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Residential satisfaction and mobility behaviour among the young: insights from the post-Soviet city of Riga

Wohnzufriedenheit und Mobilitätsverhalten zwischen der Jugend: Einsichten aus der Post-Sowietischen Stadt Riga
Jānis Krūmiņš, Guido Sechi et Māris Bērziņš

Résumés

Urban residential areas in the former Soviet Union and Central Eastern Europe have experienced radical demographic and socioeconomic changes, with relevant consequences for residents. Although many studies have addressed post-socialist urban change at the macro level, little is known about individuals’ residential satisfaction. Besides, in this domain, two gaps must be acknowledged. First, most studies on residential satisfaction tend to focus on ‘static’ predictors, overlooking the interrelation of residential satisfaction with mobility behaviour, in spite of it being widely acknowledged in literature. Second, the analysis of residential satisfaction among specific socio-demographic groups tends to overlook younger residents in favour of groups which are considered to be more vulnerable.
The aim of this study is to investigate how both mobility and static factors affect young individuals’ assessment of residential satisfaction. The research is based on 2015 panel survey data. The survey sample consists of around 700 permanent residents of Riga in the 15-34 age range. The findings suggest that residential satisfaction is significantly influenced, among other factors, by aspects of everyday mobility. In particular, our results highlight that transport modes and habits significantly affect residential satisfaction among younger residents, whereas they are negligible among elder ones.

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Texte intégral

This study was supported by the Latvian Council of Science through the National Research Program 5.2. “Economic Transformation, Smart Growth, Governance and Legal Framework for the State and Society for Sustainable Development - a New Approach to the Creation of a Sustainable Learning Community (EKOSOC-LV) - Project 5.2.4 “Renewal of society through reducing the risk of depopulation, through demographic development and strengthening links with the diaspora for the transformation of the Latvian economy”).

Introduction

1Residential satisfaction – a subject of research in diverse areas of social and regional science – can be defined as the match between an individual’s ideal environment and the objective and subjective characteristics of her / his actual environment (Huang et al. 2015; Sahraoui et al., 2016). It is considered a relevant component of life quality (Huang et al., 2015). Determinants of residential satisfaction are very complex and findings in this domain are not conclusive. Housing characteristics, neighbourhood environment and quality, household type, family characteristics and socio-demographic features, migration behaviour have been found to correlate significantly with residential satisfaction (Mohit, Adel, 2014; Huang et al., 2015; Lin, Li, 2017). The relationship between residential satisfaction and life and everyday mobility is particularly challenging and, in a certain sense, not fully explored. As for the former, residential mobility is considered both as a consequence of residential satisfaction and as a process which allows to improve it (Spackova et al., 2016). As for everyday mobility and its modes, they are related to neighbourhood satisfaction by affecting the perception of distance from work, school, shops etc. (Mohit, Adel, 2014).

2Literature on residential satisfaction has developed in different directions in European and US studies, the former being more focused on differences between rental and ownership, the latter on gender, ethnicity and age differences (Pelin Sarioglu-Erdogdu, 2015).

3Age-focused residential satisfaction literature has generally focused on the elderly, seen as particularly vulnerable to changes in the physical, functional and social aspects of their living environment and more dependent from such environment due to retirement and lower mobility (Temelova, Slezakova, 2014; Zhang, Zhang, 2017). On the other hand, younger residents – generally considered as more mobile and less attached to their residence place – are commonly overlooked in residential satisfaction studies, with the partial exception of students in university dormitories, whose satisfaction is generally found to be mostly affected by housing quality and social factors (Ning, Chen, 2016).

4Residential satisfaction in the specific context of Central-Eastern Europe and former USSR is a relevant issue, due to the substantial physical and social transformation of former socialist countries in the last decades, but it tends to be overlooked in favour of strong emphasis on macro-scale processes (Kahrik et al., 2016). A rather developed micro-level analysis thread focuses on the social transformation and reputation of neighbourhoods in post-socialist cities (see e.g. Gentile, 2016). Among the few studies on residential satisfaction in the CEE, Hanak et al. (2015) find neighbourhood quality perception and logistics to be significant predictors among residents of the three main cities in Czech Republic. Herfert et al. (2013) investigate types of residential satisfaction and residential mobility, and their interrelations, in large scale housing estates of five large post-socialist European cities.

Theoretical model

5In agreement with the most relevant literature, we hypothesize that residential satisfaction is affected by both subjective perceptions and objective characteristics of the housing and neighbourhood; family chracteristics; and life mobility (length of residence). Next to it, we incorporate predictors related to everyday mobility and modes of transport, which are generally neglected in quantitative modeling of residential satisfaction. Socio-demographic variables (household income, gender, educational level) are also included in the model as predictors.

Study context

6Riga is the largest city in Latvia, and home to 641,423 (2017) inhabitants that is approximately one third of country’s nearly 2 million population. There are several historical layers that define the contemporary urban structure of Riga. Thus, the city has evolved in three major phases, and its socio-spatial structure consists of three major urban zones, as it could be found in a great majority of cities in Central and Eastern Europe (e.g. Sykora, 2009; Kovacs, Herfert, 2012).

7The first layer, the historical core of inner-city or Old Town was formed since the 13th century and nowadays its medieval core lies in the very central location among the other inner-city neighbourhoods (Figure 1). The second layer started its formation after the World War II, when Latvia was annexed by the Soviet Union. In following decades, the construction of large-scale panel housing estates started in order to establish an egalitarian Soviet society by settling people from different socio-economic categories in these new neighbourhoods. However, despite the fact that under the central planning system, the state sought to ensure satisfactory and equal living standards for all, previous studies have found significant levels of residential differentiation (French, Hamilton, 1979; Kornai, 1992; Enyedi, 1998). This can be mainly explained with massive in-migration flows from other states of the Soviet Union. These Russian-speaking immigrants usually received preferred conditions with new apartments allocated in the newly built large-scale housing estates (Kulu, 2003; Gentile, Tammaru 2006). Likewise, in neighbouring Tallinn the quality of housing and its residential attractiveness in Riga is largely determined by the interplay of historical legacies of housing construction and geographical location within the particular city. Thus, the quality of dwellings in older and more distant or peripheral large-scale panel housing estates has significantly deteriorated over time (Kahrik, Tammaru, 2010).

8Since the restoration of independence in 1991, political and economic restructuring took place, and Riga started to lose population due to negative demographic rates and by out-migration. Despite the fact that Riga lost thousands of Russian speaking out-migrants during 1990s, many still opted to stay. According to national statistics, the share of ethnic minorities even today constitutes more than half of city’s population (CSB, 2017), thus competing with Latvians for better conditions in a free market oriented economy. The studies have confirmed that the members of the Russian-speaking minority in Latvia have adjusted worse to economic restructuring and suffered more from employment losses in different industrial sectors in which they were overrepresented (Aasland, 2002; Lindermann, 2013; Muiznieks et al., 2013). Nevertheless, today slightly more than 75 percent of the inhabitants of Riga live in Soviet-era mass housing areas or neighbourhoods dominated by this distinctive type of housing. According to 2011 Population Census, 55% of all residents living in Soviet mass housing were Russians, Belarussians or Ukrainians, while this share was considerably lower for Latvians (38.8%). In contrast, the share of Latvians is slightly higher in the inner city and considerably higher in the outer city – the third layer of housing. This area mostly constitutes of newly built and expensive apartments, and provides house to higher income groups of population, and had rapidly emerged through processes of suburbanization after 1991.

Figure 1. Neighbourhoods divided by urban zones in Riga.

Figure 1. Neighbourhoods divided by urban zones in Riga.

Source: authors’ figure; Riga city council

9Three urban zones highly differ not only by ethnic composition, but also by the age structure of residents. In 2011, the average age of residents of panel housing estates was 42.7 years, whereas the inhabitants of inner city (40.2) and outer city (39.6) were considerably younger. Several studies that examine post-socialist city metropolitan regions, reveal the difference in sociodemographic and socioeconomic characteristics between the residents of core city and suburban regions (Kahrik, Tammaru, 2008; Spackova, Ourednicek, 2011). While the core city is more attractive to younger people, families with children are more represented among suburbanites. In such case, the inner city of Riga can be functionally associated with the former, whereas the outer city is considered as mostly suburban area.

10Statistics prove that the residents of inner and outer urban zone are younger than those of panel housing estates built during the Soviet time. In 2016, the share of 15-34 years old residents in neighbourhoods varied from 21% to 38% (Figure 2). For 24 out of 58 neighbourhoods the share of young adults exceeds 25%.

11

Figure 2. Share of young residents (15-34 years old) by neighbourhoods of Riga in 2016.

Figure 2. Share of young residents (15-34 years old) by neighbourhoods of Riga in 2016.

Authors’ analysis of data derived from Central Statistics Bureau of Latvia

Data and methodology

12The empirical analysis was based on panel survey data collected in 2015 and including 2,043 respondents resident in Riga, in the 15-74 age range. Out of the overall sample, 703 respondents are in the 15-34 years age range.

13The analysis has been based on multiple linear regression.

14The dependent variable (residential satisfaction) is a metric scale built upon psychometric items measured on 4-point Likert scales, measuring satisfaction with the residential environment. The predictors include scales, metric, ordinal, dichotomous and categorical variables:

  • Quality of lighting, quality of water infrastructure, quality of public transport and quality of roads are scales built upon psychometric items measured on 4-point Likert scales;

  • Frequency of use of public transport, car, and bicycle, and attitude towards panel housing estates, are single items measured on 4-point Likert scales;

  • Family size is a metric variable;

  • Education level and household income are an ordinal variables (5 levels);

  • Presence of children aged under 18, life mobility, everyday commuting, type of housing and type of neighbourhood are dichotomous variables;

  • Gender is categorical.

15Exploratory factor analysis has been used as a supporting technique in order to create scales on the basis of psychometric items.

16Relevant descriptive statistics for the sample are listed in Tables 1 and 2. They are broken down by age groups (respondents aged 15-34 vs respondents aged over 34).

Table 1. Socio-demographic and socio-economic sample composition. Descriptive statistics.

15-34

Over 34

Total

Gender

Males

42.8%

38.0%

39.6%

Females

57.2%

62.0%

60.4%

Education level

Primary

10.2%

3.7%

6.0%

Secondary

57.9%

65.1%

62.6%

Tertiary

31.9%

31.2%

31.4%

Family size

One person

10.5%

22.6%

18.5%

Two persons

25.1%

38.8%

34.0%

Three persons

37.4%

19.4%

25.7%

Four persons

20.5%

13.7%

15.9%

Five persons (or more)

6.5%

5.5%

5.9%

School age (0-18) children in household

Yes

49.9%

29.3%

36.4%

No

50.1%

70.7%

63.6%

Household income (per person)

Low

11.7%

16.2%

14.7%

Moderately low

15.2%

29.9%

24.8%

Average

12.7%

17.2%

15.6%

Moderately high

13.4%

9.8%

11.1%

High

16.1%

12.4%

13.7%

Does not know

30.9%

14.5%

20.1%

Internal migration

Mobile respondents

45.1%

50.8%

48.8%

Non-mobile respondents

54.9%

49.2%

51.2%

Commuting

Urban commuters

29.4%

32.6%

31.3%

Non commuters

70.6%

67.4%

68.7%

Type of dwelling

Private housing

8.4%

8.4%

8.4%

Flat

91.6%

91.6%

91.6%

Use of public transport

Have not used during the last year

8.2%

6.7%

7.2%

Less than once in a week

21.1%

16.7%

18.2%

At least once a week

21.6%

31.4%

28.0%

Every or almost every day

49.1%

45.2%

46.5%

Use of private transport

Have not used during the last year

31.2%

44.6%

39.9%

Less than once in a week

17.9%

13.9%

15.3%

At least once a week

23.0%

18.7%

20.2%

Every or almost every day

27.9%

22.9%

24.6%

Use of bicycle

Have not used during the last year

48.5%

74.4%

65.5%

Less than once in a week

19.0%

11.9%

14.4%

At least once a week

20.2%

10.9%

14.0%

Every or almost every day

12.4%

2.8%

6.1%

17Overall, compared to elder ones, younger residents in our sample, as an average, live in larger households with 3 or more persons in family. Elderly, in contrast, are more prone to have 1 or 2 persons per household. More persons in family mean that younger respondents also have higher share of those who have school aged children in their household.

18Younger respondents in our sample use means of private or bicycle transport more frequently than elderly ones. Both groups are equally mobile when using public transport. Higher share of young respondents uses public transport every or almost every day, compared to the elderly. In contrast, those respondents who are older than 34 years, are more prone to use public transport once or twice in a week. Overall, younger respondents are more mobile by the means of use of public, private and bicycle transport.

19Interestingly, younger respondents are slightly less mobile by the means of mobility. 45.1% of younger respondents have changed their place of residence since 2007, whereas for the elderly this share exceeds the non-mobile and reaches 50.8%. Younger respondents are also less inclined to have a working place in another neighbourhood. In this case, 29.4% of 15-34 years old respondents can be considered as urban commuters, while for the elderly this share is slightly higher (32.6%).

Table 2. Attitudinal variables. Mean values.

15-34

Over 34

Range

Quality of lighting

9.24

9.24

3 - 12

Water quality

6.24

6.22

2 - 8

Quality of public transport

3.84

3.75

2 - 8

Quality of roads

9.24

9.15

4 - 16

Attitude towards Soviet mass housing

2.99

3.03

1 - 4

20Both groups equally assess the quality of lighting in their neighbourhood, while younger respondents have slightly higher evaluation of water quality, and the quality of public transport, and the road infrastructure. The elderly, in contrast, have slightly better attitude towards Soviet mass housing.

Regression analysis: results

21The model for the cohort of respondents aged below 35 has a very high overall significance and a moderate goodness-of-fit and explanatory power.

22Residential satisfaction is positively affected by positive assessment of neighbourhood infrastructure (lighting and, to a much lesser extent, water), by the presence of children aged below 18 in the household, and life mobility. It is negatively affected by positive assessment of road infrastructure in the city; frequency of car and public transport use; family size; and, to a lesser extent, living in a flat. Assessment of public transport, household income, commuting habits, bicycle use, type of neighbourhood, type of dwelling, gender and education are non-significant factors.

Table 3. Linear regression: residential satisfaction. Respondents aged 15-34.

Independent variable

Standardized coefficient (Beta)

Scale: quality of lighting

.172***

Scale: quality of water infrastructure

.112*

Scale: quality of public transport

-.086

Scale: quality of roads

-.236***

Family size

-.117*

Household income

-.086

Children under 18: yes

.147**

Life mobility:yes

.098*

Everyday commuting:yes

-.014

Frequency of public transport use

-.137**

Frequency of car use

-.164***

Frequency of bicycle use

-.027

Type of housing: flat

-.103*

Type of neighbourhood: panel housing estate

-.016

Attitude towards dwelling

.082

Gender: female

.031

Education level

.053

Constant

7.038***

Sample size

703

F(sig.)

6.799(.000)

R-square

.275

Adjusted R-square

.235

23The model for the cohort of respondents aged 35 and above (Table 4) has a very high overall significance and a moderate goodness-of-fit and explanatory power.

24Residential satisfaction is positively affected by positive assessment of neighbourhood infrastructure (lighting and water) and positive assessment of panel housing estate. It is negatively affected by positive assessment of road infrastructure in the city and family size.

25Assessment of public transport, household income, presence of children aged below 18 in the household, life mobility, commuting habits, public transport, car and bicycle use, type of neighbourhood, gender and education are non-significant factors.

Table 4. Linear regression: residential satisfaction. Respondents aged 35-74.

Independent variable

Standardized coefficient (Beta)

Scale: quality of lighting

.211***

Scale: quality of water infrastructure

.135***

Scale: quality of public transport

-.046

Scale: quality of roads

-.211***

Family size

-.132**

Household income

-.077

Children under 18: yes

-.017

Life mobility:yes

-.054

Everyday commuting:yes

.052

Frequency of public transport use

.054

Frequency of car use

.038

Frequency of bicycle use

.027

Type of housing: flat

-.040

Type of neighbourhood: panel housing estate

-.001

Attitude towards dwelling

.077*

Gender: female

.031

Education level

.053

Constant

5.484***

Sample size

1340

F(sig.)

9.325 (.000)

R-square

.257

Adjusted R-square

.230

Discussion of results

26Overall, results show that residential satisfaction among younger Riga residents is affected by everyday mobility modes, neighbourhood quality perception, family characteristics, and, to a much lesser extent, household characteristics and length of residence. The considered socio-demographic factors, and housing characteristics, have been found to be non-significant.

27Although commuting behaviour is not in itself a significant predictor, the strongest predictors in the model relate to transport use and infrastructure, showing a relevant impact of everyday mobility on residential satisfaction.

28When comparing results for younger Riga residents and elder ones, some relevant differences have been found. Among the selected categories of predictors, the most striking difference relates to the impact of mobility (transport) modes, which is found to be negligible among elder residents. Minor differences are related to household and family characteristics and length of residence (life mobility).

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Table des illustrations

Titre Figure 1. Neighbourhoods divided by urban zones in Riga.
Crédits Source: authors’ figure; Riga city council
URL http://journals.openedition.org/belgeo/docannexe/image/28347/img-1.jpg
Fichier image/jpeg, 952k
Titre Figure 2. Share of young residents (15-34 years old) by neighbourhoods of Riga in 2016.
Crédits Authors’ analysis of data derived from Central Statistics Bureau of Latvia
URL http://journals.openedition.org/belgeo/docannexe/image/28347/img-2.jpg
Fichier image/jpeg, 856k
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Jānis Krūmiņš, Guido Sechi et Māris Bērziņš, « Residential satisfaction and mobility behaviour among the young: insights from the post-Soviet city of Riga », Belgeo [En ligne], 3 | 2018, mis en ligne le 15 novembre 2018, consulté le 23 janvier 2019. URL : http://journals.openedition.org/belgeo/28347 ; DOI : 10.4000/belgeo.28347

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Auteurs

Jānis Krūmiņš

University of Latvia, kruminsjanis3@gmail.com

Guido Sechi

University of Latvia, guidosechi78@gmail.com

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Māris Bērziņš

University of Latvia, maris.berzins@lu.lv

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