Return On Investment Research Articles

Macroeconomic variables and initial public offerings in Sri Lanka: a principal component analysis approach

PurposeThis study aims to comprehensively examine the relationship between initial public offering (IPO) activities and macroeconomic factors in Sri Lanka.Design/methodology/approachThis study uses principal component analysis (PCA) and autoregressive distributed lag (ARDL) techniques to examine the relationship between IPO activities and macroeconomic factors. Ten macroeconomic variables are transformed into principal components (factors) using PCA. Then, ARDL is applied to investigate the long- and short-term relationships between IPO activities and the transformed macroeconomic factors.FindingsThe empirical investigation identifies three principal factors from the ten macroeconomic variables, of which two factors have a significant long-run association with IPO activities: “return on investment (RTOI)” and “economic and market development (ECMD).” In the short run, “trade openness and banking sector development (TOBD)” and RTOI are significantly associated with IPO activities.Research limitations/implicationsThe study was based on 30 years of observations, which passed all diagnostic tests but may be insufficient for generalizing the findings. Future studies could use high-frequency data (monthly or quarterly) to increase the number of observations and repeat the method and analysis. Also, while the symmetrical ARDL method was used in this study, an asymmetrical ARDL method may provide more insightful results and interpretations.Practical implicationsThe study highlights the importance of considering both long- and short-term associations when analyzing the impact of macroeconomic variables on IPO activities.Originality/valueThis study is the first to comprehensively examine the relationship between IPO activities and macroeconomic variables using PCA and the ARDL technique. The study provides insight into the macroeconomic factors that influence IPO activities in Sri Lanka and highlights the importance of considering long- and short-term associations.

The case for investment in nutritional interventions to prevent and reduce childhood and adolescent overweight and obesity in Peru: a modelling study

BackgroundBetween 2006 and 2016 the prevalence of overweight and obesity among children and adolescents aged 5–19 years in Peru increased from 22.7 to 27.0%. This investment case quantifies the economic impacts of childhood and adolescent overweight and obesity in Peru. It identifies and quantifies the potential impact of a set of new or expanded interventions that can strengthen current national efforts to prevent and reduce child and adolescent overweight and obesity.MethodsA deterministic Markov cohort model with a societal cost perspective estimated reductions in mortality and morbidity from implementing interventions to prevent and reduce child and adolescent overweight and obesity and the impact in savings in healthcare costs and gains in wages and productivity. Interventions identified through a review of published literature includes a school-based social marketing campaign, exclusive breastfeeding promotion and support, a healthy food and drink policy for school premises, and a 20% subsidy on fruits and vegetables for people living below the national poverty line. The return on investment (ROI) was calculated along with the estimated cost savings associated with the interventions. Analysis was conducted to test ROI sensitivity to changes in the key parameters and assumptions.ResultsBetween 2025 and 2092, the expected combined direct and indirect healthcare costs attributable to child and adolescent overweight and obesity in Peru are 210.6 billion USD. The direct healthcare costs are 1.8 billion USD, and the indirect costs are 208.8 billion USD. Expected savings for all interventions combined is 13.9 billion USD with a per-person savings of 12,089.8 USD. The expected ROI of the four interventions combined is 39.3 USD (30-years), 64.6 USD (50-years), and 164.1 USD (66-years) per one USD invested.ConclusionsThe overweight and obesity epidemic among children and adolescents in Peru requires wide-ranging and expanded implementation of policies to achieve long-term reductions in prevalence. This study’s findings show that the four priority interventions have high ROIs and can be used to guide policy to address the complex interplay of factors that contribute to the obesogenic environment.

Techno-Economic Analysis of Near-Infrared (NIR) Systems at Feed Millsas a Low-Cost, High-Speed Alternative to Feed Ingredient Testing

Improperly balanced diets not only impact the quality of animal production but also the profits of a livestock operation. Typically, the nutrient and chemical content of feed ingredients and forages are determined using well-established wet chemistry tests. However, these tests can be expensive and time-consuming. Moreover, the increasing use of various by-products which are known to have large variations in chemical and nutrient content warrants a real-time on-site feed and forage testing system. Near infrared (NIR) spectroscopy systems are quick and effective on-site testing tools. While NIR systems are being adopted for on-farm or at feed mill ingredient and forage testing, little is known about the economic impacts of such an investment for a livestock or feed mill operator. This study developed a baseline model and an Excel based spreadsheet application for performing Return on Investment (ROI) analysis to determine the feasibility of using an on-farm or at feed mill NIR testing system. ROI was calculated based on the nutrient cost saved or spent determined from the difference of estimated nutrient content and actual calculated value. The findings from this study will promote low-cost alternatives for onfarm or at feed mill ingredient testing, positively impacting quality of animal products and minimizing costs.

Cost effectiveness and return on investment analysis for surgical care in a conflict-affected region of Sudan.

The delivery of healthcare in conflict-affected regions places tremendous strains to health systems, and the economic value of surgical care in conflict settings remains poorly understood. Our aims were to evaluate the cost-effectiveness, societal economic benefits, and return on investment (ROI) for surgical care in a conflict-affected region in Sudan. We conducted a retrospective study of surgical care from January to December 2022 at the Mother of Mercy-Gidel Hospital (MMH) in the Nuba Mountains of Sudan, a semi-autonomous region characterized by chronic and cyclical conflict. We collected data on all patients undergoing surgical procedures (n = 3016), including age, condition, and procedure. We used the MMH budget and financial statements to measure direct medical and non-medical expenditures (costs) for care. We estimated the proportion of expenditures for surgical care through a survey of surgical vs non-surgical beds. The benefits of care were calculated as averted disability-adjusted life-years (DALYa) based on predicted outcomes for the most common 81% of procedures, and then extrapolated to the overall cohort. We calculated the average cost-effectiveness ratio (CER) of care. The societal economic benefits of surgical care were modeled using a human capital approach, and we performed a ROI analysis. Uncertainty was estimated using sensitivity analysis. We found that the CER for all surgical care was $72.54/DALYa. This CER is far less than the gross domestic product per capita in the comparator economy of South Sudan ($585), qualifying it as very cost-effective by World Health Organization standards. The total societal economic impact of surgical care was $9,124,686, yielding a greater than 14:1 ROI ratio. Sensitivity analysis confirmed confidence in all output models. Surgical care in this conflict-affected region of Sudan is very cost-effective, provides substantial societal economic benefits, and a high return on investment.

ANALYSIS OF FINANCIAL ECONOMIC INDICATORS FROM A SUSTAINABILITY PERSPECTIVE: STUDY WITH COMPANIES IN THE ENERGY SECTOR LISTED ON B3

Global demand for electricity is growing continuously. Therefore, the analysis of the companies involved becomes timely. This study investigates the impact of the disclosure of sustainability reports, with and without audit opinions, on the economic and financial performance of companies listed on B3 during the period from 2019 to 2023. Methodologically, the research has a descriptive approach, documentary procedure and quantitative nature. Its temporal dimension is longitudinal. The sample, composed of 77 companies selected probabilistically, was divided into: 47 companies that published reports with an audit opinion, 12 that published without an opinion, and 18 that did not publish reports. Through the Kruskal-Wallis test, the results indicated that the companies present similar performances in metrics such as current liquidity, dry liquidity, general liquidity, net margin and asset turnover. However, statistically significant differences were observed in the quick liquidity ratio, debt ratios (level and composition), as well as return on investment (ROI) and return on equity (ROE) indicators. This study contributes to the literature by providing insights into how sustainability reporting can influence various aspects of the financial management of electric power companies.

Economic impact case study of a wearable medical device for the diagnosis of obstructive sleep apnoea

BackgroundAcuPebble SA100 (‘AcuPebble’) is a novel wearable medical device to diagnose obstructive sleep apnoea (OSA). This paper investigates the potential economic impact of the technology in the UK through cost savings analysis, and the redirection of savings into further diagnoses.MethodsA cost comparison study was conducted, comparing AcuPebble to the standard diagnostic approach of home respiratory polygraphy (HRP) and in-clinic polysomnography (PSG), estimating the net benefit value (NBV) and return on investment (ROI). Cohort size was varied to model the effects of volume discounted pricing and staff training costs. To demonstrate the potential for cost savings, data on the healthcare costs of undiagnosed OSA patients were used to quantify the benefit of increased OSA diagnosis rates, as facilitated by AcuPebble.ResultsFor 500 uses of AcuPebble, the NBV in the diagnostic pathway over one year would be in excess of £101,169, increasing to £341,665 for 1,500 uses, £1,263,993 for 5,000 uses, and to £2,628,198 for 10,000 uses, with ROIs of 2.02, 3.03, 5.05, and 6.56, respectively. Given an initial cohort of 1,500 patients, 4,555 extra AcuPebble studies could be completed by redirecting resources from HRP/PSG. Direct cost savings to the NHS from resultant lower undiagnosed rates could be between £24,147 and £4,707,810, based on the cost per use and the percentage of tests that result in a positive diagnosis (varied from 25 to 75% positives).ConclusionsAcuPebble presents an opportunity for substantial healthcare savings, enabling an increase in the number of people tested, diagnosed and treated for OSA.

Design analysis of a sustainable techno-economic hybrid renewable energy system: Application of solar and wind in Sigulu Island, Uganda

Sustainable energy is central to achieving the global Sustainable Development Goals (SDGs), particularly in electrifying underserved communities. This study examines Sigulu Island, which lacks grid electricity and relies on costly, polluting diesel generators. On-site assessments revealed a daily load demand of 1,455.705 kWh. This study designed and analyzed a Sustainable Techno-economic Hybrid Renewable Energy System (STHRES) combining solar photovoltaics and wind turbines, with battery backup, to meet the island's energy needs. The research adopted both qualitative and quantitative methods, gathering atmospheric weather conditions specific to Sigulu Island. Solar panels and wind turbines were identified as the most viable options, with the system incorporating 677 units of 1 kW solar panels and 27 units of 1 kW wind turbines, generating 839.97 kW and 640.08 kW daily, respectively. Additionally, 527 Li-ion batteries were used to store approximately 1480.05 kW of surplus energy demand to manage fluctuations capable of sustaining the island for 8 hours during a total blackout. The initial installation costs are estimated at $90,393.04 for solar PV, $27,729.82 for wind turbines, $159,169.81 for batteries, and $92,407.00 for the inverter. The STHRES is projected to save $56,917.93 annually, covering 15.4 % of the installation costs compared to diesel operations. Moreover, this system will reduce Uganda's carbon footprint by 436,035.6 kgCO₂ annually, equivalent to a 0.01 % reduction in national emissions. The proposed system decreases the Net Present Cost (NPC) from $426,617.60 to $369,699.67 and the Cost of Energy (COE) from $32.12/kWh to $ 27.79/kWh. With a 9 % Internal Rate of Return (IRR) and a 3 % Return on Investment (ROI), STHRES has a payback period of 8.2 years, demonstrating its financial and environmental benefits for Sigulu Island.

A Study on Advertising Strategies of Yana Travels, Bengaluru

Advertising strategies referto the overall plan or approach that a business or organization usesto promote its products or services to a target audience. These strategies are designed to create awareness, generate interest, and ultimately persuade potential customers to take specific actions, such as making a purchase, signing up for a service, or engaging with a brand. Advertising strategies refer to the planned approach businesses use to promote their products or services to target audiences, aiming to achieve specific marketing objectives such as brand awareness, customer engagement, and sales growth. In this study, we delve into the advertising strategies adopted by travel companies, examining how these firms design and execute campaigns to stand out in a highly competitive industry. With the rise of digital platforms and evolving consumer preferences, travel companies are now leveraging diverse advertising channels, including social media, influencer partnerships, search engine optimization (SEO), and paid online ads, alongside traditional media such as television and print. This article explores how these strategies are crafted to resonate with various customer segments, addressmarket seasonality, and enhance brand visibility. The research also evaluates the impact of these advertising efforts on customer engagement, brand loyalty, and return on investment (ROI). By offering insights into successful marketing approaches, this study aims to guide travel companies in refining their advertising strategies to stay competitive in a rapidly changing marketplace.

Analysis and Interpretation of Physiological Social Demographic Parameter in Menopausal Women

A woman's menopause is normal period of her life. Some females have both emotional and physical symptoms throughout menopause. Depression is one of the many difficulties that some women experience after menopause. This project aims to enhance menopausal women's quality of life by predicting the onset of depression and tackling the lack of experts, knowledge, and awareness in this field. An interesting and difficult area of artificial intelligence study is the use of machine learning to forecast when postmenopausal women may have depressive symptoms. Through the use of supervised machine learning, this study develops a system that is remarkably accurate. Return on investment (ROI), area under the curve (AUC), recall, specificity, accuracy, F-Measure, and ROC are some of the metrics used by different classification methods to evaluate classifier performance. Random Forest and DT had the greatest accuracy rate of 99.04% among the classifiers we tested. In addition to predicting a patient's likelihood of having depression, this study analyzes the menopause according to its four stages: pre-, peri, meno-, and post-menopause. As a result, ML could be used to diagnose postmenopausal women with depression for the first time.

Research on Intelligent Advertising Precision Placement in the New Media Era

In the era of new media, advertising placement has undergone a revolutionary change from the traditional mass push to personalized intelligent advertisement precise placement. The intelligent advertising precision placement strategy, based on the 4I theory, has significant advantages in the new media era. By incorporating the principles of amusement and interactivity, immediacy strategy, and personalization strategy, brands can enhance user engagement, improve the communication effect of advertisements, and achieve higher conversion rates and return on investment (ROI). The findings of this study hold great importance for brands’ advertising strategies in the new media era.

Research on the Analysis and Optimization of Advertising Strategies on YouTube

The research presented in this paper investigates YouTube advertising and its problems and prospects with an emphasis on ad fatigue, ad-blocking tools, and targeting issues in digital advertising. The paper focuses on the aspects that might influence the effectiveness of YouTube ads based on the literature review and the case study of the YouTube channel Verdeliss. Some of the discoveries presented show that such factors as entertainment and informativeness are vital for capturing the audience’s attention, whereas ad irritation and targeting errors negatively impact the ads’ performance. Some of the strategies suggested are increasing the ad variety and relevance, refining targeting algorithms, and reducing the effects of ad blockers to enhance the return on investment (ROI) and user interaction. This study highlights the need to overcome these challenges to enhance digital advertising, especially on YouTube, so as to meet the users’ needs and firm goals. Based on these strategies, future research should endeavor to use empirical research to validate these strategies and other emerging methods of digital advertising in the dynamic online environment.

Case Study on Transforming Financial Decision-Making with Big Data and Advanced Analytics

This case study examines the transformative impact of big data, artificial intelligence (AI), and machine learning (ML) on financial decision-making. These technologies enable more informed, data-driven investment strategies and improved risk management by providing real-time insights and predictive analytics. While they enhance key performance metrics such as return on investment (ROI) and portfolio stability, challenges remain. Issues like data quality, skill gaps, and regulatory compliance hinder seamless integration. Addressing these challenges is essential to fully unlocking the potential of advanced analytics in the finance sector.

Effect of Management Information System on Growth of Agro-Firms in Anambra State

The study examined the effect of management information systems on the growth of agro-firms in Anambra State. The objectives were to: determine the effect of decision-making information systems on the Return on Investment (ROI) of agro-businesses in Anambra State, Nigeria, and ascertain the extent to which database management systems affect the ROI of agro-businesses in Anambra State, Nigeria. The study adopted a survey research design, with data generated from both primary and secondary sources. The data collection method was a questionnaire, which was randomly administered to staff of selected agro-firms. The population of the study was 6,727, while the sample size was 1,293, out of which 929 questionnaires were retrieved. The hypotheses were tested using the multiple regression analysis method at a 0.05% level of significance. The findings revealed that decision-making information systems had a significant effect on the ROI of agro-businesses in Anambra State, with a t-statistic of 7.743 and a probability value of 0.000. Additionally, database information systems had a significant effect on the ROI of agro-businesses in Anambra State, with a t-statistic of 2.476 and a probability value of 0.013. The study concluded that management information systems have a significant positive effect on agro-firms in Anambra State. It recommended that agricultural firms should invest in advanced decision support tools to aid data-driven decisions that maximize ROI. Furthermore, agro-business managers should focus on optimizing their database information systems to improve data organization and accessibility. Regular maintenance and updates of the database systems are crucial for ensuring accurate and timely information, which can positively impact ROI.

Implementing Loss Prevention by Identifying Trends and Insights to Help Policyholders Mitigate Risks and Reduce Claims

Loss prevention is a critical focus for both insurers and policyholders, as rising claim volumes lead to increased premiums and financial losses. This paper explores the implementation of loss prevention strategies through the identification of trends and insights derived from historical data, predictive analytics, and emerging technologies. By leveraging these insights, insurers can recommend proactive risk mitigation measures to policyholders, reducing the occurrence of claims and overall risks. The study begins by analyzing historical data trends across various sectors such as auto, property, and health insurance, identifying key factors that drive claims. Predictive analytics is then applied to forecast future risks, allowing insurers to develop personalized strategies for mitigating those risks. Emerging technologies like Internet of Things (IoT) devices and artificial intelligence (AI) are highlighted for their role in providing real-time data and early warning systems, which help to prevent incidents before they escalate into claims. This paper also outlines practical loss prevention strategies for policyholders, such as installing smart home devices to monitor potential hazards, encouraging safe driving habits through telematics, and promoting health and wellness programs to lower medical claims. These risk mitigation strategies are shown to provide significant return on investment (ROI) for policyholders by reducing claims frequency and severity. Through case studies and data analysis, the paper demonstrates that proactive loss prevention not only benefits policyholders by lowering their risk exposure but also helps insurers reduce claims costs and enhance profitability. In conclusion, this research highlights the importance of trend identification, predictive analytics, and emerging technologies in the future of loss prevention, offering a path forward for insurers and policyholders to work collaboratively in mitigating risks.

Maximizing the Impact and ROI of Leadership Development: A Theory- and Evidence-Informed Framework.

Globally, organizations invest an estimated USD 60 billion annually in leadership development; however, the workplace application of learning is typically low, and many programs underperform or fail, resulting in wasted time and money and potential harm. This article presents a novel theory- and evidence-informed framework to maximize the outcomes and return on investment (ROI) of leadership development programs. The foundation of the framework derives from four separate literature reviews: three systematic reviews on leadership development, including the only two to isolate gold-standard elements of effective design, delivery, and evaluation, and one on "training transfer". Informed by innovative principles of leadership development and unique theoretical models and frameworks, this framework consists of 65 evidence-informed strategies that can be applied as a foundation (9), and before (23), during (17), at the conclusion of (11), and sometime after (5), programs, to maximize impact and ROI. Implications for practice and further research are also presented. Given the stakes, there is an urgent need for evidence and tools to maximize the impact and ROI of leadership development. This novel framework provides robust theory- and evidence-informed guidance for governments, policymakers, and those funding, designing, delivering, and supporting development.

Developing Methods for Assessing the Impact of Digital Innovations on the Economic Efficiency of Enterprises: Methodology for Measuring ROI of Digital Projects

This study aims to develop methodologies for assessing the return on investment (ROI) of digital projects, crucial for understanding the economic impact of digital innovations on enterprises. Traditional ROI metrics often fail to capture the comprehensive value generated by digital projects. The proposed integrative framework employs advanced analytical methods, including cost-benefit analysis, real options analysis, and predictive analytics, to evaluate both tangible and intangible benefits. It incorporates dynamic risk management and scenario planning to address uncertainties and future challenges. Continuous feedback and iterative improvements ensure the framework's accuracy and relevance, enabling enterprises to optimize economic efficiency and strategic decision-making. This holistic approach offers an understanding of the multifaceted value of digital innovations.

Assessing the Impact of Digital Transformation on Business Operations: A Case Study Analysis

This study assesses the impact of digital transformation on business operations through a case study of Zivame, an Indian SME in the retail sector. The research aims to explore how digital technologies improve operational efficiency, customer engagement, and financial performance. Using qualitative research methods, semi-structured interviews were conducted with key decision-makers at Zivame. Thematic analysis was employed to analyze the data. The results indicate significant operational improvements, including a reduction in order fulfillment time and increased inventory turnover. Customer satisfaction and repeat purchase rates also improved substantially following the implementation of Customer Relationship Management (CRM) systems and other digital tools. Zivame faced challenges such as employee resistance to change and high initial investment costs, which were mitigated through targeted employee training programs. The financial analysis revealed a growing return on investment (ROI) from 31% in 2020 to 44% in 2023. The study’s findings underscore the importance of digital transformation for Indian SMEs, showing that, with strategic planning and investment, businesses can improve their competitiveness and achieve long-term success. These findings contribute to the broader literature on digital transformation in emerging markets and offer practical insights for SMEs embarking on similar journeys.

MODEL OF CHARACTERISTICS OF HIGH-PERFORMANCE ORGANIZATIONS INFLUENCING THE PERFORMANCE OF SMALL AND MEDIUM ENTERPRISES IN THE CENTRAL REGION OF THAILAND

Purpose: To develop a model that explores the characteristics of high-performance organizations and their impact on the performance of small and medium enterprises (SMEs) in the central region of Thailand. Theoretical framework: The performance of an organization involves two variables: 1.) Financial results, including metrics such as higher returns on assets (ROA), return on equity (ROE), leverage ratio, earnings growth, and return on investment (ROI) (The Stock Exchange of Thailand, 2022). 2.) Organizational leadership and governance results, emphasizing the pivotal role of senior leaders in organizational leadership and governance, financial accountability, legal compliance, ethical conduct, social responsibility, and community support was assessed using four aspects adopted from Kajornatthapol P. and Surachai U., (2011). Design/methodology/approach: The study analyzed international publications on blended learning in management and business, focusing on authors, journals, and cooperation between countries. It employed a quantitative approach, using a questionnaire to gather data from SME executives in Thailand's central region (3,283 cases). Sampling used nonprobability and purposive methods, with a sample size suitable for structural equation modeling (SEM). The questionnaire comprised four parts assessing organizational characteristics, performance, respondent information, and opinions. Financial results were evaluated on a 5-level scale. Content validity was ensured through expert evaluations, and reliability was confirmed via Cronbach's alpha (0.86) and item-total correlation (>0.30). Data were analyzed using descriptive statistics, confirmatory factor analysis, and various evaluation indices. The research aims to enhance understanding of high-performance SMEs in Thailand's central region. Findings: The research findings indicate a growing volume of studies on high-performance organizations in the context of SMEs in Thailand's central region, with a limited number of influential authors, institutions, and journals. The model developed successfully aligns with empirical data, revealing positive impacts of organizational leadership, strategic planning, customer focus, knowledge management, workforce focus, and operations focus on SME performance. These findings underscore the importance of promoting awareness of these factors within the Thai SME sector to foster more high-performance enterprises, aligning with Thailand's development goals. The research contributes valuable insights applicable not only locally but also globally, emphasizing the significance of sustainable practices aligned with Thailand 4.0 and collaborative efforts between government and private sectors for national sustainability. Research, Practical & Social implications: The research yields significant implications for research, practice, and society. It sets a foundation for future studies on high-performance organizations in SMEs, emphasizing leadership, strategic planning, and customer focus. Moreover, it enhances executive education by offering insights into organizational performance improvement. Practically, it guides SMEs in Thailand and beyond to optimize operations and achieve sustainable growth through the adoption of high-performance characteristics. Policymakers can leverage these findings to design initiatives supporting SME development, aligning with economic goals. Societally, the research underscores the importance of sustainability and responsible practices, advocating for knowledge management and strategic alignment with national plans. Collaboration between government, private sectors, and civil society is vital to promoting sustainable business practices and fostering inclusive growth. Originality/value: The research demonstrates a growing number of publications in the field of management and business, particularly in co-authorship with leading countries. It highlights the significance of the Model of Characteristics of High-Performance Organizations in understanding and enhancing SME performance in Thailand's central region, contributing to the existing body of knowledge.

Techno-economic Analysis Conversion of Empty and Partially Filled Paddy Grain Waste into Glucose through Bioconversion Route

Waste generated from Malaysia’s paddy milling factories, known as empty and partially filled paddy grain (EPFG), has been improperly managed as it can be further utilized for sustainable resources such as feedstock via biorefinery. However, the critical driver for a biorefinery is whether the proposed design is profitable. In this study, the conversion of EPFG into glucose as an alternative to sustainable management was analysed in terms of their economic performance as feedstock. The process design involved the production of non-concentrated glucose from EPFG using hydrothermal pre-treatment and enzymatic process, which led to the 76% conversion yield. The economic performance for the plant is at 1.04 million USD, 46.9%, and 34.3% for net present value (NPV), return on investment (ROI), and internal rate return (IRR), respectively. The minimum sugar selling price (MSSP), when zero NPV, is at 0.42 $/kg when the co-product revenue is considered. Sensitivity analysis results indicate that the MSSP is highly sensitive to plant size. This economic evaluation serves as an introductory guide to assess the economic performance of paddy milling waste to glucose via enzymatic hydrolysis. The results of the present study could provide insight for the Malaysian paddy industry in managing the EPFG, hence increasing their market potential.

Techno-economic of Residential Application for Grid-Connected Photovoltaic-Battery under Net Energy Metering

Nowadays, the demand for electrical energy is increasing due to the application of electrical equipment such as air conditioning, refrigerators, television, computers etc. Grid-connected photovoltaic is a network that allows for significant penetration of electricity by PV generation into the national utility grid under Net Energy Metering (NEM) incentive. Under NEM incentive, the owner can offset the energy for 10 years to reduce the electricity billing. Unfortunately, after that, the self-consumption (SELCO) program is implemented. Under SELCO program, the energy generated by PV will be consumed by the owner and there is no rebate for excess energy to the grid. This paper represents the techno-economic analysis of different rated power of PV design installed for residential applications. The 1.04kWp, 1.56kWp and 2.08kWp PV are designed to charge 5.544kWh battery and simulated by using PVsyst software. The payback period is calculated under Net Energy Metering (NEM) 3.0 incentive. As a result, 1.56kWp is the optimize sizing for grid-connected PV-battery with electricity billing saving at RM730.20 per year under one-on-one program and RM660.61 under SELCO program. Thus, return on investment (ROI) of this system design is 16.5 years.