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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

    20 May 2018, Volume 26 Issue 5 Previous Issue    Next Issue
    Articles
    Study on Price Discrimination Strategies with Consumer Anticipated Regret
    LIU Wei-qi, ZHANG Jin-jing
    2018, 26 (5):  1-8.  doi: 10.16381/j.cnki.issn1003-207x.2018.05.001
    Abstract ( 869 )   PDF (1275KB) ( 629 )   Save
    Firms in many industries (including telecommunications, financial services, newspaper and magazine subscriptions, and Internet-based commerce) can recognize their previous customers and can thus price discriminate on the basis of purchase history. Advances of information technologies ease collection of customer data, and data-driven marketing further promotes adoption of BPD. Not surprisingly, such behavior-based price discrimination (BPD) has drawn growing research interests over the past decade or so. Consumers' valuation uncertainty is introduced, and it is assumed that consumers do not observe their values of each product before purchase when the firms practice BPD.Once the true values are determined, their purchase decisions made under such uncertainty may lead to post-purchase regret. So they will consciously anticipate the possible regrets before decision making, i.e., anticipated regret. To investigate the effects of customer anticipated regret on dynamic price competition, behavior-based price discrimination (BPD) in a two-period experience good duopoly with a discrete value distribution is considered. First, adynamic game model between the consumer and both firms is established. Furthermore, the equilibrium configuration when the firms practice BPD is summarized in two types of regret aversion:(a)rS>rR=0 and (b)rR>rS=0,which can provide firms with guidelines about how should the firm use behavior-based pricing (BBP) to discriminate between its own and competitors' customers in a competitive market and how to most profitably manage the consumer's anticipated regret. The results of the study show that:(1) the consumer's anticipated regret can significantly impact his purchase decision byaffectingconsumer'sprice sensitivity; (2) the firms should reward repeat customers when the segment of consumers who realized a high value in period 1 is relatively small and when the high-low value difference is high and when the consumersswitching regret aversion is very weak or repeat-purchase regret aversion is relatively strong and reward switchers otherwise; (3) the consumer's anticipated regret has non-monotonic effects on firms' profits. Finally, some numerical examples are present to investigate the impacts of consumers' anticipated regret on the retailer'sprofit and prices to repeat customers and switchers. The results of this study can help managers develop better price discrimination strategy and marketing policies.
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    A Study on Stock Index Futures Arbitrage by ETF with High Frequency Data
    WANG Liang, QIN Long-hao, LIU Xiao, CHEN Jie
    2018, 26 (5):  9-20.  doi: 10.16381/j.cnki.issn1003-207x.2018.05.002
    Abstract ( 764 )   PDF (891KB) ( 436 )   Save
    In this paper, the arbitrage process between stock index futures and spot based on the ETF portfolio is studied through high frequency data. In consideration of the transaction cost through the 12 futures contract in 2013 with 5 minutes high frequency data, the model of ETF arbitrage fund portfolio stock index futures is constructed using no arbitrage interval analysis method. It is found that the reverse arbitrage opportunity of China's stock index futures market is less than positive arbitrage opportunity. The mispricing rate in the process of spot and future arbitrage is high and shows non-equilibrium. Moreover, the introduction of margin trading inhibits the arbitrage behavior. Due to a higher cost rate of margin trading, which also makes arbitrage-free interval of margin trading investor expand, it gets the positive arbitrage opportunity greater than the positive arbitrage. As the transaction time of the quarter-month contract is relatively long, so its arbitrage opportunity is far more than other types of index futures. But continuous positive arbitrage opportunity of the quarter-month contract is more than the other types of contracts, and the continuous reverse arbitrage opportunity of it is significantly fewer than other types of contract. Although the future delivery date price limitation is of 20% by the trading rules, it is found that in the delivery day, total number of over boundary of arbitrage-free interval, longest duration of over boundary, average mispricing rate, return of instantaneous arbitrage, continuous arbitrage opportunity of two types investors are almost same. For the delivery day, the volatility degree of index future price last two hours is significantly lower than the volatility of two hours before, it is because that the final delivery price of future is confirmed by average stock index futures price of last two hours, which makes the price stabilize. This study is helpful to improve the efficiency of stock index futures arbitrage trading to a certain extent.
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    Auctions for Online Peer-to-Peer Lending under Stochastic Demand
    ZHOU Zheng-long, MA Ben-jiang, HU Feng-ying
    2018, 26 (5):  21-30.  doi: 10.16381/j.cnki.issn1003-207x.2018.05.003
    Abstract ( 725 )   PDF (898KB) ( 512 )   Save
    Auctions are common in everyday life and have penetrated into all areas of online markets, including supply chain procurement, resource allocation, and online e-commerce transactions. In recent years, the auction theory has also been extended to online peer-to-peer (P2P) lending markets for analyzing the interests of lenders and borrower. However, many related researches on online P2P lending markets of China mainly focuse on risk control, behavior decision, trust and supervision. Fewer literatures explore China's online P2P lending trading mechanisms through the auction theory. Therefore, the existing deficiencies of trading mechanisms of China's online P2P lending markets are mainly analyzed, and the current trading mechanisms are improved through the auction theory. In this process, a lending contract is first set up to determine the initial loan demand, then two open-descending closed auction mechanisms on online P2P lending markets are designed, which include pre-symmetric and asymmetric auction models. This paper shows that a variation of the standard open-descending auction is an optimal mechanism for the borrower. These two mechanisms will consist of two stages (both take place before the borrower's demand realizes). In Stage 1, the borrower will run a standard open-descending auction for an initial fixed quantity. In Stage 2, the winning lenders from Stage 1 will receive one additional offer from the borrower to supply more units at unit prices no higher than the auction's ending price. Results show that these two mechanisms are optimal for borrower; and borrower and lenders are more familiar with these simple auctions. Therefore, it can be used to improve China's trading mechanisms of online P2P lending markets. Results of examples analysis also show that, as long as trading mechanisms of online P2P lending markets can be normally operated, these two open-descending closed auction mechanisms can further reduce the borrower's payment cost. And these mechanisms can be an effective improvement scheme compared with the trading mechanism provided by China's existing auction platform, which is conducive to the healthy development of China's P2P lending markets.
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    A Study on Disaggregating China's National Carbon-reduction Target based on Interactive Iterations
    DU Juan, XU Jing-hua
    2018, 26 (5):  31-39.  doi: 10.16381/j.cnki.issn1003-207x.2018.05.004
    Abstract ( 634 )   PDF (1894KB) ( 396 )   Save
    Greenhouse gas emissions are supposed to lead to global warming and climate change, among which carbon dioxide is the most significant one generated by humans. Tackling this issue requires global action and joint efforts from all over the world. As a high-speed developing country, China has become the world's largest energy-consumer and the biggest carbon-dioxide producer. In order to take an active role in fighting global warming, China intends to cut carbon emissions by a remarkable percentage, and to establish the national market for trading carbon emissions. Under the frame of efficiency analysis, the directional distance function (DDF) is used to evaluate performance with undesirable outputs, and an iterative procedure is further developed to disagg regate China's national reduction target of carbon emissions at the provincial level. The results indicate that different provincial regions tend to share different levels of reduction target depending on their geographical features, economic conditions and industrial structures. Most provinces and municipalities located in the more economic-developed coastal areas should substantially lower carbon emissions. In contrast, economic zones in central and west China demonstrate a much smaller decreasing scale. Thirty provincial regions are further classified into four clusters jointly by economic development and carbon emissions. With respect to each cluster, a detailed discussion is given in its current development status, as well as some instructive suggestions on an eco-friendly and sustainable development.
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    Research of Baltic Dirty Tanker Index Model Based on the Improved Mean Reversion
    FENG Wen-wen, KUANG Hai-bo, MENG Bin
    2018, 26 (5):  40-50.  doi: 10.16381/j.cnki.issn1003-207x.2018.05.005
    Abstract ( 822 )   PDF (1811KB) ( 479 )   Save
    In order to reduce the influence of freight fluctuation to the operation and decision-making of crude oil transportation and related enterprises. It is necessary to master the fluctuation law and changing characteristics of international crude oil freight. Effectively grasping the fluctuations and changing characteristics of freight has a vital significance for the operators to invest and manage the companies. In view of Baltic Dirty Tanker Index (BDTI) fluctuation mechanism, and after applying methods of unit root test and variance ratio test to verify the mean reversion characteristic of BDTI verification, this paper analyzes the mean reversion characteristic of BDTI to study its variation trend. Meanwhile, a time related model is established to forecast and analysis the BDTI which improves the traditional mean reversion model, and the corresponding method for parameters estimation is given. The improved model is verified through the numerical simulation both on the fitting effect and prediction accuracy. First, through the characteristics test, the mean regression equation with average level changes over time is established. Second, by using Korlgomov forward differential equation, a prediction model is set up on the base of improved mean reversion model to obtain the predictive value and confidence intervals, then predicted values are obtained through the fitting path of BDTI historical samples. Finally, through the analysis of BDTI published by Clarkson Database, result shows that on the one hand, the crude oil freight index has a significant mean return characteristic. And on the other hand, by forecasting and analyzing the crude oil freight index, the average relative error of this improved model is 0.1597 which is less than the traditional model's 0.1908, while the goodness of fit of improved model is 0.9420 which is a little higher than the tradition's 0.9396. The results show that the improved prediction model has better fitting effect than the traditional model, so it can better reflect the actual situation of the market. This means that the improvement of the mean regression model might be beneficial to the further study and application of the mean regression models. In the aspect of management and operation, the analysis and prediction of freight fluctuation and improvement of the mean regression model will be helpful for investment enterprises to make more excellent investment decision-making proposals.
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    Adjexpectile as A Risk Measure: Properties、Optimization and Asset Allocation Applications
    ZHOU Jing, LUO Le
    2018, 26 (5):  51-61.  doi: 10.16381/j.cnki.issn1003-207x.2018.05.006
    Abstract ( 740 )   PDF (1745KB) ( 593 )   Save
    A suitable financial risk measure is especially important. Distinct risk measures have different impacts on asset pricing, portfolio hedging, capital allocation, and investment performance evaluation. Standard deviation、VaR and ES are commonly used risk measurement tools,but there are lots of defects. For example, the standard deviation makes the upside and downside movements of returns be same punishment; VaR depends only on the probability of more extreme realizations but not on their values, and is not subadditivity risk measure; Expected Shortfall(ES) is a conditional expected value below the quantile, which although overcomes VaR's drawbacks, but only depends on catastrophic loss, thus being more conservative. Newey and Powell (1987) define the "asymmetric least squares" (ALS) and put forward the concept of expectile. It has some excellent properties, such as:strictly monotone increasing; positive homogeneity; translation invariance; superadditivity; prudentiality and sensitiveness to tail events. What's more, it's an average that balances between conditional upside mean and conditional downside mean.In this paper, the expectile is extended to asset allocation, and put forward to Adjexpectile's concept based on Levy theorem. Its economic and financial meaning can be understood as follows:when the portfolio return is lower than its τ quantile, after trading off conditional downside mean punishment, the size of the losses below the expected return. The coherent risk measure of Adjexpectile is discussed. Generally Adjexpectile satisfies subadditivity and positive homogeneity, further meeting the convexity, providing a theoretical basis for Adjexpectile portfolio optimization. Also, the relationship between Adjexpectile and shortfall、VaR、standard deviation, as well as Adjexpectile risk contribution and Euler decomposition is discussed. To Adjexpectile portfolio optimization, the nonparametric method is used to convert Adjexpectile into a linear programming problem. In the empirical analysis part, six asset indexes are enployed to the optimization allocation. Because the characteristics of six indexes data are more complex, having left skewness, also having right skewness and leptokurtosis, so for a given τ value, the average of four CARE modeles is taken to estimate different index α value into portfolio optimization calculation. The conclusions are summarized as follows:(1) Portfolio efficient frontier areas:to standard deviation as a risk measure, 99% Adjexpectile portfolio frontier is better than 99% shortfall frontier, overlaps the mean standard deviation portfolio frontier; to Shortfall as risk measurement, 99% Adjexpectile portfolio frontier is better than 99% shortfall portfolio frontier. The charm of Adjexpectile as risk measure is shown. (2) Portfolio risk diversification areas:mean Adjexpectile asset allocation is more dispersed than the mean standard deviation and mean Shortfall. This further embodies its advantage.
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    Supply Chain Optimal Strategy under Trade Credit Based on Tax Shield Effect
    XIE Jia-ping, DONG Guo-shu, ZHANG wei-si, YANG Guang
    2018, 26 (5):  62-73.  doi: 10.16381/j.cnki.issn1003-207x.2018.05.007
    Abstract ( 656 )   PDF (1533KB) ( 390 )   Save
    Paying corporate income tax is an obligation that all enterprises must undertake. The tax burden is a cost that all businesses cannot afford to ignore. But the tax act has led to a tax shield for businesses with financing. It could offset some of the taxes that should be paid by the capital-raising companies. So, to target to optimize supply chain enterprises in the financial system, it embodies in the supply chain enterprises have financing leverage risk and cost and tax shield effect in the process of weighing, and combines with different ways of financing interest cash situation analysis, so that more accurate and practical business decision-making has been done.Research is based on trade credit financing pattern, introducing the tax shield effect, and establishes a trade credit model with tax shield in a two-stage supply chain composed of a single core supplier and a single dealer. The research studies supply chain dealers' quantity strategy with financing needs are and core suppliers price strategy, discusses the value of explicit and implicit interest means on the enterprise supply chain. And the decision-making guidance is provided for the choice of the means of payment in the trade credit.Through the Stackbelberg game and optimization and comparative analysis, the best order decision of the distributor and the best price decision of the supplier are found, and further according to the way of interest on cash or a pre-determined recessive and dominant plan breath way of financing demand point, we put on the supply chain enterprise respectively in four kinds of situations. The comparison and analysis of the profit of enterprise target in different situation is analyzed, and the decision in the highest profit situation is the optimal decision choice of the enterprise.Through the comparative analysis, it is found that when dealers need financing after the quantity of goods is determined, if tax on the interest deduction ceiling is lower than the similar bank loan rate in the same period, implicit interest settlement is far more valuable to dealers; When dealers need financing before ordering and credit line is lower than a critical value under explicit way, dealers are motivated to prefer radical ordering strategy with the way of implicit interest. At the same time, the cost of tax and purchasing and expected earning is a tradeoff for dealers. Different ways of interest with a special turn are chosen when the order quantity is different. When suppliers need financing before ordering, if production cost balance under two way of interest settlement is lower than a critical value, implicit interest settlement is more valuable to suppliers; When suppliers need financing after ordering, suppliers should choose the better way of interest settlement combing with pricing strategy.Finally, an example is used to discuss the distributed photovoltaic power plant and power grid generation in the process of trade credit payment delay occurs, profits and the decision variables of the power plant and power grid and the decision variables and the relationship between important parameters. The conclusion of this paper is proved by numerical analysis. Our research will help the analysis of enterprise decisions in other financing modes of supply chain finance. The disadvantages of ignoring the tax factors of traditional supply chain financial models are remedied. It not only makes the financing in the supply chain enterprise decision-making more accurate and more guiding significance, but also provides strong evidence for financing on the supply chain enterprise's capital structure adjustment and the establishment of financial decisions. Because the research is based on the fact that the enterprise income tax is taken as the breakthrough point in many types of taxes, so for other relevant tax and financial system of supply chain optimization and decision-making, research has inspired lead role. Other relevant research can be based on this model and follow the research idea of this paper.
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    Growth Enterprise Financing under Supply Chain Management: Debt Financing Versus Equity Financing
    YU Hui, WANG Yu
    2018, 26 (5):  74-85.  doi: 10.16381/j.cnki.issn1003-207x.2018.05.008
    Abstract ( 896 )   PDF (1176KB) ( 739 )   Save
    Debt financing, which was once the main financing choice of growth enterprise, is gradually and partly replaced by equity financing due to the rapid development of equity financing and the difficulties and high cost of debt financing. However, there is no consensus on the optimal financing choice when growth enterprise raises fund for its new project. From the perspective of firm value and capital cost,the pecking order theory shows that firms tend to choose internal financing and prefer debt to equity if external financing is required. Does it still hold true for growth enterprise considering the combination of financing and operation management? Present study considers a risk neutral retailer facing good market opportunity employs debt or equity financing to exploit the market, after which its demand function becomes D=a-bp+βe, where β and e represent its growth and effort, respectively.The financing amount B depends on the ordering cost and effort cost, and is used to meet the capital needs of supply chain operation. In debt financing, the rate is fixed to r, and the financing amount is limited by λA, where λ is mortgage rate and A is the fixed asset of retailer. This limitation does not exist in equity financing, where P/B method (the P/B ratio is set to α) is adopted to determine the valuation of grow enterprise with own fund η and fixed asset A. Thus, the valuation of enterprise is α(A+η), and the stock share of the retailer changes to (α(A+η))/(α(A+η)+B). Based on these, the debt and equity financing models under the supply chain management for a growth retailer are construeted, and its optimal financing choice via comparing the retailer's maximum profits under the optimal operation and financing decisions between debt and equity financing is investigated. Additionally, a numerical simulation which is partly based on the data of Chinese stock market is also present to clearly reveal the financing choice. The key finding is that the optimal financing choice is affected by supply chain cooperation, firm growth and valuation. Without the supply chain cooperation, the undervalued retailer with high growth or the overvalued one prefers equity to debt, but the undervalued one with low or medium growth follows the pecking order theory. However, the financing choice of retailer is dominated by its growth under supply chain cooperation. Firm valuation only works in the financing choice of the retailer with medium growth. These differences between the cases with and without supply chain cooperation stem from the dominant right of the supplier. Our results contribute to the financing decision of growth enterprise and the exploration of the interaction between operation and financing, and also provide insight into the model research of equity financing from the perspective of supply chain.
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    A Study on the RFID Investment Decision Model for the Revised Joint Replenishment and Delivery Problem
    CUI Li-gang, DENG Jie, WANG Lin, ZHANG Jin-Long, XU Mao-zeng
    2018, 26 (5):  86-97.  doi: 10.16381/j.cnki.issn1003-207x.2018.05.009
    Abstract ( 698 )   PDF (2135KB) ( 496 )   Save
    The increasing in the customers' requirement diversifications, followed by the quick response changing of logistics, brings great challenges to replenishment-delivery operations under the multi-item circumstance. Radio frequency identification (RFID) helps realize the information sharing in the whole supply chain by tracing the status of products in real-time. However, in light of the high cost of RFID, it is necessary to balance the risks and the returns before systematical investment in the replenishment-delivery processes. Accordingly, under the assumption that RFID implementation helps improve the ordering efficiency and JIT (Just in Time) efficiency, a revised joint replenishment and delivery (JRD) based RFID investment decision model is proposed. Through coordinating the multi-item joint replenishment and multi-client joint delivery, the revised JRD with RFID deployed tries to achieve the minimum total cost, thereby the optimal basic cycle time and the replenishment frequencies of multi-item are obtained. Thereafter, the differential evolutionary (DE) algorithm is applied to solve the proposed JRD model by redesigning its evolutionary process considering the model structure. Numerical experiments reveal the following conclusions:(a) DE has been testified to be an efficient and effective algorithm in searching the optimal results. (b) RFID helps decrease the total cost of the JRD model, but the equilibrium between the investment scale and the returns should not be overlooked. (c) RFID investment in a single process of JRD is worse than that in the whole system, and RFID investment in a high cost sector promises more gaining. This research contributes the literature within the realm of investigating the RFID investment effects to the replenishment-delivery system, and the results can provide certain references for the practitioners to initiate RFID projects.
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    Optimal Purchasing Policies of Capital-constrained Retailers under Different Decision-making Objectives
    SHI Jin-zhao, GUO Ju-e, Richard Y. K. FUNG, XIA Bing
    2018, 26 (5):  98-108.  doi: 10.16381/j.cnki.issn1003-207x.2018.05.010
    Abstract ( 661 )   PDF (1453KB) ( 454 )   Save
    In recent years, the interfaces of enterprises' operational and financial decisions have received substantial attentions in academia. Among them, the "capital-constrained newsvendor" (CCNV) problem which focuses on studying the impacts of liquidity constraints on retailers' inventory policies is widely concerned. With a random price-dependent market demand, the capital-constrained retailer's integrated purchase timing, quantity, and financing decisions under two different decision-making objectives, i.e. expected-profit-maximizing and default-rate-minimizing, are respectively studied.The simplest supply chain structure comprising one supplier and one retailer is examined. The retailer is assumed to be capital-constrained (its internal capital is not enough to afford the optimal orders), but it can borrow from banks to fulfill its purchasing. The supplier offers two purchase time windows to the retailer, i.e. "early-purchasing during the lead time with a lower price but high demand uncertainty" and "late-purchasing at the beginning of the selling season with a higher price but no demand uncertainty". In each purchase time window, the retailer's optimal purchase quantity and the corresponding financing policies are studied under two different decision-making objectives respectively. On this basis, the optimal purchase timing policies are investigated under each objective and the differences between the policies are highlighted. Some main conclusions of this research are summarized as follows.(a) In the case of early-purchasing, the retailer's optimal purchase quantity and corresponding financing policies are different under two proposed decision-making objectives, while its policies under these objectives are the same in the case of late-purchasing. Furthermore, a default-rate-minimizing objective may induce some loss of expected profit in early-purchasing and the loss is decreasing with the retailer's internal capital level.(b) Under an expected-profit-maximizing objective, the retailer can conditionally obtain an "information bonus" in late-purchasing, while it will bear a higher wholesale price. Thus, it needs a trade-off between the "conditional information bonus" and the "inevitable cost loss" in late-purchasing, and then makes the optimal purchase timing decision. A multi-parameter based method is proposed to solve the timing decision problem. On the other hand, under a default-rate-minimizing objective, the retailer's timing decision is indifferent since it can always achieve a zero default rate by performing appropriate quantity strategies in both purchase time windows.
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    Dynamic Equilibrium of a Supply Chain Network Based on Retailers' Long-term Regret Aversion
    XU Ming-jiao, ZHOU Yan
    2018, 26 (5):  109-117.  doi: 10.16381/j.cnki.issn1003-207x.2018.05.011
    Abstract ( 600 )   PDF (2122KB) ( 345 )   Save
    In this paper, a dynamic equilibrium of a supply chain network, in which the demand is time-varying and random, is studied. Since the demand is uncertain and seasonal, the retailers in the network consider the negative effect of under-stock regret and over-stock regret, and make their optimal decisions based on long-term regret aversion. The optimal decision behaviors of manufactures, retailers considering the long-term regret aversion and demand markets are modeled by the variational inequalities. Numerical examples are given in three long-term regret cases to find the effect of retailers' long-term regret aversion on the equilibrium order quantities, profits and regret values. The results show that the equilibrium order quantities, profits and regret values are different when the degree of retailers' regret aversion are in the increasing case, unchanging case, and decreasing case. These conclusions can provide supposes for the decision makers of the supply chain network to make the best decisions considering the long-term regret aversion.
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    The Vehicle Routing Problem with the Recycling of Oil Pipelines and Oil Casings and the Differential Evolution Algorithm based on Niching Clearing
    PAN Wen-wen, GUO Hai-xiang, DU Tian-song, LIU Xiao, WANG De-yun
    2018, 26 (5):  118-128.  doi: 10.16381/j.cnki.issn1003-207x.2018.05.012
    Abstract ( 618 )   PDF (2438KB) ( 482 )   Save
    In order to avoid the problem that drilling cannot continue to work due to material shortage, warehouses often distribute pipelines and casings more than planed demand in the production of oilfield. In some cases, the excess pipelines and casings can't be used up. And if unused pipelines and casings are not recycled effectively, resources would be wasted. But the recycling would be in vain if the recycling cost is higher than the value of pipelines and casings. Based on the above, the Vehicle Routing Problem considering recycling value of pipelines and casings is studied, and a model which has a special constraint which requires that the recovery costs are lower than the current value of the pipelines and casings is proposed, and improved Differential Evolution Algorithm which is more effective than Genetic Algorithm is implemented. Numerical experiments are performed on real data from the south oilfield of the Ordos Basin belonging to North China branch of Sinope. The recovery scheme of the 94 oil wells includes 17 paths, and the transportation cost is RMB 37,200 lower than the value of oil pipelines and oil casings which is RMB 150,300. Finally, the sensitivity analyses performed examine the robustness of the proposed model. The results show that the unit price directly affects the recovery expense, and the number of vehicles is the most affected by the amount of unused pipelines and casings. In particular, our study not only has practical significance for saving resources and reducing the cost in the oil-field industry, but also has a great theoretical significance for the theoretical research of reverse logistics.
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    Order Scheduling Model and Algorithm for Hot-Rolled Seamless Steel Tube with Delivery Requirements
    WU Zi-xuan, LI Tie-ke, ZHANG Wen-xin, WANG Bai-lin, Wang Jian-jian
    2018, 26 (5):  129-137.  doi: 10.16381/j.cnki.issn1003-207x.2018.05.013
    Abstract ( 680 )   PDF (866KB) ( 368 )   Save
    The market demand for hot-rolled seamless steel tube presents multi-variety and small-batch characteristics, and delivery addresses and delivery time of orders are usually different. In this paper, the problem of hot-rolled order scheduling of seamless steel tube is extracted and defined from actual production. Hot-rolled order scheduling is the process of combining production orders into rolling batches and scheduling rolling batches sequence. In order to meet customer needs and ensure production efficiency and continuity, delivery factors, such as delivery address and delivery time, are introduced to the order scheduling. Moreover, considering delivery requirements and process characteristics, a model for this order scheduling problem is built to optimize the delivery period, ensure concentrated production and distribution, and minimize the total setup time of machines. A two-stage algorithm is provided further. In the first stage, to minimize differences among delivery time and addresses of orders, a hierarchical clustering algorithm is put forward on cohesion policy to cluster orders with the same process constraints and similar delivery requirements, thereby forming an initial rolling plan. In the second stage, a hybrid variable neighborhood search algorithm is presented to improve the initial plan in terms of setup times and earlyness/tardiness. Results of experiments with actual order data show the effectiveness of the model and algorithm. This research has a useful reference for the study of order scheduling problem of other steel products or products involving complex process and delivery constraints.
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    Website Space Optimization Strategy of Pharmaceutical E-tailing under Category Management and Exogenous Demand Model
    LI Jian-bin, ZHENG Yu-ting, DAI Bin
    2018, 26 (5):  138-146.  doi: 10.16381/j.cnki.issn1003-207x.2018.05.014
    Abstract ( 675 )   PDF (1439KB) ( 476 )   Save
    With the liberalization of the policy, pharmaceutical e-tailing keeps surging forward challenging the status of traditional pharmacies. Unlike the daily use products sold by traditional e-tailing, pharmaceutical products sold by pharmaceutical e-tailing have extremely high brand concentration which means the difference between similar products is brand only. In this article, the decision making problem is studied from the perspective of pharmaceutical e-tailing in order to expand its market share.Customers usually are unwilling to go through all the website space of pharmaceutical e-tailing, but only browse the home page and make the purchasing decision. Therefore, how to optimize the website space especially the home page in order to expand the market is an interesting question. Comparing with the shelf space optimization in offline channel, the website space optimization in online channel is quite different. The traditional shelf space optimization regard all the positions in single shelf is homogeneous, while the website space optimization consider the perception of viewer to define the space of website especially the home page is heterogeneous. First the market share and substitutions between products are estimated through the demand exogenous model with the input of historical sales volume. Then we the market share and substitutions between products are regarded as the input of the website space optimization in order to generate the display list and order in home page of pharmaceutical e-tailing.In traditional research of category management, Multinomial Logit model which has vulnerability that it assumes the stochastic components of utility follow independent identical distribution is adopted. In reality, there are many factors which can simultaneously affect the utility and the market share of different choices. Considering the extremely high brand concentration of pharmaceutical products, Multinomial Logit model is invalid here. Therefore, the exogenous demand model which has more degree of freedom is employed to incorporate market variables into the consumers' buying behavior.Based on the shelf management model with slotting fee and the maximum potential market share obtained by exogenous demand model, ignoring the number of exhibition,an website space optimization model of integer programming based on an brand-new concept named the biggest market share is construeted to maximize the utility of the pharmaceutical e-tailing by deciding the sequence of posted products.Meanwhile, using the sales data of 111.com during August 1st to October 30th in 2015, an empirical study is conducted to investigate the potential performance of the proposed website space optimization model. The data is first sifted in order to get rid of the abnormal ones and input the normal data into the estimating model. Results demonstrate that the website space optimization model we proposed can significantly improve the sales of pharmaceutical e-tailing by 8.06% in average, and up to 27.21%. Although we lack of chance to evaluate the effect of changing the display number of product in home page, we theoretically measure that fewer display may also reach the profit that pharmaceutical e-tailing expects.
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    Peer Effects on Entrepreneurial Activity: Model and Empirical Study
    YAN Yan-yang, DENG Jia-yi, WEN Dan-yan
    2018, 26 (5):  147-156.  doi: 10.16381/j.cnki.issn1003-207x.2018.05.015
    Abstract ( 900 )   PDF (1271KB) ( 412 )   Save
    The study of this paper proved that peer effects exist in entrepreneurial activities. After theoretical analysing based on the game model, it is found that individual will make the decision of starting a business due to influence of adventurous and competing spirit of surrounding entrepreneurs, or to the technology and experience gained through social learning during contacting with surrounding entrepreneurs. Both of them make entrepreneurial activities have peer effects. Further empirical study using cross-section data from the Chinese Family Panel Studies (CFPS) confirmed the above deductionshowing that:(1) the statistically remarkable peer effects in individual entrepreneurial activitiesmeans that entrepreneurial activities of neighborhood have obvious demonstration effect on individuals, which increases their expectation of participation inentrepreneurial activities. (2) applications of media transmission in information era, such as television and Internethave replacement to some extent of peer effects among physical neighbours. In the technical aspect of peer effects identification, we adopt instrumental variable method to suppress interference of correlated effects and reflection problems. The results of this paper indicate that publicities through various channels, including community interaction and various media methods, has indispensable effects in promoting public entrepreneurship,even though entrepreneurial activities are free choice behavior of individual in market participation.
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    Evolutionary of Uncooperative Behaviors Caused by Price Change and Cost Change in Project of Complex Products of System
    CHEN Zhan-duo
    2018, 26 (5):  157-168.  doi: 10.16381/j.cnki.issn1003-207x.2018.05.016
    Abstract ( 726 )   PDF (2169KB) ( 434 )   Save
    Uncooperative behaviors of contractors caused by environmental uncertainty during contract conduction is one of the key factors which lead failure of Complex Products of System (CoPS) project. In this paper, effects on uncooperative behaviors of CoPS contractors caused by environmental fluctuation, which is divided into market price change and product cost change, are studied. Firstly the revenue functions of buyer and seller in the case of price decline are discussed, the logic relationship between each variables and price decline is revealed, constructs the replicator dynamics equation is constracted, the evolutionary path of user's uncooperative behavior is analyzed, and cooperative threshold and uncooperative threshold which are decided by the degree of price decline are concluded. And then the seller's uncooperative behavior in the case of cost up is analyzed in the same logic of price decline. Finally, numerical simulations are used to demonstrate the effects of different initial conditions of values on the evolutionary path. It is found that:(1) All the variables in revenue functions of both contractors are related with the degree of the price decline when price declining, and all the variables in revenue functions of both contractors are related with the degree of the cost up when cost growing. (2) The relationship between buyer's behavior and price decline:the evolutionary result is cooperative strategy when price decline is less than the threshold of buyer's cooperative strategy (we calls as "buyer's cooperative threshold"); the evolutionary result is uncooperative strategy when price decline is higher than the threshold of buyer's uncooperative strategy (we calls as "buyer's uncooperative threshold"); however, the evolutionary result depends on seller when price decline is between the "buyer's cooperative threshold" and the "buyer's uncooperative threshold". (3) The relationship between seller's behavior and cost up:the evolutionary result is cooperative strategy when cost up is less than the threshold of seller's cooperative strategy (we calls as "seller's cooperative threshold"); the evolutionary result is uncooperative strategy when cost up is higher than the threshold of seller's uncooperative strategy (we calls as seller's uncooperative threshold); however, the evolutionary result depends on buyer when cost up is between the "seller's cooperative threshold" and the "seller's uncooperative threshold". Study reveals the non-linear relationship between uncooperative behaviors and price falling or cost rising, and identifies the cooperative threshold and uncooperative threshold of both seller and buyer. The study provides a new perspective for contractual governance in CoPS and similar project management context under environment uncertainty. The study can provide decision support for management practice to improve the success rate of CoPS and similar project by governing uncooperative behavior caused by environment uncertainty.
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    Analysis on the Behavioral Strategy of Participants on Online Lending Market based on Evolutionary Game Theory——A Trilateral Game Perspective
    LIU Wei, XIA Li-qiu
    2018, 26 (5):  169-177.  doi: 10.16381/j.cnki.issn1003-207x.2018.05.017
    Abstract ( 1062 )   PDF (1487KB) ( 647 )   Save
    The default events often occur on online lending market which damages the interests of participants due to lack of supervision and credit risk management. In this paper, a trilateral evolutionary game model which includes online lending platform, financial regulators and investors on online lending market is constructed. From the evolutionary game perspective, How the strategies of online lending platform, financial regulators and investors influence the operation of online lending market is addressed, and PaipPaiDai platform is taken as a case for numerical simulation analysis. The findings show that the difference of the results of trilateral game is significant with different initial values. The evolutionary game of participants' strategy does not have stable center point and stable equilibrium point on online lending market. In addition, online lending platform tends to take self-discipline strategy when financial regulators take strict supervision measures. Online lending platform tends to select self-discipline strategy gradually with the investment amounts increase. Finally, the countermeasures and suggestions are put forward to regulate the participants' behavior and risk control on online lending market.
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    The Impact of Rating Inconsistency on Online Review Helpfulness: A Perspective on Attribution Theory
    MIAO Rui, XU Jian
    2018, 26 (5):  178-186.  doi: 10.16381/j.cnki.issn1003-207x.2018.05.018
    Abstract ( 1022 )   PDF (966KB) ( 609 )   Save
    Helpful online reviews can decrease information overload, help customers make better decisions and increase customers' satisfaction about the websites. Therefore, so what makes a helpful online review has become an important topic for scholars and practitioners. Individual review rating has been investigated to be an import factor impacting the review helpfulness by the extant literature, but the literature provides inconsistent views on the direction of the impact. From the perspective of attribution theory, the inconsistent findings are reconciled by proposing the inconsistency between the individual review rating and the average rating as a factor influencing review helpfulness and taking the number of product reviews and the direction of rating inconstitency as moderators. 832233 online hotel reviews are collected from Ctrip.com using a Web data crawler and analyzed by zero-inflated negative binomial regression model. The empirical results show that rating inconsistency has a significant negative impact on review helpfulness. The high rating inconsistency will lead consumers' non-product-related attributions of the review and decrease the review helpfulness. The number of product reviews and the direction of rating inconsistency moderate the impact of rating inconsistency on review helpfulness. The impacts are more salient for the reviews with high product review volumns and for the reviews whose rating is bigger than the average rating. Our findings provide new perspective for understanding the review helpfulness and for online market owners on how to design online review systems and manage reviews on their websites.
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    Study on the Cooperation Model Decisions for Hotels and OTAs in the Off-season
    LIN Ya-qin, GUO Qiang, ZHANG Zhi-wen, ZHAO Da
    2018, 26 (5):  187-196.  doi: 10.16381/j.cnki.issn1003-207x.2018.05.019
    Abstract ( 1060 )   PDF (1931KB) ( 744 )   Save
    The occupancy rate is so important to hotel revenue and investment recovery that hotels have to implement revenue management, alleviating the plight of low occupancy rate in the off-season. Fortunately, in the era of Internet Plus, strengthen cooperation with Online travel agents (OTAs) can advance a possible solution to this problem, and right decisions in cooperation modes can further alleviate the predicament, coordinating hotel service supply chain, improving the overall benefits of hotel service supply chain and benefiting hotels and OTAs both. Today, the mainly cooperation modes of hotels and OTAs are the merchant model and the agent model, but which one is better and how should hotels and OTAs make a right decision on model choices? However, there has been still no scholar studying these significant problems. Therefore, establishing Stackelberg static equilibrium models, the optimal cooperation model decisions of one hotel and one OTA in the off-season are discussed, and obtain the optimal results in several common situations are obtained with the method of Graphic and example analysis. The specific research process is as follows. Firstly, through reverse derivation, the optimal decisions of the OTA and the hotel in the merchant model where the OTA is leader and the agent model where the hotel is leader are obtained, preparing for the following comparative study. At the same time, the sensitivity of the key parameters is analyzed. And then, the optimal cooperation model decisions of the hotel and the OTA are demonstrated and obtained base on analysis results above, and it is found that in most cases the merchant model is the best choice for the hotel, but not for the OTA, and they will choose the merchant model when reach agreement in the off-season. It should be noted that, proposing of the case data in this paper is mainly based on a number of online hotel sales information retrieval and pre project in hospitality industry. This study not only provides the cooperation mode decision support for hotels and OTAs in operational significance, but also fills the research vacancy in comparison, selection and optimization of cooperation models of OTAs and hotels, providing a reference for later related researches.
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