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主管:中国科学院
主办:中国优选法统筹法与经济数学研究会
   中国科学院科技战略咨询研究院

Table of Content

    25 February 2024, Volume 32 Issue 2 Previous Issue   
    Research on Frequency of the Joint Network Connectedness of Systemic Financial Risks in China ——Based on the Locally Stationary Non-parametric Time-varying Vector HAR Model
    Qiang Fu,Zelong Shi
    2024, 32 (2):  1-10.  doi: 10.16381/j.cnki.issn1003-207x.2021.1266
    Abstract ( 276 )   HTML ( 37 )   PDF (1171KB) ( 237 )   Save

    In the past decade, China has experienced two critical events - the 2015 stock market disaster and the coronavirus disease 2019 (Covid-19), which have had a great impact on the financial markets. Through the comparison of the two crises, it is found that the impact of the stock market disaster on financial markets is much stronger and longer than the coronavirus disease 2019, although the financial markets experienced sharp declines in both crises. It matters to both governments and academia to find out the reasons behind the differences in the causes of the two crises to financial risks and further figure out the sources of systemic risks.Taking the high-frequency data of financial stocks as object, a locally stationary non-parametric time-varying vector HAR model (tv-VHAR model) under high dimensions is constructed firstly in this article by assuming that the parameters of the vector Heterogeneous Autoregression Model (HAR model) are functions of time t/T. On this basis, the estimation problem under the Curse of dimensionality is solved by applying the Quasi-Bayesian Local Likelihood methods to the tv-VHAR model. Secondly, the frequency component of the joint connectedness is proposed in this article to increase the measurement accuracy of the systemic financial risks by revising the Baruník and K?ehlík (2018) model. Finally, the systemic financial risks in China are systematically analyzed and is proved to have the following 5 features:(1) From October 2010 to October 2020, the total joint connectedness of the financial system risks in China showed a relatively high value and fluctuated continuously.(2) In normal times, high-frequency components account for a larger proportion of the total joint connectedness, followed by the medium-term components, and finally the long-term components. (3) During the crises, the proportion of the high-frequency components declines rapidly, while that of the medium- and long-term components rises rapidly, which sometimes exceeds the former. (4) It is found that the Covid-19 exerted less influence on investors' mid- to long-term belief changes, and the influence lasts for shorter while analyzing in the perspective of frequency, though the total joint connectedness of the critical event are similar. (5) It is found that large securities companies and joint-stock commercial banks mainly act as risk communicators and occupy a dominant position in financial network risk contagion. However, the four major state-owned commercial banks mainly act as risk receivers, and can play as a stabilizer in the financial system as they have the ability to resist risks. In addition, small securities companies and other financial institutions also act as risk receivers.

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    Intertemporal Pricing Strategy Considering Cost Information Transparency and Learning Effect
    Jun Wang, Wenkang Ma, Xinman Lu
    2024, 32 (2):  11-22.  doi: 10.16381/j.cnki.issn1003-207x.2021.2549
    Abstract ( 181 )   HTML ( 26 )   PDF (1277KB) ( 179 )   Save

    As a result of the disclosure of the firm itself or third-parties, a firm’s product-cost information is increasingly transparent to consumers. Meanwhile, durable products usually undergo a production learning effect, which allows the firm to reduce its future unit production cost in the process of repeated manufacturing. Cost transparency, production learning effect and strategic consumers are considered simultaneously in this study. Thus, research questions could be proposed as follows. First, how does the production learning effect affect the pricing strategy and profit of a firm, as well as consumer surplus? Second, under the existence of production learning effect, what is the firm's cost information disclosure strategy? What are the functions of cost transparency? Finally, will the production learning effect change the role of cost transparency?To answer the above questions, a two-period signaling game model is established to explore how cost transparency and learning effect affect the firm’s intertemporal price discrimination and profit, as well as consumers’ strategic waiting decision and surplus. The strategies of the firm and consumers under cost transparency and non-transparency are analyzed, and the impacts of cost transparency and production learning effect are examined. Parameter β is used to indicate the degree of production learning effect.First, the results demonstrate that β can divide the equilibrium outcome into separating and pooling outcomes under information asymmetry. Second, the enhancement of production learning effect is beneficial to both the high-cost firm and consumers and harmful to the low-cost firm. Finally, when the production learning effect is not significant, cost transparency will benefit both the high-cost firm and consumers and harm the low-cost firm; when this effect is significant, cost transparency will still benefit the high-cost firm but damage both the low-cost firm and consumers. These conclusions can provide theoretical guidance for the research on strategic consumers and information asymmetry in the future. Furthermore, firms and consumers can also gain practical experience from our study.

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    Risk-efficiency Mixed Consensus Model Considering Consensus Efficiency and Misjudgment Risk
    Lisheng Jiang,Huchang Liao
    2024, 32 (2):  23-30.  doi: 10.16381/j.cnki.issn1003-207x.2021.2645
    Abstract ( 129 )   HTML ( 9 )   PDF (807KB) ( 98 )   Save

    Due to the high complexity of real-life decision-making problems, the knowledge and experience of a single expert are often not sufficient to meet decision-making needs. Therefore, a group of experts is required to participate in the decision-making process. Because of the differences in experts’ fields of expertise and knowledge, the evaluations of experts may differ or even be oppose. In this case, it is necessary to measure the group consensus degree, i.e., the distance between the consensus center and the evaluations of experts. When the group consensus degree is less than a given consensus threshold, the minimum adjustment consensus model is often used to help decision makers guide experts to revise their opinions so that the group can reach consensus. In the current study, the consensus center used in the minimum adjustment consensus model is the mean of experts’ evaluations derived from aggregation operators. However, influenced by the distribution of information in the group, the consensus center is uncertain. How should a decision maker determine the value of the consensus center? Is there a risk of misjudgment in using a given value of the consensus center to judge if a group reaches the consensus degree? Little research has been conducted on these issues.To answer these questions, firstly, in terms of consensus efficiency, the highly efficient consensus center is defined and then a minimum adjustment consensus model is proposed based on the highly efficient consensus center. Next, on account of the consensus misjudgment risk, the reliable consensus center is defined and propose a minimum adjustment consensus model based on the reliable consensus center. Afterwards, a risk-efficiency mixed consensus model is further proposed, which considers both consensus efficiency and consensus misjudgment risk. A numerical example shows that the proposed models have the following advantages: 1) the minimum adjustment consensus model based on the highly efficient consensus center has less expert evaluation adjustment than the classical minimum adjustment consensus model; 2) the minimum adjustment consensus model based on the reliable consensus center has lower group consensus misjudgment risk than the classical minimum adjustment consensus model; 3) the risk-efficiency mixed consensus model can balance the consensus misjudgment risk and efficiency flexibly by a weight.The problem of consensus misjudgment risk and efficiency caused by the uncertainty of consensus center is discussed and three types of models are proposed that can analyze both consensus misjudgment risk and efficiency, which enriches group decision theory.

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    Study on Supplier's Risk Strategy of Military-civilian Collaborative Innovation about Complex Equipment under Total Supply Disruption
    Xin Huang,Hongzhuan Chen,Yixin He,Jing Ding
    2024, 32 (2):  31-42.  doi: 10.16381/j.cnki.issn1003-207x.2020.1914
    Abstract ( 109 )   HTML ( 5 )   PDF (667KB) ( 85 )   Save

    Under the condition of trade friction, it is more and more common for domestic suppliers to participate in equipment development and innovation activities. As the representative of high-end equipment, the implementation of collaborative development of complex equipment in the context of national “civil military integration” can promote the upgrading and high-quality development of equipment. Supply disruption occurs frequently, how to deal with the situation of complete disruption and how to make use of the potential civil (military) suppliers and the main manufacturers to carry out collaborative innovation becomes a research difficulty. Based on the cooperation of complex equipment, the innovation of cooperative development is discussed. Taking the military (civil) suppliers who enters the cooperative development of complex equipment as the starting point, and explores the impact of different types of suppliers' risk attitude (military, civil) on the overall collaborative innovation strategy, then discusses whether the incentive strategy of main manufacturers has any impact. Firstly, the production quantity and revenue function of the main manufacturers, military (civil) suppliers of collaborative innovation are constructed. Secondly, taking whether the main manufacturers share the cost of supplier collaborative innovation as the research point, considering the loss cost of collaborative innovation, whether the main manufacturers have incentive to share the cost of collaborative innovation of complex equipment is analyzed, the corresponding Stackelberg game model is constructed, and the equilibrium according to the Stackelberg model is calculated. Finally, with the help of the calculation results and numerical verification analysis, the external conditions for the implementation of collaborative innovation and the risk strategies for military (civil) supplier is obtained. The results show that: when the external interruption is small, the main manufacturer and military (civil) suppliers could participate in the complex equipment development process cooperatively, and military (civil) supplier automatically choose to bear the loss cost of collaborative innovation, which is conducive to the implementation of collaborative innovation and the maximization of profits in the supply chain. At the same time, the more cautious risk strategy the military (civil) supplier adopts, the more conducive to the optimal process innovation degree and the optimal value of assembly innovation degree. It is also beneficial for the main manufacturer to implement the process innovation cost sharing strategy, the more favorable. The influence of suppliers' risk attitude on the incentive strategy of complex equipment collaborative innovation activities is analyzed, which is under the possible conditions of external interruption, and provides some reference for the conditions of complex equipment civil military collaborative development, and the risk strategy selection of civil military suppliers participate are discussed.

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    Four-Party Evolutionary Game Analysis of Product Quality Regulation Considering Internal Employee's Participation
    Zheyun Zhao,Yumin Liu,Xiaoying Liang,Ning Wang
    2024, 32 (2):  43-53.  doi: 10.16381/j.cnki.issn1003-207x.2020.2406
    Abstract ( 111 )   HTML ( 5 )   PDF (815KB) ( 154 )   Save

    Internal employee plays an increasing role in the recent practice of product quality regulation, such as carcinogenic Three Squirrels, inferior masks and kit during the period of COVID-19, Changsheng Vaccine incident, et al. Existing researches focused on the product quality supervision system comprised of government regulation, enterprise self-discipline and media supervision, which ignore the role of internal employee. Based on previous studies, a new regulation subject, internal employee or whistle-blower, is introduced. Then the evolutionary game model comprised of employee, government, enterprise, media and the public is constructed to analyze the effect of employee whistle-blowing on product quality regulation. The results show that employee participation is a beneficial supplement to external quality regulation subjects dominated by the government, which alleviates the low efficiency of government regulation caused by information asymmetry and limited regulation resources. Whistle-blower protection and reward system are the main factors jointly affecting employee’s strategy selection. Whether an employee’s whistle-blowing can play a supervisory role over enterprises and governments is not only influenced by government accountability and enterprise punishment, but also by whether report information is concerned by the media and the public. Finally, he important influence of whistle-blower on the strategy selection of enterprises and government is analyzed through combining the case of the Changsheng Vaccine incident. The interactive mechanism among potential whistle-blower, media, government, enterprise and the public is studied under the scenario of product quality regulation, which enriched the study of internal employee in product regulation. Besides, this research can be further extended to other areas, such as financial regulation, et al.

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    A risk-Averse Inventory Decision-making Model with Quality Incompleteness
    Jie Chen,Lingbo Xing,Weisheng Li,Zhixiang Chen,Chongping Chen
    2024, 32 (2):  54-64.  doi: 10.16381/j.cnki.issn1003-207x.2021.0339
    Abstract ( 90 )   HTML ( 4 )   PDF (942KB) ( 72 )   Save

    Quality uncertainty is one of the most important risk sources of the inventory system, which has a negative correlation with the supply capacity on the supply side. Meanwhile, the corresponding linkage effect induced by the quality uncertainty has a disturbing effect on the decision-making behavior of the inventory system, and then affects the risk preference of decision-makers. Therefore, based on the uncertainty of supply capacity, purchase price, wholesale price, residual value and other factors caused by quality imperfection, an inventory decision model with risk aversion under imperfect quality is proposed by Markov process. According to the results of the new model and numerical simulation, the following important conclusions and management implications can be drawn:Firstly, the effect of quality level and supply capacity on optimal expected order quantity and expected profit of inventory system has consistent attribute, that is, the effect of quality level and supply capacity on both have a positive correlation. When the quality level and supply capacity are in the optimal state, the optimal expected order quantity and expected profit reach the optimal value, otherwise vice versa. In addition, if the quality process{Zk} meets ergodicity and irreducibility, the inventory system has a good robustness, and the decision maker can obtain relatively stable expected profits as long as he takes a robust ordering strategy.Secondly, under the multiple random decision environment which is formed by the quality level, supply ability, pleased, wholesale price, the salvage value and demand, the transmission mechanism of risk aversion factor has an invariance property to the decision making mechanism, that is, the attribute of relationships (positive correlation) between risk aversion factor η and optimal expected order quantity and expected profit is not affected by exogenous random factors. This further verifies an important conclusion in behavioral science, that is, in different decision-making environments, the higher the degree of risk aversion of decision makers, the more conservative they will adopt strategies.Thirdly, the relevant conclusion shows that the post-decision information set has certain advantages which is derived from incorporating Markov process into the theoretical framework of the classic risk-averse newsboy model, that is, based on the statistical regularity of Markov process, the traditional post-decision information can be extended from two dimensions to five, and then enrich the ideological connotation of the post-decision information set, to describe the movement mechanism for the optimal expected order quantity, expected profit, order quantity robustness, expected profit stability, return expected profit and other elements of the inventory system. Obviously, Multi- dimensionalization of post-decision information set is more conducive to revealing the statistical structure of stochastic inventory system and perfecting the evaluation mechanism of reliability and performance of inventory system.

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    Research on Pricing and Channel Strategies of BODS Omni-channel Green Supply Chain with Stochastic Reference Price
    Zhibing Lin,Qing Wu
    2024, 32 (2):  65-74.  doi: 10.16381/j.cnki.issn1003-207x.2021.1221
    Abstract ( 91 )   HTML ( 6 )   PDF (603KB) ( 68 )   Save

    In the context of new retail era, the “Buy-Online and Deliver-from-Store”(BODS) omni-channel model has been adopt by some green manufacturers to expand the green product market. In addition, the demand for green products is affected by the stochastic reference price of consumers. Therefore, in this paper, a BODS omni-channel green supply chain consisting of a risk-neutral manufacturer and a risk-averse retailer is proposed with stochastic reference price using a Stackelberg game framework. After the wholesale price and green degree of products are decided by the manufacturer first, one part of the products are wholesale to the retailer, who decides the marginal income of these products; the other part of the products are directly sold to consumers by the manufacturer through the online channel, but delivered by the retailer, who charges a commission for each unit of products from the manufacturer. With these assumption, a decentralized decision model is constructed, the decentralized decision-making equilibrium is given by the backward-induction method. On this basis, the influence of consumer’ stochastic reference price and commission coefficient on the optimal pricing decision and expected profit under decentralized decision model is analyzed. Then, the supply chain coordination issue is discussed based on centralized decision model. Next, the model is extended to a mixed-channel model. Finally, the channel strategies preferences of supply chain members are discussed by numerical methods.The results show that (1)In the BODS omni-channel green supply chain, the greater the dispersion of the consumers’ stochastic reference price, the more beneficial to the manufacturer and the supply chain, but not necessarily to the retailer; In addition, the larger the BODS channel’s commission coefficient, the more beneficial to the supply chain; (2)The supply chain can be coordinated by a combination of revenue-sharing and cost-sharing contracts; (3)When the basic market demand for offline channel is small, the manufacturer prefers the traditional dual-channel strategy, while the retailer prefers the BODS omni-channel strategy. When the basic market demand for offline channel is large, the manufacturer prefers the BODS omni-channel strategy, while the retailer prefers the traditional dual-channel strategy.

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    Research on the Marketing Strategy of Community Group Buying Supply Chain Based on Network Externality
    Qiuxiang Li,Jing Zhang,Yimin Huang,Ershi Qi
    2024, 32 (2):  75-86.  doi: 10.16381/j.cnki.issn1003-207x.2021.1420
    Abstract ( 138 )   HTML ( 21 )   PDF (944KB) ( 145 )   Save

    The network externalities and marketing strategies of the community group buying supply chain are studied. Based on the network externalities of community group buying products and the different entities responsible for marketing efforts, six marketing decision models are constructed to explore the effects of network externalities and effort levels on product demand, pricing, and platform and team leader returns. The optimal marketing strategy selection problem for the platform and team leader under six marketing methods is analyzed. It is found that: (1) Under different marketing methods, network externalities are positively correlated with product demand, pricing, and profits of platforms and team leaders within a certain range. Beyond a certain range, team leaders or platforms may engage in free riding behavior. (2) In the absence of network externalities, when the marketing efforts of the platform are low, the profits of the platform and the team leader are highest when the team leader separately markets. When the marketing efforts of the platform are high, the revenue of the platform and team leader is highest when the platform is separately marketed. (3) When there is network externality, when the platform's marketing efforts are low, the platform's revenue is highest when the team leader is marketing alone, and the team leader's revenue is higher when the platform and team leader are marketing simultaneously. When the marketing efforts of the platform are high, the revenue of the platform and team leader is highest when the platform is separately marketed.The impact of network externalities on the selection of community group buying platforms and marketing efforts by group leaders in the community group buying supply chain is studied. Based on the different entities that bear marketing costs, different marketing decision-making models without and with network externalities are constructed, and the optimal marketing strategies under different marketing efforts are analyzed; And combined with numerical analysis, the relationship between different decision models is compared, and corresponding management insights are provided. It is found that: (1) under the independent marketing approach of the platform, network externalities are positively correlated with the platform's marketing efforts, platform pricing, product demand, and the revenue of the platform and team leaders within a certain range. Beyond this range, team leaders may engage in free riding behavior. (2) In the case of individual marketing by team leaders, network externalities are positively correlated with marketing efforts, platform pricing, product demand, and the revenue of both the platform and team leaders within a certain range. Beyond this range, the platform may engage in free riding behavior. (3) In the case of simultaneous marketing by team leaders and platforms, network externalities are positively correlated with their marketing efforts, platform pricing, and product demand. However, network externalities are positively correlated with the platform and team leader's revenue within a certain range. Beyond a certain range, the platform or team leader may engage in free riding behavior. (4) The choice of platform and team leader marketing models depends on the level of marketing efforts of both when there is or is no network externality.For the platform, the team leader is closest to consumers and has more advantages in marketing. The platform can take appropriate incentive measures to increase product sales and obtain higher profits. Secondly, it makes reasonable use of the network externalities of community group buying products, establishes reasonable sales prices, and effectively reduces problems such as low price dumping and vicious competition on community group buying platforms in this study. For team leaders, they should make reasonable use of their own advantages for marketing efforts, not just rely on community group buying platforms, but take the initiative to obtain higher profits and achieve mutual benefit and win-win between community group buying platforms and team leaders.

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    Logistics Cooperation and Operations Decision of fresh E-commerce Supply Chain Considering Random Demand
    Xin Cui,Chunfa Li,Chi Zhou,Xinxin Mi,Yao Shen
    2024, 32 (2):  87-98.  doi: 10.16381/j.cnki.issn1003-207x.2021.1751
    Abstract ( 204 )   HTML ( 21 )   PDF (1342KB) ( 191 )   Save

    Logistics drives the operation of fresh products e-commerce supply chain. During the logistics process of fresh products from fresh product supplier to consumers, various suppliers can provide fresh-keeping logistics services. Third-party logistics providers can act as service providers and operate fresh-keeping logistics services independently. Logistics providers can cooperate with fresh product suppliers to jointly operate fresh-keeping logistics services. It is also a new trend for some fresh e-commerce platforms to build logistics networks. How do the supply chain members of fresh e-commerce supply chain choose among the above three logistics cooperation modes? To solve the problem, it focuses on the logistics cooperation model of fresh e-commerce supply chain in this paper, and a Stackelberg game model is established.Our supply chain model is composed of the fresh product supplier, the fresh e-commerce platform, the logistics service provider and consumers. We marked the independent operation mode of logistics provider as Mode A, the cooperation mode between logistics provider and fresh product supplier as Mode B, and the cooperation mode between logistics provider and fresh e-commerce platform as Mode C. The product price, product freshness and product demand of the three modes are compared, and the predicted value of product demand and the preference of cooperation mode of supply chain members is studied by numerical simulation.The results show that logistics cooperation can definitely improve the retail price of products and delivery freshness of the products. When the logistics provider operate independently, the order quantity of the fresh e-commerce platform should be very small, because it has to bear too much ordering cost. When logistics provider cooperates with fresh supplier or fresh e-commerce platform, the e-commerce platforms can increase the order quantity of products. When consumers are not sensitive to the price of a product, but sensitive to the freshness of a product, it is easy for supply chain members to collaborate. To achieve cooperation, members of the supply chain need to negotiate to determine the proportion of benefit distribution.

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    Green Technology Selection and Product Pricing Research under CT and Government Subsidies
    Yanchun Pan,Xiaochen Ma
    2024, 32 (2):  99-107.  doi: 10.16381/j.cnki.issn1003-207x.2021.1779
    Abstract ( 111 )   HTML ( 11 )   PDF (914KB) ( 75 )   Save

    In this paper, under the background of carbon emission cap and trade (C&T) policy, the Stackelberg game model of maximizing government welfare and controlling and emission enterprise’s profit is constructed to explore the choice of green technology and product pricing decisions of controlling and emission enterprises under different government subsidies (unit product subsidy and green technology cost subsidy). Furthermore, the influence of different government subsidies on carbon emission control enterprises and social welfare is further analyzed. The results show that compared with the cost subsidy of green technology, the optimal price of unit product subsidy is higher, and will lead to more green production and consumption. The cost subsidy of green technology has lower carbon emissions and higher corporate profits. When the total budget of government subsidy is the same, the cost subsidy of green technology is more likely to encourage enterprises to invest in green technology. It is shown that government subsidies cannot guarantee the investment in green technologies and the reduction of total carbon emissions of enterprises, but depend on the range of green technology cost, carbon emission reduction rate and carbon emission intensity of enterprises. In addition, the social welfare under unit product subsidy is better than the social welfare under green technology cost subsidy. Numerical experiments verify the results of this paper. Finally, some suggestions on government subsidy policy are given.

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    Minsum k-sink Location Problem on Dynamic Path Networks with Non-confluent Flow Constraint
    Hongmei Li,Xiangyue Zhang,Taibo Luo,Yinfeng Xu
    2024, 32 (2):  108-118.  doi: 10.16381/j.cnki.issn1003-207x.2021.2181
    Abstract ( 57 )   HTML ( 5 )   PDF (1104KB) ( 47 )   Save

    Over the past few decades, public healthy and security have been threatened by various natural disasters, accidents, and events occurred throughout the world. The losses the disasters bring can be decreased with appropriate emergency shelter locations. In this paper, the k-sink location problem in dynamic path networks under the non-confluent flow constraint is considered, with the goal of minimizing the total completion time. A dynamic path network is consisted of an undirected path with positive edge lengths, general edge capacity, and positive vertex supplies. For each edge, a general traffic speed is given to indicate the time that a unit weight need to travel a unit distance on this edge. The weight on the same vertex can be evacuated to different shelters during the evacuation, i.e., the non-confluent flow constraint.Firstly, according to the uniqueness of the divider between any two adjacent sinks, the optimal dividers and the corresponding weight division are determined. Secondly, the congestion situation during the evacuation is detailed analyzed, and based on that, the original dynamic path network is transformed to a new path network with new vertex weight. And no congestion occurs during the evacuation on the new dynamic path network. Thirdly, an Okn3-time algorithm is proposed based on dynamic programming.Numerical experiments and a practical example are both presented in this paper. The practical example is based on a road in Chang’an district, Xi’an. Numerical results show that as the number of sinks increases, the non-confluent flow model is more effective. According to the results of the practical example, the feasibility and effectiveness of the proposed algorithm are verified. To improve the efficiency of evacuation, non-confluent evacuation model will be a general trend. The models and algorithms constructed in this paper can provide theoretical support for future research and practical application.

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    Study on the Impact of Internet Credit Payment on Retailer's Inventory Decision
    Daao Wang,Huan Wang,Shinan Zhao,Lirong Jian
    2024, 32 (2):  119-128.  doi: 10.16381/j.cnki.issn1003-207x.2022.2230
    Abstract ( 80 )   HTML ( 6 )   PDF (904KB) ( 150 )   Save

    The rapid development of Internet technology has driven the rise of the online retail market. Consumer shopping behavior and habits have undergone significant changes. Using Internet credit payments, consumers with high expectations for products but limited budgets can immediately purchase their favorite products. By providing Internet credit payments, online retailers attract potential consumers with early consumption needs to increase sales and seize market share in financial services. More and more retailers are launching Internet credit payments to activate the potential of consumer demand. Considering consumer behavior, the impact of Internet credit payments provided by retailers on their optimal order quantity and expected profit is investigated. Firstly, based on consumers' budgets and expectations, the probabilities of consumers immediately purchasing goods and purchasing goods through Internet credit payments are constructed. Considering the stochastic conditions of market demand, profit functions are constructed under two scenarios: retailers providing Internet credit payment products and not providing them. The optimal order quantity of retailers in two scenarios is calculated. Secondly, sensitivity analysis is applied to investigate the effects of market default rate, consumer expectations and budgets, and daily service rates on the optimal order quantity and expected profit of retailers. The results indicate that retailers need to comprehensively consider the optimal order quantity and expected profit when pricing goods, as the retail price under the optimal order quantity may not necessarily lead to the maximum expected profit. When providing Internet credit payments, retailers should not design the installment payment period too short. In addition, there are critical thresholds for daily service rates and penalty rates. When it exceeds the threshold, retailers can earn more profits by providing Internet credit payments. Finally, JD Baitiao is used as an example to compare and analyze the optimal order quantity and expected profit under two scenarios: not providing and providing Internet credit payment. A theoretical basis is provided for exploring the impact of Internet credit payments on retailers' optimal inventory decisions.

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    Pricing Decision of Product Service Supply Chain: Impact of Data Resource Mining and Sharing Strategies
    Dongxia Liu,Hong Chen
    2024, 32 (2):  129-140.  doi: 10.16381/j.cnki.issn1003-207x.2022.0007
    Abstract ( 124 )   HTML ( 14 )   PDF (1161KB) ( 99 )   Save

    The rapid development of digital economy promotes the transformation of manufacturing enterprises into services and enriches the business content of manufacturing and sales enterprises in the products services supply chain. Manufacturing service provider not only produces products but also provides comprehensive service packages of products, whiles sales service integrator not only sells products but also provides specific and personalized on-site services. As the most important production factor in digital economy, data resources are becoming the key resources for enterprises to obtain sustainable competitive advantages. In 2018, the proportions of Chinese manufacturing enterprises chose data mining strategy and engaged in network collaboration, service-oriented manufacturing and personalized customization were 33.7%, 24.7% and 7.6%. Mining and sharing of data resources will have a new impact on product and service decisions in product service supply chain. Considering the potential value of data resources, a two-stage dynamic game model of product service supply chain is constructed based on data resource mining strategy and data resource sharing strategy. The optimal operation behavior of supply product service chain under data resource mining strategy and data resource sharing strategy is described. By comparing the decision-making results of product service supply chain under data resource mining strategy and data resource sharing strategy and non-data-resource-mining and sharing, the influence of data resource mining strategy and data resource sharing strategy on product service supply chain are analyzed. Finally,the numerical examples are simulated. The results show that data resource mining strategy and data resource sharing strategy can increase the profit of manufacturing service provider and sales service integrator. The potential value of data resources provides “external incentives” under data resource mining strategy. Manufacturing service providers and sales service integrators are willing to reduce the wholesale price and retail price of products to obtain a larger market. To compensate for the loss caused by product price reduction, the manufacturing service provider will increase the service fee charged to the sales service integrator, while the sales service integrator will reduce the service fee charged to the customer to obtain more data resources. Data resource mining strategy can bring about the growth effect of product and service market. The higher the degree of certainty of data resource value and the higher the conversion coefficient of data resource value, the more obvious the market growth effect is. The higher the degree of data resource sharing and absorption capacity of data resources, the more excess profits the data resource sharing strategy can bring, and the stronger the motivation of manufacturing service providers and sales service integrators to choose the data resource sharing strategy. When the degree of data resource sharing is less than the threshold, data resource sharing strategy can make consumers get the most consumer surplus, increase user stickiness, make the same kind of users gathering, and form the scale effect of data sharing. When the degree of data resource sharing is higher than the threshold, sales service integrator will have the advantage of data information, and increase the retail price of products and service fees charged to customers to obtain higher profit level, resulting in the "winner-takes-all" effect. This study has scientific guiding significance for enterprise to understand the new changes of product and service under data resource mining and sharing strategy and has important reference for further studying the operation behavior of product service supply chain.

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    Service Mechanism and Pricing Based on Fairness Preference of Regular Customers for Non-Monopoly System
    Baomei Ma,Sifeng Liu,Jian Liu
    2024, 32 (2):  141-151.  doi: 10.16381/j.cnki.issn1003-207x.2020.2130
    Abstract ( 74 )   HTML ( 2 )   PDF (717KB) ( 124 )   Save

    Service providers often adopt customer segmentation strategies in the presence of heterogeneous customers (hold different waiting costs). However, when the service operates as a queuing system, network externality among all the customers makes segmentation tricky: shorter wait time provided to one customer type must come at the expense of others, as segmentation redistributes waiting time from higher- to lower-priority customers. Moreover, when customers can compare wait time received by different customer types, customers receiving a worse wait time than expected, due to having a lower service priority, may experience a fairness perception effect that may cause customers to transfer, switch, or balk within the service system, then affect the service provider’s revenue. The first exact analysis of a service provider offering two classes of non-preemptive priority service is provided, which considers both customer perception of fairness and the heterogeneous of service values.First, customers’ fairness perception is modelled as a negative utility (i.e.,α(W2-W1)) on the regular customer proportional to the waiting time difference between the two queues (i.e.,W2-W1) and the parameter of fairness (i.e.,α). Then, the perspective of revenue and a non-monopoly system in which customers can leave the system freely are considered. The findings indicate that whether a service provider should use customer segmentation depends on the value of regular customers and customer’s fairness perception. At first, the service provider should adopt two queues and keep the priority queue and regular queue in relative proximity to present the advantages of shorter waiting times in priority services when the value of regular customers is small, and fairness is weak. With an increasing fairness preference, however, the service provider should maintain only priority service. Considering customer's fairness, it is found that if the value of regular customers is large, a profit-maximizing service provider should cancel the priority fee and induce all the customers to enter priority or keep a regular queue only. Finally, the properties of optimal results are analyzed with the existing results, and then management insight is proposed.The findings are verified by numerical simulation, and this research focuses on the scientific mechanism of classification service and the corresponding optimal service pricing, providing a more practical motivation. The findings confirm the extant research on customer segmentation and the benefits of offering differentiated service and pricing, while also challenging some commonly accepted notions and practices.

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    Industry Allocation, Clustering Degree and Fund Performance
    Qi Zhou,Zhongfei Li,Baijun Deng
    2024, 32 (2):  152-165.  doi: 10.16381/j.cnki.issn1003-207x.2021.1602
    Abstract ( 86 )   HTML ( 8 )   PDF (1502KB) ( 67 )   Save

    Fund market is the most rapid development and largest financial investment tool of market economy countries in the past 20 years, the difficulty of fund selection is no less than the stock. However, most of the research on fund is the attribution analysis of fund performance, and few researches on fund risk from the comprehensive perspective of fund manager, fund market and investors. The research on fund selection strategy is even less. Firstly, based on the market model of US active fund management industry constructed by Feldman et al. (2020), combined with the complex network method, the industrial allocation clustering index suitable for measuring the development level of Chinese fund market is integrated, and the industrial allocation data are used to quantify the efforts of fund managers. On this basis, the optimization problem of fund managers and investors is proposed, and the quantitative relationship in equilibrium between industrial allocation clustering index and fund managers' efforts, as well as that between the index and fund returns is derived. Then the recursive degradation estimation method is used for empirical analysis. Lastly, based on theoretical derivation and empirical analysis, a fund selection strategy is proposed based on the efforts of fund managers, which improves the portfolio analysis framework of “Theory + Empirical+Strategy”. The results of this paper can also provide reference for the research of FOF investment strategy.

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    Research on Closed-loop Supply Chain Pricing and Profit Distribution Based on Noncooperative-cooperative Biform Game and Deposit Return to Recyclers
    Chunxiang Huang,Dengfeng Li
    2024, 32 (2):  166-177.  doi: 10.16381/j.cnki.issn1003-207x.2021.2244
    Abstract ( 81 )   HTML ( 7 )   PDF (935KB) ( 118 )   Save

    The rapid development of China's economy has made the industry's characteristics of “high energy consumption and high emissions” increasingly prominent. Rapid industrialization has inevitably led to serious conflicts between China's economic development and environmental performance, and problems such as ecological deterioration and resource depletion continue to emerge. With the continuous enhancement of public awareness of environmental protection, the economic and environmental benefits generated by the recycling and remanufacturing of waste products and closed-loop supply chains have gradually been valued and recognized by all sectors of society. But the profits brought by remanufacturing activities to manufacturers are not enough to motivate them to actively participate in recycling and remanufacturing production activities, and the government can play a promoting role. Hereby, how the members of the closed-loop supply chain can simultaneously optimize pricing decisions and profit distribution when the government implements the deposit return system for recyclers has become an interesting issue.In this paper, a noncooperative-cooperative biform game of a closed-loop supply chain with a recycler and two competing manufacturers is established under the deposit return system implemented to recycler by the government, and the influence of deposit refund system on member strategy selection and profit distribution in the closed-loop supply chain is studied. A supply chain transaction model that integrates the non-cooperative part and the cooperative part is constructed through coupling integration of cooperative game and non-cooperative game. In the non-cooperative part, continuous price strategy of two manufacturers which named situation in the closed-loop supply chain is constructed. Then the Nash equilibrium is used to analyze manufacturer's optimal price strategy and optimal profit of members when considering the payment value from the cooperative part. In the cooperation part, von Neumann alliance characteristic function and Shapley value are used to analyze the decision-making and profit distribution of the closed-loop supply chain under any competition situation formed by the non-cooperative part. Finally, a numerical analysis is given to illustrate how deposit or other factors affect the members’ optimal decision of the noncooperative-cooperative biform game under the deposit return system, which reflects the effect of the deposit return system on recycler.The results show that (1) The return of the deposit to the recycler increases the product recovery rate and the sales price, which promotes the recycling and remanufacturing of waste products and the profitability of supply chain members, but the government should pay attention to the reasonable setting of the deposit. (2) Recycling difficulty and cost of recycling influence decisions of recyclers and manufacturers. Excessive difficulty or high cost is not conducive to recycling and remanufacturing. Hence, enterprise managers should consider appropriate recycling strategies and upgrade their technology accordingly. (3) The cost advantage of recycling and remanufacturing can provide an incentive for manufacturers to take an active part in recycling and remanufacturing, and thus reap higher benefits.

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    The Showroom Strategies of the Online Retailer: From the Perspective of Consumer Returns
    Ru Liu,Jian Peng,Yongsheng Cheng,Zhenghua Deng,Xing Qiao
    2024, 32 (2):  178-187.  doi: 10.16381/j.cnki.issn1003-207x.2020.1657
    Abstract ( 95 )   HTML ( 3 )   PDF (695KB) ( 122 )   Save

    With the popularization of the internet and the development of e-payment, online shopping has become one of the main shopping methods for consumers. However, online shopping also has the problem of high product return rate. To reduce the return rate of products, more and more e-commerce enterprises open up showrooms to provide product samples for consumers to experience before they purchase the products. The existence of showrooms will affect consumers' original purchase behavior, and the existence of return cost will also affect the decision and profit of each member of the supply chain. In this paper, an offline to online supply chain consisting of a manufacturer and an online retailer is studied with customer returns considered. The online retailer offers a refund guarantee, which allows consumers to return the products that do not meet their expectations to the online retailer for a full refund.The main work in this paper includes four parts. First, a two-stage game model is established between the manufacturer and the online retailer with the product return considered. The optimal decisions and profits of supply chain members are obtained. Second, the impact of the existence of showrooms on the pricing strategies, product return rates and profits of online retailers as well as their upstream manufacturers are analyzed. Third, the effects of the refund guarantee provided by online retailers are investigated to consumers on the performance of pricing strategies and profits of supply chain members. Finally, the effects of the existence of showrooms and refund guarantees on consumer surplus are further explored.The results show that, under different refund guarantee conditions, online retailers have different strategies on whether to develop showrooms. With refund guarantees, the development of showrooms can increase product demand and reduce product return rate. Whether online retailers develop showrooms, the effects of the refund guarantee on the pricing strategies of both partners depend on the product return rate and the return loss of online retailers. Moreover, the impact of the existence of showrooms and the refund guarantee on consumer surplus depends on product return rate and the return loss of consumers. With the refund guarantee, the showrooms can always effectively improve consumer surplus since product returns can be avoided through product experience before purchase.In summary, the existence of showrooms and the return guarantees have a significant impact on consumers’ purchase behavior. The effects of the existence of showrooms and the return guarantees on the pricing strategies, product return rates and profits of supply chain members are investigated in this paper and the conclusions will be instructive for online retailers and manufacturers in practice.

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    Stochastic Optimization for Fresh E-commerce Network Design and Order Fulfillment under Uncertain Demand
    Jun Zhuang,Dong Yang
    2024, 32 (2):  188-198.  doi: 10.16381/j.cnki.issn1003-207x.2021.2177
    Abstract ( 123 )   HTML ( 11 )   PDF (1678KB) ( 142 )   Save

    With the popularization of online shopping and the implementation of stay-at-home orders, China’s fresh food e-commerce market has been growing rapidly and it has changed our buying habits for fresh food. Currently, there are mainly three forms of fresh food e-commerce in China, namely front warehouse, in-store as warehouse, and community buying group. Among them, as a popular form, front warehouse plays a vital role in ensuring the freshness and on-time delivery rates of fresh foods because it can well address the last three-kilometer delivery problem. However, high investment cost of front warehouses in warehouses location, order fulfillment and inventory holding has become one of the main bottlenecks in restricting its further development for fresh food e-commerce. To deal with the problem with front warehouses, the front warehouse location and order fulfillment problem for fresh e-commerce are addressed, considering the uncertainties in fresh product demands and the shelf-life constraints of fresh products. This problem can be formalized as a two-stage stochastic programming model where the warehouse location and inventory replenishment decisions can be made in the first stage before the realization of uncertain customer demands, and the order fulfillment decisions are made in the second-stage after uncertain customer demands are observed. Due to the computational difficulties and non-linearity in solving the two-stage stochastic programming model, a sample-average-approximation based Benders decomposition algorithm (SBD) is proposed to transform the stochastic model into a sample approximation model by using Latin hypercube sampling method. As a result, this approximation model is a mixed integer programming model and thus can be solved by Benders decomposition algorithm. Finally, a case study about a fresh food e-commerce company in Shanghai, China, which aims to deploy a front-warehouse distribution network for online fresh products, is used to verify the feasibility and effectiveness of the proposed algorithms. It demonstrates that the presented two-stage stochastic programming model can effectively reduce order fulfillment costs for fresh food e-commerce when uncertainties are dealt with. Furthermore, the experimental results reveal that the SBD algorithm performs better than the commercial solver CPLEX, both in small-scale instances and large-scale instances. In addition, the sensitivity analysis indicates that the unit holding cost, expired cost and shortage cost have a significant effect on total order fulfillment cost for fresh food e-commerce. In summary, the proposed two-stage stochastic programming model and corresponding SBD algorithms can well handle the decisions problem with front warehouse locations and order fulfillment for online fresh food e-commerce when uncertainties are encountered.

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    Research on the Correlation Between Industry Risk and Industry Network Structure in China
    Jiliang Sheng,Yi Huang,Juchao Li
    2024, 32 (2):  199-209.  doi: 10.16381/j.cnki.issn1003-207x.2021.2369
    Abstract ( 79 )   HTML ( 5 )   PDF (2173KB) ( 83 )   Save

    In recent years, financial markets have become extremely volatile, especially the global financial crisis in 2008 and the continued global plunge in global stock markets caused by the COVID-19 in 2020. This has drawn lots of attention from academia trying to measure systemic risks and grasp the system risk spread across sectors or markets. The complex relationship between financial markets and their internal elements is the carrier of systemic risk transmission, and their connectedness patterns or structures play an important role in the formation and infection process of systemic risks. For the interconnectedness within a market, once one sector encounters a risk shock, the risk will affect other sectors through strong linkages and contagion mechanisms, and even spread to the entire financial markets. China is currently in a critical period of supply-side reform and economic transformation. As international financial markets become increasingly connected, domestic financial market reforms are gradually deepening and financial innovations are changing rapidly. As the second largest market in the world, Chinese financial system is increasingly attracting attention from countries around the world following a series of liberalisation policies. Also note the unevenness of the development of China's financial sector and the differences in its contribution. In this context, investigation into the connectedness among financial markets and the systemic risk spillovers contagion mechanism across sectors or markets become important and necessary.Pearson correlation coefficients and Granger causality tests are used to construct undirected and directed industry networks, CoVaR models are used to calculate industry risk, and quantile regressions are combined with to explore the interrelationship between industry risk and network structure.With the help of module analysis, the clustering of industry networks under different extreme events and the transmission paths of risks between modules are analysed in depth, while the effect of network structure on industry exposures is examined. The results show that:Both industry networks show a tendency for finance to become the centre of the network, and the directed network constructed by Granger causality test can better explain industry risk. Financial market shocks can have an impact on the structure of industry networks, with different mechanisms for the spread of industry networks under different extreme events. There is also a significant impact of network structure on industry risk, with reductions in industry network clustering coefficients and global efficiency and increases in meso-centrality reducing industry exposure.The findings of this paper have a certain value of participation in financial risk prevention and industrial structure enhancement.

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    Optimal Selection of Relief Procurement Time in the Early Stage of Epidemics
    Yin Xiang
    2024, 32 (2):  210-220.  doi: 10.16381/j.cnki.issn1003-207x.2021.2631
    Abstract ( 53 )   HTML ( 2 )   PDF (843KB) ( 118 )   Save

    Rational allocation of emergency medical resource is crucial for epidemic prevention and control. However, in the early stage of the epidemic, emergency departments are often difficult to accurately predict its spread trend in the first time, and need to update and revise the prediction results through continuous learning of new information in the later stage. Thus, early launch of emergency procurement plans may lead to idle resources due to the inaccurate prediction of epidemic evolution, and late launch may lead to the risk of resource shortage. In this context, optimal selection of the start time of resource procurement becomes an important decision problem faced by emergency departments.Since the 21st century, emergency procurement problems has been widely concerned and deeply studied by scholars. However, most of the existing studies only focus on supplier selection, order allocation, contract design problems under the background of natural disasters such as earthquake and hurricane, but little attention is paid to the start point selection of emergency procurement under the background of epidemic. In particular, compared with natural disasters, the evolution of the epidemic has dynamic and time-varying characteristics, which brings new challenges to the procurement optimization problem.In this context, a novel emergency procurement optimization problem is present under the epidemic situation. Firstly, in order to obtain the optimal start time of emergency procurement, an epidemic observation stopping time (or emergency start-up time) judgment rules is proposed, and the boundary characteristics and influencing factors of the optimal start-up time are analyzed. Secondly, in order to obtain an effective supplier selection and order allocation scheme after starting procurement, a novel mixed integer programming model is proposed after comprehensively considering the differences of each supplier in order quantity, supply capacity, procurement lead time and shortage risk. Thirdly, the above two problems are integrated and a data-driven framework model of emergency procurement is constructed based on the optimization process of “epidemic prediction, emergency response effect comparison, stop-judgment and parameter update”. Finally, the model is applied in a case study, and the simulation results show that the data-driven model not only ensures that procurement decisions are based on epidemic data, but also ensures that epidemic data are updated in real time.

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    Study on the Influence of Government Multi-tool Combination on Enterprise Innovation Behavior
    Kai Zhao,Lei Li
    2024, 32 (2):  221-230.  doi: 10.16381/j.cnki.issn1003-207x.2022.2728
    Abstract ( 99 )   HTML ( 12 )   PDF (1447KB) ( 61 )   Save

    To further improve the coordination of government innovation policy operation and the efficiency of implementation, and dig out the optimal innovation “combination boxing” strategy that can effectively stimulate enterprise innovation behavior, it is urgent to deeply explore and evaluate the actual effects of different innovation policy tools and their combinations. When evaluating the effectiveness of innovation policies, especially the multi-tool combination, both self-selection of enterprises for policies and government agencies’ picking-the-winner strategies often lead to endogenous issues. The multi-level treatment effect model is used which can effectively identify the multi-tool combination, and the actual effect of different innovation policy tools and their policy-mix on the innovation behavior of enterprises in China is evaluated, under the premise of effectively solving the endogenous and selection bias issues. To satisfy the random distribution conditions of causal inference, the multi-level treatment effect model should meet the Conditional Independence Assumption (CIA) and the Overlap Assumption (OA), and the functional expression of conditional expectation value of enterprise innovation can be written as Εyj|x=Εyi|Ti=j,x=β0j+xβ1j. Thereby, the Average Treatment Effect (ATE) when the treatment level changes from Ti to k{0,1,,J}can be estimated. Based on the data of listed enterprises in China from 2009 to 2019, it is found that the multi-tool combination consisting of direct subsidy, tax incentive and government procurement tools may become the government’s optimal implementation strategy of innovation policy, both in stimulating the R&D input and the innovation quality of enterprises. From the perspective of stimulating substantive innovation, government multi-tool combination is more suitable for state-owned enterprises. From the perspective of stimulating strategic innovation, the optimal strategy does not exist. It not only helps to evaluate the effect of innovation policy combination scientifically and reasonably, but also provides empirical basis and practical guidance for improving the design of innovation policy system in this study.

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    Pricing and Advertising Strategy in Advance Selling
    Hua Zhang,Li Li,Xiang He,Xingzhen Zhu,Jiao Hu,Wensheng Yang
    2024, 32 (2):  231-241.  doi: 10.16381/j.cnki.issn1003-207x.2021.0134
    Abstract ( 95 )   HTML ( 5 )   PDF (1015KB) ( 79 )   Save

    Advance selling is a marketing strategy to sell products or services before the normal sales period. With the development of information technology, advance selling is becoming more common in the retail and service industry. Pricing and advertising are important issues in advance selling. When a consumer purchases a product during the advance-selling period and the normal sales period, the valuation of the product may be different, so consumers will purchase it strategically. To examine retailers’ optimal pricing and advertising during the advance selling period, in this paper, the commodity type differences and consumer preferences are taken into account, and the three situations of different types of goods in advance selling are analyzed: valuation increase, valuation decrease and valuation unchanged. Also, consumers’ strategic behavior is considered, and whether consumers will enter the market in the advance selling period are influenced by advertising. In addition, different with the normal sales period, the value-added effect is brought by obtaining earnings in advance, so the value-added coefficient is set in the advance selling period. Through constructing seller advance-selling model, the advance-selling strategy is analyzed under the joint decision of pricing and advertising.The result shows that in the case of valuation decrease, retailers should implement the advance selling strategy if the price of the normal sales period is higher and the value-added coefficient in advance selling period is low. In the case of valuation increase, retailers should take premium advance selling strategies if the price of normal sales period is lower. On the contrary, retailers should adopt discount advance selling strategies if the price of normal sales period is higher. In the case of valuation decrease, retailers should adopt discount advance selling strategies. In the case of valuation unchanged, when the price of normal sales period is higher, retailers should adopt discount advance selling strategies. When the price of normal sales period is lower, retailers should take original price strategies. In addition, retailers’ optimal advertising level increases with product valuation coefficient, the increment coefficient of the capital obtained in advance and the price of the normal sales period. Moreover, retailers’ profit increases with product valuation coefficient and the value-added coefficient in advance selling period. Also, the profit will increase first and then decreases with the price in the normal sales period.Management insights are provided for sellers in the advance selling. Before advance selling, it is necessary for sellers to conduct a market survey of the consumer market and analyze the valuation of advance-selling goods. And in the advance-selling strategy of different types of goods, sellers should implement different advertising and price strategies.

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    Evolutionary Game on Technological Innovation of Enterprises in Complex Product R&D Network
    Naiding Yang,Yu Wang,Yan Wang,Yanlu Zhang
    2024, 32 (2):  242-253.  doi: 10.16381/j.cnki.issn1003-207x.2021.1296
    Abstract ( 86 )   HTML ( 10 )   PDF (1263KB) ( 100 )   Save

    Under the dual incentive of marketization and specialization, enterprises gradually become the main carrier of key technology breakthrough in complex product R&D network. Based on two important technological innovation modes, namely technology imitative innovation and technology collaborative innovation, an evolutionary game model of technological innovation of R&D enterprises in complex product R&D network is constructed under the lack of government role and with government subsidy supervision, considering the factors of technological innovation conversion rate, technology quantity and policy tools, studying the effect of policy tools on the evolution of technology imitation innovation to technology collaborative innovation of R&D enterprises in complex product R&D network. The dynamic evolution of technology innovation behavior and its influencing factors through simulation are also researched. The results show that government tools are inevitable in the development of complex products; Government regulation and punishment can promote R&D enterprises to choose technology collaborative innovation; However, whether the core technology competitiveness of R&D enterprises significantly improves or not still needs further verification.

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    Research on the Influence of O2O Take-out Promotion Strategy on Consumers' Purchase Intention
    Qi Zhong,Guanqiao Qu,Jiafu Tang
    2024, 32 (2):  254-264.  doi: 10.16381/j.cnki.issn1003-207x.2021.2164
    Abstract ( 156 )   HTML ( 17 )   PDF (700KB) ( 141 )   Save

    In the post-epidemic era, how the O2O take-out industry can improve user experience and increase purchase willingness through differentiated promotion strategies is a problem that O2O take-out platform and catering businesses are very concerned about. The mechanism of the O2O take-out price promotion strategy is focused on in this study. The 13 common price promotion methods of O2O take-out are categorized into three types of promotion strategies: coupons, discounts, and additional service fee discounts. Based on the Stimulus-Organism-Response model (SOR model), the perceived promotion value factor is introduced, according to the logic line of price promotion strategy - perceived value - purchase intention, the theoretical model is established. 567 valid sample data are collected through online questionnaire survey for statistical analysis, and a structural equation model is used for hypotheses testing. The influence path and mechanism of O2O take-out promotion strategies with different prices on potential consumers' purchase intention are empirically tested in this paper, and the intermediary effect of the perceived promotion benefit and the perceived promotion cost is verified. The empirical results show that among the three types of price promotion strategies, the purchase intention of potential consumers is most significantly impacted by the coupon promotion strategy; The purchase intention of O2O take-out consumers is only minimally affected by the discount strategy of additional service fee; What’s more, under the discount strategy, consumers are required to make a final purchase decision after weighing the perceived promotion cost and the perceived promotion benefit, it is different from the coupon strategy that directly prompts O2O take-out consumers to make purchase decisions. It not only provides a theoretical framework for the mechanism of O2O take-out price promotion strategy, but also expands the application of promotion theory, perceived value theory and SOR model in some emerging fields in this study. The research conclusions provide theoretical basis and practical guidance for O2O take-out platforms and catering businesses to design and improve their existing promotion strategies and enhance consumers' purchasing willingness.

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    Research on Pricing and Subsidy Strategies of Ride-sharing Platform Based on Driver's Service Effort level
    Yanan Song,Ruijuan Nan,Wei Gu,Daoping Wang
    2024, 32 (2):  265-275.  doi: 10.16381/j.cnki.issn1003-207x.2021.2252
    Abstract ( 85 )   HTML ( 3 )   PDF (1384KB) ( 56 )   Save

    The pricing and subsidy strategies of ride-sharing platform are important decision issues in the operation of platform. The subsidy strategies can be divided into subsidy to driver and subsidy to passengers. The influence of the two kinds of subsidy strategies on the service of driver and the demand of passenger should be fully considered when making subsidy strategies. A Stackelberg game model is established in which platform is leader and driver is follower, the pricing and subsidy strategies of ride-sharing platform are studied,the equilibrium results of different subsidy strategies adopted by platform are compare and analyzed, and the analysis of the model is carried out through data simulation. The results show that the optimal strategy of the platform is to adopt non-subsidy strategy when the commission ratio charged by the platform is less than 1/3, and the optimal strategy for the platform is to subsidize to the driver when the commission ratio charged by the platform is more than 1/3. Compared with the platform to adopt non-subsidy strategy, the platform subsidizes to the driver could improve the service effort level of the driver and increase profit of platform. When the efficiency of service is lower than a certain threshold, the platform subsidizes to driver, which could achieve a win-win situation for the platform and the driver, and realize the total profit close to the total profit of centralized decision-making. The research conclusions provide a reference for ride-sharing platform to make pricing and subsidy strategies.

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    Strategies of Manufacturers Introducing Live Streaming
    Le Wang,Yang Song,Tijun Fan
    2024, 32 (2):  276-284.  doi: 10.16381/j.cnki.issn1003-207x.2021.2472
    Abstract ( 173 )   HTML ( 18 )   PDF (768KB) ( 188 )   Save

    With the development of internet technology, the online direct selling mode is rapidly emerging. However, the direct selling mode by the manufacturer suffer from product untouchability, which will directly affect consumers’ perceived value of the product. As a new online sales mode, live streaming can improve consumers’ perceived value by increasing the touchability of the product, and the price discount during live streaming can also improve consumers' willingness to buy. However, it takes time for consumers to watch the live streaming, which brings hassle cost. Therefore, whether manufacturers introduce live streaming and what pricing strategy to adopt after introduction live streaming are urgent issues to be studied.In order to solve this question, two models of whether the manufacturer introduces a live streaming sales mode are considered. Consumers in the market are divided into live streaming time consumers and non-live streaming time consumers. Considering the consumer’s perceived value of the product and the hassle cost, the consumer’s utility function is constructed, and the manufacturer simultaneously decides the prices of the live streaming product and the direct selling product to maximize its profit. Then the KKT condition is used to solve for the manufacturer's equilibrium pricing and profit to determine the manufacturer's live streaming introduction strategy.The results show that the decision of manufacturers live streaming introduction is related to the average perceived value of products and the change range of perceived value. The higher the hassle cost for consumers to watch live streaming, the lower the demand for live streaming, and the manufacturers raise the direct selling price to obtain more revenue. The profits of manufacturers and demand for direct selling first decrease and then increase with the increase of consumers' hassle cost of watching live streaming. Moreover, with the increase of the perceived value of live streaming for the product, manufacturers increase the sales price of live streaming and reduce the direct selling price to expand the total demand of products. The manufacturer's profit first decreases and then increases with the increase in the perceived value of live streaming for the product. The introduction of live streaming changes the mode of single-channel direct selling and increases the difficulty of manufacturers' decision-making. The research has certain guiding significance for live streaming introduction and pricing strategy of manufacturers in the market.

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    A consensus Model for Large-group Emergency Decision-making Based on Group Wisdomfusion under Social Network Environment
    Xuanhua Xu,Ting Xiao,Xiaohong Chen
    2024, 32 (2):  285-297.  doi: 10.16381/j.cnki.issn1003-207x.2022.0525
    Abstract ( 126 )   HTML ( 8 )   PDF (902KB) ( 144 )   Save

    Aiming at the difficulty of incomplete information and reaching consensus in large-group emergency decision-making,a group wisdom fusion modelintegrating the wisdom of a wide range of groups for emergency decision making are constructed. On this basis, a consensus model for large group emergency decision making was designed to improve the level of group consensus.Firstly, the public group wisdom is mined in social media to obtain public topics and weights, which are used as decision-making attribute information to participate in the emergency decision-making process.Secondly, cohesion coefficient and coupling coefficient are defined based on trust relationship and preference relationshipamong experts, and cluster weights were determined. The group wisdom fusion model is applied to integrate expert wisdom and public wisdom, and hte comprehensive group wisdom result is obtained.Then, consensus feedback adjustment parameters are determined according to the characteristics of emergency decision-making problems, and consensus measurement based on the results of group wisdom fusion is conducted. By analyzing the cohesion characteristics and coupling characteristics of cluster, the type of cluster is identified and the preference adjustment suggestions are proposed to achieve a high consistency large group decision result. As a result, the rationality and superiority of the model methodproposed in this paper are verified by applying it to the case of “preventing and controlling of public health safety incident related to infectious diseases”.

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    Study on the Grid-based Early Warning Model for Online Rumors of Public Health Emergencies
    Guirong Zhang,Zhixiang Dong,Ting Xia
    2024, 32 (2):  298-306.  doi: 10.16381/j.cnki.issn1003-207x.2021.1501
    Abstract ( 81 )   HTML ( 12 )   PDF (1206KB) ( 110 )   Save

    In order to improve the problem of low efficiency and insufficient reliability of online rumors early warning, a grid-based early warning model for online rumors of public health emergencies is established. Firstly, the depth of confusion of online rumors to individual audience is identified longitudinally by quantifying the basic characteristics of online rumors based on the grey-weighted correlation analysis. Secondly, the spread of online rumors to audience groups is predicted horizontally combined the dynamic game of incomplete information with simulation. Finally, the assessment results of both vertical and horizontal dimensions are integrated to define the overall social influence of online rumors, and a visual four-level early warning classification for mild, warning, severe,and danger is carried out, and four emergency management and control strategies of delay, suppression, confronation and suppression are correspondingly proposed. The case of “Shuanghuanglian” is taken as an example to verify the effectiveness of the online rumors grid-based early warning model and its choke tactics. In terms of theoretical research value, it is the first time that the dual perspectives of “identification-warning” and “dissemination-warning” are combined to predict the early-warning level of the overall social influence of online rumors. Based on the interaction between information and audience, the information vagueness of online rumor is estimated more comprehensively, and both the individual cognitive judgment of the audience and the game psychology of the audience group are considered in the evaluation of the spread of online rumors. At the same time, the whole process of this study relies on big data, artificial intelligence and other automatic technologies to improve the objectivity of the evaluation of social influence of online rumors. On the basis of visualizing the four-level warning (mild level, warning level, severe level and danger level) of the overall social influence of online rumors, four emergency management and control strategies are proposed respectively, which promoted the study of online rumors governance.

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    Dynamic Ensemble Time Series Forecasting Model Based on Regime-switching Regression
    Qianqian Feng,Xiaolei Sun,Jun Hao
    2024, 32 (2):  307-314.  doi: 10.16381/j.cnki.issn1003-207x.2022.0599
    Abstract ( 82 )   HTML ( 7 )   PDF (584KB) ( 58 )   Save

    The determination of optimal individual model sets and the setting of ensemble weights are two critical problems for ensemble forecasting, which are related to the prediction performance of the ensemble model. On the one hand, the prediction performance of individual model is unstable and the static ensemble prediction model cannot fully exploit the prediction advantages of individual models; on the other hand, ergodic method to determine the optimal model subset is faced with high computational complexity. To this end, a dynamic ensemble forecasting model is proposed with a regime-switching regression method. First, the optimal individual model set is determined by calculating the mutual information between the individual forecasts and the original data; second, the regime-switching regression is used to ensemble the individual forecasts and get the final prediction values. Through the prediction experiments on the sovereign credit default swaps in nine sample countries, it is found that the proposed regime-switching regression ensemble model performs well, not only better than the individual and combination prediction models but also better than the sliding window technology dynamic combination forecasting model.

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    Optimal Location and Capacity of Pre-cooling Facilities Considering the First-Mile Loss of Fresh Agri-products
    Zujun Ma, Yiran Wang
    2024, 32 (2):  315-323.  doi: 10.16381/j.cnki.issn1003-207x.2021.2618
    Abstract ( 107 )   HTML ( 17 )   PDF (797KB) ( 148 )   Save

    High loss rate has always been a pain point in the circulation of fresh agri-products. As the “First Mile” of cold chains, pre-cooling is the key to affecting the quality of fresh agri-products. In recent years, the construction of pre-cooling facilities in producing areas has been promoted in China. However, due to the difficulty of constructing pre-cooling stations in traditional building forms in fields, centralized pre-cooling is mostly adopted in regions where conditions permit. However, centralized pre-cooling stations are generally far away from the producing area of agri-products. If their locations are not reasonable, the loss rate of fresh agri-products will remain high. Therefore, it is necessary to find the best location scheme of pre-cooling stations considering the “First Mile” loss of fresh agri-products, so as to effectively reduce the loss and logistics costs in the circulation of agri-products. Although little literature has considered the pre-cooling station location problem, only the number and location of pre-cooling stations are considered. However, the type and capacity of pre-cooling stations are not involved. Moreover, different pre-cooling methods for different types of fresh agri-products are not considered, and the “First Mile” loss from producing areas to pre-cooling stations is ignored. Economies of scale in the construction of pre-cooling stations are also not considered.In this paper, the loss of multi-type fresh agri-products after being picked in the logistics process of producing areas→pre-cooling facilities→logistics centers is considered, and corresponding pre-cooling facilities suitable for their pre-cooling needs is built. By considering the economies of scale in the construction and operations of various pre-cooling facilities, a mixed-integer linear programming model is developed to optimize the layout of pre-cooling facilities and determine the number, location, type, and capacity of pre-cooling facilities. A genetic algorithm is proposed to solve the model according to its characteristics. Finally, the effectiveness of the proposed model and algorithm are verified by numerical experiments and a case study on the optimal layout of pre-cooling facilities for fresh agri-products in Chengdu. The results show that the first-mile loss of fresh agri-products and the economies of scale in the construction of pre-cooling facilities will significantly affect the location of pre-cooling facilities. In practice, it is necessary to combine the characteristics of fresh agri-products and the technical and economic indicators of constructing pre-cooling facilities to optimize their locations.

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    Multi-period International Supply Chain Network Equilibrium under Technology Diffusion and Trade Protectionism
    Haixiang Wu,Bing Xu
    2024, 32 (2):  324-334.  doi: 10.16381/j.cnki.issn1003-207x.2021.2060
    Abstract ( 82 )   HTML ( 4 )   PDF (863KB) ( 50 )   Save

    International technology diffusion is an important way to improve a country's technological innovation capability. However, under the current situation of the resurgence of international trade protectionism, the effect of technology diffusion obtained by enterprises through international trade is weakening. Under this new international situation, how to formulate coping strategies to improve its technological level and achieve long-term economic and social development is an urgent problem faced by all countries, especially developing countries. In view of this, Nash equilibrium, variational inequality and Lagrange dual theory are used to establish a multi-stage international supply chain network equilibrium model to analyze the impact of raising tariffs and limiting technology diffusion on technological progress, the interests of supply chain members and the economic and environmental benefits of the whole society. In the model, different values of the tax factor Ktmn are set to distinguish the VAT on domestic sales from the tariff on foreign sales. It should be noted that the taxes in this article are ad valorem taxes. By setting different technology diffusion influence factors etim, the government can control technology diffusion differently. In addition, the government subsidizes the technology investment of manufacturers, and the amount of subsidy is a certain proportion of the technology investment. Combined with numerical examples and network equilibrium variational inequality conditions, the projection contraction algorithm is used to design the program and run it through Matlab software. The following conclusions are drawn from the analysis of numerical results: Under the condition that the costs of enterprises in the two countries are symmetrical and the two countries take equal measures to limit the technology diffusion, increasing the rate of tariff growth will expand the production and consumption of local products, increase the consumer surplus, but reduce corporate profits and social welfare and the technical level of products. Appropriate technical subsidies are beneficial to consumers, enterprises and the whole society, and are conducive to the improvement of technical level. Restricting technology diffusion is not good for consumers, enterprises and society as a whole, nor is it conducive to the development of technology level. Therefore, countries or regions with similar economic strength and scientific and technological level should strive to build free trade zones to achieve mutual benefit and win-win results brought about by free trade and technical cooperation.

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