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1 – 10 of 23Yaming Wang, Jie Han, Junhai Li and Chunlan Mou
This research is aimed to examine how environmental pollution affects consumers' preference for self-improvement products.
Abstract
Purpose
This research is aimed to examine how environmental pollution affects consumers' preference for self-improvement products.
Design/methodology/approach
Through a series of three experimental studies, this research substantiates our hypotheses by employing various manipulations of environmental pollution and examining different types of self-improvement products.
Findings
The research demonstrates that environmental pollution enhances consumers' preference for self-improvement products via the mediation of perceived environmental responsibility. And the effect is negatively moderated by social equity sensitivity.
Originality/value
The recurrent incidence of environmental pollution has elicited significant concern among the general public and academic scholars. An overwhelming majority of research examining the impact of pollution on consumer behavior has concentrated on its influence on environmentally friendly and healthy consumption patterns. Nevertheless, the current research proposes that pollution fosters a preference for products associated with self-improvement, mediated by perceived environmental responsibility, with the effects being moderated by social equity sensitivity.
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WenFeng Qin, Yunsheng Xue, Hao Peng, Gang Li, Wang Chen, Xin Zhao, Jie Pang and Bin Zhou
The purpose of this study is to design a wearable medical device as a human care platform and to introduce the design details, key technologies and practical implementation…
Abstract
Purpose
The purpose of this study is to design a wearable medical device as a human care platform and to introduce the design details, key technologies and practical implementation methods of the system.
Design/methodology/approach
A multi-channel data acquisition scheme based on PCI-E (rapid interconnection of peripheral components) was proposed. The flexible biosensor is integrated with the flexible data acquisition card with monitoring capability, and the embedded (device that can operate independently) chip STM32F103VET6 is used to realize the simultaneous processing of multi-channel human health parameters. The human health parameters were transferred to the upper computer LabVIEW by intelligent clothing through USB or wireless Bluetooth to complete the transmission and processing of clinical data, which facilitates the analysis of medical data.
Findings
The smart clothing provides a mobile medical cloud platform for wearable medical through cloud computing, which can continuously monitor the body's wrist movement, body temperature and perspiration for 24 h. The result shows that each channel is completely accurate to the top computer display, which can meet the expected requirements, and the wearable instant care system can be applied to healthcare.
Originality/value
The smart clothing in this study is based on the monitoring and diagnosis of textiles, and the electronic communication devices can cooperate and interact to form a wearable textile system that provides medical monitoring and prevention services to individuals in the fastest and most accurate way. Each channel of the system is precisely matched to the display screen of the host computer and meets the expected requirements. As a real-time human health protection platform technology, continuous monitoring of human vital signs can complete the application of human motion detection, medical health monitoring and human–computer interaction. Ultimately, such an intelligent garment will become an integral part of our everyday clothing.
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Jie Yang, Manman Zhang, Linjian Shangguan and Jinfa Shi
The possibility function-based grey clustering model has evolved into a complete approach for dealing with uncertainty evaluation problems. Existing models still have problems…
Abstract
Purpose
The possibility function-based grey clustering model has evolved into a complete approach for dealing with uncertainty evaluation problems. Existing models still have problems with the choice dilemma of the maximum criteria and instances when the possibility function may not accurately capture the data's randomness. This study aims to propose a multi-stage skewed grey cloud clustering model that blends grey and randomness to overcome these problems.
Design/methodology/approach
First, the skewed grey cloud possibility (SGCP) function is defined, and its digital characteristics demonstrate that a normal cloud is a particular instance of a skewed cloud. Second, the border of the decision paradox of the maximum criterion is established. Third, using the skewed grey cloud kernel weight (SGCKW) transformation as a tool, the multi-stage skewed grey cloud clustering coefficient (SGCCC) vector is calculated and research items are clustered according to this multi-stage SGCCC vector with overall features. Finally, the multi-stage skewed grey cloud clustering model's solution steps are then provided.
Findings
The results of applying the model to the assessment of college students' capacity for innovation and entrepreneurship revealed that, in comparison to the traditional grey clustering model and the two-stage grey cloud clustering evaluation model, the proposed model's clustering results have higher identification and stability, which partially resolves the decision paradox of the maximum criterion.
Originality/value
Compared with current models, the proposed model in this study can dynamically depict the clustering process through multi-stage clustering, ensuring the stability and integrity of the clustering results and advancing grey system theory.
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Jinzhou Li, Jie Ma, Yujie Hu, Li Zhang, Zhijie Liu and Shiying Sun
This study aims to tackle control challenges in soft robots by proposing a visually-guided reinforcement learning approach. Precise tip trajectory tracking is achieved for a soft…
Abstract
Purpose
This study aims to tackle control challenges in soft robots by proposing a visually-guided reinforcement learning approach. Precise tip trajectory tracking is achieved for a soft arm manipulator.
Design/methodology/approach
A closed-loop control strategy uses deep learning-powered perception and model-free reinforcement learning. Visual feedback detects the arm’s tip while efficient policy search is conducted via interactive sample collection.
Findings
Physical experiments demonstrate a soft arm successfully transporting objects by learning coordinated actuation policies guided by visual observations, without analytical models.
Research limitations/implications
Constraints potentially include simulator gaps and dynamical variations. Future work will focus on enhancing adaptation capabilities.
Practical implications
By eliminating assumptions on precise analytical models or instrumentation requirements, the proposed data-driven framework offers a practical solution for real-world control challenges in soft systems.
Originality/value
This research provides an effective methodology integrating robust machine perception and learning for intelligent autonomous control of soft robots with complex morphologies.
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Luo Yue, Yan Meng, Eunji Lee, Pengpeng Bai, Yingzhuo Pan, Peng Wei, Jie Cheng, Yonggang Meng and Yu Tian
The incorporation of phosphide additives is regarded as a highly effective strategy for enhancing the lubricative qualities of base oils. This study aims to assess the lubrication…
Abstract
Purpose
The incorporation of phosphide additives is regarded as a highly effective strategy for enhancing the lubricative qualities of base oils. This study aims to assess the lubrication behavior and efficacy of various phosphide additives in polyethylsiloxane (PES) through the employment of the Schwingum Reibung Verschleiss test methodology, across a temperature range from ambient to 300°C.
Design/methodology/approach
PES demonstrated commendable lubrication capabilities within the Si3N4/M50 system, primarily attributable to the Si-O frictional reaction film at the interface. This film undergoes disintegration as the temperature escalates, leading to heightened wear. Moreover, the phosphide additives were found to ameliorate the issues encountered by PES in the Si3N4/M50 system, characterized by numerous boundary lubrication failure instances. A chemical film comprising P-Fe-O was observed to form at the interface; however, at elevated temperatures, disintegration of some phosphide films precipitated lubrication failures, as evidenced by a precipitous rise in the coefficient of friction.
Findings
The results show that a phosphide reactive film can be formed and a reduction in wear rate is achieved, which is reduced by 64.7% from 2.98 (for pure PES at 300°C) to 1.05 × 10–9 μm3/N m (for triphenyl phosphite at 300°C).
Originality/value
The data derived from this investigation offer critical insights for the selection and deployment of phosphide additives within high-temperature lubrication environments pertinent to PES.
Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-04-2024-0139/
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Xingchen Zhou, Pei-Luen Patrick Rau and Zhuoni Jie
This study aims to reveal how mobile app stickiness is formed and how the stickiness formation process differs for apps of different social levels.
Abstract
Purpose
This study aims to reveal how mobile app stickiness is formed and how the stickiness formation process differs for apps of different social levels.
Design/methodology/approach
This study proposed and validated a stickiness formation model following the cognitive–affective–conative framework. Data were collected from surveys of 1,240 mobile app users and analyzed using structural equation modeling. Multigroup analysis was applied to contrast the stickiness formation process among apps of different social levels.
Findings
This study revealed a causal link between cognitive, affective and conative factors. It found partial mediation effects of trust in the association between perceptions and satisfaction, and the full mediation role of satisfaction and personal investment (PI) in the effects of subjective norm (SN) on stickiness. The multigroup analysis results suggested that social media affordances benefit stickiness through increased PI and strengthened effects of SN on PI. However, it damages stickiness through increased perceived privacy risk (PPR), decreased trust and strengthened effects of PPR on trust.
Originality/value
This study contributes to both stickiness scholars and practitioners, as it builds a model to understand the stickiness formation process and reveals the effects of the “go social” strategy. The novelty of this study is that it examined social influences, considered privacy issues and revealed two mediation mechanisms. The findings can guide the improvement of mobile app stickiness and the application of the “go social” strategy.
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This study aims to explore the relationship between fraud triangle theory (FTT) and the accounting fraud phenomenon in all listed companies in China.
Abstract
Purpose
This study aims to explore the relationship between fraud triangle theory (FTT) and the accounting fraud phenomenon in all listed companies in China.
Design/methodology/approach
The CSMAR database is used as the sample, including 16,063 data of all listed companies in Shanghai and Shenzhen markets for the 2010–2020 period. The authors also use quantitative methods, such as regression analysis, to investigate the relationship between five variables (cover three elements of FTT) and fraud occurrence.
Findings
Results show that leverage and liquidity ratios positively affect fraud detection, whereas return on net equity, audit size and independent director percentage negatively affect fraud detection.
Originality/value
This study enriches theoretical research on the causes of accounting fraud in China and is of great significance to the sound development of China’s capital market.
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Xiangkai Zhang, Renxin Wang, Wenping Cao, Guochang Liu, Haoyu Tan, Haoxuan Li, Jiaxing Wu, Guojun Zhang and Wendong Zhang
Human-induced marine environmental noise, such as commercial shipping and seismic exploration, is concentrated in the low-frequency range. Meanwhile, low-frequency sound signals…
Abstract
Purpose
Human-induced marine environmental noise, such as commercial shipping and seismic exploration, is concentrated in the low-frequency range. Meanwhile, low-frequency sound signals can achieve long-distance propagation in water. To meet the requirements of long-distance underwater detection and communication, this paper aims to propose an micro-electro-mechanical system (MEMS) flexible conformal hydrophone for low-frequency underwater acoustic signals. The substrate of the proposed hydrophone is polyimide, with silicon as the piezoresistive unit.
Design/methodology/approach
This paper proposes a MEMS heterojunction integration process for preparing flexible conformal hydrophones. In addition, sensors prepared based on this process are non-contact flexible sensors that can detect weak signals or small deformations.
Findings
The experimental results indicate that making devices with this process cannot only achieve heterogeneous integration of silicon film, metal wire and polyimide, but also allow for customized positions of the silicon film as needed. The success rate of silicon film transfer printing is over 95%. When a stress of 1 Pa is applied on the x-axis or y-axis, the maximum stress on Si as a pie-zoresistive material is above, and the average stress on the Si film is around.
Originality/value
The flexible conformal vector hydrophone prepared by heterogeneous integration technology provides ideas for underwater acoustic communication and signal acquisition of biomimetic flexible robotic fish.
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Qing Ray Cao, Isaac Elking, Vicky Ching Gu and James J. Hoffman
The purpose of this study is to examine the extent to which a firm is able to leverage its information system (IS) innovativeness to improve supply chain resilience through…
Abstract
Purpose
The purpose of this study is to examine the extent to which a firm is able to leverage its information system (IS) innovativeness to improve supply chain resilience through developing and employing its analytics capability. It further considers how this mediating effect of analytics capability can be enhanced by internal and external integration.
Design/methodology/approach
Building on the logic of organizational information processing theory, a mediated moderation model is developed and tested using structural equation modeling and partial least squares regression based on survey responses from 247 working professionals.
Findings
The results indicate that IS innovativeness improves a firm’s supply chain resilience through enhanced analytics capability, with higher levels of internal and external integration further strengthening the effects of this mediating relationship.
Originality/value
This study is among the first to empirically test the effects of IS innovativeness and analytics capability on supply chain resilience and to examine the impacts of internal and external integration as key factors affecting the strength of these relationships. The findings complement existing literature through providing new insights into the linkage between IS strategy and supply chain resilience and highlighting the importance of relationships throughout the supply chain to enhance the efficacy of a firm’s analytics capability within this domain.
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Hong Guo, Xiaokai Niu and Zhitian Xie
The occurrence of segment cracks caused by load changes in shield tunnels would affect the safety of the tunnel structure. To this end, a three-dimensional fine shield tunnel…
Abstract
Purpose
The occurrence of segment cracks caused by load changes in shield tunnels would affect the safety of the tunnel structure. To this end, a three-dimensional fine shield tunnel segment model based on the extended finite element method (XFEM) is established.
Design/methodology/approach
The cracking law of shield segment cracks is studied in two forms: overloading and unloading. The relationship between crack length, width and depth and transverse convergence and deformation is analyzed.
Findings
The results show that the cracks in shield tunnels mainly occur on the outer side of the arch waist and the inner side of the crown and bottom. Under overloading and unloading conditions, the length, width and depth of cracks increase non-linearly as the transverse convergence deformation increases. Under the same convergent deformation, the deeper the buried depth, the smaller the crack length, width and depth. Meanwhile, under overloading conditions, the influence of buried depth on the width and depth of cracks is more significant. In terms of crack width and depth, unloading conditions are more dangerous than overloading conditions.
Originality/value
The findings have a guiding effect for the management of cracks in shield tunnels during operation.
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