Yong Liu

Dr. Yong Liu


Research Focus & Metrics

Academic Career Length

16Years (2011-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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JDJunliang Du
Junliang Du
YLYong Liu
Yong Liu
WDWei-Xue Diao
Wei-Xue Diao
Green technology innovation is an important means to break out of the constraints of resources and the environment, enhance the competitiveness of enterprises, and achieve the upgrading of industrial structures, and promote high-quality economic growth. In order to realize the overall improvement of the green technology innovation capability of Chinese enterprises, it is necessary to measure the efficiency of industrial enterprises’ green technology innovation and explore their regional differences. In this paper, from the perspective of a two-stage innovation value chain, by introducing the industrial carbon emissions per unit of Gross Domestic Product (GDP) and the “three wastes” pollutants into the research framework of green technology innovation efficiency, we established a novel green innovation efficiency evaluation indicator system for industrial enterprises. Furthermore, we used a two-stage network DEA with shared input to measure the efficiency of regional enterprises’ green technology innovation and explored the regional differences in industrial enterprises’ green technology R&D and the efficiency of green technology achievement transformation. Finally, we provide some suggestions for improving China’s industrial enterprises’ green innovation efficiency, so that they can ameliorate the significant regional imbalances and differences and realize high-quality economic growth.

8 May 2017 in Journal of Knowledge Management
Verified
Journal Article
Closed access
YLYong Liu
Yong Liu
Kevin LiKevin Li
Kevin Li
Purpose: The purpose of this paper is to propose a novel prospect-based two-sided matching decision model for matching supply and demand of technological knowledge assisted by a broker. This model enables the analyst to account for the stakeholders’ psychological behaviours and their impact on the matching decision in an open innovation setting. Design/methodology/approach: The prospect theory and grey relational analysis are used to develop the proposed two-sided matching decision framework. Findings: By properly calibrating model parameters, the case study demonstrates that the proposed approach can be applied to real-world technological knowledge trading in a market for technology (MFT) and yields matching results that are more consistent with the reality. Research limitations/implications: The proposed model does not differentiate the types of knowledge exchanged (established vs novel, tacit vs codified, general vs specialized) (Ardito et al., 2016, Nielsen and Nielsen, 2009). Moreover, the model focuses on incorporating psychological behaviour of the MFT participants and does not consider their other characteristics. Practical implications: The proposed model can be applied to achieve a better matching between technological knowledge suppliers and users in a broker-assisted MFT. Social implications: A better matching between technological knowledge suppliers and users can enhance the success of open innovation, thereby contributing to the betterment of the society. Originality/value: This paper furnishes a novel theoretical model for matching supply and demand in a broker-assisted MFT. Methodologically, the proposed model can effectively capture market participants’ psychological considerations.

3 August 2021 in Industrial Management & Data Systems
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Journal Article
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SFShaoxiong Fu
Shaoxiong Fu
HLHongxiu Li
Hongxiu Li
YLYong Liu
Yong Liu
Purpose: Social media platforms are currently facing the challenge of declining user activity. Building on the push–pull–mooring (PPM) framework, the current study developed a research model to evaluate factors that affect Facebook discontinuance.Design/methodology/approach: The proposed research model assessed how push factors (e.g. Facebook fatigue and dissatisfaction), a pull factor (e.g. alternative attractiveness) and mooring factors (e.g. personal norms and habit of using Facebook) affected the discontinued usage behavior regarding Facebook. The proposed research model was validated using empirical data (n = 412) collected from Facebook users.Findings: Facebook fatigue, dissatisfaction and alternative attractiveness significantly and positively affected discontinued Facebook usage. Personal norms and habit of using Facebook had a converse influence in this regard. Dissatisfaction had a stronger positive impact than Facebook fatigue and alternative attractiveness on the discontinued usage behavior regarding Facebook. Habits of using Facebook had a greater negative effect than personal norms of using Facebook on the discontinued usage behavior regarding Facebook by users.Originality/value: This study extends extant literature on social media discontinuance to identify the antecedents of discontinuous usage behavior in social media. This study enriches the literature on social media discontinuance by shedding light on the different degrees of effect of the push, pull and mooring factors on discontinuous social media usage behavior.

31 August 2021 in Annals of Operations Research
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Journal Article
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PDF file
YLYong Liu
Yong Liu
WRWenwen Ren
Wenwen Ren
QXQian Xu
Qian Xu
ZLZhi-Yang Liu
Zhi-Yang Liu

17 July 2019 in Environmental Science and Pollution Research
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Journal Article
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PDF file
WHWenquan HU
Wenquan HU
TJTong Jin
Tong Jin
YLYong Liu
Yong Liu

1 January 2020 in Electronic Commerce Research and Applications
Verified
Journal Article
Closed access
YLYong Liu
Yong Liu
JLJiao Li
Jiao Li
WRWenwen Ren
Wenwen Ren
JFJeffrey Yi-Lin Forrest
Jeffrey Yi-Lin Forrest