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Jian Liang [4]Jiafeng Liang [3]Jianqing Liang [1]Jiaqi Liang [1]
Jiaqing Liang [1]Jiarong Liang [1]
  1. Monetary Intelligence and Behavioral Economics: The Enron Effect—Love of Money, Corporate Ethical Values, Corruption Perceptions Index, and Dishonesty Across 31 Geopolitical Entities.Thomas Li-Ping Tang, Toto Sutarso, Mahfooz A. Ansari, Vivien K. G. Lim, Thompson S. H. Teo, Fernando Arias-Galicia, Ilya E. Garber, Randy Ki-Kwan Chiu, Brigitte Charles-Pauvers, Roberto Luna-Arocas, Peter Vlerick, Adebowale Akande, Michael W. Allen, Abdulgawi Salim Al-Zubaidi, Mark G. Borg, Bor-Shiuan Cheng, Rosario Correia, Linzhi Du, Consuelo Garcia de la Torre, Abdul Hamid Safwat Ibrahim, Chin-Kang Jen, Ali Mahdi Kazem, Kilsun Kim, Jian Liang, Eva Malovics, Alice S. Moreira, Richard T. Mpoyi, Anthony Ugochukwu Obiajulu Nnedum, Johnsto E. Osagie, AAhad M. Osman-Gani, Mehmet Ferhat Özbek, Francisco José Costa Pereira, Ruja Pholsward, Horia D. Pitariu, Marko Polic, Elisaveta Gjorgji Sardžoska, Petar Skobic, Allen F. Stembridge, Theresa Li-Na Tang, Caroline Urbain, Martina Trontelj, Luigina Canova, Anna Maria Manganelli, Jingqiu Chen, Ningyu Tang, Bolanle E. Adetoun & Modupe F. Adewuyi - 2018 - Journal of Business Ethics 148 (4):919-937.
    Monetary intelligence theory asserts that individuals apply their money attitude to frame critical concerns in the context and strategically select certain options to achieve financial goals and ultimate happiness. This study explores the dark side of monetary Intelligence and behavioral economics—dishonesty. Dishonesty, a risky prospect, involves cost–benefit analysis of self-interest. We frame good or bad barrels in the environmental context as a proxy of high or low probability of getting caught for dishonesty, respectively. We theorize: The magnitude and intensity of (...)
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  2. Monetary Intelligence and Behavioral Economics Across 32 Cultures: Good Apples Enjoy Good Quality of Life in Good Barrels.Thomas Li-Ping Tang, Toto Sutarso, Mahfooz A. Ansari, Vivien Kim Geok Lim, Thompson Sian Hin Teo, Fernando Arias-Galicia, Ilya E. Garber, Randy Ki-Kwan Chiu, Brigitte Charles-Pauvers, Roberto Luna-Arocas, Peter Vlerick, Adebowale Akande, Michael W. Allen, Abdulgawi Salim Al-Zubaidi, Mark G. Borg, Luigina Canova, Bor-Shiuan Cheng, Rosario Correia, Linzhi Du, Consuelo Garcia de la Torre, Abdul Hamid Safwat Ibrahim, Chin-Kang Jen, Ali Mahdi Kazem, Kilsun Kim, Jian Liang, Eva Malovics, Anna Maria Manganelli, Alice S. Moreira, Richard T. Mpoyi, Anthony Ugochukwu Obiajulu Nnedum, Johnsto E. Osagie, AAhad M. Osman-Gani, Mehmet Ferhat Özbek, Francisco José Costa Pereira, Ruja Pholsward, Horia D. Pitariu, Marko Polic, Elisaveta Gjorgji Sardžoska, Petar Skobic, Allen F. Stembridge, Theresa Li-Na Tang, Caroline Urbain, Martina Trontelj, Jingqiu Chen & Ningyu Tang - 2018 - Journal of Business Ethics 148 (4):893-917.
    Monetary Intelligence theory asserts that individuals apply their money attitude to frame critical concerns in the context and strategically select certain options to achieve financial goals and ultimate happiness. This study explores the bright side of Monetary Intelligence and behavioral economics, frames money attitude in the context of pay and life satisfaction, and controls money at the macro-level and micro-level. We theorize: Managers with low love of money motive but high stewardship behavior will have high subjective well-being: pay satisfaction and (...)
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  3.  27
    Multi-view graph convolutional networks with attention mechanism.Kaixuan Yao, Jiye Liang, Jianqing Liang, Ming Li & Feilong Cao - 2022 - Artificial Intelligence 307 (C):103708.
  4.  32
    The Challenges of Medical Ethics in China: Are Gene-Edited Babies Enough?Zeng Jie Ye, Xiao Ying Zhang, Jian Liang & Ying Tang - 2020 - Science and Engineering Ethics 26 (1):123-125.
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  5.  41
    Effects of Uncertainty on ERPs to Emotional Pictures Depend on Emotional Valence.Huiyan Lin, Hua Jin, Jiafeng Liang, Ruru Yin, Ting Liu & Yiwen Wang - 2015 - Frontiers in Psychology 6.
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  6. Anticipation of Negative Pictures Enhances the P2 and P3 in Their Later Recognition.Huiyan Lin, Jing Xiang, Saili Li, Jiafeng Liang & Hua Jin - 2015 - Frontiers in Human Neuroscience 9.
  7.  17
    The Strong Local Diagnosability of a Hypercube Network with Missing Edges.Min Xie, Jiarong Liang & Xi Xiong - 2018 - Complexity 2018:1-10.
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  8.  8
    Security Risk Analysis of Active Distribution Networks with Large-Scale Controllable Loads under Malicious Attacks.Jiaqi Liang, Yibei Wu, Jun’E. Li, Xiong Chen, Heqin Tong & Ming Ni - 2021 - Complexity 2021:1-12.
    With the development of distributed networks, the remote controllability of the distributed energy objects and the vulnerability of user-side information security protection measures make distributed energy objects extremely vulnerable to malicious control by attackers. Hence, the large-scale loads may produce abnormal operation performance, such as load casting/dropping synchronously or frequent and synchronous casting and dropping, and hence, it can threaten the security and stable operation of the distribution networks. First, we analyze the security threats faced by industrial controllable load, civil (...)
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  9.  13
    Cue Valence Influences the Effects of Cue Uncertainty on ERP Responses to Emotional Events.Huiyan Lin, Jiafeng Liang, Ting Liu, Ziping Liang & Hua Jin - 2020 - Frontiers in Human Neuroscience 14.
  10.  8
    VoCSK: Verb-oriented commonsense knowledge mining with taxonomy-guided induction.Jingping Liu, Tao Chen, Chao Wang, Jiaqing Liang, Lihan Chen, Yanghua Xiao, Yunwen Chen & Ke Jin - 2022 - Artificial Intelligence 310 (C):103744.
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  11.  21
    Modeling and Dynamic Control of a Class of Semibiomimetic Robotic Fish.Shouxu Zhang, Bo Jiang, Xiaoxuan Chen, Jian Liang, Peng Cui & Xinxin Guo - 2018 - Complexity 2018:1-8.
    This paper proposes a new robotic fish which avoids the complex mechanical structure and reduces the model complexity comparing to the existing bioinspired robotic fish, giving rise to a semibiomimetic robotic fish. The generalized Lagrange equation is adopted to establish the dynamic model of the robotic fish. The controllability of the system is analyzed, upon which a trajectory tracking control algorithm is designed by using the feedback linearization technique. The simulation results show that the dynamic model adopted in this paper (...)
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