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The impact of CEOs’ different identities on Chinese family firms’ business operations has always been an important and controversial topic. Based on data on Chinese family listed firms from 2014 to 2018, this paper studies the effects of family’s other members being CEO or professional managers on long-term investment, and further explores the effect differences between different ownership patterns. This paper finds that professional managers and family’s other members being CEO are both negatively correlated with long-term investment. In the family firms controlled by multiple natural persons, the negative effect between the family’s other members being CEO and the long-term investment scale is strengthened. This paper provides reasonable suggestions for Chinese family firms to hire a CEO.
Yue Hu; Sheng Ma; Xinxin Xu; Yuhan Wang. CEO Identity Difference, Ownership Pattern and Long-Term Investment: Evidence from Chinese Family Listed Firms. Proceedings of the Fifteenth International Conference on Management Science and Engineering Management 2021, 440 -451.
AMA StyleYue Hu, Sheng Ma, Xinxin Xu, Yuhan Wang. CEO Identity Difference, Ownership Pattern and Long-Term Investment: Evidence from Chinese Family Listed Firms. Proceedings of the Fifteenth International Conference on Management Science and Engineering Management. 2021; ():440-451.
Chicago/Turabian StyleYue Hu; Sheng Ma; Xinxin Xu; Yuhan Wang. 2021. "CEO Identity Difference, Ownership Pattern and Long-Term Investment: Evidence from Chinese Family Listed Firms." Proceedings of the Fifteenth International Conference on Management Science and Engineering Management , no. : 440-451.
Innovation ability has become an important factor affecting the global competitiveness and sustainable development of state-owned enterprises (SOEs) in China, particularly during the COVID-19 period. This study examined the association between heterogeneous shareholders and SOE innovation, in addition to the moderating impact of corporate governance characteristics and the COVID-19 pandemic on this association. Using data from Chinese A-share listed mixed ownership enterprises (MOEs), we found that the mixed ownership reform of SOEs positively affected firm innovation compared to other MOEs by reducing agency costs, indicating that the manager view channel was proven. We also found that heterogeneous shareholders resulted in more innovation output in state-owned holding mixed ownership enterprises (SHMOEs) with affiliated managers, in those audited by lower reputation accounting firms or that had a lower external marketization, or during the COVID-19 period. The implications of this study are of importance for improving heterogeneous shareholders’ active participation in the mixed ownership reform of SOEs.
Rui Wang; Sheng Ma; Xinxin Xu; Pan Song. Heterogeneous Shareholders’ Participation, COVID-19 Impact, and Innovation Decisions of State-Owned Firms: Evidence from China. Sustainability 2021, 13, 4406 .
AMA StyleRui Wang, Sheng Ma, Xinxin Xu, Pan Song. Heterogeneous Shareholders’ Participation, COVID-19 Impact, and Innovation Decisions of State-Owned Firms: Evidence from China. Sustainability. 2021; 13 (8):4406.
Chicago/Turabian StyleRui Wang; Sheng Ma; Xinxin Xu; Pan Song. 2021. "Heterogeneous Shareholders’ Participation, COVID-19 Impact, and Innovation Decisions of State-Owned Firms: Evidence from China." Sustainability 13, no. 8: 4406.
This paper examined the location choices of Chinese outward FDI (OFDI) from 2005–2016 with a particular focus on the Association of Southeast Asian Nations (ASEAN) countries. It was found that Chinese OFDI in ASEAN countries was generally focused on areas that had large potential markets and low tax rates. Unlike previous studies, it was found that primary and secondary industry labor costs were the main motivators rather than resource-seeking. The business environment in the host countries was also found to have positive and significant effects on Chinese OFDI location choice for the agricultural, mining, construction, and information industries. The insights in this paper could provide useful suggestions for both governments and investors.
Sheng Ma; Xinxin Xu; Ziqiang Zeng; Lin Wang. Chinese Industrial Outward FDI Location Choice in ASEAN Countries. Sustainability 2020, 12, 674 .
AMA StyleSheng Ma, Xinxin Xu, Ziqiang Zeng, Lin Wang. Chinese Industrial Outward FDI Location Choice in ASEAN Countries. Sustainability. 2020; 12 (2):674.
Chicago/Turabian StyleSheng Ma; Xinxin Xu; Ziqiang Zeng; Lin Wang. 2020. "Chinese Industrial Outward FDI Location Choice in ASEAN Countries." Sustainability 12, no. 2: 674.
By utilizing the monthly potato market price data from 2011 to 2015 and time series model such as X11 seasonal adjustment method and H-P (Hodrick–Prescott) filtering method, this paper analyzes the period and rule of potato market price fluctuation. The study found that the peak of the National Potato Price Index appears around every May, the lowest point appears around every October, the highest and lowest points appear alternately each year. In the past 5 years, the potato price fluctuation in China is large, the fluctuation frequency is high, on the average, the drop of peak and valley variation rate is 42.18%, the average rising month for each cycle is 7.25 months, with an average cycle length of 14.25 months.
Qianyou Zhang; Xinxin Xu; Yuanling Zhang; Yuerong Zheng; Jinqiu Tian. Study on Fluctuation and Regulation of Potato Market Price in China: Based on the View of Stable Crop for the Potato. Advances in Intelligent Systems and Computing 2019, 770 -779.
AMA StyleQianyou Zhang, Xinxin Xu, Yuanling Zhang, Yuerong Zheng, Jinqiu Tian. Study on Fluctuation and Regulation of Potato Market Price in China: Based on the View of Stable Crop for the Potato. Advances in Intelligent Systems and Computing. 2019; ():770-779.
Chicago/Turabian StyleQianyou Zhang; Xinxin Xu; Yuanling Zhang; Yuerong Zheng; Jinqiu Tian. 2019. "Study on Fluctuation and Regulation of Potato Market Price in China: Based on the View of Stable Crop for the Potato." Advances in Intelligent Systems and Computing , no. : 770-779.
Predicting traffic crashes has been an important topic of traffic safety research for the past many years. This paper investigates the data from police crash reports provided by the Washington State Department of Transportation. The data consists of records of four years from January 2011 to December 2014 for three main interstate highways (including I-5, I-90, and I-405). A deep learning model using a recurrent neural network (RNN) combined with particle swarm optimization (PSO) is developed and employed to predict the crash density in different severity levels such as property damage only (PDO) and fatal-injury crashes, based on 48,154 crash records that have occurred. All the crash records are randomly divided into training set, validation set, and test set with the proportion ratio of 70, 15, and \(15\%\). The cross-validation is employed to prevent the model from over fit during the training period. A normalized probability-based PSO is designed for optimizing the identified significant factors which can improve the prediction accuracy. The weighted mean squared error (MSE) of the prediction result is employed to measure the performance of the developed model. Nine explanatory variables are selected from fifteen contributing factors. The proposed model is compared with generalized nonlinear model-based mixed multinomial logit approach (GNM-based mixed MNL). The results show that the new model has lower fatal-injury and PDO MSEs. Sensitivity analysis on the selected variables demonstrates the capability of the new model for generating interpretable parameters. The findings of this study provide new insights into the prediction of crash density and severity from the perspective of using roadway segment-based crash records.
Xinxin Xu; Ziqiang Zeng; Yinhai Wang; John Ash. Crash Density and Severity Prediction Using Recurrent Neural Networks Combined with Particle Swarm Optimization. Advances in Intelligent Systems and Computing 2019, 566 -580.
AMA StyleXinxin Xu, Ziqiang Zeng, Yinhai Wang, John Ash. Crash Density and Severity Prediction Using Recurrent Neural Networks Combined with Particle Swarm Optimization. Advances in Intelligent Systems and Computing. 2019; ():566-580.
Chicago/Turabian StyleXinxin Xu; Ziqiang Zeng; Yinhai Wang; John Ash. 2019. "Crash Density and Severity Prediction Using Recurrent Neural Networks Combined with Particle Swarm Optimization." Advances in Intelligent Systems and Computing , no. : 566-580.
As many countries are now seeking to protect their own markets rather than indulge in global trade, this paper examines whether this type of de-globalization behavior has been having any effect on international investment relationships through a systematic analysis of international investment network (IIN) in 127 economies from 2005 to 2016. Unlike previous studies that only analyzed portfolio investment data, the bilateral international investment data were estimated using a matrix-based iteration approach, and the IIN established using complex network theory. Using bilateral international investment data made the results more reliable and somewhat closer to reality. To analyze the structural properties and evolution of the IIN, complex network indicators including a new one named node similarity were developed. The node similarity is defined as the proportion of common relationships of the current economy between two successive years which is useful to reveal the dynamics of the IIN. This paper finds that there are heterogenous and hierarchal properties in the IIN, several economies had a wide range of international investment partners, while most others had only a small range of investment partners and were more likely to form tight groups within the network. The economies in the IIN were tending towards smaller but closer communities, a new trend of regional financial cooperation was developing. The IIN is divided into more communities over time while the top active and central economies often locate in different communities. These findings imply that the structure of the IIN is changing geographically during the de-globalization rather than independent with regions. The regional cooperation has made positive effect on the international investment. The governments should ensure that they continue to support liberal financial policies and to promote better regional financial cooperation.
Xinxin Xu; Sheng Ma; Ziqiang Zeng. Complex network analysis of bilateral international investment under de-globalization: Structural properties and evolution. PLOS ONE 2019, 14, e0216130 .
AMA StyleXinxin Xu, Sheng Ma, Ziqiang Zeng. Complex network analysis of bilateral international investment under de-globalization: Structural properties and evolution. PLOS ONE. 2019; 14 (4):e0216130.
Chicago/Turabian StyleXinxin Xu; Sheng Ma; Ziqiang Zeng. 2019. "Complex network analysis of bilateral international investment under de-globalization: Structural properties and evolution." PLOS ONE 14, no. 4: e0216130.
This paper focuses on developing a framework of a vehicle-to-device (V2X) communication system for enhancing vehicle and pedestrian safety at un-signalized intersections. A comprehensive review of the literature has been made to investigate existing V2X safety applications. A cost-effective, solar-energy driven, small, and lightweight communication node device is developed to communicate with connected vehicles (CVs) via LoRa and dedicated short range communications (DSRC), and with pedestrians and unconnected vehicle through cell phones and other mobile devices via Bluetooth. A mobile application that allows pedestrians and drivers of unconnected vehicles to communicate with the communication node device and vice versa is also designed. A crash prediction algorithm is developed to identify unsafe conditions and determine appropriate CV-based safety countermeasures to be presented to system users. Finally, a CV simulation test bed is established in VISSIM to evaluate the safety benefits of the proposed methodology under various traffic and landscape conditions. The simulation results indicate that the number of conflicts increases when the penetration rate of connected devices decreases.
Xinxin Xu; Ziqiang Zeng; Yinhai Wang; John Ash. A Framework of a V2X Communication System for Enhancing Vehicle and Pedestrian Safety at Un-Signalized Intersections. Smart Technologies for Energy, Environment and Sustainable Development 2018, 51 -63.
AMA StyleXinxin Xu, Ziqiang Zeng, Yinhai Wang, John Ash. A Framework of a V2X Communication System for Enhancing Vehicle and Pedestrian Safety at Un-Signalized Intersections. Smart Technologies for Energy, Environment and Sustainable Development. 2018; ():51-63.
Chicago/Turabian StyleXinxin Xu; Ziqiang Zeng; Yinhai Wang; John Ash. 2018. "A Framework of a V2X Communication System for Enhancing Vehicle and Pedestrian Safety at Un-Signalized Intersections." Smart Technologies for Energy, Environment and Sustainable Development , no. : 51-63.
This paper aims to develop a crash counts by severity based hotspot identification method by extending the traditional empirical Bayes method to a generalized nonlinear model-based mixed multinomial logit approach. A new safety performance index and a new potential safety improvement index are developed by introducing the risk weight factor and compared with traditional indexes by employing four hotspot identification evaluating methods. The comparison results reveal that the new safety performance index derived by the generalized nonlinear model-based mixed multinomial logit approach is the most consistent and reliable method for identifying hotspots. Finally, a regional map based analytical platform is developed by expanding the safety performance module with the new safety performance index and potential safety improvement functions.
Xinxin Xu; Ziqiang Zeng; Yinhai Wang; John Ash. A Crash Counts by Severity Based Hotspot Identification Method and Its Application on a Regional Map Based Analytical Platform. Proceedings of the Eleventh International Conference on Management Science and Engineering Management 2017, 286 -299.
AMA StyleXinxin Xu, Ziqiang Zeng, Yinhai Wang, John Ash. A Crash Counts by Severity Based Hotspot Identification Method and Its Application on a Regional Map Based Analytical Platform. Proceedings of the Eleventh International Conference on Management Science and Engineering Management. 2017; ():286-299.
Chicago/Turabian StyleXinxin Xu; Ziqiang Zeng; Yinhai Wang; John Ash. 2017. "A Crash Counts by Severity Based Hotspot Identification Method and Its Application on a Regional Map Based Analytical Platform." Proceedings of the Eleventh International Conference on Management Science and Engineering Management , no. : 286-299.
The mixed multinomial logit (MNL) approach, which can account for unobserved heterogeneity, is a promising unordered model that has been employed in analyzing the effect of factors contributing to crash severity. However, its basic assumption of using a linear function to explore the relationship between the probability of crash severity and its contributing factors can be violated in reality. This paper develops a generalized nonlinear model-based mixed MNL approach which is capable of capturing non-monotonic relationships by developing nonlinear predictors for the contributing factors in the context of unobserved heterogeneity. The crash data on seven Interstate freeways in Washington between January 2011 and December 2014 are collected to develop the nonlinear predictors in the model. Thirteen contributing factors in terms of traffic characteristics, roadway geometric characteristics, and weather conditions are identified to have significant mixed (fixed or random) effects on the crash density in three crash severity levels: fatal, injury, and property damage only. The proposed model is compared with the standard mixed MNL model. The comparison results suggest a slight superiority of the new approach in terms of model fit measured by the Akaike Information Criterion (12.06 percent decrease) and Bayesian Information Criterion (9.11 percent decrease). The predicted crash densities for all three levels of crash severities of the new approach are also closer (on average) to the observations than the ones predicted by the standard mixed MNL model. Finally, the significance and impacts of the contributing factors are analyzed.
Ziqiang Zeng; Wenbo Zhu; Ruimin Ke; John Ash; Yinhai Wang; Jiuping Xu; Xinxin Xu. A generalized nonlinear model-based mixed multinomial logit approach for crash data analysis. Accident Analysis & Prevention 2017, 99, 51 -65.
AMA StyleZiqiang Zeng, Wenbo Zhu, Ruimin Ke, John Ash, Yinhai Wang, Jiuping Xu, Xinxin Xu. A generalized nonlinear model-based mixed multinomial logit approach for crash data analysis. Accident Analysis & Prevention. 2017; 99 ():51-65.
Chicago/Turabian StyleZiqiang Zeng; Wenbo Zhu; Ruimin Ke; John Ash; Yinhai Wang; Jiuping Xu; Xinxin Xu. 2017. "A generalized nonlinear model-based mixed multinomial logit approach for crash data analysis." Accident Analysis & Prevention 99, no. : 51-65.
This research aims to establish a methodology of metasynthesis-based intelligent big data processing paradigm which works based on the mechanisms of metasynthesis-architecture, metasynthesis-technology, and the principle of meta- synthesis-intelligence. The proposed method will achieve the ability of intelligent data acquisition, data identification, data structure design, data analysis, and make decisions automatically and intelligently based on integrated big data processing technologies, decision making modeling methods, and intelligent algorithms. The human involvement, societal characteristics, dynamic characteristics, and uncertainty are also considered in this study. The current research status is analyzed including the big data architectures, big data processing systems, big data management, big data application. In order to deal with the complexity of big data system and establish an intelligent big data processing problem-solving methodology, an idea of “3M” structure of metasynthesis is proposed. The methodology framework is built based on the academic thoughts of metasynthesis. The application prospects for this methodology is discussed for future research.
Ziqiang Zeng; Xinxin Xu; Jonathan Shi. Metasynthesis-Based Intelligent Big Data Processing Paradigm. Advances in Intelligent Systems and Computing 2016, 455 -466.
AMA StyleZiqiang Zeng, Xinxin Xu, Jonathan Shi. Metasynthesis-Based Intelligent Big Data Processing Paradigm. Advances in Intelligent Systems and Computing. 2016; ():455-466.
Chicago/Turabian StyleZiqiang Zeng; Xinxin Xu; Jonathan Shi. 2016. "Metasynthesis-Based Intelligent Big Data Processing Paradigm." Advances in Intelligent Systems and Computing , no. : 455-466.
This paper focuses on investigating the cross-border financial contagion based on a fuzzy dynamical system scenario simulation from a perspective of analyzing the volatility of international capital flows for a panel of 50 countries in emerging markets and advanced economies from 1980 to 2011. Increasing evidence has shown that financial globalization has developed into a complex nonlinear dynamical system made up of economic subsystems with extensive financial connections and linkages. The contagion effects of the spread of bonanzas in the 50 countries are identified and analyzed. The Hodrick-Prescott filter is employed to address the long-term net capital inflow trend. The comovement of financial contagion between the source country of financial turbulence and the volatility-affected country is described as a fuzzy dynamical system in which the driving and response systems are coupled. A fuzzy dynamical system scenario simulation model under a liberal economy is established by employing nonlinear differential equations to describe the contagion mechanism and the international capital flow volatility effects. The model is then extended to a dynamical system model with macroeconomic control. The coupling strength uncertainty is addressed by employing an interval type-2 fuzzy theory method. The properties of the volatility equilibrium point for the two models are discussed, and the volatility contagion principles based on locally asymptotic stability analysis are derived to explain the different volatility transmission patterns. Policy suggestions are given in three situations for providing managerial insights for policymakers and the explorations of response strategies are also presented. The global financial crisis in 2008 is used as an experimental study to demonstrate the validity and effectiveness of the simulation and modeling method.
Xinxin Xu; Ziqiang Zeng; Jiuping Xu; Mengxiang Zhang. Fuzzy Dynamical System Scenario Simulation-Based Cross-Border Financial Contagion Analysis: A Perspective From International Capital Flows. IEEE Transactions on Fuzzy Systems 2016, 25, 439 -459.
AMA StyleXinxin Xu, Ziqiang Zeng, Jiuping Xu, Mengxiang Zhang. Fuzzy Dynamical System Scenario Simulation-Based Cross-Border Financial Contagion Analysis: A Perspective From International Capital Flows. IEEE Transactions on Fuzzy Systems. 2016; 25 (2):439-459.
Chicago/Turabian StyleXinxin Xu; Ziqiang Zeng; Jiuping Xu; Mengxiang Zhang. 2016. "Fuzzy Dynamical System Scenario Simulation-Based Cross-Border Financial Contagion Analysis: A Perspective From International Capital Flows." IEEE Transactions on Fuzzy Systems 25, no. 2: 439-459.