territorial impact assessment: integrating territorial aspects in sectoral policies

Evaluation and Program Planning 34 (2011) 163–173

Territorial impact assessment: Integrating territorial aspects in sectoral policies

Mojca Golobic a,b,*, Naja Marot b,1

a Biotechnical Faculty, University of Ljubljana, Jamnikarjeva 101, 1000 Ljubljana, Sloveniab Urban Planning Institute of the Republic of Slovenia, Trnovski pristan 2, 1127 Ljubljana, p.p. 4717, Slovenia

A R T I C L E I N F O

Article history:

Received 8 July 2010

Received in revised form 29 January 2011

Accepted 6 February 2011

Available online 3 March 2011

Keywords:

Territorial impact assessment

Territorial cohesion

Slovenia

Energy policy

A B S T R A C T

Territorial impact assessment has recently gained attention as a tool to improve the coherence of sector

policies with territorial cohesion objectives. The paper presents a method for territorial impact

assessment and the results of applying this method on Slovenian energy policy. A two phase approach

first disaggregates the problem into a three-dimensional matrix, consisting of policy measures,

territorial objectives and territorial units. The synthesis phase aggregates measures and objectives in

physical, economic or socio-cultural groups and observes their interrelation through an input–output

matrix. The results have shown that such a two level approach is required to obtain complete and useful

information for policy developers. In contrast to the relatively favourable evaluation of individual

measures on the first level of assessment, the synthesis has revealed substantial and systemic

weaknesses: considerable imbalance of energy policy favouring territorial effectiveness and mainly

neglecting territorial identity as well as its counterproductiveness in reducing regional disparities.

� 2011 Elsevier Ltd. All rights reserved.

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1. Introduction

Impact assessments have become a popular tool in the policydevelopment process since the 80s with the initiative and methodsof OECD2 (OECD, 1995). Later on they were integrated as aninevitable part of EU policy preparation processes (CEC, 2001,2002, 2004b, 2005a, 2005b, 2009b). The policy making practice hasbrought a set of assessment approaches, differing in terms of levelof assessment (strategic vs. project); in types of targeted policydocuments (policies, programmes, plans, strategies), types ofconcerned impacts (environmental, social, regulatory, economic),applied methods (e.g. quantitative vs. qualitative), reference frame(sustainable development, good governance principles, competi-tiveness, equity) and legal status (obligatory or non-obligatory)(Miklavcic & Weaver, 2005). An important distinction regards theapplication of the assessment results in decision making: they can

* Corresponding author at: Biotechnical Faculty, University of Ljubljana,

Jamnikarjeva 101, 1000 Ljubljana, Slovenia. Tel.: +386 1 320 30 65.

E-mail addresses: [email protected], [email protected] (M. Golobic),

[email protected] (N. Marot).1 Tel.: +386 1 420 13 13; fax: +386 1 420 13 30.2 Less common abbreviations, used in the article: ARL – Die Akademie fur

Raumforschung und Landesplanung/Academy for regional research and planning,

BMVBS – Bundesministerium fur Verkehr, Bau und Stadtentwicklung/Federal

Ministry of Transport, Building and Urban Development, ESDP – European Spatial

Development Perspectives, FSA – Financial Service Authority, LEM – Leopold-Ekins-

Medhurst matrix, NAO – National Audit Office (in Great Britain), NEP – national

energy policy (in Slovenia), ReNEP – Resolution on national energy policy (in

Slovenia).

0149-7189/$ – see front matter � 2011 Elsevier Ltd. All rights reserved.

doi:10.1016/j.evalprogplan.2011.02.009

be used ex-post, ex-durante or ex-ante and either as policydevelopment (optimization) or administrative decision (standard-ization) support (Golobic & Zakrajsek, 2007). One of the mostrecently emerging assessment approaches is territorial impactassessment (TIA). TIA is conceived as a strategic assessment ofsectoral policies and their measures in terms of their impacts onterritorial cohesion (Schindegger & Tatzberger, 2004).

Territorial cohesion was introduced as a community aim withthe Third Cohesion Report saying that ‘‘people should not bedisadvantaged by wherever they happen to live or work in theUnion’’ (CEC, 2004a, p. 27), suggesting that the quality of placeswhere people live and work in can influence their access toeconomic and social opportunities and the quality of their life(Davoudi, 2005). The concept of territorial cohesion derives fromexisting objectives such as sustainability, competitiveness andquality of life, but puts them in territorial perspective. As it wasclaimed during the Dutch presidency territorial cohesion is steeredtowards incorporating a spatial perspective into decisions nowmade primarily on economic and social grounds (Davoudi, 2005;Dutch Presidency, 2004; VROM, 2004). Although territorialcohesion has been accepted in policy agendas and documents, itis still not universally known or recognized concept. The criticsmainly mention lack of common and clear understanding of whatterritorial cohesion represents legally or politically (Finka, 2007).The second point of critique claims that the territorial cohesionconcept brings little added value compared to economic and socialcohesion, which both aim to reduce structural disparities andpromote co-ordination between the regional and sectoral policies;while suffering the same problems such as too vague definition,

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M. Golobic, N. Marot / Evaluation and Program Planning 34 (2011) 163–173164

conflicting goals, difficulties in measuring (Chicoye, 1992; ESPON3.1, 2004b; Faludi, 2004, 2007; Lennert & Robert, 2010). Despitethese critics, the territorial cohesion has been acknowledged as anormative base to develop and perform territorial impactassessment to inspect territorial consequences (the spatialdevelopment impacts) of the interaction of disparate EU policiesin particular places (Duhr, Colomb, & Nadin, 2010), and promotethe coherence of EU policies with their territorial impacts(Camagni, 2006b; Luxembourg Presidency, 2005).

The approach presented in this paper is based on the territorialcohesion concept as defined in Territorial Agenda of European Union(BMVBS, 2007b, Article 3 and 8) – a common framework forterritorial policies: territorial cohesion represents the main condi-tion for sustainable economic growth and delivery of social andeconomic cohesion and should secure polycentric spatial develop-ment, better and more efficient use of available resources, spatialintegration of different areas, better living conditions and quality oflife with equal opportunities, oriented towards regional and localpotentials. The complex and trans-sectoral idea of the concept can bepresented and so far acknowledged both by academia and policymakers (Battis & Kersten, 2008; Camagni, 2009). For now, territorialcohesion consists of three main components:

- Territorial quality: the quality of living and working environment;comparable living standard across territories; similar levels ofaccess to services of general interest and to knowledge;

- Territorial efficiency: resource efficiency with respect to energy,land and natural resources; competitiveness of the economicfabric and attractiveness of the territory; internal and externalaccessibility; territorial integration and cooperation betweenregions and

- Territorial identity: presence of ‘‘social capital’’, local know-howand cooperation between regions; and a competitive advantageof each place and territory

As Camagni (2002) states the first two objectives are ratherfamiliar and in line with economic and social cohesion objectives,the third dimension – territorial identity represents the missingelement of connecting the social capital of one locality to itsterritory, e.g. spatial division of labour and its implication onto thelocal development.

Both the Territorial Agenda of EU (BMVBS, 2007b) and theGreen Paper on Territorial Cohesion (CEC, 2009a) which summa-rized the concepts related to territorial cohesion acknowledge thatthe sector policies and their interventions influence the territoriesin which they are implemented. For most cases the effects willdiffer from one territory to another depending on territorialcontext and the interventions of other policies active in thatterritory (ARL, 2008). Consequently, their territorial impactsshould be carefully planned and monitored afterwards. Theterritorial impacts of most EU policies have been evaluated bythe European Spatial Planning Observatory Network (ESPON) inseveral of their projects3 (ESPON 2.1.1., 2004a; ESPON 2.1.4.,2005b, etc.). The results confirm that most policies and theirmeasures do not take territorial cohesion or multifaceted impactsinto consideration. This increases hazards for problems such as

3 When we refer to ESPON projects in this paper, we mean projects of policy

impacts which include territorial impact assessment. Projects are as following:

ESPON 2.1.1 Transport Policy Impact (2004a), ESPON 2.1.3 CAP impact (2005a),

ESPON 2.1.4 Energy (2005b), ESPON 2.1.5 Fishery (2006a); ESPON 2.2.1 Territorial

Effects of Structural Funds (2006b); ESPON 2.2.2 Pre-Acession aid (2005c); ESPON

2.2.3 Territorial Effects of Structural Funds in urban areas (2006c); ESPON 2.3.1

ESDP Impact (2006d); ESPON 2.4.1 Environment (2006e); ESPON 3.1 Integrated

tools for European spatial development (2004b) and ESPON 3.2 Scenarios (2006f).

Projects’ reports are available on-line: http://www.espon.eu/mmp/online/website/

content/projects/243/239/index_EN.html.

asymmetrical shocks due to different policy effects in differentenvironments, economic destabilization of certain areas, non-controlled real estate speculations and unsustainable develop-ment, all of which lead to high social costs. TIA is seen as apotentially powerful tool to provide more awareness (ex-ante andex-post) of the territorial implications, synergies or costs of non-co-ordination (ARL, 2008).

The first document to explicitly recognize the need for theassessment of territorial impacts was the European SpatialDevelopment Perspectives (CEC, 1999) which mentions territorialimpact assessment as an instrument for assessing certain plansand strategies as well as for improving the coordination betweensectors (transport, agriculture, regional development, R&D, ICT)and territorial objectives. The White Paper on Governance (CEC,2001) mentions the need for considering territorial impacts ofsector policies with the aim to replace the sector-orientedapproach with a more integrated one. This should lead to morecoherent policies which would consequently improve territorialcohesion. The aim of TIA and territorial cohesion coincide with theestablishment of better co-operation in both horizontal terms(between policies) and vertical terms (between actors/stake-holders at different geographical and administrative level; Finka,2007). The aims of good governance require the policy makingprocesses to become faster, more robust and relieved of all non-necessary administrative burdens (CEC, 2007b). This requirementcan on the one hand discourage policy makers from applying yetanother assessment procedure. On the other hand, requirement fortransparency and provision of arguments for the decision makingprocess may be in favour of introducing a tool like TIA.

Despite the vagueness of the territorial cohesion concept weconsider that its sensitivity to territorial scale and parameters,consideration of territorial potentials and regional identity is animportant contribution compared to other more widely acceptedconcepts of human well-being and development. With TIAterritorial cohesion objectives also gains a necessary tool tosupport its measurement and implementation. However, theuncertainties and problems related to policy evaluation in generalas well as assessing territorial impacts of policies providemotivation for authors to try to develop and test a TIA approachfrom its concept to a related tool for implementation.

2. An overview of existing TIA approaches

Currently, there is no common or prescribed approach to TIAanalysis. The variability of approaches regarding the territoriallevel, the method of evaluation and the understanding ofcorrelations between the policies and impacts reflects thecomplexity of the territorial cohesion concept. In most countriesthe TIA procedure is not a part of the official regulatory process.Usually it is integrated in other formalized assessment or it servesas a complementary analysis. The latter can be part of on-goingpolicy decision making or it can present an ex-post evaluation toolfor existing policy and an aid for search of the alternatives to it. Forexample, in Great Britain, the assessment of territorial impacts isintegrated into impact assessment (IA) which is part of theirBetter Regulation Initiative (FSA, 2005; NAO, 2001, 2007). Of the150–200 analyses performed every year, 33% are (in)directlyrelated to the territory. For a new transportation act policy makersset up pilot areas to test the measures in real circumstances andevaluate their benefits and costs before they are fully imple-mented (NAO, 2000). However, a significant work on TIA was notprovided with a direct policy-making implication, but within thescope of ESPON research programme. These policy impactprojects concentrate mostly on ex-post analysis of potentialinfluences of European sector policies on EU countries’ nationalterritories mostly on NUTS2 and NUTS3 level.

http://www.espon.eu/mmp/online/website/content/projects/243/239/index_EN.html

http://www.espon.eu/mmp/online/website/content/projects/243/239/index_EN.html

M. Golobic, N. Marot / Evaluation and Program Planning 34 (2011) 163–173 165

No matter the variety of criteria and methods in observedevaluations, all TIA approaches follow the main steps of any impactassessment: definition of the evaluation scope and framework;hypothesis about causal and consecutive relationships; and finallyevaluation. The evaluation framework for most of the TIA deriveseither from ESDP (CEC, 1999), updated with Territorial Agenda(BMVBS, 2007b) and Green Paper (CEC, 2009a) or from nationalspatial policy documents. The causal-consecutive relations areconstructed taking the (sector) policy measures as causes and theireffects in a given territorial unit as a consequence.

Regarding practical implementation, there is a variety ofmodels and tools applied for TIA: SASI (recursive simulationmodel of socio-economic regional development), CGEurope (aspatial computable general equilibrium model), STIMA model(Spatial Telecommunications Impact Assessment) for transportpolicy (ESPON 2.1.1 Transport policy impact; ESPON, 2004a);statistical methods such as group analysis for agriculture (ESPON2.1.3 CAP impact; ESPON, 2005a; regression analysis, econometricmodels – OECD interlink model, IMF multimod, GEM-E3 generalequilibrium model (ESPON 2.1.4 Energy; ESPON, 2005b). Theapproaches based on quantitative models to some degreeencounter the problem of incomplete and lacking data. Thereforethey may be either complemented with or replaced by qualitativemethods such as interviews, questionnaires and Delphi expertevaluation. Simple or complex indicators support the findings withquantitative evidence.

Another approach is to monitor the impacts as case studies inpilot areas (Yin, 2008). Such approach is valuable in terms ofrevealing and explaining the mechanisms of cause–effect relation-ship more into details; it is also easier to support with reliable andcomplete data. However, it is not adequate to disclose potentialdifferences in the impacts among different territorial units. For thisaim it is necessary that the area of interest is more or less coveredin equal detail and without ‘‘blank spots’’. If possible, a combina-tion of case study with the top-down approach would provide thenecessary detailed information and in this regard be the mosteffective.

Most TIA approaches refer to concepts such as territorialcohesion and territorial potentials, which are related and adjustedto the presently prevailing European Union discourse on policymaking and assessment procedures, but this does not limit the useof the method to EU context. In principle, the method can be usedwhenever an interrelation between a specific policy (with a set ofassociated measures) is to be investigated in terms of its impactson objectives related to spatial (territorial) development and theterritorially differentiated results are required. The governmentallevel of policy can also vary (it can be European, national, regionalor even local). Further more, its strong link to sustainabledevelopment components also makes it universally applicable.

TIA can cover a wide set of impacts, focusing the evaluation ondifferences in impacts’ territorial distribution, and thus includesterritorial dimension in the evaluation approach. In terms ofcontents, in all reviewed approaches the analysis is limited to thelinear measure–effect relationship and linear operations areapplied to synthesise the results. As such, they follow the logicof classic economic evaluations and could easily be replaced by, forexample, cost benefit analysis if the territorial issues wereintegrated on either side of the equation. Such approach ishowever not consistent with the interrelational logic of territorialcohesion concept and misses an important opportunity to considernon-linear, circular logic of interrelations among its basicconstituents (economic, social and physical). These are incom-mensurable and therefore not allowed to directly aggregate(Martinez-Alier, Munda, & O’Neill, 1998; Uusikyla, 2009). Territo-rial cohesion as a result of complex interactions cannot beinfluenced by public policies directly but only through influencing

social, physical and economic systems in a way which is coherentwith the other two systems. Following this interpretation, neithereconomic nor any other sectoral perspective of assessing policyimpacts is adequate from the territorial cohesion perspectivesince they only assess their impacts on their own primaryobjectives (economic, socio-cultural or physical–environmental)while neglecting that these measures have differentiated impactson each of the three systems (S, E, P; Schnellenbach, 2005). As such,they are lacking the true strategic dimension, where each of thesethree dimensions is interrelated with the other two: as the cause orthe target of the impact (Radej, 2008).

Also, the policy making process is in reality far from a linearflow of rational decision making (Dalal-Clayton & Sadler, 2005) buta complex and uncertain process of several feed-back loops andside effects. An impact assessment procedure, if it is to be a policydevelopment support tool, must take this into account. In theiroriginal approach Leopold, Clarke, Hanshaw, and Balsley (1971)argue that the synthesis conclusion is the task and responsibility ofpolicy-makers and explicitly reject the summation of policyimpacts into aggregate impact indicator. Many impact assessmentprocedures follow the same fragmented approach to policyevaluation, such as EU’s Impact Assessment Guidelines (CEC,2005b, 2009b), Better Regulation Action Plan (CEC, 2002),territorial impact assessment (ESPON 3.2, 2006f), The EuropeanStrategic Environmental Assessment Directive (European Parlia-ment, Council, 2001), and several others. However, as Radej (2008)argues, without synthesis the assessment fails to provide usefulinput for policy makers and may even enable the manipulative useof the results.

The TEQUILA simulation package, developed by Camagni inESPON 3.2 (ESPON, 2006f; Camagni, 2006a, 2006b), mostexplicitly builds on a territorial cohesion concept. The model ismultilevel: firstly, general impacts are assessed; later on they arereviewed on regional level. As such, it was considered as anappropriate starting point for developing our approach. However,by treating the impacts as a one-way cause–effect relation and byusing summation for aggregating the results it applies a similarlinear perspective to territorial cohesion as other approaches. It isalso very data and knowledge demanding and is therefore difficultto be expected to be easily applicable in a real policy makingcontext.

3. The aim and hypotheses of the research

The aim of the presented research was to develop an approachand tools for TIA which would build on interrelational concept ofterritorial cohesion and could deliver useful information for thepolicy making process.

The hypothesis is that the assessment conclusions derived froman analytical (micro)observation of a disaggregated problem aredifferent from those resulting from a two phase (analytical-synthesis) approach. The assessment based only on analyticalphase gives incomplete and potentially misleading information.Upgrade by a relevant synthesis the assessment provides morecomplete and policy making relevant information.

The second hypothesis refers to the pilot case of the assessment.Prediction is that Slovenian energy policy is not coordinated withterritorial cohesion objectives. Policy measures have not only theintended impacts on the targeted objective, but also secondaryimpacts on various territorial objectives, which can be positive aswell as negative.

The impacts of individual measures are territorially heteroge-neous. Considering only an average impact across the nationalterritory may conceal important information on negative as well aspotentially positive impacts in certain regions which should haveimplications for policy development.

Fig. 2. Hypercube concept of TIA. Source: ESPON 3.1, 2004b, p. 55


4. Method

The starting point for development of TIA method was theapproach first proposed by ESPON project Spatial Scenarios andOrientations (ESPON 3.2, 2006f) and followed by others (Battis &Kersten, 2008; Camagni, 2006b), which explains territorialcohesion by three dimensions of territorial efficiency, qualityand identity. These can also be presented by Venn diagram as aresult of overlapping and interrelating between socio-cultural (S),physical (P) and economic (E) scopes (Fig. 1). Territorial efficiency,shorter Te, presents the intersection between P and E (P\E),territorial identity (Ti; S\E) and territorial quality (Tq; P\S).

As Lozano (2008) presented there are more ways of sustain-ability (thus also territorial cohesion) graphic representation suchas Venn diagram, concentric circles or planning hexagon. Regard-ing the author all seem to lack conceptual coherence, intercon-nectedness among the aspects, completeness, trans-disciplinarilyand dynamic time dimension. The later problem author tried tosolve by introducing the tunnel-kind of shape – rotating cylinderwhich would add time dimension. Nevertheless, for the purpose ofTIA we have chosen Venn’s diagram among the others due to itsgood representation of overlapping sustainability elements andbecause of no need for time sensitive representation. Graphicalillustration is welcome since abstract concepts are sometimesdifficult to express clearly and compactly only with words (Carney &Levi, 2002). Venn’s diagram is a traditional and universallyunderstood concept for representing non-linear interrelations.

Territorial impacts are in this approach interpreted as the‘‘hypercube’’ structure; a three dimensional interpretation of atraditionally two dimensional Leopold matrix (Leopold et al.,1971), a widely used evaluation tool. One dimension is defined bythe measures of sector policy, the second one by the territorialobjectives and the third one by the parameters of territorialcontext (i.e. territorial units) (Fig. 2).

The main methodological issues to be resolved within thisresearch concern the complexity of the territorial cohesion conceptin terms of territorial and intersectoral relations and the question of(dis)agreggation of the problem for purposes of scientific observa-tion and synthesising the results for purposes of policy development.

Scientific approach uses analysis and observation of smallersub-problems for understanding of the complex phenomena.However, the applicability of TIA in policy making processes alsorequires synthesis, which articulates the results into a messagecomprehensible to a far larger audience than those familiar with

Fig. 1. Venn diagram of territorial cohesion (TC). Source: ESPON 3.2, 2006f.

sophisticated multivariate analyses (Hamez, 2005). In our pilotstudy TIA approach is structured in two phases: analytical andsynthetic (inter-relational). The analytical level of observationenables the evaluation of individual policy measures in terms oftheir contribution towards different territorial objectives and theinsight into expected consequences in specific territorial contexts.The approach in this phase follows the ‘‘hypercube’’ structureproposed in ESPON 3.2 project (ESPON, 2006f). Each of theintersecting cubes therefore represents an impact of one policymeasure on one territorial objective in one territorial unit. Each ofthese impacts was described by indicators, examined andevaluated. The majority of indicators and the assessment methodwere qualitative. The indicators were used as a guideline for theexperts and to provide a more coherent interpretation of theresults. They also served as an indication of the existing situationand differences among the regions. Quantitative use of indicatorswas not possible mainly due to difficulties in defining thresholdsfor majority of the indicators. The indicators have been selectedfrom previous studies and assessments.4 The cooperating expertsconsidered each indicator’s data availability, frequency of use,referential period and content suitability. Finally, 19 indicatorswere selected as suitable. A Delphi procedure with a group ofexperts5 was used to arrive at evaluations of individual impacts.Similar qualitative methods are often applied for the exploration ofcomplex systems with a weak knowledge about indirect relationsbetween input and output (Jacob et al., 2008; Nijkamp & Van Pelt,1989; Schindegger & Tatzberger, 2004). A qualitative approach alsoavoids a bias (usually towards economic aspects) resulting fromunequal data availability and difficulties in applying quantification

4 Indicators’ list is based upon the indicators used in the national regulation on

reporting of spatial development progress (not applied in practice), methodology of

spatial and development planning integration, study on indicator measuring spatial

development on national and regional level, year reports of national Institute of

Macroeconomic Analysis and Development, environmental indicators developed by

The Environmental Agency of the Republic of Slovenia, methodology of measuring

development discrepancies in Slovenian regions, etc.5 Members of the expert group had the following expertise and qualifications:

environmental, territorial, strategic impact assessments (landscape planner),

environmental strategic impact assessment (chemical engeneer), economic

evaluation (economist), energy policy (machine engeneer), regional planning

and regulatory impact assessment.

Fig. 3. An example of evaluation form.


consistently to all impacts (Hamez, 2005). Qualitative values werethen translated to a common 5-point scale for the needs of furtherprocessing. Such semi-quantification is a commonly used alterna-tive solution to full quantification (Nijkamp & Van Pelt, 1989).However, the rigorous interpretation of such a scale requires thatthreshold values are defined. Because thresholds were in our casedescriptive, the use of the obtained numbers is limited: theycannot for example be used for quantitative estimation of impactsbut are still useful for comparing and synthesizing the results.

The assessment procedure was supported with an on-lineevaluation tool. By entering the project site the evaluators couldsimply access available information on policy measures, descrip-tion of territorial cohesion objectives with indicators and theirvalues and trends, and description of territorial units. Their taskwas then to identify and evaluate impacts in any of the measure/objective/territorial unit combination. Each impact was assigned avalue from �2 (strong negative impact) to +2 (strong positiveimpact). They were asked to give a descriptive argumentationwhich was also stored in the on-line evaluation form. An exampleof such form is presented in Fig. 3. Each expert performed theevaluation individually. After completion of the first round, wechecked the results for consistency and convergence. Theevaluators met in a workshop, where they verified the validityof their assessments and clarified extreme deviations. Then theassessment session was repeated.

The result of this analytical level of the assessment was aplethora of partial information, requiring some sort of synthesis.This part of TIA is based on the trans-disciplinary nature of theterritorial cohesion, and its three main components: territorialefficiency, territorial identity and territorial quality (Fig. 3). Thesynthesis is done with a mezzo-matrix approach of synthesisproposed by Radej (2008). This approach is an improved version ofthe Leopold–Ekins–Medhurst (LEM) matrix used in the assessmentof structural funds (Ekins & Medhurst, 2006). This aggregationapproach takes incommensurability of scopes into account and is inanalogous forms applied in various standard impact assessmentprocedures, such as strategic impact assessment (EuropeanParliament, Council, 2001), the territorial impact assessment

(ESPON 3.2, 2006f), and assessment of the contribution of the EUstructural funds to sustainability of regional development (GHK,PSI, IEEP, CE, & National Evaluators, 2002). In these approachesincommensurability is respected only for objectives but not forpolicy measures, although these are also not neutral in scope. Radej(2008) therefore suggests that not only target (territorial objectivesin case of TIA) but also source (policy measures) of impacts shouldonly be aggregated partially – within each scope. The Leopoldmatrix was therefore vertically and horizontally reduced to threescopes of sustainability (socio-cultural, physical and economic)which also fit within TIA concept. Assessed impacts can beaggregated within each of these three scopes but not betweenthem. The matrix transformation requires distribution of the policymeasures and territorial objectives in three scopes. In case of acomplex measure or objective its primary aim is used as thecriterion for grouping. The aggregated assessment score is obtainedby averaging marks of individual impacts within each scope.

With this procedure we obtain the square input–output matrixof Leontief (1970), which shows transformations of inputs (policymeasures) through direct (primary) and indirect (secondary)impacts into outputs (territorial objectives). This rearrangementshifts the focus of evaluation from the relationship betweenpolicies and their direct goals on the relationships (overlaps)between different assessment scopes which exactly corresponds tothe concept of territorial cohesion.

The matrix can be further synthesized in a correlation matrix.Correlation matrix compacts obtained results so that it links one-way relations between two scopes, such as E\P, with itssymmetrical opposite and P\E, to obtain bi-directional orreciprocal relations which explain how different scopes worktogether. Diagonal elements of the matrix explain how policymeasures of one scope impact territorial objectives of the samescope (E\E, S\S, etc.). These elements are not of primary interestfor observing territorial cohesion. The non-diagonal fields of thematrix can be interpreted as main elements of territorial cohesion.For example, territorial quality is described by the impact of(primarily economic) measures on (primarily) physical territorialobjectives AND by the impacts of physical measures on economic

Table 1Leontief matrix for territorial impact assessment.

Outputs (territorial objectives)

Inputs (sector policy measures)

Economic (E)

Objective 1

Objective 4

. . .

Socio-cultural (S)

Objective 2

Objective 5

. . .

Physical (P)

Objective 3

Objective 6

. . .

Economic (E)

measure a

measure d

. . .

E\E

Intrasectoral assessment (effectiveness)

E\S

Intersectoral assessment (indirect impacts)

E\P

Socio-cultural (S)

measure b

measure e

. . .

S\E S\S

Intrasectoral assessment (social impacts)

S\P

Physical (P)

measure c

measure e

. . .

P\E P\S F\F

Intrasectoral assessment (environment)

Source: Golobic et al., 2008.


objectives (Tq = S\P & P\S); by analogy Ti = S\E & E\S andTe = P\E & E\P (Tables 1 and 2). High and balanced scores for Tq, Tiand Te indicate strong contribution of the policy towards territorialcohesion.

5. Pilot case: Slovenian energy policy

This model for TIA was tested on a pilot case in the nationalpolicy making context. The first axis of the TIA hypercube model istherefore in our case represented by Slovenian energy policy andits measures. Present Slovenian energy policy is influenced by EUEnergy policy (CEC, 2006a, 2006b, 2007a, 2007c) and defined bythe Energy Act (1999), The Resolution of National EnergyProgramme (ReNEP, 2004) and respective regulation. Evidenceof weak implementation of national energy programme and needto renovate this document were main arguments for the decisionto use it as an object of assessment.

The decision is supported by the strong interrelation betweenenergy and spatial policies, also recognized by the TerritorialAgenda (BMVBS, 2007b, Article 22), which mentions two majorgoals of territorial cohesion related to energy:

- Development of decentralized, efficient, safe and environmen-tally friendly production of energy from renewable resources, thepotential of which is underused;

- Improvement of networks and coordination of the condition ofthe energy sector with the purpose of better use of regionalpotential which can create development opportunities especiallyin the countryside.

The pilot application of TIA was expected to confirm thehypotheses which were formulated following the comments fromthe spatial development and energy policy makers and energyexperts. These are:

- The coordination of energy and spatial policies is weak,- Many of the energy policy measures do not effectively achieve

their primary objectives,

Table 2Correlation matrix concept.

Outputs on the territory

Inputs of energy policy

Socio-cultural Physical

Economic measures Ti, territorial identity

S\E and E\S

Te, territorial efficiency

E\P and P\E

Socio-cultural

measures

Tq, territorial quality

S\P and P\S


- Energy policy measures have diverse impacts; the targeted onesas well as unexpected; positive as well as negative,

- The impacts of energy policy objectives are not territoriallyhomogeneous,

- The structure of Slovenian spatial policy objectives is incoherentand thus not very useful for assessment purposes.

According to ReNEP, long-term goals of the energy policy arereliable supply, competitive market and preservation of theenvironment. These are to be reached through several measures,which were used as an input for the model. Description of everymeasure consists of 13 elements: name, label, description, targets,target group, level of implementation, sources for implementation,schedule, territorial frame, preliminary impact assessment,remarks, date of inscription and sources for it. From the initiallist of 69 measures,6 27 were selected as relevant, having potentialterritorial dimension. Some of the measures with insignificant yetimportant influence on the territory were included in theevaluations as ‘‘measure clusters’’ such as mechanisms fortechnical and reliable operation of energy networks, developmentof modern, and safe and transparent energy market. Fifty-sixpercent of chosen measures is environmentally oriented, 14% focuson market competitiveness and 30% on reliable supply. Measureswere grouped according to their main focus of intention to threepillars of sustainable development (see Table 3).

The second axis of TIA hypercube was described by theterritorial cohesion objectives which were taken from SpatialDevelopment Strategy of Slovenia (Ministry of the Environment,Spatial Planning and Energy, 2004). These represent nationalpolicy framework, and are also consistent with a more generalterritorial cohesion concept as defined by European SpatialDevelopment Perspectives (CEC, 1999), Territorial Agenda(BMVBS, 2007b) and the Leipzig Charter (BMVBS, 2007a). Theobjectives were grouped according to their main relation to threesustainability principles: economic, socio-cultural and physical(environmental) (Table 3) to formulate the foundation for thefurther synthesis with regard to the concept of territorial cohesion.Each of these three principles was additionally described by a set ofindicators. The choice of indicators was based on criteria ofrelevance for territorial cohesion objectives, sensitivity forterritorial impacts and data availability. Values of these indicators

6 Measures beside national energy policy originate in supporting national action

plans and programmes such as national action plan for energy efficiency, statues as

for example rules for the rational use of energy during the heating and cooling of the

buildings and heating up the hot running water, non-governmental initiatives and

programmes, investment plans of energy suppliers, financial incentives to support

use of renewables and energy efficiency etc.

Table 3Distribution of objectives of the Slovenian spatial policy, indicators and energy policy measure among the pillars of sustainable development.

Development objectives Indicators Energy policy measures

Economic aims (E)

- C01 rational and effective spatial

development

- C03 increased competitiveness of

Slovenian towns in Europe

- C06 development of complementary

functions of rural and urban areas

- C07 integration of infrastructure

corridors with the EU infrastructure

systems

- GDP per capita

- Share of unemployed age 50 and up

- Index of development deprivation

- Index of daily commuting

- Gross added value of the companies

per capita, EUR

- Gross value of investments into capital

assets in mio EUR

- Index of development deprivation

- Current expenditure for the

environmental protection per km2

ReNEP 01.01.01 Long-term production of lignite in the

Velenje mine

ReNEP 01.02.01 Long-term production of electricity in

Nuclear Power Plant Krsko

ReNEP 01.04.01 Construction of hydro power-plant on

the lower Sava river

ReNEP 01.04.02 Construction of the pumped–storage

hydro power plant Avce and Kozjak

ReNEP 01.05.02 Investments into new production units

in Zasavje

ReNEP 02.03.01 Enabling the access to cross-border

transmission possibilities

ReNEP G2 Development of the modern, safe, transparent

and efficient energy market

ReNEP G3 Provision of the earth gas market liberty

Socio-cultural aims (S)

- C02 polycentric development of the

network of cities, towns and other

settlements

- C05 harmonious development of areas

with common spatial development

characteristics

- C10 cultural diversity as the foundation

of the national spatial identity

- Share of unemployed age 50 and up

- Index of number of newly built

housing units

- Motorization level – number of

automobiles per 1000 people

- Share of unemployed youth among

all unemployed

- Number of beds in old people’s homes

per 1000 people age 65 and up

ReNEP 02.01.01 Rules for defining the market prices and

the redemption of the electricity from the qualified

producers

ReNEP 02.03.03 Definition of the share of each production

source for the electricity and the way of its representation

ReNEP 03.02.02 Rules for the rational use of energy during

the heating and cooling of the buildings and heating up

the hot running water

ReNEP 03.07.02 Project Energy consulting for inhabitants

ReNEP 03.12.01 Foundation of the Faculty of Energy

Technology

ReNEP 03.12.02 Project Children are changing the energy

culture

ReNEP 03.14.01 Non-governmental organization in the field

of energy provision

ReNEP 03.06.16 programmes supporting transparency,

openness, education, promotion and qualification process,

pilots projects

ReNEP G1 Mechanisms of guarantying the technically

reliable functioning of the energy network and the increase

of the energy provision quality

Physical aims (P)

- C04 high-quality development and

attractiveness of cities, towns and

other settlements

- C08 prudent use of natural resources

- C09 spatial development harmonized

with spatial limitations

- C11 nature conservation

- C12 environmental protection

- Density of road network

- Share of highway length compared to

the whole length of Slovenian highways

- Share of housing units using heating system

- Use of potable water in litres per capita

- Share of area, promulgated as Natura 2000

- Investments into protection of biological

variety and landscape protection per km2

- Share of the waste, deposited in the waste

disposal

- Collected waste per capita in tonnes

ReNEP 03.01.02 Action programme to decrease the green

house emissions by 2012

ReNEP 03.03.03 Crediting environmental investments

ReNEP 03.06.01 Financial incentives for the investments’

measures for the use of renewable sources in the

households in years 2007 and 2008

ReNEP 03.06.02 Project GEF–Removing the barriers for the

increased use of biomass as an energy source

ReNEP 03.11.01 Obligatory local energy concepts

ReNEP 03.02.08 Regulation claiming the energy efficiency

of non-industrial buildings

ReNEP 03.02.05 Financial incentives for increasing the

energy efficiency of existing buildings and the sustainable

construction of housing units and buildings in the service

sector and industry

ReNEP 03.06.12 Financial incentives for the energy efficient

systems for the heating of households and service sector’s

buildings

ReNEP G4 International projects such as technological

platforms for the increase of the renewables share in the

production of the electricity and in the provision of the heat

ReNEP G5 Assessment of the fossil fuels used for the heating

for all users

Source: SDSS – Spatial Development Strategy of Slovenia, 2004; see Footnotes 4 and 6.


were collected for four consecutive years (2004–2007) to indicatetrend, as for example in Nijkamp and Van Pelt (1989).

The third axis provides territorial context for the abstractrelation between the policy measures and territorial cohesion.Although a single unit is certainly not equally well adapted forevaluation of each impact and can be too generalizing (Inkinen,2005), this was considered an optimal compromise betweenensuring territorial sensitivity of the model and data availability.

The same unit (NUTS3 regions) was used for all impacts also withan aim to provide a universally (across policy sectors) useful andadministration applicable model. It is a solution accepted also inother cases (ESPON). Slovenian NUTS3 level is presented with 12regions which also represent development regions in case of EUfunds’ policy implementation. Although these regions do not haveexecutive competence, national policy, such as NEP measures areoften designated and delivered according to the regional principle

Table 4Average estimations which entered the further synthesis process.

Measures\Objectives C01 C02 CO3 C04 C05 C06 C07 C08 C09 C10 C11 C12

ReNEP 01.01.01 �0.09 0.22 0,03 �0.07 0.12 0.01 3.01 �0.6 �0.05 0.06 �0.17 �0.76

ReNEP 01.02.01 0.88 �0.09 0.45 �0.27 �0.2 �0.25 0.48 0.4 �0.13 �0.04 �0.22 0.58

ReNEP 01.04.01 0.74 0.17 0.14 0.16 0.11 0.3 0.14 0.39 0.09 �0.1 �0.23 0.44

ReNEP 01.04.02 0.17 0.01 0.06 �0.1 0.03 0.28 0.29 0.25 0 0 �0.23 0.32

ReNEP 01.05.02 0.51 0.29 0.06 �0.04 0.11 0.03 0.01 0.03 �0.04 0.04 �0.15 0.13

ReNEP 02.01.01 0.16 0 0.49 0.32 0.16 0 �0.17 0.61 0 0 0.05 0.05

ReNEP 02.03.01 0.82 0.13 0.49 0 0.16 0 1.94 �0.41 0 0 �0.17 �0.17

ReNEP 02.03.03 0.16 0 0.16 0.16 0.16 0.16 0.16 0.65 0 0 0.16 0.32

ReNEP 03.01.02 1.13 0.49 0.49 0.82 0.32 0.49 0.49 1.47 0.49 0.65 0.32 1.41

ReNEP 03.02.02 0.86 0.27 0.86 1.43 0.59 0 0 1.24 0.27 0.39 0.59 1.54

ReNEP 03.03.03 1.05 0.49 0.9 1.2 0.49 0.65 0.32 1.45 0.32 0.16 0.98 1.78

ReNEP 03.06.01 0.98 0.16 0.39 0.56 0.49 0.49 0 1.62 0.65 0.16 0.42 1.31

ReNEP 03.06.02 0.94 0.45 0.49 0.68 0.72 1.08 0.14 1.32 0.42 0.35 0.11 1.15

ReNEP 03.07.02 0.65 0.32 0.32 0.98 0.16 0.16 0 0.82 0.16 0 0.32 1.29

ReNEP 03.11.01 1.45 1.08 1.08 1.29 0.98 1.29 0 1.55 0.58 0.26 0.56 1.45

ReNEP 03.12.01 0.51 0.9 0.56 0.12 0.32 0 0.2 0.49 0.32 0 �0.17 0.32

ReNEP 03.12.02 0.32 0.16 0.16 0.32 0.16 0.16 0 0.65 0.16 0.33 0.49 0.65

ReNEP 03.14.01 0.5 0.16 0.32 0.49 0.16 0.32 0 0.65 0.16 0 0.49 0.98

ReNEP 03.02.08 1.22 0.47 0.86 1.24 0.27 0 0 1.35 0.27 0.19 0.59 1.35

ReNEP 03.06.16 0.82 0 0.16 0.32 0.16 0 0 1.13 0.23 0.16 0.65 1.13

ReNEP 03.06.12 1.06 0.19 0.86 1.16 0.19 0.39 0 1.16 0.39 0.19 0.59 1.18

ReNEP Gl 0.82 0.32 0.56 0.98 0.32 0.16 0.98 0.43 0.32 0 0.16 0.49

ReNEP G2 0.65 0.32 0.65 0.16 0 0.16 1.15 0.82 0 0 0.49 0.82

ReNEP G3 0.33 �0.17 0.38 0.49 0.2 0 1.31 0.32 0 0 0.16 0.65

ReNEP G4 0.97 0.16 0.32 0.32 0.49 0.98 0.32 0.98 0.32 0.1 0.22 0.65

ReNEP G5 0.65 0.49 0.49 0.98 0.42 0.65 0.16 1.31 0.65 0.49 0.88 1.62



(i.e. following the cohesion indicators of the regions and theregional development plans). Every region is described with 12elements: code, name, regional central town, list of municipalities,basic statistical data (surface, population, etc.), short description,table of chosen spatial development indicators, a vision and afeature of regional development policy for two EU financial periods(2002–2006, 2007–2013), data about the position of the energysector in the region.

These three sets of inputs with relevant descriptionstherefore served as a framework and knowledge base forevaluation of individual impacts (measure/objective/territorialunit combinations). The evaluation procedure could theoretical-ly start from each of these three components, but in general weproposed to begin by choosing one policy measure. To betterillustrate the procedure we present one example of suchevaluation more into detail. After choosing the measure (x)to be first examined (for example long-term production of

electricity in Nuclear Power Plant Krsko), the evaluator consideredwhether this measure has an impact on the objective y

(for example rational and effective spatial development) in regionz (for example Zasavje). After consulting the available informa-tion on all three components (if considered necessary) he/shegave the estimation (for example 1, mild positive impact) andexplained it (for example: rational and effective solution since no

new land is needed for the production of such large amount of

electricity). Then he/she moves on to the next region. Afterevaluating all regions he/she then goes on to the next objective,until all x–y–z combinations have been examined.

The results expectedly differ across measures and acrossregions. An impact in respective region is for example positivedue to job preservation, yet negative since it limits other moreecologically oriented economic activities. The impact on objectiveof polycentric development was for example in average negativebut was positive for nearby regions since it offers qualified jobs forinhabitants. For other regions it was evaluated as negative since itwill not boost the use of more alternative sources. Altogether thismeasure received the largest number of negative scores andprevailingly influences only one region. Overall the measure hasmildly positive impact on the territorial cohesion but achievement

of seven objectives can be potentially hampered due to imple-mentation of this measure: polycentric development, high qualitydevelopment and attractiveness of cities, harmonious develop-ment of areas with common spatial development characteristics,development of complementary functions of rural and urban areas,harmonized spatial development, cultural diversity and natureconservation. On the contrary this measure will positivelyinfluence meeting the goals of rational and effective spatialdevelopment, increased competitiveness of Slovenian towns,integration of infrastructure corridors, prudent use of naturalresources and environmental protection.

Evaluators did not always agree on extent or even directionof impacts. In case of above mentioned measure this happenedfor 8 out of 12 objectives. The Delphi workshop revealed thatthese discrepancies occur due to the background of theevaluators, different referential frameworks, but also due todifferent interpretations of measures and objectives. Some ofthese disagreements were levelled out after the workshop in thesecond round of evaluations, but several persisted, indicatingconflicting nature of a measure. Since they are considered to be alogical consequence of the complex nature of policy-territoryinterrelations, they were not assumed to restrict the validity ofthe results.

After the second round of evaluation, the 6 estimations for eachimpacts (one by each evaluator) were averaged and entered thesynthesis phase (Table 4).

6. Results

The results of the analytical level of evaluation do not confirmthe hypothesis of weak coordination between sector and spatialpolicies. 65% of all evaluated impacts are neutral or positive. 8% areestimated to be only and very positive. Several energy policymeasures were therefore assessed as having positive impact. Theseare mostly the indirect measures, such as administrative regula-tions and financial supports, and the impacts are not regionallydifferentiated. The most positive impact is expected on territorialobjectives, which are related to the settlement network and urbanareas:

Table 5Leontief matrix of energy policy impacts to the territorial elements of Slovenia.



Economic Socio-cultural Physical

Economic measures 1 0 0

Socio-cultural measures 1 0 2

Physical measures 2 1 2


Fig. 4. Level of territorial cohesion achieved, by components.Source: Golobic et al.,

2008; designed by N. Marot.


- Increased competitiveness of Slovenian cities in the Europeancontext,

- Balanced development of areas with common spatial-develop-ment characteristics,

- Qualitative development and attractiveness of cities and othersettlements,

- Development of a polycentric settlement network and- Rational and effective spatial development.

Eleven percent of the relations will likely cause no effect. Only3% of the impacts energy policy is likely to obviate achievement ofthe spatial development objectives, especially environmentallyoriented ones, such as nature conservation, environmentalprotection and prudential use of natural resources. There weresix measures out of 26 identified as having some negative impact.

As assumed, the majority of the measures do not influence justone objective but several and often in both, negative and positivedirections. Such relations occurred in 13% of the evaluatedmeasure–objective pairs. The most controversial impacts arecaused by the projects developed on a specific location whichdifferent evaluated assessed either positive or negative.

The hypothesis that the impacts of energy policy measures arenot territorially homogeneous was only partly confirmed. Al-though intuitively the assessors would agree with the hypothesis,they were not able to find evidence for regionally differentiatedimpacts for about half of the measures. This was the case for mostadministrative and financial measures, where the cause–effectchain is blurred and impacts may occur indirectly. For othermeasures, the level of impact in regions differs due to level ofeconomic development, the importance of energy sector inindividual region and the scale of single measure.

The synthesis based on the relational mezzo matrix (Table 5)shows positive or zero impact of the energy policy on objectives ofspatial development strategy which is consistent with findings onthe analytical level. However it also reveals rather strongimbalance. The intrasectoral impacts are stronger within thephysical scope, moderate within the economic one and absentwithin the socio-cultural scope. Strongest impacts come frommeasures targeting physical system as they have strong impactalso on the economic scope and moderate impact on social scope.Economic measures have weakest impacts: only a moderate one ontheir own scope while impacts on the other two scopes are absent.Measures of socio-cultural scope have moderate impact oneconomic and strong impact on physical scope. Physical andeconomic objectives are relatively well influenced, while the socio-cultural scope is barely affected.

Table 6Correlation matrix of energy policy impacts on territorial elements in Slovenia*.



Socio-cultural

Economic measures Ti, territorial identity S\E and E\S = (1, 0) very

unbalanced impact of energy policy in favour o

Socio-cultural measures

Source: Golobic et al., 2008.*(2, 2) = strong correlation between territorial elements; (2, 1 or 1, 2) = moderate; (1, 1

The correlation analysis (Table 6) indicates an even lessfavourable situation with only very weak to weak positive impactof NEP on the elements of territorial cohesion as shown in Fig. 4.The most outstanding imbalance is caused by priority of territorialeffectiveness leaving territorial quality and identity behind.

An important aspect of territorial cohesion is regionaldistribution of impacts. Here, the analytical level of analysisidentifies two regions as being strongly affected, with another fourbeing in the middle group, while there is little or no impact in theremaining six. In all the regions of the first two groups energyinfrastructure is presently of high importance.

Relational–correlational level of assessment slightly compro-mises these results. In general, regional differentiation of impactsis very weak, while a different region comes up as a ‘‘winner’’ interms of positive impacts on socio-cultural system and onterritorial quality as a result of stronger integration of physicaland socio-cultural systems. These results indicate regionalinsensitivity of the national energy programme tending to evenwiden regional disparities. As such it does not contribute to one ofthe main aspects of territorial cohesion.

7. Discussion and lessons learned

The pilot application of the proposed TIA approach improvedinformation delivery for policy makers in several aspects. Althoughthis is difficult to empirically verify, the feedback we got from thepolicy makers involved as observers and participants in the project,was favourable. The first aspect that improves the information forpolicy makers is the data base with transparent and easily

Physical

weak correlation,

f economy

Te, territorial efficiency E\P and P\E = (0, 2) weak

correlation, unbalanced impact of energy policy

in favour of economy

Tq, territorial quality S\P and P\S = (1, 2) weak

correlation, balanced impact

or 2, 0 or 0, 2) = weak; (1, 0 or 0, 1) very weak; (0, 0) = no correlation.


retrievable information for each impact. The data base can besearched starting from any measure, territorial objective or regionof interest. An overview of the measures for example indicates thatmeasures of replacing the fossil fuels with renewables are nothaving desired effect; similar is true for measures meant to boostenergy efficiency. The data base is open, allowing policy makers toadd new or alternative measures and test them by the sameprocedure.

The results have also shown that the synthesis of the resultsbrings not only a quantitative difference in terms of shorter, clearerinformation, which is easier to comprehend, but brings also aqualitative leap. In the presented case the most obvious conclusionfrom the analytical level is that most of the impacts of theSlovenian energy policy can be considered (slightly) positive andonly a few need caution due to potentially negative impacts.Further findings show that the national energy programmeintegrates the environmental aspect in a number of its measures.These disaggregated expert assessments could be summed up in arather satisfactory picture of impacts of national energy policy onterritorial objectives. Put into the strategic perspective thesefindings lose some of the initial appeal. Relation and correlationsteps of synthesis reveal the main systemic weakness of NEP: itslow correlation between the scopes and therefore weak compo-nents of territorial cohesion; especially the identity and qualityones. One of the possible explanations for this lack of considerationfor socio-cultural scope is that policy makers have not yetinternalized the social objectives in their mentality as they havedone with the environmental ones. The question can here be askedwhether the energy policy should at all consider the social wellbeing or should it just contribute to the economic progress throughimprovement of its own sector? The perspective of sustainabledevelopment and territorial cohesion requires that every nationalpolicy should consider the development integrally and should aimbeyond the own sectoral scope (Radej, 2008). Another lessfavourable finding from the synthesis level is that the observedenergy programme does little to lessen the regional discrepancies– in several aspects it even widens them.

We can conclude that the answer to a pertinent question ofpolicy assessment ‘‘to synthesize or not to synthesise’’ is ‘‘yes’’.Nevertheless, the disaggregated individual assessments are stillimportant – not only as a necessary step in producing knowledgeto be further synthesized, but also when it comes to optimizationof individual policy measures. The analytical phase also identifiesthe measures and territorial unit(s) with potentially negativeimpacts, where amendments are especially necessary. All thisinformation can be blurred in the synthesis. It is also important toprovide the argumentation and thus transparency and credibilityof the assessment.

If we accept a synthesis to be a necessary part of the assessment,the relevant question would then be ‘‘how’’? In general, anymethod that recognizes non-liner interrelations and can beadjusted for territorial sensitivity could be used; for examplesome approaches to sustainability assessment; and there is noobstacle to link the territorial cohesion concept to these methods.The strengths of the proposed approach are that it respects theincommensurability of different scopes (E, S, P) throughout thesynthesis procedure and observes their interrelations. As such, itconsistently follows the idea of territorial cohesion and its idea ofinterrelations.

The vagueness of the territorial cohesion concept, which wealready discussed in the introduction chapter, also implies aweakness of the proposed method since it makes difficult torigorously and unambiguously define the criteria for distributionof measures, objectives and indicators among the groups: Ti, Te orTq. The experiment described in this paper reveals probably themain difficulty in operationalization of territorial cohesion concept

through TIA. Partly this could be improved by sensitivity testing,involving several runs of the process with alternative distributionsamong the groups. This would especially made sense if there wasdisagreement between the stakeholders regarding this issue,which was not the case in our evaluation. Nevertheless, themethod is not restricted to territorial cohesion but it can be appliedto any similar concept involving multi level and/or trans sectoraldimensions. Such strategic insight into sector policy/territorialcohesion relation should help policy makers to (re)orient theirconceptual view on policy in general. This is a sort of informationthat they would hardly get from a more traditional impactassessment approach. However, there are some conditions thatmust be fulfilled to rally make use of such information. The firstone is a close intertwinement between the assessment and policymaking procedure (Bennett, 2004; BMVBS, 2007a; CEC, 1997;Davoudi, 2005). However, this is an ambiguous requirement sinceit also increases the possibility that the policy process, generalpolicy climate and dominant discourses would pre-empt or permitcertain kinds of analyses (Owens, Rayner, & Binao, 2004). The roleof the impact assessments is often ‘‘strategic’’; i.e. to providejustification for decisions which have already been taken and aredriven principally by political anticipations of gain (Miles (1998)and Nelkin (1979) in Haas (2004)). It does therefore not all dependson the quality of TIA procedure, but maybe even more on generalculture of decision and policy-making.

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Dr. Mojca Golobic (Assistant Professor, Degree in Landscape Architecture): Prof. Dr.Mojca Golobic graduated and earned a Ph.D. in landscape planning at LjubljanaUniversity, Biotechnical faculty. She has since worked as a researcher at the Urbanplanning institute of the Republic of Slovenia. In 2008 she got a position as a lecturer atUniversity of Ljubljana, Department of Landscape Architecture, where she teaches thecourses on environmental planning, landscape conservation and participative plan-ning. She was Fulbright visiting lecturer at Harvard Graduate School of Design (2003/2004). Her recent research work includes leading two national projects on territorialimpacts assessment and participating in two Alpine space projects on vulnerabilityassessment and adaptation to climate change.

Dr. Naja Marot (Degree in Geography): Naja Marot has finalised Ph.D. at the UrbanPlanning Institute of the Republic of Slovenia. Focus of her research was on Slovenianspatial planning legislation and its implementation. Naja has been a visiting researcherat German Federal Office for Building and Regional Planning and a Fulbright visitingscholar at Taubman College of Architecture and Urban Planning at the University ofMichigan. She has presented papers at numerous international planning events andhas published in planning journals in Slovenia and other CEE countries. Her otherresearch focuses are regional planning, impact assessments, and renewal of post-mining areas.

territorial impact assessment: integrating territorial aspects in sectoral policies

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