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Organisational competence vs transferability of knowledge in cluster organisations and technology parks


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Results of the analysis of variance in cluster organisations and technology parks: [CPs] - [AIK] (N=269)

AIKCompetence of collaborating organisations
CPS1(1–2), (N=118) (1)CPS1(3), (N=53) (2)CPS1(4–5), (N=98) (3)TOTAL (N=269)
MeanStd. DeviationMeanStd. DeviationMeanStd. DeviationMeanStd. Deviation
AIK13.021.183.510.993.760.773.381.06
Parameters of ANOVA for variables (AIK1), (CPs1) F=14.82, p=0.000<0.01. The mean difference for the competence groups 1 and 2; 1 and 3 is significant at the 0.01 level
AIK22.470.993.280.723.460.852.991.01
Parameters of ANOVA for variables (AIK2), (CPs1) F=36.63, p=0.000<0.01. The mean difference for the competence groups 1 and 2; 1 and 3 is significant at the 0.01 level
AIK32.491.003.210.933.160.902.881.01
Parameters of ANOVA for variables (AIK3), (CPs1) F=17.35, p=0.000<0.01. The mean difference for the competence groups 1 and 2; 1 and 3 is significant at the 0.01 level
AIK42.190.973.001.042.951.042.621.08
Parameters of ANOVA for variables (AIK4), (CPs1) F=19.73, p=0.000<0.01. The mean difference for the competence groups 1 and 2; 1 and 3 is significant at the 0.01 level
AIK52.291.093.131.003.361.132.841.20
Parameters of ANOVA for variables (AIK5), (CPs1) F=28.12, p=0.000<0.01. The mean difference for the competence groups 1 and 2; 1 and 3 is significant at the 0.01 level

Access to information and knowledge [AIK] in cluster organisations and technology parks (N=132, 137)

VariablesCluster organisationsTechnology parks
MinMaxMeanStd. Dev.MedianModeMinMaxMeanStd. Dev.MedianMode
AIK1153.521.1144153.261.0034
AIK2153.091.1033152.890.9033
AIK3153.021.0633152.740.9432
AIK4152.761.0433152.491.1022
AIK5152.951.2033152.741.1833

Theoretical perspective of organisational competence

Theoretical perspectiveCompetence contentReference
Evolutionary economics (firm-level ontogenetic evolution)The specific content of economic behaviour addresses the issue of basic behaviour continuity in terms of skills, routines, learning, cognition (elements associated with competence).Competence is built in evolution economics — organisations possess bounded rationality due to the lack of competence. Competence puzzle focuses on the role of learning and practice.Organisational routine is treated as an organisational analogue of individual skill. Routinised behaviour can be complex and effectiveNelson and Winter (2002)
Evolutionary economics (dynamic capabilities)Dynamic capabilities as the source of competitive advantage. “Capabilities emphasise the key role of strategic management in appropriately adapting, integrating, and reconfiguring internal and external organisational skills, resources, and functional competences toward changing environment” (Teece and Pisano, 1994:1).Organisational competences are defined as distinctive routines or processes that are enabled by integrated clusters of firm-specific assets, individuals and groups (Teece et al., 1997:516).Firm's dynamic capabilities are determined by processes, positions and pathsTeece and Pisano (1994), Teece et al. (1997), Winter (2003), Eisenhardt and Martin (2000)
Strategic management theory (the core competence approach)Define core competences as roots of competitiveness.Provide a competence-based organisation's concept.Identified methods for core-competence buildingPrahalad and Hamel (1990)
Strategic management theory (resource-based view of the firm)Propose an idea to look at a firm as a set of resources rather than products.Resources are defined as tangible and intangible assets, such as knowledge, routines (effective procedures) that are difficult to replicate.Capabilities and competences are identified as resourcesWernerfelt (1984), Wernerfelt (1995), Amit and Schoemaker (1993)

The results of the correlation analysis in cluster organisations and technology parks: [CPl] - [AIK] (N=132, 137)

Access to information and knowledge [AIK]Cluster organisationsTechnology parks
Cramer's VpCramer's Vp
AIK10.324p<0.00010.2590.012
AIK20.3030.0010.2990.000
AIK30.322p<0.00010.2770.003
AIK40.2740.0080.2400.048
AIK50.3010.0010.2140.197

Parameters of the logistic regression models

VariablesTotal sample, N=229Cluster organisation sample, N=93Park sample, N=136
BSig.Exp(B)BSig.Exp(B)BSig.Exp (B)
AIK10.2540.2071.2891.0040.0312.7290.0940.7031.099
AIK20.2030.3781.225−0.4840.2260.6160.5150.1031.674
AIK30.3170.131.3730.8120.0452.2530.1280.6331.137
AIK40.6120.0011.8440.9050.0262.4730.5340.0151.705
CPI_1_2_30.0260.9321.0260.6150.3071.849−0.110.7770.895
CPs1_1_2_30.7110.0012.0370.7550.042.1270.7710.0042.162
Constant−6.4660.0000.002−11.1070.0000.000−5.8250.0000.003
Logistic regression results:
χ2(6), (p)73.028, (p<0.01)43.95, (p<0.01)36.524, (p<0.01)
Nagelkerke R20.3750.5070.332
Predicted percentage correct76.978.577.9

Competence proximity [CPs] in terms of the scope of competences in cluster organisations and technology parks (N=132, 137)

VariablesCluster organisationsTechnology parks
MinMaxMeanStd. Dev.MedianModeMinMaxMeanStd. Dev.MedianMode
CPs1152.801.3634152.781.2132
CPs2152.601.2431152.851.2132
CPs3152.271.1621152.931.2833
CPl163.881.4233163.260.8333

The results of the correlation analysis in cluster organisations and technology parks: [CPs] - [AIK] (N=132, 137)

CPSCc/pCluster organisationsTechnology parks
AIK1AIK2AIK3AIK4AIK5AIK1AIK2AIK3AIK4AIK5
CPs1Cc0.323**0.416**0.333**0.405**0.359**0.157*0.415**0.211**0.258**0.408**
p0.0000.0000.0000.0000.0000.0280.0000.0030.0000.000
CPs2Cc0.269**0.328**0.244**0.264**0.222**0.1330.306**0.273**0.376**0.375**
p0.0000.0000.0010.0000.0020.0610.0000.0000.0000.000
CPs3Cc0.194**0.277**0.305**0.170*0.153*0.208**0.0840.1240.073−0.048
p0.0080.0000.0000.0200.0340.0030.2420.0820.2990.492

Results of the crosstabs analysis: [CPs] - [AIK6] (N=268)

AIKCPs1 (1–3)CPs1 (4–5)Total
AIK6: definitely not, rather not, hard to sayCount13844182
% within work with other companies that have/do not have the same competence80.70%45.40%67.90%
% of total51.50%16.40%67.90%
AIK6: rather yes, definitely yesCount335386
% within work with other companies that have/do not have the same competence19.30%54.60%32.10%
% of total12.30%19.80%32.10%
TotalCount17197268
% of total63.80%36.20%100.00%

Results of the analysis of variance in cluster organisations and technology parks: [CPl] - [AIK] (N=230)

AIKCompetence proximity of collaborating enterprises in terms of the level of development
CPl(1–2) (N=26) (1)CPl(3) (N=145) (2)CPI(4–5) (N=59) (3)Total (N=230)
MeanStd. DeviationMeanStd. DeviationMeanStd. DeviationMeanStd. Deviation
AIK12.881.403.570.923.321.063.431.04
Parameters of ANOVA for variables (AIK1), (CPI) F=5.49, p=0.005<0.01. The mean difference for the competence groups 1 and 2 is significant at the 0.01 level
AIK22.461.173.280.922.850.913.070.99
Parameters of ANOVA for variables (AIK2), (CPI) F=10.35, p=0.000<0.01. The mean difference for the competence groups 1 and 2; 2 and 3 is significant at the 0.01 level
AIK32.501.172.990.903.021.112.941.00
Parameters of ANOVA for variables (AIK3), (CPI) F=2.97, p=0.054>0.05. Mean differences for competence groups are not statistically significant
AIK42.231.372.711.042.761.092.671.10
Parameters of ANOVA for variables (AIK4), (CPI) F=2.39, p=0.094>0.05. Mean differences for competence groups are not statistically significant
AIK52.421.423.051.152.801.212.911.21
Parameters of ANOVA for variables (AIK5), (CPI) F=3.35, p=0.037<0.05. The mean difference for the competence groups 1 and 2 is significant at the 0.05 level

Variables in the study

Competence proximity in terms of the scope of competences [CPs]
CPs1Our company works with cluster companies/park tenants that have the same or very similar competence (belong to the same industry, have a similar business profile)
CPs2Our company works with cluster companies/park tenants that have expertise in a different field to ours (they belong to the same industry, and their competencies are complementary to ours)
CPs3Our company works with cluster companies/park tenants that have completely different competences (they belong to other industries)
Likert scale (1–5): Definitely not (1) Rather not (2) Hard to say (3) Rather yes (4) Definitely yes (5)
Competence proximity in terms of the level of competence development [CPl]
In the cluster/park, we cooperate primarily with companies whose level of development (technology, knowledge, quality of staff) is:

Much lower than the level represented by our company

Lower than the level represented by our company

Similar to the level represented by our company

Higher than the level represented by our company

Much higher than the level represented by our company

None of the above because we do not cooperate with cluster companies/park tenants

Access to information and knowledge [AIK]
AIK1One of the effects of joining the cluster/location in the park is that my company has gained access to a wide variety of information (albeit general information)
AIK2One of the effects of joining the cluster/location in the park is that my company has gained access to selected information, fully tailored to the profile and needs of my business
AIK3One of the effects of joining the cluster/location in the park is that my company has gained priority in receiving important information about changes in the external environment
AIK4One of the effects of joining the cluster/location in the park is that my company is less worried about sharing certain confidential information with selected cluster companies
AIK5One of the effects of joining the cluster/location in the park is that my company, together with other selected cluster companies/park tenants, takes part in processes of creating new knowledge (through working groups, project groups etc.)
Likert scale (1–5): Definitely not (1) Rather not (2) Hard to say (3) Rather yes (4) Definitely yes (5)