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This paper aims to develop a robot for tightening charged bolt to solve the shortcomings of high labor intensity, low efficiency, high risk and poor reliability in artificially tightening drainage board bolt of strain clamp for high voltage transmission line. Realizing bolt-nut capture and location by manipulator is a critical process to complete the whole working task. To solve such key technology, an autonomous location control method for N-joint robot manipulator based on kinematics was proposed.

Through D-H kinematics analysis under flexible working environment of transmission line, the autonomous location control of double manipulators can be abstracted as a nonlinear approximation problem based on joint inverse kinematics. In addition, regarding the complex coupling relationship among different joint angles and the complex decoupling process which leads to the non-uniqueness of inverse solution, an improved backpropagation (BP) network was proposed based on the combination of dynamic adaptive adjustment of learning rate and variable momentum factor, so that the inverse kinematics of manipulator can be solved and the optimization evaluation mechanism of inverse solution can be presented. The proposed autonomous location control method is of adaptability to flexible environment and structural parameters of different drainage boards. The simulation results verified the effectiveness of the proposed method. Compared with the other location control, this method can achieve faster location speed, higher precision and lower hardware cost. Finally, the field operation test further validated that such autonomous location control method was of strong engineering practicability.

The proposed autonomous location control method is adaptable to a flexible environment and to the structural parameters of different types of drainage board. Simulation results confirm the effectiveness of the proposed method, which, in comparison with other approaches to location control, can achieve faster location, higher precision and lower hardware cost. Finally, a field test further confirms the engineering practicability of the proposed autonomous location control method.

The proposed method can achieve faster location speed, higher precision which meet the requirement of real-time control relative to the standard BP algorithm. Moreover, it is of strong adaptability to flexible environment and structural parameters for different drainage board. Field operation experiment further validated the engineering practicability of the method.

An accurate detection of overhead ground wire under open surroundings with varying illumination is the premise of reliable line grasping with the off-line arm when the inspection robot cross obstacle automatically. This paper aims to propose an improved approach which is called adaptive homomorphic filter and supervised learning (AHSL) for overhead ground wire detection.

First, to decrease the influence of the varying illumination caused by the open work environment of the inspection robot, the adaptive homomorphic filter is introduced to compensation the changing illumination. Second, to represent ground wire more effectively and to extract more powerful and discriminative information for building a binary classifier, the global and local features fusion method followed by supervised learning method support vector machine is proposed.

Experiment results on two self-built testing data sets A and B which contain relative older ground wires and relative newer ground wire and on the field ground wires show that the use of the adaptive homomorphic filter and global and local feature fusion method can improve the detection accuracy of the ground wire effectively. The result of the proposed method lays a solid foundation for inspection robot grasping the ground wire by visual servo.

This method AHSL has achieved 80.8 per cent detection accuracy on data set A which contains relative older ground wires and 85.3 per cent detection accuracy on data set B which contains relative newer ground wires, and the field experiment shows that the robot can detect the ground wire accurately. The performance achieved by proposed method is the state of the art under open environment with varying illumination.

To predict the price of battery-grade lithium carbonate accurately and provide proper guidance to investors, a method called MFTBGAM is proposed in this study. This method integrates textual and numerical information using TCN-BiGRU–Attention.

The Word2Vec model is initially employed to process the gathered textual data concerning battery-grade lithium carbonate. Subsequently, a dual-channel text-numerical extraction model, integrating TCN and BiGRU, is constructed to extract textual and numerical features separately. Following this, the attention mechanism is applied to extract fusion features from the textual and numerical data. Finally, the market price prediction results for battery-grade lithium carbonate are calculated and outputted using the fully connected layer.

Experiments in this study are carried out using datasets consisting of news and investor commentary. The findings reveal that the MFTBGAM model exhibits superior performance compared to alternative models, showing its efficacy in precisely forecasting the future market price of battery-grade lithium carbonate.

The dataset analyzed in this study spans from 2020 to 2023, and thus, the forecast results are specifically relevant to this timeframe. Altering the sample data would necessitate repetition of the experimental process, resulting in different outcomes. Furthermore, recognizing that raw data might include noise and irrelevant information, future endeavors will explore efficient data preprocessing techniques to mitigate such issues, thereby enhancing the model’s predictive capabilities in long-term forecasting tasks.

The price prediction model serves as a valuable tool for investors in the battery-grade lithium carbonate industry, facilitating informed investment decisions. By using the results of price prediction, investors can discern opportune moments for investment. Moreover, this study utilizes two distinct types of text information – news and investor comments – as independent sources of textual data input. This approach provides investors with a more precise and comprehensive understanding of market dynamics.

We propose a novel price prediction method based on TCN-BiGRU Attention for “text-numerical” information fusion. We separately use two types of textual information, news and investor comments, for prediction to enhance the model's effectiveness and generalization ability. Additionally, we utilize news datasets including both titles and content to improve the accuracy of battery-grade lithium carbonate market price predictions.

As Chinese imported cross-border e-commerce has entered a stage of rapid development, the problem of consumer shopping risk is increasingly prominent and the crisis of consumer trust is intensified. The theory of establishing consumer trust in traditional online shopping can no longer meet the need of cross-border context.

The researchers used the methods of network logs and grounded theory. The data collection and analysis are conducted on consumer comments from Tmall Global, NetEase Koala and JD Worldwide in the product comment area. This article explored and extracted the moderating variables of consumer perceived risk and cross-border characteristics in cross-border e-commerce. Based on the theory of “perceived risk – consumer trust – consumer purchase decision – making,” this article deduced mechanism of consumer dynamic trust based on the whole process of cross-border e-commerce transaction.

In the prepurchase, purchase and postpurchase stages of cross-border e-commerce transactions, consumers' perceived cognitive risk, transaction risk and utility risk are moderated by the cultural distance, geographical distance and institutional distance caused by the cross-border transaction subjects. On this basis, the preinfluence factors of trust in each transaction stage are synthesized to respectively influence the establishment of cognitive trust, emotional trust and behavioral trust, so as to affect consumers to make the order payment, confirm receipt and praise repurchase decisions. At the same time, with the advance of prepurchase, purchase and postpurchase transactions in cross-border online shopping, consumer trust presents a dynamic evolutionary path of “cognitive trust – emotional trust – behavioral trust.”

This article expands the application context of the theory of consumer rational behavior from traditional online shopping to the context of cross-border online shopping and expands the scope of interpretation of the theory of consumer rational behavior. This article also supplements the theoretical gaps in the dynamic evolution of consumer trust in cross-border online shopping, enriches the decision-making process model of consumers in the context of cross-border online shopping and provides new ideas for follow-up research.

The purpose of this study is to investigate the impact of board secretaries’ characteristics on annual report readability using an original method that evaluates the readability of Chinese characters.

The authors manually collect board secretaries’ characteristics from the China Securities Market and Accounting Research database and obtain annual reports from the China Information website. Ordinary least square regression is applied to evaluate the impact, and then robustness tests and additional regression analyses are conducted.

Board secretaries’ legal-professional expertise, international expertise and role duality improve annual report readability. However, their political connections are negatively associated with it. The effect of expertise (role duality) is more pronounced for firms with lower ex ante litigation risk (board secretaries with equity holdings). Furthermore, higher readability increases the compensation of board secretaries, whereas lower readability increases their turnover. Finally, annual report readability is positively related to firm performance.

The authors only investigate listed firms in China from 2007 to 2017 because of the difficulties of obtaining data and text mining.

The authors provide managerial insights for regulators aiming to establish an effective governance mechanism with Chinese characteristics. First, certain requirements for board secretaries’ expertise can improve annual report readability. Further, firms can consider appointing board members or senior executives as board secretaries to enhance disclosure quality.

To the best of the authors’ knowledge, this study is the first to verify the effect of board secretaries’ characteristics on disclosure quality, especially annual report readability. Moreover, this study proposes a novel measure of annual report readability for Chinese texts.

With the rising concerns of compulsive use of social media, it is important to understand why users develop such unplanned and irrational behaviors. Leveraging the uses and gratification theory, the authors aim to explore the determinants of compulsive use of social media from the dual perspectives of individual needs (need to belong (NTB) and need for uniqueness) and peer-related factors (referent network size and perceived peer activeness). Due to the importance of self-construal in cognitive deliberation on peer influences, the moderating effects of self-construal were taken into consideration.

The authors empirically test their model by conducting an online survey with 459 WeChat users.

The results show that compulsive use of social media is predicated by both individual needs and influence from peers. Moreover, peer influence could be attenuated when individuals develop a high degree of independent self-construal.

The authors' study contributes to the research of compulsive behavior in the context of social media use by incorporating the dual effects of individual needs and social influence. The authors also offer managerial insights on eradicating the formation of compulsive behaviors.

The authors examine the dual effects of individual needs and peer influence in predicting compulsive use of social media and the moderating role of self-construal, which have been rarely investigated in this context.

This article intends to explore how organizational learning affects innovation in public library services, and the role of public librarians in innovation in library services.

This study collected 375 valid questionnaires from 19 public libraries in Shanghai and Zhejiang based on organizational learning, organizational innovation and employee psychological empowerment theory. Additionally, SPSS and HLM are used to analyze the relationship among the three processes of organizational learning: knowledge acquisition, knowledge sharing and knowledge application, and public library service innovation.

Results show that organizational learning has a significant positive effect on the service innovation of public libraries. Knowledge acquisition and knowledge application in the process of organizational learning have a significant positive influence on the service innovation of public libraries, but the impact of knowledge sharing on service innovation is weak. Employee psychological empowerment has a negative regulating influence on knowledge sharing–public library service innovation, but no significant influence on knowledge application–public library service innovation and knowledge acquisition–public library service innovation.

This research explores the effectiveness of the theory of organizational learning in the field of public libraries and also confirms the role of librarians in the work of public libraries. Together, they promote the innovation of public libraries.

The purpose of this study is to provide better service to hotel customers during the COVID-19 era. Specifically, this study focuses on understanding the changes in hotel customer satisfaction during the epidemic and formulating effective marketing strategies to satisfy and attract guests.

As the first victim of the COVID-19 virus, China’s hotel industry has been profoundly affected and customer satisfaction and needs have also changed. Taking 105,635 hotel reviews obtained from Tripadvisor.com in Beijing and Shanghai as samples, this study explores the changes in consumer satisfaction by using text-mining methods.

The results suggest that there are significant differences in overall ratings, spatial distribution and ratings of different traveller types before and after the epidemic. Generally, customers have higher “tolerance” and are more inclined to give higher ratings and pay more attention to hotel prevention and control measures to reduce health risks after the COVID-19.

This paper proves the changes in customer satisfaction before and after the COVID-19 at the theoretical level and reveals the changes in customer attention through the topic model and provides a basis for guiding hotel managers to reduce the impact of the COVID-19 crisis.

Empirical findings would provide useful insights into tourism management and improve hotel service quality during the COVID-19 epidemic era.

This research explores the hotel customer satisfaction in the field of hotel management before COVID-19 and after COVID-19, by using text mining to analyse mandarin online reviews. The results of this study will suggest that the hotel industry should continuously adjust its products and services based on the effective information obtained from customer reviews, so as to realize the activation and revitalization of the hotel industry in the epidemic era.

Based on conservation of resources (COR) theory, this study aims to examine the impact of daily illegitimate tasks on employees' daily silence and daily voice behavior, as well as the mediating role of daily ego depletion and the moderating role of trait mindfulness.

Through daily diary approach, 81 employees were followed for 10 consecutive workdays. Multilevel analysis was employed to examine the hypothesized relationships.

The results showed that daily illegitimate tasks are positively related to daily silence behavior and negatively related to daily voice behavior; daily ego depletion plays a mediating role in these relationships. Trait mindfulness moderates the effect of daily illegitimate tasks on daily ego depletion and the indirect effect of daily illegitimate tasks on daily silence and daily voice.

Managers should be mindful of minimizing the assignment of illegitimate tasks. Additionally, it is recommended that the organization provide training courses for employees to help them reduce ego depletion. Finally, organizations should focus on fostering high levels of mindfulness among their employees.

This study contributes to the existing literature by investigating the immediate impact of illegitimate tasks on employee voice and silence at within-person level. By doing so, it enhances comprehension of the consequences associated with illegitimate tasks. Meanwhile, this study offers additional insights into the underlying mechanisms and boundary conditions of the effect of illegitimate tasks from a resource perspective.

This paper aims to address the question of what can significantly impact employees' IB and how employees' IB may be effectively stimulated by investigating key factors such as employees' knowledge sharing, innovation passion, absorptive capacity and risk-taking behaviour on workplace innovation. The moderating role of risk-taking behaviour on the link between absorptive capacity and innovation behaviour is also investigated.

Based on the principles of social exchange theory, the study design explores the complex relationship among knowledge sharing, innovation passion, absorptive capacity and risk-taking vis-à-vis employees' innovation behaviour within a unified analysis framework. Methodologically, employees in the information technology industry in China were surveyed via a questionnaire instrument, with a total of 318 valid questionnaires being collected online. Following a reliability and validity test of the questionnaire, the Smart PLS was used to verify the research model.

Statistically significant results reported were as follows: (1) employees' innovation behaviour is positively impacted by knowledge sharing, innovation passion and absorptive capacity; (2) employees' innovation behaviour is negatively impacted by risk-taking behaviour; (3) knowledge sharing is positively impacted by innovation passion; (4) absorptive capacity is positively impacted by innovation passion; and (5) risk-taking behaviour regulates the relationship between absorptive capacity and innovation behaviour.

Owing to limited research resources, 318 front-line employees were surveyed via an online questionnaire vis-à-vis the sampling method only, specifically taking knowledge sharing, innovation passion, absorptive capacity and risk-taking behaviour as antecedent variables with implications on how employees' innovation behaviour may be stimulated.

The mechanism of augmenting employees' innovation behaviour is chiefly explained from the perspective of innovation passion and risk-taking behaviour, which are conducive towards promoting employees' willingness to improve knowledge sharing and innovation behaviour. The social exchange theory is used as a basis to form an integrated model for the research, contributing to a cumulative theoretical perspective for future work on the impact of innovation passion and risk-taking behaviour on innovation.