15 research outputs found
Investor Perceptions of Macroeconomic Factors When Making Real Estate Investment Decisions in Colombo Municipal Council Area, Sri Lanka
No full textThis research examines the investor perceptions of macroeconomic factors when making real estate investment decisions in the Colombo Municipal Council Area, Sri Lanka. Using stratified sampling and quantitative analysis, the study found that the Gross Domestic Production growth rate and exchange rate positively influence investor perceptions, with 40% and 73% of investors considering these factors, respectively. Despite high inflation, 80% of investors consider real estate as a hedge against inflation. In contrast, Average Weighted Prime Lending Rate and Average Weighted Fixed Deposit Rate negatively affect investment demand, and it considered by 79% and 66% of investors, respectively. The Inflation Rate, Average Weighted Prime Lending Rate, and the Exchange Rate are the primary factors considered by the Real Estate Investors when making investment decisions. The COVID-19 pandemic and financial crisis impacted over 76.5% of investors significantly. Notably, 52% of investors expressed discomfort in investing in real estate under the current economic conditions
Park Aid Systems: Factors That Affect Consumer Purchase Decisions
No full textBackover crashes in the United States result in at least 300 fatalities and 17,000 injuries every year. Backover crashes occur when a non-occupant of a vehicle is struck by a vehicle moving in reverse. Children are particularly vulnerable. Of the 300 fatalities, at least 100 deaths are children under the age of five. Limited visibility is one factor behind these deaths. The deaths are especially tragic, since the availability of a simple park aid device can expand a driver’s field of vision during a reversal maneuver. Park aid devices include a rearview camera or a sensory system.
This project is undertaken to determine the factors which influence a consumer’s willingness to pay for a vehicle with an already installed park aid system. We determine that these factors include consumer demographics (income and age), vehicle attributes (including drive type, width, height, mileage, make), vehicle operating costs (annual expenditure on fuel, gas price), and locational variables (an urban/rural setting, town population). We set up a binary iii choice model to capture the impact of these variables. For the analysis, we rely on several datasets to build two regression models. The first model combines vehicle registration data from the Maine Bureau of Motor Vehicles with data from the 2010 US Census. The second regression model uses survey results from the 2009 National Household Travel Survey. The results show that older, more affluent consumers are more likely to purchase these vehicles. Additionally, park aid devices are usually found in luxury vehicle models or vehicles with a higher retail price. Furthermore, these devices are more likely to be included in family vehicles such as minivans, or larger vehicles such as vans and SUVs. Finally, a simple forecast shows that the number of vehicles with a park aid system will continue to grow. A Bass model and a Gompertz model are used for forecasting purposes.
The data used for this study has several limitations. We could only include vehicles with a pre-installed park aid device. We could not measure customers who chose an optional vehicle package solely based on the reason that they wanted the technology. Furthermore, we cannot include customers who chose to install an aftermarket park aid option. We believe that these factors will have a significant impact on our results. Once consumers who chose the optional package or the aftermarket installation are taken into account, it can greatly increase the stock of vehicles with a park aid device. An aftermarket device costs less than $100 and is more affordable
Investigation on non-revenue water and potential energy saving in Greater Colombo region
No full textThe main purpose of this study is to identify critical factors influencing high nonrevenue
water percentage which directly affects energy usage in greater Colombo region. It
also addresses finding methods to minimize the percentage of non-revenue water. This study
was carried out through a data analysis where the energy related data and quantities of
water production data were collected from Ambathale water Treatment Plant. The NRW data
was collected from relevant officers involved in distribution systems of National Water
Supply and Drainage Board.
This study only covers the greater Colombo region (Colombo city limits). All other
regions have issues related to non-revenue water in different levels. Therefore, generalization
of this specific sector results for other provinces may have limitations.
Analysis of Colombo city region statistics shows that the water supply entity in Sri
Lanka (National Water Supply and Drainage Board) is unable to reduce the Non Revenue
Water percentage in Colombo city region which results in higher energy loss in the water
supply system.
Necessary recommendations and suggestions are made for the implementation of
programs to reduce non-revenue water percentage for a significant figure in greater Colombo
region since this region has the highest NRW percentage in Sri Lanka. Improvement of
service level to consumers, optimization of operational efficiency, reduction of production
costs by reducing of specific energy consumption of water and institutional developments
are some of the factors that can be achieved.
Facilitating access to safe drinking water for people has great impact on socioeconomic
development in Sri Lanka. Therefore, results of this study may help to develop a
program to reduce non-revenue water percentage in greater Colombo region and thereby
reduction of electrical energy usage, while ensuring the safe drinking water for higher
percentage of the population living in greater Colombo region
AI-Driven Investment Property Recommendations Using Spatial Big Data, Price Trends, and Amenity Mapping
No full textIn the real estate domain, investment decisions rely heavily on spatial and economic context, yet most digital platforms still provide static listings with limited personalization or geographic intelligence. The primary objective of this paper is to introduce and validate a spatially enriched recommendation system for real estate investment that integrates Artificial Intelligence (AI), Geographic Information Systems GIS), and big data analytics. Evaluated on over 70,000 property listings, the system leverages historical property trends, spatial amenity density, and price deviation metrics to identify undervalued or highgrowth-potential properties across urban areas. It combines location-sensitive scoring models with price per square foot analysis and Z-score based outlier detection to recommend listings that deviate positively from local price norms while offering strong amenity access. By evaluating properties based on proximity to hospitals, schools, banks, parks, transit, and other infrastructure, the model delivers context-aware investment insights. Key findings show the proposed model achieves a 70% match accuracy with expert evaluations, significantly outperforming baseline models. The implications of this work include a new framework for data-driven decision-making that can improve market efficiency, particularly in fragmented real estate markets like those in South Asia.
 
Group sequential design for time-to-event outcome with non-proportional hazards using the concept of relative time utilizing two different Weibull distributions
No full textA group sequential design allows investigators to sequentially monitor efficacy and safety as part of interim testing in phase III trials. Literature is well developed in the case of continuous and binary outcomes, however, in case of trials with a time-to-event outcome, popular methods of sample size calculation often assume proportional hazards. In situations where the proportional hazards assumption is inappropriate as indicated by historical data, these popular methods are very restrictive. In this paper, a novel simulation-based group sequential design is proposed for a two-arm randomized phase III clinical trial with a survival endpoint for the non-proportional hazards scenario. By assuming that the survival times for each treatment arm follow two different Weibull distributions, the proposed method utilizes the concept of Relative Time to calculate the efficacy and safety boundaries at selected interim testing points. The test statistic used to generate these boundaries is asymptotically normal, allowing p-value calculation at each boundary. Many design features specific to time-to-event data can be incorporated with ease. Additionally, the proposed method allows the flexibility of having the accelerated failure time model and the proportional hazards model as constrained special cases. Real life applications are discussed demonstrating the practicality of the proposed method
Consumer Behaviour and Preferences in Apartment Purchasing Decisions: Case Study in Proposed Apartment Project in Malabe, Sri Lanka
No full textThe escalating demand for housing in suburban regions of Sri Lanka necessitates a comprehensive understanding of consumer preferences in apartment purchase decisions. This study investigates factors influencing apartment purchase intentions in Malabe, a rapidly emerging suburban growth center near Colombo. Previous research has focused primarily on high-end condominiums in Colombo, leaving a gap in understanding suburban preferences and end users’ priorities. The study aims to identify key factors affecting apartment purchase decisions among potential buyers and examine preferences regarding pricing, financing, amenities and sustainability features. A Quantitative research approach was employed, using purposive sampling to collect data through a structured questionnaire survey administered to 194 respondents interested in real estate transactions. Descriptive statistics were used to summarize responses and rank factor importance. Key findings reveal that price and proximity to work are the primary factors influencing apartment purchase decisions. Three-bedroom apartments dominate demand, especially in higher price ranges. External financing is the preferred funding method, but buyers tend to maintain conservative loan-to-price ratios. Eco-features are considered important, with most respondents willing to pay a premium for sustainable features, although cost sensitivity remains high. These insights provide valuable guidance for developers and policymakers in tailoring suburban apartment projects to meet market demands while addressing sustainability concerns.
 
Phosphate Solubilizing Bacteria and Fungi Isolated from Rubber (Hevea brasiliensis) Root Rhizosphere, Their Biofilm Formation and Phosphate Solubilizing Abilities
No full textThe ability of some soil microorganisms and their biofilm combinations to convert insolubleforms of phosphorus to an accessible form is an important trait associated with plant Pnutrition. The phosphorus solubilizing potential of bacteria and fungi isolated from Hevearhizosphere and their effective biofilm communities were evaluated using solid and liquidmedia under in vitro conditions. Phosphate solubilization ability of them were tested oncalcium phosphate media by analysing the soluble P content after incubation at 28±2°C. Outof the microbial isolates, 10 bacterial colonies and one fungal colony formed haloes (clearzones) around the isolate growing on solid media containing calcium phosphate as the solephosphate source. Spectrophotometric quantification of phosphorus solubilization in theliquid media showed that the ten bacterial isolates, and ten fungal isolates solubilizedinsoluble calcium phosphate in to the liquid media in the range of 200 – 450 and 200 – 300mg P L-1 respectively. Biofilm showed significantly higher P solubilization (853.3±25.17 mgP L-1) than their bacteria and fungi counterparts alone. Phosphate solubilization of bacteria,fungi and their biofilm could be attributed to the secretion of organic acids. A significant dropin the pH of the broth media (4.7 to 5.6) compared to the pH of the control treatment (6.8-7.0)was observed. pH change in the media could be due to secretion of organic acids bymicroorganisms and/or utilisation of compounds in the broth media. Although there was asignificant synergistic effect on P solubilization due to biofilm formation, pH in the liquidmedia of their mono cultures and biofilm were not significantly different. This observationwarrants further investigation
Determination of desirable properties of bacteria, fungi and their biofilm associated with rubber rhizosphere
No full textPain and Health-Related Quality of Life in Autosomal Dominant Polycystic Kidney Disease: Results from a National Patient-Powered Registry
No full textRationale & Objective: Autosomal dominant polycystic kidney disease (ADPKD) affects health-related quality of life (HRQoL) including pain, discomfort, fatigue, emotional distress, and impaired mobility. Stakeholders prioritized kidney cyst-related pain as an important core outcome domain in clinical trials, leading to the development of disease-specific assessment tools. Study Design: The ADPKD Registry is hosted online with multiple disease-specific patient-reported outcomes modules to characterize the patient experience in the United States. Setting & Participants: The ADPKD Registry allows consented participants access to a Core Questionnaire that includes demographics, comorbid conditions, current symptoms, and kidney function. Participants complete subsequent modules on a 3-month schedule, including 2 validated HRQoL tools, the ADPKD-Pain and Discomfort Scale (ADPKD-PDS), the ADPKD Impact Scale (ADPKD-IS) and a Healthcare Access and Utilization module. Exposures: Patient-reported latest estimated glomerular filtration rate or creatinine used to calculate stage of chronic kidney disease. Outcomes: Health-related quality of life, measured using validated ADPKD-specific tools; access to polycystic kidney disease-specific health care. Analytical Approach: For the 2 HRQoL tools, scores were calculated for physical, emotional, and fatigue domains; pain severity; and pain interference (based on the licensed user manuals). Associations to health care access were also assessed. Results: By July 2022, 1,086 individuals with ADPKD completed at least 1 of the HRQoL modules, and 319 completed 4 over a year. Participants were an average age of 53. In total, 71% were women, and 91% were White, with all chronic kidney disease (CKD) stages represented. In total, 2.5% reported being treated with dialysis, and 23% had a kidney transplant. CKD stage 4/5 participants reported the most dull kidney pain, whereas sharp kidney pain was evenly distributed across early CKD stages. Dull kidney pain had an impact on sleep regardless of CKD stage. There was a strong positive correlation between the ADPKD-PDS and ADPKD-IS. Patients with a neutral or positive HRQoL were less likely to have been denied access to imaging or other care. Limitations: Currently, all the information collected is patient reported without health record validation of clinical variables. Conclusions: Use of the HRQoL tools in the ADPKD Registry provided a broad cross-sectional assessment in the United States and provided granular information on the burden of pain across the CKD spectrum in ADPKD. The ADPKD Registry allowed assessment of ADPKD impact in a community that experiences decline in health and kidney function over decades. Plain-Language Summary: The Autosomal Dominant Polycystic Kidney Disease Registry is a longitudinal, patient-powered research tool created with the goal to better understand the impacts of ADPKD on affected individuals in the United States. Here, we analyze pain and other health-related quality of life outcomes in 1,086 individuals using validated tools and comment on the utility of these tools for future use in clinical trials and observational studies. We found that sharp pain, dull pain, fullness discomfort, and other related impacts affected individuals across the disease spectrum, although some participants reported more dull pain in later stages (CKD stages 4 and 5). Future analysis of these trends over time will be valuable in understanding how to assess and address the burden of pain in autosomal dominant polycystic kidney disease
Availability and leaching of nutrients after biofilm biofertilizer applications into a Red Yellow Podsolic soil
No full text
