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The study aims to explore and develop a smart route planning system for the cross-docking delivery operations of a large supermarket chain using an action research (AR) approach and assessing through a design science research (DSR) lens.

This study took a problem-solving AR (PAR) approach toward the delivery operational issue of the case firm. The research process has accorded with the solution incubation and the refinement phases defined by a DSR framework. An intervention-based research framework for DSR is developed to assess the validity of this study as a DSR research and derive mid-range theories.

Dramatic operational and financial improvements were achieved for the case firm. Significant and unintended environmental and social benefits were also found. A design proposition (DP) and several mid-range theories are proposed as an extension of AR research to DSR research.

A problem-solving DSR research can be better assessed by the intervention-based DSR framework developed in this study. DSR studies should be encouraged for both practical and theoretical advancement purposes.

A challenging business problem-solving study can be tackled effectively through an industry/academic collaboration taking a PAR approach to deliver substantial values and organization transformational results.

Drivers and store associates are safer with smart delivery operations in the case firm.

There are still limited PAR design science case studies in the supply chain/logistics research literature. The research experience and findings gained from this study provide more insights toward how this type of research can be conducted and assessed.

The purpose of this research paper is to present a pragmatic and systematic approach to conduct and document Design Science Research (DSR) activities with Focus Groups (FGs), exploring its continuous usage and providing traceability between problem, requirements, solutions and artefacts.

The approach is to conduct the research and produce the meta-model for DSR with FG, a DSR approach was adopted using a conceptual model for Action Design Research already available. The artefact is the result from a specific literature review to define requirements, a careful design and a refinement stage where it was widely used and tested in real IS implementation projects.

Rigorous and committed stakeholder engagement is a critical success factor in complex projects. The main outcome of this research is a specific meta-model for DSR with FG that delivers new insights and practical guidelines for academics and professionals conducting and documenting real-world research and development initiatives deep-rooted in stakeholders' participation.

The meta-model has been endorsed as a practical and useful artefact by the stakeholders participating in the IS projects where it was adopted. However, to fully demonstrate its capabilities and to become more robust, the model has to be further used and tested in other application situations and environments.

The usage of FGs in DSR has already been proposed as an effective way, either to study artefacts, to propose improvements in its design or to acknowledge the utility of those artefacts in field use. The paper provides a sound contribution to this line of research by presenting a meta-model that integrates process and data, as well as a set of practical templates and forms that may be used by researchers and practitioners to conduct their projects.

Service design is a multidisciplinary approach that is key to service innovation, as it brings new service ideas to life. In this context, the development of new service design methods and models for creating new service futures is an important stream of service design research. Such developments can benefit from a systematized research methodology that builds on existing knowledge and robustly evaluates the suitability of research contributions. To address this challenge, the purpose of this paper is to present design science research (DSR), an established methodology from the information systems field, and examine how it can be useful for service design research by supporting the development of new artifacts, such as service design constructs, methods and models.

This paper presents DSR and related literature and shows how DSR can support service design research through a step-by-step approach. A methodology to develop prescriptive-driven solutions for classes of problems, DSR can support service design research in developing rigorous and relevant research. One illustrative example of a service design research effort using the DSR approach is presented.

Building on DSR’s robust methodological background, this paper discusses how DSR can support service design research, namely, through the development of new methods and models, and how DSR can be adapted to leverage service design research participatory, iterative, human-centric and creative approach.

This paper provides an overview of DSR and proposes it as a methodology to conduct service design research, offering step-by-step guidance on the application of DSR in service design research and discussing how it can be adapted according to the specific characteristics of service design research and drive future research.

Design science research (DSR) is a structured approach for solving complex ill-structured problems in organizations through the development of an artefact followed by its validation. This paper aims to evaluate existing DSR methodology and propose specific accents to promote DSR for environmental, social and governance (ESG)-oriented operational excellence (OPEX) initiatives within organizations.

This commentary paper is based on an abductive reasoning approach to evaluate and understand DSR and assess its effectiveness for developing solutions to typical ESG-oriented OPEX-based problems within organizations.

Existing literature on DSR is reviewed, after which it is evaluated on its ability to contribute to the implementation of sustainable solutions for ESG-oriented OPEX-based problems. Based on the review, specific DSR methodological accents are proposed for the development of ESG-oriented OPEX-based solutions in organizations.

This conceptual paper contributes to the conceptual understanding of the applicability, limitations and contextual preconditions for applying DSR. This paper proposes an explicit and, in some ways, alternative view on DSR research for OPEX researchers to apply and further the body of knowledge on matters of sustainability (ESG) in operations management.

Currently, there is limited understanding and application of the DSR methodology for OPEX-based problem-solving initiatives, as appears in the scant literature on DSR applied for the implementation of OPEX based initiatives for ESG purposes. This paper aims to challenge and provide accents for DSR applied to OPEX-related problems by means of a DSR framework and thereby promotes intervention-based studies among researchers.

The proposed step-by-step methodology contains novel elements and is expected to be of help for OPEX-oriented academicians and practitioners in implementing DSR methodology for practical related problems which need research interventions from academics from Higher Education Institutions.

The systems approach is an exemplar of design science research (DSR), whereby specific designs yield generic knowledge. DSR is increasingly being adopted in logistics and operations management research, but many point to neglect of the human aspects of solutions developed. The authors argue that it is possible to look back at the history of the systems movement to seek precedent for ‘dealing’ with the social components, providing a methodologically pluralistic ‘research design’ framework. Thereby, systems approaches are foundational to providing a design-based ‘science’ to progressing the logistics and supply chain management field, dealing with contemporary topics such as resilience.

The authors undertake a discursive assessment of relevant streams of engineering, social science and systems research, with a conceptual development of how the latter influences supply chain design approaches.

Building on a phenomenological framework, the authors create a generic design science research design (DSRD) that enables researchers to choose and integrate the right tools and methods to address simple, complicated and complex problems, dealing with technological, process and social problems.

The DSRD provides a framework by which to exploit a range of methodological stances to problem solving, including quantitative modelling perspectives and ‘soft’ systems social science approaches. Four substantive gaps are identified for future research – establishing the root cause domain of the problem, how to deal with the hierarchy of systems within systems, establishing appropriate criteria for the solution design and how best to deal with chaotic and disordered systems.

The authors argue that the systems approaches offer methodological pluralism by which a generic DSRD may be applied to enhance supply chain design. The authors show the relevance of the DSRD to supply chain design problems including in reducing supply chain dynamics and enhance resilience. In doing so, the study points towards an integrated perspective and future research agenda for designing resilient supply chains.

Project complexity is becoming increasingly challenging for project managers. Much valuable research has been done on the concept of project complexity. The research reported in this paper aims to provide a new means (the “Complexity Navigation Window”) and guiding principles for the navigation of project complexity in practice.

This paper applied action design research (a methodology for design science research) to design and evaluate the Complexity Navigation Window (CNW), which will serve as a representation of project complexity as a key component of the user interface for a decision support system (DSS) for managing project complexity.

Formative evaluations of the CNW by 16 project management practitioners indicated that the artefact is relevant, comprehensible and heading in a promising direction to guide decision-making. The evaluation also highlighted project managers' difficulty in using the (conceptual) representation by itself to assess a project's current situation accurately, which in turn limits their ability to understand a project's current complexity and decide an appropriate course of strategy. A conceptual framework by itself is insufficient. This finding motivates further research to develop and evaluate a DSS that would partially automate the assessment process (by surveying stakeholders and automatically assessing and representing project complexity according to the CNW), which should aid in increasing the accuracy (and timeliness) of project complexity assessments and contribute to appropriate strategy formulation and timely revision.

The formative evaluation of the CNW indicates relevance for practitioners and the further features of the DSS may still yield even higher perceived utility from the full artefact.

The paper provides improved understanding of practitioners' perceptions of project complexity and ability to assess it for a given project. The paper describes the design of a new visualisation for navigating and managing complexity. The paper further presents four strategies for managing project complexity. Finally, the paper also provides a methodological discussion on the potential of ADR in advancing project management research.

To explore the value and the case for designing antifragile socio-technical information systems (IS) in an era of big data, moving beyond traditional notions of IS design towards systems that can leverage uncertainty for gains.

A design science research (DSR) approach was adopted, comprising four stages, including problem identification and solutions definition, conceptual artifact or socio-technical system design, preliminary evaluation, and communication and knowledge capture.

A conceptual socio-technical artifact that identifies antecedents to antifragile IS design. When operationalised, the antecedents may produce the desired antifragile outcome. The antecedents are categorised as value propositions, design decisions and system capabilities.

This research is conceptual in nature, applied and evaluated in a single big data analytics case study in Facebook-Cambridge Analytica. Future research should empirically validate across a range of real-world big data contexts, beyond the presented case study.

Uncertainty generally results in socio-technical system failures, impacting individuals, organisations and communities. Conversely, antifragile IS can respond favourably to the shocks and stressors brought forth by periods of elevated uncertainty.

Antifragile IS can drive socio-technical systems to respond favourably to uncertainty and stressors. Typically, these socio-technical systems are large, complex structures, with increased connectivity and the requirement to generate, process, analyse and use large datasets. When these systems fail, it affects individuals, organisations and communities.

Existing IS design methodologies and frameworks largely ignore antifragility as a possible designable outcome. Extant research is limited to abstract architectural design, and approaches based on the proposition of principles. This research contributes to knowledge of antifragile IS design, by deriving a conceptual artifact or socio-technical system based on antecedent-outcome relationships that leverage uncertainty towards performance gains.

The purpose of this paper is to develop a method for information classification. The proposed method draws on established standards, such as the ISO/IEC 27002 and information classification practices. The long-term goal of the method is to decrease the subjective judgement in the implementation of information classification in organisations, which can lead to information security breaches because the information is under- or over-classified.

The results are based on a design science research approach, implemented as five iterations spanning the years 2013 to 2019.

The paper presents a method for information classification and the design principles underpinning the method. The empirical demonstration shows that senior and novice information security managers perceive the method as a useful tool for classifying information assets in an organisation.

Existing research has, to a limited extent, provided extensive advice on how to approach information classification in organisations systematically. The method presented in this paper can act as a starting point for further research in this area, aiming at decreasing subjectivity in the information classification process. Additional research is needed to fully validate the proposed method for information classification and its potential to reduce the subjective judgement.

The research contributes to practice by offering a method for information classification. It provides a hands-on-tool for how to implement an information classification process. Besides, this research proves that it is possible to devise a method to support information classification. This is important, because, even if an organisation chooses not to adopt the proposed method, the very fact that this method has proved useful should encourage any similar endeavour.

The proposed method offers a detailed and well-elaborated tool for information classification. The method is generic and adaptable, depending on organisational needs.

This paper aims to address the long-standing problem of suboptimal student team experiences for instructors and students by incorporating the student voice by co-creating a virtual team collaborative environment to improve team collaboration in the online classroom.

This paper presents a novel design science research approach and relates two elaborated action design science research (eADSR) cycles that design, implement and evaluate the student team experience in online courses requiring teamwork.

The outcome is a holistic view of a virtual team classroom environment specified with technologies and practices that may be employed to optimize the student team experience. The eADSR process yields non-obvious diagnoses and actionable steps for continually incorporating the ever-changing social aspects unique to students in addition to the evolving technological landscape.

This paper is valuable to faculty members interested in applying eADSR processes to incorporate the student voice to address pedagogical and learning challenges in the classroom. Additionally, it provides a DSR-based model that can be implemented in the classroom to improve student team collaboration as well as transparency for the instructor and the students in terms of team member contributions with the goal to alleviate student and faculty frustrations. This topic is particularly relevant in light of COVID-19 as students and faculty alike are thrust into new online classroom environments.

Employing eADSR in the classroom is a novel and unique approach to create a replicable model for virtual team collaboration that can be added to the classroom.

Robotic process automation (RPA) has recently emerged as a technology focusing on the automation of repetitive, frequent, voluminous and rule-based tasks. Despite a few practical examples that document successful RPA deployments in organizations, evidence of its economic benefits has been mostly anecdotal. The purpose of this paper is to present a step-by-step method to RPA investment appraisal and a business case demonstrating how the steps can be applied to practice.

The methodology relies on design science research (DSR). The step-by-step method is a design artefact that builds on the mapping of processes and modelling of the associated costs. Due to the longitudinal nature of capital investments, modelling uses discounted cashflow and present value methods. Empirical grounding characteristic to DSR is achieved by field testing the artefact.

The step-by-step method is comprised of a preparatory step, three modelling steps and a concluding step. The modelling consists of compounding the interest rate, discounting the investment costs and establishing measures for comparison. These steps were applied to seven business processes to be automated by the case company, Estate Blend. The decision to deploy RPA was found to be trivial, not only based on the initial case data, but also based on multiple sensitivity analyses that showed how resistant RPA investments are to changing circumstances.

By following the provided step-by-step method, executives and managers can quantify the costs and benefits of RPA. The developed method enables any organization to directly compare investment alternatives against each other and against the probable status quo where many tasks in organizations are still carried out manually with little to no automation.

The paper addresses a growing new domain in the field of business process management by capitalizing on DSR and modelling-based approaches to RPA investment appraisal.