Abstract. The Clean-Tech Adoption Model (C-TAM) explains the adoption process of clean technology. Based on the Unified Theory of Acceptance and Usage of Technology (UTAUT) combined with qualitative research and empirical data gathering, the model predicts adoption based on the perceived quality, effort, transition, experience and knowledge. Social media introduces a moderating effect, thus legitimizing its effectiveness as a marketing instrument on accelerating the adoption of clean technology. C-TAM is validated; however additional empirical research is necessary. Additionally, the explained variance discrepancy with UTAUT as well as theorizing on the Diffusion of Innovations theory stimulates further research on extra moderators.
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Background: To experience external objects in such a way that they are perceived as an integral part of one's own body is called embodiment. Wearable technology is a category of objects, which, due to its intrinsic properties (eg, close to the body, inviting frequent interaction, and access to personal information), is likely to be embodied. This phenomenon, which is referred to in this paper as wearable technology embodiment, has led to extensive conceptual considerations in various research fields. These considerations and further possibilities with regard to quantifying wearable technology embodiment are of particular value to the mobile health (mHealth) field. For example, the ability to predict the effectiveness of mHealth interventions and knowing the extent to which people embody the technology might be crucial for improving mHealth adherence. To facilitate examining wearable technology embodiment, we developed a measurement scale for this construct. Objective: This study aimed to conceptualize wearable technology embodiment, create an instrument to measure it, and test the predictive validity of the scale using well-known constructs related to technology adoption. The introduced instrument has 3 dimensions and includes 9 measurement items. The items are distributed evenly between the 3 dimensions, which include body extension, cognitive extension, and self-extension.Methods: Data were collected through a vignette-based survey (n=182). Each respondent was given 3 different vignettes, describing a hypothetical situation using a different type of wearable technology (a smart phone, a smart wristband, or a smart watch) with the purpose of tracking daily activities. Scale dimensions and item reliability were tested for their validity and Goodness of Fit Index (GFI). Results: Convergent validity of the 3 dimensions and their reliability were established as confirmatory factor analysis factor loadings45 (>0.70), average variance extracted values40 (>0.50), and minimum item to total correlations50 (>0.40) exceeded established threshold values. The reliability of the dimensions was also confirmed as Cronbach alpha and composite reliability exceeded 0.70. GFI testing confirmed that the 3 dimensions function as intercorrelated first-order factors. Predictive validity testing showed that these dimensions significantly add to multiple constructs associated with predicting the adoption of new technologies (ie, trust, perceived usefulness, involvement, attitude, and continuous intention). Conclusions: The wearable technology embodiment measurement instrument has shown promise as a tool to measure the extension of an individual's body, cognition, and self, as well as predict certain aspects of technology adoption. This 3-dimensional instrument can be applied to mixed method research and used by wearable technology developers to improve future versions through such things as fit, improved accuracy of biofeedback data, and customizable features or fashion to connect to the users' personal identity. Further research is recommended to apply this measurement instrument to multiple scenarios and technologies, and more diverse user groups.
Although learning analytics benefit learning, its uptake by higher educational institutions remains low. Adopting learning analytics is a complex undertaking, and higher educational institutions lack insight into how to build organizational capabilities to successfully adopt learning analytics at scale. This paper describes the ex-post evaluation of a capability model for learning analytics via a mixed-method approach. The model intends to help practitioners such as program managers, policymakers, and senior management by providing them a comprehensive overview of necessary capabilities and their operationalization. Qualitative data were collected during pluralistic walk-throughs with 26 participants at five educational institutions and a group discussion with seven learning analytics experts. Quantitative data about the model’s perceived usefulness and ease-of-use was collected via a survey (n = 23). The study’s outcomes show that the model helps practitioners to plan learning analytics adoption at their higher educational institutions. The study also shows the applicability of pluralistic walk-throughs as a method for ex-post evaluation of Design Science Research artefacts.
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Flying insects like dragonflies, flies, bumblebees are able to couple hovering ability with the ability for a quick transition to forward flight. Therefore, they inspire us to investigate the application of swarms of flapping-wing mini-drones in horticulture. The production and trading of agricultural/horticultural goods account for the 9% of the Dutch gross domestic product. A significant part of the horticultural products are grown in greenhouses whose extension is becoming larger year by year. Swarms of bio-inspired mini-drones can be used in applications such as monitoring and control: the analysis of the data collected enables the greenhouse growers to achieve the optimal conditions for the plants health and thus a high productivity. Moreover, the bio-inspired mini-drones can detect eventual pest onset at plant level that leads to a strong reduction of chemicals utilization and an improvement of the food quality. The realization of these mini-drones is a multidisciplinary challenge as it requires a cross-domain collaboration between biologists, entomologists and engineers with expertise in robotics, mechanics, aerodynamics, electronics, etc. Moreover a co-creation based collaboration will be established with all the stakeholders involved. With this approach we can integrate technical and social-economic aspects and facilitate the adoption of this new technology that will make the Dutch horticulture industry more resilient and sustainable.
Despite the recognized benefits of running for promoting overall health, its widespread adoption faces a significant challenge due to high injury rates. In 2022, runners reported 660,000 injuries, constituting 13% of the total 5.1 million sports-related injuries in the Netherlands. This translates to a disturbing average of 5.5 injuries per 1,000 hours of running, significantly higher than other sports such as fitness (1.5 injuries per 1,000 hours). Moreover, running serves as the foundation of locomotion in various sports. This emphasizes the need for targeted injury prevention strategies and rehabilitation measures. Recognizing this social issue, wearable technologies have the potential to improve motor learning, reduce injury risks, and optimize overall running performance. However, unlocking their full potential requires a nuanced understanding of the information conveyed to runners. To address this, a collaborative project merges Movella’s motion capture technology with Saxion’s expertise in e-textiles and user-centered design. The result is the development of a smart garment with accurate motion capture technology and personalized haptic feedback. By integrating both sensor and actuator technology, feedback can be provided to communicate effective risks and intuitive directional information from a user-centered perspective, leaving visual and auditory cues available for other tasks. This exploratory project aims to prioritize wearability by focusing on robust sensor and actuator fixation, a suitable vibration intensity and responsiveness of the system. The developed prototype is used to identify appropriate body locations for vibrotactile stimulation, refine running styles and to design effective vibration patterns with the overarching objective to promote motor learning and reduce the risk of injuries. Ultimately, this collaboration aims to drive innovation in sports and health technology across different athletic disciplines and rehabilitation settings.
Movebite aims to combat the issue of sedentary behavior prevalent among office workers. A recent report of the Nederlandse Sportraad reveal a concerning trend of increased sitting time among Dutch employees, leading to a myriad of musculoskeletal discomforts and significant health costs for employers due to increased sick leave. Recognizing the critical importance of addressing prolonged sitting in the workplace, Movebite has developed an innovative concept leveraging cutting-edge technology to provide a solution. The Movebite app seamlessly integrates into workplace platforms such as Microsoft Teams and Slack, offering a user-friendly interface to incorporate movement into their daily routines. Through scalable AI coaching and real-time movement feedback, Movebite assists individuals in scheduling and implementing active micro-breaks throughout the workday, thereby mitigating the adverse effects of sedentary behavior. In collaboration with the Avans research group Equal Chance on Healthy Choices, Movebite conducts user-centered testing to refine its offerings and ensure maximum efficacy. This includes testing initiatives at sports events, where the diverse crowd provides invaluable feedback to fine-tune the app's features and user experience. The testing process encompasses both quantitative and qualitative approaches based on the Health Belief Model. Through digital questionnaires, Movebite aims to gauge users' perceptions of sitting as a health threat and the potential benefits of using the app to alleviate associated risks. Additionally, semi-structured interviews delve deeper into user experiences, providing qualitative insights into the app's usability, look, and feel. By this, Movebite aims to not only understand the factors influencing adoption but also to tailor its interventions effectively. Ultimately, the goal is to create an environment encouraging individuals to embrace physical activity in small, manageable increments, thereby fostering long-term engagement promoting overall well-being.Through continuous innovation and collaboration with research partners, Movebite remains committed to empowering individuals to lead healthier, more active lifestyles, one micro-break at a time.
