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15 December 2023, Volume 31 Issue 12 Previous Issue    Next Issue

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Risk Spillover of Soybean Futures Market Based on Dynamic Model Averaging Wu-yi YE,Ai-lin LI,Shou-kun JIAO 2023, 31 (12):  1-10.  doi: 10.16381/j.cnki.issn1003-207x.2022.2789 Abstract ( 289 )   HTML ( 46 )   PDF (778KB) ( 417 )   Save It is of great significance to study the risk spillover effect between soybean futures markets in China and the United States under extreme circumstances. A dynamic model based on the average method and the method of the bureau of digit conditional value at risk are combined to study. The risk spillover effects of Chinese soybean futures market influenced by policy and economic environment change is studied. And it analyses the risk spillover effects influenced by spot market， downstream products of soybean， macro-economic variables， international market trading， etc. It is found that different policies and economic environments affected the soybean futures market risk spillover effects in different ways， such as reserve policy stability of China’s soybean futures price fluctuations， the night trading system to increase the interaction of the agricultural product futures market of China and the United States to increase the degree of impact on the domestic market in the international market. At the same time， the study shows that each control variable has a different contribution to the change in the risk spillover effect of the Chinese and American agricultural futures markets in different periods. For example， soybean oil futures price and WTI crude oil price have a great influence on the risk spillover effect in the early stage of the night trading system. The impact of shipping indices， exchange rates and WTI crude oil prices was at a low level during the COVID-19 pandemic. Figures and Tables | References | Related Articles | Metrics

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Multi-Level Order Flow Imbalance and Price Impact Zhi-dong LIU,Chao WANG 2023, 31 (12):  11-22.  doi: 10.16381/j.cnki.issn1003-207x.2022.2771 Abstract ( 106 )   HTML ( 4 )   PDF (1713KB) ( 231 )   Save In order-driven financial market， order flow imbalance is the main driving force for price movement. To deeply explore the price impact of order flow imbalance， dynamic limit order book， and quantify time-varying characteristics of multi-level order flow imbalance are reconstructed， then the price impact and cross impact are discussed. The mechanism and trader's behavior characteristics behind the result are explored. Our empirical analysis results show that，first，multi-level order flow imbalance contains deeper levels information of limit order book. It can provide higher explanatory power for the contemporaneous price impact. Second， from the perspective of multi-asset trading， the information of other limit order book is also included in multi-level order flow imbalance， multi-asset models with cross-impact do not provide additional explanatory power for contemporaneous impact. Third， the post-double-selection granger causality testing can effectively identify the continuous guidance relationship between different sample stocks' multi-level order flow imbalance and realize the portrayal of cross impact. Multi-level order flow imbalance not only contains private information held by informed traders， but also implies behavioral characteristics of multi-asset traders. Figures and Tables | References | Related Articles | Metrics

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The Transmission Effect of SMEs' Financial Distress on the Credit Risk of Suppliers Jing GU,Ya-ting HU 2023, 31 (12):  23-33.  doi: 10.16381/j.cnki.issn1003-207x.2021.1048 Abstract ( 130 )   HTML ( 11 )   PDF (649KB) ( 364 )   Save The financial distress of small and medium-sized enterprises（SMEs）will bring a series of negative effects to themselves， from its startup to its decline. Multiple theories and much empirical evidence have been proposed to interpret this phenomenon. At the same time， the distress events can lead to negative wealth and profitability outcomes for supply chain members in the short time and long time. In fact， the financial distress of SMEs has become a major concern in disruptions to normal activities， but only a few contributions in the literature have focused on the transmission effect of SMEs’ financial distress on the credit risk of suppliers. Credit risk refers to the risk caused by the borrower's possible default and failure to repay the loan and interest. The credit risk may propagate further， sometimes even with amplifications， leading to a negative performance outcomes for the members， reducing the overall operational efficiency and competitiveness of the supply chain. To this end， a transmission model is constructed to analyze the impact of SMEs’ financial distress on the credit risk of suppliers. During modeling， classical Jarrow–Turnbull model is used as reference to denote the intensity of default risk\alphaand the probability of default riskF(t). Furthermore， the above mechanism is tested by the sample of Small and Medium-sized Board from 2010 to 2018. The results are as follows based on the theoretical model and empirical research： Firstly， there is a positive relationship between the financial distress of SMEs and the credit risk of suppliers. Secondly， the suppliers’ own factors have a greater impact on their credit risk than that of SMEs’ financial distress. Additionally， this process has a time effect of two years， and suppliers of high scale， high-customer-concentration and state-owned nature are more resistant to credit risk. On the contrast， manufacturing， primary and secondary industry suppliers have weaker risk resilience. The findings of this paper， on the one hand， provide reference for the credit risk prevention and management of SMEs and the supply chain system. On the other hand， promoting the stability and competitiveness of supply chain node-enterprises. Figures and Tables | References | Related Articles | Metrics

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Do Commodity Futures Improve the Performances of Traditional Portfolios? Evidence from the Chinese Market De-hua SHEN,Yue LI 2023, 31 (12):  34-45.  doi: 10.16381/j.cnki.issn1003-207x.2020.2035 Abstract ( 86 )   HTML ( 8 )   PDF (573KB) ( 151 )   Save Many foreign researchers have studied the role of commodity futures in traditional portfolios. Most of them believe that commodity futures can improve the performances of traditional portfolios through increasing returns or reducing risks of portfolios. However， few studies investigate the commodity performances of portfolios in China and the conclusions are controversial.Based on the market of stock， bond， and commodity futures in China from 2015 to 2019， the in-sample and out-of-sample performances resulting from adding commodity futures are analyzed. The data of CSI 300 Index， CSI Aggregate Bond Index， and a series of Wind Commodity Indexes are employed， respectively. 9 different portfolio strategies including 1/N， Strategically-Weighted， Risk-parity， Reward-to-Risk Timing， Minvar， Mean-Variance， Bayes-Stein shrinkage， Black-Litterman strategy， and portfolio selection with higher moments are used. And investors are divided into conservative and aggressive investors.The empirical results indicate that the commodity performances of portfolios are depended on the strategy employed. Firstly， out-of-sample performances are worse than in-sample performances. Under the out-of-sample setting， 1/N， Strategic Weighted， Risk Parity， Minvar， and Black-Litterman strategy show that commodity futures are beneficial to all kinds of investors. Reward-to-Risk Timing， Mean-Variance， Bayes-Stein shrinkage， and portfolio selection with higher moments show opposite performances. Secondly， considering the “view” return and the reliability matrix， the Black-Litterman strategy is the best of all portfolio strategies. Thirdly， weights of commodity futures and the rolling Sharpe ratio are reported. Commodity futures in weights with volatilities of more than 5% often show poor performances. Besides， bonds overweight was obvious during the sample period.The findings of this paper suggest that commodity futures in China do improve the performances in traditional portfolios when appropriate strategies are chosen. Besides， it is crucial to estimate the parameter in the models. Figures and Tables | References | Related Articles | Metrics

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Research on Impacts of Performance Compensation Commitments on Timing of Mergers and Acquisitions under Information Asymmetry Teng NIU,Xi ZHAO 2023, 31 (12):  46-56.  doi: 10.16381/j.cnki.issn1003-207x.2020.2365 Abstract ( 89 )   HTML ( 8 )   PDF (785KB) ( 167 )   Save The continuing advancement of economic globalization makes firms face a more complex external environment. Considering this background， the decision-makers of mergers and acquisitions （M&As） should be more judicious in launching M&A initiations. The decision-makers must compare the advantages and disadvantages of the initiations at various points in time when determining the merger timing. Moreover， there is information asymmetry between the two parties to a merger； a merged firm typically has access to more information about the transaction than a merging firm， allowing the merged firm to gain excess returns by taking advantage of the asymmetric information. Therefore， the merging firms may adopt tactics to mitigate the impacts of information asymmetry. In China， a common tactic to reduce information asymmetry between the two sides is to sign a performance compensation commitment. Performance compensation commitments might motivate the management of the merged firm and help improve its performance after the merger； however， performance compensation commitments may also have negative consequences such as excessive premiums and short-sighted actions. Therefore， it is essential to develop performance compensation commitments reasonably and rationally. Taking account of the impacts of performance compensation commitments， merger timing is analyzing using a real options game under information asymmetry.In the real options game model constructed in this paper， the cash flows of the merged firm are assumed to obey a geometric Brownian motion. The initial level of cash flows of the merged firm and the evolution of cash flows are public information. However， the cost of the merged firm in the integration phase is private information. The merging firm does not know exactly the cost of the merged firm in the integration phase but only its probability distribution. To reduce the impacts of information asymmetry， the merging firm offers alternative M&A proposals that may be accompanied by performance compensation commitment agreements， and the merged firm is free to choose. By analyzing the game equilibrium， the following conclusion is obtained： first， there is an optimal range of the penalty in the performance compensation commitment； second， under the asymmetric information， the merging firm only needs to make the performance compensation commitment agreement with the high-cost-type merged firm； third， only the optimal timing of high-cost-type is distorted by the information asymmetry， and it is also affected by the performance compensation commitment； fourth， with the increase of penalty and the decrease of the cost difference between the two types of the merged firms， the timing of the high-cost-type merger is moved forward and the distortion of the profits of the merging firm is reduced.It contributes to the literature in two ways.　First， performance compensation commitments and merger timing decisions are incorporated into a unified analytical framework， which complements the existing factors influencing merger timing. Second， the existing research about merger timing is expanded by considering the impacts of information asymmetry. Figures and Tables | References | Related Articles | Metrics

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Fund Size, Investor Attention and Fund Performance Persistence Yong-ji ZHANG,Tian-xiong LI,Zhi SU,Qiong HUANG 2023, 31 (12):  57-68.  doi: 10.16381/j.cnki.issn1003-207x.2021.2003 Abstract ( 103 )   HTML ( 14 )   PDF (628KB) ( 120 )   Save High return funds are the stars in the fund market and attract investors’ attention， but their excellent performance is not persistent. It is normal that star funds become “shooting stars” in market， and one of the most important reasons is the herd behavior of investors.Based on the data of China’s equity mutual funds from 2005 to 2020， the impact of “performance flow relationship” （PFR） on fund performance persistence is studied by using the mediating effect model. The empirical results show that： （1） PFR causes diseconomies of scale. The higher the performance of the fund in the past year， the more net fund flow in the current quarter， which will lead to a decline of the performance in the next half year. Net fund flow is apartial mediator. （2） The decrease ofholding concentration can explain the internal mechanism of diseconomies of scale. The increase of net fund flow leads to the decrease of fund holding concentration， which leads to the decline of performance， and this mechanism has a more rapid impact on small-cap and medium-cap funds. （3） Investors’ limited rationality from time series dimension affects PFR. During the bull market， the optimistic market weakens investors’ attention to fund past performance， so PFR has no effect on fund performance persistence. （4） Investors’ limited rationality from cross-sectional dimension affects PFR. Investors purchase funds based on simple performance evaluation criteria. The funds with one factor α but without multi factor α in history get excess net fund flow， which causes the mismatch between management scale and management skill of fund managers. The sample is further divided into “pseudo star fund” group and “real star fund” group. It is found that diseconomies of scale only exist in “pseudo star fund” group. Figures and Tables | References | Related Articles | Metrics

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Can Executives with IT Background Promote FinTech Innovation? Jiang-ze DU,Xi-zhuo CHEN,Le-an YU 2023, 31 (12):  69-78.  doi: 10.16381/j.cnki.issn1003-207x.2022.1295 Abstract ( 119 )   HTML ( 10 )   PDF (542KB) ( 182 )   Save The rapid development of FinTech is transforming traditional financial systems and driving global economic growth through the integration of new technologies. Effective FinTech innovation system is crucial for the high-quality development of China's digital economy. While existing literature focuses on FinTech as an explanatory variable for the development of the real economy and financial industry， it lacks exploration of the micro-level source of FinTech， leaving the question of how to promote FinTech innovation unanswered. It aims to measure the level of FinTech innovation for financial firms at the individual level and analyze the impact of executives with IT backgrounds on FinTech innovation. The patent data used in this study comes from the National Intellectual Property Administration and China Intellectual Property Right net， which includes all patent application information and current status of patents filed in China. The financial data related to the enterprise comes from China Stock Market & Accounting Research Database. Using a deep learning-based Chinese text classification method to identify FinTech patents， and combining the patent data with A-share listed financial enterprises' data from 2013 to 2020， it is found that executives with IT backgrounds can indeed promote FinTech innovation. The robustness of the conclusion is confirmed after considering possible endogeneity. Mechanism tests reveal that this effect is achieved through increased R&D investment and is also influenced by myopic behavior and the direction of the firm's innovation search. Further research demonstrates that the differences in executive positions， FinTech categories， and implementation of FinTech industry policies are important heterogeneity factors affecting the relationship between executives with IT backgrounds and FinTech innovation. The main contributions of this paper are threefold. First， it fills the research gap by exploring how to promote FinTech innovation at the micro level from the perspective of innovation research， treating FinTech as an innovation output. Second， it uncovers the differences and mechanisms of IT background executives' influence on FinTech innovation， providing decision support for financial enterprise managers and policymakers. Third， the method proposed in this study， which utilizes character-level convolutional neural networks for identifying FinTech patents， contributes to the research on FinTech innovation at the micro-level. Figures and Tables | References | Related Articles | Metrics

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An Interest Rate Term Structure Model Based on the Hypothesis of Irrational Traders: A Theoretical and Empirical Study Hua CHEN,Xiao-ya ZHENG,Rong CHEN,Nai-ju SHI 2023, 31 (12):  79-86.  doi: 10.16381/j.cnki.issn1003-207x.2020.1090 Abstract ( 68 )   HTML ( 9 )   PDF (612KB) ( 73 )   Save The efficient market hypothesis based on rational expectation hypothesis holds that when the market is completely efficient， asset prices completely reflect all information and obey martingale process. However， a large number of empirical studies show that many anomalies of interest rates are actually the expression of irrational sentiment in the market. The “failure” of the efficient market hypothesis shakes the rational expectation assumption of the term structure model of interest rates. Traders are divided into noise traders who represent irrational trading and information traders who represent rational trading， and a term structure model of interest rates is established based on traders' irrational assumption. Taking Chinese market as a sample， the irrational fluctuation degree and influencing factors of the weighted interest rate of pledge style repo and that of exchange repo are studied. The results show that in the same market， the longer the term of interest rate is， the higher the degree of irrational volatility is； the irrational volatility of exchange rate in the same period is higher than that in the inter-bank market； “interest rate duration”， “regulatory system” and “net amount of operating funds in the open market of the central bank” are not the factors leading to the irrational fluctuation of China's interest rates， and the “investor heterogeneity” factor has an impact on the irrational fluctuation of China's interest rates Movement has a significant effect. The research shows that： the open market operation has not played a role in restraining the irrational fluctuation of interest rate， so how to restrain the irrational fluctuation of interest rate through better system construction and policy operation should be the key policy consideration； in addition， noise trading and investor heterogeneity are important factors leading to irrational interest rate fluctuations， and the central bank should strengthen the management of interest rate expectation in the money market to restrain interest rate The rate fluctuates irrationally. Figures and Tables | References | Related Articles | Metrics

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Multi-Period Crowdsourcing Logistics Service Quality Optimization Considering Delay Insurance Xiu-li MENG,Yi-fan WU,Bo LIU 2023, 31 (12):  87-95.  doi: 10.16381/j.cnki.issn1003-207x.2021.1807 Abstract ( 92 )   HTML ( 10 )   PDF (807KB) ( 168 )   Save With the rapid development of China’s crowdsourcing logistics industry， the modern crowdsourcing logistics industry service quality promoting effect and ways of logistics insurance become a hot topic in China’s logistics industry and academia. Existing literature has done research on the improvement of logistics service quality by logistics insurance， the optimization effect of delay insurance on crowdsourcing logistics service quality is studied.The optimization effect of delay insurance service on the quality of multi-period crowdsourcing logistics service is considered and a three-tier crowdsourcing logistics service network model is developed with service demanders， crowdsourcing platforms and service providers. The variational inequality is used to describe the equilibrium state considering the optimal behavior of each member of the crowdsourcing logistics service network. The result shows that due to the difference between the perceived quality and actual quality of the crowdsourcing logistics service by the service demanders， the delay insurance service has a significant effect on the quality of the crowdsourcing logistics service during multiple transaction periods， and the profits of the crowdsourcing platforms and the service providers first decline and then gradually increase to a stable state and are higher than the profits without delay insurance. In the initial stage of implementation of delay insurance， the quality of crowdsourcing logistics services and the profits of crowdsourcing platforms will increase with the increase in the amount of compensation and the purchase ratio. Due to the difference in the profits distribution ratio of the delay insurance service， the profits of the service providers will not increase linearly but have an inflection point， which require the crowdsourcing platforms to adjust the parameters of the delay insurance according to the actual situation. When the delay insurance parameters are adjusted again after reaching a stable state， each equilibrium decision will show a linear increase or decrease with the change in the amount of compensation and the purchase ratio， and there will no longer be an inflection point. Figures and Tables | References | Related Articles | Metrics

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Two-stage Mean Semi-variance Portfolio Optimization with Stock Return Prediction Using Machine Learning Peng ZHANG,Shi-li DANG,Mei-yu HUANG,Jing-xin LI 2023, 31 (12):  96-106.  doi: 10.16381/j.cnki.issn1003-207x.2021.2308 Abstract ( 226 )   HTML ( 25 )   PDF (2248KB) ( 354 )   Save Since accurately predicting stock return sequences can improve the performance of portfolio optimization models， the results have indicated that machine learning methods have a greater capacity to confront problems with nonlinear， nonstationary charateristics than econometric models. Consequently， a novel two-stage method is proposed for well-diversified portfolio construction based on stock return prediction using machine learning， which includes two stages. To be specific， the purpose of the first stage is to select diversified stocks with high predicted returns， where the returns are predicted by machine learning methods， i.e. eXtreme Gradient Boosting（XGBoost）， support vector regression（SVR）， K-Nearest Neighbor（KNN）， and evaluate and select the model. In the second stage， considering the constraints such as transaction costs and threshold constraints， the predictive results are incorporated into the mean semi-variance （M-SV） model， mean-variance model and equally weighted model to determine optimal portfolio. Finally， using China Securities 300 Index component stocks as study sample， the empirical results demonstrate that the XGBoost+MSV model achieves better results than similar counterparts and market index in terms of return and return-risk metrics. Figures and Tables | References | Related Articles | Metrics

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Modeling and Optimization Solution of Two-stage Emergency Supply Chain Network under Uncertain Environment Hai DONG,Xiu-xiu GAO,Ming-qi WEI 2023, 31 (12):  107-116.  doi: 10.16381/j.cnki.issn1003-207x.2020.2151 Abstract ( 139 )   HTML ( 9 )   PDF (869KB) ( 258 )   Save In recent decades， all kinds of natural disasters and public health emergencies have occurred frequently. In order to reduce the loss and casualties caused by emergencies as much as possible， emergency supplies must be delivered to all the points of need in the shortest possible time. Therefore， the center location and material distribution in the emergency network become the key problems to be solved after an emergency. To improve the operational efficiency and reliability of the emergency supply chain network， the location and distribution of the emergency supply chain network are studied from the perspective of system integration and optimization. The supply chain network studied includes the supply point of emergency supplies， the transit warehouse of supplies and the demand point. According to the characteristics of emergencies， considering the uncertainty of emergency supplies supply and demand， a two-stage emergency supply chain network planning model is constructed by adopting the multi-transport mode distribution model. Firstly， based on the robust optimization theory， the uncertain demand and supply are represented as interval data， and the linear duality theory is used to transform the uncertain parameter constraints， and a multi-objective robust optimization model is established， with the network response time， cost and carbon emissions as the minimum optimization objectives. Secondly， a meta-heuristic algorithm is used to solve the model. Considering the shortcomings of the standard cuckoo algorithm， which uses fixed step size control factor and fixed discovery probability to search the optimal solution， an optimal cuckoo search （OCS） algorithm based on dynamic parameter adjustment strategy is proposed in this paper. OCS algorithm is applied to four test problems， namely DZT1， DZT3， DTLZ2 and DTLZ5， and the optimization results are compared with those of CS algorithm and NSGA-II algorithm to verify the effectiveness of the proposed algorithm. The experimental results show that compared with CS algorithm， the solving ability of OCS algorithm has been significantly improved. The introduction of the dynamic adaptive adjustment strategy can effectively improve the convergence and uniformity of the algorithm. In addition， the experimental results show that the OCS algorithm has a strong competitiveness compared with the mainstream NSGA-II algorithm. Finally， the emergency supply chain network decision-making problem with uncertain parameters is studied by using the emergency material allocation data of the disaster areas of Wuhan. The results show the effectiveness of the multi-objective robust optimization model， and the sensitivity analysis results verify the effective inhibition effect of the robust control coefficient on the uncertain disturbance. This study can provide effective guidance for the construction of emergency supply chain network in emergencies. Figures and Tables | References | Related Articles | Metrics

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The Research on Emergency Material Reserve and Contract Design under Asymmetric Information Hui FENG,Cheng-feng HUANG,Li ZHANG,Wen-qiang SHI,Liang JIN 2023, 31 (12):  117-127.  doi: 10.16381/j.cnki.issn1003-207x.2021.1222 Abstract ( 106 )   HTML ( 4 )   PDF (533KB) ( 77 )   Save In recent years， sudden natural disasters and public health incidents have brought serious threats to people's health and life safety， and have greatly hindered social and economic development. After disasters， the demand for emergency supplies usually increases explosively， in order to improve emergency response capabilities， the government needs to jointly reserve emergency supplies with a supplier in advance， that is， in addition to the government's regular reserves， the supplier is responsible for the production and storage of some emergency supplies as the flexible reserve quantity， and the flexible reserve quantity is determined according to the flexible procurement contract provided by the government. However， in the process of actual government-enterprise alliance， the degree of risk aversion of supplier is their private information， and the government cannot accurately grasp the reserve willingness of supplier. Therefore， based on the analysis of game relationship between supply chain costs and profits in emergency situations， a Stackelberg game model led by the government in different situations is established， and the model is verified by numerical simulation.Our findings contribute to the use of contract design mechanisms to coordinate the literature of emergency supply chains under asymmetric information， and provide assistance to the government in deciding how to stimulate the cooperate willingness of supplier in order to achieve emergency purposes.The main work of this paper includes　firstly， propose the government's optimal contract design and the supplier's optimal flexible reserve under symmetrical information and asymmetrical information respectively； secondly， on the basis of the above， supply chain member’s optimal pricing and optimal reserve strategy under different risk aversion types are analyzed； third， the government’s optimal contract design and the changes in the costs and benefits of supply chain members under complete information and asymmetric information are compared； finally， the impact of asymmetry information on the willingness to share information of supplier and the influence of negotiation mechanisms is further discussed.The results show that when the government accurately understands the type of supplier risk aversion， the flexible procurement contract can achieve the perfect coordination of the humanitarian supply chain； due to the existence of asymmetric information， the government’s disadvantage information will lead to an increase in expected costs， and supplier advantage information will bring additional benefits， the government’s information value is greater than the supplier’s information rent， leading to the loss of expected profits of the supply chain system； under certain conditions， the supplier will choose information sharing negotiations to share their private information with the government， promote the expected profit of the supply chain system to achieve the optimal level. Figures and Tables | References | Related Articles | Metrics

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Inventory Decision Considering Returns under Omni-channel Retailing Rui-zhen XIE,Yao ZHANG 2023, 31 (12):  128-137.  doi: 10.16381/j.cnki.issn1003-207x.2020.2308 Abstract ( 104 )   HTML ( 5 )   PDF (705KB) ( 227 )   Save Omni-channel retailing is a new model that combines online store and offline physical store. In the context of omni-channel retailing， retailers provide consumers with more options for return channels， including same-channel return mode （offline/online purchase， offline/online return） and cross-channel return mode （online store purchase， offline physical store return）. For retailers， although the cross-channel return service can reduce the logistics cost of returns to an extent and increase the consumer traffic of offline physical store， the choice of return channels and the re-sale of returned products brings challenges to the inventory management. If the inventory is higher than consumer demand， it will bring the pressure of inventory holding cost to retailers. If inventory falls short of consumer demand， retailers will incur out-of-stock cost. Based on the analysis， the inventory decision under omni-channel retail considering returns is studied in two cases： same-channel returns and cross-channel returns. On the basis of considering consumer returns and the resale of returned products， the newsvendor model is used to construct inventory decision models in the case of same-channel returns and cross-channel returns aiming at maximizing retailers' profit， and the models are analyzed. The numerical analysis shows that， the proportion of online consumers using ROPS （reserve-online and pick-up-and-pay-in-store） to purchase when out of stock， the proportion of resale of returned products， the proportion of online returns， and the proportion of cross-channel returns have a significant impact on the inventory of the offline physical store and online store and profit. Specifically， under the cross-channel returns mode， the inventory decision quantity of offline physical store should be directly proportional to the proportion of online consumers using ROPS to purchase when out of stock or the proportion of online returns， and inversely proportional to the proportion of resale of returned products or the proportion of cross-channel returns； the inventory decision quantity of the online store should be directly proportional to the proportion of online consumers using ROPS mode to purchase when out of stock， the proportion of online returns or the proportion of resale of returned products， and inversely proportional to the proportion of cross-channel returns. The difference between the same-channel returns model and the cross-channel returns model is that the proportion of online returns or the proportion of resale of returned products has no significant influence on the inventory decision in the offline store. In particular， when the cross-selling profit is large， the profit of the retailers will increase with the proportion of cross-channel returns， but the profit of the retailers may decrease with the proportion of online returns. In terms of practical application， although there is still a certain gap between the model construction and the reality， the relevant conclusions can also provide a certain theoretical foundation and decision-making reference for the retailers' omni-channel retailing operation management. Figures and Tables | References | Related Articles | Metrics

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Research on Knowledge Diffusion of Closed-Loop Supply Chain Domain: A Main Path Analysis De-jian YU,Li-bo SHENG,Deng-feng LI 2023, 31 (12):  138-148.  doi: 10.16381/j.cnki.issn1003-207x.2021.1583 Abstract ( 73 )   HTML ( 3 )   PDF (1023KB) ( 175 )   Save Studying the research hotspots and the path of theme evolution in the closed-loop supply chain （CLSC） field is important for guiding the future research in China. Under this circumstance， the co-word analysis and the main path analysis are adopted to analyze 555 papers in the CSCD and CSSCI databases during 2004 to 2020 systematically， aiming to dig out research hotspots， explore their relevance and reveal the knowledge diffusion in this field. The results show that： （1） pricing strategy and coordination have always been the hot topics in this field； （2） in recent years， the emphasis on government policies and environmental protection has gradually increased； （3） The research has gone through three main stages， namely， the pricing decision-making of members and coordination mechanism under decentralization and concentration CLSC， the simple CLSC with fairness concerns， and CLSC where multiple members at the same level compete with fairness concerns. It will help researchers grasp recent research hotspots and potential development directions， help them understand the process of knowledge diffusion in this field， for the purpose of grasping the research progress of this field from a macro level comprehensively. Figures and Tables | References | Related Articles | Metrics

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Blockchain Technology, Supply Chain Networks and Data Sharing: Based on the Perspective of Evolutionary Game Guo-qiang SUN,Yu-fei XIE 2023, 31 (12):  149-162.  doi: 10.16381/j.cnki.issn1003-207x.2022.2727 Abstract ( 152 )   HTML ( 18 )   PDF (1134KB) ( 251 )   Save Supply chain networks achieve precise coordination of supply and demand through real-time data sharing， reducing production blindness and mitigating the “bullwhip effect.” They also open up new market opportunities and generate comparative advantages， leading to steady improvements in productivity and breaking the zero-sum game of supply chain relationships. However， potential opportunism risks in actual transactions can result in a high failure rate of supply chain network cooperation， reaching 50%~70%. Therefore， intelligent technology is urgently needed to innovate the digital governance model of supply chain networks， solve data isolation problems and opportunism dilemmas， and promote digital transformation of supply chain networks. A three-party evolutionary game model of government and upstream and downstream subgroups in supply chain networks is constructed to explore the mechanism behind opportunity sharing behavior in supply chain networks and then blockchain technology is introduced to determine the optimal strategy choices of participating entities under different influencing factors. It analyzes the impact of initial willingness， costs， benefits， etc. on the willingness and efficiency of data sharing in supply chain networks and conducts simulation analysis. The results show that， first， under the empowerment of blockchain technology， the initial willingness of the three parties significantly affects the formation of the final stable equilibrium state， which helps to improve the efficiency of data sharing in supply chain networks. Second， increasing the incentive and punishment intensity of data sharing can increase the willingness of upstream and downstream subgroups to share data， while reducing marginal costs and speculative gains can effectively suppress opportunity sharing behavior. Third， when the incentive intensity is greater than the critical value， the government's loose regulation tends to promote data sharing behavior， while when the punishment intensity is lower than the critical value， the government's strict regulation also leads to opportunity sharing behavior， rendering the blockchain regulation ineffective. Finally， the lower the regulatory cost and the more significant the negative and positive social effects， the more the government is inclined to continue to exert supervision efforts. By analyzing the collaborative mechanism of the upstream and downstream subgroups and the government， theoretical support and decision-making basis are provided for digital governance of supply chain networks under the new development pattern. Figures and Tables | References | Related Articles | Metrics

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Research on Investment Timing Decision of Blockchain for Shipping Companies under Demand Uncertainty Jie WU,Jia-guo LIU 2023, 31 (12):  163-174.  doi: 10.16381/j.cnki.issn1003-207x.2022.2770 Abstract ( 72 )   HTML ( 3 )   PDF (833KB) ( 128 )   Save Blockchain is a distributed ledger technology， its decentralized， paperless， open， and transparent features can increase the trust among shipping companies and improve the efficiency of shipping business clearance， which is popular among modern shipping companies. At present， some shipping companies have already carried out the practice of blockchain， a typical example is the cooperation between shipping giant Maersk and IBM to improve the service level of the shipping business through blockchain. However， in the actual operation of shipping enterprises， due to the impact of geopolitics， COVID-19， technological change， climate change and other factors， there are many uncertainties in the global freight demand and the application of blockchain technology， especially in the face of fierce competition in the market， when to adopt blockchain has become a big problem troubling the operation of shipping companies. In this background， aiming at the application problem of blockchain in shipping companies， the change of competition form among shipping companies before and after the adoption of blockchain is taken as the entry point， the timing decision model is constructed under different competition scenarios， and uses real options theory to explore the investment timing strategy of blockchain for shipping companies under freightdemand uncertainty. In addition， we use numerical analysis to further explore the impact of different market and technological environments on the investment timing strategy of blockchain for shipping companies， and verify the robustness of the model through extended analysis. It shows that the stronger the incentive for shipping companies to invest blockchain early in a competitive price environment， and conversely， the weaker the incentive for shipping companies to invest blockchain early in a competitive service environment. Further discussion reveals that shipping companies can adopt differentiated blockchain investment timing strategies in the face of different demands， technologies as well as competitive environments. Then， the extended analysis reveals that government subsidies can provide incentives for shipping companies to invest blockchain in advance， while high operating costs can hinderthe blockchain promotion process. Finally， this paper provides forward policies and suggestions for governments and shipping companies to accelerate the application of blockchain technology from the perspectives of market competition， market demand， and technical environment. Figures and Tables | References | Related Articles | Metrics

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A Game Analysis on the Impact of External Knowledge on Process Innovation Considering Manufacturer's Heterogeneity Wei LIU,Ke XU 2023, 31 (12):  175-184.  doi: 10.16381/j.cnki.issn1003-207x.2020.1205 Abstract ( 71 )   HTML ( 3 )   PDF (626KB) ( 230 )   Save In this paper， the AJ R&D competition model and asymmetric R&D model are used to propose a 2-stage non-cooperative game model about the impact of external knowledge on process innovation in oligopolistic competition market composed of two heterogeneous manufacturers based on knowledge-based view and open innovation theory. The subgame Nash equilibrium solution is solved by inverse regression method， then the equilibrium solution theoretically is analyzed， and numerical simulation is performed. Our findings is that the manufacturer has a larger market share with cost advantage of process innovation for heterogeneous manufacturers， and the equilibrium amount of external knowledge assimilated by the manufacturer will change with the initial cost difference coefficient. Overall， enterprise heterogeneity has caused imbalance in process innovation competition. In the process of process innovation， external knowledge assimilated by the manufacturers has a positive effect on its equilibrium output， and there is a threshold for its impact on the equilibrium profit which increases first and then decreases. Due to spillover effects， external knowledge assimilated by the manufacturer also has a positive effect on the equilibrium output and profits for the opposite manufacturer， but the equilibrium output and profits of the opposite manufacturer depend on the competitive relationship between two manufacturers. Some managerial implications are put forward to promote the use of external knowledge and the effectiveness of process innovation further is enhanced. Figures and Tables | References | Related Articles | Metrics

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Cost Compensation Method for Incentives Based on Dynamic Non-cooperative Game and Super-efficiency DEA Qian-zhi DAI,Xiao-chi XU,Xi-yang LEI,Qian ZHAO 2023, 31 (12):  185-192.  doi: 10.16381/j.cnki.issn1003-207x.2022.1859 Abstract ( 78 )   HTML ( 3 )   PDF (837KB) ( 118 )   Save In practice， a common problem faced by managers is how to motivate decision-making units （DMU） to improve their performance by means of cost compensation. It is especially common in the problems of cost supervision and price mechanism in the monopoly industry and public welfare service industry. The existing cost compensation studies do not provide sufficient positive incentives for effect DMUs， and also do not consider the non-cooperative game relationship that often occurs among DMUs in the face of interests. Therefore， dynamic non-cooperative game is combined with super-efficiency data envelopment analysis （DEA） and a dynamic game super-efficiency DEA algorithm with bidirectional incentive effect is proposed. The convergence of the algorithm is proved and the optimal solution is a unique Nash equilibrium point. The proposed method is applied to 25 provincial-level power grid enterprises of a power grid group in China from 2016 to 2019， and the effectiveness of the method is verified. The results of the case study show that： 1） The operating efficiency of power grid enterprises in different regions is significantly different， and the motivation of performance improvement is not strong； 2） The proposed cost compensation scheme can generate positive or negative incentives for DMU with different performance， and the proposed method is helpful to strengthen the motivation of DMUs to actively improve their performance.It further enriches the DEA theoretical research of cost compensation for incentives and provides an effective management tool for relevant managers in this study. Figures and Tables | References | Related Articles | Metrics

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Joint Strategy of Option Order and Deposit Inflation Pre-sale with Considering Consumers' Risk Aversion Qi XU,Qi DONG,Bao-li SHI 2023, 31 (12):  193-202.  doi: 10.16381/j.cnki.issn1003-207x.2020.2504 Abstract ( 70 )   HTML ( 3 )   PDF (774KB) ( 146 )   Save The joint strategy of flexible ordering and pre-sale can reduce the risk of inventory overstock and product out of stock caused by uncertain demand. However， how to formulate pre-sale strategies to attract more consumers to pre order products and formulate more flexible ordering strategies is an important issue for retailers to optimize their operations. Two pre-sale modes are considered， namely， retailer discount and “deposit inflation”， and the risk aversion of strategic consumers' pre-sale behavior is considered， consumer valuation and utility function are constructed， and the optimal pre-sale price of discount pre-sale and the optimal final payment price under “deposit inflation” pre-sale are discussed； The wholesale ordering and option combination ordering strategies of retailers under two pre-sale modes are studied， and the corresponding optimal total ordering quantity is obtained. Through comparison and numerical calculation， the influence of different influencing factors on the ordering and pre-sale decision choice is analyzed， and the critical threshold under different strategies is obtained. The research shows that under the same pre-sale mode， retailers' option ordering is better than wholesale ordering， and the optimal expected profit of retailers' option combination ordering is greater than that of wholesale ordering. Option portfolio ordering is more flexible； Consumer valuation， wholesale price and deposit inflation rate affect retailers' pre-sale decisions， and the higher the degree of consumer risk aversion， the wider the application scope of “deposit inflation” pre-sale， and the more favorable the retailers choose “deposit inflation” pre-sale mode. The joint strategy of option portfolio ordering and “deposit inflation” pre-sale can effectively reduce the operational risk of retail enterprises caused by demand fluctuations. Figures and Tables | References | Related Articles | Metrics

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Green Vehicle Routing Model and Its Solution Algorithm in Cold-chain Logistics Distribution Xian-cheng ZHOU,Tao-ying JIANG,Cai-hong HE,Li WANG,Yang LV 2023, 31 (12):  203-214.  doi: 10.16381/j.cnki.issn1003-207x.2022.0461 Abstract ( 135 )   HTML ( 14 )   PDF (974KB) ( 271 )   Save In recent years， fresh food e-commerce in China has developed rapidly， with a significantly growing demand for cold-chain logistics distribution. In order to promote energy conservation and emission reduction in cold-chain logistics， the Green Vehicle Routing Problem in Cold-chain Logistics Distribution （GVRPCLD） has attracted increasing attention from both academia and industry. The GVRPCLD discussed in this paper involves set constraints， including （1） distribution center locations， （2） capacity-constrained homogeneous refrigerated vehicles， （3） customers’ number， locations， demands， time windows， service times， and （4） a low temperature kept in the cabin during distribution. The optimal vehicle routing plan is expected to realize the dual goals of total cost minimization and customer satisfaction maximization. Specifically， there are five types of costs that are included in the total cost， which are vehicle usage cost， deterioration cost， cooling cost， fuel consumption and carbon emission cost， and piecewise penalty costs for earliness and tardiness of deliveries. In the design， a freshness decay function is firstly applied to calculate the deterioration cost during distribution. Based on the comprehensive mode emission model （CMEM）， the measurement functions of fuel consumption and carbon emission are determined， with the consideration of the influence of vehicle load， speed， low temperature and other factors on fuel consumption and carbon emission rate. Then， a customer satisfaction function is established according to the relationship between delivery time and customer satisfaction. Finally， a dual-objective GVRPCLD optimization model is constructed. In order to solve the GVRPCLD model， a hybrid algorithm （VNSNSGA-II） is designed in this paper， which is based on the Non-dominated Sorting Genetic Algorithm II （NSGA-II） and the Variable Neighborhood Search （VNS）. The basic idea of the algorithm can be described as follows. Firstly， the VNS is used to optimize some chromosomes in the population to expand the solution space. Secondly， the NSGA-II is performed to obtain non-dominated sorting and crowding degree. Thirdly， based on the individual's rank and crowding distance， the top 50% of chromosomes are obtained and retained as new parent population. Finally， the Pareto-optimal set is obtained by iteration. The simulation results show the following. For one thing， the GVRPCLD model can achieve multi-objective optimization among logistics cost， deterioration cost， fuel consumption and carbon emissions， and customer satisfaction. Furthermore， it is found that logistics cost is negatively correlated with customer satisfaction， indicating that the delivery plan makers can choose different delivery options according to their preference. Last but not least， the proposed VNSNSGA-II is tested， and it is confirmed that the algorithm can contribute to a Pareto-optimal set. Figures and Tables | References | Related Articles | Metrics

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Empirical Study on the Impact of Technological Progress on the Environmental Efficiency of China's Power Industry: Based on SBM Super Efficiency-ML-Tobit Jian-jun PAN,Guang-ming HOU,Ji-fa GU,Hua-feng ZHANG,Jun-peng WANG,Ze-wei CHEN 2023, 31 (12):  215-227.  doi: 10.16381/j.cnki.issn1003-207x.2021.0883 Abstract ( 74 )   HTML ( 2 )   PDF (1069KB) ( 122 )   Save TSBM super efficiency model and ML model are adopted to measure the environmental efficiency and its growth rate of China's power industry in 30 provinces from 2009 to 2018 from a static and dynamic perspective， the static efficiency and dynamic efficiency are splitted， and the impact of technological progress on them is analyzed； Using Tobit regression model， the impact of technological progress and other factors on the environmental efficiency and growth rate of power industry in China and six power grid regions is tested. The results show that the annual average environmental efficiency of China's power industry during the study period is 0.769， which still has a large room for improvement； The improvement of pure technical efficiency in Central China Power Grid and Northeast China Power Grid has a low contribution to the improvement of environmental efficiency； The regional pure technical efficiency of China Southern Power Grid has significantly promoted the improvement of environmental efficiency； The environmental efficiency of China's power industry has increased at an average annual rate of 5.6%， of which the average annual growth rate of technological progress is 3.7%. Technological progress has made a great contribution to the improvement of environmental efficiency of China's power industry. Since the 12th Five Year Plan， the technological progress of China's power industry has accelerated； Technological progress is a key factor affecting the environmental efficiency and growth rate of power industry， which has a significant positive impact on it. It is suggested to continue to increase scientific and technological investment and strengthen scientific and technological innovation， so as to continue to promote the improvement of environmental efficiency of China's power industry； All regions should be proactive and take effective measures according to local conditions， accelerate the development of clean electric energy such as nuclear power and optimize the power supply structure. Figures and Tables | References | Related Articles | Metrics

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Research on the Impact of the Classification Recycling Expenses Bearing Mode on the Recovery Channels and the Coordination Mechanism Xi-qiang XIA,Meng-yuan LU,Biao Chen,Rui Wu 2023, 31 (12):  228-239.  doi: 10.16381/j.cnki.issn1003-207x.2022.0881 Abstract ( 64 )   HTML ( 2 )   PDF (621KB) ( 169 )   Save Classified recycling is an important way to improve the efficiency of resource utilization， but the recycling channel will be affected by the cost-bearing modes of classified recycling. To analyze the impact of classified recycling costs on recycling channels， a game model of decentralized and centralized decision-making involving a recycler and a processor is constructed based on different cost-bearing modes of classified recycling. The main findings of the research are： （1）Classified recycling can increase the revenue of both the recycler and the processor， but only when consumers' sensitivity to the price of waste products is less than a certain threshold， the recycler and the processor are willing to carry out classified recycling； （2）When decentralized decision-making， both the processor and the recycler are responsible for the classified recycling costs better than only one of them is responsible for the classified recycling costs； when the centralized decision is made， the classified recycling effort， the number of waste products recycled， and the revenue of the recycling channel are better than the situation when the decentralized decision is made； （3） Designing a coordination mechanism based on Nash bargaining cost sharing contract is beneficial to increase the revenue of the processor and the recycling channel， but the revenue of the recycler is damaged in this contract model； （4） The two-part tariff contract and revenue-sharing contract， by reallocating equilibrium profits of the recycling channel under the Nash bargaining cost-sharing contract model， can increase the profits of the recycler and the processor when the ratio of fixed fees promised by the processor to the recycler and the profit sharing is within a certain range. This results in Pareto improvement in the supply chain. However， the overall profit of the recycling channel does not reach the level of centralized decision-making； （5） The revenue-sharing-cost-sharing contract not only increases the profits of of the recycler and the processor but also achieves centralized decision-making of overall profit in the recycling channel， thereby achieving supply chain coordination. Figures and Tables | References | Related Articles | Metrics

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Research on the Effect of Environmental Tax Policy Based on Differential Game Yan SONG,Lu ZHANG,Ming ZHANG 2023, 31 (12):  240-248.  doi: 10.16381/j.cnki.issn1003-207x.2022.2767 Abstract ( 91 )   HTML ( 3 )   PDF (683KB) ( 173 )   Save The implementation of environmental tax policy is of great significance to promote ecological environment protection and green development. However， some researchers have not reached a broad consensus on whether environmental tax policy can effectively and pragmatically solve environmental pollution problems. They assume that the actual situation of the implementation effect of environmental tax policy is not yet ideal， and emphasize that the continuous improvement of environmental tax policy can promote its implementation effect to return to the ideal situation proposed by Pigou. It is argued that existing studies have responded to the controversy by only addressing when and under what conditions environmental tax policy is effective. A more general question is whether， as a punitive tax， environmental tax policy tools can solve environmental pollution problems in the established economic ecosystem， achieving a combination effect of environmental benefits， social benefits， and economic benefits？ This crucial question is mainly answered.By introducing the cumulative stock of environmental pollution and the stock of environmental governance capital investment， and using the continuous time differential game model， the effect of environmental tax policy is studied， and the internal mechanism of environmental tax policy between environmental pollution governance and environmental protection capital investment is expounded. The results show that： （1） In a perfect economic ecosystem， the optimal environmental tax policy design is equal to the shadow price of the cumulative stock of unit pollutant emission. The optimal environmental tax is related to the pollutant emission coefficient， the level of capital investment in product production and pollution control， etc. （2） The environmental tax policy design has a complex impact on the economy ecosystem. In a short time， it will reduce the cumulative stock of environmental pollution first and then increase， resulting in limited environmental benefits. But in a long time， it will reduce the cumulative stock of environmental pollution and improve the stock level of environmental governance capital investment， exerting greater environmental benefits and economic benefits. （3） When the environmental tax policy is implemented stably for a long time and forms a forced mechanism for polluting enterprises， the comprehensive effect of its environmental， economic and social benefits can promote the high-quality development of the economic ecosystem.The research conclusion of this paper provides a scientific basis for decision-making departments to attach importance to the rigid and stable implementation of environmental tax policy tools. It can help to explain the differentiated reality of environmental tax policy effects in different periods and empirical results of different researchers. It also can reveal the policy functional effects of environmental tax in the specific context of considering cumulative quantity， promoting the development of the economy towards green and sustainable direction. Figures and Tables | References | Related Articles | Metrics

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How does Industrial Collaborative Agglomeration Affect the Green Resilience of Manufacturing Industry? ——Empirical Analysis Based on Catastrophe Progression and Double Fixed Dynamic Spatial Durbin Model Gen LI,Xin-yu LIU,Jia-guo LIU,Ying ZHOU 2023, 31 (12):  249-260.  doi: 10.16381/j.cnki.issn1003-207x.2022.2766 Abstract ( 100 )   HTML ( 1 )   PDF (695KB) ( 182 )   Save Under various internal and external impulses such as resource and environment constraints and weak independent innovation ability， how to enhance the economic affordability of China's manufacturing industry， that is， the green resilience of manufacturing industry， is of great significance to accelerate the green transformation of manufacturing industry. Based on the adaptive resilience theory， the green resilience index system of manufacturing industry is constructed. Then it uses the catastrophe progression model to calculate the green resilience of manufacturing industry in 30 provinces （cities， autonomous regions） in China from 2005 to 2020. Finally it applies the double fixed dynamic spatial Durbin model to empirically analyze the impact mechanism of industrial collaborative agglomeration on the green resilience of manufacturing industry. The results show that， on the whole， under the three spatial matrices of economic distance， geographical distance and economic and geographical distance nesting， China's manufacturing green resilience has significant positive spatial autocorrelation， and the impact of industrial collaborative agglomeration on manufacturing green resilience presents an inverted “U” shape and has a significant spatial spillover effect；The collaborative agglomeration of technology intensive manufacturing industry and high （low） end producer services has an inverted U-shaped impact on the green resilience of manufacturing industry， while the collaborative agglomeration of labor， capital intensive manufacturing industry and high （low） end producer services has no obvious impact on the green resilience of manufacturing industry；The collaborative agglomeration in the eastern and central regions has an inverted “U” shaped impact on the green resilience of manufacturing industry， while the collaborative agglomeration in the western regions has no obvious impact on the green resilience of manufacturing industry. This study improves the green resilience of manufacturing industry from the aspects of continuously optimizing the layout of manufacturing industry， reasonably and appropriately guiding the integrated development of the two industries， and strengthening the important position of technology intensive manufacturing industry. Figures and Tables | References | Related Articles | Metrics

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Mutual Resistance or Mutual Forbearance? Study on Platforms Multimarket Competition Strategy Zhi-wen LI,Bao-jiao WANG,Yi LU,Le Texier THOMAS 2023, 31 (12):  261-271.  doi: 10.16381/j.cnki.issn1003-207x.2022.2224 Abstract ( 89 )   HTML ( 8 )   PDF (614KB) ( 97 )   Save Platforms cross-market operation has become more and more popular in recent years， and this puts the issue of platforms multimarket competition under the spotlight. Based on the Hotelling model， a multimarket competition system consisting of markets （a main market and a subsidiary market）， platforms， sellers， and consumers， is buit and the competitive strategy selection of platforms among three options is analyzed： no multimarket competition in both the main and the subsidiary market， multimarket competition without exclusive contract， and multimarket competition with exclusive contract. The following findings are derived by the analysis. （1） Departing from the traditional multimarket competition theory， platforms multimarket competition does not necessarily lead to mutual forbearance between platforms. Specifically， mutual forbearance depends on whether platforms choose multimarket competition with exclusive contract or not. （2） The optimal multimarket competition strategy of the platforms is contingent on the cross-network externalities and the intrinsic benefit that platforms provide to users in the main market. （3） When platforms choose multimarket competition without exclusive contract， the user surplus and total social welfare are the highest. The user surplus and total social welfare are the lowest when platforms choose no multimarket competition. Figures and Tables | References | Related Articles | Metrics

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High Dimensional Dynamic Higher-order Portfolio Selection Based on the Varying-coefficient Multi-factor Semi-nonparametric Distribution Model Guang-lin HUANG,Wan-bo LU 2023, 31 (12):  272-280.  doi: 10.16381/j.cnki.issn1003-207x.2022.2759 Abstract ( 57 )   HTML ( 1 )   PDF (638KB) ( 145 )   Save Markowitz's mean-variance portfolio model pioneered modern portfolio theory. However， due to the financial assets being non-normal and time-varying distributed， the efficiency of the mean-variance portfolios is difficult to achieve， which makes investors face serious welfare losses. High dimensional dynamic higher-order portfolio can effectively solve the existing drawbacks of the classical mean-variance portfolios； however， its application also meets several difficulties.A time-varying higher-order co-moment estimate， labeled as VC-MF-TVSNP， is proposed by combining a varying-coefficient multi-factor model and a time-varying semi-nonparametric （TVSNP） model. The model specification， estimation， and selection approaches are given in this paper. The multi-factor model can efficiently reduce the “curse of dimensionality” problem in the time-varying higher-order co-moments estimation， and the semi-parametric structure can efficiently solve the “model misspecification” problem. Then a high-dimensional dynamic high-order moment investment analysis is given based on the component stocks of the Chinese CSI 300 index.The empirical studies show that the VC-MF-TVSNP model can effectively capture the time-varying structure of higher-order co-moments of asset returns， and it is more suitable for the latent structure of asset returns. High-dimensional dynamic portfolio based on the VC-MF-TVSNP model can generate higher and more stable economic value， which is further confirmed by robust analysis.To a large extent， the VC-MF-TVSNP model solves the “curse of dimensionality” and the “model misspecification” problem efficiently， which can provide a more precise estimation of high dimensional time-varying higher-order co-moment estimation rather than the existing approaches， and give investors a better reference for asset allocation. Figures and Tables | References | Related Articles | Metrics

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Characteristics and Formation of Multi-Project Cooperation and Competition Networks in Complex Program Wen-xin SHEN,Yu-jia WENG,Xian ZHENG,Wen-zhe TANG 2023, 31 (12):  281-289.  doi: 10.16381/j.cnki.issn1003-207x.2022.2749 Abstract ( 89 )   HTML ( 0 )   PDF (444KB) ( 344 )   Save Exploring the formation mechanism of multi-project cooperation and competition networks in complex programs is critical to improving its performance. This study aims to understand the characteristics and formation of multi-project cooperation and competition networks in complex program from the network perspective. Based on social network theory and social exchange theory， this research identifies the effects of pure structural factors （i.e.， Reciprocity， Popularity， and Transitive triad）， attribute-based factors （i.e.， geographic proximity， project size， and project duration）， and covariate networks on forming cooperation and competition networks. The graphs of cooperation and competition networks are drawn and their network characteristics are analyzed and compared. Based on the data of 923 inter-project interface tasks collected from a large-scale construction program in China， the hypotheses are empirically tested by an exponential random graph model. The results are as follows： （1） Cooperative and competitive relationships coexist among multiple projects in complex programs. The density and connection number of the cooperation networks are about twice that of the competitive network； （2） There are similarities and differences in the factors influencing the formation of cooperative and competitive networks. Reciprocity has a positive effect on driving the formation of both kinds of networks， while cooperation networks also exhibit positive popularity； （3） Cooperation and competition networks can mutually contribute to the formation of each other. This research is not only helpful to deepen managers' understanding of the formation of the cooperation and competition network in multi-project settings， but also helps to formulate more comprehensive and effective resource allocation strategies from the network perspective， thereby promoting the collaboration between project teams. Figures and Tables | References | Related Articles | Metrics

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Price Resonance and the Security and Stability of Hog Industry Chain: A Prediction Based on Price Mode Dissipation Jian-fei LI,Kun TANG,Yang SHEN 2023, 31 (12):  290-300.  doi: 10.16381/j.cnki.issn1003-207x.2021.2707 Abstract ( 70 )   HTML ( 2 )   PDF (726KB) ( 194 )   Save The hog industry chain is a typical dissipative structure system. The security and stability of the chain is the internal entropy flow while the price resonance is external， which determines the dynamic evolution of the system. Based on dissipative structure theory and Hidden Markov model， combining neural network and forward algorithm， Baum-Welch algorithm and Viterbi algorithm in machine learning， a stable state prediction method of hog industry chain based on price modal dissipation of each node of the chain is proposed. The STL-NAR model is used to predict the prices of corn， piglet and hog. Then the price resonance of the chain is represented as different price modes to confirm the smoothness of price transmission through application of symbolic dynamics. The Hidden Markov Model is also applied to evaluate and predict the security and stability and abnormal risk of the chain. The empirical results show that， the STL-NAR model has good predictive performance for the smoothness of price transmission at each node of the industry chain， and it can provide a reference for the prediction and alertness of abnormal price fluctuations. There is a Markov property between the price resonance and the security and stability of the industry chain and the smoothness of price transmission can effectively predict the security and stability of the chain， which provides insights into future scientific research and judgment. Figures and Tables | References | Related Articles | Metrics

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An Event POI Recommendation System for Groups in EBSN Shi-feng LIU,Lai-song KANG,Da-qing GONG 2023, 31 (12):  301-310.  doi: 10.16381/j.cnki.issn1003-207x.2021.0383 Abstract ( 70 )   HTML ( 3 )   PDF (790KB) ( 223 )   Save With the rapid development of event-based social networks （EBSN）， online platforms， such as Meetup and Douban， attract more and more groups to create， discover and share offline social events， such as concerts， exhibitions， and parties. A suitable venue is essential for the groups to organize a successful event. Therefore， the point of interest （POI） recommendation has become an effective solution to alleviate the information overload that identifies attractive and interesting venues from multiple options. However， event POI recommendation for groups in EBSN is very challenging compared to the traditional recommendation tasks， e.g.， movie recommendation. One reason is the lack of history for a particular event which arises a serious cold-start problem， the other is it involves complex interactions between multiple entities （such as users， groups， events， POI， etc.）. In this paper， multiple entities and their interactions in EBSN are considered， and an event POI recommendation algorithm is proposed based on heterogeneous information network （HIN） and attention mechanism to recommend appropriate POI for groups to host events. First， a principled method is developed to obtain the latent representation of the Meetup entities （groups， events， and POIs） via embedding， which incorporates both qualitative and quantitative information. Then， to explicitly characterize meta-path based context for improving the modeling of the interaction， a priority based sampling technique is used to select high-quality path instances and effective representations of the groups， events， POIs， and meta-path based context is learned for implementing a powerful interaction function. In the original embedding method， each meta-path indeed receives equal attention， which lacks the ability to capture varying semantics from meta-paths in different interaction scenarios. Meanwhile， an effective embedding method for modeling meta-path based context should be interaction-specific， which is able to provide highly discriminative semantics in various complicated recommendation scenarios. Thus， by combining the two parts of attention components， the original representations for the groups， events， POIs， and meta-path based context is improved in a mutual enhancement way， which is called the Co-Attention mechanism. Finally， experiments are conducted on two real-world datasets， namely， Meetup-NYC and Meetup-CHI. Extensive experimental results based on the real-world dataset have demonstrated the superiority of our model in recommendation effectiveness. Our model works especially well for recommending new POIs， which contains little prior history of organizing events. It is believed that our proposed neural model provides a promising approach to utilize HIN information and attention mechanism for improving event POI recommender systems. Figures and Tables | References | Related Articles | Metrics

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Study on the Scale and Structural of Discipline Layout for Research Institution Yang MENG,Deng-sheng WU 2023, 31 (12):  311-316.  doi: 10.16381/j.cnki.issn1003-207x.2023.12.030 Abstract ( 67 )   HTML ( 3 )   PDF (517KB) ( 143 )   Save The measurement of the scale and structural characteristics of disciplinary layout is crucial for optimizing disciplinary arrangements and effective research management. Based on research project data， comprehensive evaluation indicators are established for disciplinary layout， assessing it from the dimensions of disciplinary variety， balance， and disparity. It focuses on various research institutions within the Chinese Academy of Sciences in this paper， utilizing National Natural Science Foundation （NSFC） data from 2013 to 2017 for empirical analysis. The research findings indicate that the proposed analytical framework effectively depicts the scale and structural features of disciplinary layout. Through the computation of research fund data， it is observed that the disciplinary layout of the Chinese Academy of Sciences does not necessarily pursue a “bigger is better” approach in terms of funding distribution； instead， certain disciplines hold advantageous positions， securing more funding opportunities. Furthermore， the degree of disparity between disciplines moderately influences the evaluation of disciplinary diversity， although the impact of different disparity settings on evaluation results is relatively small. Correlation analysis of the RS-M and RS-S indices of research institutions with the number and total amount of projects funded by NSFC reveals no significant correlation between disciplinary diversity and the number or total amount of NSFC-funded projects. Figures and Tables | References | Related Articles | Metrics

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Study on Interval Benchmarking Based on Efficiency Compensation Mechanism——Taking Forest Carbon Sink Efficiency as An Example Yan HUANG,Li-ye CHEN,Nan WU,Ying-ming WANG,Yong-wu DAI 2023, 31 (12):  317-328.  doi: 10.16381/j.cnki.issn1003-207x.2023.0311 Abstract ( 64 )   HTML ( 1 )   PDF (640KB) ( 214 )   Save Due to the input-output data are interval numbers in interval data envelopment analysis（DEA）， the production possibility set（PPS） used as the evaluation reference may not be consistent with the production point of the evaluated decision-making unit（DMU）， which leads to positive and negative spillovers in interval efficiency evaluation. Based on the existing interval efficiency DEA model considering the unity and comprehensiveness of the evaluation， an efficiency compensation mechanism is proposed， and an interactive efficiency evaluation model is constructed based on the best and worst PPS by setting compatible constraints， which reduces the positive and negative spillovers to a certain extent. Subsequently， the spillover of the evaluation results is expressed through the definition of the degree of likelihood between the general interval efficiency and the benchmarking interval， and the accessibility of the decision unit efficiency in conjunction with the spillover degree is defined. The benchmarking in terms of effectiveness and accessibility is defined， which makes the benchmarking construction adaptable to a variety of decision-making environments. Due to the fact that the input-output data of forest carbon sinks is not an accurate value， treating this input-output data as interval numbers is more in line with the actual situation. The method proposed in this article is very suitable forevaluating the efficiency of forest carbon sequestration in China. Choose the forest carbon sink data from remote sensing measurements in 2017 and forestry related data from the same year to evaluate the performance of forest carbon sinks in 30 provinces of China.Based on the efficiency evaluation results， 8 provinces were selected as benchmarking. The results show that these 8 provinces have economic， resource， or management advantages in the development of forest carbon sink， which provides guidance for the development path of forest performance management in China and has practical reference value. Figures and Tables | References | Related Articles | Metrics

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Research on the Impact of Loans Rollover Policy on Default Risk of Enterprises Based on Structural Model Xiang-zhong HUANG,Chang-wu ZOU,Yuan GAO 2023, 31 (12):  329-339.  doi: 10.16381/j.cnki.issn1003-207x.2023.0297 Abstract ( 58 )   HTML ( 0 )   PDF (530KB) ( 131 )   Save To examines the impact of loan rollover policies on the default risk of small and micro enterprises， a structural credit risk model containing elements of loan rollover policy has been established， where firm asset value follows a diffusion process with jumps. The numerical simulation results show that longer-term lending， lower interest rate， smaller lending halts loss and lower loan rollover cost can provide lower default threshold value and smaller default risk. The numerical simulation results are verified by empirical analysis using the data of listed enterprises in the National Equities Exchange and Quotations. Heterogeneity analysis shows that the factors of loan rollover policy have more obvious influence on non-state enterprises and the loan halts loss has a significant impact on the default risk of all types of enterprises. The analysis of the impact mechanism shows that the loan rollover policy affects the default risk of enterprises through fluidity channel and income channel. Loan rollover is literatured on in three aspects. First， different loan rollover policy elements are included into a unified structural credit risk model， which helps us to better understand how the loan rollover affecting corporate default risk. Secondly， our model treat bank’s lending halts as an external shock to change the value of corporate assets， which providing a new perspective for understanding the reasons for asset value jumps. Third， a theoretical explanation is provided for the policies of “further strengthening the development and promotion of loan rollover products” and “safely handling the lending rollover without repayment of principal” for small and micro enterprises in China， and certain policy inspiration is provided for smoothing the channel of transmission from loose currency to credit expansion. Figures and Tables | References | Related Articles | Metrics

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Can the Supply Chain Network Location Improve the Level of Innovation Diversity of Enterprises? Xiao-yang ZHAO,Chang-jun YI,Jia LIAO 2023, 31 (12):  340-349.  doi: 10.16381/j.cnki.issn1003-207x.2023.0302 Abstract ( 92 )   HTML ( 4 )   PDF (424KB) ( 192 )   Save Enterprises are an important part of the implementation of the innovation-driven development strategy. Encouraging enterprises to carry out diversified and disruptive innovation programs is not only an important way to build new advantages in international competition， but also a fundamental driving force for China’s high-quality economic development. Innovation diversity refers to the continuous accumulation of knowledge resources and the diversification of technological capabilities of firms. It represents the potential of firms to develop new technologies， which reflects the quality of innovation. With the increasing complexity of emerging technologies such as big data and artificial intelligence， it is difficult for a single firm’s closed innovation to break through containment technologies. Therefore， building and maintaining effective networks is gradually becoming a key factor in the success of corporate innovation. In the context of the new round of technological change， the production of high-quality products and breakthroughs in cutting-edge technology are increasingly inseparable from the cooperation of enterprises upstream and downstream of the supply chain. Individual competition among enterprises has gradually evolved into competition among supply chains. Based on the social network theory， the supply chain network is the result of the relationships that a firm establishes with its direct or indirect customers and suppliers. Therefore， the various strategic decision-making behaviors of an enterprise can be regarded as a function of its position in the supply chain network. A firm’s position in the supply chain network structure determines its ability to access knowledge and information. Core enterprises in the supply chain network can utilize their resource advantages to reduce the cost of knowledge acquisition and improve their innovation ability in the process of knowledge transfer. Then， the supply chain network location will inevitably affect the innovation diversity of the firms. The questions this paper focuses on are （1） Does supply chain network location affect the level of innovation diversity in a firm？ （2） If there is an effect， what is its mechanism？ （3） Under what circumstances will the effect be enhanced or weakened？ Answering the above questions is of great practical and theoretical significance for fully utilizing the innovation effect of supply chain networks.The social network analysis is adopted to construct a supply chain network with a sample of all A-share listed companies in China from 2008 to 2020. The relationship between supply chain network location and corporate innovation diversification is also discussed and tested. The results show that the closer to the center of the supply chain network， the higher the level of corporate innovation diversification. The mechanism test shows that supply chain network location can influence firms’ innovation diversification by broadening financing channels and enhancing absorptive capacity. Further analysis shows that the impact of supply chain network on firms’ innovation diversification is more significant in the sample of non-state-owned enterprises as well as in the manufacturing industry.The relationship between the location of supply chain network and the innovation diversity of enterprises is focused on by constructing the indicators of supply chain network and innovation diversity of enterprises， which expands the related literature on the innovation effect of supply chain network. The findings of the study not only provide policy references for enterprises to actively integrate supply chain network resources in order to achieve technological breakthroughs， but also provide a theoretical basis for the government to accelerate the digital transformation of supply chains. Figures and Tables | References | Related Articles | Metrics

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The Impact of Digital Development on Corporate Green Innovation Li-ting FANG,Guan-lan ZHANG,Kun-ming LI 2023, 31 (12):  350-360.  doi: 10.16381/j.cnki.issn1003-207x.2023.0308 Abstract ( 213 )   HTML ( 29 )   PDF (535KB) ( 292 )   Save As the world's largest carbon emitter， China is committed to building a sustainable environmental governance system， and optimizing the industrial structure and energy structure. Green innovation is an important support for transforming the mode of economic development and promoting the construction of ecological civilization. How to promote enterprises to carry out effective and high-quality green innovation is an important issue to be solved urgently in the new era. At present， the rapid development of the digital economy and the depth of its influence are unprecedented. It has become a new force in the global restructuring of factor resources and economic structure， and in the changing of the competitive landscape. Therefore， in the context of digital economy， enterprise digital transformation will soon become an important driving force for the upgrading of green innovation strategy. In particular， the impact of digital development on the upgrading of enterprises' green innovation strategy is worthy of in-depth discussion.All A-share listed companies are selected from 2011 to 2020 as research samples. Based on natural resource base view and transaction cost theory， panel quantile regression model and adjustment mechanism model are constructed. The impact of enterprise digital development on green innovation and the specific transmission path is discussed， and then the regulatory role of financing constraints and local intellectual property protection on the impact of digital economy is explored. The results show that there is a significant positive correlation between enterprise digital development and green innovation， that is， enterprise digital development has a lagging incentive effect on green innovation， and can promote the output of green invention patents and green utility patents. According to the panel quantile regression， the innovation-driving effect of digital development is different for enterprises with different levels of green innovation output. With the continuous improvement of enterprises' green innovation level， the incentive effect of digital development is more and more significant. In addition， the regulatory mechanism analysis results show that the promotion effect of enterprise digital development on green innovation is more significant in enterprises with low financing constraints and strong local intellectual property protection. This study has certain reference significance for the consequences of digital economy and the development of enterprise green innovation. Figures and Tables | References | Related Articles | Metrics