A design science-based case study of retail chain delivery operations and its implications

Design Science Research (DSR) is a paradigm that centres on the development and evaluation of artefacts. While central, a proper scientific evaluation can significantly increase the work required to complete a DSR project. The high costs, workload, and delays caused by evaluations have been shown to lead to poor or absent evaluations. These findings present two paradoxes: (1) evaluation is considered essential, yet it is commonly done poorly or not at all; (2) DSR promises to improve research relevance through timely artefact development and reliability through scientific evaluation, yet poor and lengthy evaluations cause DSR to often fail to deliver on its promise. To address these paradoxes, this paper presents MEDS (Methods for Evaluation in Design Science), a four-step evaluation method that includes three component methods new to the evaluation guidance literature: MuSCoW (Must, Should, Could, Won’t), the DSR Evaluation Selection Framework, and Short-Scoping of evaluation methods. MEDS aims to address the above paradoxes and guide DSR researchers, especially novices, to achieve a programme of effective and resource-efficient DSR evaluations as an on-going component of existing DSR methodologies. By carefully planning, orchestrating, and scoping evaluation activities, MEDS delivers a rigorous evaluation programme without overwhelming researchers with a massive evaluation burden.

Since its inception, the Information Systems discipline has been striving to develop impactful papers that contribute to cumulative knowledge development. Yet, there is a surprising lack of insights on how scientific impact can be accomplished and to which extent this impact represents a substantial engagement with, and extension of the knowledge contributions of the original papers. Especially for review articles and design science research, there are both competing conceptions of what makes these papers impactful and a lack of empirical evidence that would inform this debate. Furthermore, there is a latent skepticism as to whether this sometimes staggering impact of review articles actually represents knowledge development. In a similar way, it is unclear how and to which extent design science research has stimulated meaningful, cumulative knowledge development in information systems. The goal of this thesis is therefore to (1) explain and to (2) distinguish the scientific impact of review articles and design science research. Specifically, the first goal considers overall scientific impact as the dependent variable whose association with antecedent factors is analyzed by regression methodologies. The second goal zooms in on the concept of scientific impact and considers it as a relation between citing and cited papers that is explored through methodologies of manual content analysis and machine learning classification. With Paper 1, I develop the foundation of knowledge development through review articles by crystallizing their contributions and aligning them with their underlying knowledge conversion processes in an overarching framework. This framework is based on the abstraction and codification of knowledge and thereby integrates two essential dimensions of knowledge development. Overall, the foundation developed in the first paper informs the underlying conception of knowledge development of both review articles and citing papers. Addressing the first goal, Papers 2 and 3 develop and test scientometric impact models explaining the scientific impact of review articles and design science research, respectively. Beyond common control variables related to the journal and author level, they offer distinct insights for each type of paper. For review articles, I identify strong effects related to methodological transparency and the development of a research agenda, which vary depending on the type of review. For design science research, I show that theorization and novelty drive scientific impact. Concerning the second goal, Papers 4 and 5 distinguish different types of scientific impact of review articles and design science research, respectively. To analyze the different types of impact that review articles have on their overwhelming number of citing papers, I develop machine learning classifiers. Specifically, I distinguish ideational impact, which corresponds to a substantial engagement with and development of the knowledge contributions of the review article, from perfunctory impact, which corresponds to more trivial connections to the review article. In a similar, though not automated way, I analyze the types of impact of information systems design theories, a particular type of design science research. These analyses primarily focus on whether follow-up research tests and extends these theories. Based on our content analysis, I identify an alarming paucity of follow-up research in this area and develop specific guidelines for the design science community to address this challenge. The thesis concludes with an overview of the research contributions, implications for research practice, future research opportunities, and final remarks.

Design science research (DSR) aims to deliver innovative solutions for real-world problems. DSR produces Information Systems (IS) artifacts and design knowledge describing means-end relationships between problem and solution spaces. A key success factor of any DSR research endeavor is an appropriate understanding and description of the underlying problem space. However, existing DSR literature lacks a solid conceptualization of the problem space in DSR. This paper addresses this gap and suggests a conceptualization of the problem space in DSR that builds on the four key concepts of stakeholders, needs, goals, and requirements. We showcase the application of our conceptualization in two published DSR projects. Our work contributes methodologically to the field of DSR as it helps DSR scholars to explore and describe the problem space in terms of a set of key concepts and their relationships.

This book is an introductory text on design science, intended to support both graduate students and researchers in structuring, undertaking and presenting design science work. It builds on established design science methods as well as recent work on presenting design science studies and ethical principles for design science, and also offers novel instruments for visualizing the results, both in the form of process diagrams and through a canvas format. While the book does not presume any prior knowledge of design science, it provides readers with a thorough understanding of the subject and enables them to delve into much deeper detail, thanks to extensive sections on further reading. Design science in information systems and technology aims to create novel artifacts in the form of models, methods, and systems that support people in developing, using and maintaining IT solutions. This work focuses on design science as applied to information systems and technology, but it also includes examples from, and perspectives of, other fields of human practice. Chapter 1 provides an overview of design science and outlines its ties with empirical research. Chapter 2 discusses the various types and forms of knowledge that can be used and produced by design science research, while Chapter 3 presents a brief overview of common empirical research strategies and methods. Chapter 4 introduces a methodological framework for supporting researchers in doing design science research as well as in presenting their results. This framework includes five core activities, which are described in detail in Chapters 5 to 9. Chapter 10 discusses how to communicate design science results, while Chapter 11 compares the proposed methodological framework with methods for systems development and shows how they can be combined. Chapter 12 discusses how design science relates to research paradigms, in particular to positivism and interpretivism. Lastly, Chapter 13 discusses ethical issues and principles for design science research.

Evaluation of design artefacts and design theories is a key activity in Design Science Research (DSR), as it provides feedback for further development and (if done correctly) assures the rigour of the research. However, the extant DSR literature provides insufficient guidance on evaluation to enable Design Science Researchers to effectively design and incorporate evaluation activities into a DSR project that can achieve DSR goals and objectives. To address this research gap, this research paper develops, explicates, and provides evidence for the utility of a Framework for Evaluation in Design Science (FEDS) together with a process to guide design science researchers in developing a strategy for evaluating the artefacts they develop within a DSR project. A FEDS strategy considers why, when, how, and what to evaluate. FEDS includes a two-dimensional characterisation of DSR evaluation episodes (particular evaluations), with one dimension being the functional purpose of the evaluation (formative or summative) and the other dimension being the paradigm of the evaluation (artificial or naturalistic). The FEDS evaluation design process is comprised of four steps: (1) explicate the goals of the evaluation, (2) choose the evaluation strategy or strategies, (3) determine the properties to evaluate, and (4) design the individual evaluation episode(s). The paper illustrates the framework with two examples and provides evidence of its utility via a naturalistic, summative evaluation through its use on an actual DSR project.

INTRODUCTION
 This paper partly envisages the research results of the European Regional Development Fund (ERDF) project (see Acknowledgements). The task is to create an innovative digital game in the cross-cutting genres of art game and educational game. The game presents the specific aspects of digital art games and their historical background. Work on the new game will be carried out in a collaboration of the researcher, Dr.art. Ieva Gintere (Vidzeme University of Applied Sciences, Latvia) and the game artist, Mag.art. Kristaps Biters (Latvia). The game is being created in the framework of a Post-doctoral project led by Ieva Gintere during 2018-2021.
 MATERIALS AND METHODS
 Unity3d for game design. Blender 3d object design. Audacity and Abletone music generation and editing. Photoshop, illustrator for game texture, art design.
 RESULTS
 The study presents an insight into contemporary digital game theory and a new threefold method of game creation named RKTR (research / knowledge transfer / research). In this model, the game is created on the basis of research and knowledge transfer: knowledge gained in the research process is transferred to the players. The game also functions as a platform of new knowledge construction as the secondary task of the game is to collect the results of the players in order to analyse the new creative tendencies and to foresee the art trends of tomorrow.
 The proposed method focused on the aspect of knowledge transfer is constructed as a three-level spiral:
 - research-based game creation (the game is based on the results of research),- knowledge transfer (the game transfers the research results to the player),- use of the gameplay results in research (the game creators collect the data of the gameplay for new research).
 The existing game designers and theoreticians carry out research in action where the game design is united with the game research. In the discourse of digital gaming, this is a widespread method. However, there is a missing part in this model. Knowledge gained in this type of research does not flow beyond the circle of the game’s creators and researchers. This knowledge stays within the society of the game’s designers and researchers, and functions as a tool for their future work. Knowledge is an instrument for experts, and it is not transferred to the regular player. The existing model of a research-based game helps to obtain formal and professional knowledge: it is a know-how, it tells a designer how to build a game, but it is not meant for the player. The aim of the new digital game that is being created in this project, is to connect the research results with the player so that the knowledge acquired in the research process is effectively transferred to the general public.
 DISCUSSION
 Taking into account that art today is largely interactive, the new art game will let its user play with trends of digital art such as noise, generative art and others, and to create new ones. The aim of this project is to raise the interest of a wide-ranging public for contemporary art and to point out the newest creative tendencies in art. The game would develop the creative skills of players and teach them the current trends in digital art. At the same time the game would project the inheritance of art from the age of modernism into the digital world by teaching the player to recognize it (for instance, generative art is a successor to the Fluxus movement in modernism). The new art game is intended to educate the player and to stimulate his/her creative forces.
 The Design Science Research method is being used in this study in order to cross-cut such remote fields as the general public, the arthouse world, codes of modern art and the tastes of the general public. The Design Science Research method helps boost efficiency and interest towards contemporary art games. It intends to integrate seemingly distant disciplines and seeks parallels in different areas in order to gain new knowledge and adapt fresh approaches. By finding common aspects in different areas, Design Science Research fuses areas and invites new trends into a research field.
 ACKNOWLEDGEMENTS
 This study has been supported by a grant from the European Regional Development Fund research “Leveraging ICT product innovations by enhancing codes of modern art” No. 1.1.1.2/VIAA/1/16/106 within the Activity 1.1.1.2 “Post-doctoral Research Aid” of the Specific Aid Objective 1.1.1 “To increase the research and innovative capacity of scientific institutions in Latvia and the ability to attract external financing, investing in human resources and infrastructure” of the Operational Program “Growth and Employment”. Homepage of the research: http://va.lv/en/research/research/leveraging-ict-product-innovations-enhancing-codes-modern-art

Several papers have addressed the theory foundation of DSR. While researchers usually emphasize that the existence of such a knowledge base (KB) is essential for high quality design science research (DSR), opinions depart what kind of knowledge comprises such a knowledge base and which qualitative requirements apply regarding the knowledge leveraged. Some researchers demand that DSR is based on descriptive formal theories, while other scholars extend the width of the knowledge base also to unverified empirical evidence, conceptual knowledge and prescriptive knowledge. In order to provide some guidance for practical DSR, we apply literature review methodology on recent DSR articles to determine the common practice regarding the use and development of knowledge bases in previous projects. Based on this investigation, we discuss current issues, derive implications for future research and suggest measures to strengthen the role of the knowledge base in DSR.

The papers in this special section focus on design science research in information systems and technology. The rapid digital transformation of businesses and society creates new challenges and opportunities for information systems (IS) research, with the designing of system becoming a strong focus. Technologies, such as blockchain, cloud computing, and wearable devices, have spawned a paradigmatic shift in the design of IS. Thus, design science research in IS has evolved to become a mature yet thriving area of research. Design science seeks to extend the boundaries of human and organizational capabilities by designing new and innovative constructs, models, methods, processes, and systems. Scholars having diverse backgrounds in fields, such as IS, computer science, software engineering, energy informatics, and medical informatics, are actively engaged in generating novel solutions to interesting design problems in IS.

Due to rapidly changing business environments, purchasing and supply management (PSM) organisations are constantly confronted with new problems impacting organisational performance. PSM research can address these problems through design science research. Design science is also regarded as the science of the artificial. Design science research is a methodology that aims to systematically generate knowledge for the design, synthesis, testing, and evaluation of human-made artefacts (e.g., tools, interventions, policies) that solve practical problems. PSM artefacts such as the purchasing portfolio matrix invented by Kraljic (1983) represent a valuable opportunity to solve problems in the PSM discipline. However, our artificial-intelligence (AI)-based analysis of the discipline's flagship journal, the Journal of Purchasing and Supply Management (JPSM), indicates that design-oriented publications in PSM are underrepresented, accounting for less than 4% of the total publications. We argue that existing PSM research should be complemented with more design-oriented research, and address the following research question: How can PSM scholars publish more design-oriented research? Our objectives are to (1) provide arguments for advancing PSM as a design science, (2) nurture a better understanding of design science research as a methodology, and (3) propose publication guidelines that enable researchers to present design-oriented research in a management journal.

Design science research (DSR) has become a well-accepted research paradigm in information system research. DSR aims at solving people’s obstacles by creating solutions and thus bringing about human development. In this paper, we present lessons learned from design projects conducted in Tanzania since 2015. These projects focused on solving Tanzanian challenges in a number of sectors: street vending businesses, women traders, small-scale farmers, micro traders, and education. We reviewed six projects carried out in Tanzania using documentary review and open-ended questionnaires. The findings revealed how researchers reinforce the DSR framework, and the motives, challenges, and lessons learned from the application of DSR in sparse resource settings to inform future designs. The findings of the current study will help existing and future IT designers, policymakers, curriculum developers, researchers, and other information and communications technologies for development stakeholders to come up with appropriate solutions for inclusive development.

Action research (AR) prides itself on being a field of both theoretical and practical inquiry. Its scholarly identity rests heavily on framing participants as engaged, subjective, and participatory beings who learn and change through research processes. Yet, action research struggles to be considered a rigorous methodological field of inquiry and certainly there have been those who have raised questions about its validity as a research method. Where action research is used, qualifications and justifications abound as people struggle to have their research heard over other disciplines and techniques that claim more validity or appropriateness of methods. As a community development practitioner, I have employed AR approaches in the design and application of projects. As an academic, I have had the opportunity to design and facilitate meetings using participatory action research methods for data collection and to develop ground-up interventions with primary health care professionals. Therefore, I was eager to read about AR theoretical developments and to examine this text for its core purpose: as a to guide research and practice. The handbook boasts 32 chapters covering theory, practices, exemplars, and skills which I reviewed with particular attention to where, how, and why I would use the content and whether it offered what a research handbook should—practical assistance in design, application, analysis, and synthesis for AR. Overall, the handbook does provide extensive examples about research projects and process. In future editions though, I would like to see more attention to complementary methods that can be employed in AR and attention to methods for the analysis of data generated via action research approaches. URN: urn:nbn:de:0114-fqs0903268

ABSTRACTModelling is a central activity in practical engineering and something that is also useful in engineering education research (EER). Additionally, qualitative research methods have found important applications in engineering research, although their use in EER has not always been widely accepted. Design science research is a qualitative research approach in which the object of study is the design process, i.e. it simultaneously generates knowledge about the method used to design an artefact and the design or the artefact itself. This paper uses techniques from design science research to analyse the method used when deriving the ‘learning of a complex concept’ (LCC) model, which we developed while designing teaching sequences for a course on electrical engineering. Our results demonstrate the value of design science research in EER and suggest that the LCC model is generally applicable in this field.

Not much is known about how design knowledge is re-used in Design Science Research (DSR). The concepts of generalization and transfer as different types of knowledge-building and re-use are discussed in other disciplines and in Information System Research in general, but less so in DSR. Offermann et al. [1] proposed three ranges of design theories and seven strategies for how to create and generalize design knowledge. In this paper, we classify all DESRIST 2006 - 2010 publications according to design range and research strategy. By doing so, we empirically ground the merely theoretically established research strategies, and are able to discover three additional strategy types. The literature analysis shows that the specification of design range and strategy in abstracts is often incomplete or misleading. Based on the analysis we recommend template abstracts for design science publications which guide researchers on how to include all relevant information about design knowledge they (re-)used.

The debate ensues as to whether the traditional focus of computing research on theory development and verification and therefore has adequate immediate practical relevance. Despite increasing claims of the potential of design science research (DSR) to enhance the utility of the IT artifact and consequently practical relevance of research, many computing researchers seem to be reticent to accept this paradigm as a legitimate form of scholarly research. DSR is a relatively new paradigm in computing and little is known about its uptake in South Africa. In this paper, we investigate the opinions about DSR among South African computing scholars. Findings from a survey of 53 respondents indicate low adoption rates. The paper also investigates some of the key barriers preventing the uptake of DSR. The paper concludes with some implications as well as suggestions for building a local DSR community.

In Education, we develop artifacts: classes, didactic resources and educational practices. It is possible to interrelate the development of an artifact with the production of theoretical knowledge, and Design Science Research (DSR) is the approach we present on this article, used to do scientific research connected to the development of artifacts. Through this approach, the goal is to design a different reality, modified by artifacts designed to solve problems in given contexts, with the scientific knowledge being the result of the investigation of the use of the artifact in a given situation. DSR is an approach that is still under discussion; in this article, we show how our research group has been appropriating DSR. In particular, we present the DSR Model in which we synthesized the main lessons learned by our group. In order to exemplify the use of the DSR Model, we present the research on Smart Musical Mats. We consider that the DSR Model has been helping make our group’s researches more rigorous in theoretical, epistemological and methodological terms and, thus, more relevant in scientific terms. We present this model because we consider it to be a useful instrument to support other researchers that want to consider and use DSR.