Gender and Mobility – A Literature Review on Women's (Non-)Use of Shared Mobility Services

2023 | International Conference on Business Informatics | Citations: 0

Authors: Kendziorra, Jennifer; Barmann, Michelle Nathalie; Witte, Anne-Katrin; Kusanke, Kristina

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Topics: database system ride sharing platform smart city ease of use

Methods: literature study conceptual modelling structured literature research

The Quest for National Digital Agility: Digital Responses to Covid-19 in Five Countries

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

Authors: Kendziorra, Jennifer; Witte, Anne-Katrin; Winkler, Till; Tong, Yu; Kwon, Juhee; Mishra, Abhay Nath

Abstract: Countries worldwide have employed various digital solutions to contain and cope ... Expand

Abstract: Countries worldwide have employed various digital solutions to contain and cope with the COVID-19 pandemic. In this explorative case research, we examine national-level digital responses to the pandemic in four specific areastracking and tracing, health data reporting, teleconsultation, and vaccination mobilization-across five countries: China, Denmark, Germany, South Korea, and the US. Drawing on the notion of agility and digital infrastructures, our cross-case analysis unveils how the countries' digital responses to the pandemic have been shaped by their national health system characteristics. In addition, we highlight how existing digital health infrastructures, regulatory adaptations, and industry collaborations fostered the alacrity with which nations responded to the pandemic. We define national-level digital agility as the ability of a nation to leverage digital infrastructure capabilities to address urgent societal challenges in a contextually appropriate way. Our key contribution is a model of this complex, but urgently needed concept containing five building blocks, that jointly explain and contribute to building such agility. Despite focusing on addressing the existing challenges of the ongoing COVID-19 pandemic, we believe that researchers and policymakers can also take away from our framework ideas to tackle other socio-environmental challenges. Collapse

Topics: IS agility pandemic health information system information technology infrastructure healthcare data

Methods: case study conceptual modelling cross sectional research multiple case study natural experiment

Introduction to the Practitioner Research Insights Minitrack

2023 | HICSS | Citations: 0

Authors: Keskin, T.; Rayes, A.; Mangla, U.; Yurko, H.

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Topics: innovation management

Methods: case study

ON CONTEXTUAL CONTRADICTION: A FIELD STUDY OF DIGITAL PAYMENT INCLUSION IN MEXICO

2023 | European Conference On Information Systems | Citations: 0

Authors: Kessel, Lino; Mora, Juan Camilo Giraldo

Abstract: Digital payment technology allows financially excluded communities to access fi ... Expand

Abstract: Digital payment technology allows financially excluded communities to access financial services by crossing infrastructural, regulatory, and economic boundaries. However, there are also cases where its presence might lead to exclusion. In addition to these diverse findings, it remains unclear why exclusion prevails in Mexico, where digital payment technology is highly developed for Latin America. Consequently, this study addresses how and why the Mexican context conditions digital payment inclusion. Based on a dynamic understanding of context and a field study, we operationalise Mexico's contextual conditioning through inequalities. Using observations, interviews and documents, the study's results reveal what we term contextual contradiction. Socio-economic infrastructure separation, evolutionary regression, and informal legislation are contextual contradictions which convey a dynamic conditioning leading to digital payment inclusion and exclusion. These findings contribute to debates on contextual explanation by addressing how context and phenomenon emerge together without bounding, stabilising, or situating context. Collapse

Topics: electronic payment information system use mobile application legal context systems analysis

Methods: qualitative interview field study literature study theory development mixed method

Toward Identifying the Factors Associated with Conversational Agents’ Performance

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Khan, Abdul Kader; Palvia, Prashant

Abstract: With advances in computing and a preference for convenience in completing digit ... Expand

Abstract: With advances in computing and a preference for convenience in completing digital tasks, conversational agents (CAs) have gained widespread popularity throughout the world. However, most of the CAs seem to lack several necessary capabilities to satisfy the users' needs. Our study focused on text-based CAs (also known as chatbots) and examines the factors associated with their performance. The literature on IS success and adoption suggest that various factors related to the technology, users, and tasks can jointly play a role in satisfying user needs. Thus, we adopt a holistic approach to evaluating chatbot performance by identifying chatbot attributes, user attributes, and task attributes and their impact on chatbot performance from the users' view. We conducted interviews with chatbot users and using a qualitative approach, provide a theoretical framework for chatbot performance evaluation. All the interviews were conducted with the users of rule-based chatbots as these are widely used by all sizes of organizations. Collapse

Topics: user satisfaction task complexity privacy digital platform user requirement

Methods: chatbot qualitative interview qualitative content analysis literature study grounded theory

Augmenting Password Strength Meter Design Using the Elaboration Likelihood Model: Evidence from Randomized Experiments

2023 | Information Systems Research | Citations: 0

Authors: Khern-am-nuai, Warut; Hashim, Matthew J.; Pinsonneault, Alain; Yang, Weining; Li, Ninghui

Abstract: Password-based authentication is the most commonly used method for gaining acces ... Expand

Abstract: Password-based authentication is the most commonly used method for gaining access to secured systems. Unfortunately, empirical evidence highlights the fact that most passwords are significantly weak, and encouraging users to create stronger passwords is a significant challenge. In this research, we propose a theoretically augmented password strength meter design that is guided by the elaboration likelihood model of persuasion (ELM). We evaluate our design by leveraging three independent and complementary methods: a survey-based experiment using students to evaluate the saliency of our conceptual design (proof of concept), a controlled laboratory experiment conducted on Amazon Mechanical Turk to test the effectiveness of the proposed design (proof of value), and a randomized field experiment conducted in collaboration with an online forum in Asia to establish proof of use. In each study, we observe the changes in users’ behavior in response to our proposed password strength meter. We find that the ELM-augmented password strength meter is significantly effective at addressing the challenges of password-based authentication. Users exposed to this strength meter are more likely to change their passwords, leading to a new password that is significantly stronger. Our findings suggest that the proposed design of augmented password strength meters is an effective method for promoting secure password behavior among end users.History: Alessandro Acquisti, Senior Editor; Pallab Sanyal, Associate Editor.Funding: The authors gratefully acknowledge financial support from the Social Science and Humanities Research Council of Canada (SSHRC) [Grant 435-2018-0605].Supplemental Material: The online appendix is available at https://doi.org/10.1287/isre.2022.1125. Collapse

Topics: password website data security electronic authentication application programming interface

Methods: experiment survey laboratory experiment experimental group field experiment

Theories: elaboration likelihood model

When do details matter? News source evaluation summaries and details against misinformation on social media

2023 | International Journal of Information Management | Citations: 0

Authors: Kim, Antino; Moravec, Patricia L.; Dennis, Alan R.

Abstract: News source evaluations based on fact-checking can help curb the consumption and ... Expand

Abstract: News source evaluations based on fact-checking can help curb the consumption and spread of fake news on social media. Prior research has primarily considered source evaluations with intuitive icons that indicate whether or not news sources are reputable. But can we increase the power of these icons by adding more detailed infor­ mation about the evaluation that explains the reasons for the icon? What additional benefit would such evalu­ ation details bring? Would they have the same effect for both positive and negative evaluations? We conducted two online experiments to understand the effects of a source evaluation icon (a positive or negative summary of the evaluation) and more detailed evaluation information explaining the reasons for the icon. Our results show an asymmetric effect of positive and negative icons and details. Negative icons reduced the believability of the articles, but adding evaluation details supporting the icon had no additional effect. In contrast, positive icons had no significant effects, but adding evaluation details significantly increased believability. We also found that users were more likely to view the evaluation details when the content of the article aligned with their pre-existing opinions, but the valence of the icon (positive or negative) did not affect this decision. Collapse

Topics: social media Facebook fake news user interface usability

Methods: experiment theory development descriptive statistic linear regression analysis survey

ROLEX: A Novel Method for Interpretable Machine Learning Using Robust Local Explanations

2023 | Management Information Systems Quarterly | Citations: 2

Authors: Kim, Buomsoo (Raymond); Srinivasan, Karthik; Kong, Sung Hye; Kim, Jung Hee; Shin, Chan Soo; Ram, Sudha

Abstract: Recent developments in big data technologies are revolutionizing the field of h ... Expand

Abstract: Recent developments in big data technologies are revolutionizing the field of healthcare predictive analytics (HPA), enabling researchers to explore challenging problems using complex prediction models. Nevertheless, healthcare practitioners are reluctant to adopt those models as they are less transparent and accountable due to their black-box structure. We believe that instance-level, or local, explanations enhance patient safety and foster trust by enabling patient-level interpretations and medical knowledge discovery. Therefore, we propose the RObust Local EXplanations (ROLEX) method to develop robust, instance-level explanations for HPA models in this study. ROLEX adapts state-of-the-art methods and ameliorates their shortcomings in explaining individual-level predictions made by black-box machine learning models. Our analysis with a large real-world dataset related to a prevalent medical condition called fragility fracture and two publicly available healthcare datasets reveals that ROLEX outperforms widely accepted benchmark methods in terms of local faithfulness of explanations. In addition, ROLEX is more robust since it does not rely on extensive hyperparameter tuning or heuristic algorithms. Explanations generated by ROLEX, along with the prototype user interface presented in this study, have the potential to promote personalized care and precision medicine by providing patient-level interpretations and novel insights. We discuss the theoretical implications of our study in healthcare, big data, and design science. Collapse

Topics: explainable artificial intelligence usability user interface local interpretable model agnostic explanation problem solving

Methods: machine learning design artifact computational algorithm longitudinal research ablation analysis

Theories: lemon market theory

An empirical study of community cohesiveness, community attachment, and their roles in virtual community participation

2023 | European Journal of Information Systems | Citations: 2

Authors: Kim, Dan J.; Salvacion, Mark; Salehan, Mohammad; Kim, Dae Wan

Abstract: Although active participation of members is a critical success factor for virtua ... Expand

Abstract: Although active participation of members is a critical success factor for virtual communities, few members actively participate in activities in virtual communities (e.g., posting, commenting, sharing, etc.). This study explores the differences between passive and active community participation from community cohesiveness and community attachment perspectives. Drawing upon a context-specific cohesiveness-attachment-participation framework based on cognition-affection-conation traits of human psychology, we propose a research model and empirically test the roles of community cohesiveness and attachment in virtual community participation. The results suggest that community members’ active participation is positively influenced by both community cohesiveness and community attachment. Visitation, as the passive mode of participation, is influenced by community attachment only. The findings not only inspire future IS research to consider community cohesiveness, attachment, and participation as vital research constructs in other social contexts, but it also helps managers build managerial actions, such as prioritising their limited business resources to increase community members’ active participation, for the success of virtual communities. Collapse

Topics: online community Facebook social network Twitter YouTube

Methods: survey partial least squares path modeling PLS tool survey design statistical hypothesis test

Identity and Status: When Counterspeech Increases Hate Speech Reporting and Why

2023 | Information Systems Frontiers | Citations: 0

Authors: Kim, Jae Yeon; Sim, Jaeung; Cho, Daegon

Abstract: Much has been written about how social media platforms enable the rise of networ ... Expand

Abstract: Much has been written about how social media platforms enable the rise of networked activism. However, few studies have examined how these platforms’ low-information environments shape how social movement activists, their opponents, and social media platforms interact. Hate speech reporting is one understudied area where such interactions occur. This article fills this gap by examining to what extent and how the gender and popularity of counterspeech in comment sections influence social media users’ willingness to report hate speech on the #MeToo movement. Based on a survey experiment (n = 1250) conducted in South Korea, we find that YouTube users are more willing to report such sexist hate speech when the counterspeech is delivered by a female rather than a male user. However, when the female user’s counterspeech received many upvotes, this was perceived to signal her enhanced status and decreased the intention to report hate speech, particularly among male users. No parallel patterns were found regarding other attitudes toward hate speech, counterspeech, YouTube, the #MeToo movement, and gender discrimination and hate speech legislation. These findings inform that users report hate speech based on potentially harmful content as well as their complex social interactions with other users and the platform. Collapse

Topics: YouTube social media legal context

Methods: survey experiment Student's t-test experimental group parametric test

Theories: communication theory