Yong Qiu, Yuting Gao, Jianting Liu, Wenzhou Wang, Yalin Tian and Xiaoran Sun
The continuous upgrading of new technologies and rapid changes in their external environment have made organizations more dependent than ever on the ability of their employees to…
Abstract
Purpose
The continuous upgrading of new technologies and rapid changes in their external environment have made organizations more dependent than ever on the ability of their employees to quickly identify problems and make timely course corrections. This dependency is not limited to individual employee voice but extends to the collective voice of the team. In the Chinese context, collective silence prevails. Following social identity theory, this study aims to explore the mechanisms and conditional processes underlying the relationship between team faultlines and team voice behavior and examine whether there are differences between the effects of objective and perceived faultlines.
Design/methodology/approach
The proposed model was tested through questionnaires with 377 team members from 71 teams, which were conducted through team leader–member pairing survey. The correlation and hierarchical stepwise regression analyses were used to test the hypotheses rigorously, and the questionnaire data was analyzed using SPSS 26.0, AMOS 25.0 and R 3.6.1.
Findings
The results show that both objective and perceived faultlines have a negative impact on team voice behavior and that the latter has a stronger negative effect. Team psychological safety mediates the relationship between team faultlines and team voice behavior. In addition, benevolent leadership, moral leadership and Zhongyong thinking positively moderate the negative effect of objective faultlines on team voice behavior; Zhongyong thinking also moderates the mediating effect of team psychological safety on the relationship between objective faultlines and team voice behavior.
Originality/value
The results of this study provide a deeper understanding of team faultlines and team voice behavior, and practical implications are provided for managers and future researchers to improve voice behavior in organizations.
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Yuting Cui, Fanghui Huang, Zhiqun Zhao and Fan Gao
Firstly, this study diagnosed professional competence amongst Chinese vocational students within a broad range of the manufacturing sectors; then, the authors examined how…
Abstract
Purpose
Firstly, this study diagnosed professional competence amongst Chinese vocational students within a broad range of the manufacturing sectors; then, the authors examined how different types of P-E fit (job, organisation and vocation) and internship quality jointly shape the newly acquired professional competences of interns.
Design/methodology/approach
This study utilised the COMET methodology to conduct a large-scale assessment of professional competence amongst 961 graduates from vocational colleges who had successfully completed internships. Participants actively engaged in the data collection process by responding to questionnaires that sought contextual information concurrently.
Findings
The majority of students have attained fundamental functional competencies, indicating their fulfillment of basic requirements. However, there is a tendency to overlook the cultivation of shaping competence. Three types of P-E fit and task characteristics are positively correlated with professional competence. The indirect relationship between P-E fit and professional competence mediated by task characteristics was verified through P-V fit and P-J fit except for P-O fit. Overall, the model explains 39.2% of the variance in professional competence.
Originality/value
“How to promote professional competence” has been highlighted as an important topic in vocational education. This paper contributes to identify the characteristics of a quality internship program for vocational colleges and firms. These insights are important in considering a student-centred approach, design internships programmes that better fit their own abilities, needs and vocations, avoiding a one-size-fits-all approach to implement internships and thus, enhance students' professional development.
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This study aims to examine how intercultural competence (IC) among university students can be enhanced through two streams of higher education internationalization…
Abstract
Purpose
This study aims to examine how intercultural competence (IC) among university students can be enhanced through two streams of higher education internationalization: internationalization abroad and internationalization at home (IaH). By doing so, it aims to improve university students' IC through identifying which factors are more effective in fostering IC.
Design/methodology/approach
The study is not solely a literature review, but rather a conceptual exploration based on a selective review of the literature. Due to the exploratory nature of this study, we employed a thematic analysis approach to reviewing English language literature while incorporating relevant Chinese literature to ensure a more balanced representation.
Findings
We found that international students’ IC is influenced by their overseas learning experiences, which are closely related to the duration of stay, language proficiency, intercultural contact, university management and teachers and administrative support. On the other hand, domestic students’ IC has been influenced by various IaH experiences primarily within their home university campus, such as foreign language learning, international curriculum, extracurricular activities, communication between domestic and international students, integrated management of international students, the use of Internet and communication technology and so forth. Although a direct and definitive comparison is lacking, some comparative analyses suggest that IaH experiences may yield better results in enhancing the IC of domestic students.
Originality/value
This article advances the understanding of IC development. We call for further research that values the importance of IaH in the increasingly uncertain globalization and delves into comparative analysis of the effects of two streams of higher education internationalization.
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Rui Mu and Yuting Wang
To fill the gap, this article examines the inter-governmental collaboration mechanisms behind the platform curtain.
Abstract
Purpose
To fill the gap, this article examines the inter-governmental collaboration mechanisms behind the platform curtain.
Design/methodology/approach
Behind the curtain is to look at what makes things happen backstage. For collaborative e-governance platforms, scholars have assumed that technological factors and user characteristics are the determinants for platform success. Little attention has been paid to the issue of how multiple governments, acting as platform co-builders and co-operators, interact and collaborate backstage to provide integrated e-services.
Findings
Based on data from survey questionnaires sent to government employees, the results show that governments’ information processing capacities cannot directly affect collaboration; however, these capacities can impact collaboration via the mediating variable of horizontal relations. In addition, we found that higher-ranking authorities are better suited to intervene once horizontal relations have been established and that more adaptable organizations are better at forming horizontal relations with peers. For governments participating in collaborative e-governance platforms, our findings are practically applicable.
Originality/value
The research question reads as: How do various government departments acting as platform co-builders and co-operators judge their collaboration performance, and what collaboration mechanisms contribute to it? We study this research question by constructing a conceptual model based on the Organizational Information Processing Theory (OIPT) and the Collaborative Governance Theory (CGT), both suggesting information processing capacities, organizational flexibility, horizontal relations and vertical intervention as indispensable factors influencing collaboration performance in ICT-supported groupwork. We propose and test four hypotheses on the relationships among these four factors to reveal the inter-governmental collaboration mechanisms for cross-government platformisation projects.
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Mengru Zhang, Yuting Wang and Wei Wang
Although big data analytics managerial skills (BDAMS) offer opportunities for firms to foster organizational agility, existing studies present inconclusive indications of this…
Abstract
Purpose
Although big data analytics managerial skills (BDAMS) offer opportunities for firms to foster organizational agility, existing studies present inconclusive indications of this impact, with an overlooking of the intermediate pathways involved. This study explored how BDAMS affect organizational agility by investigating the mediation effect of data-driven organizational learning (DDOL) and the moderating roles of technological and market turbulence.
Design/methodology/approach
This study employed mediation and moderated mediation analyses to test the hypotheses using data collected from listed Chinese firms. Furthermore, we performed a fuzzy set qualitative comparative analysis (fsQCA) as a supplementary approach to identify the configurations that lead to organizational agility.
Findings
This study shows that DDOL partially mediates the relationship between BDAMS and organizational agility. Besides, technological and market turbulence positively moderate the effect of DDOL on organizational agility and the mediation effect of DDOL. Our additional analyses also reveal several patterns of conditions that facilitate agility.
Originality/value
This study offers a comprehensive exploration of the relationship between BDAMS and organizational agility by verifying the mediating effect of DDOL and moderating effects of technological and market turbulence. In addition, the fsQCA results highlighted the combinatorial effects of key factors in this study, reinforcing and refining the moderated mediation results.
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Yuting Lv, Xing Ouyang, Yaojie Liu, Ying Tian, Rui Wang and Guijiang Wei
This paper aims to investigate the differences in hot corrosion behavior of the GTD222 superalloy and TiC/GTD222 composite in a mixed salt of 75% Na2SO4 and 25% K2SO4 at 900°C.
Abstract
Purpose
This paper aims to investigate the differences in hot corrosion behavior of the GTD222 superalloy and TiC/GTD222 composite in a mixed salt of 75% Na2SO4 and 25% K2SO4 at 900°C.
Design/methodology/approach
The GTD222 superalloy and TiC/GTD222 nickel-based composite were prepared using selective laser melting (SLM). Subsequently, the hot corrosion behavior of the two alloys was systematically investigated in a salt mixture consisting of 75% Na2SO4 and 25% K2SO4 (Wt.%) at 900°C.
Findings
The TiC/GTD222 composite exhibited better hot corrosion resistance compared to the GTD222 superalloy. First, the addition of alloying elements led to the formation of a protective oxide film on the TiC/GTD222 composites 20 h before hot corrosion. Second, TiC/GTD222 composite corrosion surface has a higher Ti content, after 100 h of hot corrosion, the composite corrosion surface Ti content of 10.8% is more than two times the GTD222 alloy 4% Ti. The Ti and Cr oxides are tightly bonded, effectively resisting the erosion of corrosive elements.
Originality/value
The hot corrosion behavior of GTD222 superalloy and TiC/GTD222 composites prepared by SLM in a mixed salt of 75% Na2SO4 and 25% K2SO4 was studied for the first time. This study provides insights into the design of high-temperature alloys resistant to hot corrosion.
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Yuting Rong, Shan Liu, Shuo Yan, Wei Wayne Huang and Yanxia Chen
Lenders in online peer-to-peer (P2P) lending platforms are always non-experts and face severe information asymmetry. This paper aims to achieve the goals of gaining high returns…
Abstract
Purpose
Lenders in online peer-to-peer (P2P) lending platforms are always non-experts and face severe information asymmetry. This paper aims to achieve the goals of gaining high returns with risk limitations or lowering risks with expected returns for P2P lenders.
Design/methodology/approach
This paper used data from a leading online P2P lending platform in America. First, the authors constructed a logistic regression-based credit scoring model and a linear regression-based profit scoring model to predict the default probabilities and profitability of loans. Second, based on the predictions of loan risk and loan return, the authors constructed linear programming model to form the optimal loan portfolio for lenders.
Findings
The research results show that compared to a logistic regression-based credit scoring method, the proposed new framework could make more returns for lenders with risks unchanged. Furthermore, compared to a linear regression-based profit scoring method, the proposed new framework could lower risks for lenders without lowering returns. In addition, comparisons with advanced machine learning techniques further validate its superiority.
Originality/value
Unlike previous studies that focus solely on predicting the default probability or profitability of loans, this study considers loan allocation in online P2P lending as an optimization research problem using a new framework based upon modern portfolio theory (MPT). This study may contribute theoretically to the extension of MPT in the specific context of online P2P lending and benefit lenders and platforms to develop more efficient investment tools.
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Dan Liu, Tiange Liu and Yuting Zheng
By studying the green development efficiency (GDE) of 33 cities in the provinces of Jiangsu, Zhejiang, and Fujian in China, this study strives to conduct an analysis of the…
Abstract
Purpose
By studying the green development efficiency (GDE) of 33 cities in the provinces of Jiangsu, Zhejiang, and Fujian in China, this study strives to conduct an analysis of the sustainable practices implemented in these developed regions, and derive valuable insights that can foster the promotion of green transformation.
Design/methodology/approach
First, the urban green development system (GDS) was decomposed into the economic benefit subsystem (EBS), social benefit subsystem (SBS), and pollution control subsystem (PCS). Then, a mixed network SBM model was proposed to evaluate the GDE during 20152020, with Moran’s I and Bootstrap truncated regression model subsequently applied to measure the spatial characteristics and driving factors of efficiency.
Findings
Subsystem efficiency presents a distribution trend of PCS > EBS > SBS. There is a particular spatial aggregation effect in EBS efficiency, whereas SBS and PCS efficiencies have no significant spatial autocorrelation. Furthermore, urbanization level contributes significantly to the efficiency of all subsystems; industrial structure, energy consumption, and technological innovation play a crucial role in EBS and SBS; external openness is a pivotal factor in SBS; and environmental regulation has a significant effect on PCS.
Originality/value
This study further decomposes the black box of GDS into subsystems including the economy, society, and environment. Additionally, by employing a mixed network SBM model and Bootstrap truncated regression model to investigate efficiency and its driving factors from the subsystem perspective, it endeavors to derive more detailed research conclusions and policy implications.
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Yuting Wang, Hefu Liu and Jie Fang
This paper aims to investigate that how to mitigate the weaker party's risk perception in imbalanced supply chain relationships by framing contracts according to complexity and…
Abstract
Purpose
This paper aims to investigate that how to mitigate the weaker party's risk perception in imbalanced supply chain relationships by framing contracts according to complexity and recurrence. The level of information technology (IT) integration is considered as the moderator influencing the effectuation of contract framing.
Design/methodology/approach
The authors conducted a questionnaire survey with 229 firms involved in imbalanced supply chains. Hierarchical regression analysis was used to test the hypotheses.
Findings
The authors found contractual complexity positively influenced performance and relational risk, while contractual recurrence negatively impacted performance and relational risk. This study further reveals the positive moderating effect of IT integration in influencing contractual complexity on relational risk and performance risk and the negative impact of IT integration in influencing contractual recurrence on relational risk and performance risk.
Research limitations/implications
Overall, this study posits the coordinating role of contracts in reducing the weaker party's risk perception in imbalanced supply chain relationships.
Practical implications
The authors concluded by illustrating how to customize contracts based on the level of IT integration to maximize their role in reducing risk perception.
Originality/value
This study is embedded in imbalanced supply chain relationship, aiming to solve the problem of high-risk perception held by the weaker party, which is a salient threat to the sustainability of collaboration. Contract framing is proposed as an effective approach for mitigating risk perception, which should be carefully designed based on the level of IT integration of the relationship. The authors found that contractual complexity has a positive influence on performance and relational risk, but contractual recurrence has a negative impact on performance and relational risk. This study further reveals the moderating effect of IT integration on the effectuation of contractual framing.
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Xiancheng Ou, Yuting Chen, Siwei Zhou and Jiandong Shi
With the continuous growth of online education, the quality issue of online educational videos has become increasingly prominent, causing students in online learning to face the…
Abstract
Purpose
With the continuous growth of online education, the quality issue of online educational videos has become increasingly prominent, causing students in online learning to face the dilemma of knowledge confusion. The existing mechanisms for controlling the quality of online educational videos suffer from subjectivity and low timeliness. Monitoring the quality of online educational videos involves analyzing metadata features and log data, which is an important aspect. With the development of artificial intelligence technology, deep learning techniques with strong predictive capabilities can provide new methods for predicting the quality of online educational videos, effectively overcoming the shortcomings of existing methods. The purpose of this study is to find a deep neural network that can model the dynamic and static features of the video itself, as well as the relationships between videos, to achieve dynamic monitoring of the quality of online educational videos.
Design/methodology/approach
The quality of a video cannot be directly measured. According to previous research, the authors use engagement to represent the level of video quality. Engagement is the normalized participation time, which represents the degree to which learners tend to participate in the video. Based on existing public data sets, this study designs an online educational video engagement prediction model based on dynamic graph neural networks (DGNNs). The model is trained based on the video’s static features and dynamic features generated after its release by constructing dynamic graph data. The model includes a spatiotemporal feature extraction layer composed of DGNNs, which can effectively extract the time and space features contained in the video's dynamic graph data. The trained model is used to predict the engagement level of learners with the video on day T after its release, thereby achieving dynamic monitoring of video quality.
Findings
Models with spatiotemporal feature extraction layers consisting of four types of DGNNs can accurately predict the engagement level of online educational videos. Of these, the model using the temporal graph convolutional neural network has the smallest prediction error. In dynamic graph construction, using cosine similarity and Euclidean distance functions with reasonable threshold settings can construct a structurally appropriate dynamic graph. In the training of this model, the amount of historical time series data used will affect the model’s predictive performance. The more historical time series data used, the smaller the prediction error of the trained model.
Research limitations/implications
A limitation of this study is that not all video data in the data set was used to construct the dynamic graph due to memory constraints. In addition, the DGNNs used in the spatiotemporal feature extraction layer are relatively conventional.
Originality/value
In this study, the authors propose an online educational video engagement prediction model based on DGNNs, which can achieve the dynamic monitoring of video quality. The model can be applied as part of a video quality monitoring mechanism for various online educational resource platforms.