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Based on social cognitive theory, this study aims to explore the psychological mechanism behind consumer verification behavior following tourism e-commerce live-streaming.

Based on grounded theory, data were collected through 20 semi-structured in-depth interviews and analyzed.

This study identified that companies commonly use reminder messages and secondary promotions to facilitate the verification of tourism live-streaming products. Throughout this process, consumers undergo various psychologies related to verification. Specifically, they experience four positive verification psychologies: fear of missing out, anticipated emotions, status self-esteem and promotional perception. They also encounter two negative verification psychologies: psychological reactance and invasiveness. In addition, environmental factors such as the type of tourism live-streaming products and tourism destinations, along with individual trait factors like cognitive miserliness, tourism experience, autonomy, regulatory mode and impulsiveness, play significant roles in shaping verification behavior. These factors collectively influence the formation of verification behavior.

This study can provide recommendations for tourism companies to conduct marketing events following live-streaming. It is one of the earlier comprehensive studies discussing how to promote verification behavior following tourism e-commerce live-streaming. It helps to understand the psychological mechanism underlying the formation of verification behavior.

To adapt to the rapidly changing market environment, firms must constantly adjust and change their knowledge base to develop new technologies. The purpose of this paper is to analyze the improvement path of firms’ breakthrough innovation from the perspective of knowledge recombination in the context of dynamic change in the knowledge base. By analyzing the influencing mechanism of environmental dynamism on the relationship between the two, this paper provides a theoretical foundation for managers to make knowledge recombination decisions under a dynamic external environment while further enriching the firm’s innovation achievements.

Using data from 220 manufacturing firms listed on the Shanghai and Shenzhen A-share stock from 2010 to 2018, an extensive panel data set was constructed to investigate the effect of knowledge recombination, which was divided into recombination creation and recombination reuse, on firms’ breakthrough innovation. In addition, the authors differentiated environmental dynamism as market dynamism and technological dynamism and then examined its moderating role in the above relationships.

The research results show that various recombination behaviors of knowledge elements have a differentiated effect on firms’ breakthrough innovation presented as follows: Knowledge recombination creation is significantly positively correlated with firms’ breakthrough innovation, while knowledge recombination reuse is significantly negatively correlated with firms’ breakthrough innovation. In addition, environmental dynamism has a considerable moderating effect between knowledge recombination and firms’ breakthrough innovation further, emphasizing that the moderating effect on different types of knowledge recombination behaviors is significantly distinct.

First, given that this study refers to several Chinese noted databases to collect second-hand data for empirical analysis, future research could use first-hand data by collecting questionnaire survey and interview to provide a more practical and detailed research conclusion. Second, the authors focused on the contextual variable to explore the moderating role of environmental dynamism on the relationship between knowledge recombination and breakthrough innovation. Nevertheless, the indirect effects of other internal factors were not discussed. The authors advocate future studies to involve other moderators from employee social and phycological perspectives, such as trust in colleagues in the proposed theoretical models in this study.

This study is conducive for managers to attach great attention to knowledge management practices in the firm and to understand the critical role of knowledge recombination in affecting innovation performance under dynamic environmental changes. Moreover, this study provides practical guidance and serves as a reference for firms to strengthen their knowledge recombination ability as full utilization of existing knowledge elements and exploration of new knowledge values.

Primarily, from the perspective of dynamic changes in the knowledge base, this paper explores how the knowledge recombination behaviors affect firms’ breakthrough innovation, thereby enriching and extending the relationship theory between knowledge recombination capabilities and breakthrough innovation, while new and valuable ideas are provided in the study of issues related to the firms’ breakthrough innovation; Moreover, this study analyzes the moderating effects of diverse types of environmental dynamism on the relationship between knowledge recombination and firms’ breakthrough innovation from a multi-dimensional perspective proposing that the moderating effects of environmental dynamism on different knowledge recombination behaviors are distinct.

Given the complexity of building information modeling (BIM) adoption decisions in small- and medium-sized enterprises (SMEs) in the Architecture, Engineering and Construction (AEC) industry, understanding BIM adoption decision-making through the net effect of a single factor on BIM adoption decisions alone is limited. Therefore, this paper analyzed the co-movement effect of managers' psychological factors on the BIM adoption decisions from the perspective of managers' perceptions. The purpose is to let managers have a deep understanding of their BIM adoption decisions, and put forward targeted suggestions for the AEC industry to promote the adoption of BIM by SMEs.

Data from 192 managers in SMEs collected by the questionnaire were used in a fuzzy set qualitative comparative analysis (fsQCA). Due to the limitations of fsQCA in making the best use of the data used, as a complement to fsQCA, necessary conditions analysis (NCA) was used to analyze the extent to which necessary conditions influenced the outcome.

(1) NCA analysis shows that high perceived resource availability (PRA) and high performance expectancy (PE) are necessary conditions for high BIM adoption intention (AI). (2) fsQCA analysis shows that high PE is the single core condition for high AI. fsQCA analysis identifies three configurations of managers' psychological factors, reflecting three types of managers' decision preferences, namely benefit preference, loss aversion and risk avoidance, respectively. Different decision preferences may lead to different BIM adoption strategies, such as full in-house use, partial in-house/outsourcing and full outsourcing of BIM processes. (3) High perceived risk (PR) and low perceived business value of BIM (PBV) are the core conditions for low AI.

This paper expands on the application of fsQCA to context of BIM adoption decisions. Based on the results of fsQCA analysis, this paper also establishes the relationship between managers' decision-making psychology and BIM adoption strategy choice and analyzes the impact of different decision biases on BIM adoption strategy choice. It concludes with suggestions for encouraging managers to adopt BIM and for avoiding decision-making bias.

In complex environments, a spherical robot has great application value. When the pendulum spherical robot is stopped or disturbed, there will be a periodic oscillation. This situation will seriously affect the stability of the spherical robot. Therefore, this paper aims to propose a control method based on backstepping and disturbance observers for oscillation suppression.

This paper analyzes the mechanism of oscillation. The oscillation model of the spherical robot is constructed and the relationship between the oscillation and the internal structure of the sphere is analyzed. Based on the oscillation model, the authors design the oscillation suppression control of the spherical robot using the backstepping method. At the same time, a disturbance observer is added to suppress the disturbance.

It is found that the control system based on backstepping and disturbance observer is simple and efficient for nonlinear models. Compared with the PID controller commonly used in engineering, this control method has a better control effect.

The proposed method can provide a reliable and effective stability scheme for spherical robots. The problem of instability in real motion is solved.

In this paper, the oscillation model of a spherical robot is innovatively constructed. Second, a new backstepping control method combined with a disturbance observer for the spherical robot is proposed to suppress the oscillation.

This study examines the antecedents and dynamics of authoritarian leadership and extends the effects of managers' sleep quality to employee behavior.

On the basis of self-regulation theory, 513 unit day samples were analyzed using cross-level path analysis and a Monte Carlo simulation test.

Managers' sleep quality is positively related to authoritarian leadership and positive emotions play a mediating role. Authoritarian leadership is positively related to employees' counterproductive behavior. Managers' sleep quality affects employees' counterproductive behavior through managers' positive emotions and authoritarian leadership.

Individuals should learn to reduce stress and maintain a positive mood. Organizations should reduce employees' overtime work and work stress and find other ways to improve employees' sleep quality.

First, we considered authoritarian leadership to be dynamic and studied it on a daily basis. Second, we studied the antecedents of authoritarian leadership from the perspective of leaders' states (sleep quality and emotions). Third, we discussed the effect of managers' sleep quality on employee behavior.

The study aims to examine how different types of green brand ritual (GBR) influence customer engagement behavior and the mediation mechanisms and boundary conditions of the positive and negative pathways.

The study conducts two online experiments to collect data from a total of 940 consumers in China. Hypotheses are tested by independent samples t-test, two-way ANOVA and Hayes' PROCESS model.

Different kinds of GBR have different effects on customer engagement behavior. Internal GBR is more likely to play a positive role by inciting connectedness to nature. External GBR is more likely to play a negative role by inciting psychological resistance. This dual effect is especially pronounced for warm brands rather than competent brands.

The study pioneers the brand ritual into the field of interactive marketing and enriches its dual effect research. Additionally, the study figures out whether the category of brand ritual can trigger negative effect.

Inappropriate brand rituals are worse than no rituals at all. The results provide guidance for green companies to design effective brand rituals to strengthen the connection with consumers. Green brands should describe brand rituals in vivid detail and consciously lead consumers to immerse themselves in them.

This study aims to investigate how firms of different sizes respond to competitive pressure from peers.

This study employs machine learning techniques to measure competitive pressure based on management discussion and analysis (MD&A) documents and then utilises the constructed pressure indicator to explore the relationship between competitive pressure and corporate risk-taking behaviours amongst firms of different sizes.

We find that firm sizes are positively associated with their risk-taking behaviours when firms respond to competitive pressure. Large firms are inclined to exhibit a high level of risk-taking behaviours, whereas small firms tend to make conservative decisions. Regional growth potential and institutional ownership moderate the relationships.

Utilising text mining techniques, this study constructs a novel quantitative indicator to measure competitive pressure perceived by focal firms and demonstrates the heterogeneous behaviour of firms of different sizes in response to competitive pressure from peers, advancing research on competitive market pressures.

The purpose of this paper is to propose an new online path planning method for porcine belly cutting. With the proliferation in demand for the automatic systems of pork production, the development of efficient and robust meat cutting algorithms are hot issues. The uncertain and dynamic nature of the online porcine belly cutting imposes a challenge for the robot to identify and cut efficiently and accurately. Based on the above challenges, an online porcine belly cutting method using 3D laser point cloud is proposed.

The robotic cutting system is composed of an industrial robotic manipulator, customized tools, a laser sensor and a PC.

Analysis of experimental results shows that by comparing with machine vision, laser sensor-based robot cutting has more advantages, and it can handle different carcass sizes.

An image pyramid method is used for dimensionality reduction of the 3D laser point cloud. From a detailed analysis of the outward and inward cutting errors, the outward cutting error is the limiting condition for reducing the segments by segmentation algorithm.

This study proposes a predictive neural network model reference decoupling control method for the coupling problem between the leg joints of hydraulic quadruped robots, and verifies its decoupling effect..

The machine–hydraulic cross-linking coupling is studied as the coupling behavior of the hydraulically driven quadruped robot, and the mechanical dynamics coupling force of the robot system is controlled as the disturbance force of the hydraulic system through the Jacobian matrix transformation. According to the principle of multivariable decoupling, a prediction-based neural network model reference decoupling control method is proposed; each module of the control algorithm is designed one by one, and the stability of the system is analyzed by the Lyapunov stability theorem.

The simulation and experimental research on the robot joint decoupling control method is carried out, and the prediction-based neural network model reference decoupling control method is compared with the decoupling control method without any decoupling control method. The results show that taking the coupling effect experiment between the hip joint and knee joint as an example, after using the predictive neural network model reference decoupling control method, the phase lag of the hip joint response line was reduced from 20.3° to 14.8°, the amplitude attenuation was reduced from 1.82% to 0.21%, the maximum error of the knee joint coupling line was reduced from 0.67 mm to 0.16 mm and the coupling effect between the hip joint and knee joint was reduced from 1.9% to 0.48%, achieving good decoupling.

The prediction-based neural network model reference decoupling control method proposed in this paper can use the neural network model to predict the next output of the system according to the input and output. Finally, the weights of the neural network are corrected online according to the predicted output and the given reference output, so that the optimization index of the neural network decoupling controller is extremely small, and the purpose of decoupling control is achieved.

Online reviewers' identity information is an essential cue by which consumers judge reviews on ecommerce platforms. However, few studies have explored how prior anonymous reviews and focal reviews affect reviewers' preference for anonymity. The purpose of this paper is to investigate why reviewers seek anonymity in terms of prior anonymous reviews and focal reviews.

Based on restaurant reviews collected from meituan.com, one of the largest group-buying ecommerce platforms in China, this study employed logistic regression to examine how prior anonymous reviews and focal reviews are associated with reviewers' preference for anonymity.

Results show that the volume and sequence of prior anonymous review are positively associated with the likelihood of reviewers' preference for anonymity, whereas focal review valence is negatively correlated with this preference. Focal review length is positively correlated with reviewers' preference for anonymity but negatively moderates the roles of review valence and prior anonymous reviews on this preference.

This study expands the information disclosure literature by exploring determinants of user identity disclosure from a reviewer perspective. This research also offers a methodological contribution by employing a more accurate measure to calculate reviewers' preference for anonymity, enhancing the empirical results. Lastly, this work supplements the online review literature on how prior anonymous reviews and focal reviews are associated with reviewers' identity disclosure.