SOCIAL ECONOMIC POTENTIAL
Introduction
The social economics theory heavily relies on the concept of „social innovation‟ which is significant in scientific research, business administration, public debate and ethical controversy. The business administration literature increasingly stresses how many technological innovations fail if they are not integrated into a broader perspective in which changes in social relations within, but also embedding, the firms play a key role (Moulaert, 2016). Besides, the forthcoming transition to Industry 4.0 threatens to invoke potential social problems through the social dimensions of new technologies and innovations. The scientific discussion of social innovation in the context of Industry 4.0 sheds light on the potential job losses, human substitution by technological innovations, end of privacy, and potential loss of human control (Morrar et al., 2017).
However, in order to foresee all forthcoming socio-economic consequences of further technological progress, the stream of social economics literature lacks deeper insights on firms‟ innovative incentives that have been studied by representatives of empirical industrial organisation and new trade theories. This article strives to fill up this gap providing a short but comprehensive review thereof.
The evidence provided by the representatives of empirical industrial organisation theory
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The representatives of the empirical industry organisation found and confirmed the wide heterogeneity of companies in terms of productivity, distinguishing highly productive exporting companies. The importance of productivity for companies‟ survival in a competitive struggle has been confirmed too. These facts are confirmed by both static and dynamic empirical studies, as follows: Syverson (2011); Das et al.
(2007), Eslava et al. (2008), Foster et al. (2008), De Loecker (2011), Roberts et al. (2012), De Loecker et al. (2014).
An important group of empirical dynamic models consists of research on investment by companies in the innovation of goods or processes. First of all, there are Shaked et al. (1982, 1983), Gabszewicz et al. (1979) theoretical models, from which it follows that undertakings have to make additional investments in order to improve the quality of goods, and the number of undertakings remaining on the market is exhaustive; the first market entered companies are inclined to occupy high-quality commodity niches. Later, following models of the industrial organisation (Dutta et al. (1995), van Dijk (1996), Lambertini et al. (2007)) showed that, in the absence of the financing possibilities for quality innovation in goods, companies tend to supply low-quality goods initially. Bacchiega et al. (2011) notice that even though, as evidenced by various empirical observations, the innovation in goods and processes is often combined, the interaction between investment in the quality of goods and the reduction of marginal costs is still not investigated sufficiently enough. In his model, companies offering high and low-quality goods in an oligopolistic competition of vertically differentiated goods have to decide on the investment in R&D and innovation activities: process or commodity innovation. The theoretical modelling results showed that the low-quality companies in the Bertrand competition choose process innovations, and the companies selling high-quality goods continue to invest in improving the quality of the goods. In general, as Bacchiega et al. (2011) notice, in the industry organisation‟s literature, the approach based on the technological lifecycle prevails, i.e. companies prefer to innovate in goods, but not in processes, because, as is believed, the return on goods innovation is higher and faster. However, Adner et al. (2001) offered the example of Škoda that showed the opposite: it may also be the case when companies are seeking to reduce marginal costs before they invest in product innovation. Meanwhile, by employing the Schmitt‟s (2003) model of vertical differentiation, Bacchiega et al. (2011) demonstrated that, if companies are heterogenic in terms of their abilities, they will also differ
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in their tendency to deploy process innovations: more efficient enterprises would always be tempted to continue process innovation regardless of how much they invest in improving product quality. By the way, Spielkamp et al. (2009) found that investing in R&D and innovation activities are linked to high uncertainty and risk: even 87%
of European enterprise-tested innovation projects were financed by their funds, but not by credit institutions.
The results obtained by modelling through the gaming theory revealed that incentives (in the form of expected profits) to invest in R&D and innovation activities are higher when the competition is lower, but companies are more likely to invest in R&D and innovative activities to reduce their variable costs in the case of more severe competition. The model developed by Qiu (1997) examined both Cournot and Bertrand competition, in which companies can reduce their marginal costs by R&D and innovative activities, i.e. by increasing their productivity. It was concluded that greater profitability, specifically for the Cournot competition, should encourage companies to engage in R&D and innovative activities. Similar results were obtained by Symeonidis (2003), who created a model with Bertrand and Cournot competition equilibrium when companies invested in R&D and innovative activities. Meanwhile, Aghion et al. (2006) empirical studies demonstrated that companies and industries with the most advanced knowledge and technology are more likely to innovate and increase their efficiency, but only if there is competitive pressure. It can, therefore, be assumed that the most productive oligopolistic enterprises are keen to accumulate not only financial resources but also knowledge necessary for the pursuit of R&D and innovative activities. In addition to these findings, in their model, Filippini and Vergari (2012) found out that in Bertrand competition among oligopolistic companies the owners of innovations had no interest in disseminating of obtained knowledge, but favours the granting of exclusive rights to innovation based on licences, which promotes the differentiation of goods. However, in their model, Brander et al. (2015) showed that companies invest in horizontal differentiation of their products only if such investments are sufficiently efficient, i.e. product differentiation is not too costly. Also, the results suggested that Bertrand Company is always more tempted to differentiate its products than the Cournot one, while Bertrand Company is not more effective than the Cournot firms in differentiating their products – in the case of Bertrand‟s competition, the surplus of consumers is less than was previously thought.
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Special attention should also be drawn to the Aghion et al. (2002) study, where he analysed the relationship between the intensity of competition and investment in R&D and innovation activities.
Calibrated and specified according to the basis of related empirical studies the suggested theoretical model showed that there is an upside-down relationship between the intensity of competition and investment in R&D and innovation activities: as the intensity of competition increases, the incentives for innovation decrease. However, when higher levels of competition are reached, incentives to invest in productivity or differentiation of goods (e.g. in the improvement of product quality) increase again as a result of the rising expected return on investment, related either with greater differentiation of the goods or with the higher expected productivity of the innovating enterprise. The latter study demonstrated that the research of incentives for investing in R&D and innovation activities must be taken into account while the intensity of competition, the productivity level of companies and the differentiation of goods were studied.
The uneven distribution of firms‟ skills in terms of productivity and goods differentiation also leads to an uneven distribution of the ability of firms to carry out R&D and innovative activities and investment in it. This connection was affirmed by Redding‟s (2010) empirical research, which suggested that, in those industrial sectors in which R&D and innovative activities were carried out consistently, the division of enterprises by productivity and other characteristics of their heterogeneity in the industry is permanent.
According to Redding (2010), in the USA, one-third of all producers every five years enter and withdraw from the market. Moreover, they differ significantly in terms of productivity, size, the intensity of capital and knowledge usage, and other characteristics. Also, it should be noted that in the dynamic industry sectors, innovation in boosting productivity and competitive advantage (product differentiation, etc.) occurs permanently.
From all empirical dynamic industrial models in the field, in particular, should be distinguished the Doraszelski‟s et al. (2013) empirical dynamic model which investigated the impact of investments in R&D and innovation activities on the productivity of enterprises and their high heterogeneity under this indicator. In the model, the specification of the first-line controlled Markov process assumes that companies accumulate productivity shocks. Therefore, undertakings experiencing a flat-rate cost of R&D and innovation activities were not
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necessarily characterised by the same level of productivity as it was assumed in the standard structural empirical models. Thus, it was observed that investments in R&D and innovation activities were linked to high uncertainty and that the link between them and productivity growth is not linear. Kancs et al. (2012) used this empirical phenomenon for their econometric strategy and found out that the productivity of companies might and depended on the intensity of investment in R&D and innovation activities. However, the growth of productivity becomes significant only from the specific threshold of the investment intensity. It was also observed that the high-technology manufacturing sectors were characterised by a higher intensity of investment in R&D and innovation activities and higher productivity growth.
In his empirical dynamic model, Amoroso (2014) found that the co-operation between undertakings and with scientific institutions in the R&D and innovative activities significantly reduces the costs and risks of such activities (investments in innovative activities compared to investments in R&D activities are 1.5 to 3 times lower). However, there is a significant likelihood that companies opt for co-operation only when they can reduce the cost of innovation development by at least a quarter, while in case the cost of the R&D this rate costs saving rate should reach at least 50%. This study also illustrated to what extent the costs of R&D and innovative activities were important for businesses. Therefore, it was not a coincidence the evidence Santos (2015) found in her empirical dynamic model that the higher company‟s market shares the greater investment in R&D and innovative activities, i.e. they were linked positively. These conclusions were supported by a more detailed study of Foster et al. (2016), also based on a dynamic model. They disclosed that the differences in the companies‟ markets shares did not reflect their heterogeneity in terms of productivity. The demand for company goods is characterised by inertia. The demand for goods is being developed year by year; therefore, businesses that lunch new goods in the market is slowly accumulating in demand.
Many of these and other empirical studies that were not mentioned in this literature review indicated that they were inspired by the theoretical model for the heterogeneity of enterprises (in terms of productivity) provided by Melitz (2003) where he revealed the significance of a new trading theory. It is still not uncommon that empirical industrial organisation research is often searching for evidence of this and subsequent analogous theoretical models.
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The evidence provided by the representatives of new trade theory The new trade theory has its contribution to the theory of firms‟
innovations and their incentives in this kind of activities.
This theory enjoys many same assumptions that it borrowed from industrial organisation theory in particular in terms of goods differentiation and firms‟ heterogeneity as the basis for theoretical models. Therefore, since an industrial organisation theory and a new trade theory have a lot of in common in terms of corporate behaviour, new insights or methodological solutions, made in the field of one of these theories, might contribute to another one.
Although, Melitz (2003), in essence, only improved the basic pattern of the new trade theory (1979, 1980, 1991, 1995) in such a way as to enable the heterogeneity of the undertakings to be assessed in terms of their productivity, it meant a huge advance in the new trade theory that up to then was based on the assumption of firms homogeneity (uniformity). These improvements generally made monopoly competition patterns more realistic and opened up new opportunities for economic analysis, which were lacking in the industrial organisation.
The model proposed by Melitz (2003) attracted significant economists‟
interest: as mentioned, a wide range of theoretical and empirical works followed his ideas. For example, Helpman et al. (2003) showed that companies with higher productivity could carry out more expensive projects. Also, the authors published empirical research showing that exporters have higher productivity than companies operating in national markets only, while multinational enterprises had significantly higher productivity (on average more than 15%) compared to ordinary exporters. They also established empirically that the company‟s distribution by productivity could be described according to the Pareto distribution function. It means that the productivity ceteris paribus is a factor determining the market share of the undertakings. In other words, there are less productive firms on the market which, without being able to cover the costs of export and direct investment abroad, only focus on domestic demand. Furthermore, only a small proportion of companies whose productivity is sufficient to cover the fixed costs of the export or foreign direct investment activities can decide on export or foreign direct investments.
Many studies, such as, for example, provided by Bernard et al.
(1999) and Clerides et al. (1998) found out that companies had already reached higher productivity before they entered the export market, while they innovated in anticipation of the start of exports to overseas markets
78 (Melitz, 2008).
Intuitively it can be assumed that, if the largest companies are the most productive, the prices of their goods should also be the lowest.
However, many empirical studies show that the largest and most productive companies do not have a negative correlation between productivity and commodity prices. On the contrary, their prices are significantly higher than those of competitors. The reason for these hides beyond their investments in R&D and innovative activities performed to enhance the differentiation of their goods, especially in terms of the value of the goods expected by buyers. As Gervais (2013) noticed, these findings contradicted the formal model of Melitz (2003).
As Schott (2004) illustrated with an empirical example of exports to the United States, companies operated in high income, capital and knowledge-based countries exported to them at relatively higher prices.
Following the data, Gervais (2013) made some insights: firstly, more productive companies were making more attractive products for consumers; secondly, if consumers were rational for differentiated goods, their exposed valuations reflected not only the efficiency of a production process but also the quality of products. Duvaleix-Tréguer et al. (2015), noticed that the quality of the enterprise products correlates with its investment intensity, with the costs of R&D, the innovation of the product and technological processes and the cost of acquiring the quality standard certificates. The obtained evidence showed that more efficient companies were selling more high-quality products, covering more markets.
As revealed by Baldwin‟s et al. (2009) empirical research, the high-quality and priced goods were the most competitive; their exports could cover the highest commercial costs associated with their large transportation distances. Therefore, more distant markets were reached by the export of on average higher-quality goods. In other words, if consumers were concerned about the quality of an item, then the product at which the highest price is claimed is the most competitive and the lowest prices observed were the least competitive (Baldwin et al., 2011).
In additions, Mayer et al. (2011), found that greater productivity for companies also allows them to produce and sell more product types, but by intensifying competition between companies, they decline the production of the least profitable products (the companies produce only the most efficient products reflecting increasing competition).
Therefore, increased productivity allows companies to invest more in the development of a product mix, which means that companies can also
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invest more in the quality of goods with increasing productivity. In other words, more productive businesses can invest more in product differentiation.
A particular attention should be drawn to the Johnson (2012) Heterogenic Enterprise Model which showed that productivity could have a compensatory effect on prices: on the one hand, higher productivity lowers prices by reducing marginal production costs; on the other hand, higher productivity allows the company to improve the quality of products, which increases marginal costs and prices. The fact that high-productivity enterprises would set absolute higher or lower prices than lower productivity companies depended on the company‟s incentives to improve product quality.
Melitz et al. (2008) showed that larger countries had a wider range of goods, and also contained more and more productive companies with lower margins due to intensified competition, although businesses still earned higher profits (due to higher sales). The study revealed that competitive pressures were forcing companies to increase their productivity. These conclusions were confirmed by Baldwin et al.
(2014) showing that companies do not need to be large; they need to be efficient in order to remain competitive.
Conclusions
The literature of empirical industrial organisation and new trade theories has been concentrating heavily on firms‟ innovative and R&D incentives in the last decades. Therefore, its review might give a hand to the further development of the theory of social economics.
A lot of covered studies confirm that the uneven distribution of firms‟ skills in terms of productivity and goods differentiation also leads to an uneven distribution of their ability to carry out R&D and innovative activities. The Pareto distribution function suits as an approximation for a firm‟s distribution in terms of their productivity and hence – firms‟ incentives for costly activities of new products or processes development. Only small percentage of firms can afford it.
However, these highly productive firms have great potential to carry out new value-adding products and processes development, while gathering market power and market share. In terms of competition, it potentially might result in tougher conditions for firms‟ activities and even leaving the market.
Therefore, social economics should take greater attention to all the threats and potentials that might bring further technological
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advancement, especially in terms of the forthcoming fourth industrial revolution.
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