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1 – 10 of 545Miao Ye, Lin Qiang Huang, Xiao Li Wang, Yong Wang, Qiu Xiang Jiang and Hong Bing Qiu
A cross-domain intelligent software-defined network (SDN) routing method based on a proposed multiagent deep reinforcement learning (MDRL) method is developed.
Abstract
Purpose
A cross-domain intelligent software-defined network (SDN) routing method based on a proposed multiagent deep reinforcement learning (MDRL) method is developed.
Design/methodology/approach
First, the network is divided into multiple subdomains managed by multiple local controllers, and the state information of each subdomain is flexibly obtained by the designed SDN multithreaded network measurement mechanism. Then, a cooperative communication module is designed to realize message transmission and message synchronization between the root and local controllers, and socket technology is used to ensure the reliability and stability of message transmission between multiple controllers to acquire global network state information in real time. Finally, after the optimal intradomain and interdomain routing paths are adaptively generated by the agents in the root and local controllers, a network traffic state prediction mechanism is designed to improve awareness of the cross-domain intelligent routing method and enable the generation of the optimal routing paths in the global network in real time.
Findings
Experimental results show that the proposed cross-domain intelligent routing method can significantly improve the network throughput and reduce the network delay and packet loss rate compared to those of the Dijkstra and open shortest path first (OSPF) routing methods.
Originality/value
Message transmission and message synchronization for multicontroller interdomain routing in SDN have long adaptation times and slow convergence speeds, coupled with the shortcomings of traditional interdomain routing methods, such as cumbersome configuration and inflexible acquisition of network state information. These drawbacks make it difficult to obtain global state information about the network, and the optimal routing decision cannot be made in real time, affecting network performance. This paper proposes a cross-domain intelligent SDN routing method based on a proposed MDRL method. First, the network is divided into multiple subdomains managed by multiple local controllers, and the state information of each subdomain is flexibly obtained by the designed SDN multithreaded network measurement mechanism. Then, a cooperative communication module is designed to realize message transmission and message synchronization between root and local controllers, and socket technology is used to ensure the reliability and stability of message transmission between multiple controllers to realize the real-time acquisition of global network state information. Finally, after the optimal intradomain and interdomain routing paths are adaptively generated by the agents in the root and local controllers, a prediction mechanism for the network traffic state is designed to improve awareness of the cross-domain intelligent routing method and enable the generation of the optimal routing paths in the global network in real time. Experimental results show that the proposed cross-domain intelligent routing method can significantly improve the network throughput and reduce the network delay and packet loss rate compared to those of the Dijkstra and OSPF routing methods.
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The business world today is witnessing ever-growing disruption. This study highlights corporate social responsibility (CSR) as an effective strategy for firms in disrupted…
Abstract
Purpose
The business world today is witnessing ever-growing disruption. This study highlights corporate social responsibility (CSR) as an effective strategy for firms in disrupted industries to consider in order to differentiate themselves and to increase their chance of survival facing disruption.
Design/methodology/approach
In this study, the authors test the hypotheses using a multilevel modeling (MLM) design to capture the group and intergroup effects at the industry level and at the firm level. The empirical analysis is based on a panel sample of 1,193 firms over the 10-year period from 2010 to 2019.
Findings
The empirical analysis indicates that CSR has a positive impact on corporate financial stability and the effect is especially significant for firms in disrupted industries. Further investigation suggests that this positive effect largely runs through traits of the social pillar, such as human rights, employee relations, customer protection, product responsibility and community impact. The results are robust after controlling for other firm-specific characteristics and after addressing endogeneity concerns.
Originality/value
This study examines whether, and through which channel, CSR helps enhance corporate financial stability and mitigate bankruptcy risk in disrupted industries. To the best of the authors' knowledge, this study is the first attempt to explore the use of CSR as an effective strategic response to disruption. Further analysis indicates that the social capital built through CSR plays an important role in helping enhance corporate financial stability.
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Adah-Kole Emmanuel Onjewu, Richard B. Nyuur, Salima Paul and Yong Wang
Although recent literature has examined diverse measures adopted by SMEs to navigate the COVID-19 turbulence, there is a shortage of evidence on how crisis-time strategy creation…
Abstract
Purpose
Although recent literature has examined diverse measures adopted by SMEs to navigate the COVID-19 turbulence, there is a shortage of evidence on how crisis-time strategy creation behaviour and digitalization activities increase (1) sales and (2) cash flow. Thus, predicated on a novel strategy creation perspective, this inquiry aims to investigate the crisis behaviour, sales and cash flow performance of 528 SMEs in Morocco.
Design/methodology/approach
Novel links between (1) aggregate wage cuts, (2) variable operating hours, (3) deferred payment to suppliers, (4) deferred payment to tax authorities and (5) sales performance are developed and tested. A further link between sales performance and cash flow is also examined and the analysis is conducted using a non-linear structural equation modelling technique.
Findings
While there is a significant association between strategy creation behaviours and sales performance, only variable operating hours have a positive effect. Also, sales performance increases cash flow and this relationship is substantially strengthened by e-commerce digitalization and innovation.
Originality/value
Theoretically, to the best of the authors’ knowledge, this is one of the first inquiries to espouse the strategy creation view to explain SMEs' crisis-time behaviour and digitalization. For practical purposes, to supplement Moroccan SMEs' propensity to seek tax deferrals, it is argued that debt and equity support measures are also needed to boost sales performance and cash flow.
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Victor Atiase, Yong Wang and Samia Mahmood
Training remains an important factor in developing the managerial effectiveness and capability of small and medium-sized enterprises (SMEs), yet there are concerns regarding the…
Abstract
Purpose
Training remains an important factor in developing the managerial effectiveness and capability of small and medium-sized enterprises (SMEs), yet there are concerns regarding the quality of training provided to SME managers in Ghana, hence the weak managerial capabilities observed in SME management. This study, therefore, examines the impact of managerial training on the effectiveness of SME managers in Ghana.
Design/methodology/approach
Drawing on the human capital theory (Becker, 1962; Rosen, 1977), this study employs the variance-based estimating technique, partial least square structural equation modelling (PLS-SEM) in estimating the effects of training on the managerial effectiveness of SME managers. Adopting a stratified random sampling technique, the study uses primary data collected from 506 SMEs in Ghana to test 4 hypothesised paths.
Findings
First, the model result indicates that training accessibility and training content are statistically significant in explaining managerial effectiveness at a 1% level. However, both training efficiency and training frequency are statistically insignificant in explaining managerial effectiveness in Ghana. Second, while the industry category is found to influence the relationship between training and managerial effectiveness, gender, manager's age and education are insignificant in explaining any effects.
Research limitations/implications
Though the sample size is large, the findings from this study could not be generalised to the whole of Ghana since it is regionally based. The study could benefit immensely from a triangulated method where a qualitative dimension could provide deeper insight into some of the findings in this study.
Originality/value
Studies of this nature focussing on the managerial effectiveness of SME managers in the Ghanaian context is rare. This is one of the few studies in the Ghanaian research context which focuses on the capability development approach in the delivery of managerial training to SMEs.
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Huiyu Cui, Honggang Guo, Jianzhou Wang and Yong Wang
With the rise in wine consumption, accurate wine price forecasts have significantly impacted restaurant and hotel purchasing decisions and inventory management. This study aims to…
Abstract
Purpose
With the rise in wine consumption, accurate wine price forecasts have significantly impacted restaurant and hotel purchasing decisions and inventory management. This study aims to develop a precise and effective wine price point and interval forecasting model.
Design/methodology/approach
The proposed forecast model uses an improved hybrid kernel extreme learning machine with an attention mechanism and a multi-objective swarm intelligent optimization algorithm to produce more accurate price estimates. To the best of the authors’ knowledge, this is the first attempt at applying artificial intelligence techniques to improve wine price prediction. Additionally, an effective method for predicting price intervals was constructed by leveraging the characteristics of the error distribution. This approach facilitates quantifying the uncertainty of wine price fluctuations, thus rendering decision-making by relevant practitioners more reliable and controllable.
Findings
The empirical findings indicated that the proposed forecast model provides accurate wine price predictions and reliable uncertainty analysis results. Compared with the benchmark models, the proposed model exhibited superiority in both one-step- and multi-step-ahead forecasts. Meanwhile, the model provides new evidence from artificial intelligence to explain wine prices and understand their driving factors.
Originality/value
This study is a pioneering attempt to evaluate the applicability and effectiveness of advanced artificial intelligence techniques in wine price forecasts. The proposed forecast model not only provides useful options for wine price forecasting but also introduces an innovative addition to existing forecasting research methods and literature.
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Hong-Feng Li, Jun Sun, Xiao-Yong Wang, Lei-Lei Xing and Guang-Zhu Zhang
The purpose of this paper is to add expanded perlite (EP) immobilized microorganisms that replace part of the standard sand in mortar to improve the self-healing ability of mortar…
Abstract
Purpose
The purpose of this paper is to add expanded perlite (EP) immobilized microorganisms that replace part of the standard sand in mortar to improve the self-healing ability of mortar cracks and reduce the water absorption of mortar after healing.
Design/methodology/approach
Bacillus pseudofirmus spores were immobilized with EP particles as self-healing agents. The effects of adding self-healing agents on the compressive strength of mortar specimens were observed. The ability of mortar specimens to heal cracks was evaluated using crack microscopic observation and water absorption experiments. The filler at the cracks was microscopically analyzed by scanning electron microscope and X-ray diffraction experiments.
Findings
First, the internal curing effect of EP promotes the hydration of cement in mortar, which generates more amount and denser crystal structure of Ca(OH)2 at mortar cracks and improves the self-healing ability of mortar. Second, the self-healing ability of mortar improves with the increase of self-healing agent admixture. Adding a self-healing agent of high admixture makes the planar undulation of calcite crystal accumulation at mortar cracks more significant. Finally, the initial crack widths that can be completely healed by adding EP and self-healing agents to the mortar are 200 µm and 600 µm, respectively.
Originality/value
The innovation points of this study are as follows. (1) The mechanism of the internal curing effect of EP particles on the self-healing ability of mortar cracks was revealed by crack microscopic observation tests and microscopic experiments. (2) The effect of different self-healing agent amounts on the self-healing ability of mortar cracks has been studied. (3) The effects of EP particles and self-healing agents on healing different initial widths were elucidated by crack microscopic observation tests.
Graphical abstract
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Yong Wang, Meijun Meng, Yang Li, Qingjie Zhou, Bofeng Cai, Shuo Chen and Dandan Yang
This research aims to explore how consumers' local brand choices differ between air-polluted days and clean days, and why the difference occurs.
Abstract
Purpose
This research aims to explore how consumers' local brand choices differ between air-polluted days and clean days, and why the difference occurs.
Design/methodology/approach
Two studies were conducted. Study 1 used the longitudinal consumption data of various yogurt brands and daily air quality indexes in 2014 and 2015. Study 2 conducted three rounds of surveys on a clean day, a general air-polluted day and a seriously air-polluted day.
Findings
The findings indicate that consumers show less tendency of attribution and compensatory consumption during air-polluted days, which in turn decrease their willingness to choose local brands.
Practical implications
Implications are provided for future research and marketing practice, especially for local companies that rely heavily on local consumers, and retailers in heavy air-polluted areas.
Originality/value
This paper is the first to illustrate the influence of air pollution on consumers' local brand choices, and it extends current understanding on air pollution and consumer choices by discovering psychological process underneath to explain the effect.
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The purpose of this paper is to improve the automation of selective disassembly sequence planning (SDSP) and generate the optimal or near-optimal disassembly sequences.
Abstract
Purpose
The purpose of this paper is to improve the automation of selective disassembly sequence planning (SDSP) and generate the optimal or near-optimal disassembly sequences.
Design/methodology/approach
The disassembly constraints is automatically extracted from the computer-aided design (CAD) model of products and represented as disassembly constraint matrices for DSP. A new disassembly planning model is built for computing the optimal disassembly sequences. The immune algorithm (IA) is improved for finding the optimal or near-optimal disassembly sequences.
Findings
The workload for recognizing disassembly constraints is avoided for DSP. The disassembly constraints are useful for generating feasible and optimal solutions. The improved IA has the better performance than the genetic algorithm, IA and particle swarm optimization for DSP.
Research limitations/implications
All parts must have rigid bodies, flexible and soft parts are not considered. After the global coordinate system is given, every part is disassembled along one of the six disassembly directions –X, +X, –Y, +Y, –Z and +Z. All connections between the parts can be removed, and all parts can be disassembled.
Originality/value
The disassembly constraints are extracted from CAD model of products, which improves the automation of DSP. The disassembly model is useful for reducing the computation of generating the feasible and optimal disassembly sequences. The improved IA converges to the optimal disassembly sequence quickly.
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Pingping Hou, HongYan Huang, Yong Wang, Jun Zhang and Dewen Sun
The purpose of this study is to prepare a robust superhydrophobic coating on concrete substrate with remarkable chemical and mechanical durability through “all-covalent” strategy.
Abstract
Purpose
The purpose of this study is to prepare a robust superhydrophobic coating on concrete substrate with remarkable chemical and mechanical durability through “all-covalent” strategy.
Design/methodology/approach
Amino-modified silica nano/micro-particles were prepared through two synthetic steps. “All-covalent” strategy was introduced to prepare a robust superhydrophobic coating on concrete surface via a “all-in-one” dispersion and a simple spraying method. The successful construction of the products was confirmed by Fourier transform infrared spectroscopy, water contact angles (WCA), X-ray photoelectron spectroscopy (XPS) and scanning electron microscope (SEM). The concrete protective properties were verified by solution immersion test, pull-off test and rapid chloride migration coefficient test. The mechanical durability was tested by falling sand impact.
Findings
Hierarchical structures combined with the low-surface-energy segments lead to typically superhydrophobic coating with a WCA of 156° and a sliding angle of 1.3°. The superhydrophobic coating prepared through “all-covalent” strategy not only improves chemical and mechanical durability but also achieves higher corrosion and wear resistance than the comparison sample prepared by physically blending strategy. More importantly, the robust superhydrophobic coating showed excellent adhesion and protective performance of concrete engineerings.
Practical implications
This new “all-covalent” superhydrophobic coating could be applied as a concrete protective layer with properties of self-cleaning, anti-graffiti, etc.
Originality/value
Introduction of both silica nanoparticles and silica microparticles to prepare a robust superhydrophobic coating on concrete surface through “all-covalent” strategy has not been systematically studied previously.
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Ying Zhu, Yong Wang, Joicey Wei and Andy Hao
Few studies illustrate how contextual effects (e.g. assimilation and contrast) in pay-per-click ad design may impact consumers' attitudes and purchase intention. To fill this…
Abstract
Purpose
Few studies illustrate how contextual effects (e.g. assimilation and contrast) in pay-per-click ad design may impact consumers' attitudes and purchase intention. To fill this research gap, the authors provide theoretical predictions and empirical evidence on how ad design may prompt an assimilation and/or a contrast effect that may influence consumers' attitudes toward the ad and the brand and purchase intention. They also investigate whether the impact of contextual effects on consumers' decisions depends on the level of vividness in the ad.
Design/methodology/approach
A 2 (vividness: dynamic motion vs. static page) × 2 (information design: assimilation vs. contrast) × 2 (aesthetic design: assimilation vs. contrast) between-subjects experimental design is used to examine the effects of vividness, information design and aesthetic design. Conditional process analysis is used to assess the mediating role of attitudes toward the ad and the brand in the relationship between contextual effects and purchase intention.
Findings
For dynamic ads (i.e. high vividness) but not for static ads (i.e. low vividness), combined information contrast and aesthetic contrast designs generate a more favorable attitude toward the brand and a higher purchase intention than do combined information assimilation and aesthetic assimilation designs. Notably, combined information contrast and aesthetic contrast designs have the strongest effects than any other combination of assimilation and contrast designs of information and aesthetics. Attitudes toward the ad and the brand are significant mediators between contextual factors and intention to purchase.
Research limitations/implications
The study examines the effectiveness of online ads from a new theoretical angle based on the attributes of pay-per-click ads.
Practical implications
The results suggest that when advertisers decide to use dynamic ads, they should adopt a contrast design for both the ad information and its aesthetics.
Originality/value
This study fills a research gap in the contextual effects literature, including providing evidence of an underlying process in the relationship between certain contextual effects and purchase intent. It also extends previous findings of assimilation/contrast in information design to aesthetics design and advances the literature on vividness by examining a moderation effect of vividness.
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