Browsing by Author "Dikmen, Irem"

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Citation - Scopus: 1
An Activity-Based Lessons Learned Model To Support Scheduling Decisions in Construction
(Emerald Group Publishing Ltd, 2025) Yilmaz, Anil; Akcay, Emre Caner; Dikmen, Irem; Birgonul, M. Talat
PurposeThe aim of this study is to develop an activity-based lessons-learned model that allows construction companies to capture, store, classify and reuse activity-related lessons learned (LL) from previous projects, thereby increasing the reliability of time estimates in scheduling.Design/methodology/approachScheduling is a knowledge-intensive process that requires the utilization of data and expert opinion elicitation from various levels of an organization in construction projects. This research consists of five successive steps: performing a needs analysis, proposing an activity-based lessons-learned process model, validating the proposed process model, developing a tool to apply the proposed model in a computer environment and testing the applicability of the tool. To implement the proposed model in practice, a web-based tool, namely the Construction Industry Scheduling with Activity-Based Lessons Learned Tool (ConSALL Tool), was developed. Its functionality was evaluated using black-box testing. The tool was then applied in a real construction project.FindingsResults show that ConSALL has the potential to improve scheduling decisions in construction projects by incorporating data and experience from previous projects. Findings from this research can be used to develop similar models and AI tools to foster activity-based learning in other project-based industries as well as the construction industry.Originality/valueThis paper presents an innovative approach to enhancing construction project scheduling by leveraging LL from past projects. The development and application of the ConSALL Tool demonstrate a practical implementation of the proposed model, providing a framework that can be adapted to other industries to improve project planning and execution.
Citation - WoS: 9
Citation - Scopus: 10
Real Options Valuation of Photovoltaic Investments: a Case From Turkey
(Pergamon-elsevier Science Ltd, 2024) Or, Bartu; Bilgin, Gozde; Akcay, Emre Caner; Dikmen, Irem; Birgonul, M. Talat
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.