MACH-T: A Behavior-based Mobile Node Trust Evaluation Algorithm

2023 | HICSS | Citations: 0

Authors: Thurston, Karen; Conte De Leon, Daniel

Abstract: Resiliency and availability in community and public service networks may be econ ... Expand

Abstract: Resiliency and availability in community and public service networks may be economically enhanced by building new ad hoc networks of private mobile devices and joining these to public service networks at specific trusted points. Resiliency in such ad hoc networks relies on the afforded increased availability but also on security which is in turn built on trust. In this article, we describe MACH-T, a novel behavior-based algorithm for mobile ad hoc network node trust building. MACH-T uses historical mobile node geographic location traces to incrementally calculate node trust values based on the concepts of node capability, commitment, and consistency. We describe experiments and results from evaluating MACH-T using real GPS traces from the Microsoft Research Geolife and University of Rome Tor Vergata Roma Taxi datasets. Our results show that MACH-T builds a reliable trust value and corresponding confidence value based on learned patterns of time spent in qualifying geographic locations. Collapse

Topics: global navigation satellite system mobile system Android broadband cellular network

Methods: experiment computational algorithm descriptive statistic digital trace data literature study

Price-aware matrix factorization model for personalized recommendations

2023 | Information & Management | Citations: 0

Authors: Tian, Jin; Shi, Xiaoyu; Li, Minqiang

Abstract: Recommendation methods aim to assist consumers in their decision-making process ... Expand

Abstract: Recommendation methods aim to assist consumers in their decision-making process to find products that they are quite likely interested in. Current recommendation methods generally use online consumer reviews or ratings to predict consumers’ preferences for products. In e-commerce transactions, price plays a significant role in con­ sumers’ purchase decisions. And each consumer’s preference for product prices is specific. In this paper, we propose a novel price-aware recommendation method based on the matrix factorization model which fully considers the effect of price. We distill the price preferences of consumers from ratings and discover consumers’ real preferences for products. We further calculate the price sensitivities of consumers, not only considering the difference in price preference between a consumer and others but also focusing on the consumers’ price pref­ erences in a specific price range. The final predicted ratings are calculated by adding the term of price effect into the matrix factorization framework. The results show that the proposed method has achieved high accuracy and performed better than several existing methods in both rating prediction and Top-N recommendation. And the products we recommend for consumers are more in line with their price preferences. Moreover, we find that, to some extent, the proposed method can solve the long-tail product recommendation problem with the consid­ eration of the price effect. Collapse

Topics: recommender system online review user satisfaction consumer behavior

Methods: experiment computational algorithm Student's t-test parametric test case study

Exploring the Role of AI Explanations in Delivering Rejection Messages: A Comparative Analysis of Organizational Justice Perceptions between HR and AI

2023 | International Conference on Information Systems | Citations: 0

Authors: Tian, Yuyang; Claudy, Marius; Xu, David (Jingjun); LIAO, Stephen Shaoyi

Abstract: The increasing use of AI decision systems in recruitment processes has created ... Expand

Abstract: The increasing use of AI decision systems in recruitment processes has created challenges, including potential resistance from job applicants. To address this issue, drawing on organizational justice theory, we identify dimensions of AI explanations in the employment context and examine their impact on job applicants' perceptions of organizational justice. We conducted an experiment to understand applicants' reactions to AI versus HR managers without explanations and examined the impact of AI explanations on organizational justice perceptions and acceptance intention. Our findings show that without explanation, AI is perceived as lower organizational just and acceptance intention compared to HR managers. Organizational justice mediates the effects between outcome/process explanations of AI on acceptance intention. However, outcome explanations have a stronger impact compared to process explanations. Our study contributes to understanding explanation structures for AI-based recruitment and offers practical implications for developing explanations that improve the perceived justice of AI recruitment systems. Collapse

Topics: artificial intelligence explainable artificial intelligence human resource management Google+ website

Methods: parametric test computational algorithm one sample t-test ANOVA experiment

Theories: distributive justice theory procedural justice theory equity theory organizational justice theory

Lessons Learnt from Online Teaching and Beyond: What now? Three Countries Speak

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

Authors: Steyn, Adriana; Slyke, Craig Van; Dick, Geoff; Rodríguez-Abitia, Guillermo; Twinomurinzi, Hossana

Abstract: ... Expand

Abstract: Collapse

Topics: IS education pandemic online learning system covid 19 digital transformation

Methods: survey

Theories: institutional theory

Keeping Your Maturity Assessment Alive

2023 | Business & Information Systems Engineering | Citations: 0

Authors: Stoiber, Christoph; Stöter, Maximilian; Englbrecht, Ludwig; Schönig, Stefan; Häckel, Björn

Abstract: Maturity models are valuable management tools for assessing and managing capabil ... Expand

Abstract: Maturity models are valuable management tools for assessing and managing capabilities and therefore creating a basis for their identification, prioritization, and further development. Numerous maturity assessment methods have been developed to support organizations in applying maturity models. However, these methods are mostly used for unique assessments and only provide a snapshot of the current state of capabilities and their maturity. Certainly, this does not reflect the continuous change of capabilities within dynamic organizational environments. Moreover, the systematic selection of suitable maturity models and the identification of the actions that should be targeted following the maturity assessment require more attention. To fill these research gaps, this study proposes the generally applicable Continuous Maturity Assessment Method (CMAM) that enables comprehensive and continuous maturity assessments. The CMAM comprises five steps that extend and advance existing principles of maturity assessment and can be implemented as an organizational routine. The rigorous development of the CMAM followed basic principles of the design science research methodology, including an evaluation of six organizations in different industry sectors and an extensive industrial case study. Collapse

Topics: database system evaluation criteria

Methods: case study survey maturity model qualitative interview personal interview

Theories: theory of abduction

Artificial Intelligence for Sign Language Translation – A Design Science Research Study

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

Authors: Strobel, Gero; Schoormann, Thorsten; Banh, Leonardo; Möller, Frederik

Abstract: Although our digitalized society is able to foster social inclusion and integra ... Expand

Abstract: Although our digitalized society is able to foster social inclusion and integration, there are still numerous communities suffering from inequality. This is also the case with deaf people. About 750,000 deaf people in the European Union and over 4 million deaf people in the United States face daily challenges in terms of communication and participation. This occurs not only in leisure activities but also, and more importantly, in emergency situations. To provide equal environments and allow people with hearing handicaps to communicate in their native language, this paper presents an AI-based sign language translator. We adopted a transformer neural network capable of analyzing over 500 data points from a person's gestures and face to translate sign language into text. We have designed a machine learning pipeline that enables the translator to evolve, build new datasets, and train sign language recognition models. As proof of concept, we instantiated a sign language interpreter for an emergency call with over 200 phrases. The overall goal is to support people with hearing inabilities by enabling them to participate in economic, social, political, and cultural life. Collapse

Topics: artificial intelligence communication service infrastructure smartphone information system use innovation management

Methods: machine learning design artifact machine translation artificial neural network qualitative interview

Theories: socio technical theory

Designing forecasting software for forecast users: Empowering non-experts to create and understand their own forecasts

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Stromer, Richard; Triebe, Oskar; Kim, Elijah; Hausleitner, Bernhard; Kobiella, Charlotte; Zanocco, Chad; Rajagopal, Ram

Abstract: Ram, "Designing forecasting software for forecast users: Empowering non-experts ... Expand

Abstract: Ram, "Designing forecasting software for forecast users: Empowering non-experts to create and understand their own forecasts" (2023). AMCIS AbstractForecasts inform decision-making in nearly every domain. Forecasts are often produced by experts with rare or hard to acquire skills. In practice, forecasts are generally used by domain experts and managers with little forecasting expertise. Our study focuses on how to design forecasting software that empowers nonexpert users. We study how users can make use of state-of-the-art forecasting methods, embed their domain knowledge, and how they build understanding and trust towards generated forecasts. To do so, we codesigned a forecasting software prototype using feedback from users and then analyzed their interactions with our prototype. Our results identified three main considerations for non-expert users: (1) a safe stepwise approach facilitating causal understanding and trust; (2) a white box model supporting human-reasoningfriendly components; (3) the inclusion of domain knowledge. This paper contributes insights into how nonexpert users interact with forecasting software and recommends ways to design more accessible forecasting software. Collapse

Topics: usability human computer interaction decision making Python graphical user interface

Methods: design artifact personal interview cognitive walkthrough survey qualitative interview

Embracing Absence: Researching What is Not There

2023 | International Conference on Information Systems | Citations: 0

Authors: Sullivan, Rick; Hannon, Oliver; Hovorka, Dirk

Abstract: In the absence of light, we find means to push back the darkness; when data is ... Expand

Abstract: In the absence of light, we find means to push back the darkness; when data is sparse, we find surrogates measures or extrapolate from existing data. Absences play a role in how we respond to the world. Here, we seek to better understand engagement with absences relationally initiating a productive research pathway for engaging with absences in Information Systems (IS) research. We argue the existence of absences can be considered, their implications can be examined, and their unique importance within different contexts can be demonstrated through careful articulation in reflexive research. Through an exploration of absence in selected literature we outline a variety of ways absences are interpreted and shape the world. Further, using examples of the intersection of IS and "care" we demonstrate the impact of absences in context. Doing so we build a path forward for IS scholars to imaginatively engage with absences in the future. Collapse

Topics: decision making information system use health information system reference discipline

Methods: literature study

The effect of fear and situational motivation on online information avoidance: The case of COVID-19

2023 | International Journal of Information Management | Citations: 0

Authors: Sultana, Tahmina; Dhillon, Gurpreet; Oliveira, Tiago

Abstract: During the COVID-19 pandemic, a plethora of online sources for information and n ... Expand

Abstract: During the COVID-19 pandemic, a plethora of online sources for information and news dissemination have emerged. Extant research suggests that very quickly, individuals become disinterested and begin avoiding the information. In this study, we investigate how an individual’s fear and situational motivation impact Online Information Avoidance. Using the self-determination theory and information avoidance theories, we argue that fear and external regulation are associated with increased Online Information Avoidance. We also argue that intrinsic motivation and identified regulation are associated with a decrease in Online Information Avoidance. Our findings suggest that fear, intrinsic motivation, and external regulation drive Online Information Avoidance, where intrinsic motivation is the most significant driver. We also found that identified regulation is a crucial inhibitor of Online Information Avoidance. While focusing on COVID-19, our study contributes to the broader information systems research literature and specifically to the information avoidance literature during a pandemic or a prolonged crisis. Our study’s findings will be useful for governments, health organizations, and communities that utilize online platforms, forums, and related outlets to reach larger audiences for disseminating pertinent information and recommendations during a crisis. Collapse

Topics: intrinsic motivation self efficacy pandemic healthcare data

Methods: survey partial least squares path modeling theoretical contribution mediation analysis statistical hypothesis test

Theories: self determination theory

The Janus Effect of Generative AI: Charting the Path for Responsible Conduct of Scholarly Activities in Information Systems

2023 | Information Systems Research | Citations: 7

Authors: Susarla, Anjana; Gopal, Ram; Thatcher, Jason Bennett; Sarker, Suprateek

Abstract: Funding: A. Susarla was funded by an R01 grant from the National Library of Medi ... Expand

Abstract: Funding: A. Susarla was funded by an R01 grant from the National Library of Medicine, through [Grant R01LM013443]. Collapse

Topics: generative AI cybersecurity behavior internet technology intellectual property IS discipline

Methods: chatGPT literature study survey qualitative interview structural equation modeling