Challenges that surveys are facing are increasing data collection costs and declining budgets. During the past years, many surveys at Statistics Netherlands were redesigned to reduce costs and to increase or maintain response rates. From 2018 onwards, adaptive survey design has been applied in several social surveys to produce more accurate statistics within the same budget. In previous years, research has been done into the effect on quality and costs of reducing the use of interviewers in mixed-mode surveys starting with internet observation, followed by telephone or face-to-face observation of internet nonrespondents. Reducing follow-ups can be done in different ways. By using stratified selection of people eligible for follow-up, nonresponse bias may be reduced. The main decisions to be made are how to divide the population into strata and how to compute the allocation probabilities for face-to-face and telephone observation in the different strata. Currently, adaptive survey design is an option in redesigns of social surveys at Statistics Netherlands. In 2018 it has been implemented in the Health Survey and the Public Opinion Survey, in 2019 in the Life Style Monitor and the Leisure Omnibus, in 2021 in the Labour Force Survey, and in 2022 it is planned for the Social Coherence Survey. This paper elaborates on the development of the adaptive survey design for the Labour Force Survey. Attention is paid to the survey design, in particular the sampling design, the data collection constraints, the choice of the strata for the adaptive design, the calculation of follow-up fractions by mode of observation and stratum, the practical implementation of the adaptive design, and the six-month parallel design with corresponding response results.
Challenges that surveys are facing are increasing data collection costs and declining budgets. During the past years, many surveys at Statistics Netherlands were redesigned to reduce costs and to increase or maintain response rates. From 2018 onwards, adaptive survey design has been applied in several social surveys to produce more accurate statistics within the same budget. In previous years, research has been done into the effect on quality and costs of reducing the use of interviewers in mixed-mode surveys starting with internet observation, followed by telephone or face-to-face observation of internet nonrespondents. Reducing follow-ups can be done in different ways. By using stratified selection of people eligible for follow-up, nonresponse bias may be reduced. The main decisions to be made are how to divide the population into strata and how to compute the allocation probabilities for face-to-face and telephone observation in the different strata. Currently, adaptive survey design is an option in redesigns of social surveys at Statistics Netherlands. In 2018 it has been implemented in the Health Survey and the Public Opinion Survey, in 2019 in the Life Style Monitor and the Leisure Omnibus, in 2021 in the Labour Force Survey, and in 2022 it is planned for the Social Coherence Survey. This paper elaborates on the development of the adaptive survey design for the Labour Force Survey. Attention is paid to the survey design, in particular the sampling design, the data collection constraints, the choice of the strata for the adaptive design, the calculation of follow-up fractions by mode of observation and stratum, the practical implementation of the adaptive design, and the six-month parallel design with corresponding response results.
The percentage of sports and leisure shoes sold worldwide is gradually increasing. However, consumers have little or no objective information on the mechanical properties of the shoes. A justified selection protocol of sports and leisure shoes based on static and dynamic shoe properties considering the intended use is essential. Today, commonly accepted dynamic test protocols for (sports) shoes do not exist. The development of an artificial parametric foot as part of an innovative robot gait simulator is a tool to objectify shoe properties independently from possible compensations encountered during assessment of test persons. This contribution discusses the development of an artificial foot enabling objective testing of the mechanical and functional properties of sports and leisure shoes.
The project ‘Towards resilient leisure, tourism and hospitality (LTH) ecosystems in Europe’ addresses the critical problem of unsustainable practices in the tourism and travel industry. The LTH industry is ‘back on track’ after recovering from the global Covid-19 crisis. Destinations show increased numbers of international arrivals and rapid growth of tourism-related revenues. It is foreseen that cities like Amsterdam, but also vulnerable natural areas, will receive record numbers of visitors in the coming decade. The dominant economic model operating within the industry nonetheless prioritizes short-term gains, resulting in extreme exploitation of resources, labour, and local communities, evidenced by negative impacts in European destinations like Venice and the Canary Islands. The project aims to shift the industry’s focus to long-term sustainability, addressing systemic constraints and facilitating a transition that aligns with European priorities for a sustainable and just future. It builds vital connections between regional, national, and European research priorities by addressing and advocating for climate and social justice. Regionally, it investigates best practices across diverse tourism environments in Finland, Spain, Sweden, the UK, Scotland, and The Netherlands. Nationally, it challenges the status quo by proposing alternative governance frameworks that individual countries could adopt to encourage sustainable tourism practices. On a European scale, the project aligns with EU goals of climate action and sustainable development, supporting objectives of the European Green Deal and the United Nations Sustainable Development Goals (SDGs). It aims to build solid theoretical foundations necessary for a transition towards more resilient and environmentally and socially inclusive LTH ecosystems. Through integrating insights from multiple regions, the project transcends local boundaries and offers scalable solutions that can influence policy and industry standards at both national and European levels. The project's transdisciplinary nature ensures that proposed solutions are grounded in diverse eco-socioeconomic contexts, making them robust and adaptable.
