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Local context of local government participation in the innovation networks: Evidence from Poland Cover

Local context of local government participation in the innovation networks: Evidence from Poland

Open Access
|Sep 2023

Figures & Tables

Figure 1.

Stages of the study process.
Source: The authors’ own compilation based on Gorzelany-Dziadkowiec et al. [2019]. LGUs, local government units.
Stages of the study process. Source: The authors’ own compilation based on Gorzelany-Dziadkowiec et al. [2019]. LGUs, local government units.

Variables in the equation

BS.E.WalddfSig.Exp (B)
Step 1aSLI2.1780.43924.5551−0.0018.826
BEI0.0010.0010.82210.3651.001
NRE0.0050.0041.20910.2721.005
ENE000.11810.7311
DEB−0.0010.0011.17410.2790.999
TEP00010.9911
TLG0.2250.2540.78810.3751.252
Constant−2.9861.2365.83310.0160.051

Model summary

Step−2 Log likelihoodCox & Snell R squareNagelkerke R square
1170.781a0.2060.3

List of independent variables used in the empirical analysis

No.VariableExplanation of the variableThe type of factorThe expected direction of impact on the participation of LGUs in innovation networks
1SLICooperation with SLI such as technology transfer centers, BEI, science and technology parks, technology incubators, academic business incubators, regional and local loan funds, seed capital funds, advisory and training centers, business angel networks, or chambers of commerce (no – 0; yes – 1).InstitutionalPositive
2BEIBEI per 10,000 ENE such as technology transfer centers, BEI, science and technology parks, technology incubators, academic business incubators, regional and local loan funds, seed capital funds, advisory and training centers, business angel networks, or chambers of commerce (up to 150 BEI – 1; from 151 to 250 – 2; from 251 to 350 – 3; from 351 to 450 – 4; from 451 to 550 – 5; from 551 to 650 – 6; from 651 to 750 – 7; over 751 – 8).InstitutionalPositive
3NRENRE per 10,000 working-age population such as newly registered public and private enterprises (up to 100 – 1; from 101 to 150 – 2; from 151 to 200 – 3; from 201 to 250 – 4; from 251 to 300 – 5; over 300 – 6).EconomicPositive
4ENEENE in total such as public and private enterprises (up to 500 – 1; from 501 to 1,000 – 2; from 1,001 to 1,500 – 3; from 1,501 to 2,000 – 4; over 2,000 – 5).EconomicPositive
5DEBDebt of LGU per capita (from PLN –2,000 to –1,000 [–2]; from –999 to –0.01 [–1]; PLN 0 [0]; from 0.01 to 999 [1]; from 1,000 to 2,000 [2]).EconomicNegative
6TIPTotal income of LGU per capita (up to PLN 4,500 – 1; from 4,500.01 to 5,000 – 2; from 5,000.01 to 5,500 – 3; from 5,500.01 to 6,000 – 4; from 6,000.01 to 6,500 – 5; over PLN 6,500.01).EconomicPositive
7TEPTotal expenditure of LGU per capita (up to PLN 4,500 – 1; from 4,500.01 to 5,000 – 2; from 5,000.01 to 5,500 – 3; from 5,500.01 to 6,000 – 4; from 6,000.01 to 6,500 – 5; over PLN 6,500.01).EconomicNegative
8NCIAmount of cultural infrastructure such as libraries, cinemas, theaters, and cultural centers, i.e., (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11).CulturalPositive
9PDEPopulation density of LGU territory per 1 km2 (up to 100 per 1 km2 – 1; from 101 to 250 – 2; from 251 to 500 – 3; from 501 to 1,000 – 4; over 1,000 – 5)DemographicPositive
10NINNumbers of LGU inhabitants (up to 5,000 inhabitants – 1; from 5,001 to 10,000 – 2; from 10,001 to 15,000 – 3; from 15,001 to 20,000 – 4; from 20,001 to 50,000 – 5; from 50,001 to 100,000 – 6; over 100,000 – 7).DemographicPositive
11ALMAge of LGU manager (aged over 60 years – 1; from 56 years to 60 years – 2; from 51 years to 55 years – 3; from 46 years to 50 years – 4; from 41 years to 45 years – 5; from 36 years to 40 years – 6; from 31 years to 35 years – 7; age up to 30 years – 8).ManagerialPositive
12GLMGLM (men – 0; female – 1; diverse – 2).ManagerialNeutral
13ELMELM (technical secondary school – 1; secondary school – 2; higher education – 3; higher administrative education – 4; higher law education – 5; higher economic education – 6).ManagerialPositive
14ILMPolitical ILM (politically dependent – 0; politically independent – 1).PoliticalNegative
15TLGTLG (rural municipalities – 1; urban-rural municipalities – 2; urban municipalities – 3; cities on district rights – 4).AdministrativePositive
16VOIVoivodeship (seat of LGU in one of the following voivodeships, ordered by the level of economic development from the least economically developed to the most economically developed according to Michoń [2017]: Warmińsko-Mazurskie – 1; Świętokrzyskie – 2; Lubelskie – 3; Podlaskie – 4; Kujawsko-Pomorskie – 5; Opolskie – 6; Podkarpackie – 7; Łódzkie – 8; Lubuskie – 9; Zachodniopomorskie – 10; Śląskie – 11; Małopolskie – 12; Pomorskie – 13; Wielkopolskie – 14; Dolośląskie – 15; Mazowieckie – 16).GeographicalPositive

Case processing summary

Unweighted Casesa NPercent
Selected casesIncluded in analysis184100
Missing cases00
Total184100
Unselected cases 00
Total 184100

Block 1: Method enter Omnibus tests of model coefficients

Chi-squaredfSig.
Step 1Step42.4937<0.001
Block42.4937<0.001
Model42.4937<0.001

Classification tablea

Predicted
Observed  MINPercentage correct
01
Step 1MIN01231291.1
1242551
Overall percentage 80.4

Descriptive statistics of quantitative variables

MeanStd. deviationNMinimumMaximumReference to the country average
BEI411.6995226.2526018444950864
NRE135.945753.908011844259894.56
ENE1,370.45111,757.346081841048,8701,175
DEB18.9948397.11936184−1,2002,000−82
TIP5,431.8032972.579481843,988.769,797.65,969.49
TEP5,416.95981,039.393751843,871.510,350.76,051.49
NCI2.51095.244811840591.1
PDE311.4239568.8902418493,243123
NIN11,567.467415,782.5512618420099,35015,495.58

Dependent variable encoding

Original valueInternal value
00
11

Correlation coefficient between quantitative variables

MINBEINREENEDEBTIPTEPNCIPDENIN
Pearson correlation0.1310.1300.170−0.1570.0700.124−0.012−0.0330.067
Sig. (one-tailed)0.0380.0390.0110.0160.1720.0470.4370.3290.182
N184184184184184184184184184

Contingency coefficient

MIN SLIALMGLMELMILMVOITLG
Nominal by nominalPhi0.4700.184−0.0490.2330.1500.2720.256
Approximate significance0.0010.5130.5030.0750.3880.5540.007
Nominal by nominalCramér’s V0.4700.1840.0490.2330.1500.2720.256
Approximate significance0.0010.5130.5030.0750.3880.5540.007
N184184184184184184184184

Block 0: Beginning block

Classification Tablea,b
Observed Predicted
MIN Percentage correct
01
Step 0MIN01350100
14900
Overall percentage 73.4

Variables not in the equation

ScoredfSig.
Step 0VariablesSLI40.61<0.001
TLG  9.92710.002
BEI  3.17610.075
NRE  3.12310.077
ENE  5.28610.021
DEB  4.55810.033
TEP  2.8310.093
Overall Statistics 45.2057<0.001
DOI: https://doi.org/10.2478/ijme-2023-0007 | Journal eISSN: 2543-5361 | Journal ISSN: 2299-9701
Language: English
Page range: 243 - 263
Submitted on: Jun 3, 2022
Accepted on: Feb 28, 2023
Published on: Sep 30, 2023
Published by: Warsaw School of Economics
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2023 Malgorzata Godlewska, Marta Mackiewicz, published by Warsaw School of Economics
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.