The authors design and demonstrate a process for carrying out design science (DS) research in information systems and demonstrate use of the process to conduct re- search in two case studies. Several IS researchers have pioneered the acceptance of DS research in IS, but in the last 15 years little DS research has been done within the discipline. The lack of a generally accepted process for DS research in IS may have contributed to this problem. We sought to design a design science research process (DSRP) model that would meet three objectives: it would be consistent with prior lit- erature, it would provide a nominal process model for doing DS research, and it would provide a mental model for presenting and appreciating DS research in IS. The process includes six steps: problem identification and motivation, objectives for a solution, design and development, evaluation, and communication. We demonstrated the process by using it in this study and by presenting two case studies, one in IS planning to develop application ideas for mobile financial services and another in re- quirements engineering to specify feature requirements for a self service advertising design and sales system intended for wide audience end users. The process effectively satisfies the three objectives and has the potential to help aid the acceptance of DS research in the IS discipline.

DS research process for the Digia study.

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... We use the process model by Peffers et al. [31] which consists of six activities: ...

... Based on this approach, during a Relevance Cycle, a research context is set up which defines the requirements for the research in terms of the problem to be addressed as well as the acceptance criteria for evaluating the research results. This cycle is covered in the first two steps of Peffers et al. [31] activities and defines the criteria used in steps 4 and 5. The results from these steps determine whether additional iterations of relevance cycle are needed. ...

... This is including any extensions to the existing theories and methods, the new design products and processes as well as all experiences gained by performing the research [33]. This cycle starts with step 3 and is concluded by step 6 of Peffers et al. [31] activities. ...

... The authors employed the Design Science Research methodology by Peffers et al. (2007) and applied the first four activities of this process model. Compared with traditional, description-oriented research, which discovers and justifies unexplained phenomena, design-oriented research designs and evaluates solutions for relevant problems (Peffers et al., 2006). Following this design-oriented research approach, researchers, external startups, and corporates who were already exploiting digital platform business models came together in workshops to design and evaluate a new validation process. ...

... With the similarities between a pipeline and digital platform in mind, the researchers looked at the elements in the validation processes that validate the similarities in the business models and extracted these as the element for the new validation process. In doing so, the participants remained consistent with the current literature and were more likely to be complete and robust with their modeling (Peffers et al., 2006). Next, the participants identified differences and used current literature to point out what elements and factors needed to be considered and added to validate a digital platform business model. ...

... Following the fourth step of the Design Science Research methodology, demonstration, SPEC was applied to test its efficacy in solving the identified shortcomings. Peffers et al. (2006) suggest doing so by involving it "in experimentation, simulation, a case study, proof, or other appropriate activity" (p. 90). ...

Digital platform business models are disrupting traditional business processes and reveal a new way of creating value. Current validation processes for business models are designed to assess pipeline business models. They cannot grasp the logic of digital platforms, which increasingly integrate Artificial Intelligence (AI) to ensure success. This study developed a new validation process for early market validation of digital platform business models by following the Design Science Research methodology. The designed process, the Smart Platform Experiment Cycle (SPEC), is created by combining the Four-Step Iterative Cycle of business experiments, the Customer Development Process, and the Build-Measure-Learn feedback loop of the Lean Startup approach and enriching it with the knowledge of digital platforms. It consists of five iterative steps showing the startup how to design their platform business model and corresponding experiments and how to run, measure, analyze, and learn from the outcomes and results. To assess its efficacy, applicability, and validity, SPEC was applied in the German startup GassiAlarm, a service marketplace business model. The application of SPEC revealed shortcomings in the pricing strategy and highlighted to what extent their current business model would be successful. SPEC reduces the risk of building a product or service the market deems redundant and gives insights into its success rate. More applications of the SPEC are needed to validate its robustness further and to extend it to other types of digital platform business models for improved generalization.

... Before addressing this empirical aspect, we start with a literature review that covers the theoretical background of our study, including a brief overview of big data in general, a focus on developing countries and an overview on indices. In the following step, the chosen design science research approach (Peffers et al. 2006) is applied as a baseline for constructing our index, including descriptions of the data collection, cleaning, weighting and normalisation processes, and an evaluation of the BDRI. The latter is performed through the application of the BDRI, using data on African countries. ...

... This approach is relevant herein, since the BDRI is applicable to a technology-related field, and the index will be designed and evaluated accordingly. According to Peffers et al. (2006) the design science research process should include the following six conceptual steps in the field of IS: problem identification and motivation, objective for a solution, design and development, demonstration, evaluation and communication. Details on the application of these steps to the design of our index is shown in Fig. 2. As described in the previous section, the topic of big data has been intensively researched and defined by many researchers. ...

... improvements that are measurable on users, organisations, and society (Baskerville et al. 2018). A cyclical process was followed to complete index development based on the DSR process by Peffers et al. (2006) as depicted in Fig. 4. The knowledge flows followed design as an iterative search process, with multiple iterations of evaluation, development and suggestion and consequently redesign of the BDRI drivers and components. Cycling back to earlier activities, in particular from Demonstration and Evaluation can depend on the reason for cycling back and will form different knowledge flows accordingly (Venable et al. 2017). ...

The use of big data promises to drive economic growth and development and can therefore be a value-adding factor, but compared to private or public organisations, the country level is rarely investigated, and that is even more evident for developing countries. Another topic hardly ever considered in the big data research field is 'big data readiness', which means the level of preparation and willingness to exploit big data. We address these shortcomings in the literature and focus on the big data readiness of developing countries. Thus, the first research question is: what components are required for an index measuring big data readiness, and how can such an index be designed? We use a design science approach to develop the "Big Data Readiness Index" (BDRI), which is then applied to all African countries to answer our second research question: how do African countries perform in terms of the BDRI? Our analysis yields country rankings that show relatively high BDRI scores for coastal countries, such as South Africa, Kenya and Namibia, and for islands, such as Mauritius. Related implications for both research and policy are discussed.

... The purpose of the research context definition process is to identify the research problem or opportunity and characterise the solution space. This definition is done by identifying the research goals and establishing what the current knowledge is that is available either in the form of published scientific, technical, professional literature, or expert knowledge; and identifying the theoretical frameworks (INCOSE, 2015;Peffers et al., 2006;Wieringa, 2014). The research context should also identify the contribution of the research effort to justify why the research is required, motivate the researcher to pursue the solution, understand the researchers grasp of the problem and encourage the audience or stakeholders of the research to accept the results. ...

... The research context should also identify the contribution of the research effort to justify why the research is required, motivate the researcher to pursue the solution, understand the researchers grasp of the problem and encourage the audience or stakeholders of the research to accept the results. (Hevner et al., 2004;Peffers et al., 2006). The research context definition can be equated to the business or mission analysis process as is defined in the INCOSE Systems Engineering Handbook. ...

We live in an artificial world constructed of things that have been designed with a specific utility in mind. This utility aims to solve some problem or need that that is being experienced. Whereas natural and social science research is concerned with the explanation and prediction of observed phenomena and finding new truths or proofs as in "why do things work the way they do?", Design science and design science research is more concerned with how things out to be to attain goals and to function. Within this context, this paper proposes using design science research methodology that can be used for the design of a research instrument. Introduction

... Innovation process modeling approach in higher education adapted fromPeffers et al. (2006). ...

While a consensus has emerged on the importance of creativity in graphic design and multimedia field, little systematic research has attempted to understand its facilitators or inhibitors in the graphic and multimedia education across colleges and universities. The current investigation surveys a sample of experts as well as professors teaching across the Arab World concerning their perceptions on the most significant correlates of creative thinking among students. Results point to the importance of: (1) instructors' engagement; (2) appropriate use of instructional strategies, tools, and resources; (3) institutional support; (4) peer support; and (5) the removal of red-tape regulatory frameworks. Most importantly, this research highlights the need to move away from the rigid higher education creativity model assuming perfection, precision, accuracy, and optimal effectiveness to a more flexible creativity framework. The Multi-Layered Autonomous Phases Model (MLAPM) is proposed as an alternative approach to cultivating creativity at the higher education level. The MLAPM applies to all levels beginning with the students and the instructor in the classroom and all instructional tools applied, moving upward to the institutional administration levels. The model offers cost-effective, flexible, dynamic, and effective practices that improve levels of creativity and creative thinking among students without the need to invest in new costly equipment, tools, curriculum, or instructional programs.

... The research method used is Design Science Research Method (DSRM) [20,24,40,66]. DSRM proposes a set of steps or activities to complete the design and construction Content courtesy of Springer Nature, terms of use apply. ...

Enterprise architecture has become an important driver to facilitate digital transformation in companies, since it allows to manage IT and business in a holistic and integrated manner by establishing connections among technology concerns and strategical/motivational ones. Enterprise architecture modelling is critical to accurately represent business and their IT assets in combination. This modelling is important when companies start to manage their enterprise architecture, but also when it is remodelled so that the enterprise architecture is realigned in a changing world. Enterprise architecture is commonly modelled by few experts in a manual way, which is error-prone and time-consuming and makes continuous realignment difficult. In contrast, other enterprise architecture modelling proposal automatically analyses some artefacts like source code, databases, services, etc. Previous automated modelling proposals focus on the analysis of individual artefacts with isolated transformations toward ArchiMate or other enterprise architecture notations and/or frameworks. We propose the usage of Knowledge Discovery Metamodel (KDM) to represent all the intermediate information retrieved from information systems' artefacts, which is then transformed into ArchiMate models. Thus, the core contribution of this paper is the model transformation between KDM and ArchiMate metamodels. The main implication of this proposal is that ArchiMate models are automatically generated from a common knowledge repository. Thereby, the relationships between different-nature artefacts can be exploited to get more complete and accurate enterprise architecture representations.

  • Simon Rusche
  • Sebastian Rockstuhl
  • Simon Wenninger

With around 32% of global greenhouse gas emissions, companies in the manufacturing industry have a significant impact on the achievement of the Sustainable Development Goals through their corporate actions. Only a few approaches exist that are oriented towards external sustainability goals and additionally integrate a past and future perspective. This work addresses this gap and develops an index to assess the sustainability performance of manufacturing companies by the respective target achievement of different sustainability dimensions along a time horizon. To ensure the comparability of different companies, a broad set of quantitatively measurable performance indicators, addressing cross-company goals, is developed with the help of a literature review. In this vein, economic, ecological, and social aspects as well as upstream and downstream activities in the value chain and product characteristics are considered. In addition to increasing transparency for various stakeholders, the developed index can also be used as a basis for decision-making, as a monitoring tool, as well as a framework for the development of corporate strategy and orientation.

In Tanzania, street traders face the challenge of limited markets caused by employing weak marketing and promotion strategies. This study developed a mobile application to solve the problem addressed using participatory design. Qualitative data were collected using focus group discussions and brainstorming from 80 respondents involving both street traders and customers in different workshops and meetings. Data were used for the design and development of the Machinga application. Furthermore, quantitative data for application evaluation were collected from 96 respondents using questionnaires. In addition, 20 interviews were conducted to validate the evaluation results. Thematic and descriptive analysis were performed for both qualitative and quantitative data. The results show that the mobile application has prospective features which solve the problem of limited markets in the street trading community. The application is perceived positively by end-users because of embracing their prior requirements and meeting the evaluation criteria of usefulness, ease-of-use, learnability, and user satisfaction. The study recommends further training of users to enable the application to attain its multiplier effect on the vast population. This study confirms the relevance of participatory design in ICT4D projects for informal workers as it allowed the involvement of end-users and reflected their voices in terms of the technology they desire.

Abstract This study presents a new method,to effectively determine requirements for information systems involving widely dispersed end users, such as customers, suppliers, business partners, and other end-users outside the organization, and demonstrates the efficacy of the method,in a case study. Recently more IS have been targeted towards users outside the organization, making effective requirements engineering (RE) difficult. Outside users may have little relationship with the firm, are more costly to reach, may have different world views, and may not be available for iterative RE efforts. We identified seven problems associated with RE for wide audience end users and seven associated desirable characteristics for RE method that would address them. We reviewed IS, RE, and manufacturing literature to identify methods,that addressed these characteristics and found three methods,that supported four to five of the desired characteristics.We developed a method, wide audience requirements engineering (WARE), intended to support all seven characteristics.Major WARE features include a flexible, structured interviewing process (laddering), cognitive modeling (CSC), interpretive analysis, and a presentation tool that allows managers to view the requirements at several levels of aggregation by âÄúdrilling downâÄù all the way to the original interviews. We used WARE to develop the requirements for a major information system, directed at outside users, at Helsingin Sanomat, FinlandâÄôs largest newspaper. The demonstration showed,that WARE was effective for its intended purpose. The requirements developed using WARE became,the basis for a three year development,roadmap,for the system. The use of WARE helped managers and developers understand user preferences, reasoning, and priorities. Keywords: Requirements Gathering and Analysis, Critical Success Chains, CSC, Laddering, Wide Audience End-users (WARE), Requirements Engineering, Requirements Elicitation, Systems Analysis, Means-ends Analysis Permanent URL: http://sprouts.aisnet.org/4-27 Reference: Tuunanen, T., Peffers, K., Gengler, C. (2004). "Wide Audience Requirements

The study of the design process, design theory and methodology has been a preoccupation of engineers, designers and researchers over the last four to five decades. As the end of this millenium is approached and with the renewed interest around the world in engineering design, it is fitting to examine the state of the art and current status of issues I elating to design philosophies, theory and methodology. Over the East 40 years, many approaches to design have been put forward by various researchers, designers and engineers, both in academia and industry, on how design ought to and might be carried out. These proposals on design have tended towards what has come To be regarded as design philosophies, design models and design methods. The thesis of this paper is to discuss various aspects of generic research in design, within the above classifications in the light of the work that has been done in the last four decades. Discussions will focus on various definitions of design, design theory and methodology, the nature and variety of design problems, design classifications, philosophies, models, methods and systems.

  • Ivan Hybs
  • John Gero John Gero

This paper describes a model of design as a series of transformation processes and extends that model initially to include the behaviour of the designed product in its environment. This extended model is then recast through an analogy with natural evolution as an evolutionary process model of design through the inclusion of the evolutionary-style processes of cross-over and mutation and the introduction of design genes and the notion of inheritance from one generation to the next.

  • J. Eekels
  • N F M Roozenburg

The misunderstanding that engineering is just a part of science (at the most applied science) and that engineering design is only a kind of scientific research (often considered rather trivial) is still widespread, especially among scientists. Yet it is a misunderstanding. In the present paper the structures of scientific research and of engineering design will be compared and, apart from a few very evident similarities, a large number of essential differences will be discussed. The conclusions are on the one hand that science and engineering are strongly interwoven and mutually dependent on each other, but on the other hand that there are fundamental differences between scientific research and engineering design. They consequently require specific methodologies.

  • A. J. FULCHER
  • P. HILLS

Summary Design research as an academic, intellectual field of study is new in comparison to engineering science research or research into the established natural sciences. This paper considers the current state of progress, describes the 'artificial' nature of design and the necessity for design research, and highlights the need for clearer macro goals and agreed methods of research. A methodology is proposed based on a foundational value system, which will first enable descriptive research profiles to be created from which prescriptive classifications can be attempted by deductive and inductive reasoning. The value system proposed is one in which national prosperity and improvement in the quality of life are achieved by industrial relevance and responsiveness. It is argued that meaningful classification must include a breadth and depth of parameters to reflect the value system and that such a classification will enable a more effective and efficient exploitation of the field.