This study examines the nexus of green supply chain practices (G-SCP) toward financial performance (FnP) from the perspective of China. Second, the study explores the moderating impact of i4.0 model of technologies between the connection of G-SCP and FnP. The outcomes confirmed a positive correlation between G-SCP and FnP. Furthermore, a moderation of i4.0 technologies was confirmed between the association of G-SCP and FnP. This study assures that G-SCPs are essential for organisations such as optimising FnP. This study additionally provided insights into i4.0 model of technologies which is found to be a valid factor that affects relational strength. However, this study provides interesting and fruitful applications for the relevant management and future directions for the scholars to consider more studies in future to validate the current outcomes.

In order to overcome the problems of low quality index, innovative thinking path coefficient, and high error value in traditional methods, a high quality construction method of innovation and entrepreneurship education system from the perspective of three comprehensive education is proposed. Firstly, analyse the participants and influencing factors in the construction of the innovation and entrepreneurship education system from the perspective of comprehensive education. Secondly, establish a preliminary innovation and entrepreneurship education system. Finally, after evaluating the quality of the innovation and entrepreneurship education system, we will optimise and adjust the preliminary construction system to achieve high-quality construction of the innovation and entrepreneurship education system. The experimental results show that the quality index of the innovation and entrepreneurship education system constructed in this article is high, the path coefficient of innovative thinking is high, and the average evaluation error value is low.

The swift expansion of Internet of Things (IoT) devices has resulted in unparalleled prospects for connectivity and information sharing. However, the pervasive deployment of IoT devices also give rise to security risks with the potential for privacy breaches and data vulnerabilities over the few years, the incorporation of Blockchain technology with IoT has shown to be a viable solution for overcoming these security challenges. The aim of the paper is contribute to the ongoing discourse on securing IoT ecosystems through Blockchain technology. The paper presents a review of the security threats, challenges in blockchain and IoT integration, issues and opportunities. It examines the potential of Blockchain as a solution to mitigate these threats, offering a detailed analysis of Blockchain-based security mechanisms and their integration with IoT environments. An examination of different consensus protocols and existing security techniques employed in Blockchain-IoT integration is presented. Additionally, the paper outlines evaluation parameters for assessing the effectiveness of Blockchain-based solutions in securing IoT infrastructures.

In the Metaverse technology, also known as MVTECH, individuals connect with one another via the use of avatars. This technology creates an immersive virtual environment. With the MVTECH, a lot of opportunities were promised to be made available to a variety of industries, including higher education. A research model was developed by combining the essential elements of the 'unified theory of acceptance and use of technology' (UTAUT) with the variables of 'perceived curiosity' (PC) and 'extraversion' (EXT). 'Effort expectancy' (EE), 'performance expectancy' (PE), 'social influence' (SI), and 'facilitating conditions' (FC) are a few of these components. The information came from an online poll that was sent to 422 kids in Jordan schools. The 'structural equation modelling' (SEM) study showed that students' feelings about the Metaverse were greatly affected by their involvement in PE, FC, and EXT. The PC construct had a big effect on the EE construct.

In order to solve the problems of low system integrity, poor closeness and reliability of evaluation indicators in traditional methods, a construction method of teaching service quality evaluation index system under the digital background is proposed. Complete the selection of evaluation indicator data through the ripple effect model. By calculating the Min's distance to measure the similarity of evaluation index data and removing data with high similarity, principal component analysis (PCA) is used to normalise and reduce the dimensionality of the data. Using extreme learning machine algorithm to classify and process evaluation indicators, and achieving research on the construction of teaching service quality evaluation indicator system. The case analysis results show that when the number of indicators is 1000, the completeness of the indicator system of the proposed method is 98%, the closeness is closer to 1, and the maximum reliability is 97%, which has the characteristics of high feasibility.

The study aims to investigate the impact of proactive personality on new graduates' networking activity for job searching, as well as how proactive personality affects networking behaviour for job searching via network size and tie strength. In order to do this, the relationships among proactive personality, network size, tie strength, and networking activity are explained using both individual difference theory and social network theory. Using the convenient sampling method, a sample of 773 graduates from various Vietnamese universities was obtained. Analysis of moment structures (AMOS) software was used for data analysis to investigate the mediating effects. Our findings showed that job seekers' proactive personalities had a positive effect on their networking behaviour. More crucially, our research revealed that network size and tie strength operate as mediators between proactive personality and networking activity, which underscores the connection between these two factors in job searches. Further discussion is given to the study's theoretical and practical implications.

This research proposes a cascade feed forward network (Cascade FFN) for the optimal call admission control (CAC) over networks. Initially, the long-term evolution (LTE) network is simulated and the incoming call is recognised as a new call or else handoff call. Likewise, the handoff call is identified by various channel parameters. Finally, the CAC is performed using the Cascade FFN, which is obtained by incorporating the deep feed forward network (DFN) and cascaded deep neuro-fuzzy network (DNFN). After the admission of the new user, number of active users in the individual cell is updated. The simulation is performed based on various parameters and the proposed model has gained throughput of 444058 bps, cell power of 54.267 dBm, delay of 0.081 s, user call drop of 940, call blocking probabilities of handoff and new user as 0.693, and 0.677; and the call dropping probabilities of handoff and new user is 0.733, and 0.740.

The research on online financial product marketing information push is of great significance for improving the efficiency of financial institutions, optimising product design, and promoting financial technology innovation and digital transformation. In order to solve the problems existing in current methods, an online financial product marketing information push method based on social relationship network analysis is proposed. This method uses social network to analyse and calculate the influence of user relationship, and combines with two-way gated recurrent unit (GRU) neural network to extract user interest. Push online financial product marketing information based on user interests and multi-Markov chain. Experimental results show that the proposed method performs well in accuracy, push time and user retention rate. Therefore, this method has the characteristics of high precision and high efficiency.

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In order to solve the problems of low internal risk identification rate, low accuracy of internal control strategy execution, and long response time in traditional methods, an optimisation method of internal control strategies in enterprises under the background of digital empowerment is proposed. Analysing the impact of digital empowerment on internal control in enterprises, identifying the problems existing in internal control, and proposing an optimisation path for internal control strategies from the perspectives of clarifying and integrating strategic objectives and internal control processes, accurately identifying and monitoring key control points (KCPs) in real time, balancing cost-effectiveness and risks, tailoring and continuously optimising internal control systems, and comprehensively optimising other key measures for internal control. The test results show that the maximum internal risk identification rate of this method is 97.8%, the maximum accuracy of internal control strategy execution is 97.7%, and the average response time is 37.09 min.