艾森克人格问卷结构效度层面理论研究

研究目的:以层面理论方法检验艾森克人格问卷结构效度;研究方法:以558名大学新生为被试,以85个项目的艾森克人格问卷为研究工具,以层面理论和SSA分析技术作为问卷意义表达及数据分析方法;研究结果:最小空间分析三维结构异化系数为0.18,艾森克人格问卷的测试数据相关矩阵在几何空间中的极化结构清晰,艾森克提出的人格理论的三个维度结构得到验证.     

Analysis of postponement strategy by EPQ-based models with planned backorders

This paper develops economic production quantity (EPQ)-based models with planned backorders to evaluate the impact of the postponement strategy on a manufacturer in a supply chain. We derive the optimal total average costs per unit time for producing and keeping n end-products in a postponement system and a non-postponement system, respectively. By comparing the optimal total average costs of the two systems, we evaluate the impact of postponement on the manufacturer under four circumstances. Our results show that postponement strategy can give a lower total average cost under certain circumstances. We also find that the key factors in postponement decisions are the variance of the machine utilization rates and the variance of the backorder costs.     

An adaptation of the EOQ formula for JIT quasi-pull system production

This research demonstrates for the first time that in a just-in-time (JIT) quasi-pull production environment, a model adapted from the Economic Order Quantity and made up of two specific formulas can be employed for calculating an optimised lot size. The assumptions of our model are: a low level of defects, and insignificant shortage backordering and failure of the equipment. JIT quasi-pull production is the state typically reached by many manufacturing companies because it is almost impossible to achieve zero set-ups and zero work-in-process (WIPs) even in the best Lean Production implementations. In this model, finished products are shipped at once in a JIT way. The two developed formulas are specialised: one for balanced stations/processes and the other for unbalanced stations; the formulas allow calculation of an optimised lot size. Several applications of the formulas have been tested and discussed through a case study. Findings demonstrated that the optimised quantity of a lot size has to be smaller than the customer’s daily demand for the product. Moreover, in case of unbalanced stations with long cycle times, the formula forces the company to reduce its set-up times and the cycle times. The new model will be of interest to practitioners who are seeking a way to balance the costs of set-ups and the cost of holding some WIPs and offers interesting avenues for new research.     

订单生产模式下垄断竞争市场的延期支付契约研究

在垄断竞争的市场结构环境下,研究按照订单生产模式进行生产时,由生产商和零售商组成的供应链为应对外部市场环境的变化,采用延期支付契约前后的利润变化情况;从生产商和零售商两个视角,分别针对传统市场长期均衡情况、实施延期支付契约后的短期均衡情况、实施延期支付契约后的长期均衡情况建立利润模型,介绍模型的求解过程;通过具体的算例,结合灵敏度分析方法,讨论在垄断竞争巾场中应用延期支付契约时随着产品需求弹性系数的变化供应链利润的变化情况.分析比较后发现,通过应用延期支付契约,短期内可以使生产商和零售商获得巨大的超额利润;而在长期均衡状况下,实施延期支付契约前后供应链中各成员企业的利润变化并不明显.     

Note: A note on the production and inventory systems taking account of time value

This paper deals with the optimal inventory decisions taking account of time value by applying the concept of the present value method, and modifies the bounds for the optimal cycle time described in Chung et al. (Production Planning & Control, 1998, 9, 580–584). A modified algorithm to compute the optimal cycle time is developed to improve the paper of Chung et al. Finally, a numerical example is given to illustrate the algorithm discussed in this paper.     

A new EPQ model: integrating lower pricing,rework and reject situations

The economic production quantity (EPQ) is a well-known and commonly used inventory control technique. It has been used for well over 50 years to optimize lot sizes in transportation/production. The standard results are easy to apply but are based on a number of assumptions. A common assumption in the EPQ model is that all units produced are of perfect quality, this will underestimate the actual required quantity. Many researchers have studied the effects after relaxing this assumption on the EPQ model. The previous studies had considered that imperfect quality and defective items are either to be reworked instantaneously and kept in stock or rejected at a cost. The objective of this paper is to provide a framework to integrate lower pricing, rework and reject situations into a single EPQ model. A 100% inspection is performed in order to identify the amount of good quality items, imperfect quality items and defective items in each lot. This model assumes that items of imperfect quality, not necessarily defective, could be used in another production situation or sold to a particular purchaser at a lower price. The electronic and clothing industries give good examples for such situations. A mathematical model is developed and a numerical example is presented to illustrate the solution procedures. It is found that the time factor of when to sell the imperfect items is critical, as this decision will affect the inventory cost and the batch quantities.     

A note on “The EPQ with partial backordering and phase-dependent backordering rate”

Pentico et al. [The EPQ with partial backordering and phase-dependent backordering rate. Omega 2011;39(5):574-7] recently proposed an EPQ model with partial backordering. They tried to determine the minimum average total cost per year from the three cases: to lose all sales, to meet all demand, and to allow stockouts with partial backordering. In this paper, we solve the same model without differential calculus and present a different decision procedure. Without the comparison of those costs, a numerical example is illustrated to determine the optimal production policy by our criteria.     

对罪犯的艾森克个性问卷(EPQ)调查分析——以四川宜宾某监狱234名男性为例

罪犯个性特征是犯罪心理学研究的主要内容之一,本研究采用艾森克个性问卷(EPQ),对6种类型234名入狱罪犯个性特征进行了调查,结果发现罪犯组与常模组在艾森克个性问卷(EPQ)的4个维度上的得分均具有显著性差异,不同类型罪犯之间个性无显著性差异;罪犯的个性特征与罪犯受教育程度、居住地等人口统计学变量之间存在较为密切的联系。     

A note on the deterministic EPQ with partial backordering

In a recent paper published in Omega [Pentico DW, Drake MJ, Toews C. The deterministic EPQ with partial backordering: a new approach. Omega 2009; 37(3):624–36], the authors proposed an EPQ model with partial backordering. In the EPQ model, a critical value of backordering rate was developed, below which the optimal production policy is either to lose all sales or meet all demand, above which the optimal policy is to allow stockouts with partial backordering and meet fractional demand. However, there exists a flaw in the critical value of backordering rate, which will be amended in this note.     

A supplement to the EPQ with partial backordering and phase-dependent backordering rate

In this note, we extend Pentico et al. (2011)'s [1] EPQ model where the authors considered two different backordering rates during shortage period; they assumed the backordering rate increases only from the start of production phase. We propose two models that allow the backordering rate to increase anytime during the production phase, and thus provide more flexibility for decision-makers to vary the backordering rate.