Investment Decision Model Research Articles

Research on Investment Decision of Substation Project Based on Life Cycle Cost

In this paper, the life cycle cost theory is applied to the study of investment decision-making of substation engineering, and the scientific, reasonable and objective comprehensive evaluation of substation engineering is realized. Based on the analysis of the calculation method of life cycle cost, a theory-based investment decision model for substation engineering is established. Finally, taking a substation project as an example, it proves that the model can effectively analyse the investment cost of different schemes, objectively reflects the economic differences between schemes, and provides a favorable judgment basis for investment decision-making of Power Grid Substation projects, which has a certain practical value.

An agent-based model for energy investment decisions in the residential sector

Energy-related investment decisions in the buildings sector are heterogeneous in that the outcome for each individual varies according to budget, values, and perception of a technology, even if an apparently identical decision task is faced. In particular, the rate of adoption of new energy-efficient technologies is often hard to model and underlines the need for an advanced approach to capture diversity in decision-making, and enable the inclusion of economic, comfort, environmental and social aspects. This paper presents an enhanced agent-based model that captures several characteristics of consumer behaviour that influence investment decisions. Multiple agents with different objectives, search strategies, and decision methods are implemented. A case study is presented which illustrates the benefits of the approach for the residential sector in the UK. The agent-based method shows diversity in investment decisions, without requiring the constraints on uptake needed in many models. This leads to a range of technologies in the market during a transition phase, continuous investment in low capital cost technologies, and eventually the emergence of a low carbon system based on new mass market technologies. The system that emerges is vastly different from one observed when economically rational investment is assumed and uptake constraints are applied.

Investment decision-making research of oil tanker considering the reduce of oil spill risk

An oil spill accident at sea contributes to an economic loss for oil tanker companies, and the uncertainty of shipping price has a serious impact on the oil tanker investment decision. In view of this, this study establishes an optimal investment decision model, considering the cost of oil spill under uncertain freight conditions with the expectation of investment income as the main optimization target. First, on the basis of the principle of demand and supply function curve, the relation equation of the fluctuating freight rate is established according to the traffic volume, and the size of the freight rate is obtained by considering any alterations of the transportation scale. Second, based on the tanker freight demand uncertainty, a model considering the additional maintenance costs of the oil spill as well as the optimal investment timing and scale is established. Finally, an empirical analysis is undertaken to know the optimal investment timing and scale of the tanker. The results show that on one hand, with the increase in freight uncertainty, the waiting value and scale to reduce the risk from uncertainty increase, and the additional maintenance costs for preventing oil spill will reduce the probability of oil spills and the requirement for investment timing and scale.

MNEs corporate social responsibility: an optimal investment decision model

Based on an assumption that corporate social responsibility (CSR) is an investment decision, we provide a theoretical model that suggests how multinational enterprises (MNEs) should optimally invest in CSR. Our model proposes the optimal timing (when) and level (how much) of CSR investment with an economic calculation of expected return and payoff uncertainty of CSR in local markets. We also specify various multi-level factors (i.e. individual, organisation, industry, and institution) that may affect the investment structure. Our model suggests that MNEs' CSR decisions can be understood as a strategic investment seeking the optimal economic outcomes depending on the expected return and payoff uncertainty in each foreign affiliate. This study contributes to the literature by integrating research streams that have been polarised over the issue of the necessity of CSR for MNEs, and by offering a more complete understanding of how MNEs should invest in CSR.

MNEs' corporate social responsibility: an optimal investment decision model

Based on an assumption that corporate social responsibility (CSR) is an investment decision, we provide a theoretical model that suggests how multinational enterprises (MNEs) should optimally invest in CSR. Our model proposes the optimal timing (when) and level (how much) of CSR investment with an economic calculation of expected return and payoff uncertainty of CSR in local markets. We also specify various multi-level factors (i.e. individual, organisation, industry, and institution) that may affect the investment structure. Our model suggests that MNEs' CSR decisions can be understood as a strategic investment seeking the optimal economic outcomes depending on the expected return and payoff uncertainty in each foreign affiliate. This study contributes to the literature by integrating research streams that have been polarised over the issue of the necessity of CSR for MNEs, and by offering a more complete understanding of how MNEs should invest in CSR.

Application of Instance-Based Entropy Fuzzy Support Vector Machine in Peer-To-Peer Lending Investment Decision

Loan status prediction is an effective tool for investment decisions in peer-to-peer (P2P) lending market. In P2P lending market, most borrowers fulfill the repayment plan; however, some of them fail to pay back their loans. Therefore, an imbalanced classification method can be utilized to discriminate such default borrowers. In this context, the aim of this paper is to propose an investment decision model in P2P lending market which consists of fully paid loans classified via the instance-based entropy fuzzy support vector machine (IEFSVM). IEFSVM is a modified version of the existing entropy fuzzy support vector machine (EFSVM) in terms of an instance-based scheme. IEFSVM can reflect the pattern of nearest neighbors entropy with respect to the change of its size instead of fixing it in unified neighborhood size. Therefore, IEFSVM allows the class change of nearest neighbors in the determination of fuzzy membership. Applying the model to the lending club dataset, we determine loans that are predicted to be fully paid. Then, we also provide a multiple regression model to generate an investment portfolio based on non-default loans that are predicted to yield high returns. Throughout the experiment, the empirical results reveal that IEFSVM outperforms not only EFSVM but also the six other state-of-the-art classifiers including the cost-sensitive adaptive boosting, cost-sensitive random forest, EasyEnsemble, random undersampling boosting, weighted extreme learning machine, and cost-sensitive extreme gradient boosting in terms of loan status classification. Also, the investment performance of the multiple regression model using IEFSVM is higher and more robust than that of two other benchmarks. In this regard, we conclude that the proposed investment model is a decent and practical approach to support decisions in the P2P lending market.

Towards improved port capacity investment decisions under uncertainty: a real options approach

ABSTRACTPort activity plays an important role in facilitating international trade. Sufficient capacity is indispensable for a port to attract flows to a region and retain them. The capacity decision is the result of a trade-off between investment and waiting costs. Traditional methods to value expansion projects do not deal adequately with managerial flexibility in the face of uncertainty from different sources in the complex port environment. In this paper, real options (RO) models are identified as an alternative method to making project valuations and investment decisions, as they attribute the correct value to managerial flexibility under uncertainty. In order to be able to build and use such RO models for port capacity investment decisions, the sources and implications of uncertainty in the port and the different RO model specifications need to be understood. To this end, both the literature about uncertainty in the port context and the literature about real options models are reviewed in order to provide researchers who want to build their own decision-making models, with the necessary knowledge of both fields. The review makes clear that the complex interactions in and competition between the logistics chains and their actors coming together in ports have significant impacts on port capacity. Uncertainty is also caused by uncertain international trade flows and changes in legislation following new technologies and environmental impacts. An analysis of the components of some general RO models shows how the options of flexible output, investment size and timing are valued by RO models in a setting with demand uncertainty. Moreover, the review presents researchers with insights in how to deal with cooperative and competitive interactions in the chain, time to build, cyclical markets and legislation changes. It also shows how to value the expansion and the phased investment options. The new insights resulting from this review are subsequently combined in a framework that serves as a guideline to build RO models for port capacity investments. Finally, an exemplifying application of the framework is used to build an actual port capacity investment decision model.

An Investment Decision Model of Distribution Network Planning Based on Correlation Mining of Reconstruction Measures and Loss Load Index

In recent years, how to build a reliable, high-efficient, high-tech and environmental-friendly distribution network infrastructure and service system, especially to accurately assess the reliability impact of various technical measures and establish optimal investment decision model for the future distribution network planning, has great theoretical and practical significance. However, the traditional analysis of investment decision model of distribution network is based on complex power flow calculation, which is not suitable for current construction of large and smart distribution network with multi-agent interaction under electrical market environment. Therefore, in this paper, based on the sample data, the correlation mining methods of the reconstruction measures and loss load index, such as neural network method, are applied to analyse the relationship between different types of reconstruction measures and loss load index. Based on the correlation mining methods, the relationship between the reconstruction measures and loss load index can be obtained and the value of loss load can be fast predicted. Through the comparison the relationship between reconstruction measures and loss load index, the optimal reconstruction measures can be chosen, and the data relationship based accurate investment decision model can be built. Experimental result shows the accuracy and effectiveness of the presented methodology.

Microloans, education and growth

AbstractThis paper constructs a two‐period overlapping generations model of human capital investment decisions where a microloan program designed to finance entrepreneurial activities is active. It is shown that, in the presence of human capital externalities, microloans that are small and have immediate repayment can be growth depressing, and welfare decreasing, through their effect on the opportunity cost of schooling. By increasing the opportunity cost of schooling, such microloans divert investment away from human capital: by failing to internalize the social returns to education, households’ individually optimal investment decisions in the face of microcredit availability act to depress the growth of the economy and result in suboptimal welfare outcomes. Conditions under which these negative effects can occur are identified and potential solutions are suggested.

A combined thermal power plant investment decision-making model based on intelligent fuzzy grey model and ito stochastic process and its application

Uncertainties are often involved in the investment decision making of the coal-fired power plant. They are often characterized by diversity and fuzziness. In order to minimize their adverse effects on the evaluation of investment, we proposed a novel combined thermal power plant investment decision-making model. This model takes the Net Present Value(NPV) as the objective function, and takes the predictions of revenue and cost as the center. With regard to revenue prediction, Self-adapting Intelligent Grey prediction Model (SIGM) combined with Interval Grey number Prediction Model based on the Triangular whitenization weight function(IGPM_T) model is employed to forecast the changing tendency of the on-grid price, which is the decisive factor for revenue of power plant. With respect to cost prediction, Ito stochastic process theory is utilized to simulate the variation tendency of the operating cost of power generation. In order to acquire the key drift and floating coefficients in the formula of Ito process, the combinatorial simulation experiment is conducted, and by visual comparison, rational coefficient combination is determined. Finally, the reliability and validity of the proposed combined model are verified through an example of a coal-fired power plant, and results show that the proposed model can provide satisfactory evaluation for thermal power plant investment.

영상콘텐츠 제작활성화를 위한 지방자치단체 투자결정 모형 연구 : 강원도 사례를 중심으로

문화콘텐츠는 미디어의 관점에서 보면 미디어를 구성하는 내용물이지만 경제적 관점에서 볼 땐 재화로서 기능한다. 일반적으로 재화의 경제적가치는 시장가치와 비시장가치로 구분되는데 시장가치의 경우 따로 언급할 필요가 없을 정도로 화폐등 물질로 교환할 수 있는 가치를 의미하는 반면 비시장가치는 실질적으로 물질적 교환의 행위가 객관적 가치에 따라 이루어질 수 없는 가치를 의미한다. 모든 재화가 시장가치와 비시장가치가 존재한다고 볼 수 있지만 특히 문화콘텐츠는 시장가치와 비시장가치의 비중이 균등하게 작용하는 대표적 재화라 할 수 있다.이 점에서 문화콘텐츠의 가치평가는 기존의 기술평가, 제품평가와 같은 맥락에서만 고려될 수 없고 문화콘텐츠의 가치 범위가 이윤과 더불어 그 용어를 사용하는 사용자들 저마다의 관점이 적용되는 특성으로 인해 이전의 가치평가와는 전혀 다른 방식의 접근을 요구한다.BR 지방자치단체에서 문화콘텐츠에 투자와 제작지원을 하는 가장 큰 이유는 역시 지역경제에 도움을 주기 위함이다. 이는 문화콘텐츠의 재화적 가치 보다는 공적가치에 무게가 실린 태도인데 재화적 가치를 획득한 콘텐츠가 인지도와 호감도를 상승시키는 점을 감안할 때 문화콘텐츠의 재화적 가치는 공적 가치에 매우 큰 긍정적 영향을 미친다고 하겠다. 이런 이유로 문화콘텐츠의 가치평가에서 재화적 가치측정이 공적 가치와도 밀접하다고 볼 수 있으며 기존의 문화콘텐츠 가치평가가 지방자치단체의 문화콘텐츠 투자결정에 도움이 된다는 것을 부정할 수 없다.BR 우려적 관점으로 출발한 본고는 지방자치단체의 영상콘텐츠 투자모형에 관해서 자료조사와 델파이조사, 전화조사, 대면조사 등을 통해서 다음과 같은 결론을 도출 할 수 있었다. 첫째, 지방자치단체의 영상콘텐츠 투자는 재화적 가치는 물론이고 공적 가치를 고려한 투자가 이우러져야 한다. 둘째, 기존의 콘텐츠 가치평가가 재화적 가치에 집중되었음에도 불구하고 재화적 가치가 공적가치에 긍정적 영향을 미치는 점을 감안할 때 지자체의 투자모형에도 적용할 필요가 있다는 것이다. 셋째, 기존의 가치평가 영역에서 고려되지 않았던 공적 가치영역도 투자평가에 포함시킴으로서 공공기관의 역할에 보다 충실할 수 있는 모형을 구축할 수 있었다. BR 본 연구는 몇가지 점에서 의의를 가질 수 있는 데 먼저 지방자치단체의 문화콘텐츠 투자결정에서 일종의 규범적 기준을 제시했다는 점이다. 그리고 이와 관련한 선행연구가 부재했던 점을 미루어볼 때 향후 이 분야의 연구에 있어서 선도적인 방향성을 제시했다는 점에서 일정부분 의미가 있다고 하겠다.

Perfectionist decision-making style and ethical investment willingness

PurposeThe purpose of this paper is to examine the ethical investment willingness decision-making process to understand how investors evaluate corporate social responsibility (CSR) actions.Design/methodology/approachData were collected through a survey of 298 individual investors and analyzed using structural equation modeling.FindingsResults reveal that perfectionist decision-making style is positively related to perceived moral intensity, substitutability of financial returns, and ethical investment willingness. In addition, perceived moral intensity and substitutability of financial returns are positively related to ethical investment willingness. Finally, perceived moral intensity is positively related to substitutability of financial returns, and a two-factor causal mediation model is supported.Research limitations/implicationsThe limitation of this study was that the pre-tests and sampling methods required all participants to have investing experience; however, procurement of trading information for each investor was impossible; thus, actual investment behaviors were undetermined. This study shed light on the mediating roles of perceived moral intensity and the substitutability of financial returns. Future studies can further investigate the factors influencing perceived moral intensity and the substitutability of financial returns.Practical implicationsFuture ethical investment education can focus on cultivate the ability to distinguish ethical investments and change ethical investment willingness into actual investment behavior.Originality/valueUnderstanding the relationship between these variables can help understand why ethical investment willingness varies among investors and how the traditional financial theory investment decision model should be revised as, internationally, more people have begun to observe CSR and sustainable development.

Research on investment decisions model of trans-regional transmission network based on the theory of NPV

The investment decision model of trans-regional transmission network in the context of Global Energy Internet was studied in this paper. The key factors affecting the trans-regional transmission network investment income: the income tax rate, the loan interest rate, the expected return on investment of the investment subject, the per capita GDP and so on were considered in the transmission network investment income model. First, according to the principle of system dynamics, the causality diagram of key factors was constructed. Then, the dynamic model of transmission investment decision was established. A case study of the power transmission network between China and Mongolia, through the simulation of the system dynamic model, the influence of the above key factors on the investment returns was analyzed, and the feasibility and effectiveness of the model was proved.

Study on optimized decision-making model of offshore wind power projects investment

China’s offshore wind energy is of great potential and plays an important role in promoting China’s energy structure adjustment. However, the current development of offshore wind power in China is inadequate, and is much less developed than that of onshore wind power. On the basis of considering all kinds of risks faced by offshore wind power development, an optimized model of offshore wind power investment decision is established in this paper by proposing the risk-benefit assessment method. To prove the practicability of this method in improving the selection of wind power projects, python programming is used to simulate the investment analysis of a large number of projects. Therefore, the paper is dedicated to provide decision-making support for the sound development of offshore wind power industry.

Study on generation investment decision-making considering multi-agent benefit for global energy internet

. This article has studies on the generation investment decision in the background of global energy interconnection. Generation investment decision model considering the multiagent benefit is proposed. Under the back-ground of global energy Interconnection, generation investors in different clean energy base not only compete with other investors, but also facing being chosen by the power of the central area, therefor, constructing generation investment decision model considering multiagent benefit can be close to meet the interests demands. Using game theory, the complete information game model is adopted to solve the strategies of different subjects in equilibrium state.

Getting ready for future carbon abatement under uncertainty – Key factors driving investment with policy implications

Carbon capture and storage (CCS) is considered a key technology option for abating CO2 emissions in carbon-intensive sectors, e.g. the power sector. However, high investment costs and risk hinder the diffusion of CCS. To avoid stranded assets or high future costs for retrofitting, new plants can be made carbon capture ready (CCR) to enable them to accommodate future CCS retrofitting at low additional costs. Current CCR investment decisions are closely related to future CCS retrofitting and CCS operation decisions in subsequent stages, all of which would be affected by uncertainties. We develop a three-stage CCR investment decision model under multiple uncertainties which allows for investment and especially operating flexibilities. Applying this model to China shows that CCS operating flexibility under the carbon-pricing scheme may actually lower the probability of investing in a CCR plant, and neglecting it may overestimate the propensity for investing in CCR. Moreover, learning effects, which reduce the costs of future CCS retrofitting, may be detrimental to CCR investment, indicating that the policy support for research on, development of, and deployment of CCS to reduce CCS costs should be coordinated with CCR investments. Although higher electricity prices can increase the value of an investment opportunity, it may restrain CCR investment. Finally, CCR investment does not appear to be economically viable under current conditions in China because of low carbon prices, high carbon price risks, high CCR investment costs and the high opportunity costs of CCS operation.

Altruistic preference for investment decisions in the logistics service supply chain

In order to obtain the feasible condition that both the logistics service integrator (LSI) and functional logistics service provider (FLSP) have altruistic preferences, this paper establishes four investment decision models with Stackelberg game. It is found that supply chain coordination can not be achieved when both the LSI and FLSP have altruistic preferences, then the ex-post payment contract and 'revenue sharing + franchise fee' contract are proposed to solve this problem. Some important conclusions are found. First, when both the LSI and FLSP have altruistic preferences, the utilities of LSI and FLSP are higher than the utilities when only the LSI or FLSP has an altruistic preference. Second, both contracts can increase the utilities of LSI and FLSP when the range of altruistic preference coefficients meets a specific constraint. Third, when the LSI's altruistic preference degree is equal to the FLSP's altruistic preference degree, the supply chain profit can reach the highest level. [Received 1 October 2017; Revised 3 October 2017; Accepted 15 April 2018]

Sufficient Statistics for Unobserved Heterogeneity in Structural Dynamic Logit Models

We study the identification and estimation of structural parameters in dynamic panel data logit models where decisions are forward-looking and the joint distribution of unobserved heterogeneity and observable state variables is nonparametric, i.e., fixed-effects model. We consider models with two endogenous state variables: the lagged decision variable, and the time duration in the last choice. This class of models includes as particular cases important economic applications such as models of market entry-exit, occupational choice, machine replacement, inventory and investment decisions, or dynamic demand of differentiated products. The identification of structural parameters requires a sufficient statistic that controls for unobserved heterogeneity not only in current utility but also in the continuation value of the forward-looking decision problem. We obtain the minimal sufficient statistic and prove identification of some structural parameters using a conditional likelihood approach. We apply this estimator to a machine replacement model.

Research on Investment Decision Model of Distribution Grid Project Based on Transformer District

Distribution grid is the main bridge connecting the power grid enterprises with the vast number of electrical power users. The investment decision making of the distribution grid is one of the important management issues of which the Grid Corporation often faces. In this paper, based on the actual data produced from electric business system, considering the data availability and the scientific evaluation parameters of the electric grid equipment, a distribution grid equipment evaluation system is set up, and the cluster analysis method is used to classify the transformer district and get the objective classification results. On the basis of this, the priority of equipment investment of transformer district in different classifications is given, which provides decision support for the equipment investment of the electric grid corporation.

Empirical Regularities of Nigeria’s Foreign Private Portfolio Investment Return and Volatility

ABSTRACT This paper examined the Empirical Regularities of Nigeria’s Foreign Private Portfolio Investment Return and Volatility. The study covered the periods between 1981 and 2014. An EGARCH model was specified. The analysis involves carrying out the tests for Financial Assets and Risk assumptions. The study revealed that Foreign Private Portfolio Investment Returns show Volatility clustering. Secondly, Foreign Private Portfolio Investment Return and Risk were found to have Thick tail. Variance Ratio Test [VRT] was used to test the weak form efficiency of the efficient market hypothesis and hence the non-predictability of financial markets. The Results showed that changes in one direction are more often followed by similar changes in either direction (volatility clustering). Given that Nigeria’s Foreign Private portfolio investment empirical imperatives is regular like that of the rest of the world, the paper thus recommends that investment decision models used by advanced analyst in developed countries can be applied to developing countries like Nigeria with little modification with respect to Foreign Private Portfolio Investment as their assets and risks display similar characteristics with assets and risks in developed countries.