Yufei Zhang, Youliang Li and Qiaoling Hu
The purpose of this paper is to fabricate colorless cotton fabrics with good antibacterial activity and durability.
Abstract
Purpose
The purpose of this paper is to fabricate colorless cotton fabrics with good antibacterial activity and durability.
Design/methodology/approach
Chitosan (CS) based silver nanoparticles (AgNPs) were formed in CS solutions as the antibacterial agent. The reducing agent was sodium borohyride. The concentrations of the CS solutions ranged from 0.1 to 1 percent (w/v). Cotton fabrics were impregnated by these CS/AgNPs solutions.
Findings
All of these fabrics exhibited superior antibacterial activities. The antibacterial activity still showed great efficiency even after 81 home launderings. Moreover, the results of color change and whiteness indicated that the cotton fabrics treated by CS/AgNPs complex with higher CS concentration had less color change compared with other samples.
Practical implications
Fabrics treated by this method could reduce the brown color brought by AgNPs. The paper also suggests that cotton fabrics treated by AgNPs formed in a relatively higher CS concentration not only had good antibacterial activity but also were colorless.
Originality/value
The influence of CS ratio in CS/AgNPs complexes on the antibacterial activity and color of cotton fabrics was studied, which has been rarely reported in previous papers. The fabrics prepared by this method are promising candidates for a wide range of general applications.
Details
Keywords
The purpose of this paper is to investigate whether and how affiliation with the government-controlled business association, namely, China Federation of Industry and Commerce…
Abstract
Purpose
The purpose of this paper is to investigate whether and how affiliation with the government-controlled business association, namely, China Federation of Industry and Commerce (CFIC), affects corporate philanthropy in an emerging market.
Design/methodology/approach
Through an analysis of survey data gathered from Chinese private firms, this paper conducts multiple regressions to examine the impact of the CFIC membership on corporate philanthropy.
Findings
Empirical results show that the CFIC membership of private entrepreneurs is significantly positively associated with corporate philanthropy. Moreover, this study finds that the provincial marketization level and the firm Communist Party branch attenuate the positive association between CFIC membership and corporate philanthropy, indicating that the effect of CFIC on corporate philanthropy is more pronounced in regions with lower marketization level and firms without Communist Party branch. The findings are robust to various alternate measures of corporate philanthropy and remain valid after controlling for potential endogeneity.
Practical implications
Firms will be more active in corporate philanthropy to respond to the government’s governance appeal when they join the CFIC. This highlights the implications of political connections and in particular on the value of government-controlled business associations in the Chinese business world.
Originality/value
This study extends the literature on the determinants of corporate philanthropy and deepens the theoretical understanding of the governance role of business association with Chinese characteristics.
Details
Keywords
Ming Huang, Zhiqiang Zhang, Peizi Wei, Fei Liu and Youliang Ding
In order to make sure of the safety of a long-span suspension bridge under earthquake action, this paper aims to study the traveling wave effect of the bridge under multi-support…
Abstract
Purpose
In order to make sure of the safety of a long-span suspension bridge under earthquake action, this paper aims to study the traveling wave effect of the bridge under multi-support excitation and optimize the semi-active control schemes based on magneto-rheological (MR) dampers considering reference index as well as economical efficiency.
Design/methodology/approach
The finite element model of the long-span suspension bridge is established in MATLAB and ANSYS software, which includes different input currents and semi-active control conditions. Six apparent wave velocities are used to conduct non-linear time history analysis in order to consider the seismic response influence in primary members under traveling wave effect. The parameters α and β, which are key parameters of classical linear optimal control algorithm, are optimized and analyzed taking into account five different combinations to obtain the optimal control scheme.
Findings
When the apparent wave velocity is relatively small, the influence on the structural response is oscillatory. Along with the increase of the apparent wave velocity, the structural response is gradually approaching the response under uniform excitation. Semi-active control strategy based on MR dampers not only restrains the top displacement of main towers and relative displacement between towers and girders, but also affects the control effect of internal forces. For classical linear optimal control algorithm, the values of two parameters (α and β) are 100 and 8 × 10–6 considering the optimal control effect and economical efficiency.
Originality/value
The emphasis of this study is the traveling wave effect of the triple-tower suspension bridge under multi-support excitation. Meanwhile, the optimized parameters of semi-active control schemes using MR dampers have been obtained, providing relevant references in improving the seismic performance of three-tower suspension bridge.
Details
Keywords
Youliang Huang, Haifeng Liu, Wee Keong Ng, Wenfeng Lu, Bin Song and Xiang Li
Product configuration is considered as one of the most successful applications of knowledge‐based approaches in the past decade. Knowledge‐based configurations can be classified…
Abstract
Purpose
Product configuration is considered as one of the most successful applications of knowledge‐based approaches in the past decade. Knowledge‐based configurations can be classified into three different approaches, namely, rule‐based, model‐based and case‐based approaches. Past research has mainly focused on the development of reasoning techniques for mapping requirements to configurations. Despite the success of certain conventional approaches, the acquisition of configuration knowledge is usually done manually. This paper aims to explore fundamental issues in product configuration system, and propose a novel approach based on data mining techniques to automatically discover configuration knowledge in constraint‐based configurations.
Design/methodology/approach
Given a set of product data comprising product requirements specification and configuration information, the paper adopted an association rule mining algorithm to discover useful patterns between requirement specification and product components, as well as the correlation among product components. A configuration was developed which takes XML‐based requirement specification as input and bases on a constraint knowledge base to produce product configuration as output consisting of a list of selected components and the structure and topology of the product. Three modules are developed, namely product data modelling, configuration knowledge generation and product configuration generation module. The proposed approach is implemented in the configuration knowledge generation module. The configuration generation module realizes a resolution of constraint satisfaction problem to generate the output configuration.
Findings
The significance and effectiveness of the proposed approach is demonstrated by its incorporation in our configuration system prototype. A case study was conducted and experimental results show that the approach is promising in finding constraints with given sufficient data.
Originality/value
Novel knowledge generation approach is proposed to assist constraint generation for Constraint‐based product configuration system.
Details
Keywords
Feng Zhang, Youliang Wei and Tao Feng
GraphQL is a new Open API specification that allows clients to send queries and obtain data flexibly according to their needs. However, a high-complexity GraphQL query may lead to…
Abstract
Purpose
GraphQL is a new Open API specification that allows clients to send queries and obtain data flexibly according to their needs. However, a high-complexity GraphQL query may lead to an excessive data volume of the query result, which causes problems such as resource overload of the API server. Therefore, this paper aims to address this issue by predicting the response data volume of a GraphQL query statement.
Design/methodology/approach
This paper proposes a GraphQL response data volume prediction approach based on Code2Vec and AutoML. First, a GraphQL query statement is transformed into a path collection of an abstract syntax tree based on the idea of Code2Vec, and then the query is aggregated into a vector with the fixed length. Finally, the response result data volume is predicted by a fully connected neural network. To further improve the prediction accuracy, the prediction results of embedded features are combined with the field features and summary features of the query statement to predict the final response data volume by the AutoML model.
Findings
Experiments on two public GraphQL API data sets, GitHub and Yelp, show that the accuracy of the proposed approach is 15.85% and 50.31% higher than existing GraphQL response volume prediction approaches based on machine learning techniques, respectively.
Originality/value
This paper proposes an approach that combines Code2Vec and AutoML for GraphQL query response data volume prediction with higher accuracy.
Details
Keywords
Ilker Murat Ar, Coşkun Hamzaçebi and Birdogan Baki
The purpose of this paper is to explore the teaching performance of Turkish Business Schools (BSs). It also aims to determine the degree of importance of factors affecting the…
Abstract
Purpose
The purpose of this paper is to explore the teaching performance of Turkish Business Schools (BSs). It also aims to determine the degree of importance of factors affecting the teaching performance of Turkish BSs. The final objective is to test the functionality and applicability of the model.
Design/methodology/approach
This study presents a ranking approach based on grey relational analysis (GRA). While evaluating the BSs, data were collected for 19 Turkish BSs in terms of five main criteria such as OSS score; Number of faculty members; Number of students per faculty member; the mean of KPSS score; and the standard deviation of KPSS score. In the analysis, three weighted methods were integrated into the GRA in order to weight the criteria.
Findings
According to this result, the main factor influencing the teaching performance of Turkish BSs is the OSS score. This study can also confirm that the results obtained from the ranking orders using the proposed methods are reliable and these results can help decision makers to identify the best alternative.
Research limitations/implications
In order to provide benchmarking data more effectively, in future, it would be helpful to collect data from both foundation and state universities with a research focus. Moreover, as an interesting suggestion for future research, fuzzy environment may be further integrated into the framework of GRA.
Originality/value
In contrast to prior research, this study makes comparisons based on the scores of national exams instead of different bibliometric indicators. Furthermore, there are no studies which have used GRA and these weighted methods as combined in education sector.
Details
Keywords
Outlines the history of accounting in China and reviews the literature published in English on the full range of Chinese accounting issues. Summarizes the contents of three books…
Abstract
Outlines the history of accounting in China and reviews the literature published in English on the full range of Chinese accounting issues. Summarizes the contents of three books, refers to sections in other books and analyses journal articles by period, journal, research topic and research method. Argues that this accounting research has historical, academic and practical value,believes it will continue to improve and calls for greater use of more rigid research methodologies in this area.
Details
Keywords
Reza Kiani Mavi, Neda Kiani Mavi, Reza Farzipoor Saen and Mark Goh
Despite unanimity in the literature that eco-innovation (EI) leads to sustainable development, evidence remains limited on measuring EI efficiency with the Malmquist productivity…
Abstract
Purpose
Despite unanimity in the literature that eco-innovation (EI) leads to sustainable development, evidence remains limited on measuring EI efficiency with the Malmquist productivity index (MPI). In conventional data envelopment analysis (DEA) models, decision-making units (DMUs) are inclined to assign more favorable weights, even zero, to the inputs and outputs to maximize their own efficiency. This paper aims to overcome this shortcoming by developing a common set of weights (CSW).
Design/methodology/approach
Using goal programming, this study develops a CSW model to evaluate the EI efficiency of the organization for economic co-operation and development (OECD) countries and track their changes with MPI during 2010–2018.
Findings
Achieving a complete ranking of DMUs, findings show the higher discrimination power of the proposed CSW compared with the original DEA models. Furthermore, results reveal that Iceland, Latvia and Luxembourg are the only OECD countries that have incessantly improved their EI productivity (MPI > 1) from 2010 to 2018. On the other hand, Japan is the OECD country that has experienced the highest yearly EI efficiency during 2010–2018. This paper also found that Iceland has the highest MPI over 2010–2018.
Practical implications
More investment in environmental research and development (R&D) projects instead of generic R&D enables OECD members to realize more opportunities for sustainable development through minimizing energy use and environmental pollution in any form of waste and greenhouse gas emissions.
Originality/value
In addition to developing a novel common weights model for DEA-MPI to measure and evaluate the EI of OECD countries, this paper develops a CSW model by including the undesirable outputs for EI analysis.
Details
Keywords
Shaohua Yang, Murtaza Hussain, R.M. Ammar Zahid and Umer Sahil Maqsood
In the rapidly evolving digital economy, businesses face formidable pressures to maintain their competitive standing, prompting a surge of interest in the intersection of…
Abstract
Purpose
In the rapidly evolving digital economy, businesses face formidable pressures to maintain their competitive standing, prompting a surge of interest in the intersection of artificial intelligence (AI) and digital transformation (DT). This study aims to assess the impact of AI technologies on corporate DT by scrutinizing 3,602 firm-year observations listed on the Shanghai and Shenzhen stock exchanges. The research delves into the extent to which investments in AI drive DT, while also investigating how this relationship varies based on firms' ownership structure.
Design/methodology/approach
To explore the influence of AI technologies on corporate DT, the research employs robust quantitative methodologies. Notably, the study employs multiple validation techniques, including two-stage least squares (2SLS), propensity score matching and an instrumental variable approach, to ensure the credibility of its primary findings.
Findings
The investigation provides clear evidence that AI technologies can accelerate the pace of corporate DT. Firms strategically investing in AI technologies experience faster DT enabled by the automation of operational processes and enhanced data-driven decision-making abilities conferred by AI. Our findings confirm that AI integration has a significant positive impact in propelling DT across the firms studied. Interestingly, the study uncovers a significant divergence in the impact of AI on DT, contingent upon firms' ownership structure. State-owned enterprises (SOEs) exhibit a lesser degree of DT following AI integration compared to privately owned non-SOEs.
Originality/value
This study contributes to the burgeoning literature at the nexus of AI and DT by offering empirical evidence of the nexus between AI technologies and corporate DT. The investigation’s examination of the nuanced relationship between AI implementation, ownership structure and DT outcomes provides novel insights into the implications of AI in the diverse business contexts. Moreover, the research underscores the policy significance of supporting SOEs in their DT endeavors to prevent their potential lag in the digital economy. Overall, this study accentuates the imperative for businesses to strategically embrace AI technologies as a means to bolster their competitive edge in the contemporary digital landscape.