Using Design Science Research to Develop a Modeling Technique for Service Design

Knowledge-intensive business services (KIBS) are business-to-business services that are characterized as being knowledge intensive, relying on expert employees, and providing knowledge-based solutions to customers. As a context for service design, KIBS bring unique challenges regarding the need to communicate about value cocreation among companies entering into a service exchange. Unfortunately, until now, there have been limited contributions in the area of modeling languages to support the cocreation of value during business exchanges. In this paper, an abstract language (metamodel) is proposed to support IT designers in understanding value cocreation in the field of IT-related business services. A value creation metamodel is first structured around three dimensions: the nature of the value, the method of value creation, and the business object impacted by the value. Then, value cocreation is modeled as a specialization of the value creation metamodel. This new language is illustrated with a case study related to KIBS in the financial sector.

Enhancing medical radiation science education through a design science research methodology

Natural science research is the most common and widely used research methodology. Various fields such as physics, biology, social and behavioral apply this research methodology. However, not all research is suitable for using the natural science research methodology in computer fields such as information technology, computer science, and information systems. Research that aims to solve problems by developing an artefact is more suitable for using the design science research methodology. Unfortunately, there are still many researchers who do not understand or even do not know this methodology. In this paper, we discuss the design science research methodology framework to reintroduce this methodology. The discussion starts with the theory of design science research, which explains five stages, from the explicated problem to the evaluation stage. Furthermore, an example of the application of this methodology is presented for the timetabling problem. This application example shows how the design process was and what the results were. This paper is expected to provide knowledge to researchers, especially for researchers who should use this methodology.

This article proposes to conceptualize service system entities as intentional agents in order to account for the high‐level interests and expected benefits that drive their interactions. Such a conceptualization offers a useful ground for the design of service systems through agent‐oriented modeling, in particular i* (short for distributed intentionality). i* could provide an improved support to the design of service system interactions by focusing on why actors engage in service relationships and how they evaluate the value of a service engagement. Such an approach goes beyond current process‐based design approaches that support the design of service activities but that are unable to link them to actors' perception of value. We develop our argumentation from the results of a multiple‐case study of knowledge‐intensive business services (KIBS), in particular academic research and development service engagements. © 2012 Wiley Periodicals, Inc.

We propose a methodological framework based on design science research for the design and development of data and information artifacts in data analysis projects, particularly managerial performance analysis. Design science research methodology is an artifact-centric creation and evaluation approach. Artifacts are used to solve real-life business problems. These are key elements of the proposed approach. Starting from the main current approaches of design science research, we propose a framework that contains artifact engineering aspects for a class of problems, namely data analysis using machine learning techniques. Several classification algorithms were applied to previously labelled datasets through clustering. The datasets contain values for eight competencies that define a manager’s profile. These values were obtained through a 360 feedback evaluation. A set of metrics for evaluating the performance of the classifiers was introduced, and a general algorithm was described. Our initiative has a predominant practical relevance but also ensures a theoretical contribution to the domain of study. The proposed framework can be applied to any problem involving data analysis using machine learning techniques.

The involvement of customers as co-creators in new service innovation is increasingly being suggested as a successful strategy to improve the success rate of new services. Value-in-use is a central theme for the service-dominant logic because the customer is always a co-creator of value. Co-creation involves customer engagement in the creation of offerings through ideation, design and development. The objective of this paper is to develop the framework for successful development and implementation of customer value co-creation process in service innovation. Based on literature review, three phases of value co-creation have been developed. First, motivation for customer value co-creation is one of the important aspects to consider by a service firm. Extrinsic and intrinsic motivations play a key role for customer motivation to participate. Second, customers' role in value creation process have greater been developed. Customer experience during interaction becomes central to the value creation process. Customer participation in value creation process is divided into two parts: participation behaviour and citizenship behaviour. Third, criteria for superior value co-creation process have been developed. This research brings the framework that motivation for value co-creation creates positive impact on value co-creation process, which in turn leads to generate positive value co-creation experience.

Recent research has suggested that consumers collectively co-create value through consumption practices. This paper provides additional insights into value creation by demonstrating how individual consumers play distinct roles in the value creation process. By focusing on microdimensions of co-consuming groups, we show how individual consumers engage in value creation processes in the context of brand culture. We bring together concepts of value creation, working consumers, and double exploitation to demonstrate the roles played by consumers and communities in value co-creation. We focus on value creation in a particular type of co-consuming group: an online football fan community. Results show that co-consuming groups are platforms for value creation. We argue that double exploitation is not necessarily a threat to consumers because it may instead enable them to play active roles in value co-creation and gain power against brand owners. This paper contributes to the existing literature on brand community and the value co-creation paradigm by: (1) demonstrating the dynamic roles played by consumers in the value co-creation; (2) revealing new forms of consumer organization; and (3) illustrating how working consumers work among themselves in managing brand communities.

The emerging impact of cloud computing in businesses has become a great driving force for business success and cannot be understated. The lack of a tailored functional application software, even though a framework exists, poses a significant challenge to SMEs. Without a digital corresponding software solution, SMES struggle to conduct a practical assessment since the framework offers only theoretical guidance. A well-developed cloud implementation assessment tool is essential for SMEs to thrive. The main aim of the study was to develop a robust cloud implementation assessment system for SMEs to evaluate their cloud implementation readiness. Design Science Research Methodology (DSRM), is a kind of research methodology which aims at developing and evaluating innovative artefacts, in the form of models, frameworks, designs, or prototypes, to solve complex and practical problems. Framework Usability Validation used. On the Clarity of the framework, none of the respondents strongly disagreed, representing 0%. 8 respondents, representing 15.4% disagreed, and 3 respondents, representing 5.8% were unsure. The system was developed using the Django Python web framework. Out of 43 respondents, 18 participants (42%) found the Learn Cloud Phase helpful, 3 participants (7%) found the Assessment and Cloud Choice Phase helpful, and 15 participants (35%) found the Migration Phase helpful. Additionally, 4 participants (9%) reported that all phases were helpful, 2 participants (5%) indicated that none of the phases were helpful, and 1 participant (2%) was uncertain about the helpfulness of any phase. In this paper, the design science Research (DSR) method was utilised to develop and evaluate the cloud implementation assessment system for SMEs. Key features of the developed system include learn cloud, assessment, cloud choice and migration phase. The developed system was said to be very useful and suitable, solidifying its value as a helpful resource for small businesses aiming to utilise cloud technology. A cloud assessment system was developed to aid in assessing SMEs' cloud readiness and implementation. Generally, SMEs responded positively to the cloud computing implementation framework.

Based on reviewing foremost literature, this paper discusses various design science research methodologies and related to them case studies. I have identified common activities that may create an outline of a reference model for design science. The model will apply to a design step activity in any design science methodology. I also present my assumptions, based on structured interviews, that the current abstract level of design science methodologies may cause poor quality of content of its artefacts. As for the measurement of quality, I discuss representational information quality dimensions. The contribution of the paper is to relate design sciences theories with research activities by providing a design science process oriented framework. My observations indicate that it will help improve the quality of design science artefacts.KeywordsDesign Science MethodologySystematic FrameworkDesign Science Literature ReviewInformation Quality Dimensions

Course and instructor evaluations (CIE) are essential tools for assessing educational quality in higher education. However, traditional CIE systems often suffer from inconsistencies between structured responses and open-ended feedback, leading to unreliable insights and increased administrative workload. This study suggests a modular system to address these challenges, leveraging sentiment analysis and inconsistency detection to enhance the reliability and efficiency of CIE processes.BackgroundImproving the reliability of CIE data is crucial for informed decision-making in higher education. Existing methods fail to address discrepancies between numerical scores and textual feedback, resulting in misleading evaluations. This study proposes a system to identify and exclude inconsistent data, providing more reliable insights.MethodsUsing the Design Science Research Methodology (DSRM), a system architecture was developed with five modules: data collection, preprocessing, sentiment analysis, inconsistency detection, and reporting. A dataset of 13,651 anonymized Turkish CIE records was used to train and evaluate machine learning algorithms, including support vector machines, naive Bayes, random forest, decision trees, K-nearest neighbors, and OpenAI’s GPT-4 Turbo Preview model. Sentiment analysis results from open-ended responses were compared with structured responses to identify inconsistencies.ResultsThe GPT-4 Turbo Preview model outperformed traditional algorithms, achieving 85% accuracy, 88% precision, and 95% recall. Analysis of a prototype system applied to 431 CIEs identified a 37% inconsistency rate. By excluding inconsistent data, the system generated reliable reports with actionable insights for course and instructor performance. The purpose of this study is to design and evaluate a new system using the Design Science Research (DSR) approach to enhance the accuracy and reliability of course evaluation processes employed in higher education institutions. The modular system effectively addresses inconsistencies in CIE processes, offering a scalable and adaptable solution for higher education institutions. By integrating advanced machine learning techniques, the system enhances the accuracy and reliability of evaluation reports, supporting data-driven decision-making. Future work will focus on refining sentiment analysis for neutral comments and broadening the system’s applicability to diverse educational contexts. This innovative approach represents a significant advancement in leveraging technology to improve educational quality.

Correctly identifying and classifying food is decisive in food safety. The food sector is constantly evolving, and one of the technologies that stands out is augmented reality (AR). During practical studies at Companhia de Entreposto e Armazéns Gerais de São Paulo (CEAGESP), responsible for the largest food storage in South America, difficulties were identified in classifying aromatic herbs due to the large number of species. The project aimed to create an innovative AR application called ARomaticLens to solve the challenges associated with identifying and classifying aromatic herbs using the design science research (DSR) methodology. The research was divided into five stages according to the DSR methodology, from surveying the problem situation at CEAGESP to validating the application through practical tests and an experience questionnaire carried out by CEAGESP specialists. The result of the study presented 100% accuracy in identifying the 18 types of aromatic herbs studied when associated with the application’s local database without the use of an Internet connection, in addition to a score of 8 on a scale of 0 to 10 in terms of the usability of the interface as rated by users. The advantage of the applied method is that the app can be used offline.

The workshop «Linkages between Actors in the Innovation System» (June 13-15), organized by the HSE ISSEK Laboratory for Economics of Innovation, assessed the weight of various components of the innovation system on its overall dynamics. The event was attended by leading international researchers from the UK, Norway and Sweden, HSE representatives and other specialists. The agenda of discussions included: entrepreneurship as a driver of new industries as exemplified by service design; science, technology and innovation in Russia; knowledge-intensive business services and technology transfer as incentives for innovation in enterprises; innovation skills and behavioral patterns of key actors of the innovation system and people; technology audit; green-growth strategies for the oil-gas sector; and the design of innovation policy in a «systems of innovation» perspective.

This study uses the Design Science Research Methodology (DSRM) approach in creating an artifact on the perspective of the Information System. Design Science as a valuable tool for creating a new artifact or developing an existing artifact through research. The DSRM Framework described in this study discusses the implementation of each stage, namely, Explicated Problem, Define Requirement, Design and Development, Demonstration, and Evaluation and is complemented by the implementation of case studies of artifact creation in DSRM stages. The Digital Maturity Measurement in question is a service to measure digital maturity in various dimensions. Each DSRM stage is mapped to a case study of that service. Canvas visualization is presented to describe a complete picture of how the artifacts of Digital maturity services are built with the DSRM approach. This research also provides guidance on the principles, procedures, and characteristics needed to build effective research.

In the technology enabled, competitive service environment, organizations try to innovate their service while redesigning their processes to increase efficiency. The present study is aimed at developing a design method that brings together, complementarily, constructs and approaches from two fields: Service Design, which offers a human-centered, holistic focus on creating novel services and Business Process Reengineering, mainly organizational, process redesign and process efficiency focused. The Service Design for Business Process Reengineering (SD4BPR) method was developed following a Design Science Research methodology and it was applied in a business environment for the improvement of the Pre-Sale processes of a software development company dedicated to the health area. The development of the method and its process of work are presented and discussed in order to show how SD4PBR can support the design of technology-enabled services while taking into consideration organizational issues and desired business efficiency.

PurposeThe main goal of this research work is the optimization of the purchasing business process in the Moroccan public sector in terms of transparency and budgetary optimization. The authors have worked on the public university as an implementation field.Design/methodology/approachThe design of the research work followed the design science research (DSR) methodology for information systems. DSR is a research paradigm wherein a designer answers questions relevant to human problems through the creation of innovative artifacts, thereby contributing new knowledge to the body of scientific evidence. The authors have adopted a techno-functional approach. The technical part consists of the development of an intelligent recommendation system that supports the choice of optimal information technology (IT) equipment for decision-makers. This intelligent recommendation system relies on a set of functional and business concepts, namely the Moroccan normative laws and Control Objectives for Information and Related Technology's (COBIT) guidelines in information system governance.FindingsThe modeling of business processes in public universities is established using business process model and notation (BPMN) in accordance with official regulations. The set of BPMN models constitute a powerful repository not only for business process execution but also for further optimization. Governance generally aims to reduce budgetary wastes, and the authors' recommendation system demonstrates a technical and methodological approach enabling this feature. Implementation of artificial intelligence techniques can bring great value in terms of transparency and fluidity in purchasing business process execution.Research limitations/implicationsBusiness limitations: First, the proposed system was modeled to handle one type products, which are computer-related equipment. Hence, the authors intend to extend the model to other types of products in future works. Conversely, the system proposes optimal purchasing order and assumes that decision makers will rely on this optimal purchasing order to choose between offers. In fact, as a perspective, the authors plan to work on a complete automation of the workflow to also include vendor selection and offer validation. Technical limitations: Natural language processing (NLP) is a widely used sentiment analysis (SA) technique that enabled the authors to validate the proposed system. Even working on samples of datasets, the authors noticed NLP dependency on huge computing power. The authors intend to experiment with learning and knowledge-based SA and assess the' computing power consumption and accuracy of the analysis compared to NLP. Another technical limitation is related to the web scraping technique; in fact, the users' reviews are crucial for the authors' system. To guarantee timeliness and reliable reviews, the system has to look automatically in websites, which confront the authors with the limitations of the web scraping like the permanent changing of website structure and scraping restrictions.Practical implicationsThe modeling of business processes in public universities is established using BPMN in accordance with official regulations. The set of BPMN models constitute a powerful repository not only for business process execution but also for further optimization. Governance generally aims to reduce budgetary wastes, and the authors' recommendation system demonstrates a technical and methodological approach enabling this feature.Originality/valueThe adopted techno-functional approach enabled the authors to bring information system governance from a highly abstract level to a practical implementation where the theoretical best practices and guidelines are transformed to a tangible application.