The implications of heterogeneous habit in consumer beverage purchases on soda and sin taxes

In this article, we study the heterogeneity of habit strength in households’ demand for regular carbonated sweetened beverages (CSBs) and beer in the United States. A demand model that nests a smooth transition function is used to describe habit-based consumption patterns, revealing heterogeneous strengths of habits among households. We find that more habitual consumers, those with a strong preference for a particular product, are not as sensitive to price or expenditure as the aggregate population. This finding is further supported by simulations of the potential effects of soda and beer taxes. We find the aggregate response to soda and beer taxes is smaller than when the influence of habit is assumed to be homogeneous.     

Demand-driven integration and divorcement policy

Traditionally, vertical integration has concerned industrial economists only insofar as it affects market outcomes, particularly prices. This paper considers reverse causality, from prices – and more generally, from demand – to integration in a model of a dynamic oligopoly. If integration is costly but enhances productive efficiency, then a trend of rising prices and increasing integration could be due to growing demand, in which case a divorcement policy of forced divestiture may be counterproductive. Divorcement can only help consumers if it undermines collusion, but then there are dominating policies. We discuss well-known divorcement episodes in retail gasoline and British beer, as well as other evidence, in light of the model.     

Minimal Euclidean distance chart based on support vector regression for monitoring mean shifts of auto-correlated processes

Though traditional control charts have been widely used as effective tools in statistical process control (SPC), they are not applicable in many industrial applications where the process variables are highly auto-correlated. In this study, one new minimal Euclidean distance (MED) based monitoring approach is proposed for enhancing the monitoring mean shifts of auto-correlated processes. Support vector regression (SVR) is used to predict the values of a variable in time series. Through calculating minimal Euclidean distance (MED) values over time series, a novel MED chart is developed for monitoring mean shifts, and it can provide a comprehensive and quantitative assessment for the current process state. The performance of the proposed MED control chart is evaluated based on average run length (ARL). Simulation experiments are conducted and one industrial case is illustrated to validate the effectiveness of the developed MED control chart. The analysis results indicate that the developed MED control chart is more effective than other control charts for small process mean shifts in auto-correlated processes, and it can be used as a promising tool for SPC.     

A robustness study of a multi-echelon inventory model via simulation

This paper examines the robustness of a standard model of multi-echelon inventory systems, specifically the models discussed in Axsäter (Oper. Res. 48(5) (2000) 686). A simulation model was developed to explore the model's ability to predict system performance for a two-echelon one-warehouse, multiple retailer system using (R,Q) inventory policies under conditions that violate the model's fundamental modeling assumptions. In particular, the impact of non-stationary demand on this stationary demand inventory model was examined. The model performs well at the low demand and large retailer order batch size situations, but our testing of the model indicated that care must be taken when applying this model to situations that violate its fundamental assumption. These results should help practitioners to better understand the assumptions of these models and to determine when or when not to apply these models in practice.     

On a general periodic preventive maintenance policy incorporating warranty contracts and system ageing losses

In this paper, a general periodic preventive maintenance (PM) policy for a repairable revenue-generating system is developed and studied. We define ‘ageing losses’ as the difference in revenues generated by an ideal system (no ageing) and a real system that ages over the same period of consideration. It is assumed that preventive maintenance slows the system deterioration process and therefore reduces ageing losses. The proposed model is general in the sense that (1) both the warranty contracts and system ageing losses are incorporated in the maintenance cost modeling and (2) the implementation of PM actions does not have to be strictly periodic. A cost model is developed for the buyer under two decision variables—the calendar time of the first PM and the degree of each PM. Numerical examples are then presented to show the effectiveness of the proposed model. Sensitivity analyses are further conducted to investigate the impact of model parameters on optimal solutions.     

基于长短期记忆网络的轨道交通短期OD客流量预测

为了更准确地掌握轨道交通客流在线网中的时空分布,更高效地匹配客流需求与运输能力,实现提高轨道交通运输效率、改善运营服务质量的目的,提出了一种基于长短期记忆网络的短期OD(交通起止点)客流量预测方法。以历史客流数据为基础,定性分析车站间OD客流量的时空相关性,利用回归分析法定量分析客流影响因素,筛选出运营时刻、运营日特征、最低气温3个时间特征。为提高预测精度,以长短期记忆网络为基础,结合时间特征,为每对起讫点单独构建预测模型,形成了基于长短期记忆网络的轨道交通短期OD客流量预测模型。以苏州市为例进行验证,结果表明,加入了时间特征的短期OD客流量预测模型较移动平均模型、仅利用历史客流数据训练的基于LSTM网络的短期OD客流量预测模型,预测结果与真实值之间的误差降低了6.27%～8.58%,所提出的方法和模型可为轨道交通运营部门制定列车运行计划、组织客运工作提供更准确的数据资料。     

New Research Directions in Engineering Economics—Modeling Dependencies with Copulas

Understanding and quantifying dependencies among variables often arises in stochastic capital investment and real option analysis. In such modeling situations, Pearson product moment linear correlation is widely used as a dependence measure. Linear correlation has several limitations. More recently, copulas have been used in financial economics and insurance to model dependencies. We contribute to the engineering economy literature by introducing copulas to model dependent risks that will enhance research and practice. We demonstrate the usefulness of copula-based sampling in simulation of project risk and regression analysis for forecasting. We also discuss potential copula research in engineering economic analysis.     

基于数据挖掘算法的变压器热点温度时序预测方法

为了解决油浸式电力变压器热点温度预测方法缺乏对短期热点温度走势的预测,无法满足动态增容决策要求的问题,以SFPSZ-180000/220型变压器为研究对象,首先,研究对比发现变压器的热点温度与负载率相关性最大,在此基础上,建立了基于支持向量回归的局部地区负荷预测模型,为变压器热点温度预测提供数据;其次,提出了基于数据挖掘算法的变压器热点温度时序预测方法,并在此基础上分别建立了支持向量回归、BP神经网络、决策树3种数据挖掘预测模型;最后,对一般输入-输出的建模方法的预测结果与基于时间延迟方法的预测结果,以及不同时间延迟下3种数据挖掘模型的预测结果进行了对比分析。结果表明,有外在输入的支持向量回归预测模型结果比BP神经网络和决策树吻合度更高,并且时间延时更小,预测结果精确度更高。有外在输入的支持向量回归预测模型在很大程度上提高了变压器热点温度预测精度,其预测结果可为变压器的动态增容决策提供有效参考。     

“3·11”日本大地震对能源市场的影响

3月11日以来,日本地震、海啸、核泄漏三重灾害,造成社会经济重大损失。日本经济短期受重创,中期将提振,但长期低迷的局面不会改变;日本地震不会改变全球经济复苏大势;对中国经济的影响利弊共存,但影响有限。地震重创了日本能源体系,将引发全球油气市场供需出现一些新变化：日本部分炼厂关闭致使亚太地区石油供需结构发生变化,成品油价格可能上涨,轻重原油价差可能扩大;核电危机将促使日本大量增加LNG进口,并将影响全球能源结构;日本化工产品生产受到冲击,带动全球部分化工品价格升高。日本核电危机造成各国对核电安全的担忧,可能影响世界各国核电发展,导致油气需求增加、中长期油价走高。日本大地震启示中国：应完善对突发事件的应急响应机制;加快推进天然气价格机制改革,加快发展天然气;适当调整原油和成品油进出口结构,统筹运作;推进与资源国的能源合作,确保能源的长期稳定供应。     

Strategic safety stock placement in supply chain design with due-date based demand

We present a strategic safety stock placement model in supply chain design for assembly-type product with due-date based demand, where demand data are based on dates when company has to ship to customers rather than order receiving dates. We formulate multi-echelon stock placement by guaranteed-service model with demand propagation equations through backward explosion, where demand can be either stationary or nonstationary. The stock placement model is incorporated into network design problem and its optimization procedure is provided. We show effectiveness of the optimization procedure and other significant features of the model through numerical examples of a machinery product supply chain.     

Evaluating the robustness of lead time demand models

This paper examines the robustness of lead time demand models for the continuous review (r, Q) inventory policy. A number of classic distributions, (e.g. normal, lognormal, gamma, Poisson and negative binomial) as well as distribution selection rules are examined under a wide variety of demand conditions. First, the models are compared to each other by assuming a known demand process and evaluating the errors associated with using a different model. Then, the models are examined using a large sample of simulated demand conditions. Approximation results of inventory performance measures—ready rate, expected number of backorders and on-hand inventory levels are reported. Results indicate that distribution selection rules have great potential for modeling the lead time demand.     

Impact of demand uncertainty on supply chain cooperation of single-period products

Cooperation is an approach of improving competitive advantages of a supply chain. A two-echelon supply chain consisting of a manufacturer and a retailer for a single-period product is studied, and retail-market demand uncertainty is described by coefficient of variation. We develop a cooperation mechanism to address the cooperation and its implementation between the manufacturer and the retailer, two market situations are considered: (i) the wholesale price and the order quantity are decision variables, (ii) the wholesale and the retail prices as well as the order quantity are decision variables. In both market situations, our research shows that: (1) the cooperation mechanism can improve the overall channel profits and the supply chain members’ allocated profits, (2) the described cooperation is conditional on retail-market demand uncertainty: it can be implemented if, and only if, the fluctuation of retail-market demand is relatively small and coefficient of variation of retail-market demand does not exceed an upper bound. Impacts of retail-market demand uncertainty on wholesale price, order quantity and/or retail price have also been investigated through analytical and numerical analyses. Although our research is based on the assumption that the manufacturer dominates the supply chain in the non-cooperative situation, which is not the case for most retailer-driven supply chains, this research is still significant on providing guidelines for practitioners in current China mid-level car market that is similar to situations described in the paper.     

Proliferation of Brewers’ Brands and Price Uniformity in Canadian Beer Markets

In this paper, we study retail pricing in Canadian beer markets, where access to the liquor distribution system and the retail price list is restricted by government ownership and control of the system. We consider alternative explanations for price uniformity in the differentiated beer products market. While an analysis of retail beer price data from six Canadian provinces for a 10-year period shows that no single explanation of price uniformity strongly dominates the others, some of the results are consistent with menu cost and demand uncertainty theories of price uniformity.     

Optimal Capacity,Product Substitution,Linear Demand Models,and Uncertainty

We study the capacity, pricing, and production decisions of a monopolist producing two substitutable products with flexible capacity. Although the capacity decision needs to be made ex ante, under demand uncertainty, pricing and production decisions can be postponed until after uncertainty is resolved. We show how key demand parameters (the nature of uncertainty, market size, and market risk) impact the optimal capacity decision under the linear demand function. In particular, we show that if the demand shock is multiplicative, then in terms of the “invest or not” decision, the firm will be immune to forecast errors in parameters of the underlying demand distribution. Furthermore, incorrectly modeling the demand shock as additive, when, in fact, it is multiplicative, may lead to overinvestment. On the other hand, although the concept of a growth in market size leads to similar conclusions under both additive and multiplicative demand shocks, how market risk affects the optimal capacity decision depends critically on the form of the demand shock as well as its correlation structure. Our analysis provides insights and principles on the optimal capacity investment decision under various demand settings.     

Distributional Consequences of Alternative Mortgage Instruments

One of the major factors hindering the introduction of alternative mortgage instruments is the possibility of adverse consequences to certain groups of households seeking to obtain credit for homeownership. This study examines this issue through an analysis of cross-sectional household data obtained from the 1970 Survey of Consumer Finances. Using multiple regression analysis, a series of structural demand models are derived and estimated. These models relate the probability of homeownership, levels of housing consumption, mortgage credit usage, and downpayment to income, assets, and other socioeconomic variables, to variables representing the relative price of housing and homeownership, and to certain variables representing the present value and cash flow costs of mortgage credit. Several mortgage-related variables are found to be influential in housing demand decisions. These models are then used to simulate alternative instrument introduction. The graduated-payment and price-level adjusted mortgages are predicted to be superior to the current instrument of mortgage finance in encouraging homeownership, housing consumption, and the use of mortgage credit among all household classes. The standard variable-rate mortgage, especially one tied to a short-term interest rate, is predicted to be inferior to the standard instrument, with the most adverse impacts upon lower-income, young, elderly, and black households.     

Optimal production–inventory strategies for a HMMS-type reverse logistics system

The aim of the paper is to find optimal inventory policies in a reverse logistics system with special structure. It is assumed that demand is a known continuous function in a given planning horizon and return rate of used items is a given function. There is a constant delay between the using and return process. We investigate two stores. The demand is satisfied from the first store, where the manufactured and remanufactured items are stored. The returned products are collected in the second store and then remanufactured or disposed. The costs of this system consist of the quadratic holding costs for these two stores and the quadratic manufacturing, remanufacturing and disposal costs.The model is represented as an optimal control problem with two state variables (inventory status in the first and second store) and with three control variables (rate of manufacturing, remanufacturing and disposal). The objective is to minimize the sum of the quadratic deviation from described inventory levels in stores and from described manufacturing, remanufacturing and disposal rates. In this form, the model can be considered as a generalization of the well-known Holt et al. (Planning Production, Inventories, and Work Forces, Prentice-Hall, Englewood Cliffs, NJ, 1960) model with two warehouses. After solving the problem, we give some numerical examples to represent the optimal path in dependence of the demand rates.     

Office Rent in the Chicago CBD

This study focuses on the Chicago CBD office market, an important market at the local, regional, national and international levels. The purpose of this study is to develop a hedonic regression model that explains the variation in office rent per square foot. Five functional forms (linear, reciprocal, logarithmic, semi-log and log-linear) of the model are considered. A generally log-linear model is determined to be the best model based on a series of Box-Cox/Box-Tidwell type transformations and likelihood ratio tests. The regression results reveal that the model has very high explanatory power. The methodology of this study differs substantially from that of previous studies on this topic. Perhaps most importantly, the unit of analysis is the office unit rather than the building. This choice suggested the use of specific lease terms for actual transactions and location of the unit within the building as new variables. Finally, the modeling of location of the building within the CBD was found to be a critical step.     

运输费用、需求分布与产业转移——基于区位论的模型分析

产业转移的理论基础是注重生产成本分析的雁阵模型和产品生命周期理论,但这两类理论并没有考虑空间因素的影响。本文在现有产业转移理论的基础上,使用"分散式转移"和"集中式转移"的阶段划分来描述产业转移的一般过程,并引入运输费用、需求分布等空间变量,构建了基于区位论思想的两地区模型;在规模报酬不变和规模报酬递增的假定下,分别讨论了产业转移的实现条件和形式,发现地区生产成本的相对变化并不必然导致产业转移的发生。使用该模型分析中国现实,发现集中式转移对于促进区域协调发展的作用要大于分散式转移;而运输费用的下降和内需的扩大将提高集中式转移的动力,地方保护主义阻碍了集中式转移但助推了分散式转移。     

Closed-Form Mortgage Valuation Using Reduced-Form Model

Valuing mortgage-related securities is more complicated than valuing regular defaultable claims due to the borrower's prepayment behavior as well as the possibility of default. Some researchers use a structural-form model to obtain the closed-form formulas for the mortgage value. With this method, however, it is difficult to identify the critical region of early exercise. As an alternative, the reduced-form model developed in this article is able to value the mortgage without setting boundary conditions, and it can thereby accurately handle the multidimensional space of correlated state variables. The purpose of this article is to derive a closed-form solution of the mortgage valuation equation under a general reduced-form model that embeds relevant economic variables. This new approach enables portfolio managers to undertake sophisticated portfolio optimization and hedging analyses. An implementation procedure for the model is also provided to demonstrate how the valuation framework can be utilized in practical applications.     

An integrated multi-depot hub-location vehicle routing model for network planning of parcel service

The paper describes why optimal design of depot and hub transportation networks for parcel service providers makes it necessary to develop a generalized hub location and vehicle routing model (VRM). Analogous problems occur for postal, parcel and piece goods service providers. A generalized hub location and VRM is developed which encompasses the determination of the number, locations of hubs and depots and their assigned service areas as well as the routes between the demand points and consolidation points (depots, hubs). Because this task leads to a very complex transport design problem, a heuristic solution concept has to be developed. The applicability to a case study is demonstrated; the case of completely new system configuration for Austria is considered. Management must simultaneously decide the number, location, service areas and routes from demand points to depots and vice versa (the pickup and delivery structure) as well as the number and locations of hubs and the routes of depot–hub and hub–hub transports (the hub location or line haul structure), The developed management support decision model leads for real cases to a tremendous number of some million binary variables as well as continuous variables and million of constraints.