What makes motherhood so expensive?: The role of social expectations, interdependence, and coordination failure in explaining lower wages of mothers

This paper utilizes expectations imposed by society to explain lower wages of mothers compared to non-mothers in the labor market. Social expectation, interdependence between mothers’ labor supply and childcare services, and lack of coordination between employers, employees (mothers), and childcare services explain how an economy can be caught in a ‘trap’ exhibiting large wage differences. Higher levels of human capital, increased coordination along with affordable childcare services in a more modern economy allows for specialization, increasing returns, and the possibility for a better outcome due to multiple equilibria.     

基于供应链管理的企业外包策略选择分析

外包是企业从传统纵向一体化管理模式向供应链管理模式转变的重要途径。然而,外包策略的有效选择对企业实际运作来说并非易事。该文从供应链管理的角度出发,通过对核心业务、顾客价值以及产品特性和业务类型的分析,探讨了在不同竞争环境中如何通过外包策略的选择来增强企业的竞争优势。     

Supply Chain Conflict Due to Store Brands: The Value of Wholesale Price Commitment in a Retail Supply Chain*

Store brands are of increasing importance in retail supply chains, often causing channel conflict, as the retailer's product directly competes with the manufacturer's national brand. Extant research on the resulting channel interactions either assumes the national brand manufacturer can credibly commit to maintaining a wholesale price or that he lacks such ability. However, these two scenarios imply very different supply chain interactions, as only a national brand manufacturer with commitment ability can strategically adjust a national brand wholesale price to prevent a store brand introduction by the retailer. We specifically analyze the impact of this assumption on the manufacturer, the retailer, and the customers. We determine when long‐term contracts that provide the manufacturer with such commitment ability can improve supply chain profitability.     

The Potential for Cannibalization of New Products Sales by Remanufactured Products*

The potential for cannibalization of new product sales by remanufactured versions of the same product is a central issue in the continuing development of closed‐loop supply chains. Practitioners have no fact‐based information to guide practice at firms and academics have no studies available to use as the basis for assumptions in models. We address the cannibalization issue by using auctions to determine consumers’ willingness to pay (WTP) for both new and remanufactured products. The auctions also allow us to better understand the potential impact of offering new and remanufactured products at the same time, which provides us insights into the potential for new product cannibalization. Our results indicate that, for the consumer and commercial products auctioned, there is a clear difference in WTP) for new and remanufactured goods. For the consumer product, there is scant overlap in bidders between the new and remanufactured products, leading us to conclude that the risk of cannibalization in this case is minimal. For the commercial product, there is evidence of overlap in bidding behavior, exposing the potential for cannibalization.     

Electronic Data Interchange: Research Review and Future Directions*

For nearly two decades, electronic data interchange (EDI) has been widely viewed as a technology pivotal to supply chain management that has also provided benefits to firms on multiple levels. Despite a substantial body of literature, there are a number of conflicting and inconclusive research results in this field. In this study, we synthesize the diverse body of research in EDI by organizing the literature into an initial theoretical framework. Based on a meta‐analysis of results from the empirical literature, we seek to clarify conflicting results from the literature in order to develop a more unified theoretical framework of contextual variables associated with EDI adoption factors and outcomes. From a managerial standpoint, our literature‐based framework offers a set of guidelines for making successful EDI adoption and implementation decisions.     

Free Knot Splines with RJMCMC in Survival Data Analysis

The B-spline representation is a common tool to improve the fitting of smooth nonlinear functions, it offers a fitting as a piecewise polynomial. The regions that define the pieces are separated by a sequence of knots. The main difficulty in this type of modeling is the choice of the number and the locations of these knots. The Reversible Jump Markov Chain Monte Carlo (RJMCMC) algorithm provides a solution to simultaneously select these two parameters by considering the knots as free parameters. This algorithm belongs to the MCMC techniques that allow simulations from target distributions on spaces of varying dimension. The aim of the present investigation is to use this algorithm in the framework of the analysis of survival time, for the Cox model in particular. In fact, the relation between the hazard ratio function and the covariates being assumed to be log-linear, this assumption is too restrictive. Thus, we propose to use the RJMCMC algorithm to model the log hazard ratio function by a B-spline representation with an unknown number of knots at unknown locations. This method is illustrated with two real data sets: the Stanford heart transplant data and lung cancer survival data. Another application of the RJMCMC is selecting the significant covariates, and a simulation study is performed.     

Modeling bivariate survival data using shared inverse Gaussian frailty model

ABSTRACT

The shared frailty models are often used to model heterogeneity in survival analysis. The most common shared frailty model is a model in which hazard function is a product of a random factor (frailty) and the baseline hazard function which is common to all individuals. There are certain assumptions about the baseline distribution and the distribution of frailty. In this paper, we consider inverse Gaussian distribution as frailty distribution and three different baseline distributions, namely the generalized Rayleigh, the weighted exponential, and the extended Weibull distributions. With these three baseline distributions, we propose three different inverse Gaussian shared frailty models. We also compare these models with the models where the above-mentioned distributions are considered without frailty. We develop the Bayesian estimation procedure using Markov Chain Monte Carlo (MCMC) technique to estimate the parameters involved in these models. We present a simulation study to compare the true values of the parameters with the estimated values. A search of the literature suggests that currently no work has been done for these three baseline distributions with a shared inverse Gaussian frailty so far. We also apply these three models by using a real-life bivariate survival data set of McGilchrist and Aisbett (1991 McGilchrist, C.A., Aisbett, C.W. (1991). Regression with frailty in survival analysis. Biometrics 47:461–466.[Crossref], [PubMed], [Web of Science ®] , [Google Scholar]) related to the kidney infection data and a better model is suggested for the data using the Bayesian model selection criteria.     

EVVMA and cusum control charts in the presence of correlation

The statistical properties of control charts are usually evaluated under the assumption that the observations from the process are independent. For many processes however, observations which are closely spaced in time will be correlated. This paper considers EWMA and CUSUM control charts for the process mean when the observations are from an AR(1) process with additional random error. This simple model may be a reasonable model for many processes encountered in practice. The ARL and steady state ARL of the EWMA and CUSUM charts are evaluated numerically using an integral equation approach and a Markov chain approach. The numerical results show that correlation can have a significant effect on the properties of these charts. Tables are given to aid in the design of these charts when the observations follow the assumed model.     

Developing “A Framework for Planning U.S. Federal Statistics, 1978–1989”

The Statistical Policy Division of the Office of Management and Budget has the overall responsibility for the planning and coordination of U.S. government statistics. The present staff of the Statistical Policy Division is attempting, through an integrated publication entitled “A Framework for Planning U.S. Federal Statistics, 1978–1989,” to state its perspective on necessary developments in the coming years. This article illustrates the character of the Framework materials and outlines the process for public review and comment on this undertaking.     

High-order extensions of the Double Chain Markov Model

The Double Chain Markov Model is a fully Markovian model for the representation of time-series in random environments. In this article, we show that it can handle transitions of high-order between both a set of observations and a set of hidden states. In order to reduce the number of parameters, each transition matrix can be replaced by a Mixture Transition Distribution model. We provide a complete derivation of the algorithms needed to compute the model. Three applications, the analysis of a sequence of DNA, the song of the wood pewee, and the behavior of young monkeys show that this model is of great interest for the representation of data that can be decomposed into a finite set of patterns.