Self-reporting Limitations in Information Systems Design Science Research

2023 | Business & Information Systems Engineering | Citations: 0

Authors: Barata, João; da Cunha, Paulo Rupino; de Figueiredo, António Dias

Abstract: Besides increasing transparency and demonstrating awareness of the author, self- ... Expand

Abstract: Besides increasing transparency and demonstrating awareness of the author, self-reported limitations enable other researchers to effectively learn from, build on, validate, and extend the original work. However, this topic is understudied in information systems design science research (IS DSR). The study has assessed 243 IS DSR papers published in the period 2013–2022 and built a typology of the 19 most relevant limitations, organized into four categories: (1) Input Knowledge and Technology, (2) Research Process, (3) Resulting Artifact, and (4) Design Knowledge. Further, the contribution suggests actions to mitigate each type of limitation throughout the entire IS DSR project lifecycle. The authors have also created guidelines to report the limitations in a useful way for knowledge accumulation. The proposed typology and guidelines enable reviewers and editors to better frame self-reported limitations, assess rigor and relevance more systematically, and provide more precise feedback. Moreover, the contribution may help design researchers identify, mitigate, and effectively communicate the uncertainties inherent to all scientific advances. Collapse

Methods: literature sample literature study design science theory development synthesis

Natural Language Processing for Medical Texts – A Taxonomy to Inform Integration Decisions into Clinical Practice

2023 | International Conference on Information Systems | Citations: 0

Authors: Braun, Marvin; Kolbe, Lutz; Neumann, Caspar

Abstract: Electronic health records (EHR) have significantly amplified the volume of info ... Expand

Abstract: Electronic health records (EHR) have significantly amplified the volume of information accessible in the healthcare sector. Nevertheless, this information load also translates into elevated workloads for clinicians engaged in extracting and generating patient information. Natural Language Process (NLP) aims to overcome this problem by automatically extracting and structuring relevant information from medical texts. While other methods related to artificial intelligence have been implemented successfully in healthcare (e.g., computer vision in radiology), NLP still lacks commercial success in this domain. The lack of a structured overview of NLP systems is exacerbating the problem, especially with the emergence of new technologies like generative pre-trained transformers. Against this background, this paper presents a taxonomy to inform integration decisions of NLP systems into healthcare IT landscapes. We contribute to a better understanding of how NLP systems can be integrated into daily clinical contexts. In total, we reviewed 29 papers and 36 commercial NLP products. Collapse

Topics: health information system artificial intelligence database system healthcare data information technology infrastructure

Methods: natural language processing computational algorithm information extraction literature sample NLP application

Online Information Filtering: The Role of Contextual Cues in Electronic Networks of Practice

2023 | ACM SIGMIS Database | Citations: 0

Authors: Fadel, Kelly J.; Jensen, Matthew L.; Meservy, Thomas O.

Abstract: Online forums sponsored by Electronic Networks of Practice are commonly used to ... Expand

Abstract: Online forums sponsored by Electronic Networks of Practice are commonly used to exchange information related to problem solving, but the quality of solutions posted on forums can vary widely. To assist knowledge seekers, most forums offer contextual cues that signal solution quality, such as endorsements by the question poster, experts, or other community members. However, the influence of these cues on information-filtering decisions, particularly when presented simultaneously, remains poorly understood. This study draws on signaling theory to develop hypotheses about how four cue dimensions-source, valence, format, and volume-shape information filtering on an online forum. Results from three choice-based conjoint studies show that some sources are more influential than others and that positive cues weigh more heavily on filtering decisions than negative cues. Results also show that cues tend to be more influential when they employ a more granular format and reflect the input of a larger number of individuals. Collapse

Topics: decision making information storage and retrieval system logistics management website information exchange

Methods: conjoint analysis survey statistical hypothesis test literature study theory development

Theories: signaling theory

Disentangling the Tension Between Automation and Augmentation with Artificial Intelligence in Healthcare

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Grüning, Maximilian; Trenz, Manuel; Santos, Daniel Pinto dos

Abstract: Artificial Intelligence (AI) has the potential to be a powerful tool for the fu ... Expand

Abstract: Artificial Intelligence (AI) has the potential to be a powerful tool for the future of medical professionals. However, we recognize a tension between AI independence (automation) and human involvement (augmentation) in medical decision-making. To resolve this tension, we conducted a systematic literature review to gain an overview of the current knowledge of AI in healthcare. In this systematic literature review, we search and analyze the leading journals in management and information systems for a period from 2012 to 2022. We find that several tasks related to diagnosis, treatment, or administrative work can be effectively automated or augmented with AI. We contribute to information systems research by highlighting possible scenarios for the effective use of AI in medical decision-making. Understanding and mitigating these tensions are particularly important for medical decision-makers, regulators, and managers who are struggling with guidelines for the appropriate use of AI and certification of accountability. Collapse

Topics: artificial intelligence decision making robotic expert system robotic process automation

Methods: literature sample structured literature research literature study artificial neural network business process modeling

Patient centricity in IS healthcare – a framework proposing enablement, empowerment, and engagement of patients as individual IS users

2023 | International Conference on Business Informatics | Citations: 0

Authors: Maschewski, Jan; Lemmer, Kristina

Abstract: ... Expand

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Topics: health information system information system use IT workforce digital transformation database system

Methods: literature study design artifact literature sample grounded theory structured literature research

Theories: theory of everything

A Framework for Developing Cross-Sectional Surveys

2023 | International Conference on Information Systems | Citations: 0

Authors: Mehler, Maren; Ellenrieder, Sara; Akdag, Merve Turan; Wagner, Amina; Benbasat, Izak

Abstract: Although the use of cross-sectional surveys is widespread in Information System ... Expand

Abstract: Although the use of cross-sectional surveys is widespread in Information Systems (IS) research and related disciplines, few papers address the survey development process. In order to ensure a standardized approach, comparable and valid results, as well as to guide researchers in quantitative research methods, this paper presents a framework for the survey development process in IS. Based on a Design Science Research (DSR) methodology, the framework was derived from a structured literature review of leading IS journals and refined by three focus group discussions among IS experts. The framework includes several steps and considerations on the sample size, variable selection, their order in the survey, protection against bias, ensuring validity and reliability, and testing before administering the survey with a focus on documentation and reporting. Our framework supports quantitative research by providing a structured approach to create reliable and credible surveys. Collapse

Topics: website implicit knowledge ease of use privacy anonymity

Methods: survey focus group survey design literature study cross sectional survey

From broken habits to new intentions: how COVID-19 expands our knowledge on post-adoptive use behaviour of digital communication and collaboration

2023 | European Journal of Information Systems | Citations: 0

Authors: Schoch, Manfred; Gimpel, Henner; Maier, Andreas; Neumeier, Kathrin

Abstract: The COVID-19 pandemic has caused an unprecedented surge in digital communication ... Expand

Abstract: The COVID-19 pandemic has caused an unprecedented surge in digital communication and collaboration. While a rich body of knowledge exists on IS use, our understanding of changes in post-adoptive use behaviour regarding communication and collaboration is comparatively limited. Existing models assume decreasing growth rates over time and are not designed to capture spikes in use behaviour such as the one observed during the pandemic. In this mixed methods study, we propose a hybrid model of sensemaking and post-adoptive communication and collaboration use that explains changes in use behaviour and outlines the influence of external trigger events. Based on real-world data from MS Teams, we show that individual feature use varies over time, with an increasing growth rate triggered by COVID-19. To understand drivers for the heterogeneous changes, we further conduct qualitative interviews. We find habits were deliberately altered during COVID-19 and replaced with new intentions through sensemaking. We derive propositions that may encourage further research into the subject. Extended knowledge of post-adoptive behaviour and its triggers assists practitioners in adjusting to the new normal or reacting to new situations beyond COVID-19. Collapse

Topics: sensemaking IT supported collaboration information system use user behavior self efficacy

Methods: qualitative interview cluster analysis mixed method design artifact longitudinal research

Guidelines for the Development of Three-Level Models: Bridging Levels of Analysis and Integrating Contextual Influences in IS Research

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

Authors: Venkatesh, Viswanath; Weng, Qin; Rai, Arun; Maruping, Likoebe

Abstract: The use of multilevel analysis has steadily increased in information systems (IS ... Expand

Abstract: The use of multilevel analysis has steadily increased in information systems (IS) research. Many studies are doing an admirable job of integrating two-level models into their examination of IS phenomena. However, two-level models are limited in how well they enable researchers to (1) more explicitly incorporate context into theory development and testing and (2) bridge the existing gap between micro- and macrolevel research by focusing on intervening mechanisms that link hierarchically distal levels of analysis. Three-level models have emerged as a potential way to address these limitations. While the literature has clearly outlined the mechanics of how to estimate three-level models, there is very little, if any, guidance on when and how to integrate the use of such models with theory development. Consequently, IS researchers have little guidance to inform their decisions about integrating the use of three-level models with their theory development and testing. In this article, we identify the circumstances under which IS researchers should consider the use of three-level models, develop guidelines about how to map the use of three-level model estimation to the theoretical objectives, and provide an illustration of how to implement the guidelines. Collapse

Topics: offshoring accounting IT project personality internet technology

Methods: theory development hierarchical linear modeling literature study likelihood-ratio test descriptive statistic

Theories: technology acceptance model big five model

Rethinking Project Escalation: An Institutional Perspective on the Persistence of Failing Large-Scale Information System Projects

2022 | Journal of Management Information Systems | Citations: 0

Authors: Berente, Nicholas; Salge, Carolina Alves de Lima; Mallampalli, Venkata K.P.; Park, Ken

Abstract: Project escalation involves the continued, persistent commitment to a failing pr ... Expand

Abstract: Project escalation involves the continued, persistent commitment to a failing project. Through a qualitative meta-analysis of 15 published cases of large information systems (IS) projects in escalation situations, we develop an institutional perspective on IS projects in escalation situations. This perspective describes how project persistence emerges from a plurality of legitimizing institutional logics that decision-makers draw upon at different project stages to maintain and reduce their commitment to the project. Logics related to the project's approval are not the same logics that guide decisions throughout the project. For example, while we find that innovation and economic logics of return on investment are salient before approval, economic costs tend to be more salient after approval, along with technical impositions and managerial concerns. We further find that managerial logics are particularly salient in reducing commitment to projects, and we detail the differences and point out contextual triggers of external scrutiny and leadership changes that can contribute to reduced commitment to a project and eventual de-escalation. Collapse

Topics: IT project innovation management project management decision making digital transformation

Methods: meta analysis case study theory development constant comparative analysis single case study

Theories: escalation theory

Analyzing e-government design science artifacts: A systematic literature review

2022 | International Journal of Information Management | Citations: 0

Authors: Carter, Lemuria; Yoon, Victoria; Liu, Dapeng

Abstract: Design science as a research paradigm is gaining popularity in the information s ... Expand

Abstract: Design science as a research paradigm is gaining popularity in the information systems (IS) discipline. E-gov­ ernment research explores IS artifacts designed to improve the quality and efficiency of public administration and service. This paper utilizes the E-government Design Research Model (EgovDR Model) to review e-gov­ ernment designs. Through a comprehensive literature review, this paper identifies prototypical e-government tasks for design science implementation and the corresponding solutions. We demonstrate whether and how the development and evolution of e-government designs continue to gain relevance in design science research. Additionally, this paper identifies and analyzes the theories employed in the literature to illustrate how the EgovDR Model has facilitated e-government designs in increasing rigor over time. Our findings indicate the majority of the workpractice tasks in existing e-government designs are decision-support tasks. Collapse

Topics: government system criminality decision support system social identity knowledge representation

Methods: design science literature study design artifact literature sample synthesis

Theories: information theory activity theory social disorganization theory portfolio theory structuration theory