The industrial chain network is a complex system consisted by many members of the enterprise, and the complex relationship and the interaction with the external environment among…
Abstract
Purpose
The industrial chain network is a complex system consisted by many members of the enterprise, and the complex relationship and the interaction with the external environment among the node enterprises and the existence of various uncertainty all increase the risk of the industry chain. The risk of some individual node enterprises will not only affect the normal operation but also spread the risk to other enterprises by network relationship because of their own mismanagement or deterioration of the external environment. The purpose of this paper is to make an attempt to establish the risk spread model of the industrial chain based on complex networks.
Design/methodology/approach
By improving Lobos disaster diffuse model, the paper introduces two indexes: the risk spread range and the risk propagation velocity to measure of industrial chain risk communication effects, and design algorithm for industrial chain complex network structure. The risk spread range can be used to measure the coverage of the risk communication influence produced by the propagation enterprises in the industry chain and to analyse the risk spread breadth on the industrial chain network .The speed index of risk communication represents the total numbers of infection enterprises in unit simulation time.
Findings
This paper proposes the universal industrial chain risk propagation model.
Originality/value
Through proposed algorithm constructs industrial chain network, and enterprise class divide, the importance of the product chain enterprises in the industry chain is strengthened.
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Weiqi Dai, Yi Wang, Mingqing Liao, Mei Shao, Yue Jiang and Miao Zhang
One increasingly popular financing option for entrepreneurial ventures is to attract corporate venture capital (CVC) investments. Prior research tends to take a CVC-centric…
Abstract
Purpose
One increasingly popular financing option for entrepreneurial ventures is to attract corporate venture capital (CVC) investments. Prior research tends to take a CVC-centric perspective assessing the benefits and contingencies for incumbent firms or corporate investors to engage with entrepreneurial ventures. Few studies have taken the opposite perspective of investigating factors that entrepreneurial ventures need to take into account when engaging with CVC investments. As such, this study aims to investigate pre- and post-IPO entrepreneurial venture performance that partners with CVC providers or corporate investors, as well as to assess organizational and environmental contingencies.
Design/methodology/approach
This study draws on a sample of 631 entrepreneurial ventures from the CSMAR database ranging from 2009 to 2019, along with CVC financing data from the CVSource database and financial data in entrepreneurial ventures’ annual reports from the Juchao Network. This study applies multiple linear regression modelling and fixed effect panel data analyses to test the proposed hypotheses.
Findings
The results show that CVC investment contributes to entrepreneurial ventures’ financial performance, both pre- and post-IPO. However, while research and development (R&D) intensity and geographic proximity strengthen the positive relationship between CVC investment and entrepreneurial ventures’ performance pre-IPO, R&D intensity has a negative moderating effect on the relationship between CVC investment and entrepreneurial ventures’ performance post-IPO.
Practical implications
First, in emerging economies, adopting a CVC financing strategy is an important strategic choice for entrepreneurial ventures that have a great demand for external capital, resources and technology support. Second, leveraging the relationship between external financing and internal R&D investment is essential for them to maintain their core competitiveness and sustainable growth. Moreover, entrepreneurial ventures should deal with the coopetitive relationship with incumbent companies and manage their dependency on other market participants in the external environment.
Originality/value
This study focuses on the performance implications for entrepreneurial ventures engaging with CVC investments pre- and post-IPO. First, this study broadens and expands prior research on the mechanism of the relationship between CVC and entrepreneurial ventures’ financial performance. Second, the research conducts a comparative study of the moderating effects of different timings. Third, this study applies learning theory to the field of CVC in emerging economies.
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Tobias Burggraf, Toan Luu Duc Huynh, Markus Rudolf and Mei Wang
This study examines the prediction power of investor sentiment on Bitcoin return.
Abstract
Purpose
This study examines the prediction power of investor sentiment on Bitcoin return.
Design/methodology/approach
We construct a Financial and Economic Attitudes Revealed by Search (FEARS) index using search volume from Google's search engine to reveal household-level (“bankruptcy”, “unemployment”, “job search”, etc.) and market-level sentiment (“bankruptcy”, “unemployment”, “job search”, etc.).
Findings
Using a variety of quantitative methodologies such as the transfer entropy model as well as threshold regression and OLS, GLS and 2SLS estimations, we find that (1) investor sentiment has strong predictive power on Bitcoin, (2) household-level sentiment has larger effects than market-level sentiment and (3) the impact of sentiment is greater in low sentiment regimes than in high sentiment regimes. Based on these information, we build a hypothetical trading strategy that outperforms a simple buy-and-hold strategy both on an absolute and risk-adjusted basis. The results are consistent across cryptocurrencies and regions.
Research limitations/implications
The findings contribute to the ongoing debate in the literature on the efficiency of cryptocurrency markets. The results reveal that the Bitcoin market is not efficient in the sense of the efficient market hypothesis – asset prices do not fully reflect all available information and we were able to “beat the market”. In addition, it sheds further light on the debate whether Bitcoin can be considered a medium of exchange, i.e. a currency or an investment product. Because investors are reallocating their Bitcoin holdings during times of increased market sentiment due to liquidity needs, they obviously consider bitcoin an investment product rather than a currency.
Originality/value
This study is the first to examine the impact of investor sentiment measured by FEARS on Bitcoin return.
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Xichan Chen, Feng Chen, Xing Liu and Mei Zhao
The study aims to investigate the impact of industrial robot application on corporate labor cost stickiness and labor investment efficiency in China.
Abstract
Purpose
The study aims to investigate the impact of industrial robot application on corporate labor cost stickiness and labor investment efficiency in China.
Design/methodology/approach
Using the textual analysis to construct firm-level industrial robot application indicators in China, we implement the methodology in Anderson et al. (2003) and Banker and Byzalov (2014) to estimate cost stickiness.
Findings
We argue that the industrial robot uses in China would increase firms’ labor adjustment costs by increasing the employment scale and upgrading the employment structure (i.e. by employing more high-skilled and high-educated labor). Consistent with our expectation through the channel of labor adjustment costs, the use of robotics increases firms’ labor cost stickiness. We further find that the positive impact is more significant among labor-intensive industries, and among state-owned enterprises with lower labor adjustment flexibility. We also find that industrial robot uses do not decrease the labor cost stickiness even when robots are more likely to substitute labor. Finally, we find that industrial robot uses significantly facilitate more efficient hiring practices by mitigating overinvestment in labor (i.e. over-hiring).
Originality/value
Against the backdrop of intelligent manufacturing worldwide, our study sheds new insight into the effects of new technologies on corporate labor cost behavior in developing countries. We contribute to scant studies examining how robotics, AI adoption or other automation technologies (e.g. specialized machinery, software, etc.) affect corporate cost behavior.
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Xiao-Ming Li and Mei Qiu
The purpose of this paper is to investigate the mechanism of transmitting economic policy uncertainty (EPU) shocks to capital structure.
Abstract
Purpose
The purpose of this paper is to investigate the mechanism of transmitting economic policy uncertainty (EPU) shocks to capital structure.
Design/methodology/approach
The authors adopt a novel approach that bridges the asset pricing implications of EPU and the debt-financing decisions of Chinese firms by introducing a variable “policy-risk-induced equity return” (PRER). PRER is the product of the EPU beta and the EPU shock. Differentiating firms as per the signs of the EPU beta helps to shed light on the deep questions of whether their respective leverage targets and speeds of adjustment are different and how the targets and speeds are determined.
Findings
The empirical evidence shows that it is the equity market that channels EPU shocks to capital structure through PRER in China. Firms with positive (negative) EPU betas have PRER impact negatively (positively) the leverage target, conforming to the market-timing theory. EPU and non-policy uncertainty shocks cause the speed of adjustment to change over time. Overall, the intertemporal relation between EPU and leverage is negative. These results are robust to alternative leverage measures and after controlling for non-policy uncertainty shocks and conventional firm characteristics and have implications for academic research, policymaking, market stability, and corporate financing.
Originality/value
This study is the first to probe for, and provide insights into, the underlying reason why EPU impacts capital structure by connecting asset pricing to corporate financing for a large sample of Chinese publicly traded firms.
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Nicola Cobelli and Emanuele Blasioli
The purpose of this study is to introduce new tools to develop a more precise and focused bibliometric analysis on the field of digitalization in healthcare management…
Abstract
Purpose
The purpose of this study is to introduce new tools to develop a more precise and focused bibliometric analysis on the field of digitalization in healthcare management. Furthermore, this study aims to provide an overview of the existing resources in healthcare management and education and other developing interdisciplinary fields.
Design/methodology/approach
This work uses bibliometric analysis to conduct a comprehensive review to map the use of the unified theory of acceptance and use of technology (UTAUT) and the unified theory of acceptance and use of technology 2 (UTAUT2) research models in healthcare academic studies. Bibliometric studies are considered an important tool to evaluate research studies and to gain a comprehensive view of the state of the art.
Findings
Although UTAUT dates to 2003, our bibliometric analysis reveals that only since 2016 has the model, together with UTAUT2 (2012), had relevant application in the literature. Nonetheless, studies have shown that UTAUT and UTAUT2 are particularly suitable for understanding the reasons that underlie the adoption and non-adoption choices of eHealth services. Further, this study highlights the lack of a multidisciplinary approach in the implementation of eHealth services. Equally significant is the fact that many studies have focused on the acceptance and the adoption of eHealth services by end users, whereas very few have focused on the level of acceptance of healthcare professionals.
Originality/value
To the best of the authors’ knowledge, this is the first study to conduct a bibliometric analysis of technology acceptance and adoption by using advanced tools that were conceived specifically for this purpose. In addition, the examination was not limited to a certain era and aimed to give a worldwide overview of eHealth service acceptance and adoption.