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Book Chapter

A Systematic Literature Review to Identify a Methodological Approach for Use in the Modelling and Forecasting of Capital Expenditure of Hyperscale Data Centres

  • David King
  • Nadeeshani Wanigarathna
  • Keith Jones
  • Joseph Ofori-Kuragu

The theme of ‘Managing the digital transformation of the construction industry’ emphasises the importance of considering various dimensions of digitalisation and optimising the built environment. This review aims to present methodological approaches from existing literature that elucidate location-related factors impacting the capital cost of data centres. These findings facilitate adjustments to historical cost data when estimating total costs for new data centres. A systematic literature review method was employed to ensure an objective and comprehensive synthesis. In conjunction with Bayes's theory, this review identifies that a Delphi methodology is the most suitable methodological approach for forecasting and modelling capital expenditure for hyper-scale data centres. The methodology enables collective decision-making and consensus building, recognising the stakeholder's pivotal role in shaping the future of data centres. These findings offer valuable insights for researchers and practitioners in forming a methodological approach for further investigations into the location-related factors impacting the capital cost of data centres. Embracing this knowledge allows us to align research and practice, ensuring that these practices become integral to shaping the future of data centres and the digitalisation and optimisation of the built environment

  • Keywords:
  • cost; decision analysis; forecasting,
  • data centres,
+ Show More

David King

Anglia Ruskin University, United Kingdom - ORCID: 0000-0002-8026-3796

Nadeeshani Wanigarathna

Anglia Ruskin University, United Kingdom - ORCID: 0000-0001-8889-8019

Keith Jones

Anglia Ruskin University, United Kingdom - ORCID: 0000-0002-8883-9673

Joseph Ofori-Kuragu

Anglia Ruskin University, United Kingdom - ORCID: 0000-0003-2872-9437

  1. Baloi, D., & Price, A. D. (2003). Modelling global risk factors affecting construction cost performance.
  2. International journal of project management, 21(4), 261–269. (Publisher: Elsevier) DOI: 10.1016/s0263-7863(02)00017-0
  3. Bayes, T. (1763). An essay towards solving a problem in the doctrine of chances. By the late Rev. Mr. Bayes, FRS communicated by Mr. Price, in a letter to John Canton, AMFR S. Philosophical transactions of the Royal Society of London(53), 370–418. https://royalsocietypublishing.org/doi/pdf/10.1098/rstl.1763.0053?fbclid=IwAR1J7hCd54nKa6d3ULOo2yMA1j7vVuUtS3qguqUUhHNcAqOb8rufrjZijog
  4. Blackhall, K. (2007). Finding studies for inclusion in systematic reviews of interventions for injury prevention–the importance of grey and unpublished literature. Injury Prevention, 13(5), 359. DOI: 10.1136/ip.2007.017020
  5. Brauers, W. K. M. (2018). Location theory and multi-criteria decision making: An application of the MOORA method. Contemporary Economics, 12(3). https://repository.uantwerpen.be/docman/irua/248cd8/154774.pdf DOI: 10.5709/ce.1897-9254.275
  6. Broomfield, D., & Humphris, G. M. (2001). Using the Delphi technique to identify the cancer education requirements of general practitioners. Medical education, 35(10), 928–937. DOI: 10.1111/j.1365-2923.2001.01022.x
  7. Brown, S. (1993). Retail location theory: evolution and evaluation. International Review of Retail, Distribution and Consumer Research, 3(2), 185–229. (Publisher: Taylor & Francis) DOI: 10.1080/09593969300000014
  8. Campbell, S. M., Shield, T., Rogers, A., & Gask, L. (2004). How do stakeholder groups vary in a Delphi technique about primary mental health care, and what factors influence their ratings? BMJ Quality & Safety, 13(6), 428–434. DOI: 10.1136/qshc.2003.007815
  9. Crisp, J., Pelletier, D., Duffield, C., Adams, A., & Nagy, S. U. E. (1997). The Delphi method? Nursing Research, 46(2), 116–118. DOI: 10.1097/00006199-199703000-00010
  10. Daniels, R., & Mulley, C. (2012). Planning public transport networks—the neglected influence of topography. Journal of Public Transportation, 15(4), 23–41. (Publisher: Elsevier) DOI: 10.5038/2375-0901.15.4.2
  11. Fazil, M. W., Lee, C. K., & Tamyez, P. F. M. (2021). Cost estimation performance in the construction projects: A systematic review and future directions. International Journal of Industrial Management, 11 DOI: 10.15282/ijim.11.1.2021.6131
  12. Greenhalgh, T., Robert, G., Macfarlane, F., Bate, P., Kyriakidou, O., & Peacock, R. (2005). Storylines of research in diffusion of innovation: a meta-narrative approach to systematic review. Social science & medicine, 61(2), 417–430. DOI: 10.1016/j.socscimed.2004.12.001
  13. Gunaydin, H. M., & Do¨ gan, S. Z. (2004). A neural network approach for early cost estimation of structuralˇ systems of buildings. International Journal of Project Management, 22(7), 595–602. DOI: 10.1016/j.ijproman.2004.04.002
  14. Hashemi, S. T., Ebadati, O. M., & Kaur, H. (2020). Cost estimation and prediction in construction projects: a systematic review on machine learning techniques. (Issue: 10 Publication Title: SN Applied Sciences Volume: 2) DOI: 10.1007/s42452-020-03497-1
  15. Hasson, F., Keeney, S., & McKenna, H. (2000). Research guidelines for the Delphi survey technique. Journal of advanced nursing, 32(4), 1008–1015. (Publisher: Wiley Online Library) DOI: 10.1046/j.1365-2648.2000.01567.x
  16. Hsu, C.-C., & Sandford, B. A. (2007). The Delphi technique: making sense of consensus. Practical assessment, research, and evaluation, 12(1), 10. http://www.dator8.info/pdf/DELPHI/9.pdf
  17. Kerin, R. A., & Harvey, M. (1975). Evaluation of retail store locations through profitability analysis. Journal of Small Business Management (pre-1986), 13(000001), 41. (Publisher: Taylor & Francis Ltd.) https://www.idosr.org/wp-content/uploads/2021/07/IDOSR-JAH-61-22-29-2021..pdf
  18. Kheybari, S., Monfared, M. D., Farazmand, H., & Rezaei, J. (2020). Sustainable Location Selection of Data Centers: Developing a Multi-Criteria Set-Covering Decision-Making Methodology. International journal of information technology & decision making, 19(3). DOI: 10.1142/s0219622020500157
  19. King, D., Wanigarathna, N., Jones, K., & Ofori-Kuragu, J. (2023). A Delphi Pilot Study to Assess the Impact of Location Factors for Hyperscale Data Centres. In G. Lindahl & S. C. Gottlieb (Eds.), SDGs in Construction Economics and Organization (pp. 153–164). Cham: Springer International Publishing. DOI: 10.1007/978-3-031-25498-7_11
  20. Klimczak, K. (2010). Determinants of real estate investment. Economics and Sociology, 3(2), 58–66. https://www.economics-sociology.eu/files/07[7].pdf
  21. Line, C. D. O. (2008). Richardson international construction factors manual. Pahrump, NV. https://www.worldcat.org/title/richardsons-international-construction-factors-location-cost-manual/oclc/37036718
  22. Lowe, S. D., Kirchner, H., Carswell, G., Black, B., Computing, A., Green, J., & Davis, D. (2016). Building a Modern Data Center Principles and Strategies of Design. ActualTech Marketing, LLC. Retrieved https://books.google.co.uk/books?id=si2ljwEACAAJ
  23. Mahood, Q., Eerd, D. V., & Irvin, E. (2014). Searching for grey literature for systematic reviews: challenges and benefits. Research synthesis methods, 5(3), 221–234. DOI: 10.1002/jrsm.1106
  24. McAuley, L., Pham, B., Tugwell, P., & Moher, D. (2000). Does the inclusion of grey literature influence estimates of intervention effectiveness reported in meta-analyses? The Lancet, 356(9237), 1228–1231. DOI: 10.1016/s0140-6736(00)02786-0
  25. McInnes, M. D., Moher, D., Thombs, B. D., McGrath, T. A., Bossuyt, P. M., Clifford, T., ... Hooft, L. (2018). Preferred reporting items for a systematic review and meta-analysis of diagnostic test accuracy studies: the PRISMA-DTA statement. Jama, 319(4), 388–396. (Publisher: American Medical Association) https://jamanetwork.com/journals/jama/article-abstract/2670259
  26. Parameswaran, T., Jayawickrama, T. S., & Melagoda, D. G. (2019). Analysing the impact of location factors on building construction cost in Sri Lanka. In (Vol. 2019). http://ieomsociety.org/ieom2019/papers/622.pdf
  27. Rashid, E. (2017). Construction cost prediction on the basis of multiple parameters using case-based reasoning method. International Journal of Services Technology and Management, 23(4), 255–261. DOI: 10.1504/ijstm.2017.088155
  28. RICS. (2013). Cost analysis and benchmarking (Tech. Rep.). Royal Institution of Chartered Surveyors. https://www.isurv.com/downloads/download/1388/cost_analysis_and_benchmarking_%E2%80%93_uk_archived
  29. RICS. (2018). BCIS Online. Retrieved 2023-04-09, from https://service.bcis.co.uk/BCISOnline/Account/LogOn?ReturnUrl=%2fBCISOnline%2f
  30. Sharkey, S. B., & Sharples, A. Y. (2001). An approach to consensus building using the Delphi technique: developing a learning resource in mental health. Nurse education today, 21(5), 398–408. DOI: 10.1054/nedt.2001.0573
  31. 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, 60–66. (Publisher: Elsevier) DOI: 10.1016/j.autcon.2012.05.013
  32. Suarez-Almazor, M. E., Belseck, E., Homik, J., Dorgan, M., & Ramos-Remus, C. (2000). Identifying clinical trials in the medical literature with electronic databases: MEDLINE alone is not enough. Controlled clinical trials, 21(5), 476–487. DOI: 10.1016/S0197-2456(00)00067-2
  33. Tricco, A. C., Lillie, E., Zarin, W., K, K. O., Colquhoun, H., Levac, D., ... Straus, S. E. (2018). PRISMA Extension for Scoping Reviews (PRISMA-ScR) : Checklist and Explanation. Annals of Internal Medicine Volume, 169(7), 467–473 DOI: 10.7326/M18-0850
  34. Turoff, M., & Linstone, H. A. (2002). The Delphi method techniques and applications. DOI: 10.2307/1268751
  35. F. Yang and L. X. Ye, "Method of Locating Data Center Based on Delphi," 2011 Second International Conference on Innovations in Bio-inspired Computing and Applications, Shenzhen, China, 2011, pp. 299-302. DOI: 10.1109/ibica.2011.79
  36. Zhang, G. P. (2003). Time series forecasting using a hybrid ARIMA and neural network model. Neurocomputing, 50, 159–175. (Publisher: Elsevier) DOI: 10.1016/s0925-2312(01)00702-0
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  • Publication Year: 2023
  • Pages: 380-387

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  • Publication Year: 2023

Chapter Information

Chapter Title

A Systematic Literature Review to Identify a Methodological Approach for Use in the Modelling and Forecasting of Capital Expenditure of Hyperscale Data Centres

Authors

David King, Nadeeshani Wanigarathna, Keith Jones, Joseph Ofori-Kuragu

DOI

10.36253/979-12-215-0289-3.37

Peer Reviewed

Publication Year

2023

Copyright Information

© 2023 Author(s)

Content License

CC BY-NC 4.0

Metadata License

CC0 1.0

Bibliographic Information

Book Title

CONVR 2023 - Proceedings of the 23rd International Conference on Construction Applications of Virtual Reality

Book Subtitle

Managing the Digital Transformation of Construction Industry

Editors

Pietro Capone, Vito Getuli, Farzad Pour Rahimian, Nashwan Dawood, Alessandro Bruttini, Tommaso Sorbi

Peer Reviewed

Publication Year

2023

Copyright Information

© 2023 Author(s)

Content License

CC BY-NC 4.0

Metadata License

CC0 1.0

Publisher Name

Firenze University Press

DOI

10.36253/979-12-215-0289-3

eISBN (pdf)

979-12-215-0289-3

eISBN (xml)

979-12-215-0257-2

Series Title

Proceedings e report

Series ISSN

2704-601X

Series E-ISSN

2704-5846

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