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

No.	Variable	Explanation of the variable	The type of factor	The expected direction of impact on the participation of LGUs in innovation networks
1	SLI	Cooperation 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).	Institutional	Positive
2	BEI	BEI 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).	Institutional	Positive
3	NRE	NRE 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).	Economic	Positive
4	ENE	ENE 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).	Economic	Positive
5	DEB	Debt 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]).	Economic	Negative
6	TIP	Total 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).	Economic	Positive
7	TEP	Total 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).	Economic	Negative
8	NCI	Amount 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).	Cultural	Positive
9	PDE	Population 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)	Demographic	Positive
10	NIN	Numbers 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).	Demographic	Positive
11	ALM	Age 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).	Managerial	Positive
12	GLM	GLM (men – 0; female – 1; diverse – 2).	Managerial	Neutral
13	ELM	ELM (technical secondary school – 1; secondary school – 2; higher education – 3; higher administrative education – 4; higher law education – 5; higher economic education – 6).	Managerial	Positive
14	ILM	Political ILM (politically dependent – 0; politically independent – 1).	Political	Negative
15	TLG	TLG (rural municipalities – 1; urban-rural municipalities – 2; urban municipalities – 3; cities on district rights – 4).	Administrative	Positive
16	VOI	Voivodeship (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).	Geographical	Positive

1 Source: The authors’ own compilation.

ALM, age of LGU manager; BEI, business environment institutions; ELM, education of LGU manager; ENE, entities of the national economy; GLM, gender of LGU manager; ILM, independence of LGU manager; LGU, local government units; NCI, number of cultural infrastructure; NIN, number of inhabitants; NRE, newly registered entities; SLI, special local institutions; TEP, total expenditure per capita; TIP, total income per capita; TLG, type of local government; VOI, voivodeship.

Table 2.

Descriptive statistics of quantitative variables

	Mean	Std. deviation	N	Minimum	Maximum	Reference to the country average
BEI	411.6995	226.25260	184	44	950	864
NRE	135.9457	53.90801	184	42	598	94.56
ENE	1,370.4511	1,757.34608	184	104	8,870	1,175
DEB	18.9948	397.11936	184	−1,200	2,000	−82
TIP	5,431.8032	972.57948	184	3,988.76	9,797.6	5,969.49
TEP	5,416.9598	1,039.39375	184	3,871.5	10,350.7	6,051.49
NCI	2.5109	5.24481	184	0	59	1.1
PDE	311.4239	568.89024	184	9	3,243	123
NIN	11,567.4674	15,782.55126	184	200	99,350	15,495.58

1 Source: Authors’ own compilation, based on the IBM SPSS Statistic Program Version 27 as well as on Local Data Bank of Statistics Poland for 2019 available at https://bdl.stat.gov.pl/bdl/start

BEI, business environment institutions; ENE, entities of the national economy; NCI, number of cultural infrastructure; NIN, number of inhabitants; NRE, newly registered entities; TEP, total expenditure per capita; TIP, total income per capita.

Table 3.

Correlation coefficient between quantitative variables

MIN	BEI	NRE	ENE	DEB	TIP	TEP	NCI	PDE	NIN
Pearson correlation	0.131	0.130	0.170	−0.157	0.070	0.124	−0.012	−0.033	0.067
Sig. (one-tailed)	0.038	0.039	0.011	0.016	0.172	0.047	0.437	0.329	0.182
N	184	184	184	184	184	184	184	184	184

1 Source: Authors’ own compilation based on the IBM SPSS Statistic Program Version 27.

Table 4.

Contingency coefficient

MIN		SLI	ALM	GLM	ELM	ILM	VOI	TLG
Nominal by nominal	Phi	0.470	0.184	−0.049	0.233	0.150	0.272	0.256
Nominal by nominal	Approximate significance	0.001	0.513	0.503	0.075	0.388	0.554	0.007
Nominal by nominal	Cramér’s V	0.470	0.184	0.049	0.233	0.150	0.272	0.256
Nominal by nominal	Approximate significance	0.001	0.513	0.503	0.075	0.388	0.554	0.007
N	184	184	184	184	184	184	184	184

1 Source: Authors’ own compilation based on the IBM SPSS Statistic Program Version 27.

ALM, age of LGU manager; ELM, education of LGU manager; GLM, gender of LGU manager; ILM, independence of LGU manager; LGUs, local government units; SLI, special local institutions; TLG, type of local government; VOI, voivodeship.

Case processing summary

Unweighted Cases^a		N	Percent
Selected cases	Included in analysis	184	100
	Missing cases	0	0
	Total	184	100
Unselected cases		0	0
Total		184	100

1a If weight is in effect, see classification table for the total number of cases.

Dependent variable encoding

Original value	Internal value
0	0
1	1

Block 0: Beginning block

Classification Table^a,b
	Observed		Predicted
			MIN		Percentage correct
			0	1
Step 0	MIN	0	135	0	100
		1	49	0	0
	Overall percentage				73.4

1a Constant is included in the model.

1b The cut value is 500.

Variables in the equation

		B	S.E.	Wald	df	Sig.	Exp (B)
Step 0	Constant	−1.013	0.167	36.925	1	<0.001	0.363

Variables not in the equation

			Score	df	Sig.
Step 0	Variables	SLI	40.6	1	<0.001
		TLG	9.927	1	0.002
		BEI	3.176	1	0.075
		NRE	3.123	1	0.077
		ENE	5.286	1	0.021
		DEB	4.558	1	0.033
		TEP	2.83	1	0.093
	Overall Statistics		45.205	7	<0.001

Block 1: Method enter

Omnibus tests of model coefficients

		Chi-square	df	Sig.
Step 1	Step	42.493	7	<0.001
	Block	42.493	7	<0.001
	Model	42.493	7	<0.001

Model summary

Step	−2 Log likelihood	Cox & Snell R square	Nagelkerke R square
1	170.781^a	0.206	0.3

1a Estimation terminated at iteration number 5 because parameter estimates changed by less than 0.001.

Classification table^a

Predicted
Observed			MIN		Percentage correct
Observed			0	1	Percentage correct
Step 1	MIN	0	123	12	91.1
Step 1	MIN	1	24	25	51
	Overall percentage				80.4

1a The cut value is 500.

Variables in the equation

		B	S.E.	Wald	df	Sig.	Exp (B)
Step 1a	SLI	2.178	0.439	24.555	1	−0.001	8.826
	BEI	0.001	0.001	0.822	1	0.365	1.001
	NRE	0.005	0.004	1.209	1	0.272	1.005
	ENE	0	0	0.118	1	0.731	1
	DEB	−0.001	0.001	1.174	1	0.279	0.999
	TEP	0	0	0	1	0.991	1
	TLG	0.225	0.254	0.788	1	0.375	1.252
	Constant	−2.986	1.236	5.833	1	0.016	0.051

1 Source: Authors’ own compilation based on the IBM SPSS Statistic Program Version 27.

1a The variable(s) entered on step 1 are SLI, BEI, NRE, ENE, DEB, TEP, and TLG.

1 BEI, business environment institutions; ENE, entities of the national economy; NRE, newly registered entities; SLI, special local institutions; TEP, total expenditure per capita; TLG, type of local government.

References

Authors

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Articles in this issue

DOI: https://doi.org/10.2478/ijme-2023-0007 | Journal eISSN: 2543-5361 (formerly 2299-9701) | Journal ISSN: 2299-9701

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Language: English

Page range: 243 - 263

Submitted on: Jun 3, 2022

Accepted on: Feb 28, 2023

Published on: Sep 30, 2023

Published by: SGH Warsaw School of Economics

In partnership with: Paradigm Publishing Services

Publication frequency: 4 issues per year

Keywords:

entrepreneurial and innovation ecosystem,

JEL:

E02,

H70,

O30,

O52

Related subjects:

Business and economics,

Business management,

Management accounting, financial controlling, cost calculation, investment

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

Volume 59 (2023): Issue 3 (September 2023)

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

Figures & Tables

Figure 1.

Table 1.

List of independent variables used in the empirical analysis

Table 2.

Descriptive statistics of quantitative variables

Table 3.

Correlation coefficient between quantitative variables

Table 4.

Contingency coefficient

Paradigm

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