Search results

This study aims to investigate how the intangible intensive nature of firms affects the value relevance of earnings and the book value of equity between profit- and loss-reporting firms. The study also examines how firms’ intangible intensity affects the value relevance of R&D outlays between profit- and loss-reporting firms.

An empirical analysis based on Ohlson’s (1995) framework is used. A total of 54,421 firm-year observations of Indian listed firms from financial years 1992–2016 constitute the study sample.

The findings suggest that the difference in the value relevance of earnings and the book value of equity between profit- and loss-reporting firms is more significant in non-intangible intensive firms than in intangible firms. Specifically, earnings are more value relevant in profit-reporting and non-intangible intensive firms, whereas book value of equity is more value relevant in loss-reporting and intangible intensive firms. The results also suggest that the difference in the incremental value relevance of R&D information between profit- and loss-making firms is higher in intangible intensive firms than in non-intangible intensive firms.

The findings of this study can help managers, standard-setters and investors make effective decisions.

This study offers insights into the impact of intangible intensity on the value relevance of aggregated and disaggregated accounting information between profit- and loss-making firms in institutional settings where capitalization of R&D expenditures is allowed.

Cities are host to many of the world’s knowledge intensive research and innovation clusters. As such, they are likely to be attractive locations for emerging market multinational enterprises (MNEs) seeking to engage in knowledge seeking “springboard” type firm-level catch-up strategies. The purpose of this study is to therefore explore whether city-based research-intensive clusters containing deep pools of location bounded (i.e. “sticky”) knowledge are a stronger driver for greenfield research and development (R&D)-related FDI projects for Chinese MNEs than they are for developed market MNEs.

The authors use logistic modelling on 97,163 worldwide greenfield FDI projects to explore the relative likelihoods of Chinese MNEs engaging in R&D-related greenfield (i.e. “strategic asset seeking”) FDI projects as well as how city type (global or research-intensive cluster city) moderates this relationship for Chinese MNEs.

The authors find that Chinese MNEs are more likely to engage in overseas R&D FDI projects (compared with other types of project) than DMNEs and that research-intensive city clusters hold a stronger attraction for Chinese MNEs than developed market MNEs.

The authors discuss how the research contributes to the debate on emerging market MNE catch-up theory, as well as that on sub-national city location choice, by highlighting the growing importance of sub-national geography to understanding strategic asset seeking related greenfield FDI.

Sub-national city location choice is an important driver of strategic asset seeking FDI for Chinese MNEs, one that both national and local city level policymakers should pay attention to.

Chinese FDI via aggressive mergers and acquisitions to acquire key technologies has been restricted in recent years. Policymakers must consider whether they may also wish to restrict Chinese greenfield FDI in R&D-related projects, which now exhibit a pronounced upward trend.

The authors highlight the growing importance of sub-national geography to understanding strategic asset seeking related greenfield FDI in Chinese MNEs (and how it plays, more generally, a central role in their strategies).

The objective of this work is to demonstrate the relationships between the two main processes of research and development (R&D) activities: the knowledge generation phase (KPP) and the knowledge commercialization, or transfer, phase (KCP), in a sector that is intensive in this type of activity, such as the pharmaceutical sector. In addition, within the framework of the general objective of this work, the authors propose two other objectives: (1) make advances in network efficiency measurement models, and (2) determine the factors associated with efficiency in the KPP and in the KCP in companies of the pharmaceutical sector in Spain.

A Network Data Envelopment Analysis (NDEA) model (Färe and Grosskopf, 2000) with categorical variables (Lee et al., 2020; Yeh and Chang, 2020) has been applied, and a sensitivity analysis of the obtained results has been performed through a DEA model of categorical variables, in accordance with the work of Banker and Morey (1986), to corroborate the results of the proposed model. The sample is made up of 77 companies in the pharmaceutical sector in Spain.

The results obtained point to a greater efficiency of pharmaceutical companies in the KPP, rather than in the KCP. Furthermore, the study finds that 1) alliances between companies have been the accelerating factors of efficiency in the KCP (but patents have slowed this down the most); 2) the quality of R&D and the number of R&D personnel are the factors that most affect efficiency in the KPP; and 3) the quality of R&D again, the benefits obtained and the position in the market are the factors that most affect efficiency in the KCP.

The authors have not found studies that show whether the efficiency obtained by R&D-intensive companies in the KPP phase is related to better results in terms of efficiency in the KCP phase. No papers have been found that analyse the role of alliances between R&D-intensive companies and patents, as agents that facilitate efficiency in the KCP phase, covering the gap in the research on both problems. Notwithstanding, this work opens up a research path which is related to the improvement of network efficiency models (since it includes categorical variables) and the assessment of the opinions of those who are responsible for R&D departments; it can be applied to decision-making on the aspects to improve efficiency in R&D-intensive companies.

This study aims to ascertain whether technological diversification (TD) enhances firm performance and explores the effect of patent portfolio balancing (PPB) on firm financial performance and the moderating role of research and development (R&D) intensity.

This study empirically investigates a panel dataset based on 296 information and communications technology (ICT) small and medium-sized enterprises (SMEs) over 5 years, using a fixed-effects panel regression with time-lagged and moderating effects. Data are collected from a government survey and a firm and patent database.

The relationship between PPB and return on assets (ROA) is negative, indicating that TD in SMEs adversely affects firm performance. R&D intensity positively moderates the relationship between PPB and ROA, implying that follow-up R&D after creating new patents could weaken the negative relationship between TD and firm performance. This moderating effect only occurs when R&D intensity is sufficiently high, suggesting that high R&D firms could be more successful at diversification.

As TD consumes many resources, managers should set the optimal level of diversification and recognise the need for follow-up R&D for successful diversification.

This study conceptualises a unique theoretical framework for the PPB of ICT SMEs, revealing the moderating role of R&D intensity in changing the negative influence of PPB on firm performance.

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.

Intangible capital (IC) is an important factor for economic growth and firm performance. The role IC has played has become even more crucial in recent decades, possibly influencing debt capacity and default risk assessment. This paper studies how entrepreneurial and employee-based IC affects financial leverage.

Employer–employee unbalanced panel data provided by Statistics Finland that refer to Finnish small and medium-sized enterprises (SMEs) are used. Intangibles are measured with an expenditure-based method. Employee-based IC and entrepreneurial knowledge are used to explain debt financing in SMEs.

The findings imply that IC-intensive firms have less debt capacity due to weak pledgeability and asymmetric information between borrower and lender. Entrepreneurs with managerial or financial knowledge increase the firm's debt capacity compared to other entrepreneurs, especially in knowledge-intensive services (KIS). One explanation is that the entrepreneurs are more competent in negotiating with lenders as the entrepreneurs possess better financial skills. Entrepreneurs with technical knowledge decrease the firm's debt capacity in all industries.

While some earlier research focused on the IC–financial leverage relationship, hardly any study has looked at entrepreneurial IC. This paper provides new insights by including entrepreneurial IC alongside employee-based IC.

Biotech companies stand as key actors in pharmaceutical innovation. The high risk and long timelines inherent with their R&D investments might hinder their access to funding, potentially stifling innovation. This study aims to explore into the appeal of biotech companies to capital market investors, whose financial backing could bolster the growth of the biotechnology sector.

This paper uses a dataset of 774 US publicly listed biotech firms to investigate their risk and return characteristics by comparing them to pharmaceutical firms and a sample of matched non-biotech R&D-intensive firms over the sample period 1980–2021. Tests show that the conclusions remain consistent across diverse methodological approaches.

The paper shows that biotech companies are riskier than the average firm in the market index but outperform on a risk-adjusted basis both the market and a matched group of R&D-intensive firms. This is particularly true for large capitalization biotech, which is also shown to provide a diversification benefit by reducing the downside risk in past crisis periods.

This paper provides insight relevant to the current debate about the overall performance of the biotech industry in terms of policy changes and their impact on small, early-stage biotech firms. While small and early-stage biotech firms are playing an increasing role in scientific innovation, this study confirms their greater vulnerability to financial risks and the importance of access to capital markets in enabling those companies to survive and evolve into larger biotech.

Prior research shows that religiosity affects the degree of managers' risk aversion. As a result, religious firms are less likely to invest in R&D activities. Moreover, US GAAP treats these investments as expenses. For this reason, religious firms have fewer expenses in their earnings and are less likely to be in financial distress.

Data are collected from Worldscope and the Churches and Church Membership files of the American Religion Data Archive website from 1985 to 2018. With 18,199 observations in US context, the authors used the marginal effect to test the mediating effect of R&D accounting treatment.

The authors find that the marginal effect of religiosity on financial distress with US GAAP is higher than the marginal effect of religiosity on financial distress with capitalization of R&D costs, which means that accounting treatment can explain the relation between religiosity and financial distress in the US context.

The authors used linear interpolation and linear extrapolation data to be able to conduct this research over a period of 1985–2018. For future researches, the authors propose to test other factors which can explain the relationship between religiosity and financial distress based on the ethics element.

These results should be of interest to regulators because treating R&D activities as expenses can destroy the accounting performance of firms that prefer investing in risky projects. This favoritism prevents the comparison between two firms in the same industry with different risk-taking behaviors. This problem is more prevalent if the authors have two firms with different ratios of religiosity. This paper suffers from a major limitation related to data availability.

This may be the first study that investigates why religious firms are less likely to be in financial distress. This paper notes that religious firms are less likely to be in financial distress because their conservative behavior towards R&D activities coincides with the conservative R&D accounting treatment. In fact, the mismatch between expenses and revenues from R&D activities can cause financial distress.

Emerging economies have been highlighted as an important growth source of the global economy. However, this group of countries has not received enough academic attention yet. Therefore, this study aims to identify the impact of research and development (R&D) expenditure on economic growth in emerging economies.

The theoretical framework of the production function is applied to quantitatively analyse the impact of R&D expenditure on economic growth with a sample of 29 emerging economies in the period between 1996 and 2019.

The panel cointegration test confirms the existence of long-run cointegration relationships between economic growth and independent variables in these emerging economies. Besides, the estimated results show that the national R&D expenditure has positive effects on economic growth from both direct and interaction dimensions. This evidence has filled the empirical research gap in the R&D-growth nexus in the case of emerging economies. Finally, while gross capital and education have positive impacts on growth, corruption has a harmful effect on economic growth in these countries.

The results highlight that policymakers should enhance R&D expenditure and R&D activities as the key national development strategy. The investment in R&D not only helps emerging economies avoid the middle-income trap but also pushes these countries to successfully join the group of developed countries.

To the best of the authors’ knowledge, this research is among the first to examine the impact of R&D expenditure on economic growth with a homogeneous sample of emerging economies. The results are obviously helpful for policymakers to use R&D as the key development strategy for supporting economic growth in emerging economies in the future.

This paper explores the nonlinear interactions of research and development (R&D) and advertising and their synergistic effect on firm performance using Tobin's Q. This study also aims to investigate differential synergy patterns under varying levels of exports with a precision impact on performance.

Unlike a conventional statistical approach, this study uniquely presents a neural network approach to explore the dynamic interplay of strategic factors. A multilayer perceptron neural network (MPNN) is designed to capture complex interaction patterns through a predictive analytic process.

This study finds that the impact of R&D and advertising is positive, with a greater effect on high-export firms. Moreover, the experiment results show that the synergy of R&D and advertising goes beyond the formatted positive/negative frame and actually has a reinforcing effect.

This study not only conveys the significant nexus of R&D and advertising for firm performance but also provides industry managers' practical means to assess the joint effect of R&D and advertising on firm performance. The proposed analytic mechanism in particular provides pragmatic decision support to managers in harmonizing their R&D and advertising efforts for a foreseeable impact.

This paper presents an innovative analytic process using the MPNN to explore the synergy between R&D and advertising. In addition to offering new perspectives on R&D and advertising, this study presents pragmatic implications for managing those strategic resources to meet performance targets.