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In recent years, slow travel modes (walking, cycling) have gained much interest in the context of urban air quality management. This article presents the findings from a novel air quality measurement experiment in the Netherlands, by regarding cyclists as carriers and transmitters of real-world information on fine-grained air quality conditions. Using individual sensors on bicycles—connected to a GPS positioning system—online local pollution information originating from cyclists' detailed spatial mobility patterns is obtained. Such air quality surface maps and cyclists' mobility maps are then used to identify whether there are significant differences between the actual route choice and the cyclists' shortest route choice, so as to identify the implications of poor air quality conditions for their mobility choices. Thus, the article seeks to present both a detailed pollution surface map and the complex space-time mobility patterns of cyclists in a region, on the basis of online quantitative data—at any point in time and space—from bicycle users in a given locality. In addition, the article estimates their response—in terms of route choice—to detailed air-quality information through the use of a novel geoscience-inspired analysis of space-time "big data." The empirical test of our quantitative modeling approach was carried out for the Greater Utrecht area in the Netherlands. Our findings confirm that spatial concentration of air pollutants have great consequences for bike users' route choice patterns, especially in the case of non-commuting trips. We also find that cyclists make longer trips on weekends and in the evenings, especially towards parks and natural amenities. [ABSTRACT FROM AUTHOR]

Labor market dynamics is shaped by various social, psychological and economic drivers. Studies have suggested that job quit and labor market turnover are associated with job satisfaction. This study examines the determinants of job satisfaction using a large survey dataset, namely the LISS Work and Schooling module on an extensive sample of persons from the Netherlands. To handle these big data, machine learning models based on binary recursive partitioning algorithms are employed. Particularly, sequential and randomized tree-based techniques are used for prediction and clustering purposes. In order to interpret the results, the study calculates the sizes and directions of the effects of model features using computations based on the concept of Shapley value in cooperative game theory. The findings suggest that satisfaction with the social atmosphere among colleagues, wage satisfaction, and feeling of being appreciated are major determinants of job satisfaction. [ABSTRACT FROM AUTHOR]

This paper departs from the regional resilience concept -- as part of a broad strand of literature on non-linear dynamic systems in a space-economy -- and introduces the notion of prosilience to highlight the policy challenge of developing radically new and innovative strategies for regions in decline. The mining industry will be used as an illustrative case. The notion of phoenix regions is put forward to argue that an external disruption or shock in an established industrial sector in a region necessitates unconventional survival strategies oriented towards entirely new market demands and based on totally different product packages. Ansoff's model on product diversification in competitive markets forms an inspiration source for the Schumpeterian 'creative destruction' proposition advocated in this study. An illustrative case study is concisely described in the present paper, viz. the South-Limburg coal mining region in the Southern part of the Netherlands. Smart prosilience trajectories supported in particular by evidence-based decision support tools are sketched for such depressed regions, based on the so-called Pentagon intervention model. The paper is concluded with some general policy lessons for an intelligent transformation of regions in decline. [ABSTRACT FROM AUTHOR]

This paper provides an overview of regional science research in the Netherlands since the 1960s. It adopts a contextual thematic approach in identifying and interpreting regional science research topics, practices and methodologies, inspired by Toynbee's challenge and response concept. It argues that place‐based, cultural and historical conditions in the Netherlands have prompted a pragmatic and evidence‐based scientific approach, in which in particular an innovative quantitative orientation accompanied by a methodological heterogeneity has given Dutch regional science a high international profile. Over the past decades, numerous regional scientists in the country have contributed to this achievement, too many to be mentioned in this overview. This paper has its limitations and offers mainly thematic examples of original—often quantitative—research undertaken by various Dutch regional scientists, that make a difference compared to general approaches in Europe and world‐wide. From our concise review we conclude that – despite the small size of the country – the challenge and creative response model of Dutch regional science has been rather successful. [ABSTRACT FROM AUTHOR]

We investigate econometrically whether cultural diversity at the workplace boosts innovation. Our longitudinal linked employer-employee data combines two innovation surveys, with Dutch administrative, tax and regional data. We analyse the determinants of a firm's product and process innovations with respect to the firm's internal resources, employee composition and regional agglomeration externalities. We reconfirm the findings of several other recent studies showing a positive partial correlation between innovation and cultural diversity in pooled cross-sectional data; in some cases even when accounting for reverse causation. However, no statistically significant traces of benefit for innovation from cultural diversity remain after introducing firm fixed effects. [ABSTRACT FROM AUTHOR]

The varied supply of tourism services - with particular emphasis on tangible and intangible cultural aspects - corresponds ideally to visitors' characteristics and wishes. This paper considers a major tourist destination, such as Amsterdam, as an export-oriented multiproduct company, characterized by spatial and functional market segmentation and monopolistic competition reflected in product differentiation. Urban branding and attractiveness may favour tourist destination loyalty. The complex decision web of motivation and satisfaction of tourists in Amsterdam is analysed with a structural equations model (SEM). The authors find that different tourist profiles, in terms of personal characteristics and motivations, can significantly impact the satisfaction received from tourism services. Furthermore, and most interestingly, the results suggest that satisfaction does not necessarily lead to improved destination loyalty, but is contingent on the source of satisfaction. In this case, satisfaction resulting from tangible or intangible cultural sources has clearly different implications for loyalty, with relevant managerial implications. [ABSTRACT FROM AUTHOR]