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Estimation of Sport Facilities by Means of Technical-Economic Indicator

  • Tomas Hanak EMAIL logo , Lukas Hrstka , Martin Tuscher and Vojtech Biolek
Published/Copyright: June 5, 2020
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Open Engineering
From the journal Open Engineering Volume 10 Issue 1

Abstract

This paper is concerned with early cost estimation of sport facilities. Sufficiently precise cost estimation is essential for investors in the pre-investment stage where they decide on whether to pursue an investment and choose a suitable technical solution for the development of the project. Through a detailed analysis of the technical and economic documentation pertaining to seven sport facilities projects assembled using concrete prefabricated beam parts, as well as evaluation of the data thus obtained, three types of technical-economic indicators were set in relation to the enclosed building area, the number of spectator seats and the sports playing area. The results achieved indicate that evaluation of relations between these three indicators could contribute to a more effective use of investment funding on the part of the investor. Other conclusions include the finding that available indicators published by private companies active in the area of construction budgeting are not sufficiently accurate for the purposes of investment decision-making; specifically, these indicators greatly overestimate the costs of sport facilities, which can potentially lead to these projects being rejected. This contribution brings know-how for a more accurate early cost estimation of sport facilities in the Czech Republic which can, thanks to a generally applicable methodology, be used in other countries as well.

Keywords: cost; estimation; indicator; sport facilities

1 Introduction

The need to know the approximate costs is essential in a situation where the investor decides on whether to pursue and investment and needs to select a suitable technical solution for the project. As part of the pre-investment stage of a construction project, the relevant documentation has not yet been prepared in sufficient detail and it is thus impossible to obtain the exact amount of construction costs in the form of the bill of costs [1]; alternatively, aggregated technical-economic indicators can be used [2].

However, to have at least some idea about the costs, the investor can use various kinds of indicators which, based on an adequate unit of measurement (e.g. cubic metres [m3] in the case of residential buildings, square metres [m2] in the case of roads, and metres [m] in the case of utility networks), express the unit costs of construction (e.g. EUR/m3).

In the Czech Republic, these indicators are published by companies doing business in the area of construction budgeting, specifically by the companies ÚRS Praha and RTS. For example, ÚRS Praha offers the KUBIX application which enables to determine an approximate price of the whole construction project, where it is only necessary to specify a type of building (single-family house, residential building, administrative building, etc.), input some additional general information (building parameters and the level of technical standard), and then specify the planned total volume of the building or the room floor area [3]. The above-indicated companies also publish books such as Rozpočtové ukazatele 2018 (Budget Indicators 2018) [4] and Cenové ukazatele ve stavebnictví pro rok 2018 (Price Indicators in the Construction Sector in 2018) [5]. Naturally, using the indicators is not the only way to carry out early cost estimating with respect to buildings. A number of authors have used neural networks for this purpose, e.g. in relation to tunnel constructions [6] or structural systems of buildings [7]; other potential approaches include e.g. approximate cost estimating based on quantity of standard work [8] and the case-based reasoning model [9]. Obviously, for adequate estimation of construction costs it is important to estimate correct scope of work, as incorrect scope estimation may lead to both cost and time over-runs [10].

This article deals with specific structures, i.e. sport facilities. It is questionable how accurate the indicators used in practice are when applied to structures which are not built very often. Indicators for these structures are not necessarily subject to annual validation, i.e. the increasing of their accuracy based on projects implemented within the given time period. Instead, the indicator values may be updated in the form of indexing, i.e. multiplying the historical value of the indicator by an index expressing e.g. the average growth in the cost of construction works and materials. Certain indexes are published by the Czech Statistical Office, e.g. in the Prices of producers – time series; Prices of construction works [11].

The economic efficiency of an investment is often measured using the indicator of Net Present Value [12]. However, the investor may also benefit from a technical analysis of the building design, i.e. determining whether it is over- or under-designed in terms of the size of the enclosed building area. Monitoring and evaluating parameters such as the size of the enclosed area or the size of the playing area could potentially result in achieving better project value in terms of NPV.

Therefore, the aim of this contribution is to determine the value of the technical-economic indicator (TEI) for quick approximate cost estimating of newly constructed sport facilities in the Czech Republic. These structures are defined as follows: “A building pursuant to Section 3 of Decree No. 137/1998 Coll. is an above-ground spatially-concentrated structure closed off on the outside by its enclosure walls and the roof structure” [13].

The article is structured as follows: after the description of the current state of the problem and formulation of the objective, the materials and methods used are specified; the achieved results are then presented and compared to similar publicly available indicators. The final part of the contribution also outlines the direction of future research and its limitations.

2 Materials and methods

This article analyses buildings classified according to the JKSO [14] classification under “civic buildings”, subcategory 801.5 – sport facilities. In the CZ-CPA classification, “sport facilities” and “sport halls” are indicated under a common designation, i.e. 41.00.28 – “Buildings serving for social and cultural purposes, sports, education, healthcare, institutional care or religious purposes”. These types of structures need to be analysed separately in terms of a closer specification and their different pricing. Sport facilities usually have a main and secondary playing area (they are normally multifunctional, i.e. suitable for futsal, basketball, volleyball and other ball games), a spectator stand, locker rooms and sanitary facilities for athletes, locker rooms and sanitary facilities for spectators, refreshment units, connecting hallways and support rooms. In general, sport facilities offer a greater flexibility of use than sports halls and do not include e.g. football or baseball stadiums.

While these sport facilities are fairly diverse in scope (inclusion of spectator stands etc.) and this is reflected also in the different amounts of costs, we defined the following requirements for inclusion into the studied sample in order to ensure sufficient homogeneousness and comparability:

  • permanent spectator stand; and

  • meeting the value of free air space over the playing area (i.e. the sum of the volume of free air over the playing area must not exceed two thirds of the enclosed building area).

Subsequently,we found suitable sport facilities which were constructed in the past eight years or are planned for construction in the Czech Republic in the near future and a budget is already available for them, this set contained 41 potential projects. Based on the Free Access to Information Act [15], we asked project owners for the relevant documentation (project documentation, bill of costs etc.). As a result, we have received 31 positive responses. The total of 22 projects out of 31 were removed from the sample for several reasons such as the fact that the project represented a reconstruction instead of a new construction, that the facility has been built with different technology/materials or that some important data were missing in the documentation provided. It should be noted that it is the contracting authority’s responsibility to ensure the accuracy and completeness of the tender documentation, as pointed out in [16]. Finally, were able to obtain the necessary documentation pertaining to a total of nine sport facilities, of which seven are categorised according to the main supporting structure under materials category 4 (assembled from concrete prefabricated beam parts) and two fall under category 7 (metal structure). Since these construction types differ greatly, it is necessary to study the two construction-material categories separately. Taking into account the size of the sample, only category 4 is relevant to further analysis. For each sport facility, the following details were obtained:

  • year of construction

  • built-up area in m2

  • size of the playing area in m2

  • enclosed building area in m3

  • price of the entire project excl. VAT

  • price of the construction part excl. VAT

  • number of seats in the spectator stand.

In order to get a better idea how “sports facilities” according to the Czech classification system usually look like, an illustrative example is provided on Figures 1 and 2 showing the outside view and interior (playing area with permanent spectator stand) respectively.

Figure 1 Sport facility in Kašperské Hory – outside view
Figure 1

Sport facility in Kašperské Hory – outside view

Figure 2 Sport facility in Kašperské Hory – playing area with permanent spectator stand
Figure 2

Sport facility in Kašperské Hory – playing area with permanent spectator stand

For the purposes of the analysis, it was necessary to adjust the budgeted costs for items not directly related to sports purposes (e.g. access roads, water mains, gas pipes, sewerage, street lighting and landscaping). The analysed price thus includes the entire building of the sport facilities, air-handling technology, heating, electrical fittings and sanitary fittings. This price is called “price of the construction part excl. VAT”.

Since the sport facilities were not built at the same time, it was necessary to carry out indexing for base year 2018. Firstly, it was necessary to determine the price change index value:

(1)Ii=UPb/UPi

where UPb corresponds to the unit price of the base year; UPi corresponds to the unit price of the ith year (it applies for both UPb and UPi that the unit price is related to m3 of enclosed building area and is taken from the RUSO database of sport facilities – construction class 4 [4]); Ii corresponds to the price change index for the ith year.

Using the subsequent indexing of prices, the historical values were converted to correspond to base year 2018.

(2)PIj=HPj×Ii

where PIj corresponds to the indexed price of the jth project as of the base year; HPj corresponds to the price of the jth project in the ith year.

In the next step, we determined the value of three types of TEI for the individual sport facilities using the following general equation for the chosen specific units:

(3)TEIsu=PI/SU

where SU corresponds to a concrete specific unit:

  • enclosed building area (m3)

  • number of seats (pc.)

  • size of the playing area (m2).

Finally, in the last step the general value of the individual types of TEI is specified as mean and median.

3 Results and discussion

3.1 Input data set

Firstly, it should be noted that the number of sport facility projects developed in the Czech Republic is rather low. As a result of additional requirements on the projects with regard to the need to maintain the required measure of similarity (e.g. the presence of a permanent spectator stand and preparation and implementation of the project within the past five years), information on seven projects were collected. This limitation also results from the fact that the Czech Republic is a relatively small market for such a distinctive type of facilities. While they differ from each other in multiple parameters, they are classified within the same JKSO subcategory and represent (in the context of the Czech construction industry) a relevant set for the purposes of early cost estimation analysis.

The tables contain the basic input price data (Table 1) and non-price data (Table 2) pertaining to the studied set.

Table 1

Non-price input data [17].

P.IDYearBuilt-up area [m2]Size of the playing area [m2]Enclosed area [m3]No. of seats
120182,055.311,190.1021,088.68161
22016/20173,268.971,376.8135,967.69402
320141,448.48999.7014,465.33180
420152,894.211,546.8024,561.79189
520162,399.591,195.4317,464.06168
620181,420.55990.2018,866.0470
720151,612.741,104.4018,274.1748
Table 2

Price input data [17].

P.IDPrice of the entire

project [EUR]		Price of the

construction part – HPj

[EUR]
no. 13,601,0663,080,384
no. 24,335,0633,463,132
no. 31,334,8651,207,658
no. 42,944,7362,647,192
no. 53,431,0312,349,361
no. 62,322,2992,247,340
no. 72,106,2841,812,513

P.ID is the identification number of the project. In project No. 2, the construction had two stages, where the first and second stages took place in 2016 and 2017, respectively.

3.2 Calculation of the price change index

The price change index is specified for the individual years based on formula No. 1. The RUSO value for base year 2018 for the given construction type equals 285.74 EUR/m3. The calculated indexes for the individual years are indicated in Table 3.

Table 3

Price change index

YearRUSO [EUR/m3] [4]Ii
2010196.081.0911
2011193.681.1047
2012187.741.1396
2013189.531.1288
2014189.151.1311
2015195.031.0970
2016200.231.0685
2017205.381.0417
2018213.95base

The RUSO index clearly shows a drop in the years 2009 to 2012. This was a result of the economic crisis in the Czech Republic which also severely impacted the construction sector. Due to under-utilisation of production capacities, reduced investments and strong competition on the market, suppliers were forced to reduce their offering prices.

3.3 Indexing of prices for the base year

In the next step, historical prices are indexed for the base year (2018) based on formula No. 2. The resulting values are indicated in Table 4.

Table 4

Indexing of historical prices for the base year

P.IDPrice of the

construction part

– historical HPj [EUR]		Price of the

construction part

– indexed PIj [EUR]
no. 13,080,3843,080,384
no. 21,789,293 (2016) 1,673,839 (2017)3,655,554
no. 31,207,6581,366,015
no. 42,647,1922,904,051
no. 52,349,3612,510,309
no. 62,247,3402,247,340
no. 71,812,5131,988,382

3.4 Determination of TEI for the selected specific units

Table 5 shows the values of TEI for the individual specific units based on formula No. 3. Specifically, three types of TEI are used: TEIEA, TEINS and TEIPA, which means TEI per 1 m3 of enclosed area, per 1 seat, and per 1 m2 of the playing area, respectively. Table 6 indicates the statistical values of TEI (minimum, maximum, mean and median).

Table 5

Determination of TEI values for the individual projects.

P.IDTEIEA

[EUR/m3]		TEINS

[EUR/pc.]		TEIPA

[EUR/m2]
no. 1146.0719,132.822,588.34
no .2101.639,093.422,655.09
no. 394.437,588.971,366.42
no. 4118.2315,365.351,877.46
no. 5143.7414,942.322,099.92
no. 6119.1232,104.862,269.58
no. 7108.8141,424.631,800.42
Table 6

Determination of the general values of TEI.

P.IDTEIEA

[EUR/m3]		TEINS

[EUR/pc.]		TEIPA

[EUR/m2]
Min94.437,588.971,366.42
Max146.0741,424.632,655.09
Mean118.8619,950.342,093.89
Median118.2315,365.352,099.92

Table 5 clearly shows that projects differ from each other in TEI values. As concerns TEIEA, the minimum and maximum value corresponds to 94.43 EUR/m3 and 146.07 EUR/m3, respectively. This means that per 1m3 of enclosed building area, project No. 1 was 55% more expensive than project No. 3. Both mean and median are nearly identical, i.e. 118.86 EUR/m3 and 118.23 EUR/m3, respectively. Detected differences in unit prices are caused by a number of factors. Firstly, it should be noted that analyzed prices are market prices resulting from the public tender procedure. Market prices,which are the very short-period prices in the sense that the supply of a commodity/work cannot adjust itself to demand in this period, move around the normal price. Market prices differ in time and place (all projects are located in different cities) and are also influenced by real competition in any tender (measured by the number of submitted bids) and its financial volume. For instance, it has been detected, that for foundation slabs and strip foundation unit prices varies between 83.58 EUR/m3 and 112.08 EUR/m3 and 85.94 EUR/m3 and 112.08 EUR/m3 respectively, which represents relative change in price 34% and 30% respectively.

As concerns the indicator TEINS, the difference in values are more pronounced than in the case of TEIEA. Specifically, in project No. 3 the value of TEINS is approx. 5.5 times lower than in project No. 7. This is due to the fact that project No. 3 brings a much higher number of spectator seats for a lower cost.

Finally, in the case of TEIPA, the mean and median values differ only negligibly (0.03%), where the largest difference exists between projects Nos. 3 and 2, where project No. 2 is 1.94 times costlier.

Figure 3 offers an interesting comparison. The graph shows indexes of value deviations from the medians achieved within the individual projects for all three types of TEI indicators, i.e. TEIEA, TEINS and TEIPA. The deviation index is calculated as the ratio of the value of the relevant indicator in a specific project and the median.

Figure 3 Comparison of projects in terms of TEI deviation index.
Figure 3

Comparison of projects in terms of TEI deviation index.

The graph shows that project No. 4 can be considered a “standard project” since the values of TEIEA, TEINS and TEIPA are close to the median. In projects No. 6 and 7, it is clear that the seating capacity in the spectator stand was undersized in comparison to the other projects, given the financial scope of the projects. In project No. 1, it is clearly discernible that the cost was higher in all parameters (indicating either that the project accentuated quality, or that a bid with a higher offering price was selected in the tender procedure); on the other hand, project No. 3 can be considered rather less expensive. It should be noted that values of TEIEA and TEINS deviation indexes are almost the same for projects No. 1 and 4, therefore TEINS marks overlap TEIEA marks on Figure 3.

3.5 Comparison of TEIEA with the values of ÚRS and RTS indicators

Table 7 shows a comparison of the TEIEA value with the indicators published by ÚRS and RTS companies. The table indicates a number of sport facilities based on which the indicator was determined (this information is not available for the RTS indicator), the value of the indicator and the relative difference in comparison to TEIEA.

Table 7

Comparison of TEIEA values with ÚRS and RTS indicators [EUR/m3].

IndicatorTEIEA

(median)		ÚRS

[4]		RTS

[5]
Sample size73unknown
Value118.23213.95204.10
Relative difference100%181%173%

Table 7 shows that the TEIEA indicator is based on a larger number of representative sport facilities than the ÚRS indicator. The same information is not available in the case of RTS indicator. It is of interest that the ÚRS and RTS indicator values do not differ from each other very much, but comparison with TEIEA reveals a deviation of 181% and 173% for ÚRS and RTS indicators, respectively. The analysis indicates that the compared ÚRS and RTS indicators do not express a realistic price levels of sport facilities structures assembled using concrete prefabricated beam parts. This assertion can be documented on e.g. project No. 1, which shows the highest value of TEIEA = 146.07 EUR/m3. Nevertheless, this value is still considerably below that of the RTS indicator. Therefore, it can be concluded that the use of publicly available indicators can lead to an overvaluation of the approximate costs associated with the construction of sport facilities structures assembled using concrete prefabricated beam parts. The columns in Figure 4 show TEIEA values for individual projects (No. 1 – 7 and ÚRS and RTS indicators).

Figure 4 Comparison of project TEIEA, ÚRS and RTS indicators [EUR/m3].
Figure 4

Comparison of project TEIEA, ÚRS and RTS indicators [EUR/m3].

4 Conclusion

This paper addresses the issue of early cost estimation in the construction of sport facilities. Specifically, the analysis deals with a specific type of construction, i.e. sport facilities structures assembled using concrete prefabricated beam parts. This contribution aims to determine the value of the technical-economic indicator (TEI),where three specific units were specified (enclosed area, number of seats, and size of the playing areas).

The results show that the use of indicators published by the companies ÚRS and RTS leads to overestimation of the approximate investment costs of implementing the construction parts of these projects,which in turn suggests there is a need to regularly validate the indicators using data on current projects.

The use of the TEI indicator for various specific units has the potential to contribute to a more effective use of funds in various regards such as the size of the enclosed area and the number of spectator seats. Figure 1 enables to identify projects which could be modified to bring a higher added value in relation to the investment costs expended for the construction part of the project. This is an important issue if we take into account that developing sport facilities is a risky process requiring complex financial arrangements [18].

This contribution faced a research limitation consisting in a small sample containing data points in different time periods led to the need to index historical prices in relation to the selected base year. With a higher number of representative projects cost-evaluated within a shorter time period, it would potentially be possible to specify a more accurate value of TEI and carry out additional analyses of the costs and selected technical parameters.

Future research should thus focus on a systematic collection of data not only in the category analysed in this contribution, but also regarding other types of construction projects where an activity in the form of validation of publicly available data used for early cost estimation could be valuable.

Acknowledgement

This paper was prepared with the financial support for specific research projects of Brno University of Technology, Faculty of Civil Engineering, specifically project No. FAST-S-19-5954 “Economic and managerial aspects of construction projects” and project No. FAST-J-19-6052 “Business and investment project management in construction”.

References

[1] Plebankiewicz E, Leśniak A, Hromádka V, Vítková E, Kocourková G. Estimating the value of public construction works in Poland and the Czech Republic. Scientific Review Engineering and Environmental Sciences. 2016;25(2):206-19.Search in Google Scholar

[2] Nagy J. Aggregated technical and economic indicators and facilities coefficient in the building industry. Slovak Journal of Civil Engineering. 2012;20(2):8-12.10.2478/v10189-012-0008-5Search in Google Scholar

[3] ÚRS Praha [Internet]. Rychlé ocenění ÚRS (Quick Estimation ÚRS); [cited 2019 May 5]. Available from: https://deksoft.eu/programy/rychleoceneniSearch in Google Scholar

[4] ÚRS Praha a.s. Rozpočtové ukazatele 2018 (Budget Indicators 2018). ÚRS Praha; 2018.Search in Google Scholar

[5] České stavební standardy (Czech Construction Standards) [Internet]. Cenové ukazatele ve stavebnictví pro rok 2018 (Price Indicators in the Construction Sector in 2018); [cited 2019 April 12]. Available from: http://www.stavebnistandardy.cz/doc/ceny/thu_2018.htmlSearch in Google Scholar

[6] Petroutsatou K, Georgopulos E, Lambropoulos S, Pantouvakis JP. Early cost estimating of road tunnel construction using neural networks. J Constr Eng M Asce. 2012;138(6):679-87.10.1061/(ASCE)CO.1943-7862.0000479Search in Google Scholar

[7] Günaydin HM, Dogan SY. A neural network approach for early cost estimation of structural systems of buildings. Int J Proj Manag. 2004;22(7):595-602.10.1016/j.ijproman.2004.04.002Search in Google Scholar

[8] Kim KJ, Kim K, Kang CS. Approximate cost estimating model for PSC beam bridge based on quantity of standard work. KSCE J Civ Eng. 2009;13(6):377-88.10.1007/s12205-009-0377-0Search in Google Scholar

[9] Kim DY, Kim B, Han SH. Two-staged early cost estimation for highway construction projects. Proceedings from the 25th International Symposium on Automation and Robotics in Construction; 2008 Jun 26-29; Vilnius, Lithuania. Vilnius: Vilnius Gediminas Technical University Publishing House; 2008. p. 490-5.10.3846/isarc.20080626.490Search in Google Scholar

[10] Ibadov N, Kulejewski J, Krzemiński M. Fuzzy ordering of the factors affecting the implementation of construction projects in Poland. AIP Conf Proc. 2013;1558:1298-301.10.1063/1.4825749Search in Google Scholar

[11] Czech Statistical Office [Internet]. Ceny výrobců – časové řady (Prices of producers – time series); [cited 2019 May 2]. Available from: https://www.czso.cz/csu/czso/ipc_cr#cspSearch in Google Scholar

[12] Korytarova J, Papezikova P. Assessment of Large-Scale Projects Based on CBA. Procedia Comput Sci. 2015;64:736-743.10.1016/j.procs.2015.08.602Search in Google Scholar

[13] Pavlát J. [Internet]. Paragraph 33. Co je to budova a hala? (What is a building and what is a hall?); [cited 2019 Dec 20]. Available from: http://www.pavlat-znalec.cz/investing/stpr/stpr/stpr06.htmlSearch in Google Scholar

[14] České stavební standardy (Czech Construction Standards) [Internet]. JKSO (Jednotná klasifikace stavebních objektů, Unified Classification of Structural Units); [cited 2019 May 2]. Available from: http://www.stavebnistandardy.cz/thu/jkso.aspSearch in Google Scholar

[15] Act No. 106/1999 Coll., on free access to information.Search in Google Scholar

[16] Ellingerova H, Jankovichova E, Dubek S, Piatka J. Usage analysis of the information systems for valuation of the construction output. Advances and Trends in Engineering Sciences and Technologies III - Proceedings of the 3rd International Conference on Engineering Sciences and Technologies; 2019 Sep 12-14; High Tatras Mountains, Slovakia. USA: CRC Press; 2019. p. 349-55.10.1201/9780429021596-55Search in Google Scholar

[17] Hrstka L. Possibilities of price determination of object for sport and recreation. Final thesis, Brno University of Technology, 2019.Search in Google Scholar

[18] Schwarz EC, Hall SA, Shibli S. Sport Facility Operations Management. Chapter 3 - Financing sport facilities. 1st ed. Taylor & Francis; 2010.10.1016/B978-1-85617-836-5.10001-4Search in Google Scholar

Received: 2019-07-12
Accepted: 2020-04-29
Published Online: 2020-06-05

© 2020 T. Hanak et al., published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 International License.

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https://doi.org/10.1515/eng-2020-0062
Keywords for this article
cost; estimation; indicator; sport facilities
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