Economic Crisis, Turbulence and the Resilience of Innovation: Insights from the Atlantic Maritime Cluster

Abstract

Innovation is related to economic cycles. Often seen as a procyclical phenomenon, many innovation actors try and succeed in maintaining (and even increasing) their innovation efforts to gain competitive advantage during the crises. In this chapter, departing from the recent developments in regional studies, which understand resilience as an evolutionary capacity of socio-economic systems, we suggest the notion of ‘resilience of innovation’ as the capacity of an innovation process to maintain its function at different levels of operation. Drawing upon the results from a survey on knowledge provision and needs of maritime cluster innovative actors in the European Atlantic Area, our analysis focuses on the evolution of innovation and knowledge services. We provide parametric and non-parametric evidence of the differences in the provision and utilisation of these services and provide econometric evidence of the main factors that influence the resilience of innovation at the organizational level.

Appendix

1.1 Histogram of Variety of Uses and Provisions

Source: Own elaboration

1.2 Anova

		Sum of squares	df	Mean square	F	Sig.
Variety of knowledge exchange activities or services used in the last 3 years	Between groups	423.221	5	84.644	12.165	.000
	Within groups	667.955	96	6.958
	Total	1091.176	101
Variety of knowledge exchange activities or services provided in the last 3 years	Between groups	181.297	5	36.259	7.019	.000
	Within groups	495.958	96	5.166
	Total	677.255	101

1. Source: Own elaboration

1.3 Kruskal-Wallis Test

	Size of organization	N	Mean rank
Variety of knowledge exchange activities or services used in the last 3 years	0	33	29.26
	Less than 10 employees	28	48.00
	10–50 employees	13	70.08
	50–250 employees	9	84.61
	250–500 employees	11	62.09
	> 500 employees	8	73.50
	Total	102
Variety of knowledge exchange activities or services provided in the last 3 years	0	33	37.80
	Less than 10 employees	28	47.66
	10–50 employees	13	57.15
	50–250 employees	9	79.44
	250–500 employees	11	59.23
	> 500 employees	8	70.19
	Total	102

1. Source: Own elaboration

Kruskal Wallis test	Variety of knowledge exchange activities or services used in the last 3 years	Variety of knowledge exchange activities or services provided in the last 3 years
Chi-Square	43.218	27.451
Df	5	5
Asymp. Sig.	0.000	0.000

1. Source: Own elaboration
2. Notes: Kruskal Wallis test, Grouping variable: what is the size of your organization?

1.4 Mann–Whitney Test

	Universities and PROs	N	Mean rank	Sum of ranks
Variety of knowledge exchange activities or services used in the last 3 years	Other	86	47.62	4095.50
	University or PRO	16	72.34	1157.50
	Total	102
Variety of knowledge exchange activities or services provided in the last 3 years	Other	86	46.28	3980.00
	University or PRO	16	79.56	1273.00
	Total	102

1. Source: Own elaboration

	Variety of knowledge exchange activities or services used in the last 3 years	Variety of knowledge exchange activities or services provided in the last 3 years
Mann-Whitney U	354.500	239.000
Wilcoxon W	4095.500	3980.000
Z	−3.140	−4.842
Asymp. Sig. (2-tailed)	0.002	0.000

1. Source: Own elaboration
2. Note: Grouping variable: Universities and PROs

1.5 Tests for Independence

Association of between “Does your organization provide or administer any knowledge exchange services or schemes?: * Variety of knowledge exchange activities or services used in the last 3 years”.

Chi-square tests
	Value	df	Asymp. Sig. (2-sided)
Pearson Chi-square	103.831a	33	0.000
Likelihood ratio	112.200	33	0.000
Linear-by-linear association	5.112	1	0.024
N of valid cases	102

1. Source: Own elaboration
2. ^a45 cells (93.8%) have expected count less than 5. The minimum expected count is 0.04

Symmetric measures
		Value	Approx. Sig.
Nominal by nominal	Contingency coefficient	0.710	0.000
N of valid cases		102

1. Source: Own elaboration

Association between “Does your organization provide or administer any knowledge exchange services or schemes? * Variety of knowledge exchange activities or services provided in the last 3 years”.

Chi-square tests
	Value	df	Asymp. Sig. (2-sided)
Pearson Chi-square	97.740a	33	0.000
Likelihood ratio	123.252	33	0.000
Linear-by-linear association	1.394	1	0.238
N of valid cases	102

1. Source: Own elaboration
2. ^a45 cells (93.8%) have expected count less than 5. The minimum expected count is 0.04

Symmetric measures
		Value	Approx. Sig.
Nominal by nominal	Contingency coefficient	0.700	0.000
N of valid cases		102

1. Source: Own elaboration

1.6 Predictive Capacity of Probit Model

Model in E-Views: resilience c client_firm clients_export size_big univ_pros kmanag eval use provision market_variation.

1.6.1 Global Model

Mean dependent var	0.401961	S.D. dependent var		0.492715
S.E. of regression	0.309832	Akaike info criterion		0.711688
Sum squared resid	8.831618	Schwarz criterion		0.969038
Log likelihood	−26.29607	Hannan-Quinn criter.		0.815898
Restr. log likelihood	−68.72747	Avg. log likelihood		−0.257805
LR statistic (9 df)	84.86279	McFadden R-squared		0.617386
Probability(LR stat)	1.74E-14
Obs with Dep = 0	61	Total obs		102
Obs with Dep = 1	41

1. Source: Own elaboration

Global model prediction evaluation (success cutoff C = 0.5)
	Estimated equation			Constant probability
	Dep = 0	Dep = 1	Total	Dep = 0	Dep = 1	Total
P(Dep = 1) < =C	55	7	62	61	41	102
P(Dep = 1) > C	6	34	40	0	0	0
Total	61	41	102	61	41	102
Correct	55	34	89	61	0	61
% Correct	90.16	82.93	87.25	100.00	0.00	59.80
% Incorrect	9.84	17.07	12.75	0.00	100.00	40.20
Total Gaina	−9.84	82.93	27.45
Percent Gainb	NA	82.93	68.29
	Estimated equation			Constant probability
	Dep = 0	Dep = 1	Total	Dep = 0	Dep = 1	Total
E(# of Dep = 0)	52.69	8.58	61.27	36.48	24.52	61.00
E(# of Dep = 1)	8.31	32.42	40.73	24.52	16.48	41.00
Total	61.00	41.00	102.00	61.00	41.00	102.00
Correct	52.69	32.42	85.11	36.48	16.48	52.96
% Correct	86.38	79.07	83.44	59.80	40.20	51.92
% Incorrect	13.62	20.93	16.56	40.20	59.80	48.08
Total Gaina	26.57	38.87	31.52
Percent Gainb	66.11	65.00	65.56

1. Source: Own elaboration
2. ^aChange in “% Correct” from default (constant probability) specification
3. ^bPercent of incorrect (default) prediction corrected by equation