Table of Content

25 December 2021, Volume 30 Issue 12

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heory Analysis and Methodology Study

A Study onOptimal Strategies for Parallel Machine Scheduling with Processing Rate Interference

ZHENG Fei-feng, SONG Qin-rui, XU Yin-feng, LIU Ming

2021, 30(12):  1-5.  DOI: 10.12005/orms.2021.0376

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With the application of intelligent Internet and personalized consumption, manufacturing and service industries have started paying attention to providing personalized service for customers via network information platform. It drives a new service model where product and service designers interact with multiple customers simultaneously in online fashion. According to the interference of service efficiency between parallel tasks of the same designer, this paper describes the problem as a new scheduling model where parallel machine processing rate is influenced by other machines, and the objective of the model is to minimize the total completion time. First of all, for the case where there are only two designers and each designer can deal with at most two parallel tasks at any time, we put forward a modified SPT rule and prove its optimality by the induction method. Then we relax the task assignment requirement of the modified SPT rule, and show that it still keeps the optimality of solution after the relaxation. Finally, we generalize the conclusion to the case with more than two designers. The study provides a theoretical support for constructing effective scheduling strategies in online personalized service applications.

ABi-level Programming Problem Based on Time-window Delay for Resource-Constrained Project Scheduling

LIU Guo-shan, WANG Min, ZHANG Zhuan-xia

2021, 30(12):  6-12.  DOI: 10.12005/orms.2021.0377

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In this paper, a bi-level programming problem of RCPSP (resource-constrained project scheduling problem) is proposed from the perspective of owner-contractor interaction, that is, how to make interactive decision to maximize NPV (Net present value) under renewable resource constraints. Firstly, we establish the programming model for client and contractor as a leader-follower game that is enacted through bi-level hierarchical programming mechanism. The client is modeled as an upper-level problem for optimal selection of unit incentive ratio while the contractor is modeled as a lower-level problem which responds to decisions of upper level in order to schedule the activities. Secondly, in order to solve the problem, a nested adaptive genetic algorithm based on time window delay program is designed. Finally, a case study is implemented to illustrate the stability and efficiency of the algorithm, the proposed program has been tested on the PSPLIB dataset, and managerial insights are provided with respect to the impact of key parameters. The results can provide a basis for the arrangement of the project process and the formulation of the incentive mechanism between the two parties, so as to improve the interests of both parties.

Research on Multi-objective Optimization Model and Algorithm of Cold Storage Multi-temperature Joint Delivery under Dynamic Demand

DING Qiu-lei, HU Xiang-pei, WEI Juan, JIANG Yang

2021, 30(12):  13-19.  DOI: 10.12005/orms.2021.0378

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Cold storage multi-temperature joint delivery is a new distribution mode in the current cold chain logistics, which can efficiently meet the customer's demand for product diversity. This paper focuses on the dynamic change of the customer's demand in the cold storage multi-temperature joint delivery. Firstly, based on the demand forecast, the assembly proportion of the vehicle redundant space is differentiated, and the redundant space of the vehicle is reasonably utilized without full load. Then, the customer satisfaction factor is considered from time satisfaction and order completion rate, and the cold storage multi-temperature joint delivery model is established. Finally, the above model is handled by heuristics. The experimental analysis demonstrates that our approach is more practical.

Study of Project Scheduling Trade-off Optimization Based on Cost Economy under Stochastic Environment

WANG Yan-ting, HE Zheng-wen, HE Yuan-yuan

2021, 30(12):  20-27.  DOI: 10.12005/orms.2021.0379

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From the perspective of cost economy, this paper studies and tries to find out an optimal match-up between the proactive and reactive scheduling methods. A cost-based model is constructed based on the time buffer inserted, and a trade-off index SR is provided to measure the cost sharing of the two scheduling methods in the process of dealing with uncertainties. Considering the NP-hardness of the problem, a random two-point heuristic algorithm based on hybrid variable neighborhood search and tabu search is designed to solve the problem. The results show that the cost caused by improving robustness will exceed the benefit brought by decreasing the adjustment frequency; According to the contractor's sensitivity to cost, the workload of proactive scheduling and reactive scheduling in dealing with uncertainty factors changes along with the variation of the trade-off ratio, gradually from proactive scheduling dominant transforming to reactive scheduling dominant. Finally, valuable management implications are given from the perspective of project management, helping managers choose the most appropriate methods for uncertain environment.

Minimizing Costs Model and Algorithm of Centralized Commute

DONG Ji-yang, HE Wan-li

2021, 30(12):  28-34.  DOI: 10.12005/orms.2021.0380

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The paper establishes 0-1 mixed integer programming models aiming at minimizing operation costs in the centralized commute service, which has characteristics as multi-destination, multi-automobile coordination and multi-routing shifts, and taking account of customer satisfaction, we can obtain the approximate minimum cost under different degrees of satisfaction. According to the complexity and large scale of the problem, a heuristic algorithm (class label algorithm) based on kNN is developed, which promotes and generalizes the method of path construction. The numerical results show that the model and algorithm proposed is effective and feasible.

K-means Clustering Optimized by Lightning Attachment Procedure Optimization

GAO Wen-xin, LIU Sheng, XIAO Zi-ya

2021, 30(12):  35-41.  DOI: 10.12005/orms.2021.0381

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K-means clustering algorithm is a commonly algorithm applied in data mining and data analysis, but it has the disadvantages of relying on the initial value and easy to fall into the local optimum. For these shortcomings, this paper proposes an improved K-means clustering which is optimized by the lightning attachment procedure Optimization (LAPO) , which overcomes the difficulty of selecting the initial value of the clustering algorithm. This optimum improves the accuracy of the K-means clustering algorithm, and reduces the possibility of falling into a local optimum. Six real data sets are selected from the UCI data set for simulation experiments. The results show that the improved clustering algorithm has better accuracy and robustness.

Resource Flow-based Model and Algorithms for the RCPSP with Resource Transfer Times

HU Xue-jun, WANG Jian-jiang, TAN Yue-jin, Xu Pei-de, CUI Nan-fang

2021, 30(12):  42-50.  DOI: 10.12005/orms.2021.0382

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In this paper, we investigate the resource-constrained project scheduling problem(RCPSP) with resource transfer times. In order to effectively obtain the optimal solution of the problem, a resource flow-based solution representation is adopted. Accordingly, a resource flow optimization model for the RCPSP with transfer time is proposed with the objective of minimizing the project makespan. An improved neighborhood operator for rerouting resource flows is designed, which adapts to the characteristics of the problem. For solving the model, an improved tabu search algorithm and a greedy randomized adaptive search procedurewith tabu search are developed, respectively. The experimental results show that, compared with the algorithm in the literature, the proposed two algorithms can obtain optimal solutions for a larger number of project instances and consume less computation time. In addition, we analyze the performance of the algorithms in solving project instances with different characteristics, and the results provide guidance for project managers to evaluate the applicability of the algorithms based on the project characteristics.

Pricing, Service Decision and Recycling Mode of E-Closed-Loop Supply Chain Dominated by E-commerce Platform

LIU Kai, LI Chun-fa, LI Dong-dong

2021, 30(12):  51-57.  DOI: 10.12005/orms.2021.0383

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The E-closed-loop supply chain (E-CLSC) management should be supported by scientific pricing and service decision. Aimed at the centralized and decentralized recycling modes, the Stackelberg game model of E-CLSC dominated by e-commerce platform is constructed, and the pricing and platform service decision problems of E-CLSC system are studied. Through the analysis of equilibrium strategies such as product sales price and platform service level, this paper reveals the influence of investment effectiveness of the recovery subject and transfer price on E-CLSC equilibrium strategy. The research shows that: centralized recovery mode is better than decentralized recovery mode. In the decentralized recovery mode, if the investment effectiveness of the recovery subject is the same, both the manufacturer and the platform prefer the manufacturer recovery mode. Compared with the third-party recycling model, the sales price and service level of the platform are the same, but the former recycling channel is more efficient. In addition, under the platform recovery mode, unit commission is negatively correlated with recovery transfer price, while product sales price, platform service level and waste product recovery rate have nothing to do with recovery transfer price. If the investment efficiency of the recovery subject varies greatly, the manufacturer's recovery mode is not always optimal, because the difference in investment effectiveness of recycling subjects significantly affects product sales price, recycling channel efficiency, platform service level and E-CLSC member profits. Finally, the validity of the above conclusion is verified by numerical simulation.

A Tripartite Evolutionary Game Analysis of Latecomers Firms Breaking Through Low-end Locking

ZHOU Hua-rong, HE Sheng-bing, LIU You-jin

2021, 30(12):  58-64.  DOI: 10.12005/orms.2021.0384

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Latecomer enterprises breaking through low-end locking is the only way which must be passed for China's industry to move towards the middle and high end of global value chain (GVC). This paper establishes a three-party evolutionary game model including latecomer enterprises, leading enterprises and governments of latecomers, analyzes the influencing factors of latecomers' strategy selection, and conducts numerical simulation analysis of the game model. The results show that the replication dynamic systems have two possible combination of evolutionary stable strategy (ESS): {breakthrough, blockade, negative} and {no breakthrough, blockade, positive}. Which ESS the system tends to is mainly determined by enterprises' core technical capabilities. The stronger the core competence, the greater the breakthrough return, the more inclined the “breakthrough” strategy is chosen. No matter which strategy the latecomers adopt, the leading enterprises will unconditionally choose the “blockade” strategy. Government policies are conducive to preventing domestic latecomer enterprises from sliding into the stable equilibrium of “no breakthrough”, which is an important external force in breaking the low-end locking of global value chain.

Building Owners' Optimal Decision of Carbon Emissions Reduction Considering Cap-and-trade Scheme

SONG Xiang-nan, LU Yu-jie, SHEN Li-yin

2021, 30(12):  65-71.  DOI: 10.12005/orms.2021.0385

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To the huge environmental impact brought by the building sector in China, it is a significant institutional innovation to employ market-based mechanisms to control and reduce its carbon dioxide emissions. This research, firstly, explores the building owner's optimal strategy in the increasingly complex and dynamic environment driven by carbon trading by establishing a multi-objective optimization model. And then, an empirical study based on practical data has been conducted to predict the dynamic adaptive adjustment of carbon reduction decision by the owners in different scenarios.The results show that owners' carbon reduction decision is heavily influenced by the fluctuation in the intensity of subsidy and penalty. Besides, it is found that the one-size-fits-all penalty multiplier in the current carbon market is easy to make owners' illegal emissions fall into the punishment paradox of “rewards for explicit punishment”. Furthermore, the government should adopt the policy of “retrograde subsidy” and carry out precise subsidies to different owners.

Decision and Coordination of Cascade Utilization Power Battery Closed-loop Supply Chain with Economies of Scale under Government Subsidies

ZHANG Chuan, CHEN Yu-xiao

2021, 30(12):  72-77.  DOI: 10.12005/orms.2021.0386

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For a closed-loop supply chain that considers government subsidies and economies of scale, the decision and coordination under the premise of the retailer's leadership are focused on. Under the four situations of no subsidy, subsidized retailer, subsidized manufacturer, subsidized third-party recycler, the influence of subsidy object, scale effect, and remanufactured power battery ratio on members' optimal decision-making and profits are analyzed respectively. The results show that government subsidies can reduce retail prices, increase recovery rate and members' profits; Compared with subsidizing retailer and subsidizing manufacturer, subsidizing third-party recycler can increase the recovery rate and the profits of third-party recycler more obviously. Compared with subsidizing third-party recycler, subsidizing retailer and subsidizing manufacturer can reduce retail prices and increase the profits of manufacturer and retailer more obviously; The increase in the proportion of power batteries that can be used for remanufacturing can reduce the sales price of power batteries and increase the recovery rate of power batteries; The increase in third-party recycler's economies of scale is conducive to reducing retail prices, increasing the recovery rate and the revenue of each member.

Interval-Valued Pythagorean Fuzzy Power Geometric-Geometric Heronian Mean Operators and Their Application in Multiple Attribute Group Decision Making

LI Jin-jun, TI Ting-ting, BAO Yu-e, CHEN Ming-hao

2021, 30(12):  78-83.  DOI: 10.12005/orms.2021.0387

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In this paper, the power geometric (PG) operator and the geometric Heronian mean (GHM) operator are combined based on interval-valued Pythagorean fuzzy environment, and the interval-valued Pythagorean fuzzy power geometric-geometric Heronian mean (IVPFPG-GHM) operator and interval-valued Pythagorean fuzzy weighted power geometric-geometric Heronian mean (IVPFWPG-GHM) operator are proposed. In the process of fuzzy information aggregation, the novel operators not only reflect the correlation between attributes, but also avoid the interference caused by experts' singular value (too large or too small). In addition, some basic properties of new operators are also studied. Finally, multiple attribute group decision making (MAGDM) method based on IVPFWPG-GHM operator is presented, and a practical example is given to illustrate its feasibility and rationality.

Study of Dynamic Pricing and Service Decision in Supply Chain Integrating Online and Offline Channel

WANG Wei-hao, HU Jin-song

2021, 30(12):  84-91.  DOI: 10.12005/orms.2021.0388

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This paper focuses on an O2O supply chain system which consists of a traditional e-commerce company and an offline brick and mortar retailer. Extant literature illustrates that offline service can elevate the demand of the online and offline channel, which accounts for why more and more companies are willing to embrace offline shops. Among these companies, many choose to open their own-operating shops while others may be inclined to cooperate with the established retailer which exactly corresponds to the centralized and decentralized pattern. Consequently, this paper explores the optimal dynamic strategies of both players under both scenarios and conduct the sensitivity analysis of decisions regarding important parameters. Meanwhile, given the marginalization effect innate in decentralized decision, we also devise a cost-sharing incentive mechanism which intends to coordinate the supply chain. The results show that 1)when the offline channel preference increases, supply chain members should always elevate their offline pricing; 2)cost-sharing strategy can enhance the investment of brick-and-mortar retailer in service and therefore boost the goodness level; 3)cost-sharing strategy can achieve the Pareto improvement by advancing the profits of both players; 4)under certain circumstance, the cost-revenue sharing mechanism can coordinate the supply chain.

Research on Dynamic Discount Decision of Supply Chain Finance Based on Working Capital Information Matching Platform

SONG Hua, YANG Xiao-ye

2021, 30(12):  92-99.  DOI: 10.12005/orms.2021.0389

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At present, dynamic discounting based on the working capital matching platform is a new supply chain finance model which is gradually concerned by the industry. This paper builds a dynamic discounting decision model of two-stage supply chain, and reveals the mechanism of dynamic discounting to improve the cash flow of supply chain participants. First of all, by considering the independent decision-making of dynamic discounting, this paper obtains the boundary condition of daily discount rate, the daily discount rate when the utility of both parties is maximum, the optimal preparation scheme and the minimum boundary value of working capital under the buyer's mixed payment mode. Secondly, considering the optimal decision of dynamic discounting, this paper derives the optimal payment strategy under different relationship between discount rate, and it shows that dynamic discounting can obviously improve the profit situation of both supply and demand.

Research on Data Opening Strategy and Cooperative Income Distribution Mechanism Based on Differential Game

FAN Zi-fu, CHENG Jiao-jiao

2021, 30(12):  100-107.  DOI: 10.12005/orms.2021.0390

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As an important factor of production in the era of digital economy, data plays an increasingly important role in the operation of national economy. However, at this stage, China's social data is still in its infancy, so it is urgent to accelerate the data opening and sharing. In order to accurately analyze the data opening strategies of the government and the enterprises, the Nash non cooperative game, Stackelberg master-slave game and cooperative game models are constructed respectively by using differential game, and the optimal effort level, the optimal trajectory of social data opening level and the optimal return function of the government and the enterprises in three situations are obtained. Secondly, in the cooperative game situation, the time factor is introduced into Nash negotiation model to further analyze the dynamic income distribution mechanism with time consistency when the government and the enterprise cooperate. Finally,combining numerical simulation we analyze the sensitivity of related parameters. The research finds that when the proportion of government income distribution is more than 1/3, the revenue and social data opening level of Stackelberg master-slave game are higher than that of Nash non-cooperation; under the condition of cooperation, the total revenue and social data opening level of both sides can reach Pareto optimal state.

Research on the Stability of Green Technology Innovation Alliance for Government-industry-university Based on Multi-player Game

CHEN Heng, YANG Zhi, QI Kai

2021, 30(12):  108-114.  DOI: 10.12005/orms.2021.0391

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To solve the cycle of “environmental pollution-economic development”, these scientific questions that the government-university-industry alliance can facilitate the green innovation activities have been widely concerned by scholars and entrepreneurs at home and abroad. In this paper, based on evolutionary game theory, the tripartite evolutionary game model of government-enterprise-university is established to study the stability of green technology innovation alliance. Under the dynamic environment, we analyze the evolution law of government-industry-university in the process of interest game, and find key factors that affect the stability of green technology innovation alliance. Finally, the effectiveness of the model is demonstrated by numerical simulation analysis. The research results show that the government participation can effectively promote the system to optimal state in the green technology innovation alliance. The intensity of government incentives has a positive correlation with the stability of the green technology innovation alliance. At the same time, the government-industry-university should formulate reasonable default costs under the framework of the alliance contract, which can effectively avoid the opportunistic behavior of alliance members. What's more, industry groups and university groups have an optimal distribution ratio of R&D costs and green innovation benefits in the alliance.

Study of Sharing Distribution Model Based on Dynamic Genetic Algorithm

WANG Ze-peng

2021, 30(12):  115-122.  DOI: 10.12005/orms.2021.0392

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Aiming at issues of low loading rate, large number of distribution vehicles,and high cost of distribution, wecome up with an optimization pattern of urban distribution, which is based on resource sharing between different retailers. Taking fuel consumption and uncertain demand into account, and setting minimizing total cost of distribution as the objective,we build the model and use improved genetic algorithm, which are based on dynamic parameters, to solve the model. Finally, wetest the delivery method under resource sharing and algorithm by numerical example. The result shows that the sharing delivery method can reduce the number of vehicles, improve loading rate and cut the cost of distribution effectively, and at the same time, the improved genetic algorithm can solve the model efficiently and accurately.

Time Delayed GM(1,N) Model for Mixed-frequency Data

WANG Jie-fang, TIAN Chen-meng

2021, 30(12):  123-127.  DOI: 10.12005/orms.2021.0393

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Under the background of mixed frequency data with different sampling frequencies and different spacing, considering that time delay is a common phenomenon of causal action between system elements, a mixed frequency GM(1,N) modeling method with delay parameters is proposed. According to different characteristics of time delay, the models are divided into two types: GM(1,N) model with synchronous time delay and GM(1,N) model with cumulative time delay. The synchronous type is used to characterize the time-delay relationship with fixed time delay but uncertain initial time. The cumulative type is used to represent the time-delay relation of uncertain time delay length and progressive superposition of causal effect. The exponential Almon function is taken as the distribution function of time delay, which can be completely driven by data to generate various forms such as increasing, decreasing, S-type, U-type and bell type, which is helpful for mining the information of time delay in mixed frequency data. The numerical results verify the validity of the model. The model has strong applicability for the mixed frequency time-delay system with low frequency and small sample data.

Application Research

The Influence of Environmental Protection Tax on Social Distribution in View of Supply Chain

WEI Guang-xing, YAO Yan-ling

2021, 30(12):  128-135.  DOI: 10.12005/orms.2021.0394

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The Environmental Protection Tax Law implemented in 2018 provides a legal basis for pollution taxes. As a kind of new cost, the environmental protection tax will be transferred downstream along the supply chain, and hereby change the institution of social distribution. This paper probes the influence of environmental protection tax on social distribution in view of supply chain. Firstly, by exploring how it is transferred along the supply chain gradually, it is found that environmental protection tax will reduce both enterprise profits and consumer surplus. Secondly, by comparing the relative extent in reduction of enterprise profits with consumer surplus, it is found that environmental protection tax will promote the status of consumers in social distribution, and improve that of retailers too, but reduce that of manufacturers. Finally, by comparing the inductions of enterprise profits with consumer surplus and the tax revenue resulted from the environmental protection tax, it is found that environmental protection tax will result in net social welfare losses, and the tax burden sharing is very unbalanced, where the most is burdened by the manufacturers, while the least by the consumers.

Evaluation and Optimization of an Auto Seating Arrangement System

WEI Jin-rui, HUANG Yue, CHEN Xu, NI Kai-lai

2021, 30(12):  136-143.  DOI: 10.12005/orms.2021.0395

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In order to solve the seat-occupying and seat arrangement problems in libraries, this paper works onevaluating and improving the auto seating arrangement system in libraries. Take a university library for example. A Multi-Objective Grey Wolf Optimizer model (MOGWO) for solving the problem of how to allocate seat resource fairly is built under multi-objective constraints, and the different popularity among seats which is measured by Theil index is listed. Based on the reservation function, this system can reasonably restrict readers' seat selection behaviors. Finally, computational results based on high frequency data are provided to demonstrate the effectiveness of the model and the algorithm. This paper also puts forward some corresponding management suggestions and supports the decision of making management plans.

Pricing Structure of Online Platform Retailer under Independent Sales Mode

FAN Xiao-jun, LIU Yan

2021, 30(12):  144-149.  DOI: 10.12005/orms.2021.0396

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In order to cope with the increasingly fierce market competition and obtain higher profits, online platform retailers choose to enter the retail market to sell the products independently. This article focuses on the channel structure where online platform retailers are in a leading position, and analyzes the impact of online platform retailers' independent sales on channel members' profits and pricing strategies under transaction-based per-unit fee. The results show that independent sales of online platform retailers have brought positive spillover effects. When the competition coefficient is large enough, (1)the profits of channel members will be improved, and with the increase of market competition, the profits of channel members will increase more significantly; (2)online platform retailers are likely to announce higher platform fee, and possibly channel members also set higher retail price. More importantly, under the independent sales model of online platform retailers, the overall profit of the channel has been improved, and there is a Pareto improvement.

Analysis of Performance for Ambulance Emergency

WANG Xin-tian, QIANG Rui, ZHANG Yong

2021, 30(12):  150-157.  DOI: 10.12005/orms.2021.0397

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In order to accurately evaluate the performance of urban emergency medical system(120 emergency), the ambulance state is defined as idle or busy considering the urban ambulance rescue dispatching process, and the state space of the ambulance fleet is established. Based on the multiplication rule of conditional probability and detailed balance equations of birth and death process, approximate linear equations and its iterative solving algorithm are constructed to solve the work intensity of each ambulance (the proportion of the time that the ambulance is in the busy state). The mathematical procedures of performances, including the fraction of the inter-district dispatches and the response time, are given. To verify the proposed model, the performances of the ambulance system in Suzhou are evaluated, and the improvement schemes of the ambulance system deployment are proposed to equalize the work intensity and minimize the response time. The result shows that the proposed model can handle a large number of ambulances (more than 15) that the previous models cannot. The dispatch priority of ambulance in each zone, set by the rescue distances, enables ambulances to share, and balances each ambulance work intensity and the fractions of inter-district dispatches. The schemes of ambulance deployment and emergency zone partitions based on rescue performances can effectively minimize response time under a fixed number of ambulances.

Dynamic Evaluation of Development of Regional Technology Effective Supply Based on Catastrophe Progression ——Perspective of Fuzzy Incentives and Punishments

ZENG Xiao-chun, LI Sui-cheng,GAO Kun

2021, 30(12):  158-164.  DOI: 10.12005/orms.2021.0398

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The development of technology effective supply is different in different regions and different time periods, given corresponding incentives and punishments. How to determine the boundary between incentives and punishments is especially important. Considering the feelings of incentives and punishments and adopting a fuzzy boundary between incentives and punishments, this paper is used by the perspective of fuzzy incentives and punishments. Firstly, the static evaluation is based on catastrophe progression, establishing an evaluation index system for the technology effective supply in regions. Secondly, the dynamic evaluation model of regional technology effective supply is established based on the perspective of fuzzy incentives and punishments. Using the sample of 30 provinces in China from 2013 to 2018, the empirical study shows that areas with high static evaluation values are subject to large incentives, and areas with low static evaluations are subject to large punishments. This paper reflects the difference of development about the effective technology supply in different regions, while the dynamic evaluation results show that there are big differences. Comparing static results to dynamic results, this paper implements fuzzy incentives and punishments, achieves incentives and punishments, which blurs the boundary between incentives and punishments, compensates for the limitations of the clear boundary of incentive and punishment in actual regional economic development, and reflects the flexibility of regional technology effective supply development.

Spillover of Information Between Interbank and Exchange T-bond Markets in China

ZHANG Mao-jun, LI Hao, NAN Jiang-xia, WANG Guo-dong

2021, 30(12):  165-171.  DOI: 10.12005/orms.2021.0399

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In this paper, the direction, level and dynamic trends of the spillover of information between interbank and exchange T-bond markets in China are investigated by the variance decomposition of the prediction error of VAR model and Granger causality test. Our results show that the return spillovers and volatility spillovers between the interbank and the exchange T-bond market have an increasing dynamic trend; the interbank T-bond market is the senders of information in the return spillovers while the exchange T-bond market is the senders of information in the volatility spillovers. Moreover, the interest rate changes and market liquidity significantlynegatively affect the total return spillovers and volatility spillovers.

Supervision Strategy of XBRL Technology Adoption from the Perspective of Evolutionary Game

PAN Ding, XUE Yong

2021, 30(12):  172-178.  DOI: 10.12005/orms.2021.0400

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By constructing the asymmetric game model of government and enterprise, the interaction strategies of the two parties in the supervision process of XBRL technology adoption are studied, and the evolution equilibrium strategy of the model with different parameter changes is demonstrated by MATLAB simulation. The results show that the cost and benefit of XBRL technology, government supervision, punishment,and subsidy coefficient are the key factors affecting both sides of the game. By reducing technical costs, increasing penalties and supervision, and increasing subsidies to enterprises, it will help increase the incentive for companies to adopt XBRL. Finally, from the aspects of reducing the cost of technology, implementing the staged supervision strategy in different periods and promoting the coordinated development of multi-agents, the management suggestions for promoting the adoption of XBRL technology are proposed.

Quantitative Research on Futures and Options in Shanghai Copper Market

ZONG Zhe, ZHENG Chong-yang, WANG Jian-qiu, ZHAO Hui

2021, 30(12):  179-184.  DOI: 10.12005/orms.2021.0401

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As the largest copper consumer market in the world, Shanghai Copper Futures holds the most important position in China's commodity market. Especially with the official listing of the options on copper futures on the Shanghai Futures Exchange in September 2018, the way of participating in Shanghai copper market has been expanded. Although China has the world's leading copper trading market, the research on pricing futures and options on the underlying futures in the field of quantitative finance is seriously inadequate in China. In the field of quantitative finance, Schwartz Two-Factor model (1997) is considered as a benchmark model for pricing a futures contract. This paper finds that through Schwartz Two-Factor model (1997) generally works in the China's Copper Futures Market, it is still shown that flaws needed to be fixed to get better results. Therefore, this paper proposes a way to run the Schwartz Two-Factor model with stochastic parameters, so that the prediction accuracy is greatly improved. In addition to these, according to the early literature on pricing call options on futures (Hilliard and Reis (2018) & Ewald et al (2018)), this paper proposes the formula for pricing put options on futures and finds that the methods proposed and tested in this paper are useful for pricing options of Copper Futures with different features and different maturities. Last, this paper argues that there is arbitrage possibility in the Shanghai Copper market.

Research on the Risk Compensation of Science and Technology Insurance Based on VaR

LUO Yan, GU Zheng

2021, 30(12):  185-190.  DOI: 10.12005/orms.2021.0402

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VaR is an effective tool for financial enterprises to carry out comprehensive risk management, and the insurance company method of C-ROSS quantifying capital. Under the principal-agent framework, this paper studies a risk compensation contract of science and technology insurance using the VaR tool, expounds the theoretical basis of science and technology insurance risk compensation, and obtains the explicit solutions of the risk compensation contract under the cases of symmetry and asymmetry information respectively. The results indicate that fixed compensation in the contract plays a leading role, and the optimal marginal incentive coefficients could be positive or negative, decreasing with the confidence level of insurance company.

Is the Fund Holding Lottery-like Stocks Based on Lottery Preferences? ——from the Angle of Information Mining

JIA Li-na, WANG Fang-yun, LI Hui-ying, SUN Hui

2021, 30(12):  191-197.  DOI: 10.12005/orms.2021.0403

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From the perspective of fund's information mining behavior, this paper analyzes the reasons behind the fund holding lottery stocks using the stocks holdings data of funds. The empirical results show that fund shareholding ratio of lottery-like stocks increases significantly the stock price synchronicity. Funds pay more attention to intangible information in investing the lottery-like stocks, but focus more on tangible information when the market is depressed. Therefore, it can be seen that the fund's holding lottery-like stocks are the result of information mining, not a pure lottery preference. The research of this paper explains to some extent the motivation of the fund to hold lottery-like stocks, and provides a reference for the supervisory authority to better understand the fund's ability to choose stocks and investment behavior.

Risk Premium of Investor Attention and the Predictability of Stock Return

WU Ke-ke, YU Yan, DONG Da-yong

2021, 30(12):  198-203.  DOI: 10.12005/orms.2021.0404

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Using the history accumulative trading amount data, this paper constructs the risk premium of change in investor attention and level of investor attention, and test its predictive power for aggregate stock market excess return in Chinese stock market. Under the out-of-sample predictability test, the results show that the risk premium of two investor attention significantly predict the next month excess return on Chinese stock market with R2 being 2.68% and 2.50%, respectively. Compared with other predictors in the Chinese stock market, the change in investor attention and the level of investor attention risk premiums show a stronger predictive power. In addition, based on alternative forecasting windows, alternative risk aversion choices and alternative five constructing methods, the risk premium of investor attention also significantly predicts excess returns. Economically, the predictive power of investor attention risk premium for stock market comes from the changes in the business cycle. The predictive power is further improved during economic expansions.

Does Management Performance Forecast Affect the Price of Private Placement? ——from the Perspective of Intermediary Effect

YU Jun-lin, HE Rui-hua

2021, 30(12):  204-211.  DOI: 10.12005/orms.2021.0405

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This paper studies whether and how the listed companies manipulate the newstock price according to the different objects of private placement by using the performance forecast. The empirical results show that listed companies according to the different object of private placement release the performance forecast containing different information to affect the issue price strategically, and the strategic performance forecast will have a remarkable intermediary effect, in particular, if the major shareholders to participate in the subscription of new shares, tend to release bad news earnings forecast, to hold down the new share price, and if big shareholders not to participate in the subscription of new shares, tend to release good news earnings forecast, to raise the new share price; Further classified analysis shows that the performance of non-state-owned listed companies is stronger than that of state-owned listed companies and listed companies that actively disclose performance forecast than that of listed companies that forcibly disclose performance, and the intermediary role of strategic performance forecast is more significant. The conclusion of the study provides a certain reference value for investors' investment decisions and regulatory activities.

Management Science

Modeling of Seru Production System Formation Considering Product-Seru Matching

BAI Zhao-yang, WANG Hao, WANG Shu-ting, LAN Tian-tian

2021, 30(12):  212-219.  DOI: 10.12005/orms.2021.0406

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In view of the decision optimization problem of the conversion of the flow assembly line to the unit assembly system in the Japanese unit production process, this paper minimizes the total completion time and the total worker, considers the product and unit matching relationship, and designs the three-segment chromosome coding method for the problem based on the NSGA-II algorithm.We analyse the change of product and unit matching relationship on the total completion time and show the difference in the total completion time, which is gradually smaller as the number of workers increases.

Green Job Shop Scheduling Problem Considering Machine Energy Consumption

LU Hai-li, SUN Jia-qi, WU Shu

2021, 30(12):  220-225.  DOI: 10.12005/orms.2021.0407

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For the traditional job shop scheduling problem (JSP), on the premise of guaranteeing the due date, the green shop scheduling problem (GSSP) with strategy of turning off and on is studied. The objective is to minimize machine energy consumption. A mathematical programming model is established. Then, under the framework of genetic algorithm, a local adjustment decoding method is proposed according to the characteristics of the problem. This decoding method moves the operations during schedule generation and determines the start time of the process. Finally, a small-scale numerical example is given to verify the validity of the decoding. The genetic algorithm based on local adjustment decoding and sequential decoding is compared and tested by multiple sets of examples. The results show that the proposed local adjustment decoding can reduce the energy consumption of the machine and improve the efficiency of the solution.

Can the Improvement of State Governance System Mitigate Earnings Management? ——Evidence from a Quasi-Natural Experiment

CHEN Ke-jing, XING Bao-xin, WAN Qing-qing, XU Yuan-yuan

2021, 30(12):  226-231.  DOI: 10.12005/orms.2021.0408

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This paper takes Shanghai and Shenzhen A-share listed companies as the research objects and investigates the corporate governance effect of state governance system improvement from the perspective of inspection supervision. The conclusion shows that inspection supervision can effectively mitigate earnings management of enterprises, to be specific, reducing the accrued earnings management of 24% and the real earnings management of 22%. Through parallel trend test, placebo test and propensity score matching, the results are still stable. Compared with local inspection supervision, central inspection supervision has a more significant effect on the management of enterprise earnings. Inspection supervision has a stronger effect on earnings management in corrupt areas. This paper enriches the literature system that state governance system plays the role of corporate governance and reveals the important role of institutional construction in the real economy.

Sales Mode Selection of Fresh E-commerce Considering Farmers' Adulteration Behavior

LIN Qiang, MA Jia-xin, FU Wen-hui

2021, 30(12):  232-238.  DOI: 10.12005/orms.2021.0409

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On the basis of considering the farmer's adulteration behavior and e-commerce sampling test mechanism, a decision-making model of fresh e-commerce supply chain in two sales models of self-operated and platform is established by game theory, and the study comparesthe optimal decision of the parties before and after the sample detection of the e-commerce company and its expectations in different sales models. The study finds that: (1)the sample detection of e-commerce companies reduces the proportion of farmer's adulteration and improves the quality of online sales, but it does not necessarily increase the income of the companies and farmers; (2)regardless of the self-operated mode or platform mode, consumers' trace compensation and the severity of e-commerce enterprises play a role of suppression of farmers adulteration behavior; (3)when farmers sell shoddy products, the cost of sampling, internal and external punishment, credit losses, and platform usage fees will affect the selection of e-commerce companies and farmers on sales models.