MODERN SYSTEMS FOR MONITORING MARKET PRICES OF CONSTRUCTION RESOURCES: OPERATING PRINCIPLES AND CHALLENGES
Abstract
The primary objective of this study is to analyze and evaluate the modern price monitoring systems in the construction industry. Effective cost management of construction resources is critical for maintaining the competitiveness and economic stability of construction enterprises. In contemporary market conditions the ability to accurately monitor these fluctuations is essential for efficient project planning and execution. Constant price changes of construction resources can lead to significant financial losses and deviations from project budgets, emphasizing the necessity for advanced price monitoring systems. The study used literature reviews and critical analysis of existing price monitoring systems to gather comprehensive data on the principles and effectiveness of current systems. The research focused on evaluating automated data collection methods, including web scraping, integration with data suppliers, and manual data entry. The results of our study reveal that modern price monitoring systems provide a valuable tool for obtaining up-to-date market price information, and making justified decisions. However, the implementation of these systems faces several challenges. One of the primary issues is the reliability and timeliness of the data collected. Technical difficulties in integrating various data sources and the high costs associated with the implementation and training of personnel also present significant obstacles. Additionally, the absence of systematic information about market prices for construction resources complicates the monitoring and analysis processes. Rapid price fluctuations require timely and swift responses, which current systems may not always provide. The practical value of this article lies in its comprehensive analysis of the effectiveness of modern price monitoring systems and the identification of key challenges in their implementation. The study offers recommendations for improving existing approaches, such as enhancing data validation mechanisms and expanding integration capabilities with other construction management systems. Furthermore, introducing automated data collection systems from regional agencies and enterprises could significantly enhance process efficiency and accuracy, reducing reliance on manual data collection. By addressing these challenges, the construction industry can achieve more accurate cost management, reduce risks, and optimize expenses. Ultimately, the development and refinement of price monitoring systems will contribute to the economic efficiency and stable growth of construction projects.
References
2. Січний С.Б. Управління вартістю матеріально-технічних ресурсів підприємствами при будівництві об’єктів для державного замовника : дис….канд. екон. наук : 08.00.04. Київ, 2021. 241 с.
3. Benedetti I., Laureti T., Palumbo L., Rose B. Computation of High-Frequency Sub-National Spatial Consumer Price Indexes Using Web Scraping Techniques. Economies. 2022. Vol. 10(4). DOI: https://doi.org/10.3390/economies10040095
4. Raja, K.A.Karthick & Murali, Dr.K. Resource Management In Construction Project. International Journal of Scientific and Research Publications (IJSRP). 2020. Vol. 10, pp. 252–259. DOI: http://dx.doi.org/10.29322/IJSRP.10.05.2020.p10130
5. Chen, X., Chang-Richards, A.Y., Pelosi, A., Jia, Y., Shen, X., Siddiqui, M.K. and Yang, N. Implementation of technologies in the construction industry: a systematic review. Engineering, Construction and Architectural Management. 2022. Vol. 29 No. 8, pp. 3181–3209. DOI: http://dx.doi.org/10.1108/ECAM-02-2021-0172
6. CheckPrice. Актуальні ціни будівельних матеріалів. Система моніторингу цін на будівельні матеріали в Україні. URL: https://checkprice.com.ua
7. ДП «ДерждорНДІ». Моніторинг цін на матеріали. Інформація про ціни на основні дорожньо-будівельні матеріали. URL: https://nidi.org.ua
8. Tayefeh Hashemi, S., Ebadati, O.M. & Kaur, H. Cost estimation and prediction in construction projects: a systematic review on machine learning techniques. SN Applied Sciences. 2020. Vol. 2, 1703. Available at: https://doi.org/10.1007/s42452-020-03497-1
1. Sichnyi, S. (2020) Economic efficiency of determining the market price of construction resources within the limited budget. Three Seas Economic Journal, vol. 1(4), pp. 133–138. DOI: https://doi.org/10.30525/2661-5150/2020-4-19
2. Sichnyi, S. B. (2021) Upravlinnia vartistiu materialno-tekhnichnykh resursiv pidpryiemstvamy pry budivnytstvi obiektiv dlia derzhavnoho zamovnyka [Management of the cost of material and technical resources by enterprises during the construction of facilities for the state customer]: dys….kand. ekon. nauk : 08.00.04. Kyiv, 241 p. (in Ukrainian)
3. Benedetti I., Laureti T., Palumbo L., Rose B. (2022) Computation of High-Frequency Sub-National Spatial Consumer Price Indexes Using Web Scraping Techniques. Economies, vol. 10(4). DOI: https://doi.org/10.3390/economies10040095
4. Raja, K.A.Karthick & Murali, Dr.K. (2020) Resource Management In Construction Project. International Journal of Scientific and Research Publications (IJSRP), vol. 10, pp. 252–259. DOI: http://dx.doi.org/10.29322/IJSRP.10.05.2020.p10130
5. Chen, X., Chang-Richards, A.Y., Pelosi, A., Jia, Y., Shen, X., Siddiqui, M.K. and Yang, N. (2022) Implementation of technologies in the construction industry: a systematic review. Engineering, Construction and Architectural Management, vol. 29 no. 8, pp. 3181–3209. DOI: http://dx.doi.org/10.1108/ECAM-02-2021-0172
6. CheckPrice. Aktualni tsiny budivelnykh materialiv. Systema monitorynhu tsin na budivelni materialy v Ukraini [CheckPrice. Actual prices of construction materials. Price monitoring system for building materials in Ukraine]. Available at: https://checkprice.com.ua
7. DP «DerzhdorNDI». Monitorynh tsin na materialy. Informatsiia pro tsiny na osnovni dorozhno-budivelni materialy [SE «DerzhdorNDI». Monitoring of prices for materials. Information on prices for main road construction materials]. Available at: https://nidi.org.ua (accessed May 20, 2024)
8. Tayefeh Hashemi, S., Ebadati, O.M. & Kaur, H. (2020) Cost estimation and prediction in construction projects: a systematic review on machine learning techniques. SN Applied Sciences, vol. 2, 1703. DOI: https://doi.org/10.1007/s42452-020-03497-1
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