Zhi Zhou, Xiangming Mu and Xin Lin
This paper aims to propose a novel approach to constructing an economic taxonomy that demonstrates the complex relationships between firms, which are not fully revealed by…
Abstract
Purpose
This paper aims to propose a novel approach to constructing an economic taxonomy that demonstrates the complex relationships between firms, which are not fully revealed by traditional industry classification systems such as the NAICS or ICB.
Design/methodology/approach
Based on narrative economic theory, data from CNBC news reports between 01/01/2019 and 03/27/2019 regarding four selected firms, namely, Walmart, Amazon, Netflix and Boeing, were analyzed and coded as the basis to guide the construction of a firm-to-firm relationship taxonomy.
Findings
The relationships between firms are more complex than the simple relationships defined by the traditional classification systems with yes or no in terms of production process (NAICS) or major profit resource (ICB). Based on the sample firms, the authors proposed a four-layer hierarchical taxonomy framework that quantitatively reveals the inherent contradictory relationships between firms, which the authors defined as competition vs consistency. The proposed taxonomy framework is sufficiently flexible to accommodate complex relationships between firms, and it is also adaptable to new information. Under both the competition and consistency categories in the taxonomy model, more detailed subcategories are further coded into two more layers quantitatively to represent the firms' nuanced relationships.
Originality/value
This study provides a novel atheoretical approach to reveal complex firm relationships utilizing narrative text data gathered from news media. The framework of the firm relationship taxonomy constructed in this study provides an alternative and supplementary approach to the classical industry classification systems that can quantitatively specify comprehensive and dynamic connections between firms.
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Ziming Zeng, Zhi Zhou and Xiangming Mu
This paper aims to investigate the relationship between sentiment and review helpfulness and develop a method to fully use sentiment features in review helpfulness assessment. In…
Abstract
Purpose
This paper aims to investigate the relationship between sentiment and review helpfulness and develop a method to fully use sentiment features in review helpfulness assessment. In addition, this paper explores whether product type influences evaluating review helpfulness.
Design/methodology/approach
First, a high-quality data set with a manually coded helpfulness score was constructed. Second, detailed research question methods were conducted. Finally, methods were applied to the data set to extract information gain and sentiment scores. Gradient boosting and random forest methods were used to classify the data set with these features through recall, precision and F-measure to understand the research questions.
Findings
Review sentiment has a deep relationship with review helpfulness, and it can be a strong predictor of review helpfulness by refining it into more detailed scores; a combination of sentiment scores and information gain works very well on classification for two product types. Product type does not show a significant influence on helpfulness assessment.
Originality/value
This paper provides a different perspective for measuring review sentiment by clarifying the relationship between sentiment and review helpfulness, analysing the role of product type in review helpfulness assessment, and proposing a high-value feature combination. In addition, the author believes that the assessment method can be effectively applied to practical works.
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Kai-di Liu, Duo-Gui Yang, Guoliang Yang and Zhi-Tian Zhou
This paper aims to investigate the situation and evolution of sustainability performance in China.
Abstract
Purpose
This paper aims to investigate the situation and evolution of sustainability performance in China.
Design/methodology/approach
This paper adopts the global Malmquist-Luenberger (GML) productivity index based on data envelopment analysis and Tobit regression for analysis.
Findings
The results indicate the following: China’s sustainability performance has been improving since 2005 and is closely related to the national development strategy and supportive policy; regional gaps in sustainability are a prominent problem represented by the fact that South Central China is becoming a sustainability collapse zone; interprovincial heterogeneity is evident with the varying development speed and conditions; and the level of sustainability performance has a significantly positive correlation with the urbanization rate, investment completed in the treatment of industrial pollution, government appropriation for education and per capita area of paved roads, but it has a negative correlation with the possession of private vehicles.
Originality/value
As an application, this study assessing the GML productivity index of 30 provinces in China from 2005 to 2015 and analyse the sustainability performance on three regional levels (i.e. country level, regional level and provincial level). Tobit regression is also applied to recognize the factors related to the GML index with the results taken as references for policy suggestions. The results have implications for a comprehensive understanding of China's sustainability performance and policymaking in this field.
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Fang Liu, Zhongwei Duan, Runze Gong, Jiacheng Zhou, Zhi Wu and Nu Yan
Ball grid array (BGA) package is prone to failure issues in a thermal vibration-coupled environment, such as deformation and fracture of solder joints. To predict the minimum…
Abstract
Purpose
Ball grid array (BGA) package is prone to failure issues in a thermal vibration-coupled environment, such as deformation and fracture of solder joints. To predict the minimum equivalent stress of solder joints more accurately and optimize the solder joint structure, this paper aims to compare the machine learning method with response surface methodology (RSM).
Design/methodology/approach
This paper introduced a machine learning algorithm using Grey Wolf Optimization (GWO) Support Vector Regression (SVR) to optimize solder joint parameters. The solder joint height, spacing, solder pad diameter and thickness were the design variables, and minimizing the equivalent stress of solder joint was the optimization objective. The three dimensional finite element model of the printed circuit board assembly was verified by a modal experiment, and simulations were conducted for 25 groups of models with different parameter combinations. The simulation results were employed to train GWO-SVR to build a mathematical model and were analyzed using RSM to obtain a regression equation. Finally, GWO optimized these two methods.
Findings
The results show that the optimization results of GWO-SVR are closer to the simulation results than those of RSM. The minimum equivalent stress is decreased by 8.528% that of the original solution.
Originality/value
This study demonstrates that GWO-SVR is more precise and effective than RSM in optimizing the design of solder joints.
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Dina Hosam Gabr and Mona A. Elbannan
This paper aims to providea comprehensive review of the concepts and definitions of green finance, and the importance of “green” impact investments today. The core challenge in…
Abstract
Purpose
This paper aims to providea comprehensive review of the concepts and definitions of green finance, and the importance of “green” impact investments today. The core challenge in combating climate change is reducing and controlling greenhouse gas emissions; therefore, this study explores the solutions green finance provides emphasizing their impact on the environment and firms' financial performance. With increasing attention to the concept of green finance, multiple forms of green financial tools have come to fruition; the most prominent are green bonds.
Design/methodology/approach
This paper compiles a comprehensive green bond dataset, presenting a statistical study of the evolution of the green bonds market from its first appearance in 2006 until 2021.
Findings
The green bond market has seen massive growth over the years reaching $1651.92bn as of 2021. Findings show that green bonds are working towards shifting from high carbon-emitting energy to renewable energy, which is vital to economic development and growth. In congruence, green bonds are aligned with the United Nation's sustainable development goals (SDGs) amounting to $550bn for 2020, with the five most covered SDGs amounting to over 60%.
Originality/value
With growing worldwide concern for global warming, green finance became the fuel that pushes the world to act in combating and mitigating climate change. Coupled with adopting the Paris Agreement and the SDGs, Green finance became a vital tool in creating a pathway to sustainable development, as it connects the financial world with environmental and societal benefits.
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Ke Gao, Xiaoqin Zhou, Rongqi Wang, Mingxu Fan and Haochen Han
Compared with the high stiffness of traditional CNC machine tools, the structural stiffness of industrial robots is usually less than 1 N/µm. Chatter not only affects the quality…
Abstract
Purpose
Compared with the high stiffness of traditional CNC machine tools, the structural stiffness of industrial robots is usually less than 1 N/µm. Chatter not only affects the quality of robotic milling but also reduces the accuracy of the milling process. The purpose of this paper is to reduce chatter in the robotic machining process.
Design/methodology/approach
First, the mode coupling chatter mechanism is analyzed. Then the milling force model and the principal stiffness model are established. Finally, the robot milling stability optimization method is proposed. The method considered functional redundancies, and a new robot milling stability index is proposed to improve the quality of milling operations.
Findings
The experimental results prove a significant reduction in force fluctuations and surface roughness after using the proposed robotic milling stability optimization method.
Originality/value
In this paper, a new robot milling stability index and a new robot milling stability optimization method are proposed. This method can significantly increase the milling stability and improve the milling quality, which can be widely used in the industry.
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The purpose of this paper is to present the Switched Inductor Z-Source Inverter (SLZSI) topology for three-phase on-line uninterruptible power supply (UPS) by employing third…
Abstract
Purpose
The purpose of this paper is to present the Switched Inductor Z-Source Inverter (SLZSI) topology for three-phase on-line uninterruptible power supply (UPS) by employing third harmonic injected maximum constant boost pulse width modulation (PWM) control. Conventional UPS consists of step-up transformer or boost chopper along with voltage source inverter (VSI) which reduces the efficiency and increases energy conversion cost. The proposed three-phase UPS by using SLZSI has the voltage boost capability through shoot through zero state which is not available in traditional VSI and current source inverter.
Design/methodology/approach
Performance of three-phase on-line UPS based on ZLZSI by using third harmonic injected maximum constant boost PWM control is analyzed and evaluated in MATLAB/Simulink software and the results are compared with Z-source inverter (ZSI) fed UPS. Experimental results are presented for the validation of the simulation and theoretical analysis.
Findings
The output voltages, currents, THD values, voltage stress and efficiencies for different loading condition are determined and compared with the theoretical values and UPS with ZSI. The experimental results validate the theoretical and simulation results.
Originality/value
Compared with the traditional ZSI, the SLZSI provides high-voltage boost inversion ability with a very short shoot through zero state. This proposed UPS by using SLZSI increases the efficiency with less number of components, reduces the harmonics, increases the voltage gain and reduces the voltage stress.
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The study's objectives are to conduct a comprehensive review of existing knowledge, thoroughly understand the present state of green finance, identify emerging research trends…
Abstract
Purpose
The study's objectives are to conduct a comprehensive review of existing knowledge, thoroughly understand the present state of green finance, identify emerging research trends, perform content analysis and offer valuable guidance for advancing this field.
Design/methodology/approach
Data has been collected by selecting highly indexed databases, Scopus and Web of Science. These databases are well-known repositories of academic papers, journals and other scholarly publications related to various fields of study. This research uses the PRISMA methodology for conducting a structured literature review and employs a bibliometric approach to summarize the findings of the previous studies. “R” studio and Biblioshiny are used to clean the data and visualize the results. The TCCM framework is utilized to propose potential avenues for future research in the domain of green finance.
Findings
The research uncovers the potential areas in the domain of green finance for future work, encompassing green bonds, the green economy, connectivity, forces, constraints and sustainable development. Furthermore, this process enhances the theoretical underpinnings of scholarly investigations within the discipline by succinctly synthesizing and evaluating preexisting literature. This contribution could facilitate more informed and focused research endeavors in green finance.
Practical implications
The research findings have practical implications for researchers, practitioners, regulators, legislators, issuers and investors involved in green finance. The results can take initiatives to improve practices related to issuing and pricing green financial products and enhance the understanding of interconnectedness within the field.
Originality/value
This ground-breaking research sheds light on various emerging areas by taking a new approach, including the most widely read articles, authors and journals and the broader conceptual and intellectual framework. That includes finding and expanding original research streams, summarizing the most seminal works, and suggesting new research pathways.
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Pengpeng Cheng, Daoling Chen and Jianping Wang
For comfort evaluation of underwear pressure, this paper proposes an improved GA algorithm to optimize the weight and threshold of BP neural network, namely PSO-GA-BP neural…
Abstract
Purpose
For comfort evaluation of underwear pressure, this paper proposes an improved GA algorithm to optimize the weight and threshold of BP neural network, namely PSO-GA-BP neural network prediction model.
Design/methodology/approach
The objective parameters of underwear, body shape data, skin deformation and other data are selected for simulation experiments to predict the objective pressure and subjective evaluation in dynamic and static state. Compared with the prediction results of BP neural network prediction model, GA-BP neural network prediction model and PSO-BP neural network prediction model, the performance of each prediction model is verified.
Findings
The results show that the BP neural network model optimized by PSO-GA algorithm can accelerate the convergence speed of the neural network and improve the prediction accuracy of underwear pressure.
Originality/value
PSO-GA-BP model provides data support for underwear design, production and processing and has guiding significance for consumers to choose underwear.
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Li DING, Tieling XING and Guoqiang CHEN
Five different structural reactive dyes (Reactive Brilliant Blue K-3R, Everacion Blue H-ERD, Moderzol Blue FBR, Atuzol Black B and Moderzol Blue HEGN) were treated with laccase…
Abstract
Five different structural reactive dyes (Reactive Brilliant Blue K-3R, Everacion Blue H-ERD, Moderzol Blue FBR, Atuzol Black B and Moderzol Blue HEGN) were treated with laccase (Denilite II US) in order to determine the optimum decolouration conditions. The experiments showed that laccase had distinct decolouration effects on these five dyes. Under optimum conditions, the colour removal rates of Everacion Blue H-ERD and Moderzol Blue HEGN were over 90%. Furthermore, the effects of different additives, such as acid ion, metal ion, and surfactants on the decolouration rate of Reactive Brilliant Blue K-3R were discussed. The results show that the decolouration rate is significantly promoted through the addition of Cu2+ and Al3+, while it is inactivated with Fe2+ and ion surfactants. Moreover, the COD removal rates of the five dyes are more than 75%.