A Stochastic Inventory Model With Fast‐Ship Commitments

We present a multiperiod model of a retail supply chain, consisting of a single supplier and a single retailer, in which regular replenishment occurs periodically but players have the option to support fast delivery when customers experience a stockout during a replenishment period. Because expedited shipments increase the supplier's transportation cost, and possibly production/inventory costs, the supplier typically charges a markup over and above the prevailing wholesale price for fast‐shipped items. When fast shipping is not supported, items are backordered if customers are willing to wait until the start of the next replenishment period. We characterize the retailers and the supplier's optimal stocking and production policies and then utilize our analytical framework to study how the two players respond to changes in supply chain parameters. We identify a sufficient condition such that the centralized supply chain is better off with the fast‐ship option. We find a range of markups for fast‐ship orders such that the fast‐ship option is preferred by both the supplier and the retailer in a decentralized chain. However, a markup that is a win–win for both players may not exist even when offering fast‐ship option is better for the centralized chain. Our analysis also shows that depending on how the markup is determined, greater customer participation in fast‐ship orders does not necessarily imply more profits for the two players. For some predetermined markups, the retailer's profit with the fast‐ship option is higher when more customers are willing to wait. However, the retailer may not be able to benefit from the fast‐ship option because the supplier may choose not to support the fast‐ship option when fast‐ship participation increases due to the fact that the fast‐ship participation rate adversely affects the initial order size.     

Exploring the Equivalence of Two Common Mixture Models for Duration Data

The beta-geometric (BG) distribution and the Pareto distribution of the second kind (P(II)) are two basic models for duration-time data that share some underlying characteristics (i.e., continuous mixtures of memoryless distributions), but differ in two important respects: first, the BG is the natural model to use when the event of interest occurs in discrete time, while the P(II) is the right choice for a continuous-time setting. Second, the underlying mixing distributions (the beta and gamma for the BG and P(II), respectively), are very different—and often believed to be noncomparable with each other. Despite these and other key differences, the two models are strikingly similar in terms of their fit and predictive performance as well as their parameter estimates. We explore this equivalence, both empirically and analytically, and discuss the implications from both a substantive and methodological standpoint.     

Provision of basic services in slums: A review of the evidence on top‐down and bottom‐up approaches

This article synthesizes the evidence on the effectiveness of top‐down and bottom‐up approaches in providing basic services in slums in developing countries. The findings indicate that: (1) government‐led top‐down approaches focus predominantly on connectivity, but approaches led by community‐based organizations (CBOs) and non‐government organizations (NGOs) improve many additional dimensions of access; (2) legal recognition of slums improves access to services in both approaches; and (3) NGO and CBO involvement results in the right balance between the technical, social and financial resources required for effective service delivery.     

印度汽车市场崛起

尽管大多数印度人依然在用两轮交通工具，但新兴的印度中产阶级却给汽车销售业带来了有力的推动——至少当下如此。     

Nearly optimal covariate designs—Part II

This is a continuation to Part I toward our efforts for providing illustrative examples in the context of analysis of covariance (ANCOVA) models and related analyses of data. We discuss four more examples here, and these are derived from standard textbooks. We re-visit these examples with a view to suggest optimal/nearly optimal designs for estimation of the covariate parameter(s).     

Optimum covariate designs in split-plot and strip-plot design set-ups

The problem considered is that of finding optimum covariate designs for estimation of covariate parameters in standard split-plot and strip-plot design set-ups with the levels of the whole-plot factor in r randomised blocks. Also an extended version of a mixed orthogonal array has been introduced, which is used to construct such optimum covariate designs. Hadamard matrices, as usual, play the key role for such construction.     

Optimal and efficient treatment control design in the heteroscedastic one-way layout with covariates

In this article, we take up the experimental situation of a heteroscedastic one-way layout model in the presence of a set of controllable covariates. For the joint estimation of the elementary contrasts of a set of test treatments with a control and the effects of covariates, sufficient conditions for the existence of an A-optimal design are identified. When these sufficient conditions are not met, we propose highly A-efficient designs. The methods of construction of A-optimal and highly A-efficient designs are discussed. For different values of the parameters of the design, A-efficiency of the proposed designs are tabulated for a comparative study.     

Distressed Selling by Farmers: Model,Analysis, and Use in Policy‐Making

Among the various governmental schemes that support agriculture, support prices have been adopted by many developing countries. A support price for an agricultural crop is a guaranteed price at which a governmental entity agrees to purchase that crop from farmers. Despite this surety, a surprising practice of “distressed” selling 1 1 A 1‐minute news clip on distressed selling is available at: https://www.youtube.com/watch?v=U2lr5rBTpaU
has been widely observed in practice: Farmers sell a significant portion of their crops to outside agents at prices much lower than the support price. We build a tractable stochastic dynamic programming model that captures the salient features of the ground realities—limited as well as uncertain procurement capacity, high holding costs for the farmers, and lack of affordable credit—that conspire to induce distressed selling and, consequently, a significant loss of welfare of the farmers. Using real data on procurement under a support‐price program, we establish the accuracy of our model's prediction on the volume of distressed sales. Finally, we show how our model and its solution can serve as a simple and useful tool for policy‐makers to assess the relative impact of the improvements in the main determinants of distressed sales.     

Dual Sourcing Inventory Systems: On Optimal Policies and the Value of Costless Returns

We study dual sourcing inventory systems with backordering and with stationary, stochastic demands. The two supply sources differ in their unit prices and lead times. We focus on the option of making costless returns to the cheaper, longer leadtime supplier. We show that the value of this option is zero. Our analysis leading to this result includes the derivation of several structural properties of the optimal policies for dual sourcing systems with and without the return option.     

Optimal Policy for a Stochastic Scheduling Problem with Applications to Surgical Scheduling

We consider the stochastic, single‐machine earliness/tardiness problem (SET), with the sequence of processing of the jobs and their due‐dates as decisions and the objective of minimizing the sum of the expected earliness and tardiness costs over all the jobs. In a recent paper, Baker ( 2014 ) shows the optimality of the Shortest‐Variance‐First (SVF) rule under the following two assumptions: (a) The processing duration of each job follows a normal distribution. (b) The earliness and tardiness cost parameters are the same for all the jobs. In this study, we consider problem SET under assumption (b). We generalize Baker's result by establishing the optimality of the SVF rule for more general distributions of the processing durations and a more general objective function. Specifically, we show that the SVF rule is optimal under the assumption of dilation ordering of the processing durations. Since convex ordering implies dilation ordering (under finite means), the SVF sequence is also optimal under convex ordering of the processing durations. We also study the effect of variability of the processing durations of the jobs on the optimal cost. An application of problem SET in surgical scheduling is discussed.