Investment Evaluation Research Articles

Teachers' and Parents' Assessments of Primary School Children's Intellectual Investment as Predictors of Change in Need for Cognition.

The present study investigated whether parents' and teachers' evaluations of children's intellectual investment would predict a change in children's need for cognition (NFC) over one year. An exploratory look at how teachers' evaluations are predicted by a range of factors was also taken. N = 565 third-graders (298 girls; Mage = 8.40, SD = 0.59) and teachers (N = 39) were surveyed in 2021 and 2022. The parents (N = 452) provided the data in 2021. Longitudinal data were analyzed by means of latent change score models (LCSMs). Changes in the teachers' evaluations and in the children's cognitive engagement differed between the children. However, there was no effect of the parents' or teachers' assessments on the development of the children's NFC. The change in the teachers' assessment was negatively related to their initial judgment and the children's age; it was positively related to the pupils' fluid intelligence. The results and implications are discussed.

Incorporation of RFID Technology in the Inventory Management System to Optimize the Inventory Cost – ‘C’ Programming Approach

Objectives: To examine and justify the significance of Radio Frequency Identification technology in the inventory management system with scheduled shortages through a C programming approach. Methods: Radio Frequency Identification technology is examined in the inventory and analyzed between the two strategies namely i) non- Radio Frequency Identification technology and ii) Radio Frequency Identification investment in both ordering and Just In Time efficiency. The proposed methods were implemented and solved using C programming to evaluate their effectiveness and operational performance in managing inventory and reducing costs. Findings: An integrated investment evaluation model is established in this work and a comparative study has been made to analyze the assessment model with scheduled shortages in the absence and presence of Radio Frequency Identification technology by assigning the parameters using a numerical example performed by C programming. Results show that the total cost under non Radio Frequency Identification technology is 200547722.557505 whereas the total cost under Radio Frequency Identification technology investment is 100860759.476361. The number of orders placed each year under non Radio Frequency Identification technology and Radio Frequency Identification technology are 182 and 214 respectively. The results imply that the incorporation of Radio Frequency Identification technology in inventory management leads to improved efficiency and accuracy, resulting in increased profitability for an organization. Novelty: Radio Frequency Identification technology investment is incorporated into an inventory system to optimize inventory costs and annual order frequency using C programming, which remains unexplored in existing literature. 2020 Mathematics Subject Classification: 90B05. Keywords: Radio Frequency Identification technology, Investment evaluation, Inventory cost, Shortages, Economic Order Quantity

Evaluating the Well-Being Benefits and Social Value of Volunteer Gardening: Health Economics Meets Behavioral Science.

Multidisciplinary collaboration is key to strengthening the evidence base for multifaceted illness prevention interventions. We bring together health economics and behavioral science to explore the well-being benefits and social cost-benefit of volunteer gardening at an accredited botanic garden, Wales, UK. A health economics-informed social return on investment (SROI) evaluation was combined with the assessment of volunteers' basic psychological needs (autonomy, competence, and relatedness), connection to nature, and their interrelatedness in this innovative nature-based intervention study. Pre- and post-volunteering outcome data were collected using the Short Warwick-Edinburgh Mental Well-being Scale (SWEMWBS), the ICEpop CAPability measure for Adults (ICECAP-A), the 12-item diary version of the Basic Psychological Need Satisfaction and Frustration Scale (BPNSNF), the Nature Connection Index (NCI), and a bespoke Client Service Receipt Inventory (CSRI). Results indicate that volunteer gardening can provide well-being benefits to participants and cost savings to the NHS. The well-being benefits observed were estimated to generate social value in the range of GBP 4.02 to GBP 5.43 for every GBP 1 invested. This study contributes to the evidence base that simple nature-based interventions such as volunteer gardening could offer low-cost supportive environments that deliver significant well-being benefits and associated social value to local communities, including a reduced burden on overstretched local healthcare services.

Anticipatory evaluation

Starting with the Australian Evaluation Society 2024 Conference theme of ‘wayfinding’, the article reflects on how evaluators navigate time as well as space, with particular reference to how they incorporate qualitative approaches to ‘futures thinking’ into their evaluative practice. The article takes a reflexive case study approach, drawing on a simple model of evaluative practice to review the role of futures thinking in evaluation of doctoral research projects, impact investments, social assistance, and development studies as an academic field. The article focuses particularly on the role of ‘backcasting’, as well as deliberative processes and the causal mapping of narrative claims linking future possibilities to current thinking and activities.

Evaluating the social return on investment of dance movement for wellbeing in the prevention of burnout among healthcare staff: a study protocol.

Improvement in the National Health Service (NHS) employees' mental well-being and staff retention are current key issues. Evidence indicates that dance movement therapy (DMT) has been effective in improving mental health and well-being; however, a social return on investment (SROI) evaluation on DMT interventions aimed at NHS staff has not been performed. This protocol for an SROI study will explore the social value generated from DMT, specifically 'The Body Moving Self-Compassion' programme, as measured by the increase in personal well-being and resilience experienced by participants. The SROI evaluation aims to measure the monetary and social value generated through DMT by placing a monetary value which is essential for sound policy in accessing investment while contributing evidence of dance/movement's impact on health. SROI is a pragmatic form of social cost-benefit analysis which uses quantitative and qualitative methods to value relevant costs, outcomes and associated impact. A mixed-methods approach design (focus group, online questionnaire and semistructured interviews) will be employed in this SROI study. SROI takes a societal perspective and considers relevant and significant outcomes for participants. Monetary values which often do not have a market price are then assigned to these outcomes. Contingent valuation is integrated into this study to estimate individuals' choices, preferences and values associated with DMT. The social value generated by the identified outcomes will then be estimated in a similar way to cost-benefit analysis, and the ratio of social value generated per £1 invested is then calculated. Ethical approval for this study has been granted by the Faculty of Life Sciences and Education Ethics Subgroup at the University of South Wales, with Reference No. 230 236LR. The findings from this SROI study will result in a report and academic publications.

Exploring Key Drivers of Sales Revenues Forecasting: Empirical Evidence from the Aluminium Industry

In the fast-paced and fiercely competitive banking industry and increasing demand for high forecasting accuracy for effective lending decision making, mastering the art of sales revenue forecasting is crucial for banking professionals who are concerned with efficient credit assessment and investment evaluation. This study delves deep into the main independent variables that impact sales revenue forecasting, moving beyond the widely used historical sales lagging approach. Through a comprehensive qualitative analysis utilizing semi-structured in-depth interviews technique with industry experts whereby study model is developed and subsequently validated using Multiple Linear Regression (MLR) analysis. Spanning a period from 2013 to 2022, this empirical research leverages secondary data from sample of 12 selected companies who manufacture primary aluminiumfrom different economics, accordingly with related macro and micro economic figures on quarterly basis. The findings revealed that interviews claimed six independent variables have significant impact on sales revenues forecasting including (Historical Trading metal price at the metal exchange, company strategy) while only four variables were (quantities sold, historical market selling prices, and historical producer price index and historical foreign exchange rates) have significant impact on sales revenue forecasting, empowering banking credit and investment teams with the critical knowledge necessary to make informed lending and investment decisions

Investment Feasibility Analysis Using Discounted Cash Flow Valuation Method (Case Study: Gold Mine in Pit A PT XYZ)

Investment in the mining sector carries a high risk, so a comprehensive financial evaluation is required to ensure project feasibility. This study assesses the financial feasibility of gold mining investment in Pit A, PT XYZ, for the period 2025 to 2036. The purpose of this study is to evaluate the feasibility of the project through the analysis of key financial indicators such as Net Present Value (NPV), Internal Rate of Return (IRR), and Payback Period (PBP) using the Discounted Cash Flow (DCF) method. The DCF method was chosen due to its ability to project future cash flows and incorporate them into a comprehensive assessment of the potential benefits and risks of the project. In addition, sensitivity analysis was conducted to see the effect of changes in important variables such as revenue, cost of goods sold (COGS), and capital expenditure (capex) on the financial results of the project. The results show that the project is financially viable, with a positive NPV of US$404.16 million, an IRR of 52.10%, and a PBP of 3.32 years, all of which indicate a strong return on investment. Further sensitivity analysis shows that the project remains robust under various scenarios of changes in key variables. This study contributes to the investment evaluation literature in the mining sector by offering a more integrated approach to addressing investment uncertainty and risk through the combined use of the DCF method and sensitivity analysis.

The Importance of ESG in Financing and Investment Decisions

ESG has become one of the most important topics for investors around the world, and this article explores the importance of environmental, social and governance (ESG) factors in financing and investment decisions. This paper first introduces the concept of ESG from the perspective of investment and financing, and analyzes the impact of ESG on financing cost, investor demand and its application in debt financing. This paper further discusses the role of ESG factors in investment evaluation and the correlation between investment returns and ESG performance. Therefore, ESG is becoming more and more important in the process of investment and financing, and enterprises should pay more attention to and actively respond to the development and changes of ESG.

Internalizing External Accident Costs in Safety Investment Evaluation Using Cost–Benefit Analysis

The primary objectives of transportation system development in European countries include improving transport efficiency, enhancing national economic competitiveness, and promoting sustainable mobility. A key aspect of achieving these goals is the evaluation of transport externalities, particularly external accident costs, which is critical for ensuring the economic and social sustainability of road transport development. This study comprehensively evaluates external road accident costs and proposes an innovative approach to internalizing these costs through a cost–benefit analysis (CBA). By integrating these external costs into CBA, policymakers can better understand the societal impact of road safety investments, allowing for more informed decisions regarding measures to reduce road accidents and fatalities. This paper also explores the role of specific safety investments, such as installing vehicle restrain systems (VRS), buffers, and terminals on the national road network, as well as installing speed cameras, in reducing accidents and mitigating external costs. The findings highlight road safety measures’ importance in enhancing economic efficiency and social well-being, providing a solid foundation for the sustainable and efficient development of transportation systems.

Sustainability analysis of apple orchards: Integrating environmental and economic perspectives

The agricultural sector faces numerous challenges today, including the protection of biodiversity and the mitigation of environmental impact. Addressing these challenges require ensuring the stability of farmers' income, thus facilitating effective land management.The present study aims to evaluate the environmental and economic sustainability of apple orchards under two distinct systems (integrated versus organic) and a scab-resistant variety. The Life Cycle Assessment method (LCA) was employed to evaluate environmental impact, while financial and economic aspects were analysed using metrics such as Net Present Value (NPV), Equivalent Annual Value (EAV), Benefit-Cost Ratio (B/C) and Discounted Payback Period (DPP).Results analysis reveals that both inorganic fertilisation and pesticides usage have the greatest impacts in both integrated cultivation and scab-resistant orchards. In organic orchards, diesel usage emerges as a primary factor due to the substitution of chemical interventions with mechanical methods. For the same reason, labour constitutes 45 % of the organic production costs. Despite the lower environmental impact, organic treatments still contribute 22 % of the total production cost. Regarding the investment evaluation, the scab-resistant variety offers marginally lower costs than conventional varieties due to the reduction of required treatments; however, organic farming shows superior economic performance despite higher production costs, mainly attributed to higher market prices. This highlights the influence of market dynamics on business decisions in the apple sector, where farmers often have no direct control.

Forecasting Foreign Exchange Rate with Machine Learning Techniques Chinese Yuan to US Dollar Using XGboost and LSTM Model

Predicting exchange rates is important because it affects all major markets and plays a big part in the economy. The goal of this study is to forecast future values of the Chinese Yuan (CNY) to US dollar exchange rate. One of the most crucial aspects of the economy is the rate of exchange of currencies. The currency exchange rate is required in commercial terms, such as profit and investment evaluation. The purpose of CNY rate prediction is to determine the future value of the Chinese Yuan (CNY) relative to the US dollar, which can be taken into account while making decisions and lower the chance of losing money. As a result, we require a technique that can assist in accurately assisting in business selections regarding when to execute the appropriate deals. For this research study three-year dataset is used from 25 April 2020 to 26 May 2023. For this research we used two different machine learning models and comparison between the LSTM and Xgboost models first one is Long Short-Term Memory (LSTM) and second is Extreme Gradient Boosting (XGboost). The empirical results showed that the LSTM model provided better results than XGboost. Therefore, this study suggest that the LSTM model will helpful for the government monetary policymaker, economists and other stakeholders to identify and forecast the future trend of the exchange rate and make their policies accordingly.

Supporting strategy for investment evaluation of photovoltaic power generation engineering projects using multi-criteria decision analysis methods

This scientific study examines the evaluation of photovoltaic power generation projects through the application of multi-criteria decision analysis methods. Two groups of large-scale grid-connected PV power generation system projects with a nominal power of 50 MW and 500 MW respectively were analyzed and evaluated. These systems were designed to be installed in the same wider geographical area in northern Greece, but they were differentiated in the part of the PV circuit. Twelve systems were analyzed in which either monocrystalline silicon panels or poly-crystalline silicon panels or bifacial photovoltaic panels were to be installed. In these systems either central photovoltaic inverters or photovoltaic string inverters were considered for installation. The following criteria were used to evaluate the investment in these projects. These criteria were related to the profitability, the financial cost, the technical level, and the electrical energy production of the systems and these were the initial investment cost, the operation and maintenance cost, the levelized cost of electricity, the net present value, the internal rate of return, the capital recovery or payback period, the technical level of the photovoltaic circuit, the technical maturity of the photovoltaic circuit, and the annual electricity production. The evaluation of these criteria was initially conducted with fixed weighting coefficients followed by a sensitivity analysis of these weighting coefficients. The results of the evaluation using the PROMETHEE, AHP and TOPSIS multi-criteria decision analysis methods showed that the PV power generation systems which should be preferred are those with increased nominal power, where monocrystalline silicon technology panels are employed following the central inverter topology.

Holistic evaluation of energy transition technology investments using an integrated recommender system and artificial intelligence-based fuzzy decision-making approach

The most essential criteria should be determined in the selection of the suitable energy transition technologies due to budget deficit problem. Therefore, it is necessary to identify the most important criteria in energy transition technology selection. Therefore, a new study is needed to determine the most prominent issues in the correct selection of energy transition technologies. The purpose of this study is to identify the most appropriate energy transition technology alternative. Within this framework, a novel artificial intelligence (AI)-based fuzzy decision-making model has been presented. In the first part, the experts are prioritized by the help of AI methodology. In the next section, missing evaluations of energy transition technology investments are estimated via expert recommender system. Thirdly, the weights of the criteria for energy transition technology selection are computed by quantum picture fuzzy rough sets (QPFR) M-Stepwise Weight Assessment Ratio Analysis (SWARA). At the final stage, selected energy transition technology alternatives are ranked via QPFR-Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR). The main contribution of this study is the integration of AI technique to the proposed model. Similar to this issue, using M-SWARA methodology in the process of criteria weighting increases the quality of the findings. This methodology helps to consider the impact relation map of the criteria. The findings demonstrate that the most important factor is cost-effectiveness of energy transition. Similarly, it is also found that the local ecosystem is the second most significant issue. On the other side, the ranking results denote that compact renewable systems for small scale production is the most optimal solution of energy transition technology alternatives.

The Investment Evaluation Standards and Process of Venture Capital Industry in Taiwan: Taking T Venture Capital Company as an Example

Abstract The venture capital industry is characterized by high risk and high reward, demanding sharp market insight and strong assessment capabilities. This article examines the evaluation criteria used by T Venture Capital Company in selecting investment targets, offering a reference for the industry. The study utilizes a case study method, focusing on an experienced venture capital firm identified through the Taiwan Venture Capital Association's 2022 roster. Key findings from interviews and document analysis highlight five main criteria used by T Company: 1. Adjusting evaluation based on the investment stage and industry specifics. 2. Focusing on the entrepreneurial team’s background, skills, passion, and vision. 3. Prioritizing technological innovation and business model sustainability. 4. Ensuring a clear exit strategy with ongoing communication. 5. Conducting thorough due diligence for sound investment decisions. The study reveals that T Company relies on a mix of data, judgment, and flexibility in its decision-making process, adapting to each unique situation. Keywords: Venture Capital, Evaluation Criteria, Entrepreneurial Team, Technological Innovation, Due Diligence.

OPTIMIZATION OF MANAGEMENT DECISIONS IN TAX RELATIONS: NEW TECHNOLOGIES AND STANDARDS IN ACCOUNTING PROCESSES

The article addresses the critical role of accounting information in the context of tax relations, particularly in the dynamic business environment influenced by globalization. It emphasizes the necessity for structured data organization and information flow to enhance managerial decision-making processes. A significant focus is placed on the quality of accounting data, which is foundational for effective tax reporting and compliance. The study reviews existing literature, highlighting the contributions of Ukrainian researchers who stress the importance of relevant and high-quality accounting information for decision-making. The paper aims to explore the evolving approaches to accounting data formation, driven by globalization and the challenges it presents in tax interactions. It discusses the implications of adopting International Financial Reporting Standards (IFRS), which have been developed to ensure transparency, comparability, and high-quality financial reporting across borders. The article notes that while IFRS adoption is mandatory for many entities in Europe, discrepancies in implementation exist among member states, leading to varied disclosure requirements. Furthermore, the introduction of the Standard Audit File for Tax (SAF-T) is examined as a modern solution for enhancing data exchange between businesses and tax authorities. This XML format enables tax officials to access comprehensive accounting information, facilitating tax audits and compliance checks. The integration of SAF-T with IFRS reporting is posited to improve data quality and operational efficiency while addressing the increasing demand for reliable accounting information. In conclusion, the article argues that the implementation of IFRS and SAF-T can significantly enhance financial transparency and comparability, thereby reducing risks and costs associated with investment evaluations in the global market. However, it also acknowledges potential challenges in managing accounting practices and the need for advanced measures to accurately reflect a company's financial status and performance. This comprehensive analysis underscores the importance of high-quality accounting data in navigating the complexities of modern tax relations

ESG-Driven Investment Decisions in Photovoltaic Projects

As global climate change intensifies and environmental awareness increases, investing in renewable energy has become a primary economic and social development priority. Photovoltaic (PV) projects, as a clean and sustainable energy technology, have garnered significant attention due to their notable environmental and economic benefits. However, traditional investment evaluation methods such as net present value (NPV) analysis fail to adequately capture the flexibility and future uncertainties inherent in PV project investments. This paper presents a case study analysis proposing a delay option model that incorporates environmental, social, and governance (ESG) factors, providing a more scientific and flexible investment decision framework for PV projects. The case study results indicate that considering ESG factors significantly enhances the investment value of PV projects. This model not only provides comprehensive support for PV project investment decisions but also underscores the importance of establishing stringent carbon trading markets and policy incentive mechanisms to promote the widespread adoption and sustainable development of renewable energy projects.

Impact of the carbon market on investment benefits of power-grid enterprises in China: A system dynamics analysis

The power grid, as the hub connecting the power supply and consumption sides, plays an important role in achieving carbon neutrality in China. In emerging carbon markets, assessing the investment benefits of power-grid enterprises is essential. Thus, studying the impact of the carbon market on the investment and operation of power- grid enterprises is key to ensuring their efficient operation. Notably, few studies have examined the interaction between the carbon and electricity markets using system dynamics models, highlighting a research gap in this area. This study investigates the impact of the carbon market on the investment of power-grid enterprises using a novel evaluation system based on a system dynamics model that considers carbon-emissions from an established carbon-emission accounting model. First, an index system for benefit evaluation was constructed from six aspects: financing ability, economic benefit, reliability, social responsibility, user satisfaction, and carbon-emissions. A system dynamics model was then developed to reflect the causal feedback relationship between the impact of the carbon market on the investment and operation of power-grid enterprises. The simulation results of a provincial power-grid enterprise analyze comprehensive investment evaluation benefits over a 10-year period and the impact of carbon emissions on the investment and operation of power-grid enterprises. This study provides guidelines for the benign development of power-grid enterprises within the context of the carbon market.

Optimization and Demonstration of PV Power Plant Investment Evaluation and Decision Model under the Background of Marketization

Based on the real option analysis method, this paper makes an empirical analysis of the evaluation and optimization of the model, and analyzes the main factors of the investment value of photovoltaic power plants in combination with the investment decision-making characteristics of photovoltaic power plant projects under the background of marketization. The electricity price and generation income, transaction price and income are all processed by geometric Brownian motion, and the random process is obtained by Monte Carlo simulation method. Based on the sensitivity analysis of the uncertain factors of the model, the investment risk of photovoltaic power station is evaluated and the suggestions are put forward. The results show that when the on-grid electricity price increases by 10%, the net present value is about 6 million yuan in the 26th year. Therefore, how to evaluate the uncertainty factors of photovoltaic power plant investment and make scientific and reasonable investment decisions is of great significance for the development of photovoltaic power generation.

Information System for Evaluation of Investments in the Field of Information Technologies

Creating an information system for evaluating investments in the field of information technology is a relevant task as it influences the efficiency of resource utilization in this strategically important sector. Information technologies are rapidly evolving, and proper investment evaluation can contribute to maximizing profitability and reducing risks. The research highlights various approaches to addressing this issue, each defined by its own characteristics. The study analyzes the investment process, proposing a mathematical model for investment problems in the form of a multi-criteria optimization task with Boolean variables. A structural approach is used to depict the principles of the system’s operation and information flows. Development tools are selected, and a prototype of the software is implemented. Further research directions include system verification and the development of additional modules to enhance functionality.

Economic and Energy Efficiency Analysis of the Biogas Plant Digestate Management Methods

The aim of this study was to conduct a comprehensive economic and energy efficiency analysis of selected digestate management methods, considering their implications on operational costs and resource management. To achieve this aim, the study focuses on a comparative assessment of different digestate management methods, including land application, mechanical separation, the composting process and pellet production. The economic analysis involves the evaluation of the initial investment, operational expenses, and potential revenue streams associated with each method. The most economical and popular solution of digestate management is direct use as fertilizer, with total costs of 1.98 EUR·Mg−1. All of the other methods involve higher digestate management costs, respectively; for separation it is 2.42 EUR·Mg−1, for composting it is 2.81 EUR·Mg−1. The process that is the most energy-intensive, but profitable, is the production of pellets from digestate, resulting in profits of 334,926 EUR·year−1. It should be noted that the other analyzed methods of digestate management also bring many environmental benefits, affecting sustainability and reducing emissions. The results of this research will contribute unique data on the feasibility of managing the digestate and its fractions. The calculations of economic and energy values for different strategies will allow for the optimization of the overall performance of the biogas plant, thus promoting a circular economy.