浅议读者心理研究在图书馆服务中的应用

本文主要针对读者服务过程中出现的相关心理问题进行研究,分析了在读者服务过程中要重视对读者心理问题的缺陷研究,提出了馆员提供成功心理服务的情感因素以及心理服务中的工作艺术,从而使读者服务的质量得以进一步提高。     

高校创先争优活动应牢牢把握“六个要点”

高校创先争优活动应紧紧围绕“推动科学发展、促进校园和谐、服务师生员工、加强组织建设”这一中心工作积极稳步推进,要运用党员承诺、领导点评、群众评议等有效方式,充分激发高校党组织和党员的进取心、荣誉感,积极营造争当先进、争创优秀的浓厚氛围.高校深入开展创先争优活动,不应是运动式活动,应该建立长效机制.当前,高校创先争优要以坚定理想信念为重点,加强师德师能建设;以健全民主法制为切入点,加强制度建设;以培养高素质干部和党员为落脚点,加强组织建设;以提高教师教育教学能力为支撑点,促进师资队伍建设;以实施素质教育为着力点,促进高校教育科学发展;以社会主义核心价值观为闪光点,推进人才培养体系建设.     

宋朝开国史与士人的记忆及改造——以宋朝"崇文"气象为中心的考察

更真实的宋朝开国史,与宋代文献记载之间存在相当大的距离,其中北宋中叶以来士人描述的"崇文"气象,就是一个典型的例证.宋太祖虽然采取了许多有利于文教及文治的措施,但其目的主要是扭转以往长期失衡的文武关系,以稳定秩序,却并未造就具有时代特征的"崇文"倾向.宋太宗朝后期才开始落实的"崇文抑武"治国方略,到北宋中叶遂形成突出的"崇文"气象.由此直至南宋,主流的士人群体在追忆本朝开国史时,有意识地描述并改造了当时的政治状态,赋予一种"崇文"的气象.其实,这一现象乃是当时价值评判下选择历史记忆的结果,并得到国家的认同.     

信息产业对经济增长的贡献研究——以桂林市为例

本文通过引入时间序列计量经济学中的协整分析理论与方法,对1995-2005年间桂林市信息产业在经济增长中的影响进行定量研究,实证信息产业对GDP增长的影响显著,两者存在长期均衡的协整关系.信息产业发展与经济增长是格兰杰因果关系.     

基于多任务代理模型的管理者动态报酬契约设计

从Holmstrom提出的多任务代理模型出发,分析了企业管理者面临的纵向多任务特性,并将管理者投入划分为追求当期财务绩效和追求企业能力两个维度,以此为基础构建了基于多任务代理模型的管理者动态报酬契约。结果表明,基于多任务代理模型的管理者动态报酬契约相对于传统静态报酬契约具有明显的帕累托效率改进,有利于诱导管理者在不同维度上合理分配投入,避免短期效应的发生。最后,运用K集团公司的简单案例对其应用进行了简单分析。     

基于可变权重的DEA效率评价模型

传统DEA模型将投入、产出权重视为固定变量。为了更合理地对决策单元的效率进行评价,本文研究了如何将有关投入、产出变量的权重的更多信息融入效率评价模型,提出了可变权重的概念,给出了一种基于可变权重的DEA效率评价模型。本文模型是CCR模型的推广。在有关权重信息可得的前提下,本文模型较之CCR模型中效率评价上更为合理。但是,如何准确度量投入、产出权重并将其函数化,是本文方法应用的难点。一个算例分析演示了本文模型。     

决策结论的敏感度分析

本文通过决策参数的分析,对决策结论进行了敏感度分析。找出影响决策结论的参数,以及参数在什么区间内变化会(不会)影响决策方案的排序结论。并通过实例分析与验证了本方法的合理性与可行性。本文所得结论对任何以方案排序为结论的决策方法均适用。     

焕新计划下考虑消费者细分的产品定价策略

焕新计划是生产商为提升自身竞争优势而推出的一种促销手段,加入焕新计划的消费者在第一阶段可以享受全方位服务,在第二阶段可以享受以旧换新抵扣优惠。消费者将权衡加入焕新计划的费用、服务水平以及抵扣力度等因素决策是否在第一阶段加入焕新计划。本文假设时尚型消费者每阶段都会购买最新产品,而节俭型消费者第一阶段购买产品后在第二阶段继续使用,针对这两类消费者在实施焕新计划和不实施焕新计划两种情况下,构建两阶段模型以决策产品的最优定价;运用解析方法分析了产品的生产成本等参数对最优定价的影响;运用解析方法和数值算例方法对两模型进行对比。     

Building a Human Health Risk Assessment Ontology (RsO): A Proposed Framework

Over the last decade the health and environmental research communities have made significant progress in collecting and improving access to genomic, toxicology, exposure, health, and disease data useful to health risk assessment. One of the barriers to applying these growing volumes of information in fields such as risk assessment is the lack of informatics tools to organize, curate, and evaluate thousands of journal publications and hundreds of databases to provide new insights on relationships among exposure, hazard, and disease burden. Many fields are developing ontologies as a way of organizing and analyzing large amounts of complex information from multiple scientific disciplines. Ontologies include a vocabulary of terms and concepts with defined logical relationships to each other. Building from the recently published exposure ontology and other relevant health and environmental ontologies, this article proposes an ontology for health risk assessment (RsO) that provides a structural framework for organizing risk assessment information and methods. The RsO is anchored by eight major concepts that were either identified by exploratory curations of the risk literature or the exposure‐ontology working group as key for describing the risk assessment domain. These concepts are: (1) stressor, (2) receptor, (3) outcome, (4) exposure event, (5) dose‐response approach, (6) dose‐response metric, (7) uncertainty, and (8) measure of risk. We illustrate the utility of these concepts for the RsO with example curations of published risk assessments for ionizing radiation, arsenic in drinking water, and persistent pollutants in salmon.     

Inventory‐Based Dynamic Pricing with Costly Price Adjustment

We study an average‐cost stochastic inventory control problem in which the firm can replenish inventory and adjust the price at anytime. We establish the optimality to change the price from low to high in each replenishment cycle as inventory is depleted. With costly price adjustment, scale economies of inventory replenishment are reflected in the cycle time instead of lot size—An increased fixed ordering cost leads to an extended replenishment cycle but does not necessarily increase the order quantity. A reduced marginal cost of ordering calls for an increased order quantity, as well as speeding up product selling within a cycle. We derive useful properties of the profit function that allows for reducing computational complexity of the problem. For systems requiring short replenishment cycles, the optimal solution can be easily computed by applying these properties. For systems requiring long replenishment cycles, we further consider a relaxed problem that is computational tractable. Under this relaxation, the sum of fixed ordering cost and price adjustment cost is equal to (greater than, less than) the total inventory holding cost within a replenishment cycle when the inventory holding cost is linear (convex, concave) in the stock level. Moreover, under the optimal solution, the time‐average profit is the same across all price segments when the inventory holding cost is accounted properly. Through a numerical study, we demonstrate that inventory‐based dynamic pricing can lead to significant profit improvement compared with static pricing and limited price adjustment can yield a benefit that is close to unlimited price adjustment. To be able to enjoy the benefit of dynamic pricing, however, it is important to appropriately choose inventory levels at which the price is revised.