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This study aims to investigate whether there are disparities in research and development (R&D) internationalization between latecomers from economy-level technological disparities and firms with ownership-specific technological capability differences in the wind turbine industry.

Employing econometric analysis based on patent indicators, the authors examine the patent data assigned by the United States Patent and Trademark Office (USPTO) to the technologically advanced economy and the technologically emerging economy.

This study finds that latecomers from technologically advanced economies behave with no difference from early leaders in terms of international co-invention (INCO) but do show differences in another indicator – native ownership of foreign inventors (NOFIs). Additionally, latecomers from economy-level technological disparity show significant differences both in both INCO and NOFI. These results indicate that the latecomers from technologically advanced economies not only possess the nature of latecomers which motivates them to seek knowledge from foreign economies but also benefit from their advanced home base, thereby prompting them to internationalize and access cost-effective R&D resources. Moreover, the results demonstrate that latecomers from technologically emerging economies are more prone to engage in R&D internationalization to augment their own home base compared with firms from advanced economy.

This study extends the literature on R&D internationalization by introducing novel perspectives. It distinguishes some apparent distinctions of the tendency of R&D internationalization between latecomers under economy-level technological disparity as well as firms from ownership-specific technological capabilities differences. Additionally, this study disaggregates R&D internationalization into twin key dimensions: INCO and NOFI. These findings allow for a comprehensive understanding of the differences in the firm's R&D internationalization under economy-level technological disparities and ownership-specific technological differences. These findings offer valuable insights for decision-makers in navigating global innovation activities by highlighting the diverse economy-level technological advantages as well as ownership-specific advantages.

The UAE only officially formed in December 1971, now has seven Emirates joined together as a nation under one President. Since its establishment as a sovereign, independent country around just 50 years ago, the UAE has accelerated advancement across numerous sectors at notable speed, and science, technology, and Research & Development (R&D) sectors are no exception. Research Management and Administration (RMA) as a profession is in the relatively early stages of being recognised as a distinct and niche skill set; at present, the UAE largely imports experienced international talent to fill RMA roles. However, the country’s strides in progressing R&D infrastructure and goals of elevating ranks from regional to global R&D leader is beginning to generate a legitimate career ladder for RMA professionals across the country. This, paired with the UAE’s commitment to engage more Emirati nationals in the workforce, is cultivating a viable environment for the RMA profession to emerge more significantly from general administration and begin generating a skilled talent pipeline of RMA professionals within the UAE.

This chapter illustrates the concept of organisational innovation leadership (OIL) through a case study of the organisational transformation of Eddyfi Technologies to achieve superior innovative capacity through synergetic centralisation. The case study focusses on the real challenges faced when effecting organisational transformation, and how innovation leadership practices provided constructive resolutions that culminated in a successful reorganisation. We find that effective innovation leadership is conveyed primarily through establishing close relationships, open communication, and setting the example in a consistent and strict manner.

This study aims to investigate the effect of intangible capital (e.g. intangible investments and research and development (R&D) expenditures) on future profitability in an emerging economy and the moderating role of economic policy uncertainty (EPU) for companies listed on the Tehran Stock Exchange.

To this aim, information about 210 companies during 2014–2021 was collected. This study calculated EPU based on the inflation rate, interest rate, exchange rate and economic growth.

The results showed that both R&D expenditures and other intangible investments positively affect future profitability. Moreover, EPU decreases the positive effect of R&D expenditures and other intangible investments on future profitability. Hypothesis testing based on ordinary least squares and generalized method of moments regressions confirmed these results. This study emphasizes the urgent need to adjust how they operate the business during the COVID-19 pandemic.

The nature and degree of intangible assets and R&D expenditures in firms in emerging markets is an interesting area of research. However, empirical studies in this area have not led to any unanimous conclusion in emerging markets. Moreover, intangible assets and R&D expenditures become very important in the economy affected by the financial crisis and conditions of uncertainties. In light of the COVID-19 crisis, significant changes occurred at all levels and affected accounting-related issues, and the present study highlighted COVID-19. The findings of this research will not only help the managers of companies in developing countries but also, because of the dearth of similar research, they can help managers in developed countries and the global community.

This study aims to explore the dynamic interplay of key resources (i.e. research and development (R&D), advertising and exports) in affecting the performance of USA manufacturing firms. Specifically, the authors examine the dynamic impact of joint resources and predict differential effect scales contingent on firm capabilities.

This study presents a combined multiple regression analysis (MRA)-multilayer perceptron (MLP) neural network modeling and investigates the complex interlinkage of capabilities, resources and performance. As an innovative approach, the MRA-MLP model investigates the effect of capabilities under the combinatory deployment of joint resources.

This study finds that the impact of joint resources and synergistic rents is not uniform but rather distinctive according to the combinatory conditions and that the pattern is further shaped by firm capabilities. Accordingly, besides signifying the contingent aspect of capabilities across a range of resource combinations, the result also shows that managerial sophistication in adaptive resource control is more than a managerial ethos.

The proposed analytic process provides scientific decision support tools with control mechanisms with respect to deploying multiple resources and setting actionable goals, thereby presenting pragmatic benchmarking options to industry managers.

Using the theoretical underpinnings of the resource-based view (RBV) and resource orchestration, this study advances knowledge about the complex interaction of key resources by presenting a salient analytic process. The empirical design, which portrays holistic interaction patterns, adds to the uniqueness of this study of the complex interlinkages between capabilities, resources and shareholder value.

The rise of emerging economies in the innovation landscape has often been attributed to the positive spillovers of innovation capabilities from multinational corporations (MNCs). However, it is less certain that their innovative capabilities imported from the home country function effectively in the host country from the outset. This study examines the performance of the innovation capabilities of MNC subsidiaries in emerging economies over time by considering the gradual process of their learning about host countries.

We employed stochastic frontier analysis to measure innovation capabilities, our focal construct. For regression analysis, we applied the Mundlak estimator, a variant of the fixed-effects panel estimator, to a sample comprising subsidiaries of MNCs from technologically advanced nations operating in Korea between 2006 and 2016.

Our results indicate that the innovation capabilities of MNC subsidiaries initially underperform those of local firms but improve over time, eventually surpassing the capabilities of their local counterparts. Furthermore, our findings reveal that institutional distance amplifies the underperformance of the innovation capabilities of MNC subsidiaries.

This study contributes to the literature by extending both theoretical development and empirical measurement of innovation capabilities in cross-national settings. Additionally, it deepens our understanding of whether and how MNC subsidiaries adapt their innovation capabilities to the local market environment.

This study aims to analyse how multinational corporations (MNCs) organise value chain activities to penetrate new market segments. It contributes by expanding traditional decisions regarding the vertical fine-slicing of value chain activities (whether performed internally or externally) and the consideration of resource-sharing decisions (integration or separation) for each value chain function.

The authors draw on primary data collected from two case study firms operating in the large emerging Chinese market: Volvo Construction Equipment AB and Epiroc AB. In-depth cases illustrate how foreign MNCs expand into new market segments and simultaneously target both the lower-priced mid-market and the premium segments in the Chinese mining and construction industry.

The results reveal that product diversification creates challenges for managers who must oversee new (vertical) value chains, often simultaneously. Beyond geography and modes of governance, managers must decide whether to integrate or separate value chain activities for the new product lines. The study identifies four main strategic choices for firms to address this complexity, focusing on the decision to internalise or externalise (i.e. within or across organisational boundaries) and integrate or separate value chain activities between different product lines.

This study builds upon the internalisation theory and recent international business contributions that focus on value chain configurations to explain MNCs’ product diversification as a growth strategy in a host emerging market. It also sheds light on the choice of conducting new activities in-house or externally and elucidates firms’ managerial decisions to operationally integrate or separate individual value chain activities. The study provides insights into the drivers explaining managerial decisions to configure value chain activities across product lines and contributes to the growing body of literature on MNC activities in emerging economies by highlighting that product diversification impacts entry mode diversity and resource sharing across units.

The paper develops a model for enhancing R&D productivity for Indian public funded laboratories. The paper utilizes the productivity data of five Council of Scientific and Industrial Research (CSIR) laboratories for analysis and to form the constructs of the model.

The weighted average method was employed for analyzing the rankings of survey respondents pertaining to the significant measures enhancing R&D involvement of researchers and significant non-R&D jobs. The authors have proposed a model of productivity. Various individual, organizational and environmental constructs related to the researchers working in the CSIR laboratories have been outlined that can enhance R&D productivity of researchers in Indian R&D laboratories. Partial Least Squares-Structural Equation Modeling (PLS-SEM) was used to find the predictability of the productivity model.

The organizational factors have a crucial role in enhancing the R&D outputs of CSIR laboratories. The R&D productivity of researchers can be improved through implementing the constructs of the proposed model of productivity.

The R&D productivity model can be adapted by the R&D laboratories to enhance researchers’ R&D involvement, increased R&D outputs and achieving self-sustenance in long run.

The R&D laboratories can initiate exercises to explore the most relevant factors and measures to enhance R&D productivity of their researchers. The constructs of the model can function as a guideline to introduce the most preferable research policies in the laboratory for overall mutual growth of laboratory and the researchers.

Hardly any studies have been found that have focused on finding the measures of enhancing R&D involvement of researchers and the influence of significant time-intensive jobs on researchers’ productivity.