View More View Less
  • 1 Kalasalingam Academy of Research and Education, Anand Nagar, Krishnankoil 626126, Tamil Nadu, India
Open access

It is well known that the civil engineering constructions are subjected to cost risk and time overruns. The uncertainties of the cost of construction many times result in disputes among stakeholders. The recent cost fluctuation in sand price in Tamil Nadu is a good example of time and cost overruns. There are too many models developed to predict the cost of construction by using different parameters and tools. The objectives of this research are to analyse the importance of research in this field, the countries focusing on this issue, level of implementation by the practicing engineers, the tools often or successfully used, the difficulties in predicting the cost and the accuracy of prediction and bringing out a useful conclusion to provide the direction for future research. In this research, a sample of 324 research papers out of more than 2000 papers listed in Scopus database between the years 1990 and 2015 were considered and analyzed on five factors. The five factors are 1) authors affiliation – academics, industry or both; 2) country; 3) tools used – ANN, regression, time-series models, etc.; 4) complexity involved or ease of use; 5) accuracy of results. The results show interesting information.

  • [1]

    Elfaki A. O. , Alatawi S., Abushandi E. (2014), Using intelligent techniques in construction project cost estimation: 10-year survey. Advances in Civil Engineering, DOI: 10.1155/2014/107926

    • Search Google Scholar
    • Export Citation
  • [2]

    Jarkas A. M. (2012), Factors affecting construction labor productivity in Kuwait. Journal of Construction Engineering and Management, 138 (7), 811820.

    • Search Google Scholar
    • Export Citation
  • [3]

    An. S-H, Park U.-Y., Kang K.-I., Cho M.-Y., Cho H.-H. (2007), Application of support vector machines in assessing conceptual cost estimates. Journal of Computing in Civil Engineering, 21 (4), 259264.

    • Search Google Scholar
    • Export Citation
  • [4]

    Bromilow F. J. , Hinds M. F., Moody N. F. (1988), The Time and Cost Performance of Building Contracts 1976–1986. Australian Institute of Quantity Surveyors, Sydney, Australia.

    • Search Google Scholar
    • Export Citation
  • [5]

    Chau K. W. (1997), The ranking of construction management journals. Construction Management and Economics, 15 (4), 387398.

  • [6]

    Cheng M.-Y. , Hoang N.-D. (2014), Interval estimation of construction cost at completion using least squares support vector machine. Journal of Civil Engineering and Management, 20 (2), 223236.

    • Search Google Scholar
    • Export Citation
  • [7]

    Cho C. , Edward G. (2001), Building project scope definition using project definition rating index. Journal of Architectural Engineering, 7 (4), 115125.

    • Search Google Scholar
    • Export Citation
  • [8]

    Donyavi S. , Flanagan R. (2009), The impact of effective material management on construction site performance for small and medium-sized construction enterprises. In: Proceedings of the 25th Annual Conference of the Association of Researchers in Construction Management (AR-COM’09), Dainty A. R. J. (ed.), pp. 1120, Association of Researchers in Construction Management, Nottingham, UK, September 2009.

    • Search Google Scholar
    • Export Citation
  • [9]

    Drew D. , Skitmore M., Lo H. P. (2001), The effect of client and type and size of construction work on a contractor's bidding Advances in Civil Engineering strategy. Building and Environment, 36 (3), 393406.

    • Search Google Scholar
    • Export Citation
  • [10]

    Edum-Fotwe F. (2003), Developing benchmarks for project schedule risk estimation,” in System-Based Vision for Strategic and Creative Design. Bontempi F. (ed.), Swets & Zeitlinger, Lisse, The Netherlands

    • Search Google Scholar
    • Export Citation
  • [11]

    Farah Allouche (2017), Euler Hermes Economic Research. Global Sector Report Construction

  • [12]

    Flood I. , Kartam N. (1994), Neural networks in civil engineering principles and understanding. Journal of Computing in Civil Engineering, 8 (2), 131148.

    • Search Google Scholar
    • Export Citation
  • [13]

    Hogg R. , Tannis, E. (2009), Probability and Statistical inferences, 8th Ed., Prentice Hall, Upper Saddle River, NJ.

  • [14]

    Hola B. , Schabowicz K. (2010), Estimation of earthworks execution time cost by means of artificial neural networks. Automation in Construction, 19 (5), 570579.

    • Search Google Scholar
    • Export Citation
  • [15]

    ElSawy I. , Hosny H., Razek M. A. (2011), A neural network model for construction projects site overhead cost estimating in Egypt. International Journal of Computer Science Issues, 3 (1), 273283.

    • Search Google Scholar
    • Export Citation
  • [16]

    Jafarzadeh R. , Ingham J. M., Wilkinson S., González V., Aghakouchak A. A. (2014), Application of artificial neural network methodology for predicting seismic retrofit construction costs. Journal of Construction Engineering and Management, 140 (2), Article ID04013044, DOI: 10.1061/(ASCE)CO.1943-7862.0000725.

    • Search Google Scholar
    • Export Citation
  • [17]

    Ji S. H , Park M., Lee H.-S. (2012), Case adaptation method of case-based reasoning for construction cost estimation in Korea. Journal of Construction Engineering and Management, 138 (1), 4352.

    • Search Google Scholar
    • Export Citation
  • [18]

    Martin J. , Burrows T., Pegg I. (2006), Predicting Construction Duration of Building Projects”, TS 28 – Construction Economics I, October 813, 2006.

    • Search Google Scholar
    • Export Citation
  • [19]

    Chambers J. C. , Mullick S. K., Smith D. D. (1971), How to choose the Right forecasting techniques. Harward Business Review.

  • [20]

    Kaka A. P. , Price A. D. F. (1991), Relationship between value and duration of construction projects. Construction Management and Economics, 9 (4), 383400.

    • Search Google Scholar
    • Export Citation
  • [21]

    Kothari C. R. Research Methodology methods and Techniques. New Age International (P) Limited Publishers, p. 11.

  • [22]

    Kim K. J. , Kim K. M. (2010), Preliminary cost estimation model using case-based reasoning and genetic algorithms. Journal of Computing Civil Engineering, 24 (6), 499505. DOI: 10.1061/(ASCE)CP.1943-5487.0000054.

    • Search Google Scholar
    • Export Citation
  • [23]

    Mahamid I. (2011), Early cost estimating for road construction projects using multiple regression techniques. Australasian Journal of Construction Economics and Building, 11 (4), 87101.

    • Search Google Scholar
    • Export Citation
  • [24]

    Petroutsatou K. , Georgopoulos E., Lambropoulos S., Pantouvakis J. P. (2012), Early cost estimating of road tunnel construction using neural networks. Journal of Construction Engineering and Management, 138 (6), 679687.

    • Search Google Scholar
    • Export Citation
  • [25]

    Hwang S. (2011), Time series models for forecasting construction costs using time series indexes. J. Constr. Eng. Managem., 137 (9), 656662.

    • Search Google Scholar
    • Export Citation
  • [26]

    Sincich T. , Levine D. M., Stephan D. (2002), Practical Statistics by Example Using Microsoft Excel and Minitab. 2nd ed., Prentice Hall, Upper Saddle River, NJ.

    • Search Google Scholar
    • Export Citation
  • [27]

    Smith A. J. (1995), Estimating, Tendering and Bidding for Construction: Theory and Practice, Macmillan, London.

  • [28]

    Son H. , Kim C., Kim C. (2012), Hybrid principal component analysis and support vector machine model for predicting the cost performance of commercial building projects using pre-project planning variables. Automation in Construction, 27, 6066.

    • Search Google Scholar
    • Export Citation
  • [29]

    Tysoe B. A. (1981), Construction Cost and Price Indices: Description and Use. E & FN Spon, London.

  • [30]

    Wilmot C. G. , Mei B. (2005), Neural network modeling of highway construction costs. Journal of Construction Engineering and Management, 131 (7), 765771.

    • Search Google Scholar
    • Export Citation
The author instruction is available in PDF.
Please, download the file from HERE.
Submit Your Manuscript
 

Senior editors

Editor-in-Chief: Ákos, Lakatos

Founder, former Editor-in-Chief (2011-2020): Ferenc Kalmár

Founding Editor: György Csomós

Associate Editor: Derek Clements Croome

Associate Editor: Dezső Beke

Editorial Board

  • M. N. Ahmad, Institute of Visual Informatics, Universiti Kebangsaan Malaysia, Malaysia
  • M. Bakirov, Center for Materials and Lifetime Management Ltd., Moscow, Russia
  • N. Balc, Technical University of Cluj-Napoca, Cluj-Napoca, Romania
  • U. Berardi, Ryerson University, Toronto, Canada
  • I. Bodnár, University of Debrecen, Debrecen, Hungary
  • S. Bodzás, University of Debrecen, Debrecen, Hungary
  • F. Botsali, Selçuk University, Konya, Turkey
  • S. Brunner, Empa - Swiss Federal Laboratories for Materials Science and Technology
  • I. Budai, University of Debrecen, Debrecen, Hungary
  • C. Bungau, University of Oradea, Oradea, Romania
  • M. De Carli, University of Padua, Padua, Italy
  • R. Cerny, Czech Technical University in Prague, Czech Republic
  • Gy. Csomós, University of Debrecen, Debrecen, Hungary
  • T. Csoknyai, Budapest University of Technology and Economics, Budapest, Hungary
  • G. Eugen, University of Oradea, Oradea, Romania
  • J. Finta, University of Pécs, Pécs, Hungary
  • A. Gacsadi, University of Oradea, Oradea, Romania
  • E. A. Grulke, University of Kentucky, Lexington, United States
  • J. Grum, University of Ljubljana, Ljubljana, Slovenia
  • G. Husi, University of Debrecen, Debrecen, Hungary
  • G. A. Husseini, American University of Sharjah, Sharjah, United Arab Emirates
  • N. Ivanov, Peter the Great St.Petersburg Polytechnic University, St. Petersburg, Russia
  • A. Járai, Eötvös Loránd University, Budapest, Hungary
  • G. Jóhannesson, The National Energy Authority of Iceland, Reykjavik, Iceland
  • L. Kajtár, Budapest University of Technology and Economics, Budapest, Hungary
  • F. Kalmár, University of Debrecen, Debrecen, Hungary
  • T. Kalmár, University of Debrecen, Debrecen, Hungary
  • M. Kalousek, Brno University of Technology, Brno, Czech Republik
  • J. Koci, Czech Technical University in Prague, Prague, Czech Republic
  • V. Koci, Czech Technical University in Prague, Prague, Czech Republic
  • I. Kocsis, University of Debrecen, Debrecen, Hungary
  • I. Kovács, University of Debrecen, Debrecen, Hungary
  • É. Lovra, Univesity of Debrecen, Debrecen, Hungary
  • T. Mankovits, University of Debrecen, Debrecen, Hungary
  • I. Medved, Slovak Technical University in Bratislava, Bratislava, Slovakia
  • L. Moga, Technical University of Cluj-Napoca, Cluj-Napoca, Romania
  • M. Molinari, Royal Institute of Technology, Stockholm, Sweden
  • H. Moravcikova, Slovak Academy of Sciences, Bratislava, Slovakia
  • P. Mukhophadyaya, University of Victoria, Victoria, Canada
  • H. S. Najm, Rutgers University, New Brunswick, United States
  • J. Nyers, Subotica Tech - College of Applied Sciences, Subotica, Serbia
  • B. W. Olesen, Technical University of Denmark, Lyngby, Denmark
  • S. Oniga, North University of Baia Mare, Baia Mare, Romania
  • J. N. Pires, Universidade de Coimbra, Coimbra, Portugal
  • L. Pokorádi, Óbuda University, Budapest, Hungary
  • A. Puhl, University of Debrecen, Debrecen, Hungary
  • R. Rabenseifer, Slovak University of Technology in Bratislava, Bratislava, Slovak Republik
  • M. Salah, Hashemite University, Zarqua, Jordan
  • D. Schmidt, Fraunhofer Institute for Wind Energy and Energy System Technology IWES, Kassel, Germany
  • L. Szabó, Technical University of Cluj-Napoca, Cluj-Napoca, Romania
  • Cs. Szász, Technical University of Cluj-Napoca, Cluj-Napoca, Romania
  • J. Száva, Transylvania University of Brasov, Brasov, Romania
  • P. Szemes, University of Debrecen, Debrecen, Hungary
  • E. Szűcs, University of Debrecen, Debrecen, Hungary
  • R. Tarca, University of Oradea, Oradea, Romania
  • Zs. Tiba, University of Debrecen, Debrecen, Hungary
  • L. Tóth, University of Debrecen, Debrecen, Hungary
  • A. Trnik, Constantine the Philosopher University in Nitra, Nitra, Slovakia
  • I. Uzmay, Erciyes University, Kayseri, Turkey
  • T. Vesselényi, University of Oradea, Oradea, Romania
  • N. S. Vyas, Indian Institute of Technology, Kanpur, India
  • D. White, The University of Adelaide, Adelaide, Australia
  • S. Yildirim, Erciyes University, Kayseri, Turkey

International Review of Applied Sciences and Engineering
Address of the institute: Faculty of Engineering, University of Debrecen
H-4028 Debrecen, Ótemető u. 2-4. Hungary
Email: irase@eng.unideb.hu

Indexing and Abstracting Services:

  • DOAJ
  • Google Scholar
  • ProQuest
  • SCOPUS
  • Ulrich's Periodicals Directory

 

2020  
Scimago
H-index
5
Scimago
Journal Rank
0,165
Scimago
Quartile Score
Engineering (miscellaneous) Q3
Environmental Engineering Q4
Information Systems Q4
Management Science and Operations Research Q4
Materials Science (miscellaneous) Q4
Scopus
Cite Score
102/116=0,9
Scopus
Cite Score Rank
General Engineering 205/297 (Q3)
Environmental Engineering 107/146 (Q3)
Information Systems 269/329 (Q4)
Management Science and Operations Research 139/166 (Q4)
Materials Science (miscellaneous) 64/98 (Q3)
Scopus
SNIP
0,26
Scopus
Cites
57
Scopus
Documents
36
Days from submission to acceptance 84
Days from acceptance to publication 348
Acceptance
Rate

23%

 

2019  
Scimago
H-index
4
Scimago
Journal Rank
0,229
Scimago
Quartile Score
Engineering (miscellaneous) Q2
Environmental Engineering Q3
Information Systems Q3
Management Science and Operations Research Q4
Materials Science (miscellaneous) Q3
Scopus
Cite Score
46/81=0,6
Scopus
Cite Score Rank
General Engineering 227/299 (Q4)
Environmental Engineering 107/132 (Q4)
Information Systems 259/300 (Q4)
Management Science and Operations Research 136/161 (Q4)
Materials Science (miscellaneous) 60/86 (Q3)
Scopus
SNIP
0,866
Scopus
Cites
35
Scopus
Documents
47
Acceptance
Rate
21%

 

International Review of Applied Sciences and Engineering
Publication Model Gold Open Access
Submission Fee none
Article Processing Charge 1100 EUR/article
Regional discounts on country of the funding agency World Bank Lower-middle-income economies: 50%
World Bank Low-income economies: 100%
Further Discounts Limited number of full waiver available. Editorial Board / Advisory Board members: 50%
Corresponding authors, affiliated to an EISZ member institution subscribing to the journal package of Akadémiai Kiadó: 100%
Subscription Information Gold Open Access
Purchase per Title  

International Review of Applied Sciences and Engineering
Language English
Size A4
Year of
Foundation
2010
Publication
Programme
2021 Volume 12
Volumes
per Year
1
Issues
per Year
3
Founder Debreceni Egyetem
Founder's
Address
H-4032 Debrecen, Hungary Egyetem tér 1
Publisher Akadémiai Kiadó
Publisher's
Address
H-1117 Budapest, Hungary 1516 Budapest, PO Box 245.
Responsible
Publisher
Chief Executive Officer, Akadémiai Kiadó
ISSN 2062-0810 (Print)
ISSN 2063-4269 (Online)

Monthly Content Usage

Abstract Views Full Text Views PDF Downloads
Feb 2021 0 8 22
Mar 2021 0 13 20
Apr 2021 0 18 13
May 2021 0 11 15
Jun 2021 0 4 20
Jul 2021 0 10 17
Aug 2021 0 0 0