Rural Areas in the Netherlands

Haartsen, Tialda; Huigen, Paulus; Groote, Peter

doi:10.1111/1467-9663.00243

Cited by 29 publications

(35 citation statements)

References 3 publications

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“…The degree of urbanisation of a neighbourhood was defined by its address density. We considered neighbourhoods with fewer than 1,000 addresses per square kilometre to be rural, because they are generally perceived as being rural by the Dutch people (Haartsen et al, 2003). Rural neighbourhoods were excluded from the sample if they hosted a centre for asylum seekers during the period of observation, because the opening or closing of such a centre could cause a sudden increase or decrease in the population of a neighbourhood, and an inflation of the migration data.…”

Section: Methodsmentioning

confidence: 99%

“…Only six municipalities in the region had more than 50,000 inhabitants (Statistics Netherlands, 2013). Following Haartsen et al (2003), who defined areas with an address density of fewer than 1,000 addresses per square kilometre as rural, 66% of the North-Dutch were living in rural areas in 2006, compared with only 38% of the population across the Netherlands (Statistics Netherlands, 2013).…”

Section: North-netherlandsmentioning

confidence: 99%

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The self-reinforcing effects of population decline: An analysis of differences in moving behaviour between rural neighbourhoods with declining and stable populations

Elshof

Wissen

Mulder

2014

Journal of Rural Studies

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The consequences of population decline are present at different geographical scales and are often believed to be self-reinforcing. This means that population decline possibly causes changes in the living environment, which brings about more population decline. This research analysed if population decline at the neighbourhood level has an effect on the probability to move out or within rural neighbourhoods in North-Netherlands. It was expected that a preceding decline of the population in the neighbourhood increased the probability to move out of the neighbourhood, but that this effect differed for categories of the population and for moves over short and long distance. Using register data and additional surveys for 2006, a multinomial logistic regression model was constructed to estimate the effects of a preceding decline of neighbourhood populations on the probability to move over short and long distances for different categories of the population. It was found that a preceding decline of the neighbourhood population increased the probability to move out of the neighbourhood. However, this effect was only found for moves out of the neighbourhood up to 10 kilometres of especially young adults, couples with children, and people aged 65 to 75. Moreover, by calculating estimated probabilities of moving out of neighbourhoods with declining and stable populations, it was shown that the difference between actual numbers of people moving out of these two types of neighbourhoods, was small and could therefore take a long time to have serious impact on the neighbourhood population.

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Section: Methodsmentioning

confidence: 99%

Section: North-netherlandsmentioning

confidence: 99%

The self-reinforcing effects of population decline: An analysis of differences in moving behaviour between rural neighbourhoods with declining and stable populations

Elshof

Wissen

Mulder

2014

Journal of Rural Studies

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“…Thus, any generation may have distinctive social representation (Moscovici, 1984). Haartsen, Huigen, and Groote (2003) detected strong age-related differences in social representation of rurality. Young respondents based their rural Anne-Marie Lebrun 199 representations on visual-figurative and socioeconomic function aspects mainly, whereas for seniors, sociocultural aspects of the countryside were also important (Haartsen et al, 2003).…”

Section: The Social Representations Theorymentioning

confidence: 95%

Representations of a Destination City Break. Analysis Based on Free Associations

Lebrun¹

2014

Journal of Travel & Tourism Marketing

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The article demonstrates the interest in using social representations as a tool of analysis in the representation of city breaks for two generational cohorts. The main objective of this study is to identify and to compare social representations of a city break for Generation X and for Baby Boomers. The article is based on a review of the generational segmentation and the social representation literature. The results indicate no difference between both generations for strong and numerous associations but a difference for architectural and historical aspects for Baby Boomers and experiential activities for Generation X. Theoretical and managerial implications are discussed before the article concludes with limitations and directions for future research.

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“…To sum up the overall findings with regard to the situation of the districts on the map, the structure is characterised as five blocks of local housing-market type with fuzzy boundaries: (1)`truly urban'; (2)`urban periphery'; (3)`pseudo-rural' areas with a concentration of`small young families with kids'; (4)`agricultural rural' areas with large families and also industry [for a distinction between categories (3) and (4), see Haartsen et al (2003)]; and (5) areas inbetween, also characterised by`concentrations of poorer, middle-aged, and elderly residents'. Finally, it can be noted that the labels are, in some cases, related to absolute location (even though no geographical input was provided), but in other cases they are related to the relative location within the region, so that areas in small suburban municipalities group together (although being far from each other geographically).…”

Section: T Kaukomentioning

confidence: 99%

“…Preference formation has not been allowed to lead market processes until very recently, as popular areas have emerged in distant suburbs, on the one hand, and modernised flats in old architectural blocks in the inner city, on the other hand. A related aspect is that rural living is still related to agricultureönot to`pseudo-rural' preferences, as was the case in the Netherlands (see Haartsen et al, 2003).…”

Section: Evaluation Of the Findingsmentioning

confidence: 99%

Using the Self-Organising Map to Identify Regularities across Country-Specific Housing-Market Contexts

Kauko¹

2005

Environ Plann B Plann Des

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The aim to explore and monitor housing-market fundamentals (prices, dwelling features, area density, residents, etc) at a macrolocational level is motivated by various policy-related and business-related goals (for example, see Tu, 2000). Housing-market segmentation (that is, the emergence of housing submarkets), a concept with increasing relevance, relates to the differentiation of housing through the income and preferences of residents and in terms of administrative circumstances. The causes of segmentation processes pertain to a multitude of impacts related to geographical location (including topographical constraints), structural (that is, house-specific and site-specific) attributes, prices, consumer preferences and incomes, government regulation, and asymmetric information and power positions between market participants (for example, see Watkins, 2001). The monitoring of segmentation has various practical implications when a comparative evaluation of attractiveness is required.However, the research problem of determining segments and tracking the processes behind segmentation has also received attention as a purely academic endeavour within housing economics. According to Maclennan and Tu (1996), submarkets are the product of market imperfections in relation to local-level supply-and-demand structures. Thus, differentiation of preferences and product groups, trade friction and search processes lead to a complexity and variety in the housing commodity; furthermore, any equilibrium tends to be unstable, in the short term at least. Although depending on the exact definitions used, in any one housing-market context segments are likely to occur over time and space, which implies that the verification of segmentation is predominantly an empirical issue. Although a national housing market is Using the self-organising map to identify regularities across country-specific housing-market contexts Abstract. The aim of exploring and monitoring housing-market fundamentals (prices, dwelling features, area density, residents, and so on) on a macrolocational level relates to both public and private sector policymaking. Housing market segmentation (that is, the emergence of housing submarkets), a concept with increasing relevance, is defined as the differentiation of housing in terms of the income and preferences of the residents and in terms of administrative circumstances. In order to capture such segmentation empirically, the author applies a fairly new and emerging technique known as the`selforganising' map (SOM), or`Kohonen map'. The SOM is a type of (artificial) neural network öa nonlinear and flexible (that is, nonparametric or semiparametric) regression and`machine learning' technique. By utilising the ability of the SOM to visualise patterns, one can analyse various dimensions within the variation of the dataset. Segmentation may then be detected depending on the resulting patterns across the map layers, each of which represents the data variation for one input variable. Utilising an inductive modelling strategy, t...

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Rural Areas in the Netherlands

Cited by 29 publications

References 3 publications

The self-reinforcing effects of population decline: An analysis of differences in moving behaviour between rural neighbourhoods with declining and stable populations

The self-reinforcing effects of population decline: An analysis of differences in moving behaviour between rural neighbourhoods with declining and stable populations

Representations of a Destination City Break. Analysis Based on Free Associations

Using the Self-Organising Map to Identify Regularities across Country-Specific Housing-Market Contexts

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