A Fuzzy-Logical Approach for Integrating Multi-Agent Estimators

This paper proposes a novel approach for integrating estimations from multiple agents. The approach is based on the fuzzy set theory. However, compared to existing fuzzy logical methods that use fuzzy if-then rules, this method is based on solving an over-determined fuzzy equation system. The result is either a global inconsistency message or the consistent core of the equation system. We demonstrate the approach with data from an actual case study undertaken by a German automotive manufacturer

Extracting Causal Claims from Information Systems Papers with Natural Language Processing for Theory Ontology Learning

The number of scientific papers published each year is growing exponentially. How can computational tools support scientists to better understand and process this data? This paper presents a software-prototype that automatically extracts causes, effects, signs, moderators, mediators, conditions, and interaction signs from propositions and hypotheses of full-text scientific papers. This prototype uses natural language processing methods and a set of linguistic rules for causal information extraction. The prototype is evaluated on a manually annotated corpus of 270 Information Systems papers containing 723 hypotheses and propositions from the AIS basket of eight. F1-results for the detection and extraction of different causal variables range between 0.71 and 0.90. The presented automatic causal theory extraction allows for the analysis of scientific papers based on a theory ontology and therefore contributes to the creation and comparison of inter-nomological networks

Multi-National Topics Maps for Parliamentary Debate Analysis

In recent years, automated political text processing became an indispensable requirement for providing automatic access to political debate. During the Covid-19 worldwide pandemic, this need became visible not only in social sciences but also in public opinion. We provide a path to operationalize this need in a multi-lingual topic-oriented manner. Using a publicly available data set consisting of parliamentary speeches, we create a novel process pipeline to identify a good reference model and to link national topics to the cross-national topics. We use design science research to create this process pipeline as an artifact

A Framework for the Systematic Evaluation of Data and Analytics Use Cases at an Early Stage

Due to the immense growth of collected data and advancing big data technologies, there are countless potential use cases of data and analytics. But most data initiatives fail and do not bring the desired outcome. One essential reason for this situation is the lack of a systematic approach to evaluate and select promising analytics use cases. This study presents an evaluation framework that enables the systematic screening at an early stage by assessing nine criteria with the help of a scoring model. It also supports a prioritization among several use cases and facilitates the communication to decision makers. The action design research approach was followed to build, test, and evaluate the framework in three iterative design cycles. It was developed in close collaboration with Bundesdruckerei GmbH, an IT-security company owned by the German government that offers products and services for secure identities, data, and infrastructures

Hey Article, What Are You About? Question Answering for Information Systems Articles through Transformer Models for Long Sequences

Question Answering (QA) systems can significantly reduce manual effort of searching for relevant information. However, challenges arise from a lack of domain-specificity and the fact that QA systems usually retrieve answers from short text passages instead of long scientific articles. We aim to address these challenges by (1) exploring the use of transformer models for long sequence processing, (2) performing domain adaptation for the Information Systems (IS) discipline and (3) developing novel techniques by performing domain adaptation in multiple training phases. Our models were pre-trained on a corpus of 2 million sentences retrieved from 3,463 articles from the Senior Scholars' Basket and fine-tuned on SQuAD and a manually created set of 500 QA pairs from the IS field. In six experiments, we tested two transfer learning techniques for fine-tuning (TANDA and FANDO). The results show that fine-tuning with task-specific domain knowledge considerably increases the models' F1- and Exact Match-scores

Mind the Future Gap: Introducing the FOD Framework for Future-Oriented Design

There are many uncertainties and ambiguities in the design of future-oriented artifacts. Societal and environmental developments are unclear; technologies not ready; target users not accessible. Nevertheless, designing future-oriented artifacts provides opportunities to either create radical innovations that present a competitive advantage, or to engage with relevant stakeholders in a speculative way. This paper provides a framework for developing, discussing, and evaluating future-oriented artifacts, which was developed based on literature and conceptual theorizing. It consists of a process model and a morphological box, outlining eight categories of relevance along with several options to choose from. Subsequently, we applied the framework to an existing future design project to illustrate its applicability. The framework spans the space of possible design and evaluation approaches and, hence, provides a guiding schema for researchers and practitioners to discuss the potentials and implications of design concepts for future-oriented artifacts

Designing the Future With the “Delphi Design Sprint”: Introducing a Novel Method for Design Science Research

This paper introduces a novel innovation method that focuses on the development of future-oriented artifacts. The “Delphi Design Sprint” combines two existing methods—the Delphi method and Design Sprints. The development of the method follows an action research approach and was tested and validated in a university-led design project involving a panel of 20 international experts. This paper introduces the method and describes exemplary results of the project’s outcome

Predicting Healthcare Fraud in Medicaid: A Multidimensional Data Model and Analysis Techniques for Fraud Detection

It is estimated that approximately $700 billion is lost due to fraud, waste, and abuse in the US healthcare system. Medicaid has been particularly susceptible target for fraud in recent years, with a distributed management model, limited cross- program communications, and a difficult-to-track patient population of low-income adults, their children, and people with certain disabilities. For effective fraud detection, one has to look at the data beyond the transaction-level. This paper builds upon Sparrow's fraud type classifications and the Medicaid environment and to develop a Medicaid multidimensional schema and provide a set of multidimensional data models and analysis techniques that help to predict the likelihood of fraudulent activities. These data views address the most prevalent known fraud types and should prove useful in discovering the unknown unknowns. The model is evaluated by functionally testing against known fraud case

A Framework of Design Method Corroboration

Practitioners design artifacts of different kinds. Researchers and practitioners both create methods for designing such artifacts. The question arises whether those methods are actually valid and useful. In this conceptual paper, we argue that there is a need for “method corroboration”—the deliberate and reflected use and possible validation of a design method. We present a literature review of method corroboration in the IS and more specifically in the DSR literature. The findings are summarized as a conceptual model outlining eight strategies of method use, which are then condensed into a 2-by-2 framework of method corroboration. The results of this paper present insight into the current state of method corroboration in the DSR field and provide guidance for working with design methods in research and practice