Jiahao Zhang and Yu Wei
This study conducts a comparative analysis of the diversification effects of China's national carbon market (CEA) and the EU ETS Phase IV (EUA) within major commodity markets.
Abstract
Purpose
This study conducts a comparative analysis of the diversification effects of China's national carbon market (CEA) and the EU ETS Phase IV (EUA) within major commodity markets.
Design/methodology/approach
The study employs the TVP-VAR extension of the spillover index framework to scrutinize the information spillovers among the energy, agriculture, metal, and carbon markets. Subsequently, the study explores practical applications of these findings, emphasizing how investors can harness insights from information spillovers to refine their investment strategies.
Findings
First, the CEA provide ample opportunities for portfolio diversification between the energy, agriculture, and metal markets, a desirable feature that the EUA does not possess. Second, a portfolio comprising exclusively energy and carbon assets often exhibits the highest Sharpe ratio. Nevertheless, the inclusion of agricultural and metal commodities in a carbon-oriented portfolio may potentially compromise its performance. Finally, our results underscore the pronounced advantage of minimum spillover portfolios; particularly those that designed minimize net pairwise volatility spillover, in the context of China's national carbon market.
Originality/value
This study addresses the previously unexplored intersection of information spillovers and portfolio diversification in major commodity markets, with an emphasis on the role of CEA.
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Helen Inseng Duh, Hong Yu, Marike Venter de Villiers, Vladimira Steffek and Dan Shao
Large, influential and profitable young adults are being targeted for fast fashion that negatively impacts the environment. The transition from a fast to an environmentally…
Abstract
Purpose
Large, influential and profitable young adults are being targeted for fast fashion that negatively impacts the environment. The transition from a fast to an environmentally friendly slow fashion is a challenging process and culturally dependent. The process starts with slow fashion idea adoption. Thus, the authors modified an information acceptance model (IACM) to examine information characteristics (idea/information quality, credibility, usefulness, source credibility) and consumer factors (need for idea and attitudes) impacting intentions to adopt the slow fashion idea in Canada, South Africa (individualists) and China (collectivists).
Design/methodology/approach
Cross-sectional data were collected from South African (n = 197), Chinese (n = 304) and Canadian (n = 227) young adults (18–35 years old) at universities in metropolitan cities. Partial least squares structural equation modeling was used to analyze the data.
Findings
The results show that while most information characteristics and consumer factors are vital for slow fashion attitudes and intention formation, information quality and trust in the sources were a problem in individualistic cultures as opposed to the collectivist culture. This finding confirms the greater tendency of collectivists to trust disseminated information on environmental issues. In all cultures, attitudes impacted idea adoption intentions. On testing IACM, the multigroup analyses showed no significant differences between young adults in the individualistic cultures. Attitudes mediated most relationships and were highly explained by IACM (South Africa, 49.6%; China, 74.5%; and Canada, 64.5%).
Originality/value
In emerging and developed markets, this study informs environmentalists and green fashion brands of information characteristics that can create positive attitudes and slow fashion idea adoption intentions among influential young adults.
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In construction projects, engineering variations are very common and create breeding grounds for opportunistic claims. This study investigates the complementary effect between an…
Abstract
Purpose
In construction projects, engineering variations are very common and create breeding grounds for opportunistic claims. This study investigates the complementary effect between an inspection mechanism and a reputation system in deterring opportunistic claims, considering an employer with limited inspection accuracy and a contractor, which can be either reputation-concerned or opportunistic.
Design/methodology/approach
This paper applies a signaling game to investigate the complementary effect between the employer's inspection and a reputation system in deterring the contractor's possible opportunistic claim, considering the information-flow influence of claiming prices.
Findings
This study finds that in the exogenous-inspection-accuracy case, the employer does not always inspect the claim. A more stringent reputation system complements a less accurate inspection only when the inspection cost is lower than a threshold, but may decline the employer's surplus or social welfare. In the optimal-inspection-accuracy case, the employer always inspects the claim. However, only a sufficiently stringent reputation system can guarantee the effectiveness of an optimal inspection in curbing opportunistic claims. A more stringent reputation system has a value-stepping effect on the employer's surplus but may unexpectedly impair social welfare, whereas a higher inspection cost efficiency always reduces social welfare.
Originality/value
This article contributes to the project management literature by combing the signaling game theory with the reputation theory and thus embeds the problem of inspection mechanism design into a broader socio-economic framework.
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Dan Liu, Tiange Liu and Yuting Zheng
By studying the green development efficiency (GDE) of 33 cities in the provinces of Jiangsu, Zhejiang, and Fujian in China, this study strives to conduct an analysis of the…
Abstract
Purpose
By studying the green development efficiency (GDE) of 33 cities in the provinces of Jiangsu, Zhejiang, and Fujian in China, this study strives to conduct an analysis of the sustainable practices implemented in these developed regions, and derive valuable insights that can foster the promotion of green transformation.
Design/methodology/approach
First, the urban green development system (GDS) was decomposed into the economic benefit subsystem (EBS), social benefit subsystem (SBS), and pollution control subsystem (PCS). Then, a mixed network SBM model was proposed to evaluate the GDE during 20152020, with Moran’s I and Bootstrap truncated regression model subsequently applied to measure the spatial characteristics and driving factors of efficiency.
Findings
Subsystem efficiency presents a distribution trend of PCS > EBS > SBS. There is a particular spatial aggregation effect in EBS efficiency, whereas SBS and PCS efficiencies have no significant spatial autocorrelation. Furthermore, urbanization level contributes significantly to the efficiency of all subsystems; industrial structure, energy consumption, and technological innovation play a crucial role in EBS and SBS; external openness is a pivotal factor in SBS; and environmental regulation has a significant effect on PCS.
Originality/value
This study further decomposes the black box of GDS into subsystems including the economy, society, and environment. Additionally, by employing a mixed network SBM model and Bootstrap truncated regression model to investigate efficiency and its driving factors from the subsystem perspective, it endeavors to derive more detailed research conclusions and policy implications.
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Shekhar and Marco Valeri
The study aims to review how the use of technology enhances the authentic tourist experience. Technology and digitalization have enhanced tourist experiences. However, critiques…
Abstract
Purpose
The study aims to review how the use of technology enhances the authentic tourist experience. Technology and digitalization have enhanced tourist experiences. However, critiques comment on its ability to over-commercialize activity and lack of authenticity. Thus, there is a need to synthesize knowledge of technology usage to increase authentic tourist experience.
Design/methodology/approach
The study carries out a bibliometric review of the studies focusing on the use of technology in enhancing tourist experiences. Two hundred journal articles, published between 1997 and 2023 were retrieved from the Web of Science (WoS) database to carry out descriptive and network analysis using the Gephi, VOSviewer and Science of Science (Sci2) software. The components of authentic tourism experience are identified from the literature through a content analysis.
Findings
The findings of the study are broadly classified into two: first, the most frequently used keywords in the study include tourist experience and satisfaction, co-creation, virtual reality, smart tourism, technology, authenticity and heritage tourism. Second, the five major themes studied in the topic include virtual reality and tourist experience; media, tourist experience and encounters; technology, smart tourism and tourist experience; digital transformation, social media and tourist experience; and virtual reality and tourist experience which are still relevant in the literature because of the presence of study gaps.
Originality/value
The findings are used to develop a conceptual framework for the role of technology in enhancing authenticity in tourism typologies where authenticity is critical.
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Zhitian Zhang, Hongdong Zhao, Yazhou Zhao, Dan Chen, Ke Zhang and Yanqi Li
In autonomous driving, the inherent sparsity of point clouds often limits the performance of object detection, while existing multimodal architectures struggle to meet the…
Abstract
Purpose
In autonomous driving, the inherent sparsity of point clouds often limits the performance of object detection, while existing multimodal architectures struggle to meet the real-time requirements for 3D object detection. Therefore, the main purpose of this paper is to significantly enhance the detection performance of objects, especially the recognition capability for small-sized objects and to address the issue of slow inference speed. This will improve the safety of autonomous driving systems and provide feasibility for devices with limited computing power to achieve autonomous driving.
Design/methodology/approach
BRTPillar first adopts an element-based method to fuse image and point cloud features. Secondly, a local-global feature interaction method based on an efficient additive attention mechanism was designed to extract multi-scale contextual information. Finally, an enhanced multi-scale feature fusion method was proposed by introducing adaptive spatial and channel interaction attention mechanisms, thereby improving the learning of fine-grained features.
Findings
Extensive experiments were conducted on the KITTI dataset. The results showed that compared with the benchmark model, the accuracy of cars, pedestrians and cyclists on the 3D object box improved by 3.05, 9.01 and 22.65%, respectively; the accuracy in the bird’s-eye view has increased by 2.98, 10.77 and 21.14%, respectively. Meanwhile, the running speed of BRTPillar can reach 40.27 Hz, meeting the real-time detection needs of autonomous driving.
Originality/value
This paper proposes a boosting multimodal real-time 3D object detection method called BRTPillar, which achieves accurate location in many scenarios, especially for complex scenes with many small objects, while also achieving real-time inference speed.
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This study aims to explore the development and significance of sustainable finance instruments, mainly sustainable bonds. The purpose is to provide policymakers, regulators and…
Abstract
Purpose
This study aims to explore the development and significance of sustainable finance instruments, mainly sustainable bonds. The purpose is to provide policymakers, regulators and researchers with insights into the current state of sustainable finance research and also provide future research directions.
Design/methodology/approach
This study used Scientific Procedures and Rationales for Systematic Literature Reviews as a review protocol and addressed four research questions concerning publication and citation trends, major themes and future research directions in sustainable bonds.
Findings
This study indicated growing attention in sustainable bond research, with increasing publication and citation trends. Along with identifying research themes, the findings include future direction on pricing and risk assessment, market dynamics and growth potential, policy and regulatory environments and global perspectives with local context.
Research limitations/implications
Although this study provides a robust analysis of the current literature, it relies on existing publications and may not capture the latest developments in sustainable bond research. However, policymakers can benefit from insights into the growth and dynamics of sustainable bonds, enabling them to implement effective policies and regulations. Investors and businesses can use this research to inform their environmental, social and governance investment strategies and decision-making processes.
Originality/value
This paper suggests a comprehensive overview of the state of research in sustainable bonds, highlighting the emerging trends and research priorities. It also underlines the significance of sustainable finance in achieving sustainability goals and provides a roadmap for future research.
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Dan Yuan, Jiejie Du, Yaguang Pan and Chenxi Li
This study explores the role of industrial co-agglomeration and digital economy in influencing the green high-quality development of the Yellow River National Cultural Park to…
Abstract
Purpose
This study explores the role of industrial co-agglomeration and digital economy in influencing the green high-quality development of the Yellow River National Cultural Park to provide countermeasures and suggestions for promoting the whole-area high-quality development.
Design/methodology/approach
This study is based on panel data from 56 cities from 2010 to 2022. First, a Super-SBM model is built to evaluate green high-quality development. Secondly, location entropy is used to measure industrial co-agglomeration and the entropy weight method is used to measure the digital economy. Finally, the panel Tobit model is used to analyze the impact of industrial co-agglomeration and digital economy on the green high-quality development of Yellow River National Cultural Park.
Findings
This study found that (1) industrial co-agglomeration has a negative implication in green high-quality development, while the digital economy boosts green high-quality development; (2) industrial co-agglomeration is a less critical dependency on the level of development of the digital economy in influencing green high-quality development, while the facilitating effect of the digital economy is more dependent on industrial co-agglomeration and (3) the trend of slow growth in industrial co-agglomeration and digital economy development, with significant regional differences in green high-quality development.
Research limitations/implications
Undeniably, our study has several limitations. Firstly, as the study area only includes some cities in individual provinces, such as Qinghai, this paper only analyzes at the city level, which does not better reflect the differences between provinces; secondly, this study only adopts one method to determine the digital economy. In the future, other methods can be explored to measure digital economy; finally, in addition to the main role of digital economy and industrial co-agglomeration, other factors may also affect the green high-quality development of YRNCP. Future research should introduce other variables to improve the theoretical framework.
Practical implications
First, it provides countermeasures and suggestions for promoting the green high-quality development of YRNCP. Second, it helps to implement the new development concept, cultivate the new quality productivity of culture and the tourism industry and promote the green high-quality development of YRNCP. Third, it provides references to improve the management measures and related policies of the YRNCP more accurately and efficiently. Fourth, it helps to build a new development pattern and has important practical significance in promoting the high-quality development of the whole basin, protecting and inheriting the Yellow River Culture and helping the Chinese-style modernization and development, which are of great practical significance.
Social implications
The research is carried out from the new perspective of industrial co-agglomeration and digital economy, which provides the theoretical basis and reference for solving the problem of green high-quality development of YRNCP. Second, it broadens the research idea of green high-quality development. Third, it quantitatively analyzes the impact of industrial co-agglomeration and digital economy on the high-quality development of YRNCP, deepening the research on the green high-quality development of YRNCP. Fourth, it helps to enrich and improve the theoretical research related to the national cultural park development and has positive significance in promoting the management and innovation of the cultural industry and the construction of related disciplines.
Originality/value
The paper’s findings illustrate the functional relationship of the digital economy and industrial co-agglomeration with green high-quality development and propose countermeasures to facilitate the high-quality development of the Yellow River National Cultural Park.
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Abdul Quadir, Alok Raj and Anupam Agrawal
The purpose of this paper is to investigate the impact of demand information sharing on products’ greening levels with downstream competition. Specifically, this study examine two…
Abstract
Purpose
The purpose of this paper is to investigate the impact of demand information sharing on products’ greening levels with downstream competition. Specifically, this study examine two types of green products, “development-intensive” (DI) and “marginal-cost intensive” (MI), in a two-echelon supply chain where the manufacturer produces substitutable products, and competing retailers operate in a market with uncertain demand.
Design/methodology/approach
The authors adopt the manufacturer-led Stackelberg game-theoretic framework and consider a multistage game. This study consider how retailers receive private signals about uncertain demand and decide whether to share this information with the manufacturer, who then decides whether to acquire this information at a certain given cost. This paper considers backward induction and Bayesian Nash equilibrium to solve the model.
Findings
The authors find that in the absence of competition, information sharing is the only equilibrium and improves the greening level under DI, whereas no-information sharing is the only equilibrium and improves the greening level under MI, an increase in downstream competition drives higher investment in greening efforts by the manufacturer in both DI and MI and the manufacturer needs to offer a payment to the retailers to obtain demand information under both simultaneous and sequential contract schemes.
Originality/value
This paper contributes to the literature by examining how the nature of products (margin intensive green product or development intensive green product) influences green supply chain decisions under information asymmetry and downstream competition.
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Xiaohang Ren, Shuiling Hu, Xianming Sun and Dan Zhou
This paper investigates the impact of AI penetration rate on the degree of corporate greenwashing and aims to assess the potential of AI in enhancing firms' environmental…
Abstract
Purpose
This paper investigates the impact of AI penetration rate on the degree of corporate greenwashing and aims to assess the potential of AI in enhancing firms' environmental performance and reducing false disclosures.
Design/methodology/approach
This study employs a year and firm fixed-effects model to analyze data from Chinese listed firms from 2012 to 2022. We use the low-carbon city pilot as a quasi-natural experiment to address endogeneity concerns and conduct a series of robustness tests, including adding control variables and transforming the model.
Findings
The results of this paper show that the application of AI can inhibit firms' greenwashing behavior, with green innovation activities further enhancing this inhibitory effect. In state-owned firms and those with Party Organizations, the inhibitory effect of AI on corporate greenwashing is more significant. This reduction in greenwashing is more likely to be observed in firms that are heavily influenced by Confucian culture, receive higher public attention regarding their environmental impact, face less market competition, suffer from more serious pollution and face less financial constraints.
Originality/value
We propose a new research perspective that offers novel insights into promoting the green development of firms by revealing the potential of AI in reducing their greenwashing behavior. Corporate boards can explore specific strategies for applying AI to monitor, prevent and correct greenwashing, thereby enhancing corporate environmental performance and social responsibility.