Benevolence-dominant,authoritarianism-dominant,and classical paternalistic leadership: Testing their relationships with subordinate performance

We propose a new typology of paternalistic leadership styles based on how leaders demonstrate authoritarianism and benevolence, the two essential components of this type of leadership. Benevolence-dominant paternalistic leadership refers to leaders' sole dependence on the use of benevolence without their strong assertion of authority, whereas authoritarianism-dominant paternalistic leadership is based mainly on authoritarianism itself; classical paternalistic leadership, which best fits early observations of paternalistic leaders, refers to the salient combination of both leadership components. We used two distinct samples and methods to test this typology and the association with subordinate performance. Across the two studies, a field investigation with Taiwanese military supervisor-subordinate dyads and a hypothetical scenario experiment with U.S. working adults, we found a positive relationship between classical paternalistic leadership and subordinate performance as strong as that between benevolence-dominant paternalistic leadership and performance. Our findings echo the phenomenon that paternalistic leaders tend to combine benevolence with authoritarianism to affect subordinate performance.     

Loss and grief: The experience of transition to residential aged care

There is growing recognition of the experience of non-death-related loss and grief. One unexplored area of non-death-related loss and grief is associated with older people’s transition from home to residential aged care (RAC). This paper reports findings from a qualitative study that explored the experiences of people living in RAC, carer-relatives of people living in RAC and RAC staff. Using theories of loss and grief, the paper identifies features of the transition to RAC that are associated with unresolved loss and maladaptation to changed circumstances, and the types of support that would mitigate these. Using a series of focus groups with both residents and carer-relatives, as well as staff, the study found that residents and their families need more support to negotiate the multiple, often necessarily hasty decisions and bureaucratic requirements associated with transitioning to RAC, while simultaneously experiencing loss and grief. The types of support that families would welcome from service providers include facilitating shared decision making, valuing family and community carer expertise and providing practical information and assistance to fulfil administrative obligations.     

A modified common factor model for modelling mortality jointly for both sexes

Journal of Population Research - There is an increasing attention on the joint modelling of multiple populations. Populations are related in several ways, such as neighbouring countries, females...     

雄安新区科技企业创新能力评价研究

科技企业是实现科技创新的驱动者和科技成果转化的重要载体,也是推动研究开发的重要参与者,科学评价科技企业创新能力有助于企业自身不断发展壮大。在分析国内外新区科技企业创新驱动发展相关理论研究的基础上,从研发投入、研发基础、研发效益和现代科技四个角度,运用层次分析法构建科技企业创新能力评价系统,并通过实证分析说明评价系统的可靠性;根据评价系统测算出现阶段雄安新区科技企业创新能力,通过与成熟新区科技企业的比较,发现其短板和不足,力图为决策者科学合理评价、管理科技企业创新发展提供有益参考。     

Reviews

Abstract

Michelle DeMars reviews The Indispensable Academic Librarian: Teaching and Collaborating for Change; Norma Durian reviews The Library Outreach Casebook; Trina Boykin Nolen reviews Licensing Digital Content: A Practical Guide for Librarians, Third Edition.     

汇率货币模型的非线性协整关系检验——基于深度GRU神经网络

本文采用深度门控循环单元（GRU）神经网络探讨三种汇率货币模型（弹性价格、前瞻性和实际利率差模型）的非线性协整关系。GRU技术在深度学习中具有智能记忆、自主学习和强逼近能力等优点。为此，本文运用该技术对6组典型浮动汇率制国别数据进行了非线性Johansen协整检验。结果表明，汇率与宏观经济基本面之间存在非线性协整关系，从而说明了货币模型在非线性条件下的有效性，以及先进的深度学习工具在检验经济理论中的优势。     

论当代青年社会主义核心价值观培育的几个基础理论问题

青年是我国社会主义事业的重要建设者和接班人。当前,对青年进行社会主义核心价值观培育,其重要性已基本形成了共识,在理论和实践两方面也都取得了进展。本文旨在深入阐释社会主义核心价值观的文化根源,理清青年社会主义核心价值观培育的发展历程与目标定位,从而为青年社会主义核心价值观培育筑牢理论基础。     

Uniform consistency rate of kNN regression estimation for functional time series data

In this paper, we investigate the k-nearest neighbours (kNN) estimation of nonparametric regression model for strong mixing functional time series data. More precisely, we establish the uniform almost complete convergence rate of the kNN estimator under some mild conditions. Furthermore, a simulation study and an empirical application to the real data analysis of sea surface temperature (SST) are carried out to illustrate the finite sample performances and the usefulness of the kNN approach.