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The core objective of this study is to provide an in-depth quantitative assessment of the efficiency of public library knowledge services (PLKS) in China and to scrutinize the factors that have a significant impact on the efficiency of PLKS. Furthermore, this study also aims to examine the characteristics and evolving patterns of PLKS in China and to propose strategies for enhancing the quality of services provided by public libraries. The findings of this paper are expected to provide valuable references for current academic research and practice areas, guiding and promoting exploration and development in related fields.

To analyse and evaluate the operation mechanism and efficiency of PLKS, this study creatively constructs a multi-stage PLKS efficiency evaluation model and provides related indicators. Based on this process, the super-efficiency network slacks-based measure model was used to analyse the efficiency, and dynamic qualitative comparative analysis was adopted to analyse the recipes about the influencing factors of PLKS. Ultimately, through a comprehensive interpretation of the measured data and the integration of extant societal development conditions, the authors put forth relevant recommendations.

In the first stage, PLKS in China meets the basic requirements, but in the second stage, there is evident resource wastage. In addition, there are five recipes in PLKS of China. These five recipes reveal the configuration relationship between the factors that affect PLKS. The results show that PLKS in China are different in different regions, and the effects of the influencing factors are also different.

In this study, the authors provide an exhaustive deconstruction and interpretation of PLKS, thereby proposing a three-stage PLKS efficiency conversion process. Furthermore, the authors have identified a set of readily accessible and quantifiable indicators. It is worth emphasizing that the authors have taken a unique approach to analyse the elements affecting PLKS from the perspective of configuration, which has significantly broadened the boundaries and depth of PLKS research.

This study integrated the service gap of the PZB model, hidden importance and Taguchi’s quality engineering to develop a new two-dimensional strategic matrix, the Hidden Importance and Relative Quality Performance (HI-RQP) model. The HI-RQP model was then used to determine the managerial implications and improvement direction of memorable dining experience (MDE) attributes of Michelin-starred restaurants (MSRs).

This study collected 619 MDE questionnaires from customers of seven MSRs.

The results reveal that the HI-RQP model comprises four quadrants. Professional and high-quality service, carefully prepared dishes, restaurant style and customer-oriented service attitude are competitive advantages that should be maintained. Conversely, taste and freshness that exceed customers’ expectations and provide extra services to customers are MDE attributes that require urgent improvement.

Besides contributing practically to the enhancement of MDE in MSRs, the findings facilitate a more plausible identification of MDE attributes by integrating various theories into the HI-RQP model.

This study aims to empirically investigate how knowledge paradox affects collaboration performance. Knowledge paradox, which arises from the simultaneous need for knowledge sharing and protection, is common in interorganizational collaboration. Using the ambidexterity perspective, this paper aims to reexamine the effect of the knowledge paradox on collaborative performance to explore the moderating roles of structural and contextual ambidexterity.

This study used a sample of 153 firms involved in vertical and horizontal collaboration, collected via questionnaires. Hypotheses were tested using hierarchical regression analysis.

This study demonstrates that the stronger the knowledge paradox is, the higher the potential for value creation. Thus, knowledge paradox has a positive impact on collaborative performance. The functions of structural ambidexterity and contextual ambidexterity strengthen this positive relationship.

This paper not only expands the theoretical application of the knowledge paradox and ambidexterity theory in the context of interorganizational relationships but also provides significant managerial implications. By comprehending the dynamics of the knowledge paradox and the role of ambidexterity, managers can make well-informed decisions to enhance their collaborative performance.

This study aims to develop a low-cost additive-subtractive hybrid machine equipped with reverse scanning to fabricate high-precision dental surgical guides. The major focus of developing the hybrid additive manufacturing technology is to achieve clinical precision of dental tools at an affordable price.

The designed machine consists of a self-developed vat-photopolymerization-based 3D printer that can fabricate dental surgical guides. The 3D printer is integrated with a self-developed 3D scanner that will analyze the fabricated part and evaluate the dimensional discrepancies. Based on the data provided by the scanner, the integrated secondary milling process will successfully machine the part to meet the clinical precision and standard.

The efficacy of the newly developed hybrid machine is demonstrated with the fabrication of complex part, lower and upper dental surgical guides with the mean dimensional deviations of 198.1, 136.6 and 117.9 µm, respectively. The integration of the secondary scanning and machining system successfully enhanced the mean dimensional deviation of upper and lower guides by 11.88% and 28.75%, respectively. Furthermore, this study also benchmarked the dimensional accuracies achieved by this low-cost technology with the high-end commercial 3D printers. The overall cost of the machine is evaluated to be $2,399.

This paper proposes a novel hybrid additive manufacturing process with integrated reverse scanning and machining modules to fabricate high-precision dental guides. The developed machine is a low-cost alternative to the existing high-end commercial counterparts. The developed machine has the potential to make endodontic treatments more affordable.

This research addresses the challenge of polysemous words in word embedding techniques, which are commonly used in text mining. It aims to resolve word sense ambiguity by introducing a social network sense disambiguation (SNSD) model based on social network analysis (SNA).

The SNSD model treats words as members of a social network and their co-occurrence relationships as interactions. By analyzing these interactions, the model identifies words with high betweenness centrality, which may act as bridges between different word sense communities, indicating polysemy. This unsupervised method does not rely on pre-tagged resources and is validated using the IMDb dataset.

The SNSD model effectively resolves word sense ambiguity in word embeddings, proving to be a cost-effective and adaptable solution to this issue. The experimental results demonstrate that the model enhances the accuracy of word embeddings by accurately identifying the correct meanings of polysemous words.

This study is the first to apply SNA to word sense disambiguation (WSD). The SNSD model offers a novel, unsupervised approach that overcomes the limitations of traditional supervised or knowledge-based methods, providing a valuable contribution to the field of text mining.

To address the various irregularities that occurred during the development of China’s electricity market, particularly the issue of collusive pricing between upstream and downstream firms.

This study constructs a tripartite evolutionary game model involving government regulators, grid operators and power producers to address electricity market pricing chaos. By analyzing the stable strategies within each subject’s evolutionary game, adjustments to the relevant parameters are made to achieve a stable state of strategy selection.

The findings of this study indicate the following: (1) Enhancing the government’s rewards and punishments, increasing speculation and rent-seeking costs for grid operators and modifying tariff sales revenue can promote the integrity of grid operators. (2) Establishing reasonable incentives and penalties can effectively mitigate rent-seeking behaviors resulting from collusive pricing in the power industry. (3) Strengthening the accountability of higher authorities to government regulators and adjusting incentives for grid operators to comply and generators to refrain from rent-seeking behavior can increase the likelihood of rigorous inspections by government regulators.

This study elucidates the impact of factors such as the cost of speculation and sales revenue of grid operators, the cost of rent-seeking by power producers and the strength of rewards and punishments by government departments on the power sector. Adjusting these factors can significantly influence the stability of the three-party evolutionary game, providing valuable insights into the regulatory mechanisms of the power industry.

This study uses data from the Chinese banking sector to explore the relationship between green credit and risk-taking in commercial banks. It also examines whether the level of regional green development acts as a moderator regarding this relationship.

Using a dataset composed of annual observations from 57 Chinese commercial banks between 2008 and 2021, this study employs both piecewise and curvilinear models.

Our results indicate that when the scale of green credit is low (<0.164), it increases the risk-taking of commercial banks. Conversely, when the scale of green credit is high (>0.164), it reduces the risk-taking of commercial banks. Moreover, this nonlinear relationship impact exhibits bank heterogeneity. Furthermore, the results show that the level of regional green development and local government policy support negatively moderate the relationship between green credit and commercial bank risk-taking. Furthermore, we find that green credit can directly enhance the net interest margin of commercial banks.

This study is the first to provide evidence of a nonlinear relationship between green credit and risk-taking in commercial banks, and it identifies the significant roles of regional green development level and local government policy support in the Chinese context.

This paper aims to provide a reference for the development of digital transformation from the perspective of manufacturing process links.

This paper applies canonical correlation analysis based on digital technology patents in the key links of manufacturing industries (product design, procurement, product manufacturing, warehousing and transportation, and wholesale and retail) and the related indicators of economic benefits of regions in China.

(1) The degree of digitalization of manufacturing process links is significantly correlated with economic benefits. (2) The improvement of the degree of digitalization in the “product design” link, the “warehousing and transportation” link, the “product manufacturing” link and the “wholesale and retail” link has significant impacts on the economic benefits of manufacturing industry. (3) The digital degree of the “procurement” link has no obvious influence on the economic benefits of manufacturing industry.

The research results can provide reference for the formulation and implementation of micro policies. The strategy of improving the level of digital transformation of key links of manufacturing industry is put forward to better promote both the digital transformation of manufacturing industry and economic development.

This paper innovatively studies the relationship between digitalization of manufacturing process links and economic benefits. The findings can provide theoretical and empirical support for the digital transformation of China's manufacturing industry and high-quality development of economy.

Live-streaming platforms emphasize dynamic social interaction and fan engagement. Users integrate into the live-streaming community through continuous social learning activities, such as sending bullet comments, reviewing comments and interacting with celebrities. However, comprehensive research on the transactional intricacies of live-streaming e-commerce from the perspectives of community and learning is still lacking.

Focusing on the behavior characteristics of the reference group represented by online celebrities and fans in the live-streaming environment, this study utilized social learning as the theoretical basis to examine how reference groups affect consumer purchase intention through a series of intermediary effects. An empirical investigation and machine learning algorithms were utilized to explore and verify the hypothesized model.

The results show that: (1) reference groups’ behavior positively stimulated social presence and enhanced consumer purchase intention through the chain-mediating effect of social presence and trust in online celebrities; (2) celebrity characteristics (professionalism, attractiveness and interactivity) positively impacted consumer trust; (3) in addition, machine learning algorithms substantiated that reference groups’ behavior, social presence, trust and celebrity characteristics had a remarkably robust predictive effect on purchase intention.

These findings hold theoretical implications for understanding how the social community affects consumers’ purchase intention in the live-streaming context and practical significance for marketing strategies toward live-streaming e-commerce.

With increasing pressure to achieve environmental sustainability, hotel organizations implement green human resource management (GHRM) to inspire employees’ green behavior to improve environmental performance. Following the conservation of resources theory, this research aims to examine how GHRM fosters employee green advocacy.

Data were obtained from 315 employees from 24 hotels in China. This study used the SPSS PROCESS to test the mediation and moderated mediation model.

The results showed that GHRM has a positive impact on green advocacy, and harmonious environmental passion (HEP) fully mediates the positive relationship between GHRM and green advocacy. Furthermore, the relationship between GHRM, HEP and green advocacy is moderated by environmentally specific transformational leadership (ESTL). Subsequently, the findings imply that the indirect effect of GHRM on green advocacy via HEP is stronger while ESTL is higher.

This study extends the research on GHRM and green advocacy by exploring how and when GHRM stimulates employee green advocacy via HEP in the Chinese context.