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1 – 10 of 57Baojun Ma, Jingxia He, Hui Yuan, Jian Zhang and Chi Zhang
Corporate social responsibility (CSR) is significant in the financial market. Despite plenty of existing research on CSR, few studies have quantified the fine-grained aspects of…
Abstract
Purpose
Corporate social responsibility (CSR) is significant in the financial market. Despite plenty of existing research on CSR, few studies have quantified the fine-grained aspects of CSR and examined how diverse CSR aspects are associated with firms' trade credit. Based on the released CSR reports, this paper strives to measure the CSR fulfillment of firms and examine the relationships between CSR and trade credit in terms of textual features presented in these reports.
Design/methodology/approach
This research proposes a natural language processing-based framework to extract the overall readability and the sentiment of fine-grained aspects from CSR reports, which can signal the performance of firms' CSR in diverse aspects. Furthermore, this paper explores how the textual features are associated with trade credit through partial dependence plots (PDPs), and PDPs can generate both linear and nonlinear relationships.
Findings
The study’s results reveal that the overall readability of the reports is positively associated with trade credit, while the performance of the fine-grained CSR aspects mentioned in the CSR reports matters differently. The performance of the environment has a positive impact on trade credit; the performance of creditors, suppliers and information disclosure, shows a U-shaped influence on trade credit; while the performance of the government and customers is negatively associated with trade credit.
Originality/value
This study expands the scope of research on CSR and trade credit by investigating fine-grained aspects covered in CSR reports. It also offers some managerial implications in the allocation of CSR resources and the presentation of CSR reports.
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Yong Ding, Peixiong Huang, Hai Liang, Fang Yuan and Huiyong Wang
Recently, deep learning (DL) has been widely applied in various aspects of human endeavors. However, studies have shown that DL models may also be a primary cause of data leakage…
Abstract
Purpose
Recently, deep learning (DL) has been widely applied in various aspects of human endeavors. However, studies have shown that DL models may also be a primary cause of data leakage, which raises new data privacy concerns. Membership inference attacks (MIAs) are prominent threats to user privacy from DL model training data, as attackers investigate whether specific data samples exist in the training data of a target model. Therefore, the aim of this study is to develop a method for defending against MIAs and protecting data privacy.
Design/methodology/approach
One possible solution is to propose an MIA defense method that involves adjusting the model’s output by mapping the output to a distribution with equal probability density. This approach effectively preserves the accuracy of classification predictions while simultaneously preventing attackers from identifying the training data.
Findings
Experiments demonstrate that the proposed defense method is effective in reducing the classification accuracy of MIAs to below 50%. Because MIAs are viewed as a binary classification model, the proposed method effectively prevents privacy leakage and improves data privacy protection.
Research limitations/implications
The method is only designed to defend against MIA in black-box classification models.
Originality/value
The proposed MIA defense method is effective and has a low cost. Therefore, the method enables us to protect data privacy without incurring significant additional expenses.
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Wang Zengqing, Zheng Yu Xie and Jiang Yiling
With the rapid development of railway-intelligent video technology, scene understanding is becoming more and more important. Semantic segmentation is a major part of scene…
Abstract
Purpose
With the rapid development of railway-intelligent video technology, scene understanding is becoming more and more important. Semantic segmentation is a major part of scene understanding. There is an urgent need for an algorithm with high accuracy and real-time to meet the current railway requirements for railway identification. In response to this demand, this paper aims to explore a variety of models, accurately locate and segment important railway signs based on the improved SegNeXt algorithm, supplement the railway safety protection system and improve the intelligent level of railway safety protection.
Design/methodology/approach
This paper studies the performance of existing models on RailSem19 and explores the defects of each model through performance so as to further explore an algorithm model dedicated to railway semantic segmentation. In this paper, the authors explore the optimal solution of SegNeXt model for railway scenes and achieve the purpose of this paper by improving the encoder and decoder structure.
Findings
This paper proposes an improved SegNeXt algorithm: first, it explores the performance of various models on railways, studies the problems of semantic segmentation on railways and then analyzes the specific problems. On the basis of retaining the original excellent MSCAN encoder of SegNeXt, multiscale information fusion is used to further extract detailed features such as multihead attention and mask, solving the problem of inaccurate segmentation of current objects by the original SegNeXt algorithm. The improved algorithm is of great significance for the segmentation and recognition of railway signs.
Research limitations/implications
The model constructed in this paper has advantages in the feature segmentation of distant small objects, but it still has the problem of segmentation fracture for the railway, which is not completely segmented. In addition, in the throat area, due to the complexity of the railway, the segmentation results are not accurate.
Social implications
The identification and segmentation of railway signs based on the improved SegNeXt algorithm in this paper is of great significance for the understanding of existing railway scenes, which can greatly improve the classification and recognition ability of railway small object features and can greatly improve the degree of railway security.
Originality/value
This article introduces an enhanced version of the SegNeXt algorithm, which aims to improve the accuracy of semantic segmentation on railways. The study begins by investigating the performance of different models in railway scenarios and identifying the challenges associated with semantic segmentation on this particular domain. To address these challenges, the proposed approach builds upon the strong foundation of the original SegNeXt algorithm, leveraging techniques such as multi-scale information fusion, multi-head attention, and masking to extract finer details and enhance feature representation. By doing so, the improved algorithm effectively resolves the issue of inaccurate object segmentation encountered in the original SegNeXt algorithm. This advancement holds significant importance for the accurate recognition and segmentation of railway signage.
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Xiaogang Cao, Hui Wen and Bowei Cao
In this paper, the authors study the production and pricing decisions of a remanufacturing supply chain composed of a supplier, an assembler and a remanufacturer, in which the…
Abstract
Purpose
In this paper, the authors study the production and pricing decisions of a remanufacturing supply chain composed of a supplier, an assembler and a remanufacturer, in which the remanufacturing of components requires patent licensing from the supplier.
Design/methodology/approach
The authors consider three different models with government subsidy for remanufacturing: (1) no government subsidies; (2) the government subsidizes the remanufacturing behavior of the supplier and (3) the government subsidizes the remanufacturing behavior of the remanufacturer and use the Stackelberg game model to solve and analyze the equilibrium wholesale prices of components and the equilibrium outputs of new and remanufactured products under three subsidy modes.
Findings
The results show that the equilibrium wholesale prices of two kinds of components decrease with the unit patent licensing fee and the unit government subsidy, and the equilibrium quantity of the remanufactured products under the three modes is obviously higher than that of the new products.
Originality/value
Finally through numerical simulation, it is found that the equilibrium profits of the supplier, the manufacturer and the supply chain increase monotonously in relation to the unit government subsidy, while the optimal profit of the assembler in relation to the unit government subsidy tends to decrease first and then increase.
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This paper summarizes the severity of global warming, collaboration and endeavor within international government and the trend of international development for “energy-saving and…
Abstract
This paper summarizes the severity of global warming, collaboration and endeavor within international government and the trend of international development for “energy-saving and emission reduction.” The Chinese government is enduring high pressure under the environment of “global warming” and “energy-saving and emission reduction” and it has made a policy for “energy-saving and emission reduction.” Based on this, we analyzed the possibility and feasibility for our logistics to “energy-saving and emission reduction,” then propose some solutions for our logistics industry to development and “energy-saving and emission reduction.”
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Shukuan Zhao, Xueyuan Fan, Dong Shao and Shuang Wang
This study aims to investigate the impact of supply chain concentration (SCC) on corporate research and development (R&D) investment and determine the moderating roles of industry…
Abstract
Purpose
This study aims to investigate the impact of supply chain concentration (SCC) on corporate research and development (R&D) investment and determine the moderating roles of industry concentration and financing constraints on the relationship between SCC and R&D investment.
Design/methodology/approach
The study collected data from Chinese listed companies, used the fixed effects model to test the research hypotheses and further used the two-stage Heckman test and propensity score matching (PSM) to address potential endogeneity issues.
Findings
The result reveals a negative impact of SCC on corporate R&D investment. In addition, industry concentration mitigates the negative impact of SCC on corporate R&D investment, but financing constraints strengthen the negative impact.
Originality/value
This study introduces the concept of SCC and empirically tests its effect on R&D investment, further explaining the lack of corporate innovation. This study inspires companies to strengthen SC management and weigh the level of SCC with environmental factors.
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Yuanyuan Lan, Yuhuan Xia, Shuang Li, Wen Wu, Jiaqi Hui and Hui Deng
The purpose of this study is to explore the relationship between supervisor and coworkers’ workplace incivility and newcomer proactive behaviors. Drawing on conservation of…
Abstract
Purpose
The purpose of this study is to explore the relationship between supervisor and coworkers’ workplace incivility and newcomer proactive behaviors. Drawing on conservation of resources (COR) theory, the authors examined resource depletion as a mediator and newcomer proactive personality, as well as their current organizational tenure as moderators of the relationship between workplace incivility toward newcomers and their proactive behaviors.
Design/methodology/approach
A time-lagged research design was used to test hypotheses with data covering 322 newcomers and their immediate supervisors in two subsidiaries of a large food processing company in China. Regression analysis using the PROCESS macro in SPSS is used to test the hypotheses.
Findings
The results show that workplace incivility toward newcomers is negatively related to their proactive behaviors. This relationship is mediated by resource depletion. Furthermore, newcomers’ proactive personality moderates the relationship between workplace incivility and resource depletion. Moreover, both the direct effect of workplace incivility on resource depletion and its indirect effect on newcomer proactive behaviors are moderated by the combination of newcomer proactive personality and their current organizational tenure.
Originality/value
Drawing on COR theory, a theoretical framework is constructed that specifies the process through which workplace incivility affects proactive behaviors to expand collective understandings of workplace incivility in the newcomer context. Furthermore, the boundary conditions of the underlying process are investigated, which further enhances the contribution of this paper to the extant literature on workplace incivility.
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Aibing Ji, Hui Liu, Hong-jie Qiu and Haobo Lin
– The purpose of this paper is to build a novel data envelopment analysis (DEA) model to evaluate the efficiencies of decision making units (DMUs).
Abstract
Purpose
The purpose of this paper is to build a novel data envelopment analysis (DEA) model to evaluate the efficiencies of decision making units (DMUs).
Design/methodology/approach
Using the Choquet integrals as aggregating tool, the authors give a novel DEA model to evaluate the efficiencies of DMUs.
Findings
It extends DEA model to evaluate the DMU with interactive variables (inputs or outputs), the classical DEA model is a special form. At last, the authors use the numerical examples to illustrate the performance of the proposed model.
Practical implications
The proposed DEA model can be used to evaluate the efficiency of the DMUs with multiple interactive inputs and outputs.
Originality/value
This paper introduce a new DEA model to evaluate the DMU with interactive variables (inputs or outputs), the classical DEA model is a special form.
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Alina Steblyanskaya, Mingye Ai, Artem Denisov, Olga Efimova and Maksim Rybachuk
Understanding China's carbon dioxide (
Abstract
Purpose
Understanding China's carbon dioxide (
Design/methodology/approach
In this study using the input and output (IO) table's data for the selected years, the authors found the volume of
Findings
Results show that in the industries with a huge volume of
Originality/value
“Transport, storage, and postal services” and “Smelting and processing of metals” industries in China has the second place concerning emissions, but over the past period, emissions have been sufficiently reduced. “Construction” industry produces a lot of emissions, but this industry does not carry products characterized by large emissions from other industries. Authors can observe that Jiangsu produces a lot of
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Sigit and Rachel Shannon Twigivanya
This paper examines Malaysia's perception of China following the Asian Financial Crisis. The Asian Financial Crisis, which occurred in 1997, resulted in a contraction in…
Abstract
This paper examines Malaysia's perception of China following the Asian Financial Crisis. The Asian Financial Crisis, which occurred in 1997, resulted in a contraction in Malaysia's GDP, which resulted in increased unemployment in Malaysia. China is a rising economy. Several bilateral visits and trade missions meet both states to achieve an advantageous economic position. Malaysia's decision to rely on China despite historical events that had sparked tensions between the two countries. Despite Malaysia's economic downturn, the country is taking swift action to address the issue. During the crisis, Malaysia viewed Western countries as irresponsible and allowed the situation to deteriorate, which later became the reason for Malaysia's relationship with China. The crisis, however, has influenced Malaysian Chinese businesses to improve their foreign policy and bilateral relations. This paper contends that Malaysia recognizes the importance of its bilateral relationship with China in stabilizing its economic development and social activity following the crisis.
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