Search

The accelerated application of emerging technologies in the financial field in the era of informationization has put forward brand-new challenges and requirements for the development of disciplines as well as the teaching mode of economics and management majors in colleges and universities. In this paper, the teaching resource base of economics and management majors is first constructed on the basis of the RNMIE model combined with cloud computing and other technologies. Then the theory of self-organizing behavior is introduced to build a three-dimensional informatization teaching platform for economics and management majors. On this basis, combined with the online learning teaching resources analysis model, the personalized recommendation method of hybrid recommendation is used to recommend matching resources for economics and management students. The learning satisfaction assessment model is constructed with the students’ learning satisfaction assessment system and structural equation model. Simulation tests and example analyses were conducted to recommend resources and ensure student satisfaction in the three-dimensional computer-based teaching platform for economics and management in colleges and universities. It is found that when the number of nearest neighbors increases from 5 to 50, the MAE of personalized recommendation of economic and management teaching resources based on hybrid recommendation decreases by 30.91%, and the direct utility path coefficient of teaching effect on students’ learning satisfaction is 0.62. The teaching resources of economics and management constructed by combining the RNMIE model can help students realize the diversified choices of teaching resources and also provide a new reference for the innovative informationized teaching mode of economics and management majors.

Nonferrous metal industry is the foundation of China's substantial economy and plays a key role in national economy and defense construction. Industrial software is crucial for the high-quality development of the nonferrous metal industry and is associated with the in-depth implementation of national software development strategies. Currently, the industrial software development in the nonferrous metal industry is significantly restricted by the lack of knowledge models. Hence, we propose a method for constructing an intelligent model library for the nonferrous metal industry. Considering meta-model-driven engineering, we define the nonferrous metallurgical meta-model and its attributes, and propose a meta-modeling method based on the MODELING architecture. Additionally, we design an overall architecture for the intelligent model library based on industrial Internet, an agile modeldevelopment environment integrating multiple languages, and a meta-model encapsulation system based on multi-scenario black-box reuse. Moreover, a meta-model full lifecycle management platform is constructed based on a five-layer two-dimension classification standard and the domain knowledge graph. The intelligent model library for the nonferrous metal industry is developed based on the long-term accumulation of nonferrous metallurgy process mechanism, operating experiences, and intelligent methods. The good role of intelligent model library in improving the intelligent level in engineering applications is presented through the application of two typical nonferrous metallurgical scenarios. The intelligent model library of the nonferrous metal industry provides a core knowledge support for the development of industrial software and plays a fundamental role in promoting smart manufacturing and strengthening the nonferrous metal industry.

Stimulated by the burgeoning tourism industry and its vital importance to the country’s economy, this study examines the firm-specific and contextual determinants of Sri Lankan corporate hotel performance. We use data from a sample of 29 listed hotels for seven years from 2012 to 2018. This study uses a multidimensional financial performance measure (CFPS), in addition to return on assets (ROA) and return on equity (ROE). Consequently, the results from the panel regression revealed that hotels’ age and size are negatively and significantly affect financial performance. Furthermore, the results suggest that the profitability of Sri Lankan hotels is driven by managerial efficiency, Location factors, geographical diversification, and connection to a wider business network.Keywords: Firm Performance, Determinants, Corporate HotelsJEL Classifications: M410, M210, M370, L1DOI: https://doi.org/10.32479/ijefi.7880

This study examines the earning management behavior of Sri Lankan firms following IFRS convergence. Moreover, we investigate whether the earning management following IFRS convergence is similar across different companies. We separately evaluate the companies based on size, auditor type, and performance to see whether these factors can moderate earning management behavior. We collected the data from a sample of 160 companies that are listed on the Colombo Stock Exchange (CSE) for the period spanning from 2008 to 2015. The period from 2008 to 2011 was the pre-IFRS convergence and the period after 2012 was the post-IFRS period. Following prior studies, we used several measures to capture the earning management around IFRS convergence. Especially, our measures aim to identify earning smoothing and managing towards earning target and thereby determining whether the firms have engaged in earning management and its increase and decrease. The results show that the earning management, in overall, has not decreased following IFRS convergence. However, our results indicate that the post-IFRS earning management is vary between companies. That is, large companies and companies with big four auditors experienced a decrease in earning management following IFRS convergence. Similarly, certain aspects of earning management of high performing companies is also found to have decreased in post-IFRS convergence. Finally, our findings provide important implications for regulators, investors and other corporate stakeholders. Keywords: Earnings Management, IFRS Convergence, Sri Lankan Firms JEL Classifications: M410, M480, C2, C3 DOI: https://doi.org/10.32479/ijefi.8872

In order to obtain the precise contour of the conjugate cam of the rotation variable speed mechanism of the STAUBLI type electronic dobby,the data of original conjugate cam profile and other main parts of the mechanism is measured,the 3D solid model of rotation variable speed mechanism is established based on CREO software and the kinematics simulation analysis is carried out. Then the angular displacement,angular velocity as well as angular acceleration curves of the follower are obtained before the redesign. From the angle of the kinematics design,based on the theoretically derivate conjugate cam contour line of mathematic model,the conjugate cam curve equation is redesigned,the equation is solved numerically and the theoretical conjugate cam contour curve is reached out. After that,conjugate cam 3D solid model is set up on the basis of theoretical contour curve and is plugged to the rotation variable speed mechanism to present kinematics simulation analysis.The analysis results show that the movement curve of redesigned conjugate cam is smooth,which is satisfied with the working requirements.

Aiming at the problem of safe operation in the medium voltage distribution network with neutral point grounding through small resistance, the distribution network model was built, and on this basis, MW-level photovoltaic (PV) system, doubly fed Induction generator (DFIG) wind turbine, permanent magnet synchronous generator (PMSG) wind turbine and energy storage device was connected respectively in this paper. The ground current and earth potential rise was studied when the power was delivered by mistake. The simulation results show that in the system with neutral point grounding through small resistance, whether it is the traditional or the active distribution network, the three-phase power delivery method is more able to ensure the personal safety of power grid operators. However, The access to distributed generator (DG) in the distribution network will have a greater impact on ground current and earth potential rise in the case of three-phase power delivery. Especially when the ground current and earth potential rise will increase after DG connected to distribution network, which is still likely to pose a threat to personal safety and needs further research.

The objective of the paper is to introduce a conceptual framework for the study of learning behavior of an individual investor in the context of stock trading. It is developed based on the review of behavioral finance literature, and insights from cognitive, behavioral and social learning theories and related empirical evidence. The framework recognizes the investor as an entity that learns consciously and/or unconsciously for continually updating its perspectives underlying stock trading. The intentional or consciousness form of learning occurs as individual learning through reflection of past trading experiences whereas the learning happens unconsciously as social learning through inquiry and imitating the others’ behaviors. These learning processes are expected to be affected by interaction of various structures and processes, both internal and external to the investor, such as cognitive, affective, social and behavioral ones. Accordingly, the framework suggests five hypotheses to examine the determinants of these learning behaviors and to assess whether the investors learn over passage of time through the effects of these structures and processes. It promotes primary data-based behavioral finance empirical studies to track dynamics involved in learning, which could provide new insights on such behavior predicted by the adaptive market hypothesis.

As the two important form of financial market, the risk of financial securities, such as stocks and bonds, has been a hot topic in the financial field; at the same time, under the influence of many factors of financial assets, the correlation between portfolio returns causes more research. This paper presents Copula-SV-t model that it uses SV-t model to measure the edge distribution, and uses the Copula-t method to obtain the high-dimensional joint distribution. It not only solves the actual deviation with using the ARCH family model to calculate the portfolio risk, but also solves the problem to overestimate the risk with using extreme value theory to study financial risk. Through the empirical research, the conclusion shows that the model describes better assets and tail characteristics of assets, and is more in line with the reality of the market. Furthermore, Empirical evidence also shows that if the portfolio is relatively large degree of correlation, the ability to disperse portfolio risk is relatively weakness.