中国“碳中和”目标的实现路径与模式选择

围绕中国碳中和目标的实现路径与模式选择问题，提出了一个中国应对气候变化整体治理模式，即多阶段混合主导型碳中和实现模式。这一模式是以国家为核心，在一定时期和内外环境约束下，通过减排和增汇路径，对中国境内由人类活动造成的CO2排放与人为CO2吸收量之间关系进行调整和平衡的过程；其内部由宏观、中观和微观三层结构组成，每层结构各不相同。多阶段混合主导型碳中和实现模式的提出，拓展和完善了气候变化整体治理理论，为气候变化治理提供了机制借鉴。     

Efficacy Foundations for Risk Communication: How People Think About Reducing the Risks of Climate Change

Believing action to reduce the risks of climate change is both possible (self‐efficacy) and effective (response efficacy) is essential to motivate and sustain risk mitigation efforts, according to current risk communication theory. Although the public recognizes the dangers of climate change, and is deluged with lists of possible mitigative actions, little is known about public efficacy beliefs in the context of climate change. Prior efficacy studies rely on conflicting constructs and measures of efficacy, and links between efficacy and risk management actions are muddled. As a result, much remains to learn about how laypersons think about the ease and effectiveness of potential mitigative actions. To bring clarity and inform risk communication and management efforts, we investigate how people think about efficacy in the context of climate change risk management by analyzing unprompted and prompted beliefs from two national surveys (N = 405, N = 1,820). In general, respondents distinguish little between effective and ineffective climate strategies. While many respondents appreciate that reducing fossil fuel use is an effective risk mitigation strategy, overall assessments reflect persistent misconceptions about climate change causes, and uncertainties about the effectiveness of risk mitigation strategies. Our findings suggest targeting climate change risk communication and management strategies to (1) address gaps in people's existing mental models of climate action, (2) leverage existing public understanding of both potentially effective mitigation strategies and the collective action dilemma at the heart of climate change action, and (3) take into account ideologically driven reactions to behavior change and government action framed as climate action.     

乡土社会语境下梅山武术的生态发展

中国乡土武术文化的生存形态可分为原生形态、次生形态以及艺术形态。在现代中国,社会变迁主要体现在社会再生产土壤、社会再生产方式、社会再生产功能等方面的变迁,致使中国乡土武术文化的生态传承内容、动力、方式及评判标准发生变化。因此,中国乡土武术文化发展出路在于自身的文化内涵的拓深和增值,以适应民众正在或已经改变的文化需求。     

Incumbent capability enhancement in response to radical innovations

Schumpeterian market disequilibrium marked by entrepreneurial entry and incumbent exit has long held an important place in management literature. The extant literature has overwhelmingly championed the newcomer, despite incumbents' obvious advantages in resources, experience and market knowledge. The current research provides evidence for the effectiveness of the incumbent's strategy of capability enhancement (along an established technological trajectory) while responding to radical technological innovations. We develop a cognitive process model that integrates managerial cognition with capability development and deployment views, depicting the dynamics of the incumbent's capability enhancement process. We analyze the cognitive drivers of organizational actions in all stages (rigidity, triggering event, and capability renewal) and elucidate the role of top management cognition in the processes of detecting and correcting errors in a strategic course of action. We ground our model in the case of a cork-stopper industry veteran's decline as corks ceded ground to screw tops and other stoppers in the wine industry. How a major company fought back in response to the emergence of these, in the industry context, radical technological innovations, provides the basis for our narrative. The proposed theoretical model contributes to literature on technology management (with regard to incumbent strategies in response to radical innovation threats) as well as the role of cognition in strategy (providing an explanation of the cognitive underpinnings of capability development).     

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.     

Modifications of sequential designs in bioequivalence trials

Bioequivalence (BE) studies are designed to show that two formulations of one drug are equivalent and they play an important role in drug development. When in a design stage, it is possible that there is a high degree of uncertainty on variability of the formulations and the actual performance of the test versus reference formulation. Therefore, an interim look may be desirable to stop the study if there is no chance of claiming BE at the end (futility), or claim BE if evidence is sufficient (efficacy), or adjust the sample size. Sequential design approaches specially for BE studies have been proposed previously in publications. We applied modification to the existing methods focusing on simplified multiplicity adjustment and futility stopping. We name our method modified sequential design for BE studies (MSDBE). Simulation results demonstrate comparable performance between MSDBE and the original published methods while MSDBE offers more transparency and better applicability. The R package MSDBE is available at https://sites.google.com/site/modsdbe/ . Copyright © 2015 John Wiley & Sons, Ltd.     

Efficacy,Action, and Support for Reducing Climate Change Risks

A growing body of research demonstrates that believing action to reduce the risks of climate change is both possible (self‐efficacy) and effective (response efficacy) is essential to motivate and sustain risk mitigation efforts. Despite this potentially critical role of efficacy beliefs, measures and their use vary wildly in climate change risk perception and communication research, making it hard to compare and learn from efficacy studies. To address this problem and advance our understanding of efficacy beliefs, this article makes three contributions. First, we present a theoretically motivated approach to measuring climate change mitigation efficacy, in light of diverse proposed, perceived, and previously researched strategies. Second, we test this in two national survey samples (Amazon's Mechanical Turk N = 405, GfK Knowledge Panel N = 1,820), demonstrating largely coherent beliefs by level of action and discrimination between types of efficacy. Four additive efficacy scales emerge: personal self‐efficacy, personal response efficacy, government and collective self‐efficacy, and government and collective response efficacy. Third, we employ the resulting efficacy scales in mediation models to test how well efficacy beliefs predict climate change policy support, controlling for specific knowledge, risk perceptions, and ideology, and allowing for mediation by concern. Concern fully mediates the relatively strong effects of perceived risk on policy support, but only partly mediates efficacy beliefs. Stronger government and collective response efficacy beliefs and personal self‐efficacy beliefs are both directly and indirectly associated with greater support for reducing the risks of climate change, even after controlling for ideology and causal beliefs about climate change.     

On a class exhibiting trend change in average failure rate

Abstract

Weak convergence and moment convergence issues are investigated for the New Better than Average Failure Rate (NBAFR) family (introduced by Loh (1984 Loh, W. Y. 1984. A new generalization of the class of NBU distributions. IEEE Transactions on Reliability R-33 :97–113[Crossref], [Web of Science ®] , [Google Scholar])). We explore the validity of these results in the context of a more general ageing class that we introduce. We prove some new properties of this class and derive its interrelationships with other non-monotonic ageing families. Reliability and moment bounds are obtained and an interesting characterization of exponentiality is proved. Special cases of our results lead to new theorems for the NBAFR class. Finally weak convergence and related issues are established for this class.     

Myriad potential for mentoring: Understanding the process of transformational change through a gender equality intervention

This article contributes to understanding transformational change towards gender equality by examining the transformational change potential of a mentoring programme for women, a type of gender equality intervention both criticized and praised for its ability to bring about change. Drawing upon an empirical case study of a mentoring programme for women academics in a Dutch university, we explore three dimensions of transformational change: organizational members (i) discussing and reflecting upon gendered organizational norms and work practices; (ii) creating new narratives; and (iii) experimenting with new work practices. Our findings indicate five specific conditions that enable transformational change: cross‐mentoring, questioning what is taken for granted, repeating participation and individual stories, facilitating peer support networks and addressing and equipping all participants as change agents. We suggest that these conditions should be taken into account when (re)designing effective organizational gender equality interventions.     

Restricted minimax estimation in semiparametric linear models

Abstract

In this article we develop the minimax estimation approach of general linear models to the semiparametric linear models when the parameters are simultaneously constrained by an ellipsoid and linear restrictions. Combining sample information and prior constraints the minimax estimator is obtained and compared with partially least square estimator by theoretical and simulation methods.