作者机构：
[Zhang, Caihong; Zhang, CH; Gao, Xiaoxin] Beijing Forestry Univ, Sch Econ & Management, Beijing 100083, Peoples R China.;[Gao, Xiaoxin] Cent South Univ Forestry & Technol, Sch Econ, Changsha 410004, Peoples R China.;[Gao, Xiaoxin] Res Ctr High Qual Dev Ind Econ, Key Res Base Philosophy & Social Sci Hunan Prov, Changsha 410004, Peoples R China.
关键词：
University brand;Brand management;Brand positioning;University identification;Higher education marketing
摘要：
Despite its significant role, brand management is an oft-overlooked and challenging aspect in the development of academic institutions, especially in higher education context. Based on a systematic review of journal articles from various sources including ScienceDirect, Emerald Insight and SpringerLink during the 2000-2021 period, the authors of this paper seek to identify, evaluate, and analyze university brand. After careful consideration of academic publications based on their relevance for the research objectives, 43 articles have been included in this comprehensive and integrative review. Special attention is paid to the theories underlying brand management, brand positioning, brand identity of a higher education institution, marketing strategies, as well as implications for management, students, and staff. Moreover, some valuable lessons which a university can learn from a company in marketing are identified. Thereby, the competitive advantages of a university would be firmly enhanced. It is our hope that this paper will explore a new path for further research and provide another perspective for administrators, authors and practitioners in the area of university brand.
期刊：
POLISH JOURNAL OF ENVIRONMENTAL STUDIES,2023年32(6):5347-5363 ISSN：1230-1485
通讯作者：
Tao, L
作者机构：
[Tong, Jing] Cent South Univ Forestry & Technol, Coll Bangor, 498 Shaoshan South Rd, Changsha 410004, Hunan, Peoples R China.;[Tao, Li; Tao, L] Cent South Univ Forestry & Technol, Coll Econ, 498 Shaoshan South Rd, Changsha 410004, Hunan, Peoples R China.
通讯机构：
[Tao, L ] C;Cent South Univ Forestry & Technol, Coll Econ, 498 Shaoshan South Rd, Changsha 410004, Hunan, Peoples R China.
关键词：
carbon emissions;well-being performance;well-being performance of carbon emissions;Super-SBM model;industrial structure
摘要：
The rapid economic development has caused a continuous increase in carbon emissions, which has led to a series of problems such as environmental pollution and climate change, resulting in a decline in economic, ecological and social welfare. The increase in human well-being generated by each unit of carbon emissions can be expressed in terms of well-being performance of carbon emissions. Based on provincial panel data from 2005 to 2020 in China, this paper provides an in-depth exploration of the impact of the rationalization and upgrading of industrial structure on the well-being performance of carbon emissions by constructing a fixed-effect model. The conclusions of the study are as follows: (1) The rationalization of industrial structure at this stage has not yet had an impact on well-being performance of carbon emissions, and upgrading can significantly contribute to the improvement of well-being performance of carbon emissions. (2) the impact of industrial structure upgrading on well-being performance of carbon emissions is heterogeneous. Advancedization only significantly contributes to the well-being performance of carbon emissions of eastern regions, regions with low natural resource endowments, regions with high external dependence and regions with high environmental awareness. The conclusion of the paper provides an important reference for other countries to optimize the industrial structure to improve well-being performance.
摘要：
The firefly algorithm (FA) has gained widespread attention and has been widely applied because of its simple structure, few control parameters and easy implementation. As the traditional FA lacks a mutation mechanism, it tends to fall into local optima, leading to premature convergence, thus affecting the optimization accuracy. To address these limitations, from the perspective of population diversity, a complex network-based FA (CnFA) with scale-free properties is proposed in this paper. The scale-free properties of complex networks effectively ensure the diversity of populations to guide the populations in their search, thus avoiding random interactions of information among populations that could lead to superindividuals controlling the entire population. The property of the power-law distribution of nodes in complex networks is exploited to effectively avoid the premature convergence of the FA and falling into local optima. To verify the search performance of CnFA, we compared the FA and its variants, as well as multiple competitive approaches, on 30 different-dimension benchmark function optimization tasks and two time series prediction tasks. The experimental results and statistical analysis show that CnFA achieves satisfactory performance due to the better balance between exploitation and exploration in the search process. Additionally, we extended the proposed method to two other population-based algorithms, and the experimental results verify that the complex network -based mechanism can enhance the performance of not only the FA but also other population-based evolutionary algorithms.(c) 2023 Elsevier B.V. All rights reserved.
通讯机构：
[Liu, H ] C;Cent South Univ Forestry & Technol, Sch Econ, Changsha 410004, Peoples R China.
关键词：
Oil market fear;Implied volatility index;Climate policy uncertainty;Time-varying impact;TVP-VAR model
摘要：
Implied volatility index is a popular proxy for market fear. This paper uses the oil implied volatility index (OVX) to investigate the impact of different uncertainty measures on oil market fear. Our uncertainty measures consider multiple perspectives, specifically including climate policy uncertainty (CPU), geopolitical risk (GPR), economic policy uncertainty (EPU), and equity market volatility (EMV). Based on the time-varying parameter vector autoregression (TVP-VAR) model, our empirical results show that the impact of CPU, GPR, EPU, and EMV on OVX is time-varying and heterogeneous due to these uncertainty measures containing different information content. In particular, the CPU has become increasingly important for triggering oil market fear since the recent Paris Agreement. During the COVID-19 pandemic, CPU, EPU, and EMV, rather than GPR, play a prominent role in increasing oil market fear.
