基于学习遗忘曲线模型的员工生产率研究

基于学习遗忘曲线模型,研究劳动密集型产业的员工生产率。在将该模型扩展到多周期的基础上,探讨了劳动技能培训与巩固、短期雇佣与长期雇佣等对员工生产率的影响。此外,在考虑发生停产的情况下,分析了不同的人力资源管理策略对员工生产率的影响。研究结果为企业人力资源管理提供了理论依据和参考,并为企业保持较高的员工生产率提供了解决思路。     

A Genetic Algorithm for the Weight Setting Problem in OSPF Routing

With the growth of the Internet, Internet Service Providers (ISPs) try to meet the increasing traffic demand with new technology and improved utilization of existing resources. Routing of data packets can affect network utilization. Packets are sent along network paths from source to destination following a protocol. Open Shortest Path First (OSPF) is the most commonly used intra-domain Internet routing protocol (IRP). Traffic flow is routed along shortest paths, splitting flow at nodes with several outgoing links on a shortest path to the destination IP address. Link weights are assigned by the network operator. A path length is the sum of the weights of the links in the path. The OSPF weight setting (OSPFWS) problem seeks a set of weights that optimizes network performance. We study the problem of optimizing OSPF weights, given a set of projected demands, with the objective of minimizing network congestion. The weight assignment problem is NP-hard. We present a genetic algorithm (GA) to solve the OSPFWS problem. We compare our results with the best known and commonly used heuristics for OSPF weight setting, as well as with a lower bound of the optimal multi-commodity flow routing, which is a linear programming relaxation of the OSPFWS problem. Computational experiments are made on the AT&T Worldnet backbone with projected demands, and on twelve instances of synthetic networks.     

A Systematic Uncertainty Analysis of an Evaluative Fate and Exposure Model

Multimedia fate and exposure models are widely used to regulate the release of toxic chemicals, to set cleanup standards for contaminated sites, and to evaluate emissions in life-cycle assessment. CalTOX, one of these models, is used to calculate the potential dose, an outcome that is combined with the toxicity of the chemical to determine the Human Toxicity Potential (HTP), used to aggregate and compare emissions. The comprehensive assessment of the uncertainty in the potential dose calculation in this article serves to provide the information necessary to evaluate the reliability of decisions based on the HTP A framework for uncertainty analysis in multimedia risk assessment is proposed and evaluated with four types of uncertainty. Parameter uncertainty is assessed through Monte Carlo analysis. The variability in landscape parameters is assessed through a comparison of potential dose calculations for different regions in the United States. Decision rule uncertainty is explored through a comparison of the HTP values under open and closed system boundaries. Model uncertainty is evaluated through two case studies, one using alternative formulations for calculating the plant concentration and the other testing the steady state assumption for wet deposition. This investigation shows that steady state conditions for the removal of chemicals from the atmosphere are not appropriate and result in an underestimate of the potential dose for 25% of the 336 chemicals evaluated.     

Sharing inventory risk in supply chain: The implication of financial constraint

A supply chain may operate under either preorder mode, consignment mode or the combination of these two modes. Under preorder, the retailer procures before the sale and takes full inventory risk during the sale, while under consignment, the retailer sells the product for the supplier with the supplier taking the inventory risk. The combination mode shares the risk in the supply chain. The existing research has examined the supply chain modes from various operational aspects. However, the impact of financial constraint is neglected. This paper examines the impact of financial constraint and investigates the supply chain efficiency under each mode. Based on a Stackelberg game with the supplier being the leader, we show that without financial constraint the supplier always prefers the consignment mode, taking full inventory risk. Whereas, in the presence of financial constraint, the supplier will sell part of the inventory to the retailer through preorder, which shares the inventory risk in the supply chain. We show that with financial constraint, the combination mode is the most efficient mode even if the retailer earns zero internal capital.     

A TIME-SERIES APPROACH FOR CONSTRUCTING EXPECTATIONS MODELS*

This article presents an efficient way of dealing with adaptive expectations models—a way that makes use of all the information available in the data. The procedure is based on multiple-input transfer functions (MITFs): by calculating lead and lag cross correlations between innovations associated with the variables in the model, it is possible to determine which periods have the greatest effects on the dependent variable. If information about k periods ahead is required, fitted values for the expectation variables are used to generate k-period-ahead forecasts. These in turn can be used in the estimation of the transfer function equation, which not only contains the usual lagged variables but also allows for incorporation of lead-fitted values for the expectation variables. The MITF identification and estimation procedures used are based on the corner method. The method is contrasted with the Almon distributed-lag approach using a model relating stock market prices to interest rates and expected corporate profits.