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Building Information Modeling (BIM) competitions are a beneficial approach to enhance BIM education, offering students practical experience in BIM application, including mastering workflows and technical tools. However, research exploring the individual perceptions influencing participation intentions and behaviors in BIM competitions is limited. Therefore, this study aims to investigate the factors affecting university students' behavioral intention and behavior in BIM competitions, providing theoretical support for BIM competitions and educational reform.

This study employs the Structural Equation Modeling (SEM) based on the Unified Theory of Acceptance and Use of Technology (UTAUT) framework to analyze the factors influencing BIM competition participation among 970 Architecture, Engineering, and Construction (AEC) university students.

The results of the study show that social influence, attitude, and self-efficacy play critical roles in shaping students' intentions to participate in BIM competitions. Furthermore, self-efficacy, facilitating conditions, and behavioral intention significantly influence students' actual engagement in such competitions. Surprisingly, effort expectancy negatively influences intentions, as less challenging tasks can lead students to perceive their participation as less impactful on their skills and learning, reducing their behavioral intention to participate.

This research provides valuable insights into the effectiveness of BIM competitions in enhancing BIM education for AEC students. Extending the UTAUT model to include self-efficacy and attitude, provides a novel perspective for understanding students' intentions and behaviors regarding BIM competitions. The study’s theoretical support proposes incorporating BIM competitions to augment BIM teaching methods and offers suggestions for advancing the efficacy of students' involvement in BIM competitions within higher education, thus contributing to educational reform in the AEC sector.

Gamification has been widely applied in mobile fitness apps to motivate users to exercise continuously. Based on the affordances–psychological outcomes–behavioral outcomes framework, this study explores the roles of three specific gamification affordances (competition, visibility of achievement and interactivity) in self-health management (continuous use behavior and health behavior) from the perspectives of achievement satisfaction and gamification exhaustion.

We test the research model using a structural equation model (SEM) with 505 self-reported data points. Furthermore, we apply fuzzy-set qualitative comparative analysis (fsQCA) to explore configurations of gamification affordances associated with self-health management behavior, reinforcing the SEM results.

Results indicate that competition, visibility of achievement and interactivity can enhance achievement satisfaction, which further boosts self-health management behavior. However, competition and interactivity can also cause gamification exhaustion, which undermines self-health management behavior to some extent. Overall, the positive impacts of the three affordances outweigh the negative impacts.

This study provides new insights for relevant practitioners on designing gamification affordances, aiding the sustainable development of mobile fitness apps and their long-term effects on self-health management. Visibility of achievement should be emphasized, and competition and interactivity should be thoughtfully designed to minimize their negative effects.

This study extends the affordances–psychological outcomes–behavioral outcomes framework and the literature on gamification and health management by applying both SEM and fsQCA methodologies to examine the relationship between specific gamification affordances and self-health management behavior.

Many newly established Internet loss-making enterprises (NEILEs) are always willing to expand overseas within a very short time from their establishment. This phenomenon is becoming a hot research area. This paper aims to explore why these enterprises are always willing to expand overseas rapidly even if they are facing severe and persistent losses, and to study the different rapid internationalization modes and the international market entry ways for NEILEs.

This paper constructs a theoretical framework with the dual situation of negative attainment discrepancy and advantageous slack resources to explain the rapid internationalization of NEILEs. Furthermore, cross-case comparative analysis method, based on interviews, questionnaires and secondary data collection, is adopted to reveal the rapid internationalization modes and the international market entry ways of such enterprises.

Whether blocking competitors or seeking opportunities or both, NEILEs' goal of rapid internationalization depends on the severity and persistence of negative attainment discrepancy. When the severity and persistence of negative attainment discrepancy are very significant, moderate and mild, NEILEs choose sniper-type, opportunity-type and dual-type internationalization target mode in turn; it is very important for NEILEs to match advantageous slack resources and international market entry ways to achieve specific internationalization goals.

This paper enriches the understanding of NEILEs' transnational entrepreneurial behavior in the era of digital economy. The theoretical contribution of this paper is that the authors build a theoretical framework based on the logical starting point, the logical fulcrum and the logic ending point for understanding the rapid internationalization of NEILEs.

This study demonstrates that NEILEs can also expand into foreign markets according to their own characteristics. Undoubtedly, they need to choose appropriate internationalization target mode and international market entry way in line with the extent and duration of their losses, and their advantageous slack resources.

In this paper, the authors construct the rapid internationalization theory of NEILEs based on the dual situation of negative attainment discrepancy and advantageous slack resources in digital economy era. Moreover, the authors discover the behavioral characteristics and patterns of NEILEs' transnational entrepreneurship.

Grounding the research in the stimulus-organism-resource (S-O-R) framework, this study aims to address the research gap of explaining and predicting the relationship between price discounts, interactivity and professionalism on college students’ purchasing intention in live-streaming shopping. It also attempts to understand if trust plays the role of mediator in the effect of these relationships.

This study collected data using a questionnaire protocol adapted and refined from the original scales in existing studies. The partial least squares structural equation modeling was used to analyze data collected from 258 college students in China. Other than assessing the path model’s explanatory power, this study examined the model’s predictive power toward predicting new cases using PLS predict.

Results indicated that all three predictors have a positive significant relationship with trust, while only price discounts demonstrate a significant relationship with purchase intention. Simultaneously, the mediation results provide support to the S-O-R framework demonstrating that external factors (professionalism, interactivity and price discounts) can arouse organism (trust), which in return, generate a behavioral outcome (purchase intention).

This study is the first few studies that focus on college students’ behavioral responses in an online shopping environment. At the same time, this is the first study supplement the explanatory perspective with a predictive focus, which is of particular importance in making sound recommendations on managerial decision-making.

The safety management of construction machines is of primary importance. Considering that traditional construction machine safety monitoring and evaluation methods cannot adapt to the complex construction environment, and the monitoring methods based on sensor equipment cost too much. This paper aims to introduce computer vision and deep learning technologies to propose the YOLOv5-FastPose (YFP) model to realize the pose estimation of construction machines by improving the AlphaPose human pose model.

This model introduced the object detection module YOLOv5m to improve the recognition accuracy for detecting construction machines. Meanwhile, to better capture the pose characteristics, the FastPose network optimized feature extraction was introduced into the Single-Machine Pose Estimation Module (SMPE) of AlphaPose. This study used Alberta Construction Image Dataset (ACID) and Construction Equipment Poses Dataset (CEPD) to establish the dataset of object detection and pose estimation of construction machines through data augmentation technology and Labelme image annotation software for training and testing the YFP model.

The experimental results show that the improved model YFP achieves an average normalization error (NE) of 12.94 × 10^–3, an average Percentage of Correct Keypoints (PCK) of 98.48% and an average Area Under the PCK Curve (AUC) of 37.50 × 10^–3. Compared with existing methods, this model has higher accuracy in the pose estimation of the construction machine.

This study extends and optimizes the human pose estimation model AlphaPose to make it suitable for construction machines, improving the performance of pose estimation for construction machines.

This study aimed to improve the financing credit evaluation for small and medium-sized real estate enterprises (SMREEs). A financing credit evaluation model was proposed, and a blockchain-driven financing credit evaluation framework was designed to improve the transparency, credibility and applicability of the financing credit evaluation process.

The design science research methodology was adopted to identify the main steps in constructing the financing credit model and blockchain-driven framework. The fuzzy analytic hierarchy process (FAHP)–entropy weighting method (EWM)–set pair analysis (SPA) method was used to design a financing credit evaluation model. Moreover, the proposed framework was validated using data acquired from actual cases.

The results indicate that: (1) the proposed blockchain-driven financing credit evaluation framework can effectively realize a transparent evaluation process compared to the traditional financing credit evaluation system. (2) The proposed model has high effectiveness and can achieve efficient credit ranking, reflect SMREEs' credit status and help improve credit rating.

This study proposes a financing credit evaluation model of SMREEs based on the FAHP–EWM–SPA method. All credit rating data and evaluation process data are immediately stored in the proposed blockchain framework, and the immutable and traceable nature of blockchain enhances trust between nodes, improving the reliability of the financing credit evaluation process and results. In addition, this study partially fulfills the lack of investigations on blockchain adoption for SMREEs' financing credit.

Theory is a kind of condensed human knowledge. This paper is to examine the mechanism of interdisciplinary diffusion of theoretical knowledge by tracing the diffusion of a representative theory, the Technology Acceptance Model (TAM).

Based on the full-scale dataset of Web of Science (WoS), the citations of Davis's original work about TAM were analysed and the interdisciplinary diffusion paths of TAM were delineated, a supervised machine learning method was used to extract theory incidents, and a content analysis was used to categorize the patterns of theory evolution.

It is found that the diffusion of a theory is intertwined with its evolution. In the process, the role that a participating discipline play is related to its knowledge distance from the original disciplines of TAM. With the distance increases, the capacity to support theory development and innovation weakens, while that to assume analytical tools for practical problems increases. During the diffusion, a theory evolves into new extensions in four theoretical construction patterns, elaboration, proliferation, competition and integration.

The study does not only deepen the understanding of the trajectory of a theory but also enriches the research of knowledge diffusion and innovation.

The study elaborates the relationship between theory diffusion and theory development, reveals the roles of the participating disciplines played in theory diffusion and vice versa, interprets four patterns of theory evolution and uses text mining technique to extract theory incidents, which makes up for the shortcomings of citation analysis and content analysis used in previous studies.