Purpose
The purpose of this paper is to explore and compare the extent of intellectual capital (IC) and its four components in high-tech and non-high-tech small and medium-sized enterprises (SMEs) ...operating in China’s manufacturing sector, and to examine the relationship between IC and the performance of high-tech and non-high-tech SMEs.
Design/methodology/approach
The study uses the data of 116 high-tech SMEs and 380 non-high-tech SMEs listed on the Shenzhen stock exchanges during 2012–2016. The modified value added intellectual coefficient (
MVAIC
) model is used incorporating four components, namely, capital employed, human capital, structural capital and relational capital. Finally, multiple regression analysis is utilized to test the proposed research hypotheses.
Findings
The findings of this paper reveal that there is significant difference in
MVAIC
between high-tech and non-high-tech SMEs. The results further indicate a positive relationship between IC and financial performance of high-tech and non-high-tech SMEs. Specifically, IC is positively associated with firms’ earnings, profitability and operating efficiency. Additionally, capital employed efficiency, human capital efficiency and structural capital efficiency are found to be the most influential value drivers for the performance of two types of SMEs while relational capital efficiency possesses less importance.
Practical implications
This paper will provide a valuable framework for executives, managers and policy makers in managing IC within the Chinese context.
Originality/value
To the best knowledge of the authors, this is the first empirical study that has been conducted on high-tech and non-high-tech SMEs in the manufacturing sector in China.
In a time when socially impactful technology plays a central part in a variety of political and societal dynamics and processes, new forms of secrecy have emerged. The “black box” metaphor is used to ...define socio-technical systems that operate in non-transparent and prone-to-abuse ways. Frequently, Big Tech companies, their platforms, services and practices have been described as such, especially for their secretive nature and lack of transparency. Whistleblowers and leaks have contributed extensively and at various levels to the understanding of these systems, providing otherwise unaccessible information for public debate. Based on the discussion of a series of recent instances and a review of the available literature, this paper discusses the peculiarities of whistleblowing from Big Tech companies, and how the practice is helping to shed light on various and new technological black boxes and secrecy, while also expanding the scope of whistleblowing itself.
•Financial and trade globalization were introduced for environmental footprints.•The research applied a dynamic connectedness framework and VAR model.•Financial and trade globalization will ...contribute to polluting the environment.•There are positive spillover effects among environmental footprints, globalization, and economic complexity.
China faces the challenge of promoting high-tech industries and concomitantly reduces ecological footprints. This research analyzes the directional spillover impacts and connectedness for financial and trade globalization, high-tech industries, and environmental footprints of China. The authors used the data of financial globalization, trade globalization, economic complexity, middle and high-tech industrial contribution, and ecological footprint of China throughout 1996Q1 to 2019Q4. The empirics contribute to the debate on the impacts of the high technology industry, financial globalization for the environmental sustainably in the era of the digital economy. The study finds positive spillover effects from financial globalization (FGI), and economic complexity towards ecological footprints. Further, the high technology industrial contribution has a less significant impact on reducing environmental footprints. Overall, the findings are robust to the presence of structural change effects and the cleaner production objectives for China's case. Concomitantly, the empirical findings allow us to report innovative conclusions and implications regarding the sustainable development goals (SDG-7, 10), high-industry, and environmental sustainability in China.
This study examines the role of global value chain (GVC) participation in high technology exports using data over 120 countries during the 1995–2019 period. Our results suggest that GVC participation ...matters for high‐tech exports. While GVC participation with higher income countries is significantly associated with high‐tech exports, GVC participation with lower income countries has no effect. However, regardless of the origin countries, high‐tech GVC participation raises high‐tech exports. Moreover, GVC participation has a positive impact on high‐tech exports to lower income countries. Finally, we present evidence that the determinants of high‐tech exports vary by the income level of destination countries.
Does organizational learning orientation impede radical innovation? The results show that a high level learning orientation promotes myopic learning and incremental innovation, but constrains ...experimentation and radical innovation in emerging domains. The study tests hypotheses using two separate data analyses, comparing traditional PLS-SEM with fsQCA. The empirical results show that fsQCA captures better predictive outcomes than PLS-SEM. Entrepreneurs and high-tech firms should interpret the findings with some cautions because of their prosperity based on competency and learning orientation in specific fields. For the high-tech industry and entrepreneurial ventures, superior capability in a particular area leads to exploitative learning and cultivate incremental innovation.
Despite extensive discussion about the important role of government in enterprise development, the function of government grants in the innovation activities of high-technology (high-tech) industries ...is still unclear. In this paper, the stochastic frontier model and a unique panel data set of 17 high-tech industries in China spanning the 2001–2011 period are applied to explore how government grants affect the innovation performance of these industries. Results indicate that the innovation efficiency of high-tech industries rapidly improved in the past decade. However, it is found that government grants exert a negative influence on innovation efficiency of high-tech industries. However, the impact of private R&D funding is significant and positive. Furthermore, when the high-tech industries are grouped into five sub-industries, the results show that government grants had different effects on the innovation in each sub-industry.
•Government grants have a negative impact on innovation of China's High-tech Industry.•Private R&D funding and other funds cast positive effect on innovation.•Government grants have different impacts on innovation of different sub-industries.•The innovation efficiency of High-tech industry grew rapidly but is relatively low.
•Combine with the insights of internal and external governance, explore how the managerial power and network centrality affect high-tech enterprise’s innovation performance in big data ...environment.•Enterprise's managerial power and network centrality have significant positive impacts on innovation performance.•Network centrality plays a partial mediating role through the effects of resource acquisition, reputation incentive and R&D competition.•The relationships among managerial power, network centrality and innovation performance are more significant in the strong big data environment.
The emergence of big data brings both opportunities and challenges to high-tech enterprises. How to keep competitive advantages and improve innovation performance is important for enterprises in big data environment. Except from organizational learning ability and the use of advanced technology, the corporate governance also plays an important role in the process of enterprise’s innovation practice. This article creatively combines with the insights of internal and external governance, and explores how the managerial power and network centrality affects enterprise’s innovation performance in big data environment. Considering about the differences among distinct regional big data environment (strong/weak), this paper also takes classification research on it. The research findings show that managerial power has a significant positive impact on innovation performance, managerial power could enhance enterprise’s centrality in network, and the enterprise which located in network central position has more advantages in obtaining resources and significantly improves firm’s innovation performance. Network centrality plays a mediating role on managerial power and innovation performance. Further research finds that the positive effects of managerial power and network centrality are more significantly in the strong big data environment. These findings enrich the research of high-tech enterprise innovation from a combinative governance view, and contribute to the literatures on enterprise innovation in big data environment.
The physical attractiveness stereotype maintains that what is beautiful is good. Does this also apply to Chief Executive Officers (CEOs) and influence their compensation? There are numerous debates ...on CEO compensation, and scholars have long been interested in understanding the factors that impact CEO compensation. Of the empirical studies investigating the antecedents of CEO compensation, little attention has been paid to CEO facial attractiveness. Drawing mainly from the physical attractiveness stereotype, we argue that CEO attractiveness increases CEO compensation, and the effect becomes stronger when the CEO has worked as a CEO in other firms, but weaker when the CEO is female or works for a high‐technology firm. We tested our hypotheses by coding facial attractiveness for all CEOs in S&P 500 firms over 10 years (861 CEOs and 4,395 firm‐year observations). Results partly support our predictions and show that the effect of CEO facial attractiveness on compensation is not only robust but also economically significant. Moderating effects were found using prior CEO experience and high tech industry as moderators. However, we found no moderating effect of CEO gender on the relationship between CEO facial attractiveness and compensation. This study suggests that CEO compensation is not an entirely rational process, and compensation committees appear to be biased in favor of beautiful individuals.
► We study the impact of venture capital investments on young high-tech firm growth. ► We disentangle the treatment and selection effect of venture capital (VC). ► A longitudinal dataset of 538 ...Italian young high-tech firms (NTBFs) is used. ► The treatment is of large magnitude while the selection effect appears to be negligible. ► Most of the impact is obtained immediately after the first round of VC finance.
The financial and innovation literature generally claims that venture capital (VC) investments spur the growth of new technology-based firms (NTBFs). However, it has proved difficult so far to separate the “treatment” effect of the VC investment from the “selection” effect attributable to the ability of the VC investor to screen high growth NTBFs. The aim of this work is to test whether VC investments have a positive treatment effect on the growth of employment and sales of NTBFs. For this purpose we consider a 10-year longitudinal data set for 538 Italian NTBFs, most of which are privately held. The sample includes both VC-backed and non-VC-backed firms. We estimate Gibrat-law-type dynamic panel-data models augmented with time-varying variables that capture the VC status of firms. To control for the endogeneity of VC investments we use several GMM estimators. The econometric results strongly support the view that VC investments positively influence firm growth. The treatment effect of VC investments is of large economic magnitude, especially on growth of employment. Most of it is obtained immediately after the first round of VC finance. Conversely, the selection effect of VC appears to be negligible in the Italian context.
The Chinese high-tech industry has developed greatly since the beginning of China's “National High-tech R&D (863) Program” and “China Torch Program”. This paper introduces a conceptual model extended ...from the innovation value chain model to simultaneously estimate the R&D and commercialization efficiencies for the high-tech industries of 29 provincial-level regions in China. To match reality, a network DEA incorporating both shared inputs and additional intermediate inputs is constructed to open the “black box” view of decision making units used in single-stage DEA. This study is the first attempt to link the R&D and commercialization with a solid theoretical foundation and feasible mathematical methods. The empirical findings show that most of the 29 regions have low efficiency in the commercialization sub-process compared to the R&D sub-process, although there are regional differences in China's high-tech industry. Pearson correlation shows that the R&D sub-process is not closely correlated to the commercialization sub-process in terms of efficiency. Our analysis can provide information for the formulation of policies to achieve high innovation efficiency.
•It constructs a two-stage conceptual framework for performance evaluation under the innovation value chain theory.•It gives insight into the appropriate proportion of shared resources in each sub-process.•It analyzes the high-tech industry innovation activities from the perspective of the regional innovation system.•It provides some policy implications and recommendations of China's high-tech innovation.
