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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.

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.

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.

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.

With the rapid development of short videos in China, the public has become accustomed to using short videos to express their opinions. This paper aims to solve problems such as how to represent the features of different modalities and achieve effective cross-modal feature fusion when analyzing the multi-modal sentiment of Chinese short videos (CSVs).

This paper aims to propose a sentiment analysis model MSCNN-CPL-CAFF using multi-scale convolutional neural network and cross attention fusion mechanism to analyze the CSVs. The audio-visual and textual data of CSVs themed on “COVID-19, catering industry” are collected from CSV platform Douyin first, and then a comparative analysis is conducted with advanced baseline models.

The sample number of the weak negative and neutral sentiment is the largest, and the sample number of the positive and weak positive sentiment is relatively small, accounting for only about 11% of the total samples. The MSCNN-CPL-CAFF model has achieved the Acc-2, Acc-3 and F1 score of 85.01%, 74.16 and 84.84%, respectively, which outperforms the highest value of baseline methods in accuracy and achieves competitive computation speed.

This research offers some implications regarding the impact of COVID-19 on catering industry in China by focusing on multi-modal sentiment of CSVs. The methodology can be utilized to analyze the opinions of the general public on social media platform and to categorize them accordingly.

This paper presents a novel deep-learning multimodal sentiment analysis model, which provides a new perspective for public opinion research on the short video platform.

The combination of improved PSO (IPSO) algorithm and artificial neural network (ANN) model for intelligent monitoring of the bearing performance of the hydrostatic turntable.

This paper proposes an artificial neural network model based on IPSO algorithm for intelligent monitoring of hydrostatic turntables.

The theoretical model proposed in this paper improves the accuracy of the working performance of the static pressure turntable and provides a new direction for intelligent monitoring of the static pressure turntable. Therefore, the theoretical research in this paper is novel.

Theoretical novelties: an ANN model based on the IPSO algorithm is designed to monitor the load-bearing performance of a static pressure turntable intelligently; this study show that the convergence accuracy and convergence speed of the IPSO-NN model have been improved by 52.55% and 10%, respectively, compared to traditional training models; and the proposed model could be used to solve the multidimensional nonlinear problem in the intelligent monitoring of hydrostatic turntables.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-03-2024-0081/

The purpose of this study is to empirically explore the impact of government subsidies for the digital economy on corporate innovation. It aims to determine whether these subsidies promote innovation, and to examine the specific ways in which they inspire corporate innovation.

This study selects Chinese A-share listed companies during the period from 2007 to 2019 as the research object. It employs panel data to empirically examine the impact of government subsidies in the digital economy on corporate innovation.

The findings reveal that government subsidies for the digital economy effectively promote corporate innovation. They significantly increase the number and share of invention patents and improve the quality of corporate innovation. Moreover, it is noted that the positive impact is largely confined to non-state-owned enterprises, small firms and those in highly competitive markets.

The contribution of this paper lies in focusing on government subsidies in the digital economy, which is distinct from the general government subsidies in a broad sense.

This study aims to examine the relationship between leadership behavior, organizational justice, person–organization fit and organizational citizenship behavior in the context of Vietnamese academic libraries. Using social exchange theory, this research indicates the impact of leadership behavior on organizational citizenship behavior. This study also examines the mediating role of organizational justice and person–organization fit in the relationship between leadership behavior and organizational citizenship behavior.

A total of 248 responses are obtained from academic library personnel in Vietnam, which are used to examine the research hypotheses.

The findings partially support the hypotheses because two leadership dimensions significantly influence organizational citizenship behavior, and organizational justice mediates the relationship between relationship-oriented leadership and organizational citizenship behavior. However, person–organization fit does not mediate the relationship between leadership behavior and organizational citizenship behavior.

Results indicate that two types of leadership behavior can significantly impact the organizational citizenship behavior of the librarians. Academic libraries should provide opportunities to librarians to engage in citizenship behavior by implementing organizational justice intervention.

This research contributes to the social exchange theory by integrating leadership behaviors, organizational justice, person–organization fit and organizational citizenship behaviors. Given that no prior studies have investigated the associations among four constructs, the obtained findings are a new exploration.

Social media texts as a data source in depression research have emerged as a significant convergence between Information Management and Public Health in recent years. This paper aims to sort out the depression-related study conducted on the text on social media, with particular attention to the research theme and methods.

The authors finally selected research articles published in Web of Science, Wiley, ACM Digital Library, EBSCO, IEEE Xplore and JMIR databases, covering 57 articles.

(1) According to the coding results, Depression Prediction and Linguistic Characteristics and Information Behavior are the two most popular themes. The theme of Patient Needs has progressed over the past few years. Still, there is a lesser focus on Stigma and Antidepressants. (2) Researchers prefer quantitative methods such as machine learning and statistical analysis to qualitative ones. (4) According to the analysis of the data collection platforms, more researchers used comprehensive social media sites like Reddit and Facebook than depression-specific communities like Sunforum and Alonelylife.

The authors recommend employing machine learning and statistical analysis to explore factors related to Stigmatization and Antidepressants thoroughly. Additionally, conducting mixed-methods studies incorporating data from diverse sources would be valuable. Such approaches would provide insights beneficial to policymakers and pharmaceutical companies seeking a comprehensive understanding of depression.

This article signifies a pioneering effort in systematically gathering and examining the themes and methodologies within the intersection of health-related texts on social media and depression.

Given the COVID-19 Pandemic outbreak and the role of medical textiles for protection, this study aims to identify the leading research foci on using textile materials for personal protection in pandemic situations.

A systematic review and systemic analysis of the literature on the subject were performed using the process knowledge development – constructivist (ProKnow-C) methodology.

A bibliographic portfolio with 16 relevant studies was obtained. This portfolio represents the main focus of this research field, including the main filtration mechanisms, ways of disinfecting N95 respirators and proposed methods to evaluate the filtration efficiency of different materials with potential for mask development.

To the best of the authors’ knowledge, this is the first time the ProKnow-C methodology was used in the textile field. Thus, future studies can benefit from using the Proknow-C for selecting and analyzing relevant textile studies following a systematic approach.

This study aims to explore the dynamics between the brand manufacturer’s revenue model choice and the platform’s private label product entry strategy, specifically, (1) Under the wholesale and agency models, when should the platform introduce its private label product to compete with the manufacturer? (2) Facing the potential threat of the platform’s entry, how should the manufacturer choose between the wholesale and agency models? (3) How does the platform’s entry strategy affect the manufacturer’s price decisions and demand? (4) What are the implications of the strategic interaction between the manufacturer’s model selection and the platform’s encroachment on social welfare and consumer surplus?

This study develops a multistage game model consisting of a manufacturer, a platform and consumers. The model describes the strategic interaction between the manufacturer and the platform, where the manufacturer first chooses one of the revenue models from the agency model and the wholesale model, followed by the platform’s decision whether to offer its own products to enter the competition, after which the two parties set the price of their products to compete on price according to their strategies, then the consumers make purchase decisions based on the principle of utility maximization.

For the platform, to not hurt its profitability in the manufacturer channel with too much competition, lower social utility sensitivity and lower similarity of product imitation rather favor platform entry. Platform entry affects manufacturers’ retail prices and demand differently across different revenue models. Interestingly, if the social utility sensitivity and imitation similarity are moderate, when the commissions extracted by the platform are low, manufacturers still have the incentive to adopt the wholesale model rather than the agency model. In addition, platform entry into competition increases consumer surplus and social welfare only when consumer sensitivity to social utility is low.

The research model innovatively describes the strategic interaction between the manufacturer and the platform; to more accurately portray the consumer demand model, this model also introduces the parameters of the similarity of the platform’s products to the products of the manufacturer, as well as the social utility sensitivity of consumers. Conclusions are drawn on the choice of platform entry strategy versus the choice of revenue model for manufacturers. Relevant managerial insights are provided for both platforms and manufacturers, which partially explains the existing market situation.

In modern China, sports and nationalism always have close connection, and nationalism is the important reason for the promotion of Chinese sports. However, the relationship between Chinese sports and nationalism in globalised China could be much more examined by academics, as well as its influencing factors. This chapter selects the Beijing 2008 Olympic Games as the context and representative three Chinese sports heroes in the period of globalisation to study. The findings show that in some extent, Beijing 2008 Olympic Games and three Chinese sports heroes represent the national image of China in the globalised world, also bearing the burden of washing away historical humiliation and pursuing national glory. Furthermore, it is manifested that China have a complex nationalism in the process of hosting the 2008 Olympic Games. Under the influence of mass media, market economy and sports professionalisation, nationalism still exists in Chinese sports, but people gradually start to reflect on the ‘Juguo Tizhi’, the traditional Chinese sports system and the concept of ‘winning glory for the nation’. The relationship between Chinese nationalism and sports shows the important implications of rapid Chinese sports development.

This study aims to explore whether top management team (TMT) faultlines affect corporate digitalization and what the impact mechanism is, thus effectively promoting the digital transformation of enterprises from the perspective of optimizing TMT structure.

This study sampled companies that were listed in China between 2011 and 2020. Using the two-way fixed effect model, it empirically tests the impact of TMT faultlines on the digital transformation of enterprises.

TMT task-related faultline significantly positively impacts enterprise digital transformation, while the bio-demographic faultline has a significant negative effect. The regulatory role played by Chief Executive Officer (CEO) power intensity in the relationship between the bio-demographic faultline and digital transformation is a negative one. The above relationship is strongly influenced by industry technical sophistication, corporate location and listing board.

The research has promoted the development of the upper echelons theory in the context of digitalization. Moreover, it enlightens the research of digital transformation’s influencing factors and mechanisms. However, no suitable mediating variable was found.

This research has significant implications for managers to optimize the internal structure of the TMT according to different enterprises’ business strategies in order to establish an efficient management team.

This study provides a new theoretical framework for TMT’s role in enterprise digital transformation. Further, it makes a beneficial exploration of the boundary and situational conditions of their relationship.