The current study aims to examine the symmetric and asymmetric effects of climate change (CC) on rice productivity (RP) in Malaysia. The Autoregressive-Distributed Lag (ARDL) and Non-linear Autoregressive Distributed Lag (NARDL) models were employed in this study. Time series data from 1980 to 2019 were collected from the World Bank and the Department of Statistics, Malaysia. The estimated results are also validated using Fully Modified Ordinary Least Squares (FMOLS), Dynamic Ordinary Least Squares (DOLS), and Canonical Cointegration Regression (CCR). The findings of symmetric ARDL show that rainfall and cultivated area have significant and advantageous effects on rice output. The NARDL-bound test outcomes display that climate change has an asymmetrical long-run impact on rice productivity. Climate change has had varying degrees of positive and negative impacts on rice productivity in Malaysia. Positive changes in temperature and rainfall have a substantial and destructive impact on RP. At the same time, negative variations in temperature and rainfall have a substantial and positive impact on rice production in the Malaysian agriculture sector. Changes in cultivated areas, both positive and negative, have a long-term optimistic impact on rice output. Additionally, we discovered that only temperature affects rice output in both directions. Malaysian policymakers must understand the symmetric and asymmetric effects of CC on RP and agricultural policies that will promote sustainable agricultural development and food security.

This study aims to examine the factors that affect organizational performance in the manufacturing industry of Bangladesh. This study identifies transformational leadership, human capital, and job satisfaction as significant determinants of organizational performance. The analysis focused on the employees of diverse manufacturing organizations in Bangladesh treated as the targeted population. The data collection was conducted using a survey methodology, wherein a questionnaire was distributed to the participants via postal mail along with a cover letter to enhance comprehension. The ultimate sample consisted of 294 participants, obtained from a pool of 400 individuals who were sent survey questionnaires. The response rate for the survey was 73.5%. Furthermore, a significance level of 5% was employed to assess the hypotheses, and the data pertaining to the research objective of this study were analyzed using SPSS software. The study results indicate that organizational performance is significantly influenced by transformational leadership, human capital, and job satisfaction. These three independent variables explain (R2) 59.6% variance in organizational performance. It is also found that transformational leadership (β-value = 0.443) has the highest impact on the organizational performance of manufacturing firms. This study provides implications for organizational management to improve long-term organizational performance.

In this study, we examine the research trends and collaboration networks in AI-driven transformation in banking by utilizing 751 Scopus-indexed documents from 2020 to 2026. We found that the number of publications continues to grow until 2024, and the literature is spread out over a series of conference proceedings, with a core set of highly cited foundational papers that define the overall landscape of research. In addition, keyword analysis and mapping of conceptual structure indicate a core set of research focused on applications of artificial intelligence and machine learning to risk management, fraud detection, cybersecurity, and market analysis. Thematic mapping of the search results shows that "artificial intelligence in banking" is a core theme, while generative AI, including ChatGPT and large language models, is a niche theme. The motor themes quadrant shows a sparse set of papers, which indicates that cutting-edge areas are still in their infancy. Further, we found that national production is dominated by a single predominant producer, while fragmented co-authorship networks are evident, with a mere 23.7% international collaboration. The study further proposes a future research agenda that includes the integration of GenAI with fundamental banking tasks, adversarial robustness, explainability and fairness, and impact, with the aim of shifting from a niche theme to a field-defining motor theme. This broadening area of artificial intelligence in banking also accelerates SDG 8(Decent Work and Economic Growth) and SDG 9(Industry, Innovation and Infrastructure).

During this global pandemic, people in different sectors are really passing hectic days with mental and physical illness especially teachers or faculties who are providing online education at the tertiary level. This paper aims at finding the factors associated with job satisfaction for them. We discussed the job satisfaction attributes by using a regression model with factors analysis. For doing this research, we collected data from private and public universities in Bangladesh through Google form and analyzed the data with SPSS 26.0. The factors that we found through literature review include Monetary factors, Professional development factors, Physical factors, and psychological factors. We found that these factors have a direct impact on job satisfaction for teachers at tertiary level especially in this global pandemic and found our model significant. This paper will be helpful for the university authority to take proper steps to enhance the job satisfaction for faculties.

Bangladesh is a riverine country where majority of the people lead their life depending on agriculture. With the advancements of ICT, throughout the world agricultural sector has been updated and developed. Bangladesh has already attempted to adopt ICT in agriculture and started getting benefits for the longer period of time. This paper aims at finding out the effect of Information and Communication Technology (ICT) on padday production. The study was conducted at Zinardi union, Palash Thana, Narsingdi District, Bangladesh. Exploratory Factor Analysis (EFA) approach has been undertaken to test the data. Findings stated that ICT has significant impact on paddy cultivation in the selected union.