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Artificial intelligence (AI) is an important source of competitive advantage as it enables task augmentation and automation. However, while AI can create significant value, it is important to note that AI investments are fraught with risks and uncertainties. Thus, managers are likely to carefully evaluate potential AI investments before committing to investing. However, we know little about how managers' appraisal of AI influences their investment choices. Drawing upon theorization in the areas of business value of AI, agentic information systems (IS) appraisal, and time-situated agency, we extend existing theory in two ways: (1) development of an AI classification (foundational typology) that proposes two dimensions (action autonomy and learning autonomy) for classifying AI by type and level of autonomy; and (2) development of propositions that leverage time-situated agency and the AI classification to explicate how managers' delegation preferences influence their AI investment appraisal. This paper contributes a foundational theoretical platform for furthering AI investment appraisal research. In addition, the paper sets an agenda for future research in this area. [ABSTRACT FROM AUTHOR]

Purpose – Due to the disruptive nature of digital transformation, firms can hardly ignore the further digitalisation of processes and business models. Implementing such initiatives triggers enormous investments in infrastructure and software, making the evaluation of digital investments crucial for a firm’s competitive situation. Design/methodology/approach – Given the dynamics and uncertainties inherent in digital transformation, a qualitative, inductive research approach based on semi-structured interviews with high-level finance executives has been employed. Findings – Our findings indicate widespread dissatisfaction with traditional investment appraisal methods for evaluating digital investments. Data also suggest that non-financial considerations are frequently taken into account, albeit implicitly, as participants struggled to clearly conceptualize these criteria. Originality/value – The literature indicates important research gaps regarding the applicability and usage of traditional, predominantly financial, investment appraisal methods in digital contexts. This research enhances our understanding of digital investment evaluation, by (i) developing an exploratory conceptual framework of potential qualitative evaluation criteria and (ii) providing an in-depth and detailed understanding of the barriers to implementing investment appraisal methods.

Investment appraisal of agricultural projects (APs) is particularly demanding due to several factors. Namely, APs may have longer time horizons, higher external and internal volatility, and uncertainty caused by less control of production and external conditions (e.g., climatic conditions and market demand). Indeed, these APs may face high and different risks that should be managed properly. Nevertheless, both the literature and practice do not address such complexity and uncertainty conveniently. Thus, this research aimed to develop an integrative and easy-to-use framework to support the investment appraisal of APs, which goes beyond the traditional approach based on simple and deterministic models. This framework is based on an approach that includes several capital budgeting techniques integrating extended multi-index methodology (EMIM), Monte Carlo simulation (MCS), and real options analysis (ROA). This framework allows dealing with different risk and uncertainty scenarios and managerial flexibilities, which allow alternative and additional investment options. A simpler and easier approach can be particularly important for family agribusinesses, which usually do not use sophisticated decision-making tools. An AP in an agrosilvopastoral system (i.e., agriculture, livestock, forestry) was used to present and discuss the proposed methodology considering the relevance of such systems for sustainable agriculture and their higher risk and complexity when compared to traditional approaches. The main contribution of the framework is structuring a set of steps based on several tools to carry out investment appraisal in APs. [ABSTRACT FROM AUTHOR]

Climate-smart agriculture (CSA) is a climate-resilient practice that stands out globally as an important practice through which we can deal with emerging challenges through adaptation and mitigation to increase crop productivity and resilience. Despite its significance, a comprehensive cost–benefit analysis of the adoption of these practices has not yet been carried out. This study aims to bridge the knowledge gap between the cost and effectiveness of CSA practices adopted by small-scale farmers in growing rice, wheat and maize, the most staple crops in the Gandaki River Basin of Nepal. In this study, net present value (NPV), internal rate of return (IRR), benefit–cost (BC) ratio, net benefit investment (NK) ratio and payback period, along with the value of externalities (social and environmental), were employed to assess the profitability of CSA practices. The findings indicate that almost all the CSA practices analyzed were profitable, with the exception of solar water management in maize with very low IRR (6%) and a longer payback period. The outcome of this study offers valuable insights for farmers in choosing profitable CSA technology and for policy makers in promoting better CSA technology, upscaling CSA practices, and formulating new agricultural policies and programs in the context of the changing climate. [ABSTRACT FROM AUTHOR]

This theoretical paper presents a real options valuation method (SCV) based on Wiśniewski's concept, double Monte Carlo simulation (2MC). In this methodology, option valuation involves determining the difference between the average value of a project with an option and the average value of a project without option and is calculated using financial simulation models characterizing these investments. Calculated values of project with option and without depends on the input parameters (deterministic or/and stochastic), that are already used by managers. The real options valuation methodology is presented using a numerical example of a flexible investment. The analysis demonstrates the usefulness of the SCV method, especially in the early stages of investment implementation, for complex and multi-stage projects, and in the presence of multiple sources of risk, that can be easily modeled using market data. An additional conclusion from the paper is the difference between the values ​​of real options, determined using the SCV method, and the value of decision flexibility (2MC method), as well as their economic significance and their application in practice. [ABSTRACT FROM AUTHOR]

Aiming at the deficiencies presented by the traditional methods of highway project investment evaluation, the proposed highway investment evaluation method was based on system dynamics. First, we constructed an evaluation index system from profitability, solvency, and risk resistance and clarified the positive and negative causality within the investment evaluation system of highway projects; second, we determined the boundaries of the system dynamics model and divided it into six sub-systems, namely, income, cash flow, investment evaluation, profit, cost, investment and financing, and liabilities; and then, we established the system dynamics model of highway investment evaluation based on the sub-systems. The model made up for the limitations of the traditional discounted cash flow method; finally, taking the China's Yunnan Province an Expressway project as an example, using VENSIM software simulation, we get the evaluation results of the system dynamics model and make a comparative analysis with the discounted cash flow method, which showed that the calculation inaccuracies of the NPV and other financial indicators were in a reasonable range, and the evaluation method had strong operability and practicability. The system dynamics investment evaluation model provided a systematic, intuitive, whole-process investment evaluation method, which provided a theoretical basis for the analysis and decision-making of the investment effect of highway projects. [ABSTRACT FROM AUTHOR]

Generally negative prevailing views of infrastructure delivery performance is sclerotic and in need of an evidence-based reappraisal. This study evaluated the project delivery performance of National Highways, the government company responsible for delivering England's road investment strategy which completed 138 road/highway major schemes over 16 years between 2001 and 2016.93% of major schemes had a benefit-cost ratio, BCR, of 1 or more which means most projects delivered more benefit than their cost. 69% have a high BCR of 2 or more, delivering benefits at least twice the cost of the project. Typical cost performance was a 2.4% overrun with 42% of projects delivered on or under budgeted cost. The overall value of cost overruns was compensated for by the value of underruns so the net cumulative balance was below zero. Cost performance improved over time, with a typical cost underrun of −6% observed in projects completed in the latter half of the studied time period. The improvement to delivery cost performance is most likely to be explained by changes in policy and practice, including: improved estimation of costs; Strengthened appraisal and approval; Developing procurement strategy; Improving programme management; Implementing lessons learned.

Affect is generally characterised as distinct from, and detrimental to, reason in investment appraisal. This paper, in contrast, illustrates that affect is integral to reasoning, particularly when uncertainty disturbs investment appraisal. Investment appraisals produce uncertain projections about the future, which generate discomfort. This causes actors to undertake adaptive activities to craft calculations they can become comfortable with, which we characterise as epistemic participation and shaping the politics of expectations. These activities constitute a dualistic fusion of comfort and reason: discomfort initiates and informs reasoning to regain comfort. We further show the effects of the laborious efforts accompanying this accretion of both knowledge and comfort. Our arguments are supported by an analysis of investment appraisal for a 30‐year capital project. [ABSTRACT FROM AUTHOR]

Which business idea or project would be successful? Is it worth investing in it and to what extent? What is the risk level and how can it be mitigated to achieve success? All these questions are relevant to both entrepreneurs and investors, especially when it comes to high-risk start-ups. The purpose of this paper is to present a methodology for intelligent effectiveness and risk assessment (IERA) of investments in high-risk start-ups, with a focus on space industries. Such an assessment is challenging for several reasons, including the lack of unified statistics on space industries, evaluation of benefits other than economic ones, long-term development challenges, etc. The developed IERA methodology integrates a combination of various known methods used in the space industries for both investment appraisal and risk assessment. The application of various AI-based tools for methodology criteria, weights, and scores contributes to obtaining realistic values and ensures the success of the analysis results, thereby benefiting the project itself. Thus, the applied IERA methodology can be implemented in real-time, based on a broad knowledge base, with high accuracy, and requiring significantly fewer financial resources. The main advantage of the developed methodology is the assurance it provides to both entrepreneurs and investors, offering them sufficient certainty and confidence. [ABSTRACT FROM AUTHOR]

This paper reviews the basic issues involved in identifying and providing solutions to transport problems. The paper argues that solutions focusing solely on investment in capacity or second-best solutions to pricing such as road pricing and free public transport ignore the essential economic relationships involved in transport. The paper provides a critique of investment and pricing and argues for a more integrated approach in which optimal pricing is a core consideration in any investment decisions. This is seen as particularly important in a post Covid-19 world where many of the fundamental drivers of transport demand have changed, and public authorities face significant constraints on budgets whilst new pressures such as commitments to net zero in the face of global warming threats add additional pressures. The paper offers some thoughts on the principles involved in establishing a more suitable structure for dealing with the transport problem. • Identifies the core elements of the transport problem as pricing and investment. • Reviews problems in implementing first-best pricing. • Critiques investment decisions in the light of wider economic impacts. • Considers changes brought about by the Covid-19 pandemic and the move to net-zero. • Offers a set of principles for reforming transport policy. [ABSTRACT FROM AUTHOR]

Knowledge of the value generated within higher education institutions is of great interest for various agents, particularly managers, as well as governments and society. University mission statements and their scope complicate any comparable measurement of the effects each university may have within a particular region. Perhaps the most adequate term for it and one that includes simple economic impact is value. This study is centered on the estimation of the short-term economic impact of the University of Granada (UGR). Using a method based on the input–output framework and multipliers, the total (direct, indirect, and induced) effects of UGR on production, income, and employment are quantified, differentiating between economic sectors. The total economic impact of UGR is 3.2 times the expenditure of the agents linked to the activities of the university, which implies that each Euro that the government invested was converted into 7.1 Euros. Its effect on total production surpassed two-thousand million Euros, with an income of one-thousand million Euros and over 25,000 equivalent jobs. Quantification of the impact is a measure of the importance of UGR within the province of Granada and the performance of public-sector investment in higher education. [ABSTRACT FROM AUTHOR]

Investing in information technology allows firms to enhance their capabilities and performance and in doing so grow and create value. Yet we still lack a detailed understanding about how this process occurs. In this paper we are able to trace out the pathway from identifying an opportunity to invest in ICT, through the decision to realise an investment or not, and if it does progress at what scale. Using a large bespoke UK business survey about investment decision-making, our initial results show that 72% of firms had an ICT investment opportunity but, of those who had an opportunity, only 70% took advantage of their opportunity. Of those that did the scale of investment was between £50,000 and £100,000 on average. ICT opportunities, investments, and scale of investment were increasing in firm size but negatively related to firm age. Investment scale rose as the ability to secure equity funding increased. In this respect, smaller firms may be at a relative disadvantage in terms of their ability to take advantage of ICT opportunities and this is problematic as they are also less likely to identify opportunities per se. [ABSTRACT FROM AUTHOR]

Quantifying uncertainty over technologies, costs, and prices that stem from site-specific conditions, technological particularities and future projections is an important element in the investment appraisal of desalination facilities. Yet, the majority of economic assessments in the field of desalination plants, so far, use deterministic estimation methods based on ‘best guess’ estimates and ceteris paribus sensitivity analyses. Aiming to fill this gap, this paper introduces a new approach towards comparing alternative technological options for desalination facilities under uncertainty based on the Levelized Cost of Water (LCOW). The proposed framework combines Monte Carlo simulations with scenario analysis and random-walk-based models to account for the cone of uncertainty of the LCOW. For purely illustrative purposes, five alternative combinations of desalination technologies and energy sources are examined in the State of Kuwait. The findings show that the proposed framework, although it cannot eliminate uncertainty, can assist decision-makers in managing it by framing the range of possible outcomes of the LCOW. In this way, it offers an insight into the accuracy of the estimates and allows the validation of the impact of risks and uncertainties against the acceptable tolerance level. Yet, several issues need to be addressed in future research.

In manufacturing systems, defective items are produced for machine drift and error. Usually, an imperfect production rate is random, and if the items are not reworked, these are considered trash and harm the environment. The proposed model aims to reduce waste by reworking defective products and maximizing profit. For profit maximization or overall cost minimization of the manufacturing system, setup cost has significant. A discrete investment for each phase is introduced with an inequality investment constraint for reducing the setup cost. Selling price-dependent demand is trained for more generalized applications for various industries. The proposed model is a multi-phase manufacturing system with optimum batch size, selling price, and investment with an irregular, imperfect production rate. Defects are detected at the first inspection, and the reworked items are checked if the reworked items are all non-defective in the second inspection. The model conducts a two-stage inspection. One is for detecting defective items, and another is for checking if all items are not defective after reworking. The model is solved with the Karush–Kuhn–Tucker (KKT) method, and the global maximum profit is obtained. The model shows that all investments should be assigned to maximize the profit and the optimal solution. Reducing setup cost with the investment is better than a constant setup cost. [ABSTRACT FROM AUTHOR]

Research background: An investment appraisal applies a single discount rate across all effects. However, this may be insufficient for heterogenous environmental impacts, mixing private and public goods as well as use and non-use values, where individuals may have multiple intertemporal preferences due to their duality to act as consumer or citizen.

Typically, the economic analysis of Renewable Energy Projects (REP) has been assessed considering Classical Methodologies of Investment Analysis (CMIA) in which only a few set of indicators are included, highlighting the Payback, Net Present Value and Internal Rate of Return. This excessive reliance on CMIA has been criticized because it neglects managerial flexibility, and it may end up leading to the project's undervaluation. This paper attempts firstly, to identify and describe the complementarity among economic evaluation methodologies for REP. Secondly, a novel framework is proposed for conducting the economic analysis to help decision-makers in identifying the most suitable methodology before proceeding with the investment. The findings of the study suggest that CMIA may be suitable for the cases of projects presenting low volatility. However, the analysis should be supplemented by a new set of indicators for projects with medium or high volatility. The Multi-Index Methodology (MIM), the Extended Multi-Index Methodology (EMIM) and the Real Options Analysis (ROA) are proposed to increase the investors’ perception towards both the project’s profitability and risk and to account for flexibility. The application of the proposed framework is demonstrated for the case of a Small Hydropower Plant (SHP) investment project. The outcomes of this paper also include the opportunities for decision-makers to flexibly respond to changes in the business and economic market using the proposed conceptual framework.

Developing countries have many cities which contain a historic district that include older buildings and streets as well as traditional activities and/or events. Such historic districts have survived and not changed to match the new developments. However, the continuing pressure of the population growth and the geographic expansion often represents a serious threat to these heritage assets which thought of as a block in the way of advance. This paper discusses the implementation of the heritage economics principles and its methodologies in the investment appraisal for the preservation of heritage assets in developing cities and countries, taking into consideration the characteristics of cultural heritage in such environment and discusses the options and anticipations that might face the planners of urban areas. The paper also summarizes the methodology used for the investment appraisal in the projects that aim at reusing the assets of material heritage. It also explains and gives information about the traditional status of developing countries; that's to clarify the implementation of post-investment assessment techniques on the projects concerned with the preservation of heritage assets in developing countries.

Background: As opportunities grow for resource-constrained countries to use eHealth (digital health) to strengthen health systems, a dilemma arises. Wise eHealth investments require adequate appraisal to address opportunity costs. Economic appraisal techniques conventionally utilised for this purpose require sufficient economic expertise and adequate data that are frequently in short supply in low- and middle-income countries. This paper aims to identify, and, if required, develop, a suitable framework for performing eHealth investment appraisals in settings of limited economic expertise and data., Methods: Four progressive steps were followed: (1) identify required framework attributes from published checklists; (2) select, review, and chart relevant frameworks using a scoping review; (3) analyse the frameworks using deductive and inductive iterations; and, if necessary, (4) develop a new framework using findings from the first three steps., Results: Twenty-four candidate investment appraisal attributes were identified and seven relevant frameworks were selected for review. Analysis of these frameworks led to the refinement of the candidate attributes to 23 final attributes, and each framework was compared against them. No individual framework adequately addressed sufficient attributes. A new framework was developed that addressed all 23 final attributes., Conclusions: A new evidence-based investment appraisal framework has been developed that provides a practical, business case focus for use in resource-constrained African settings.

The use of renewable energy sources, especially wind energy, has been widely developed, mostly during the last decade. The main objective of the present study is to conduct a literature review focused on the evaluation under uncertainty of wind energy investment using the real options approach to find out whether public opposition (NIMBY projects) has been contemplated, and if so, what have been the flexible strategies applied for its intervention. Overall, 97 publications were analyzed, identifying 20 different models or approaches, which were grouped into eight categories: 1. Real options, 2. Optimization, 3. Stochastics, 4. Financial evaluation, 5. Probabilistic, 6. Estimation, 7. Numerical prediction, and 8. Others. The real options approach, present in 32% of the studies, was the most popular. Twenty-eight types of uncertainties were identified, which were grouped, for better analysis, into nine categories. In total, 62.5% of the studies included the price of electricity as a source of uncertainty; 18.8%, the velocity of wind; and 15.6%, the feed-in rates-subsidy. Both random and non-random techniques were applied to assess the real options and to model the uncertainties. When evaluating real options, the Monte Carlo simulation technique was the most preferred, with 16 (51.6%) applications, followed by non-randomized techniques, decision tree, and dynamic programming, with eight (25.8%) applications each. There is a marked tendency to use stochastic processes to model uncertainty, particularly geometric Brownian motion, which was used in 61.3% (19) of the studies in the sample. When searching for "real options AND (nimby OR public opposition)", no study was found, which shows the possibility of developing research on this aspect to determine its impact on investments in wind energy projects. [ABSTRACT FROM AUTHOR]

Net present value (NPV) is a widely used technique in capital budgeting. In this paper, we develop a Bayesian NPV framework using a Gibbs sampler. This approach allows decision-makers to integrate their knowledge, past experience, and uncertain and volatile cash flows from carbon emissions credits into decisions dealing with energy efficient, sustainable manufacturing equipment. The results indicate NPV is highly dependent on the nature of volatility and uncertainty of the cash flows. Without inclusion of this information through the Bayesian framework results, NPV becomes overstated, and thus it may provide biased guidance for the investment. The results developed in this paper further show that the frequency of very high and low cash flows and to a lesser degree their variability adversely impacts NPV. The results may also explain reasons for the economic phenomenon known as the energy efficiency gap. [ABSTRACT FROM PUBLISHER]

In the automotive industry, a Body-in-White (BIW) refers to the first step, the basic structure, in the production of a vehicle. Once a BIW production line has been built, the (maximum) capacity is fixed and throughput is therefore limited by the equipment specified during the design phase. The main metric used to inform the production line design is the Net Ideal Cycle Time (NICT). Unfortunately the state of practice to estimate the NICT is a basic heuristic that does not account for production variation. In this paper we challenge the current estimation approach by proposing an alternative that assumes actual production to follow a Weibull distribution. The proposed model is derived and estimated from empirical data. The results suggest that BIW production lines have traditionally been designed with too low a capacity, resulting in planned throughput rarely being achieved. On the other hand, increasing the design capacity implies higher initial investment. In this paper it is demonstrated that the higher investment required is offset by reduced losses, resulting in more reliable planning and returns. [ABSTRACT FROM AUTHOR]

Investment alternatives selection involves a variety of criteria that should be evaluated to provide a solid basis for decision-making. Some prior research has proposed methodologies and frameworks to support such alternatives selection. However, many of them present intrinsic limitations related to their applicability and complexity. Thus, this paper presents a framework for decision-making concerning investment alternatives that are usually related to equipment selection for a manufacturing process, technology selection for product development, product portfolio selection, and production strategy selection, among others. The framework is based on a multi-criteria approach that considers three main criteria: (i) strategy, which considers company market competitiveness; (ii) quality, which considers client requirements; and (iii) economic aspects, considering the overall financial benefits of the investment. These criteria are evaluated with the support of well-known tools from traditional management engineering such as SWOT, QFD, NPV and Payback. The results obtained through the use of these tools are rated using the MAUT method. Two major contributions are offered by this framework: (i) the integration of three key criteria for decision-making that enables to obtain a balanced analysis of the investment alternatives and (ii) the intrinsic easy-to-implement characteristic of the framework – based on the use of traditional tools. The proposed framework was applied in a tailor-made furniture company to support a make-or-buy decision, and the obtained results are discussed. [ABSTRACT FROM PUBLISHER]

To reduce the Sulphur emission from shipping and ensure clean shipping, a number of Sulphur Emission Control Areas (SECA) were enforced in special areas around the globe. From 2015, in SECA, ship owners are not allowed to use fuel with more than 0.1% Sulphur content. One of the major concerns for the SECA regulation is that maritime stakeholders have had to take into consideration the costs as well as the tolerable risks of their compliance investment options. Besides that, low freight rates have increased the competition and had caused financial pressure on ship owners so that lower capital reserves and low credibility levels limit the manoeuvring space for investment activities.

• We describe crowding on-board and at stations based on automated transit data. • Travelers consider the influence of crowding on comfort and on walking speeds. • AA Dutch rail corridor with a rich set of passenger data is studied. • Pedestrian flows, densities and train car loads are well reproduced. • Applications include transit planning, crowding estimation, or disruption management. We present a transit model that, based on automated fare collection and train tracking data, describes pedestrian movements in train stations and vehicle-specific train ridership distributions. Our approach differs from existing models in that we describe on-board passenger dynamics and pedestrian dynamics at stations in a joint framework. We assume that travelers first decide on the train(s) they will take, and then pursue their journey through the network by successively choosing pedestrian paths, waiting positions on platforms, and specific train cars. Travelers explicitly maximize their travel utility. We model how crowding influences their walking speeds, and how it affects travel utility both at stations and on-board. To illustrate the framework, we present a real case study of a major Dutch rail corridor, for which we collect a rich set of passenger, pedestrian and train operation data. We observe a good agreement of model estimates with empirical observations, and discuss the use of the model for various transit-related problems including level-of-service assessment, crowding estimation, transit optimization, and integrated investment appraisal. [ABSTRACT FROM AUTHOR]

Purpose: The Stress-Prevention@Work implementation strategy has been demonstrated to be successful in reducing stress in employees. Now, we assess the economic return-on-investment to see if it would make for a favourable business case for employers. Methods: Data were collected from 303 health-care workers assigned to either a waitlisted control condition (142 employees in 15 teams) or to Stress-Prevention@Work (161 employees in 15 teams). Main outcome was productivity losses measured using the Trimbos and iMTA Cost questionnaire in Psychiatry. Measurements were taken at baseline, 6, and 12 months post-baseline. Results: The per-employee costs of the strategy were €50. Net monetary benefits were the benefits (i.e., improved productivity) minus the costs (i.e., intervention costs) and were the main outcome of this investment appraisal. Per-employee net benefits amounted to €2981 on average, which was an almost 60-fold payout of the initial investment of €50. There was a 96.7% likelihood for the modest investment of €50 to be offset by cost savings within 1 year. Moreover, a net benefit of at least €1000 still has a likelihood of 88.2%. Conclusions: In general, there was a high likelihood that Stress-Prevention@Work offers an appealing business case from the perspective of employers, but the employer should factor in the additional per-employee costs of the stress-reducing interventions. Still, if these additional costs were as high as €2981, then costs and benefits would break even. This study was registered in the Netherlands National Trial Register, trial code: NTR5527. [ABSTRACT FROM AUTHOR]

The use of renewable energy sources, especially wind energy, has been widely developed, mostly during the last decade. The main objective of the present study is to conduct a literature review focused on the evaluation under uncertainty of wind energy investment using the real options approach to find out whether public opposition (NIMBY projects) has been contemplated, and if so, what have been the flexible strategies applied for its intervention. Overall, 97 publications were analyzed, identifying 20 different models or approaches, which were grouped into eight categories: 1. Real options, 2. Optimization, 3. Stochastics, 4. Financial evaluation, 5. Probabilistic, 6. Estimation, 7. Numerical prediction, and 8. Others. The real options approach, present in 32% of the studies, was the most popular. Twenty-eight types of uncertainties were identified, which were grouped, for better analysis, into nine categories. In total, 62.5% of the studies included the price of electricity as a source of uncertainty; 18.8%, the velocity of wind; and 15.6%, the feed-in rates-subsidy. Both random and non-random techniques were applied to assess the real options and to model the uncertainties. When evaluating real options, the Monte Carlo simulation technique was the most preferred, with 16 (51.6%) applications, followed by non-randomized techniques, decision tree, and dynamic programming, with eight (25.8%) applications each. There is a marked tendency to use stochastic processes to model uncertainty, particularly geometric Brownian motion, which was used in 61.3% (19) of the studies in the sample. When searching for “real options AND (nimby OR public opposition)”, no study was found, which shows the possibility of developing research on this aspect to determine its impact on investments in wind energy projects.

In the article the analysis of international data collection systems for analysis of investment projects. Examples of the international statistical, financial and audit organizations publish articles and data which are necessary in the analysis of investment at the level of a single project, and at the level of the country. Analyzes the volume of investments in EU countries and Russian Federation, as well as comparative analysis. In Russia the analysis of dynamics of investments in fixed capital by kinds of economic activities are considered sources of financing. According to the results of the analysis of the findings and practical recommendations for improving the efficiency of the organization's funds.