The Relationship between Organizational Culture, Job Satisfaction, and Commitment of Lecturers at Universities

Purpose: The study aimed to determine the influence of factors on job satisfaction and the relationship between satisfaction, organizational culture, and the organizational commitment of lecturers at universities in Ho Chi Minh City. Design/Methodology/Approach: This was a quantitative study in which the authors compile theories, analyze and synthesize scales for research concepts, and propose research models. The online survey collected 532 answer sheets from professors and lecturers from universities in Ho Chi Minh City, of which 525 were valid and included in SmartPLS 3 to evaluate the validity and reliability of the scale and to analyze the relationship among the concepts in the suggested model. Findings: The results show that several factors significantly impact employee satisfaction in the field of education, such as job promotion, leadership or supervision, working environment, income, and the job itself. In addition, both satisfaction and organizational culture impact organizational commitment. The study's findings have implications for educational institutions, lecturers, policymakers, researchers, and funding agencies. They highlight the importance of factors like leadership development and organizational culture in enhancing job satisfaction and commitment among lecturers, offering valuable insights for improving the educational environment in Ho Chi Minh City and beyond. Originality: The results aligned with previous studies presented in the literature section. However, this study revealed some specific characteristics of lecturers in universities in Ho Chi Minh City, Vietnam, where lecturers focused on personal development but were committed to the organization via job satisfaction and culture. Doi: 10.28991/ESJ-2023-SIED2-021 Full Text: PD

Converging artificial intelligence and blockchain technologies for security and risk management in banking

The focus of this thesis is on understanding the potential applications of blockchain and AI technologies in the banking and finance sector for better risk management and cybersecurity. In this thesis, I will do an extensive literature review of research on AI and Blockchain in the top eight information systems journals and some top-rated computer science journals. The intention is to examine the use of blockchain and AI to enhance remote work security and fraud detection in the Banking and Finance sector

Effects of Data Standardization on Hyperparameter Optimization with the Grid Search Algorithm Based on Deep Learning: A Case Study of Electric Load Forecasting

This study investigates data standardization methods based on the grid search (GS) algorithm for energy load forecasting, including zero-mean, min-max, max, decimal, sigmoid, softmax, median, and robust, to determine the hyperparameters of deep learning (DL) models. The considered DL models are the convolutional neural network (CNN) and long short-term memory network (LSTMN). The procedure is made over (i) setting the configuration for CNN and LSTMN, (ii) establishing the hyperparameter values of CNN and LSTMN models based on epoch, batch, optimizer, dropout, filters, and kernel, (iii) using eight data standardization methods to standardize the input data, and (iv) using the GS algorithm to search the optimal hyperparameters based on the mean absolute error (MAE) and mean absolute percent error (MAPE) indexes. The effectiveness of the proposed method is verified on the power load data of the Australian state of Queensland and Vietnamese Ho Chi Minh city. The simulation results show that the proposed data standardization methods are appropriate, except for the zero-mean and min-max methods

New Algorithms for Balancing Energy Consumption and Performance in Computational Clusters

In this paper, we propose new real-time measurement-based scheduling algorithms to achieve a trade-off between the energy efficiency and the performance capability of computational clusters. An investigation is performed using a specific scenario of computing clusters with realistic parameters. Numerical results show that a trade-off between the performance and the energy efficiency can be controlled by the proposed algorithms

Comparing the Harrod-Domar, Solow and Ramsey growth models and their implications for economic policies

Purpose – The principal aim of this paper is to review three basic theoretical growth models, namely the Harrod-Domar model, the Solow model and the Ramsey model, and examine their implications for economic policies. Design/methodology/approach – The paper utilizes a positivist research framework that emphasizes the causal relationships between the variables in each of the three models. Mathematical methods are employed to formulate and examine the three models under study. Since the paper is theoretical, it does not use any empirical data although numerical illustrations are provided whenever they are appropriate. Findings – The Harrod-Domar model explains why countries with high rates of saving may also enjoy high rate of economic growth. Both the Solow and Ramsey models can be used to explain the medium-income trap. The paper examines the impact of Covid shocks on the macroeconomy. While the growth rate can be recovered, it may not always possible to recover the output level. Research limitations/implications – For the Harrod-Domar model, the public spending decreases the private consumption at the period 1, but there is no change in the capital stock and hence the production in subsequent periods. For the Ramsey model with AK production function, both the private consumption and the outputs will be lowered. In both the Harrod-Domar and Ramsey models with Cobb-Douglas production function, if the debt is not high and the interest rate is sufficiently low, it is better to use public debt for production rather than for consumption. If the country borrows to recover the Total Factor Productivity after the Covid pandemic, both the Harrod-Domar and Ramsey models with Cobb-Douglas production function show that the rate of growth is higher for the year just after the pandemic but is the same as before the pandemic. Practical implications – The economy can recover the growth rate after a Covid shock, but the recovery process will generally take many periods. Social implications – This paper focuses on economic implications and does not aim to examine social implications of policy changes or Covid-type shock. Originality/value – The paper provides a comparison of three basic growth models with respect to public spending, public debts and repayments and Covid-type shocks

Bending and vibration analysis of multi-folding laminate composite plate using finite element method

This paper deals with the bending and vibration analysis of multi-folding laminate composite plate using finite element method based on the first order shear deformation theory (FSDT). The algorithm and Matlab code using eight nodded rectangular isoparametric plate element with five degrees of freedom per node were built for numerical simulations. In the numerical results, the effect of folding angle on deflections, natural frequencies and transient displacement response for different boundary conditions of the plate were investigated