Intelelctual Capital of Polish Counties

Intellectual Capital for Communities in the Knowledge Economy

“Innovative Ecosystems. Joint Intangibles and Territories”

28&29 May 2015World Conference on Intellectual Capital for Communities

- 11th Edition -

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Measuring Intellectual capital at the county level in Poland

Jan Fazlagić. Poznan Univerity of Economics. Poznan. [email protected]

Robert Skikiewicz. Poznan University of Economics. Poznan. [email protected]

This research is sponsored by: National Centre for Research (NCN) „Kapitał Intelektualny powiatów polskich” and conducted in the Poznan University of Economics (ID: 2013/09/B/HS4/00476)

28&29 May 2015World Conference on Intellectual Capital for Communities

- 11th Edition -

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mailto:[email protected]


Agenda

• How we define IC of a county• Why measure IC at county level?• How to measure IC at county level?• Some empirical findings• Summary

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Why measure IC at county level? (1)

„… Villages are too small. countries are too big…”

Paul Roamer.

American Economist

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Why measure IC at county level? (2)

•Global competition (among cities)•Migrations; mobile workforce•International comparisons•Growing importance of cities in economic development

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Peculiarities of IC of a county (1)

• A public good. Its value is derived to large extent from the public investments and through interventions of public institutions,

• Created to a large extent through non-market, social relations (as opposed to market transactions in business)

• Limited and stable as far as the geographical borders of a county are concerned –non mobile

• Determined by human capital in a specific way – you cannot ’fire’ underperforming ‘HR’ (=citizens).

• Pre-determined by law regulations and objectives

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Peculiarities of IC of a county (2)

Metaphors of IC in a county:

1) A mini-state – wars, „foreign policy”

2) Business incubator – incentives, quality of the ecosystem, networking, ‘silicon valley’-mindset

3) Family business – trust, common goals, arguments

4) BA - Ba" can be thought of as a shared space for emerging relationships. This space can be physical (eg. office, dispersed business space), virtual (e.g., email, teleconference), mental (eg. shared experiences, ideas, ideals) or any combination of them. Ba provides a platform for advancing individual and/or collective knowledge

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How we define IC of a county (1)

• According to the OECD definition intangible assets are assets that do not have a physical or financial embodiment.

• Termed ‘intellectual assets’ in previous OECD work intangible assets have also been referred to as knowledge assets or intellectual capital.

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How we define IC of a county? (2)

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Definition MeasurementThe ability to comply with the requirements stated by the law on Self-Government

Schooling system (secondary level)

•Educational Value-Added

The efficiency in utilising internal and external opportunities

Tourism resources •Forest Area / no. of touristsInfrastructure•Investment in business infrastructure/revenues from start-ups

„Intellectual capital of a county is collective intelligence of the citizens”(IQ is about the problem-solving capacity so should be the definition of IC)

•IQ tests of ciitizens or … counties•HC developement•Collective intelligence

Ability to perceive opportunities and mitigate risks

How different counties behaved in comparable situations – a comparative analysis

Research methods (1)

Qualitative methods:

1. Long-term vs. short term orientation (analysis of mission statements of Polish counties)

2. Semi-structured interviews

3. Focus groups

Research methods (2)

• One-way ANOVA – conducted in order to verify if differences between results on matura of groups of counties obtained on the basis of average gross monthly wages and salaries and unemployment rate are statistically significant.

• Correlation analysis results – carried out to check how strong is the relationship between results on matura and other economic variables of a county.

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Relationship between average gross monthly wages and salaries

and results on matura at the county level

2010-2012

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Average scores of math & science subjects

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Average scores of mathematics

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Average scores of Polish language, history and civic educ. subjects

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Average scores of Polish language

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EVD of math & science subjects

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EVD of mathematics

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EVD of Polish language, history and civic educ. subjects

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EVD of Polish language

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One-way ANOVA results

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F test statistic level of significance

Average scores of math & science subjects 3.96 0.01

EVD of math & science subjects 1.16 0.32

Average scores of mathematics 3.58 0.01

EVD of mathematics 1.17 0.32


6.11 0.00


3.10 0.03

Average scores of Polish language 5.53 0.00

EVD of Polish language 2.53 0.06

Correlation analysis results 2010-2012

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Pearson correlation

coefficientlevel of

significance






0.208 0.000


0.172 0.001



Relationship between average gross monthly wages and salaries

and results on matura at the county level

2011-2013

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Correlation analysis results 2011-2013

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Pearson correlation

coefficientlevel of

significance





Average scores of Polish language. history and civic educ. subjects

0.193 0.000

EVD of Polish language. history and civic educ. subjects

0.146 0.004



Relationship between average unemployment rate and results

on matura at the county level

2010-2012

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Average scores of math & science subjects 2010-2012

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Average scores of mathematics

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Average scores of Polish language 2010-2012

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EVD of math & science subjects 2010-2012

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EVD of mathematics

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EVD of Polish language

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One-way ANOVA results

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F test statistic level of significance






6.95 0.00000002


3.47 0.00072176



Correlation analysis results

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Pearson

correlation coefficient

level of significance

Average scores of math & science subjects -0.324 0.000

EVD of math & science subjects -0.193 0.000

Average scores of mathematics -0.316 0.000

EVD of mathematics -0.167 0.001


-0.316 0.000


-0.180 0.000

Average scores of Polish language -0.303 0.000

EVD of Polish language -0.157 0.002

Summary

• Our theories about what IC is shape our measurement methods

• Qualitative research methods are underutilised – so far much emphasis is put on traditional macroeconomic measures –we need to create new methods of colelcting data on IC (e.g. qualitative analysis of information; microproductivity

• Longitudal data is more useful

Thank you for your attention!

Project’s website:Kapitalpowiatow.ue.poznan.pl

• Jan Fazlagić. Poznan Univerity of Economics. Poznan. [email protected]

• Robert Skikiewicz. Poznan University of Economics. Poznan. [email protected]



Leadership & Management

Intelelctual Capital of Polish Counties