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How AI-Based Systems Can Induce Reflections: The Case of AI-Augmented Diagnostic Work

2023 | Management Information Systems Quarterly | Citations: 0
Authors: Abdel-Karim, Benjamin; Pfeuffer, Nicolas; Carl, K. Valerie; Hinz, Oliver

Abstract: This paper addresses a thus-far neglected dimension in human-artificial intelli ... Expand

Abstract: This paper addresses a thus-far neglected dimension in human-artificial intelligence (AI) augmentation: machine-induced reflections. By establishing a grounded theoretical-informed model of machine-induced reflection, we contribute to the ongoing discussion in information systems (IS) regarding AI and research on reflection theories. In our multistage study, physicians used a machine learning-based (ML) clinical decision support system (CDSS) to see if and how this interaction can stimulate reflective practice in the context of an X-ray diagnosis task. By analyzing verbal protocols, performance metrics, and survey data, we developed an integrative theoretical foundation to explain how ML-based systems can help stimulate reflective practice. Individuals engage in more critical or shallower modes depending on whether they perceive a conflict or agreement with these CDSS systems, which in turn leads to different levels of reflection depth. By uncovering the process of machine-induced reflections, we offer IS research a different perspective on how such AI-based systems can help individuals become more reflective, and consequently more effective, professionals. This perspective stands in stark contrast to the traditional, efficiency-focused view of MLbased decision support systems and also enriches theories on human-AI augmentation. Collapse

Semantic filters: learning theory

Topics: artificial intelligence decision making decision support system algorithmic transparency recommender system

Methods: cognitive walkthrough survey theory development qualitative interview Student's t-test

Theories: learning theory information systems theory theory of abduction
The relative values of big data analytics versus traditional marketing analytics to firm innovation: An empirical study
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2023 | Information & Management | Citations: 0
Authors: Cheng, Colin C.J.; Shiu, Eric C.

Abstract: Although big data analytics (BDA) does enhance innovation performance, it remain ... Expand

Abstract: Although big data analytics (BDA) does enhance innovation performance, it remains unclear whether BDA contributes more or less than traditional marketing analytics (TMA) to firm innovation. This study tests hy potheses based on data collected from multiple sources by using four-wave survey and archival data from 201 firms. The results indicate that BDA has a stronger positive effect on new product development (NPD) perfor mance than TMA, over time. However, TMA, when coupled with exploitative innovation strategy, has a stronger positive effect on NPD performance than if coupled with exploratory innovation strategy. Conversely, BDA, when coupled with exploratory innovation strategy, has a stronger positive effect on NPD performance than if coupled with exploitative innovation strategy. Collapse

Semantic filters: learning theory

Topics: innovation management analytical information system big data research and development marketing management

Methods: survey archival research partial least squares path modeling conceptual modelling Chow test

Theories: learning theory ambidexterity theory knowledge based theory of the firm
SOLVING THE DATA-DRIVEN NEWSVENDOR WITH ATTENTION TO TIME

2023 | European Conference On Information Systems | Citations: 0
Authors: Feddersen, Leif; Cleophas, Catherine

Abstract: Inventory management systems support firms in planning for an uncertain future ... Expand

Abstract: Inventory management systems support firms in planning for an uncertain future by using demand forecasts and optimization models to make restocking decisions. Recent work on the "data-driven" newsvendor found that incorporating machine learning (ML) can improve the success of inventory management by accounting for demand-driving information. However, ML methods are infamously hard to interpret, which may hinder their acceptance. To ameliorate this, we show how to apply an interpretable attention-based architecture, the Temporal Fusion Transformer (TFT), to the data-driven newsvendor problem. Our approach replicates and extends the original TFT time series forecasting method to the inventory management domain. We evaluate our method on two real-world retail datasets, each covering 260 perishable food items, and provide domain-specific benchmarks. The computational study illustrates TFT's interpretable predictions and their comparatively high accuracy. Our work aims to lay the groundwork for further design science research on transparency in human-AI collaboration in this domain. Collapse

Semantic filters: learning theory

Topics: human AI collaboration human computer interaction Python decision making accounting

Methods: time series analysis longitudinal research artificial neural network feature engineering machine learning

Theories: learning theory
Machine Learning based Financial Aid Management Process

2023 | Americas Conference on Information Systems | Citations: 0
Authors: Gottipati, Swapna; Shankararaman, Venky; Rao, Komirisetti Chalapathi; Vetrivillalan, Vennila

Abstract: Advanced programming skills are required for computing courses on merging topic ... Expand

Abstract: Advanced programming skills are required for computing courses on merging topics, and students often struggle to develop these skills to solve complex problems. Faculty tackle this challenge by providing extra lectures, practice sessions, technologies, and education tools. This paper discusses the challenges faced by computer science students in developing advanced programming skills and explores the use of AI chatbots, specifically ChatGPT, as a support tool for learning. We study the engagement and effectiveness of ChatGPT in helping students learn advanced programming skills using two engagement learning frameworks (CIE and MELT) for evaluation. The study involves designing a lab exercise for students to complete using ChatGPT and collecting data through surveys. We present the findings of the study and discuss the limitations of the work. Collapse

Semantic filters: learning theory

Topics: problem solving online learning system artificial intelligence IS effectiveness

Methods: chatGPT survey chatbot sentiment analysis natural language processing

Theories: educational theory learning theory
DIGITAL TECHNOLOGY-ENABLED DYNAMIC CAPABILITIES, ACTION SPEED, AND ACTION VOLUME: THE MEDIATING EFFECT OF STRATEGIC RENEWAL

2023 | European Conference On Information Systems | Citations: 0
Authors: Hüneke, Jacqueline; Greven, Andrea

Abstract: The information systems research stream on dynamic capabilities (DCs) considers ... Expand

Abstract: The information systems research stream on dynamic capabilities (DCs) considers how technology impacts strategic management at the organizational level in the turbulent environment evoked by digital transformation. However, the underlying mechanisms of how organizations use technologies effectively to increase their competitive advantage through competitive actions is underexplored. This paper seeks to empirically investigate the impact of digital technology-enabled DCs on action speed and action volume, two indicators of competitive aggressiveness. Furthermore, we propose the mediating role of strategic renewal. Our PLS-SEM analysis based on survey data from 174 German business units indicates that digital technology-enabled DCs directly enhance strategic renewal, action speed, and action volume. We also detect a partial mediating effect of strategic renewal on the relationship between digital technology-enabled DCs and action volume. This study offers insights into the underlying mechanisms that may allow organizations to enhance their competitive aggressiveness through the application of digital technologies. Collapse

Semantic filters: learning theory

Topics: digital transformation competitive advantage strategic management IT productivity technological change

Methods: survey PLS tool instrumental variables estimation partial least squares path modeling survey design

Theories: learning theory
Could Gamification Designs Enhance Online Learning Through Personalization? Lessons from a Field Experiment
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2023 | Information Systems Research | Citations: 1
Authors: Leung, Alvin Chung Man; Santhanam, Radhika; Kwok, Ron Chi-Wai; Yue, Wei Thoo

Abstract: The COVID-19 pandemic has highlighted the importance of online learning. As lear ... Expand

Abstract: The COVID-19 pandemic has highlighted the importance of online learning. As learner autonomy is relatively high in online environments, learners must engage in self-regulated learning (SRL) to achieve optimal learning outcomes. Because most learners are unable to consistently engage in SRL, gamification interventions are being implemented to improve SRL engagement; however, mixed results cast doubt on the efficacy of this approach. Massively open online courses (MOOCs), a type of online learning environment, are currently experiencing rapid growth due to widespread adoption by many institutions. In MOOCs, there is no instructor intervention; hence, students have difficulty regulating their own learning and are easily distracted. Therefore, this study investigates whether mixed-research results regarding the efficacy of gamification can be attributed to lack of attention to individual learner traits during design. For this purpose, the study analyzes MOOCs as an instance of online learning by applying SRL theory and gamification principles. We altered a traditional MOOC platform to provide different types of gamified performance feedback to facilitate learners’ SRL engagement. We then examined whether this matched with goal orientation, an individual learner trait to influence SRL and learning outcomes. Using learning-analytics tools, we tracked 760 college students’ SRL engagement on a MOOC platform over five weeks. As theorized, SRL engagement and learning outcomes of participants who had a strong performance-avoidance goal orientation increased with positively framed performance feedback that involved no social comparisons; however, the same feedback had a negative impact on participants with a strong mastery goal orientation. Our findings add to SRL theory by demonstrating that gamification designs can enhance SRL engagement and learning outcomes in online learning, but with a caveat—this occurs only when there is a match with learner traits—confirming the gamification principle stating that task improvements and meaningful engagement can only occur through thoughtful gamification design.History: Raghu Santanam, Senior Editor; J. J. Hsieh, Associate Editor.Funding: Financial supported from the University Grants Committee’s (UGC’s) Special Grant for the Strategic Development of Virtual Teaching and Learning [Project Number 6430900], the UGC Teaching and Learning Funding [Project Numbers 6391211 and 6391001], and the Digital Innovation Laboratory of Department of Information Systems, City University of Hong Kong is gratefully acknowledged.Supplemental Material: The online appendix is available at https://doi.org/10.1287/isre.2022.1123. Collapse

Semantic filters: learning theory

Topics: gamification online learning system electronic mail IT skill business intelligence

Methods: experimental group pilot experiment survey experiment digital trace data

Theories: learning theory
Co-creation, Failure Learning, and Relaunch Success: Evidence from Online Crowdfunding Market

2023 | International Conference on Information Systems | Citations: 0
Authors: Liu, Xiaochen; JIN, Yu; Fang, Yulin; Ye, Qiang

Abstract: With intense competition and relatively inexperienced founders, the crowdfundin ... Expand

Abstract: With intense competition and relatively inexperienced founders, the crowdfunding market has reported high failure rates. However, the IT components of the crowdfunding market provide entrepreneurs with more opportunities for experimentation and trial, leading to a new phenomenon of post-failure relaunches. Research into campaign relaunch success is urgently needed but under-researched. By combining failure learning theory with a collective perspective, the present study examines how investors' cocreation, in terms of advocacy and feedback, can benefit crowdfunding relaunch success directly or indirectly (by motivating founders' failure learning). The study tested the proposed mediation model with 1,902 failure-relaunched Kickstarter campaigns, with most hypotheses supported. Furthermore, the study explores the role of the time interval between crowdfunding relaunch and prior release. The findings indicate that an increased time interval enhances the positive effects of founders' learning efforts on relaunch success while attenuating the potential positive effects of investors' advocacy, implying a tradeoff in timing decisions. Collapse

Semantic filters: learning theory

Topics: crowdsourcing crowdfunding participatory design logistics management marketing management

Methods: design methodology regression analysis method computational algorithm logarithmic transformation theory development

Theories: learning theory
A Self-Regulated Learning Approach to Educational Recommender Design

2023 | Americas Conference on Information Systems | Citations: 0
Authors: McNett, Alicia; Noteboom, Cherie

Abstract: The field of education has the potential to better facilitate student learning ... Expand

Abstract: The field of education has the potential to better facilitate student learning by employing educational recommenders that adapt the learning process to the needs of individual learners. While existing research has shown promise and explores a variety of types of educational recommenders, there is currently a lack of research that ties educational theory to the design of these systems. The theory considered here, selfregulated learning, focuses on putting students in control of their learning and is appropriate in situations where learning is autonomous. This research proposes a design science approach to investigate a theoretical base of self-regulated learning (SRL) for a knowledge-based recommender design framework. Existing research on knowledge-based recommender design with an inclusion of an ontology component will guide development of this artifact. Anticipated results include the formation of design principles to inform the creation of SRL guided recommenders for both practical applications and future research. Collapse

Semantic filters: learning theory

Topics: IS problem

Methods: survey computational algorithm design science machine learning design principle

Theories: theory of task technology fit information systems theory learning theory
Re-examining post-acceptance model of information systems continuance: A revised theoretical model using MASEM approach
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2023 | International Journal of Information Management | Citations: 0
Authors: Mishra, Anubhav; Shukla, Anuja; Rana, Nripendra P.; Currie, Wendy L; Dwivedi, Yogesh K.

Abstract: This study extends the post-acceptance model of information systems (IS) continu ... Expand

Abstract: This study extends the post-acceptance model of information systems (IS) continuance, which is widely used to explain users’ satisfaction and IS continuance intentions. The extended model includes additional variables such as perceived ease of use (PEOU), attitude, trust, and enjoyment. The proposed model was tested using metaanalytic structural equation modeling (MASEM). The analysis included 1,056 observations on fifteen relation ships from 214 independent studies with a combined sample of 84,343. The results confirm the significance of all the relationships proposed in the original model. Furthermore, the findings indicate that PEOU directly in fluences perceived usefulness, satisfaction, and attitude. Trust and enjoyment both have a positive impact on users’ satisfaction and IS continuance, wherein the effect of enjoyment was higher than trust. post-consumption satisfaction resulted in a favorable attitude toward technology, which further affected IS continuance. From a theoretical perspective, the current study acknowledges the shift in users’ attitude toward technology and em phasizes the hedonic value of IS usage as users report a higher degree of satisfaction toward responsive, easy to use, and enjoyable technologies. Marketers should focus on the enjoyment and gratifications derived from technology to increase potential IS usage. Collapse

Semantic filters: learning theory

Topics: information system use perceived usefulness technology adoption social media ease of use

Methods: meta analysis structural equation modeling descriptive statistic literature sample hierarchical linear modeling

Theories: post acceptance model unified theory of acceptance and use of technology expectation confirmation theory extended unified theory of acceptance and use of technology learning theory
Towards a Scalable Digital Skills Training Architecture for Resource-Constrained Environments: The Case of Ayitic Goes Global in Haiti
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2023 | Communications of the Association for Information Systems | Citations: 0
Authors: Rao, Lila; McNaughton, Maurice; Verma, Sameer

Abstract: In developing countries such as Haiti, which are marked by high unemployment an ... Expand

Abstract: In developing countries such as Haiti, which are marked by high unemployment and gender inequality, online education has the potential to change lives. Returns on education are particularly high in Information Communications Technology (ICT)-intensive jobs and IT outsourcing offers opportunities for remote employment, providing alternatives for economic diversification and job creation that are particularly relevant for youth and women. However, the problem faced by many developing countries, is that traditional models, frameworks, architectures, and platforms for online learning do not lend themselves well to their context and, therefore, it is important to develop context-specific platforms. This need for suitable platforms has motivated the research question that this paper seeks to address, that is: What is the appropriate architecture that supports learning strategies for delivering scalable digital skills training in a resource-constrained environment? We propose an architecture that was developed specifically for blended learning in resource-constrained environments and describe how a prototype for this was designed, built, and deployed in Haiti. The initial responses to the application of the architecture, including the testimonials of the participants and the interest expressed by other countries of the region in adopting the proposed architecture, have been extremely positive. Collapse

Semantic filters: learning theory

Topics: online learning system digital literacy IT skill cloud computing Google+

Methods: design process design artifact literature study

Theories: learning theory

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Found 229 articles

How AI-Based Systems Can Induce Reflections: The Case of AI-Augmented Diagnostic Work

The relative values of big data analytics versus traditional marketing analytics to firm innovation: An empirical study

SOLVING THE DATA-DRIVEN NEWSVENDOR WITH ATTENTION TO TIME

Machine Learning based Financial Aid Management Process

DIGITAL TECHNOLOGY-ENABLED DYNAMIC CAPABILITIES, ACTION SPEED, AND ACTION VOLUME: THE MEDIATING EFFECT OF STRATEGIC RENEWAL

Could Gamification Designs Enhance Online Learning Through Personalization? Lessons from a Field Experiment

Co-creation, Failure Learning, and Relaunch Success: Evidence from Online Crowdfunding Market

A Self-Regulated Learning Approach to Educational Recommender Design

Re-examining post-acceptance model of information systems continuance: A revised theoretical model using MASEM approach

Towards a Scalable Digital Skills Training Architecture for Resource-Constrained Environments: The Case of Ayitic Goes Global in Haiti