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This study aims to develop an associative text analyzer (ATA) to support users in quickly grasping and interpreting the content of large amounts of text through text association recommendations, facilitating the identification of the contextual relationships between people, events, organization and locations for digital humanities. Additionally, by providing text summaries, the tool allows users to link between distant and close readings, thereby enabling more efficient exploration of related texts.

To verify the effectiveness of this tool in supporting exploration of historical texts, this study uses a counterbalanced design to compare the use of the digital humanities platform for Mr. Lo Chia-Lun’s Writings (DHP-LCLW) with and without the ATA to assist in exploring different aspects of text. The study investigated whether there were significant differences in effectiveness for exploring textual contexts and technological acceptance as well as used semi-structured in-depth interviews to understand the research participants’ viewpoints and experiences with the ATA.

The results of the experiment revealed that the effectiveness of text exploration using the DHP-LCLW with and without the ATA varied significantly depending on the topic of the text being explored. The DHP-LCLW with the ATA was found to be more suitable for exploring historical texts, while the DHP-LCLW without the ATA was more suitable for exploring educational texts. The DHP-LCLW with the DHP-LCLW was found to be significantly more useful in terms of perceived usefulness than the DHP-LCLW without the ATA, indicating that the research participants believed the ATA was more effective in helping them efficiently grasp the related texts and topics during text exploration.

The study’s practical implications lie in the development of an ATA for digital humanities, offering a valuable tool for efficiently exploring historical texts. The ATA enhances users’ ability to grasp and interpret large volumes of text, facilitating contextual relationship identification. Its practical utility is evident in the improved effectiveness of text exploration, particularly for historical content, as indicated by users’ perceived usefulness.

This study proposes an ATA for digital humanities, enhancing text exploration by offering association recommendations and efficient linking between distant and close readings. The study contributes by providing a specialized tool and demonstrating its perceived usefulness in facilitating efficient exploration of related texts in digital humanities.

This study aims to examine whether the adoption of artificial intelligence (AI) by audit firms and their clients affects audit efficiency and audit quality.

This study empirically examines the abovementioned research question based on data from China for the years 2011 to 2020. It uses audit report lag as a proxy for audit efficiency and the likelihood of annual report restatement as a proxy for audit quality. It adopts the propensity score matching and the two-stage OLS regression model to address the endogeneity issue led by firms’ innate complicated functions.

The findings show that when audit firms and their clients use AI separately, there's a positive link between AI use and audit report lag. However, when audit firms and clients use AI together, there's a negative link between AI use and audit report delays that enhance overall audit efficiency. Next, the authors observe a negative link between AI use and the likelihood of a restatement. Finally, the authors find that the association between AI adoption and audit quality is driven by increased audit effort lag. Results are consistent and robust to endogeneity tests and sensitivity analyses.

Findings can complement the audit quality and corporate governance literature by clarifying that external audit must evolve through digitalization and the incorporation of newly developed digital tools, such as AI.

The development and evolution of stakeholder collaborative innovation in megaprojects is impacted by various influencing factors. The effect of influencing factors on collaborative innovation performance (CIP) in megaprojects is not a simplistic linear relationship but an iterative and non-linear relationship that requires a dynamic perspective to analyze. Therefore, this paper adopts the system dynamic (SD) approach to investigate the dynamic and interactive relationships between the CIP and the influencing factors.

The study first develops a research framework with the system boundary of “CIP system – organizational collaboration subsystem – knowledge collaboration subsystem – strategic collaboration subsystem”. Then, the causal relationship model, the stock-flow model, and the mathematical equations were determined based on the literature review and the expert interviews. Finally, five performance improvement scenarios were designed according to the practice context of CIP in megaprojects, and simulations were performed using the Vensim PLE software to investigate the CIP from a dynamic perspective.

The findings reveal that the effect of different influencing factors on CIP grows non-linearly, with the cumulative effect becoming more pronounced as time advances. The incentive mechanism has the most significant effect, and the combined effect of multiple influencing factors has a highly significant facilitating effect on improving CIP. Strategic collaboration, organizational collaboration and knowledge collaboration are mutually conditional and reinforcing with each other, which ultimately promotes the improvement of CIP.

This study uncovers the inherent pattern and the interactive dynamic mechanism of factors for improving CIP in the context of megaprojects. It enriches the theoretical research in the area of collaborative innovation in megaprojects and provides practical management strategies for improving CIP.

The lubricating fluid stored in the porous matrix will spontaneously exude to supplement the lubricating film in the damaged area, thus ensuring the long-term self-lubricating function of the porous surface. To reveal the repair mechanism of oil film, it is necessary to understand the flow characteristics of oil in micropores. The purpose of this study guides the design of micropore structure to realize the rapid exudation of oil to the porous surface and the rapid repair of the lubricating film.

In this paper, cylindrical orifice, convergent orifice and divergent orifice were studied. The numerical model of lubricating oil exudation in micropores was established. The distribution characteristics of oil pressure, velocity and three-phase contact line in the process of oil exudation were investigated. The effects of different orifice shapes and orifice structure parameters on the pinning and spreading characteristics of oil droplet were analyzed. Then the internal mechanisms of oil droplet formation and spread on the orifice surface were summarized.

The results show that during the process of oil exudation, the three-phase contact line of the oil drop is pinned once at the edge of the cylindrical and convergent orifice. Compared with the three orifice structures, the inlet pressure of the oil drop is low, and the oil velocity at the pinning point is stable in the divergent orifice. Resulting in favorable oil exudation. It is easier for oil droplet to depin by appropriately reducing the wall wetting angle, increasing the aperture or controlling the wall inclination angle. Ensure the self-healing and long-lasting lubrication film of porous oil-bearing surfaces.

The effect of pore structure on the flow behavior of lubricating fluid has always been concerned. But the mechanism by which different orifice shape affect the pinning behavior of oil droplets is not yet clear, which is crucial for understanding the self-healing mechanism of oil films on porous surfaces. It is meaningful to analyze the mechanism of oil exudation and spreading on the porous surface of oil in the special orifice, to optimize the design of the orifice structure.

Orifice shape has influence on internal flow field parameters. There is no report on the influence of orifice shape on the film formation process of oil seepage and diffusion from pores. The effects of different orifice shapes and orifice structure parameters on the characteristics of oil droplet pinning and diffusion were studied.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-04-2024-0118/

This study explores whether media coverage of Chinese food safety guide consumer behaviour and determines its impact.

Using data from the China Family Panel Studies, this study implements unsupervised machine learning methods to quantitatively identify themes in news media coverage of food safety across various provinces and regions. Based on these findings, this study examines the impact of coverage of food safety on consumer behaviour related to FAFH.

We find that media coverage of food safety in the restaurant sector significantly decreases household expenditure on FAFH relative to total expenditure. While negative coverage substantially decreases expenditure on FAFH, non-negative coverage significantly increases it. Reports of food safety incidents outside consumers’ province are negatively correlated with expenditure on FAFH, whereas reports within province significantly increases such spending. Further, the negative impact of media coverage on FAFH spending is less pronounced among higher-income families, households headed by individuals with high educational levels and those with low sensitivity to newspaper information. A robust government information infrastructure also mitigates this negative impact.

The findings have important policy reference value for promoting the healthy development of catering and other life services by improving news reporting and the regulatory system.

This article employs machine learning methods to identify news reports related to food safety in the catering industry quantitatively and incorporates them into the study of household consumption in China. Consequently, this not only fills a gap in the existing literature but also provides a new perspective for interdisciplinary research in economics, sociology and computer science.

This research explores the community's role in feeding a culturally sustainable development project over time and the practices which operationally allow the bridging of cultural heritage management and sustainable development according to the approach of “culture as sustainability”.

The primary and secondary sources relate to nearly 20 years of life of the Tuscan Mining Geopark case belonging to the United Nations Educational, Scientific and Cultural Organization (UNESCO) European and Global Geopark Networks. Textual analysis was applied to the dataset. The interpretative approach was aligned with other investigations within this research field.

The results highlight how a bold project in an uncertain context harnessed bottom-up mobilisation and accountability to stimulate a sustainable community empowerment. The ability to experiment and learn from experience depicts an organisational logic far from the top-down and predefined design practice widely contested in the literature.

Despite a single case study was analysed, it enables researchers to craft a conceptual model for culturally sustainable development projects, and it fills the literature gap on how to operationalise culture as sustainability under the managerial perspective.

The model assembles an organisational process view and practices that can be tailored to a cultural context with insights for developing culturally sustainable projects.

The research increases the observations of community empowerment within culturally sustainable development projects. It demonstrates how the “incompleteness of the design” was not a weakness but rather a trigger of effective organisational practices.

This study aims to explore the mechanism of boundary-spanning search on firm’s innovation performance under environmental dynamics from the perspective of strategic knowledge integration.

A survey was conducted among Chinese firm managers and R&D personnel, resulting in the collection of 315 valid samples. Hierarchical regression analysis was mainly adopted to demonstrate the hypothesized relationships, while the Sobel test and bootstrap method were used to further validate the mediating effects.

The results demonstrate that boundary-spanning search in different dimensions is a critical factor in the improvement of firm innovation performance (FIP). Two types of strategic knowledge integration are the main factors causing FIP and mediate the influence of boundary-spanning search on FIP. Furthermore, environmental dynamics moderate the relationship among boundary-spanning search, strategic knowledge integration and FIP.

Managers need to strengthen the boundary-spanning search for market and technical knowledge, which will promote firm innovative performance. Managers also need to implement strategic knowledge integration, which specifically includes using planned strategic knowledge integration to compensate for knowledge deficiencies, thereby achieving predetermined objectives; and using emergent strategic knowledge integration to update their understanding of internal and external environments, and to reset strategic objectives. In dynamic environments, managers should emphasize strategic knowledge management activities more.

From a strategic management perspective, this study categorizes strategic knowledge integration into planned and emergent forms. By applying the logic of knowledge acquisition, integration and creation, it explores how boundary-spanning search affects FIP through strategic knowledge integration as the intermediary and the boundary conditions of environmental dynamics. This not only provides a deeper understanding of the nature and effects of boundary-spanning research but also enhances the theory of strategic knowledge management.

Experiential learning is crucial in education, as it offers hands-on, practical experiences that enable individuals to develop their skills and knowledge more engagingly and interactively. In recent years, experiential learning has become a significant aspect of education. To provide academic scholars with a thorough roadmap for further investigation, this study aims to provide useful insights into the bibliometric and content analysis of experiential learning, including keywords, well-known authors, publications, nations and topics.

This research does a rigorous bibliometric analysis to give a thorough and visually instructional assessment of the evolution and advancement of the literature on experiential learning. Its fast development between 1976 and 2022 is meticulously tracked in the research. By using VOSviewer and Biblioshiny tools, the present study presents a concise overview of 507 records retrieved from the Scopus database using the keyword “Experiential Learning”, following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis protocol. Deeper text mining was done using Python libraries “Pandas” and “Natural Language Toolkit” and regular expressions.

The findings reveal a surge in the number of publications on experiential learning and provide insights, particularly using the theory, context, characteristics, methodology analysis, supporting researchers and practitioners to understand learning better and provide perspectives for future research. Descriptive bibliometric analysis showed that most contributions are from the USA, the UK and Canada. In-depth content analysis revealed five clusters: developments in learning, management education, engineering curricula, organisational learning and knowledge management and entrepreneurship education. The keyword co-occurrence analysis enabled linkages between relevant fields of study and significant research domains. The most commonly used theories were: experiential learning theory, social learning theory, relational coordination theory, empowerment theory, feedback learning theory, effectuation theory and human capital theory.

This study uses information from the Scopus database to do a bibliometric analysis of experiential learning from 1976 to 2022. This study serves as a valuable resource for researchers in the field, helping them to position their work more explicitly within the existing literature and highlighting potential areas for future research. It does this by thoroughly analysing the literature on experiential learning using bibliometrics.

This study aims to identify the attitudes of Chinese residents towards tourists and tourism development. Based on periods of observation, temporary residency and several visits for more than a decade, and supplemented by data collected from 478 residents, the study examines to what extent the rural villagers identify the tourism induced changes as being an outcome of official Chinese policies. The villages, Xidi, Hongcun and Nanping, are three heritage villages in Anhui Province and represent appropriate case studies for such an examination due to their differing histories of tourism administrative procedures. Findings contribute to scholarly knowledge by putting pro-poor tourism and community participation under scrutiny in Chinese context. A change of residents’ perceptions towards tourism could potentially be consequential for tourists’ experience and the sustainability of tourism development, particularly in emerging rural destinations.

Breakthrough technological innovation is of vital significance for firms to acquire and maintain sustainable competitive advantages. The construction of an innovation ecosystem and the interaction with heterogeneous participants have emerged as a new dominant model for driving sustained breakthrough technological innovation in firms. This study aims to explore the effects of collaborative modes within the innovation ecosystem on firms’ breakthrough technological innovation and the ecological legitimacy mechanisms involved.

The research employs data from 212 innovative firms and conducts empirical research using a two-stage structural equation modeling (SEM) and artificial neural network (ANN) analysis.

The results indicate that firm-firm collaboration (FF), firm-user collaboration (FU), firm-government collaboration (FG), firm-university-institute collaboration (FUI) and firm-intermediary collaboration (FI) all have significant positive effects on breakthrough technological innovation (BTI), with FU being particularly crucial. Furthermore, the results confirm the positive moderating effects of ecological legitimacy (EL) on the relationships between FF and BTI, as well as between FU and BTI. Conversely, EL has a negative moderating effect on the relationship between FUI and BTI, as well as between FI and breakthrough technological innovation. Additionally, EL does not have a significant influence on the relationship between FG and BTI.

Through resource dependence theory (RDT), this study unveils the black box of how collaboration modes within innovation ecosystems impact breakthrough technological innovation. By introducing ecological legitimacy as a contextual factor, a new research perspective is provided for collaboration innovation within innovation ecosystems. The study employs a combination of SEM and ANN for modeling, complementing nonlinear relationships and obtaining robust results in complex mechanisms.