An analytic network process based risk assessment model for PPP hydropower investments

The number of public-private partnership (PPP) projects has gone up especially in developing countries. The risk assessment of PPP projects is essential in ensuring project success. The objective of this study is to develop an Analytic Network Process (ANP) based risk assessment model for hydropower investments, and a tool to facilitate quantification of risk ratings based on this model. The results show that the three most important risk factors that affect the overall risk rating of a PPP hydropower investment are legal risks, contractor/subcontractor risks, and operator risks. In addition, the three most important risk clusters were identified as stakeholders, government requirements, and resources, whereas market was the least important cluster. The tool that measures the risk rating of a PPP of hydropower project was tested on ten real cases, and satisfactory results were obtained in terms of its predictive capability. The contributions of this research include (1) identification of the risk factors and clusters of factors associated with PPP hydropower investments; (2) determination of the priority of each risk factor and cluster; (3) development a tool that guides the investors through the risk assessment of PPP hydropower investments

Desired points at minimum cost in the “Optimize Energy Performance” credit of leed certification

This paper presents a method that guides designers in obtaining the desired number of earned points in the “Optimize Energy Performance” credit of the “Energy and Atmosphere” category of LEED version 4 (v4) certification at minimum cost. The model creates different scenarios, identifies the LEED points and  costs for each scenario. The energy analysis calculations are performed by Sefaira, the quantities of materials are received from Autodesk Revit, and the cost information comes from the RSMeans Database. A macro in Excel automates the process. An office building was used as a case study to illustrate the applicability of the proposed method. The minimum cost necessary to achieve any number of points in the “Optimize Energy Performance” credit were calculated, such as a minimum cost of $842,500 to obtain 16 points, and$476,684 for 5 points. The primary contributions of this research include (1) the development of a tool that allows designers to pick the most economical alternative for the desired points in the “Optimize Energy Performance” credit, and (2) the first time integrated use of an energy simulation software (Sefaira), a cost database (RSMeans), and a BIM software (Autodesk Revit)

Modeling information flow in the supply chain of structural steel components

 Accessing the required information in the supply chain of structural steel components is critical for minimiz­ing costly reworks and delays. This paper identifies the information items generated in the different phases of the supply chain related to structural steel components and formalizes the process of producing and using this information. Precise details about different features of the components (e.g., their geometry and weight, connection details, cutting/bending/ punching requirements, and the type and grade of the material) are set in the various tasks performed in the different phases of the supply chain. Regardless of whether one uses paper-based systems or advanced technologies such as smart tags and radio-frequency identification (RFID), a better understanding is achieved of the processes through which a structural steel component passes. The results of this research can be used to streamline the information flow in the supply chain of structural steel components, regardless of the type of tracking technology used, hence reducing delays and reworks

Negotiating the selling price of hydropower energy using multi-agent systems in BOT

During the feasibility study of BOT (Build-Operate-Transfer) hydropower investments, the selling price of energy is the most critical parameter that impacts the net present value (NPV) estimated by the investors. Investors usually consider the price of energy guaranteed by the government during their feasibility studies which is the worst case scenario. However, it is apparent that negotiations that take place between investor and broker determine the price of energy which is affected by various sources of uncertainty associated with the energy demand and country conditions. The objective of this study was to make a realistic estimate of the investor’s selling price by modeling the negotiation process between investor and broker using a multi-agent system (MAS). Thus, the factors affecting the negotiation process were identified, a negotiation protocol between the parties was set up, negotiation scenarios were determined, and modelled by using a MAS. The model was tested on a hydropower investment in Turkey and generated more realistic results compared to the current practice. Investors and brokers may benefit from this study because it considers the potential changes in the market as well as the negotiating postures of parties under different scenarios

Estimating the profitability of hydropower investments with a case study from Turkey

Energy demand has been increasing, but traditional sources of energy are depletable. New investments are needed in renewable energy production. Hydroelectric power plants are often considered a feasible renewable source of energy and are often organized as a public private partnerships (PPP). However, risk factors stemming from the macro environment as well as project conditions should be considered in performing feasibility studies. The objective of this study was to develop a method that can be used to predict the profitability of hydropower investments considering the relevant risk factors. To that end, a cash flow that represents the construction and operation period is set up, the risk fac­tors involved in such projects are identified, the impacts of these risk factors on the cash flow parameters are assessed, and Monte Carlo simulation is performed to estimate the net present value (NPV) of a hydropower investment. The proposed method was tested in a hydropower investment located in Turkey and generated credible results that could be of great benefit to potential investors operating in similar conditions. The primary contribution of this research is the creation of a method that allows investors to assess the profitability of a hydropower investment by using a stochastic approach

Barriers to Undertaking Green Building Projects in Developing Countries: A Turkish Perspective

Green buildings (GBs) play an important role in achieving sustainable development goals. However, the implementation of green technologies in building projects has not reached the desired level in developing countries such as Turkey because of barriers stemming from country-related factors as well as factors related to design and construction. The objective of this study was to explore the barriers to undertaking GB projects in Turkey. A questionnaire survey was administered to 116 construction practitioners to analyze the criticality of barriers to GB design and construction in the Turkish construction industry. Both descriptive and inferential statistics were adopted to evaluate the data obtained from the questionnaire survey. The findings suggest that the major barriers that hinder the adoption of GBs in Turkey are higher construction cost, lack of knowledge about GBs, lack of an authorized GB rating system, unavailability of GB materials, and inadequate market demand, whereas longer design time is the least critical barrier. The results of factor analysis indicate that the barriers to undertaking GB projects can be grouped under five “factors”, i.e., cost- and demand-related barriers, market-related barriers, people-related barriers, government-related barriers, and time-related barriers. In light of the results, policy makers and construction practitioners can devise strategies to promote GBs in Turkey, which can also be valid in other developing countries with similar socio-economic conditions

Predicting Employer and Worker Responsibilities in Accidents That Involve Falls in Building Construction Sites

Fall-related accidents have received more attention in building construction than in civil construction as fall-from-heights is more common in building construction. In addition to social costs, construction companies face a significant financial burden when fall-related accidents occur. The major portion of the direct cost of accidents that involve falls includes the compensation paid by the employer to the worker. The employer and the worker try to reach an agreement on the size of the compensation, however, most of the time the process is contentious. The objective of this study is to predict the parties’ responsibilities for a fall-related accident by modeling the relationship between the employer and the worker using a multi-agent system. The research pursued a three-step method, including collection of data, development of a multi-agent model, and testing of the model. The model provides satisfactory results and can be used to quantify the employer’s and the worker’s responsibilities in construction fall accidents, hence avoiding any escalation to pursue arbitration or litigation

Exploring the Critical Risk Factors of Public–Private Partnership City Hospital Projects in Turkey

Governments face challenges in delivering essential public services due to their limited funds. This has led to an increasing reliance on the Public–Private Partnership (PPP) model, an alternative financing model involving a long-term collaboration between the private and public sectors to provide public services. Turkey, as a developing country facing financial limitations, has embraced the PPP model to address urgent public needs. Over the past decade, the Turkish Government has extensively utilized the PPP model, particularly in executing city hospital projects. However, investors have faced challenges in project execution due to various risk factors. Therefore, the main objective of this study is to explore the critical risk factors associated with PPP city hospital projects in Turkey. In this context, a comprehensive literature review was conducted to identify potential risks related to PPP city hospital projects. A questionnaire survey was implemented to assess the probability of occurrence and the severity of the impact of these risk factors. The collected data underwent analysis to determine the priority of these risk factors. The findings revealed that the top five most critical risk factors in PPP city hospital projects in Turkey are “foreign exchange rate fluctuations”, “inflation rate volatility”, “high finance costs”, “fiscal issues”, and “economic crises”. Conversely, “unavailability of equipment” was identified as the least significant risk factor. The insights gained from this research can offer valuable guidance for prospective investors interested in participating in PPP city hospital projects in Turkey and other developing countries with similar conditions

Real Options Valuation of photovoltaic investments: a case from Turkey

Investments in renewable energy resources have become inevitable due to increasing energy demand and energy prices, diminishing non-renewable energy resources, and the outgrowth of carbon footprints. Photovoltaic (PV) systems offer high solar energy potential in sustainable energy production whereas their high initial costs necessitate critical strategic valuation of investments. Valuation with conventional methods has been challenging due to existence of uncertainties such as fluctuating PV panel prices, changing meteorological conditions with certain effects on power generation, and governmental policies on energy market regulations. This study aims to propose a real options approach to valuation of residential rooftop PV system investments considering these uncertainties and demonstrate benefits of this approach with an application on the residential PV investment decisions in Turkey. The proposed method, Real Options Valuation (ROV) with Least-Squares Monte Carlo Simulation (LSMC) considers the deferral option of the investor by utilizing stochastic simulations, the discounted cash flow method, linear regression, and backward dynamic programming and thus evaluates the effects of uncertainties on financial attractiveness of residential PV investments. The case study findings proved that ROV with LSMC having a 7-years deferral option supported the investment decision with realizable cost-effective options while “NPV method” resulted in an infeasible investment. Scenario analysis was also conducted to explore policy options that can be used to promote solar energy investments in Turkey. This study has a potential to have practical contributions for investors as well as implications for policy-makers