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The view that dynamic capabilities theory can help explain how lean organizations improve has been put forward by scholars. However, there is still a lack of research on the matching relationship between the application of lean practice and the internal elements of enterprise organization from the perspective of dynamic capabilities. The purpose of this study is to validate the moderating effect of dynamic capabilities on the relationship between lean practices and operational performance.

This study used the method of survey and empirical research to collect sample data from 263 enterprises in China. Through literature review, this study put forward the moderating hypotheses around dynamic capabilities, lean practices and operation performance and used the method of regression analysis to validate these hypotheses.

The results showed that dynamic capabilities have a partially moderating effect on the application of lean practices. Specifically, dynamic capabilities have a significant moderating effect on the relationship between just-in-time, total quality management, total preventive maintenance and operational performance, while dynamic capabilities have no significant moderating effect on the relationship between human resource management and operational performance.

The research conclusion complements and enriches the lean practices literature from the perspective of dynamic capabilities. Existing studies mainly focus on the moderating role of external environmental factors, while there is a lack of empirical research on the role of dynamic capabilities in lean practices literature. The research results will help enterprises further understand the matching relationship between lean practices and dynamic capabilities and then improve the success of lean practices application.

This paper aims to explore the impact of cycle superposition on bank liquidity risk under different levels of financial openness so that banks can better manage their liquidity risk. Meanwhile, it can also provide some ideas for banks in other emerging economies to better cope with the shocks of the global financial cycle.

Employing the monthly data of 16 commercial banks in China from 2005 to 2021 and based on the time-varying parameter vector autoregressive model with stochastic volatility (TVP-SV-VAR) model, the authors first examine whether the cycle superposition can magnify the impact of China's financial cycle on bank liquidity risk. Subsequently, the authors investigate the impact of different levels of financial openness on cycle superposition amplification. Finally, the shock of the financial cycle of the world's major economies on the liquidity risk of Chinese banks is also empirically analyzed.

Cycle superposition can magnify the impact of China's financial cycle on bank liquidity risk. However, there are significant differences under different levels of financial openness. Compared with low financial openness, in the period of high financial openness, the magnifying effect of cycle superposition is strengthened in the short term but obviously weakened in the long run. In addition, the authors' findings also demonstrate that although the United States is the main shock country, the influence of other developed economies, such as Japan and Eurozone countries, cannot be ignored.

Firstly, the cycle superposition index is constructed. Secondly, the authors supplement the literature by providing evidence that the association between cycle superposition and bank liquidity risk also depends on financial openness. Finally, the dominant countries of the global financial cycle have been rejudged.

The study aims to investigate the effects of intellectual capital and its constituents on the performance of listed companies operating in China's construction sector. The study also intends to examine the moderating role of digital transformation.

Hypotheses will be tested using Modified Value-Added Intellectual Capital (MVAIC). The sample will be comprised of 93 Shenzhen and Shanghai A-share listed companies within the construction industry from the period of 2015–2021. Multiple regression analysis was employed to investigate the influence of intellectual capital, its components and digital transformation on the performance of construction firms.

The study's results reveal that the performance of construction firms greatly depends on intellectual capital and its components. Furthermore, digital transformation plays a vital moderating role between intellectual capital and its components and construction firm performance.

This study addresses a critical inquiry on how construction managers can employ intellectual capital to enhance the performance of firms during digital transformation. Additionally, this research bridges this gap by guiding construction managers to concentrate on their external surroundings when examining firm performance.

By focusing on the predictors influencing construction firms' performance, this study contributes to the existing corpus of knowledge. This study employs resource orchestration theory (ROT) to determine how the different components of intellectual capital impact the performance of construction firms, with digital transformation acting as a moderating variable. This research will be valuable to researchers, construction industry professionals and policymakers.

Digital technologies over time are becoming increasingly pervasive and relatively affordable, finding a large diffusion in Small and Medium Enterprises (SMEs) also for internationalization purposes. However, less is known about the specific mechanisms by which this can be achieved. Specifically, we focus on how SMEs can face the international environment, leveraging digital technologies and thanks to their intellectual capital (IC).

We analyze the relationship between digital technologies and the internationalization of SMEs, exploring the mediating role of IC in its three dimensions: human, relational and innovation capital, and assessing the possible moderating effects posed by international institutional conditions, specifically the Sino-US trade frictions. The relationships are tested using a sample of companies listed on China’s A-share Growth Enterprise Market (GEM) from 2010 to 2021.

Digital technologies help to internationalize SMEs. However, this positive relationship is affected (mediated) by the presence of an already consolidated IC. In addition, the institutional conditions of the international market, such as the Sino-US trade friction, moderate the components of IC differently. Specifically, the overall mediating effect of human and relational capital is boosted, while this does not happen for innovation capital.

First, this study contributes to the literature on organizational resilience, especially digital resilience, confirming its validity in the context of internationalization and, in particular, those processes adopted by SMEs. Second, we clarify the mechanisms through which digital technologies exert their impact on the process of internationalization and in particular the prominent necessity of having IC. Third, our conclusions enrich the understanding of how IC components react to turbulence in international markets.

Sharing and disseminating debunking information are critical to correcting rumours and controlling disease when dealing with public health crises. This study investigates the factors that influence social media users' debunking information sharing behaviour from the perspective of persuasion. The authors examined the effects of argument adequacy, emotional polarity, and debunker's identity on debunking information sharing behaviour and investigated the moderating effects of rumour content and target.

The model was tested using 150 COVID-19-related rumours and 2,349 original debunking posts on Sina Weibo.

First, debunking information that contains adequate arguments is more likely to be reposted only when the uncertainty of the rumour content is high. Second, using neutral sentiment as a reference, debunking information containing negative sentiment is shared more often regardless of whether the government is the rumour target, and information containing positive sentiment is more likely to be shared only when the rumour target is the government. Finally, debunking information published by government-type accounts is reposted more often and is enhanced when the rumour target is the government.

The study provides a systematic framework for analysing the behaviour of sharing debunking information among social media users. Specifically, it expands the understanding of the factors that influence debunking information sharing behaviour by examining the effects of persuasive cues on debunking information sharing behaviour and the heterogeneity of these effects across various rumour contexts.

This study aims to use cognitive appraisal theory to explain how organizational disruption influences the development of envy resulting in unethical selling practices, turnover intentions and a reduction in customer orientation that causes disruption to impact customer relationships. This research helps to address drivers of salesperson envy, the potential disruptions to customer relationships and the required need to invest in psychological resources to offset these negative effects.

A total of 211 salespeople were surveyed to test the hypotheses. First, the measurement model was validated using a confirmatory factor analysis. Next, the hypotheses were tested using structural equation modeling AMOS 27. Mediation and moderated mediation were tested using the bootstrap method. Estimands were created within AMOS to test the indirect and interaction effects in the full model. A post hoc analysis further informed the findings.

The results show that the development of envy increases under conditions of organizational disruptions, leading to potential customer disruptions through turnover intentions, unethical selling behaviors and a reduction in customer orientation. In addition, the mediation analysis shows that envy drives the relationship between organizational disruption and unethical selling, turnover intentions and customer orientation through fully mediated relationships. Finally, the interaction effects between organizational disruption and psychological capital show high levels of psychological capital help to decrease the development of envy, thus reducing unethical selling behaviors and turnover intentions while increasing customer orientation.

The study provides practitioners with insights into how to reduce envy by investing in the psychological capital of their salesforce. The study also provides suggestions for handling disruptions and managing envy to prevent actions that act to damage customer relationships.

Salespeople are likely to encounter organizational disruption. Sales managers need to be prepared to manage the outcomes of organizational disruption as it impacts the sales force. Understanding how disruptions impact customer relationships through envy is an important yet under-explored topic. This research adds to and expands the sales literature using cognitive appraisal theory to help address drivers of salesperson envy and its potentially negative impact on customer relationships and shows the required need to invest in psychological resources to offset these negative effects. The study also helps expand the recent focus on worldwide disruptions by adopting another context for disruption stemming from organizational disruption.

This study aims to examine the moment-to-moment (MTM) effects of in-consumption dynamic comments on consumers' responses to digital engagement and the underlying mechanisms involved, as well as the interactive role of advertisements embedded in short-form online video.

This study uses data extracted from 2,081 videos posted on the prominent Chinese online live platform, Bilibili. The hypotheses are tested using regression models and natural language processing.

The results indicate that the intensity of live comments at the beginning negatively affects users' digital engagement, while a corresponding increase in live comments at the end elicits a positive effect. A linear trend and peak difference in live comments intensity positively affect digital engagement, while the variability of live comment intensity exerts a negative effect. These MTM effects were driven by sentiments of live comments. Furthermore, in-video advertisements are likely to amplify the negative beginning effect on users' digital engagement and mitigate the negative variability of live comments.

This study is the first to examine the direct effects of MTM comments from the online temporal sequence perspective, differentiating the process- and performance-based engagement. The mechanism and interactive role of in-video advertisements were identified. These findings contribute to literature on interactive marketing and provide valuable guidance for influencer marketing.

This study aims to extract knowledge of ancient Chinese scientific and technological documents bibliographic summaries (STDBS) and provide the knowledge graph (KG) comprehensively and systematically. By presenting the relationship among content, discipline, and author, this study focuses on providing services for knowledge discovery of ancient Chinese scientific and technological documents.

This study compiles ancient Chinese STDBS and designs a knowledge mining and graph visualization framework. The authors define the summaries' entities, attributes, and relationships for knowledge representation, use deep learning techniques such as BERT-BiLSTM-CRF models and rules for knowledge extraction, unify the representation of entities for knowledge fusion, and use Neo4j and other visualization techniques for KG construction and application. This study presents the generation, distribution, and evolution of ancient Chinese agricultural scientific and technological knowledge in visualization graphs.

The knowledge mining and graph visualization framework is feasible and effective. The BERT-BiLSTM-CRF model has domain adaptability and accuracy. The knowledge generation of ancient Chinese agricultural scientific and technological documents has distinctive time features. The knowledge distribution is uneven and concentrated, mainly concentrated on C1-Planting and cultivation, C2-Silkworm, and C3-Mulberry and water conservancy. The knowledge evolution is apparent, and differentiation and integration coexist.

This study is the first to visually present the knowledge connotation and association of ancient Chinese STDBS. It solves the problems of the lack of in-depth knowledge mining and connotation visualization of ancient Chinese STDBS.

The paper aims to elucidate effective strategies for promoting the adoption of green technology innovation within the private sector, thereby enhancing the value of public–private partnership (PPP) projects during the operational phase.

Utilizing prospect theory, the paper considers the government and the public as external driving forces. It establishes a tripartite evolutionary game model composed of government regulators, the private sector and the public. The paper uses numerical simulations to explore the evolutionary stable equilibrium strategies and the determinants influencing each stakeholder.

The paper demonstrates that government intervention and public participation substantially promote green technology innovation within the private sector. Major influencing factors encompass the intensity of pollution taxation, governmental information disclosure and public attention. However, an optimal threshold exists for environmental publicity and innovation subsidies, as excessive levels might inhibit technological innovation. Furthermore, within government intervention strategies, compensating the public for their participation costs is essential to circumvent the public's “free-rider” tendencies and encourage active public collaboration in PPP project innovation.

By constructing a tripartite evolutionary game model, the paper comprehensively examines the roles of government intervention and public participation in promoting green technology innovation within the private sector, offering fresh perspectives and strategies for the operational phase of PPP projects.

This paper aims to present a systematic literature review and bibliometric analysis of research papers published on chat generative pre-trained transformer (ChatGPT), an OpenAI-developed large-scale generative language model. The study’s objective is to provide a comprehensive assessment of the present status of research on ChatGPT and identify current trends and themes in the literature.

A total of 328 research article data was extracted from Scopus for bibliometric analysis, to investigate publishing trends, productive countries and keyword analysis around the topic and 34 relevant research publications were selected for an in-depth systematic literature review.

The findings indicate that ChatGPT research is still in its early stages, with the current emphasis on applications such as natural language processing and understanding, dialogue systems, speech processing and recognition, learning systems, chatbots and response generation. The USA is at the forefront of publishing on this topic and new keywords, e.g. “patient care”, “medical”, “higher education” and so on are emerging themes around the topic.

These findings underscore the importance of ongoing research and development to address these limitations and ensure that ChatGPT is used responsibly and ethically. While systematic review research on ChatGPT heralds exciting opportunities, it also demands a careful understanding of its nuances to harness its potential effectively.

Overall, this study provides a valuable resource for researchers and practitioners interested in ChatGPT at this early stage and helps to identify the grey areas around this topic.