Science Parks and talent attraction management: university students as a strategic resource for innovation and entrepreneurship

Figures & data

Figure 1. Research model.

Table 1. Descriptive statistics of the surveyed Science Parks, 2018.

1. Science Parks – sample and response rate:
N (population): 120		No valid Science Parks: 3
n (response): 59		Response rate (%): 50.43
No response: 58

2. Science Parks – business data
			Response 59 parks		No response 58 parks
		N	Mean	Std	N	Mean	Std	Sig. (2-tailed)
Science Park start year		59	1997.64	8.92	56	2001.75	10.96	0.029*
Total number of firms in each park		59	157.88	129.92	55	358.15	1706.01	0.370
Total number of employees in each park		58	3742.33	5188.57	33	3335.48	4788.97	0.713
Park management in each park^1		59	22.85	22.29	34	17.38	25.10	0.280

3. Science Park location and university collaboration
Your Park/Area is located^2:				Mean	Std
On a university (or other Higher Education Institution) campus:				0.27	0.45
On land or premises owned by a government:				0.30	0.46
On land or premises owned by a private firm:				0.14	0.35
Other:				0.29	0.46
Incubator localized in the Science Park^2:				0.77	0.43
Research institute localized in the Science Park^2:				0.08	0.27
The Science Park's core activity is business incubation^2:				0.27	0.45
The incubator in the Park/Area supports its start-ups in the
search for qualified professionals^3:				3.54	1.13
Collaboration with universities^2:
Scientific infrastructure				0.61	0.49
Common services				0.58	0.50
Research groups				0.61	0.49
Formal agreements				0.83	0.38
No relationship				0.03	0.18

Notes: * = p < 0.05.

¹ = Number.

² = Yes (1), No (0).

³ = 1–5.

Table 2. Variables used in the study.

(i) Partnerships with talents and firms/universities
Cadorin et al. (2019a) underlines that a major advantage of Science Parks is that the parks offer services that firms find difficult to provide in collaboration with other stakeholders, such as networks with educational and research entities and firms and discover partners in contracts and agreements (partnerships). Science parks are an instrument of interaction between firms and universities, facilitating links to the training and recruitment of qualified manpower for park firms (Vedovello, 1997). Also, park’s incubator supports entrepreneurial academics (Huffman & Quigley, 2002) offering facilities (Etzkowitz & Klofsten, 2005; Walcott, 2002; Westhead & Storey, 1995) and business advice (Albahari, Barge-Gil, Pérez-Canto, & Modrego, 2018; Cadorin et al., 2017). In addition, Cadorin et al. (2019b) show that the exchange of knowledge and talent between universities and park companies is one of many activities that parks perform.
(ii) Science Park talent attraction activities
Science Parks offer a favourable environment for firms to adopt a collaborative network improving their talent management practices (Hu, 2008; Schweer et al., 2012). Younger and mature firms benefit from talent activities undertaken by Parks. The former relies on the park’s support to recruit skilled professionals to fill the expertise gap of their team (Albahari et al., 2018; Phan et al., 2005). The latter demands a broad spectrum of talents (Siegel et al., 1993) and the park and its local university offer a continual flow of graduates (Etzkowitz, 2008; Florida, 1999).
(iii) Networking and attracting dimensions
The network of relations with universities and its students involves, for example, the promotion of recruitment fairs and events to attract the university alumni network (Cadorin et al., 2019a), as well as the integration between young talent and the management of parks and their tenant companies (Cadorin et al., 2019b). Environmental factors related to the quality of life, such as pleasant and affordable housing and good school options (Lecluyse, Knockaert, & Spithoven, 2019), along with working conditions and opportunities for relationships with other fellow workers (Thunnissen & Van Arensbergen, 2015) are crucial in attracting talent to Science Parks.
Variables	Mean	Std	Measure
1. The management team carries out activities in partnership with the university to enhance informal relationships between students and firms in the Science Park	4.29	0.70	1–5
2. The management team carries out activities in partnership with the university to enhance informal relationships between faculty and firms in the Science Park	4.29	0.70	1–5
3. The management team provides services to promote the exchange of knowledge and the development of joint projects between tenant firms and the university	4.29	0.72	1–5
4. The management team develops specific activities to support the talent-attracting activities of tenant firms	4.10	0.76	1–5
5. The management team is directly or partially involved in the management of the Science Park firms	3.51	1.12	1–5
6. The management team offers services and facilities for incoming firms and their employees, in order to assist them in resolving legal and family issues (housing, schools, medical assistance etc)	3.24	1.10	1–5
7. Attracting prominent firms to the Science Park is an efficient way to attract talent	4.19	0.71	1–5
8. The management team count on university student collaboration in the decision-making process	3.08	1.02	1–5
9. The management team cooperates with student organizations in order to get fresh ideas and spread park information among students	3.85	0.81	1–5
10. The management team develops activities to promote and support entrepreneurial students and researchers	4.36	0.64	1–5
11. The management team develops activities to attract senior professionals to the park tenants	3.71	0.95	1–5
12. The management team works to create a positive flow of foreign talents into the Science Park	3.85	0.96	1–5
13. The management team promotes activities to reach out and attract former university students (alumni network)	3.61	1.00	1–5
14. Influencing students to remain in the park after graduation is an efficient way to attract talent	3.80	0.85	1–5
15. The events and activities promoted by the management team play a relevant role in attracting talent to the Science Park	4.25	0.68	1–5
16. Support and encouragement to start a new business	4.46	0.57	1–5
17. Opportunities to work in an innovative environment	4.66	0.51	1–5
18. Opportunities to work with excellent professionals	4.46	0.60	1–5
19. Opportunities to work in prominent firms	4.36	0.69	1–5
20. Better opportunities to find a job	4.32	0.71	1–5
21. Quality of life facilities, e.g. parks and social meetings places	4.19	0.71	1–5
Control variables
22. Science Park – age	20.17	8.86	Years
23. Science Park – number of firms	157.89	129.92	Number
24. Science Park – park management	22.85	22.29	Number
25. Science Park – total number of employees	3678.90	5166.67	Number

Table 3. Correlation matrix: four factors and four control variables.

	1.	2.	3.	4.	5.	6.	7.
1. Involving tenant firms/students and attraction of former students (alumni)
2. Dimensions for students to remain in the Science Park after graduation	.216
3. Informal and formal partnerships with park management and students	.380**	.457**
4. Science Park talent attraction activities	.566**	.486**	.544**
5. Science Park – age	-.033	-.173	-.312*	-.034
6. Science Park – number of firms	-.020	.169	.080	.143	.328*
7. Science Park – park management	-.409**	.000	.003	-.255	.070	.127
8. Science Park – total number of employees	.052	.123	.055	.143	.036	.539**	.065

Notes: *p < 0.05, ** p < 0.01.

Table 4. Regression analyses. Unstandardized coefficients beta and standard errors (in parentheses).

	Model 1^a			Model 2^b			Model 3^c			Model 4^d
		Tolerance	VIF		Tolerance	VIF		Tolerance	VIF		Tolerance	VIF
Involving tenant firms/students and attraction of former students (alumni)	0.312*** (0.065)	0.953	1.049				0.165* (0.065)	0.953	1.049	0.072 (0.074)	0.675	1.482
Dimensions for the students to remain in the Science Park after graduation	0.343*** (0.091)	0.953	1.049				0.308** (0.090)	0.953	1.049	0.205* (0.097)	0.759	1.318
Science Park talent attraction activities				0.474*** (0.097)	1.000	1.000				0.300* (0.128)	0.540	1.850
Intercept	1.722 (2.401)			9.644 (1.566)			6.360 (2.932)			5.843 (2.312)
Adjusted R square	0.440			0.284			0.266			0.321

* p < 0.05, **, p < 0.01, ***p < 0.005

^a = Sig. 0.000***, dependent factor: Science Park talent attraction activities.

^b = Sig. 0.000***, dependent factor: Informal and formal partnerships with students and firm/university.

^c =  Sig. 0.000***, dependent factor: Informal and formal partnerships with students and firm/university.

^d = Sig. 0.000***, dependent factor: Informal and formal partnerships with students and firm/university.

Table A1. Factor analysis: Principal axis factoring with Varimax rotation (rotated factor matrix) ^abc.

Variables	Factor 1	Factor 2	Factor 3	Factor 4	Factor 5 ^d	Factor 6 ^d
Factor names	Involving tenant firms/students and attraction of former students (alumni)	Dimensions for the students to remain in the park after graduation	Informal and formal partner-ships with students and firms/university	Science Park talent attraction activities
Cronbach α	α = 0.818	α = 0.814	α = 0.822	α = 0.784
Variable
1.	0.039	0.220	0 . 659	0.370	0.187	-.0.056
2.	0.160	0.248	0.808	0.168	0.033	−0.159
3.	0.320	0.135	0.543	0.089	−0.166	0.233
4.	0.169	0.133	0.222	0.522	0.411	−0.099
5.	0.717	0.004	0.147	0.058	−0.178	-.0.01
6.	0.656	0.093	−0.063	0.335	0.129	−0.282
7.	−0.043	0.506	0.266	0.367	0.218	−0.014
8.	0.710	0.072	0.084	0.108	0.341	−0.062
9.	0.362	0.111	0.430	0.133	0.541	0.045
10.	0.086	0.150	0.726	0.047	0.145	0.048
11.	0.439	0.153	0.254	0.141	0.049	−0.584
12.	0.481	0.087	0.049	0.641	0.082	−0.097
13.	0.746	0.022	0.267	0.155	0.115	0.197
14.	0.338	0.268	0.297	0.615	−0.013	0.202
15.	0.129	0.337	0.442	0.535	−0.174	0.059
16.	0.063	0.266	0.100	0.049	0.031	0.408
17.	0.061	0.657	0.199	0.039	−0.334	0.152
18.	0.059	0.764	0.162	0.086	−0.166	−0.049
19.	0.027	0.498	0.224	0.235	0.086	−0.096
20.	0.004	0.696	0.186	0.056	0.306	0.122
21.	0.172	0.621	−0.049	0.119	0.335	0.181

Notes: ^a= Cumulative variance 59.826%.

^b = (Cronbach α) > 0.500.

^c = KMO = 0.668 and Bartlett’s test of sphericity = 0.000.

^d= Only one variable. It will be excluded from further analysis.

Table A2. Correlation matrix on the variable level between the 25 variables in the study (SP = Science Park).

Variables	1.	2.	3.	4.	5.	6.	7.	8.	9.	10.	11.	12.	13.	14.	15.	16.	17.	18.	19.	20.	21.	22.	23.	24.
1. The man – between students and firms in the SP
2. The man – between faculty and firms in the SP	.751*
3. The man team provides services to promote	.416*	.485**
4. The man team develops specific activities to	.531**	.368**	.103
5. The man team is directly or partially involved	.107	.240	.317*
6. The man team offers services and facilities for	.179	.246	.108	.382**	.457**
7. Attracting prominent firms to the SP is an	.415**	.345**	.198	.382**	-.008	.163
8. The man team count on university student coll	.232	.232	.200	.322*	.490**	.639**	.145
9. The man team cooperates with student organis	.418**	.418**	.315*	.477**	.244	.216	.354**	.540**
10. The man team develops activities to promote	.504**	.659**	.411**	.245	.135	.074	.386**	.165	.477**
11. The man team develops activities to attract	.285*	.389**	.124	.257*	.361**	.462**	.236	.435**	.348**	.287*
12. The man team works to create a positive flow	.299*	.273*	.214	.494**	.317*	.603**	.271*	.382**	.326*	.146	.424**
13. The man team promotes activities to reach out	.263*	.337**	.517**	.326*	.571**	.476**	.080	.522**	.481**	.276*	.316*	.529**
14. Influencing students to remain in the park after	.511**	.423**	.437**	.355**	.322*	.385**	.439**	.359**	.384**	.265*	.227	.597**	.455**
15. The events and activities promoted by the man	.495**	.495**	.408**	.414**	.257*	.170	.506**	.190	.290*	.422**	.274*	.400**	.248	.626**
16. Support and encouragem to start a new busin	.141	.097	.052	.090	.102	-.066	.171	.170	.080	.257*	-.167	.035	.138	.269*	.184
17. Opportun to work in an innovative environ	.182	.327*	.316*	.002	.093	.084	.321*	-.043	-.002	.271*	.115	.138	.074	.236	.447**	-.113
18. Opportun to work with excellent professionals	.341**	.341**	.250	.162	.175	.042	.408**	.077	.112	.108	.207	.094	.102	.324*	.428**	-.021	.134
19. Opportun to work in prominent firms	.322*	.358**	.207	.292*	.058	.159	.393**	.103	.224	.256*	.265*	.240	.130	.392**	.353**	-.146	.214	-.009
20. Better opportunities to find a job	.369**	.369**	.187	.228	-.083	.122	.465**	.153	.300*	.278*	.064	.124	.205	.371**	.184	-.210	.151	.028	.090
21. Qual of life, e.g. parks and soc meeting places	.204	.134	.130	.318*	.058	.208	.447**	.264**	.354**	.118	.082	.246	.227.	.237	.257*	-.140	.035	-.172	.155	.257*
Control variables
22. Science Park – age	-.204	-.218	.281*	-.167	.040	-.008	-.104	-.089	-.243	-.310*	-.019	.110	-.057	.002	-.098	-.163	-.113	-.021	-.146	-.210	-.140
23. Science Park – number of firms	.135	.006	.061	.127	-.151	.119	.166	-.007	-.162	.055	.056	.108	-.087	.090	.131	-.082	.004	.1234	.214	.152	.035	.328*
24. Science Park – park management	.022	-.004	-.012	-.307*	-.215	-.170	.051	-.393**	-.283*	.004	-.352**	-.293*	-.455**	-.070	-.114	-.104	.027	.095	-.009	.028	-.172	.070	.127
25. Science Park – total number of employees	.102	-.025	.108	.131	-.087	.218	.114	.059	.033	-.014	.062	.175	-.051	.121	-.009	-.143	-.070	.090	.112	.090	.155	.036	.539**	.065

Notes * = Correlation is significant (0.05-level), 2-tailed,** = Correlation is significant (0.01-level), 2-tailed.

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