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Urban Benchmarking. Urban Benchmarking in practice – a few examples 6 XI 2013 | Warsaw| Jakub Rok. Aim of the presentation. To present the process of results ’ benchmarking, basing on examples applying Polish databases and ESPON tools . . Introductory remarks.
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Urban Benchmarking Urban Benchmarking inpractice – a fewexamples 6 XI 2013 | Warsaw| Jakub Rok
Aim of thepresentation • To presenttheprocess of results’ benchmarking, basing on examplesapplyingPolishdatabases and ESPON tools.
Introductoryremarks • Examplespresentedhereshould be treated as excersisesonly - theyare not a full-fledged benchmarking process. Whatdoestitmean? • We focused on resultsassessment; tappingthefull learning potential of UB requiresanalysingtheprocesses as well. • We employedonlyquantitative data; qualitative data wouldallowus to deepentheanalysis • Eachexampleisbased on one chosen data source; usingvariousdatabasesallows to selectmoreappropriateindicators • We didn’tincludethecivicparticipationintheexamples. However, thisprocessiscrucial for shapingtheresearch agenda and collectiveinterpretation of results. Feedbacksobtainedin a consultationprocessallow for an on-goingrefinement of thewhole benchmarking activity.
UB: the central administration’sperspective I • AIM: Comparingsocio-economic performance incoal-based industrial regions whichundergorestructuration withSlaskievoivodeship • Strategiccontext: Europe 2020 • Thematic field: labour market, demography, strength of theeconomy • Reference group: similareconomicbackground + comparable role inthe national economy + Central and Eastern Europe • Ruhr area and Saararea (Germany), Ostravaarea (Czech Republic), Jiu Valley (Romania) • Selectingindicators – ESPON HyperAtlas
UB: the central administration’sperspective II • INDICATORS • Labour market • Economicallyactivepopulation (15-64 y.o.) • Unemploymentrate • Demography • Share of youngpeople (15-29 y.o.) intheeconomicallyactivepopulation • Strength of theeconomy • GDP per capita PPP • Labourproductivity PPP Referencelevel: adjacent regions Source: ownelaboration, based on ESPON HyperAtlas
UB: the central administration’sperspective II GDP per capita: typology Source: ownelaborationbased on ESPON HyperAtlas Threespatiallevels of deviation Relative to contry average Indicator’svalue
UB: theregionaladministration’sperspective I • AIM: Evaluation of theenvironment protection performanceinmajor cities of the Kujawsko-Pomorskie Voivodeship • Drawing on thechallnegesidentifiedintheNational Strategy for Energy Security and Environment andRegional Development Strategy • Thematicfields: land management, energetics, air quality, waterquality, waste management, ecologicalawareness • Reference: average performance of 4 major cities • Bydgoszcz, Toruń, Grudziądz, Włocławek • Selection of indicators – BDL database
UB: thelocaladministration’sperspective I • And now, thereal UB example – Łódź city 2011 • AIM: Provideevidence-basedarguments for themunicipal, long-term strategy of development • Thematicfields: • Attractinginvestors, Public transportation system, Civicparticipation, Communal services, Metropolitanareacooperation, Labour market, Municipally-ownedcompanies • Reference group: competetivecities • Białystok, Gdynia, Kraków, Poznań, Rzeszów, Warszawa, Wrocław • Data sources: quantitative data fromvarioussources + qualitative data fromownresearch
Conclusion • 3 BASIC MODES OF BENCHMARKING • Universal comparisons (e.g. major cities of a given region) • Comparisonsbased on a specificfeature (e.g. coal-based industry) • Distance to top performer • WHAT TO THINK OF WHEN PLANNING URBAN BENCHMARKING? • Thematic field: doesitmatchtheaim? Doesitincludethestrategiccontext? • Reference group: doesitmatchtheaim? Doesitallow for effectivecomparison? • Data: do variableshave a discrimatorypower? Aretheyreliable? • Calculations: how to improvetheindicators’ appropriateness? How to increasetheirexplanatorypower?
Thankyou for yourattention Jakub Rok j.rok@uw.edu.pl Center for EuropeanRegional and LocalStudies (EUROREG) Universityof Warsaw www.euroreg.uw.edu.pl