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    25 October 2023, Volume 32 Issue 10
    Theory Analysis and Methodology Study
    Fuzzy Robust Project Scheduling Optimization Based on Decision-maker's Risk Preference
    TANG Ziyang, HE Zhengwen, WANG Nengmin
    2023, 32(10):  1-8.  DOI: 10.12005/orms.2023.0311
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    In the realm of project scheduling, the increasing prevalence of intelligent manufacturing and advanced technologies has led to a growing emphasis on project integration and systematization. However, this rise in complexity and uncertainty is particularly pronounced in R&D projects, which often involve numerous innovative and unique activities, resulting in limited historical data. Consequently, decision-makers must heavily rely on expert judgment to assess activity uncertainty. Fuzzy logic has emerged as a powerful tool for expressing expert information, as it allows data to be derived from expert estimates while aligning with their preferences. It proves especially valuable in handling R&D projects characterized by difficult-to-predict task complexities and unclear partner needs. Meanwhile, the high uncertainty associated with the innovative nature of R&D project activities makes project execution highly susceptible to external disruptions. To enhance project stability and mitigate the impact of activity disturbances, decision-makers need to consider project robustness carefully. This entails accurate estimation of uncertain activity durations and the rational arrangement of project plans to minimize time and resource conflicts during execution. Hence, the challenge of how decision-makers can effectively use expert fuzzy information for robust project scheduling in the absence of historical data is of paramount importance.
    It is essential to recognize that in the context of fuzzy robust project scheduling, decision-makers exhibit diverse risk preferences. When formulating plans, decision-makers often introduce varying time slacks between activities to safeguard the stable execution of tasks based on each activity's potential impact on time and resource conflicts. These differing risk preferences lead to distinct judgments regarding the possibility of conflicts between activities, resulting in the incorporation of time slacks of different sizes between activities and, consequently, the creation of project schedules with varying levels of robustness. The decision-maker's risk preference significantly influences the schedule generation process. If the consideration of conflicts is too conservative or too aggressive, the project may not align with the decision-maker's expectations, leading to time delays and resource wastage. Therefore, generating a reasonable and satisfactory project schedule according to different risk preferences of decision-makers holds substantial practical value.
    Existing research on robust project scheduling typically assumes that the duration of uncertain activities follows a random distribution. However, there has been limited investigation into the fuzzy robust project scheduling problem. Additionally, few scholars have considered the risk preferences of decision-makers in the field of project scheduling. Previous literature has primarily focused on comparing project scheduling optimization results under different risk preferences, without incorporating risk preference into the optimization model. To the best of our knowledge, there are no studies that have considered the risk preference of decision-makers in the fuzzy robust scheduling problem. Therefore, this paper holds unique research value.
    Therefore, this paper addresses the fuzzy robust project scheduling problem considering the decision-makers' risk preferences. The objective is to arrange the start time of each activity in the project constrained by the renewable resources and project plan duration. The objective is to maximize the robustness of the project schedule under the specified preference, ensuring stable project execution in an uncertain environment, while meeting the decision-maker's satisfaction criteria.
    Firstly, to aid decision-makers in formulating optimal project schedules in the scenarios lacking historical data, this paper introduces a proactive fuzzy project scheduling optimization model that incorporates decision-makers' risk preferences. The uncertain activity durations are described by the six-point fuzzy numbers. By employing possibility theory to express the credible function of these fuzzy numbers, the paper identifies potential time conflicts between activities with precedence relationship constraints, and possible resource conflicts arising from activities executed simultaneously and utilizing the same resource. The proposed “fuzzy overlap” serves as a surrogate measure to evaluate schedule robustness, capturing the potential conflict areas between related activities. Additionally, the weight parameters of the credibility function represent the risk preference factors of project decision-makers.
    Secondly, a complexity analysis of the model reveals its NP-hard property, indicating the need for a heuristic approach. Hence, the paper adopts an alternate tabu search algorithm tailored for solving robust project scheduling problems with high initial solution quality. The algorithm employs decoding of the activity list and the time slack list to generate the schedule. Subsequently, it refines the solution through alternating iterations, considering the respective neighbors of the two lists.
    Finally, the proposed tabu search method is validated and evaluated using an actual project case, XHQMGZ, with 40 activities. The research makes a sensitivity analysis of key parameters, namely the risk preference value, project deadline, and resource availability. The obtained results demonstrate a significant improvement in the robustness of the project schedule generated by the fuzzy-overlap based research method when compared to the practical project schedule. The overall fuzzy overlap value of the project is notably reduced, leading to a considerable reduction in activity conflicts. Moreover, as decision-makers' risk preferences move from the conservative to the optimistic, the possibility of conflicts between activities in the schedule increases, thereby increasing the sum of project conflict intervals. When deadlines and resource availability are tightly constrained, variations in decision-makers' risk preferences have a more pronounced impact on changes in the sum of project conflict intervals, especially in scenarios where decision-makers exhibit risk-averse preference. Additionally, when decision-makers hold risk-optimistic preferences, an increase in deadlines has a greater influence on the sum of project conflict intervals than an increase in resource availability.
    This research incorporates the risk preference factor of decision-makers into the fuzzy robust value project scheduling approach, resulting in an enhanced understanding and control of project execution. As a future direction, it is worth exploring different reactive scheduling strategies of decision-makers under risk preferences, which could enable finer project control and management before and during project execution. This would further contribute to the optimization of project outcomes in uncertain and complex environments.
    Optimization Method for Power-changing AGV Scheduling of Automatic Terminal Based on Heuristic Rules
    LI Linman, LI Yuqing, WANG Mengya, LIU Ran, PAN Ershun
    2023, 32(10):  9-15.  DOI: 10.12005/orms.2023.0312
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    As the main equipment for the horizontal transportation of containers in automated terminals, the Automated Guided Vehicle's (AGV) operational efficiency will directly affect the overall efficiency of the terminal. Therefore, the scheduling problem of AGV has gradually become one of the research hotspots of terminal optimization problems. At present, the research on the AGV scheduling problem in automated terminals lacks consideration of the charging or battery swapping process, and few scheduling decisions are made in the synchronous loading and unloading operation mode.
    Given the operation plan of the quay crane and yard crane, this paper considers the characteristics of synchronous loading and unloading operation mode and generates the AGV schedules to realize the joint decision of its container operation sequence and battery swapping time. The AGV scheduling method proposed in this paper has the following two purposes: One is to maximize the operational efficiency of the terminal, that is, to reduce the waiting time and delay time of container tasks; The other is to minimize the energy consumption of AGV, that is, to reduce the proportion of no-load and waiting time of AGV.
    Therefore, this paper takes the minimization of total time cost as the scheduling optimization goal, and comprehensively considers four specific indicators such as no-load time, AGV waiting time, task waiting time, and shore delay time to balance AGV energy consumption and the overall efficiency of the terminal. Aiming at the above joint decision-making problem of AGV operation and battery swapping, an integer programming model is established. According to the characteristics of synchronous loading and unloading operation mode, a heuristic rule based on “task relative priority” is designed. At the same time, in order to reduce the mutual waiting time between AGV and task, a scheduling rule of “earliest available time” is introduced, and the node transfer rule and pheromone update process of the ant colony algorithm are improved accordingly. In order to verify the effectiveness of the proposed model and method, a numerical example is designed based on the data of the fourth phase of Yangshan Port, and different rules and methods are compared and analyzed. The instance analysis results show that in the synchronous loading and unloading mode of the automated terminal, the “relative priority of tasks” scheduling rule proposed in this paper reduces the idle time of AGVs, improves the utilization rate, and reduces energy consumption. At the same time, the waiting time between AGV and tasks is also reduced, and the satisfaction rate of quay cranes and yard cranes is increased, which improves the overall operation efficiency of the automated terminal. The improved ant colony algorithm can also obtain better solutions and improve the search efficiency of the algorithm while ensuring the convergence speed. In addition, the proposed scheduling method can be further extended to other application scenarios of battery-swapping AGVs.
    However, there are still some shortcomings in this paper. The model allocates container tasks under a static environment and does not consider the dynamic changes and uncertain factors of the actual production environment, such as the random arrival of tasks. How to take the uncertainties into account in the AGV scheduling process to generate a robust schedule to make a better response in dynamic environments will be a future research direction.
    Alternating Offers Bargaining with Random Proposers and Loss Aversion
    FENG Zhongwei, LIU Yuanwei, TAN Chunqiao
    2023, 32(10):  16-22.  DOI: 10.12005/orms.2023.0313
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    In a real negotiation, the bargaining power of the enterprise has an important impact on the negotiation result. For example, Wal-Mart and Carrefour, as the retail giants, tend to make the profits of their suppliers very low when negotiating with their suppliers, because Wal-Mart and Carrefour have a greater bargaining power. One of the characteristics of stochastic alternating-offer negotiation game is that the preference of players is independent of time. In reality, the “pie share” finally obtained by players depends not only on the offer at the current moment, but also on the offer at all previous moments, that is, the preference of players depends on the history of negotiation game.
    In addition, the economic and psychological experimental studies show that players often show loss aversion in the negotiation process. People are more motivated to minimize losses than maximize gains. Given the situations in which the psychological factors inherent in loss aversion play an important role in negotiation, a natural extension of the classical random alternating-offer negotiation game model is considered by incorporating the loss aversion behavior of players. In real negotiation, if the player's share in the current negotiation stage is lower than that in the previous negotiation stage, the participant may not accept the offer in the current negotiation stage. This is called loss-aversion phenomenon. Loss aversion was introduced by KAHNEMAN and TVERSKY. The simple and elegant version of SHALEV is adopted, where player's preference is characterized by a basic utility function, a reference point as well as a loss aversion coefficient. Therefore, this paper will explore the influence of loss aversion behavior of players on random alternating-offer negotiation game, in which the reference point of player is equal to the highest offer rejected by opponents in the past negotiation stage.
    In view of the fact that the bargaining power of enterprises has an important influence on the negotiation results in the negotiation of practical problems, in order to make the model more reasonable and make its conclusion more scientific, this paper considers random alternating-offer negotiation game with loss aversion by incorporating player's bargaining power, where the probability of making proposals in each round of negotiations reflects the bargaining power of a player and the initial reference point is not equal to zero. A random alternating-offer negotiation game with loss aversion is proposed. Different from the classical stochastic alternating-offer negotiation game model, our work incorporates players' loss aversion behavior into the stochastic alternating-offer negotiation game model. Furthermore, a Markov equilibrium is constructed, and the existence and uniqueness of Markov equilibrium are proven. This paper analyzes the influence of loss aversion and bargaining power on Markov equilibrium, discusses the convergence of Markov equilibrium when the probability of negotiation breakdown tends to zero.
    This paper explores the influence of loss aversion on two-player stochastic alternating-offer negotiation game. We construct Markov equilibrium and show its uniqueness based on the assumptions of immediate acceptance of equilibrium offers, indifference between accepting and rejecting equilibrium offers, and strategies depending only on the current reference points. The main results of this study include the following points: First, Markov equilibrium strategy is unique, and the players' strategy only depends on the current reference point. Second, the players are hurt by their own loss aversion behavior and benefit from the loss aversion behavior of their opponents. Third, when the probability of negotiation breakdown tends to 1, although the loss aversion level of a player is higher than that of the opponent, this player can still get more than half of the share as long as the bargaining power in the negotiation process is high enough.
    Speculation in Epidemic Prevention, Long-term Efficient Supervision, and Conformity Preference: Evolutionary Game Modeling and Analysis
    ZHANG Dingning, GUO Peng
    2023, 32(10):  23-30.  DOI: 10.12005/orms.2023.0314
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    During the regular control of the epidemic, regional and aggregated epidemics with airports, ports and scenic restaurants as the source have emerged. This indicates that there are difficulties in implementing epidemic prevention at the enterprise level, among which epidemic prevention speculation is an important reason. Theoretical and practical experience proves that effective government regulation can reduce the probability of corporate speculation, but the effectiveness of regulation is affected by a variety of factors such as regulatory approach and benefits. Long-term effective regulation requires flexible selection of efficient regulatory approaches according to environmental changes, which manifests as behavioral interactions between firms and regulatory groups. Moreover, empirical studies point out the prevalence of conformity behavior in public crisis response, which manifests as behavioral interactions within the respective groups of enterprises or regulators. This paper integrates the perspective of intra-group and inter-group behavioral interactions and considers conformity preferences to study the problem of corporate anti-speculation and government regulatory approach selection. It remedies the shortcomings of existing studies in analyzing this issue from a single perspective and provides a basis for relevant management practices.
    The article uses the evolutionary game approach to analyze the problem of corporate epidemic prevention speculation and government regulation choice in the process of normalized epidemic prevention, and introduces a conformity utility function to improve the game benefit matrix. It is assumed that there is a conformity preference in the process of both corporate epidemic prevention and government regulation strategy selection, and the strategy value includes two parts: Gain utility and herding utility. According to the results of evolutionary stability analysis, five critical value functions are proposed to analyze the role and conditions of the influence of revenue and strategy factors on the evolution of both parties' behaviors under the interaction of situational factors.
    The study results show that a) the conformity preference of corporate and government could promote the impact of initial strategies of both sides on speculation in epidemic prevention, and b)the decrease of corporate conformity preference or the aggravation of epidemic severity could promote the impact of epidemic prevention cost differential and speculation fines and epidemic prevention losses differential on speculation. When the above conditions are met, enterprises' speculation in epidemic prevention could be curbed by raising the initial proportion of enterprises with strict prevention strategies, reducing the epidemic prevention cost differential, and raising speculation fines or epidemic prevention losses differential. In that case, “result-based regulation” is the efficient regulation method. It is also found that increasing the initial proportion of “process-based regulation” could curb corporate speculative behavior and became the efficient regulatory way.
    The article has enriched the research perspective of analyzing the problem of corporate speculation and government regulation, but there are some limitations. In-depth research can be conducted in the future from the following aspects. Firstly, this study is theoretical in nature and lacks empirical confirmation. In the future, the findings of this study can be empirically tested by collecting and organizing relevant data. Secondly, the structure of group networks and relationship boundaries are not considered in the construction of the conformity utility model, and the social network modeling technique can be used to optimize the conformity preference utility model in the future.
    Utilizing Smoothing Modified Hestenes-Stiefel Conjugate Gradient Method to Solve Multi-person Noncooperative Games Problem
    LYU Shichun, DU Shouqiang
    2023, 32(10):  31-36.  DOI: 10.12005/orms.2023.0315
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    Game theory is an important research branch of operations research. It can also be seen as a mathematical optimization method for solving the optimization problem of optimal strategies corresponding to multiple individuals or groups under certain constraints. Game theory currently has a wide application background in many fields such as political economy, social management science, and national defense and military. In its application, it can be divided into cooperative game problems and noncooperative game problems based on whether the players cooperate or not. The noncooperative game problem studies how people utilize the optimal strategy to maximize their benefits in a situation where interests are mutually constrained. The Nash equilibrium theory has important applications in noncooperative game problems. Nash equilibrium indicates that each participant has a finite number of strategies and allows for mixed strategies, and the Nash equilibrium point must exist. The Nash equilibrium problem of noncooperative games has broad application prospects in the current information age. In the fields of artificial intelligence and new generation mobile communication technology, Nash equilibrium problems based on large-scale intelligence have been extensively proposed, and the research on noncooperative game problem is of great significance. Complementary problems are also a kind of optimization problems with a wide range of mathematical and operational research applications. The theories and methods of complementary problems are widely applied to various related fields, such as economic equilibrium problems, optimal control problems and related field. With the arrival of the big data era, tensor, as high-dimensional arrays, is used to expand the high-dimensional of matrix. In recent years, tensors have been widely used in fields such as multidimensional image processing and complex data analysis. As combining research of complementary and tensor, the research on tensor complementarity problem has developed rapidly. And the concepts of tensor eigenvalue complementarity problem and stochastic tensor complementarity problem have been proposed. The research on tensor complementarity problem has made significant progress in terms of solution set properties and error bound analysis. The proposal of various structural tensors has laid a theoretical foundation for the study of tensor complementarity problem in game problem and sparse solution problem. Conjugate gradient method, as an important optimization method, has the characteristics of simple structure, small computational storage, and global convergence. Since it was accepted, it has been widely applied in solving large-scale equations, large-scale unconstrained optimization problems, and other related optimization problems. In recent years, the application of first-order methods with low computational complexity, fast solving, and moderate accuracy in solving machine learning has become increasingly widespread. As an important class of first-order methods, conjugate gradient methods will attract widespread research attention again.
    In this paper, a smoothing modified Hestenes-Stiefel(HS) conjugate gradient method is proposed to solve the multi-person noncooperative games problem. The general model of multi-person noncooperative game is transformed into a tensor complementarity problem, further into a non-smooth equation system by using complementarity function, and then smoothed. Finally, it is equivalent to an unconstrained optimization problem. The proposed method can randomly select initial points, and has the characteristics of high stability and small storage, making it an effective method for solving non-cooperative game problems with multiple players. At the end of the paper, numerical examples and conclusions are presented, and numerical results of the effectiveness for the proposed method are presented in the numerical examples section.
    Evolutionary Game Research on Collaborative Innovation among Local Government, Rare Earth Enterprises and New Energy Enterprises
    JIA Yanglei, XU Ligang, ZHOU Yiting
    2023, 32(10):  37-42.  DOI: 10.12005/orms.2023.0316
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    Due to the important correlation between rare earths and new energy technology products such as wind turbines, new energy drive motors, and nickel hydrogen batteries, in recent years, local governments in China have built collaborative innovation platforms, developed a series of incentive industrial development policies such as financial subsidies and tax incentives, to promote rare earth industry and new energy industry to strengthen resources sharing and strive to break through the bottlenecks of industrial technology. However, there are some drawbacks in the mechanism of collaborative innovation of rare earth industry, new energy industry that is led by local government, such as the weakened effect of local government leading function, the low motivation and efficiency of industries which participate in it. According to these shortages, the tripartite evolutionary game model about collaboration innovation, guided by local government, and led by rare earth enterprises and new energy enterprises, is constructed. In order to figure out the game evolution strategies of local government, rare earth enterprise and new energy enterprise in different situations, the strategy choices among the three parties during the collaborative innovation process are analyzed.
    Providing the collaboration innovation center constructed by three parties as a case, where the Jiangxi Provincial Government and Ganzhou Municipal Government are the government side, Jiangxi Jinli Permanent Magnet Technology Co., Ltd. (hereinafter referred to as “Jinli Permanent Magnet”) is the rare earth enterprise side, and Xinjiang Jinfeng Technology Co., Ltd. (hereinafter referred to as “Jinfeng Technology”) is the new energy enterprise side, the factors that influence the strategy choices of their collaboration are studied by simulation. In this article, the local government data is obtained through relevant policies and documents, and the research and development costs and tax refund data of Jinli Permanent Magnet and Jinfeng Technology are obtained from the annual reports of listed companies on CNINFO (www.cninfo.com.cn). The paper analyzes the impact of the initial willingness of participating entities, local government subsidies, regulatory efforts, and losses on the evolution results using Matlab R2018b software.
    Based on the above analysis, the following conclusions can be drawn: (1)Local governments decide whether rare earth enterprises and new energy enterprises choose to participate in collaborative innovation. When local governments show high willingness to actively implement policies, regardless of whether one of the rare earth enterprises or new energy enterprises has a high willingness, the other party will choose to participate. (2)The willingness and evolutionary path of rare earth enterprises and new energy enterprises to participate are not affected by each other's initial intentions. Compared to rare earth enterprises, the decrease in participation willingness of new energy enterprises has a more significant impact on the speed of local governments' evolution towards active promotion. (3)When the subsidies provided by local governments for collaborative innovation are within a critical range, the amount of subsidies is proportional to the rate at which rare earth enterprises and new energy enterprises evolve towards participation. Local governments, rare earth enterprises, and new energy enterprises are stable in their ideal strategies. When the critical value is exceeded, local governments, rare earth enterprises, and new energy enterprises do not meet the stability conditions. (4)High intensity supervision and evaluation by local governments, as well as fines for violations, are effective strategies to promote the participation of rare earth and new energy enterprises. The losses caused by the passive implementation of local governments are important factors that hinder their active implementation.
    The results reveal that: (1)The willingness of rare earth enterprises and new energy enterprises to participate in collaborative innovation is not affected by each other's initial willingness, but accelerated with the improvement of local governments' willingness to actively implement policies. (2)The incentive and supervision intensity of local governments is positively correlated to the willingness of rare earth enterprises and new energy enterprises to participate in collaborative innovation.(3)The greater the cost of local government laziness and inaction, the more inclined it is to choose the “active implementation” strategy.
    This paper conducts simulations on local governments and enterprises based on evolutionary game theory, and draw some important conclusions. However, due to the limitations of survey objects and conditions, the assignment of payment matrix parameters only reflects the typical situation of enterprises, lacking a large amount of data support. There is a certain gap between our work and the reality.
    Research on Technology Collaborative Innovation Strategy between Internet Enterprises and New Energy Automobile Enterprises Based on Differential Game
    ZHANG Tao, TANG Xi, WU Junmin, MAO Xiangyu, WEI Xiaozhuo
    2023, 32(10):  43-49.  DOI: 10.12005/orms.2023.0317
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    Green and sustainable development has become the theme of global economic development, and the State Council promulgates products “Made in China 2025”, which clearly positions “green development” and “innovation-driven” as the basic policy for the future development of China's manufacturing industry.As an important field of China's green industry development, the new energy vehicles (NEVs) industry is also developing rapidly in line with the trend of the times.In a new scientific and technological change in the background, the integration of Internet technology with NEVs technology, and automobile manufacturing with automobile “intelligence” to promote NEVs industry to complete the transformation and upgrading has become an inevitable trend. Due to the difficulty of automotive smart chip technology research and development and rapid replacement, the existing cooperation model cannot promote the NEVs enterprises and Internet companies to carry out optimal cooperation. Therefore, it is urgent and important to study the optimal cooperation mechanism of technological co-innovation between Internet enterprises and NEVs enterprises to enhance the international core competitiveness of China's NEVs and establish a latecomer's advantage. Although existing studies have carried out in-depth research on R&D and innovation in the NEVs industry, the new issue of collaborative R&D and innovation between Internet enterprises and NEVs enterprises has rarely been addressed, and the coordination of interests among the main subjects of collaborative innovation has been neglected.
    Therefore, aiming at the problem of technology collaborative innovation between Internet enterprises and NEVs enterprises, this paper takes Internet enterprises and NEVs enterprises as the research object, and constructs a differential game model. The HJB equation is used to analyze the optimal R&D efforts of Internet enterprises and NEVs enterprises, the optimal technology collaborative innovation subsidies of Internet enterprises to NEVs enterprises and the optimal cooperation mode of the two enterprises under three cooperative technology innovation game situations. Through the comparative analysis of the three game conclusions, it is found that: (1)The subsidies of Internet enterprises to NEVs enterprises are negatively correlated with the income distribution coefficient. (2)The research and development investment of NEVs enterprises is more effective than that of Internet enterprises in improving the overall revenue. (3)Efforts made by Internet enterprises and NEVs enterprises for technological breakthroughs of NEVs can maximize the overall benefits of the R&D cooperation between the two sides. (4)In Stackelberg master-slave mode, Internet companies and NEVs enterprises' respective R&D efforts, R&D revenues and total R&D revenues are superior to those in Nash non-cooperation mode, reaching Pareto equilibrium. (5)In the collaborative cooperation mode, Internet enterprises and NEVs enterprises are the best among the three modes in terms of their respective R&D efforts, R&D earnings and total R&D earnings, and a perfect Pareto equilibrium is achieved.
    Finally, this paper verifies the correctness of the theoretical results through the analysis of numerical examples and puts forward corresponding suggestions based on the conclusions, with a view to providing references for Chinese government to promote the synergistic technological cooperation between NEVs enterprises and Internet enterprises. Specifically, firstly, different modes of co-innovation cooperation should be vigorously carried out; Secondly, Internet enterprises should shoulder more responsibility as well as share the cost of co-innovation R&D; Then, basic R&D investment in NEVs should be increased; And lastly, deeper technological co-innovation cooperation should be carried out.
    Research on Supply Strategy Based on Product Substitution and Emergency Supply
    HOU Xinru, XU Xinsheng, GUO Libin
    2023, 32(10):  50-56.  DOI: 10.12005/orms.2023.0318
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    In a traditional supply chain, each member makes inventory decisions based on maximizing its individual profit, resulting in ordering quantities amplified from retailers, distributors, and suppliers, generating the bullwhip effect and causing supply chain costs to surge. In order to improve customer service and reduce the bullwhip effect, the vendor management inventory (VMI) model has emerged. The core idea of the VMI model is that the supplier sets the retailer's inventory level by sharing the retailer's current inventory information. This model greatly reduces the waste of resources caused by the uncertainty of independent forecasts of both supply and demand and improves the operational efficiency of the supply chain. It is important to note that even under the VMI model, decision-making based on a stochastic inventory system still faces many risks. Although some companies would adopt the sales season emergency supply (replenishment) behavior to avoid the risk of stock-outs, they still cannot completely avoid the decision-making risk of stochastic demand. In view of this, this paper introduces the VMI model into the stochastic demand supply chain system with product substitution andemergency supply. The impact of product substitution and emergency supply on supply strategy and supply chain performance under the VMI model is investigated. And based on the fact that two suppliers can supply urgently, we consider the expansion scenario of the risk-averse situation of two suppliers. Based on our theoretical analysis, we provide managerial insights into inventory management practices in enterprises.
    Specifically, this paper considers a two-echelon supply chain system consisting of a retailer and two suppliers. For this system, under stochastic demand and the VMI mode, the retailer sells two substitute products with similar functions, and the two products are provided by two suppliers, respectively. Prior to the start of the selling season, the two suppliers determine their respective supply quantities to the retailer. At the beginning of the season, market demand is clear, and if a customer's preferred product is out of stock, some customers choose not to replace it, while others choose a substitute. At the end of the selling season, the suppliers dispose of the unsold products and receive clearance proceeds. For this system, the scenario of no product substitution is considered first, and then the scenarios of product substitution and emergency supply are considered separately. Through the cost-benefit analysis, we provide the optimal supply strategy to each supplier under the above scenarios. Moreover, to make our research more practical, we consider an extension scenario in which both risk-averse suppliers can provide emergency supply. Then, we analyze the optimal supply strategy and profit of each risk-averse supplier.
    Our research shows that both supply quantity and total product sales increase under product substitution compared to the no-product-substitution scenario. In addition, product substitution results in a win-win situation for both suppliers and retailer, with the effect increasing as the substitution rate increases. When only one supplier is available for emergency supply, the supplier with emergency supply capability benefits the most and achieves a win-win situation with the retailer. At the same time, the supplier with emergency supply capability does not blindly increase supply quantity before the start of the selling season, which greatly avoids the loss of oversupply due to excessive initial inventory. When both suppliers are available for emergency supply, product stock-outs will be effectively avoided, and retailer profit will be maximized. When both risk-averse suppliers can provide emergency supply, the risk faced by the supplier mainly will come from the oversupply of the product. In order to effectively avoid the risk of oversupply caused by the fluctuation of market demand, the supplier's optimal supply decreases with the increase in risk-aversion degree. However, for risk-averse suppliers, risk minimization and expected profit maximization are conflicting objectives, and they should balance the risk and profit when formulating supply strategies to avoid losing sight of the other.
    Nevertheless, this paper still has some limitations. Only two product substitutions in the current market under the VMI model are examined in this paper. Supplier supply strategies with multiple products and the presence of adjacent market influences will be an interesting research direction in the future. In addition, this paper is only based on the conventional VMI model, and the introduction of supply chain disruption, revenue sharing contract or cost sharing contract into the VMI model deserves further research.
    Two-sided Matching Decision-making Method with Hesitant Fuzzy Element Preference Based on TOPSIS
    DENG Zhibin, YUE Qi
    2023, 32(10):  57-62.  DOI: 10.12005/orms.2023.0319
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    The theory and method of two-sided matching has discovered extensive utilization across diverse sectors and daily existence, yielding significant economic and societal worth. It expedites the procedure of pairing two subjects contingent upon their inclinations, be it job seekers and employers, students and universities, or buyers and sellers. Nevertheless, the decision-making milieu within authentic two-sided matching procedures is frequently intricate, ensuing in the absence of preference data from both sides. Additionally, the inherent indeterminacy of decision-making augments the ambiguity of the furnished preference information.
    To tackle these practical scenarios in the realm of two-sided matching research, a proposition novel two-sided matching decision-making method on hesitant fuzzy element information is proposed in this paper. Primarily, the problem of one-to-one two-sided matching based on hesitant fuzzy elements is expounded, thus enabling a more adaptable representation of preferences. Through these hesitant fuzzy elements, the uncertainty and ambiguity inherent in decision-making are aptly captured, allowing decision-makers to convey their preferences as a spectrum of possibilities rather than rigid values. Subsequently, the technique known as Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is employed to extract the satisfaction levels of decision-makers. Secondly, the TOPSIS method is used to calculate subject satisfaction. By normalizing the hesitant fuzzy elements information provided by two-sided subjects, the distance between each alternative solution and the ideal solution is calculated, and based on this, the subject satisfaction is obtained. The applied satisfaction calculation method effectively enhances the description of two-sided subject preferences. By normalizing the hesitant fuzzy element information provided by both parties and determining the relative proximity of each alternative to the ideal solution, this method enhances the evaluation of preferences, accounting for multiple criteria and the accompanying uncertainty. Moreover, this approach takes into consideration the constraints of one-to-one matching and establishes a multi-objective programming model for two-sided matching. This model incorporates the satisfaction levels of decision-makers, the matching constraints, and the imperative of equity, all while determining the optimal solution to the two-sided matching conundrum. Recognizing the relative significance of diverse criteria in the process of matching decision-making, a linear weighted method is employed to surmount the model. To assert the dependability and soundness of the proposed approach, a case study on the pairing of personnel with jobs has been conducted.
    The research findings elucidate that the tool for representational rendering of fuzzy information, comprised of hesitant fuzzy elements, proficiently articulates the information for preference evaluation furnished by two-sided subjects amidst intricate circumstances. The method put forth triumphantly resolves the quandary of decision-making in two-sided matching within an environment pervaded by hesitant fuzzy preferences. The outcome of comparative analysis reveals that the amalgamation of a positive ideal solution and a negative ideal solution effectively upholds the equity of the resultant matching solution and facilitates the formation of gratifying matching resolutions. By taking into consideration both fairness and diversification of information, the proposed approach to decision-making augments the perks of two-sided matching platforms and enhances matching efficacy.
    This research enhances the already extensive corpus of literature on decision-making methodologies for two-sided matching within intricate contexts. The proposed approach to decision-making takes into account the equitability of both subjects, the variegation of information, and the indeterminacy of preferences, thereby furnishing a foundation for bolstering the advantages of two-sided matching platforms and refining matching efficiency. In addition, this research effectively advances the application understanding of the theoretical framework of fuzzy-based two-sided matching in decision-making processes. It also holds potential practical value across multiple industries, including job recruitment, university admissions, and online marketplace platforms.
    Risk Early Warning of Sea Lanes Based on Dynamic Bayesian Network
    JIANG Meizhi, LYU Jing, WANG Shuang
    2023, 32(10):  63-68.  DOI: 10.12005/orms.2023.0320
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    Sea lanes is an important carrier of cargo transport, and its safety is related to the development of China's maritime trade. With the continuous development of ocean shipping transportation, its risk level is constantly increasing. Risk early warning is an effective way to reduce the probability of emergency. In order to ensure the safety of sea lanes, it is of great significance to study the risk early warning of sea passage. The existing research on the risk of sea lanes mainly includes risk analysis, evaluation, management and emergency response, which is little on risk early warning. Therefore, this paper constructs a risk early warning model of sea lanes based on DBN to provide a decision reference for ensuring the safety of sea transport and improving the risk early warning and emergency response capability of sea lanes.
    BN is one of the methods of expression and reasoning of uncertain knowledge in the field of artificial intelligence. DBN introduces time variable on the basis of BN, which can carry out dynamic analysis and early warning of emergencies. EM algorithm and Viterbi algorithm are used to learn the parameters of DBN model and predict the risk of sea lanes respectively. EM algorithm is an iterative algorithm, mainly used to calculate the mode or maximum likelihood estimation of the posterior distribution, and is widely used in the so-called incomplete data statistical inference problem such as missing data, truncated data, cluster data, data with unwelcome parameters. EM algorithm is simple and stable, and can find the optimal convergence value very reliably. Viterbi algorithm is a dynamic programming algorithm, which is used to find the hidden state sequence that is most likely to produce the observed event sequence, and is widely used in dynamic prediction and programming.
    A risk early warning model based on DBN is proposed to predict the risk of sea lanes. The factors are identified according to the statistics of historical emergencies. The initial network structure of DBN is worked out based on the risk characteristics of sea lanes. The historical data of emergencies happening in Indian Ocean from 2008 to 2017 is used for warning the risk of sea lanes. The case study data in this paper come from the risk events in the Indian Ocean, and the observation data come from wind speed from Remote Sensing Systems, sea weather forecast, ship traffic statistics, military exercises, and reports published by the Labor Market Association.
    A comparative analysis of DBN model using BN model and Markov model is conducted to verify the effectiveness of the proposed model. F-measure, accuracy, precision and recall are used as indicators to evaluate the accuracy of risk warning results. The sensitivity analysis is conducted to determine the sensitivity between sea passage risks and influencing factors.
    The results show that the risk of sea lanes is within a small range but has a downward trend overall. Compared with the BN and Markov models, the results of the DBN model have higher accuracy, which is 9.3% and 9.2% higher than that of the BN and Markov models, respectively. The risk early model established in this paper can effectively alert the risk of sea lanes, identify the key risk factors, and provide decision-making references for improving the risk early warning and emergency management capabilities of sea lanes.
    This study applies the DBN-based model to predict the risk of sea lanes. The expansion of DBN in risk early warning and the applicability of further development algorithms to other types of early warning research can be studied in the future. Future works can also be extended in applying the DBN-based model to other safety management problems.
    Optimizing Emergency Material Reserve Considering Supplier Participation and Social Environment
    XIANG Yin
    2023, 32(10):  69-75.  DOI: 10.12005/orms.2023.0321
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    Maintaining a reasonable reserve of emergency materials in advance is an effective way in response to sudden disasters. But in reality, it is difficult to meet the surge demand in post disaster period only by relying on the government's reserve materials, and suppliers are required to join the emergency material reserve. However, due to the differences of social environment (e.g.disaster probability, social vulnerability, population density) among regions, the emergency material reserves requirements are also different among regions. For example: i)Material reserves should prioritize covering areas with a high probability of disaster occurrence; ii)Due to the difference of social vulnerability in different regions under the same disaster level, emergency material reserves should give priority to cover areas with low vulnerability; iii)The number of people affected by the same level of disaster varies, which requires that population density also be taken into account when preparing emergency supplies. Therefore, it is valuable to study the government-enterprises joint reservation of emergency relief from the perspective of social environment.
    In recent years, disaster relief related problems have received extensive attention and in-depth research from both domestic and foreign scholar. The existing literature basically takes the government as the decision maker and applies the operational research method to optimize the facility location, reserve quantity and distribution plan of emergency materials. Most of these literatures are based on P-median, P-center, Set covering, location-allocation, location-routing and other classical models, starting from the simplest static problems and further expanding to stochastic and dynamic problems, which provide theoretical reference for this paper. However,there are still some limitations: i)Existing studies mainly consider the manageable factors such as cost, fund, demand and capacity, while ignoring the differences of social environment; ii)Existing studies only focus on individual dimensions of the demand characteristics, but are lack of the comprehensive consideration of demand characteristics including “diversity”, “modularity”, “timeliness difference” and “fairness” in disaster relief.
    Therefore, different from existing papers, we propose a novel bi-objective mixed integer model which not only takes account the social environment(disaster occurrence probability, social vulnerability, population density), but also comprehensively considers the demand characteristics including modularity, timeliness, and fairness requirements of multi-material reserves. The objective function of the model is to minimize disaster risk and system cost at the same time. The variables to be determined include the location plan of emergency facilities, the selection plan of suppliers, the quantity of material reserve, and the distribution plan of emergency materials after disaster. To solve the bi-objective model, a ε-constraint method is applied to get the Pareto solution set.
    Finally, we apply our model in a real-case study. A simulation analysis is carried out on the background of the Sichuan earthquake disaster, and the results show: i)The optimal decision of relief allocation is influenced by both social environmental factors and storage requirements; ii)The two goals of risk and cost are contradictory, so it is necessary to set a reasonable budget to achieve maximum emergency efficiency; iii)The marginal utility of unit emergency material reserve cost increases with the increase of disaster level; iv)Increasing the number of suppliers participating in the relief storage process can not only reduce disaster risks, but also reduce costs; v)Although increasing fairness requirements will lead to a decline in emergency reserve efficiency, stronger fairness requirements can reduce the fluctuation range of costs and risk targets, and have higher robustness.
    Research on Pricing Decisions of Dual-channel Supply Chain Considering Risk Aversion and Free-riding
    WANG Heping, YAN Xiaochen, ZHAO Dan, LI Yan
    2023, 32(10):  76-82.  DOI: 10.12005/orms.2023.0322
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    The COVID-19 pandemic has had a significant impact on the retail industry, accelerating changes in retail channel selection and consumer behavior. As a result, more and more manufacturers are turning to online platforms and online retailers to expand their market share. This has led to the development of a dual channel sales model that includes both online and offline sales. Offline sales refer to traditional retailers purchasing products from manufacturers and selling them in physical stores. In contrast, online sales have two channels: Direct sales and distribution channels. Direct sales refer to manufacturers setting up flagship stores on online sales platforms where they are responsible for promoting and selling products to attract consumers. On the other hand, distribution channels refer to online retailers purchasing products directly from manufacturers and engaging in self-operated sales through online sales platforms. The dual channel sales model is beneficial as it can better meet customers' differentiated needs. In addition to having a preference for products, consumers may also exhibit purchasing behavior that favors different channels. The smooth flow of information has also led some consumers to engage in “free-riding” behavior by purchasing products online after experiencing them for free in offline retail stores. In addition, consumer behavior under the dual channel sales model leads to increased uncertainty in demand, which may result in risk aversion behavior among traditional retailers. This can have a significant impact on pricing decisions, requiring consideration of inter-channel competition and consumer personalized channel selection behavior on demand.
    To address this issue, this paper uses the theory of dual channel supply chain, mean-variance theory, Stackelberg model and other related theories to build a dual channel supply chain model with manufacturers as leaders and retailers as followers. The model examines the impact of “free-riding” behavior and consumer retail preferences on pricing decisions under the dual channel sales model. The results show that: First, regardless of the online direct sales or online distribution model, when manufacturers learn that traditional retailers have risk aversion behavior and take price reduction measures, they will try to maximize their own profits by increasing wholesale prices. Second, the optimal price for manufacturers' online retail is not affected by traditional retailers' risk aversion behavior in the online direct sales model. However, in the online distribution model, when the cross price elasticity coefficient exceeds a certain threshold, it will cause online retailers to set lower prices to attract customers and ensure market share. Third, the study finds a significant synergistic effect between consumer retail preferences and market demand on the optimal price of retailers in both the online direct sales and online distribution sales models. This means that traditional retailers should actively expand market demand to mitigate the impact of risk aversion behavior on their own profits. Finally, government subsidies can help alleviate the losses caused by traditional retailers' risk aversion behavior and the impact of opening online retail channels on the traditional retail industry.
    In addition, future research will also consider manufacturers' risk aversion behavior to study their cross effects. Overall, this study provides valuable insights into pricing decisions made by manufacturers and retailers under the dual channel sales model. It will contribute to economic recovery in the post-pandemic era and provide intellectual support for pricing decisions made by manufacturers and retailers.
    Discussions on the Simplex Method Based on Replacing Cost Coefficients with Reduced Costs
    HAN Weiyi, QIAO Lixin, LIU Songsong
    2023, 32(10):  83-87.  DOI: 10.12005/orms.2023.0323
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    Linear programming is a basic research field of operations research. Since 1947, numerous algorithms have been proposed, which are mainly divided into three categories: Simplex method, ellipsoid method and interior point algorithm. In view of the inherent warm start technique of simplex algorithm and its natural advantages in solving integer programming, it still has competitive advantages compared to the interior point algorithm. This shows that the improved simplex algorithm still has important theoretical and practical value. At present, simplex method mainly has three variants, namely, the primal simplex algorithm, the dual simplex method and the primal-dual simplex method. Compared with the traditional simplex algorithm, the newly simplex method based on replacing cost coefficients with reduced costs neither changes the computed results nor the number of iterations, but it improves the efficiency of computing reduced costs. In fact,as an improvement of simplex methods, this method doesn't change existing pivoting rules, which is its prominent feature. It can also make some properties and characteristics of the simplex algorithm become obvious. Furthermore, the new algorithm helps to develop or improve algorithms for some operations research problems, and it can make the computational process simple.
    In the paper, the new algorithm will further be investigated. Firstly, the new algorithm can not only reveal the inner relationship between primal models and dual models more deeply, but also provide intuitive proof and explanation for the boundedness property of dual theory of linear programming, which is often proved by contradiction. Secondly, a new column elimination rule is proposed. For a variable, if its reduced cost is negative in the k-th simplex tableau and its column vector is non-negative in the r-th simplex tableau, we can eliminate the column of this variable from the model which make the new model with the column deleted have the same optimal solution as the original model. It can effectively reduce the computational scale of linear programming. Thirdly, we can apply the above column elimination technique to improve the column generation method to solve effectively large-scale linear programming models. The new column generation method is very suitable for linear programming problems where most column vectors are nonnegative. Our experiments show that the algorithm only costs three iterations to eliminate approximately 75% variables from the original linear programming model for 100 random generated models with 20 basic variables and 80 non basic variables. Finally, the new algorithm can also simplify the potential method of transportation simplex method and computational efficiency can always be doubled at least. In fact, transportation simplex method is known to be the most competitive algorithm for transportation problem in practice. The new potential method provides a new formula for computing reduced costs, in which the cost of variable is always replaced by the last iteration's reduced cost of variable. Generally, we still use the given costs to compute reduced costs of variables in the first iteration. It means that only one dual variable is nonzero in m+n dual variables, which help to explain why reduced costs of many variables don't change.
    In conclusion, as a variant, the simplex method based on replacing cost coefficients with reduced costs can not only directly improve the computational efficiency of the primal simplex method, dual simplex method, primal-dual simplex method and other simplex methods, but also it can improve goal simplex method, transportation simplex method, branch and bound method and other algorithms based on the simplex method. Therefore, the new method not only greatly enriches the theory of simplex method and dual theory in linear programming, but also improves the computational efficiency of simplex method. It should be pointed that the method helps to propose new pivoting rules for simplex method.
    Customer Behavior and Pricing Strategy in the Unobservable M/M/c Queue with Synchronous Multiple Vacations
    SUN Wei, XIE Xumeng, LI Shiyong
    2023, 32(10):  88-94.  DOI: 10.12005/orms.2023.0324
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    Due to the randomness of both the arrival intervals of customers and the service times of servers, queueing phenomena is inevitable in our daily life. When a customer arrives at a certain queueing system, he/she always estimates his/her personal expected residual utility according to the system information he/she gets first, and then decides whether to join the queue or not. Regardless of the visible queueing phenomena like going to the hospital for treatment, purchasing tickets at the train station and so on, or the invisible queueing phenomena like shopping online, consulting business by telephone and so on, there are always several servers in most queueing scenarios. Thus, the research on the balking behavior of customers in the multi-server queueing systems has important practical significance in improving service efficiency, reducing service cost and improving resource utilization and many other aspects.
    Considering two information levels: Nearly unobservable case and entirely unobservable case, we study the customers' balking behavior and the pricing strategy in an M/M/c queueing system with synchronous multiple vacations. Once the system is empty, all servers will enter the vacation state synchronously. After a vacation, if there is still no customer in the system, all servers will continue to the next vacation, otherwise they will start to work meanwhile. The nearly unobservable case means that the servers' state is disclosed to the customer but the queue length is not, and the entirely unobservable case means that customers don't know both the servers' state and the queue length. Based on the two information levels, we deduce the stationary distribution of the queue length and some performance indicators like the mean sojourn time of customers by using the quasi birth and death process theory and the matrix geometric method. Next, we obtain the customers' equilibrium balking strategy and socially optimal balking strategy by formulating the personal expected residual utility and the social welfare per unit time from the view of the individual optimization and the system optimization respectively, on which we set the pricing strategy for social welfare optimization. Finally, we numerically make sensitivity analysis of the equilibrium arrival rate,the optimal arrival rate, the optimal social welfare and the optimal price with respect to c, then observe the trend and their relationship as well as the influence of system information on customer behavior.
    As a result, we get the following conclusions. Firstly, regardless of the nearly unobservable case or the entirely unobservable case, the number of servers always has the positive influence on both the equilibrium arrival rate and the socially optimal arrival rate of customers, and the optimal behavior of customers in the entirely unobservable case is always the comprehensive reflection of that in the nearly unobservable case where the servers' state is on vacation and working. Next, the amount of system information held by customers has an impact on both the equilibrium behavior and the socially optimal behavior of them, but the information of the servers' state has more and more limited influence on the customers' behavior as the number of the servers increases. Besides, no matter what information level the system is at, there always exists inconsistence between the equilibrium and the socially optimal balking behaviors of customers, and their selfishness will make the system overcrowded. To regulate the customers' behavior, the pricing strategy can be made for the system, i.e., charging customers for optimizing social welfare. It's found that the service price always increases with the increase of the number of servers, but the increase rate slows down when the number of servers increases to a certain number, and eventually, the service price stabilizes. When the number of servers exceeds a certain threshold, the pricing strategy for the entirely unobservable case is consistent with that for the nearly unobservable case when the servers are working. Last but not least, it's advisable for the system manager to set the number of the servers when the service price basically tends to be steady, which can not only achieve the purpose of optimizing the social welfare, but also save the operating costs as much as possible.
    In this paper, we mainly analyze the customers' balking behavior and pricing strategy in an M/M/c queue with synchronous multiple vacations based on the nearly unobservable case and the entirely unobservable case. In the future, we can also consider introducing some threshold strategies like the N-policy into the multi-server queueing systems and analyze the customers' balking behavior and the pricing strategy in view of various information levels.
    Reconstruction of COVID-19 Epidemic Scenario: A Modified Model Based on Rolling Grey GM(1,1)
    ZHU Xiaoxiao, LIU Ming, CAO Jie
    2023, 32(10):  95-101.  DOI: 10.12005/orms.2023.0325
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    In the past 20 years, a series of major public health emergencies such as SARS(2003),H1N1(2009), MERS(2012), Ebola(2014), Zika(2016), and COVID-19(2019) have broken out in the world. These major public health emergencies have not only severely threatened human health and life safety but also dealt heavy blows to the global economy. Taking the COVID-19 pandemic as an example,General Secretary Xi Jinping emphasized that the COVID-19 pandemic is “the most serious global public health emergency since the end of World War II”. This epidemic is not just a test for any one country, but a massive trial for the whole world. As of January 15, 2022, the total number of confirmed COVID-19 infections worldwide had reached 324 421 646, with a cumulative death toll of 5 543 545.
    After the occurrence of a sudden public health event,it is vitally important to promptly grasp the epidemic's development pattern and accurately predict the spread of the epidemic, which is of significant reference value for emergency prevention and control of major epidemic outbreaks. Among them,infectious disease dynamics models, as the most effective means of epidemic spread evolution modeling,are significantly influenced by different prevention and control measures in their construction. However, this method requires high-quality parameter data, and any slight error may lead to a large discrepancy between the final prediction results and the actual data. On the other hand,the grey GM(1,1) model is an essential tool for modeling and predicting scenarios with minimal data and poor information. To fully utilize the advantages of both models and improve the fitting accuracy of the model, a combined optimization model is constructed by integrating them to predict the development trend of the epidemic.
    This paper takes the scenario reconstruction of the COVID-19 epidemic in Wuhan as an example. Firstly,considering the priority of new and old information,a rolling mechanism is adopted to dynamically update the initial values of data series,and a rolling grey GM(1,1) model is constructed for predicting the trend of the epidemic changes. Then,the SEIH1H2RD infectious disease dynamics model is modified by integrating the prediction results of the rolling grey GM(1,1) model. Notably,this model takes into full account many realistic influencing factors such as city lockdowns and the construction of emergency hospitals. Lastly,to verify the fitting effect of the modified model,a posterior difference test is used to analyze the fitting accuracy between the model fitting results and actual epidemic data. We also examine the influence of different rolling decision cycle values in the rolling grey GM(1,1) model on the model's fitting accuracy. Moreover,to fully demonstrate the corrective effect of the rolling grey GM(1,1) model on the infectious disease dynamics model,we apply different preference coefficients for quantitative analysis.
    The results of the numerical tests show that: 1)The infectious disease dynamics model,modified by the rolling grey GM(1,1) model proposed in this paper,performs well in both short-term and long-term modeling fitting. This model fully integrates the absolute advantage of the grey GM(1,1) model in short-term prediction and the astonishing effect of the infectious disease dynamics model in fitting the long-term development trend of the outbreak. It expands the application space of different models,promotes the cross-fusion of different models,and improves the fitting accuracy of a single model. 2)Although the rolling grey GM(1,1) model has some corrective effect on the infectious disease dynamics model,it is not the case that the larger the weight of the rolling grey GM(1,1) model,the better. There is a threshold effect in the weight distribution between the two.
    To facilitate the calculation,this paper only uses the equivalent interval value method to study the impact of different preference coefficient values on model performance. In the future,we will research introducing intelligent algorithms to determine the optimal value of preference coefficients,thereby making the prediction model have better adaptive performance.
    Pruning Approach to Neural Networks Based on Zero-norm Regularization
    LIU Zhi
    2023, 32(10):  102-107.  DOI: 10.12005/orms.2023.0326
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    Deep Neural Network (DNN) has become ubiquitous in our daily life ranging from autonomous driving to smart home. It has become an inevitable trend to introduce DNN model into mobile devices and embedded systems. The redundancy of parameters has always been the main reason for hindering neural network inference and making it difficult to deploy on mobile system.
    In recent years, academia and industry have proposed many methods for model compression, such as model compression, knowledge distillation, and network pruning. Neural network pruning, as an important means of network model compression, reduces network parameters by removing some neural connections, effectively overcoming the high computational cost and high memory resource proportion caused by neural network weight redundancy. Our method in this article is a further extension of the network pruning model and solving algorithm.
    In this work, we propose an effective pruning method for neural networks against the problem of high computational costs and considerable memory bandwidth caused by huge complexity and parameters redundancy of neural network model. This method improves the sparsity of model weights by introducing zero-norm regularized term into the neural network model, and compresses the model by deleting those zero weights. For the proposed zero-norm regularized neural network model, by establishing the global exact penalty for its equivalent MPEC form, we obtain an equivalent Lipschitz surrogate.
    Based on the equivalent local Lipschitz surrogate, considering that when the activation function is sigmod, the loss function of the final optimization model is a combination of smooth and non-smooth terms, and the smooth part can be solved through existing frameworks, while the non-smooth part has an exact expression, we design an proximal alternating direction multiplier method (P-ADMM) to solve the smooth loss model induced by sigmod activation function. Numerical experiments conducted for P-ADMM validate their efficiency. The tests for the MLP and LeNet-5 network respectively yield 97.43% and 99.50% sparsity without the loss of accuracy. The results of numerical experiment show that our method effectively reduces the complexity of the model, and has better sparse ratio compared with other pruning methods. Meanwhile, it has the advantages of convenient implementation and easy extension.
    This article proposes a (P-ADMM) method for solving the smooth loss network pruning model. For the highly non convexity of the neural network model, although the paper utilizes alternating solution and the computational graph framework to solve the model, the convergence speed of the algorithm is slow in the later stage. Therefore, one of the future research directions is whether to propose an acceleration strategy to improve the convergence rate of the algorithm, and whether to directly solve the non-convex and non-smooth model using gradient methods for backpropagation algorithms and computational graph frameworks. Another interesting research direction is how to design effective algorithms to find a solution when the smooth loss function is non smooth, and what convergence properties the algorithm possesses.
    A Rainbow Version of Ore Theorem
    GAO Liqing, WANG Jian
    2023, 32(10):  108-113.  DOI: 10.12005/orms.2023.0327
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    Let G1,G2,···,Gn be n graphs on the same vertex set V with |V|=n. If C is a cycle of length n such that each edge belongs to a different graph, then we call C a rainbow Hamilton cycle on {G1,G2,···,Gn}. Similarly, if P is a path of length n-1 such that each edge belongs to a different graph of G1,G2,···,Gn-1, then we call P a rainbow Hamilt on path on {G1,G2,···,Gn-1}. Recently, Joos and Kim have proved a rainbow version of Dirac theorem, i.e., if each of G1,G2,···,Gn has minimum degree at least n/2, then {G1,G2,···,Gn} contains a rainbow Hamilton cycle. In this paper, by the shifting method we show that if each of G1,G2,···,Gn has at least $\left(\begin{array}{c} n-1 \\ 2 \end{array}\right)+2$ edges, then {G1,G2,···,Gn} contains a rainbow Hamilton cycle. Moreover, if each of G1,G2,···,Gn-1 has at least $\left(\begin{array}{c} n-1 \\ 2 \end{array}\right)+1$ edges, then {G1,G2,···,Gn-1} contains a rainbow Hamilton path.
    The shifting operator is a powerful tool in extremal set theory, which was invented by Erdös, Ko and Rado and further developed by Frankl. The shifting operator can be applied to graphs and hypergraphs and preserve the number of edges. It is well known that the shifting operator cannot increase the matching number of graphs and hypergraphs. In the present paper, we show that if a graph system {G1,G2,···,Gn} does not contain a rainbow Hamilton cycle, then one can apply the shifting operator to G1,G2,···,Gn simultaneously without producing a rainbow Hamilton cycle. By applying the shifting operator to G1,G2,···,Gn repeatedly, eventually we shall obtain a sequence of shifted graphs G1,G2,···,Gn.
    For two pairs (x1,x2)and (y1,y2), define the shifted partial order<as: (x1,x2)<(y1,y2) if and only if either x1≤y1 and x2≤y2 or x1≤y2 and x2≤y1 hold. The shifted graphs have the following nice property: if x1x2 is an edge of G and G is shifted, then for any pair (x1,x2)<(y1,y2),y1y2 is also an edge of G. Let Hn,a,b be a graph with the vertex set {1,2,···,n} such that (i)the subgraph induced by {1,2,···,a} is a complete graph; (ii){a+1,a+2,···,n} forms an independent set; (iii)The neighbors of x are 1,2,···,b for each x in{a+1,a+2,···,n}. It is easy to see that Hn,a,b is a shifted graph. Moreover, Hn,a,b is non-Hamiltonian if n-a≥b and a≥b.
    By applying a technique developed by Akiyama and Frankl, we show that some Gi has to be a subgraph of Hn,a,b for some a and b. We prove the result by distinguishing two cases: n is odd and n is even. For n=2k, let f1={1,2k},f2={2,2k-1},···,fk={k,k+1}and let fk+1={2,2k},fk+2={3,2k-1},···,f2k-1={k,k+2},f2k={1,k+1}. Then f1,f2,···,f2k form a Hamilton cycle. Since {G1,G2,···,Gn} does not contain a rainbow Hamilton cycle, we infer that there exists i such that fi$\notin$Gi. If i=2k, then {1,k+1}$\notin$E(Gn). By using the property of shifted graphs, we obtain that Gi has to be a subgraph of H2k,k,0. If i≤k, then we have fi={i,2k+1-i}$\notin$E(Gi). It follows that Gi has to be a subgraph of H2k,2k-i,i-1. If i≥k, set j=i-k, then fi={j,2k-j}$\notin$E(Gi). Since fi<fj={j,2k+1-j},fj$\notin$E(Gi). Then we can show that Gi has to be a subgraph of H2k,2k-j,j-1.
    For n=2k+1, let f1={1,2k+1},f2={2,2k},···,fk={k,k+2}and let fk+1={2,2k+1},fk+2= {3,2k},···,f2k={k+1,k+2},f2k+1={1,k+1}. It is easy to see that these edges form a Hamilton cycle. Since {G1,G2,···,Gn}does not contain a rainbow Hamilton cycle, there exists i such that fi$\notin$Gi. If i=2k+1,then {1,k+1}$\notin$E(Gi). Then Gi has to be a subgraph of H2k+1,k,0. If i≥k+1, set j=i-k, then fi={j+1,2k+2-j}$\notin$E(Gi), implying that Gi has to be a subgraph of H2k+1,2k+1-j,j. If 1≤i≤k, then fi={i,2k+2-i}$\notin$E(Gi). As f′={i+1,2k+2-i} satisfies fi<f′,Gi has to be a subgraph of H2k+1,2k+1-i,i. By computations, we show that all these Hn,a,b graphs have at most $\left(\begin{array}{c} n-1 \\ 2 \end{array}\right)+1$ edges, which leads to a contradiction. Thus, we conclude that if each of G1,G2,···,Gn has at least $\left(\begin{array}{c} n-1 \\ 2 \end{array}\right)+2$ edges, then{G1,G2,···,Gn} contains a rainbow Hamiltonian cycle. By a similar argument, we establish the corresponding result for rainbow Hamiltonian paths as well.
    Analysis of the Influence of Government Guidance and Supervision on the Strategic Choice of the Main Body of the Rural Ecological Agriculture Industry Chain under the Background of “Dual Circulation”
    ZHU Qin, QIU Xin, LIN Yongqin, WU Qiang, KONG Lin
    2023, 32(10):  114-121.  DOI: 10.12005/orms.2023.0328
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    General Secretary Xi Jinping proposed in 2020 to build a new development pattern of“dual cycle”, and for agriculture as the basic industry, its industrialization development is the basis for building a “domestically large cycle as the main body” strategy. Studies have found that the key to the continuous and healthy development of the agricultural industry chain is the efficient synergy between industrial subjects. Among them, the government's guidance and supervision played an important role. However, there are currently few research results in this aspect. Based on this, this article takes the “dual cycle” as the background, and takes a typical case of the rural ecological agricultural revitalization industry chain based on the ecological breeding community in Ji'an, Jiangxi. It analyzes the government's guidance and regulatory behavior through numerical simulation on the selection of the main strategy of rural ecological agriculture industry chain.
    This article mainly adopts the evolutionary game analysis method, based on the connotation and significance of the rural ecological agricultural revitalization industry chain under the context of fully analyzing the “dual-cycle”, with the breeding industry, planting and processing industry. Among them, in terms of the assumptions of the model symbol, this article considers the impact of market transaction costs for each subject, government-guided agricultural subsidies, and betrayal costs of corporate defaults. The strategy of the game subject is expressed by changing parameters. Based on the constructed game model, the three subjects of the three main body of the rural ecological agricultural revitalization industry chain are used to calculate the dynamic equation of each game subject based on the game matrix, and the evolutionary decision path of the game subject is analyzed; Lee Yapanov's first method, calculate the ebic comparison matrix characteristic value of each strategy balance point, analyze the evolutionary stability conditions of each equilibrium point; then use the MatlaBR2019A software for numerical simulation, test the effectiveness of the model analysis, and ensure that the effectiveness of the model analysis is to ensure the effectiveness of the model analysis. On the basis of effective models, the impact of government guidance and regulatory behaviors is made of numerical simulation, and corresponding management countermeasures are proposed according to the simulation results. The parameter assignment adopted by simulation is based on the actual significance of the parameter, and fully considers the size relationship between the parameters to assume the assumption.
    The government guidance agricultural subsidy policy has obvious guidance to the development of the main strategy of the industrial chain to cooperate with cooperation, and improves the new momentum of guiding agricultural subsidy policies to activate the high-quality development of rural ecological agriculture. The economic benefits of the main body of the industry, the government strengthen the prevention and supervision and supervision of agricultural surface source pollution, strengthen the social responsibility and ecological responsibility awareness of the industrial subject, is a key factor for the choice of cooperation between various industries. The prevention and control of agricultural facial source pollution can help promote the development of rural ecological agricultural revitalization industrial chains with the core of support, planting, and addition as its core; Rural ecological agricultural rejuvenation industry chain joint meeting system, guide the industry to formulate standardized agricultural industry chain main body cooperation behavior specifications, and calculate the scientific and reasonable industrial chain main body breach of contract costs to help promote the evolution of cooperation between the main strategies of the product of the industry chain of rural ecological agriculture.
    Application Research
    Study of the Incentive-Supervision Mechanism of Government Guide Fund with Double Moral Hazard
    WANG Bin, LI Jianping
    2023, 32(10):  122-128.  DOI: 10.12005/orms.2023.0329
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    The establishment of a government guide fund is a strategic measure taken by the Chinese government to encourage and guide social capital to invest in technology-based small and medium-sized enterprises, promote technological innovation and entrepreneurship, and accelerate the cultivation of strategic emerging industries. For the past years, with the rapid development of government guide fund at all levels, it has become a key force in promoting regional economic development and industrial transformation and upgrading. However, with the increasing scale and investment of government guide fund, the moral hazard in the investment operation has become more and more serious so as to be one of the important factors restricting the sustainable development of government guide fund. In order to control and mitigate the moral hazard, there is an urgent need to improve the internal governance mechanism of government guide fund at present.
    In its investment operation, government guide fund entrusts its capital to the fund manager for investment, and entrusts the supervision agency to supervise the investment at the same time in order to prevent the moral hazard of the fund manager. As a result, a double principal-agent relationship is formed. The return of the government guide fund comes from the performance of the sub fund, which depends on the choice of effort behavior made by two agents. Due to the information asymmetry between the government guide fund and its two agents, and inconsistency in their interests and goals pursued, both agents may take opportunistic behavior in order to maximize their utility. By improving the internal governance mechanism of government guide fund, the speculative motives of both agents can be suppressed and they are prompted to choose behaviors that align with the interests of government guide fund. This is of great significance for ensuring the achievement of policy objectives.
    This paper studies how to design the internal governance mechanism of the government guide fund under the condition considering that both agents have the possibility of moral hazard and the coexistence of incentive mechanism, external supervision and punishment mechanism. At first, the supervision cost and penalty function are implanted into the HOLMSTROM and MILGROM incentive model. The model is expanded to establish a tripartite game model between government guide fund and its two agents. Then, this model is used to analyze the impact of changes in incentive intensity, supervision intensity and punishment intensity on default tendency, discuss the critical conditions for default behavior to occur, and study the role of supervision in suppressing default tendency of agent in order to determine whether the introduction of supervision mechanism is effective in reducing default tendency. Meanwhile, how the different compensation forms and the changes in incentive intensity will affect the optimal supervision intensity is analyzed to determine whether it is necessary to implement incentive compensation systems for supervision agency.
    The result shows that: Firstly, by introducing external supervision and punishment mechanisms, the default behavior of the fund manager can be suppressed more effectively, and the fund manager is prompted to take actions that are in line with the interests of the government guide fund. Moreover, the default behavior decreases with the increase of supervision and punishment intensity. Secondly, the willingness of the supervision agency to implement supervision increases with the increase in the incentive intensity for it. By implementing incentive pay system, the moral hazard of supervision agency can be alleviated to a certain extent, which is conducive to maximizing the social benefits of the fund. Thirdly, setting a reasonable incentive level plays an important role in motivating the supervision agency to implement supervision. The incentive level for the supervision agency decreases with the increase of its risk aversion, the incentive level for the fund manager and the volatility of the fund performance. Finally, the costs of supervision and punishment intensity also have a significant impact on the optimal incentive level. These conclusions can provide theoretical and policy guidance for improving the management of government guide fund.
    Production Decisions of Construction Machinery Remanufacturing Enterprises Considering Carbon Emission Reduction under Equity Investment Based Carbon Fund
    CHEN Weida, LU Mengfei
    2023, 32(10):  129-135.  DOI: 10.12005/orms.2023.0330
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    Carbon fund is a green finance tool set up for emission reduction projects or carbon market investment. Equity investment based carbon fund is a fund that invests in energy conservation and emission reduction. As one of the high-energy consuming industries, the construction machinery industry can significantly save resources and reduce carbon emissions by implementing remanufacturing strategies. Moreover, they are prone to funding shortages due to the unique nature of their products, resulting in a demand for financing and emission reduction. Thus,the fund can provide them with a new financing method. At the theoretical level, this paper can enrich the relevant theoretical researches of carbon funds and production decisions. At the practical application level, not only does this help enterprises reduce carbon emissions, but also alleviates financial pressure, achieving a win-win situation of environmental and economic benefits.
    Under the carbon quota and trading policies, this paper establishes the optimization models of capital constrained construction machinery remanufacturing enterprises that do not finance and do not reduce emissions and that finance and reduce emissions through equity investment based carbon funds, and uses Kuhn Tucker conditions to solve them. Through numerical simulation, this paper explores the impact of equity investment/emission reduction rate, initial capital, diseconomies of scale coefficient and consumer acceptance on their production decisions. The simulation data refers to the actual situation of construction machinery remanufacturing enterprises,carbon trading markets and settings of other related researches. The results show that compared with the situation of no financing, the production of new products and total production increase, while the production of remanufactured products decreases. Profits do not always increase, but there is a single optimal emission reduction rate that maximizes the profits. An appropriate equity investment amount/emission reduction rate is conducive to financing emission reduction. Different emission reduction rates can lead to changes in the production structure. In addition, the increase of the diseconomies of scale coefficient of construction machinery will reduce the total output of enterprises and consumer surplus, but will not always reduce profits.
    There are still some limitations to this article. Thus, this study can be further extended to situations involving multiple cycles or emission reduction rates that are supposed to use as decision variables. Additionally, it can analyze the impact of different types of carbon funds, such as loan based carbon funds on the production decisions of construction machinery remanufacturing enterprises.
    Firm's Optimal Investment Decision in Responding to Climate Change Based on Option Value Model
    WANG Yangjie, WANG Jiaquan, LI Yangyang
    2023, 32(10):  136-143.  DOI: 10.12005/orms.2023.0331
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    Global climate change has sparked widespread concern worldwide, with the international community calling for strict control of energy-related carbon dioxide emissions to mitigate climate change. As the key implementers of policy objectives, resolute investments in energy-saving and emission reduction technologies not only directly impact the Chinese government's ability to achieve emission reduction targets but also determine the implementation of the fundamental national policies of resource conservation and environmental protection. Various uncertainties related to climate change may further increase the risks faced by firms in their decisions regarding energy-saving and emission reduction investments. While scholars have demonstrated the impact of various uncertainty factors on firm investment decisions, the research on the uncertainty stemming from climate change and its influence on firm decisions regarding energy-saving and emission reduction investments remains limited. There is a lack of a comprehensive understanding of the costs and uncertainties faced by micro-level entities, such as firms, in their efforts to mitigate climate change. Particularly, among the various uncertainty factors, the size of the discount rate can directly affect decision-makers' estimates of the relationship between future returns and current costs and, consequently, determine their optimal investment decisions. Currently, there is scarce research that analyzes decision-makers' responses to climate change uncertainty by introducing discount rates in option value models. Therefore, an in-depth exploration of the mechanisms behind firm decisions on energy-saving and emission reduction technology investments, in conjunction with option value models, holds theoretical and practical significance for further improving China's energy-saving and emission reduction policies, developing a low-carbon economy, mitigating climate change, and accelerating the construction of an ecological civilization.
    Based on the option value theory, this paper proposes energy-saving and emission reduction investment decision-making rules for firms to respond to climate change uncertainty based on production levels. Under the rule, industrial firms could deal with the uncertainty of climate change according to their outputs. First, we propose a traditional firm investment rule. Second, we develop an output decision model considering the uncertainties faced by industrial firms. Based on uncertainty models of emissions reduction and various cost function formulations, a novel optimal investment rule for implementing energy-saving and emission-reduction actions “based on firm's production scale” has been derived. Finally, based on the theoretical model we develop, we perform a numerical simulation and, in particular, explore the impacts of uncertainty and social discount rate on firms' optimal investment decisions. Further, we also investigate the dynamic path of firms' option value, which shows the applicability of this new investment rule.
    Combining theoretical analysis with numerical simulation results, we find that the greater the uncertainty faced by firms, the higher the threshold for deciding whether to invest in emission reduction projects. As a result, the option value of holding emission reduction investment opportunities by firms increases, thus increasing the likelihood of firms adopting a cautious approach of observing and waiting before taking emission reduction actions. This result suggests that uncertainty could increase the probability that firms wait and delay to invest in emission reduction actions. Considering that the impact of global climate change becomes more and more obvious, future policy uncertainty will become a key factor affecting firms' emission reduction investment decisions. By considering both of the uncertainty of climate change and discount rate, the proposed investment rule can provide decision-making support for optimal investment of firms in dealing with climate change.
    Study on Credit Risk Contagion Mechanism of Green-car Industry Based on Complex Network
    LIU Yan, ZHANG Hongxin
    2023, 32(10):  144-150.  DOI: 10.12005/orms.2023.0332
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    At present, enterprises form complex relationships with network characteristics based on creditor's rights and debts, guarantees and cross-shareholdings, etc. The “credit chain” which is inherent in the correlation relationship has gradually become an important risk infection path among enterprises. The credit chain formed by the association relationship of a single enterprise's credit risk spreads and enlarges in the industry, which is the credit risk contagion. The outstanding feature of the new energy automobile industry is the upper, middle and downstream “deep linkage”. The scope of risk impact of a single enterprise is no longer limited to the enterprise itself. Through the network of mutual credit support path overflow to the upper and lower credit related parties, the industry credit risk correlation has gradually increased. Based on this, we adopt the complex network method to study the credit risk transmission mechanism of the green-car industry, which on the one hand makes a useful supplement to the relevant achievements of the credit risk transmission of green-car industry, and on the other hand has a strong guiding significance to prevent the industry credit risk transmission from evolving into a systemic risk.
    Based on the above background, this paper selects 25 representative enterprises in the new energy automobile industry as research objects, and the data source is the financial data of enterprises in each year in the Wind database. In this paper, the default distance in the KMV model is used to measure the credit risk level of each enterprise in different years, and the Pearson coefficient is used to measure the credit risk correlation degree of each enterprise in different years, and on this basis, the industry credit risk threshold network is constructed. Finally, the evolution of network characteristics is studied in stages through the complex network model. In the aspect of network research, first of all, degree centrality, network centralization, average path length and clustering coefficient are used to describe the evolution of the overall network features, and then the minimum spanning tree method is used to analyze the local features of the network, so as to put forward corresponding policy suggestions for related investors.
    This paper finds that: (1)The credit risk network has typical characteristics of “scale-free” and “small world”, with uneven distribution of credit risk correlation. (2)The concentration degree of network correlation shows a trend of fluctuation, and higher correlation concentration reflects the tightness of credit risk correlation structure and becomes the catalyst of risk contagion. (3)The prominent feature of industry network different from that of financial network is that its topology shows the community structure of upper, middle and lower link clustering, and linkage effect of each clustering is different. Such inter-link clustering and inter-clustering linkage form a mechanism of endogenous network contagion.
    Based on the above findings, this paper puts forward the following suggestions: (1)Make full use of the advantages of the two types of enterprises. Industrial credit risk monitoring should not only pay attention to the risk exposure of a single enterprise, but also deeply understand the contagion linkage phenomenon formed by the characteristics of the network “small world”, and make full use of the advantages of the “two types” of enterprises to solve the problem of industrial risk contagion. (2)To achieve comprehensive collaborative monitoring of industrial credit risks, explicit external government supervision should have a strong demonstration and guidance role in the overall risk prevention and control of the industry, while implicit market regulation should have a prominent advantage in the management of risk contagion among internal enterprises. Therefore, the monitoring design that adopts the coordination of government “supervision” and market “control” has high application value in risk prevention. (3)To implement classified risk infection early warning, credit risk threshold warning lines for different links of upper, middle and downstream should be formulated based on comprehensive consideration of enterprise policy sensitivity and consumers' expected response, and targeted sub-link dynamic monitoring of industry risk infection should be implemented based on different market conditions.
    Research on Cooperation Business Model Selection Mechanism between New Energy Vehicle Manufacturers and Ladder Utilization Enterprises: Based on the Perspective of Retired Battery Ladder Utilization
    XU Yingying, FU Liya, LYU Xichen, SUN Dian
    2023, 32(10):  151-157.  DOI: 10.12005/orms.2023.0333
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    With the intensification of global warming and the depletion of petroleum resources, the promotion and use of new energy vehicles have become an important initiative for China to cope with the pressure of energy security, ecological and environmental protection. However, as the ownership of new energy vehicles continues to rise in China, the recycling of decommissioned batteries has become an urgent problem. According to the forecast of China Automotive Technology and Research Center, the number of retired power batteries reached 200,000 tons in 2020, and it is estimated that the annual scrap of power batteries may reach 350,000 tons by 2025. In fact, the retired batteries of new energy vehicles still have nearly 80% capacity. Although they can't be used for new energy vehicles, they can be used in many scenarios such as power stations, substations and home energy storage. This way of exerting the surplus value of power batteries and realizing degraded application is ladder utilization. As important subjects of retired battery recycling, new energy vehicle manufacturers and ladder utilization enterprises urgently need to explore and form a stable and mature cooperative business model in battery recycling. Therefore, it is of great practical significance to deeply explore the “win-win” business model of new energy vehicle manufacturers and ladder utilization enterprises under the market mechanism, and further study the effective boosting mechanism of government policies for solving the development problem of power battery industry.
    The existing research on the ladder utilization of power batteries in new energy vehicles mainly focuses on product pricing, strategy selection in maximizing the interests of automobile manufacturers, and how to implement policies to improve the recovery rate and recovery efficiency. The theoretical contributions of this paper are as follows: Firstly, the ladder utilization enterprises are included in the research framework, and four business models of cooperation between new energy vehicle manufacturers and ladder utilization enterprises are put forward; Secondly, from the market role and government influence, we explore the Pareto equilibrium of maximizing the strategic income of the new energy vehicle manufacturers and the ladder utilization enterprises; Third, we come up with the methods and countermeasures to solve the “deadlock” (the two sides can not reach a stable cooperation model).
    In this paper, the game models of ladder utilization cooperative business model selection under the influence of market mechanism and government participation are constructed respectively. Through stability analysis and numerical simulation, it is found that: (1)New energy vehicle manufacturers and ladder utilization enterprises can form four cooperative business models. They can reach stable cooperation only if certain conditions are met. (2)When new energy vehicle manufacturers and ladder utilization enterprises are in a deadlock that cannot form a stable business model, reducing the operating cost of battery recycling outlets and the transaction costs of both sides or increasing the residual value of batteries after ladder utilization can all help to break the deadlock. (3)When new energy vehicle manufacturers and ladder utilization enterprises have reached a stable cooperative business model, changes in government subsidies and supervision can not boost the cooperation between the two sides. When the two sides are in a “deadlock” in cooperation, increasing subsidies for recycling network construction or strengthening ladder utilization supervision can promote the formation of stable cooperation, but the mechanism is different.
    There is still room for further expansion in the study. With the mature development of ladder utilization of power batteries in new energy vehicles, in addition to new energy vehicle manufacturers and ladder utilization enterprises, there are other entities involved in battery recycling, such as third-party recycling service enterprises and research institution. Therefore, in the future research, we will include more participants in the process of retired power battery ladder utilization, and further explore the business model to promote the rapid development of power battery industry in new energy vehicles.
    Advertising Expenditures and Stock Price Crash Risk
    HUANG Jinbo, CHEN Lingxi, ZHOU Xianbo
    2023, 32(10):  158-164.  DOI: 10.12005/orms.2023.0334
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    The original intention of advertising is to increase product awareness and improve the enterprise's value. However, the advertising-induced abnormal volatility of stock price makes scholars link the advertisement expenditures with the stock price crash risk. For example, Luckin Coffee was exposed to forge a transaction of 2.2 billion yuan on April 2, 2020, including a false increase in advertising expenses of more than 460 million yuan, which led to a sharp fall of 85% in the stock price of Luckin Coffee. Another case is that the advertising expenses of Shapuaisi Pharma were nearly 900 million yuan from 2014 to 2017, accounting for nearly 30% of the operating revenue. The Food and Drug Administration revealed that the product's advertising exaggerated its efficacy and delayed patient treatment on December 4, 2017, ultimately leading to a sharp drop in the stock price on the same day. In addition, BYD Auto suffered from the “advertising door” event on July 12, 2018, in which Li Juan, the management of the enterprise, forged the company's seal and used the company's name to carry out advertising cooperation business, with a cumulative amount of up to 1.1 billion yuan, ultimately leading to a decline of 7.5% in BYD's share price.
    The above cases indicate that in the context of the separation of ownership and management rights, corporate management may violate the wishes of the owners and the original intention of advertising investment, and excessively invest in advertising in pursuit of short-term benefits. Some managers may even take advantage of their positions to use the company's advertising investment as a self-interest tool for personal gain. The question that arises from this is: Can the increase in corporate advertising investment still achieve the goal of improving corporate performance and stabilizing the stock market price? Or is it that corporate advertising investment has become a self-interest tool for management, leading to an increase in advertising investment which not only fails to stabilize the company's stock price, but also exacerbates the risk of stock price collapse? Theoretically, appropriate advertising investment can improve product competitiveness, which is conducive to the stability of stock price, while excessive advertising investment may be a tool for managers to pursue a short-term benefit or cover up poor performance, thus inducing crash risk. The contribution of this paper is to provide a new perspective for the causes of stock price crash risk and the economic consequences of advertising investment.
    According to the analysis above, using the panel data of all listed companies in China's A-share market from 2011 to 2019, this paper firstly studies the impact of advertising investment on stock price crash risk from an empirical perspective. We obtain corporate advertising expenditures from Wind database, and the rest of the variables' data from CSMAR database. The stock price crash risk is measured by negative coefficient of skewness and down-to-up volatility. This paper briefly analyzes the sample data based on descriptive statistics, and then uses the fixed effect model of Panel data for regression analysis. In the heterogeneity analysis section, all enterprises are classified according to information transparency, enterprise size, and enterprise nature to test whether there is cross-sectional difference in the impact of advertising investment on stock prices. The mechanism test uses the mediating effect model to explore whether advertising investment affects the stock price crash risk through the number of media reports and analysts' tracking. Finally, we examine the robustness of the benchmark regression results by changing the sample interval and core explanatory variable indicators.
    Our search results show that the increase in advertising investment in this year will exacerbate the stock price crash risk in the following year in China. This result indicates that the manager of enterprises strategically pursues short-term benefits while neglecting the long-term growth of enterprise performance, leading to the increase of stock price crash risk; It also implies that advertising investment not only affects the product market, but also has spillover effects on the financial market. The spillover effect of advertising investment on stock prices is more significant in low information transparency, large enterprises and state-owned enterprises. The mechanism tests show that the spillover effect of advertising expenditures will be strengthened by increasing media reports and analyst track. It means that an increase in advertising investment will increase the number of media reports and analyst tracking, and the “sensationalism” of media reports and analyst optimism bias will further aggravate stock price crash risk. Our results are alive at different regression samples and alternative variable measures.
    We conclude that advertising investment is a “double-edged sword”, and solving the principal-agent problem is the key to enlarging its benefit and preventing its negative impact. Therefore, our research results have strong policy implications.
    OFDI, Industrial Structure Upgrading and Green Total Factor Productivity
    ZHANG Jian, WANG Bo
    2023, 32(10):  165-170.  DOI: 10.12005/orms.2023.0335
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    Achieving high-quality development of China's economy has become the direction and focus of China's current and future economic development, the key to which lies in making the past factor-driven shift to innovation-driven, and focusing on Green Total Factor Productivity(GTFP). GTFP is a comprehensive measurement based on traditional TFP, taking into account factors such as energy consumption and environmental pollution, which can more objectively and truthfully reflect economic development performance and is more in line with the contemporary concept of green development. Therefore, exploring the driving path and promotion mechanism of GTFP is crucial to achieving high-quality economic development. In recent years, under the implementation and promotion of the “going global” strategy and the “the Belt and Road” initiative policy, China's Outward Foreign Direct Investment(OFDI) has shown a rapid growth trend. Under “New Normal”, China needs to fully release the structural dividend of factor allocation through industrial restructuring, and focus on promoting supply side structural reform to achieve the improvement of GTFP. There is a two-way interaction relationship between OFDI and industrial structure upgrading. OFDI drives the upgrading of domestic industrial structure, and the optimization and upgrading of domestic industrial structure also help multinational enterprises to “go global” for overseas investment and further improve the level of OFDI. Thus, this paper analyzes the relationship among OFDI, industrial structure upgrading and GTFP, and tries to find OFDI strategies and industrial structure adjustment policies to promote domestic green transformation from this relationship, and the synergistic development of OFDI and industrial structure upgrading, which has important theoretical and practical value for achieving high-quality economic development in China.
    Through combing the literature, it is found that there is a complex relationship among OFDI, industrial structure upgrading, and TFP(GTFP). However, the current literature studies mainly focus on the relationship between two of the three, OFDI, industrial structure upgrading and TFP (GTFP) , and rarely discuss the impact of the synergistic development of OFDI and industrial structure upgrading on GTFP. Moreover, the potential “threshold effect” due to the stage mismatch of the relationship between the two is ignored. Based on this, this paper first uses SBM directional distance function and GML index to measure the GTFP of China's provinces from 2004 to 2018. Secondly, the general panel data model and the panel threshold model are constructed to empirically test the synergistic effect of OFDI and industrial structure upgrading on domestic GTFP, and the possible “threshold effect” of the green productivity growth effect of OFDI and industrial structure upgrading due to the stage mismatch between them. The research value of this paper is to provide policy recommendations for the promotion of China's GTFP from the perspective of OFDI and industrial structure upgrading.
    The results are as follows: First, OFDI has significantly promoted the GTFP, which supports the reverse green technology spillover effect of OFDI existing in China, which has become new momentum for China accelerating the GTFP in the new development stage. Second, industrial structure upgrading has a positive effect on China's GTFP. Third, the synergistic development of OFDI and industrial structure upgrading has significantly promoted the GTFP in China. Finally, the green productivity growth effect of OFDI and industrial structure upgrading has a “threshold effect” because of the stage mismatch between the two. Specifically, with the change of OFDI threshold range, the impact of industrial structure upgrading on the GTFP shows the feature of the nonlinear increasing marginal efficiency, which effectively strengthens the “synergistic effect” of OFDI and industrial structure upgrading. Under the threshold of industrial structure upgrading, OFDI has an obvious U-shaped effect on GTFP, that is, only when the level of industrial structure is raised to a certain height, OFDI will significantly promote GTFP growth, and there is a significant “synergistic effect” between OFDI and industrial structure upgrading.
    Based on the findings of this paper, the following suggestions are proposed. First, give full play to OFDI's reverse green technology spillover effect and promote the improvement of domestic GTFP.Second, make multi-dimensional efforts to enhance the level of advanced industrial structure and leverage the green productivity growth effect of industrial structure upgrading.Third,strengthen the “synergistic effect” of OFDI and industrial structure upgrading to achieve the green productivity growth effect of “1+1>2”. Finally,break the “threshold effect” in the synergistic development of OFDI and industrial structure upgrading, and realize the matching synergistic development of OFDI and industrial structure upgrading.
    “Politics-Market” Ambidextrous Capability and Company FDI Performance
    DU Xiaojun, ZHANG Zheng, SHI Ruxin, TANG Chenxi
    2023, 32(10):  171-177.  DOI: 10.12005/orms.2023.0336
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    With the increasing protectionism in the Western developed countries, China and the developing countries along the Belt and Road have increasingly shown a wide scope for cooperation and demand due to their economic complementarities and interconnected interests, and Chinese enterprises have been increasing their outbound investment in the developing countries along the Belt and Road. However, developing countries along the Belt and Road are characterised by high political risks. In these high political risk host countries, Chinese enterprises face both “political constraints” and “market constraints”. There is a lack of theoretical insight and empirical evidence on how firms can address both “political” and “market” challenges to improve investment performance.
    This paper introduces the dual capability of “politics and market” as a research sample, taking Chinese listed companies that entered the “Belt and Road” developing countries with high political risk from 2008 to 2014. The study examines the impact of the interaction between the political ability to enter the “political market” and the market ability to enter the “product market” on investment performance, reveals the combination of capabilities that affects the investment performance of enterprises, and constructs a framework of factors that affect the investment returns of multinational enterprises in high political risk host countries. The data is mainly collected from annual reports of listed companies, Guo-Tai-An Data Centre (CSMAR) and Wind Information Financial Terminal.
    Relying on developing country contexts and using the outward investment of Chinese firms as empirical evidence, this paper finds that: (1)The results of benchmark regressions show that political capabilities, market capabilities (technology dimension) and their interactions all enhance firms' outbound investment performance; (2)Heterogeneity analysis shows that state-owned firms and firms with high organizational redundancy rely more on nurturing and developing dual capabilities to achieve the desired investment performance than non-state-owned firms and firms with low organizational redundancy. The conclusions suggest that success in the “political market” is as important as success in the “product market”, and that there are synergies between the success of firms in both markets. The results still hold through robustness tests of instrumental variables, joint cubic equation estimation, controlling for the impact of financial crises and replacing political competence measures.
    This study has implications for Chinese firms' OFDI decisions and operations: (1)In order to obtain the desired investment performance, Chinese firms should consider whether they have the political capabilities to handle the political market risks in the host country; (2)Chinese firms involved in OFDI should also build and develop market capabilities to cope with the product market challenges in the host country; (3)In the face of the constraints and challenges of the dual markets in the high political risk host country, Chinese enterprises need to consciously apply the dual path of “and/merger”, seeking to link and complement the mechanisms of the two capabilities in the two markets to enhance the performance of Chinese enterprises' international participation.
    Can “Internet+” Become A “Booster” for Technological Innovation in Colleges
    HAN Xianfeng, LIU Juan, LI Boxin
    2023, 32(10):  178-184.  DOI: 10.12005/orms.2023.0337
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    As a main force of basic research and high-tech fields, colleges play an irreplaceable and significant role in the national innovation system. However, the scientific and technological innovation in college in China has had practical problems with low investment in innovation resources. In the new era, how to effectively improve the technological innovation efficiency in college is not only a key move to improve the national basic innovation capabilities, but also an important support for accelerating the construction of innovative nation. At the same time, the integration between internet and various fields of the social economy has become an unstoppable trend of the times, and it will have a profound impact on promoting “mass innovation and entrepreneurship”. An inspiring question is whether “Internet+” has driven the efficiency of technological innovation in college. If the answer is yes, what kind of space-time difference is there? How can we more effectively excavate and release the “Internet+” overflowing bonus of technological innovation activities and realize the inter-regional balance upon college innovation? To accurately answer the above questions will be of great significance to the formulation and implementation of future relevant national policies.
    By using provincial panel data and such technologies as variable coefficient model and error correction model, the paper initially conducts an empirical study on the heterogeneous effect of “Internet+” on the technical innovation efficiencyin college. First of all, based on the five dimensions-internet popularization, internet information supply, internet infrastructure, internet business application, and internet development environment, 12 subdivision indicators are selected to build a “Internet+” comprehensive level indicator system, and global main component analysis method is adopted when constructing the “Internet+” comprehensive level index at the inter-provincial level. Secondly, on the basis of panel unit root inspection and co-integration test, based on the variable coefficient model, the paper evaluates the long-term connection between the “Internet+” and the technological innovation efficiency in college. Meanwhile, from the dual dimension of direct investment and environmental regulation, it inspects the heterogeneity impact of the technical innovationefficiency in college which may be caused by the interaction between “Internet+” and other policy factors. Finally, by introducing the residual sequence generated by the long-term equilibrium relationship model, a first-order error correction model is used to further analyze the short-term heterogeneous volatility effect of “Internet+” on the innovation efficiency in college.
    Based on theoretical deduction and empirical analysis, this paper analyzes the long-term and short-term internal relationship between “Internet+” and the technological innovation efficiency in college. The results show that, “Internet+” has a significant long-term and short-term promotion effect on the efficiency of the technological innovation in college, and it can be a “booster” to drive technological innovation in college. The “strategic combination” of “Internet+”, FDI and environmental regulation will help to strengthen the long-term “booster” function of the “Internet+” for the efficiency of the technological innovation in college. “Internet+” has a significant short-term heterogeneous correction effect on the long-term equilibrium of college technological innovation efficiency, and there is a spatial difference concerning the speed when the technological innovation efficiency adjusts itself to equilibrium. “Internet+” has the obvious heterogeneous features when boosting the technology innovation efficiency of universities, to be specific, the central and western colleges could benefit more from the development of “Internet+”, and the innovation spillover dividend of “Internet+” in the long term is higher than that in the short term.
    The limitations of this paper may be: On the one hand, the heterogeneous influence of “Internet+” on the efficiency of technological innovation in college in the long and short term is only discussed from a linear perspective, and the function law of “Internet+” can be further explored from a nonlinear perspective in the future; On the other hand, the research based on provincial data is a little bit rough, and more subdivided panel data such as prefecture-level, county-level and college-affiliated listed companies can be used in the future to explore the empowering effect of “Internet+” in different contexts.
    An Empirical Study on the Influence of Actors under the Background of the Internet Based on Hypergraph Method
    LI Mingjie, MA Fuxiang, MA Xiujuan, ZHOU Bin, GAO Shujie
    2023, 32(10):  185-190.  DOI: 10.12005/orms.2023.0338
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    Currently, the film quality assessment has focused on various fields such as complex networks, communication, economics and literature. Among them, for modelling and obtaining the properties of collaborative relationship among actors, using the complex network as a research tool has become a major approach. However, as the real world is becoming more complex and diversified, actor collaboration methods and relationship tend to become more complicated. At the same time, based on complex networks' modelling methods, it is difficult to fully represent some of the unique characteristics that the system has. Conversely, in real networks, which are modelled using the hypernetwork theory, it has been able to help researchers to better understand the complexity of real systems. Moreover, it must be noted that most of scholars have conducted empirical studies from the perspective of film production, while few investigate its linkage with the participating actors. In fact, the influence of actors is not only a key factor in determining the quality of a film, but also an important reference for casting the film. In other words, in the process of film production, the selection of influential actors and actresses helps to improve the quality of films, thus promoting the development of the film industry. Therefore, under the background of the Internet, this paper explores how the quality of a film can be improved through the selection of actors.
    Based on the hypergraph theory, this paper takes films as hyperedges and actors as nodes, establishes an actor hypernetwork and obtains the topological properties of this hypernetwork. Moreover, to better analyze the influence of actors under the background of the Internet, this paper proposes three actor influence analysis models based on the hypernetwork structure, weights and the combination of both. 1)Firstly, we us the actor hypernetwork model to calculate topological metrics of nodes in a hypernetwork. Then, we use it to construct an actor influence model based on a hypernetwork structure. Finally, the model is used to estimate actor influence. 2)Given the limitations of the physical structure of the hypernetwork topology metrics, i.e., they do not accurately reflect the reality of actors' personal values, and therefore, this paper counts the actor's awards, the number of followers on social platforms and stylistic positioning. Based on empirical data, this paper constructs an alternative model of actor influence analysis to further analyze the reality of actor. 3)Based on the two models, considering the topological indicators of the hypernetwork and realistic influencing factors, this paper proposes a comprehensive actor influence analysis model, which provides a comprehensive assessment of actor influence. Sample data are collected from the official platform (https://www.maoyan.com/), which covers data periods from January 2015 to December 2019, totaling 551 domestic films released in the mainland and 2,157 actors. In addition, several categories of authoritative awards are included: The Golden Statue Awards (GSA), the Golden Rooster Awards (GRA), the Golden Horse Awards (GHA), the Hundred Flowers Awards (HFA), and the Ornamental Column Awards (OCA). Furthermore, the number of actors' fans is counted on the official platform (https://weibo.com/).
    Using the three actor influence analysis models to analyze and compare actors' influence, the research results reveal that the node degree and node hyperdegree of actor-weighted hypernetworks follow a power law distribution. In addition, the hypernetwork has large aggregation coefficients and small average path lengths, i.e., it has small-world properties. Specifically, the hypernetwork structure and weights-based combination can reflect the actual influence of actors more comprehensively and objectively. The results calculated by the first model are deviated from the reality perception. The analysis result of the second model is that actors such as “Andy Lau” and “Zhang Ziyi” have strong influence, which is in line with the reality. However, there has been a lack of actors' personal value in recent years, and the result is not accurate enough. In contrast, the third model considers the role of an actor's personal value and audience recognition in his influence in recent years, which is a more objective and comprehensive reflection of the actual influence of actors in the film industry. And this paper proposes that the influence analysis method can be used not only for the prediction of actors' influence, thus providing a certain reference for film casting, but also for the influence analysis of other industries. Finally, it is also possible to study the importance of actors from the perspective of a cooperative game and further identify the most compatible way of assessing the characteristics in the actor's industry.
    Method of Selecting and Appointing Members of the Board of Supervisors in Enterprises: Based on the Individual Advantage Characteristics of Performance Ability
    GUO Baorong, ZHAO Xinan, HU Lizhi, QU Yingying
    2023, 32(10):  191-197.  DOI: 10.12005/orms.2023.0339
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    The board of supervisors plays an important role in the modern enterprise system. Scientific selection and appointment of the members of the board of supervisors and the establishment of the board of supervisors with matching abilities and positions have become the primary issues to promote the effective governance of the board of supervisors. However, at present, there is a lack of effective analysis methods based on the individual characteristics of the members of the board of supervisors and the coordination between the ability of supervisors and the overall ability of the board of supervisors in terms of the formation of the board of supervisors and the analysis of the governance ability of the board of supervisors. In this paper, we use the grounded theory, the individual advantage characteristics identification method and the overall capacity optimization and integration analysis method to construct a method and implementation process for the selection and recruitment of supervisory board members.
    First of all, the programmed rooting theory is used to analyze the operation process of the supervisory boards of five typical listed companies over the years, and the index system of supervisory board's required performance ability is constructed by refining and summarizing the programmed rooting. Then, for general joint-stock enterprises, on the basis of the idea of Jingyou, the individual advantage characteristic identification technique is applied to identify the performance advantage structure of each supervisory board member by taking the identification of the performance ability of each supervisory board candidate member as a logical starting point, and further applying the individual agent evaluation to solve the problem of duplication of functions among the candidate members. Finally, we construct the measurement method of “individual-group” effective matching from the perspective of overall coordination of the supervisory board, so as to realize the optimization of the supervisory board as a whole and the decision-making support for its formation. The paper also demonstrates the operation process and results of the proposed method through examples.
    According to the need of scientific and effective formation of supervisory board, this paper proposes a new method of selecting and recruiting supervisory board members to support the formation of supervisory board on the basis of constructing the indicator system of supervisory board's performance ability, which belongs to the combination of the two multi-attribute decision-making methods, and the method of selecting and recruiting supervisory board constructed in this paper is weakly effective at least because the individual agent evaluation is a weakly effective method and the method of evaluating democratically according to the class is at least also weakly effective. In the arithmetic example, the evaluation methods obtained are valid because the weights of the obtained by-class evaluations are all greater than 0. In conclusion, this paper constructs a decision support method that effectively addresses the formation of a team in the context of supervisory board formation.
    The method proposed in this paper not only helps to achieve the division of labour and coordination within the supervisory board, but also helps to maximize the ability of the supervisory board to perform its duties as a whole, and is easy to be accepted by the candidates for the supervisory board, thus improving the theory and method of the selection and management of the supervisory board members.
    The selection method proposed in this paper reduces the difference in the selection results caused by a large gap in subjective evaluation as much as possible. However, as long as subjective evaluation is involved, it is inevitably affected by proximity. In the follow-up research, the combination of subjective and objective methods can be considered, such as weighted analysis of appraisers' judgment and special treatment of diverging opinions, etc., for the selection and recruitment of members of the board of supervisors.
    Deposit Insurance Pricing Method Based on the Structures of Bank Assets and Liabilities
    LYU Xiaoning
    2023, 32(10):  198-204.  DOI: 10.12005/orms.2023.0340
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    From the perspective of premium structure, more and more countries and regions are implementing the deposit insurance system of risk differential premium. The core of differential rate system is to require the premium rate level to reflect the different levels of risks faced by banks, but most differential rate pricing methods only focus on the volatility of total assets and total liabilities of banks, ignoring the impact of the structure of assets and liabilities on the risks faced by banks. From the asset side of the bank, different types of bank assets face different risks. Very safe asset portfolios may reduce the risk level of the bank, while other types of asset portfolios may increase the risk of the bank. Therefore, when calculating the deposit insurance premium level of the bank, the proportion of risky assets in its assets should be taken into account. Similarly, from the perspective of the bank's liability side, the total liabilities of the bank can be divided into general debt and secondary capital debt composed of long-term debt and long-term bonds, etc. Secondary capital debt has become a line of defense for bank bankruptcy. Therefore, the proportion of secondary capital debt in a bank's liabilities should also be considered as an influencing factor in determining its deposit insurance premium rate.
    Traditional deposit insurance option pricing methods usually take bank assets and liabilities as two whole parts, the premium rate can only reflect the volatility of the total assets of the bank, and it is usually assumed that the deposits of commercial banks are equal to their total liabilities and are all insured, so the calculated deposit insurance premium level ignores the impact of different asset and liability structures of different banks. Some scholars try to pay attention to the asset structure of banks in the research process of deposit insurance pricing, and some scholars pay attention to the impact of bank liability structure on deposit insurance premium rate. However, the existing studies tend to separate the detailed analysis of the asset side from the liability side, and few studies pay attention to the comprehensive impact of different structures of the asset side and the liability side of banks on their deposit insurance premium level. Considering the different structures of bank assets and liabilities, improving the traditional deposit insurance option pricing method and building a more accurate deposit insurance pricing model can make the calculated premium rate more accurately reflect the risk situation of banks, so as to better realize the fairness and accuracy of the differential premium rate.
    This paper firstly subdivides the asset structure and liability structure of the bank. According to the standard of whether there is default risk, the bank assets are divided into risk assets and risk-free assets. According to the different order of repayment, bank liabilities are divided into priority debt, insured deposit debt and secondary capital debt. On this basis, this paper improves the deposit insurance option pricing method, proposes a deposit insurance pricing model considering the structure of bank assets and liabilities, and simulates the annual deposit insurance premium level of 16 listed banks in China under the condition of estimating the volatility of bank risk assets and the market value of bank senior debt. Finally, the correlation between the rate of each bank and its risk degree is analyzed. The simulation and calculation data are taken from the Wind database during the study period from 2016 to 2020.
    The basic conclusions include: (1)The deposit insurance premium rate of listed banks in China during 2016-2020 is generally low: The average premium rate of China Merchant Bank is relatively high, followed by Bank of Ningbo and China Construction Bank, and other banks are relatively low; The deposit insurance premium rate of the banking industry in 2018 is relatively high, and the premium rate in the remaining years is relatively low; The level of deposit insurance premium decreases with the increase of the proportion of insured deposits. (2)The deposit insurance premium calculated in this paper is positively correlated with the ratio of risky assets of banks and negatively correlated with the ratio of secondary capital debt of banks; The correlation coefficient between the premium level and the ratio of secondary capital debt of banks is larger in absolute value; The deposit insurance premium rate can basically reflect the level of risks faced by banks.
    Executive Exercise Performance Conditions and Investment Behavior: From the Perspective of Risk-taking Intermediary
    LI Miao, HU Wenxiu
    2023, 32(10):  205-211.  DOI: 10.12005/orms.2023.0341
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    The issue of the effectiveness of equity incentives has been a great concern, and more scholars have studied the impact of equity incentives on investment behaviour, but no consistent conclusions have been reached, which may be due to the fact that equity incentive programmes are considered homogeneous. In practice, the different settings of each element of the equity incentive programme are the key to influencing the company's investment behaviour, and only the design of an appropriate incentive programme can play a positive incentive role. However, most of the previous studies only explore the impact of equity incentives on investment behaviour from the perspective of whether equity incentives are implemented or not, and fewer studies reveal the impact of different elements of equity incentives on investment behaviour in detail, and the relevant studies are also mainly conducted from the perspective of the level of equity incentives and the elements of the equity incentive mode, and fewer studies explore the impact of investment behaviour from the perspective of performance conditions of the exercise of the right, and the only relevant studies are mainly based on the perspective of incentive motivation to study the impact of equity incentives on the efficiency of investment. They believe that incentive motivation can improve the efficiency of investment, while the implementation of equity incentives of non-incentive motivation worsens the efficiency of investment. Existing studies mainly suffer from the following shortcomings: (1)Fewer studies reveal the mechanism of the impact of exercise performance conditions on investment behaviour from the perspective of the mediating effect of risk-taking; (2)Most of the existing studies conclude that equity incentives have a linear relationship with investment efficiency, and do not propose an appropriate value for exercise performance conditions; (3)Most of the existing studies measure investment efficiency in terms of overall efficiency and fewer of them conduct path analyses from the perspective of overinvestment and underinvestment, respectively; and (4)The existing studies rarely include a number of different elements of incentive schemes in the same framework for discussion. Based on these, this paper examines the impact of different vesting conditions on firms' investment behaviour and the mediating role of risk-taking, as well as the moderating role of the exercise period and the equity incentive mode. The following research hypotheses are proposed: Hypothesis H1: The effect of exercise performance conditions on firms' investment efficiency shows an inverted U-shaped relationship. Hypothesis H2: Risk taking has a mediating effect on the effect of performance conditions on investment efficiency. Hypothesis H3: Exercise period has a significant positive moderating effect between exercise performance conditions and investment efficiency, and exercise period strengthens the inverted U-shaped relationship between exercise performance conditions and investment efficiency. Hypothesis H4: Stock option incentives are more conducive to investment behaviour than restricted stock incentives, as evidenced by the stronger performance of stock options in the role of exercise performance conditions in stimulating overinvestment and mitigating underinvestment.
    Sample selection and data source of this paper are: A-share listed companies that implement equity incentive plans in China from 2009 to 2020 are taken as the research samples. And we do the following data processing: (1)Excluding the financial and insurance companies, ST and *ST companies; (2)Deleting the sample that adopts two incentive modes at the same time; (3)Deleting some samples that adopt the indicators of the growth rate of main business income, EVA, etc.; (4)Deleting the samples that incentivise only the core technical staff, finally selecting the samples of 1568, and using the software of data analysis in Stata16.0. From the perspective of risk-taking intermediary the paper analyses the influence mechanism of executive exercise performance conditions on the company's investment behaviour. The results show that: The impact of exercise performance conditions on firm investment efficiency has an inverted U-shaped relationship and derives the inflection point of the curve (optimal exercise performance conditions), revealing that risk-taking has a mediating effect between exercise performance conditions and firm investment efficiency, and that the exercise period has a significant positive moderating effect between exercise performance conditions and investment efficiency, i.e., the exercise period strengthens the inverted U-shaped relationship between exercise performance conditions and investment efficiency; Compared with restricted stock, the stock option mode encourages executives' risk-taking ability more, which may mitigate underinvestment due to risk aversion to some extent, but may also exacerbate overinvestment.
    This paper enriches the research on the relationship between equity incentives and investment behaviour, proposes a risk-taking path for the impact of exercise performance conditions on investment behaviour, provides a theoretical explanation for the existing controversy over the conclusions on the impact of equity incentives on investment behaviour, and refines and deepens the research on the relationship between equity incentives and investment behaviour in terms of exercise period and equity incentive mode. The study provides some managerial insights: (1)Only by setting appropriate exercise performance conditions can the investment efficiency of enterprises be improved; (2)Reasonably determining the exercise period of equity incentives can effectively coordinate the contradiction of conflicting goals between shareholders and operators, and improve the investment efficiency of enterprises; (3)For underinvested enterprises should try to choose the stock option mode to reduce their risk aversion and be motivate to be bold enough to develop new projects and investments, so as to alleviate the underinvestment of enterprises.
    Has High-level Open Policy Improved Environmental Quality? ——A Quasi-natural Experiment From the FTZ
    ZHANG Xin, YANG Lanpin
    2023, 32(10):  212-218.  DOI: 10.12005/orms.2023.0342
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    As a major measure to accelerate the construction of a higher-level open economic system in the new era, the free trade zone(FTZ) will inevitably become an important carrier for promoting our country's high-level opening up and sustainable economic development. At present, academic research on high-level opening is mainly qualitative, while empirical research on the economic performance of high-level opening is not much, and there is less research on the environmental effects and mechanism of high-level Glasnost such as free trade pilot zones. What impact does the high-level Glasnost represented by the pilot free trade zone have on environmental quality? Based on the establishment of the FTZ as a quasi-natural experiment, this paper uses the DID method to identify the environmental effects of high-level open policies, and uses the mediation effect model and the Bootstrap method to test its transmission mechanism. This study selects sample data from 31 provinces in China from 2000 to 2017, and empirically studies the effect of free trade pilot zone policies on environmental quality improvement. The data come from the National Statistical Yearbook, China Environmental Statistical Yearbook, and China Urban Statistical Yearbook over the years. In order to further verify the above benchmark regression conclusions, robustness tests are conducted through methods such as parallel trend hypothesis test, sample randomness hypothesis test, exclusion of interference from other policies test, and placebo test.
    The study finds the following conclusions. The FTZ has a significant emission reduction effect on the comprehensive index of environmental pollution, sulfur dioxide emissions, solid waste emissions, and total wastewater emissions, and this result still holds after the counterfactual test and multiple robustness tests. There is a spatial difference in the improvement effect of the free trade experimental zone on environmental quality, which is “strong in the east, weak in the west, and not obvious in the middle”, as well as a temporal heterogeneity that increases with the growth cycle. The pilot free trade zone has improved the environmental quality through five Mesomeric effect, including institutional innovation, high-level trade, factor structure optimization, industrial structure upgrading and financial innovation development. Therefore, this study proposes the following countermeasures and suggestions. Firstly, the pilot scope and reasonable layout of free trade pilot zones should be accelerated. The second is to promote the transformation and upgrading of trade Glasnost. The third is to promote the transformation from policy-oriented openness to institutional openness. The fourth is to formulate Glasnost to promote the optimization of factor structure and industrial upgrading. This study provides a scientific basis for the transformation of China's traditional Glasnost and the formulation of high-level Glasnost.
    Management Science
    Dual Path of Empowering Leadership Affecting Knowledge Sharing within Projects
    WEI Meng, HAO Shengyue
    2023, 32(10):  219-225.  DOI: 10.12005/orms.2023.0343
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    Knowledge sharing in projects can promote the integration of knowledge among different members, which is significant for improving project resilience, reducing project costs, and improving project efficiency. Therefore, more and more literature has explored the factors affecting knowledge sharing in projects. Project managers are the core of a project team, and their leadership profoundly affects the perception and actions of team members. Exploring knowledge sharing from the perspective of project manager leadership is a cutting-edge topic in the current cross research of knowledge management theory, leadership theory, and project management theory. However, most of the relevant studies focus on transformational leadership, charismatic leadership, and knowledge leadership, and there are insufficient discussions on empowering leadership. Based on affective events theory, we explore the influence of project managers' empowering leadership on knowledge sharing in projects, focus on the mediating role of perceived organizational support and perceived insider status in this relationship, as well as the moderating role of project urgency, and construct a conceptual model for empowering leadership, perceived organizational support, perceived insider status, project urgency, and knowledge sharing in projects. We distribute electronic and written questionnaires to members of China's construction project teams, and recover 220 valid questionnaires. Then, we use structural equation model to carry out empirical analysis on 220 valid data.
    The empirical results show that: (1) Project managers' empowering leadership has a significant promoting effect on knowledge sharing within projects; (2)Perceived organizational support and perceived insider status mediate the relationship between project managers' empowering leadership and knowledge sharing in projects; (3)Project urgency plays an inverted U-shaped role in regulating the relationship between project managers' empowering leadership and perceived organizational support, and plays a U-shaped role in regulating the relationship between perceived insider status and knowledge sharing within projects. In other words, the main paths for empowering leadership to affect knowledge sharing in projects are: (1)Empowering leadership-perceived organizational support-knowledge sharing in projects, and (2)empowering leadership-perceived insider status-knowledge sharing in projects. These two paths are constrained by project urgency.
    The innovation of this paper lies in: (1)Revealing the impact of project managers' empowering leadership on knowledge sharing; (2)Revealing the internal dual paths between leadership and knowledge sharing by affective events theory; (3)Revealing the moderating effect of project urgency on the dual mediating paths between managers' empowering leadership and knowledge sharing. In future research, the scope of data collection should be further expanded to make research conclusions more universal. Meanwhile, modifying or reconstructing conceptual models from a dynamic perspective is a direction worth exploring. In addition, whether other project characteristics (such as project complexity and project proximity)will constrain dual paths is a question worth pondering in future related research. Moreover, the extreme value of project urgency on dual path regulation and the threshold value of superposition effect should be clarified in subsequent research, so as to better guide the establishment of a knowledge governance strategic system.
    Research on the Targeted Delivery Strategy of Competitive Enterprises' Electronic Coupons Considering Consumers' Preference
    SI Yinyuan, MENG Qingliang, YANG Wensheng, FU Zhu
    2023, 32(10):  226-232.  DOI: 10.12005/orms.2023.0344
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    In a market with uncertain quality perception, consumers often make purchase decisions based on product quality and price. However, different consumers have varied perceptions of product quality and price. As an effectively promotional and advertising tool, e-coupons can not only convey information about a company's products and quality, but also better meet the needs of consumers with different preferences. At present, the ability of enterprises to obtain information has been significantly improved, and they can effectively identify consumer preferences and target coupons accordingly. Compared with traditional price promotion, targeted coupons pay attention to the matching of coupon delivery scope and consumer demand, which can effectively overcome the problem of poor pertinency of price promotion targets and improve consumers' cognition and acceptance of products. In practice, more and more enterprises carry out targeted coupon promotions. Taking Volkswagen DotCom as an example, merchants combine user preferences to push preferential information on specific commodities in the vicinity, which can significantly reduce consumers' search costs and strengthen consumers' knowledge of the products.
    When confronted with groups of consumers with different preferences, how to develop an effective e-coupon strategy? How to make a scientific and reasonable decision on the combination of e-coupon and product price based on consumer preferences to maximize revenue? The solution of these problems plays an important role in improving the competitiveness of enterprises. Therefore, in view of the issue of e-coupon delivery in the market of heterogeneous product competition, we innovate from the perspective of consumer preference, analyze the relationship among consumer preference, coupon face value and consumer demand (utility), and use hotelling model to build a decision-making model of coupons with the same/different face value under the influence of directional ability, in order to explore the enterprise e-coupon delivery strategy under the product quality difference.
    The results show that coupon face value is positively correlated with product price and quality, while the level of targeting ability is negatively correlated with consumer price sensitivity, and the relationship with quality sensitivity depends on product differences. The discriminatory pricing of coupons changes the price and directional ability strategies of enterprises. The face value of coupons for price-sensitive consumers is higher than that under the unified pricing strategy, while the face value of coupons for quality-sensitive consumers is lower than that under the unified pricing strategy. Moreover, the ability of enterprise orientation under the discriminatory pricing strategy is higher than that under the uniform pricing strategy. Compared with uniform pricing strategy, coupon discriminatory pricing can enhance enterprises' competitive advantage in the market and obtain greater market profits, especially for enterprises at a disadvantage in the market.
    The research conclusions can provide some theoretical references for online marketing enterprises to launch coupons and acquire targeting ability. However, there are still shortcomings: The research is more focused on the enterprise coupon delivery strategy under the situation of heterogeneous consumers and heterogeneous enterprise products, and most of them are the optimal decision of enterprises under static conditions. In the future, it can be extended to the dynamic competition of product quality and price under the existence of many homogeneous conditions in reality, as well as the competition of enterprise product quality and price under complex circumstances.
    Review of Aircraft Maintenance Scheduling
    XIE Kexin, XU Genyan, SU Yi, LIANG Zhe
    2023, 32(10):  233-239.  DOI: 10.12005/orms.2023.0345
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    Aircraft needs various maintenance and regular checks to ensure aircraft airworthiness. A low-quality maintenance plan can lead to aircraft requiring far more maintenance during service, reducing the available time of the aircraft. At the same time, unreasonable maintenance intervals prevent the full utilization of maintenance resources. The decline in aircraft utilization and the increase in maintenance costs have an intangible impact on the profitability of airlines. We categorize the aircraft maintenance, specifically describe the existing modeling methods and related algorithms for aircraft maintenance scheduling at different stages, and supplement other research issues related to aircraft maintenance. We intend to provide ideas for airline decision-making while also providing systematic theoretical references and suggestions for academic research in this direction.
    We first provide a comprehensive and detailed introduction to the concepts related to aircraft maintenance, including maintenance time interval indicators and the general classification of maintenance in airline operations. Then, according to the length of time before execution, the scheduling is divided into three stages: Long-term scheduling, mid-term scheduling and short-term scheduling. There are significant differences in the types of maintenance planned in these three stages. Long-term scheduling typically targets maintenance that is time-consuming, costly, and has high requirements for locations. It aims to minimize the number of check and maintenance while meeting various maintenance resource limitations and requirements to save costs. The algorithms used in long-term scheduling are briefly introduced, and a two-stage long-term maintenance scheduling method is emphatically illustrated. Mid-term scheduling is a transitional stage between long-term and short-term scheduling. It requires a rough scheduling of maintenance tasks for the next month or more based on the results of long-term scheduling but without considering flight plans. In the short-term scheduling stage, the development of maintenance plans is closely related to flights, with a focus on considering the rationality and robustness of the connection between flights and maintenance. The network modeling of most aircraft maintenance routing problems can be classified into two categories: Path-based and arc-based. Both time-space network and connection network can be used for arc-based modeling, and there are certain differences in the modeling methods of corresponding decision variables. The connection network is more convenient for evaluating the connection quality between aircraft flights, and between flight and maintenance, while the time-space network is more likely to consider the location of aircraft at different times. In addition, there may be some unexpected events in actual operation, such as weather deterioration, damage to maintenance equipment, and the absence of maintenance personnel. These will result in the fact that aircraft is not able to complete the assigned maintenance on time, and the airline will have to recover the aircraft maintenance scheduling in real time to minimize the impact of unpredictable scenarios. Lastly, the maintenance base planning, the allocation of other maintenance resources and maintenance monitoring driven by data are introduced. The optimization of these problems can improve the efficiency of aircraft maintenance. Finally, we find that there are still some optimization directions in aircraft maintenance scheduling and related issues, such as considering more strategic factors in long-term maintenance scheduling, indicators related to scheduled letter checks in short-term maintenance scheduling, and integrating short-term maintenance scheduling and maintenance crew scheduling problems for solution.
    This study categorizes research on aircraft maintenance scheduling based on the actual business processes and requirements of airlines. At the same time, various subcategories are further determined based on different modeling formulation, and their application situations are elaborated and analyzed. This classification framework helps scholars to deeply understand the application scenarios of this research direction, in order to discover research problems with application value. On the other hand, identifying future research opportunities should help academic researchers and practitioners to develop new models and improve the performance of the existing models.
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