Gender‐Sensitive Research in a Chinese Community

The aim of this article is to foster an awareness of the need for gender‐sensitive research in the context of the methodological and ethical challenges posed by such research. We trace the development of gender sensitivity and masculinity in social work practice and research and connect this to an overview of the issues posed by research on sensitive topics. Reflecting on a research project involving Chinese male sexual abuse survivors, we draw conclusions illustrating and proposing a range of methodological practices and ethical safeguards. We underscore the importance of gender‐sensitivity in performing research on sensitive topics with men in a Chinese community.     

A new stratified three-stage unrelated randomized response model for estimating a rare sensitive attribute based on the Poisson distribution

This article suggests an efficient method of estimating a rare sensitive attribute which is assumed following Poisson distribution by using three-stage unrelated randomized response model instead of the Land et al. model (2011 Land, M., S. Singh, and S. A. Sedory. 2011. Estimation of a rare sensitive attribute using poisson distribution. Statistics 46 (3):351–60. doi:10.1080/02331888.2010.524300.[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]) when the population consists of some different sized clusters and clusters selected by probability proportional to size(:pps) sampling. A rare sensitive parameter is estimated by using pps sampling and equal probability two-stage sampling when the parameter of a rare unrelated attribute is assumed to be known and unknown.

We extend this method to the case of stratified population by applying stratified pps sampling and stratified equal probability two-stage sampling. An empirical study is carried out to show the efficiency of the two proposed methods when the parameter of a rare unrelated attribute is assumed to be known and unknown.     

Bayesian estimation of rare sensitive attribute

Randomized response models have been used to estimate a population proportion of a sensitive attribute. A randomized device is typically employed to protect respondent's privacy in a survey. In addition, an unrelated question is asked to improve the statistical efficiency. In this article, we propose Bayesian estimation of rare sensitive attribute using randomized response technique, which includes a rare unrelated attribute. Two cases are considered, the proportion of a rare unrelated attribute is known and unknown. A simulation study is conducted to assess the performance of the models using mean absolute error and coverage probability. The results show that the performance depends on the parameters and is robust to priors.     

数据驱动下收货方质量偏好与电商配送服务质量优化

针对"互联网+大数据"优化电商配送服务质量问题,明确不同收货方的质量需求稳定性,引导电商根据收货方不同质量敏感性提供相对精准服务,提升配送服务质量。模拟投票结果的形成过程聚类得到收货方对服务质量偏好的记忆性特征：（1）"无记忆"型收货方;（2）"记忆"型收货方;（3）"不确定"型收货方;（4）收货方总体。进一步推导不同规划类型求解空间,设计得到"无记忆"型收货方动态规划精确求解方法,及其他三种类型近似求解粒子群算法。研究过程中,配送资源质量感知度被嵌入到模型约束;"无记忆"型收货方的质量需求规划问题转化为零库存策略最优解问题,进而证明存在精确解;"记忆"型收货方呈现出对质量感知的累积;"不确定"型收货方模型通过赋值即可得总体收货方表达式。结果表明：数据驱动研究框架借助大数据资源,使得电商更易通过收货方的质量偏好设计更加匹配的配送方案;不确定服务需求得到有效满足,投入成本的利用率更高;通过特征分类的方式,尽可能地抽取能够精确最优化的部分,缩小NP范围,提高整体求解的精确度。     

平台品牌认知对产品购买行为的影响研究:品牌敏感的调节作用

以往对平台企业的研究大多集中在产业经济和战略管理等领域,文章试图从“认知—情感—行为”层级关系理论的视角构建平台企业品牌认知对产品购买行为影响的作用机制,提出平台品牌对消费者行为的独特影响.研究发现:在传统服装商贸平台领域,消费者对平台的品牌认知并没有对平台产品行为产生积极影响;产品品牌敏感度负向调节平台品牌情感对消费者平台产品行为的影响.这一研究结论可为传统商贸类平台组织创建优质品牌提供思路和借鉴.     

Improved randomized response in additive scrambling models

Randomized response models deal with stigmatizing variables appearing in health surveys. Additive and subtractive scrambling in split sample and double response yield unbiased mean and sensitivity estimators of high precision. The split sample method is protective of privacy. The double response method is as protective only conditionally. To achieve the maximum efficiency, the scrambling variables must be similar to each other and the probability of obtaining a true response must be as large as possible. The randomized response procedures yield more efficient estimates of the average total number of classes missed by university students.     

Poking a sleeping bear: the challenge of organizational recruitment for controversial topics

ABSTRACT

Researchers often approach employers to investigate employees’ work and family experiences. Organizational willingness to grant access to employees can vary, especially when the research topic is seen as controversial or contentious for the employer. This paper explores this methodological challenge using a research example from Manitoba, Canada, which explored the use of parental leave by male employees and the impact of managerial attitudes and corporate culture on usage. Sixty large employers were recruited with only seven of those organizations agreeing to participate. In this paper, the reasons organizations gave for declining to participate and the implications of their decisions for the research are examined. Although the final sample included 905 managers and employees, participating organizations tended to be employee-focused and family-friendly employers. Organizations declined participation for a variety of reasons: avoiding raising the issue with unions, awareness that their policies unfairly benefited female leave takers, and simply not seeing the relevance of a topic relating to men’s work–family experiences. A dialogue often absent from the literature, it is important to understand how employers can limit researchers’ access to employees on controversial topics. The existence of such barriers suggests alternative avenues to recruit participants directly when topics are contentious for employers.     

Evaluation from a Gender+ Perspective as a Key Element for (Re)gendering the Policymaking Process

ABSTRACT

Feminist scholars have challenged the neutrality of policymaking processes and the outputs resulting from these processes. However, some elements of policymaking have not been studied as well as others. In this article I explore the concept of evaluation from a gender+ perspective as an essential step for a complete gender mainstreaming strategy, which can help to identify gender issues that should be integrated into the content of evaluated policies and to ensure gender does not get lost in the policymaking process. This exploration is carried out by relying on feminist policy and evaluation studies.     

An optional randomized response model for estimating a rare sensitive attribute using Poisson distribution

The crux of this article is to estimate the mean of the number of persons possessing a rare sensitive attribute based on the Mangat (1991 Mangat, N.S. (1991). An optional randomized response sampling technique using non–stigmatized attribute. Statistica. 51(4):595–602. [Google Scholar]) randomization device by utilizing the Poisson distribution in simple random sampling and stratified sampling. Properties of the proposed randomized response (RR) model have been studied along with recommendations. It is also shown that the proposed model is more efficient than that of Land et al. (2011 Land, M., Singh, S., Sedory, S.A. (2011). Estimation of a rare attribute using Poisson distribution. Statistics. 46(3):351–360.[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]) in simple random sampling and that of Lee et al. (2013 Lee, G.S., Uhm, D., Kim, J.M. (2013). Estimation of a rare sensitive attribute in stratified sampling using Poisson distribution. Statistics. 47(3):575–589.[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]) in stratified random sampling when the proportion of persons possessing a rare unrelated attribute is known. Numerical illustrations are also given in support of the present study.