Skip to main content

Advertisement

Log in

Vietnamese real estate corporations’ performance using the hybrid model of data envelopment analysis and grey system theory

  • Original Article
  • Published:
Neural Computing and Applications Aims and scope Submit manuscript

Abstract

Real estate is believed to grow even stronger in the next few years in Vietnam, so this study is conducted to closely monitor market changes and provide updated findings about this field. However, with such an asset and capital-intensive industry, it is necessary for investors understanding companies' operation efficiency besides their stocks indicators. The paper looks into operation of real estate corporation with highest market capitalization and ranks their performance efficiency using the data envelopment analysis. This study gives a better “past–present–future” insights for decision makers. The findings indicate that the real estate market will continue its upward trend in the next few years. For the policymakers, this study will help short-term development strategies. For companies with low forecasting shown by grey forecasting, they need to apply new projects and methods in their operations and business model to make more progress in the future. In the view of the investors, this research can be used as a source of information in business assessments and investment decisions.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1

Similar content being viewed by others

Explore related subjects

Discover the latest articles and news from researchers in related subjects, suggested using machine learning.

References

  1. Ahmed AA, Mohamad A (2017) Data envelopment analysis of efficiency of real estate investment trusts in Singapore. Int J Law Manag 59(6):826–838. https://doi.org/10.1108/IJLMA-06-2016-0058

    Article  Google Scholar 

  2. Anderson RI, Fok R, Springer T, Webb J (2002) Technical efficiency and economies of scale: a non-parametric analysis of REIT operating efficiency. Eur J Oper Res 139(3):598–612

    Article  Google Scholar 

  3. Animasaun IL, Ibraheem RO, Mahanthesh B, Babatunde HA (2019) A meta-analysis on the effects of haphazard motion of tiny/nano-sized particles on the dynamics and other physical properties of some fluids. Chin J Phys 60:676–687

    Article  MathSciNet  Google Scholar 

  4. Bers M, Springer T (1997) Economies-of-scale for real estate investment trusts. J Real Estate Res 14(3):275–291

    Article  Google Scholar 

  5. Charnes A, Cooper WW, Rhodes E (1978) Measuring the efficiency of decision making units. Eur J Oper Res 2(6):429–444

    Article  MathSciNet  Google Scholar 

  6. Chen Q, Li F (2017) Empirical analysis on efficiency of listed real estate companies in China by DEA. iBusiness 9(03):49

    Article  Google Scholar 

  7. Chen YS, Chen BY (2011) Applying DEA, MPI, and grey model to explore the operation performance of the Taiwanese wafer fabrication industry. Technol Forecast Soc Change 78(3):536–546

    Article  Google Scholar 

  8. Cook WD, Tone K, Zhu J (2014) Data envelopment analysis: Prior to choosing a model. Omega 44:1–4

    Article  Google Scholar 

  9. Deng J-L (1982) Control problem of grey systems. Syst Control Lett 1(5):288–294

    Article  MathSciNet  Google Scholar 

  10. Farrell MJ (1957) The measurement of productive efficiency. J R Stat Soc Ser A (Gen) 120(3):253–281

    Article  Google Scholar 

  11. Harun SL, Tahir HM, Zaharudin ZA (2012) Measuring efficiency of real estate investment trust using data envelopment analysis approach. In: The fifth foundation of islamic finance conference, pp 1–12. https://www.academia.edu/download/32681284/siti_latipah_measuring_efficiency_of_real_estate_investment.pdf

  12. Kuo Y, Yang T, Huang GW (2008) The use of grey relational analysis in solving multiple attribute decision-making problems. Comput Ind Eng 55(1):80–93

    Article  Google Scholar 

  13. Koriko OK, Adegbie KS, Shah NA, Animasaun IL, Olotu MA (2021) Numerical solutions of the partial differential equations for investigating the significance of partial slip due to lateral velocity and viscous dissipation: the case of blood-gold Carreau nanofluid and dusty fluid. Numer Methods Partial Differ Equ. https://doi.org/10.1002/num.22754

    Article  Google Scholar 

  14. Lin CT, Yang SY (2003) Forecast of the output value of Taiwan’s opto-electronics industry using the Grey forecasting model. Technol Forecast Soc Chang 70(2):177–186

    Article  Google Scholar 

  15. Lin SL, Wu SJ (2011) Is grey relational analysis superior to the conventional techniques in predicting financial crisis? Expert Syst Appl 38(5):5119–5124

    Article  Google Scholar 

  16. Lin YH, Wang JS, Pai PF (2004) A grey prediction model with factor analysis technique. J Chin Inst Ind Eng 21(6):535–542

    Google Scholar 

  17. Liu SF, Xie NM (2011) New grey evaluation method based on reformative triangular whitenization weight function. J Syst Eng 26(2):244–250

    Google Scholar 

  18. Mao M, Chirwa EC (2005) Combination of grey model GM (1, 1) with three-point moving average for accurate vehicle fatality risk prediction. Int J Crashworthiness 10(6):635–642

    Article  Google Scholar 

  19. Miller SM, Springer TM (2007) Cost improvements, returns to scale, and cost inefficiencies for real estate investment trusts. In: Returns to scale, and cost inefficiencies for real estate investment trusts. Available at: http://opencommons.uconn.edu/cgi/viewcontent.cgi?article=1097&context=econ_wpapers

  20. Miller SM, Clauretie TM, Springer TM (2006) Economies of scale and cost efficiencies: a panel-data stochastic-frontier analysis of real estate investment trusts. Manch Sch 74(4):483–499

    Article  Google Scholar 

  21. Nguyen NT, Tran TT (2017) A novel integration of DEA, GM (1, 1) and neural network in strategic alliance for the Indian electricity organizations. J Grey Syst 29(2):80–101

    Google Scholar 

  22. Nguyen NT, Tran TT (2018) A study of the strategic alliance for Vietnam domestic pharmaceutical industry: a dynamic integration of a hybrid DEA and GM (1, 1) approach. J Grey Syst 30(4):134–151

    Google Scholar 

  23. Nguyen NT, Tran TT (2019) Optimizing mathematical parameters of Grey system theory: an empirical forecasting case of Vietnamese tourism. Neural Comput Appl 31(2):1075–1089

    Article  Google Scholar 

  24. Peng Wong W, Gholipour HF, Bazrafshan E (2012) How efficient are real estate and construction companies in Iran’s close economy? Int J Strateg Prop Manag 16(4):392–413

    Article  Google Scholar 

  25. Qi W, Jia S (2010) The empirical study on productivity of Chinese real estate enterprises based on DEA-based Malmquist model. In: 2010 second international conference on communication systems, networks and applications, vol 1. IEEE, pp 248–251. Available at: https://ieeexplore.ieee.org/abstract/document/5588705/

  26. Shah NA, Animasaun IL, Chung JD, Wakif A, Alao FI, Raju CSK (2021) Significance of nanoparticle’s radius, heat flux due to concentration gradient, and mass flux due to temperature gradient: The case of Water conveying copper nanoparticles. Sci Rep 11(1):1–11

    Article  Google Scholar 

  27. Shah NA, Animasaun IL, Ibraheem RO, Babatunde HA, Sandeep N, Pop I (2018) Scrutinization of the effects of Grashof number on the flow of different fluids driven by convection over various surfaces. J Mol Liq 249:980–990

    Article  Google Scholar 

  28. Tsai CH, Chang CL, Chen L (2003) Applying grey relational analysis to the vendor evaluation model. Int J Comput Internet Manag 11(3):45–53

    Google Scholar 

  29. Wang CN, Nguyen NT, Tran TT (2014) An empirical study of customer satisfaction towards bank payment card service quality in Ho Chi Minh banking branches. Int J Econ Financ 6(5):170–181

    Google Scholar 

  30. Wang CN, Nguyen XT, Wang YH (2016) Automobile industry strategic alliance partner selection: the application of a hybrid DEA and grey theory model. Sustainability 8(2):173

    Article  Google Scholar 

  31. Wang T, Wang G (2009) Empirical analysis of operating efficiency of China’s real estate industry. Sci Technol Ind 9(10):39–43

    Google Scholar 

  32. Wei G (2011) Grey relational analysis model for dynamic hybrid multiple attribute decision making. Knowl-Based Syst 24(5):672–679

    Article  Google Scholar 

  33. Wakif A, Animasaun IL, Satya Narayana PV, Sarojamma G (2019) Meta-analysis on thermo-migration of tiny/nano-sized particles in the motion of various fluids. Chin J Phys 68:293–307. https://doi.org/10.1016/j.cjph.2019.12.002

    Article  Google Scholar 

  34. Wen KL (2004) Grey systems: modeling and prediction. Yang's Scientific Research Institute

  35. Wu G, Tang C, Zhang M, Wu W (2005) Study on grey model GM (1, 1) forecasting for airport passenger throughput. China USA Bus Rev 4(5):70–75

    Google Scholar 

  36. Yuan-yuan J, Li-xin L, En-yuan L (2010) Analysis on the efficiency of real estate industry based on DEA in Ningbo City. In: 2010 International conference on management science & engineering 17th annual conference proceedings. IEEE, pp 1632–1637. Available at: https://ieeexplore.ieee.org/abstract/document/5720001/

  37. YuChun L, Fang Z, ChangZhu Y, WeiHua B (2001) The use of “grey system” analysis methodology for automated boiler water chemistry control in electric power plants. Anti-Corros Methods Mater 48:96–100

    Article  Google Scholar 

  38. Zheng X, Chau KW, Hui EC (2011) Efficiency assessment of listed real estate companies: an empirical study of China. Int J Strateg Prop Manag 15(2):91–104

    Article  Google Scholar 

Websites

  1. Article: Cổ phiếu bất động sản hút dòng tiền (2018). Retrieved from http://tinnhanhchungkhoan.vn/chung-khoan/co-phieu-bat-dong-san-hut-dong-tien-222623.html

  2. Article: Điểm sáng thu hút đầu tư nước ngoài năm 2017 và triển vọng năm (2018). Retrieved from http://www.mof.gov.vn/webcenter/portal/vclvcstc/r/m/ncvtd/ncvtd_chitiet?dDocName=MOFUCM119902&dID=121662&_afrLoop=37848164253286274#!%40%40%3FdID%3D121662%26_afrLoop%3D37848164253286274%26dDocName%3DMOFUCM119902%26_adf.ctrl-state%3D1cs7daunvu_4

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Nhu-Ty Nguyen.

Ethics declarations

Conflict of interest

The authors declare that there is no conflict of interests regarding the publication of this paper.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendices

Appendices

See Tables 13, 14, 15, 16, 17, 18, 19 and 20.

Table 13 Correlation of inputs and outputs—2014
Table 14 Correlation of inputs and outputs—2015
Table 15 Correlation of inputs and outputs—2016
Table 16 Correlation of inputs and outputs—2017
Table 17 Correlation of inputs and outputs—2018
Table 18 Efficiency Change (2018–2022)
Table 19 Frontier Shift (2018–2022)
Table 20 Malmquist Productivity Index (MPI) (2018–2022)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Nguyen, NT., Le, VA.B. & Tran, TT. Vietnamese real estate corporations’ performance using the hybrid model of data envelopment analysis and grey system theory. Neural Comput & Applic 33, 17209–17222 (2021). https://doi.org/10.1007/s00521-021-06311-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00521-021-06311-0

Keywords