| The overseas railway project investment market of Chinese enterprises is mostly in the sensitive zone of the political and economic environment of Asia,Africa and Europe,and the risk of railway project investment has multiplied.With the transformation of investment models and the complex and changeable investment environment,exploring the weights of the early warning indicators and risk thresholds with local characteristics,looking into the operating principles of the risk early warning models,and quickly matching risk responses have become the focus of Chinese companies.Therefore,Chinese companies urgently need to build an intelligent risk early warning system,which can accurately match the output from risk early warning to risk responses,and improve the company's ability to grasp and predict the investment risk of railway projects in the country where the project is located.It helps to clarify the project investment market from a strategic perspective and ensure the effectiveness of Chinese companies' overseas railway project investment.The core of the thesis is to carry out the investment risk early warning of overseas railway projects from the perspective of Chinese companies.Based on the perspective of Chinese companies,the thesis conducts research based on the logic of “Early Warning Index-Risk Threshold-Risk Early Warning Model-Risk Response-Early Warning System Design-Early Warning System Application”.The main research work of the thesis is as follows:First of all,the thesis establishes an early warning indicator system for investment risks of overseas railway projects,breaking through the limitations of existing research that only analyzes political risks,economic risks,legal risks,and social and cultural risks from the general infrastructure dimension.Specially focus on a type of project,including the engineering market risk of railway project investment into the early warning indicator system.They are the demand for transportation infrastructure,the capacity of existing railway projects,the growth rate of urban population,the availability of electricity,and the credit of the local company,the number of local suppliers,the number of competitive companies,and the efficiency of contract execution.Then,the early warning indicator system is supplemented by the unique weight of each country.This enhances the project characteristics and location characteristics of risk warning indicators.Secondly,the thesis constructs an early warning model of investment risk for overseas railway projects.The risk early warning model includes two contents: risk threshold calculation and alarm measurement.According to the numerical change characteristics of various risk warning indicators in each country over the years,this paper calculates the threshold interval suitable for the risk characteristics of each country's railway project,and finds that not every risk threshold interval is evenly divided.For 37 early warning indicators,the risk threshold interval evenly divided in the [0,1] are: government credit level R4,financing difficulty R6,tax rate R7,exchange rate R9,project country debt ratio R10,policy change R11,strict work permit system R13,material clearance time R14,human resources employment restriction R16,investment enterprise exit cost R17,strict technical standards for railway projects R18,strict HSSE standards R19,contract dispute handling efficiency R20,social security R21,terrorism R22,natural disasters R24,cultural distance R25,employee skill training R27,public attitudes R28,transportation infrastructure demand R30,existing railway project capacity R31,power availability R33,local supplier credit R34,number of local suppliers R35,number of competitive companies R36.The indicators with a relatively large value range of the risk threshold interval in the I and II interval are: political stability R2,corruption control R3,inflation R8,construction permit processing time R12,land acquisition difficulty R15,epidemic R23,employee work attitude R26,contract execution efficiency R37.The indicators with a larger range of risk threshold values in the IV and V levels are: the relationship between the investing country and the host country R1,administrative efficiency R5,residents' education level R29,urban population growth rate R32.In addition,this article uses the GM model and the extension matter-element model to measure the risk.For the risks that have occurred,the early warning model will activate the extension matter-element model to measure the risk;for the risks that have not occurred,the early-warning model can use past risk data to predict the value of future risk early warning indicators,and start the extension matter-element again to diagnose risk.This realizes the early warning of comprehensive investment risks and six types of investment risks for railway projects,and provides technical support for Chinese enterprises to grasp investment risks.Third,the thesis designs the investment risk response for the overseas railway projects,which realizes that the input terminal embeds the investment fault characteristic attribute value,and the output terminal can output the configuration of risk response.It is discovered that the risk response should be based on land use planning,rational employment,compliance management,financing risk,tax risk,inflation,exchange rate risk,legality of work visas for expatriates,employment policies for local employees,local ecological protection policies,land acquisition risks,litigation risks,language barriers,religious differences,understanding of ambiguity,education level,public attitudes to the project,railway traffic volume,population density,existing railway conditions in the country where the project is located,and competitiveness of other enterprises.Fourth,the thesis builds a risk early warning system for the investment risk of overseas railway projects to make up for the inefficiency of traditional risk management.The study found that the early warning system consists of four levels: software and hardware infrastructure layer,data collection layer,application support layer and application layer.The hardware and software infrastructure layer is mainly to provide the necessary technical support for the early warning system.The data collection layer is the data foundation for the early warning system operation.The application support layer gathers the core algorithm models for the early warning system operation.The application layer is to realize the visualization and user-friendliness of the early warning results.The early warning system can select the early warning time and the early warning area,display the early warning indicator weight,risk threshold and risk map,and output detailed investment risk response strategies according to actual needs.It will realize data collection,data processing,expert interaction,and management decision-making,and clarify the management system to improve the efficiency of the collaborative operation of the early warning model.Fifth,the paper constructed a 9-year panel data matrix for 49 countries,launched risk early warning and result verification of sample countries from 2010 to 2019,and verified the risk response module through Nigeria railway investment risks.The study found that the leading risks of comprehensive investment risks for overseas railway projects from 2010 to 2012 were Grade IV and Grade V.From 2013 to 2015,it gradually weakened,and the main risk level of the sample countries was level III and below.From 2016 to 2018,it slowly changed to level IV and level V risks.Nigeria's comprehensive investment risk grade is ?,and economic risk,public security risk and social and cultural risk are ? grade,which has a greater conformity with the actual situation in Nigeria. |
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