EFFECT OF FORESTLAND AVAILABILITY BY OWNERSHIP TYPE ON LICENSE SALES FOR HUNTING: A SPATIAL APPROACH

Abstract The effect of forestland availability under different ownership types on license sales for hunting in nine Southeastern states is empirically evaluated. An equation that represents license sales for hunting is estimated assuming the sale of hunting licenses in a particular county is related to the characteristics of that county as well as the characteristics and license sales for hunting in its neighboring counties. The positive effects of the amounts of both national and private forestland on license sales reaffirm the potential benefits of maintaining forestland to stimulate hunting. The positive spillover effect of national forests on license sales for hunting suggests that availability and close access to hunting in national forests within neighboring counties are important in supporting hunting license sales in a county. This study contributes to the general understanding of the drivers affecting individuals’ decisions to use natural resources for hunting. Advances in natural resource modeling, specifically the spatial process model and geospatial data used in this research, make it possible to examine the interactions between the spatial dynamics and ownership attributes of the natural system, allowing policy makers to design natural resource management practices that respond to a system characterized by these interactions.     

Contract type and decision right of sales promotion in supply chain management with a capital constrained retailer

From the practices of Chinese consumer electronics market, we find there are two key issues in supply chain management: The first issue is the contract type of either wholesale price contracts or consignment contracts with revenue sharing, and the second issue is the decision right of sales promotion (such as advertising, on-site shopping assistance, rebates, and post-sales service) owned by either manufacturers or retailers. We model a supply chain with one manufacturer and one retailer who has limited capital and faces deterministic demand depending on retail price and sales promotion. The two issues interact with each other. We show that only the combination (called as chain business mode) of a consignment contract with the manufacturer’s right of sales promotion or a wholesale price contract with the retailer’s right of sales promotion is better for both members. Moreover, the latter chain business mode is realized only when the retailer has more power in the chain and has enough capital, otherwise the former one is realized. But which one is preferred by customers? We find that the former is preferred by customers who mainly enjoy low price, while the latter is preferred by those who enjoy high sales promotion level.     

A quantitative analysis of the Greek soft-drink market,or: How your advertisement will help your competitor's sales

This paper is deailing with the application of quantitative methods in analysing the Greek soft drink market. Single equation and simultaneous-equation regression models are developed and tested against real time-series data. The use of these methods in a real life case brought out the serious problem of interelationships existing between advertising and sales of products with minor differences and also marked the need of its further investigation.     

若干经济数学模型的研究与应用

本文论述了近些年我们在投入产出模型、广告最优随机控制模型、最佳营销管理模型以及时间序列—马尔可夫链组合预测模型等方面所做的研究工作，同时也论及国内外在上述几方面的研究状况．     

具有销售成本的小额信贷模型

首先剖析了我国小额贷款实践的现状和存在的问题,通过理论和数学模型分析,指出信贷约束本身并不是贫困产生和持续的充分条件.由于农户存在产品销售成本带来的销售规模效应给农户的贫困的影响及其对农村小额信贷项目的影响,过低的贷款额度可能会使得小额贷款项目对农户失去吸引力,造成小额贷款需求萎缩.因此,适当扩大小额贷款的额度限制,有利于农户更加积极地参与到小额贷款项目中,通过正当经营,增加收入,从而提高生活水平.     

应用Markov链方法分析销售策略

本简单地分析了销售的过程，利用认知心理得到的销售状态指标和Markov链在Pfeifer工作的基础上建立的客户关系模型，对几种不同的销售策略进行了比较。分析结果表明，在与客户关系不好的情况下．采用先改善与客户的关系、后实施销售活动效果比直接销售好些。     

Dynamic pricing inventory control under fixed cost and lost sales

This paper studies a periodic review pricing and inventory replenishment problem which encounters stochastic demands in multiple periods. In many inventory control problems, the unsatisfied demand is traditionally assumed to be backlogged but in this paper is assumed to be lost. In many practical problems, a consumer who could not buy what he/she wants in one store is not willing to wait until that store restocks it but tries to buy alternatives in other stores. Also, in this paper, the random variable for the demand function is assumed to be general, which means that any probability function for the random variable can be applied to our result. Cost terms consist of the holding cost by the leftover, the shortage cost by lost sales, and the strictly positive fixed ordering cost. The objective of this paper is to dynamically and simultaneously decide the optimal selling price and replenishment in each period by maximizing the expected profit over the finite selling horizon. We show that, under the general assumption on the random variable for the demand, the objective function is K$K$-concave, an (s,S)$(s\text{,}S)$ policy is optimal for the replenishment and the optimal price is determined based on the inventory level after the replenishment in each period.     

Demand seasonality in retail inventory management

We investigate the value of accounting for demand seasonality in inventory control. Our problem is motivated by discussions with retailers who admitted to not taking perceived seasonality patterns into account in their replenishment systems. We consider a single-location, single-item periodic review lost sales inventory problem with seasonal demand in a retail environment. Customer demand has seasonality with a known season length, the lead time is shorter than the review period and orders are placed as multiples of a fixed batch size. The cost structure comprises of a fixed cost per order, a cost per batch, and a unit variable cost to model retail handling costs. We consider four different settings which differ in the degree of demand seasonality that is incorporated in the model: with or without within-review period variations and with or without across-review periods variations. In each case, we calculate the policy which minimizes the long-run average cost and compute the optimality gaps of the policies which ignore part or all demand seasonality. We find that not accounting for demand seasonality can lead to substantial optimality gaps, yet incorporating only some form of demand seasonality does not always lead to cost savings. We apply the problem to a real life setting, using Point-of-Sales data from a European retailer. We show that a simple distinction between weekday and weekend sales can lead to major cost reductions without greatly increasing the complexity of the retailer’s automatic store ordering system. Our analysis provides valuable insights on the tradeoff between the complexity of the automatic store ordering system and the benefits of incorporating demand seasonality.     

Bayesian demand updating in the lost sales newsvendor problem: A two-moment approximation

We consider Bayesian updating of demand in a lost sales newsvendor model with censored observations. In a lost sales environment, where the arrival process is not recorded, the exact demand is not observed if it exceeds the beginning stock level, resulting in censored observations. Adopting a Bayesian approach for updating the demand distribution, we develop expressions for the exact posteriors starting with conjugate priors, for negative binomial, gamma, Poisson and normal distributions. Having shown that non-informative priors result in degenerate predictive densities except for negative binomial demand, we propose an approximation within the conjugate family by matching the first two moments of the posterior distribution. The conjugacy property of the priors also ensure analytical tractability and ease of computation in successive updates. In our numerical study, we show that the posteriors and the predictive demand distributions obtained exactly and with the approximation are very close to each other, and that the approximation works very well from both probabilistic and operational perspectives in a sequential updating setting as well.     

Optimal ordering policies for periodic-review systems with a refined intra-cycle time scale

Chiang [C. Chiang, Optimal ordering policies for periodic-review systems with replenishment cycles, European Journal of Operational Research 170 (2006) 44–56] recently proposed a dynamic programming model for periodic-review systems in which a replenishment cycle consists of a number of small periods (each of identical but arbitrary length) and holding and shortage costs are charged based on the ending inventory of small periods. The current paper presents an alternative (and concise) dynamic programming model. Moreover, we allow the possibility of a positive fixed cost of ordering. The optimal policy is of the familiar (s, S) type because of the convexity of the one-cycle cost function. As in the periodic-review inventory literature, we extend this result to the lost-sales periodic problem with zero lead-time. Computation shows that the long-run average cost is rather insensitive to the choice of the period length. In addition, we show how the proposed model is modified to handle the backorder problem where shortage is charged on a per-unit basis irrespective of its duration. Finally, we also investigate the lost-sales problem with positive lead-time, and provide some computational results.