A multi-criteria decision-making synthesis method to determine the most effective option for modernising a public building

    Jovita Starynina Affiliation
    ; Leonas Ustinovichius   Affiliation


The study presents a sustainable building modernisation model that uses knowledgebased decision-making methods to general reconstruct old public buildings, intending to achieve the best level of energy use on the design scene. The rapid development and dissemination of standards cause multiple research opportunities in the fields of process automation and adaptation of BIM technologies to the prerequisites of existing buildings. Decision-making was widely supported by imitating structures used in the late stages of design. However, its application is not sufficient at the beginning, which affects design solutions with a significant impact on the performance of the completed building. Construction design is a multifaceted discipline where architects, engineers, contractors, and builders influence design decisions. This modernisation way uses digital systems and simulations to estimate the expected energy consumption of construction faster and economically. BIM and critical characteristics are the basis of the model, where design and general processing needs to follow to pre-built instructions. This solution allows estimating energy demand in reconstructed buildings and correlation of parameters.

First published online 25 September 2020

Keyword : sustainable, energy, MCDM, BIM, decision making

How to Cite
Starynina, J., & Ustinovichius, L. (2020). A multi-criteria decision-making synthesis method to determine the most effective option for modernising a public building. Technological and Economic Development of Economy, 26(6), 1237-1262.
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Nov 17, 2020
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Banasik, A., Bloemhof-Ruwaard, J. M., Kanellopoulos, A., Claassen, G. D. H., & van der Vorst, J. G. (2018). Multi-criteria decision making approaches for green supply chains: A review. Flexible Services and Manufacturing Journal, 30(3), 366–396.

Barlish, K., & Sullivan, K. (2012). How to measure the benefits of BIM – A case study approach. Automation in Construction, 24, 149–159.

Bortolini, R., & Forcada, N. (2018). Facility managers’ perceptions on building performance assessment. Frontiers Engineering Management, 5(3), 324–333.

Bryde, D., Broquetas, M., & Volm, J. M. (2013). The project benefits of Building Information Modelling (BIM). International Journal of Project Management, 31, 971–980.

Chalal, M. L., Medjdoub, B., Bezai, N., & Shrahily, R. (2020). Big Data to support sustainable urban energy planning: The EvoEnergy project. Frontiers Engineering Management, 7(2), 287–300.

Chong, H.-Y., Lee, C.-Y., & Wang, X. (2017). A mixed review of the adoption of Building Information Modelling (BIM) for sustainability. Journal of Cleaner Production, 142(4), 4114–4126.

Edirisinghe, R., London, K., Kalutara, P., & Aranda-Mena, G. (2017). Building information modelling for facility management: are we there yet? Engineering, Construction and Architectural Management, 24(6), 1119–1154.

European Commission. (2011a). Energy efficiency plan 2011 (COM/2011/109 final).

European Commission. (2011b). Energy Roadmap 2050 (COM/2011/885 final).

European Commission. (2012). Communication from the Commission to the European Parliament and the Council–Strategy for the sustainable competitiveness of the construction sector and its enterprises (COM/2012/0433). FIN:EN:PDF

European Commission. (2014). A policy framework for climate and energy in the period from 2020 up to 2030 (COM/2014/16 final). 52014DC0015

European Union. (2010). Directive 2010/31/EU of the European Parliament and of the Council of 19 May 2010 on the energy performance of buildings (EPBD2010/31/EU).

Garcia, E. G., & Zhu, Z. (2015). Interoperability from building design to building energy modelling. Journal of Building Engineering, 1, 33–41.

Goh, T. N. (1989). Some practical considerations in the design of manufacturing process experiments. Journal of Mechanical Working Technology, 20, 219–228.

Govindan, K., Shankar, K. M., & Kannan, D. (2016). Sustainable material selection for construction industry – A hybrid multi criteria decision making approach. Renewable and Sustainable Energy Reviews, 55, 1274–1288.

Gray, M., Gray, J., Teo, M., Chi, S., & Cheung, F. (2013). Building information modeling, an international survey. Brisbane, Australia.

Gu, N., & London, K. (2010). Understanding and facilitating BIM adoption in the AEC industry. Automation in Construction, 19, 988–999.

Habib, C., Makhoul, A., Darazi, R., & Couturier, R. (2019). Health risk assessment and decision-making for patient monitoring and decision-support using wireless body sensor networks. Information Fusion, 47, 10–22.

Habibi, S. (2017). Micro-climatization and real-time digitalization effects on energy efficiency based on user behavior. Building and Environment, 114, 410–428.

Hashemkhani Zolfani, S., Zavadskas, E. K., & Turskis, Z. (2013). Design of products with both International and Local perspectives based on Yin-Yang balance theory and SWARA method. Economic Research-Ekonomska Istraživanja, 26(2), 153–166.

He, Y., & Xu, Z. (2019). Multi-attribute decision making methods based on reference ideal theory with probabilistic hesitant information. Expert Systems with Applications, 118, 459–469.

Hemsath, T. L., & Bandhosseini, K. A. (2017). Energy modeling in architectural design. Taylor & Francis.

Hu, M. (2019). Does zero energy building cost more? – An empirical comparison of the construction costs for zero energy education building in United States. Sustainable Cities and Society, 45, 324–334.

Hwang, C., & Yoon, K. (1981). Multiple attribute decision making: methods and applications: a state-ofthe-art survey. Springer-Verlag.

Ilce, A. C., & Ozkaya, K. (2018). An integrated intelligent system for construction industry: A case study of raised floor material. Technological and Economic Development of Economy, 24(5), 1866–1884.

Jensen, P. A., Maslesa, E., Berg, J. B., & Thuesen, C. (2018). 10 questions concerning sustainable building renovation. Building and Environment, 143, 130–137.

Jia, Q., Wei, L., & Li, X. (2019).Visualizing sustainability research in business and management (1990– 2019) and emerging topics: a large-scale bibliometric analysis. Sustainability, 11(20), 5596.

Jose, P. C., Luis, B., & Ricardo, M. (2019). Optimising building sustainability assessment using BIM. Automation in Construction, 102, 170–182.

Jung, Y., & Joo, M. (2011). Building information modelling (BIM) framework for practical implementation. Automation in Construction, 20, 126–133.

Kaklauskas, A., Zavadskas, E. K., Raslanas, S., Ginevicius, R., Komka, A., & Malinauskas, P. (2006). Selection of Low-E windows in retrofit of public buildings by applying multiple criteria method COPRAS: A Lithuanian case, Energy and Buildings, 38(5), 454–462.

Kamari, A., Schultz, C. P. L., & Kirkegaard, P. H. (2019). Constraint-based renovation design support through the renovation domain model. Automation in Construction, 104, 265–280.

Kaya, I., Çolak, M., & Terzi, F. (2018). Use of MCDM techniques for energy policy and decision‐making problems: A review, International Journal of Energy Research, 42(7), 2344–2372.

Kreider, R., Messner, J., & Dubler, C. (2010). Determining the frequency and impact of applying BIM for different purposes on projects. Paper presented at the Proceeding 6th International Conference on Innovation in Architecture, Engineering and Construction (AEC), Pennsylvania State University, University Park, PA, USA.

Kreiner, H., Passer, A., & Wallbaum, H. (2015). A new systemic approach to improve the sustainability performance of office buildings in the early design stage. Energy and Buildings, 109, 385–396.

Krylovas, A., Kosareva, N., & Zavadskas, E. K. (2018). Scheme for statistical analysis of some parametric normalization classes. International Journal of Computers, Communications & Control (IJCCC), 13(6), 972–987.

Kumar, A., Sah, B., Singh, A. R., Deng, Y., He, X., Kumar, P., & Bansal, R. C. (2017). A review of multi criteria decision making (MCDM) towards sustainable renewable energy development. Renewable and Sustainable Energy Reviews, 69, 596–609.

Lee, K. H., Kim, I. H., & Choo, S. Y. (2015). Model study of design components for energy-performance-based architectural design using BIM LOD 100. Journal of Green Building, 10(2), 179–197.

Leite, F., Akcamete, A., Akinci, B., Atasoy, G., & Kiziltas, S. (2011). Analysis of modeling effort and impact of different levels of detail in building information models. Automation in Construction, 20, 601–609.

Linderoth, H. (2010). Understanding adoption and use of BIM as the creation of actor networks. Automation in Construction, 19(1), 66–72.

MacCrimmon, K. R. (1968). Decision-making among multiple-attribute alternatives: a survey and consolidated approach (DTIC Document).

Maghsoodi, A. I., Abouhamzeh, G., Khalilzadeh, M., & Zavadskas, E. K. (2018). Ranking and selecting the best performance appraisal method using the MULTIMOORA approach inte grated Shannon’s entropy. Frontiers of Business Research in China, 12(1), 2–21.

Mahdavi, A., & Tahmasebi, F. (2015). Predicting people’s presence in buildings: An empirically based model performance analyses. Energy and Buildings, 86, 349–355.

Mahdiraji, H. A., Turskis, Z., Jafarnejad, A., & Rezayar, A. (2019). Non-cooperative two-echelon supply chains with a focus on social responsibility. Technological and Economic Development of Economy, 25(6), 1162–1187.

Martinaitis, V., Zavadskas, E. K., Motuzienė, V., & Vilutienė, T. (2015). Importance of occupancy information when simulating energy demand of energy efficient house: A case study. Energy and Buildings, 101, 64–75.

Merschbrock, C., & Figueres-Munoz, A. (2015). Circumventing obstacles in digital construction design – a workaround theory perspective. Procedia Economics and Finance, 21, 247–255.

Ministry of Environment of the Republic of Lithuania (2016). Construction technical regulation “Design and certification of energy performance of buildings” (STR 2.01.02:2016).

Nazarko, L., & Melnikas, B. (2019). Operationalising responsible research and innovation – tools for enterprises. Engineering Management in Production and Services, 11(3), 21–28.

Pinheiro, S., Donnell, J., Wimmer, R., Bazjanac, V., Muhic, S., Maile, T., Frisch, J., & Treeck, C. (2018). Model view definition for advanced building energy performance simulation. Paper presented at the CESBP/BauSIM 2016 Conference, Dresden, Berlin.

Radović, D., Stević, Ž., Pamučar, D., Zavadskas, E. K., Badi, I., Antuchevičiene, J., & Turskis Z. (2018). Measuring performance in transportation companies in developing countries: a novel rough ARAS model. Symmetry, 10(10), 1–24.

Rodrigues, F., Matos, R., Alves, A., Ribeirinho, P., & Rodrigues, H. (2018). Building life cycle applied to refurbishment of traditional building from Oporto, Portugal. Journal of Building Engineering, 17, 84–95.

Ruzgys, A., Volvačiovas, R., Ignatavičius, Č., & Turskis, Z. (2014). Integrated evaluation of external wall insulation in residential buildings using SWARA-TODIM MCDM method. Journal of Civil Engineering and Management, 20(1), 103–110.

Saaty, T. L. (1994). Fundamentals of decision making and priority theory with the AHP. RWS Publications.

Salman, A. (2011). Building Information Modeling (BIM): trends, benefits, risks, and challenges for the AEC industry. Leadership and Management in Engineering, 11(3), 241–252.

Siksnelyte, I., Zavadskas, E. K., Streimikiene, D., & Sharma, D. (2018). An overview of multi-criteria decision-making methods in dealing with sustainable energy development issues. Energies, 11(10), 1–21.

Simanaviciene, R., & Ustinovichius, L. (2012). A new approach to assessing the biases of decisions based on multiple attribute decision making methods. Elektronika ir elektrotechnika, 117(1), 29–32.

Simanaviciene, R., Liaudanskiene, R., & Ustinovichius, L. (2012). A new synthesis method of structural, technological and safety decisions (SyMAD-3). Journal of Civil Engineering and Management, 18(2), 265–276.

Somboonwit, N., Boontore, A., & Rugwongwan, Y. (2017, February 25–27). Obstacles to the automation of building performance simulation: adaptive building integrated photovoltaic (BIPV) design. Paper presented at the 5th AMER International Conference on Quality of Life, Bangkok, Thailand.

Turskis, Z., Zavadskas, E. K., & Kutut, V. (2013). A model based on ARAS-G and AHP methods for multiple criteria prioritizing of heritage value. International Journal of Information Technology & Decision Making, 12(01), 45–73.

Volk, R., Stengel, J., & Schultmann, F. (2014). Building Information Modeling (BIM) for existing buildings-Literature review and future needs. Automation in Construction, 38, 109–127.

Wang, N., & Adeli, H. (2015). Self-constructing wavelet neural network algorithm for nonlinear control of large structures. Engineering Applications of Artificial Intelligence, 41, 249–258.

Winkowski, C. (2019). Classification of forecasting methods in production engineering. Engineering Management in Production and Services, 11(4), 23–33.

Yazdani, M., Zarate, P., Zavadskas, E. K., & Turskis, Z. (2019). A Combined Compromise Solution (CoCoSo) method for multi-criteria decision-making problems. Management Decision, 57(9), 2501–2519.

Yin, X., Liu, H., Chen, Y., & Al-Hussein, M. (2019). Building information modelling for off-site construction: Review and future directions. Automation in Construction, 101, 72–91.

Zavadskas, E. K., Antucheviciene, J., Saparauskas, J., & Turskis, Z. (2013). MCDM methods WASPAS and MULTIMOORA: verification of robustness of methods when assessing alternative solutions. Economic Computation and Economic Cybernetics Studies and Research, 47(2), 5–20.

Zavadskas, E. K., Antucheviciene, J., Turskis, Z., & Adeli, H. (2016a). Hybrid multiple-criteria decisionmaking methods: A review of applications in engineering. Scientia Iranica. Transaction A, Civil Engineering, 23(1), 1–20.

Zavadskas, E. K., Govindan, K., Antucheviciene, J., & Turskis, Z. (2016b). Hybrid multiple criteria decision-making methods: A review of applications for sustainability issues. Economic Research-
Ekonomska Istraživanja, 29(1), 857–887.

Zavadskas, E. K., Kaklauskas, A., & Sarka, V. (1994). The new method of multicriteria complex proportional assessment of projects. Technological and Economic Development of Economy, 1(3), 131–139.

Zavadskas, E. K., Kaklauskas, A., Banaitis, A., & Kvederyte, N. (2004). Housing credit access model: The case for Lithuania. European Journal of Operational Research, 155(2), 335–352.

Zavadskas, E. K., Kaklauskas, A., Turskis, Z., & Kalibatas, D. (2009). An approach to multi-attribute assessment of indoor environment before and after refurbishment of dwellings. Journal of Environmental Engineering and Landscape Management, 17(1), 5–11.

Žėkas, V., Martinaitis, V., Streckienė, G., & Vilutienė, T. (2014). A quantitative evaluation of theoretical renewable energy potential of the building site. Journal of Civil Engineering and Management, 20(6), 873–883.

Zemlickienė, V., & Turskis, Z. (2020). Evaluation of the expediency of technology commercialization:
a case of information technology and biotechnology. Technological and Economic Development of Economy, 26(1), 271–289.

Zou, X. W. P., Alam, M., Phung, V. M., Wagle, D., Stewart, R., Bertone, E., Sahin, O., & Butine, C. (2017). Achieving energy efficiency in government buildings through mandatory policy and program enforcement. Frontiers Engineering Management, 4(1), 92–103.