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1 – 10 of 44
Article
Publication date: 6 December 2023

Xiaolong Lu, Xudong Sui, Xiao Zhang, Zhen Yan and Junying Hao

This study aims to investigate the effect of V doping on the microstructure, chemical stability, mechanical and vacuum tribological behavior of sputtered MoS2 coatings.

Abstract

Purpose

This study aims to investigate the effect of V doping on the microstructure, chemical stability, mechanical and vacuum tribological behavior of sputtered MoS2 coatings.

Design/methodology/approach

The MoS2-V coatings are fabricated via tuning V target current by magnetron sputtering technique. The structural characteristic and elemental content of the coatings are measured by field emission scanning electron microscopy, X-ray diffractometer, electron probe X-ray micro-analyzer, Raman, X-ray photoelectron spectroscopy, high resolution transmission electron microscope and energy dispersive spectrometer. The hardness of the deposited coatings are tested by a nanoindentation technique. The vacuum tribological properties of MoS2-V coatings are studied by a ball-on-disc tribometer.

Findings

Introducing V into the MoS2 coatings results in a more compact microstructure. The hardness of the coatings increases with the doping of V. The MoS2-V coating deposited at a current of 0.2 A obtains the lowest friction coefficient (0.043) under vacuum. As the amount of V doping increases, the wear rate of the coating decreases first and then increases, among which the coating deposited at a current of 0.5 A has the lowest wear rate of 2.2 × 10–6 mm3/N·m.

Originality/value

This work elucidates the role of V doping on the lubrication mechanism of MoS2 coatings in a vacuum environment, and the MoS2-V coating is expected to be applied as a solid lubricant in space environment.

Details

Industrial Lubrication and Tribology, vol. 76 no. 1
Type: Research Article
ISSN: 0036-8792

Keywords

Article
Publication date: 29 March 2024

Zhiqun Zhang, Xia Yang, Xue Yang and Xin Gu

This study aims to examine how the knowledge breadth and depth of a patent affect its likelihood of being pledged. It also seeks to explore whether these relationships change…

Abstract

Purpose

This study aims to examine how the knowledge breadth and depth of a patent affect its likelihood of being pledged. It also seeks to explore whether these relationships change diversely in different technological environments.

Design/methodology/approach

A complementary log-log model with random effects was conducted to test the hypotheses using a unique data set consisting of 348,927 invention patents granted by the China National Intellectual Property Administration from 1985 to 2015 belonging to 74,996 firms.

Findings

The findings reveal that both knowledge breadth and depth of a patent positively affect its likelihood of being pledged. Furthermore, the knowledge breadth and depth entail different degrees of superiority in different technological environments.

Research limitations/implications

This study focuses on the effect of an individual patent’s knowledge base on its likelihood of being selected as collateral. It does not consider the influence of the overall knowledge characteristics of the selected patent portfolio.

Practical implications

Managers need to pay attention to patents’ knowledge characteristics and the changes in technological environments to select the most suitable patents as collateral and thus improve the success rate of pledge financing.

Originality/value

This study explores the impact of multidimensional characteristics of knowledge base on patent pledge financing within a systematic theoretical framework and incorporates technological environments into this framework.

Details

Journal of Knowledge Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1367-3270

Keywords

Article
Publication date: 14 March 2024

Ashani Fernando, Chandana Siriwardana, David Law, Chamila Gunasekara, Kevin Zhang and Kumari Gamage

The increasing urgency to address climate change in construction has made green construction (GC) and sustainability critical topics for academia and industry professionals…

Abstract

Purpose

The increasing urgency to address climate change in construction has made green construction (GC) and sustainability critical topics for academia and industry professionals. However, the volume of literature in this field has made it impractical to rely solely on traditional systematic evidence mapping methodologies.

Design/methodology/approach

This study employs machine learning (ML) techniques to analyze the extensive evidence-base on GC. Using both supervised and unsupervised ML, 5,462 relevant papers were filtered from 10,739 studies published from 2010 to 2022, retrieved from the Scopus and Web of Science databases.

Findings

Key themes in GC encompass green building materials, construction techniques, assessment methodologies and management practices. GC assessment and techniques were prominent, while management requires more research. The results from prevalence of topics and heatmaps revealed important patterns and interconnections, emphasizing the prominent role of materials as major contributors to the construction sector. Consistency of the results with VOSviewer analysis further validated the findings, demonstrating the robustness of the review approach.

Originality/value

Unlike other reviews focusing only on specific aspects of GC, use of ML techniques to review a large pool of literature provided a holistic understanding of the research landscape. It sets a precedent by demonstrating the effectiveness of ML techniques in addressing the challenge of analyzing a large body of literature. By showcasing the connections between various facets of GC and identifying research gaps, this research aids in guiding future initiatives in the field.

Details

Smart and Sustainable Built Environment, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2046-6099

Keywords

Article
Publication date: 19 May 2023

Yi-Ling Gao, Bengang Gong, Zhi Liu, Juan Tang and Chengfu Wang

Recycling and reuse of the electric vehicle (EV) batteries are ways to extend their limited lives. If batteries can be traced from production to recycling, it is beneficial for…

Abstract

Purpose

Recycling and reuse of the electric vehicle (EV) batteries are ways to extend their limited lives. If batteries can be traced from production to recycling, it is beneficial for battery recycling and reuse. Using blockchain technology to build a smart EV battery reverse supply chain can solve the difficulties of lack of trust and data. The purpose of this study is to discuss the behavioural evolution of a smart EV battery reverse supply chain under government supervision.

Design/methodology/approach

This study adopts evolutionary game theory to examine the decision-making behaviours of the government, EV manufacturers with recycled used batteries and third-party EV battery recyclers lacking professional recycling qualification.

Findings

On the smart reverse supply chain integrated by blockchain technology, a cooperative recycling strategy of the third-party EV battery recycler is the optimal choice when the government tends to actively regulate. The probability of the EV manufacturer choosing the blockchain adoption strategy exceeds (below) the threshold, and the government prefers negative (positive) supervision. According to numerical analysis, in the mature stage in the EV battery recycling industry, when the investment cost of applying blockchain is high, EV manufacturers' willingness to apply blockchain slows down, the government accelerates adopting a negative supervision strategy and third-party EV battery recyclers prefer cooperative recycling.

Practical implications

The results of this study provide opinions on the strength of government supervision and the conditions under which EV manufacturers and third-party EV battery recyclers should apply blockchain and cooperate. On the other hand, this study provides theoretical analysis for promoting the application of blockchain technology in smart reverse supply chain.

Originality/value

Compared with previous research, this study reveals the relevance of government supervision, blockchain application and cooperation strategy in smart EV battery reverse supply chain. In the initial stage, even if the subsidy (subsidy reduction rate) and penalty are high and the penalty reduction rate is low, the EV manufacturer should rather give up the application of blockchain technology. In the middle stage in the EV battery recycling industry, the government can set a lower subsidy (subsidy reduction rate) combined with a penalty or a higher penalty (penalty reduction rate) combined with a subsidy to supervise it. The third-party EV battery recycler is advised to cooperate with the EV manufacturer when the subsidy is low or the penalty is high.

Details

Industrial Management & Data Systems, vol. 123 no. 10
Type: Research Article
ISSN: 0263-5577

Keywords

Article
Publication date: 1 December 2023

Hao Wang, Hamzeh Al Shraida and Yu Jin

Limited geometric accuracy is one of the major challenges that hinder the wider application of additive manufacturing (AM). This paper aims to predict in-plane shape deviation for…

Abstract

Purpose

Limited geometric accuracy is one of the major challenges that hinder the wider application of additive manufacturing (AM). This paper aims to predict in-plane shape deviation for online inspection and compensation to prevent error accumulation and improve shape fidelity in AM.

Design/methodology/approach

A sequence-to-sequence model with an attention mechanism (Seq2Seq+Attention) is proposed and implemented to predict subsequent layers or the occluded toolpath deviations after the multiresolution alignment. A shape compensation plan can be performed for the large deviation predicted.

Findings

The proposed Seq2Seq+Attention model is able to provide consistent prediction accuracy. The compensation plan proposed based on the predicted deviation can significantly improve the printing fidelity for those layers detected with large deviations.

Practical implications

Based on the experiments conducted on the knee joint samples, the proposed method outperforms the other three machine learning methods for both subsequent layer and occluded toolpath deviation prediction.

Originality/value

This work fills a research gap for predicting in-plane deviation not only for subsequent layers but also for occluded paths due to the missing scanning measurements. It is also combined with the multiresolution alignment and change point detection to determine the necessity of a compensation plan with updated G-code.

Details

Rapid Prototyping Journal, vol. 30 no. 2
Type: Research Article
ISSN: 1355-2546

Keywords

Article
Publication date: 11 October 2023

Ayman Wael Al-Khatib

This study mainly aims to explore the causal nexus between big data-driven organizational capabilities (BDDOC) and supply chain innovation capabilities (SCIC) and innovation…

Abstract

Purpose

This study mainly aims to explore the causal nexus between big data-driven organizational capabilities (BDDOC) and supply chain innovation capabilities (SCIC) and innovation performance (IP), then explore the indirect effect of SCIC and also test the moderating effects for both internal supply chain integration (ISCI) and external supply chain integration (ESCI) into the relationship between BDDOC and SCIC.

Design/methodology/approach

In order to test the conceptual model and the hypothesized relationships between all the constructs, the data were collected using a self-reported questionnaire by workers in Jordanian small and medium manufacturing enterprises. Partial least squares-structural equation modeling (PLS-SEM) was employed to test the model.

Findings

The paper reached a set of interesting results where it was confirmed that there is a positive and statistically significant relationship between BDDOC, SCIC and IP in addition to confirming the indirect effect of SCIC between BDDOC and IP. The results also showed that there is a moderating role for both ESCI and ISCI.

Originality/value

This study can be considered the first study in the current literature that investigates these constructs as shown in the research model. Therefore, the paper presents an interesting set of theoretical and managerial contributions that may contribute to covering part of the research gap in the literature.

Article
Publication date: 24 December 2021

Hao Jiao, Jifeng Yang, Cheng Jiang and Jiawei Yu

This research helps firms pursue an open innovation strategy but want to minimize competitive pressure from other external entities. A theoretical framework is constructed to…

Abstract

Purpose

This research helps firms pursue an open innovation strategy but want to minimize competitive pressure from other external entities. A theoretical framework is constructed to analyze the impact of openness on innovation performance, exploring different effect of firms' external search channels.

Design/methodology/approach

This paper employs a stepwise hierarchical regression approach to assess the effect of openness on technological innovation considering the role of information technology adoption and political ties. The effect is conducted using a large-scale sample of 1,073 Chinese manufacturing firms over the period 2011–2013 as empirical research objects.

Findings

There are two stages of the open technological innovation process while the information technology (IT) adoption and political ties are the key consideration in emerging markets. Openness is curvilinearly (taking an inverted U-shape) related to innovation performance. Both information technology adoption and political ties generally help firms to turn broadly sourced external knowledge into technological innovation performance. This will stimulate “one plus one is greater than two” effect not only in the process of achieving performance goals, but also in the process of technological innovation.

Originality/value

This quantitative research illustrates the importance relationship between firms' open behaviors and technological innovation performance in emerging markets. It helps us understand firms' current constrains of open strategy of technological innovation and helps domestic or foreign investors to make strategic collaboration choices in emerging economies according to the degree of openness, informatization level, political connections, which is equally important for research and practice.

Details

International Journal of Emerging Markets, vol. 18 no. 10
Type: Research Article
ISSN: 1746-8809

Keywords

Article
Publication date: 22 December 2023

Chang Lu, Yong Qi, Shibo Hao and Bo Yu

This study aims to explore the effect of collaboration networks (domestic and international collaboration networks) on the innovation performance of small and medium-sized…

Abstract

Purpose

This study aims to explore the effect of collaboration networks (domestic and international collaboration networks) on the innovation performance of small and medium-sized enterprises (SMEs). It also investigates the mediating role of business model innovation, the moderating role of entrepreneurial orientation and government institutional support between them.

Design/methodology/approach

Hierarchical regression analysis is adopted to test the hypotheses based on survey data provided by 223 manufacturing SMEs in China.

Findings

The results reveal that domestic and international collaboration networks positively affect SMEs' innovation performance. Business model innovation mediates domestic and international collaboration networks-SMEs’ innovation performance relationships. Entrepreneurial orientation positively moderates international collaboration networks–SMEs’ innovation performance relationship, and government institutional support positively moderates domestic and international collaboration networks–SMEs’ innovation performance relationships.

Practical implications

The findings indicate that managers of SMEs should invest in domestic and international collaboration networks and business model innovation to enhance SMEs' innovation performance. Moreover, entrepreneurial orientation and government institutional support should be valued when SMEs try to enhance their innovation performance by embedding in domestic and international collaboration networks.

Originality/value

This study broadens the authors' understanding of the relationship between collaboration networks and firms' innovation performance by classifying collaboration networks into domestic and international dimensions and investigating their direct impacts on SMEs' innovation performance. Besides, this study reveals how and when domestic and international collaboration networks influence the innovation performance of SMEs.

Details

Business Process Management Journal, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1463-7154

Keywords

Article
Publication date: 5 December 2023

Hao Wang and Yunna Liu

This study aims to construct a mental health service system for middle school students in the post-COVID-19 era with the framework of Six Sigma DMAIC (define, measure, analyze…

Abstract

Purpose

This study aims to construct a mental health service system for middle school students in the post-COVID-19 era with the framework of Six Sigma DMAIC (define, measure, analyze, improve and control) and analyze the influencing factors of the mental health service system to study the implementation strategies of quality-oriented mental health services in middle schools.

Design/methodology/approach

This study was conducted in Tianjin, China, from September to November 2022, and 350 middle school students from Tianjin Public Middle School were selected as subjects. A questionnaire survey was used to collect data. In this study, the Six Sigma DMAIC method, sensitivity analysis method, exploratory factor analysis and principal component analysis were used to analyze the mental health services provided to middle school students.

Findings

Based on the Six Sigma DMAIC framework, this study indicates that the contribution rate of the mental health service process factor is the largest in the post-COVID-19 era. The mental health cultivation factor ranks second in terms of its contribution. Mental health quality and policy factors are also important in the construction of middle school students’ mental health service system. In addition, the study highlights the importance of parental involvement and social support in student mental health services during the post-COVID-19 era.

Originality/value

To the best of the authors’ knowledge, a study on middle school students’ mental health in the post-Covid-19 era has not yet been conducted. This study developed a quality-oriented mental health system and analyzed the influencing factors of mental health for middle school students based on data analysis and the Six Sigma DMAIC method.

Details

International Journal of Lean Six Sigma, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2040-4166

Keywords

Article
Publication date: 17 October 2022

Jiayue Zhao, Yunzhong Cao and Yuanzhi Xiang

The safety management of construction machines is of primary importance. Considering that traditional construction machine safety monitoring and evaluation methods cannot adapt to…

Abstract

Purpose

The safety management of construction machines is of primary importance. Considering that traditional construction machine safety monitoring and evaluation methods cannot adapt to the complex construction environment, and the monitoring methods based on sensor equipment cost too much. This paper aims to introduce computer vision and deep learning technologies to propose the YOLOv5-FastPose (YFP) model to realize the pose estimation of construction machines by improving the AlphaPose human pose model.

Design/methodology/approach

This model introduced the object detection module YOLOv5m to improve the recognition accuracy for detecting construction machines. Meanwhile, to better capture the pose characteristics, the FastPose network optimized feature extraction was introduced into the Single-Machine Pose Estimation Module (SMPE) of AlphaPose. This study used Alberta Construction Image Dataset (ACID) and Construction Equipment Poses Dataset (CEPD) to establish the dataset of object detection and pose estimation of construction machines through data augmentation technology and Labelme image annotation software for training and testing the YFP model.

Findings

The experimental results show that the improved model YFP achieves an average normalization error (NE) of 12.94 × 103, an average Percentage of Correct Keypoints (PCK) of 98.48% and an average Area Under the PCK Curve (AUC) of 37.50 × 103. Compared with existing methods, this model has higher accuracy in the pose estimation of the construction machine.

Originality/value

This study extends and optimizes the human pose estimation model AlphaPose to make it suitable for construction machines, improving the performance of pose estimation for construction machines.

Details

Engineering, Construction and Architectural Management, vol. 31 no. 3
Type: Research Article
ISSN: 0969-9988

Keywords

1 – 10 of 44