International R&amp;D funding and patent collateral in an R&amp;D-based growth model

Huang, Wei-chi; Lai, Ching‐chong; Chen, Ping-Ho

doi:10.1016/j.iref.2017.07.009

Cited by 15 publications

(11 citation statements)

References 37 publications

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“…The theoretical underpinning of this study builds on the well-established literature suggesting that access to credit and effective contract enforcement, which are relational risks reducing, incentivize R&D investments (Agénor et al, 2014;Brown et al, 2012;Khanna and Mathews, 2016;Seitz and Watzinger, 2017). On the one hand, R&D is a cost-intensive activity, often requiring external financing because R&D investing firms easily exhaust their internal funds (Agénor et al, 2014;Huang et al, 2017). 3 On the other hand, investments in research projects often require collaboration with multiple 2 For an extensive review of literature, see Akçomak and Müller-Zick (2018).…”

Section: Hypothesis Developmentmentioning

confidence: 99%

Trust and R&D investments: evidence from OECD countries

Ndubuisi

2020

Journal of Institutional Economics

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This paper examines two potential mechanisms – access to credit and reduction in relational risks – through which social trust can affect R&D investments. Social trust can increase R&D investments by expanding firms' access to external finance with which they can use to fund promising R&D projects. It can also increase R&D investments by reducing relational risks that expose firms to ex-ante and ex-post holdups or expropriation risks. Using industry-level data on R&D investment intensities in 20 OECD countries, I test these mechanisms by evaluating whether more external finance dependent and relational risk vulnerable industries exhibit disproportional higher R&D investment intensities in trust intensive countries. The results indicate that external finance dependent industries and relational risks vulnerable industries experience relatively higher R&D investment intensities in trust-intensive countries. Therefore, the results underline access to external finance and reduction in relational risks as causal pathways linking social trust and R&D investments.

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Section: Hypothesis Developmentmentioning

confidence: 99%

Trust and R&D investments: evidence from OECD countries

Ndubuisi

2020

Journal of Institutional Economics

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“…Reasonable use of a patent knowledge graph method to explore new product R&D hot-spots in the manufacturing field can improve the process of new product R&D and technology development. The patent is a vital index for measuring the R&D investment and productivity of enterprises [93][94][95]. For enterprises, the goal of patent application and authorization is to protect R&D achievements.…”

Section: Human-to-thing: Knowledge Graphmentioning

confidence: 99%

The Architecture of Mass Customization-Social Internet of Things System: Current Research Profile

Dou

Sun

Wu³

et al. 2021

IJGI

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In the era of big data, mass customization (MC) systems are faced with the complexities associated with information explosion and management control. Thus, it has become necessary to integrate the mass customization system and Social Internet of Things, in order to effectively connecting customers with enterprises. We should not only allow customers to participate in MC production throughout the whole process, but also allow enterprises to control all links throughout the whole information system. To gain a better understanding, this paper first describes the architecture of the proposed system from organizational and technological perspectives. Then, based on the nature of the Social Internet of Things, the main technological application of the mass customization–Social Internet of Things (MC–SIOT) system is introduced in detail. On this basis, the key problems faced by the mass customization–Social Internet of Things system are listed. Our findings are as follows: (1) MC–SIOT can realize convenient information queries and clearly understand the user’s intentions; (2) the system can predict the changing relationships among different technical fields and help enterprise R&D personnel to find technical knowledge; and (3) it can interconnect deep learning technology and digital twin technology to better maintain the operational state of the system. However, there exist some challenges relating to data management, knowledge discovery, and human–computer interaction, such as data quality management, few data samples, a lack of dynamic learning, labor consumption, and task scheduling. Therefore, we put forward possible improvements to be assessed, as well as privacy issues and emotional interactions to be further discussed, in future research. Finally, we illustrate the behavior and evolutionary mechanism of this system, both qualitatively and quantitatively. This provides some idea of how to address the current issues pertaining to mass customization systems.

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“…e research contents include theoretical introduction and theoretical discussion on intellectual property pledge loan [2,3], intellectual property pledge loan mode and government behavior [4], risk early warning based on the perspective of financial institutions [5], and value of intellectual property pledge [6]. At the same time, some scholars have conducted exploratory empirical research on the influencing factors of the patent pledge loan model [7].…”

Section: Introductionmentioning

confidence: 99%

The Influencing Factors of Intellectual Property Pledge Loan Trust: A Social Network Theory-Based Experimental Study

Yan

Wang

Cui

et al. 2021

Discrete Dynamics in Nature and Society

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This paper studies the behavior of intellectual property pledge loan based on a specific social network and uses the method of experimental research to analyze the impact of factors on the comprehensive trust of intellectual property pledge loan. The results show that if direct cooperation records between enterprises and banks are complete, the larger the scale of cooperation, the higher the trust of intellectual property pledge loans, and the nearer the cooperation record to the present time, the greater the credibility of enterprise cooperation. If there is no direct cooperation record between enterprises and banks, or cooperation record is incomplete, in accordance with the trust evaluation of the recommended members on the intellectual property pledge loan enterprise, the smaller the degree of trust at a certain recommendation node, the lower the credibility of enterprises at this node correspondingly, and the lower the perceived risk tolerance of banks, the lower the cooperation satisfaction in the intellectual property pledge loan enterprises.

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International R&D funding and patent collateral in an R&D-based growth model

Cited by 15 publications

References 37 publications

Trust and R&D investments: evidence from OECD countries

Trust and R&D investments: evidence from OECD countries

The Architecture of Mass Customization-Social Internet of Things System: Current Research Profile

The Influencing Factors of Intellectual Property Pledge Loan Trust: A Social Network Theory-Based Experimental Study

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