产品类型差异下的消费者渠道偏好异质性 ———基于调节定向理论∗

产品类别是消费者行为研究的重要变量,消费者渠道偏好往往因为产品类别的不同而迥异。 消费者购买不同类型产品时的渠道偏好有何不同? 基于调节定向理论,引入产品实用享乐性与风险性,探 究消费者购买不同类型产品时的消费者渠道偏好差异。 围绕产品的实用享乐性、风险性与消费者渠道偏好 的调节定向匹配提出了 4 个假设,运用实验法采集数据,通过对样本数据的多项 Logistic 分析,对假设进行 了检验,并提出企业顾客管理建议,以期为企业根据产品类型区别建设渠道提供决策支持。     

一类四阶非线性常微分方程的两点边值问题解的存在性与唯一性

本文利用Hammerstein型积分算子和上下解方法,研究了一类四阶非线性常微分方程的两点边值问题     

重庆市“伞型”经济发展战略研究

分析“伞型”经济发展战略的内涵及实施之必要性,提出重庆直辖市实施战略的八大策略,并强调金融对区域主导产业成长的重要作用。     

村干部“名”与“实”的历时性嬗变——基于浙江赵村的实地调查

关于村干部角色行为的研究有两种取向：一是对村干部应该如何的“名”的研究,二是对村干部实际如何的“实”的研究。赵村的村干部的“名”与“实”经历了从融合到偏离的历史性嬗变。改革开放后,因对村干部有了新的要求与期待,历史变迁的惯性及相应的政策及制度性规定为村干部角色行为提供了基础,包办型村干部经历了“名”与“实”的短暂融合。但随着村庄出现可赢利的巨额集体资产,村干部以派性斗争为核心争夺村庄权力,以自我获利为目的,造成村庄集体资产流失,村民利益受损,赢利型村干部的“名”与“实”严重偏离。以制度治村为核心的纠偏机制的运行,以期扭转赢利型村干部“名”与“实”偏离的行为,却导致了放任型村干部的出现,这实际上是另一种形式的“名”与“实”的偏离,村干部“名”与“实”偏离的困境依然没有摆脱。     

Diverging Paths? A Comparative Look at Childcare Policies in Japan,South Korea and Taiwan

This article compares state policies to support childcare in Japan, South Korea and Taiwan, using fuzzy set ideal type analysis to determine the nature of institutional arrangements with respect to labour, money and time provisions. We then note their implications for familialization and defamilialization in the three countries. Our analysis suggests a common pattern towards the increased use of financial support amongst the three countries over time; however, this commonality does not mean their childcare policies are converging, as the financial supports differ in focus, with Japan concentrating on familialization by valuing family care, and Korea exclusively employing policy to facilitate the use of market‐based care services. For its part, Taiwan has been strengthening familialization by increasing the leave compensation to value time off to provide care. The different labour, money and time dimensions vis‐à‐vis the familialization/defamilialization matrix suggest varying implications of institutional arrangements for gender.     

中国古代调解制度探析

古代社会解决纠纷的途径多种多样,调解作为其中一种主要方式有着举足轻重的作用。在介绍中国传统调解制度的类型及特点的基础上,探讨传统调解制度对于古代封建社会的价值所在,认为其虽然存在一定的缺点,但是其有益的部分对我国当前的纠纷解决机制的完善有很大的借鉴作用。     

Bayes shrinkage estimator for consistency assessment of treatment effects in multi-regional clinical trials

The primary objective of a multi-regional clinical trial is to investigate the overall efficacy of the drug across regions and evaluate the possibility of applying the overall trial result to some specific region. A challenge arises when there is not enough regional sample size. We focus on the problem of evaluating applicability of a drug to a specific region of interest under the criterion of preserving a certain proportion of the overall treatment effect in the region. We propose a variant of James-Stein shrinkage estimator in the empirical Bayes context for the region-specific treatment effect. The estimator has the features of accommodating the between-region variation and finiteness correction of bias. We also propose a truncated version of the proposed shrinkage estimator to further protect risk in the presence of extreme value of regional treatment effect. Based on the proposed estimator, we provide the consistency assessment criterion and sample size calculation for the region of interest. Simulations are conducted to demonstrate the performance of the proposed estimators in comparison with some existing methods. A hypothetical example is presented to illustrate the application of the proposed method.     

Comparing diagnostic tests: test of hypothesis for likelihood ratios

Likelihood ratios (LRs) are used to characterize the efficiency of diagnostic tests. In this paper, we use the classical weighted least squares (CWLS) test procedure, which was originally used for testing the homogeneity of relative risks, for comparing the LRs of two or more binary diagnostic tests. We compare the performance of this method with the relative diagnostic likelihood ratio (rDLR) method and the diagnostic likelihood ratio regression (DLRReg) approach in terms of size and power, and we observe that the performances of CWLS and rDLR are the same when used to compare two diagnostic tests, while DLRReg method has higher type I error rates and powers. We also examine the performances of the CWLS and DLRReg methods for comparing three diagnostic tests in various sample size and prevalence combinations. On the basis of Monte Carlo simulations, we conclude that all of the tests are generally conservative and have low power, especially in settings of small sample size and low prevalence.     

Response‐adaptive designs for binary responses: How to offer patient benefit while being robust to time trends?

Response‐adaptive randomisation (RAR) can considerably improve the chances of a successful treatment outcome for patients in a clinical trial by skewing the allocation probability towards better performing treatments as data accumulates. There is considerable interest in using RAR designs in drug development for rare diseases, where traditional designs are not either feasible or ethically questionable. In this paper, we discuss and address a major criticism levelled at RAR: namely, type I error inflation due to an unknown time trend over the course of the trial. The most common cause of this phenomenon is changes in the characteristics of recruited patients—referred to as patient drift. This is a realistic concern for clinical trials in rare diseases due to their lengthly accrual rate. We compute the type I error inflation as a function of the time trend magnitude to determine in which contexts the problem is most exacerbated. We then assess the ability of different correction methods to preserve type I error in these contexts and their performance in terms of other operating characteristics, including patient benefit and power. We make recommendations as to which correction methods are most suitable in the rare disease context for several RAR rules, differentiating between the 2‐armed and the multi‐armed case. We further propose a RAR design for multi‐armed clinical trials, which is computationally efficient and robust to several time trends considered.     

Strong law of large numbers and complete convergence for non-identically distributed WOD random variables

In this paper, we establish the strong law of large numbers and complete convergence for non-identically distributed WOD random variables. We derive some new inequalities of Fuk–Nagaev type for the sums of non-identically distributed WD random variables. All these results further extend and refine previous ones.