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Article
Publication date: 1 February 2019

Zhiwu Hong, Linlin Niu and Gengming Zeng

Using a discrete-time version of the arbitrage-free Nelson–Siegel (AFNS) term structure model, the authors examine how yield curves in the US and China react to exchange rate…

Abstract

Purpose

Using a discrete-time version of the arbitrage-free Nelson–Siegel (AFNS) term structure model, the authors examine how yield curves in the US and China react to exchange rate policy shocks as China introduces gradual reforms to make its exchange rate regime more flexible. The paper aims to discuss this issue.

Design/methodology/approach

The authors characterize the specification of the discrete-time AFNS model, prove the uniqueness of the solution for model identification, perform specification analysis on its canonical form and detail the MCMC estimation method with a fast and reliable prior extraction step.

Findings

Model decomposition reveals that in the US yield responses, changes in risk premia for medium- to long-term yields dominate changes in yield expectation for short- to medium-term yields, indicating that the portfolio rebalancing effect due to varying risk perception is stronger than the signaling effect due to policy rate expectation.

Practical implications

The results are helpful in diagnosing market sentiment and exchange rate risk pricing as China further internationalizes its currency.

Originality/value

The methodology can be easily extended to study yield curve responses to other scenarios of policy shocks or regime changes.

Details

China Finance Review International, vol. 9 no. 3
Type: Research Article
ISSN: 2044-1398

Keywords

Content available
Article
Publication date: 16 August 2019

Xu Zheng and Stan Hurn

430

Abstract

Details

China Finance Review International, vol. 9 no. 3
Type: Research Article
ISSN: 2044-1398

Article
Publication date: 20 June 2022

Linlin Xie, Tianhao Ju, Ting Han and Lei Hou

As megaprojects bear extensive and profound social responsibilities throughout the project life cycle, formulating effective measures for improving construction enterprise social…

Abstract

Purpose

As megaprojects bear extensive and profound social responsibilities throughout the project life cycle, formulating effective measures for improving construction enterprise social responsibility is key to project success. Given the current research is relatively lack of these measures, this study aims to formulate a meta-network framework to improve the megaproject social responsibility behaviour (MSRB) for construction enterprises.

Design/methodology/approach

First, this study implements literature review, expert interview and field investigation to identify the construction enterprise MSRB and its influencing factors. Second, this study evaluates the MSRB implementation level of the selected construction enterprises and proposes the above mentioned meta-network framework. Next, this meta-network is configured to reflect the impact of MSRB strategic adjustment. Last but not least, a real-world case study is carried out to validate this framework.

Findings

The best MSRB performance is always witnessed from the contractor group, followed by the project client group and the site supervisor group. The outcomes of implementing certain managerial strategies indicate that (1) social responsibility cognition is a critical factor for all the groups; (2) communication mechanism and normative pressure are the critical factors for clients; (3) coercive pressure is a critical factor for supervisors and (4) cultural cognitive pressure is a critical factor for clients and contractors.

Originality/value

The use of the framework in proactive assessment and management of MSRB can lead to effective strategies for construction enterprises to increase the efficiency and quality of projects.

Details

Engineering, Construction and Architectural Management, vol. 30 no. 9
Type: Research Article
ISSN: 0969-9988

Keywords

Open Access
Article
Publication date: 21 November 2018

Lei Wen and Linlin Huang

Climate change has aroused widespread concern around the world, which is one of the most complex challenges encountered by human beings. The underlying cause of climate change is…

1594

Abstract

Purpose

Climate change has aroused widespread concern around the world, which is one of the most complex challenges encountered by human beings. The underlying cause of climate change is the increase of carbon emissions. To reduce carbon emissions, the analysis of the factors affecting this type of emission is of practical significance.

Design/methodology/approach

This paper identified five factors affecting carbon emissions using the logarithmic mean Divisia index (LMDI) decomposition model (e.g. per capita carbon emissions, industrial structure, energy intensity, energy structure and per capita GDP). Besides, based on the projection pursuit method, this paper obtained the optimal projection directions of five influencing factors in 30 provinces (except for Tibet). Based on the data from 2000 to 2014, the authors predicted the optimal projection directions in the next six years under the Markov transfer matrix.

Findings

The results indicated that per capita GDP was the critical factor for reducing carbon emissions. The industrial structure and population intensified carbon emissions. The energy structure had seldom impacted on carbon emissions. The energy intensity obviously inhibited carbon emissions. The best optimal projection direction of each index in the next six years remained stable. Finally, this paper proposed the policy implications.

Originality/value

This paper provides an insight into the current state and the future changes in carbon emissions.

Details

International Journal of Climate Change Strategies and Management, vol. 11 no. 3
Type: Research Article
ISSN: 1756-8692

Keywords

Article
Publication date: 28 April 2023

Linlin Zhang, Haoran Jiang, Tongwen Hu and Zhenduo Zhang

Drawing upon person–supervisor fit theory, a model is developed to illustrate how leader–member trait mindfulness (in)congruence may impact leader–member exchange (LMX) and how…

Abstract

Purpose

Drawing upon person–supervisor fit theory, a model is developed to illustrate how leader–member trait mindfulness (in)congruence may impact leader–member exchange (LMX) and how such trait mindfulness (in)congruence can indirectly influence taking charge.

Design/methodology/approach

Polynomial regression and response surface methodology are used to analyze 237 valid matched leader–member dyads.

Findings

LMX increases as leaders' and members' trait mindfulness become more aligned; LMX is higher when leader–member dyads are congruent at high levels (vs low levels). In the case of incongruence, LMX is higher when the member's trait mindfulness exceeds that of the leader. Furthermore, the relationship between leader–member trait mindfulness (in)congruence and taking charge is mediated by LMX.

Practical implications

The joint and interactive role of high trait mindfulness in leader–member dyads can help them to generate high-quality interpersonal exchange, as well as to cope with challenges posed by present and future changes.

Originality/value

The linear, nonlinear, simultaneous and interactive effects of dyadic trait mindfulness expand previous research, clarifying that the evaluation of leader–member congruence and incongruence at various degrees, and for various patterns of trait mindfulness, is more informative than examining the direct effect alone.

Details

Journal of Managerial Psychology, vol. 39 no. 3
Type: Research Article
ISSN: 0268-3946

Keywords

Article
Publication date: 25 January 2013

Sifeng Liu, Yingjie Yang, Ying Cao and Naiming Xie

The purpose of this paper is to review systematically the research of grey relation analysis (GRA) models.

494

Abstract

Purpose

The purpose of this paper is to review systematically the research of grey relation analysis (GRA) models.

Design/methodology/approach

Three different approaches, the springboard to build a GRA model, the angle of view in modelling, and the dimension of objects, are analysed, respectively.

Findings

The GRA models developed from the models based on relation coefficients of each point in the sequences in early days to the generalized GRA models based on integral or overall perspective. It evolved from the GRA models which measure similarity based on nearness, into the models which consider similarity and nearness, respectively. The objects of the research advanced from the analysis of relationship among curves to that among curved surfaces, and further to the analysis of relationship in three‐dimensional space and even the relationship among super surfaces in n‐dimensional space.

Originality/value

The further research on GRA models is proposed. One is about the property of GRA model. An in‐depth knowledge about the properties of GRA model will help people to understand its function, applicable area and requirements for modelling. The other one is about the extension of research object system. The object to be analysed should be extended from the common sequence of real numbers to grey numbers, vectors, matrices, and even multi‐dimensional matrices, etc.

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