The value of VMI beyond information sharing under time-varying stochastic demand

This study aims to determine the incremental value vendor-managed inventory (VMI) provides beyond that of independent decision-making with full information sharing (IS) under time-varying stochastic demand with service-level constraints. For this purpose, we apply mixed integer linear programming formulations to examine benefits for a supplier, a retailer and the system as a whole. To highlight the benefits of VMI vs. IS, a comprehensive numerical study is carried out considering a large number of business settings under both static and rolling horizons.     

Inventory lot-sizing with supplier selection under non-stationary stochastic demand

Inventory lot-sizing and supplier selection problem has been studied in the literature considering mainly time-varying deterministic demand. However, in real life, most of the products exhibit non-stationary stochastic demand. In this context, we propose an integer linear programming model for inventory lot-sizing and supplier selection problem under non-stationary stochastic demand with all-units quantity discounts and fill rate constraints. Through detailed analysis of experimental results, we show the impacts of fill rate requirements and demand coefficient of variation on costs, inventory levels and order allocations.     

随机需求时上游段VMI模式共赢条件

考虑实施上游段VMI模式后,订货（配送）主动权的转移导致订货（配送）策略的不同,以及制造商对各零部件需求速率的不同导致其对各零部件的订货周期也不一致的情况。假设外界需求随机,通过建立模型,结合模拟仿真,对实施上游段VMI模式前后各企业的经济效益进行比较,探讨实施VMI且制造商销售价格不变时,供应商是否存在合理的销售价格涨幅区间。该区间的价格既能弥补供应商因管理制造商零部件库存多消耗的成本,也能使制造商和供应商的经济效益都有所提高,实现共赢,为上游段VMI模式的推广提供理论依据。     

The bullwhip effect on inventory under different information sharing settings based on price-sensitive demand

Information sharing (IS) is proved to be a valid method to counter demand variability amplification along the supply chain, or bullwhip effect (BWE). Different from the traditional way of measuring the BWE based on order quantity, we measure the BWE on inventory in different IS settings and try to find the best IS approach. In this paper, the retailer will face the market demand which is price-sensitive, and the price follows a first-order autoregressive process. This demand model includes some indexes that can provide more useful managerial insights than previously studied parameters. Our study identifies the best IS setting under any conditions, and clarifies that the benefits of IS will be evident when the overall market product pricing process is highly correlated over time, the demand shocks to the retailer are high, the price sensitivity coefficient is small, the overall market shocks are low, the retailer’s lead-time is long and the manufacturer’s lead-time is short.     

Demand information sharing and channel choice in a dual-channel supply chain with multiple retailers

In this paper, under a dual-channel supply chain consisting of a manufacturer and multiple retailers, we investigate vertical and horizontal information sharing in different channel structures and the manufacturer’s choice on whether or not to keep a direct channel. To this end, we first study the dual-channel structure where uncertain demand is a linear function of price with a generalised-distribution base demand and show that the retailers have incentives to share information horizontally but not vertically, while the manufacturer is better off with vertical information sharing but its expected profit is not affected by horizontal information sharing. We next examine the retail-channel structure and find the basic results remain unchanged. Finally, we provide closed-form internal and external conditions under which the manufacturer can benefit from owning a dual-channel structure. Our study extends the existing literature by combining information sharing and dual-channel choice, introducing channel difference, discussing the impact of channel structure on horizontal and vertical sharing as well as providing interesting managerial insights for channel choice.     

Reliability analysis of multi‐state series systems with performance sharing mechanism under epistemic uncertainty

For real engineering systems, it is sometimes difficult to obtain sufficient data to estimate the precise values of some parameters in reliability analysis. This kind of uncertainty is called epistemic uncertainty. Because of the epistemic uncertainty, traditional universal generating function (UGF) technique is not appropriate to analyze the reliability of systems with performance sharing mechanism under epistemic uncertainty. This paper proposes a belief UGF (BUGF)‐based method to evaluate the reliability of multi‐state series systems with performance sharing mechanism under epistemic uncertainty. The proposed BUGF‐based reliability analysis method is validated by an illustrative example and compared with the interval UGF (IUGF)‐based methods with interval arithmetic or affine arithmetic. The illustrative example shows that the proposed BUGF‐based method is more efficient than the IUGF‐based methods in the reliability analysis of multi‐state systems (MSSs) with performance sharing mechanism under epistemic uncertainty.     

Factors associated with the all-terrain vehicle mortality rate in the United States: an analysis of state-level data

The purpose of this article is to determine and quantify the factors associated with the all-terrain vehicle (ATV) mortality rate in the United States, based on an analysis of state-level data. From 1990 through 1999, there were about 2400 reported deaths in the U.S. involving ATVs. The population-based mortality rate during this time period amounted to about 0.84 deaths per million persons per year, but varied considerably among the 50 states-ranging from a low of 0.09 deaths per million person-years in Rhode Island to a high of 6.33 deaths per million person-years in West Virginia. This variation provides an opportunity for quantifying some of the key factors associated with the ATV mortality risk. The analysis was conducted in a two-stage regression process, with the state mortality rates estimated in the second stage with a negative binomial regression model. The results indicate that the ATV mortality rate was systematically related to ATV usage rates (a measure of risk exposure) and a number of the characteristics of the potential rider pool. These included: the proportion of the state populations that was male, young, lived in rural areas, was college educated, and non-Hispanic white.