Design Science Research Process Research Articles

Bot log mining: An approach to the integrated analysis of Robotic Process Automation and process mining

Process mining and Robotic Process Automation (RPA) are two technologies of great interest in research and practice. Process mining uses event logs as input, but much of the information available about processes is not yet considered since the data is outside the scope of ordinary event logs. RPA technology can automate tasks by using bots, and the executed steps can be recorded, which could be a valuable data source for process mining. With the use of RPA technology expected to grow, an integrated view of steps performed by bots in business processes is needed. In process mining, various techniques to analyze processes have already been developed. Most RPA software also includes basic measures to monitor bot performance. However, the isolated use of bot-related or process mining measures does not provide an end-to-end view of bot-enabled business processes. To address these issues, we develop an approach that enables using RPA logs for process mining and propose tailored measures to analyze merged bot and process logs. We use the design science research process to structure our work and evaluate the approach by conducting a total of 14 interviews with experts from industry and research. We also implement a software prototype and test it on real-world and artificial data. This approach contributes to prescriptive knowledge by providing a concept on how to use bot logs for process mining and brings the research streams of RPA and process mining further together. It provides new data that expands the possibilities of existing process mining techniques in research and practice, and it enables new analyses that can observe bot-human interaction and show the effects of bots on business processes.

A Strategy Development Framework for Educational Technology: An integrated Design Science Research and Modified Delphi Approach

Emerging technologies are transforming educational practices, but successful integration requires improving the quality and efficiency of learning. New technology emerges in hype cycles but adoption and performance lag over time. A strategy development framework is needed for decision-makers to understand the complex interaction of all the factors to consider when making new technology investments. The research explores how strategy development occurs through the dynamic interaction of strategy with learning, and technology integration. It analyses the key elements of a strategy map for learning with technology and how they influence each other within the overall strategy map. The research design integrated the different cycles of Design Science Research (DSR) with a modified Delphi Technique in two phases of research. During the first research phase, Delphi panel members were interviewed to understand current challenges and practices in learning with technology. The results of the literature review and thematic data analysis from the interviews were used to create a hypothetical strategy map and a strategy development framework, as an artefact, as part of the DSR process. This framework was shared with Delphi members in the second phase of research, and they were requested to evaluate the framework for its fit and utility in similar contexts of learning with technology. The feedback contributed to the refinement of the artefact and highlighted the key operational focus areas for learning with technology. The key operational focus areas identified were the need to increase the basic technology literacy of students and educators, continuous professional development in terms of online pedagogy, and the need for principles in terms of multimedia design. Other focus areas were an online design blueprint and an improvement in learning and teaching experiences through efficiencies and productivity of ed-tech technologies. This study contributes a strategy development framework for educational technology which enhances theories around the analytical and conceptual processes when planning and implementing new emerging technologies in learning. Analytical processes include external and internal analysis and a SWOT analysis of aspects related to learning with technology. Other key outcomes of the study include a hypothetical strategy map for learning with technology which aligns business objectives to a financial, customer, internal business process and learning and growth perspective.

Not yet another BPM lifecycle: A synthesis of existing approaches using BPMN

ContextBusiness Process Management (BPM) is considered an important management approach that encompasses a set of methods for managing the business processes of an organization. To maximize the benefits of BPM, scholars have conceptualized its steps in schematic diagrams with interrelated phases called BPM lifecycles. As this approach has been established, the phenomenon of perpetual proposition of BPM lifecycles has been observed in relevant literature. This practice obscures what should be relatively straightforward: a consensus among researchers and practitioners regarding the steps that a business process should flow through during its lifecycle. ObjectiveThe aim of this work is to investigate the existing BPM lifecycle models proposed in literature, identify convergences and variations in these models, analyze their core components and locate common patterns that will enable the synthesis of a BPM lifecycle that is conceptualized with Business Process Model and Notation (BPMN), the community de-facto business process modeling notation. MethodTo formalize the research problem and develop the design of a solution, the Design Science Research Process (DSRP) model was adopted. To investigate the perpetual proposition of BPM lifecycles in literature, the authors conducted a Systematic Literature Review (SLR). On whether recurring patterns can emerge from the BPM lifecycles, a normalization process was introduced to homogenize the data and four metrics were used to evaluate the results. The emerging patterns were assembled into a graph that formed the basis for proposing a synthetic BPM lifecycle. ResultsThe outcome of the paper is three-fold: First, the identification of four major inefficiencies of existing BPM lifecycles, namely varying granularity, inconsistent nomenclature, subjective polysemy, and lack of formal conceptualization approaches. Also, a standardized definition of the inclusive steps that exist in the lifecycles by clustering the existing ones in a conceptually systematic manner. Finally, a synthetic BPM lifecycle is conceptualized that systematizes the existing concepts and their interrelations based on a formalized BPMN model in two levels of granularity: a basic version that illustrates the functional and control-flow aspects of the BPM lifecycle and an enhanced version incorporating additionally the resource and data perspectives. ConclusionThis paper proposes a BPMN-based conceptualization of the BPM lifecycle that can facilitate the management of business processes by providing enhanced clarity, improved resource management, and predefined error handling in a BPM initiative. By systematizing the control-flow, data, and resource perspective of the BPM lifecycle, stakeholders can gain a clear understanding of the sequence of steps, the interrelated data flows, and the distribution of work.

Determining design criteria for indoor positioning system projects in hospitals: A design science approach.

Indoor navigation systems (indoor positioning systems) can improve orientation for patients in hospitals and help employees to track assets. Many hospitals would like to implement indoor positioning systems but do not know how. To support them in doing this, and to gain knowledge about the requirements for indoor positioning system implementation, our research identifies the design criteria relevant to indoor positioning system implementation projects. A design science research process is built to design and evaluate an artifact. For this, five indoor positioning system developers and five hospital IT management representatives from various hospitals and companies in Germany are interviewed. Further, controlled experiments are conducted in Germany, using an ultrasound-based indoor positioning system. We determined and tested indoor positioning system functions, evaluated indoor positioning system performance criteria, and identified the operating conditions in hospitals. Our results show that indoor positioning system functions should provide a benefit to a hospital's daily operations, that some performance criteria are more important than others, and that operating conditions are important, e.g., radiation. As a theoretical contribution, we show how design science research can be applied to the context of indoor positioning systems in hospitals. In addition, we make a practical contribution in that our propositions can be used for future indoor positioning system developments.

IRECS Framework: Identification of Requirements for Enterprise Collaboration Systems

A review of the literature in the field of CSCW shows that the adoption of Enterprise Collaboration Systems (ECS) is challenging and that there is a need for a structured approach for their implementation. The IRECS Framework (Identification of Requirements for Enterprise Collaboration Systems), described in this paper, addresses this call in the form of a comprehensive classification of the digital support of collaborative work and a complementary taxonomy of empirically observed examples. The IRECS classification comprises five layers – from a high-level business view of collaborative work to a detailed consideration of the software modules that fulfil the functional requirements. The development of the framework followed a ten-year Design Science Research process. The framework is designed to serve the needs of researchers and practitioners alike. The detailed classification provides a valuable analytical lens for research. The framework and its concrete examples can also be used in practice as a guidance and checklist in the software selection process of organisations.

Customers’ Motives to Engage in Social Media-based Product Idea Contests – Empirical Evidence from Germany

An empirical motive study based on the design science approach is presented. The aim of the study is to develop specific problem-solving knowledge in the form of artefacts that can be directly applied in marketing practice. The problem-solving knowledge relates to consumers’ motives for participating in product idea contests (PICs) in the fast-moving consumer goods sector. The research phases underlying the motive study are guided by a five-phase design science research process. As a result of this research process, two artefacts are developed: a multi-item motive scale and a factor analytic motive model. The motive model includes six participation motives – three intrinsic (enjoyment with creative tasks, altruism and search for new/better product solutions) and three extrinsic motives (material–financial reward, identification with the user community and positive feedback from participants/company). Finally, the motive model enables the derivation of recommendations for action for the PIC management.

Usability Enhancement through Heuristics: A Framework for Mobile Money Transfer Systems

The widespread use of mobile technology has enabled the introduction of various mobile money services. Many factors contribute to the success of mobile money transfer systems, and usability measures the level of success. Usability heuristics principles developed by Nielsen, a pioneer in usability engineering, have existed and are popularly used to assess the usability of computer systems. However, in the wake of emerging new technologies such as mobile applications and mobile money transfer systems, there is a need for domain-specific heuristics. The purpose of the study is to investigate the usability of mobile money transfer systems and develop a usability heuristic framework that enhances Mobile Money Transfer Systems. The study covered mobile money transfer systems in Kenya. The research adopted a mixed method design that included the Design Science Research methodology and survey design. The Design Science Research process provided the structure for the study and the survey design guided the questionnaire administration. Data were obtained using questionnaires. The target population was Mobile Money Transfer System consumers in Nairobi County, Kenya. The data collected was analysed using both descriptive and factor analysis. A mobile money transfer system usability heuristics framework was developed using the findings. A sample of 396 was used, with a response rate of 81.1%. This framework was validated by mobile money transfer systems experts, who agreed that the developed framework can be applied in the real world with an average weighted mean of 4.55, allowing for further development. This research contributes to knowledge of usability heuristics required to evaluate mobile money transfer systems, reducing the development time and cost.

Development of an Enjoyable Educational Game on Fundamental Programming: Designing for Inclusion and Learning Analytics

A well-discussed problem is how to attract a new public to computer programming, and especially how to reach girls and women. At the same time research reports on that children spend considerable amounts of time playing different types of games, where educational games today are part of formal, informal and non-formal learning. However, many educational games still have a design that appeals more to boys than to girls. Another problem addressed in this paper is how to measure the learning outcomes of an education game. It is a challenge per se to design for joyful gaming, but to assess the learning outcomes is important if the game should be accepted by teachers and a part of teaching and learning activities. The aim of this study was to describe and discuss the design and development of an educational game where girls would like to play together and at the same time learn fundamental programming. The research question that guided this study was: " How could a motivating and inclusive educational game on fundamental programming be designed and developed, with minimal prerequisites for students and teachers?". The overall strategy for the design and development of the was the Design Science Research (DSR) approach. This work was carried out according to the recognised DSR process with the five phases of: 1) Explicating the problem, 2) Defining the requirements, 3) Designing and developing the artefact, 4) Demonstrating the artefact, and 5) Evaluating the artefact. Phase one was based on a minor literature study, while Phase 2 was a combination of a larger and more systematic literature study combined with game testing. Phase 3 was conducted with brain storming sessions for design followed by implementation in the Unity game development tool. Finally, the game has been demonstrated for, and tested by, a group of academic game developers. Results from the formative evaluation look promising, but the important next step in this project is a more formal evaluation using game-based learning analytics with a larger and more diverse test audience.

Towards design science methodology for developing mobile learning applications

ABSTRACT Mobile learning applications are being developed to support the teaching and learning process. The lack of an accepted methodology for developing these applications motivated the establishment of a design science research process for developing mobile learning applications. Design science methodology from the information systems domain was inherited and modified by consolidating common practices found in the development of mobile learning applications. The proposed methodology consolidates a set of logically related processes to support the development of mobile learning applications with ease and ensure quality results. Expert review of the proposed methodology was conducted, and the results indicate it can positively contribute to the development of mobile learning applications.

Near-Infrared Spectroscopy for Bladder Monitoring: A Machine Learning Approach

Patients living with neurogenic bladder dysfunction can lose the sensation of their bladder filling. To avoid over-distension of the urinary bladder and prevent long-term damage to the urinary tract, the gold standard treatment is clean intermittent catheterization at predefined time intervals. However, the emptying schedule does not consider actual bladder volume, meaning that catheterization is performed more often than necessary, which can lead to complications such as urinary tract infections. Time-consuming catheterization also interferes with patients' daily routines and, in the case of an empty bladder, uses human and material resources unnecessarily. To enable individually tailored and volume-responsive bladder management, we design a model for the continuous monitoring of bladder volume. During our design science research process, we evaluate the model's applicability and usefulness through interviews with affected patients, prototyping, and application to a real-world in vivo dataset. The developed prototype predicts bladder volume based on relevant sensor data (i.e., near-infrared spectroscopy and acceleration) and the time elapsed since the previous micturition. Our comparison of several supervised state-of-the-art machine and deep learning models reveals that a long short-term memory network architecture achieves a mean absolute error of 116.7 ml that can improve bladder management for patients.

A morphology of digital direct-to-consumer (D2C) models

Establishing a digital direct-to-consumer (D2C) business is a complex and challenging, yet also highly attractive opportunity for many companies. To leverage this opportunity, managers need to understand what types of digital D2C models exist and how to configure them. Based on a review of the D2C literature, an analysis of 15 D2C online shops and interviews with experts from the respective firms, this paper develops a morphological box of D2C models using a design science research process. The morphological box serves as a tool that provides orientation for managers to find a suitable D2C configuration for their business.

COVID-Bot, an Intelligent System for COVID-19 Vaccination Screening: Design and Development.

BackgroundCoronavirus continues to spread worldwide, causing various health and economic disruptions. One of the most important approaches to controlling the spread of this disease is to use an artificial intelligence (AI)–based technological intervention, such as a chatbot system. Chatbots can aid in the fight against the spread of COVID-19.ObjectiveThis paper introduces COVID-Bot, an intelligent interactive system that can help screen students and confirm their COVID-19 vaccination status.MethodsThe design and development of COVID-Bot followed the principles of the design science research (DSR) process, which is a research method for creating a new scientific artifact. COVID-Bot was developed and implemented using the SnatchBot chatbot application programming interface (API) and its predefined tools, which are driven by various natural language processing algorithms.ResultsAn evaluation was carried out through a survey that involved 106 university students in determining the functionality, compatibility, reliability, and usability of COVID-Bot. The findings indicated that 92 (86.8%) of the participants agreed that the chatbot functions well, 85 (80.2%) agreed that it fits well with their mobile devices and their lifestyle, 86 (81.1%) agreed that it has the potential to produce accurate and consistent responses, and 85 (80.2%) agreed that it is easy to use. The average obtained α was .87, indicating satisfactory reliability.ConclusionsThis study demonstrates that incorporating chatbot technology into the educational system can combat the spread of COVID-19 among university students. The intelligent system does this by interacting with students to determine their vaccination status.

Eco²-Screening Method Supporting SME-Product and Process Innovations in Electronics Manufacturing Services Sector

Consumption exceeds ecological limitations and still the market develops an insufficient incentive for the consideration of environmental aspects in the supply chain. In order to mitigate negative environmental effects, influence is needed in the earliest possible phase of innovation processes. Numerous studies, however, detect systematic use of ecological and economical innovation instruments mainly in large enterprises. In inverse consequence small and medium enterprises (SMEs) implement fewer environmental innovations, even though 99 % of the enterprises in Germany count less than 500 employees and adhere significant innovation potential. In order to provide a scope for action for SMEs an instrument for consideration of environmental product and process implications is needed that claims little economical resources of users and is easily applicable. Based on the Design Science Research Process a Screening method is developed for SMEs in the Electronics Manufacturing Services sector to enable a monitoring of ecological and economical optimization of innovation processes, while not demanding costly Life Cycle Assessment or additional questioning of suppliers. The eco²-screening method uses existing data and follows a modular design.

An Organizational and Governance Model to Support Mass Collaborative Learning Initiatives

Mass collaboration can bring about major transformative changes in the way people can work collectively. This emerging paradigm promises significant economic and social benefits and enhanced efficiency across a range of sectors, including learning and education. Accordingly, this article introduces, demonstrates in use, and evaluates an organizational and governance model designed to provide guidance and execution support for the implementation and operation of mass collaborative learning initiatives. The design science research process is adopted to guide the design and development of the proposed model. The model stands on three streams of work, addressing key aspects and elements that have a supporting influence on community learning: (i) identify the positive and negative factors in existing and active examples of mass collaboration; (ii) adopt contributions of collaborative networks in terms of structural and behavioral aspects; and (iii) establish adequate learning assessment indicators and metrics. The model is used for a case study in which vocational education and training meet the needs of collaborative education–enterprise approaches. Initially, the validation of the model is verified by the partners and stakeholders of a particular project in the area of education–enterprises relations to ensure that it is sufficiently appropriate for applications in a digital platform developed by such projects. The three first steps of (the proposed) applicability evaluation (adequacy, feasibility, and effectiveness) are then performed. The positive results gained from model validation and its applicability evaluation in this project indicate that not only is the model fairly adequate, feasible, and effective for applications in the developed digital platform but also that it has a high potential for utilization in supporting and directing the creation, implementation, and operation of mass collaborative learning initiatives. Although the validation was carried out in the context of a single project, in fact, it was based on a large “focus group” of experts involved in this international initiative, which is in accordance with the Design Science Research method. Thus, this article reflects a kind of applied research of a socio-technical nature, aiming to find guidelines and practical solutions to the specific issues, problems, and concerns of mass collaborative learning initiatives.

Continuous auditing in public sector and central banks: a framework to tackle implementation challenges

PurposeThis paper aims to analyse the implementation challenges faced by internal audit departments of public sector organisations and central banks when implementing continuous auditing (CA) systems. CA aims to monitor internal control systems and risk levels on a continuous basis to support the audit process. This study identifies the implementation challenges of CA systems and proposes adequate countermeasures.Design/methodology/approachThis study employs the design science information system research and the design science research process methodologies to ensure the rigor of this analysis. These research methodologies are adopted to tackle identified organisational problems and propose solutions. This methodological approach consists in the following phases: identification of the problems and motivation; definition of the objectives of the solution; research design and development; evaluation; communication.FindingsThis study detects several implementation challenges for public sector organisations and central banks and proposes adequate solutions. This study finds that these challenges are related to organisations’ complexity, institutional rigidity, potential threats to internal auditors’ independence and the issue of considering CA system as a “real time error correction” mechanism. The solutions involve the development of a business process focussed audit approach to enable internal auditors to analyse CA indicators, and the use of CA systems to support each phase of the audit process.Originality/valueThis study contributes to the scant strand of literature on internal auditing in central banks. Given the exceptional demand for guidance concerning internal auditing in the public sector and in central banks, this paper provides guidelines for these organisations to implement CA systems and to tackle implementation challenges. The analysis allows internal audit departments within central banks to better support their organisations in the achievement of their important regulatory and policy objectives.

Shedding light on blind spots – Developing a reference architecture to leverage video data for process mining

Process mining is one of the most active research streams in business process management. In recent years, numerous methods have been proposed for analyzing structured process data. In many cases, however, only the digitized parts of processes are directly captured by process-aware information systems, whereas manual activities often leave blind spots in the process analysis. While video data can contain valuable process-related information that is not captured in information systems, a standardized approach to extracting event logs from unstructured video data remains lacking. To solve this problem and facilitate the systematic usage of video data in process mining, we have designed the ViProMiRA, a reference architecture that bridges the gap between computer vision and process mining. The various evaluation activities in our design science research process ensure that the proposed ViProMiRA allows flexible, use case-driven, and context-specific instantiations. Our results also show that a prototypical implementation of the ViProMiRA is capable of automatically extracting more than 70% of the process-relevant events from a real-world video dataset in a supervised learning scenario.

Applying Design Science Research for Developing Business Artifacts

The paper introduces a theoretical substantiation of applying the Design Science Research process in Business Analytics approaches. Nowadays, Business Analytics, as part of information systems science and closely related to the business environment, offer innovative support to various business analysis. The key issues of the Design Science Research process are business artifacts. Our proposal is focused on data model and data visualizations, two main business artifacts in Business Analytics. Theoretical considerations are implemented in a sustainability analysis.

A Big Data Driven Decision Making Model: A case of the South African banking sector

The quest to develop a Big Data Driven Decision Making framework to support the incorporation of big data analytics into the decision-making process resulted in the development of a decision making model. The study was conducted within the banking sector of South Africa, with participants from three leading South African banking institutions. The conducted research followed the design science research process of awareness, suggestion, development, evaluation and conclusion.
 This study developed a theoretical Big Data Driven Decision Making model which illustrates the decision-making process in banking using big data. The study further determined the organizational supports that need to be in place to support the big data analytics decision-making process.

The Design of Reciprocal Learning Between Human and Artificial Intelligence

The need for advanced automation and artificial intelligence (AI) in various fields, including text classification, has dramatically increased in the last decade, leaving us critically dependent on their performance and reliability. Yet, as we increasingly rely more on AI applications, their algorithms are becoming more nuanced, more complex, and less understandable precisely at a time we need to understand them better and trust them to perform as expected. Text classification in the medical and cybersecurity domains is a good example of a task where we may wish to keep the human in the loop. Human experts lack the capacity to deal with the high volume and velocity of data that needs to be classified, and ML techniques are often unexplainable and lack the ability to capture the required context needed to make the right decision and take action. We propose a new abstract configuration of Human-Machine Learning (HML) that focuses on reciprocal learning, where the human and the AI are collaborating partners. We employ design-science research (DSR) to learn and design an application of the HML configuration, which incorporates software to support combining human and artificial intelligences. We define the HML configuration by its conceptual components and their function. We then describe the development of a system called Fusion that supports human-machine reciprocal learning. Using two case studies of text classification from the cyber domain, we evaluate Fusion and the proposed HML approach, demonstrating benefits and challenges. Our results show a clear ability of domain experts to improve the ML classification performance over time, while both human and machine, collaboratively, develop their conceptualization, i.e., their knowledge of classification. We generalize our insights from the DSR process as actionable principles for researchers and designers of 'human in the learning loop' systems. We conclude the paper by discussing HML configurations and the challenge of capturing and representing knowledge gained jointly by human and machine, an area we feel has great potential.

A barrier diagnostic framework in process of digital transformation in higher education institutions

PurposeExisting literature has reported a barrier list that could affect the implementation of digital transformation in higher education, yet the research question of how to identify barriers remained unanswered. Thus, this study intended to address this gap.Design/methodology/approachThe research design adopted a mixed-methods approach based on the problem-centered design science research (DSR) process model for the development and evaluation of framework.FindingsThis study proposed a systematic framework of three sets of components: (1) the initial set of barriers; (2) the barrier rating scheme and (3) the barrier scoring matrix. The three-component of the framework is to identify and prioritize barriers to the successful implementation of digital transformation in higher education.Research limitations/implicationsThe evaluation of the framework was only based on an expert opinion.Practical implicationsThis study provided a direction to the policymakers for designing sensible strategies to increase the chances of a successful digital transformation in higher education.Originality/valueThis study contributes to the knowledge body by offering a more systematic understanding of barriers to digital transformation in higher education.