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This study is carried out to demonstrate the computational practicalities of environmental construction economics necessary to offer early-stage cost advice. A case study of a private sector client’s development proposal is used. This is for the acquisition of a vacant freehold land of 1.2 acres brownfield site to develop a Grade A office complex with plans to achieve the BREEAM Excellent rating green building certification.

A three-stage methodology was deployed: Order of cost estimating, before life cycle costing and then development appraisal. The Order of Cost Estimate is generated using the BCIS online database, following the procedural guideline of the New Rules Measurement (NRM). The life cycle costing was carried out from an environmental perspective to explore two design options – Design A and Design B, in terms of which would offer the best value for money whilst reducing carbon emissions.

Based on the outcome of the life cycle costing computations, Design B was chosen as the advised development due to minimal differences in net present values and annual equivalents. Further evaluation of Design B, using the residual method of developmental appraisal was carried out, with all necessary assumptions made. From the extensive computations carried out, the project is considered unviable, as it reports a loss. Alternative use of the site or an alternative site is thus recommended to check if a greater return on investment is tenable.

The study narratively interweaves the application of three computational techniques that are core to offering early-stage cost advice.

I seek to identify whether cash flow management can affect the performance and risk of the Greek listed companies.

This study examines the relationship of cash flow management with performance and risk, using a sample of 80 non-financial companies listed in the Athens Exchange. The study covers the period 2018–2022, and panel data analysis is applied. Both financial performance and stock return are taken into consideration, while risk concerns the volatility of the companies’ share prices. The various explanatory variables used include the net cash flow, free cash flow, cash conversion cycle days, cash flow from operating activities, cash flow from investing activities, cash flow from financing activities, inventory days, customer days and supplier days.

The empirical results provide evidence of a positive relationship between financial performance and net cash flow and free cash flow. In addition, operating cash flow is positively related to financial performance. The opposite is the case for investing and financing cash flow. Finally, some evidence of a negative relationship between financial performance and inventory and customer days is provided too. On the other hand, stock return and risk are not related to the cash flow management variables at all.

To the best of my knowledge, this is one of the few studies to examine the relationship of cash flow management with performance and risk, using data from the Greek stock market. The results can form an effective selection tool for investors seeking Greek companies with the highest financial performance potential, which may reward them with higher dividends.

This study evaluates the economic effectiveness of higher education in Lithuania by measuring returns to investment in higher education for both individual university graduates and the state, particularly aiming to discover how higher education investments impact economic returns at both micro (individual) and macro (national) levels.

A dual methodological approach has been applied, utilizing both the Mincer earnings equation and the full discounting method, to draw a clear distinction between the returns enjoyed by individuals and those accrued to the country. Calculations for individual economic returns are done using the most recent available Lithuanian Department of Statistics data on the wage structure, while national return on education was based on the State Tax Inspectorate and Lithuanian Public Finance databases.

The research confirms that Lithuanian investments in education positively influence both individual earnings and society at large, mainly due to the low cost of education and the high returns. For individuals, net present value varies from €126,000 to €224,000, and the internal rate of return is from 7% to 46%, with the highest return being for males working in companies of 50–249 employees and holding a bachelor’s degree. It is also noteworthy that one additional year spent in education increases earnings on average by 4.1%. The financing of first cycle studies costs the state two times less than second and third cycle studies. For this reason, the net present value (NPV) and internal rate of return (IRR) of first cycle studies are higher than those of second and third cycle studies.

While higher education is generally and globally seen as a way to ensure financial stability and career advancement at the individual level and socioeconomic development at the national one, the question of cost versus benefits at both levels is principal and diachronic. Our research quantifies the NPV and IRR of education investments and highlights the differential economic returns of various education levels, where policymakers can utilize these insights to inform strategic decisions regarding education funding and resource allocation. This study, therefore, provides explicit quantitative answers and presents individuals and policymakers with tangible results and practicable direction in their decision-making. The findings are applicable to the specific country-focus, but also constitute an applicable case study in the international context, particularly for European and other countries of comparable economic structure and developmental stage.

The primary aim of this study is to provide actionable guidance for augmenting profitability in photovoltaic power plant investments within Iran’s solar energy sector. By emphasizing prudent capital management and strategic investment decisions, our research seeks to assist emerging businesses in attaining sustained success in this domain.

This study presents a comprehensive approach to refined decision-making in Iran’s solar energy sector. Our methodology integrates the best-worst method, ArcGIS software for site selection, and the TOPSIS method for decision-making, aiming to enhance precision and reliability.

Our research has identified ten promising regions suitable for photovoltaic power plant installations in Iran. Leveraging the TOPSIS method, we have made optimal selections among these alternatives. Furthermore, our exhaustive cost analysis, incorporating factors like land prices, system maintenance, revenue estimation, and various financial scenarios, has yielded insights into project cost-effectiveness.

By filling a notable gap in the literature regarding optimal site selection and investment strategies for photovoltaic power plants in Iran, our research contributes to the sustainable development of solar energy infrastructure. Through a thorough literature review and the development of a novel methodology, we offer valuable guidance for businesses and investors seeking success in Iran’s solar energy sector. Our study represents a significant advancement by introducing a novel methodology that integrates the best-worst method, ArcGIS software, and the TOPSIS method for site selection and investment analysis. These findings furnish valuable guidance for businesses seeking success in the solar energy sector, thereby contributing to the sustainable development of renewable energy infrastructure in Iran and beyond.

The aim of this Education Briefing is to comment on the problematic issues that sometimes arise when using the internal rate of return (IRR) and/or the net present value (NPV) as a measure of expected investment performance. The briefing looks at the sometimes conflicting signposts that each benchmark presents and highlights ways that decision-makers can overcome or mitigate the effects of those problematic issues.

After a short review of the IRR and NPV techniques, this Education Briefing provides numerous examples of problematic issues that arise with certain cash flow profiles and suggests how to address them.

Both the IRR and NPV provide simple benchmarks that can mislead the decision-maker who is not familiar with the nuances of both techniques.

This review should heighten the reader’s ability to spot characteristics of proposed investments that may signal that a quick decision based on performance metrics may lead to disappointing results. These characteristics include: scale effects, unusual cash flow patterns and/or investments with dissimilar expected lives. Mutually exclusive investments merit special attention.

This is a review of existing performance measurement models.

To propose a new investment-income valuation model by real options approach (ROA) for old community renewal (OCR) projects, which could help the government attract private capital's participation.

The new model is proposed by identifying the types of options private capital has in the OCR project, selecting the option model most suitable for private capital investment decisions, improving the valuation model through the triangular fuzzy numbers to take into account the uncertainty and flexibility, and demonstrating the feasibility of the calculation model through an actual OCR project case.

The new model can valuate OCR projects more accurately based on considering uncertainty and flexibility, compared with conventional methods that often underestimate the value of OCR projects.

The investment-income of OCR projects shall be re-valuated from the lens of real options, which could help reveal more real benefits beyond the capital growth of OCR projects, enable the government to attract private capital's investment in OCR, and alleviate government fiscal pressure.

The proposed OCR-oriented investment-income valuation model systematically analyzes the applicability of real option value (ROV) to OCR projects, innovatively integrates the ROV and the net present value (NPV) as expanded net present value (ENPV), and accurately evaluate real benefits in comparison with existing models. Furthermore, the newly proposed model holds the potential to be transferred to various social welfare projects as a tool to attract private capital's participation.

This study aims to develop a framework for the optimal selection of construction project portfolios for a construction holding company. The objective is to minimize risks, align the portfolio with the organization’s strategic objectives and maximize portfolio returns and net present value (NPV).

The study develops a multi-objective genetic algorithm approach to optimize the portfolio selection process. The construction company’s portfolio is categorized into four main classes: water projects, building projects, road projects and healthcare projects. A mathematical model is developed, and a genetic algorithm is implemented using MATLAB software. Data from a construction holding company in Iraq, including budget and candidate projects, are used as a case study.

The case study results show that out of the 34 candidate projects, 13 have been recommended for execution. These selected projects span different portfolio classes, such as water, building, road and healthcare projects. The total budget required for executing the selected projects is $64.55m, within the organization’s budget limit. The convergence diagram of the genetic algorithm indicates that the best solutions were achieved around generation 20 and further improved from generation 60 onwards.

The study introduces a specialized framework for project portfolio management in the construction industry, focusing on risk management and strategic alignment. It uses a multi-objective genetic algorithm and risk analysis to minimize risks, increase returns and improve portfolio performance. The case study validates its practical applicability.

This study contributes to project portfolio management by developing a framework specifically tailored for construction holding companies. Integrating a multi-objective genetic algorithm allows for a comprehensive optimization process, taking into account various objectives, including portfolio returns, NPV, risk reduction and strategic alignment. The case study application provides practical insights and validates the effectiveness of the proposed framework in a real-world setting.

The purpose of this study is to examine the application of sustainable building design and operation within a university setting to determine its economic efficacy and potential for further university investment.

This study incorporated a life cycle cost analysis (LCCA), simple payback period and discounted payback period calculations to determine the return on investment, including a sensitivity analysis when comparing the energy use and financial benefits of the sustainable design of a multi-use facility at Toronto Metropolitan University with buildings of similar size and use-type.

It was found that there is a positive business argument for Canadian Universities to consider the use of sustainable design to reduce energy use and greenhouse gas (GHG) emissions. A reasonable payback period and net present value within an institutional context were determined using a life-cycle cost assessment approach.

This study was limited to the measure of only a single location. Certain assumptions regarding energy pricing and interest rates and the related sensitivities were anchored on a single year of time, and the results of this study may be subject to change should those prices or rates become significantly different over time. Considerations for future research include a longitudinal approach combined with a more detailed analysis of the effect of use-type on the variables discussed.

For university administrators, the results of this study may encourage institutions such as universities to approach new building projects through the lens of energy efficiency and environmental sustainability.

GHG emissions are a well-proven contributor to global climate change, and buildings remain a significant source of GHG emissions in Canada due to their winter heating and summer cooling loads. As a result, sustainable building design on university campuses can mitigate this impact by optimizing and reducing energy consumption.

Research related to the economic evaluation of sustainable building design on university campuses is generally limited, and this study represents the first of its kind in regard to an LCCA of a sustainably designed building on a Canadian University campus.

The Public–Private Partnership (PPP) modality plays an important role in the procurement of global infrastructure projects. Regarding PPP's complex transaction structure, pricing of a PPP project is critical to both parties where the government pursues a high value for money (VFM) and the investor strives to maximize its financial gains. Despite the straightforward win–win principle, a formidable compromise is often the case to end up with a fairly acceptable price, subject to many determinants such as the risk profile, expected return, technological innovation and capacities of both parties. Among them, this study chooses to examine the “managing flexibility” (MF) capacity of investors in pricing of a PPP project, in light of the widely recognized importance of a real-option perspective toward the long term, complex and uncertain PPP arrangement. This study addresses two major questions: (1) how is MF in PPP projects to be valued and (2) how are PPP projects to be priced when considering a project's MF value.

A binomial tree model is used to evaluate the MF value in PPP projects. Based on the developed MF pricing model, net present value (NPV) and adjusted VFM value are then calculated. Finally, a multi-objective decision-making method (MODM) was adopted to determine the optimal level of returns based on invested capital (ROIC), return on operation maintenance (ROOM) and concession period.

The applicability and functionality of the proposed model is investigated using a real project case. For a given return, extended NPV and adjusted VFM value were calculated and analyzed using sensitivity analysis. Factor influence is shown by the model to be dependent on factor impact on cash flow. Subsequently, a multi-objective decision-making (MODM) model was adopted to determine the optimal level of returns, where the solution approximates the real-world bidding price. Results confirm that the pricing model provides a reliable and practical PPP proposal pricing tool.

This study proposes an integrated framework for valuing MF in PPP projects and thus more accurately determine optimal pricing of PPP projects than revealed in extant research. The model offers a practical tool to aid in the valuation of PPP projects.

The purpose of this paper is to analyse five biases in the valuation of financial investments using a mental time travel framework involving thought investments – with no objective time passing.

An investment’s initial value, together with any periodic funding cash-flows, are mentally projected forward (at an expected rate of return) to give the value at the investment horizon; and this projected value is mentally discounted back to the present. If there is a difference between the initial and present values, then this can imply a bias in valuation.

The study identifies (and gives examples of) five real-world valuation biases: biased funding cash-flow estimates (e.g., mega infrastructure projects); biased rate of return projections (e.g., market crises, tech stock carve-outs); biased discount rate estimates (e.g., dual-listed shares, dual-class shares, short-termism, time-risk misperception, and long-termism); time-duration misestimation or perception bias when projecting (e.g., time-contracted projections which lead to short-termism); and time-duration misestimation or perception bias when discounting (e.g., time-extended discounting which also leads to short-termism). More than one bias can be operating at the same time and we give an example of low levels of retirement savings being the result of the biased discounting of biased projections. Finally, we consider the effects of the different biases of different agents operating simultaneously.

The paper examines key systematic misestimation and psychological biases underlying financial investment valuation pricing anomalies.