Optimum designs for parameter estimation in a mixture experiment with two correlated responses

In this paper, we investigate a mixture problem with two responses, which are functions of the mixing proportions, and are correlated with known dispersion matrix. We obtain D- and A-optimal designs for estimating the parameters of the response functions, when none or some of the regression coefficients of the two functions are the same. It is shown that when no prior knowledge about the regression coefficients is available, the D-optimal design is independent of the dispersion matrix, while the A-optimal design depends on it, provided the response functions are of different degree. On the other hand, when some of the regression coefficients are known to be the same for both the functions, the D-optimal design depends on the dispersion matrix when the two response functions are not of the same degree.     

The immigration issue in Assam and conflicts around it

Assam, the northeastern state of India, has experienced strong anti-outsider sentiment for more than half a century now. What makes the Assam case unique is that it has faced both internal as well as illegal international migration in massive scales giving rise to intense existential fear and apprehension among its smaller indigenous communities. Their lack of the required political authority and the indifferent attitude of the Indian Union government in addressing the issue have only multiplied its magnitude. The article explicates the politico-economic dynamics of the immigration issue in Assam and the social tension and conflicts around it in a historical perspective and suggests that a multi-pronged approach backed by strong political will is imperative to negotiate the challenges of immigration in the state in an effective manner.     

How do changes in income,employment and health insurance affect family mental health spending?

Using eight two-year panels from the Medical Expenditure Panel Survey data for the period 2004 to 2012, we examine the effect of economic shocks on mental health spending by families with children. Estimating two-part expenditure models within the correlated random effects framework, we find that employment shocks have a greater impact on mental health spending than do income or health insurance shocks. Our estimates reveal that employment gains are associated with a lower likelihood of family mental health services utilization. By contrast employment losses are positively related to an increase in total family mental health. We do not detect a link between economic shocks and mental health spending on behalf of fathers.

     

Uncertainty Analysis Based on Probability Bounds (P-Box) Approach in Probabilistic Safety Assessment

A wide range of uncertainties will be introduced inevitably during the process of performing a safety assessment of engineering systems. The impact of all these uncertainties must be addressed if the analysis is to serve as a tool in the decision-making process. Uncertainties present in the components (input parameters of model or basic events) of model output are propagated to quantify its impact in the final results. There are several methods available in the literature, namely, method of moments, discrete probability analysis, Monte Carlo simulation, fuzzy arithmetic, and Dempster-Shafer theory. All the methods are different in terms of characterizing at the component level and also in propagating to the system level. All these methods have different desirable and undesirable features, making them more or less useful in different situations. In the probabilistic framework, which is most widely used, probability distribution is used to characterize uncertainty. However, in situations in which one cannot specify (1) parameter values for input distributions, (2) precise probability distributions (shape), and (3) dependencies between input parameters, these methods have limitations and are found to be not effective. In order to address some of these limitations, the article presents uncertainty analysis in the context of level-1 probabilistic safety assessment (PSA) based on a probability bounds (PB) approach. PB analysis combines probability theory and interval arithmetic to produce probability boxes (p-boxes), structures that allow the comprehensive propagation through calculation in a rigorous way. A practical case study is also carried out with the developed code based on the PB approach and compared with the two-phase Monte Carlo simulation results.     

Acquisition of Telecommunications Bandwidth Under Economies of Scale in Size and Duration of Contracts*

Significant advances in information technology have brought about increased demand for bandwidth. Buyers of bandwidth often encounter bandwidth prices that are decreasing over time. Additionally, bandwidth prices at any point in time are decreasing in total bandwidth purchased and length of contracts. Therefore, buyers face complex decisions in terms of the number of contracts to buy, their bandwidth, and their lengths. In this article, we formulate models for the acquisition of bandwidth from a buyer's perspective. We begin with a model that allows varying contract durations under deterministic demand and without allowing shortages or overlapping contracts. We then formulate a simpler model, which restricts contract lengths over the planning horizon to be equal. We also solve the problem under probabilistic demand and allowing for shortages, which are satisfied by buying additional bandwidth at a premium. We perform numerical sensitivity analysis to compare the results of the models and illustrate the results with numerical examples. The numerical analyses illustrate that using relatively simple equal‐length contracts produces approximately the same results as the more complicated unequal‐length contract strategy.     

Like Mother(-in-Law) Like Daughter? Influence of the Older Generation’s Fertility Behaviours on Women’s Desired Family Size in Bihar,India

This paper investigates the associations between preferred family size of women in rural Bihar, India and the fertility behaviours of their mother and mother-in-law. Scheduled interviews of 440 pairs of married women aged 16–34 years and their mothers-in-law were conducted in 2011. Preferred family size is first measured by Coombs scale, allowing us to capture latent desired number of children and then categorized into three categories (low, medium and high). Women’s preferred family size is estimated using ordered logistic regression. We find that the family size preferences are not associated with mother’s fertility but with mother’s education. Mother-in-law’s desired number of grandchildren is positively associated with women’s preferred family size. However, when the woman has higher education than her mother-in-law, her preferred family size gets smaller, suggesting that education provides women with greater autonomy in their decision-making on childbearing.     

Efficient formation of storage classes for warehouse storage location assignment: A simulated annealing approach

Class-based storage policy distributes products among a number of classes and for each class it reserves a region within the storage area. The procedures reported in the literature for formation of storage classes primarily consider order-picking cost ignoring storage-space cost. Moreover, in these procedures items are ordered on the basis of their cube per order index (COI), and items are then partitioned into classes maintaining this ordering. This excludes many possible product combinations in forming classes which may result in inferior solutions. In this paper, a simulated annealing algorithm (SAA) is developed to solve an integer programming model for class formation and storage assignment that considers all possible product combinations, storage-space cost and order-picking cost. Computational experience on randomly generated data sets and an industrial case shows that SAA gives superior results than the benchmark dynamic programming algorithm for class formation with COI ordering restriction.     

Managing Logistics in Regional Banknote Supply Chain Under Security Concerns

We study the logistics problem faced by Regional Branches (RBs) of a central bank in managing the currency supply under security concerns. While making banknote supply decisions to Sub‐Branches (SBs), the management of RB must achieve two goals simultaneously: (i) guarantee that each SB has sufficient inventories of all denominations of banknotes to satisfy the demands from all commercial banks within its service area, and (ii) control the annual spending on this banknote supply operation. Due to security concerns, the following methods are implemented in the process of transporting banknotes: (i) the capacity of a cash truck is limited by the total face value (instead of the physical space) of banknotes, and (ii) empty decoy trucks are deployed along with the trucks filled with banknotes. After deriving a polynomial‐time strategy to guarantee an optimal solution for the special Bin‐Packing Problem faced in this study, we provide an exact formulation for the RB's supply planning problem. We also propose several polynomial‐time algorithms for deriving either optimal or near‐optimal solutions for the problem under different settings. Using the weekly demand data obtained from the central bank, we verify the performance of our algorithms, and analyze the impacts of changes in these features and in the fleet capacity on the total cost incurred by an RB under various scenarios.     

Production knowledge and its impact on the mechanisms of governance

A framework is developed outlining how production knowledge and capabilities influence firm boundaries by impacting the transaction costs of markets and hierarchies. A central implication of the framework is that at lower levels of these capabilities the transaction costs of markets decline at a faster rate than the costs of hierarchy, while at higher levels of these capabilities the transaction costs of hierarchy decline at a faster rate than the costs of markets. The discriminating role of production capabilities arises because markets and hierarchies utilize different types of control (prices and output control versus authority and behavior control), and hence require different levels of knowledge to be efficient. The analysis suggests firms often maintain some production knowledge when contracting for various inputs since it not only reduces transactional hazards in markets, but also because in comparative institutional terms, initial gains in knowledge make markets more efficient than internal organization. In addition, the analysis suggests that there would be a U shaped relationship between the propensity to integrate vertically and the extent of production capabilities as opposed to a monotonically increasing relationship. I find support for the U shaped relationship in a cross sectional sample of 1553 manufacturing firms.