suggests that delivering and watching group project presentations is a valuable learning experience. In this research, we examine the limits of student engagement and learning in an asynchronous online context. Specifically, 249 undergraduate students were assigned to perform peer evaluations of multiple tenminute project presentations. The online learning platform collected objective viewing behavior for each student, allowing us to use viewing time as a proxy for engagement. We also collected self-reported attitudes towards the assignment, finding that while students value providing feedback, they do not consider it a valuable use of their time. Students who engage more are also likely to receive a better final course grade. Finally, students exhibit different types of viewing behavior (i.e., personas) when evaluating multiple videos. Based on these results, we provide suggestions for improving the design of online group presentation and peer-review assignments. Collapse

Topics: presentation software online learning system virtual teamwork

Methods: survey self reported survey Student's t-test parametric test case study

Theories: theory of bounded rationality

Introduction to the Design and Appropriation of Knowledge and AI Systems Minitrack

2022 | HICSS | Citations: 0

Authors: Smolnik, Stefan; Hadaya, Pierre; Holford, W David

Abstract: ... Expand

Abstract: Collapse

Topics: system support presentation software decision making artificial intelligence

Methods: literature sample

Developing Digitalization Strategies for SMEs: A Lightweight Architecture-based Method

2022 | HICSS | Citations: 0

Authors: Tschoppe, Nils; Drews, Paul

Abstract: Like larger companies, small and medium-sized enterprises (SMEs) need to develop ... Expand

Abstract: Like larger companies, small and medium-sized enterprises (SMEs) need to develop and implement digitalization strategies. These help to address necessary organizational- and technology-related changes in order to create competitive advantages. However, SMEs often face specific challenges, including a lack of IT know-how, relevant market information and appropriate methods for developing a strategy. In this paper, we present a lightweight, architecture-based method including its underlying model for the development and implementation of digitalization strategies in SMEs. It was developed by following the Action Design Research (ADR) method and in cooperation with two medium-sized companies. Rather than adopting highly abstract and complex enterprise architecture (EA) frameworks, we suggest creating easy-to-use visualizations of the enterprise architecture, the business ecosystem and related crosslayer dependencies. While transferring the discipline of EA into the context of digital entrepreneurship, we derived four design principles which help to enrich the theoretical body of knowledge in this research area. Collapse

Topics: information system use digital entrepreneurship enterprise architecture strategic management presentation software

Methods: design principle action design research personal interview

Digital Innovation during COVID-19: Transforming Challenges to Opportunities

2021 | Communications of the Association for Information Systems | Citations: 0

Authors: Chen, Yu; Roldan, Malu

Abstract: The coronavirus disease of 2019 swiftly changed almost all aspects of our live ... Expand

Abstract: The coronavirus disease of 2019 swiftly changed almost all aspects of our lives and society. In this paper, we depict course adjustments that we made to an undergraduate digital innovation course project, called Innovation Farm (IF), in response to the pandemic. Designed as an in-person course project, IF requires students to create AIpowered Android apps to address important social issues. As stay-at-home orders came into effect in March, 2020, we shifted the course to the online modality refocused its student topics to address social issues that COVID-19 has engendered. Accordingly, we also discuss three challenges that we faced and the strategies we employed to cope with them; namely, framing students' social innovation topics in the COVID-19 context, using virtual studios for online groupwork, and hosting a virtual pitch competition. Surprisingly, these strategies not only addressed the challenges but also created unintended benefits and opportunities. We hope to encourage educators to consider the possibilities in transforming challenges to opportunities during these unprecedented times. Collapse

Topics: innovation management video conference pandemic Google+ spreadsheet

Methods: design artifact design methodology

Cloud and edge based data analytics for privacy-preserving multi-modal engagement monitoring in the classroom

2021 | Information Systems Frontiers | Citations: 0

Authors: Preuveneers, Davy; Garofalo, Giuseppe; Joosen, Wouter

Abstract: Learning management systems are service platforms that support the administratio ... Expand

Abstract: Learning management systems are service platforms that support the administration and delivery of training programs and educational courses. Prerecorded, real-time or interactive lectures can be offered in blended, flipped or fully online classrooms. A key challenge with such service platforms is the adequate monitoring of engagement, as it is an early indicator for a student’s learning achievements. Indeed, observing the behavior of the audience and keeping the participants engaged is not only a challenge in a face-to-face setting where students and teachers share the same physical learning environment, but definitely when students participate remotely. In this work, we present a hybrid cloud and edge-based service orchestration framework for multi-modal engagement analysis. We implemented and evaluated an edge-based browser solution for the analysis of different behavior modalities with cross-user aggregation through secure multiparty computation. Compared to contemporary online learning systems, the advantages of our hybrid cloud-edge based solution are twofold. It scales up with a growing number of students, and also mitigates privacy concerns in an era where the rise of analytics in online learning raises questions about the responsible use of data. Collapse

Topics: privacy cloud computing online learning system website JavaScript

Methods: deep learning literature study biometric measurement TensorFlow oculometry

Introduction to the Design and Appropriation of Knowledge and AI Systems Minitrack

2021 | HICSS | Citations: 0

Authors: Smolnik, Stefan; Hadaya, Pierre; Holford, W David

Abstract: The objective of this minitrack is to contribute to the body of knowledge that ... Expand

Abstract: The objective of this minitrack is to contribute to the body of knowledge that helps scholars and practitioners increase their collective understanding of (1) how knowledge and artificial intelligence (AI) systems are planned, designed, built, implemented, used, evaluated, supported, upgraded, and evolved; (2) how knowledge and AI systems impact the context in which they are embedded; and (3) the human behaviors reflected within and induced through both (1) and (2). By knowledge and AI systems, we mean systems in which human participants and/or machines perform work (processes and activities) related to the creation, retention, transfer and/or application of knowledge using information, technology, and other resources to produce informational products and/or services for internal or external customers. Such systems may include, but are not limited to, knowledge management systems, decision systems, social media, expert systems, machine learning systems, and other AI systems as well as any other IT-enabled knowledge processes.It is the ninth year of the minitrack. We received seven papers this year and after a rigorous review process, we accepted three for publication in the proceedings and online presentation at the conference.The first paper, co-authored by Ali Intezari, Morteza Namvar, and Ramin Taghinejad, aims at providing a theoretical framework that explains the complexity of knowledge in an organizational context, and how knowledge management (KM) can be integrated into an organization's existing enterprise system. To do so, the authors introduce the concept of knowledge identity (KI) that refers to the collective construal that an organization's members have about their previous, current and future knowledge needs. They also provide a critical perspective about the assumptions that underline organizations' practice of KM and argue how these assumptions influence KI.In the second paper, which is nominated for the HICSS-54 2021 Best Paper Award, Camille Grange and Alain Pinsonneault develop a theoretical framework that emphasizes the socio-ethical factors surrounding the decision made by organizations to deploy a highly automated decision-making system. Previous literature on adoption and intention to adopt omits inquiring whether the adoption decision or the process leading to the decision is socially responsible. Thus, in developing their framework, the authors specify a new set of constructs to reflect the phenomenon and introduce the theoretical logic underlying the relationships between these constructs.The third paper, co-authored by Peter Hofmann, Philipp Stähle, Christoph Buck, and Harald Thorwarth, addresses the lack of guidance on the development and application of data-driven applications fostering an organization's absorptive capacity. Based on a structured literature review, the authors derive seven data-driven application capabilities and match them with an established conceptualization of absorptive capacity. While previous literature did not allow for a specific analysis, the authors' functional representation concretely demonstrates how data-driven applications composed of separate capabilities can foster absorptive capacity in different ways.We wish to thank all of the authors who submitted work for consideration in this minitrack. We also thank the dedicated reviewers for the time and effort they invested in reviewing the papers. We believe that the accepted papers contribute to furthering our understanding on the creation and appropriation of knowledge and AI systems. All author teams provide presentation slides and/or a presentation video that could be accessed during the conference in January 2021. We hope that all provided materials (papers, slides, videos) inspire discussions, networking, and new ideas and research endeavors. Collapse

Topics: organizational context enterprise information system presentation software knowledge management absorptive capacity

Methods: literature sample theory development

Harder and Smoother on Touchscreens? How Interaction Mode Affects Consumer Product Judgment

2020 | HICSS | Citations: 0

Authors: Liu, Yang; Jiang, Zhenhui

Abstract: Emerging technologies, such as touchscreen interaction and mid-air gesture-based ... Expand

Abstract: Emerging technologies, such as touchscreen interaction and mid-air gesture-based interaction, are changing the ways we interact with products virtually. However, despite research on how these technologies can be leveraged to improve consumers’ shopping experience, few studies have explored how they affect consumer product judgment. This study explores how two types of gesture-based human-device interaction modes (i.e., touchscreen interaction and mid-air interaction) influence consumers’ judgment on product haptic attributes (i.e., softness and roughness). Results from a lab experiment reveal that interacting with a product via touchscreen, as compared via a mid-air gesture controller, leads to a lower perception of product softness and roughness. Furthermore, such effects are more salient among users with a higher level of need for touch. The results imply that people may mistakenly use the incidental haptic experience gained from interaction device (e.g., the solid and smooth haptic experience a user feels when interacting with touchscreen surface) in product judgment although such experience is not directly related to the product being evaluated. Theoretical contributions, practical implications, and future research are discussed. Collapse

Topics: website electronic commerce laptop computer perceived ease of use presentation software

Methods: descriptive statistic multivariate analysis of covariance experiment analysis of covariance conceptual modelling

Theories: cognitive theory