Fast and rigorous: Configurational determinants of strategic decision-making balance

A longstanding debate in the strategic decision-making literature has focused on whether top management teams (TMTs) can effectively balance speed and comprehensiveness when making important decisions. In our research, we build on early insights and pivot from considering whether TMTs can engage indecision-making that balances these tensions to focus instead on when certain types of TMTs are able to achieve such balance. We employ a novel configurational analytical approach and a theoretical framework built from role theory to examine the CEO-TMT interface in a new way. In so doing, we are able to identify specific CEO-TMT constellations that support decision-making that is both fast and rigorous. Using a unique primary dataset and an abductive, configurational approach grounded in fuzzy set qualitative comparative analysis (fsQCA), we identify six specific leader-team configurations that each facilitate decision processes characterized by rigorous intra-team debate, meaningful reconciliation of divergent ideas, and fast decision speed (which we describe as strategic decision-making balance). The range of CEO-TMT configurations that emerge from our analyses contribute new theory and findings for the strategic decision-making and interface literatures more broadly, as well as the specific research streams on executive gender, humility, and TMT structure.     

New two-stage sampling designs based on neoteric ranked set sampling

Neoteric ranked set sampling (NRSS) is a recently developed sampling plan, derived from the well-known ranked set sampling (RSS) scheme. It has already been proved that NRSS provides more efficient estimators for population mean and variance compared to RSS and other sampling designs based on ranked sets. In this work, we propose and evaluate the performance of some two-stage sampling designs based on NRSS. Five different sampling schemes are proposed. Through an extensive Monte Carlo simulation study, we verified that all proposed sampling designs outperform RSS, NRSS, and the original double RSS design, producing estimators for the population mean with a lower mean square error. Furthermore, as with NRSS, two-stage NRSS estimators present some bias for asymmetric distributions. We complement the study with a discussion on the relative performance of the proposed estimators. Moreover, an additional simulation based on data of the diameter and height of pine trees is presented.     

社区教育视角下社区共同体意识的生成理路——基于四川省J县的社区教育实践

社区教育与社区治理具有高度耦合性，社区教育的资源性输入会形成社区治理的意识性输出。通过对四川省J县社区教育实践的分析，发现社区共同体意识的具体生成理路是：社区教育以知识生产、价值生产、情感生产、制度生产为依托，以利益生成为动力，以共识生成为旨归，通过社区教育的资源性输入建构了社区共同体的意识性输出链路。针对社区共同体意识生成中动态转化性较弱、横向传导性较差、纵向转化率较低的问题，需要从调适社区教育项目、建构关联点和提升关联密度、强化教育—实践和个体利益—社区利益微链路层面入手，实现输入—输出链路的优化。探究社区教育视角下社区共同体意识的生成理路，对于形塑社区教育与社区治理融合共生机制、促成社区教育与社区治理目标耦合、实现社区治理共建共商共享目标具有重要的理论价值和实践意义。     

Inference and optimal design of multiple constant-stress testing for generalized half-normal distribution under type-II progressive censoring

The generalized half-normal (GHN) distribution and progressive type-II censoring are considered in this article for studying some statistical inferences of constant-stress accelerated life testing. The EM algorithm is considered to calculate the maximum likelihood estimates. Fisher information matrix is formed depending on the missing information law and it is utilized for structuring the asymptomatic confidence intervals. Further, interval estimation is discussed through bootstrap intervals. The Tierney and Kadane method, importance sampling procedure and Metropolis-Hastings algorithm are utilized to compute Bayesian estimates. Furthermore, predictive estimates for censored data and the related prediction intervals are obtained. We consider three optimality criteria to find out the optimal stress level. A real data set is used to illustrate the importance of GHN distribution as an alternative lifetime model for well-known distributions. Finally, a simulation study is provided with discussion.     

半参数空间ZISF的估计、分类与蒙特卡罗模拟

零无效率随机前沿模型（ZISF）包含随机前沿模型和回归模型，两模型各有一定的发生概率，适用于技术无效生产单元和技术有效生产单元同时存在的情形。本文在ZISF的生产函数中引入空间效应和非参函数，并假设回归模型的发生概率为非参函数，构建了半参数空间ZISF。该模型可有效避免忽略空间效应导致的有偏且不一致估计量，也避免了线性模型的拟合不足。本文对非参函数采用B样条逼近，使用极大似然方法和JLMS法分别估计参数和技术效率。蒙特卡罗结果表明：①本文方法的估计精度和分类精度均较高。随着样本容量的增大，精度增加。②忽略空间效应或者非参数效应，估计精度和分类精度降低，文中模型有存在必要性。③忽略发生概率的非参数效应会严重降低估计和分类精度，远大于忽略生产函数的非参数效应的影响。     

A Simple Toxicokinetic Model Exhibiting Complex Dynamics and Nonlinear Exposure Response

Uncertainty in model predictions of exposure response at low exposures is a problem for risk assessment. A particular interest is the internal concentration of an agent in biological systems as a function of external exposure concentrations. Physiologically based pharmacokinetic (PBPK) models permit estimation of internal exposure concentrations in target tissues but most assume that model parameters are either fixed or instantaneously dose-dependent. Taking into account response times for biological regulatory mechanisms introduces new dynamic behaviors that have implications for low-dose exposure response in chronic exposure. A simple one-compartment simulation model is described in which internal concentrations summed over time exhibit significant nonlinearity and nonmonotonicity in relation to external concentrations due to delayed up- or downregulation of a metabolic pathway. These behaviors could be the mechanistic basis for homeostasis and for some apparent hormetic effects.     

基于交叉效率DEA与群体共识的区间乘性语言偏好关系群决策

针对区间乘性语言偏好关系群决策问题，提出了一种基于交叉效率DEA和群体共识的群决策方法。首先，提出乘性语言偏好关系导出函数的定义，并构建产出导向的DEA模型，证明了一致性乘性语言偏好关系的DEA效率得分与排序向量之间存在比例关系。在此基础上，建立基于理想值的交叉效率DEA模型，提出乘性语言偏好关系的通用排序方法。同时，基于群体共识建立目标规划模型来计算各语言偏好关系的权重系数。最后，利用Monte Carlo随机模拟的方法对群体语言偏好空间进行统计分析，得到群决策期望排序向量及其可信度。算例分析表明本文方法能够有效的避免信息损失，具有较强的适用性和较高的可信度。     

An exploration of social & emotional factors impacting well-being in women who have sex with women (WSW)

Abstract

“Women who have sex with women” or WSW have unique perspectives within the LBGTQ spectrum. The purpose of this study included documenting perceptions, feelings, and experiences among WSW. Thirty-seven women participated in six focus groups, ages ranged from 20–64 years. Responses were transcribed and thematically coded. Four themes emerged as influencing factors: shame and fear, community, gender roles, and normalcy. Each major theme produced minor themes providing a context within major themes. Results offer valuable insights that can assist community members, health professionals, and scientists to better appraise the disparities and stigma impacting social and emotional well-being among WSW.     

The problem of intersectionality as an approach to digital activism: the Women’s March on Washington’s attempt to unite all women

ABSTRACT

This study examined the convergence of activism and intersectionality to understand how communicators create messages about social justice issues using social media. This is particularly relevant for public relations today, as digital activism almost ubiquitously involves bringing together conflicting publics who are active and social media-savvy, meanwhile maintaining an organizational brand/mission. Using the 2017 Women’s March on Washington (WMW) as an object of study, we explored how campaign messages reflected principles of intersectionality, consensus- and dissensus-based communication, and organizational self-reflection. We conducted a thematic analysis of posts from the WMW’s social media accounts as well as media quotes by the organizational leaders to get at the leaders’ intentions in their message design. Data suggested that messages of inclusivity as well as of necessary discord were employed to enact political change for WMW’s publics. We argue that although the WMW was not wholly intersectional, particularly in determining its political agenda, the efforts toward intersectionality are notable for theory-building and reflective practice, particularly for social mediated campaigns. The study proposes a theory for digital intersectional communication to guide future research and advocacy work.