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In the process of building the “Belt and Road” and “Bright Road” community of interests between China and Kazakhstan, this paper proposes the construction of an inland nuclear power plant in Kazakhstan. Considering the uncertainty of investment in nuclear power generation, the authors propose the MGT (Monte-Carlo and Gaussian Radial Basis with Tensor factorization) utility evaluation model to evaluate the risk of investment in nuclear power in Kazakhstan and provide a relevant reference for decision making on inland nuclear investment in Kazakhstan.

Based on real options portfolio combined with a weighted utility function, this study takes into account the uncertainties associated with nuclear power investments through a minimum variance Monte Carlo approach, proposes a noise-enhancing process combined with geometric Brownian motion in solving complex conditions, and incorporates a measure of investment flexibility and strategic value in the investment, and then uses a deep noise reduction encoder to learn the initial values for potential features of cost and investment effectiveness. A Gaussian radial basis function used to construct a weighted utility function for each uncertainty, generate a minimization of the objective function for the tensor decomposition, and then optimize the objective loss function for the tensor decomposition, find the corresponding weights, and perform noise reduction to generalize the nonlinear problem to evaluate the effectiveness of nuclear power investment. Finally, the two dimensions of cost and risk (estimation of investment value and measurement of investment risk) are applied and simulated through actual data in Kazakhstan.

The authors assess the core indicators of Kazakhstan's nuclear power plants throughout their construction and operating cycles, based on data relating to a cluster of nuclear power plants of 10 different technologies. The authors compared it with several popular methods for evaluating the benefits of nuclear power generation and conducted subsequent sensitivity analyses of key indicators. Experimental results on the dataset show that the MGT method outperforms the other four methods and that changes in nuclear investment returns are more sensitive to changes in costs while operating cash flows from nuclear power are certainly an effective way to drive investment reform in inland nuclear power generation in Kazakhstan at current levels of investment costs.

Future research could consider exploring other excellent methods to improve the accuracy of the investment prediction further using sparseness and noise interference. Also consider collecting some expert advice and providing more appropriate specific suggestions, which will facilitate the application in practice.

The Novel Coronavirus epidemic has plunged the global economy into a deep recession, the tension between China and the US has made the energy cooperation road unusually tortuous, Kazakhstan in Central Asia has natural geographical and resource advantages, so China–Kazakhstan energy cooperation as a new era of opportunity, providing a strong guarantee for China's political and economic stability. The basic idea of building large-scale nuclear power plants in Balkhash and Aktau is put forward, considering the development strategy of building Kazakhstan into a regional international energy base. This work will be a good inspiration for the investment of nuclear generation.

This study solves the problem of increasing noise by combining Monte Carlo simulation with geometric Brownian motion under complex conditions, adds the measure of investment flexibility and strategic value, constructs the utility function of noise reduction weight based on Gaussian radial basis function and extends the nonlinear problem to the evaluation of nuclear power investment benefit.

The study examines the IPO resilience grounded on the firm’s intrinsic factors.

We examine the association of IPO performance and post-listing firm’s performance with issuers' pre-listing financial and qualitative traits using panel data regression.

IPOs floated in the Indian market from July 2009 to March 31, 2022, evince the notable influence of issuers' pre-IPO fundamentals and legitimacy traits on IPO returns and post-listing earning power. Where the pandemic’s favorable impact is discerned on the post-listing year earning power of the issuer firms, the loss-making issuers appear to be adversely affected by the Covid disruption. Perhaps, the successful listing equipped the issuers with the financial flexibility to combat market challenges vis-à-vis failed issuers deprived of desired IPO proceeds.

High initial returns followed by a declining pattern substantiate the retail investors to be less informed vis-à-vis initial investors, valuers and underwriters, who exit post-listing after profit booking. Investing in the shares of the newly listed ventures post-listing in the secondary market can shield retail investors from the uncertainty losses of being uninformed. The IPO market needs stringent regulations ensuring the verification of the listing valuation, the firm’s credentials and the intent of utilizing IPO proceeds. Healthy development of the IPO market merits reconsidering the listing of ventures with weak fundamentals suspected to withstand the market challenges.

Given the tremendous rise in the new firm venturing into the primary market and the spike in IPOs countering the losses immediately post-opening, the study examines the loss-making and young firms IPOs separately, adding novelty to the study.

This paper aims to examine the performance efficiency of 56 real estate assets within the rental sector in the UAE to evaluate the relative operation efficiency in relation to revenue generation.

The data envelopment analysis (DEA) approach was used to measure the relative operational efficiency of the studied assets in relation to the revenue performance. This method could produce a more informed and balanced approach to performance measurement.

The outcomes show that scores of efficiencies ranging from 7% to 99% in some of the models. The results showed that on average buildings are 75% relatively less efficient in maintenance, in term of revenue generation, than the benchmark set. Likewise, on average, the inefficient buildings are 60% relatively less efficient in insurance. Result also shows that 95% of the building assets in the sample are by and large operating at decreasing returns to scale. This implies that managers need to considerably reduce the operational resources (input) to improve the levels of revenue.

This study recommends that the FM operational variables that were found to inefficiently contribute to the revenue should be re-examined to test the validity of the findings. This is necessary before generalising or interpolating the results that are presented in this study.

The information obtained about operational performance can help FM managers to understand which improvements in the productivity of inefficient FM resources are required, providing insight into how to reduce operating costs and increase revenue.

This paper adds value in using new FM operational parameters to evaluate the efficiency of the performance of built assets.

Egypt has set plans to transform into a green economy which requires major reforms in the waste sector as one of the most vital sectors crucial for this transformation. This study aims at inspecting the current status of the Egyptian waste sector to highlight the major policy reforms needed. Furthermore, it assesses the economic viability of establishing waste-to-energy (WtE) projects under the current regulations that govern the sector.

The study employed an inductive analytical approach to scrutinize the institutional and regulatory framework of the waste and WtE sectors. Furthermore, a novel techno-economic analysis was conducted to assess the profitability of a WtE plant that employs moving grate incineration technology.

The analysis of the waste sector revealed its deteriorating state and the dire need for immediate restructuring through more stringent regulations to establish an integrated waste management system (IWMS) that incorporates WtE technologies as well as a number of corrective actions that would help enhance the sector. Additionally, the techno-economic analysis revealed the need to amend the current WtE regulation to comprise a gate fee as an indispensable revenue stream for WtE projects.

This study is one of a few studies that uses a new technique of analysis to explore the potential role that WtE projects can play in Egypt as a part of an IWMS that aims at transforming the waste sector into a resource sector while providing a renewable and sustainable source of energy.

This study aims to provide insights into US and Australian analysts' views regarding the relative importance of disclosing the direct method (DM) or indirect method (IM) statement of cash flows and forecasting firm performance.

Evidence is collected from responses to 104 surveys and 52 interviews completed by US and Australian analysts from 2017 to 2022. The survey and interview questions are developed with reference to the literature.

US and Australian analysts believe that the DM format provides incremental benefits compared to the IM for (1) confirming the reliability of earnings; (2) improving earnings confidence; (3) more accurate ex ante forecasts of operating cash flow and earnings; and (4) identifying opportunistic accruals manipulation. Analysts view that DM disclosure can lower firm-level cost of equity, although US interviewees more uniformly expect lower costs of equity under DM disclosure when firms yield low earnings quality. DM disclosure is also more important during unstable economic periods, as proxied by COVID-19.

Limited research currently exists regarding disclosure of the DM or IM and its impact on analysts' forecasting accuracy, earnings quality, economic uncertainty and cost of equity. Previous research has relied on archival research to examine differences between the DM and IM methods and are limited by data availability. Our findings are particularly relevant to the US market with few US firms reporting the DM format.

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 aggressive competition in the real estate market forces real estate developers to tackle the challenge of selecting the best project construction phasing alternative. The real estate industry is characterized by high costs, high profit and high risks. The schedules of real estate projects are also characterized by having large number of repetitive activities that are executed over a long duration. The repetitiveness, long duration of execution, the high amounts of money involved and the high risk made it desirable to leverage the impact of changes in phasing plans on net present value of amounts incurred and received over the long execution and selling duration. This also changes the project progress, and delivery time as well as their respective impact on customer degree of satisfaction. This research addresses the problem of selecting the best phasing alternative for real estate development projects while maximizing customer satisfaction and project profit.

The research proposes a model that generates all construction phasing alternatives and performs decision-making to rank all possible phasing alternatives. The proposed model consists of five modules: (1) Phasing Sequencing module, (2) Customer Satisfaction module, (3) Cash-In calculation module, (4) Cost Estimation module and (5) Decision-making module. A case study was presented to demonstrate the practicality of the model.

The proposed model satisfies the real estate market's need for proper construction phasing plans evaluation and selection against the project's main success criteria, customer satisfaction and project profit. The proposed model generates all construction phasing alternatives and performs multi-criteria decision making to rank all possible phasing alternatives. It quantifies the score of the two previously mentioned criteria and ranks all solutions according to their overall score.

The research proposes a model that assist real estate market's need for proper construction phasing plans evaluation and selection against the project's main success criteria, customer satisfaction and project profit. The proposed model can be used to conclude general guidelines and common successful practices to be used by real estate developers when deciding the construction phasing plan. In this study the model is based on business models where all the project units are sold, rental cases are not considered. Also, the budget limitations that might exist when phasing is not considered in the model computations.

The model can be used as a complete platform that can hold all real estate project data, process revenues and cost information for estimating profit, plotting cash flow profiles, quantifying the degree of customer satisfaction attributable to each phasing alternative and providing recommendation showing the best one. The model can be used to conclude general guidelines and common successful practices to be used by real estate developers when tackling the challenge of selecting construction phasing plans.

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 study examines the influence of a firm's life cycle on the cash flow classification of Indian firms.

The study employs Dickinson's (2011) cash flow patterns to classify firm years under various life-cycle stages. Cash flow classification is employed to measure a firm's classification shifting (CS) practices. The study includes Indian firms listed on the Bombay Stock Exchange during 2012–2020, an ordinary least squares regression model, a fixed-effect model and a panel corrected with standard error regression method.

Firms face different opportunities and challenges at different stages of the firm's life cycle and therefore adopt cash flow CS. The results show that firms adopt cash flow CS during introduction, growth and decline stage of life cycle either to boost or to reduce operating cash flows.

This study is one of its kind to study the influence of a firm's life cycle on the cash flow classification of Indian firms.

This study aims to investigate the impact of corporate diversification and growth opportunities on the performance of real estate investment trusts (REIT) in Malaysia and Singapore before and during the pandemic.

The sample consists of 33 public-listed REITs across Singapore and Malaysia. A dynamic panel system generalized method of moments (DPS-GMM) estimation is used to account for unobservable factors and a relatively short sample period (2009–2022).

Results indicate that the impact of diversification is contingent on the market where the REIT is based and other institutional factors. The estimates also show that diversified REITs are better able to weather period of economic uncertainty.

We provided a definitive answer as to why corporate diversification leads to conflicting outcomes – market and institutional factors, strategic intent and the overall economic environment. We also show that the impact of typical firm controls (i.e. free cash, size) can differ. Future firm-level work should thus study similar phenomenon more contextually and carefully consider these varying effects.

The literature is divided on the impact of diversification on firm performance. By using a two-country sample, we show conclusive evidence that this contradictory outcome is due to market and institutional factors. We also show evidence that strategic intent is an important factor that influences the outcomes of diversification, regardless of market. We also infer that excess cash aids the resilience of the firm, contrary to the negative perception of excess cash during normal times. Firm size, in contrast, does not contribute to firm performance during a crisis.