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This study investigates how the complexity of sentiment in online reviews affects perceived helpfulness. Analyzed over 730,000 reviews from Tripadvisor.com, the research explores how information overload and increased cognitive load impact consumer decision-making.

This study applied the BERT deep learning model to analyze sentiment complexity in online reviews. Based on cognitive load theory, we examined two key factors: the number of attributes mentioned in a review and the variation in sentiment valence of across attributes to evaluate their impact on cognitive load and review helpfulness.

The results show that a higher number of attributes and greater variation in sentiment valence increase cognitive load, reducing review helpfulness. Reviewers’ expertise and review readability further moderate these effects, with complex or expert-written reviews worsening the negative impact.

This research introduces a method for measuring attribute-level sentiment complexity and its impact on review helpfulness, emphasizing the importance of balancing detail with readability. These findings provide a foundation for future studies on review characteristics and consumer behavior.

Based on the Cognitive Appraisal Theory of Stress, this study aims to reveal the mechanism of peer abusive supervision on bystander proactive behavior through two different paths: bystander assertive impression management motivation and bystander defensive impression management motivation. Besides, the moderating effects of bystander uncertainty tolerance on the two paths are also explored.

In this study, 438 employees and their direct leaders from eight Chinese companies were surveyed in a paired survey at three time points, and the empirical data was analyzed using Mplus 7.4 software.

Peer abusive supervision leads bystanders to develop assertive impression management motivation and, thus, to exhibit more proactive behaviors. At the same time, peer abusive supervision also causes bystanders to develop defensive impression management motivation, which reduces the frequency of performing proactive behaviors. In addition, this study finds that bystander uncertainty tolerance plays a moderating role in influencing bystander assertive impression management motivation and bystander defensive impression management motivation in response to peer abusive supervision.

Starting from the bystander perspective, this study verifies the double-edged sword effect of peer abusive supervision on bystander proactive behavior as well as the mechanism of differentiated effects through cognitive appraisal, which broadens the scope of the research on abusive supervision, and deepens the academic understanding and development of the Cognitive Appraisal Theory of Stress. At the same time, it also provides new ideas for organizations to reduce the negative effects of workplace abusive behavior.

This paper explores the association between directors’ and officers’ liability insurance (D&O insurance) and management tone manipulation.

This study uses data from A-share listed non-financial companies from 2009 to 2021 as its sample for empirical tests. In addition, the study relies on text analysis and the construction of models to investigate the relationship between D&O insurance and management tone manipulation.

The authors find that the purchase of D&O insurance will lead to management tone manipulation in the “management discussion and analysis” part of companies’ annual reports, and operating risk and agent cost are the two paths for the effect. Further analysis shows that having a male CEO and employing high-quality auditors can weaken the positive impact of D&O insurance on tone manipulation.

This paper provides a new approach for studying the literature related to D&O insurance and management behavior, and the findings enrich our understanding of the influencing factors and the mechanism of management tone manipulation, thus revealing policy implications for further standardization of the terms and system of D&O insurance in China.

The purpose of this study is to reveal the mechanism of humble leadership inducing abusive supervision from the low-status compensation perspective, examining the mediation role of leader perceived thread to status. Besides, the moderation effect of regulatory focus on the mediation path is discussed.

This study conducted a three-wave longitudinal survey. The data was collected from 438 leaders and their employees in five Chinese enterprises. This study used Mplus 7.4 and adopted a bootstrapping technique for data analysis.

Humble leadership has a positive effect on leader perceived threat to status. Leader perceived threat to status plays a mediation role between humble leadership and leader abusive supervision. Leader regulatory focus is the “gate valve” that humble leadership fosters leader abusive supervision. That is, when the leader promotion focus is high, leader perceived threat to status bred by humble leadership is low, resulting in less abusive supervision. When the leader prevention focus is high, humble leadership brings relatively more abusive supervision through perceived threat to status.

This study explores why humble leadership breeds abusive supervision behaviors and reveals the mechanism behind the negative effect of humble leadership based on low-status compensation theory. This study not only promotes the continuous development of the field of humble leadership research through empirical research but also provides guidance for effectively suppressing the negative effects of humble leadership, promoting strengths and avoiding weaknesses and suppressing inappropriate management behaviors in management practice.

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.

This study aims to investigate the factors that affect the intention to use public mobile libraries and enhance the quality of mobile library services to attract and retain users.

A questionnaire survey was conducted with 391 valid users in China. Based on the stimulus–response theory and user individual characteristics, a model was developed to examine the factors influencing the intention to use public mobile libraries. The model was tested using statistical software, such as SPSS 25.0 and AMOS 24.0.

The results indicate that technological factors, content factors, individual factors and psychological factors significantly influence the intention to use public mobile libraries. The impact of system quality and perceived ease of use in technological factors is relatively balanced. Among content factors, information quality is the most significant, while information literacy has a greater influence compared to subjective norms in individual factors. In psychological factors, perceived matching and perceived pleasure both positively influence usage intention, while perceived cost has a negative impact.

Firstly, this study only investigates users’ intention to use, but intention does not necessarily equate to actual usage behaviour (King and He,2006). Future research can introduce new variables to explore users’ adoption and continuous usage behaviours. Secondly, this study does not differentiate between different types of mobile library users. Future research can consider different user types, such as potential users and current users, to investigate the similarities and differences in their willingness to adopt mobile library services. Thirdly, this study is primarily cross-sectional. Future research can consider longitudinal studies to provide more in-depth insights into user behaviour.

This paper identifies external and internal stimulus factors and conducts a comprehensive investigation into the factors influencing the intention to use public mobile libraries, thus providing generalizable research findings. Unlike previous studies, this research introduces the information literacy variable, enriching the model of factors affecting users' intention to use mobile libraries and yielding more comprehensive conclusions. Consequently, the study aims to be grounded in the actual usage ideas and intentions of diverse user groups, constructing a model that highlights factors influencing the intention to use public mobile library services.

From a social perspective, this study offers four implications for improving the utilization of public mobile libraries. Firstly, it is crucial to integrate digital resources, enhance information quality in public mobile libraries and improve platform usability. Secondly, adopting a user-oriented approach is essential to improve the service level of public mobile libraries and stimulate residents’ participation. Thirdly, efforts should be made to strengthen user information literacy and increase information utilization. Fourthly, top-level design improvements, effective promotion efforts and user behaviour guidance are essential for the success of public mobile libraries.

This study contributes to the improvement of public mobile library services and the advancement of modern public cultural services by identifying the key factors that drive the intention to use such services. The findings have practical implications for promoting high-quality development and enhancing the popularity of public mobile libraries.

According to the problem of crude oil price forecasting, the purpose of this paper is to propose a multi-step prediction method based on the empirical mode decomposition, long short-term memory network and GM (1,1) model.

First, the empirical mode decomposition method is used to decompose the crude oil price series into several components with different frequencies. Then, each subsequence is classified and synthesized based on the specific periodicity and other properties to obtain several components with different significant characteristics. Finally, all components are substituted into a suitable prediction model for fitting. LSTM models with different parameters are constructed for predicting specific components, which approximately and respectively represent short-term market disturbance and long-term influences. Rolling GM (1,1) model is constructed to simulate a series representing the development trend of oil price. Eventually, all results obtained from forecasting models are summarized to evaluate the performance of the model.

The model is respectively applied to simulate daily, weekly and monthly WTI crude oil price sequences. The results show that the model has high accuracy on the prediction, especially in terms of series representing long-term influences with lower frequency. GM (1,1) model has excellent performance on fitting the trend of crude oil price.

This paper combines GM (1,1) model with LSTM network to forecast WTI crude oil price series. According to the different characteristics of different sequences, suitable forecasting models are constructed to simulate the components.

The purpose of this review is to comprehensively consider the material properties and processing of additive titanium alloy and provide a new perspective for the robotic grinding and polishing of additive titanium alloy blades to ensure the surface integrity and machining accuracy of the blades.

At present, robot grinding and polishing are mainstream processing methods in blade automatic processing. This review systematically summarizes the processing characteristics and processing methods of additive manufacturing (AM) titanium alloy blades. On the one hand, the unique manufacturing process and thermal effect of AM have created the unique processing characteristics of additive titanium alloy blades. On the other hand, the robot grinding and polishing process needs to incorporate the material removal model into the traditional processing flow according to the processing characteristics of the additive titanium alloy.

Robot belt grinding can solve the processing problem of additive titanium alloy blades. The complex surface of the blade generates a robot grinding trajectory through trajectory planning. The trajectory planning of the robot profoundly affects the machining accuracy and surface quality of the blade. Subsequent research is needed to solve the problems of high machining accuracy of blade profiles, complex surface material removal models and uneven distribution of blade machining allowance. In the process parameters of the robot, the grinding parameters, trajectory planning and error compensation affect the surface quality of the blade through the material removal method, grinding force and grinding temperature. The machining accuracy of the blade surface is affected by robot vibration and stiffness.

This review systematically summarizes the processing characteristics and processing methods of aviation titanium alloy blades manufactured by AM. Combined with the material properties of additive titanium alloy, it provides a new idea for robot grinding and polishing of aviation titanium alloy blades manufactured by AM.

The purpose of this paper is to assess the hydrogen embrittlement sensitivity of carbon gradient heterostructure materials and to verify the reliability of the scratch method.

The surface-modified layer of 18CrNiMo7-6 alloy steel was delaminated to study its hydrogen embrittlement characteristics via hydrogen permeation, electrochemical hydrogen charging and scratch experiments.

The results showed that the diffusion coefficients of hydrogen in the surface and matrix layers are 3.28 × 10⁻⁷ and 16.67 × 10⁻⁷ cm²/s, respectively. The diffusible-hydrogen concentration of the material increases with increasing hydrogen-charging current density. For a given hydrogen-charging current density, the diffusible-hydrogen concentration gradually decreases with increasing depth in the surface-modified layer. Fracture toughness decreases with increasing diffusible-hydrogen concentration, so the susceptibility to hydrogen embrittlement decreases with increasing depth in the surface-modified layer.

The reliability of the scratch method in evaluating the fracture toughness of the surface-modified layer material is verified. An empirical formula is given for fracture toughness as a function of diffused-hydrogen concentration.

Complex mechanical 3D computer-aided design (CAD) model embodies rich implicit design knowledge. Through discovering the key function parts and key function module in 3D CAD assembly model in advance, it can promote the designers’ understanding and reuse efficiency of 3D assembly model in design reuse.

An approach for discovering key function module in complex mechanical 3D CAD assembly model is proposed. First, assembly network for 3D CAD assembly model is constructed, where the topology structure characteristics of 3D assembly model are analyzed based on complex network centrality. The degree centrality, closeness centrality, betweenness centrality and mutual information of node are used to evaluate the importance of the parts in 3D assembly model. Then, a multi-attribute decision model for part-node importance is established, and the comprehensive evaluation for key function parts in 3D assembly model is accomplished by combining Analytic Hierarchy Process and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS). Subsequently, a community discovery of function module in assembly model-based Clauset–Newman–Moore (CNM)-Centrality is given in details. Finally, 3D CAD assembly model of worm gear reducer is taken as an example to verify the effectiveness and feasibility of proposed method.

The key function part in CAD assembly model is evaluated comprehensively considering assembly topology more objectively. In addition, the key function module containing key function part is discovered from CAD assembly model by using CNM-Centrality-based community discovery.

The approach can be used for discovering important design knowledge from complex CAD assembly model when reusing the assembly model. It can help designers capture and understand the design thinking and intent, improve the reuse efficiency and quality.

The paper first proposes an approach for discovering key function module in complex mechanical 3D CAD assembly model taking advantage of complex network theory, where the key function part is evaluated using node centrality and TOPSIS, and the key function module is identified based on community discovery.