Models and metrics to assess humanitarian response capacity

The race to meet vital needs following sudden onset disasters leads response organizations to establish stockpiles of inventory that can be deployed immediately. These government or non-government organizations dynamically make stockpile decisions independently. Even though the value of one organization's stock deployment is contingent on others' decisions, decision makers lack evidence regarding sector capacity to assess the marginal contribution (positive or negative) of their action. To our knowledge, there exist no metrics describing the system capacity across many agents to respond to disasters. To address this gap, our analytical approach yields new humanitarian logistics metrics based on stochastic optimization models. Our study incorporates empirical data on inventory stored by various organizations in United Nations facilities and in their own warehouses to offer practical insights regarding the current humanitarian response capabilities and strategies. By repositioning inventory already deployed, the system could respond to disasters in the same expected time with a range of 7.4%–20.0% lower cost for the items in our sample.     

Scale effects of R&D as reflected in earnings and returns

Using returns to scale as a conceptual foundation, we explore how R&D-related earnings performance and earnings variability depend upon firm size. We find that the positive association between the level of future earnings and R&D intensity increases with firm size, and that the positive association between the volatility of future earnings and R&D intensity decreases with firm size, consistent with R&D productivity increasing with scale. We also show that R&D scale is associated with lower market returns, consistent with the idea that R&D investment risk declines with scale.     

Testing weak form efficiency on the Toronto Stock Exchange

In order to test for weak form efficiency in the market a vast pool of individual stocks must be analyzed rather than a stock market index. In this paper, a model-based bootstrap is used to generate a series of simulated trials and a modified chart pattern recognition algorithm is applied to all stocks listed on the Toronto Stock Exchange (TSX). The number of patterns detected in the original price series is compared with the number of patterns found in the simulated series. By simulating the price path specific time dependencies present in real data are eliminated, making price changes purely random. Patterns, if consistently identified, carry information which adds value to the investment process, however, this informativeness does not guarantee profitability. Conclusions are drawn on the relative efficiency of some sectors of the economy. Although the null hypothesis of weak form efficiency on the TSX cannot be rejected, some sectors of the Canadian economy appear to be less efficient than others. In addition, pattern frequencies appear to be negatively dependent on the two moments of return distributions, variance and kurtosis.     

Classification of micro,small and medium enterprises (M-SME) based on their available levels of knowledge

This paper proposes a novel and practical method of classifying micro, small and medium enterprises (M-SME) based on their available levels of knowledge. This classification considers that the specific problems that dominate a company’s operations are related to the level of knowledge available. Therefore, identifying the dominant problem groups facing the company can enable an estimate of the level of knowledge available in the enterprise.Data from 2698 Mexican M-SMEs are used to identify operational problems. The main problem groups are obtained through a cluster analysis. The proposed classification consists of three levels of knowledge based on the interpretation of the dominant problem groups in each enterprise. Each of the 2698 Mexican M-SME are classified by a discriminant analysis.Nearly half of the M-SME are classified as having a lower level of available knowledge, and only 10% are classified with the highest level. No difference is observed between the size of the company and the level of available knowledge. This means that growth in the number of employees and sales of M-SMEs is not necessarily accompanied by an accumulation of knowledge that companies can use to improve their operations.     

Sustainable design of a closed-loop location-routing-inventory supply chain network under mixed uncertainty

Considering economic, environmental and social impacts, this paper presents a new sustainable closed-loop location-routing-inventory model under mixed uncertainty. The environmental impacts of CO₂ emissions, fuel consumption, wasted energy and the social impacts of created job opportunities and economic development are considered in this paper. The uncertain nature of the network is handled using a stochastic-possibilistic programming approach. Furthermore, for large-sized problems, a hybrid meta-heuristic algorithm and lower bounds are developed and discussed. Finally, a real case study is provided to demonstrate the applicability of the model in real-world applications, and several in-depth analyses are conducted to develop managerial implications.     

A robust inventory routing policy under inventory inaccuracy and replenishment lead-time

In this paper, we study an inventory routing problem under replenishment lead-time and inventory inaccuracy, which exist extensively in distribution systems for fresh products, but are often ignored in existing research. To solve the problem, a robust inventory routing policy is developed in three steps. At first, we propose the methods of updating the probability of the current net inventory and predicting those in future periods. For each candidate route, we develop a Robust TQL Algorithm to optimize the replenishment time, replenishment quantity and replenishment stage length. Finally, a genetic algorithm-based method is developed to optimize the delivery route.     

Diversification strategy with random yield suppliers for a mean–variance risk-sensitive manufacturer

We consider the diversification strategy for a mean–variance risk-sensitive manufacturer with unreliable suppliers. We first analyze the linear model and find that the suppliers are selected according to the descending order of their contributed marginal expected profit, and increasing the manufacturer’s risk-averseness leads to a more even allocation of demand across the suppliers. Then, we study the general newsvendor model. By approximating the leftover inventory with a normal distribution, we establish the general properties of the active supplier set and show that the supplier selection rule is similar to that under the risk-neutral setting when the demand uncertainty is large. Moreover, we conjecture that the selection rule also applies when the demand uncertainty is low, which we verify with an extensive numerical study. Our paper makes two contributions: First, we establish the properties of the optimal diversification strategy and develop corresponding insights into the trade off between cost and reliability under the mean–variance framework. Second, we perform comparative statics on the optimal solution, with a particular emphasis on investigating how changes in the supplier’s cost or reliability affect the risk-averse manufacturer’s ordering decisions and customer service level.     

基于事项凭证类别的分析与设计

在基于事项法会计研究的基础上,具体探讨了事项凭证的应用,核心研究企业经济业务活动分类及事项凭证类别,并以采购收款业务为例,详述如何借助不同类别的事项凭证格式进行经济业务的采集处理,从而实现事项凭证的生成。     

浅谈高校绩效管理工作的问题及对策

介绍绩效管理在高校人力资源管理中的意义,对目前高校绩效管理工作中存在的问题进行总结分析,指出基于岗位分类的绩效管理体系的重要性,并提出构建基于岗位的绩效管理体系的若干建议,为高校管理部门提供参考。     

Relationship regarding the demand for labor between domestic temporary and foreign workers: Korean case

With the progress of globalization, South Korea, one of the emerging industrial countries, has recently witnessed a sharp increase in the number of enterprises that employ foreigners. However, there are only a limited number of studies on the influence that such an increase has had on the labor market in the Republic of Korea. Thus, using ‘Workplace Panel Survey’ data surveyed by the Korea Labor Institute (KLI), this paper examines the relationship concerning the labor demand of an establishment between domestic temporary and foreign workers. Analysis using a bivariate Tobit model shows that a typical Korean firm attempts to employ domestic temporary and foreign workers simultaneously. Further, the empirical analysis found that any establishment that is relatively newly established and has difficulty in recruiting domestic workers hires foreign workers, but there is no evidence that establishments hire foreign workers rather than domestic temporary workers to save on the production cost.