Table of Content

28 March 2022, Volume 31 Issue 2 Previous Issue    Next Issue

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Vehicle Routing Optimization of Reverse Logistics Based on Product Recovery Pricing WANG Yong, ZUO Jiaxin, JIANG Yiong, XU Maozeng 2022, 31 (2):  199-216.  doi: 10.3969/j.issn.1005-2542.2022.02.001 Abstract ( )   PDF (3081KB) ( )   In order to overcome the short comings of the study of reverse logistics vehicle routing optimization in a reasonable combination of product recovery price adjustment and vehicle routing optimization scheduling, taking the intelligent recycling bin as the research object, and considering the multi-frequency recovery and vehicle sharing scheduling strategy, this paper proposed a reverse logistics vehicle routing optimization scheme based on product recovery pricing. First, this paper established a linear function between the collection quantity and the recycling price. Next, it established a reverse logistics operating cost model including shared vehicle transportation cost, the vehicle maintenance cost, and the penalty cost of the time window violation and environmental externality benefit, and proposed the maximum product profit model of the recycling center. Then, it designed a K-means clustering algorithm according to the characteristics of the model, to consider the space location, recycling frequency, and time window constraints of the intelligent recycling bin, and therefore proposed an improved genetic algorithm-particle swarm optimization (GA-PSO) hybrid algorithm which combined the strong global search ability of GA and the fast conergence speed of PSO. After that, it adopted the elite retention strategy to enhance the efficiency of the hybrid algorithm. A compaison of the hybrid genetic algorithm (HGA), genetic algorithm-tabu search (GA-TS) and hybrid ant colony optimization (HACO) verified the validity of the proposed model and algorithm. Fnally, it studied the proposed method based on a real-world case study of the intelligent reverse logistics network in Chongqing, China, and analyzed and discussed the recycling frequency and vehicle sharing at different product recovery pricing. The results show that the model and algorithm proposed n this paper can be used for effetively selection of the optimal pricing strategy. resource sharing of recycling vehicles, and reasonable vehicle routing optimization scheduling, and can effectively reduce the transportation cost of reverse logistics while maximizing the revenue of the recovery center, which can provide decision reference and method support for reverse logistics enterprises in the product recovery pricing strategy and vehicle routing optimization scheduling. Related Articles

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A Dual-channel Supply Chain Inventory Decision Model Based on Joint Contract with A Risk-averse Retailer ZHU Baolin, XUE Lin, JI Shoufeng, QIU Ruozhen 2022, 31 (2):  217-229.  doi: 10.3969/j.issn.1005-2542.2022.02.002 Abstract ( )   PDF (6330KB) ( )   In this paper, the issue of inventory coordination concerning the dual-channel supply chain for a risk-averse retailer under uncertain conditions is studied The optimal inventory decision models under the centralized and decentralized conditions for dual-channel supply chain considering the risk-averse retailer are established and the joint contract including revenue sharing and buyback contract is proven to achieve an inventory coordination in the dual-channel supply chain. The influences of the uncertain factors of yield and demand, the risk aversion factor, and the market allocation ratio on the optimal decisions of manufacturers and retailers are analyzed. It is shown that the joint contract including revenue sharing and buyback contract can achieve Pareto improvement of the dual-channel supply chain. Finally, the feasible scope of Pareto improvement of the joint contract is discussed. Numerical examples verify the effectiveness of the model and method. Related Articles

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Optimal Financing Strategy and Quality Decision for a Capital-constrained Manufacturer CAI Min, LUO Jjianwen 2022, 31 (2):  230-240.  doi: 10.3969/j.issn.1005-2542.2022.02.003 Abstract ( )   PDF (2837KB) ( )   Considering the fact that market demand is sensitive both to retailing price and product quality, this paper examines the optimal financing and operational decisions in supply chain where a capital constrained manufacturer determines the product quality and sells goods to a capital sufficient retailer. The manufacturer's financial pressure can be alleviated via three financing schemes, i.e., advance payment, bank financing, and hybrid financing (a combination of equity financing and bank financing). In addition, it formulates the Stackelberg game models to derive the optimal decisions and compare the respective profit  for each party in three financing modes. Moreover, it analyzes the effects of various parameters on the optimal decisions, including quality investment cost efficient, unit production cost efficient, advance payment ratio, and equity financing ratio. The results show that the product quality will be higher under advance payment mode than that under bank financing mode when the manufacturer's initial capital is in certain range and the advance payment ratio is bellow certain threshold. Though the product quality and ordering quality in hybrid financing is higher than those in bank financing, the overall profit of the supply chain is lower than that in bank financing. Related Articles

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Evolution of Trading Policy Stock Index Futures and Stock Market Quality LIU Muhan, XIONG Xiong, ZHANG Yongjie 2022, 31 (2):  241-254.  doi: 10.3969/j.issn.1005-2542.2022.02.004 Abstract ( )   PDF (1040KB) ( )   Under the background of the gradual relaxation of trading policies in China's stock index futures market, this paper studies the changing characteristics of stock market quality, which provides empirical evidences for regulators to support and develop the financial derivatives. From a cross-sectional perspective of individual stocks, it matches index component stocks (sample group) and non-component stocks (control group). The descriptive statistics, difference test, and regression analysis indicate that with the release of trading policy, although the overall volatility of the market increases, the trading of stock index futures has an inhibitory effect on the volatility of component stocks. Stock index futures have a certain "transaction transfer effect" on the overall liquidity of the market, but the index component stocks are less affected. Based on the above results, it can be concluded that the more attractive stock index futures trading policy is to investors, the more conducive it is to improve the quality of the stock market and give full play to the role of stock index futures. Related Articles

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A Credit Risk Evaluation Model for Imbalanced Data Classification Based on Class Balanced Loss Modified Cross Entropy Function YANG Lia, SHI Baofeng, DONG Yizhe 2022, 31 (2):  255-269.  doi: 10.3969/j.issn.1005-2542.2022.02.005 Abstract ( )   PDF (1330KB) ( )   To address the problem that imbalanced credit scoring data sets lead to over-recognition for non-default samples and under-recognition for default samples, this paper creates a novel credit risk evaluation model by introducing the class balanced loss function. It compares the BPNN-CBCE (back propagation neural network-class balanced cross entropy) with the BPNN-CE (back propagation neural network-cross entropy), the SVM (support vector machines), the DT (decision tree), the RF (random forest), and the KNN (K-nearest neighbor) to verify the effectiveness of the BPNN-CBCE model in predicting the credit risk of 1 534 farmers, loan data of a financial institution in China. In addition, it tests the robustness of the BPNN-CBCE model by using the German credit data published by UCI (University of California). The results show that for farmers, loan data, the default recall of the BPNN-CBCE is 41. 3% higher than those of other models, and the AUC (area under curve) of the BPNN-CBCE is 15. 6% higher than those of other models. For German credit data, the BPNN-CBCE model is also better than the BPNN- CE, the SVM, the DT, the RF and the KNN models in AUC and default recall, Therefore, the BPNN- CBCE credit risk evaluation model has a good ability to identify the default samples in the imbalanced credit data of farmers, and can reduce the losses caused by misjudgment of default customers by financial institutions. This paper is contributive because the balance factor ω in class balanced loss is used to adj ust the weight of non-default and default samples loss in target loss, which compensates for the defect that the cross-entropy loss function cannot adjust the weight? and overcomes the excessive recognition of non-default samples and the insufficient recognition of default samples caused by the sample imbalance. In addition, the random covering method is used to sample non-default or default samples without putting them back until the whole sample space Xnon-defauit or Xdefault is fully covered, and the number of effective samples for non-default or default loan customers is calculated. Moreover, the use boundary of class balanced loss expanded, providing new ideas for solving the credit risk evaluation of imbalanced samples. This research method has a good robustness and can be directly applied to the credit risk assessment of financial institutions. Related Articles

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Impact Mechanism of Female Entrepreneurs, Social Cognitive Traits on New Venture Performance：from the Perspective of SCT XIE Xuemei, WU Yonghui, GAO Min 2022, 31 (2):  270-289.  doi: 10.3969/j.issn.1005-2542.2022.02.006 Abstract ( )   PDF (1451KB) ( )   In recent years, with the emergence of female entrepreneurship, the study of female entrepreneurs’social cognitive traits has gradually attracted attention. Based on the social cognitive theory (SCT) perspective, this study focuses on the female entrepreneurs as the research object, four cognitive traits (i.e., entrepreneurial self-efficacy, entrepreneurial passion, grit, and self-control) as cognitive factors. opportunity recognition as a behavioral factor, Guanxi network and gender discrimination as environmental factors, thus builds the ternary interaction model of “cognition-behavior-environment” This study explores the complex relationship between female entrepreneurs’ social cognitive traits and new ventures’ performance. The results show that female entrepreneurs’ social cognitive traits (entrepreneurial self-efficacy, entrepreneurial passion, grit and self-control) have positive impacts on the new ventures’ performance. Opportunity recognition plays a mediating role in this relationship. The environmental factors-Guanxi network and gender discrimination moderate the mediating role of opportunity recognition in the relationship between female entrepreneurs’social cognitive traits and new ventures’ performance. This study takes the research path of “female entrepreneurs’ social cognitive traits-opportunity recognition-new venturds, performance” to explore the internal mechanism of the transformation of female entrepreneurs, social cogniive traits into female entrepreneurs, ehavior, and further influence the new ventures, performance. And through he introduction of the Guanxi network and gender discrimination, this study helps to understand the role of environmental factors in the relationship between female entrepreneurs, social cogntion and action path. Related Articles

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Mechanism of Vision-for-Change-Communication on Employees, Commitment to Change from the Perspective of Sensemaking LI Fangyuan, ZHOU Xiaohu, ZANG Hui 2022, 31 (2):  290-301.  doi: 10.3969/j.issn.1005-2542.2022.02.007 Abstract ( )   PDF (1040KB) ( )   Based on the process of "enactment-selection-retention" of sensemaking, this paper demonstrates anc tests the influencing mechanism of vision-for-change-communication on employees’ commitment to change. Ar analysis of the threewave survey data from 235 employees indicates that cognitive crafting could mediate the relationships between the vision-for-change-communication and employees’commitment to change. Change of self efficacy not only moderates the relationship between vision-for-change-communication and cognitive crafting, but also moderates the mediating effect caused by cognitive crafting. The conclusions complement the previous researches on the content perspective and communication perspective of vision for change, enrich the literature on individual differences in sensemaking in the context of change. and provide some inspiration for the practice or organizational change management. Related Articles

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Entry，Competition，and Regulation of Platform Enterprises ZHANG Jianhu, LI Changying, XIE Shenxiang 2022, 31 (2):  302-316.  doi: 10.3969/j.issn.1005-2542.2022.02.008 Abstract ( )   PDF (1098KB) ( )   This paper studies the entry, competition, and regulation of platform enterprises in the case of targeted advertising by using the Salop (1979) model. It is found that when the advertising orientation accuracy is low (high), the equilibrium advertising volume is inversely (positively) proportional to the advertising orientation accuracy of the platform. Compared to the social optimum,  equilibrium advertising is excessive (inadequate) when the advertising orientation accuracy is low (high). Free entry may lead to too many or too few platforms, depending on the degree of product differentiation and the advertising orientation accuracy. When the government solely controls the entry of platforms, the number of platforms is socially excessive (deficient) when the advertising orientation accuracy is low (high) compared with the social optimization. When the government solely regulates the advertising volume, the advertising volume can be too high or too low, depending on the degree of product differentiation and the advertising orientation accuracy. Related Articles

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CFW-Boost Model for Cause-and -effect Analysis in Enterprise Financial Risk Warning ZAO Xuefeng, WU Weiwei, GUO Xu, SHI Huining 2022, 31 (2):  317-328.  doi: 10.3969/j.issn.1005-2542.2022.02.009 Abstract ( )   PDF (1393KB) ( )   At present? most models generally conduct early financial warning with low-dimensional features, which lacks early warning analysis with high dimensional features as the background, and the early warning accuracy and robustness of the model need to be further improved. On the premise of constructing multiple types of financial features with financial indicators and non-financial indicators, a CFW-Boost is obtained in combination with the causal relationship of features and integrating multiple, CART trees. The performance of CFW-Boost is empirically analyzed by using other early warning models to compare and train. The findings indicate that? compared with other models.CFW-Boost has a higher accuracy and a more stable warning performance. CFW-Boost reduces the feature dimension through feature causality analysis, which can well avoid the influence of feature redundancy on the robustness of the model. The value of the CFW-Boost optimal dimension is the largest, indicating that CFW-Boost has a stronger superiority in high-dimensional features than other models. The CFW-Boost proposed in this paper is empirically in line with the market law and can provide beneficial reference for enterprises and market supervision departments. Related Articles

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Analyst Performance and Star Analyst Selection：Evidence Based a Quasi-Experiment of 'New Fortune' LIU Xiaomeng, ZHOU Aimin 2022, 31 (2):  329-342.  doi: 10.3969/j.issn.1005-2542.2022.02.010 Abstract ( )   PDF (1248KB) ( )   Based on the suspension and restart of 'New Fortune Best Analysts', this paper studies the impact of star analyst appraisal on the financial analysis industry by using the difference-in-difference (DID) framework and other methods. It is found that rating becomes more effective after the suspension. while optimistic bias is larger, and the degree of diligence is lower among analysts. Due to the reform and restart of 'New Fortune', rating becomes even more effective after the restart, the optimistic bias of analysts decreases, but the degree of diligence increases. These results indicate that even though there are some drawbacks, the appraisal of star analyst generally improves the industry. The correct way to deal with the problems caused by analyst selection should be to improve the selection system and strengthen the self-discipline of the industry rather than suspend the selection mechanism. Related Articles

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Effect of Monetary Incentive on Physicians, Contribution Behavior in Online Healthcare Community WANG Panpan, WU Zhiyan, LUO Jifen 2022, 31 (2):  343-352.  doi: 10.3969/j.issn.1005-2542.2022.02.011 Abstract ( )   PDF (991KB) ( )   How to motivate voluntary contribution is vital for keeping online community (OC) vibrant Recently, scholars start to identify the impacts of monetary incentives on voluntary contribution in OC. but few researches have been conducted on multi-sided platforms. Leveraging a natural experimental design, this paper investigates the impact of paid service channel (telephone consultation service) on voluntary contribution of physicians in a service dominant online community-online healthcare community (OHC).The results indicate that after receiving telephone consultations, physicians exert more efforts on free text consultation services to provide more timely and detailed medical advices. Meanwhile, the motivating effect of telephone consultation varies across physicians with different levels of social interactions. Compared to physicians with a high level of social interaction, physicians with a low level of social interaction exert more efforts on free text consultation service after receiving telephone consultations. The previous research on the impacts of monetary incentives on voluntary contribution in OC are mainly based on product dominant communities, this paper extends monetary incentives to service dominant two-sided online platforms. Using a natural experimental design, it identifies causal impact of monetay incentive and heterogeneity across physicians which could help policy making on platform design and governance. Related Articles

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Privacy Exchange Behavior of APP Users, Considering Different Usage Scenarios HAN Zhen, SHI Lei, ZHAO Yanlin 2022, 31 (2):  353-361.  doi: 10.3969/j.issn.1005-2542.2022.02.012 Abstract ( )   PDF (1558KB) ( )   The rich functions of APP not only bring convenience to users’ lives, but also make many users face the risk of privacy leakage. The trade-off between functions and privacy is one of the most important and active issues in the field of user privacy behavior research. The introduction of psychological latent variables and usage scenario variables can take into account the influence of subjective and objective factors and improve the ability to explain and predict users’privacy exchange behavior. First, based on the CPM theory, psychological latent variables are proposed, and a MIMIC model is constructed. Next, the usage scenario variable of privacy exchange behavior is proposed based on TAM, and four usage scenarios are set. Finally, an integrated choice and latent variable (ICLV) model is established. The results show that usage scenarios have a significant impact on users’ privacy exchange behavior, and the influencing factors of users’privacy exchange behavior are different in different scenarios. Privacy-oriented users are less affected by scenario factors, and the probability of privacy exchange behavior in each scenario is low, while function-oriented users have a higher probability to exchange except the "free registration” scenario. Related Articles

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Impact of Service Robots on Conspicuous Consumption Decision LI Jiaxin, TANG Yanfei, WANG Liangyan 2022, 31 (2):  362-373.  doi: 10.3969/j.issn.1005-2542.2022.02.013 Abstract ( )   PDF (8960KB) ( )   In recent years, service robots have become one of the important means for more and more businesses to improve quality and efficiency, which has attracted widespread attention in academia. In the conspicuous consumption scenario, this paper reveals that compared with human servers, consumers are less likely to make conspicuous consumption when facing service robots. This happens because consumers pay more attention to their inner-self in face of robots, rather than to their social image in public. The degree of robot artificial intelligence (AI) personalization will moderate this effect. When robots are intelligent enough to provide personalized recommendation, consumers pay more attention to themselves and make less conspicuous consumption. This paper provides a theoretical guidance for whether and how to adopt service robots in business practice, and also enriches the research results in the field of AI service. Related Articles

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Intellectual Property Protection，Research and Development Investment，and Regional Green Innovation Performance XIAO Zhenhong, LI Yan 2022, 31 (2):  374-383.  doi: 10.3969/j.issn.1005-2542.2022.02.014 Abstract ( )   PDF (1035KB) ( )   A two-dimensional evaluation system is constructed based on the connotation of regional greoi innovation performance. Based on the Chinese provincial panel data from 2009 to 2017, the Super-SBM model is used to measure the green innovation performance of each region. The protection of intellectual property rights on regional green through the intermediary model and the impact of innovation performance and its action path are explored. The results show that the increase in the intensity of intellectual property protection will positively affect the efficiency and effectivoiess of regional green innovation through research and development investment. In addition, the effect of human resources investment in research and development investment is stronger than the effect of research and development investment. Moreover, the intensity of intellectual property protection has a more significant impact on the efficiency of regional green innovation than the efficiency of regional greoi innovation. Intellectual property protection has a non-linear impact on the efficiency of regional green innovation? and there is an "optimal protection interval". Furthermore, there is an obvious heterogeneity in the regional greoi innovation performance in China, and most regions are in the range of low green innovation efficiency and low green innovation benefit. Related Articles

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Product Configuration Optimization Problems in Cloud Manufacturing with Uncertainity LI Jia, YANG Dong 2022, 31 (2):  384-395.  doi: 10.3969/j.issn.1005-2542.2022.02.015 Abstract ( )   PDF (5941KB) ( )   An increasing number of enterprises realize their personalized production by means of cloud manufacturing technology. To deal with the uncertainties in cloud manufacturing, a robust optimization approach to product configuration is proposed with the objective of minimizing the total configuration cost. The uncertainties in cloud manufacturing cost and time are characterized by using budget-based robust representation. The robust model is transformed into a robust counterpart model using the duality theory. As a result, commercial solvers such as CPLEX can be employed to solve the model to optimality. A configuration case is designed to illustrate the effectiveness of the robust model. Numerical experiments are conducted to demonstrate that the proposed model is more robust and can substantially improve the delivery date of products. Related Articles

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A Method for Determination of Emergency Levels Considering the Risk Attitude of Experts in Double Reliability YE Xin, BAI Yuxuan, ZHANG Lei 2022, 31 (2):  396-405.  doi: 10.3969/j.issn.1005-2542.2022.02.016 Abstract ( )   PDF (2474KB) ( )   The determination of mass emergency levels is the decision-making basis for starting scientific hierarchical responses, which needs to integrate the judgment of different experts in many fields for a comprehensive judgment. Considering the risk attitude of experts facing uncertain decision-making? a method is proposed to determine the emergency level based on the double reliability of "expert weight and self-reliability". First, based on the double reliability, a complete evidence generation method considering expert risk attitude and the semantic relevance of emergency level is constructed. In addition, an improved evidence fusion method is proposed by comprehensively considering the subjective and objective information of evidence, so that the original tendency information of experts can be fully and effectively retained in the fusion results. Moreover, a discrimination test method of fusion results is given to avoid the situation of low differentiation between levels. Furthermore? the feasibility and scientificity of the method are verified by an example. The experimental results show that the self-reliability and risk attitude of experts will affect the results of emergency level judgment. The method of determination of the emergency level considering these two factors can improve the reliability and credibility of decision-making. Related Articles

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Distributed Dispatching Strategy of Virtual Power Plant Based on Energy Blockchain WANG Haiqun, FEI Fei, CHEN Kailing 2022, 31 (2):  406-413.  doi: 10.3969/j.issn.1005-2542.2022.02.017 Abstract ( )   PDF (2908KB) ( )   In order to improve the safety and economy of distributed energy dispatching in virtual power plants, and in view of the high risk, high cost and low efficiency of traditional centralized dispatching schemes, a distributed dispatching strategy for virtual power plants based on energy blockchain is proposed. The blockchain technology is introduced into the energy Internet system to form an energy blockchain network to realize distributed dispatching of virtual power plants. By using the criterion of equa consumption micro-increasing rate, the goal of virtual power plant power dispatch optimization is achieved. Using the PBFT (practical Byzantine fault tolerance) consensus algorithm in the blockchain, each distributed energy node has the complete key data of the entire network. When the load fluctuates, each node calculates the new power of its own unit and uploads the updated value to the chain for consensus. Realizing the reasonable distribution of new loads among units. The analysis of calculation examples shows that the algorithm proposed in this paper is credible and effective. The use of the blockchain technology to realize the economically optimized dispatching of DERs (distributed energy resources) in virtual power plants provides a credible reference scheme for the future operation mode of virtual power plants. Related Articles