19916 research outputs found
Sort by
PROPERTY MANAGEMENT SYSTEM
No full textThe real estate industry generates and manages large amounts of data, including tenant information, lease agreements, property maintenance schedules, and financial transactions. Reliance on traditional manual methods often results in inefficiencies, fragmented data, and delays in decision-making. To overcome these challenges, this project presents the design and implementation of a Real Estate Property Management System (REMS) for Future Properties, a company aiming to optimize its operations through digital transformation.
The proposed system is developed on Microsoft Dynamics 365 as the core platform, integrated with the Microsoft Power Platform tools (Power Apps, Power Automate, and Power Pages). This integrated framework provides a centralized solution for data management, workflow automation, and real-time reporting. The REMS consolidates tenant and property information, streamlines lease and financial management, and introduces tenant self-service capabilities to enhance engagement.
The system incorporates five key modules: Tenant and Lease Management – maintaining tenant records, digital lease agreements, and automated lease renewal reminders. Property Management – managing property details, occupancy tracking, and document storage through a user-friendly, mobile-enabled interface. Maintenance Management – enabling tenants to submit requests via a portal, generating work orders, and automating escalation of unresolved issues. Financial Management – tracking rent and payments, issuing overdue reminders, managing expenses, and providing dynamic financial reports. Reporting and Analytics – offering real-time insights into occupancy, revenue, and maintenance performance through customizable dashboards.
By centralizing data and automating critical processes, REMS enhances operational efficiency, reduces manual workloads, and improves organizational transparency. Property managers gain access to accurate, real-time insights for informed decision-making, while tenants benefit from streamlined communication and responsive services via the self-service portal.
The expected outcomes of this project include increased tenant satisfaction, improved financial oversight, and more efficient property operations. Additionally, the integration of automation and analytics ensures scalability and positions Future Properties to remain competitive in a rapidly evolving real estate market. This project represents a significant advancement toward digital transformation by providing a modern, efficient, and data-driven approach to property management
Predicting Global Healthcare Supply Chain Delays: A Machine Learning Approach Leveraging Country-level Logistics Metrics
Get PDFIn global healthcare logistics, ensuring the timely delivery of medical commodities is critical, particularly in low- and middle-income countries characterized by infrastructural limitations and operational uncertainties. This research introduces an advanced, data-driven predictive framework designed to forecast delivery delays by synthesizing granular, internal shipment-level data from the USAID Global Health Supply Chain Program (GHSC-PSM) with external country-level logistics capabilities indicators derived from the World Bank’s Logistics Performance Index (LPI). Rather than relying on retrospective trend analyses, this study employs machine learning algorithms such as Random Forest, XGBoost, Support Vector Machines (SVM), and Multi-Layer Perceptron (MLP) to detect shipment delays proactively. A distinctive methodological innovation lies in explicitly integrating country logistics capabilities such as customs efficiency, infrastructure quality, and timeliness with internal shipment metadata, enabling a more comprehensive and precise prediction of delays. Empirical validation demonstrates that this integrative approach significantly enhances predictive performance, revealing systemic inefficiencies and enabling targeted managerial interventions. Consequently, logistics managers can leverage these insights to strategically optimize healthcare logistics and supply chains. This study contributes to a rigorously validated and scalable predictive tool, facilitating a strategic shift from reactive to anticipatory logistics management within global health supply chains
THE EFFECTS OF BEING THE OLDEST DAUGHTER AND A CARETAKER
Get PDFIn many households, oldest daughters are a pivotal person as they have many responsibilities. One of the main responsibilities is caretaking their younger siblings. These young women are responsible for child rearing, nurturing, educating and guiding their younger siblings, essentially becoming a parental figure. While this is an issue in many households, it is not thoroughly discussed within the research field. The purpose of this study is to examine how oldest daughters are affected by becoming a caretaker for their younger siblings and how it results in these young girls having a negative impact in their well-being that results in emotional and behavioral instability. This proposed quantitative study is a questionnaire to evaluate the assumed responsibilities of the oldest daughter, the amount of time and effort placed into the role, and how it affected their mental well-being. This study is designed to inform social workers of the issue and its impact to better their understanding of the issue to support these women affected by their responsibilities as a caretaker
#TOOMUCHCONTENT: A QUANTITATIVE ANALYSIS ON SOCIAL MEDIA TIME USAGE AND ITS IMPACT ON YOUNG ADULT ANXIETY AND/OR DEPRESSION IN THE UNITED STATES
Get PDFAs technology continues to advance and grow, society has seen a surge in popularity of various social media sites. Social media has become increasingly popular among young adults, with some spending over 10 hours each day on social media. Social media can be utilized for community building, fostering relationships, providing safe spaces, inspiration, creative expression, and may even provide users with acceptance, validation, and a sense of belonging. Considering these factors, social media may also affect individuals negatively— specifically mental health-wise, in terms of anxiety and depression. This study aimed to identify whether a correlation exists between time spent on social media and anxiety and/or depression levels, as well as distinguish a correlation between type of user, passive user or active user, and anxiety and/or depression levels. Results showed no significant influence of both type of user and hours of use on participants’ anxiety and depression levels. Future studies may conduct a longitudinal qualitative study to achieve in-depth and causal results, as well as include the context of social media content, users’ life factors affecting mental health outside of the internet, and mental health history
Increasing Inclusive Practices in an Elementary School Using Transcendental Phenomenology
Get PDFThis transcendental phenomenology study examined two schools, one comprehensive elementary school and one segregated special education center, as they transitioned to become one school to create more inclusive spaces for students with extensive support needs (i.e., intellectual and developmental disabilities). The transition occurred over a three-year period. The study used purposive sampling. Three general education and three special education teachers and the principal completed individual interviews during Year 3 of the transition. Classroom observations were conducted. The study used thematic analysis and revealed themes that described the school restructuring process: uncertainty during restructuring process; uncertainty around access based on students’ abilities and activities; and perceptions of additive and subtractive lens during the restructuring process. Implications include providing sufficient support in teacher education programs, professional development and support for teachers, administrators, parents and students
PROACTIVE LEADERS’ DEVELOPMENT OF EMPLOYEE LEARNING GOAL ORIENTATION AND VOICE IN THE MITIGATION OF WORK-RELATED RUMINATION
Get PDFWork-related rumination aggravates stressors and demands at work. Past research has suggested that individuals with a learning goal orientation (LGO) cope better with ambiguity and challenges at work. Moreover, proactive leaders play an active role in influencing employees’ orientations and appraisals by modeling self-regulation through the encouragement of metacognition, employment of far-sighted goal-setting, and the utilization of participative behaviors like information-sharing that facilitates employees to take the initiative and adopt a more knowledge-seeking and developmental attitude towards their work. Using path modeling and confirmatory analysis, the study examined 1) whether the relationships between proactive leader behaviors and employee work-related rumination were mediated by employee learning goal orientation, 2) whether perceived voice climate moderated these relationships, and 3) whether proactive leader behaviors composed an overall construct of proactive leadership. Findings suggested that when leaders engaged in far-sighted goal-setting, a reduction in employee work-related rumination emerged through employee LGO. Support was found for a multidimensional structure of proactive leadership, where perceived voice climate determines the impact of proactive leader behaviors on employee LGO. This study helped understand the potential for proactive leaders to transform employees’ orientations toward work, enhancing their coping styles towards work and other domains and positively influencing employee well-being