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In this chapter, we analyzed the effects of internationalization on innovation, productivity, and firm performance among multinational pharmaceutical companies as representatives of a global knowledge-based industry. The empirical analysis used multiple stepwise regressions based on a sample of 149 firms headquartered in Europe and the US. The results indicate that innovation outcomes are positively correlated to the number of foreign subsidiaries (scope internationalization), whereas surprisingly, formal research and development (R&D) does not seem to directly influence innovation. This suggests that the firms benefit from local overseas subsidiaries to create and implement new innovative offerings. The number of foreign subsidiaries has a U-shaped relationship to patent productivity suggesting that firms can gain advantages by locating cost-intensive activities in low-cost countries and critical tasks in advanced market locations. Firm performance has a U-shaped relationship to sales abroad (scale internationalization) and the relationship is further enhanced by a high focus on R&D. This suggests that sales abroad enable scale economies, where R&D improves quality and relevance of products and thereby boosts performance. Finally, to validate the findings we conducted two semi-structured interviews with representative industry experts and gained further insights for an extended interpretation of results.

This chapter measures total factor productivity growth (TFPG) using Malmquist productivity index (MPI) and the growth of MPI of Indian Textile Industry employing nonparametric data envelopment analysis (DEA), during 1995–2016, exploring company (firm) level Center for Monitoring of Indian Economy (CMIE) Prowess data; examines whether TFPG has improved after the withdrawal of multifiber trade agreement (MFA) since 2005; decomposes TFPG into technical change (TC), technical efficiency change (TEC), and scale efficiency change (SEC); and explains the factors behind the movement of TFPG, considering the effect of R&D (RD), exports (EX), marketing expenditures (MKTs) advertisement expenditures (ADVs), imports (IMP), using second-stage panel regression. Empirical evidence supports fluctuating pattern of TFPG during 1995–2016, with a marginal declining tendency. TFPG has increased in 1999–2000, 2000–01, 2009–10, and 2012–13. After dismantling MFA, MPI level has significantly declined, with an increase in its growth rate, but the increase is not statistically significant. The effect of EX, RD, ADV are nonlinear, U-shaped, and IMP and MKT are inverted U-shaped, implying that the sign effect of any variable depends on its size. There are joint interaction effects of (a) RD and EX; RD and MKT which are positive, (b) ADV and MKT as represented by the ratio (ADV/MKT), having nonlinear inverted U-shaped relation. The joint interaction effect supports that the impact of one variable depends on the magnitude of other. The marginal effect of EX, IMP, and ADV are positive; increase in these variables promotes TFPG. The greater role of ADV over MKT is evident. The marginal effect of RD is negative; the average level of RD is too low to generate positive effects, and, thus, there is an urgency of increasing RD. The promising part of the decomposition analysis is that highest contribution to growth rate of TFPG is the growth rate of TEC followed by growth rate of TC, and thus by increasing TEC and TC, higher growth rate of TFPG is achieved and may be beneficial in the long run and may lead to absorption of economic shocks for an economy facing recession in its output growth. Some policy suggestions are made for boosting up TFPG.

Efficiency and productivity has always being a key issue in economic science. The analysis of the impact of research and development (R&D) has been extensively studied in industries and countries of more or less aggregated level. This chapter aims to investigate the impact of corporate R&D in performance of low-tech industries, medium-tech, and high-tech in OECD countries.

This chapter aims to answer the questions: Is the impact of R&D significant for all types of industries? If so, what are the differences and the magnitude of these effects in each of these types of industries?

To this end, an unbalanced data set from 2000 to 2011 was collected for the main countries of Europe and the United States concerning low-, medium-, and high-tech to analyze the impact of the magnitude of corporate R&D and capital accumulation on productivity of these industries. The productivity of industries was measured by stochastic parametric frontier functions, in order to measure the efficiency of R&D and accumulation of capital on labor productivity.

The main results highlight the impact of corporate R&D on productivity of high-tech industries, but for other industries those relations are not clear. However, capital accumulation became crucial on low technology to improve their performance. These results, although needing to include a more extensive data set of industries across countries, refer the need for policy and decision makers to allocate public funds for R&D in high-tech industries, while the investment in capital seems crucial, particularly in low-tech industries to improve the productivity.

There is growing empirical evidence that firm heterogeneity is technologically non-neutral. This chapter extends the Gandhi, Navarro, and Rivers (2020) proxy variable framework for structurally identifying production functions to a more general case when latent firm productivity is multi-dimensional, with both factor-neutral and (biased) factor-augmenting components. Unlike alternative methodologies, the proposed model can be identified under weaker data requirements, notably, without relying on the typically unavailable cross-sectional variation in input prices for instrumentation. When markets are perfectly competitive, point identification is achieved by leveraging the information contained in static optimality conditions, effectively adopting a system-of-equations approach. It is also shown how one can partially identify the non-neutral production technology in the traditional proxy variable framework when firms have market power.

“It should also be noted that the objective of convergence and equal distribution, including across under-performing areas, can hinder efforts to generate growth. Contrariwise, the objective of competitiveness can exacerbate regional and social inequalities, by targeting efforts on zones of excellence where projects achieve greater returns (dynamic major cities, higher levels of general education, the most advanced projects, infrastructures with the heaviest traffic, and so on). If cohesion policy and the Lisbon Strategy come into conflict, it must be borne in mind that the former, for the moment, is founded on a rather more solid legal foundation than the latter” European Commission (2005, p. 9)Adaptation of Cohesion Policy to the Enlarged Europe and the Lisbon and Gothenburg Objectives.

This study examines how foreign R&D investment may explain interfirm variations in productivity performance of home country firms in terms of spillovers. Many have studied spillovers from MNCs to host country’s firms, but there is still scarce evidence on spillovers from outward FDI to the home country. This study analyzes spillovers from foreign R&D investment and hypothesizes that the benefit of outward R&D spillovers occurs only when knowledge accumulated in foreign R&D centers is effectively transferred to MNCs’ parent companies at home. This benefit depends on the mandate of foreign R&D units, their embeddedness in the host economy, and their entry mode. Using detailed firm-level data for Switzerland, our findings seem to support our arguments.

Systemic industries comprise groups of firms making component products that are valued as complements by consumers (PC, automobiles, aircraft, networking). In this study, we investigate the distribution of research effort across the technological system by individual firms as a basis for building competitive advantage. Our empirical setting is a sample of component makers in the personal computer system. We show that even in a sample dominated by focused component manufacturers, diversified research effort in the broader technological system improves R&D productivity in the component technology. Broad scope R&D in the rest of the system also increases the marginal benefits of research efforts in the component technology, though at a diminishing rate. We explore the determinants of this complementarity between the scope of system level research and the focus on component level research, and derive implications for competitive advantage.

This chapter applies the five drivers of productivity framework to regional microdata for Egypt and extends it by introducing an index of industrial clusters as an explanatory factor of the productivity performance of local private sector firms. Applying structural equation models, the geographic concentration of sectoral economic activity is found to have a positive and statistically significant effect on labor productivity. The transmission mechanism is conjectured to be the positive spillovers that are created, which local firms can tap into. In contrast, a higher concentration of skilled workers in an industrial sector in a region is associated with lower levels of labor productivity – a finding that suggests there may be structural deficiencies in the allocation of skilled workers. Regional policy should focus on net investments in gross capital formation throughout the country, for which the national and regional governments should improve how public investments are managed and the institutional framework – including the rule of law, bureaucracy and red tape, conflict of interest, transparency, and governance – so that private investment (both local and foreign) may substantially increase.