This article addresses drivers and partner features in vertical or horizontal cooperation. A survey is used to assess their impact and to evaluate whether respondents give significantly different scores to comparable influencing factors depending on the type of cooperation. The results show that internal stakeholder support and investments needed for collaboration turn out to be more critical in the case of horizontal collaboration. Innovation potential of the partner features and the fit between the cooperating organizations are judged as more important partner features in the case of horizontal cooperation.
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Background: A large number of people participate in individual or unorganized sports on a recreational level. Furthermore, many participants drop out because of injury or lowered motivation. Potentially, physical activity–related apps could motivate people during sport participation and help them to follow and maintain a healthy active lifestyle. It remains unclear what the quality of running, cycling, and walking apps is and how it can be assessed. Quality of these apps was defined as having a positive influence on participation in recreational sports. This information will show which features need to be assessed when rating physical activity–related app quality. Objective: The aim of this study was to identify expert perception on which features are important for the effectiveness of physical activity–related apps for participation in individual, recreational sports. Methods: Data were gathered via an expert panel approach using the nominal group technique. Two expert panels were organized to identify and rank app features relevant for sport participation. Experts were researchers or professionals in the field of industrial design and information technology (technology expert panel) and in the field of behavior change, health, and human movement sciences who had affinity with physical activity–related apps (health science expert panel). Of the 24 experts who were approached, 11 (46%) agreed to participate. Each panel session consisted of three consultation rounds. The 10 most important features per expert were collected. We calculated the frequency of the top 10 features and the mean importance score per feature (0-100). The sessions were taped and transcribed verbatim; a thematic analysis was conducted on the qualitative data. Results: In the technology expert panel, applied feedback and feedforward (91.3) and fun (91.3) were found most important (scale 0-100). Together with flexibility and look and feel, these features were mentioned most often (all n=4 [number of experts]; importance scores=41.3 and 43.8, respectively). The experts in the health science expert panels a and b found instructional feedback (95.0), motivating or challenging (95.0), peer rating and use (92.0), motivating feedback (91.3), and monitoring or statistics (91.0) most important. Most often ranked features were monitoring or statistics, motivating feedback, works good technically, tailoring starting point, fun, usability anticipating or context awareness, and privacy (all n=3-4 [number of experts]; importance scores=16.7-95.0). The qualitative analysis resulted in four overarching themes: (1) combination behavior change, technical, and design features needed; (2) extended feedback and tailoring is advised; (3) theoretical or evidence base as standard; and (4) entry requirements related to app use. Conclusions: The results show that a variety of features, including design, technical, and behavior change, are considered important for the effectiveness of physical activity–related apps by experts from different fields of expertise. These insights may assist in the development of an improved app rating scale.
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The sharing economy holds promise for the way we consume, work, and interact. However, consuming in the sharing economy is not without risk, as institutional trust measures (e.g. contracts, regulations, guarantees) are often absent. Trust between sellers and buyers is therefore crucial to complete transactions successfully. From a buyer ́s perspective, a seller ́s profile is an important source of information for judging trustworthiness, because it contains multiple trust cues such as a reputation score, a profile picture, and a textual self-description. The effect of a seller’s self-description on perceived trustworthiness is still poorly understood. We examine how the linguistic features of a seller’s self-description predict perceived trustworthiness. To determine the perceived trustworthiness of 259 profiles, 189 real buyers on a Dutch sharing platform rated their trustworthiness. The results show that profiles were perceived as more trustworthy if they contained more words (which could be an indicator of uncertainty reduction), more words related to cooking (indicator of expertise), and more words related to positive emotions (indicator of enthusiasm). Also, a profile’s perceived trustworthiness score correlated positively with the seller’s actual sales performance. These findings indicate that a seller’s self-description is a relevant signal to buyers, eventhough it is cheap talk (i.e. easy to produce). The results can guide sellers on how to self-present themselves on sharing platforms and inform platform owners on how to design their platform so that it enhances trust between platform users.
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Many lithographically created optical components, such as photonic crystals, require the creation of periodically repeated structures [1]. The optical properties depend critically on the consistency of the shape and periodicity of the repeated structure. At the same time, the structure and its period may be similar to, or substantially below that of the optical diffraction limit, making inspection with optical microscopy difficult. Inspection tools must be able to scan an entire wafer (300 mm diameter), and identify wafers that fail to meet specifications rapidly. However, high resolution, and high throughput are often difficult to achieve simultaneously, and a compromise must be made. TeraNova is developing an optical inspection tool that can rapidly image features on wafers. Their product relies on (a) knowledge of what the features should be, and (b) a detailed and accurate model of light diffraction from the wafer surface. This combination allows deviations from features to be identified by modifying the model of the surface features until the calculated diffraction pattern matches the observed pattern. This form of microscopy—known as Fourier microscopy—has the potential to be very rapid and highly accurate. However, the solver, which calculates the wafer features from the diffraction pattern, must be very rapid and precise. To achieve this, a hardware solver will be implemented. The hardware solver must be combined with mechatronic tracking of the absolute wafer position, requiring the automatic identification of fiduciary markers. Finally, the problem of computer obsolescence in instrumentation (resulting in security weaknesses) will also be addressed by combining the digital hardware and software into a system-on-a-chip (SoC) to provide a powerful, yet secure operating environment for the microscope software.
De technische en economische levensduur van auto’s verschilt. Een goed onderhouden auto met dieselmotor uit het bouwjaar 2000 kan technisch perfect functioneren. De economische levensduur van diezelfde auto is echter beperkt bij introductie van strenge milieuzones. Bij de introductie en verplichtstelling van geavanceerde rijtaakondersteunende systemen (ADAS) zien we iets soortgelijks. Hoewel de auto technisch gezien goed functioneert kunnen verouderde software, algorithmes en sensoren leiden tot een beperkte levensduur van de gehele auto. Voorbeelden: - Jeep gehackt: verouderde veiligheidsprotocollen in de software en hardware beperkten de economische levensduur. - Actieve Cruise Control: sensoren/radars van verouderde systemen leiden tot beperkte functionaliteit en gebruikersacceptatie. - Tesla: bij bestaande auto’s worden verouderde sensoren uitgeschakeld waardoor functies uitvallen. In 2019 heeft de EU een verplichting opgelegd aan automobielfabrikanten om 20 nieuwe ADAS in te bouwen in nieuw te ontwikkelen auto’s, ongeacht prijsklasse. De mate waarin deze ADAS de economische levensduur van de auto beperkt is echter nog onvoldoende onderzocht. In deze KIEM wordt dit onderzocht en wordt tevens de parallel getrokken met de mobiele telefonie; beide maken gebruik van moderne sensoren en software. We vergelijken ontwerpeisen van telefoons (levensduur van gemiddeld 2,5 jaar) met de eisen aan moderne ADAS met dezelfde sensoren (levensduur tot 20 jaar). De centrale vraag luidt daarom: Wat is de mogelijke impact van veroudering van ADAS op de economische levensduur van voertuigen en welke lessen kunnen we leren uit de onderliggende ontwerpprincipes van ADAS en Smartphones? De vraag wordt beantwoord door (i) literatuuronderzoek naar de veroudering van ADAS (ii) Interviews met ontwerpers van ADAS, leveranciers van retro-fit systemen en ontwerpers van mobiele telefoons en (iii) vergelijkend rij-onderzoek naar het functioneren van ADAS in auto’s van verschillende leeftijd en prijsklassen.
Drones have been verified as the camera of 2024 due to the enormous exponential growth in terms of the relevant technologies and applications such as smart agriculture, transportation, inspection, logistics, surveillance and interaction. Therefore, the commercial solutions to deploy drones in different working places have become a crucial demand for companies. Warehouses are one of the most promising industrial domains to utilize drones to automate different operations such as inventory scanning, goods transportation to the delivery lines, area monitoring on demand and so on. On the other hands, deploying drones (or even mobile robots) in such challenging environment needs to enable accurate state estimation in terms of position and orientation to allow autonomous navigation. This is because GPS signals are not available in warehouses due to the obstruction by the closed-sky areas and the signal deflection by structures. Vision-based positioning systems are the most promising techniques to achieve reliable position estimation in indoor environments. This is because of using low-cost sensors (cameras), the utilization of dense environmental features and the possibilities to operate in indoor/outdoor areas. Therefore, this proposal aims to address a crucial question for industrial applications with our industrial partners to explore limitations and develop solutions towards robust state estimation of drones in challenging environments such as warehouses and greenhouses. The results of this project will be used as the baseline to develop other navigation technologies towards full autonomous deployment of drones such as mapping, localization, docking and maneuvering to safely deploy drones in GPS-denied areas.
