SATISFIED BUT THINKING ABOUT LEAVING: THE

REASONS BEHIND RESIDENTIAL SATISFACTION AND

RESIDENTIAL ATTRACTIVENESS IN SHRINKING

PORTUGUESE CITIES

Ana Paula Barreira, Luís Catela Nunes, Maria Helena Guimarães, and Thomas Panagopoulos

Corresponding author: Ana Paula Barreira (e-mail: aprodrig@ualg.pt; voice: +351 289 800

900). Centre for Advanced Studies in Management and Economics (CEFAGE), University of

Algarve, Campus de Gambelas, Building 9, P–8005–139 Faro, Portugal.

Luís Catela Nunes (e-mail: lcnunes@novasbe.pt). Nova School of Business and Economics,

Campus de Campolide, P-1099-032 Lisbon, Portugal.

Maria Helena Guimarães (e-mail: mhguimaraes@uevora.pt). Landscape Dynamics and Social

Processes Group of Institute of Mediterranean Agricultural and Environmental Sciences

(ICAAM), University of Évora, Núcleo da Mitra, Edifício Principal, Apartado 94, P-7002-554

Évora, Portugal.

Thomas Panagopoulos (e-mail: tpanago@ualg.pt). Research Centre for Spatial and

Organizational Dynamics (CIEO), Universidade do Algarve, Campus de Gambelas, Building 9,

P–8005–139 Faro, Portugal.

Acknowledgements

This work was funded by the European Regional Development Fund through the Operational

Programme for Competitiveness Factors and by national funding from the Foundation for

Science and Technology under project EXPL/ATP-EUR/0464/2013 entitled ‘Policy guidelines

for regeneration in shrinking cities’.

Abstract

Creating liveable cities is a policy priority, especially for cities that are experiencing population loss. A decline in the number of inhabitants is commonly associated with low levels of residential satisfaction. However, such a supposition does not often find empirical support in shrinking cities. In the present study, we identify variables that influence the level of residential satisfaction, as well as those influencing residential attraction (captured by the intention of current residents to leave their city in the near future). The study is based on a face-to-face questionnaire administered to 701 residents in four shrinking Portuguese cities. As expected, lower levels of residential satisfaction lead to an increased intention to leave the city. The results also show that the variables explaining residential satisfaction mostly differ from those explaining residential attractiveness. The specific characteristics of each city influence citizens’ assessment of residential satisfaction, but the variables impacting residential attractiveness are universal.

Keywords: shrinking cities; residential satisfaction; residential attractiveness; intention to move

out; Portuguese cities

Word count: 8833

1

1. IntroductionUntil recently, the dominant view of researchers, planners, and politicians was that urban success

required urban growth because growth was a guarantee of individuals’ well-being and standard

of living (International Organization for Migration [IOM], 2011). However, contrary to some

predictions, empirical studies have shown that residents in shrinking cities (i.e., those undergoing

population decline) experience satisfaction from living in such cities (Delken, 2008; Hollander,

2011). The attachment of residents to their city, along with improvements in the quality of life

resulting from a city becoming smaller (Pallagst, Schwarz, Popper & Hollander, 2009), may

explain their high levels of satisfaction with their city. However, and despite evidence for

residential satisfaction, certain American and German shrinking cities are continuing to lose

inhabitants (Wiechmann & Pallagst, 2012). The observed decline emphasizes the need to identify

the characteristics of such cities that can contribute to residential attractiveness, that is, the

characteristics that counter or reinforce inhabitants’ intention to leave. However, studies that

have investigated how the attributes of cities influence both residents’ satisfaction and their

assessment of cities’ attractiveness are scarce, with the work of McCrea, Shyy, and Stimson

(2014) being an exception. Identifying the attributes that explain both residential satisfaction and

the attractiveness of the place where individuals live is crucial for informing policies and for

defining planning strategies aimed at achieving sustainable development.

Research into the characteristics and dynamics of shrinking cities has captured the attention of

scholars as the phenomenon spreads in Europe. Only very recently has urban population decline

begun to be analysed in Portugal (Panagopoulos & Barreira, 2012; Sousa, 2010), but the number

of publications is increasing (e.g., Alves, Barreira, Guimarães & Panagopoulos, 2016;

Guimarães, Barreira & Panagopoulos, 2015; Guimarães, Nunes, Barreira & Panagopoulos, 2016;

Panagopoulos, Guimarães & Barreira, 2015; Sousa and Pinho, 2015). However, little is known

about the main attributes that either help to secure individuals in a place or force them to leave

(residential attractiveness), or about the level of residential satisfaction that individuals obtain

from cities whose populations are declining. Through analysing data obtained from a face-to-

face questionnaire survey conducted in four shrinking Portuguese cities, this study aims to gain a

deeper understanding of the above issues by identifying the characteristics that influence

inhabitants’ level of satisfaction with their city of residence and also the factors that influence

their intention to leave in the near future.

2

2. Literature Review

2.1. Inhabitants’ Assessment of Residential Satisfaction

The ways in which individuals in a society obtain satisfaction is a topic of interest in several

research areas, including economics, sociology, and psychology (Lambiri, Biagi & Royuela,

2007; Sirgy et al., 2006). Satisfaction can be related to different aspects of life such as health,

familial relationships, work, income, and standard of living (e.g., Lee, 2008; Sirgy, Gao &

Young, 2008). One aspect that impacts an individual’s satisfaction is the satisfaction obtained

from the place of residence, which implies a confrontation between the individual’s

achievements in that place and his/her aspirations or needs (McCrea, Stimson & Western, 2005;

Sirgy, Rahtz, Cicic & Underwood, 2000). Residential satisfaction is a multi-dimensional

construct (Francescato, 2002) that involves assessment of the spatial, human, and functional

aspects of a place (Amérigo, 2002), and is defined as the level of pleasure or gratification that

individuals obtain from the place in which they live (Bonaiuto, Fornara & Bonnes, 2003).

The literature describes residential satisfaction as being influenced by inhabitants’

sociodemographic characteristics as well as by the social and physical attributes of the place

where they live. Residents’ characteristics such as age (Bonaiuto, Aiello, Perugini, Bonnes &

Ercolani, 1999; Lu, 2009), income (Dekker, de Vos, Musterd & van Kempen, 2011; Grinstein-

Weiss et al., 2011), and education (Lee, 2008; Lu, 2009) are commonly identified as positively

influencing residential satisfaction (i.e., older, wealthier, and more educated individuals are more

satisfied with their place of residence). However, some investigations have failed to find a

relationship between income and residential satisfaction (e.g. Mellander, Florida & Stolarick,

2011). Moreover, some studies have reported a negative relationship between education and

residential satisfaction, as individuals with higher levels of education may have more difficulty

in fulfilling their expectations in particular places (Filkins, Allen & Cordes, 2000; Hur &

Morrow-Jones, 2008). Gender also makes a difference, with women stating that they are more

satisfied with their place of residence than are men (Kamalipour, Yeganeh & Alalhesabi, 2012;

Perez, Fernandez-Mayoralas, Rivera & Abuin, 2001).

Typically, the following have also been shown to positively influence inhabitants’ assessment

of residential satisfaction: a longer duration of residence (Amérigo & Aragonés, 1997; Bonaiuto

et al., 1999); being a homeowner (Dekker et al., 2011; Perez et al., 2001); being surrounded by a

3

pleasant and aesthetic urban environment (Florida, Mellander & Stolarick, 2011; Parkes, Kearns

& Atkinson, 2002); and being part of a social network (Bonaiuto et al., 1999; Parkes et al.,

2002). However, a longer period of residence has been identified by some authors (e.g. Dekker et

al., 2011; Lu, 1999) as affecting residential satisfaction negatively, because a longer contact with

the environment may heighten inhabitants’ perception of the negative aspects of the locality.

Homeownership has also been found by some researchers as having limited or no influence on

citizens’ assessment of residential satisfaction (e.g. Florida et al., 2011; Parkes et al., 2002).

However, residential satisfaction is positively related to the attributes of people’s homes (Azimi

& Esmaeilzadeh, 2017; Perez et al., 2001) and to inhabitants’ level of civic engagement

(Manturuk, Lindblad & Quercia, 2010; Perez et al., 2001).

The existence of certain features in the place where individuals live can increase or decrease

their level of residential satisfaction and can be combined into pull or push factors, respectively,

generally through a statistical technique such as factor analysis. The most commonly reported

features associated with residential satisfaction are the absence of noise, the existence of green

spaces, and the proximity to certain facilities such as commercial areas and schools as well as to

employment and recreational activities (Andersen, 2008; Cao & Wang, 2016; Dekker et al.,

2011; McCrea et al., 2005; Neal & Neal, 2012; Parkes et al., 2002), and such features can be

aggregated into pull factors encapsulating living conditions and accessibility to facilities. In

contrast, features such as the need to maintain homes, a lack of safety, or poor access to work

(Cao & Wang, 2016; McCrea et al., 2005; Woo & Morrow-Jones, 2011) constitute push factors,

which decrease the level of residential satisfaction.

2.2. Inhabitants’ Assessment of Residential Attractiveness

Residential attractiveness is a new concept and still requires a consensual conceptualisation

(Miot, 2015; Niedomysl, 2010). However, in general terms, residential attractiveness can be

defined as place-based preconditions that make prospective inhabitants desire to move there or

that make those already living there desire not to move to another location (Fertner, Groth,

Herslund & Carstensen, 2015). Residential attractiveness can derive from public strategies

aiming to restore the residential functions of a place, thus promoting both the attachment and

attraction of populations (Miot, 2015). Some authors have argued that differences in the

4

available features explain differences between urban areas in their capacity to be attractive to

people (Buch, Hamann, Niebuhr & Rossen, 2014; Mellander, Florida & Stolarick, 2011).

Places are viewed as attractive if the available features fulfil the needs, demands, and

preferences of inhabitants (van den Berg, van de Meer & Oligaar, 2006; Niedomysl, 2010). Such

features can be combined through factor analysis into pull factors. In contrast, the absence of

certain features such as educational institutions and hospitals (van den Berg et al., 2006; Braun,

2008) decrease the attractiveness of a place and can be regarded as push factors. The European

Commission (2006) considers that an attractive place has to provide accessibility and mobility,

public services and institutions, an effective economic structure, and an appealing natural and

physical environment, as well as stimulating technological, cultural, and touristic environments.

An increase in the attractiveness of a place tends to be related to job opportunities (van den

Berg et al., 2006; Braun, 2008). A causal relationship between employment and population

movements is found in the literature (IOM, 2011; Seo, 2002). Localities that are more

economically active generate more job opportunities, typically attracting the younger generations

(Lutz, 2001; Zimmermann, 2005) and the more highly skilled workers (Buch et al., 2014; Krabel

& Flöther, 2012). Jointly with economic attractors, housing affordability has also been revealed

as a factor that positively influences migration flows (van den Berg et al. 2006; Seo, 2002).

The attractiveness of a place can also result from place attachment, which derives from the

affective bonds developed with the place of residence (Hidalgo & Hernández, 2001; Sampson &

Goodrich, 2009). Place attachment translates into feelings of pride and identity about the place

(Hernández, Martín, Ruiz & Hidalgo, 2010), into trust in the community (Raymond, Brown &

Weber, 2010), and into a sense of stability and security (Billig, 2006), which reduce the incentive

for residents to move out (Andersen, 2008; Hidalgo & Hernández, 2001). Factors that positively

influence place attachment are the length of residence (Bonaiuto et al., 1999; Lewicka, 2011),

age (Hidalgo & Hernández, 2001; Kamalipour et al., 2012), and homeownership and education

(Abellán & Rojo, 1997; Hidalgo & Hernández, 2001). Women develop greater levels of place

attachment feelings compared with men (Kamalipour et al., 2012).

5

2.3. Residential Satisfaction, Residential Attractiveness, and Intention to Stay or To Move Out

Residential satisfaction has an ambiguous relevance in the literature in explaining individuals’

decisions to stay in or move out from a certain location. Low residential satisfaction is

commonly identified as a predictor of out-migration (Andersen, 2008; Kearns & Parkes, 2003).

However, empirical evidence (e.g. Fang, 2006; Livingston, Bailey & Kearns, 2010) also shows

that even when individuals are dissatisfied with the place in which they live, this does not often

extend to an actual move. Moreover, and despite reports of residential satisfaction, when

individuals identify places that they feel are more attractive, such individuals are willing to move

there. Ogu (2002) has emphasized the need to distinguish between ‘real’ problems and uniform

reports of residential satisfaction, as urban areas can possess unpleasant characteristics, which

are not captured only through the assessment of residential satisfaction. This means that

assessing the attractiveness of a place is at least as important as assessing residential satisfaction

in explaining individuals’ decisions to stay or leave.

By examining four different urban environments, including disadvantaged urban areas,

McCrea et al. (2014) found using survey data that inhabitants in those environments reported

similar levels of residential satisfaction, but their evaluations of the attributes making those areas

attractive places differed between environments. In this sense, the measurement of a city’s

attractiveness, rather than the measurement of residential satisfaction, might better characterize

the subjective quality of life. The work of McCrea et al. suggested that the existence of certain

features that ensure residential satisfaction may not be sufficient to prevent inhabitants from

moving out.

2.4. The Context of Shrinking Cities

The issue of shrinking environments has been steadily gaining interest from researchers as the

phenomenon of declining populations spreads to a larger number of countries, regions, and cities

(Khavarian-Garmsir, Pourahmad, Hataminejad & Farhoudi, 2017; Oswalt & Rieniets, 2006;

2007; Turok & Mykhnenko, 2007). Economic transformation and suburbanization processes are

the most cited reasons for the reduction in the number of inhabitants in cities (Haase, Bernt,

Grobmann, Mykhnenko & Rink, 2013). The existence of satellite cities and harsh climatic

conditions are also identified as factors in the Portuguese case (see Guimarães et al., 2015). The

6

departure of residents from cities generates housing degradation and brownfields (Hollander &

Németh, 2011; Wiechmann & Pallagst, 2012), which create conditions that favour disorder and a

lack of safety (Dekker et al., 2011; Kleinhans & Bolt, 2013) and a consequent reduction in the

appeal of such cities. In contrast, shrinking cities also provide attracting attributes compared with

growing cities, such as the affordability of housing, the presence of natural amenities, an absence

of traffic congestion, and less pollution (Hollander, 2011; Pallagst et al., 2009).

Given the above, in some areas showing population decline, and in which reports of high

levels of residential dissatisfaction may be expected, individuals reveal that they are in fact

satisfied with their place of residence (Delken, 2008; Hollander, 2011). McCrea et al. (2005)

examined urban domains such as neighbourhoods and metropolitan regions and noted that

population size was not particularly important for the determination of residential satisfaction.

Accordingly, a willingness to change city of residence would not be expected in shrinking cities

because inhabitants report satisfaction with their city; however, in apparent contradiction, data

show decreasing numbers of inhabitants in such cities. This may be due to the fact that as the

number of inhabitants decreases, actual or perceived changes occur in the residential context that

may trigger inhabitants’ wishes to move to another location. The changed or new characteristics

of the place may no longer meet their preferences and needs (Bonaiuto et al., 1999; 2003). As

such, in a context of population decline, although assessments of residential satisfaction may

provide some insights, it is just as critical to understand which features make the city sufficiently

attractive to explain inhabitants’ desire to stay.

In shrinking cities, where the exodus of people may lead to the remaining inhabitants feeling a

psychological sense of low worth, it is crucial to value the attractive features of the city that

might balance negative characteristics, even in cases where reports of residential satisfaction are

found. In shrinking contexts, two strategies can be chosen to deal with it: to accept population

decline but ensure an acceptable level of quality of life for the residents who stay, or to take

actions aimed at reversing the population loss (Haase, Hospers, Pekelsma & Rink, 2012;

Hospers, 2014). Under the first strategy, residential satisfaction seems more important, but under

the second strategy, residential attractiveness assumes critical relevance.

7

3. Case Study: The Shrinking Cities of PortugalPortugal has 158 cities, which in 2011 contained 44% of the national resident population. When

records from 1991 to 2011 are compared, 31 cities showed population loss, with 8 of them losing

more than 10% of their inhabitants and a further 6 showing a persistent decline, corresponding to

an overall reduction in the number of inhabitants in these 31 cities of 13.2% between 1991 and

2011 (census data – National Statistics [INE]). Several overlapping causes (see details in

Guimarães et al. 2015) have contributed to the reduction in the number of inhabitants in these

cities. In conjunction with negative rates of natural population change, cases of city shrinkage

due to suburbanization, economic transformation, climatic drivers, or the satellite effect have

been identified. Because the different causes of shrinkage may influence the assessments of

residential satisfaction and of a city’s residential attractiveness, four case-study cities were

selected, namely Oporto, Barreiro, Moura, and Peso da Régua, as cases typifying

suburbanization, economic transformation, climatic drivers, and the satellite effect, respectively.

For a detailed description of the population growth in shrinking cities in Portugal see Alves et al.

(2016).

Oporto, the second most populous city in the country, is located in northwestern Portugal and

was the city that registered the greatest relative population loss (21.5%) between 1991 and 2011

(from 302,500 to 237,600 inhabitants; INE). While Oporto was losing inhabitants, the four

neighbouring municipalities: Gondomar, Maia, Matosinhos and Vila Nova de Gaia gained in the

same period (1991-2011) 133,800 inhabitants (+20.6%), which explains that the main cause of

population decline has been suburbanization. Oporto has consistently gained inhabitants until

1981, moment in which reached its peak, having double the number of inhabitants since the

beginning of the century as the result of the increasing movement of citizens from rural into

urban areas (Alves et al. 2016). Since 1981, the city lost ~ 90,000 inhabitants, putting population

in 2011 at the level registered in 1930.

Barreiro, located on the southern bank of the Tejo River and facing Lisbon (the capital city),

showed the second-largest population loss in relative terms between 1991 and 2011 (21.2%,

from 47,900, its pick, to 37,700 inhabitants; INE). The highest growth of the city occurred

between 1960 and 1981, in which the population almost doubled (an increase of ~ 23,000

inhabitants), due the rapid industrialization of the country occurred during these period,

becoming Barreiro the most important city for the chemical industry (Alves et al. 2016). The

8

growth of population was explained by the job opportunities generated by the industry with

higher wages than agricultural and phishing activities. However, such population growth, built

on a mono-activity, led lately to its decline due the lower diversification of the economic basis.

Therefore, the main cause of the population decline was the abrupt closure of factories, which

left behind brownfields and abandoned facilities.

Moura has slowly grown between 1900 and 1930 (average growth of 8.3% per decade),

accelerating its growth until 1960, when the city had its peak with 12,130 inhabitants (an average

growth of 17.6% per decade). Since then the city has been losing inhabitants with a recovery of

7% between 1991 and 2001, returning to decline afterwards (Alves et al. 2016). Accordingly,

Moura exhibited recent city shrinkage, with a decrease in the number of inhabitants of 9% (from

9200 to 8400 inhabitants; INE) between 2001 and 2011. Moura, which is located in the country’s

interior, in the Alentejo region, still relies today on agricultural activities that are less appealing

to the younger as better employment opportunities in the tertiary sector are available in the coast.

Additionally, the harsh environmental conditions in Moura compared with the coast, namely the

maximum average temperature of 32.2ºC in August and the minimum average temperatures of

5.7ºC in January, does not help to retain inhabitants. Further, Moura is subject to intense heat

weaves (e.g., 44.8ºC at 8 of August of 2016).

Peso da Régua, located in the Douro region in northern-central Portugal, showed a persistent,

although small, population decline between 1991 and 2011 (from 10,300 to 10,000 inhabitants;

INE). The nearest town (25 km away) is Vila Real, whose population increased by 33% between

1991 and 2011 (INE). Peso da Régua does not offer higher-education opportunities, whereas

Vila Real does and therefore attracts many young people. Therefore, Peso da Régua is

considered to be a satellite city of Vila Real. The satellite effect explains its growth until 1981

when reached 10,600 inhabitants, exhausting at that time its potential for attracting inhabitants.

The purchasing power in Peso da Régua of 79.2, in 2011, below the national average of 100,

whereas in Vila Real the value was 101.5 (INE), helps explain the decline in inhabitants. The

primary sector is the main economic activity in Peso da Régua which might contribute to the

decrease of the city’s appeal.

9

4. Aims and Method

4.1. Research Goals

Although recent empirical studies have demonstrated that inhabitants of shrinking cities report

high levels of residential satisfaction (Delken, 2008; Hollander, 2011), population decline often

tends to become aggravated in such cities. The results of those studies highlight the need to

jointly assess residential satisfaction and the attractiveness of the city as a place in which to live.

The main goal of the present work is to provide insights into the influences on residential

satisfaction and residential attractiveness in the context of shrinking Portuguese cities.

Understanding the drivers of satisfaction and its influence on population movement can be of

great utility for policymakers, who are frequently concerned with the impacts of population

decline. Therefore, we also try to understand how residential satisfaction influences the

willingness to move away from a shrinking city in the near future as well to identify the factors

that influence inhabitants’ intention to leave those cities. Moreover, the paper examines whether

the demographic, socio-economic, and civic engagement characteristics of inhabitants affect

their assessments of the level of residential satisfaction and of their willingness to leave the city

in the near future.

Thus, this work poses the following research questions:

1) Which pull/push factors of shrinking cities influence inhabitants’ assessments of

residential satisfaction and residential attractiveness?

2) Are inhabitants’ assessments of residential satisfaction and residential attractiveness

affected by their demographic, socio-economic, and civic engagement characteristics?

3) Is there a relationship between inhabitants’ residential satisfaction and their intention

to leave a shrinking city?

4.2. Materials, Sample, and Procedure

Data to answer the research questions posed were obtained by conducting a survey with a

questionnaire entitled ‘How to deal with population loss in your city,’ which was conducted

face-to-face in the four selected shrinking cities during July 2014. A total of 701 completed

questionnaires were obtained from individuals aged 18 years or over. A random stratified

sampling scheme was used, which ensured a maximum margin of error of 7.45% for the 95%

confidence interval on the population proportion. The sampling scheme was stratified in two

10

steps. First, a stratification was made according to the number of inhabitants in each city and

their distribution in the parishes that comprise each city, namely, Oporto (15 parishes), Barreiro

(3), Moura (3), and Peso da Régua (2), according to data from the 2011 national census. Second,

a stratification was made according to the typology of households characterizing each city1, again

using 2011 national census data. The survey was applied to the following types of households: 1)

one person (15–64 years old) with or without other(s) (<15 years old); 2) one person (>64 years

old); 3) two persons (both 15–64 years old) with or without other(s) (<15 years old); 4) two

persons in which at least one is >64 years old; and 5) three persons (>15 years old) with or

without other(s) (<15 years old).

The questionnaire was composed of three parts. The first part identified the demographic

characteristics of each respondent, including questions regarding age, gender, education level,

and household composition. In this part, respondents were also asked to assess their degree of

residential satisfaction as scored on a five-point scale from 1 (very dissatisfied) to 5 (very

satisfied). The first part also included three other questions regarding the respondent’s perception

of the evolution of the city’s population (declining, stable, or increasing), the respondent’s

intention of leaving the city of residence within one year (answered with ‘1 – yes’ or ‘0 – no’),

and the respondent’s willingness to be involved in activities to deal with the shrinkage

phenomenon. The binary variable ‘intention of living the city of residence within one year’ was

used as a measure of the residential attractiveness of the studied shrinking cities.

The second part of the questionnaire listed the main attributes to be assessed by each

respondent concerning their relevance to the attractiveness of the city. The selection of the listed

attributes was based on the literature and on the specific characteristics of the studied cities. This

part was composed of 24 attributes that may attract inhabitants (pull attributes) and 24 attributes

that may repel inhabitants (push attributes). Respondents were asked to assess the importance of

each attribute according to the following five-point Likert scale: 5 – crucial, 4 – very important,

3 – moderately important, 2 – weakly important, and 1 – irrelevant.

The third part asked about the socio-economic characteristics of the respondent, namely,

homeownership, type and era of construction of his/her house, years of residence in the city,

income, and the number of employed family members.

1 Details can be found in Panagopoulos et al. (2015).

11

Table 1 presents descriptive statistics regarding the responses to the first and third parts of the

questionnaire. The distribution of the sample matches the demographic characteristics of each

city as the sampling method took into account the distribution of households by parish and by the

typology of households living in each city. For the purpose of comparing the sample with the

population characteristics of each city, Table 1 also presents the available 2011 census data for

the four studied cities for age, gender, educational level, household size, household income, the

number of people employed in the family, homeownership, and era of construction of the house.

(INSERT TABLE 1 HERE)

The survey showed that individuals’ levels of residential satisfaction were high in shrinking

cities (Figure 1), thus confirming the findings of previous studies (Delken, 2008; McCrea et al.,

2014). For the full sample (all cities), 78% of the respondents were either satisfied or very

satisfied with their city of residence, thus supporting the proposition that shrinkage is not

detrimental to residential satisfaction.

(INSERT FIG. 1 HERE)

Almost all of the respondents of Oporto, the city with the greatest population loss in relative

terms, reported that they were satisfied living there, with 89% expressing satisfaction (scores of 4

or 5). This finding is reinforced by the fact that only a small proportion of the city’s inhabitants

(3%) revealed an intention to leave. Residents of Peso da Régua were also found to be satisfied

with their city, with 80% scoring 4 or 5 for residential satisfaction, and to have a moderate

intention of leaving the city. In contrast, Barreiro, the city with the second-largest decline in

population in relative terms, showed the lowest level of residential satisfaction of the four cities,

with only 59% of respondents assigning a score of 4 or 5. The intrinsic characteristics of Barreiro

as an old industrial city might explain the below-average result. The surveyed inhabitants of this

city were revealed to have the highest intention of leaving (16%) compared with the surveyed

inhabitants of the other cities. The inhabitants of Moura indicated high levels of residential

satisfaction: 89% reported scores of 4 or 5, but they also had a high intention of leaving the city

(10%).

Table 2 presents the 24 pull attributes and 24 push attributes contained in the second part of

the questionnaire. The table also presents five pull factors and four push factors, which were

derived using factor analysis, as detailed in Guimarães et al. (2016). The five pull factors and

four push factors are included in the data analysis presented in the following sections.

12

(INSERT TABLE 2 HERE)

4.3. Statistical Models

A logistic regression model was used to assess the relative influence of the respondents’

demographic and socio-economic characteristics, including residential satisfaction, on their

intention of leaving the city of residence (residential attractiveness). Defining the dichotomous

variable yi = 1 if a respondent i intends to leave the city, and yi = 0 if not, the probability that a

respondent intends to leave the city corresponds to the probability that an estimated linear

function of the respondent’s characteristics, plus a random error, exceeds an estimated threshold:

Prob (yi = 1 ) = Prob (1 x1,i +...+ k xk,i +i > c1 ) (1)

where x1,i,..., xk,i are k explanatory variables capturing the characteristics of respondent i, 1 ,..., k

are coefficients, c1 is the threshold, and the random error i is assumed to be logistically

distributed. It follows that the probability of observing yi = 1 is given by:

Prob (yi = 1 ) = F ( -c1 + 1 x1,i +...+ k xk,i ) (2)

where F(z) = 1 / (1 + e-z) is the cumulative logistic distribution.

The parameters of the model, c1, 1,..., k, are estimated by maximum likelihood. Average

marginal effects were calculated to better interpret the estimated coefficients. These effects

capture how the predicted probability of leaving the city is affected by each of the explanatory

variables (see StataCorp, 2013).

The variable ‘residential satisfaction’ was measured on a Likert scale ranging from ‘very

dissatisfied’ to ‘very satisfied’. Because there were very few responses for the two lowest levels

of satisfaction (only 1.3% answered ‘very dissatisfied’, and only 2.6% answered ‘moderately

dissatisfied’), these levels were merged with the third level ‘neither satisfied nor dissatisfied’. To

simplify notation, the levels ‘very dissatisfied’, ‘moderately dissatisfied’, and ‘neither satisfied

nor dissatisfied’ were recoded to 1, ‘moderately satisfied’ was recoded to 2, and ‘very satisfied’

was recoded to 3. An ordinal logistic regression model was used to identify the respondents’

demographic and socio-economic characteristics explaining residential satisfaction. This model

is a simple extension of the logistic regression model. The probability of observing a respondent

stating a satisfaction level j corresponds to the probability that the estimated linear function of

13

the respondent’s characteristics, plus the random error, is within the range of thresholds defined

for that level j:

Prob (yi = j ) = Prob (cj-1 <1 x1 +...+ k xk +i < cj ) (3)

where c0, c1, c2, and c3 are the thresholds, with c0 = and c3 = . In this case, the average

marginal effects capture how the predicted probability of the highest level of residential

satisfaction is affected by the explanatory variables. The explanatory variables considered were

respondent’s characteristics, including age, gender, educational level, household size, household

income, number of people employed in the family, homeownership, era of construction of the

house, type of building, years of residence in the city, perception of population change, and

willingness to participate in urban regeneration programs, as well as the five pull and four push

factors described in Table 2. We present only the final estimated models after sequentially

discarding variables that were not statistically significant at the 10% level of significance.

One key feature of our analysis is the fact that the survey data include responses from

residents in four different cities, with each city having a particular shrinkage type. Therefore, we

present the results of two variants of the regression model: one that does not control for the city

of residence (‘non-controlled model’), and one that includes a dummy variable for each city as

explanatory variables (‘controlled model’).

4. Results

4.1. Variables Influencing the Level of Residential Satisfaction

Estimation results for the ordered logistic regression model without including the ‘city’ dummy

variables are presented in Table 3. Older (compared with younger) respondents tend to be more

satisfied. Respondents with higher (compared with lower) education levels are less satisfied, as

are respondents who have lived in the city for longer (compared with shorter) durations.

Regarding the pull factors, high scores for the city’s ‘living conditions’, ‘recreational and

environmental amenities’, and ‘social ties’, all imply high satisfaction levels. In contrast, low

satisfaction levels are reported when high scores are given to push factors related to the city’s

‘shrinking atmosphere’, ‘surroundings and visual attributes’, and ‘working conditions’.

(INSERT TABLE 3 HERE)

14

Estimation results for the model in which the ‘city’ dummy variables were included as

explanatory variables are reported in Table 4. Only the ‘city’ dummy variable for Barreiro is

statistically significant, with its negative sign indicating lower residential satisfaction levels in

this city even after controlling for all the other respondents’ characteristics. The impacts of age

and education level in this controlled model are similar to those in the non-controlled model. The

effect of years of residence is no longer significant, but this variable already had a weak

significance level in the non-controlled model. The major difference between the two models is

the influence of the pull and push factors. In the controlled model, the only significant pull factor

is related to ‘accessibility’ conditions, and it has a positive impact on the level of residential

satisfaction. The pull factors reported as significant in the non-controlled model (i.e., ‘living

conditions’, ‘recreational and environmental amenities’, and ‘social ties’) lose their significance

in the controlled model. For the push factors, the impact of the ‘surroundings and visual

attributes’ push factor is no longer significant, while the remaining factors maintain their

negative impact on satisfaction. We conclude that the ‘surroundings and visual attributes’ push

factor is essentially related to the specificities of the cities. Both the ‘shrinking atmosphere’ and

the ‘working conditions’ push factors negatively affect satisfaction levels, even after controlling

for city-specific characteristics.

(INSERT TABLE 4 HERE)

4.2. Variables Influencing Residential Attractiveness

Table 5 presents the estimated logistic regression model explaining the intention to leave the city

of residence in the near future as a function of the respondents’ characteristics and also including

dummy variables for each city. In this case, the characteristics that are specific to each shrinking

city appear to play no role in explaining the intention to leave after controlling for respondents’

characteristics. The results for the non-controlled model are practically the same and have been

omitted to save space.

(INSERT TABLE 5 HERE)

As expected, the more satisfied respondents report a lower probability of leaving the city in

the near future. However, even after controlling for satisfaction, there are other factors that

influence the intention to leave shrinking cities. As expected, older respondents are less likely to

leave the city. Those more willing to participate in urban regeneration programs have a higher

15

intention of moving out, although the statistical significance of this variable is the weakest (p-

value = 0.064). Employment also plays a role in the intention to leave: the higher the number of

employed people in the household, the lower the likelihood that the respondent will leave the city

in the near future. Similarly, respondents assigning higher scores to the ‘live and work’ pull

factor also have a lower intention of leaving the city. In contrast, respondents assigning higher

scores to the push factors ‘lack of services’ and ‘shrinking atmosphere’ have a higher intention

of moving out.

5. DiscussionThe empirical findings support the literature identifying age as a predictor of residential

satisfaction (Bonaiuto et al., 1999; Lu, 2009), with older inhabitants of the shrinking cities

studied here reporting higher levels of satisfaction compared with younger residents. Moreover,

age also positively influences the desire to remain in those cities, which is related to the higher

degree of place attachment (Hidalgo & Hernández, 2001; Kamalipour et al., 2012). However,

education and length of residence both negatively influence residential satisfaction, which is in

accordance with the findings of Hur and Morrow-Jones (2008) and Dekker et al. (2011),

respectively. Longer durations of living in a shrinking city increase inhabitants’ awareness of

living in a city that is declining in population, which in turn decreases their level of residential

satisfaction. Further, since the level of residential satisfaction decreases with increasing

education level, shrinking cities may no longer fulfil the needs of the more educated inhabitants.

However, neither education level nor the length of residence plays any role in the willingness of

inhabitants to leave those cities, contradicting the findings of Hidalgo and Hernández (2001) and

Lewicka (2011). This result may be because even though some inhabitants may feel dissatisfied

with the place in which they live, this may not eventuate in an actual intention to move (Fang,

2006; Livingston et al., 2010).

Neither income nor gender appears to influence residential satisfaction or the desire to leave

the surveyed shrinking cities. The irrelevance of income in explaining residential satisfaction

supports the finding of Mellander et al. (2011), while the absence of gender significance

contradicts the finding of Kamalipour et al. (2012). Similarly, there are no gender differences in

explaining the residential attractiveness of the studied cities, in contrast to the study of

16

Kamalipour et al. (2012), which suggested that women (compared with men) are more attached

to place and are therefore less prone to changing residential location.

Contrary to previous studies, homeownership and the characteristics of homes do not explain

residential satisfaction (Azimi & Esmaeilzadeh, 2017; Dekker et al., 2011) or residential

attractiveness (Abellán & Rojo, 1997; Seo, 2002). Our results also contradict the finding of

Manturuk et al. (2010) that inhabitants’ civic engagement increases residential satisfaction.

However, the ‘willingness of inhabitants to participate in urban regeneration programs’

negatively influences the desire to remain in the studied shrinking cities, thus contradicting the

predictions that those more actively involved in the community feel more pride about the city

and have greater feelings of trust and security (Billig, 2006; Hernández et al., 2010; Raymond et

al., 2010). This result is of concern because retaining the more engaged inhabitants in shrinking

cities is crucial for finding ways to deal with the population loss.

The ‘living conditions’ pull factor, which comprises attributes such as the cities’ safety as

well as their appearance, the affordability of houses, and access to certain facilities like good

schools and transportation, is the most influential factor explaining residential satisfaction. The

relevance of such attributes is in accordance with previous studies (e.g. Neal & Neal, 2012;

Parkes et al., 2002; Woo & Morrow-Jones, 2011). This result shows that shrinking cities provide

residential satisfaction so long as the cities do not exhibit social and physical degradation that

may undermine living conditions (Hollander, 2011; Pallagst et al., 2009). The ‘recreational and

environmental amenities’ pull factor, which comprises the existence of spaces for open-air sports

as well as good environmental quality attributes, influences the assessment of residential

satisfaction in a positive manner, as found by previous studies (Cao & Wang 2016; Dekker et al.,

2011). The ‘social ties’ pull factor also has a positive effect on residential satisfaction, supporting

earlier investigations (Bonaiuto et al., 1999; Parkes et al., 2002). However, when the model is

controlled for city of residence, the relevance of these pull factors disappears, and they are

replaced by the ‘accessibility’ pull factor. This result reveals that these pull factors, namely,

‘living conditions’, ‘recreational and environmental amenities’, and ‘social ties’, seem to be

intrinsically related to the city of residence, given that their effect is lost in the controlled model.

The ‘accessibility’ pull factor includes the proximity to leisure and green areas and emerges as

the main influential factor for residential satisfaction in the controlled model. The proximity of

17

areas that are aesthetically appealing has been previously mentioned by Florida et al. (2011) and

Parkes et al. (2002) as positively influencing residential satisfaction.

However, when the analysis considers the intention of leaving shrinking cities, none of the

above pull factors is relevant; instead, ‘live and work’ is the only pull factor influencing

residential attractiveness. Given that the number of employed family members is another

variable that also explains residential attractiveness, the results confirm that economic activity is

central to capturing or retaining inhabitants (van den Berg et al., 2006; Braun, 2008). Thus, to

reduce inhabitants’ intention of leaving, shrinking cities must rely on the maintenance of jobs;

otherwise, they will continue to lose inhabitants, despite being reported as good places in which

to live (high residential satisfaction).

The ‘shrinking atmosphere’ and ‘working conditions’ push factors impact negatively on

residential satisfaction; however, only the first of these factors influences the intention to leave

the cities. The perception that cities are losing population impels the current inhabitants to find

other places to live, which means that those cities are no longer entirely capable of fulfilling the

needs and desires of their residents (van den Berg et al., 2006; Niedomysl, 2010). The

‘surroundings and visual attributes’ push factor also reduces the level of residential satisfaction

in the non-controlled model, but this effect is not significant in the controlled model. The ‘lack of

services’ push factor is not a determinant of residential satisfaction, contradicting previous

findings (e.g. Neal & Neal, 2012; Parkes et al., 2002), but this factor does increase the desire of

inhabitants of shrinking cities to move out, as cities with poor services are not regarded as

appealing places in which to live. Both van den Berg et al. (2006) and European Commission

(2006) have pointed out that the absence or low level of certain services tends to push current

inhabitants out. High levels of residential satisfaction reduce the intention to leave the studied

cities, supporting the earlier studies of Kearns and Parkes (2003) and Andersen (2008).

6. ConclusionsShrinking cities represent a particular context, one that is generally associated with less

appealing living conditions and lower levels of residential satisfaction compared with other

urban contexts. When inhabitants of shrinking cities report high levels of residential satisfaction,

this does not mean that they are not confronted with residential issues that may impel them to

18

move out of the cities. As such, assessing residential satisfaction may be different from

measuring the attractive features of a city as a place to live.

In the presented case study of four shrinking cities in Portugal, residents indicated overall

satisfaction with their respective cities. The empirical findings presented show that with the

exception of age, no common demographic or socio-economic characteristics explain residential

satisfaction and residential attractiveness.

The pull factors that determine residential satisfaction are ‘living conditions’, ‘recreational

and environmental amenities’, and ‘social ties’ in the model uncontrolled for city of residence, or

‘accessibility’ when city of residence is included as an explanatory variable. However, ‘live and

work’ is the only pull factor that explains the intention to leave a shrinking city (i.e., residential

attractiveness). The push factors that explain residential satisfaction are ‘working conditions’ and

‘surroundings and visual attributes’, whereas the ‘lack of services’ explains the intention to leave

shrinking cities. The exception is the push factor ‘shrinking atmosphere’, which has a negative

effect on both residential satisfaction and residential attractiveness.

With regard to the intention to leave the city, economic aspects emerged as the most

important of the cities’ characteristics that may impel individuals to move out, with an emphasis

on the availability of services and jobs. Therefore, a major conclusion of this study is that city-

specific characteristics influence the assessment of residential satisfaction whereas the factors

that influence the intention to leave are common to all the cities. These findings support the

proposition that residential satisfaction and residential attractiveness are predominantly different

and reinforce the argument of McCrea et al. (2014) that there is a need to measure what is most

important. If shrinkage is a condition accepted by the local government, then attributes

associated with recreational and environmental amenities as well as with accessibility factors that

ensure residential satisfaction should be prioritized. One possible strategy is to create conditions

that could support an economy oriented towards providing health, recreational, and care services

for the elderly, the so-called ‘grey economy’. In contrast, if the strategy taken by decision-

makers is aimed at stabilizing or even reversing shrinkage, then the focus should be placed on

those attributes that improve the city’s attractiveness, which are related to increases in the

provision of services and job opportunities.

Regardless of the strategy adopted, because residential satisfaction has a positive effect on

residential attractiveness, governments cannot neglect the former. Accordingly, shrinking cities

19

must work to reduce the perception that the cities are becoming smaller, given that a perception

of a ‘shrinking atmosphere’ negatively affects both residential satisfaction and attractiveness,

thus requiring a planning approach that strengthens the resilience of such cities.

ReferencesAbellán, A., & Rojo, F. (1997). Migración y movilidad residencial de las personas de edad en

Madrid. Anales de Geografía de la Universidad Complutense, 17, 175–193.

Alves, D., Barreira, A. P., Guimarães, M. H., & Panagopoulos, T. (2016). Historical trajectories

of currently shrinking Portuguese cities: A typology of urban shrinkage. Cities, 52, 20−29.

Amérigo, M. (2002). A psychological approach to the study of residential satisfaction. In J. I.

Aragonés, G. Francescato, & T. Gärling (Eds.), Residential environments: Choice,

satisfaction and behavior (pp. 81–100). Westport: Bergin and Garvey.

Amérigo, M., & Aragonés, J. I. (1997). A theoretical and methodological approach to the study

of residential satisfaction. Journal of Environmental Psychology, 17(1), 47–57.

Andersen, H. S. (2008). Why do residents want to leave deprived neighbourhoods? The

importance of residents’ subjective evaluations of their neighbourhood and its reputation.

Journal of Housing and the Built Environment, 23(2), 79–101.

Azimi, N. & Esmaeilzadeh, Y. (2017). Assessing the relationship between house types and

residential satisfaction in Tabriz, Iran. International Journal of Urban Sciences, 21(2),

185‒203.

van den Berg, L., van de Meer, J., & Oligaar, A. (2006). The attractive city: Catalyst of

Sustainable Urban Development. XVI Congreso de Estudios Vascos: Garapen Iraunkorra-

IT. Donostia: Eusko Ikaskuntza, 485−491.

Billig, M. (2006). Is my home my castle? Place attachment, risk perception, and religious faith.

Environment & Behavior, 38(2), 248−265.

Bonaiuto, M., Aiello, A., Perugini, M., Bonnes, M., & Ercolani, A. P. (1999). Multidimensional

perception of residential environment quality and neighborhood attachment in the urban

environment. Journal of Environmental Psychology, 19(4), 331‒352.

20

Bonaiuto, M., Fornara, F., & Bonnes, M. (2003). Indexes of perceived residential environment

quality and neighbourhood attachment in urban environments: a confirmation study on the

city of Rome. Landscape and Urban Planning, 65(1–2), 41–52.

Braun, E. (2008). City Marketing: Towards to an Integrated Approach. Erasmus School of

Economics, Erasmus University Rotterdam.

Buch, T., Hamann, S., Niebuhr, A., & Rossen, A. (2014). What Makes Cities Attractive? The

Determinants of Urban Labour Migration in Germany. Urban Studies, 51(9), 1960‒1978.

Cao, X. (J.), & Wang, D. (2016). Environmental correlates of residential satisfaction: An

exploration of mismatched neighhborhood characteristics in the Twin Cities, Landscape

and Urban Planning, 150, 26−35.

Dekker, K., de Vos, S., Musterd, S., & van Kempen, R. (2011). 

Residential Satisfaction in Housing Estates in European Cities: A Multi-level Research

Approach. Housing Studies, 26(4), 479‒499.

Delken, E. (2008). Happiness in shrinking cities in Germany. Journal of Happiness Studies,

9(2), 213–218.

European Commission (2006). Cohesion Policy and cities: the urban contribution to growth and

jobs in the regions. Communication from the Commission to the Council and Parliament.

COM 385 final. Brussels.

http://ec.europa.eu/regional_policy/archive/consultation/urban/com_2006_0385_en.pdf

[10-06-2016].

Fang, Y. (2006). Residential satisfaction, moving intention and moving behaviours: A study of

redeveloped neighbourhoods in Inner-City Beijing. Housing Studies, 21(5), 671−694.

Fertner, C., Groth, N. B., Herslund, L., & Carstensen, T. A. (2015) Small towns resisting urban

decay through residential attractiveness. Findings from Denmark. Geografisk Tidsskrift-

Danish Journal of Geography, 115(2), 119−132.

Filkins, R., Allen, J., & Cordes, S. (2000). Predicting community satisfaction among rural

residents: An integrative model. Rural Sociology, 65(1), 72–86.

Florida, R., Mellander, C., & Stolarick, K. (2011). Beautiful Places: The Role of Perceived

Aesthetic Beauty in Community Satisfaction. Regional Studies, 45(1), 33‒48. 

21

Francescato, G. (2002). Residential satisfaction research: The case for and against. In J. I.

Aragonés, G. Francescato, & T. Gärling (Eds.), Residential environments: Choice,

satisfaction and behavior (pp. 15–34). Westport: Bergin and Garvey.

Grinstein-Weiss, M., Yeo, Y., Anacker, K., van Zandt, S., Freeze, E. B., & Quercia, R. G.

(2011). Homeownership and neighborhood satisfaction among low- and moderate-income

households. Journal of Urban Affairs, 33(3), 247–265.

Guimarães, M. H., Barreira, A. P., & Panagopoulos, T. (2015). Shrinking cities in Portugal –

Where and why. Revista Portuguesa de Estudos Regionais, 40(3), 23–41.

Guimarães, M. H., Nunes, L. C., Barreira, A. P., & Panagopoulos, T. (2016). Residents’

preferred policy actions for shrinking cities. Policy Studies. DOI:

http://dx.doi.org/10.1080/01442872.2016.1146245

Haase, A., Bernt, M., Grobmann, K., Mykhnenko, V., & Rink, D. (2013). Varieties of shrinkage

in European cities. European Urban and Regional Studies, 23(1), 1–17.

Haase, A., Hospers, G.-J., Pekelsma, S., & Rink, D. (2012). Front-runners in innovative citizen

participation – Shrinking Areas, European Urban Knowledge Network.

Hernández, B., Martín, A.M., Ruiz, C., & Hidalgo, M.C. (2010). The role of place identity and

place attachment in breaking environmental protection laws. Journal of Environmental

Psychology, 30(3), 281–288.

Hidalgo, M. C., & Hernández, B. (2001). Place attachment: Conceptual and empirical questions.

Journal of Environmental Psychology, 21(3), 273–281.

Hollander, J. B. (2011). Can a city successfully shrink? Evidence from survey data on

neighborhood quality. Urban Affairs Review, 47(1), 129–141.

Hollander, J. B., & Németh, J. (2011). The bounds of smart decline: a foundational theory for

planning shrinking cities. Housing Policy Debate, 21(3), 349–367.

Hospers, G.-J. (2014). Policy responses to urban shrinkage: From growth thinking to civic

engagement. European Planning Studies, 22(7), 1507–1523.

Hur, M., & Morrow-Jones, H. (2008). Factors that influence residents' satisfaction with

neighborhoods. Environment and Behavior, 40(5), 619–635.

International Organization for Migration (2011). Economic cycles, demographic change and

migration. International Dialogue on Migration Workshop – The future of migration:

Building capacities for change, Background Paper, 12–13 September.

22

Kamalipour, H., Yeganeh, A. J., & Alalhesabi, M. (2012). Predictors of place attachment in

urban residential environments: A residential complex case study. Procedia- Social and

Behavioral Sciences, 35, 459‒467.

Kearns, A., & Parkes, A. (2003). Living in and leaving poor neighbourhood conditions in

England. Housing Studies, 18(6), 827–852.

Khavarian-Garmsir, A. R., Pourahmad, A., Hataminejad, H. & Farhoudi, R. (2017). A

comparative assessment of economic and physical inequality between shrinking and

growing cities: a case study of Khuzestan province, Iran. International Journal of Urban

Sciences, DOI: 10.1080/12265934.2017.1358653.

Kleinhans, R. & Bolt, G. (2013). More than just fear: On the intricate interplay between

perceived neighborhood disorder, collective efficacy, and action. Journal of Urban Affairs,

36(3), 420–446.

Krabel, S., & Flöther, C. (2012). Here Today, Gone Tomorrow? Regional Labour Mobility of

German University Graduates. Regional Studies, 48(10), 1609‒1627.

Lambiri, D., Biagi, B., & Royuela, V. (2007). Quality of life in the economic and urban

economic literature. Social Indicators Research, 84(1), 1–25.

Lee, Y.-J. (2008). Subjective quality of life measurement in Taipei. Building and Environment,

43(7), 1205–1215.

Lewicka, M. (2011). Place attachment: How far have we come in the last 40 years? Journal of

Environmental Psychology, 31(3), 207-230.

Livingston, M., Bailey, N., & Kearns, A. (2010). Neighbourhood attachment in deprived areas:

Evidence from the north of England. Journal of Housing and the Building Environment,

25(4), 409−427.

Lu, M. (1999). Determinants of residential satisfaction: Ordered logit vs regression models.

Growth and Change, 30(2), 264‒287.

Lutz, J. M. (2001). Determinants of population growth in urban centres in the Republic of

Ireland. Urban Studies, 38(8), 1329–1340.

Manturuk, K., Lindblad, M., & Quercia, R. (2010). Friends and neighbors: Homeownership and

social capital among low‐to moderate‐income families. Journal of Urban Affairs, 32(4),

471–488.

23

McCrea, R., Shyy, T.-K., & Stimson, R. J. (2014). Satisfied residents in different types of local

areas: Measuring what’s most important. Social Indicators Research, 118(1), 87–101.

McCrea, R., Stimson, R., & Western, J. (2005). Testing a moderated model of satisfaction with

urban living using data for Brisbane–South East Queensland, Australia. Social Indicators

Research, 72(2), 121–152.

Mellander, C., Florida, R., & Stolarick, K. (2011). Here to stay – The effects of community

satisfaction on the decision to stay. Spatial Economic Analysis, 6(1), 5‒24.

Miot, Y. (2015). Residential Attractiveness as a Public Policy Goal for Declining Industrial

Cities: Housing Renewal Strategies in Mulhouse, Roubaix and Saint-Etienne (France).

European Planning Studies, 23(1), 104‒125.

Neal, Z., & Neal, J.W. (2012). The public school as a public good: Direct and indirect pathways

to community satisfaction. Journal of Urban Affairs, 34(5), 469−485.

Niedomysl, T. (2010). Towards a conceptual framework of place attractiveness: A migration

perspective. Geografiska Annaler: Series B, Human Geography, 92(1), 97–109.

Ogu, V. I. (2002). Urban residential satisfaction and the planning implications in a developing

world context: The example of Benin City, Nigeria. International Planning Studies, 7(1),

37–53.

Oswalt, P., & Rieniets, T. (Eds.) (2006). Atlas of Shrinking Cities. Hatje Cantz Publishers.

Oswalt, P., & Rieniets, T. (2007). Global context. Shrinking cities. Shrinking Cities Web Site:

http://www.shrinkingcities.com/globaler_kontext.0.html?andL=1.

Pallagst, K., Schwarz, T., Popper, F. J., & Hollander, J. B. (2009). Planning shrinking cities.

Progress in Planning, 72(4), 223–232.

Panagopoulos, T., & Barreira, A. P. (2012). Perceptions and shrink smart strategies for the

municipalities of Portugal. Journal Built Environment, 38(2), 276–292.

Panagopoulos, T., Guimarães, M. H., & Barreira, A. P. (2015). Influences on citizens’ policy

preferences for shrinking cities: a case study of four Portuguese cities. Regional Studies

Regional Science, 2 (1), 141−170.

Parkes, A., Kearns, A., & Atkinson, R. (2002). What makes people dissatisfied with their

neighborhood? Urban Studies, 39(13), 2413–2438.

24

Perez, F. R., Fernandez-Mayoralas, G., Rivera, F. E. P., & Abuin, J. M. R. (2001). Ageing in

place: Predictors of the residential satisfaction of elderly. Social Indicators Research,

54(2), 173–208.

Raymond, C. M., Brown, G., & Weber, D. (2010). The measurement of place attachment:

Personal, community, and environmental connections. Journal of Environmental

Psychology, 30(4), 422–434.

Sampson, K. A., & Goodrich, C. G. (2009). Making place: Identity construction and community

formation through ‘sense of place’ in Westland, New Zealand. Society & Natural

Resources, 22(10), 901−915.

Seo, J.-K. (2002). Re-urbanisation in regenerated areas of Manchester and Glasgow: New

residents and the problems of sustainability, Cities, 19(2), 113−121.

Sirgy, M. J., Gao, T., & Young, R. F. (2008). How does residents’ satisfaction with community

services influence Quality of Life (QOL) outcomes? Applied Research in Quality of Life,

3(2), 81−105.

Sirgy, M. J., Michalos, A. C., Ferriss, A. L., Easterlin, R. A., Patrick, D., & Pavot,

W. (2006).The Quality-Of-Life (QOL) research movement: Past, present, and future.

Social Indicators Research, 76(3), 343-466.

Sirgy, M. J., Rahtz, D. R., Cicic, M., & Underwood, R. (2000). A method for assessing residents’

satisfaction with community based services: A quality of life perspective. Social Indicators

Research, 49(3), 279–316.

Sousa, S. A. (2010). Planning for shrinking cities in Portugal. Ph.D. Thesis. Faculty of

Engineering, University of Oporto. Oporto.

Sousa, S., & Pinho, P. (2015). Planning for Shrinkage: Paradox or Paradigm. European Planning

Studies, 23(1), 12−32.

StataCorp, 2013, Stata 13 Base Reference Manual, College Station, TX: Stata Press.

Turok, I., & Mykhnenko, V. (2007). The trajectories of European cities, 1960–2005. Cities,

24(3), 165–182.

Wiechmann, T., & Pallagst, K. M. (2012). Urban shrinkage in Germany and the USA: A

comparison of transformation patterns and local strategies. International Journal of Urban

and Regional Research, 36(2), 261–280.

25

Woo, M. & Morrow-Jones, H. A. (2011). Main factors associated with homeowners' intentions

to move. International Journal of Urban Sciences, 15(3), 161‒186.

Zimmermann, K. F. (2005). European labour mobility: Challenges and potentials. De Economist,

153(4), 425–450.

26