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Abstract
Innovation is the rallying call of the day for firms to remain competitive and grow in an increasingly competitive global marketplace. However, innovation is still poorly understood beyond the buzzword, and this is especially so in the case of the service sector. This article has two aims: first, it explains innovation in the service sector; then, using data from the Community Innovation Survey III, it analyzes the impact of multinationality in the propensity of innovation in services in Portugal. The indicators of innovation propensity—our dependent variables—are two sets of variables: input innovation variables (intramural and extramural research and development), and output innovation variables (patents). We find that multinational firms indeed affect the propensity to innovate in the services sector, possibly because these firms are part of a network, and these linkages can have spillover effects, making innovation diffusion more efficient. Our results show that size matters and that medium and large firms have a better propensity to innovate.
We would like to thank the Observatório da Ciência e do Ensino Superior (OCES) of the Ministry of Science, Technology, and Higher Education for their support and data assistance for our study and the Portuguese Science Foundation (Fundação para a Ciência e Tecnologia) for financial support received.
Notes
Source: Portuguese CIS III.
Source: Portuguese CIS III.
Source: Portuguese CIS III.
Data Source: Portuguese CIS III.
Source: Portuguese CIS III.
The cut value is 0.500.
∗indicates Significance at 5%.
–Odds Ratio: Exp(
).
Sometimes referred to as the Bertrand Paradox in economics, if consumers perceive two goods as being identical, and then assuming that marginal costs were same and constant, then marginal cost pricing would be the only equilibrium.
The European Innovation Scoreboard was proposed in Lisbon Summit and is a set of indicators to benchmark the innovation in Europe. The Community Innovation Survey (CIS) is the main statistical instrument of the European Union that allows the monitoring of Europe's progress in the area of innovation. The CIS provides a better understanding of the innovation process and analyzes the effects of innovation on the economy (on competitiveness, employment, economic growth, trade patterns, etc.).
Logistic Regression permits such that the dependent variables are dichotomic and independent variables are of any type, and permits the assessment of the effects of interaction to estimate the impact if certain events occur.
The variable “size” (3)—small firms—was excluded owing to their correlation with other variables of the model.
The variable “commerce” was excluded for its correlation with other variables of the model.
If the firms have 0 patents we classified as 0; If the firms have more than 1 patents we classified as 1.
NACE: 511; 513; 514; 515; 516; 517.
NACE: 602; 611; 622; 631; 632; 634; 641; 642.
NACE: 651; 652; 660; 671; 672.
NACE: 721; 722; 723; 724; 725; 726; 732; 742; 743.