The integration of services and manufacturing is a trend that seems to be increasing. Nevertheless, the usual empirical difficulties of measurement are, in general, even more serious in services industries (as pointed by Bartelsman & Doms, 2000, and Coombs & Miles, 2000). That is the reason why the large majority of services studies use descriptive methods, a common characteristic of areas of investigation that are still in their early stages of development. Descriptive analysis is obviously valuable and it is through it that clues might be found for more rigorous approaches. However, these difficulties should not be an argument for not trying to use quantitative methods. Even with the severe limitations imposed by the available data, these tentative steps seem very useful because they reveal directions for further qualitative inquiry and, in this interaction, we hope, progress can be made.
Economic theory predicts that trade reforms can affect firm-level productivity through several channels. This Section describes the theoretical linkages behind these channels, representing the basis for the empirical analysis. As it is depicted by Figure 1, there is not a unique and well-defined model capturing the trade and productivity linkages, but rather a number of different approaches aimed at capturing different mechanisms through which economic integration can impact firms’ performance. In Figure 1 we identify four main channels through which trade reforms can influence productivity: competition, intermediate inputs, exports, FDI. Each one of this channels can affect both internal restructuring, i.e. productivity changes within the firm, and external restructuring, i.e. productivity changes due to market shares reallocation between firms, exit and entry. In the next sub-Sections we discuss in detail each one of these channels, except the FDI one because, due to data limitations, we are unable to study this channel in our empirical analysis.
In addition, it cannot be ruled out that the IPR measures in the models are correlated with some omit- ted variable representing the propensity to invest in intangible assets, which cannot be observed in the data. As a result of this possible omitted variable bias, IPR coefficients estimated in econometric models capture not only the effect of the use of formal IPRs for intangible assets protection, but also the positive effect of those intangible assets themselves. The result that the relationship is found to be stronger for SMEs than for large companies is consistent with this hypothesis. Most large compa- nies rely in some way or another on intangible assets, whereas many smaller firms often build their business on tangible assets alone. Trade marks, designs and patents provide legal protection for specific but not all types of intangible asset. Hence, the group of large firms not owning these par- ticular forms of IPR may consist of firms that generate other types of intangible asset (e.g. copyrights or trade secrets) and therefore exhibit high economicperformance. In contrast, the group of SMEs not owning trade marks, patents or designs is likely to consist of many companies that do not own any intangible assets at all.
Once we take into account past innovation strategy as explicative factors for the economicperformance in the crisis the results are less clear cut than in the first line of analysis. On the one hand technological and organizational innovations positively impact on firmperformance (labour productivity), but on the other hand training, environmental innovations and ICT have a negative impact on other performance indicators. The signs are driven by specific innovative elements that are included in each innovation sphere, thus it should not be correct to say that ICT, environmental innovations or training programs negatively impact on economic performances, rather it is better saying that some elements of those innovation spheres are negatively related to the performance of the firm in the crisis. Moreover, it can by hypothesized that the more dynamic and competitive firms before the crisis, opened to international competition and for such reason active on several innovation spheres are those more largely displaced by the drop in international demand with respect to the firms linked to local markets, which had a less intense innovative activity. More dynamic firms before the crisis could show worse economicperformance during the crisis, but they potentially have the capacity to survive and to better compete in the medium-long run. The resilience of the firm to the recession is not even related to the existence of complementarities between innovation strategies. The disruptive power of the recession seems to have shadowed the potential role of innovation synergies on the economicperformance of the firm. The same irrelevance of complementarities emerges between industrial relations and innovation strategies, although industrial relations when interacted with innovation activities turn their sign from negative to positive in some cases.
16 include economic factors, such as high costs or lack of demand, enterprise factors, as a lack of skilled personnel or knowledge, and legal factors, such as regulations or tax rules. Figure 4 in the appendix gives detailed reasons which explain these possible negative results. First, cost factors include: excessive perceived risks, too high costs, lack of funds within the enterprise, lack of finance from sources outside the enterprise (venture capital and public sources of funding). Possible knowledge related factors are: insufficient innovation potential (R&D, design, etc.), lack of qualified personnel within the enterprise or in the labour market, lack of information on technology or markets, deficiencies in the availability of external services, difficulties in finding co-operation partners, organisational rigidities within the enterprise (attitude of personal and managers towards change, managerial structure of the firm), inability to devote staff to innovation activity due to production requirements. Then, market factors involve: uncertain demand for innovative goods or services, and potential market dominated by established enterprises. Institutional factors are referred to: lack of infrastructure, weakness of property rights, and legislation, regulation, standards and taxation. Finally, other reasons leading firms not to innovate are the lack of necessity to innovate due to earlier innovations, and because of lack of demand for them.
export status (Arnold and Hussinger 2005, Bernard and Wagner 1997, 2001, Wagner 2007). For instance, employing data of the Statistical Office of Lower Saxony, Wagner (2002) uses a matching approach comparing export starters with non-starters. Beside the well-known fact that exporters are better in a range of different firm characteristics, the author finds only weak evidence of the impact of exporting on labor productivity. Arnold and Hussinger (2005) use 389 German firm-level data from the Mannheim Innovation Panel between 1992 and 2000. Applying a propensity score matching approach, the authors conclude that productivity causes exports and therefore self- selection is existent; however, the other way round does not hold. The only analysis that finds empirical evidence of causality running from exporting to productivity in Germany is the study by Fryges and Wagner (2008). Allowing for continuous treatment, the authors apply the generalized propensity score methodology to German micro-level data in Lower Saxony from 1995 to 2005. Their results show that only within different sub-intervals of the exports-to- sales ratio does exporting raise labor productivity growth.
Further, we check for composite reliability (CR) of the latent variables (see Table 1). Values over .70 indicate an overall reliability of the latent variables (Hair 1998). Results show a good reliability of the constructs. In addition, we check for the overall fit of the model. The results show that the model has an overall significance, p < 0.01, and an acceptable goodness of fit, despite being at theoretical limits. CFI (compara- tive fit index), CMIN/DF, root mean square error of approximation (RMSEA) indi- cate a good level of reliability of the model (see Table 2). The debate going over the multitude of indexes used to asses global fit of models (Škerlavaj et al. 2010; Hair et al. 2015) indicates, and research supports it (Bollen and Long 1993), that using more than one index is more convenient. In our case, supporting CFI and RMSEA, the degrees of freedom do not exceed 2 (1.748), thus, showing a good fit of the structural model to the data.
Many authors argue that regulation is the most important driver of eco-innovation (Porter and van der Linde 1995; Kammerer, 2009) with other incentives such as cost reductions, interest group campaigning and the effect of supply chain pressure also playing a large role in nurturing a greener environment (Leitner, Wehrmeyer and France 2010). In an imperfect market Rennings (1998) argues that eco-innovation policy is the most cost efficient strategy to deal with the double externality facing firms (this is due to the spill-over effects resulting from R&D expenditure on new innovations and from the spill-over effects resulting from the new products and services themselves). Kemp et al. (2000) propose that environmental regulations are valuable as they have both an informative and normative content in that they translate the demand for a greener environment into specific policies and they give strict guidelines to polluters and eco-innovators as to what is required. Indeed they suggest that the most important impact of eco-regulation is that it can change the level and nature of competition between firms. OFWAT (2011) concurs with this view and argues that regulations can drive innovation by incentivising firms to think differently while also providing them with information about how to change/adapt their technologies. In addition environmental regulation can often help firms with limited information about consumer needs and wants. Indeed by offering incentives to innovate eco-regulation can reduce (or eliminate) the prisoners dilemma faced by firms considering investing in novel forms of eco-innovation where consumer demand is not known (Zhang, Gensler and Garcia 2011). It is important to note at this point that regulation is not always needed. In some cases consumer demand, interest group pressures and social corporate responsibility is enough to induce firms to develop/adapt/use more environmentally friendly products, process and management systems (Hörte and Halila, 2008).
As for the analysis using measures of innovation different from productiv- ity, a recent contribution by Liu and Buck (2007) considers the effect of three main channels of international spillovers (R&D activities of foreign MNEs, export sales and expenditure on imported technology) on product innova- tion. The analysis is carried out by using a panel of sub-sector level data for Chinese high-tech industries, and new products are defined as either novel or improved products. The authors show a positive and significant effect of all the interactions between a measure of absorptive capacity and the three internationalization modes on product innovation; only export remains pos- itive and significant taken by itself. It is worth noting that while domestic R&D looses significance when the other variables are introduced, firm size remains one of the most relevant determinant of innovation in all specifica- tions. A second contribution by Salomon and Shaver (2005), using firm-level data, finds evidence of learning by exporting considering product innovation for Spanish manufacturing firms from 1990 to 1997. Information on product innovation is drawn from a survey where firms self-report the number of new or better products and the number of patent applications. The authors find a positive causal effect of both the status of exporter and export volumes on innovationperformance, conditional on the firm’s size, R&D expenditure and advertising intensity. In particular, the increase in product innovation takes place soon after exporting. In contrast to the previously mentioned contributions, firm size is never significant, while R&D expenditure and previous innovation have, respectively, a positive and a negative impact on innovation. Two other contributions provide evidence of the existence of a positive association between export and innovation without aiming at iden- tifying causal effects Castellani and Zanfei (2007) and Gorodnichenko et al. (2008) 8
competitive advantage and market share according to the level of importance they give to innovations, which are vital factors for companies to build a reputation in the marketplace and therefore to increase their market share. Metcalfe (1998) stated that when the flow of newness and innovations desiccates, firms’ economic structure settles down in an inactive state with little growth. Therefore, innovation plays a significant role in creating the differences of performance and competition among firms, regions and even countries. For instance, the study by Fagerberg et al. (2004) revealed that innovative countries had higher productivity and income than the less-innovative ones. OECD reports pointed out that companies that developed innovations in a more decisive way and rapidly, had also more qualified workers, paid higher salaries and provided more conclusive future plans for their employees. In fact, the effects of innovations on firmperformance differ in a wide spectrum from sales, market share and profitability to productivity and efficiency (OECD Oslo Manual, 2005).
industries, and differences in the propensity of firms to innovate (Brown and Eisenhardt, 1995: 343; Dosi, 1988). However, in this research tradition the actual product development process remains a “black box”. The second research tradition, which is business-oriented, opens up that “black box”. It examines how specific new products are developed, and indicates “the organizational stru ctures, roles and processes that are related to enhanced product development” (Brown and Eisenhardt, 1995: 375; Ancona and Caldwell, 1992). The entrepreneurs and the innovations are placed in the centre of the analysis . This second tradition, in the terminology of the economics -based research tradition, discusses in essence the efficiency of the innovation trajectory; to what degree are innovative inputs transformed into innovative outputs? It splits up into three strea ms. The three streams take product development as respectively (1) a rational plan (eg. NewProd , Cooper, 1992), (2) a communication web (Katz and Tushman, 1981) and (3) problem solving (Imai, et al., 1985; Takeuchi and Nonaka, 1986; Womack, et al., 1990). However, the three streams are unable to clarify the variety in innovation output and innovationperformance, as the unit of analysis is primarily the project level. The unit of analysis in the econo mics -based research tradition is the firm. As a consequence, the economics -based research tradition is better suited for enhancing our understanding of the relation between innovation output and innovation perfo rmance.
above market prices, which has a positive effect on firmperformance. This may be the reason as to why the innovative firms performed better after the financial crisis. As the market demand went down in 2008, innovative firms had the possibility to lower prices without losing profitability compared to non-innovative firms, which are assumed to have a smaller profit margin and less market power. Another reason that may explain the result is through the theory of absorptive capacity. According to this theory innovative firms are better at recognizing the value of new information and applying it in their business model. This can be the reason why innovative firms are more robust to the financial crisis than non-innovative firms. It is possible that innovative firms are better at predicting changes in the market and adapt their business to new circumstances. An example could be an innovative mobile application developer that can quickly collect and use information about changes in in the market. As a result of the financial crisis the developer decides to refocus the business to meet new demands and starts to sell mobile applications for unemployed people seeking new jobs. This process may not be as easy for an non-innovative firm that perhaps sees changes in the market, but has a harder time adapting the business quickly as the non-innovative business may be more capital intensive. The theory of dynamic capabilities relates to a similar effect but is more focused on the ability of firms to change, build and reconfigure both internally and externally to changes in the business environment. The start of the financial crisis of 2008 generated a wave of economic unrest in all of the U.S. and innovative firms’ ability to quickly mobilize resources and address needs in the market as a result of the financial crisis may be the reason why innovative firms perform better after the financial crisis than before.
Over the last twenty years, many labor market economists have strongly recommended that high unemployment should be reduced by making European labor markets more flexible. An example is the OECD's Jobs Study (1994). Subsequent to the Jobs Study, a literature has developed that tries to substantiate that more flexible labor markets would not only be favorable for employment, but may also allow for higher economic growth and higher productivity growth (e.g. Nicoletti and Scarpetta, 2003). Nonetheless, flexible labor contracts as determinants of innovation or productivity growth are still under-researched. There are only few firm-level studies, including Laursen and Foss (2003), Michie and Sheehan (2003), Kleinknecht et al. (2006), Arvanitis (2005), and Lucidi and Kleinknecht (2009). This is regrettable, as labor relations and human resour- ces have been suggested to have a significant impact on innovation through their influ- ence on knowledge processes (Amabile et al., 1996; Guest, 1997; Trott, 1998).
Table 10 estimates the impact of the intensity of ICT use upstream on the extend of IT outsourcing at the firmlevel. Column (1) presents the results of a basic specification and shows a negative impact (coef. -0,1649; std. err. 0.1101). However, the estimate is not very precise and cannot be interpreted as statistically different from zero. Note that this result is maintained when alternative variables that measure the ICT infras- tructure within the surveyed firms are introduced in the analysis, as well as addition firm-specific control variables in Columns (2)-(6). Interpreting this result cautiously, even though it is not significant, it hints at a negative relationship between the use of ICT by a firm’s suppliers (i.e. upstream) and that firm’s extend of IT outsourcing. In words, the more ICT intensive a firm’s suppliers are, the less IT outsourcing that firms require. Interestingly, this result suggests a substitution effect between inputs provided by suppliers with an intense use of ICT and a firm’s demand for external IT services.
Public procurement is the purchase of goods and services by governments and state-owned companies. During the last fifteen years, both at the European and national levels, public procurement has been intensely revitalised as a demand-side policy instrument to foster innovation. Such a renewed attention can be found in many documents and initiatives of the European Commission. Among other reports, we can recall the guide on public procurement as a driver of innovation in Small and Medium-sized Enterprises (SMEs) and in public services (European Commission, 2014). Furthermore, relevant EC initiatives have been directed to closely monitoring national policy frameworks and spending on innovation procurement across Europe, as well as to quantifying its impact compared to other procurement approaches (cf. EC, 2016a). Finally, increasing evidence that public procurement for innovation is still underexploited, especially in supporting innovative start-ups and SMEs, has led the Commission to express the need for a new guidance document (EC, 2016b). Then, on May 2018 the Commission has published a “Guidance on innovation procurement” to encourage public buyers of goods and services to use public procurement as a means to stimulate innovations (EC, 2018).
This cluster accounts for around 20% of the sample firms. These are firms that we call Moderate Innovators, combining practices inherent to the DUI mode with procedures specific to the STI mode. As Jensen et al. (2007) also concluded, in our test the cluster that combines two modes of innovation is that which reveals the strongest performance, as discussed in detail in the next section. In terms of characterization variables, this is a group consisting predominantly of SMEs located in a metropolitan context (either in Lisbon or Porto). In addition to SMEs, it is important to highlight the significance of micro firms in this cluster. It is moreover the only one where the probability of finding firms of this size is notably higher than in the other clusters. In general, firms in this group have a relatively higher level of technological intensity compared to those identified in the previous mode of innovation, with predominantly industrial firms of medium technological intensity (MLT and MHT), or firms operating in the field of knowledge services (KS).
16. Overall, 483 firms can be identified as one of these six types, and they represent 86% of the total sample. Therefore, we discuss the number of firms identified as these six types focusing on firm scale and location. Before we discuss these results, we must consider each type. Type 2 is the most desirable pattern for both economic development and environmental protection. Although type 1 is good for economic development, it is undesirable in terms of environmental protection. Here, we categorize types 1 and 2 as the “ improvement group .” Moreover, type 5 contributes to expanding the Chinese economy but is undesirable from an economic standpoint because its financial performance worsens. Type 15 is undesirable because its product design changes for the purposes of environmental protection. Another possibility is that scale efficiency decreases because of the decreased capital equipment utilization caused by declining demand. Finally, the corporate performance of types 13 and 16 renders them non-competitive in the market. Because these three types have negative TFP joint and TFP market
The second research tradition, which is business-oriented, opens up that ‘black box’. It examines how specific new products are developed, and indicates ‘the organizational structures, roles and processes that are related to enhanced product development’ (Brown & Eisenhardt, 1995, 375; Ancona & Caldwell, 1992). The entrepreneurs and the innovations are placed in the center of the analysis. This second tradition, in the termi- nology of the economics-based research tradition, discusses in essence the efficiency of the innovation trajectory; to what degree are innovative inputs transformed into innova- tive outputs? It splits up into three streams; the three streams take product develop- ment as (1) a rational plan, (2) a communication web and (3) problem solving, taking as objects of research, respectively, successful and failed products, project groups, and de- velopment projects. Well-known rational plan-researches are the Sappho-studies and the NewProd studies. Much of communication web-research starts from the work by Allen at MIT, and involves, e.g., Katz & Tushman (1981). Case-based research on the Japanese miracle by Imai, et al. (1985), and Takeuchi & Nonaka (1986), evolved into major MIT and Harvard research by, amongst others, Womack, et. al. (1990) taking the line that an innovation is about problem solving, as in the activities step model. The three streams of the second tradition are well established and, taken together, rich sources for further research. However, together they do not clarify the variety in innova- tion output and innovationperformance, because the unit of analysis is mainly the pro- ject level. For the relation between innovation output and innovationperformance the first economics-based research tradition is better suited. The unit of analysis in this tra- dition is the firm.
The notion that an innovative milieu can trigger the stimulus of economic change has been acknowledged by GREMI (Crevoisier 2004). According to GREMI, two key constructs form this concept; firstly, the milieu assists the process of collective learning which is crucial for SMEs and secondly, the networks within a milieu reduce uncertainties related to production, the market and support (Simmie 2005). The second element of Camagni’s definition signifies definite benefits from collective learning or socially embedded learning. As actors develop networks, they tend to trade their ‘know-how’ and exchange ideas and information through informal or formal collaborations. These individuals, making contacts with each other in a given location, represent the activities available in the milieu by exhibiting shared trust. Information and knowledge flow easily from their communication and thus learning entailing innovation is developed due to reduced uncertainties (Sweeney 1987).
The comparative analysis of the five instruments mentioned (Table 1) shows that all focus on input indicators, in some cases designated “conditions”, and output indicators. To a certain extent, there exists an almost linear view of innovation. However, the adoption of a more systemic approach, as analysed previously, brings a set of new indicators that the instruments used up until now have yet to totally take on board, such as the quality and intensity of the interactions established between the actors in the innovation system, only present in the Summary Innovation Digest, from the European Commission, and Innovation Digest, from the Innovation Barometer, the valuing of knowledge and the economic and social effects and impacts. Various limitations have therefore been identified.