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Über dieses Buch

This book constitutes the proceedings of the 13th International Conference on Design Science Research in Information Systems and Technology, DESRIST 2018, held in June 2018 in Chennai, India.

The 24 full papers presented in this volume were carefully reviewed and selected from 96 papers. The contributions are organized in topical sections named: HCI and Design, Design Foundations, Design Foundations, Design in Healthcare, Advances in Data Science and Analytics, ICT for Development, Designing Cybersecurity, and Design Applications.

Inhaltsverzeichnis

Frontmatter

HCI and Design

Frontmatter

Design Principles for Room-Scale Virtual Reality: A Design Experiment in Three Dimensions

Abstract
Virtual reality hardware, and software tools that support developing for virtual reality applications, are rapidly maturing. Specifically, room-scale virtual reality hardware that lets users walk around in virtual environments is becoming increasingly easier to purchase and adopt. With this follows a need for researching potential design theories for how to design and evaluate this class of systems. We contribute with a nascent design theory containing a high-level conceptual framework of dimensions and design principles of how to design room-scale virtual reality applications that create engaging user experiences. We identify meta-requirements from kernel theories from the human-computer interaction paradigm and evaluate two different VR artefacts and their applicability. Two central, higher level design principles are derived from the evaluation.
Jonas Schjerlund, Magnus Rotvit Perlt Hansen, Josefine Gill Jensen

Designing Conversational Agents for Energy Feedback

Abstract
Reducing and shifting energy consumption could contribute significantly to a more sustainable use of energy in households. Studies have shown that the provision of feedback can encourage consumers to use energy more sustainably. While there is wide variety of energy feedback solutions ranging from in-home displays to mobile applications, there is a lack of research on whether and how conversational agents can provide energy feedback to promote sustainable energy use. As conversational agents, such as chatbots, promise a natural and intuitive user interface, they may have great potential for energy feedback. This paper explores how to design conversational agents for energy feedback and proposes design principles based on existing literature. The design principles are instantiated in a text-based conversational agent and evaluated in a focus group session with industry experts. We contribute with valuable design knowledge that extends previous research on the design of energy feedback solutions.
Ulrich Gnewuch, Stefan Morana, Carl Heckmann, Alexander Maedche

ServiceDesignKIT: A Web Platform of Digital Service Design Techniques

Abstract
A broad spectrum of design techniques is available to support digital service design processes. With the growing number of available design techniques, selecting suitable design techniques becomes increasingly challenging, especially for design novices. In this paper, we present design principles and their instantiation in the Web platform ServiceDesignKIT for supporting design novices in the process of identifying and selecting design techniques. ServiceDesignKIT is a platform that combines an experts’ top-down knowledge-based classification with novices’ bottom-up suggested tags. With this work, we contribute to the body of design knowledge of Web-based platforms that provides simple and efficient access to design techniques.
Xuanhui Liu, Erwin Tak-Ming Leung, Peyman Toreini, Alexander Maedche

Design Foundations

Frontmatter

Making Sense of Design Science in Information Systems Research: Insights from a Systematic Literature Review

Abstract
This study presents insights from a systematic literature review of design science in IS. A lack of agreement on how to classify and demarcate design science from behavioral science research led to the iterative development of a theoretically-grounded, encompassing framework of knowledge contributions in the larger context of general scientific inquiry as well as associated coding schemata. The results of the systematic literature review support our framework and the idea that paradigmatic boundaries (e.g., design science versus behavioral science research) are difficult to uphold for contemporary information systems research.
Alexander Herwix, Christoph Rosenkranz

Design Science in the Field: Practice Design Research

Abstract
There exist different types or genres of design science research (DSR) in information systems, like laboratory-oriented and practice-oriented DSR. This paper investigates arguments for a practice-oriented approach to DSR. It uses the research approach of practice research as a starting point to elaborate on a practice-oriented DSR approach we label Practice Design Research (PDR). In doing so, we address two unresolved issues in IS DSR: Theorizing and evaluation. PDR consists of two inter-related sub-activities: theorizing and situational design inquiry. The conduct of situational design inquiry is described as iterative cycles of (1) pre-evaluate, (2) plan & design, (3) test & intervene and (4) post-evaluate. We justify the foundations of these iterative sub-activities/cycles through a theoretically informed argument based on pragmatist philosophy and practice theory.
Göran Goldkuhl, Jonas Sjöström

Utilizing, Producing, and Contributing Design Knowledge in DSR Projects

Abstract
We distinguish several design knowledge types in IS research and examine different modes of utilizing and contributing design knowledge that can take place during design science research (DSR) projects. DSR projects produce project design knowledge, which is project-specific, possibly untested, conjectural, and temporary; thus, distinct from the more stable contributions to the propositional and prescriptive human knowledge bases. We also identify solution design knowledge as distinct from solution design entities in the prescriptive knowledge base. Each of the six modes of utilizing or contributing knowledge (i.e. design theorizing modes) we examine draws on different knowledge types in a different way to inform the production of project design knowledge (including artifact design) in a DSR project or to grow the human knowledge bases in return. Design science researchers can draw on our design theorizing modes and design knowledge perspectives to utilize the different extant knowledge types more consciously and explicitly to inform their build and evaluation activities, and to better identify and explicate their research’s contribution potential to the human knowledge bases.
Andreas Drechsler, Alan R. Hevner

Design in Healthcare

Frontmatter

Designing “Living” Evidence Networks for Health Optimisation: Knowledge Extraction of Patient-Relevant Outcomes in Mental Disorders

Abstract
Over 70 randomised controlled trials (RCTs) are published in MEDLINE every day; in which the volume and velocity of unstructured evidence data have become a great challenge to human manual processing capabilities. There is an emerging need for a dynamic, evolving design of “living” evidence networks as the best source of health optimisation in evidence-based medicine. This study, therefore, investigated the text and layout features of unstructured full-texts in the biomedical literature to design IT artefacts for building high-quality and up-to-date evidence networks of RCTs. As a result, network meta-analyses can be automated for comparative adverse effects of treatments in chronic disorders such as Major Depressive Disorder and Bipolar Disorder. The study outcomes extended the technological boundary of health optimisation technologies, and contributed to the cumulative development of patient-relevant health care and shared decision-making.
Hoang D. Nguyen, Øystein Eiring, Danny Chiang Choon Poo

Assessing Strategic Readiness for Healthcare Analytics: System and Design Theory Implications

Abstract
The adoption of analytics solutions in hospitals is a recent trend aimed at fact-based decision making and data-driven performance management. However, the adoption of analytics involves diverse stakeholder perspectives. Currently, there is a paucity of studies that focus on how the practitioners assess their organizational readiness for health analytics (HA) and make informed decisions on technology adoption given a set of alternatives. We fill this gap with our study by designing a strategic assessment framework guided by a DSRM approach that iteratively extends our past artifact. Our approach first entails the use of many in-depth case-studies, as well as embedded experts from the industry to inform the objective setting and design process. These inputs are then supported by two multi-criteria decision-making methods. We also evaluate our framework with healthcare practitioners for both design validity and future iterations of this project. Implications of our work for theory of design and action are also highlighted.
Sathyanarayanan Venkatraman, Rangaraja P. Sundarraj, Ravi Seethamraju

Easy Nutrition: A Customized Dietary App to Highlight the Food Nutritional Value

Abstract
Healthy Eating is a two-part system that should strike a balance between food quality and food quantity. In this study, we have designed, developed, and evaluated a nutrition app called, Easy Nutrition to highlight the nutritional value/quality of the food we eat. We introduced the novel concept of Nuval rather than old concepts such as calorie counting. In this context, Easy Nutrition presents the food nutrition in a simple, easy to understand manner. Easy Nutrition also tackles the cultural differences by suggesting recipes tailored to users’ food preferences. This paper delineates the build and evaluate phase of Easy Nutrition. Easy Nutrition has been evaluated from a sociotechnical perspective in for its of utility and quality. We conducted a cross-sectional study on Amazon Mechanical Turk platform to evaluate Easy Nutrition on a wide population. The results show that Easy Nutrition demonstrates a fairly high level of usability (SUS = 69.1), attractiveness (mean = 1.59), and hedonic and pragmatic quality.
Mayda Alrige, Samir Chatterjee

Taxonomy Development for Virtual Reality (VR) Technologies in Healthcare Sector

Abstract
The paper presents a Design Science Research (DSR) project, which was conducted to develop taxonomy for Virtual Realty VR technology in healthcare. In this paper, we discuss the process involved to design a comprehensive taxonomy framework of VR technologies that classify VR tools within the healthcare industry. The framework is intended to help practitioners, researchers, and developers to agree on a common language in order to analyze the usefulness and gaps in existing VR applications in healthcare. The taxonomy guide evaluates the process of VR tools to determine where each VR device fits in the healthcare industry; identifies the uniqueness and originality of new VR devices; and recognizes the needs and gaps for further VR application development within this industry.
Maram Almufareh, Duaa Abaoud, Md Moniruzzaman

Dengue Prediction Using Hierarchical Clustering Methods

Abstract
The occurrence of dengue is rapidly increasing in every year. Considering the welfare of the public, it is essential to have detailed study on the affected areas of dengue and its intensity for the control of disease. This paper uses hierarchical clustering technique to classify the data of dengue cases reported and deaths occurred in various states of India. An agglomerative clustering of ward method is used for clustering. The outcomes are represented in Indian map using shape file with RStudio. The data is predicted for 2018, by logarithmic transformation using linear models of regression. K-Nearest Neighbour algorithm is used for predicting the cluster data for 2018. The results have shown that the frequency of dengue happening or the intensity is considerably reduced in many states.
S. Vandhana, J. Anuradha

Collaborative Literature Search System: An Intelligence Amplification Method for Systematic Literature Search

Abstract
In this paper, we present a method for systematic literature search based on the symbiotic partnership between the human researcher and intelligent agents. Using intelligence amplification, we leverage the calculation power of computers to quickly and thoroughly extract data, calculate measures, and visualize relationships between scientific documents with the ability of domain experts to perform qualitative analysis and creative reasoning. Thus, we create a foundation for a collaborative literature search system (CLSS) intended to aid researches in performing literature reviews, especially for interdisciplinary and evolving fields of science for which keyword-based literature searches result in large collections of documents beyond humans’ ability to process or the extensive use of filters to narrow the search output risks omitting relevant works. Within this article, we propose a method for CLSS and demonstrate its use on a concrete example of a literature search for a review of the literature on human-machine symbiosis.
Andrej Dobrkovic, Daniel A. Döppner, Maria-Eugenia Iacob, Jos van Hillegersberg

Advances in Data Science and Analytics

Frontmatter

ALDA: An Aggregated LDA for Polarity Enhanced Aspect Identification Technique in Mobile App Domain

Abstract
With the increased popularity of the smart mobile devices, mobile applications (a.k.a apps) have become essential. While the app developers face an extensive challenge to improve user satisfaction by exploiting the valuable feedbacks, the app users are overloaded with way too many apps. Extracting the valuable features from apps and mining the associated sentiments is of utmost importance for the app developers. Similarly, from the user perspective, the key preferences should be identified. This work deals with profiling users and apps using a novel LDA based aspect identification technique. Polarity aggregation technique is used to tag the weak features of the apps the developers should concentrate on. The proposed technique has been experimented on an Android review dataset to validate the efficacy compared to state-of-the-art algorithms. Experimental findings suggest superiority and applicability of our model in practical scenarios.
Binil Kuriachan, Nargis Pervin

Development of a Data-Driven Business Model Transformation Tool

Abstract
Rapidly changing environments and customer demands force companies to transform their business models in ever shorter periods of time. However, existing approaches like the business model canvas and corresponding tools mainly focus on documentation on a strategic level and do not actively support the business model transformation process from a current state towards a target state. To address this problem, we derive requirements for a business model transformation tool. We translate these requirements into design principles and present a toolset for data-driven business model transformation. This toolset enables companies to extract status quo business models from existing operational information systems. Furthermore, it allows the representation of explicit relationships between the different value dimensions of a business model and enables quantifying the impact of changes. The result of this paper is a set of requirements, design principles as well as a tool instantiation, which can actively support the business model transformation process.
Dominik Augenstein, Christian Fleig, Alexander Maedche

Towards Collaborative Data Analysis with Diverse Crowds – A Design Science Approach

Abstract
The last years have witnessed an increasing shortage of data experts capable of analyzing the omnipresent data and producing meaningful insights. Furthermore, some data scientists mention data preprocessing to take up to 80% of the whole project time. This paper proposes a method for collaborative data analysis that involves a crowd without data analysis expertise. Orchestrated by an expert, the team of novices conducts data analysis through iterative refinement of results up to its successful completion. To evaluate the proposed method, we implemented a tool that supports collaborative data analysis for teams with mixed level of expertise. Our evaluation demonstrates that with proper guidance data analysis tasks, especially preprocessing, can be distributed and successfully accomplished by non-experts. Using the design science approach, iterative development also revealed some important features for the collaboration tool, such as support for dynamic development, code deliberation, and project journal. As such we pave the way for building tools that can leverage the crowd to address the shortage of data analysts.
Michael Feldman, Cristian Anastasiu, Abraham Bernstein

ICT for Development

Frontmatter

An Argument for Post-Hoc Collective Intelligence

Abstract
Despite the advancement of artificial intelligence there are still some problems which are beyond current computing capabilities including some high dimensional pattern recognition tasks and those that require creativity or intuition. These problems are often delegated to interested participants through carefully engineered human computation systems, crowdsourcing systems or collective intelligence systems. However, all these systems require a fore-planned platform to coordinate the production of the intellectual product such as a vote or a statement from the human participants. Outside of these platforms, however, there is a vast amount of independently created intellectual products, for example in tweets, YouTube comments, online articles, internal company reports and minutes. These are largely untapped due to a lack of awareness of the potential that exists within them and the inaptness of the tools and techniques that would be required exploit the data. In this paper we propose Post-Hoc Collective Intelligence (PHCI) as a novel research and argue that it has important distinctions from the closely related research areas. In so doing we present an informed argument for the PHCI framework having 5 components which give structure to implementation and research pursuits.
Dean J. Jones, Gunjan Mansingh

An Ontological Approach to Classifying Cybercrimes in an ICT4D Context

Abstract
While the phenomenon of cybercrime remains a challenge for governments worldwide, it is even more of a challenge for countries in an ICT4D context since they possess limited technical skills and resources to respond to, investigate and prosecute nefarious cyber activities. Despite the challenges, governments have responded by establishing legal frameworks and Computer Security Incident Response Teams. However, scholars argue that the cybercrime phenomenon is still not well understood; which is compounded by the lack of an accepted, uniform cybercrime classification scheme or ontology with which to classify cybercrimes. While few classification schemes have been published, same are limited in that they are not comprehensive; i.e., they are unable to account for the range of and ever changing types of cybercrimes and, the schemes are largely incompatible, focusing on different perspectives. This makes holistic and consistent classification improbable. To address these gaps we propose a formal cybercrime classification ontology, expressed in OWL Ontology Language. In designing our ontology we were guided by the steps of the design science research methodology. This paper contributes a formal ontology of a ‘shared conceptualization’ of cybercrimes by police practitioners and researchers. The ontology presented here is improved over prior works since it incorporates multiple perspectives and its design is better able to handle existing and future cybercrimes, a most salient feature given the dynamic nature of cybercrimes. We demonstrate the ontology by applying it to an actual cybercrime case. The designed ontology effectively classifies the cybercrime and has the potential to improve cybercrime classification in ICT4D and developed contexts.
Charlette Donalds, Kweku-Muata Osei-Bryson

Extending DSR with Sub Cycles to Develop a Digital Knowledge Ecosystem for Coordinating Agriculture Domain in Developing Countries

Abstract
Still a large percentage of the world population, especially in developing countries are depending on agriculture for their livelihood. The agriculture domain in many developing countries is not well coordinated leading to over and under production of crops resulting in widely fluctuating market prices, waste and economic hardship for farmers. Rapidly growing Smartphone usage among farming community has opened new possibilities to develop a mobile based artefact to coordinate the agriculture production. We have developed an overall artefact; a Digital Knowledge Ecosystem using Design Science Research (DSR) methodology to solve this complex problem. The main project had many research challenges to solve and they were assigned to several sub-projects to address. The outputs of sub-projects created several artefacts. They were integrated to develop the overall artefact to achieve the main goal of the overall project. Managing the complexity of the overall project was a challenge. For this, we had to split three main cycles of DSR: Relevance, Design and Rigor into 6 DSR sub-cycles; Relevance – Problem Understanding and Relevance – Suitability Validation, Rigor – Learning and Rigor –Contribution, Design - Heuristic Search and Design - Functional Validation. This split enabled us to better coordinate the activities to address different aspects of the problem performed by different researchers, often in parallel at multiple geographical locations. The resulted mobile based Digital Knowledge Ecosystem initially developed for farmers in Sri Lanka is now being trialled in India and adapted to develop a Mobile based Information System for Nutrition Driven Agriculture for African Countries.
Tamara Ginige, Lasanthi De Silva, Anusha Walisadeera, Athula Ginige

Designing Cybersecurity

Frontmatter

Strategic Planning for IS Security: Designing Objectives

Abstract
Management of information systems (IS) security in organizations has been hampered by the apparent lack of inclusion of organizational security objectives in the traditional strategic planning process. In order to improve IS security strategic planning, we argue that there should be a renewed emphasis on security planning objectives. In this paper we present two sets of objectives – fundamental and means. We then define an evaluation mechanism for assessing the security posture of a firm. Based on case work in healthcare, we illustrate the usefulness of the security evaluation method for designing enterprise security.
Gurpreet Dhillon, Gholamreza Torkzadeh, Jerry Chang

A Prediction Model of Privacy Control for Online Social Networking Users

Abstract
With the growing popularity of social network sites (SNS), organizations have started to leverage them for encouraging both personal and professional data sharing. However, inherent privacy problems in social networks have become a concern for organizations deploying them. So companies have started investing in systems for evaluating employees’ behaviors on SNSs. In evaluating employees’ behaviors on SNSs, this study aims at developing a mechanism for learning users’ behaviors on SNS and predicting their control of privacy on SNS. Privacy prediction is based on the revelation of actual privacy characteristics of users through the analysis of their SNS usage patterns. Using the Design Science research methodology, this study presents the design and instantiation of a prediction model that is trained using survey data and SNS data of graduate students from a prominent Northeastern University in the United States, which is used to generate class labels associated with their privacy control. The prediction model provides a data analytics component for reliable predictions of users’ privacy control using Machine Learning algorithm SVM and a randomized ensemble of decision trees. The results suggest that the prediction model represents a reliable method for predicting privacy control based on user actions on SNS.
Rohit Valecha, Rajarshi Chakraborty, H. Raghav Rao, Shambhu Upadhyaya

A Knowledge Interface System for Information and Cyber Security Using Semantic Wiki

Abstract
Resilience against information and cyber security threats has become an essential ability for organizations to maintain business continuity. As bullet-proof security is an unattainable goal, organizations need to concentrate to select optimal countermeasures against information and cyber security threats. Implementation of cyber risk management actions require special knowledge and resources, which especially small and medium-size enterprises often lack. Information and cyber security risk management establish knowledge intensive business processes, which can be assisted with a proper knowledge management system. This paper analyzes how Semantic MediaWiki could be used as a platform to assist organizations, especially small and medium-sized enterprises, in their information and cyber security risk management. The approach adopts design science research and service design methodologies in the derivation and evaluation of the system.
Riku Nykänen, Tommi Kärkkäinen

Design Applications

Frontmatter

Capturing User Generated Video Content in Online Social Networks

Abstract
We build and evaluate an innovative artifact for the investigation of social content derived-platforms specifically to gain a unique understanding of the content shared and underlying behaviors of the contributors to these technology platforms. The artifact‘s innovation is derived from the solution’s unique approach to converting and analyzing the multimedia – especially video - content to gain interesting insights into the social network connectivity of the actors on a given technology platform. The artifact directly addresses a practical need for industry practitioners to analyze social video network content using a rigorous and evidence-based DSR approach.
Clinton Daniel, Matthew Mullarkey, Alan R. Hevner

Software-Embedded Evaluation Support in Design Science Research

Abstract
Even though the practice of integrating evaluative features into software has long been applied in commercially available software, it is still underrepresented in the Information Systems (IS) community. This paper presents a framework for embedded evaluation support. We are aware of the challenges of evaluation of socio-technical systems and take this issue into consideration in our framework. Our framework is the result of conceptualizations drawing from the evaluation discourse discussion on the topics of artifact evaluation in DSR. We also demonstrate our ideas through two examples of embedded evaluation support mechanisms designed and used in a DSR project in the Swedish healthcare sector.
Jonas Sjöström, Leona Chandra Kruse, Amir Haj-Bolouri, Per Flensburg

Towards a Collaborative, Interactive Web Services Composition Approach Based on an Intentional Group Recommender System

Abstract
Nowadays, organizations are integrating human-computer interaction (HCI) into their information systems. This trend resulted in gathering developers and end-users in different tasks, particularly, the interactive Web services composition (WSC) task. Indeed, to search for solutions that go beyond their individual limited views, an increasing demand of collaboration among users has emerged. However, they are still facing uncomfortable situations especially when they are invited to select the appropriate Web service among functionally similar ones. More support is then needed to provide an effective composition. In this regard, a group recommender system providing the required functionality while considering the users’ preferences, might be highly useful. In this paper, we present a holistic process spanning from capturing users requirements, constructing a global goal model “ColMAP” reflecting their intentions to performing a collaborative, interactive WSC. A step-by-step example illustrates the proposed process. We expect that this approach will pave the way for interactively, collaboratively engineered information systems.
Meriem Kasmi, Yassine Jamoussi, Henda Hajjami Ben Ghézala

Backmatter

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