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Although the literature has highlighted that a firm’s board is critical for firm innovation, the impact of board characteristics on firm innovation has always been examined separately, leading to inconclusive research results. Based on the complexity theory, this paper incorporates four board characteristics, including board size, board ownership, board independence and CEO duality, to examine the impact of the combinations of different board characteristics on firm innovation through qualitative comparative analysis.

Using the panel data of listed manufacturing firms in China from 2007 to 2022, this paper conducted the fuzzy set qualitative comparative analysis to test the proposed hypotheses.

The research results show that no single board characteristic can explain firm innovation, as board size, board ownership, board independence and CEO duality can lead to either positive or negative firm innovation. Moreover, firm innovation depends on a complex combination of board characteristics.

This paper makes the following contributions: Firstly, this paper advances the firm innovation literature by extending the role of board characteristics on firm innovation, thereby offering a new way to model firm innovation in terms of board characteristics. Secondly, this paper provides a more comprehensive account of the role of a firm’s board by integrating agency theory and resource dependence theory. Thirdly, this paper also identifies a promising avenue for further research in the field of corporate governance: the investigation of other contingency contexts in which the effect of board characteristics may be observed, with the aim of further increasing the understanding of board functioning.

To ensure accurate position and force control of massage robot working on human body with unknown skin characteristics, this study aims to propose a novel intelligent impedance control system.

First, a skin dynamic model (SDM) is introduced to describe force-deformation on the human body as feed-forward for force control. Then a particle swarm optimization (PSO) method combined with graph-based knowledge transfer learning (GKT) is studied, which will effectively identify personalized skin parameters. Finally, a self-tuning impedance control strategy is designed to accommodate uncertainty of skin dynamics, system delay and signal noise exist in practical applications.

Compared with traditional least square method, genetic algorithm and other kinds of PSO methods, combination of PSO and GKT is validated using experimental data to improve the accuracy and convergence of identification results. The force control is effective, although there are contour errors, control delay and noise problems when the robot does massage on human body.

Integrating GKT into PSO identification algorithm, and designing an adaptive impedance control algorithm. As a result, the robot can understand textural and biological attributes of its surroundings and adapt its planning activities to carry out a stable and accurate force tracking control during dynamic contacts between a robot and a human.

In recent years, the demand for oil and gas pipelines has increased rapidly. Due to the restrictions of the pipeline routing, pipelines are generally laid in parallel or in the same trench, which results in stray-current interference between the independent cathodic protection (CP) systems. The purpose of this paper is to study the interference between the long-distance parallel pipelines and to obtain the optimized operation for the CP systems.

In this study, first, the numerical model of parallel pipelines was established using the boundary element analysis software (BEASY). Second, the effects of horizontal distance between parallel pipelines, coating damage rate, soil conductivity and anode output current on the interference of parallel pipelines were studied. Finally, by varying the layout or the output currents of CP stations, an optimized operation scheme osf long-distance parallel pipelines was put forward.

Simulation results showed that with a decrease in soil conductivity or coating damage rate, the interference increased. Moreover, the interference decreased with an increase in horizontal distance between two parallel pipelines or a decrease in anode output current. It was found that there are three methods to reduce the interference between long-distance parallel pipelines: to reduce the output currents of CP stations, combined protection and to close part of the CP stations. Among them, to close part of CP stations was the optimized scheme because of the lowest operating and maintenance cost.

The optimized operation scheme proposed in this study can not only solve the interference between parallel pipelines but also provide guidance for the parallel pipelines to be built in the future. Reasonably arranging the cathodic protection stations using numerical simulation can avoid the interference in the cathodic protection systems, and reduce the construction cost.

This paper aims to reveal the factors patients consider when choosing a doctor for consultation on an online medical consultation (OMC) platform and how these factors influence doctors' consultation volumes.

In Study 1, influencing factors reflected as service features were identified by applying a feature extraction method to physician reviews, and the importance of each feature was determined based on word frequencies and the PageRank algorithm. Sentiment analysis was used to analyze patient satisfaction with each service feature. In Study 2, regression models were used to analyze the relationships between the service features obtained from Study 1 and the doctor's consultation volume.

The study identified 14 service features of patients' concerns and found that patients mostly care about features such as trust, phraseology, overall service experience, word of mouth and personality traits, all of which describe a doctor's soft skills. These service features affect patients' trust in doctors, which, in turn, affects doctors' consultation volumes.

This research is important as it informs doctors about the features they should improve, to increase their consultation volume on OMC platforms. Furthermore, it not only enriches current trust-related research in the field of OMC, which has a certain reference significance for subsequent research on establishing trust in online doctor–patient relationships, but it also provides a reference for research concerning the antecedents of trust in general.

In this age of extremely well-developed social media, it is necessary to detect any change in the corporate image of an enterprise immediately so as to take quick action to avoid the wide spread of a negative image. However, existing survey-based corporate image evaluation methods are costly, slow and static, and the results may quickly become outdated. User comments, news reports and we-media articles on the internet offer varied channels for enterprises to obtain public evaluations and feedback. The purpose of this study is to effectively use online information to timely and accurately measure enterprises’ corporate images.

A new corporate image evaluation method was built by first using a literature review to establish a corporate image evaluation index system. Next, an automatic text analysis of online public information was performed through a topic classification and sentiment analysis algorithm based on the dictionary. The accuracy of the topic classification and sentiment analysis algorithm is then calculated. Finally, three internet enterprises were chosen as cases, and their corporate image was evaluated.

The results show that the author’s corporate image evaluation method is effective.

First, in this study, a new corporate image evaluation index system is constructed. Second, a new corporate image evaluation method based on text mining is proposed that can support data-driven decision-making for managers with real-time corporate image evaluation results. Finally, this study improves the understanding of corporate image by generating business intelligence through online information. The findings provide researchers with specific and detailed suggestions that focus on the corporate image management of emerging internet enterprises.

It is a very prominent problem that Chinese universities lack school-running characteristics. In the past ten years, because of undergraduate teaching assessment requirements of the Ministry of Education, universities attach great importance to school-running characteristics. What is the reality and how to improve the effectiveness of creating the school-running characteristics of universities? It is a problem that needs to be solved. The purpose of this paper is to discuss these issues.

Using the survey method, literature study, case studies and other methods, this study reviewed ten years of school-running characteristics construction and explored some laws of creating school-running characteristics.

This study found although universities in China are beginning to attach great importance to the school-running characteristics, but they are still staying in the summarization of characteristics. School-running characteristics are very rough. Creating school-running characteristics are mainly efforts responding to the superior government. Creating school-running characteristics should be based on category characteristic. Universities need to change in competition and create characteristics within its history and culture. Universities need to refine the core idea of education, develop a big picture and then renew them in the assessment cycle.

The originality of this study was that it put forward some new laws including changing from summarizing to creating its own school-running characteristics, putting category characteristic as the prerequisite and considering the core idea of education as the focus of school-running characteristics. This research will enrich the theory building of higher education research and has some value in promoting the creation of school-running characteristics.

This paper delineates a literature review on fire-induced progressive collapse on structures and the effect of high temperature on structures and elements. After the occurrences of fire in the World Trade Center in the USA, the researchers started concentrating on the progressive collapse that happens due to high temperature. Currently, most of the researchers are working on fire-induced progressive collapse on structures using high-temperature behavior on materials which are used for construction. The researchers have been doing an intensive study to find a better strategy to prevent the building from structural fire damage or collapse with available codes and guidelines throughout the world. This paper aims to provide a better understanding and analytical solutions on the basis of the recent works done by researchers in fire-induced progressive collapse and methods adopted to find the collapse mechanism.

This paper is written by studying different literature papers of 109 related to progressive collapse on structures and fire-induced progressive collapse.

The behavior of structures due to high temperature and collapse conditions due to fire in different scenarios is identified.

This paper fulfills an identified need to study how the structure can withstand high-temperature conditions in our day-to-day lives.