Tab. 1
Theoretical perspective of organisational competence
| Theoretical perspective | Competence content | Reference |
|---|---|---|
| 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 effective | Nelson 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 paths | Teece 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 building | Prahalad 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 resources | Wernerfelt (1984), Wernerfelt (1995), Amit and Schoemaker (1993) |
Tab. 2
Variables in the study
| Competence proximity in terms of the scope of competences [CPs] | ||
| CPs1 | Our 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) | |
| CPs2 | Our 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) | |
| CPs3 | Our 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:
| ||
| Access to information and knowledge [AIK] | ||
| AIK1 | One 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) | |
| AIK2 | One 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 | |
| AIK3 | One 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 | |
| AIK4 | One 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 | |
| AIK5 | One 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) | ||
Tab. 3
Competence proximity [CPs] in terms of the scope of competences in cluster organisations and technology parks (N=132, 137)
| Variables | Cluster organisations | Technology parks | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Min | Max | Mean | Std. Dev. | Median | Mode | Min | Max | Mean | Std. Dev. | Median | Mode | |
| CPs1 | 1 | 5 | 2.80 | 1.36 | 3 | 4 | 1 | 5 | 2.78 | 1.21 | 3 | 2 |
| CPs2 | 1 | 5 | 2.60 | 1.24 | 3 | 1 | 1 | 5 | 2.85 | 1.21 | 3 | 2 |
| CPs3 | 1 | 5 | 2.27 | 1.16 | 2 | 1 | 1 | 5 | 2.93 | 1.28 | 3 | 3 |
| CPl | 1 | 6 | 3.88 | 1.42 | 3 | 3 | 1 | 6 | 3.26 | 0.83 | 3 | 3 |
Tab. 4
Access to information and knowledge [AIK] in cluster organisations and technology parks (N=132, 137)
| Variables | Cluster organisations | Technology parks | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Min | Max | Mean | Std. Dev. | Median | Mode | Min | Max | Mean | Std. Dev. | Median | Mode | |
| AIK1 | 1 | 5 | 3.52 | 1.11 | 4 | 4 | 1 | 5 | 3.26 | 1.00 | 3 | 4 |
| AIK2 | 1 | 5 | 3.09 | 1.10 | 3 | 3 | 1 | 5 | 2.89 | 0.90 | 3 | 3 |
| AIK3 | 1 | 5 | 3.02 | 1.06 | 3 | 3 | 1 | 5 | 2.74 | 0.94 | 3 | 2 |
| AIK4 | 1 | 5 | 2.76 | 1.04 | 3 | 3 | 1 | 5 | 2.49 | 1.10 | 2 | 2 |
| AIK5 | 1 | 5 | 2.95 | 1.20 | 3 | 3 | 1 | 5 | 2.74 | 1.18 | 3 | 3 |
Tab. 5
The results of the correlation analysis in cluster organisations and technology parks: [CPs] - [AIK] (N=132, 137)
| CPS | Cc/p | Cluster organisations | Technology parks | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| AIK1 | AIK2 | AIK3 | AIK4 | AIK5 | AIK1 | AIK2 | AIK3 | AIK4 | AIK5 | ||
| CPs1 | Cc | 0.323** | 0.416** | 0.333** | 0.405** | 0.359** | 0.157* | 0.415** | 0.211** | 0.258** | 0.408** |
| p | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.028 | 0.000 | 0.003 | 0.000 | 0.000 | |
| CPs2 | Cc | 0.269** | 0.328** | 0.244** | 0.264** | 0.222** | 0.133 | 0.306** | 0.273** | 0.376** | 0.375** |
| p | 0.000 | 0.000 | 0.001 | 0.000 | 0.002 | 0.061 | 0.000 | 0.000 | 0.000 | 0.000 | |
| CPs3 | Cc | 0.194** | 0.277** | 0.305** | 0.170* | 0.153* | 0.208** | 0.084 | 0.124 | 0.073 | −0.048 |
| p | 0.008 | 0.000 | 0.000 | 0.020 | 0.034 | 0.003 | 0.242 | 0.082 | 0.299 | 0.492 | |
Tab. 6
Results of the analysis of variance in cluster organisations and technology parks: [CPs] - [AIK] (N=269)
| AIK | Competence of collaborating organisations | |||||||
|---|---|---|---|---|---|---|---|---|
| CPS1(1–2), (N=118) (1) | CPS1(3), (N=53) (2) | CPS1(4–5), (N=98) (3) | TOTAL (N=269) | |||||
| Mean | Std. Deviation | Mean | Std. Deviation | Mean | Std. Deviation | Mean | Std. Deviation | |
| AIK1 | 3.02 | 1.18 | 3.51 | 0.99 | 3.76 | 0.77 | 3.38 | 1.06 |
| 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 | ||||||||
| AIK2 | 2.47 | 0.99 | 3.28 | 0.72 | 3.46 | 0.85 | 2.99 | 1.01 |
| 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 | ||||||||
| AIK3 | 2.49 | 1.00 | 3.21 | 0.93 | 3.16 | 0.90 | 2.88 | 1.01 |
| 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 | ||||||||
| AIK4 | 2.19 | 0.97 | 3.00 | 1.04 | 2.95 | 1.04 | 2.62 | 1.08 |
| 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 | ||||||||
| AIK5 | 2.29 | 1.09 | 3.13 | 1.00 | 3.36 | 1.13 | 2.84 | 1.20 |
| 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 | ||||||||
Tab. 7
The results of the correlation analysis in cluster organisations and technology parks: [CPl] - [AIK] (N=132, 137)
| Access to information and knowledge [AIK] | Cluster organisations | Technology parks | ||
|---|---|---|---|---|
| Cramer's V | p | Cramer's V | p | |
| AIK1 | 0.324 | p<0.0001 | 0.259 | 0.012 |
| AIK2 | 0.303 | 0.001 | 0.299 | 0.000 |
| AIK3 | 0.322 | p<0.0001 | 0.277 | 0.003 |
| AIK4 | 0.274 | 0.008 | 0.240 | 0.048 |
| AIK5 | 0.301 | 0.001 | 0.214 | 0.197 |
Tab. 8
Results of the analysis of variance in cluster organisations and technology parks: [CPl] - [AIK] (N=230)
| AIK | Competence 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) | |||||
| Mean | Std. Deviation | Mean | Std. Deviation | Mean | Std. Deviation | Mean | Std. Deviation | |
| AIK1 | 2.88 | 1.40 | 3.57 | 0.92 | 3.32 | 1.06 | 3.43 | 1.04 |
| 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 | ||||||||
| AIK2 | 2.46 | 1.17 | 3.28 | 0.92 | 2.85 | 0.91 | 3.07 | 0.99 |
| 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 | ||||||||
| AIK3 | 2.50 | 1.17 | 2.99 | 0.90 | 3.02 | 1.11 | 2.94 | 1.00 |
| Parameters of ANOVA for variables (AIK3), (CPI) F=2.97, p=0.054>0.05. Mean differences for competence groups are not statistically significant | ||||||||
| AIK4 | 2.23 | 1.37 | 2.71 | 1.04 | 2.76 | 1.09 | 2.67 | 1.10 |
| Parameters of ANOVA for variables (AIK4), (CPI) F=2.39, p=0.094>0.05. Mean differences for competence groups are not statistically significant | ||||||||
| AIK5 | 2.42 | 1.42 | 3.05 | 1.15 | 2.80 | 1.21 | 2.91 | 1.21 |
| 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 | ||||||||
Tab. 9
Results of the crosstabs analysis: [CPs] - [AIK6] (N=268)
| AIK | CPs1 (1–3) | CPs1 (4–5) | Total | |
|---|---|---|---|---|
| AIK6: definitely not, rather not, hard to say | Count | 138 | 44 | 182 |
| % within work with other companies that have/do not have the same competence | 80.70% | 45.40% | 67.90% | |
| % of total | 51.50% | 16.40% | 67.90% | |
| AIK6: rather yes, definitely yes | Count | 33 | 53 | 86 |
| % within work with other companies that have/do not have the same competence | 19.30% | 54.60% | 32.10% | |
| % of total | 12.30% | 19.80% | 32.10% | |
| Total | Count | 171 | 97 | 268 |
| % of total | 63.80% | 36.20% | 100.00% |
Tab. 10
Parameters of the logistic regression models
| Variables | Total sample, N=229 | Cluster organisation sample, N=93 | Park sample, N=136 | ||||||
|---|---|---|---|---|---|---|---|---|---|
| B | Sig. | Exp(B) | B | Sig. | Exp(B) | B | Sig. | Exp (B) | |
| AIK1 | 0.254 | 0.207 | 1.289 | 1.004 | 0.031 | 2.729 | 0.094 | 0.703 | 1.099 |
| AIK2 | 0.203 | 0.378 | 1.225 | −0.484 | 0.226 | 0.616 | 0.515 | 0.103 | 1.674 |
| AIK3 | 0.317 | 0.13 | 1.373 | 0.812 | 0.045 | 2.253 | 0.128 | 0.633 | 1.137 |
| AIK4 | 0.612 | 0.001 | 1.844 | 0.905 | 0.026 | 2.473 | 0.534 | 0.015 | 1.705 |
| CPI_1_2_3 | 0.026 | 0.932 | 1.026 | 0.615 | 0.307 | 1.849 | −0.11 | 0.777 | 0.895 |
| CPs1_1_2_3 | 0.711 | 0.001 | 2.037 | 0.755 | 0.04 | 2.127 | 0.771 | 0.004 | 2.162 |
| Constant | −6.466 | 0.000 | 0.002 | −11.107 | 0.000 | 0.000 | −5.825 | 0.000 | 0.003 |
| Logistic regression results: | |||||||||
| χ2(6), (p) | 73.028, (p<0.01) | 43.95, (p<0.01) | 36.524, (p<0.01) | ||||||
| Nagelkerke R2 | 0.375 | 0.507 | 0.332 | ||||||
| Predicted percentage correct | 76.9 | 78.5 | 77.9 | ||||||