APPLICATION OF TIME-COST MODEL IN CONSTRUCTION PROJECT MANAGEMENT

Transcription

1 APPLICATION OF TIME-COST MODEL IN CONSTRUCTION PROJECT MANAGEMENT Vahida Žujo *, Diana Car- ABSTRACT Time-cost model for rapid estimation of construction time appeared in the world some fifty years ago. One of model characteristics is limitation of its application solely to the research area due to economic and other differences. In this paper it is presented a construction time estimation method for building construction in the area of Federation of Bosnia and Herzegovina. The suggested model is applicable in conditions when it is not expected more intensive influence of risk factors than usual. The model is tested using a database of eight building construction projects completed in the area of Herzegovina in the period from Key words: time, cost, contracted, actual, estimate, indicators, models 1. Introduction Current practice indicates that overrun of contracted construction schedules poses a great problem. Many scientific researches confirm this thesis [1, 3]. Awareness of this problem is present in both construction practice and scientific circles. A number of researchers have dealt with this problem in their works. [11, 13]. Time cost model was developed in the sixties of the last century by Australian researcher Bromilow aiming to provide the most accurate construction time estimation possible in early project phases. [2]. The model was defined as a function of construction cost and therefore it is reasonable limitation of its application to the area of research only. After initial research, credibility of this model was later confirmed on many occasions in Great Britain, China, Texas, Malaysia, Croatia etc.[9, 4, 6, 5, 3]. Time-consuming lawsuits between investor and contractor often drag on for years and their main subject is unjustified overrun of contracted schedule. Project actors usually estimate construction time using the lump-sum method and without taking into account real performance possibilities within the given deadline. Taking into account all above mentioned and aiming to reduce the problem, it can be said there is a real need to define mathematical models for rapid construction time estimation also for the area of Bosnia and Herzegovina. * Faculty of Civil Engineering University Džemal in Mostar, BiH, bb Sjeverni logor, Mostar, BIH, vahida.zujo@unmo.ba Doc. dr. sc. Diana Car- Faculty of Civil Engineering University in Rijeka, 5 Viktora Cara Emina, Rijeka, HR, dipusic@inet.hr

2 2. Databases The subject of research are building construction objects constructed in the period from in the Federation of Bosnia and Herzegovina. Collection of data was performed by the method of survey and interviewing of engineers-in-charge in construction companies. The data were collected for the total of 53 building construction objects divided in two groups: 1. New construction 29 buildings 2. Reconstruction 24 buildings In tables 1 and 2 are shown data collected in the field by calculating basic statistical indicators. When it comes to new construction buildings, it was noticed overrun of contracted schedule in average higher than 14, 80%, and simultaneous overruns of contracted schedule and contracted cost 25, 29% higher than those calculated for reconstruction buildings. Table 1. Database with statistical indicators for building construction objects new construction Object Year of constr uctio n. Construction time actual contract ed Differ ence Construction cost [ KM ] Overruns [%] contracted actual time cost , , ,67 20, , , ,34 10, , , ,44 6, , , ,00 7, , , ,11-9, , , ,00-9, , , ,33 14, , , ,00 0, , , ,00 0, , , ,00 0, , , ,00 0, , , ,00 0, , , ,34 4, , , ,78 11, , , ,82 0, , , ,00 0, , , ,00 0, , , ,00 0, , , ,00 0, , , ,50 4, , , ,67 15, , , ,22 7, , , ,56 6, , , ,19 23, , , ,76 29, , , ,67 13, , , ,00 9, , , ,11 13,22 Konvertible Mark BiH currency

3 , , ,33 2,22 Average 11,55 6,84 Median 10,00 6,33 Minimum -10,00-9,09 Maximum 46,67 29,16 First quartile 0,00 0,00 Third 16,67 11,00 quartile Interquartile 16,67 11,00 dev. Stand.dev. 13,30 8,41 Variance 176,92 70,78 Table 2. Database with statistical indicators for building construction objects - reconstruction Obje ct Year of construc Construction time Construction cost [ KM] Overruns [%] tion contract Actua Differ contracted actual time cost ed l ence , , ,11 0, , , , , , ,00 26, , , ,00 34, , , ,50 68, , , ,28 9, , , ,00 0, , , ,56 14, , , ,00 0, , , ,48 25, , , ,48 7, , , ,00 13, , , ,00 8, , , ,00 0, , , ,00 0, , , ,00 0, , , ,00 0, , , ,00 0, , , ,00 6, , , ,34 2, , , ,66 2, , , ,33 0, , , ,00 0, , , ,00 0,00 Average 21,36 9,23 Median 0,00 1,37 Minimum -16,66 0,00 Maximum 150,00 68,57 First quartile 0,00 0,00 Third quartil 17,83 10,77 Interqu. dev 17,83 10,77 Stand.dev. 46,71 16,02 variance 2182,15 256,80

4 3. Estimation of construction time Development of model for construction time estimation T is based on application of Bromilow time-cost model where: T = K*C B C construction cost K indicator of necessary average construction time for unit value of money B indicator showing that change in construction time is dependant on change in construction cost This connotes defining of indicators K and B using logarithmic transformation of exponential equation in a linear form ln T = ln K + B* ln C Using known methodology [2, 3, 8, 10] and with assistance of one of computer programs, the main indicators of single linear regression are determined with previously performed revalorisation of contracted and actual costs related to discussed time period i.e. V/07 [7]. By visual diagram evaluation lnt-lnc it was established that certain objects significantly impair good sides of linear approximation. Aiming to get higher correlation and determination coefficients, it was repeated the linear regression procedure with reduced samples by excluding the objects with ordinal numbers 3, 6, 8 and 14 from the group 1, and the objects with ordinal numbers 32 and 33 from the group 2. In the table 3 was given a parallel review of linear regression data for entire and reduced sample. Table 3. Indicators of linear regression on entire and reduced sample Group of ENTIRE SAMPLE REDUCED SAMPLE objects Indicator Contracted Actual values Contracted Actual values values values New R 0,579 0,621 0,829 0,860 construction R 2 0,336 0,386 0,688 0,739 AR 2 0,311 0,363 0,674 0,728 reconstruction R 0,835 0,717 0,856 0,848 R 2 0,698 0,514 0,732 0,719 AR 2 0,684 0,491 0,719 0,705 R R 2 AR 2 coefficient of correlation coefficient of determination corrected coefficient of determination The model is evaluated as suitable and regression equations are accepted. In this work it was used SPSS9 computer program

5 1. For new construction buildings T = 70*C 0,52 2. For reconstruction buildings T = 79*C 0,41 where C is expressed in KM. Obtained results indicate that in average 70 working days will be necessary for construction of a new building whose value is KM, and 79 working days will be necessary for reconstruction of building. 4. Application of calculated results on new database New models were tested on new database with the total of 8 building construction objects and for only one was noticed significant deviation shown in the table 4. The other results are estimated as satisfactory. Object number 5 has a deviation of 49% and this can be explained by the fact that a maximum contracted cost in the main database for new construction building objects is 2, KM, which is 2,27 times less that contracted cost of above mentioned object. Table 4. Results of application of models on new database No. Object, location, year of construction 1 Elementary school, new construction, Šuškovo selo, Stolac Munic Secondary school, reconstruction, Sjeverni logor, Mostar, Public institution Konak, reconstruction, Mostar, Building construction objects reconstruction, Municipality, Business-Residential building Dolina sunca, new const, Mostar, Business building MIK, new const, Mostar, Secondary grammar school, reconstruction, Mostar, Business-Residential building Mukoša, reconstruction, Mostar, Contracted cost [KM] Actual time T OS Estimated time T = 70*C 0,52 T = 79*C 0,41 T/ T OS , , , , , , , , , , , , , , , ,97

6 5. Analyses and comparison with international results In comparison with available international results [12, 9, 5, 4, 3], the value of obtained indicator K is higher, which indicates smaller productivity in the Federation of Bosnia and Herzegovina. In Croatia, for example, obtained data shows that a project whose value is one million of Croatian Kuna ** can be completed in 79 days, while calculated data in this work shows that working days are necessary for realization of project whose value is KM. [3]. In other words, it means that construction of the same building in the Federation of Bosnia and Herzegovina is in average approx. 2,5 times longer than in Croatia. In Croatia, indicator B for the building construction objects is 0,60, meaning there is somewhat greater influence of project complexity on time prolongation. In general, the past researches have also showed that indicator K can greatly change depending on economical circumstances, while B is within the range of approx. 0,40-0, Conclusion After being confirmed many times in the world, it is important to point out that the credibility of Bromilow time-cost model was proved also for the area of BiH. This is just the first research of this kind and it only presents an introduction to further researches in defining models for rapid estimation of construction time. Obtained mathematical models are applicable only to the area of Federation of BiH in conditions without real assumption on potential occurrence and negative influence of risk factors. REFERENCES [1] Annual Review of Project Performance Results, Operational Evaluation Department, World Bank, [2] Bromilow, F. J. (1969). Contract time performance expectations and the reality, Building Forum 1(3), pp [3] Car Planning methodology for sustainable construction time, PhD thesis, Faculty of civil engineering, Zagreb [4] Chan, D. W.M. and Kumaraswamy, M. M. A study of the factors affecting construction duration in Hong Kong. Construction management and Economics, 13(4), 1995, pp [5] Chan, A. P.C. (1999). Time cost relationship of public sector projects in Malaysia. International Journal of Project Management, 19, pp ** HRkn is approx KM

7 [6] Choudhry, I., and Rajan, S.S.., Time cost relationship for residential construction in Texas, Texas A$M University, College Station [7] Federal office of statistics. Monthly statistical review F BiH, Sarajevo, May [8] Johnson, A., Bhattacharyya, G.K., Statistics: Principles and Methods, University of Wisconsin at Madison, [9] Kaka, A., & Price, A.D.F.. Relationship between value and duration of construction projects. Construction Management and Economics, 9, 1991, pp [10] Pauše, Ž., Introduction to mathematical statistics, Školska knjiga Zagreb, Management of risk and resources in construction projects, scientific research project MZITRH, , Faculty of civil engineering, University in Zagreb [12] Skitmor, R. M. And Ng. T. Australian project time - cost analysis: statistical analysis of intertemporal trends. Construction Management and Economics 19 (5), 2001, pp [13] Thompson, P. A., Perry, J. G., Engineering Construction Risks, Thomas Teiford, London, 1992.