We investigate entrepreneurial ecosystems that support circular start-ups and innovation. We argue that entrepreneurial ecosystems for circularity are constellations of existing entrepreneurial and innovation ecosystems that extend across geographies and sectors. Our research question centres on understanding ecosystem intermediation that facilitates the embedding of circular start-ups in different ecosystems and addresses a pertinent gap in the literature about ecosystem intermediation for circular transitions and circular start-ups Focusing on the emerging circular transition in the textiles and apparel industry, we gathered data from in-depth interviews, field observations, and archival documentation over a seven-year period. Our findings show that entrepreneurial ecosystems for circular start-ups are purposefully intermediated at a meta level, combining elements of extant ecosystems to focus on circularity. Drawing on these insights, we conceptualize ecosystem intermediation as connecting diverse ecosystems across geographic and sectoral boundaries. Our study contributes to the literatures on circular entrepreneurship, circular ecosystems, and ecologies of system intermediation as well as provides practical implications for practitioners and policy makers.
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IntroductionWithin the Entrepreneurship program at the Amsterdam University of Applied Sciences, there are a number of student start-ups that are developing inclusive, sustainable, and innovative solutions. We noticed that, during this process, they need to access certain facilities to develop a proof of concept or minimal viable product. When student start-ups tried to access facilities themselves, they found insufficient information about accessing facilities and contact persons. As Hui & Gerber (2017) stated that accessible facilities like a makerspace have a positive impact on the number of students who are embarking on the venture of a new business. Halbinger, (2020) states that there needs to be more research about university makerspaces in relation to the facilitation of student-entrepreneurship.
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Big report of the Startup EDR Project. See how the project promoted interregional collaboration and development for startups within the Ems-Dollart region.
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From start-up to scale-up to market domination in a European context. Companies planning to move into the next phase of their development must be able to finance their ambitions. Those that take the long-term view and a healthy focus on revenue generation stand the greatest chance of staying on course to success.
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This report analysis the geography of the tech sector in Amsterdam, with a focus on scaleups. After a literature review, it contains a quantitative analysis, showing and mapping the spatial clustering of various types of tech companies cluster in the Amsterdam region. Then, based on interviews, we analyse the growth dynamics, location preferences and geographical dynamics of tech scale-ups. Also, we identify which push and pull factors affect Amsterdam based tech scale-up companies in their locational decision making, on the neighborhood and building level.
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Een goed team kan elk project aan en een slecht team kan elk project verprutsen. Dat weten we in de bouw al jaren. Maar hoe realiseer je een goed team? We weten dat een goede start een belangrijke voorwaarde is. En toch slagen we er altijd weer in om deze wetenschap te negeren. Een team is: 30 mensen die elkaar niet kennen, 15 in de keet van de opdrachtgever en 15 in de keet van de bouwer en gaan met die banaan. Een slechte start leidt tot een minder presterend team en dus tot een matig project. Waarom is een projectstartup zo belangrijk en hoe pak je dat aan? In een studie door het A2 convenant is deze materie op een praktische wijze behandeld.
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Objective To evaluate the validity and reliability of the Dutch STarT MSK tool in patients with musculoskeletal pain in primary care physiotherapy. Methods Physiotherapists included patients with musculoskeletal pain, aged 18 years or older. Patients completed a questionnaire at baseline and follow-up at 5 days and 3 months, respectively. Construct validity was assessed by comparing scores of STarT MSK items with reference questionnaires. Pearson’s correlation coefficients were calculated to test predefined hypotheses. Test-retest reliability was evaluated by calculating quadratic-weighted kappa coefficients for overall STarT MSK tool scores (range 0–12) and prognostic subgroups (low, medium and high risk). Predictive validity was assessed by calculating relative risk ratios for moderate risk and high risk, both compared with low risk, in their ability to predict persisting disability at 3 months. Results In total, 142 patients were included in the analysis. At baseline, 74 patients (52.1%) were categorised as low risk, 64 (45.1%) as medium risk and 4 (2.8%) as high risk. For construct validity, nine of the eleven predefined hypotheses were confirmed. For test-retest reliability, kappa coefficients for the overall tool scores and prognostic subgroups were 0.71 and 0.65, respectively. For predictive validity, relative risk ratios for persisting disability were 2.19 (95% CI: 1.10–4.38) for the medium-risk group and 7.30 (95% CI: 4.11–12.98) for the highrisk group. Conclusion The Dutch STarT MSK tool showed a sufficient to good validity and reliability in patients with musculoskeletal pain in primary care physiotherapy. The sample size for high-risk patients was small (n = 4), which may limit the generalisability of findings for this group. An external validation study with a larger sample of high-risk patients (�50) is recommended.
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This study introduces a novel methodology for the post-analysis of operational predictability by leveraging timestamps collected through the Airport Collaborative Decision Making (A-CDM) framework. Focusing on the start-up and departure phases, the analysis highlights the importance of accurately planning and managing key timestamps, such as the Target Off-Block Time (TOBT) and Target Start-Up Approval Time (TSAT), which are critical for operational efficiency. Using one week of sample data from Schiphol Airport, this research demonstrates the potential benefits of the proposed framework in improving predictability during the start-up phase, particularly by identifying and analyzing outliers and anomalies. The start-up phase, a critical component of the outbound process, was broken down into subphases to allow for a more detailed assessment. The findings suggest that while 96% of flights maintain TOBT accuracy within ±20 minutes, 68% of flights miss their TOBT by 2 to 17.5 minutes, with 364 notable outliers. These deviations highlight areas for further investigation, with future work aiming to explore the impact of influencing factors such as weather, resource availability, and support tools. The proposed framework serves as a foundation for improving operational predictability and efficiency at airports.
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