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Selecting Rooftop Solar Photovoltaic Modules by Measuring Their Attractiveness by a Categorical-Based Evaluation Technique (MACBETH): The Case of Lithuania

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  • Andrius Tamošiūnas

    (Department of Management, Faculty of Business Management, Vilnius Gediminas Technical University, LT-10223 Vilnius, Lithuania)

Abstract

The paper examines the challenges related to solar photovoltaic (PV) development with a pivotal focus on the impacts of the dynamics of the relevant markets and technological advancements in the solar industry. In this regard, household investments into rooftop solar PV modules as one of the available incentives are investigated based on a conducted experiment in Lithuania for selecting rooftop solar PV systems for the prosumer by measuring the attractiveness of solar PV modules by a categorical-based evaluation technique (MACBETH). While a variety of multiple-criteria decision-making (MCDM) methods used by scholars have their specifics in terms of application and the divergence of results, the findings of the conducted experiment reveal MACBETH’s utility when based upon qualitative judgments about the differences in the attractiveness of offers, quantifying their relative value and accordingly ranking the latter. The findings also confirm MACBETH’s potential to be used not only to solve operational and tactical tasks but also for strategic objectives of private and public organizations aiming at competitive and sustainable development in short- and long-term contexts.

Suggested Citation

  • Andrius Tamošiūnas, 2023. "Selecting Rooftop Solar Photovoltaic Modules by Measuring Their Attractiveness by a Categorical-Based Evaluation Technique (MACBETH): The Case of Lithuania," Energies, MDPI, vol. 16(7), pages 1-22, March.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:7:p:2999-:d:1107031
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    References listed on IDEAS

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    1. Besharati Fard, Moein & Moradian, Parisa & Emarati, Mohammadreza & Ebadi, Mehdi & Gholamzadeh Chofreh, Abdoulmohammad & Klemeŝ, Jiří Jaromír, 2022. "Ground-mounted photovoltaic power station site selection and economic analysis based on a hybrid fuzzy best-worst method and geographic information system: A case study Guilan province," Renewable and Sustainable Energy Reviews, Elsevier, vol. 169(C).
    2. Rediske, Graciele & Siluk, Julio Cezar M. & Michels, Leandro & Rigo, Paula D. & Rosa, Carmen B. & Cugler, Gilberto, 2020. "Multi-criteria decision-making model for assessment of large photovoltaic farms in Brazil," Energy, Elsevier, vol. 197(C).
    3. Jalil Heidary Dahooie & Ali Husseinzadeh Kashan & Zahra Shoaei Naeini & Amir Salar Vanaki & Edmundas Kazimieras Zavadskas & Zenonas Turskis, 2022. "A Hybrid Multi-Criteria-Decision-Making Aggregation Method and Geographic Information System for Selecting Optimal Solar Power Plants in Iran," Energies, MDPI, vol. 15(8), pages 1-20, April.
    4. Al Garni, Hassan Z. & Awasthi, Anjali, 2017. "Solar PV power plant site selection using a GIS-AHP based approach with application in Saudi Arabia," Applied Energy, Elsevier, vol. 206(C), pages 1225-1240.
    5. Seker, Sukran & Kahraman, Cengiz, 2021. "Socio-economic evaluation model for sustainable solar PV panels using a novel integrated MCDM methodology: A case in Turkey," Socio-Economic Planning Sciences, Elsevier, vol. 77(C).
    6. Cook, Wade D. & Tone, Kaoru & Zhu, Joe, 2014. "Data envelopment analysis: Prior to choosing a model," Omega, Elsevier, vol. 44(C), pages 1-4.
    7. Ayough, Ashkan & Boshruei, Setareh & Khorshidvand, Behrooz, 2022. "A new interactive method based on multi-criteria preference degree functions for solar power plant site selection," Renewable Energy, Elsevier, vol. 195(C), pages 1165-1173.
    8. Olesen, Ole B. & Petersen, Niels Christian, 2016. "Stochastic Data Envelopment Analysis—A review," European Journal of Operational Research, Elsevier, vol. 251(1), pages 2-21.
    9. Thebault, Martin & Desthieux, Gilles & Castello, Roberto & Berrah, Lamia, 2022. "Large-scale evaluation of the suitability of buildings for photovoltaic integration: Case study in Greater Geneva," Applied Energy, Elsevier, vol. 316(C).
    10. Carlos A. Bana e Costa & Jean-Marie De Corte & Jean-Claude Vansnick, 2016. "On the Mathematical Foundations of MACBETH," International Series in Operations Research & Management Science, in: Salvatore Greco & Matthias Ehrgott & José Rui Figueira (ed.), Multiple Criteria Decision Analysis, edition 2, chapter 0, pages 421-463, Springer.
    11. Abrell, Jan & Kosch, Mirjam & Rausch, Sebastian, 2019. "Carbon abatement with renewables: Evaluating wind and solar subsidies in Germany and Spain," Journal of Public Economics, Elsevier, vol. 169(C), pages 172-202.
    12. Toshiyuki Sueyoshi & Mika Goto, 2019. "Comparison among Three Groups of Solar Thermal Power Stations by Data Envelopment Analysis," Energies, MDPI, vol. 12(13), pages 1-20, June.
    13. Joe Zhu, 2014. "Data Envelopment Analysis," International Series in Operations Research & Management Science, in: Quantitative Models for Performance Evaluation and Benchmarking, edition 3, chapter 1, pages 1-9, Springer.
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