Leadership is the most important factor for schools to achieve their goals.The success of the school is the success of the leadership in the school itself.This study aims to identify the characteristics of effective leadership and its influence on school effectiveness in the era of independent learning.To achieve these objectives, this study used an exploratory sequential mixed method.The initial phase of the research used qualitative methods, then the second phase developed and substantiated the initial findings widely using quantitative methods.A purposive sampling of 25 teachers was used to collect qualitative data.In the quantitative phase, a survey was conducted among 304 teachers in 59 public junior high schools in North Sumatra Province, Indonesia.The qualitative and quantitative research findings prove and support that transformational leadership is a force to realize school effectiveness in the era of independent learning.These characteristics of transformational leadership are (1) idealized influence, (2) inspirational motivation, (3) intellectual stimulation, and (4) individualized consideration.The idealized influence variable is the variable that most strongly influences school effectiveness by 41.1%; Individualized considerance is the second most powerful variable affecting school effectiveness by 38.56%; inspiration motivation is the third most powerful variable affecting school effectiveness at 31.36%; intellectual stimulation is the fourth most powerful variable affecting school effectiveness by 17.22%.
This study investigates the influence of affective commitment (AC) on unethical pro organizational behavior (UPOR) among employees in Indonesian Micro and Small Enterprises (MSEs).Drawing upon the Cognitive-Affective Personality System (CAPS) theory and Social Exchange Theory, we examine the mediating role of job embeddedness (JE), specifically focusing on the dimensions of fit to organization and fit to community.Using a sample of 118 employees from Indonesian MSEs, we conducted a quantitative study employing regression analysis.Our findings reveal that affective commitment has a significant negative effect on UPOR, contrary to our initial hypothesis.Furthermore, we found that fit to community mediates the relationship between affective commitment and UPOR, while fit to organization does not.These results highlight the importance of considering the role of non-organizational factors in shaping employees' unethical behavior and offer practical insights for managers in MSEs to foster affective commitment and mitigate UPOR.Our study contributes to the literature by providing a nuanced understanding of the relationship between affective commitment and UPOR in the context of MSEs and underscores the significance of job embeddedness, particularly fit to community, in this relationship.
This study presents a comprehensive bibliometric analysis of Reverse Logistics (RL) research from 2013 to 2023, aiming to identify key trends, influential authors, institutional contributions, and global engagement within the field.Utilizing data from 1,650 articles retrieved from the Scopus database, the Analysis reveals the growing importance of RL in supply chain management and sustainability research.The study employs various bibliometric techniques, including authorship analysis, temporal Analysis, institutional contribution analysis, global participation analysis, journal impact analysis, keyword dynamics analysis, and citation network analysis.The results highlight the significant contributions of authors such as Govindan and Kannan, the steadily increasing number of RL publications over time, and the global nature of RL research, with strong participation from countries like China, India, and the United States.The study also identifies the most influential journals in the field, such as the Journal of Cleaner Production, and the core themes and emerging trends in RL research, including sustainable development and circular economy.However, the study is limited by its reliance on a single database and potential biases in selecting search terms and inclusion criteria.Future research should consider incorporating data from multiple sources and employing more diverse methodological approaches to understand the RL research landscape comprehensively.
Despite numerous studies and implementations on text generation in the field of Artificial Intelligence (AI), the purpose of this research is to study the challenges and practicality of using Natural Language Generation (NLG) on Food and Beverages (F&B) marketing text generation using generative AI techniques.Since there are a number of different researchers that claim they are able to generate realistic text that is acceptable, we would like to investigate the degree to which AI models can effectively generate marketing text for advertising purpose.The goal of this research is to investigate several existing techniques for text generation where implementation of Long Short-Term Memory (LSTM), Open Pretrained Transformer (OPT) and Keyword to Text Generation (K2T) will be experimented.Locally collected marketing text samples will be applied to train and validate based on how realistic the generated texts are from the perspective of human expert based on realistic and practical attributes.The text-based advertisement will be developed and reviewed in the current research.A discussion based on the models' theoretical and algorithmic fundamentals has been presented from the perspective of models' performance.
In this paper, we present the development of a driving education prototype simulator, aiming to address dangerous traffic situations frequently encountered in daily life, particularly in urban areas like Klang Valley, Malaysia.Our initial driving simulator version focused on track-based training tailored to Malaysian driving exams, but we recognized its limitations in preparing learner drivers for real-world challenges due to the lack of risk.To add the value of study to our project, we designed three scenarios based on common dangerous situations observed in dashboard camera (dashcam) footage from Malaysian drivers.Due to the lack of reliable openly discussed methods on designing such scenarios and implementing it into a virtual environment, we devised a rudimentary method in the scenario designs.Our goal here is to open up the discussion to study reliable methods of designing scenarios not just for driving education but all forms of scenarios that are used for training environments.These scenarios have the potential to benefit education and training by creating realistic scenarios and environments.
