基于需求转移的易逝性产品最优动态定价策略

本文针对易逝性产品中新产品对老产品需求的转移作用,应用收入管理方法得出老产品的最优动态定价策略,并应用最大凹向包络理论给出了简化算法的方法.数值算例表明在存在需求转移的情况下,应更早的提供较低的价格.最后作者给出了包含生产和定价的综合模型.     

房地产投资的实物期权理论研究回顾与述评

笔者以为:房地产投资的实物期权理论研究从研究范围来看可分为增量房与存量房两大层次;从历史角度来看:自1985年以来,相关研究大致经历了一个从只关注客观变量的传统视角到更多关注主观性变量的现代视角的转变过程.基于此,本文对以往研究作了系统性的回顾、梳理与评论.指出决策的灵活性是把握该领域内研究脉络的一个主线.最后,本文指出了以往研究的局限性并对其发展方向作了展望.     

基于时变需求的供应链基本库存水平优化研究

在时变需求环境下,基于模型推导得到供需双方基本库存水平局部优化与整体优化决策方程,并基于算例对基本库存水平整体优化的成本绩效以及需求时变性的影响进行数据分析,得到如下重要结论:基本库存水平整体优化明显降低供应链库存成本.     

基于反向物流的商品定价和退货政策研究

综述了基于反向物流的商品定价和退货政策的最新研究成果。在此基础上,通过建立模型,对基于反向物流的商品定价策略和退货政策进行了进一步的研究,并求出了商品的最优价格和最优退货价格。基于模型,对管理提出了一些建议。最后指出了将来可能的研究方向。     

对当代大学生就业问题的理性思考

当前毕业生存在的就业问题，究竟是“人才过剩”，还是有其它制约因素?文章分析了较为严峻的就业形势和较为普遍的“有业不就”的现状，提出了转变观念，摆正心态，调整结构，对接需求，畅通渠道，完善体制的理性思考。     

流动性约束与消费行为关系的实证研究

流动性约束是指资本市场的资金流动具有单向性,流动性约束的存在可以提高储蓄水 平,降低当期累积消费. 通过三阶段生命期界的最优消费模型,证明了流动性约束的定量存在, 并通过实证检验发现,我国消费总量中受流动性约束影响的比例达到83. 46 %. 因此,增强信 贷市场的流动性,对于扩张有效需求将起重要作用.     

需求不确定下的补偿策略理论模型

在需求不确定的前提条件下就供应商对销售商的补偿策略进行了深入研究,建立了包 含风险偏好的补偿策略理论模型. 在该理论模型的基础上,运用数值分析的手段分析了风险偏 好对供应链中参与者决策行为的影响,为供应链决策者制定合理的决策提供了科学依据. 最 后,结合我国国情,重点讨论如何在我国正确实施补偿策略.     

Tolerance of Uncertainty: Links to Happenstance,Career Decision Self‐Efficacy,and Career Satisfaction

This study investigated the extent to which tolerance of uncertainty affects the relationship between happenstance skills and career satisfaction via career decision self‐efficacy. Moderated mediation analysis was conducted on data collected from 321 graduates (175 men, 146 women) of Korean universities making the school‐to‐work transition. Results showed that career decision self‐efficacy fully mediated the relationship between happenstance skills and career satisfaction. Furthermore, the moderation effect of tolerance of uncertainty had a significant impact on the relationship between happenstance skills and career decision self‐efficacy. Tolerance of uncertainty should be considered an important variable in happenstance career theory and intervention. Unplanned influences should also be considered important factors in the career decision‐making process.     

A shelf-space optimization model when demand is stochastic and space-elastic

The more customer demand is impulse-driven, the more it is space-dependent and the more it is subject to variation. We investigate the corresponding problem of retail shelf-space planning when demand is stochastic and sensitive to the number and position of facings. We develop a model to maximize a retailer׳s profit by selecting the number of facings and their shelf position under the assumption of limited space. The model is particularly applicable to promotional or temporary products.We develop the first optimization model and solution approach that takes stochastic demand into account, since the current literature applies deterministic models for shelf-space planning. By the means of an innovative modeling approach for the case with space- and positioning effects and the conversion of our problem into a mixed-integer problem, we obtain optimal results within very short run times for large-scale instances relevant in practice. Furthermore, we develop a solution approach to account for cross-space elasticity, and solve it using an own heuristic, which efficiently yields near-optimal results. We demonstrate that correctly considering space elasticity and demand variation is essential. The corresponding impacts on profits and solution structures become even more significant when space elasticity and stochastic demand interact, resulting in up to 5% higher profits and up to 80% differences in solution structures, if both effects are correctly accounted for. We develop an efficient modeling approach, compare the model results with approaches applied in practice and derive rules-of-thumb for planners.     

A delay-in-payment contract for Pareto improvement of a supply chain with stochastic demand

We consider a supply chain consisting of a single supplier and a single retailer with stochastic customer demand, which is operated over an infinite horizon. We propose a delay-in-payment contract to coordinate the supply chain. With this contract, the supplier allows the retailer to pay partial order cost at the ordering epoch, and to pay the remaining portion after a permissible number of periods. The system is formulated as a stochastic dynamic programming problem. It is shown that there exists a base-stock policy to be optimal. Compared with the traditional wholesale-price contract, the delay-in-payment contract with appropriate parameters can achieve a Pareto improvement (i.e., the performances of both the supplier and the retailer using the delay-in-payment contract are better than those using the wholesale-price contract). Numerical studies are performed to investigate both the effectiveness of the Pareto improvement, and the impact of the major parameters of the delay-in-payment contract on the system performance.