易逝品的更新换代策略研究

更新换代频繁是易逝品的一个重要特征，制定合理的更新换代策略尤为重要。文章分析了易逝品更新换代的影响因素；考虑到新产品推出时机对老产品过时的影响，指出在进行更新换代时，会导致社会福利降低、引起需求流失和企业的利润下降。基于上述问题，文章提出了三种更新换代策略。     

基于消费者保留价格的易逝品定价和订货的联合策略

文章通过分析消费者期望价值(因保留价格引起)对需求的影响,构建了与消费者期望价值有关的乘性随机需求函数,其中消费者期望价值是保留价格和销售价格的差与期望满足率的乘积。在此假设下,讨论了单一产品的最优价格和最优订货量的联合决策问题。在单一产品情况下,报童的最优订货量应使得期望缺货率为产品成本与保留价格的比值,最优价格则与保留价格、产品成本、期望满足率及需求的期望价值弹性相关。     

回购契约在易逝品供应链协调中的应用研究

在考虑易逝品的市场需求为随机需求情况下,研究了基于供应链环境下的回购契约;分别分析了零售商和制造商在没有协调情况下各自的最优决策以及在回购契约协调下双方的最优决策;推导出了在回购契约下零售商的最佳订货量。并通过数值分析,验证了在回购契约下双方的最优决策能使供应链的整体利润达到集中控制下的最优状态。     

基于高残值易逝品的供应链战略匹配研究

文章以高残值易逝品为研究对象,研究企业如何调整其供应链战略,来与其产品战略进行匹配。通过对高残值易逝型产品的特征进行分析,站在产品需求特点和供应链反应能力的角度,来确定企业在供应链各环节与之匹配的战略。     

第三方物流提供商对易逝品供应链的影响效果分析

通过在集中式系统和分散式系统下分别分析引入第三方物流提供商对供应链订货量和收益的影响，指出引入第三方物流提供商并不一定能够对供应链产生正面的效果，只有在某些条件下才能提高系统的订货量，增加整个系统或制造商和零售商的利润。     

易逝品供应链中退货逆向物流产生的原因分析

退货是易逝品逆向物流的重要组成部分。本文通过对易逝品供应链中退货的类型和原因分析,指出了加强易逝品退货逆向物流管理的重要性,并对如何减少易逝品供应链中的退货逆向物流及对退货逆向物流进行有效管理进行了研究。     

二次订货策略在易逝品供应链协调中的应用研究

针对单制造商和单零售商组成的二级供应链模式,在需求不确定的前提下,首先建立简单的一次订货模型。当预测市场需求信息更新时,零售商可以追加订货,或者制造商进行中期回购。由此建立了二次订货策略模型,并对该模型进行分析以及模拟仿真,得到与仅有一次订货机会相比较,二次订货策略能够显著提高供应链的整体期望利润,可以有效协调供应链系统,给制造商和零售商进行决策提供参考。     

易变质品定价策略选择

变质物品销售策略是企业关注的重点,价格折扣是销售策略的主要方式之一,现阶段,对价格折扣的研究多是从供应商的角度出发,通过影响商品成本来对价格折扣进行研究,研究的内容也多为降价研究。文章不同于现有的多数研究,从零售商的角度出发,通过决策商品价格达到价格折扣,研究的内容为易变质品涨价模型。     

基于成本分摊的易逝品两级供应链利益分配分析

易逝品本身的特点决定了其生产经营风险大、市场需求不确定,所以制造商和零售商之间采取采购承诺和契约的有效方式来实现风险和利益的分摊。本文从成本分摊的角度,探讨在两级供应链中利益在制造商和零售商之间的分配,以及在不同情形下的供应链总利益。     

基于库存调剂的易逝品供应链合作利益分配问题探讨

本文将解决多人合作博弈问题的Shapley值方法用于解决两级易逝品供应链合作利益分配问题。考虑由一个供应商和两个零售商所组成的两级供应链模型,零售商与供应商不合作时,零售商根据供应商的批发价确定订货量,合作时共同决定库存,零售商之间的合作为共同决定订货量且通过库存调剂(转运)共享库存,三方合作可获最大利益,采用Shapley值法可合理分配合作利益,从而使合作更稳定。     

The influence of seller learning and time constraints on sequential bargaining in an artificial perishable goods market

This paper investigates the formation of prices in a perishable goods market where agents bargain repeatedly through pair-wise interactions. After extensive field observations, we chose to focus on two aspects that seem important to actors of this market: the passage of time and update in judgement when gathering information. The main feature of the market is that a seller bargaining with a buyer has incomplete information about buyer's willingness to pay and is not sure how her trading partner will evaluate an offer or compare it with other options. On the other hand, buyers have limited time to look for goods and cannot meet all possible sellers before making a decision. Hence agents cannot calculate the best price to offer but receive information through limited interactions, and use this information to choose their actions.An agent-based model was built to represent a framework that mimics the observed market institution and where agent's possible behaviors and learning was made as consistent as possible with gathered data. Simulations were run, first for sensitivity analysis concerning main parameters, then to test the dependance of agents’ learning to (a) the time buyers can spend on the market and (b) the frequency of update in learning by sellers. To validate the model, features produced by the simulated market are compared to the stylized facts gathered for negotiation about four goods. We reproduce the main features of the data on the dynamics of offers, transaction prices and agents’ behavior during the bargaining phases.     

On pricing and hedging options in regime-switching models with feedback effect

We study the pricing and hedging of European-style derivative securities in a Markov, regime-switching, model with a feedback effect depending on the economic condition. We adopt a pricing kernel which prices both financial and economic risks explicitly in a dynamically incomplete market and we provide an equilibrium analysis. A martingale representation for a European-style index option's price is established based on the price kernel. The martingale representation is then used to construct the local risk-minimizing strategy explicitly and to characterize the corresponding pricing measure.     

Optimal locations and flow allocations for aggregation hubs in supply chain networks of perishable products

Establishment of aggregation hubs in a supply chain network (SCN) is typically a facility location-allocation (FLA) decision, which is known to be a NP-hard optimization problem. Considering the flow of heterogeneous perishable products, like fresh produce, with different spoilage rates, further increases the complexity of such a problem. This is due to the effect of transportation time and conditions, services provided in the hub, and hub proximity to supply sources, on the quality and quantity of products eventually reaching the demand destinations, and hence on the location-allocation decision. In this paper, this problem is formulated as a mixed integer linear programming (MILP) model that considers a number of problem characteristics simultaneously for the first time, to minimize the transportation, spoilage, processing, and capacity-based hub establishment costs. Due to its complexity, two hybrid algorithms that combine a meta-heuristic with a perishability-modified transportation algorithm, are proposed to solve the problem. The algorithms are based on binary particle swarm optimization (BPSO) and simulated annealing (SA). Taguchi analysis is used to tune the significant parameters of both algorithms considering different problem sizes. Computational analysis is further conducted to evaluate and compare the performances of the algorithms using randomly generated test instances and exact solutions obtained using CPLEX. Results show that while both algorithms are capable of obtaining optimum solutions for most instances, the hybrid BPSO slightly outperforms the hybrid SA in terms of consistency and solution time.     

Factor pricing of cryptocurrencies

In this paper, we study the cryptocurrency pricing factors. We review the literatures which state that the cryptocurrency market is weakly efficient. We use the Fama–MacBeth method to investigate the pricing factors. The classical equity-based risk factors including size, momentum, and value to growth from the Fama–French three factor model are studied. We use crypto-unique coin-to-token as a proxy for value-to-growth. For volatility risk factor category, we investigate realized volatility, skewness and jump. We also investigate liquidity factors including bid–ask, volume growth and Roll’s measure. The macro factors are found not to be an explanatory factor. The attention factor works sometimes. The factor model constructed by the significant factors explain most of the excess return of cryptocurrencies.     

Implied risk aversion and pricing kernel in the FTSE 100 index

This paper studies the estimation of the pricing kernel and explains the pricing kernel puzzle found in the FTSE 100 index. We use prices of options and futures on the FTSE 100 index to derive the risk neutral density (RND). The option-implied RND is inverted by using two nonparametric methods: the implied-volatility surface interpolation method and the positive convolution approximation (PCA) method. The actual density distribution is estimated from the historical data of the FTSE 100 index by using the threshold GARCH (TGARCH) model. The results show that the RNDs derived from the two methods above are relatively negatively skewed and fat-tailed, compared to the actual probability density, that is consistent with the phenomenon of “volatility smile.” The derived risk aversion is found to be locally increasing at the center, but decreasing at both tails asymmetrically. This is the so-called pricing kernel puzzle. The simulation results based on a representative agent model with two state variables show that the pricing kernel is locally increasing with the wealth at the level of 1 and is consistent with the empirical pricing kernel in shape and magnitude.     

出口贸易的技术外溢效应:基于三部门模型的实证研究

本文将经济系统分为非出口部门、初级产品出口部门和工业制成品出口部门，构建了三部门的出口贸易技术外溢效应模型。对中国“八五”及“九五”期间的各地区截面数据进行了实证分析，结果表明，在“八五”及“九五”期间，我国出口贸易对国内非出口部门的技术外溢效应主要集中在工业制成品出口部门，且工业制成品出口通过提高或有效利用本部门的要素投入和对非出口部门的技术外溢而促进经济增长。而出口部门（包括初级产品出口部门与工业制成品出口部门）与非出口部门之间的要素（劳动和资本）投入生产率差距存在收敛趋势。     

Cross-sectional implications of dynamic asset pricing with stochastic volatility and ambiguity aversion

Building on recent research that highlights the importance of macroeconomic volatility and ambiguity aversion in explaining the dynamics of stock returns, in this paper we propose a dynamic asset pricing model that simultaneously accounts for stochastic macroeconomic volatility and ambiguity, assuming that investors deal with uncertainty about the mechanics of macroeconomic fluctuations using first-release consumption and revisions to aggregate consumption on vintage data. Our results show that the proposed model captures a large fraction of the cross-sectional variation of excess returns for a wide range of market anomaly portfolios. Furthermore, while the price of risk for ambiguity is positive and significant for the vast majority of assets under study, macroeconomic volatility yields ambiguous outcomes, although it significantly increases the explanatory power of the model for specific assets. Our results suggest that macroeconomic volatility and ambiguity complement each other in explaining the cross-sectional behavior of stock returns.     

关于折旧与产品成本关系的研究

企业控制产品成本是通过控制材料费、控制工资、控制综合费用。如果某种产品成本中的折旧费用占有举足轻重的地位时,也可以通过调整折旧方法达到控制产品的目的。本文构造了在计算期内保持单位产品成本不变的折旧方法,并对其应用进行了探讨。     

EVA与价值链管理整合的研究

在企业越来越重视价值创造的今天,EVA管理体系和价值链理论应运而生。但无论是哪种方法,都会存在缺陷和不足。本文从价值链分析法的局限性角度出发,分析并阐述了把EVA分析体系应用到价值链管理的可行性,为增强和提高价值链理论的实用性提供一种新思路。     

Impact of electronic road pricing on real estate prices in Singapore

Since 1998, Singapore has had an Electronic Road Pricing (ERP) system set up with a network of toll gantries to tax vehicles entering designated areas in the city center during peak hours. Using the congestion rate hike with effect from November 1, 2010 as an exogenous shock, we test the effects of the ERP rate hike on retail, office and residential real estate prices. The results show that the November 2010 congestion toll rate increases cause a 19% drop in retail real estate prices within the cordon ERP areas relative to retail real estate prices outside the cordon ERP areas. The results are statistically and economically significant. However, the toll rate hike has no significant impact private office and residential real estate within cordoned ERP areas. The robustness and falsification tests could not reject the negative effects associated with the toll rate hike on retail real estate prices.