Table of Content

    25 January 2024, Volume 32 Issue 1 Previous Issue   
    Dynamic Financial Distress Prediction for Chinese Listed Companies Based on the Mixed Frequency Data
    Dawen Yan,Cun Li,Guotai Chi
    2024, 32 (1):  1-12.  doi: 10.16381/j.cnki.issn1003-207x.2021.1570
    Abstract ( 214 )   HTML ( 16 )   PDF (639KB) ( 342 )   Save

    In this paper, a mixed-frequency data driven financial distress prediction problem is considered. The exponential Almon weighting scheme of mixed-data sampling is introduced in the context of a Logistic regression, which allows for an individual weighting of high-frequent increments, hence distinguishing the importance of different macroeconomic period to explain the change of a listed companies’ financial status. In applying the suggested model to the period from 2007 to 2017, a total data set is used that includes 4 macroeconomic indicators of mixed annual, quarterly and monthly frequency and 15 potentially significant financial indicators of annual frequency for 350 Chinese listed manufacturing companies. The results show that (1) the model correctly classifies more financially distressed companies than classic Logistic model, in particular for forecasting horizons of 2-3 years. (2) The macroeconomic indicators observed at different frequency show their importance for both low frequency (annually) and high frequency (quarterly) financial distress prediction, while quarterly GDP growth rate and monthly inflation rate have more significant influence, both statistically and economically, on quarterly financial distress risk. All findings indicate that this paper provides a suitable approach incorporating mixed-frequency data for prediction of financial distress for listed companies in China.

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    Forecasting the Chinese Gold Futures Market Volatility Using Markov-Switching Regime and Mixed Data Sampling Model
    Yangli Guo,Feng MA
    2024, 32 (1):  13-22.  doi: 10.16381/j.cnki.issn1003-207x.2021.0213
    Abstract ( 166 )   HTML ( 17 )   PDF (707KB) ( 307 )   Save

    In this study, a new Markov-switching regime (MS-MIDAS) is constructed using Markov-switching regime (MS) and mixed data sampling (MIDAS) models, and the volatility of the Chinese gold futures market is modeled and predicted. Using the out-of-sample rolling window prediction method and the Model Confidence Set (MCS) test, it is found that: (1) In general, higher prediction accuracy is demonstrated by the mixed data sampling models with Markov-switching regime (MS-MIDAS) compared to the MIDAS model; (2) The mixed data sampling model of Markov-switching regime with jumps (MS-MIDAS-CJ) exhibits the highest prediction accuracy; (3) The empirical results remain robust for different prediction windows and different lag orders (kmax).

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    Mixed Portfolio Optimization Model Within Flexible Time Horizon
    Yongjun Liu,Jiandong Wu,Weiguo Zhang
    2024, 32 (1):  23-30.  doi: 10.16381/j.cnki.issn1003-207x.2021.0160
    Abstract ( 90 )   HTML ( 5 )   PDF (569KB) ( 202 )   Save

    Under the background of economic globalization and financial integration, investors' asset allocation needs become more and more diversified. How to construct reasonable diversified portfolio strategy has become one of the hot issues in financial theory research. To this end, a mixed portfolio selection problem composed of project, stock and risk-free assets is considered. Assuming that the investment period of the portfolio is determined flexibly by the execution period of the selected project, the investors consider the real factors such as the dependence and exclusion relationship between the projects, the transaction cost and the bankruptcy risk control. A mixed portfolio optimization model with the objective of maximizing the net present value of terminal wealth is proposed. Then, an improved multi-strategy fusion artificial bee colony algorithm is designed to solve the proposed model. Finally, a numerical example is provided to illustrate the application of our model and demonstrate the effectiveness of the solution algorithm. The computational results show that the mixed portfolio investment strategy with flexible time horizon is more effective than the existing project portfolio investment strategy with flexible time horizon.

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    Textual Analysis-based Measurement of Fintech and tests of Enabling Effect for Commercial Banks
    Jun Hu,Qiang Li,Jiacheng Dai,Yong Zeng
    2024, 32 (1):  31-41.  doi: 10.16381/j.cnki.issn1003-207x.2021.1714
    Abstract ( 196 )   HTML ( 21 )   PDF (669KB) ( 241 )   Save

    With the deep integration of digital technologies, such as big data and artificial intelligence, with financial business, the rapid development of financial technology (Fintech) is profoundly changing and reshaping the financial industry all over the world. In China, there are over 4600 licensed institutions in the banking industry and their total assets have accounted for more than 90% of that of all financial institutions as of 2019, and hence commercial banks are seen as the most important force for serving the real economy and driving the development of technology-enabled finance. In practice, most commercial banks have treated developing Fintech as an important strategy for realizing digital transformation and promoting financial inclusion. However, existing research pays little attention to the measuring of Fintech for each bank at the individual level, and thus there is a lack of the corresponding quantitative investigation on the enabling effect of Fintech for banks.It aims to measure the level of Fintech for commercial banks at the individual level and then investigate the enabling effects of Fintech on banks’ operating performance as well as inclusive finance. Specifically, based on more than 170000 textual news publicly reported by an authoritative financial website, multiple natural language processing technologies including named entity recognition, pre-training word embedding model, and LDA topic model are used to construct two basic thesauruses about commercial bank names and banking Fintech, and then Fintech Development Index for 1566 banks from 2011 to 2019 is constructed. Using a panel data from 472 banks with complete financial data, the findings of the investigation about the enabling effects of Fintech show that Fintech can not only improve the banks’ operating performance by significantly enhancing their operation ability, service ability, and risk control ability, but also is beneficial for expanding access to credit by stimulating banks to increase loan supply. However, it is found that banks’ Fintech fails to decrease loan rates, which indicates a “universal but not inclusive” problem in Fintech lending due to convenience premium or pricing discrimination.The contributions of the paper are threefold. Firstly, compared with the existing literature on measuring the development of Internet finance or digital finance at the national or regional level, the development of Fintech at the individual bank level is measured using publicly reported textual news and a variety of natural language processing techniques. The methodologies associated with automatedly constructing thesaurus and separation of compound Chinese words also provide an important reference for textual analysis-based research. Secondly, the mechanism of how Fintech can enable the banking industry is uncovered by a large-sample investigation on the effects of Fintech on banks’ operation as well as financial inclusion. Thirdly, as researchers are beginning to discuss the negative consequences of Fintech development, supplementary evidence at the cross-bank level on the “universal but not inclusive” problem in Fintech lending is provided.

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    Research on Optimal Capital Structure and Default Risk of Banks under Rigid Payment
    Lu Wen,Ling Feng
    2024, 32 (1):  42-53.  doi: 10.16381/j.cnki.issn1003-207x.2021.2487
    Abstract ( 72 )   HTML ( 6 )   PDF (1097KB) ( 167 )   Save

    In order to stabilize employment, Chinese governments usually provide the guaranteed bailout (i.e., rigid redemption) when state-owned enterprises encounter financial difficulties. The consensus is that, the rigid payment leads to the expansion of implicit debt of local governments. Therefore, its termination would restrain the debt risk. However, since state-owned enterprises are the main demanders of bank credit resources, terminating rigid payment could destabilase the banking system. Thus, how to prevent bank risks in the process of breaking rigid payment is an important question, but academia has not fully explored this problem.The rigid redemption is introduced into the model of bank capital structure and default risk and attempts to answer above question.And the relationship between the rigid payment and the bank default risk is studied in two cases where the banks’ capital structure is unadjustable and adjustable, respectively. Furthermore, standardized and internal ratings-bases regulator approaches are applied to our model and how effectively these regulations combat the incentive problems introduced by rigid payment is examined.The results show that (1) The bank default risk will increase with the weakening of rigid payment when the capital structure is fixed. (2) When the capital structure is adjustable, there is a reverse U-shaped relationship between the bank default risk and the rigid payment. (3) The capital regulation based on the standardized approach can effectively restrain the moral hazard for the bank at the time of a capital structure decision and reduce the default risk of banks in the process of breaking the rigid payment. However, the capital regulation requirements based on the internal rating approach will be weakened due to the reduction of the default probability of corporate debt under the rigid payment.

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    Information Spillovers between Investor's Public Health Emergency Attention and Industrial Stocks: Empirical Evidence from TVP-VAR Model
    Lan Bai,Yu Wei
    2024, 32 (1):  54-64.  doi: 10.16381/j.cnki.issn1003-207x.2021.1041
    Abstract ( 98 )   HTML ( 4 )   PDF (899KB) ( 82 )   Save

    The public health emergency that began in late 2019 had an unprecedentedly large impact on China's financial markets, and the role of investor attention (sentiment) on the pandemic in influencing China's stock market during this period should not be underestimated. Therefore, it is of great theoretical and practical importance for policy makers and market participants to explore the interaction between investors' attention and China's industrial stock markets during the different phases of the pandemic. Based on the traditional static spillover index, the dynamic spillover index method based on the time-varying parameter-vector autoregressive model (TVP-VAR) is used to explore the dynamic information spillovers between investors' attention and China's stock markets from before the epidemic to the outbreak and rapid spread of the epidemic, and then to the normalization of the epidemic prevention. The empirical results show that, on the one hand, there is a significant difference in the information spillover between investor attention based on Baidu index and industrial stock markets at different stages of the pandemic; on the other hand, industrial and optional consumption stocks are always spillover transmitters at different stages of the pandemic. While pharmaceutical and public sector stocks basically remain spillover receivers. The above findings can provide useful supports for regulators, listed companies and investors in making regulatory, risk management and portfolio allocation decisions.

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    Nonfinancial Corporate Debt and Resource Allocation Optimization——A Quantitative Analysis Based on the Dynamic General Equilibrium Model
    Yikang Qi
    2024, 32 (1):  65-74.  doi: 10.16381/j.cnki.issn1003-207x.2021.0957
    Abstract ( 62 )   HTML ( 3 )   PDF (776KB) ( 152 )   Save

    While the debt problem has not been completely resolved, China’s economy is still facing structural imbalance and slowing growth. The pressure from high debt and low growth rate forces the need for further in-depth research on the intrinsic relationship between these two matters. The analysis of the dynamic general equilibrium model shows that debt optimizes the allocation of financial resources among participants with different production efficiencies and promotes capital accumulation/output. Social welfare is thus improved. Under the condition of compulsory repayment, the production equilibrium condition determines the upper limit of debt, while non-mandatory repayment, the not-too-tight debt ceiling and the production equilibrium condition jointly do. Numerical simulation shows that there is a robust positive U-shaped relationship between debt-to-capital ratio and capital stock. At present, China's nonfinancial corporate debt-to-capital ratio is 33.9%, which is higher than the optimal level in history, so policymakers should adhere to deleveraging. But the problem of resource misallocation needs more attention.

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    Optimal Strategy and Welfare Effect of Urban Construction Land Quota Transition—— Based on Quantitative Spatial Model
    Xingmin Yin,Haojie Zang,Jianyue Ji,Luyao Qi
    2024, 32 (1):  75-85.  doi: 10.16381/j.cnki.issn1003-207x.2021.2292
    Abstract ( 73 )   HTML ( 3 )   PDF (768KB) ( 155 )   Save

    In recent years, the urban construction land quota transition policy has been used to solve the crowding effect and provide funds for Rural Revitalization. The main content of this policy is to allow the regions that lack the construction land quota to purchase the construction land quota from the backward regions with the surplus. However, this policy has produced certain negative effects while providing land for construction in developed cities and financial support for backward areas. How to promote regional development and improve residents' welfare at the same time requires a scientific evaluation of the transfer strategy of urban construction land quota. A quantitative spatial general equilibrium model of urban system is constructed, including production, consumption and government departments, urban construction land is internalized, by considering the local governments to maximize the objective function of the problem, the optimal transfer strategy of urban construction land quota for local government is solved, the relevant parameters are calibrated and estimated based on the existing research and Chinese data, and the transfer strategy of urban construction land quota and its welfare effect is simulated and analyzed. The relevant data of construction land index transfer came from the information platform of savings index transfer linking the increase and decrease of urban and rural construction land in Sichuan Province. It is found that allowing the transfer of urban construction land quota can improve the value of the government objective function, but only when the government takes the residents' welfare as the objective function can the residents' welfare be maximized at the same time; the transfer of urban construction land quota will not only alleviate the shortage of urban land and provide poverty alleviation funds, but also squeeze out government public service expenditure and reduce the construction land in the transferred out areas. The research of this paper provides a basis for the local government to formulate a reasonable transfer strategy of urban construction land quota, coordinate the relationship between regional production and residents' welfare, optimize the spatial layout of China's land, reasonably allocate regional urban and rural land resources, promote regional coordinated development, and realize the high-quality development of new urbanization and the rural revitalization strategy.

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    Research on Teleconsultation Appointment Scheduling Problem Based on Two-stage Stochastic Programming
    Yan Qiao,Lun Ran,Jinlin Li,Zhiyuan Wang
    2024, 32 (1):  86-93.  doi: 10.16381/j.cnki.issn1003-207x.2020.1989
    Abstract ( 116 )   HTML ( 10 )   PDF (710KB) ( 191 )   Save

    The teleconsultation service is taken as the research background and two teleconsultation appointment scheduling models separately are proposed considering sequence and without considering sequence based on two-stage stochastic programming. In this paper, the objectives of the models are to minimize the unallocated penalty cost, the waiting cost of primary hospitals’ application, the idle cost of teleconsultation room and the overtime cost. In the meanwhile, both the models consider the uncertainty of no-show and service time. Numerical experiments show that the total cost can be effectively reduced by adjusting the teleconsultation order, but the solution time of the model considering sequence is much longer than that without considering sequence. In addition, the number of teleconsultation applications and the number of scenarios in the scheduling period also have an impact on the total cost and solution time. The staff of telemedicine center can choose reasonable scheduling scheme according to the time limit of scheduling task, the number of application cases and other external factors.

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    Research on Distributed Emergency Operation Scheduling under Emergencies from the Perspective of Resilient City
    Li Huang,Chunming Ye,Peng Guo
    2024, 32 (1):  94-105.  doi: 10.16381/j.cnki.issn1003-207x.2022.0601
    Abstract ( 85 )   HTML ( 5 )   PDF (968KB) ( 134 )   Save

    In recent years, frequent natural disasters, safety accidents, public health and other emergencies often lead to a large number of sudden serious injuries or infections, which are in urgent need of surgical treatment, causing sudden and serious damage to urban resilience. However, the emergence of collaborative medical network provides the basis for the joint rescue of several hospitals. In order to solve the problem of emergency surgery under urban emergencies, a distributed emergency surgery scheduling research based on the perspective of resilient city is proposed. Firstly, a scheduling objective considering both rescue time and patient deterioration cost from the perspective of resilient city is proposed. Secondly, combined with the typical characteristics of fatigue threshold effect, truncation learning effect and patient deterioration cost in emergency surgery,as well as the characteristics of reentrant laminar flow surgery in rescue hospitals, a distributed emergency surgery scheduling model is constructed. Thirdly, a two-stage algorithm is designed to solve the allocation of patients among hospitals, surgical sequencing and surgical resource allocation in hospitals. Finally, numerical experiments are carried out to test the optimization performance of Hybrid Teaching Learning Based Optimization with Local Search (HTLBO-LS) under four heuristic algorithms, and simulation cases are proposed to further discuss the application effects of different algorithms and the medical resource allocation scheme from the perspective of urban resilience. The research results provide method and decision-making reference for distributed emergency operation scheduling under urban emergencies. For the first time, the characteristics of “distributed”, “reentrant” and “laminar flow” are considered simultaneously in this paper, which enriches the joint scheduling optimization model and algorithm of reentrant laminar flow surgery. From the perspective of urban resilience, it provides simulation design and decision support for the selection of medical resource allocation mode.

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    New Energy Vehicle Sales Forecast Based on Siscrete Time Grey Power Model
    Lianyi Liu,Sifeng Liu,Lifeng Wu
    2024, 32 (1):  106-114.  doi: 10.16381/j.cnki.issn1003-207x.2021.2567
    Abstract ( 218 )   HTML ( 17 )   PDF (701KB) ( 488 )   Save

    Accurate prediction of the new energy vehicle market’s development trend is of great practical significance for the realization of the development planning of the industry and China's energy strategic goals. Therefore, based on the existing two types of grey power models, an improved grey power model with multiple parameters is proposed, which can reflect the nonlinear effect of historical value and time sequence factors on the current value of the system. In addition, according to the information coverage principle of grey derivative, the differential form and derived discrete form of the model are given, denoted as DTGPM, and the time response function of the model is given, which avoids the complex integral solution process of the traditional grey power model. Furthermore, the heuristic algorithm is used to optimize the power parameters of the DTGPM model, and the prediction effectiveness of the model is verified by simulation experiments and practical example. Finally, the market sales volume of new energy vehicles is forecast. The forecast results show that the sales volume of new energy vehicles in China will reach 4.73 million in 2022, and is expected to reach nearly 10 million in 2025, accounting for 23.5% of the total sales volume of new vehicles.

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    Differential Game Model of Multi-party Cooperative Rescue after Earthquake in Physical-social Coupling System
    Man Yang,Dehai Liu
    2024, 32 (1):  115-124.  doi: 10.16381/j.cnki.issn1003-207x.2021.2073
    Abstract ( 59 )   HTML ( 4 )   PDF (689KB) ( 146 )   Save

    Under the dynamic change of road conditions and multi-party disaster coupling system, how to choose the disaster relief path according to the specific situation of road damage has become an urgent problem to be solved at present. Earthquake disasters and other emergencies show the characteristics of a complex physical-social coupling system. In addition, some sections of the road system appear functional failure under the action of strong earthquakes, which hinders the transport of relief supplies and evacuation of casualties. In the disaster coupling system, the government and social organizations need to participate in the rescue. First of all, in the early stage after the earthquake, it was difficult for the external rescue forces of the government to quickly enter the scene because of traffic interruption and poor information, while social forces could guide the people to carry out self-rescue and mutual rescue, but the continuous social forces occupied the rescue road, resulting in traffic congestion, “saving people will be saved by others” and other secondary disasters. Secondly, socialized disaster prevention and mitigation is an important direction of current and future disaster prevention and mitigation mechanism reform, the government and social organizations cooperate, not only effectively make up for the “government failure” defect, but also promote the stable development of society; Finally, to guarantee the amount of disaster relief required by the disaster area, the government has increased financial support for social organizations to relieve the pressure of disaster relief.According to the different input strategies of government and social organizations in disaster relief, three cooperation modes are summarized, namely non-cooperative rescue mode, cooperative rescue mode, and government subsidy mode. Then the differential game model of cooperative transportation between government and social organization is constructed. First, three differential game models of cooperative transportation between government and social organization are described. Secondly, the optimal level of the relief effort, subsidy ratio, amount of relief, and system equilibrium income of both sides of the game are obtained and analyzed. Thirdly, the balance strategies of the three modes are compared and analyzed. Finally, the sensitivity of key parameters to the equilibrium results is analyzed. It is found that three disaster relief modes have different coupling effects in the social system. Among them, the non-cooperative rescue mode is prone to fall into the “prisoner's dilemma” of not subsidizing weak participation. When the government and social organizations transition from non-cooperative relief mode to government subsidy mode, the Pareto improvement of relief efficiency can be realized. When the two parties choose to cooperate, the amount of disaster relief and the system equilibrium benefit is strictly superior to the non-cooperation and government subsidy modes. Three traffic situations in the physical system have the same coupling effect. Both the quantity and benefit of disaster relief under unblocked conditions are better than those under congestion and congestion conditions. In addition, the amount of disaster relief is affected by the joint efforts of the government and social organizations, and the amount of disaster relief increases with the increase of the input of one party. If social organizations predict that the government will increase relief spending, they will choose to maintain the original level of relief efforts to avoid unnecessary costs. In terms of case selection, the Lushan Earthquake in Sichuan Province in 2013 is selected as the case analysis object. Key parameter values are obtained from relevant authoritative organizations, such as Xinhua News Agency, China Youth Daily, and the website of the Ministry of Finance.Three modes of cooperative transportation between government and social organizations are summarized and the coupling results of physical and social systems after the earthquake are analyzed. Relevant research has certain theoretical reference significance for further improving the cooperative transportation of disaster relief materials after the earthquake.

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    Optimal Logistics Service Mode for E-commerce Supply Chain Considering Suppliers' Competition
    Xuelian Qin,Zhixue Liu
    2024, 32 (1):  125-136.  doi: 10.16381/j.cnki.issn1003-207x.2021.0425
    Abstract ( 207 )   HTML ( 18 )   PDF (891KB) ( 326 )   Save

    In the e-commerce market, many product suppliers and e-commerce platforms can provide the logistics service to consumers. It is commonly known that different logistics service modes have their pros and cons, which meets the diversified development needs of e-commerce enterprises but meanwhile leads to some problems, including the low efficiency and poor quality of e-commerce logistics service. To improve the quality of e-commerce logistics service and enhance the efficiency of e-commerce supply chain, it is of great importance to select the proper logistics service mode. Meanwhile, the rapid development of e-commerce also attracts more and more suppliers to sell their products through different types of e-commerce platforms. Many suppliers even sell products with same or similar functions on the same platform. The fierce competition among suppliers will undoubtedly influence the efficiency of different logistics service modes, and further change the firms’ logistics service mode choices. Therefore, it is necessary to explore the optimal logistics service mode for e-commerce supply chain under the scenario with suppliers’ competition.By constructing a supply chain consisting of two competing suppliers, one e-commerce platform and a continuum of heterogeneous consumers, a game-theoretical model is developed to explore the optimal logistics service mode for e-commerce supply chain considering suppliers’ competition and further examine the impact of the platform’s selling mode choice on the optimal logistics service strategy. The results show that if the e-commerce platform adopts the reselling mode or marketplace mode, the two suppliers and the platform all prefer the strategy that the platform only provides the logistics service for one product and the corresponding supplier offers the logistics service to another product when the competition is intense and the logistics service’s cost performance is high. By contrast, if the e-commerce platform adopts the hybrid mode, the two suppliers’ logistics service mode preferences are highly differentiated but the e-commerce platform always prefers to provide the logistics service for both suppliers’ products.

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    The Allocation Rule for TU-games with Coalition and Probabilistic Graph Structures and Its Applications
    Erfang Shan,Jilei Shi,Lei Cai
    2024, 32 (1):  137-145.  doi: 10.16381/j.cnki.issn1003-207x.2020.1348
    Abstract ( 42 )   HTML ( 2 )   PDF (561KB) ( 24 )   Save

    A cooperative game with transferable utility, shortly TU-game, is a pair consisting of a finite set of players and a characteristic function assigning a worth to each coalition of players. However, in many situations cooperation is restricted by cooperation structures such as hierarchical, technical or communicational structure. Aumann and Drèze (1974) first considered the situation in which there exists an exogenous coalition structure. Later, Myerson (1977) introduced TU-games with restricted cooperation possibilities represented by an undirected graph.In practice, there are some situations of cooperative decision making in which the cooperation between agents is restricted by both a communication structure and an organizational structure. van den Brink et al. (2015) considered the partition-graph value for TU-games with coalition and graph structures. The partition-graph value reflects not only the coalition structure but also the graph structure of the game will influence the allocation process, but disregards the uncertainty of cooperation structure.In this paper the TU-games with coalition and probabilistic graph structure are proposed and the partition-probabilistic graph value for the game model in introduced by considering the uncertainty of graph structure. It is shown that the partition-probabilistic graph value is uniquely determined by probabilistic partition component efficiency and probabilistic fairness. Finally, the partition-probabilistic graph value is illustrated by an example of transnational material transportation and compare it with other values.

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    Research on the Time-dependent Multi-depot Open Vehicle Routing Problem with Time Windows
    Xinyue Zhang,Peng Jin,Xiaoxuan Hu,Moning Zhu
    2024, 32 (1):  146-157.  doi: 10.16381/j.cnki.issn1003-207x.2021.0203
    Abstract ( 99 )   HTML ( 4 )   PDF (918KB) ( 173 )   Save

    A time-dependent multi-depot open vehicle routing problem with time windows is studied. Based on the traffic conditions, the travel speed function is established. Considering the constraints of vehicle capacity, the distance of vehicles and customer time windows, a mixed integer programming model is established. The objective function is to minimize total cost which includes vehicle travel time cost and vehicle fixed departure cost. A hybrid genetic algorithm (HGA) with two-dimensional coding method is proposed, for which a multi-segment single point crossover strategy, dynamic insertion operator and local search strategy are designed. Finally, 27 test cases are generated based on the Solomon VRPTW benchmark dataset, and the hybrid genetic algorithm is used to solve them. The numerical experimental results indicate that the proposed model has not only a significant impact on the total travel time of vehicles by considering the traffic conditions, choosing a reasonable departure time and avoiding the congestion period, but also the HGA is capable to obtain a satisfying solution.

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    Based on Hub-Spoke Network a Practice Heuristic Algorithm Applied to Airline Fleet Assignment
    Guohua Wu
    2024, 32 (1):  158-167.  doi: 10.16381/j.cnki.issn1003-207x.2021.2459
    Abstract ( 62 )   HTML ( 2 )   PDF (735KB) ( 57 )   Save

    The fleet assignment problem of Hub-spoke network airlines in making flight schedules is addressed. According to the demand distribution of passengers and resulting in the flight costs from the airline's historical data, an optimization algorithm by tabular operation method based on the flight cost model is designed, and an heuristic algorithm is proposed for flight planning specialist to facilitate manual calculation and to adjust aircraft types, which solves the airline fleet assignment 0-1 integer programming problem, The algorithm integrates the ideas of Hungarian algorithm and backtracking algorithm. Starting from the minimum cost of ?ight optimization, the algorithm searches the optimal value by the depth-first-search method subject to the optimization constraints, and backtracks in the nodes when the aircraft constraints are not met, finds the minimum flight cost that meets the aircraft side constraints, and obtains the optimal fleet assignment and hence gives a theoretical proof. The effectiveness of the heuristic algorithm is obtained through case study. The total cost of ten B737 and five B757 scenarios is found to be the lowest among all scenarios by manual calculation using the tabular method, reaching $409,860, which proves that a reasonable mix of aircraft types can make the company operate better. Compared with the traditional operations research algorithm this algorithm is straightforward in construction and natural in optimization mechanism, which is simple and practical, also easy to understand and master, especially for small airlines or branches to manually formulate and adjust flight schedules.

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    Optimal Pricing and Advertising of Competitive Platforms in Local Market with Mobile Service Providers
    Yongyi Zhou,Yulin Zhang
    2024, 32 (1):  168-176.  doi: 10.16381/j.cnki.issn1003-207x.2021.2613
    Abstract ( 74 )   HTML ( 7 )   PDF (653KB) ( 183 )   Save

    How an incumbent platform responds to the advertisement of an entrant platform in a market of mobile service providers is examined. It is found that: (1) If the entrant platform offers high-intensity advertising, the incumbent platform will give a higher wage on the service provider side to response the entrant. When the local market is relatively large, the entrant platform will capture market share, but its profit always is negative. (2) If the entrant platform has low-intensity advertising, the incumbent platform will not respond to the entrant, that is, the incumbent will continue to charge monopoly price and offer monopoly wage. Additionally, more mobile service providers who enter the local market also reduce the incumbent platform’s motivation to response the entrant. In such a case, the market share and profit of the entrant may be higher than the incumbent. (3) When the entrant platform has full-coverage advertising, the platform’s choice to respond or not depends on the switching costs of the service provider and the buyer.

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    Does Fixed-Rate Loans Help Small and Mirco Retailers with Insufficient Operational Capitals?
    Hongmei Guo,Menglin Qin,Xianyu Wang,Meng Wu
    2024, 32 (1):  177-186.  doi: 10.16381/j.cnki.issn1003-207x.2021.0016
    Abstract ( 53 )   HTML ( 3 )   PDF (746KB) ( 126 )   Save

    In the past decade, small and micro enterprises have faced difficulties in financing, whereas private lending is booming. In this study,how different interest rate pricing policy affects retailers' operational decisions is studied. By incorporating bankruptcy risk and its related costs, a newsvendor model is formulated in which a retailer with limited capital can finance its operational capital from a bank at a fixed loan interest rate. The optimal lending and ordering decisions of a bank and a retailer, respectively, are derived, and the optimal decisions are compared under the floating interest rate. Our results show that the only decisive factor affecting lending decisions is the value of the collateral. Bankruptcy risk and its related costs have no effect on a bank's lending decision. Moreover, the ordering decision of a retailer is based on its initial operational capital. For giant or mega-retailers who possess heavy assets, the operational decisions are unaffected by how the interest rate is priced. However, for small and micro retailers, the fixed interest rate never alleviates the insufficient operational capital of the retailer.

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    The Economic and Environmental Performance of Closed-Loop Supply Chain Considering Online Shopping Preference and Offline Retail Service
    Xiaotong Qin,Zongyu Mu,Tao Chu,Yongguang Zhong
    2024, 32 (1):  187-199.  doi: 10.16381/j.cnki.issn1003-207x.2021.1994
    Abstract ( 122 )   HTML ( 15 )   PDF (668KB) ( 349 )   Save

    In recent years, online shopping, mode of “Internet + service”, mode of online and offline integration are becoming the dominate trends of new consumption industry, whose thriving development are playing an important role in safeguarding people's livelihood, unleashing consumption potential, stabilizing economic growth, and becoming one of the most important accelerators for high-quality economic development. As online shopping is increasingly preferred by consumers, the offline retailers tend to provide retail services in response to the competition among those online direct selling platforms. Therefore, this research aims to examine how the customers’ preference for online shopping and retail services affect selling and recovery strategies in close-loop supply chains. Moreover, a decision model is built for a close-loop supply chain with dual-channels of offline retailing and online direct selling by applying consumer utility theory for a close-loop supply chain in which regarding the activity of managing used products for remanufacturing by retailers and manufacturers respectively as targets. By comparing the calculation results of different close-loop supply chain decision models, the optimal sales and recovery strategies are derived, and then the correctness of the results is verified by empirical analysis. It is found that: (1) The customers’ preferences for online purchase behavior is one of the main factors that would lead to a huge impact on the sales strategy of those manufacturers in the close-loop supply chain, which is known as its dual selling strategy on the retailer recycling and manufacturer recycling. For example, when consumers have a high willingness and preferences to purchase online, then the manufacturers would be more likely to choose the offline retailing strategy. Under this strategy, the profits of manufacturers collected in both channel of online direct selling and the dual-channel would increase, leading the manufacturers to set up online direct-selling channel after selection. When consumers' preferences for online shopping reach to a certain level, manufacturers would be more likely to close down the channel of offline retail and set up the channel of online direct selling only. Manufacturers' profits would increase gained from both channels of offline retailing and dual selling regardless of whether an increase or decrease of the sensibility of service quality to serviceability. More specifically, Low sensitivity will lead the manufacturer to choosing the dual-channel selling strategy. On the contrary, when the consumers are less preferring online shopping, high sensitivity would lead the manufacturer to choosing the offline retail strategy. On the other hand, when the customers prefer to shop online, the manufacturers would prefer the strategy of online direct selling accordingly. (2) When the offline retail channel is set up independently, the manufacturer will tend to choose a retailer recycling strategy. On the contrary, when a dual-channel of selling and operating or channel of online direct selling is set up, the manufacturer will tend to choose its own recycling strategy. It can provide a theoretical basis and important inspiration for the selling and recovery strategies and contractual coordination issues in close-loop supply chains with dual selling channels in this paper.

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    Dynamic Buffer Monitoring Based on Brittleness Risk-driven in Critical Chain Project Portfolio Scenario
    Junguang Zhang,Meihua Wang
    2024, 32 (1):  200-210.  doi: 10.16381/j.cnki.issn1003-207x.2021.1066
    Abstract ( 55 )   HTML ( 0 )   PDF (912KB) ( 39 )   Save

    In the context of project portfolio management,a critical chain project is faced with brittleness risk from outside the project because of the interaction between multiple projects. Compared with the risks faced by various activities within the project, a more serious impact of brittleness risk on the performance of project buffer management, project duration, and project cost may be caused. Namely, the project duration delay and cost overrun still can’t be avoided especially due to the brittleness risk.However,in order to solve the above problems and improve the efficiency of buffer monitoring and the overall project, the existing buffer monitoring methods mainly focus on the common risks from within the project.The brittleness risk from outside the project is neglected. In addition,most of the approaches put the buffer at the end of the activity before monitoring the buffer, which will lead to the Domino effect and can’t ensure the rationality of buffer allocation.Therefore, the research problem in this paper is that considering and analyzing the brittleness risk in critical chain project portfolio scenario to build a quantitative model to make the buffer allocation more reasonable and buffer monitoring more efficient.According to the research problem, a new method is proposed to monitor the buffer dynamically.Firstly,resource, technology, and market of the project are considered to measure the brittleness risk by using the niche theory. After determining the buffer allocation ratio, the project buffer is allocated reasonably and the buffer positions are designed for project-level brittleness risk and activity-level risk. Secondly,the trigger points of buffer monitoring are set according to the buffer allocation. Then,a dynamic buffer monitoring strategy of cumulative buffer and reallocation is constructed, which ensures continuous buffer update and avoids buffer waste. Finally, the dynamic buffer monitoring strategy is implemented to monitor and control buffer consumption in real time.The simulation results of Monte Carlo show that the new method has better performance in indicators such as warning frequency, project duration, and project duration, thus the proposed buffer monitoring method can effectively improve the comprehensive performance of the project through reasonable buffer allocation and monitoring.Based on the research results of this paper, our research will help relevant scholars better to understand the brittleness risk in critical chain project portfolio scenario and solve the dynamic buffer monitoring problem.In practice, a new perspective is also provided for the project decision-makers or managers to manage the critical chain in the complicated environment.

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    Optimal Patent Licensing in a Technology Supply Chain under Information Asymmetry
    Liang Jin,Ying Zhu
    2024, 32 (1):  211-219.  doi: 10.16381/j.cnki.issn1003-207x.2020.2462
    Abstract ( 89 )   HTML ( 2 )   PDF (638KB) ( 214 )   Save

    In recent years, the level of intellectual property protection in our country has been continuously improved. Therefore, as the key to the use of intellectual property rights, patent licensing is becoming more and more common among enterprises. However, unreasonable licensing contracts often lead to patent infringements and legal disputes, such as patent litigation disputes between Huawei and Qualcomm. In this context, the following three questions are studied: (i) How does patent-holding company design and choose the form of patent licensing contracts to avoid patent infringement disputes? (ii) How does the licensee determine its manufacturing outsourcing strategy? (iii) How will realistic factors such as market conditions and product sales affect the equilibrium of the technology supply chain?In this paper, a transnational technology supply chain consisting of a technology supplier, a branded manufacturer and an original equipment manufacturer (OEM) is considered, then three multi-stage dynamic game model are constructed with asymmetric information. In this model, the technology supplier needs to design the licensing contract and guarantee that the branded manufacturer will be willing to accept the contract. The branded manufacturer needs to determine the product sale price and R&D investment level. The OEM decide the product outsourcing production price. The main work includes four parts. At first, the optimal licensing contract is proposed and the optimal pricing and R&D investment decisions are analyzed, respectively. Second, the technology supplier’s optimal licensing contract selection and the nature of the licensing contract are analyzed. Third, to address the value of licensing contract, the optimal pricing and R&D investment decisions are compared under different types of licensing contracts. Finally, the impact of key parameter on the equilibrium of the transnational technology supply chain is illustrated through a numerical example.The results show that, in the patent licensing stage, the optimal licensing contracts includes fixed-fee licensing contract and two-part tariff licensing contract. Among them, the technology supplier can obtain more profits under a fixed fee contract. Moreover, the optimal licensing contract selection of the technology supplier is not the branded manufacturer’s possession strategy, and may result in the loss of the branded manufacturer’s profit, which reveals the cause of patent licensing conflict in industrial practice. Moreover, different forms of licensing contracts will affect the optimal decision of the manufacturer and the OEM. When the technology supplier chooses two-part tariff licensing contract, the branded manufacturer will reduce the level of R&D investment, which is conducive to improving the profit level of the OEM and consumer welfare. However, in the collaborative R&D cooperation, the economies of scale of OEM are not necessarily beneficial to branded manufacturer. Finally, from the perspective of market share, the brand manufacturers may have an incentive to invest more in research and development, which is conducive to increasing product demand and bringing positive externalities to technology supplier and OEM. At the same time, in order to make up for R&D investment, consumers may need to spend a higher price to purchase products.In summary, three multi-stage dynamic game models between the technology supplier, the branded manufacturer and the OEM are constructed to study the optimal patent licensing contract, which can provide theoretical and methodological guidance for the transnational technology supply chain competition and cooperation. In the future research, the optimal patent licensing contract design considering market competition situation can be further studied.

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    Supply Chain Information Disclosure Strategy Considering Uncertain Demands Under the Development Pattern of Dual Circulation
    Jiaguo Liu,Huimin Zhang,Mingming Yang
    2024, 32 (1):  220-230.  doi: 10.16381/j.cnki.issn1003-207x.2021.1860
    Abstract ( 86 )   HTML ( 5 )   PDF (756KB) ( 284 )   Save

    Under the new development pattern of dual circulation and facing the uncertainty of the market, it’s worth discussing whether local manufacturers with comprehensive data have the motivation to disclose information and whether more accurate demand signals are beneficial to all parties in the supply chain. A stylized signal game model under the competitive environment is constructed to study the information disclosure problem in the supply chain system. In the two modes of information encryption and information disclosure, factors affecting the strategy choices of the supply chain members such as product brand image, market demand uncertainty, and investment efficiency are considered to deduce the conditional interval for achieving the Pareto optimality of the supply chain. The results show that encrypting company information to maintain the information security of the supply chain may not be the best choice for local manufacturers. When the investment cost is higher than a certain threshold, local manufacturers will voluntarily abandon the information encryption strategy and turn to the disclosure strategy, while the multinational manufacturers always favor the information disclosure strategy. Meanwhile, there is a win-win interval for domestic and foreign supply chain members, which are specifically divided into “win-win under a high-quality image” and “win-win under a poor-quality image”. Interestingly, the size of the win-win interval is affected by the market demand uncertainty, noise deviations that interfere with market forecasts, and foreign wholesale prices. Therefore, companies should pay close attention to market fluctuations and their own brand image before making strategic choices.

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    A Differential Game Study of Supply Chain Considering Consumers' Green preference and Member's Behavior under Cap-and-trade Policy
    Fanjun Yao,Han Xiao,Ye Gao,Hongwei Gao
    2024, 32 (1):  231-241.  doi: 10.16381/j.cnki.issn1003-207x.2021.2262
    Abstract ( 127 )   HTML ( 6 )   PDF (665KB) ( 239 )   Save

    As environmental conditions deteriorate and climate change accelerates, consumers’ green preference continue to increase in order to reduce their carbon footprint. They will pay more attention to the firm’s environmental performance when purchasing products. Consumers who has green preference are willing to buy environmentally friendly products even if they cost a bit more. Meantime, several legislations, such as emission standard, carbon tax, carbon subsidy, and cap-and-trade system have been issued to reduce the emissions of carbon dioxide and other greenhouse gases by the regulators to deal with pollution reduction problems. The pollutant emissions are accumulated with the increase of production, which is not welcome by the environment and has a negative impact on firm’s reputation. Given the manufacturer’s actual emission of production, a reference level is introduced for emissions, which represents the number of emissions permits allocated to the firm by the regulator, and the market price of the carbon quota. Then the impact on the manufacturer’s profit of carbon quota is calculated with respect to actual emissions.As an important characteristic of firm’s environmental performance, green goodwill is an intangible asset that changes over time. In the dynamic equation of green goodwill, we use a parameter to scale the manufacturer’s environmental performance, i.e., the gap between the actual emission and emission standard σ(eˉ-e), which is interpreted as the consumers’ green preference. When the actual emission is smaller than the standard, i.e., eˉ-e>0, the environmental performance will have a positive impact on the green goodwill and demand. On the contrary, the impact is negative. The manufacturer’s advertising strategy also has a positive impact on the green goodwill. When the impact of environmental performance is negative, the positive effects of advertising strategy can offset the negative effects.From the short-term and long-term effects of actual carbon emissions, a differential game model is established that demands rely on green goodwill, it is found the advertising and pricing strategies of manufacturer and retailer in different decision-making models, respectively. The impact of key parameters on the strategies and profits is analyzed. Furthermore, the impact of retailer’s myopic behavior on the equilibrium strategies and outcomes is assessed. The retailer is myopic when she ignores the effect of today’s decision on future outcomes. In this setting, the strategies and profits are found and compared when retailer is myopic or far-sight. From the theoretical analysis and numerical simulations, it is found that the carbon quota price and consumers’ green preference coefficient are negatively related to the manufacturer’s advertising strategy and positively to the retailer’s pricing strategy. When the consumers’ green preference coefficient is zero, the retailer’s myopic behavior will have no influence on the advertising and pricing strategies. The environmental performance also has no impact on the decision of consumers. Green goodwill and profits are highest in the centralized decision-making model, and the manufacturer’s green goodwill in myopic scenario is higher than a far-sight scenario. Manufacturer prefers a myopic retailer because it can squeeze the retailer’s profit margins, consolidate the leadership and increase the share of profits. The results of the paper can provide implications for firms and policymakers.

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    The Channel Game between the Hotel Direct Official Website and the Online Travel Agent
    Qiang Guo,Xiaolan Chen,Xinyuan Zhao
    2024, 32 (1):  242-250.  doi: 10.16381/j.cnki.issn1003-207x.2021.1500
    Abstract ( 104 )   HTML ( 4 )   PDF (547KB) ( 176 )   Save

    The hotel’s discourse right to the online travel agent (referred to as OTA) is mainly manifested in commission bargaining power and room pricing power. In recent has years, the hotel has focused on operating the official website to regain the discourse right to the OTA, Taking this the background it targets to tackle the channel game issues between the hotel online direct channel and the OTA. The neglected cost is taken as the decision variables to construct a one-to-one game model and the realization conditions of the optimal returns are discussed under three models: the “single-channel official website model,” the “dual-channel merchant model,” and the “dual-channel agent model.” It is found that: Firstly, the hotel does not necessarily need to cooperate with OTA to achieve the best revenue. Under certain conditions, the hotel can achieve the best profit by adopting the single-channel official website model. Secondly, when a hotel decides to cooperate with an OTA, the dual-channel merchant model can be used to maximize profits, and there are two conditions for its realization. Finally, when the hotel achieves the best revenue under the dual-channel merchant model, the hotel and the OTA can only meet the participation constraint and cannot achieve incentive compatibility.

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    Opening-Up or Laissez-Faire? Research on Strategies of Retail Platform to Deal with Manufacturer Encroachment
    Xuefeng Zhang,Guo LI
    2024, 32 (1):  251-259.  doi: 10.16381/j.cnki.issn1003-207x.2021.2398
    Abstract ( 108 )   HTML ( 6 )   PDF (680KB) ( 168 )   Save

    In recent years, B2C e-commerce has become the main driving force of online retailing, and plays an increasingly important role in the national economy. Incumbent manufacturers usually have better partnerships with retail platforms, who purchase products from these manufacturers and resell them to consumers. In contrast, external manufacturers that are not well recognized by consumers usually have their cooperation standards raised by retail platforms, making it difficult for them to be included in the purchase list. Therefore, an external manufacturer that cannot sell products through retail platforms may have to encroach on the retail market through a direct channel, which will hurt the interests of the retail platforms. To avoid this, retail platforms have begun to lower their cooperation standards with those external manufacturers, or implements the opening-up strategy to attract them to set up direct-sale stores on their platforms. However, relevant research on the impact of platform’s opening-up strategy on external manufacturer encroachment is lacking, and the interaction mechanism between the two entities is unclear.In this study, the following questions are discussed: (1) Should a retail platform choose an opening-up strategy or a laissez-faire strategy to deal with the external manufacture’s encroachment? (2) How can a platform retailer use its influence to intervene in the approach sequence to obtain more benefits? (3) What are the influences of product characteristics, direct selling cost, and platform profit sharing ratio on the retail platform’s opening-up strategy? (4) How does the retail platform's opening-up strategy interact with the manufacturer’s encroachment?To this end, a supply chain consisting of an incumbent manufacturer, an external manufacturer, and a platform is constructed in this study. The retail platform is powerful and determines whether to open its platform and the approach sequence for the two manufacturers. The external manufacturer decides whether to encroach on the retail market by opening a direct channel. Game models are constructed and solved by backward induction. The influence of product quality, product substitution coefficient and profit-sharing ratio on retail platform's strategy choice are analyzed, and the interaction mechanism between retail platform's introduction strategy and the external manufacturer's encroachment behavior is discussed.Results indicate that (1) the external manufacturer encroachment will definitely hurts the incumbent manufacturer, but not necessarily the retail platform; (2) the product quality improvement does not mean that the external manufacturer can sell a higher wholesale price nor can gain a higher payoff, but may benefit the incumbent manufacturer in some cases; (3) when the direct selling cost is low, the retail platform will choose the laissez-faire strategy, and the external manufacturer will always encroach into the retail market; (4) the retail platform can effectively prevent manufacturer encroachment by using the opening-up strategy in certain cases.

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    A Data-driven Single-Period Newsvendor Problem Based on XGBoost Algorithm
    Yuting Yan,Wenjie Bi
    2024, 32 (1):  260-267.  doi: 10.16381/j.cnki.issn1003-207x.2020.0816
    Abstract ( 109 )   HTML ( 7 )   PDF (563KB) ( 190 )   Save

    Solving single-period newsvendor problem usually assumes that the demand distribution follows a particular form, predicts demand from historical data, then solves optimization models. Although this assumption simplifies the analysis, it does not reflect the true distribution of demand over time and inevitably passes on historical estimated prediction errors to the optimization process. To solve this problem, a method that combines estimation and optimization is proposed. This method adopts the form of data-driven weights to deal with the demand uncertainty related to features and introduces XGBoost algorithm to solve single- period newsvendor problem with non-stationary demand. After observing the features that affect demand, the method directly determines the optimal inventory decision. This paper's contribution to the field of operations management mainly includes twofold: 1) It integrates a scalable end-to-end tree boosting system called XGBoost into a single-period newsvendor problem. 2) The integrated estimation optimization algorithm is applied to a real-world data set under different target service levels and training sample sizes, and is compared with several standard methods for studying newsvendor problems. The results show that this method can reduce inventory costs by at least about 5%.

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    Retailer's Optimal Extended Warranty Strategy? Collaboration with Manufacturer or Not
    Zhen Liu,Qiang Guo,Jiajia Nie
    2024, 32 (1):  268-275.  doi: 10.16381/j.cnki.issn1003-207x.2021.1010
    Abstract ( 75 )   HTML ( 1 )   PDF (618KB) ( 195 )   Save

    The impact of manufacturers' innovation investment on the extended warranty service model of powerful retailer is studied. The research shows that no matter whether the manufacturer invests in innovation or not, retailer shows cooperation tendency only when the cost advantage of OEM is more than 50%. However, innovation investment relaxes the market scale and fixed cost threshold of joint venture between retailers and manufacturers, and promotes the joint venture willingness of both sides. The greater the cost advantage of OEM, the easier it is to reach cooperation, and the cooperation realizes Pareto improvement of both sides. With the change of price sensitivity and cost difference, manufacturer show different cooperative attitudes, but the cooperation motivation is always stronger than retailer. The sub game perfect Nash equilibrium shows that innovation investment is the dominant strategy of manufacturers, and retailers also "free ride" from innovation investment.Finally, through numerical analysis, it is found that the appropriate relaxation of cooperation conditions by retailer is beneficial to the improvement of consumer surplus and social welfare. The research results can provide theoretical and practical enlightenment for the extended warranty service cooperation between manufacturer and retailer.

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    Tripartite Cooperation Evolutionary Strategy of Industrial Internet Platform, Developer and Enterprise: The Role of Government Subsidies and Revenue Sharing
    Xiaoyang Zhou,Zhangzhang Li,Ying Liu,Fan Zhao,Gengzhong Feng,Shouyang Wang
    2024, 32 (1):  276-287.  doi: 10.16381/j.cnki.issn1003-207x.2021.2558
    Abstract ( 147 )   HTML ( 6 )   PDF (773KB) ( 270 )   Save

    The key to enabling the digital transformation of manufacturing enterprises and promoting the effective and sustainable development of industrial Internet is to effectively grasp the cooperative evolution mechanism between relevant participants of the industrial Internet platform and reveal the influence of different factors on the decision-making behavior of game players.Based on this, a revenue sharing contract between the platform and third-party developers is introduced, and the impact of government subsidies and the risk cost of enterprises joining the platform on the development of industrial Internet platform is taken into account, constructing a three-party evolutionary game model with three stakeholders including manufacturing enterprises, industrial Internet platforms and third-party developers. Lyapunov discriminant method is used to obtain the evolutionary stability strategy of the system under different conditions, and dynamic simulation analysis is conducted on the three-party collaborative strategy under the influence of different factors. The results show that: revenue sharing ratio plays an important role in guiding whether third-party developers choose to cooperate with the platform; the government's subsidy to enterprises and the risk cost of enterprises joining the platform not only affect the enthusiasm of manufacturing enterprises to join the platform, but also affect the cooperation between third-party developers and the platform. In addition, the effective interval of the influencing factors is defined that promote the system evolution to different stable states, providing theoretical reference for manufacturing enterprises, industrial Internet platforms and third-party developers to implement strategies.

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    The Source Governance of Plastic Pollution Based on Social Co-governance under the New Version ofPlastic Restriction Order
    Dandan Wang,Lirong Jian,Shuaishuai Fu
    2024, 32 (1):  288-298.  doi: 10.16381/j.cnki.issn1003-207x.2020.1687
    Abstract ( 75 )   HTML ( 1 )   PDF (949KB) ( 178 )   Save

    The plastic pollution source treatment is a key issue in the policy implementation of the new version of the “plastic limit order”. An evolutionary game model based on government supervision, enterprise transformation production, and public participation in supervision is established in the perspective of social co-governance, in which the impact of the government, the public, and plastic manufacturers on the governance of plastic pollution sources is considered. This model analyzes the evolutionary equilibrium strategy of pollution source treatment problems under four different scenarios. In addition, the numerical simulation is utilized to analyze the decision-making behaviors of various entities in the process of collective treatment of plastic pollution sources. According to the analysis results, some interesting conclusions can be obtained, which are shown as follows: (1) Regardless of the effect of long-term or short-term, the implementation of the new version of the "plastic restriction order” can prompt companies to choose transformation production strategies with the influence of government supervision and public supervision. It also can cut plastic pollution from the source. (2) Higher levels of government regulation can effectively restrain the illegal production behavior of enterprises. On the other hand, the public supervision can effectively restrain the production behavior of enterprises when the government has a negative regulation. (3) Increasing the economic incentives for citizen’s supervision is helpful for improving citizen’s social co-governance level in plastic pollution source treatment process.

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    Research on Multi-Value Chain Collaborative Innovation Management for Manufacturing Servitization Oriented to the Construction of Data Space System
    Jieping Han,Meiling Gu,Xiaolong Yang,Dan Zhao,Huanfen Zhang
    2024, 32 (1):  299-308.  doi: 10.16381/j.cnki.issn1003-207x.2022.2525
    Abstract ( 102 )   HTML ( 7 )   PDF (791KB) ( 249 )   Save

    Manufacturing enterprises can provide better solutions for customers and gain global competitive advantages through servitization transformation. The rapid development of big data technology has provided the source power for the transformation of data-driven manufacturing industries into services. It is of great significance to study how to use online comments and other Internet information to mine customer potential demand, and put forward a series of methods to transform customer demand into multi-value chain collaborative innovation solutions, so as to solve the problem of integrating customer demand into multi-value chain collaborative innovation solutions for manufacturing enterprises. Taking manufacturing enterprises as the research object, a multi-value chain collaborative innovation management method is proposed oriented to the construction of data space system. Python web crawler is used to collect user comment information, and customer demand topics are identified from user comments based on Latent Dirichlet Allocation (LDA) model. Secondly, by referring to the idea of quality function deployment (QFD), the identified requirements would be transformed into innovation elements by using the probabilistic semantic term set (PLTS) and then the importance is ranked. Then, a three-layer coupled innovation scheme generation Method called “chain-dimension-method” (CDM) is proposed. From the perspective of multi-value Chain, the dimension of innovation elements is divided by using multidimensional technology innovation map technology, and a series of alternative innovation schemes are generated by coupling with multiple innovation rules. Based on the research results, the data space system of manufacturing servitization is constructed. Finally, taking an electric power equipment manufacturing enterprise as an example, 10,445 user comment data of Tmall e-commerce platform are crawled and the multi-value chain collaborative innovation management method proposed in this paper is used to verify the effectiveness of the proposed data space system. The research results show that the construction of the manufacturing servitization data space system can help enterprises optimize multi-value chain collaborative innovation management decisions.

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    Impact of Leasing Mode with Renewable Energy Storage Equipment on Electricity Quality and Price
    Wei Chen,Yongle Tian,Yongkai Ma,Chunguang Bai
    2024, 32 (1):  309-318.  doi: 10.16381/j.cnki.issn1003-207x.2021.1191
    Abstract ( 89 )   HTML ( 7 )   PDF (701KB) ( 197 )   Save

    In order to solve the climate problem, China’s installed capacity of renewable energy reached about 800 million kW, ranking first in the world. However, with the enlarged scale of renewable energy generation such as hydroelectricity, wind and photovoltaic generation, grid connection consumption is becoming an increasingly serious problem. Due to the intermittence of renewable energy and the insufficient allocation of the electricity system, abandoned wind and light are still prominent in China.Through building large-scale energy storage equipment, the intermittence of renewable energy can be alleviated or even avoided, and unstable electricity can be transformed into stable and high-quality electricity by using energy storage equipment. However, the initial investment in energy storage equipment is too much. Therefore, electricity system enterprises are not highly motivated to invest in energy storage equipment. It is worth exploring that the third-party enterprises invest in energy storage equipment and then lease it to electricity system enterprises. There are three types of leasing modes. The first type is that the generator leases energy storage equipment. For example, the core leasing energy storage equipment of comprehensive energy in Hunan Province contributes to constructing energy storage equipment. The generator leases energy storage equipment to improve access to renewable energy and provides consumers with high-quality electricity. Second, electricity retailer rent energy storage equipment. Third, electricity generators and retailer share the cost of energy storage. It can be seen that the research on the leasing mode of renewable energy storage equipment is not only an urgent concern of the industry but also a topic that needs to be involved in the academic community.The following conclusions are drawn. (1) Compared with the electricity retailer and hybrid leasing mode, the electricity generator leasing mode can provide electricity of higher quality and sound price; (2) When the electricity quality preference coefficient is low, the electricity retailer leasing mode can meet higher renewable energy demand; by contrast, if the coefficient is high, the electricity generator leasing mode can provide more renewable energy. (3) Electricity quality and price increase with the rising unit price of the energy storage, and decrease with the energy storage cost coefficient.The main contributions of this paper are as follows. First, aiming at solving the problem of who would lease energy storage equipment, an electricity supply chain is creatively constructed, composed of a generator, a retailer and lessor, and the impact of different leasing modes is discussed on the decision-making of electricity quality and price, giving some enlightenment for enterprises in the electricity supply chain. Second, existing literature mainly focuses on renewable energy investment, but little considers the investment in energy storage equipment, which is the key to the sustainable development of renewable energy. Therefore, the research on the leasing mode of energy storage equipment will further extend the field of renewable energy investment. Third, under the background of carbon neutrality, the industry will invest in renewable energy storage equipment to support energy reconstructing. Based on this fact, it is pointed out that when the consumer's preference coefficient for electricity quality is small, the retailer leasing mode is more conducive to increasing the demand for renewable energy electricity; when this coefficient is large, the generator leasing mode is more conducive to stimulating the demand for renewable energy. This point will provide theoretical support for lessor to select partners and a basis for the government to formulate relevant policies.

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    Multi-period Inventory Substitute Competition under the Initial Inventory Level and the Capacity Constraints
    Jian Zhang,Shuang He,Pujie Shi,Juliang Zhang
    2024, 32 (1):  319-324.  doi: 10.16381/j.cnki.issn1003-207x.2020.2416
    Abstract ( 89 )   HTML ( 5 )   PDF (479KB) ( 139 )   Save

    Substitute competition is a common phenomenon in economy and business that affects inventory management significantly. The competition problem between two firms is studied with the initial inventory level and the capacity constraints. Two substitutable products are operated by two firms respectively. The unmet demand of one product can be met by the other product’s leftover stock, if available, and is lost otherwise. The firms compete for the substitute demand by choosing their own order quantities in multi-period. The problem is formulated as a dynamic game under independent stochastic demands and it is shown that the inventory game is submodular and the response functions are contraction maps, so the existence of a unique Nash equilibrium is guaranteed. It is found that the best response function is strictly decreasing in the rival’s decisions and decreasing in the initial inventory levels of the two products. It is found that the base-stock policy is the equilibrium policy. The capacitated case is considered where each firm can hold no more than a certain quantity of the product in each period and find that the equilibrium policy is a modified base-stock strategy. Finally, numerical studies are conducted to compare our strategy with the myopic policy and to generate managerial insights from the analytical findings. Compared with the existing literature, it contributes to the fields of multi-period inventory management and dynamic game in this paper.

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    Nourish Your Competitor?——Demand Information Sharing of E-commerce Platform in the Presence of Store Brand Encroachment
    Dongdong Yu,Chunlin Luo,Miyu Wan,Biao WANG
    2024, 32 (1):  325-334.  doi: 10.16381/j.cnki.issn1003-207x.2021.2446
    Abstract ( 138 )   HTML ( 11 )   PDF (693KB) ( 225 )   Save

    With the great success and huge data of e-commerce platforms, e-commerce platform giants such as Amazon, Kogan, JD, and T-mall aggressively expand their store brand (SB) business. The SB encroachment changes the interaction between the national brand (NB) suppliers and e-commerce platforms. The NB manufacturers not only sell NBs products on the platform but also compete with the platform. In other words, the SB encroachment transforms the relationship between the platform and manufacturer into a co-opetition relationship. The e-commerce platform faces a dilemma when deciding information sharing strategy. Hence, the issue of the market conditions under which the platform has an incentive to share information becomes more perplexing when considering the SB encroachment option.A game-theoretic model is developed to examine the interaction between demand information sharing and SB encroachment in a supply chain consisting of one supplier and one e-commerce platform. The equilibrium results are solved by backward induction. Depending on whether the e-commerce platform shares information in stage 1, and whether the platform introduces an SB in stage 2, there are 4 subgames consisting of stage 3. These 4 subgames are analyzed, respectively, and then the equilibrium demand information sharing and SB introduction strategies are drived by comparing the e-commerce platform’s profits in these 4 subgames.The results show that demand information sharing has a double marginalization effect and brand competition effect under reselling mode, while revenue increasing effect and brand competition effect will be generated under agency selling mode. Demand information sharing strategies differ significantly under different sales modes. When the entry cost is very low or sufficiently high, the e-commerce platform prefers information sharing under agency selling mode, whereas the platform keeps demand information private under reselling mode. When the entry cost is intermediate and the product substitution coefficient is high, the e-commerce platform can promote store brand encroachment through a demand information sharing strategy.

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