Market Orientation,Ownership Type,and E‐Business Assimilation: Evidence from Chinese Firms

While more and more firms have implemented e‐business in business operations, a better understanding of the factors that successfully drive the assimilation of e‐business will provide insights for firm executives and practitioners to develop effective strategies for e‐business. Different from previous studies that focus on individual‐level factors related to business executives and top management teams, this study examines how firm‐level strategic and cultural factors shape e‐business assimilation. Based on the strategy and marketing literature on market orientation and firm ownership, we developed a research model to describe how a firm's market orientation impacts e‐business assimilation. The model also describes the moderating effect of firm ownership type on the relationship between market orientation and e‐business assimilation. Based on data from 301 Chinese international trade firms, we found that two dimensions of market orientation (i.e., customer orientation, competitor orientation) had significant effects on e‐business assimilation. However, the third dimension, interfunctional coordination, was only partially significant. In addition, ownership type was a significant moderator of the effects of customer orientation and competitor orientation on e‐business assimilation, although ownership type was not a moderator of interfunctional coordination. Being one of the first studies of the impact of market orientation and firm ownership type on e‐business assimilation, we conclude with a discussion of the implications for future research and practice.     

基于高效边缘检测的彩色图像灰度化算法

为了使彩色图像灰度化后能更好地保留原始对比度和细节特征，课题组提出一种基于高效边缘检测的彩色图像灰度化算法。课题组通过对线性参数模型产生的一系列备选图像采用像素差值网络（pixel difference networks, PiDiNet）实现鲁棒性、准确性的边缘检测，边界点数最多的备选图像所对应的权重则被选为映射函数的最优解，由于引用了像素差值卷积PDC，对边缘信息敏感度增强。实验结果表明：此算法相比于其他算法能较好地保留原彩色图像的细节特征，使得输出图像轮廓清晰且自然，主客观评价均较优。     

Social Isolation and Spousal Violence: Comparing Female Marriage Migrants With Local Women

This research examined the impact of network participation, social support, and social control on the violence victimization of female marriage migrants by a spouse. Data were from a household survey of 492 cross‐border and 379 local married couples in Hong Kong in 2007. The findings indicated that female marriage migrants were more vulnerable to spousal violence and more socially isolated, compared with local women. Husbands of marriage migrants were also more socially isolated compared with men who married locally. The network participation of both husband and wife was associated positively with spousal violence against women, whereas their perceived social control was associated negatively with violence. Female marriage migrants' greater vulnerability to spousal physical assault was a result of their younger age compared with local women, but their greater vulnerability to spousal psychological aggression and sexual coercion was related, in part, to their own and their husbands' network participation as well as their level of social control.     

In vino veritas

Wine consumption,once predominantly in Europe and the USA, is rapidly evolving into a global trend, with lucrative markets opening up in the Far East, notably Japan, Taiwan, Hong Kong and mainland China.The demand for fine wines, in these regions in particular, sends prices rising through the stratosphere. Lin Y.Hin looks at the professional tasters' ratings and considers issues of score consignment and lifetime estimation.     

Models for surveillance data under reporting delay: applications to US veteran first-time suicide attempters

Surveillance data provide a vital source of information for assessing the spread of a health problem or disease of interest and for planning for future health-care needs. However, the use of surveillance data requires proper adjustments of the reported caseload due to underreporting caused by reporting delays within a limited observation period. Although methods are available to address this classic statistical problem, they are largely focused on inference for the reporting delay distribution, with inference about caseload of disease incidence based on estimates for the delay distribution. This approach limits the complexity of models for disease incidence to provide reliable estimates and projections of incidence. Also, many of the available methods lack robustness since they require parametric distribution assumptions. We propose a new approach to overcome such limitations by allowing for separate models for the incidence and the reporting delay in a distribution-free fashion, but with joint inference for both modeling components, based on functional response models. In addition, we discuss inference about projections of future disease incidence to help identify significant shifts in temporal trends modeled based on the observed data. This latter issue on detecting ‘change points’ is not sufficiently addressed in the literature, despite the fact that such warning signs of potential outbreak are critically important for prevention purposes. We illustrate the approach with both simulated and real data, with the latter involving data for suicide attempts from the Veteran Healthcare Administration.     

Delay Estimation for Some Stationary Diffusion-type Processes

In this paper the asymptotic behaviour of the maximum likelihood and Bayesian estimators of a delay parameter is studied. The observed process is supposed to be the solution of a linear stochastic differential equation with one time delay term. It is shown that these estimators are consistent and their limit distributions are described. The behaviour of the estimators is similar to the behaviour of corresponding estimators in change-point problems. The question of asymptotical efficiency is also discussed.     

Interval Estimations for the Mean of the Generalized Poisson and Generalized Negative Binomial Distributions

In this article, we extend the Wald, score, skewness-corrected score, likelihood ratio, and mid-P intervals for the means of the generalized Poisson and generalized negative binomial distributions. These distributions are the members of the discrete version of the natural exponential family (NEF) with cubic variance function (CVF). Also, the coverage probabilities, the distal and mesial noncoverage probabilities, and the lengths of the proposed confidence intervals are estimated by means of a Monte Carlo simulation study. Finally, some practical examples are provided to show the applicability of the proposed intervals in applied studies.     

Male-to-Female Transgender Individuals Building Social Support and Capital From Within a Gender-Focused Network

ABSTRACT

The literature on male-to-female transgender myriad problems such individuals face in their day-to-day lives, including high rates of HIV/AIDS, addiction to drugs, violence, and lack of health care. These problems are exacerbated for ethnic and racial minority MTFs. Support available from their social networks can help MTFs alleviate these problems. This article explores how minority MTFs, specifically in an urban environment, develop supportive social networks defined by their gender and sexual identities. Using principles of community-based participatory research (CBPR), 20 African American and Latina MTFs were recruited at a community-based health care clinic. Their ages ranged from 18 to 53. Data were coded and analyzed following standard procedure for content analysis. The qualitative interviews revealed that participants formed their gender and sexual identities over time, developed gender-focused social networks based in the clinic from which they receive services, and engaged in social capital building and political action. Implications for using CBPR in research with MTFs are discussed.     

Robust estimation for finite populations based on a working model

A common scenario in finite population inference is that it is possible to find a working superpopulation model which explains the main features of the population but which may not capture all the fine details. In addition, there are often outliers in the population which do not follow the assumed superpopulation model. In situations like these, it is still advantageous to make use of the working model to estimate finite population quantities, provided that we do it in a robust manner. The approach that we suggest is first to fit the working model to the sample and then to fine-tune for departures from the model assumed by estimating the conditional distribution of the residuals as a function of the auxiliary variable. This is a more direct approach to handling outliers and model misspecification than the Huber approach that is currently being used. Two simple methods, stratification and nearest neighbour smoothing, are used to estimate the conditional distributions of the residuals, which result in two modifications to the standard model-based estimator of the population distribution function. The estimators suggested perform very well in simulation studies involving two types of model departure and have small variances due to their model-based construction as well as acceptable bias. The potential advantage of the proposed robustified model-based approach over direct nonparametric regression is also demonstrated.