Purpose: Industrial training programs are structured educational initiatives that provide supervised, practical experience within designated timeframes in both the private and government sectors. The primary objective was to bridge the gap between theoretical knowledge and practical skills, allowing participants to apply classroom learning in real-world environments. This hands-on approach enhances competency development, understanding of industry practices, teamwork, and professional ethics, ultimately preparing individuals for successful careers in various industries. Research Methodology: Data analysis was performed using a specialized statistical software tool designed for predictive modeling and analysis. This tool was employed to examine and interpret the dataset, thus enabling the extraction of meaningful insights and predictions. The analytical process involves a series of statistical techniques, algorithms, and models to identify patterns, correlations, and trends within the data. By leveraging the capabilities of this advanced statistical package, the research team derived valuable information, made informed predictions, and drew significant conclusions from comprehensive data analysis. Results: From the instructors' perspective, industrial training significantly enhances students' proficiency in both formal and informal communication, assists them in identifying appropriate research areas for their projects, and improves their socialization and relationship-building skills. Employees reported that industrial training increased their confidence in problem solving and emphasized the importance of continuous learning. A notable challenge faced by employees during their internships is related to workplace safety. Limitations: The findings of this study are primarily applicable in educational settings. Contribution: Our study concludes that industrial training is crucial for enhancing students’ post-training abilities and knowledge. We recommend recognizing industrial training as an essential tool for improving employees' skills and capabilities.

Purpose: This  study ascertains how succession-planning practices affect employee relations in public healthcare facilities in Zimbabwe. Research Methodology: The pragmatism philosophy, which emphasizes relevance in interpreting mixed-method data, served as the foundation for this study. A sample size of 60 respondents was chosen from 120 healthcare professionals. A descriptive method was used for data analysis using SPSS and theme analyses. Results: The results revealed that although succession planning exists in healthcare institutions, its implementation is shambolic, heightening its negative impact on employee relations, as evidenced by high staff turnover. Limitations: Despite adopting a mixed-method approach, the findings could not unravel the effective implementation of succession planning in the whole country; hence, the results from one institution cannot be generalized. Contribution:  Effective succession planning results in better employee relationships, lower uncertainty, increased engagement, and boosted morale among staff members. It can also broaden our understanding of best practices in succession planning.

Purpose: This study aims to investigate the influence of consumption values (functional, social, emotional, epistemic, and conditional) on adopting a cashless society while examining the moderating effect of perceived cost and the mediating effect of cashless readiness. Research Methodology: A quantitative research approach was employed, utilizing a convenience sampling method to collect data from 200 respondents through a survey. Statistical analysis techniques such as structural equation modeling (SEM) were likely used to analyze the data and test the hypothesized relationships. Results: The study reveals that functional, epistemic, and conditional values significantly impact cashless readiness, which in turn affects the adoption of a cashless society. Perceived cost is identified as a significant moderator between cashless readiness and the adoption of a cashless society. Additionally, the findings indicate that cashless readiness partially mediates the relationship between functional, epistemic, and conditional values and the adoption of a cashless society. Limitations: A potential limitation could be the use of a convenience sampling method, which may affect the generalizability of the findings to a larger population. Contributions: The findings of this study could be valuable for mobile financial service providers, banking institutions, and governmental organizations in developing strategies to increase the adoption of digital payment systems. It contributes to the existing literature on consumer behavior and technology adoption, specifically in the context of cashless societies and mobile financial services.

Purpose: This study investigates the factors influencing retail firms' intentions to adopt Artificial Intelligence (AI) to enhance customer retention and loyalty in Dhaka, Bangladesh. The research focuses on examining how perceived usefulness, perceived ease of use, competitive pressure, technological readiness, and organizational innovativeness influence retail entrepreneurs’ adoption of AI as a strategic tool for customer engagement. Research Methodology: A quantitative research design was employed, incorporating a hypothetical-deductive approach. The study utilized a cross-sectional design, drawing a sample of 250 retail firms through stratified random sampling in Dhaka. Data were collected using structured questionnaires and analyzed using statistical techniques to assess the relationships between the variables. Results: The study identified that all five factors perceived usefulness, perceived ease of use, competitive pressure, technological readiness, and organizational innovativeness positively and significantly influence retail entrepreneurs' intentions to adopt AI. These findings emphasize the crucial role of both technological and organizational dynamics in driving AI adoption decisions within the retail sector. Limitations: The research is geographically confined to retail firms in Dhaka, which may limit the generalizability of the findings to other regions or countries. Furthermore, the study's cross-sectional design restricts the ability to monitor AI adoption trends over time, indicating that future research could benefit from employing longitudinal designs and encompassing a broader geographical scope. Contribution:  This study provides valuable insights for retail managers and entrepreneurs seeking to leverage AI to enhance customer loyalty. It underscores the importance of fostering technological readiness and cultivating a culture of innovation within retail firms. The research contributes to the expanding body of knowledge on AI adoption in emerging markets, particularly concerning customer retention strategies in the retail sector.