BUSINESS INTELLIGENCE & ANALYTICS COST ACCOUNTING: AN ACTION DESIGN RESEARCH APPROACH

2020 | European Conference On Information Systems | Citations: 0

Authors: Grytz, Raphael; Krohn-Grimberghe, Artus; Müller, Oliver

Abstract: ... Expand

Abstract: Collapse

Topics: analytical information system cost accounting accounting information system accounting organizational impact

Methods: qualitative interview design principle action design research design science personal interview

Feedback at scale: designing for accurate and timely practical digital skills evaluation

2020 | European Journal of Information Systems | Citations: 9

Authors: Piccoli, Gabriele; Rodriguez, Joaquin; Palese, Biagio; Bartosiak, Marcin Lukasz

Abstract: The global demand for digital proficiency has resulted in increasing pressure to ... Expand

Abstract: The global demand for digital proficiency has resulted in increasing pressure to "massify" education. As practical digital skills development becomes more important, there is a need to design accurate and timely performance feedback systems that can scale to a large number of learners. This paper contributes meta-requirements and design principles for designing a socio-technical artefact that offers a solution to the general problem of providing performance feedback at scale. The artefact evaluation provides interesting results for achieving the three objectives of a) scalability to a large number of learners, b) validity and reliability of the feedback, and c) positive impact on learners' behaviour and engagement with the feedback system. These results are obtained through the synergistic contribution of pedagogical prioritisation (i.e., what skills to cover), assignment design (i.e., what tasks to use to evaluate mastery) and automated measurement (i.e., grading engine functionalities for error detection). Collapse

Topics: IT skill spreadsheet mobile application MongoDB personal computer

Methods: machine learning design principle design artifact design science kernel theory

Designing a Machine Learning Model to Predict Cardiovascular Disease Without Any Blood Test

2019 | DESRIST | Citations: 1

Authors: Brahma, Arin; Chatterjee, Samir; Li, Yan

Abstract: Healthcare in the USA is struggling with alarming levels of hospital readmission ... Expand

Abstract: Healthcare in the USA is struggling with alarming levels of hospital readmission. Cardio Vascular Disease (CVD) has been identified as the most frequent cause. While the factors related to high hospital readmission are complex, according to prior research, early detection and post-discharge management has a significant positive impact. However, the widening gap between the number of patients and available clinical resources is acutely aggravating the problem. A solution that can effectively identify well patients at risk of future CVDs will allow focusing limited clinical resources to a more targeted set of patients, leading to more widespread early detection, prevention and disease progression management. This in turn, can reduce CVD-related hospital readmissions. Moreover, if the patient data required by such a solution can be collected without any blood test or invasive procedure, the addressable patient population can be vastly expanded to include home care, remote, and impoverished patients while delivering cost savings of the invasive procedures. Using a Design Science Research (DSR) approach, this research has led to the design and development of a machine learning based predictor artifact capable of identifying patients with future CVD risks. The performance of this predictor artifact, as measured by the area under the receiver operating characteristic (ROC) curve, is 0.859. The sensitivity or recall is 85.9% at probability threshold of 0.5. The significant differentiating feature of this artifact lies in its ability to do so without any blood test or invasive procedure. Collapse

Topics: artificial intelligence electronic health record cloud computing Microsoft Azure usability

Methods: random forest classification machine learning computational algorithm design science logistic regression

IT-ENABLED IDEA CROWDSOURCING – A MEAN TO PROMOTE GENDER EQUITY IN IT RESEARCH INSTITUTIONS

2017 | European Conference On Information Systems | Citations: 0

Authors: Gorbacheva, Elena; Barann, Benjamin

Abstract: The paper is aimed at enhancing understanding of how under-representation of wom ... Expand

Abstract: The paper is aimed at enhancing understanding of how under-representation of women in IT (Information Technology) research institutions, as well as other challenges related to gender equity, can be addressed with the help of IT-enabled idea crowdsourcing. A systematic literature review was conducted to understand how the topic of gender equity promotion via collaboratively used IT artefacts has been addressed in extant research. Insights from the literature review, overview of existing related IT artefacts, and iterative discussions with scholars in the IT field have resulted in a set of requirements to the idea crowdsourcing platform aimed at the promotion of gender equity in IT research institutions. These requirements were analysed further and could be categorised into those specific for the target platform and those relevant also for other idea crowdsourcing platforms (with or without further adaptation). This study addresses a novel and important research topic and might be of value for practitioners. Collapse

Topics: crowdsourcing database system IT career brainstorming technology adoption

Methods: structured literature research design artifact focus group literature study design process

Sensing the Future: Designing Predictive Analytics with Sensor Technologies

2015 | European Conference On Information Systems | Citations: 1

Authors: Furtak, Szymon; Avital, Michel; Pedersen, Rasmus U.

Abstract: As digital technologies become prevalent and embedded in the environment, "smart ... Expand

Abstract: As digital technologies become prevalent and embedded in the environment, "smart" everyday objects like smart phone and smart homes have become part and parcel of the human enterprise. The ubiquity of smart objects that produce ever-growing streams of data presents both challenges and opportunities. In this paper, we argue that extending these data streams, referred to as "predictive analytics", provides a solid basis for the design and development of IS artefacts that can generate additional value. Subsequently, we introduce a model for Designing Information Systems with Predictive Analytics (DISPA), extending Design Science Research specifically towards predictive analytics. The model is evaluated based on a case study of MAN Diesel and Turbo, a leading designer of marine diesel engines. The case illustrates that the framework provides useful guidelines for developing environmentspecific sensor based predictive models that can out-perform the traditional state of the art predictive methods especially in volatile and uncertain environments. Collapse

Topics: knowledge base data warehouse SAP R/3

Methods: machine learning design artifact design science case study mixed method

Design Principles for Research Data Export: Lessons Learned in e-Health Design Research

2013 | DESRIST | Citations: 0

Authors: Mustafa, Mudassir Imran; Sjöström, Jonas

Abstract: Information technology (IT) allows for large-scale data collection and data anal ... Expand

Abstract: Information technology (IT) allows for large-scale data collection and data analysis, e.g. through logs of user behavior and online surveys. While the issue of structured access to data is extremely important, previous research has not sufficiently emphasized design of data export for research purposes. If researchers are to make their data accessible, they must be empowered to export data in a flexible manner. In this paper, we employ action design research to develop design principles for data export in an e-Health context. Design is informed by a sociomaterial world-view, object-oriented patterns and principles, and usability goals. Through three build-intervene-evaluate cycles in an empirical setting where randomized controlled trials are designed, we propose nine design principles and a conceptual architecture for data export. Implications for research and practice are discussed. Collapse

Topics: usability systems development user interface extensible markup language anonymity

Methods: design principle design artifact design process personal interview design science

Choosing the right business process maturity model

2013 | Information & Management | Citations: 11

Authors: Van Looy, Amy; De Backer, Manu; Poels, Geert; Snoeck, Monique

Abstract: We have built and tested a decision tool which will help organisations properly ... Expand

Abstract: We have built and tested a decision tool which will help organisations properly select one business process maturity model (BPMM) over another. This prototype consists of a novel questionnaire with decision criteria for BPMM selection, linked to a unique data set of 69 BPMMs. Fourteen criteria (questions) were elicited from an international Delphi study, and weighed by the analytical hierarchy process. Case studies have shown (non-)profit and academic applications. Our purpose was to describe criteria that enable an informed BPMM choice (conform to decision-making theories, rather than ad hoc). Moreover, we propose a design process for building BPMM decision tools. Collapse

Topics: decision making business process management supply chain management spreadsheet decision support system

Methods: survey delphi study design process design artifact case study

SEQUENCING DESIGN DNA: A SET OF METHODOLOGICAL ARTIFACTS FOR SEQUENCING SOCIO-TECHNICAL DESIGN ROUTINES

2010 | International Conference on Information Systems | Citations: 0

Authors: Gaskin, James; Lyytinen, Kalle; Thummadi, Veeresh; Schutz, Douglas; Yoo, Youngjin; Weiss, Aaron; Berente, Nicholas

Abstract: With the introduction of new digital and physical tools into the workplace, the ... Expand

Abstract: With the introduction of new digital and physical tools into the workplace, the process of design has dramatically changed over the past few decades. Thus, design processes have evolved into many forms which vary, not only between organizations, but within organizations, and even within teams over time. These myriad “mutations” of the design process call for a new method to identify patterns of design activity and their change in order to deeply understand the design process. In this paper we suggest a new method for identifying patterns of activity in design teams. Such activity involves composites of distributed interactions – both socially and across digital and physical artifacts. We argue that these identifiable patterns comprise the "DNA" of design routines. To capture these patterns, we extend the sequence analysis techniques that are commonly used in genetic research to capture a design team’s interactions with both digital and physical tools over time. Collapse

Topics: user experience database languages systems development information system use user interface

Methods: design science design process metamodel time series analysis longitudinal research

Theories: theory of affordance