Towards Socially Towards Socially SustainableSustainable

Local Government: Local Government:A case of Swedish A case of Swedish

MunicipalitiesMunicipalitiesJun YAMASHITAJun YAMASHITA

Faculty of Social and Cultural Faculty of Social and Cultural Studies, Kyushu University, Studies, Kyushu University,

JAPANJAPAN

IGU Urban Commission 2011 Canterbury Meeting 14-20 August 2011 Canterbury, UK

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Introduction Introduction (1)(1) Social sustainability has been gaining

much attention (Rydin and Holman, 2004; Evans et al., 2005, 2006).

““A positive relation between the A positive relation between the social capital or social network and social capital or social network and success of environment policysuccess of environment policy.”.”

However, there are few empirical studies regarding this relation.

High level of High level of social capital social capital or networkor network

High possibility High possibility of success in of success in sustainable sustainable development development policiespolicies

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Introduction Introduction (2)(2) Two Swedish national subsidy Two Swedish national subsidy

programmes, LIP (1998-2002) and Klimp programmes, LIP (1998-2002) and Klimp (2003-8), are good research objectives to (2003-8), are good research objectives to reveal such a positive relation. reveal such a positive relation.

Because these programmes aimed at Because these programmes aimed at creating social networkscreating social networks and and reduction in negative effects of the reduction in negative effects of the global warmingglobal warming. .

Purposes in this studyPurposes in this study To identify chief actors before and after To identify chief actors before and after

LIP, and to reveal whether various kinds LIP, and to reveal whether various kinds of actors were involved after the LIP.of actors were involved after the LIP.

To contribute to identification of the To contribute to identification of the positive relation between the social positive relation between the social network and environment policy.network and environment policy.

1. Methods1. Methods

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1.1 Overview of the LIP and 1.1 Overview of the LIP and Klimp (1)Klimp (1)

Influences of LIP and Klimp Influences of LIP and Klimp projects to collaboration of actors projects to collaboration of actors were identified by were identified by urban and urban and rural areasrural areas

The urban areas: the national The urban areas: the national centrescentres,, three metropolitan three metropolitan areasareas An advantage of human and An advantage of human and

financial resourcesfinancial resources 899 LIP and 455 Klimp projects were 899 LIP and 455 Klimp projects were

implemented.implemented. The rural areas: the national The rural areas: the national

peripheriesperipheries, , Advantageous on social networksAdvantageous on social networks 944 LIP and 458 Klimp projects were 944 LIP and 458 Klimp projects were

undertaken.undertaken. Malmö and Växjö, were selected Malmö and Växjö, were selected

as a case city for each area. as a case city for each area.

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1.1 Overview of the LIP and 1.1 Overview of the LIP and Klimp (2)Klimp (2)

Actor Actor Municipalities, municipal companies, Municipalities, municipal companies,

and private companiesand private companies highly involved in highly involved in LIP and Klimp in both urban and rural areasLIP and Klimp in both urban and rural areas

Private persons and associationsPrivate persons and associations rarely rarely participated in either LIP or Klimp projects in participated in either LIP or Klimp projects in both urban and rural area.both urban and rural area.

Actors in urban and rural areas are Actors in urban and rural areas are much much similarsimilar..

The public participation was hardly reinforced The public participation was hardly reinforced in either LIP or Klimp in the urban and rural in either LIP or Klimp in the urban and rural areas.areas. a) Actors a) Actors

2) Percentage 2) PercentageUrban areas Rural areas Urban areas Rural areas

Central andcountygovernment

1.6 3.2Central andcountygovernment

6.4 4.1

Municipality 54.7 52.6 Municipality 51.2 54.1Municipalcompanies

13.6 20.9Municipalcompanies

18.0 20.1

Privatecompanies

14.9 14.0Privatecompanies

15.8 14.8

Asssociations 5.2 3.8 Asssociations 0.0 0.4Private persons 1.1 0.8 Private persons 0.2 0.4Other 8.9 4.7 Other 8.4 5.9Total 100.0 100.0 Total 100.0 100.0

Table 1 LIP Table 2 Klimp

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1.1 Overview of the LIP and 1.1 Overview of the LIP and Klimp (3)Klimp (3)

Objective Objective Various kinds of projects were implemented Various kinds of projects were implemented

in LIP in both urban and rural areas.in LIP in both urban and rural areas. Projects were concentrated in the two fields Projects were concentrated in the two fields

of energy and transport in Klimp in the two of energy and transport in Klimp in the two areasareas

Although LIP’s objectives differ from Klimp’s, Although LIP’s objectives differ from Klimp’s, there was no difference in objective between there was no difference in objective between the urban and rural areasthe urban and rural areas..

b) Objectives b) Objectives2) Percentage 2) Percentage

Urban areas Rural areas Urban areas Rural areasEnergy 28.4 35.5 Energy 30.3 40.8Water andsewage

14.3 12.2Water andsewage

0.0 0.0

Bio-diversity 12.3 8.4 Bio-diversity 0.0 0.0Waste 8.8 11.1 Waste 7.3 4.1Transport 10.8 8.9 Transport 24.0 21.6Multi-task 5.3 4.0 Multi-task 0.0 0.0Industry 1.3 2.4 Industry 0.0 0.0Housing 2.4 1.1 Housing 0.0 0.0Others 16.2 16.4 Others 38.5 33.4Total 100.0 100.0 Total 100.0 100.0

Table 1 LIP Table 2 Klimp

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1.2 Analytical methods and 1.2 Analytical methods and data (1)data (1)

The analysis of varianceThe analysis of variance and and network network analysisanalysis were utilised to identify who were utilised to identify who were chief actors.were chief actors.

For For the analysis of variancethe analysis of variance, the , the number of projects by actor and objective number of projects by actor and objective were employed as data.were employed as data.

For For the network analysisthe network analysis,, the five point the five point scale showing below was employed.scale showing below was employed.

The three indexes, namely, The three indexes, namely, the average the average shortest distance, density, and shortest distance, density, and degree centralitydegree centrality, were also used to , were also used to explicate network structures.explicate network structures.

Scores Frequency4 Two or three times a week3 Two or three times a month2 Two or three times a year1 Once a year0 No contact

2. Results2. Results

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2.1 Results derived from 2.1 Results derived from applications of the analysis of applications of the analysis of

variance (1)variance (1) There is statisticallyThere is statistically no difference no difference in in eithereither actor actor oror objective objective between urban between urban and rural areas. and rural areas.

Regarding Regarding actorsactors, far larger values of , far larger values of estimated variances estimated variances within urban and within urban and rural areasrural areas than than between these areasbetween these areas lead to statistical lead to statistical no significanceno significance of of variance ratios at 10 percent level.variance ratios at 10 percent level.

Chief actors were Chief actors were municipalitiesmunicipalities and and municipal companiesmunicipal companies in the LIP and in the LIP and Klimp projects.Klimp projects.

Promoting collaboration among Promoting collaboration among various actors was hardly attained.various actors was hardly attained.

Sources ofvariation

Sum ofsquare

Degrees offreedom

Varianceestimates

Table6 a) Actors (LIP)Between groups 144.64 1 144.64 0.00498 n.s.Within group 348,484.57 12 29,040.38Total 348,629.21 13Table 7 a) Actors (Klimp)Between groups 0.64 1 0.64 0.00009 n.s.Within group 84,631.71 12 7,052.64Total 84,632.36 13Note：n.s.: Statistically not significant at 10% level.

Variance ratio

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Sources ofvariation

Sum ofsquare

Degrees offreedom

Varianceestimates

Table 6 b) Objective (LIP)Between groups 112.50 1 112.50 0.01488 n.s.Within group 120,939.78 16 7,558.74

Total 121,052.28 17Table 7 b) Objective (Klimp)Between groups 0.50 1 0.50 0.00009 n.s.Within group 84,869.11 16 5,304.32

Total 84,869.61 17

Note：n.s.: Statistically not significant at 10% level.

Variance ratio

2.1 Results derived from 2.1 Results derived from applications of the analysis of applications of the analysis of

variance (2)variance (2) Differences in Differences in objectivesobjectives were were very very smallsmall between urban and rural between urban and rural areas.areas.

Such small figures of the estimated Such small figures of the estimated variances between the two areas brought variances between the two areas brought statistically statistically nono significancesignificance of the of the variance ratios at 10 percent level.variance ratios at 10 percent level.

Objectives in the LIP and Klimp are not Objectives in the LIP and Klimp are not different but concentrated in different but concentrated in energyenergy and and transporttransport in the LIP and Klimp in both in the LIP and Klimp in both urban and rural areas.urban and rural areas.

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2.2 Results derived from 2.2 Results derived from applications of the network applications of the network

analysis (1)analysis (1) Network structure principally Network structure principally did not did not

change before and after LIPchange before and after LIP.. The actors in both Malmö and Växjö were The actors in both Malmö and Växjö were

closely connected with each other at the closely connected with each other at the implemental stage of LIP.implemental stage of LIP.

Contrarily, social networks of actors Contrarily, social networks of actors rapidly diminished after LIP. rapidly diminished after LIP.

Before LIP Implementation After LIP1) MalmöAverage shortest distance 10.35 1.86 10.34Density 0.38 0.47 0.272) VäxjöAverage shortest distance 7.25 1.38 4.65Density 0.60 1.33 0.82

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2.2 Results derived from 2.2 Results derived from applications of the network applications of the network

analysis (2)analysis (2) Using the degree centrality, it is confirmed Using the degree centrality, it is confirmed that chief actors were that chief actors were municipalitiesmunicipalities andand municipal companiesmunicipal companies in Malmö and Växjö. in Malmö and Växjö.

No. Actors Before LIP Implementation After LIP1) MalmöM1 Municipality (Road management) 0.5 0.5 0.3M2 Municipality (Recreation) 0.0 0.1 0.1M3 Municipality (Urban Planning) 0.5 0.4 0.3M4 Municipality (Environmental Protection) 0.5 0.5 0.5M5 Municipality (Real estate) 0.2 0.3 0.2M6 Municipal company (Gas) 0.7 0.5 0.7M7 Municipal company (Distirict heating) 1.7 3.2 1.5M8 Municipal company (Water and sewage) 0.4 0.3 0.3M9 Assoication (Housing) 1 0.2 0.3 0.2M10 Assoication (Housing) 2 0.1 0.3 0.1M11 Private company (Construction) 1 0.3 0.5 0.0M12 Private company (Real estate) 1 0.1 0.2 0.0M13 Private company (Construction) 2 1.0 0.6 0.1M14 Private company (Real estate) 2 0.0 0.1 0.0M15 Private company (Housing) 0.0 0.1 0.0M16 Private company (Real estate) 3 0.6 0.3 0.2M17 Private company (Construction) 3 0.0 0.1 0.0M18 Private company (Construction) 4 0.1 0.2 0.1M19 Private company (Construction) 5 0.0 0.1 0.0M20 Private company (Construction) 6 0.2 0.2 0.1M21 Private company (Real estate) 4 0.3 0.2 0.2M22 Private company (Construction) 7 0.5 0.5 0.3M23 Private company (Construction) 8 0.3 0.3 0.3M24 Private company (Construction) 9 0.1 0.2 0.1M25 Private company (Real estate) 5 1.2 1.8 1.22) VäxjöV1 Municipality (Natural resource conservaton) 1.0 2.2 1.3V2 Municipality (Waste) 1.0 2.2 1.3V3 Municipality (Environment and social welfare) 1.2 2.3 1.5V4 Municipality (Technology) 1.4 2.3 1.7V5 Municipal company (District heating) 0.4 0.8 0.4V6 Municipal company (Energy) 0.8 1.2 1.2V7 Municipal company (Housing) 0.8 0.8 0.8V8 Association (Environmental conservation) 0.0 0.8 0.0V9 Priavte company (Transport) 1 0.0 0.8 0.4V10 Priavte company (Transport) 2 0.0 0.8 0.4V11 Priavte company (Car service) 0.0 0.4 0.0

Actors in Actors in municipalitiesmunicipalities and and municipal companiesmunicipal companies have high values of have high values of degree centrality. degree centrality.

Conversely, Conversely, private private companiescompanies, , associations and associations and organizationsorganizations have have low values.low values.

Some actorsSome actors were were notnot involved in any involved in any environmental projects environmental projects before LIP or after LIP.before LIP or after LIP.

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2.2 Results derived from 2.2 Results derived from applications of the network applications of the network

analysis (3)analysis (3) Sociogrammes also indicate that the Sociogrammes also indicate that the municipalitiesmunicipalities and and municipal companiesmunicipal companies were were chief actors.chief actors.

Among actors from Among actors from municipalitiesmunicipalities and and municipal companiesmunicipal companies, networks , networks havehave already already been formedbeen formed before LIP, were before LIP, were strengthenedstrengthened at at the implemental stage of LIP, and were lessened the implemental stage of LIP, and were lessened but still but still remained after LIPremained after LIP. .

Links between Links between municipalities or municipalities or municipal municipal companiescompanies and and other actorsother actors were were established at the established at the implemental stage of implemental stage of LIP, but were almost LIP, but were almost dissolved after LIPdissolved after LIP..

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2.2 Results derived from 2.2 Results derived from applications of the network applications of the network

analysis (4)analysis (4) A positive relation between the social A positive relation between the social network and success of environment network and success of environment policy didpolicy did not not observed observed in this study.in this study.

The energy consumptions in Malmö and The energy consumptions in Malmö and Växjö Växjö increasedincreased between 2000 and between 2000 and 2004, but the social networks were 2004, but the social networks were tightentightened and various actors involved ed and various actors involved then.then.

Contrarily, the energy consumptions in Contrarily, the energy consumptions in Växjö Växjö decreaseddecreased between 2004 and between 2004 and 2008, but the social network was 2008, but the social network was loosenedloosened then. then.

These findings differ from those in the These findings differ from those in the previous studies.previous studies.

a) Total energy consumption (MWh) 2000 2004 2008Malmö 6,737,372 7,121,428 7,515,998Växjö 2,174,709 2,459,538 2,075,023

b) Growth (%) 2000-2004 2004-2008Malmö 5.70 5.54Växjö 13.10 -15.63

Before LIP Implementation After LIP1) MalmöAverage shortest distance 10.35 1.86 10.34Density 0.38 0.47 0.272) VäxjöAverage shortest distance 7.25 1.38 4.65Density 0.60 1.33 0.82

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ConclusionsConclusions

As results derived from applications of both As results derived from applications of both the analysis of variance and network analysis, the analysis of variance and network analysis, it was explicated thatit was explicated that municipalities and municipalities and municipal companiesmunicipal companies were main actors. were main actors.

There was There was no difference in actor and no difference in actor and objectiveobjective between the centres and between the centres and peripheriesperipheries..

It was, therefore, concluded that the It was, therefore, concluded that the participation of various actors was participation of various actors was hardly enhancedhardly enhanced in the LIP and Klimp in the LIP and Klimp projects.projects.

It was also suggested that no positive but It was also suggested that no positive but aa negative or no relation between the negative or no relation between the social network and success of social network and success of environment policy environment policy in this study.in this study.

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Thank you for your Thank you for your attention.attention.

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