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Table of Content

    20 October 2020, Volume 28 Issue 10 Previous Issue    Next Issue
    Articles
    Asset Bubbles, Technological Innovation and Economic Growth
    WANG Sheng-quan, CHEN Lang-nan, LIU Ren-hao
    2020, 28 (10):  1-12.  doi: 10.16381/j.cnki.issn1003-207x.2020.10.001
    Abstract ( 589 )   PDF (3481KB) ( 418 )   Save
    The relationship between asset bubbles, technological innovation and economic growth is investigated from the perspectives of both theoretical modeling and empirical study. The previous literaturesreach the inconsistent conclusions on the impacts of asset bubbles on the economic growth. Technological innovation is normally ignored in the bubble models. However, it is found that innovation plays a key role in shaping the relationship between the asset bubbles and the economic growth. The relationship between the asset bubbles and the economic growth depends on the intensity of financial constraint faced by the firms. When the financial constraint is severer than a high threshold value, there exists a positive influence of asset bubbles on the economic growth, suggesting that the asset bubbles drive the technological innovation; vice versa.When the financial constraint fall between a high and a low threshold value, the relationship between asset bubbles and economic growth is ambiguous.
    The relationship between the asset bubbles and the economic growth through technological innovation is tested by presenting a list ofthe stylized facts, building a theoretical model and conducting an empirical study. it is found the consistent results which are shown below:
    First, the dynamic evidences between the asset price and the innovation in China are presented, and find a positive relationship between the two variables is found. Furthermore, it is found that the firms in China face the severe financial constraints, and the intensities of the constraints have become great for last few years. The above stylized facts may raise the question about whether the asset bubbles can boost the economic growth.
    Theoretically, a Schumpeterian economic growth model where the entrepreneurs face the financial constraint when they finance the R&D. As a consequence, the supply will be greater than demand in the capital market. Assume that the asset bubbles occur in this case, the rising assert price relaxes the financial constraint through mortgage loans, which implies that the entrepreneurs can finance the R&D more easily than ever before. Therefore, the asset bubbles could boost the R&D expenditure and improve the probability of successful R&D. Thus, a positive relation between the asset bubbles and the innovation is found, which is ignored in the previous literatures. The endogenous growth model is combined with the bubbles model by incorporating the technological innovation, which fill the gaps in the currently available studies.
    Empirically, the FF-TVP-SV-VAR and TVAR models are utilized to examine the relationship between the asset bubbles, the technological innovation and the economic growth by employing the monthly data covering a period from 2000 to 2016. It is found that the asset bubbles can boost the technological innovation subject to the financial constraints. In addition, the two threshold values of financial constraints are identified. Furthermore, the robustness of the baseline results is tested by employing the TVTP-MS-VAR model.
    This paper has the important policy implications. First, the asset bubbles may be beneficial to the economic growth, depending on the intensity of financial constraint. The government sectors should pay a close attention to the evolution of financial constraints and direct the funds to the R&D sectors. Second, although the asset bubbles can boost the economic growth under a certain situation, the over-bubblization may trigger the systemic risk and is unbeneficial to the economic growth. Thus, the government should monitor the dynamics of bubbles.
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    Research on Variance Minimization Hedging Based on Time-Varying Markov DCC-GARCH Model
    WANG Jia, JIN Xiu, WANG Xu, LI Gang
    2020, 28 (10):  13-23.  doi: 10.16381/j.cnki.issn1003-207x.2020.10.002
    Abstract ( 467 )   PDF (1853KB) ( 253 )   Save
    Stock market fluctuate frequently because of information shocks caused by sudden events resulting from economic, political, or natural disasters. Therefore, hedging the stock market has always been the popular research topic. Futures market, as an important part of the financial markets, is always used to operate hedging strategies in order to realize the risk transfer. The key problem of hedging theory is to determine the optimal hedging ratio. In this study, using a regime switching framework, a new estimation method of minimum risk hedging ratio is proposed. Then, taking the actual data of CSI300 index futures and spot as samples, the hedging ratios are estimated respectively from both in sample and out of sample. Compared with traditional hedging methods, the hedging performance of this new method is tested. This study is of great significance for hedgers to fully understand the hedging rules of futures market and avoid the volatility risk of spot price effectively.
    In the first part, considering the time varying characteristic of Markov regime transition probability, based on the traditional DCC-GARCH, a Markov regime switching DCC-GARCH model with time varying transition probability (TVTP-DCC-GARCH) is presented to study on the estimation method of minimum variance hedge ratio. Two-stage maximum likelihood method is used to estimate the parameters of the model. In the second part, with the actual data of CSI300 index futures and spot in sample, the hedging ratios of TVTP-DCC-GARCH is estimated, and the hedging performance is compared with other models, including a MRS-DCC-GARCH with a fixed transition probability (FTP-DCC-GARCH), DCC-GARCH, OLS, naïve hedging strategy and indices spot with no hedging. Furthermore, one-step-ahead forecasts out of sample are produced to forecast the hedging ratios of TVTP-DCC-GARCH and the hedging performance of the above models is checked.
    In summary, the DCC-GARCH model based on Markov regime switching is reasonable to study the hedging problem of CSI300 index future, and the TVTP-DCC-GARCH model has the best fitting effect. Thus, it is necessary to build a hedging model based on Markov with time varying transition probability, and explore the impact of time varying transition probability on the optimal hedging ratio in the futures market. In addition, in terms of hedging effectiveness, TVTP-DCC-GARCH model is superior to other models, which means that introducing the time varying transition probability into DCC-GARCH model can effectively improve the performance of hedging portfolio.
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    Portfolio Strategy Based on Wavelet-High Order Moments model-Take the International Crude Oil Markets as An Research Objects
    ZHU Peng-fei, TANG Yong, ZHONG Li
    2020, 28 (10):  24-35.  doi: 10.16381/j.cnki.issn1003-207x.2020.10.003
    Abstract ( 383 )   PDF (1413KB) ( 225 )   Save
    The existing high-order moments portfolio model doesn't take into account the heterogeneity of investors, ignoring the value of multiple time-scales, which is difficult to meet the investors' diversified needs. Therefore, the Maximal Overlap Discrete Wavelet Transform method is combined with the high-order moments portfolio framework to propose the Wavelet-High-order moments portfolio model. By constructing high-order moments portfolios after decomposing the time series, this model can meet the diversified needs of investors in different trading cycles. Then, using the idea of "first decompose and then integrate", a high-frequency scale integration scheme from the frequency domain perspective and a full-scale integration scheme from the time-frequency domain perspective based on the Wavelet-High-order moments portfolio model are proposed. In addition, according to the different risk preference of investors, the appropriate risk features are selected to improve model. Finally, the stability test is carried out. In view of the drastic fluctuation of international crude oil markets, the effect of the portfolio model is tested based on the data of the international crude oil markets. WTI, Brent and Dubai Crude Oil are taken as the research objects. The time spans from October 11th, 2006 to May 16th, 2018, with a total of 2800 trading days after deleting non-common trading days. The data of WTI and Brent are obtained from EIA, and the data of Dubai Crude Oil is obtained from Phoenix Financial Network. The results of the out-of-sample test indicate that, compared with the control groups, most of the Wavelet-High-order moments portfolio strategies have achieved better investment results, with the integration part performing best. And the high-frequency scale integration scheme focuses on improving revenue, while the full-scale integration scheme focuses on reducing fluctuation. By selecting appropriate preference characterristics, the original Wavelet-High-order moments portfolio strategy will be significantly improved, and the improvement effect of the two integration schemes is most significant; The robustness test confirms the above conclusions. This study broadens the research scope of high-order moments portfolio theory, and has theoretical value and practical significance for investors in crude oil market to optimize asset allocation, prevent and resolve market risks.
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    The Pricing of Relationship Loan and Optimal Loan Interest Rate under Ambiguity Aversion
    LI Hao-hua, ZHANG Xiao-qiang, LUO Peng-fei, LI Xin-dan
    2020, 28 (10):  36-42.  doi: 10.16381/j.cnki.issn1003-207x.2020.10.004
    Abstract ( 405 )   PDF (1386KB) ( 197 )   Save
    Under the new normal of the economy, the difficult financing for small and medium-sized enterprises (SMEs) is a prominent problems. The reason of the difficult financing for SMEs is that there exists information asymmetry between bank and SMEs. Stiglitz and Weiss (1981) deemed that information asymmetry causes adverse selection and moral hazard problems, and strengthen the credit rationing of bank. Thus, it makes SMEs's financing difficult and increases the cost of financing. However, the relationship loan is a important way to resolve the information asymmetry between bank and SMEs. Thus, it is significant to alleviate the financing constraint for SMEs. DeYoung et al.(2008), Bharath et al.(2009) and Beck et al.(2018) found that the relationship loan promotes information communication between bank and SMEs via multi-channel, long-term contact SMEs. It lowers the condition of financing for SMEs by making full use of SMEs' soft information. According to the data from the National bureau of statistics, it shows that 38.8 percent of SMEs with need financing can not gain the fund. The phenomenon of the stint loans and broken credit of bank happens all the time. Furthermore, the bank increases the 30 percent of interest rate for SMEs. From the above, it shows that the phenomenon of financing expensive for SMEs is common. Based on this, our model incorporates decision-makers' ambiguity aversion to study the relationship loan, and provides behavioral explanation for the phenomenon of financing expensive for SMEs.
    Following Agliardi et al.(2015), it is assumed that the cash flow X satisfies the Choquet-Brownian process:
    dXt=(μ+)Xtdt+sσXtdZt
    where μ+ denotes the growth rate of cash flow, and denotes the volatility of cash flow, and μσ are constant. m=2c-1, s2=4c(1-c), where c∈(0,1) is constant and measures the degree of the decision-makers' ambiguity about the future results. In our model, we focus on the ambiguity aversion case, i.e., c<1/2. The smaller the value of c is, the more ambiguity aversion the decision-makers are.
    Following Zhang and Huang(2016), it is assumed that there exists a relationship loan between bank and SMEs. In this contract, bank gain the portion θ of cash flow by pay cost f. Let xl denote the credit crunch threshold, which is determined by maximizing the value of bank. When bank stop providing loan for SMEs, the agents (bank and SMEs) gain nothing.
    According to the real-options approach, bank value, firm value and optimal credit crunch threshold are explicitly deriued. The impacts of the ambiguity aversion and baseline volatility on optimal loan interest rate, optimal credit crunch threshold, firm value and bank value are examined. By numerical analysis, it is discovered that ambiguity aversion increases loan interest rate, and the firm value and bank value are reduced. Ambiguity aversion delays credit crunch threshold for the low level of baseline volatility and accelerates credit crunch threshold for the high level of baseline volatility. What's more, it is found that under ambiguity neutral, firm value is a convex function of baseline volatility and bank firm is a concave function of baseline volatility. Under ambiguity aversion case, firm value and bank value decrease with baseline volatility. A behavioral explanation is provide for the high financing cost of SMEs.
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    Single-index Nonparametric Option Pricing Model——A Modified Nonparametric Pricing Approach
    LI Qing, ZHANG Hu
    2020, 28 (10):  43-53.  doi: 10.16381/j.cnki.issn1003-207x.2020.10.005
    Abstract ( 361 )   PDF (1694KB) ( 167 )   Save
    Recent years, the derivatives market developed rapidly in China. The SSE 50ETF option was introduced in February 2015, which is the first stock option in China. The number of the options are 14 by the end of the year of 2019 in China. Option is one of the most active product in financial market, and the investment risk in financial market can be hedged by option, and the option price estimated exactly is the fundament of risk hedge. However, the existing pricing models all are based on the developed financial market, and the financial circumstance is different between developed market and emerging market. As the option emerging market, pricing error will be great if we price option in China with existing pricing model, so this thesis establishes a new nonparametric option pricing model, the so-called modified nonparametric option pricing model which we called the single-index nonparametric option pricing model.
    The problem of estimating and conducting inference on the term structures of a class of economical interesting option portfolios is considered. By forming portfolios for various maturities, we can study the term structure can be studied. Also, option have different liquidity with different maturity, as we all known, the liquidity will affect the option price. However, the existing nonparametric regression option pricing models have omitted the term structure of different maturities.
    Compared with the existing multi-dimension nonparametric regression option pricing model that option prices about multi-factors, our modified model combines all of the factors of option price for one factor (the so-called single-index) by changing of variable, finally we get the one-dimension nonparametric regression equation between option prices and the single-index. Our new nonparametric option pricing model has three advantages subject to the existing nonparametric option pricing models, the first advantage is that the multi-dimension nonparametric regression option pricing model is reduced for one-dimension nonparametric regression option pricing model, so that the option price can be computed conveniently, the number of repressors and the computation of the existing nonparametric option pricing model can be reduced. The second advantage is that, the number of regression sample is additive by indexing options portfolio of multiple maturities. The third advantage is that calendar Spread can be removed by indexing smoothing option of maturities.
    The SSE 50 ETF option is listed in Shanghai Stock Exchange in 19 February 2015, which is the first stock option in China, so this thesis makes empirical analysis by the data of SSE 50 ETF option in Shanghai Stock Exchange, it is found that our single-index nonparametric model performances better than traditional Black-Scholes model, semi-parametric Black-Scholes option pricing model, multi-dimension nonparametric regression option pricing model whether in-sample or out-of-samples data, such as, for in-sample data, the MAE of traditional Black-Scholes option pricing model is 0.4594, the MAE of multi-dimension nonparametric regression option pricing model is 0.2423, the MAE of semi-parametric Black-Scholes option pricing model is 0.2336, the MAE of the our single-index nonparametric model is 0.0845.
    Our new nonparametric option pricing model will pricing exactly for option in China and other emerging market, and can be the conference for option pricing theory and models.
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    The Optimal Investment Timing of Petroleum Resources Exploration Based on Sequential Investment Theory
    WANG Ling, ZHANG Jin-suo, ZOU Shao-hui
    2020, 28 (10):  54-64.  doi: 10.16381/j.cnki.issn1003-207x.2017.1414
    Abstract ( 333 )   PDF (2066KB) ( 149 )   Save
    The traditional method to solve the investment decision of petroleum exploration projects is cash flow discount method. However, such methods ignore the importance of the irreversibility, uncertainty and the interaction between timing and quality, which may lead to short-sighted investment or poor decision-making. Considering the irreversibility, stages and uncertainties of petroleum exploration investments, combining the uncertainty of market demand and exploration reserves, the stochastic dynamic change of the transfer price of exploration reserves is obtained. Based on the sequential investment decision method, the optimal investment timing of petroleum exploration is derived, and the critical values of analytical solutions to the optimal investment timing are obtained. In addition, they are compared with the one-time investment decision-making results, and the influences of uncertainty parameters on optimal investment timing are discussed. The main contributions are as follows. (1)The critical values of the optimal investment timing for each stage of the oil exploration sequential investments are mainly due to such uncertainties as risk-free interest rates, unit exploration cost, market volatility, market drift rates, the prospectors' ability to control over the transfer price of exploration reserves, and the additional exploration reserves at each stage.(2)Sequential investment decision model can make up for the shortcomings of one-time investment which is easy to miss the investment opportunities.(3)The optimal investment timing is positively correlated with the fluctuation of market volatility and prospectors' ability to control over the transfer price of exploration reserves, and negatively correlated with the market drift rates. (4)With the development of the exploration process, the sensitivity of the optimal exploration investment timing to the parameters above is increasing. This paper can enrich and expand the application of real options theory in the investment decision-making of petroleum resource exploration projects, and provide some theoretical basis and decision-making reference for the optimal timing of the sequential investment of exploration.
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    Long-run Dynamic Effect of Macro-economy on Stock Market Volatility Based on Mixed Frequency Data Model
    LIU Feng-gen, WU Jun-chuan, YANG Xi-te, OUYANG Zi-sheng
    2020, 28 (10):  65-76.  doi: 10.16381/j.cnki.issn1003-207x.2019.1853
    Abstract ( 434 )   PDF (3067KB) ( 339 )   Save
    The different frequency in the time series original data of stock price and macro-economic variables directly leads to model misspecificationandestimation bias of the traditional econometric models in analyzingthe relationship between macro-economic fluctuations and stock market volatility. The mixed frequency autoregressive conditional heteroscedasticity model is used to empirically analyze the long-term dynamic effects of producer price index, consumer price index, coincident index of macro-economic business and the interbank interest rate on stock market volatility from the perspective of level value and change rate.At the same time, the first principal component of macroeconomic variable is extracted via principal component analysis and a macroeconomic composite index is constructed to further explore the long-term impact of macroeconomic conditions on stock price volatility. It is found that, i)the realized volatility of stock market has magnified the long-term volatility of the stock market;ii) the level value and volatility of producer price index, consumer priceindex, coincident index of macro-economic business all have significant influence on the long-term volatility of the stock market, and it presents a strong continuous effect from the volatility dimension. The interbank interest rate only has a slight influence on the long-term component of the stock market volatility in the level value dimension; iii)the volatility of the first principal component of the macro-economy and the macro-economy composite index have significant positive amplification effect on the long-term component of the stock market volatility, but the sustained effect is weak, andits level value have a slight effect on the long-term component of the stock market volatility although it lasts for a long time.This conclusion shows that unexpected shocks from macroeconomic fundamentals play an important role in stock price volatility, deepening the academic view that "stock prices are pro-cyclical, and stock price volatilityarecounter-cyclical".
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    Study on Insider Manipulation with Belief Heterogeneity
    ZHOU Qi, YOU Zuo-wei, LIU Shan-cun, HAN Jing-ti
    2020, 28 (10):  77-87.  doi: 10.16381/j.cnki.issn1003-207x.2018.1832
    Abstract ( 342 )   PDF (1461KB) ( 296 )   Save
    The belief bias of the uninformed traders is introduced to the market manipulation model. With the framework of the competitive rational expectations equilibria, a risky asset pricing model with belief heterogeneity of uninformed traders is built. A linear price function in the unique Bayesian linear equilibrium is derived, by which the market manipulation by one powerful insider is studied and thus revealed. The results of the study show that the belief bias of the uninformed traders significantly influences the demands of the informed and uninformed traders, the equilibrium price of the risky asset and the manipulation strategy of the powerful insider. But it doesn't affect the depth of the market. The insider is assumed to be powerful enough to manipulate the price by designedly spreading false information to make the uninformed traders to trade by following the false information. The insider should take into account the belief bias of the unformed traders in order to maximize his profit when spreading false information. In the linear equilibrium, the equilibrium price has a positive linear correlation with the liquidation value expressed by the false information.
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    Resources Allocation Decisions of Business and Government in The Perspective of Efficiency and Fairness
    ZENG Qian, HAN Xun, FANG Xin
    2020, 28 (10):  88-97.  doi: 10.16381/j.cnki.issn1003-207x.2020.10.009
    Abstract ( 383 )   PDF (1508KB) ( 253 )   Save
    The problem of resources allocation widely exists in public services and production activities, such as allocating hospitals, schools, production equipment and workloads in quantity, time or space. Efficiency and fairness are two important objectives. However, in real economic activities, the government usually pays attention to the fairness goal while enterprises care more about the input-output efficiency. Since the enterprise plays an important role in the social resources allocation, its utilitarian behaviors fail to achieve maximum social welfare. Therefore, the following questions are mainly studied:What are the motivations of enterprises and governments to consider efficiency and fairness? Do they have different preferences and goals? How to describe it in the recourse allocation models? What are the optimal solutions under different fairness preference scenarios? Are there differences in decision-making results among the enterprise and government?
    In this paper, the customers' fairness preference is regarded as the main motivation for enterprises, while the maintenance of social fairness and stability as the government's motivation. The concepts of customers' envy and variable weight are applied to depict them in decision-making models. By calculating the unfair loss based on customers' envy, a multi-objective enterprise model is constructed with the profit goal. The variable weight method is introduced to construct the government model is built where maximizing the service coverage is the efficiency goal and maximizing the minimum individual utility is the fairness goal. Besides, efficiency and fairness trade-off methods are designed by measuring the preferences to choose the appropriate fairness degree. Models are transformed into variational inequalities and solved by modified projection algorithm. Finally, behavior differences between those two subjects, the selection and influence of fairness parameters are further analyzed.
    The results indicate that the optimal efficiency decisions of the enterprise and government are basically the same, while the optimal fairness decisions are quite different. With the increase of customers' fairness preference, the allocation polarization of enterprise resources become more significant. As to the government, higher fairness preference of decision makers results in more equal allocation among all individuals. Our research provides a theoretical supplement for understanding the resource allocation strategies and mechanisms of different subjects, which also expands the existing methods to reflect the preferences of enterprises and governments.
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    Impact of Financial Constraint of a Retailer on Supply Chain Coordination
    DAI Jian-sheng
    2020, 28 (10):  98-108.  doi: 10.16381/j.cnki.issn1003-207x.2020.10.010
    Abstract ( 380 )   PDF (1376KB) ( 213 )   Save
    Due to limited capital, single business and operational risk, the great majority of small-and-medium-sized retailing firms are often faced with shortage of funds. What's more, it is difficult to solve shortage of operational capital through external financing owning to be incapable of providing sufficient collateral. In the absence of financing opportunities, operating decisions of the retailers will inevitably be subject to their own operating funds, and this in turn results to exert an important impact on supply chain coordination. To discuss impact of shortage of operational capital on coordination of the supply chain, in this paper a model is constructed on contract coordination of a supply chain composed of one supplier and one retailer, where the retailer's funds are used in two ways:one is the procurement of goods and the other is promotional activities. In particular, more attention is paid to impact on coordination contracts of the retailer's operating capital and funds rate.
    Firstly, on the assumption that there doesn't exist financing opportunities for the retailer, it investigates supply chain coordination via revenue sharing contract and buyback contract, respectively. A contract is called as type I coordination contract if it not only can coordinate the supply chain, but also can achieve arbitrary revenue allocation of the entire supply chain, and a contract is called as type II coordination contract if it can coordinate the supply chain, but can't achieve arbitrary allocation of the supply chain revenue. According to the retailer's operating funds, revenue sharing contract is divided into either type I coordination contract or type II coordination contract, and buyback contract has three different categories:type I coordination contract, type II coordination contract and non-coordination contract.
    Secondly, it characterizes a critical condition for revenue sharing contract and buyback contract, respectively, which can be used to determine what type of contract belongs to. This condition can be expressed by the retailer's operating funds and the bargaining powers of the channel members. Equivalence of the two contracts is as well discussed, which leads to conclusion as follows. The two contracts are not always equivalent if the retailer is confronted with capital constraint. Put particular words, if the retailer's funds are very abundant, the two contracts are totally equivalent; if the retailer's funds are relatively abundant, the two contracts are partly equivalent; if the retailer's lack of funds, the two contracts are no longer equivalent. The difference that the two contracts coordinate the supply chain with financial constraints lies in:the revenue sharing mechanism possess financing function in nature (the supplier provides financing for the retailer), but the buyback contract does not have this function.
    Last but not least, it explores impact of financial time value on supply chain coordination in the two contracts, and the results show that it is more likely to make use of buyback contract to succeed in coordination of the supply chain as the funds rate rises. However, the funds rate has no effect on revenue sharing contract. In the case of buyback contract, as the funds rate increases, the wholesale price decreases and the buyback price holds unchanged. In the case of revenue sharing contract, the time value of funds does not exert an effect on the likelihood that the supply chain can be coordinated.
    From discussion some managerial insight is obtained, which can provide theoretical reference on contract coordination for the supply chains confronted with capital constraint.
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    E-commerce Supply Chain Coordination with Capital Constraints under Service Quality Affecting Market Demand
    XU Na, BAI Shi-zhen
    2020, 28 (10):  109-117.  doi: 10.16381/j.cnki.issn1003-207x.2020.10.011
    Abstract ( 357 )   PDF (1508KB) ( 233 )   Save
    Service development with high quality has been written into national strategy. It is especially important in e-commerce with customer oriented. The service quality directly determines the shopping experience of customers, thus influencing the success rate of transactions and ultimately influencing the development of online shopping market. However, online sellers continue to encounter several challenges. Among the total complaints in China in 2017, approximately 60.59% are related to online shopping. The poor product quality, the difficulty of returns and obtaining a refund, and false promotion are the most common consumer complaints, which significantly decrease the shopping experience quality of online consumers, and hinder the development of online market. Hence, it is necessary for online sellers to improve customer service quality. Yet, online sellers are usually those individual households, mom- and-pop stores, which are characterized by capital constraints. That is, it is only an armchair strategist for them to improve service quality.
    In fact, customer shopping experience is a joint action of node enterprises in an e-commerce supply chain. In order to keep a booming development of e-commerce, it is necessary to build effective, efficient cooperation relationship between node enterprises in a supply chain. According to the public document of the State Council, named "Guidance on actively promoting innovation and application of supply chain", the supply chain finance (SCF) should serve the real economy. Clearly, it is an urgent problem to find the way to provide efficient financing channels through SCF, simultaneously, to improve service quality and benefit all parties.
    Under this background, the "credit contract based on the sales target" is brought. It means that the supplier allows the retailer to delay in payments just if the sales meet a certain condition. Such way is good for retailers to ease the funding pressure and to increase investment on improving service. Considering the effect of service quality on market demand, the repurchase contract combined with "credit contracts based on the sales target" is designed, an e-commerce supply chain coordination decision model is built it to obtain the optimal operation strategy. The results show that, the optimal decisions are helpful to remit retailer's financial pressure, encourage more investment in service, and improve customers' shopping experience. What's more, it helps to achieve channel coordination with arbitrary profit splitting, which improves the operability of contracts and guarantees the effective of the coordination mechanism. The optimal ordering decisions, service quality level decisions, credit period and sales target decisions are obtained. These decisions can help managers make full use of SCF, meanwhile, improve customer experience and realize win-win. The results help to accelerate the innovative practice application of SCF in e-commerce supply chain.
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    Multi-item/Two-stage JIT Joint Replenishment Considering Customer Response to Stock-out
    ZHANG Ke-hui, YANG Hua-long, XIN Yu-chen, LIU Qing-qi
    2020, 28 (10):  118-130.  doi: 10.16381/j.cnki.issn1003-207x.2020.10.012
    Abstract ( 392 )   PDF (1794KB) ( 152 )   Save
    Out-of-stock situations are inevitable in the multi-product joint inventory replenishment of retail commodities. Customers have several different responses to stock-out, such as abandoning purchase, delaying purchase or buying alternatives. Customer Response to Stock-out (CRS) differs among different product categories, which has a great impact on the inventory control of commodities and their alternatives. The single set of out-of-stock item and its substitute under multi-constraint is investigated, and various models have been explored in joint replenishment by prior empirical studies. However, the seemingly contradictory findings from the related studies indicate that there can be multiple sets in joint replenishment, which is still under-explored in extant literature. Moreover, there still exists irrational use of resources that some items can't satisfy the demand while others have surplus supplies. There is a lack of research into multi-item two-stage JIT joint replenishment considering comprehensive utilization of resources and maximization of revenue.
    In the view of these, the research is extended into a two-stage JIT joint replenishment of retail commodities from two aspects, taking the impact of CRS and resource restrictions on ordering decisions into account. First, the joint order strategy under the resource restriction condition is suggested according to the JIT inventory principle. Second, the product group is extended from one group to multiple groups in accord with CRS rule. On this basis, a multi-product two-stage JIT joint replenishment model considering CRS is established with the goal of maximizing the retailer's revenue. According to the characteristics of the above model, the imperialist competition algorithm (ICA) is improved in terms of initial solution generation and revolution mode of colonial countries, to obtain the approximate optimal solution more quickly. A total of 9 groups of 18 products are selected from the Gruen survey report, and the model and the solutionare verified by numerical examples in three scales:scale 1 (small:including 6 kinds of products), scale 2 (medium:including 12 kinds of products) and scale 3 (large:including 18 kinds of products).
    The results show that compared with the ordering method without considering CRS, the multi-product two-stage JIT combined ordering method with CRS consideration can not only improve the retailer's total revenue, but also improve the customer's service level. The results also show that the unit resource opportunity income and the unit residual resource opportunity income are the main factors to decide how to allocate resources effectively. If the opportunity benefits of unit inventory resource in peer group are approximate each other, no replacement would be made in peer group. While, if the opportunity benefits of unit inventory resource in peer group vary significantly and are higher than those in other groups, substitution and stock-out would be shown in the group. More specifically, if the opportunity benefits of unit surplus resource are lower than the opportunity benefits of unit resource in other groups, the surplus resources of the product would be transferred to other out-of-stock products. The findings of the research could provide references to the decision making of multi-item/two-stage JIT joint replenishment for retailers.
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    Decision Analysis of Reverse Supply Chain with Different Mixture Recycling Modes and Power Structures
    GONG Yan-de, JIANG Yu-wei, DA Qing-li
    2020, 28 (10):  131-143.  doi: 10.16381/j.cnki.issn1003-207x.2020.10.013
    Abstract ( 322 )   PDF (1599KB) ( 162 )   Save
    In order to improve the recycling rate of waste electrical and electronic products since the promulgation of the "Production Responsibility Extension System Implementation Plan", the government strongly encourages electrical and electronic product manufacturers to cooperate with retailers or third parties for recycling. In this context, based on the two power structures dominated by the manufacturer and the retailer, four types of reverse supply chain models are constructed when mixed recycling is manufacturer and retailer together or manufacturer, retailer and third party together.Using game theory, decision on mixed recycling mode was discussed from different perspectives, it is found that (1) if recycling degree is higher,that is 2s < k < 4.02742s, the optimal strategy of manufacturer is manufacturer-led and the two are mixed and recycled; If recycling degree is lower, that is k>4.02742s, the manufacturer's optimal strategy is manufacturer-led and the three firms mixed recycling. (2) Although the retailer has channel advantage in sales channel, the recycling enthusiasm is lower than the manufacturer, optimal decision for retailer is always manufacturer dominated and mixed recovery by manufacturer and retailer, the worst decision is always retailer dominated and mixed recovery by three firms. (3) If 2s < k < 3.91582s, then optimal decision for reverse supply chain system is manufacturer dominated and two firms mixed recovery, if k>3.91582s, then optimal decision for reverse supply chain system is manufacturer dominated and three firms mixed recovery. (4) According to the optimal power structure and hybrid recovery methods, reverse supply chain system's optimal decision-making is basically the same with manufacturer, optimal decision-making are both manufacturer dominated reverse supply chain; the worst strategy for three firms are retailer dominated reverse supply chain.Finally, conclusions are verified by a numerical example.The conclusions of this paper can provide theoretical references for reverse supply chain enterprises to choose recycling modes and partners.
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    Research on Distribution Channel Cooperation Strategy Considering Product Experience and Sales Efforts
    LU Fang, WU Jian, LUO Ding-ti
    2020, 28 (10):  144-155.  doi: 10.16381/j.cnki.issn1003-207x.2020.10.014
    Abstract ( 452 )   PDF (2596KB) ( 285 )   Save
    Research on product distribution channel cooperation mainly focuses on channel cost, risk aversion, consumer fairness preference and pays less attention to the product's own attributes. For products with lower experience, consumers can judge product value more accurately without experience, and network channels have an advantage in such less experienced products. For products with higher experience, the network channel cannot accurately judge the value of such products because of its virtuality. On the contrary, the physical channel can help consumers determine the true value of the product through the actual product experience. However, due to the spillover effect of the physical channel marketing efforts, the consumers of the physical channel are likely to transfer to the network channel after experiencing the product. It can be seen that the attribute of product experience has a great influence on the choice of product distribution channels. In order to maximize profits of the manufacturers, there arises a demand of the research on the cooperation strategy of distribution channels from the perspective of product experience and marketing efforts.
    The impact of product experience and marketing efforts on different channel needs are first analyzed from the perspective of consumer utility. Based on this, three distribution channel cooperation strategies of manufacturers and retailers are studied, and the different impacts of different product experience and marketing efforts for different distribution channels are explored. The first is a single cooperation strategy for manufacturers to support offline retailers to implement marketing efforts; the second is a dual cooperation strategy for manufacturers and retailers to adopt price coordination contracts under a single cooperation strategy; and the third is a multi-cooperation strategy between manufacturers and retailers to further introduce revenue sharing contracts.
    Through the numerical simulation of the three cooperation strategies, the results show that under the combined effect of product experience and marketing efforts, the three cooperation strategies can effectively improve the profit level of manufacturers and offline retailers, and the lower the product experience is, the more important the cooperation strategy is. In the initial stage of entering the market, manufacturers often need to rapidly increase corporate value. At this time, the dual cooperation strategy is the best choice. When the market matures, the dual cooperation strategy can effectively improve the offline retailer's income, but the manufacturer's revenue is reduced. In order to encourage manufacturers to support offline retailers to implement marketing efforts, it is necessary to redistribute the cooperative income. At this time, the multiple cooperation strategy is the best choice.
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    Joint Optimization of Order Sequence and Pick Position in an AS/RS with Multiple In-The-Aisle Pick Positions
    HAN Dong-ya, CHEN Ran, YU Yu-gang, GUO Xiao-long
    2020, 28 (10):  156-164.  doi: 10.16381/j.cnki.issn1003-207x.2018.1466
    Abstract ( 389 )   PDF (1676KB) ( 209 )   Save
    The automated storage and retrieval system with multiple in-the-aisle pick positions (ASRS-MIAPP) is a new type of warehousing technology which combines storage and order picking process. The typical feature is that there exists multiple picking locations at the bottom of the rack for workers. The sequence of storage and retrieval jobs as well as the assignment between the picking locations and retrieval jobs are studied to minimize total travel distance of a storage/retrieval (S/R) machine in an ASRS-MIAPP. A mixed integer programming model is proposed, and a two-stage heuristic algorithm is designed to solve this problem. In the first stage, the sequence of storage and retrieval jobs is selected which is handed over to the second stage where the one-to-one assignment of the picking locations for the given retrieval jobs is determined. The computational experiments show the effectiveness of the proposed algorithm. Compared to first-come-first-served algorithms, commonly used in the practice, the total travel distance reduces on average by 20%.
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    Research on Supply Chain Network Optimization with the Relationship of Pricing and Demand
    HU Hong-tao, BIAN Ying-ying, GUO Shu-yuan, WANG Shuai-an, YAN Wei
    2020, 28 (10):  165-171.  doi: 10.16381/j.cnki.issn1003-207x.2020.10.016
    Abstract ( 387 )   PDF (1015KB) ( 267 )   Save
    In the supply chain network, prices have a large impact on the consumer demand and profits. In this paper, a price-demand function is introduced to describe the effect of the changing price on consumer demand. Then a three-level supply chain network is constructed which constitutes manufacturer, warehouses, and consumers. By considering the pricing and demand as decision variables, a mixed integer nonlinear programming (MINLP) model is established, which aims to maximize the total profit of the supply chain. To address the MINLP model, the nonlinear objective function is firstly transformed into a nonlinear constraint. Then the nonlinear constraint is approximated by a finite number of tangents by using the outer-approximation method. Finally, a set of linear constraints are added into the model to replace the nonlinear constraint; hence the MINLP model is approximated by a mixed integer linear programming model. Although the scale of the model increases because of linearization, numerical experiments show that the outer-approximation method can still find the optimal solution of the problem on realistic-sized instances in a short time. The proposed model can guide the enterprises in the supply chain to balance the costs and benefits and to improve the customer satisfaction.
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    Dynamic Strategies of Joint Emission-Reduction and Competition Considering Reference Emission-Reduction Effort Effect
    WANG Qin-peng
    2020, 28 (10):  172-182.  doi: 10.16381/j.cnki.issn1003-207x.2018.0773
    Abstract ( 323 )   PDF (2065KB) ( 197 )   Save
    When a brand owner selects original entrusted manufacturers (OEMs) to make products, it often selects a number of different manufacturers to produce the same type but different models of products, and determines the advertising strategies according to the corresponding market performance of different types of products. In the context of current global warming, brand owners with social responsibility cooperate with their OEMs to jointly implement their emission-reduction strategies by sharing part of the cost of carbon reduction of the OEMs. Different carbon reduction and advertising strategies will affect the profitability of OEMs by influencing the demand. Therefore, they need to study how to determine the optimal carbon reduction strategies to maximize their profit. Similarly, how to determine the optimal advertising investment and carbon reduction cooperation strategies will be core issues for brand owners. At the same time, it should be noted that consumers are not only affected by the level of carbon reduction effort when purchasing products, but also affected by reference low-carbon efforts effect formed during the past purchasing experience. That is the reference carbon reduction effect. Therefore, it is necessary to figure out the impact of reference carbon reduction effect on strategies of carbon reduction and advertising.
    Considering the competition of OEMs and reference low-carbon efforts effect, a supply chain is constructed that includes two competing emission reduction OEMs and a brand owner. Issues of the dynamic strategies of the joint emissions reduction and advertising as well as supply chain coordination are analyzed based on the differential game theory. The strategies of supply chain in decentralized and centralized decision-making models have been analyzed. The differences the level of emission reduction efforts, the advertising level and the present value of the total profit between the two decision-making models have been compared. It is found that when the marginal revenue of manufacturers is low in the cooperative decision-making case, the level of carbon reduction effort is higher than that in the decentralized decision-making case; otherwise, the level of carbon reduction is higher in the decentralized decision-making case. The level of advertising in the centralized and decentralized decision-making cases does not depend on the marginal revenue of the brand owner, but depends on the relative marginal revenue of OEMs. The effects of the memory and reference parameters are investigated with the numerical analysis. To obtain the supply chain profit of the centralized decision-making case in the decentralized case, a two-way cost sharing contract is designed that OEMs and the brand owners share the carbon-reduction and advertising costs from each other. The profits of the brand owner and OEMs in the decentralized decision-making and two-way cost sharing contract cases are compared with numerical analysis. It is found that the two-way cost sharing contract does not present the Pareto improvement for supply chain members. To settle this issue, the transfer payment contract is offered to achieve the self-execution of the contract.
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    Pricing and Ordering Decisions for Experience Goods with Reference Dependence and Product Demonstrations
    XU Jian, DUAN Yong-rui, HUO Jia-zhen
    2020, 28 (10):  183-193.  doi: 10.16381/j.cnki.issn1003-207x.2020.10.018
    Abstract ( 293 )   PDF (2831KB) ( 205 )   Save
    An experience good (e.g., phone and fashion) is a product that a consumer can not readily determine the value of the product until he uses it after purchase.When consumers purchase experience goods, they will be reference-dependent due to the uncertainty of the product value. The consumer feels psychological gain when the actual outcome is better than the expectation, and feels psychological loss otherwise. In reality, a lot of firms adopt product demonstrations to help consumers reduce the valuation uncertainty. Hence, it is necessary to study the impact of reference effect and product demonstrations on the firm's pricing and ordering decisions.
    In this paper, the consumer's utility includes two components, i.e., economic utility and reference-dependent utility. Consumers are homogeneous in the uncertainty of the product value before purchase, but have their own valuations of the product after purchase. Based on the framework of newsvendor model, a joint pricing and ordering problem with the consideration of reference dependent effect is addressed, and the necessary conditions of the optimal solutions are obtained by the optimization method. Then, the impact of the product demonstration policy on the firm's decisions is explored. Demonstrations help consumers learn about the product value and arise two effects:the number of total consumers decreases and the consumer's reservation price increases. The necessary conditions of the optimal solutions under demonstrationsare obtained as well.
    The main results are summarized as follows. First of all, for any given fill rate, the price with the reference dependence is higher than that without the reference dependence only when the probability that a consumer obtains a high value is greater than a threshold. Secondly, the reference dependence of the product value and the reference dependence of the price have the opposite effect on the optimal price. Thirdly, the optimal price is increasing in the given initial order quantity when consumers are loss aversion. Furthermore, the optimal price is increasing in the demonstration degree when the seller adopts a demonstration policy. Finally, more managerial insights are obtained by numerical studies. Particularly, the reference dependence and loss aversion in the price (product value)dimension have negative (positive) effect on the firm.
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    Equipment Procurement Optimization Based on Genetic Algorithm
    LEI Shao-yong, LIU Jing-xu
    2020, 28 (10):  194-200.  doi: 10.16381/j.cnki.issn1003-207x.2020.10.019
    Abstract ( 362 )   PDF (975KB) ( 317 )   Save
    Equipment procurement constitutes an important aspect of equipment development, and it is the last link in the whole generation process of equipment from putting forward demand to forming combat capability. The success or failure of this work directly affects the quality of military equipment and the generation of combat effectiveness. At present, empirical decision making, which depends on the experience, knowledge and preferences of decision makers, can no longer meet the demands of equipment purchasing decisions. Therefore, it is urgent to explore and build a reasonable model in accordance with the characteristics of purchasing decisions, making full use of the intelligent optimization algorithm to solve the problems in realizing the optimal decision-making of equipment procurement. On the basis of synthetically considering the various factors of equipment procurement, the approach is put forward to transform the equipment procurement problem into a multi-objective fuzzy assignment problem under multi-constraint conditions, and a solution based on genetic algorithm is given. Finally, a case study is carried out to verify the feasibility and effectiveness of the algorithm. At the same time, the efficiency of the genetic algorithm and the Hungarian algorithm is compared. The experimental results show that the efficiency of genetic algorithm is much better than that of Hungarian algorithm, and with the increase of the scale of the problem, the difference of solving time is even more obvious. The complex problem of equipment purchasing decision optimization is solved, which is difficult to achieve by the traditional optimization method, and it has good application effect in practical situations, so it has significant practical value for equipment purchasing decision making. At the same time, the model put forward in this paper also has some reference value for constructing and solving other assignment problems.
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    The Social Welfare Maximization Model of Real-Time Pricing for Smart Grid
    GAO Yan
    2020, 28 (10):  201-209.  doi: 10.16381/j.cnki.issn1003-207x.2020.10.020
    Abstract ( 507 )   PDF (928KB) ( 334 )   Save
    The smart grid has allowed the analysis of electricity user's consumption in real time. This development makes it possible to adopt the real-time pricing as a tool to encourage users to consume electricity more efficiently and wisely. From the social perspective, it is desired to increase the sum of comfort obtained by each user and to decrease the expense imposed to the supply side. This aim can be formulated as maximizing the sum of utility functions of all users minus the cost function of the supply side, while the energy demand is constrained by the supply capacity, which is said to be the social welfare maximization model. By computing the Lagrangian multiplier, i.e., shadow price, of the social welfare maximization model, the real-time price is obtained. Usually, the Lagrangian multiplier is computed by the duality method. In the duality method, the price and the demand interact with each other in a distributed manner, and finally converge to a win-win agreement,which is beneficial to both the supply side and all users. In the existing methods of the social welfare maximization of real-time pricing in smart grid, some models contain both the lower limit of power supply (i.e. the minimum power generation) and the upper limit of power supply constraints, and the other models only contain the upper limit of power supply constraint for the purpose of simplification.
    Suppose that K denotes the time slots number, K is the number of users, xik denotes power consumption for the customer i at time slot k, Lk denotes electricity power generated by providers, Lkmin and Lkmax are minimum and maximum power generated by provider respectively, and Lk denotes power generated by provider at time slot k,Ui(xik,ωik) denotes utility function for the user i at time slot k, Ck(L) is the cost of L units of energy at time slot k.The following is called the social welfare maximization problem:
    $\begin{array}{l} \mathop {\max }\limits_{{L_k}^{\min } \le {L_k} \le {L_k}^{{\mathop{\rm m}\nolimits} {\rm{ax}}}} \;\sum\limits_{i = 1}^n {{U_i}} ({x_i}^k,{w_i}^k) - {C_k}({L_k})\\ {\rm{s}}.{\rm{t}}{\rm{.}}\;\;\;\sum\limits_{i = 1}^n {{x_i}^k \le } {L_k}\;\;\;\;\;\;\;\;\;\;\;\;\;(1) \end{array}$
    In this paper, the role of the lower limit power supply constraint in the model of social welfare maximization is investigated. By introducing a so-called effective cost function $\{ {C_k}(\sum\limits_{i = 1}^N {{x_i}^k} ),{C_k}({L_k}^{\min })\} $, under a mild assumption, we proved that the problem (1) is equivalent to the following problem:
    $\begin{array}{l} {\rm{max}}\sum\limits_{i = 1}^N {{U_i}} ({x_i}^k,{w_i}^k) - \max \{ {C_k}(\sum\limits_{i = 1}^N {{x_i}^k} ),{C_k}(L_k^{\min })\} \\ {\rm{s}}.{\rm{t}}{\rm{.}}\;\;\;\sum\limits_{i = 1}^N {{x_i} \le } L_k^{\max }\;\;\;\;\;\;\;\;(2) \end{array}$
    In other words, the mode with both the lower limit of power supply and the upper limit of power supply constraints and the model with only the upper limit of power supply constraint are equivalent. The assumptionthat we used is reasonable in practical application. This means that the minimum power supply constraint in the social welfare maximization model can be removed. Thus,one interval constraint and one variable are reduced in the problem (2). Meanwhile, it is showed that the problem (2) still satisfies the requirements of the online dual optimization method. This study aims at the basic social welfare maximization model, and the conclusions obtained can be extended to various improved and extended social welfare maximization models.
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    Research on The Cost of Emissions Embodied in Interprovincial Trade
    XUE Jian, ZHU Di, ZHAO Lai-jun
    2020, 28 (10):  210-219.  doi: 10.16381/j.cnki.issn1003-207x.2020.10.021
    Abstract ( 352 )   PDF (2154KB) ( 138 )   Save
    With rapid development of regional economic integration and rapid growth of interprovincial trade, emissions embodied in interprovincial trade and the cost of emissions significantly cause unbalanced development of provinces and unsustainable regional economic development in China.Based on this, an environmental input-output model is first constructed in this paper to calculate the transfer amount of sulfur dioxide emissions embodied in interprovincial trade and the cost of emissions. Secondly, the emissions cost structural rationality assessment model is constructed to judge the rationality of sulfur dioxide emissions structure. Then, a structural decomposition analysis model is constructed to investigate the driving force of the change of sulfur dioxide emissions embodied in interprovincial trade. Finally, Pan-Beijing-Tianjin-Hebei region is selected for empirical analysis. The data comes from the multi-regional Input-output table in 2007 and 2010, China Statistical Yearbook, Provincial Statistical Yearbook, China Energy Statistical Yearbook and China Environmental Statistics Yearbook. An empirical study is conducted using sulfur dioxide emissions embodied in interprovincial trade.The results show that:First, the provinces for net sulfur dioxide emissions embodied in interprovincial trade outflow are developed provinces which obtain the economic benefits indirectly such as Beijing, Tianjin and Shandong. And Beijing is the biggest beneficiary. Meanwhile, the provinces for net sulfur dioxide emissions embodied in interprovincial trade inflow are developing provinces which bear the cost of emissions such as Hebei, Shanxi and Inner Mongolia. Hebei and Shanxi bear more emission cost for developed provinces. Second, the structure of sulfur dioxide embodied in interprovincial trade in developed provinces is clearly better than that of developing provinces. The growth of trade volume in interprovincial trade is difficult to compensate for the emissions cost undertaken by developing provinces. The most unreasonable sulfur dioxide structure is Shanxi. Third, the main driving forces are negative technical effect and positive scale effect, indicating that the improvement of the technical level can effectively reduce the cost of emissions, and the expansion of the industry scale will increase the cost of emissions. Fourth, according to the empirical research results, two policy recommendations are proposed:establishing the ecological compensation management mechanism under the regional linkage governance; and an investment adjustment mechanism based on SDA results. The conclusion can be used as an important reference for regional economic development decision-making, coordinate the balanced development of the provinces within the region, and promote the sustainable growth of the regional economy.
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    The Precise Delivery Strategy of LED Advertisement in New Operational Mode of Taxi
    LI Ke, DANG Yan-zhong
    2020, 28 (10):  220-230.  doi: 10.16381/j.cnki.issn1003-207x.2020.10.022
    Abstract ( 585 )   PDF (3075KB) ( 263 )   Save
    As a new form of taxi advertising, taxi LED advertisement is deeply concerned and favored by advertisers, and its advertising effect is closely related to the delivery strategy.The traditional operational mode of taxi is mainly single shift system and double shift system.In the traditional operational mode, the LED advertising time is not flexible enough, the content is not rich enough, and the delivery area is not fine enough.In short, the current taxi LED advertising strategy is relatively extensive, and does not take into the differentiated needs of target consumer groups account.
    With the popularity of ride-hailing software applications, people have experienced the convenience of the Internet to travel.The taxi industry is experimenting with a new model of "Internet travel", suggesting that taxi operations are fundamentally changing.Especially in the new operation mode, the taxi equipped with GPS positioning equipment has accumulated a large amount of running data during the driving process, which provides the necessary conditions for the detailed design and accurate delivery of the taxi LED advertising strategy.
    The current theory and application of precision advertising research are analyzed, aiming at the new operation mode of taxi LED advertising is not accurate. A method to extract the temporal and spatial characteristics of resident travel behavior and the behavior characteristics of taxi drivers is constructed. According to the behavior patterns and preferences of residents and drivers, three precise strategies of taxi LED advertising are put forward.Immediate segment oriented delivery strategy, space oriented delivery strategy and time-space oriented delivery strategy.Finally, the real track data of a city taxi is used to verify and analyze it.The specific contents of the study are as follows:
    (1) The feature extraction of residents' travel behavior.In this paper, the difference function algorithm is used to find the peak and off-peak travel time, and a method to extract the travel behavior time feature is proposed.Secondly, the peak density clustering algorithm is used to cluster the spatial longitude and latitude data, and the map matching and regional functional identification are carried out to get the spatial characteristics of residents' travel.
    (2) The feature extraction of drivers' behavior.Firstly, the preference degree of different drivers from different drivers to different functional regions is calculated under the condition of not carrying passengers, and then the K-Means clustering algorithm is used to cluster the driver preference.Finally, based on the clustering results, the characteristics of drivers with similar behavior and those with different behaviors were observed and analyzed respectively.
    (3) The formulation of precision delivery strategy.Based on the behavior rules of residents and the behavior habits of drivers, this paper puts forward three kinds of directed delivery strategies, namely, immediate segment orientation, spatial orientation and spatio-temporal orientation.Because the travel behavior of residents fluctuates in time, according to the change of residents' behavior with time, according to the change of residents' behavior with time, the timely advertisement is put out, and the appropriate advertising content is published.Set up reasonable advertising frequency and develop differentiated advertising price.The spatial orientation strategy is to place advertisements on the functional areas that residents often travel to and from.The longitude and latitude data reflecting spatial location are classified into urban functional areas by clustering, map matching and regional functional identification, and then the types of advertising information are determined in which functional areas.Spatiotemporal targeting strategy refers to placing advertisements in different functional regions at different times.Spatio-temporal directed delivery needs to mine the behavior characteristics of taxi drivers in different time and different functional areas, find the drivers with similar characteristics, and extract the functional areas of interest to achieve accurate advertising.
    The design ideas and methods of the precise placement strategy of taxi LED advertisement are pect forward, improves the theoretical research system of taxi advertisement is improued, and the field of precision advertising is widened.The proposed precise delivery strategy has practical reference value for advertisers, advertising companies, taxi companies and other management departments involved in taxi advertising.
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