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1 – 10 of 94Guanchen Liu, Dongdong Xu, Zifu Shen, Hongjie Xu and Liang Ding
As an advanced manufacturing method, additive manufacturing (AM) technology provides new possibilities for efficient production and design of parts. However, with the continuous…
Abstract
Purpose
As an advanced manufacturing method, additive manufacturing (AM) technology provides new possibilities for efficient production and design of parts. However, with the continuous expansion of the application of AM materials, subtractive processing has become one of the necessary steps to improve the accuracy and performance of parts. In this paper, the processing process of AM materials is discussed in depth, and the surface integrity problem caused by it is discussed.
Design/methodology/approach
Firstly, we listed and analyzed the characterization parameters of metal surface integrity and its influence on the performance of parts and then introduced the application of integrated processing of metal adding and subtracting materials and the influence of different processing forms on the surface integrity of parts. The surface of the trial-cut material is detected and analyzed, and the surface of the integrated processing of adding and subtracting materials is compared with that of the pure processing of reducing materials, so that the corresponding conclusions are obtained.
Findings
In this process, we also found some surface integrity problems, such as knife marks, residual stress and thermal effects. These problems may have a potential negative impact on the performance of the final parts. In processing, we can try to use other integrated processing technologies of adding and subtracting materials, try to combine various integrated processing technologies of adding and subtracting materials, or consider exploring more efficient AM technology to improve processing efficiency. We can also consider adopting production process optimization measures to reduce the processing cost of adding and subtracting materials.
Originality/value
With the gradual improvement of the requirements for the surface quality of parts in the production process and the in-depth implementation of sustainable manufacturing, the demand for integrated processing of metal addition and subtraction materials is likely to continue to grow in the future. By deeply understanding and studying the problems of material reduction and surface integrity of AM materials, we can better meet the challenges in the manufacturing process and improve the quality and performance of parts. This research is very important for promoting the development of manufacturing technology and achieving success in practical application.
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Changqing He, Rongrong Teng and Jun Song
This study aims to explore the associations linking employees’ challenge-hindrance appraisals toward artificial intelligence (AI) to service performance while considering the dual…
Abstract
Purpose
This study aims to explore the associations linking employees’ challenge-hindrance appraisals toward artificial intelligence (AI) to service performance while considering the dual mediating roles of job crafting and job insecurity, as well as the moderating role of AI knowledge.
Design/methodology/approach
A survey was administered to a sample of 297 service industry employees. This study examined all the hypotheses with Mplus 8.0.
Findings
This study confirms that challenge appraisal toward AI has an indirect positive influence on service performance via job crafting (motivation process), whereas hindrance appraisal toward AI has an indirect negative influence on service performance via job insecurity (strain process). Meanwhile, AI knowledge, serving as a key personal resource, could strengthen the positive impacts of challenge appraisal toward AI on job crafting and of hindrance appraisal toward AI on job insecurity.
Practical implications
Organizational decision-makers should first survey employees’ appraisals toward AI and then adopt targeted managerial strategies. From the perspective of service industry employees, employees should adopt proactive coping strategies and enrich their knowledge of AI to meet the challenges brought by this technology.
Originality/value
The primary contribution of this study is that we enrich the literature on AI by exploring the dual mediators (i.e. job crafting and job insecurity) through which AI awareness affects service performance. Moreover, this study advances our understanding of when appraisals toward AI influence job outcomes by identifying the moderating role of AI knowledge.
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Chongjun Wu, Yutian Chen, Xinyi Wei, Junhao Xu and Dongliu Li
This paper is devoted to prepare micro-cone structure with variable cross-section size by Stereo Lithography Appearance (SLA)-based 3D additive manufacturing technology. It is…
Abstract
Purpose
This paper is devoted to prepare micro-cone structure with variable cross-section size by Stereo Lithography Appearance (SLA)-based 3D additive manufacturing technology. It is mainly focused on analyzing the forming mechanism of equipment and factors affecting the forming quality and accuracy, investigating the influence of forming process parameters on the printing quality and optimization of the printing quality. This study is expected to provide a µ-SLA surface preparation technology and process parameters selection with low cost, high precision and short preparation period for microstructure forming.
Design/methodology/approach
The µ-SLA process is optimized based on the variable cross-section micro-cone structure printing. Multi-index analysis method was used to analyze the influence of process parameters. The process parameter influencing order is determined and validated with flawless micro array structure.
Findings
After the optimization analysis of the top diameter size, the bottom diameter size and the overall height, the influence order of the printing process parameters on the quality of the micro-cone forming is: exposure time (B), print layer thickness (A) and number of vibrations (C). The optimal scheme is A1B3C1, that is, the layer thickness of 5 µm, the exposure time of 3000 ms and the vibration of 64x. At this time, the cone structure with the bottom diameter of 50 µm and the cone angle of 5° could obtain a better surface structure.
Originality/value
This study is expected to provide a µ-SLA surface preparation technology and process parameters selection with low cost, high precision and short preparation period for microstructure forming.
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This systematic literature review presents the state of the field of fashion and crisis communication. The quantitative coding offers insight into dominant and emergent themes in…
Abstract
Purpose
This systematic literature review presents the state of the field of fashion and crisis communication. The quantitative coding offers insight into dominant and emergent themes in one of the most crisis-prone industries. This review also offers a framework for future research.
Design/methodology/approach
This study uses a systematic literature review approach. 205 academic articles were gathered in total using the search term “fashion industry crisis”. Subsequently, they were quantitatively coded using the Diers-Lawson (2016) Crisis Communication Code Book.
Findings
Findings show an increase in the fashion industry crisis with clear emergent themes such as sustainability, emphasising the truly global and multidisciplinary nature of the industry. Findings also reveal a genuine lack of theoretical grounding, with over 80% of the articles coded using no crisis communication theory. The findings also suggest value co-creation ought to be a priority for this agenda moving forward, as it overlaps with emerging themes and is a practical tool and concept to support crisis prevention and management through an extension of the Stakeholder Relationship Model (SRM) Model.
Research limitations/implications
As a largely under-researched area in crisis communication, the findings present a new opportunity to explore fashion within its context and contribute. At this point, the research field is lacking, and there is room for theory testing and hypothesis building. The findings and themes from the research present a development of the original SRM model, SRM Val-Co.
Practical implications
As well as research implications, the proposed framework provides practical solutions for the future of the fashion industry.
Originality/value
As a largely under-researched area in crisis communication, the findings demonstrate a new opportunity to explore fashion within its context and contribute because there is a dearth of research and a lack of theoretical development. Therefore, the proposed framework provides practical solutions for the fashion industry’s future. The findings and themes from the research present a development of the original SRM model, SRM Val-Co.
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Ding Wang, Jianyao Jia, Shan Jiang, Tianyi Liu and Guofeng Ma
Despite the documented benefits of voice behavior for projects, little is known about antecedents of voice behavior in the project context, especially construction projects…
Abstract
Purpose
Despite the documented benefits of voice behavior for projects, little is known about antecedents of voice behavior in the project context, especially construction projects. Against this background, adopting a multi-team system perspective, this study attempts to investigate antecedents of team voice behavior from a contextual view.
Design/methodology/approach
This study identifies and examines six factors that influence team voice behavior. Specifically, project urgency, project temporality, and project complexity are identified from the project nature perspective. Satisfaction, trust, and commitment are generated from the relationship quality approach. Then, data from completed construction projects in China was collected to verify the effectiveness of these factors. Besides, the partial least squares structural equation modeling (PLS-SEM) technique was used in this study.
Findings
All six factors are found to be significant predictors of promotive team voice behavior. For prohibitive team voice behavior, only project complexity and project commitment make significant effects. Further, the differential effects of these factors on two types of voice behavior are revealed.
Originality/value
This study contributes to the literature on voice behavior in the project context, especially construction projects consisting of multiple teams. Also, this research enriches our knowledge on antecedents of team voice behavior in construction projects and thus affords practical implications to foster voice behavior.
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Xiaoping Liu, Shiyu Wang and Yingqian Liang
Based on the construal level theory, this research study examines the interactive effect between social crowding and corporate social responsibility (CSR) statement type on…
Abstract
Purpose
Based on the construal level theory, this research study examines the interactive effect between social crowding and corporate social responsibility (CSR) statement type on consumers' purchase intention.
Design/methodology/approach
The authors conducted two empirical experiments on a total of 508 subjects.
Findings
There is an interactive effect between social crowding and CSR statement type on consumers' purchase intention. Specifically, in high social crowding situations, concrete CSR statements lead to consumers' higher purchase intention, while in low social crowding situations, abstract CSR statements lead to consumers' higher purchase intention. Self-construal and processing fluency play a moderating and mediating role in the mechanism.
Originality/value
This research study contributes to the theoretical understanding of the interaction between social crowding and CSR statements, enriching the field of consumer behavior research on social crowding. Additionally, it offers practical insights for enterprises on how to present CSR information in crowded situations.
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Xingwen Wu, Zhenxian Zhang, Wubin Cai, Ningrui Yang, Xuesong Jin, Ping Wang, Zefeng Wen, Maoru Chi, Shuling Liang and Yunhua Huang
This review aims to give a critical view of the wheel/rail high frequency vibration-induced vibration fatigue in railway bogie.
Abstract
Purpose
This review aims to give a critical view of the wheel/rail high frequency vibration-induced vibration fatigue in railway bogie.
Design/methodology/approach
Vibration fatigue of railway bogie arising from the wheel/rail high frequency vibration has become the main concern of railway operators. Previous reviews usually focused on the formation mechanism of wheel/rail high frequency vibration. This paper thus gives a critical review of the vibration fatigue of railway bogie owing to the short-pitch irregularities-induced high frequency vibration, including a brief introduction of short-pitch irregularities, associated high frequency vibration in railway bogie, typical vibration fatigue failure cases of railway bogie and methodologies used for the assessment of vibration fatigue and research gaps.
Findings
The results showed that the resulting excitation frequencies of short-pitch irregularity vary substantially due to different track types and formation mechanisms. The axle box-mounted components are much more vulnerable to vibration fatigue compared with other components. The wheel polygonal wear and rail corrugation-induced high frequency vibration is the main driving force of fatigue failure, and the fatigue crack usually initiates from the defect of the weld seam. Vibration spectrum for attachments of railway bogie defined in the standard underestimates the vibration level arising from the short-pitch irregularities. The current investigations on vibration fatigue mainly focus on the methods to improve the accuracy of fatigue damage assessment, and a systematical design method for vibration fatigue remains a huge gap to improve the survival probability when the rail vehicle is subjected to vibration fatigue.
Originality/value
The research can facilitate the development of a new methodology to improve the fatigue life of railway vehicles when subjected to wheel/rail high frequency vibration.
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Mousumi Bose, Lilly Ye and Yiming Zhuang
Today's marketing is dominated by decision-making based on artificial intelligence and machine learning. This study focuses on one semi- and unsupervised machine learning…
Abstract
Today's marketing is dominated by decision-making based on artificial intelligence and machine learning. This study focuses on one semi- and unsupervised machine learning technique, generative adversarial networks (GANs). GANs are a type of deep learning architecture capable of generating new data similar to the training data that were used to train it, and thus, it is designed to learn a generative model that can produce new samples. GANs have been used in multiple marketing areas, especially in creating images and video and providing customized consumer contents. Through providing a holistic picture of GANs, including its advantage, disadvantage, ethical considerations, and its current application, the study attempts to provide business some strategical orientations, including formulating strong marketing positioning, creating consumer lifetime values, and delivering desired marketing tactics in product, promotion, pricing, and distribution channel. Through using GANs, marketers will create unique experiences for consumers, build strategic focus, and gain competitive advantages. This study is an original endeavor in discussing GANs in marketing, offering fresh insights in this research topic.
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Xi Zhang, Tianxue Xu, Xin Wei, Jiaxin Tang and Patricia Ordonez de Pablos
As a kind of knowledge-intensive team coordinated across physical distance, it is necessary to construct a meta-knowledge driven transactive memory system (TMS) for the knowledge…
Abstract
Purpose
As a kind of knowledge-intensive team coordinated across physical distance, it is necessary to construct a meta-knowledge driven transactive memory system (TMS) for the knowledge management of distributed agile team (DAT). This study aims to explore the comprehensive antecedents of TMS establishment in DATs and considers how TMS establishment is affected by herding behavior under the artificial intelligence (AI)-related knowledge work environment that emerges with technology penetration.
Design/methodology/approach
The data derived from 177 students of 52 DATs in a well-known Chinese business school, which were divided into 26 traditional knowledge work groups and 26 AI-related task groups to conduct a random comparative experiment. The ordinary least squares method was used to analyze the conceptual model and ANOVA was used to examine the differences in herding behavior between the control groups (traditional knowledge work DATs) and treatment groups (DATs engaged in AI-related knowledge work).
Findings
The results showed that knowledge diversity, professional knowledge, self-efficacy and social system use had significantly positive effects on the establishment of TMS. Interestingly, the authors also find that herding behavior may promote the process of establishing TMS of the new team, and this effect will be more significant when AI tasks are involved in team knowledge work.
Originality/value
By exploring the comprehensive antecedents of the establishment of TMS, this study provided a theoretical basis for knowledge management of DATs, especially in AI knowledge work teams. From a practical perspective, when the DAT is involved in AI-related knowledge works, managers should appropriately guide the convergence of employees’ behaviors and use the herding effects to accelerate the establishment of TMS, which will improve team knowledge sharing and innovation.
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Anil Kumar Goswami, Anamika Sinha, Meghna Goswami and Prashant Kumar
This study aims to extend and explore patterns and trends of research in the linkage of big data and knowledge management (KM) by identifying growth in terms of numbers of papers…
Abstract
Purpose
This study aims to extend and explore patterns and trends of research in the linkage of big data and knowledge management (KM) by identifying growth in terms of numbers of papers and current and emerging themes and to propose areas of future research.
Design/methodology/approach
The study was conducted by systematically extracting, analysing and synthesizing the literature related to linkage between big data and KM published in top-tier journals in Web of Science (WOS) and Scopus databases by exploiting bibliometric techniques along with theory, context, characteristics, methodology (TCCM) analysis.
Findings
The study unfolds four major themes of linkage between big data and KM research, namely (1) conceptual understanding of big data as an enabler for KM, (2) big data–based models and frameworks for KM, (3) big data as a predictor variable in KM context and (4) big data applications and capabilities. It also highlights TCCM of big data and KM research through which it integrates a few previously reported themes and suggests some new themes.
Research limitations/implications
This study extends advances in the previous reviews by adding a new time line, identifying new themes and helping in the understanding of complex and emerging field of linkage between big data and KM. The study outlines a holistic view of the research area and suggests future directions for flourishing in this research area.
Practical implications
This study highlights the role of big data in KM context resulting in enhancement of organizational performance and efficiency. A summary of existing literature and future avenues in this direction will help, guide and motivate managers to think beyond traditional data and incorporate big data into organizational knowledge infrastructure in order to get competitive advantage.
Originality/value
To the best of authors’ knowledge, the present study is the first study to go deeper into understanding of big data and KM research using bibliometric and TCCM analysis and thus adds a new theoretical perspective to existing literature.
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