区域经济发展差距的人力资源因素——基于吉林省和浙江省发展差距的思考

在对吉林和浙江经济发展差距描述的基础上,分析了两省人力资源的优劣,用统计数据说明了吉林省的人力资源虽然有潜在优势,但其利用人力资源的效率低于浙江省,所以经济发展态势弱于浙江,并进一步说明了两省产生差距的原因是制度创新水平不同。     

吉林省人才资源状况分析与对策研究

振兴吉林,人才资源是关键。吉林省未来10年,人才资源总量与结构均不能满足经济社会发展的需要。为此,从调整用人机制出发,吸引人才到吉林发展,至关重要。     

新世纪我国实施就业发展战略需要注意的几个问题——兼论21世纪前一二十年我国城乡劳动力供求的影响因素

就业问题已经成为一个世界性的难题。从理论上讲 ,劳动力供给和劳动力需求是影响就业状况的两个直接而又基本的因素。受此影响 ,2 1世纪前一二十年我国城乡就业形势十分严峻。这就决定了2 1世纪前一二十年我国就业发展战略在选择和实施时 ,需要注意以下问题 :促进经济发展 ,符合市场经济的要求 ,公平与效率相结合 ,城乡统筹考虑 ,长远目标与短期目标兼顾等     

上海确保市场供应稳定蔬菜价格的实践与思考

＂菜篮子＂里看形势。首先系统介绍上海多管齐下确保市场供应稳定蔬菜价格的有效做法,如落实菜篮子区县长负责制、完善蔬菜调控保障体系、强化蔬菜产销衔接功能、加强蔬菜产销能力建设等。蔬菜供应涉及千家万户,在充分发挥市场机制作用的基础上,需要政府实行有效的调控,担负起公共服务的职责,既要防止＂菜贵伤民＂,又要防止＂菜贱伤农＂。     

Optimal Expediting Policies for a Serial Inventory System with Stochastic Lead Time

In recent supply chains, often operating multiple delivery modes such as standard freight shipping and air is an effective way of addressing both delivery lead time uncertainties and service rates. We propose a model on how to optimally operate multiple delivery modes. We consider a serial supply chain and an expediting option from intermediate installations to the downstream of the chain. The goods move stochastically among the installations and the system faces a stochastic demand. We identify systems that yield simple optimal policies, in which both regular ordering and expediting follow a variant of the base stock policy. Expediting allows the system to be leaner due to the reduced regular order amount. In addition, we provide managerial insights linking expediting, base stock levels, and expediting costs based on analytical and numerical results.     

The Failure of Practical Intuition: How Forward‐Coverage Inventory Targets Cause the Landslide Effect

Seasonal demand for products is common at many companies including Kraft Foods, Case New Holland, and Elmer's Products. This study documents how these, and many other companies, experience bloated inventories as they transition from a low season to a high season and a severe drop in service levels as they transition from a high season to a low season. Kraft has termed this latter phenomenon the “landslide effect.” In this study, we present real examples of the landslide effect and attribute its root cause to a common industry practice employing forward days of coverage when setting inventory targets. While inventory textbooks and academic articles prescribe correct ways to set inventory targets, forward coverage is the dominant method employed in practice. We investigate the magnitude and drivers of the landslide effect through both an analytical model and a case study. We find that the effect increases with seasonality, lead time, and demand uncertainty and can lower service by an average of ten points at a representative company. While the logic is initially counterintuitive to many practitioners, companies can avoid the landslide effect by using demand forecasts over the preceding lead time to calculate safety stock targets.     

Promotion Planning and Supply Chain Contracting in a High–Low Pricing Environment

Demand forecast errors threaten the profitability of high–low price promotion strategies. This article shows how to match demand and supply effectively by means of two‐segment demand forecasting and supply contracts. We find that demand depends on the path of past retail prices, which leads to only a limited number of reachable demand states. However, forecast errors cannot be entirely eliminated because competitive promotions entail some degree of random (i.e., last‐minute) pricing. A hedging approach can be deployed to distribute demand risk efficiently over multiple promotional campaigns and within the supply chain. A retailer that employs a portfolio of forward, option, and spot contracts can avoid both stockouts and excess inventories while achieving the first‐best solution and Pareto improvements. We provide an improved forecasting method as well as stochastic programs to solve for optimal production and purchasing policies such that the right amount of inventory is available at the right time. By connecting a stockpiling model of demand with the supply side, we derive insights on optimal risk management strategies for both manufacturers and retailers in a market environment characterized by frequent price promotions and multiple discount levels. We employ a data set of the German retail market for a key generator of store traffic—namely, diapers.     

All You Need Is Trust? An Examination of Inter‐organizational Supply Chain Projects

This study examines the antecedents of supply chain project success. We first propose and test a model that describes the role of relationship‐level factors (trust and asymmetric dependence) and project‐level factors (between‐firm communication and within‐firm commitment) in determining supply chain project success. We find that project‐level factors completely mediate the effect of trust on project success. We conclude that trust, despite being a stronger predictor compared to asymmetric dependence, is necessary but not sufficient for supply chain project success. We then proceed to further explore the role of these factors by introducing a categorical scheme that differentiates supply chain projects based on the decision rights configuration of each project. This categorization enables us to explore how relationship‐level and project‐level factors can have different impact on performance based on the characteristics of a supply chain project. The findings offer insights into how to effectively manage supply chain projects and inter‐firm alliances.     

The Impact of Limited Supply on a Firm's Bundling Strategy

A firm's two‐product bundling decision is examined when the supply of one product is limited and consumer valuations are normally distSteckeributed. The firm can choose to sell products separately and/or through a bundle. We find that the impact of limited supply on a firm's bundling decision depends on the correlation between the consumer valuations of the two products as well as the symmetry level of the two products in terms of their attractiveness (how much they are valued by consumers). When the valuation correlation is high and the symmetry level of the two products is low, limited supply can drive bundling. When the valuation correlation is low or the symmetry level is high, limited supply can drive no bundling. When the attractiveness of both products are low or the valuation correlation is very high, limited supply has no impact on a firm's bundling decision: The firm should not bundle for all supply levels. This study offers a new driver for product bundling: the limited supply of a product. The existing bundling literature suggests that a firm should bundle symmetric products that have a low consumer valuation correlation, when bundling is driven by consumer valuation heterogeneity reduction. In contrast, when bundling is driven by limited supply, a firm should bundle asymmetric products with a high consumer valuation correlation. The benefit of supply‐driven bundling depends on the severity of supply limitation. When supply limitation is moderate, bundling creates value by expanding the market of the less attractive product. When supply limitation is severe, bundling enables a firm to extract a higher margin from the less attractive product.     

Supply Chain Design and Carbon Penalty: Monopoly vs. Monopolistic Competition

This paper studies whether imposing carbon costs changes the supply chain structure and social welfare. We explore the problem from a central policymaker's perspective who wants to maximize social welfare. We consider two stakeholders, retailers, and consumers, who optimize their own objectives (i.e., profits and net utility) and three competitive settings (i.e., monopoly, monopolistic competition with symmetric market share, and monopolistic competition with asymmetric market share). For the monopoly case, we find that when the retailer's profit is high, imposing some carbon emission charges on the retailer and the consumers does not substantially change the supply chain structure or the social welfare. However, when the retailer's profit is low, imposing carbon costs optimally can lead to a significant increase in social welfare. Moreover, the impact of imposing carbon emission charges becomes more significant when the degree of competition increases. Additionally, the quantum of benefit may depend only on factors common across industries, such as fuel and carbon costs.