An Intelligent Mechanism to Automatically Discover Emerging Technology Trends: Exploring Regulatory Technology

Technology trend analysis uses data relevant to historical performance and extrapolates it to estimate and assess the future potential of technology. Such analysis is used to analyze emerging technologies or predict the growing markets that influence the resulting social or economic development to assist in effective decision-making. Traditional trend analysis methods are time-consuming and require considerable labor. Moreover, the implemented processes may largely rely on the specific knowledge of the domain experts. With the advancement in the areas of science and technology, emerging cross-domain trends have received growing attention for its considerable influence on society and the economy. Consequently, emerging cross-domain predictions that combine or complement various technologies or integrate with diverse disciplines may be more critical than other tools and applications in the same domain. This study uses a design science research methodology, a text mining technique, and social network analysis (SNA) to analyze the development trends concerning the presentation of the product or service information on a company's website. This study applies regulatory technology (RegTech) as a case to analyze and justify the emerging cross-disciplinary trend. Furthermore, an experimental study is conducted using the Google search engine to verify and validate the proposed research mechanism at the end of this study. The study results reveal that, compared with Google Trends and Google Correlate, the research mechanism proposed in this study is more illustrative, feasible, and promising because it reduces noise and avoids the additional time and effort required to perform a further in-depth exploration to obtain the information.

Theory-Based Problem Formulation and Ideation in mHealth Analysis and Recommendations

This article reports on an investigation into how to improve problem formulation and ideation in Design Science Research (DSR) within the mHealth domain. A Systematic Literature Review of problem formulation in published mHealth DSR papers found that problem formulation is often only weakly performed, with shortcomings in stakeholder analysis, patient-centricity, clinical input, use of kernel theory, and problem analysis. The study proposes using Coloured Cognitive Mapping for DSR (CCM4DSR) as a tool to improve problem formulation in mHealth DSR. A case study using CCM4DSR found that using CCM4DSR provided a more comprehensive problem formulation and analysis, highlighting aspects that, until CCM4DSR was used, weren’t apparent to the research team and which served as a better basis for mHealth feature ideation.

Método para captura e priorização de requisitos de futuros usuários de Habitações de Interesse Social

Resumo O valor do produto, como percebido pelo usuário, envolve interações complexas entre escolhas que estes realizam, em face de um grande conjunto de atributos positivos e negativos. Nesse contexto, é possível destacar a ausência de um procedimento que aproxime o valor recebido pelo usuário do seu valor desejado. O objetivo geral deste trabalho é propor um método para captura e priorização de requisitos de usuários para subsidiar o processo de concepção e projeto de empreendimentos habitacionais de interesse social (EHIS), com base em um estudo de caso no âmbito do Programa Minha Casa Minha Vida-Entidades. Como estratégia de pesquisa optou-se pela Design Science Research. O trabalho foi dividido em três fases, além de uma revisão de literatura. Na fase exploratória, adaptou-se a técnica de análise conjunta baseada em escolhas, para a realidade da pesquisa. A fase de desenvolvimento contemplou as seguintes etapas: (a)captura dos requisitos; (b) hierarquização e priorização desses requisitos e; (c) relação entre os modelos de preferência, e os tipos de família dos futuros usuários de habitações de interesse social (HIS). Com base na última fase, de análise e reflexão, foi proposto um método para captura e priorização de requisitos de usuários, com vistas à disponibilização desses requisitos para subsidiar o processo de concepção e projeto de EHIS.

Modelling (Social) Intra/Entrepreneurship Process

This study had three objectives: to discover the main concepts and theories used in research around entrepreneurship; systematize the entrepreneurial process in a model that allows teaching it more efficiently, and substantiate the model by applying it to various social entrepreneurship projects. To this end, a systematic scoping review was carried out to identify the main concepts, theories, and processes, which constitute the six crucial building blocks to someone could be successful as a(n) (social) intra/entrepreneur. Then, a design-science approach led us to use real social innovation and social entrepreneurship cases to evaluate the constructs and the model. Consequently, it is concluded that all concepts, theories and models identified can be classified as external factors (Context and Resources), internal factors (Objectives and entrepreneurial Will) and achievements (Action and Impact). The CROWAI model fits well with the data obtained on 465 innovation and social entrepreneurship projects. Thus, this model presents a more comprehensive approach, applicable to all profitable or social intra/entrepreneurship situations, allowing this new conceptual arrangement to be more easily taught. Additionally, it makes sense to use the term ‘social’ in innovation and intra/entrepreneurship because it has excellent defining power of the scope one wants to achieve with human endeavours. Doi: 10.28991/ESJ-2022-06-01-02 Full Text: PDF

From crowd to cloud: simplified automatic reconstruction of digital building assets for facility management

Purpose The purpose of this paper is to investigate the feasibility of an end-to-end simplified and automated reconstruction pipeline for digital building assets using the design science research approach. Current methods to create digital assets by capturing the state of existing buildings can provide high accuracy but are time-consuming, expensive and difficult. Design/methodology/approach Using design science research, this research identifies the need for a crowdsourced and cloud-based approach to reconstruct digital building assets. The research then develops and tests a fully functional smartphone application prototype. The proposed end-to-end smartphone workflow begins with data capture and ends with user applications. Findings The resulting implementation can achieve a realistic three-dimensional (3D) model characterized by different typologies, minimal trade-off in accuracy and low processing costs. By crowdsourcing the images, the proposed approach can reduce costs for asset reconstruction by an estimated 93% compared to manual modeling and 80% compared to locally processed reconstruction algorithms. Practical implications The resulting implementation achieves “good enough” reconstruction of as-is 3D models with minimal tradeoffs in accuracy compared to automated approaches and 15× cost savings compared to a manual approach. Potential facility management use cases include the issue and information tracking, 3D mark-up and multi-model configurators. Originality/value Through user engagement, development, testing and validation, this work demonstrates the feasibility and impact of a novel crowdsourced and cloud-based approach for the reconstruction of digital building assets.

Motivating Users to Manage Privacy Concerns in Cyber-Physical Settings—A Design Science Approach Considering Self-Determination Theory

Connectivity is key to the latest technologies propagating into everyday life. Cyber-Physical Systems (CPS) and Internet-of-Things (IoT) applications enable users, machines, and technologically enriched objects (‘Things’) to sense, communicate, and interact with their environment. Albeit making human beings’ lives more comfortable, these systems collect huge quantities of data that may affect human privacy and their digital sovereignty. Engaging in control over individuals by digital means, the data and the artefacts that process privacy-relevant data can be addressed by Self-Determination Theory (SDT) and its established instruments. In this paper, we discuss how the theory and its methodological knowledge can be considered for user-centric privacy management. We set the stage for studying motivational factors to improve user engagement in identifying privacy needs and preserving privacy when utilizing or aiming to adapt CPS or IoT applications according to their privacy needs. SDT considers user autonomy, self-perceived competence, and social relatedness relevant for human engagement. Embodying these factors into a Design Science-based CPS development framework could help to motivate users to articulate privacy needs and adopt cyber-physical technologies for personal task accomplishment.

Using Insights from Behavioural Science and Design Thinking to Develop mHealth Interventions: a Systematic Scoping Review (Preprint)

BACKGROUND Mobile health (mHealth) interventions are increasingly being designed to facilitate health-related behaviour change. Integrating insights from behavioural science and design science can help support the development of more effective mHealth interventions. Behavioural Design (BD) and Design Thinking (DT) have emerged as best practice approaches in their respective fields. Until now, little work has been done to examine how BD and DT can be integrated throughout the mHealth design process. OBJECTIVE The aim of this scoping review was to map the evidence on how insights from BD and DT can be integrated to guide the design of mHealth interventions. The following questions were addressed: (1) what are the main characteristics of studies that integrate BD and DT during the mHealth design process? (2) what approaches do mHealth design teams use to integrate BD and DT during the mHealth design process? (3) what are key implementation considerations, design challenges, and future directions for integrating BD and DT during mHealth design? METHODS We identified relevant studies from MEDLINE, PSYCINFO, EMBASE, CINAHL and JMIR using search terms related to mHealth, behavioural design, and design thinking. Included articles had to clearly describe their mHealth design process and how behaviour change theories, models, frameworks, or techniques were incorporated. Two independent reviewers screened articles for inclusion and completed the data extraction. A descriptive analysis was conducted. RESULTS A total of 75 articles met the inclusion criteria. All studies were published between 2012 and 2021. Studies integrated BD and DT in notable ways, which we refer to as “Behavioural Design Thinking”. Five steps were followed in the “Behavioural Design Thinking” approach: (1) empathise with users and their behaviour change needs, (2) define user and behaviour change requirements, (3) ideate user-centred features and behaviour change content, (4) prototype a user-centred solution that supports behaviour change, (5) test the solution against users’ needs and for its behaviour change potential. Key challenges experienced during mHealth design included meaningfully engaging patient and public partners in the design process, translating evidence-based behaviour change techniques into actual mHealth features, and planning for how to integrate the mHealth intervention into existing clinical systems. Guidance is needed on how to conduct the design process itself, how to meaningfully engage key stakeholders, and how to operationalize behaviour change techniques in a user-friendly and context-specific way. CONCLUSIONS Best practices from BD and DT can be integrated throughout the mHealth design process to ensure that mHealth interventions are purposefully developed to effectively engage users. Although this scoping review clarified how insights from BD and DT could be integrated during mHealth design, future research is needed to identify the most effective design approaches. CLINICALTRIAL n/a