Skip to main content
SpringerLink
Log in

The impact of scale effects on the prevailing internet-based banking model in the US

  • Empirical Article
  • Published:
Service Business Aims and scope Submit manuscript

Abstract

Internet-based banks use a technology-intensive production process that may benefit from scale effects as they grow larger. This article analyzes whether the predominant Internet-primary bank in the USA generates technology-based economies of scale in the period 2002–2010. There is evidence of both favorable and adverse technology-based scale effects. As the leading Internet-primary bank gets larger, the financial performance gap with traditional banks shrinks while some of its critical competitive advantages wear down. The results suggest that unless the prevailing Internet-primary bank preserves the distinctive advantages of the Internet-based business model as it improves financial performance, it might end up converging with its branching competitors.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

Notes

  1. We chose a ± 10% range because the resulting sample includes a nearly balanced number of greater (10) and smaller (9) banks than ING Bank. Had we chosen either a narrower or a wider range (e.g., 5% or 15%), the resulting sample would be clearly uneven.

  2. For a recent review see Hsiao (2007).

  3. For further reference, see Arellano (2003) and Baltagi (2001).

  4. For details, see Hausman (1978).

References

  • Arellano M (2003) Panel data econometrics. Oxford University Press, Oxford

    Book  Google Scholar 

  • Arnold IJM, van Ewijk SE (2011) Can pure play internet banking survive the credit crisis? J Bank Finance 35:783–793

    Article  Google Scholar 

  • Baltagi BH (2001) Econometric analysis of panel data, 2nd edn. Wiley, New York

    Google Scholar 

  • Chen SH (2009) Establishment of a performance-evaluation model for service quality in the banking industry. Serv Ind J 29(2):235–247

    Article  Google Scholar 

  • De Young R (2001) The financial performance of pure play Internet banks. Fed Reserve Bank Chic Econ Perspect 25(1):60–75

    Google Scholar 

  • De Young R (2005) The performance of Internet-based business models: evidence from the banking industry. J Bus 78(3):893–947

    Article  Google Scholar 

  • Furst K, Lang W, Nolle D (2002) Internet banking: developments and prospects. Program on information resources policy. Center for Information Policy Research & Harvard University, Cambridge

    Google Scholar 

  • Gujarati D (2003) Basic econometrics, 4th edn. McGraw Hill, New York

    Google Scholar 

  • Hausman JA (1978) Specification tests in econometrics. Econometrica 46:1251–1271

    Article  Google Scholar 

  • Hsiao C (2007) Panel data analysis—advantages and challenges. Test 16(1):1–22

    Article  Google Scholar 

  • Moore RR (1998) Concentration, technology and market power in banking: is distance dead? Financial industry studies, Federal Reserve of Dallas, December, 1–24

  • Nadiri H, Kandampully J, Hussain K (2009) Zone of tolerance for banks: a diagnostic model of service quality. Serv Ind J 29(11):1547–1564

    Article  Google Scholar 

  • Pyun CS (2002) Internet banking in the U.S., Japan and Europe. Multinatl Bus Rev Fall:73–81

    Google Scholar 

  • Rackley T (2000) Planning is key to cyberbanking success. Bank Syst Technol 37(2):14

    Google Scholar 

  • Sheshunoff A (2000) Internet banking—an update from the frontlines. ABA Bank J January:51–52

    Google Scholar 

  • Yousafzai S, Pallister J, Foxall G (2009) Multi-dimensional role of trust in Internet banking adoption. Serv Ind J 29(5):591–605

    Article  Google Scholar 

Download references

Acknowledgments

Financial support from the Ministry of Science and Technology of Spain (research project ECO2009-14457-C04-04) is gratefully acknowledged. We thank FUNCAS for its support on a previous version of this manuscript (working paper 630/2011).

Author information

Authors and Affiliations

  1. Department of Corporate Finance, Universitat de València, Av. Tarongers s/n, 46022, Valencia, Spain

    Alexandre Momparler

  2. Department of Financial Economics, Universitat de València, Av. Tarongers s/n, 46022, Valencia, Spain

    Francisco J. Climent & Jose M. Ballester

Authors
  1. Alexandre Momparler
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Francisco J. Climent
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jose M. Ballester
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Alexandre Momparler.

Appendices

Appendices

1.1 Appendix 1: Financial performance ratio definitions

  1. 1.

    ROA: return on assets (annualized).

  2. 2.

    ROE: return on book equity (annualized).

  3. 3.

    SPREAD: LOANRATE minus DEPRATE.

  4. 4.

    LOANRATE: interest and fees received on loans divided by total loans (annualized).

  5. 5.

    DEPRATE: interest paid on deposits divided by total deposits (annualized).

  6. 6.

    LOANS: total loans divided by total assets.

  7. 7.

    DEPOSITS: total deposits divided by total assets.

  8. 8.

    FEES: non-interest income divided by total assets (annualized).

  9. 9.

    NIEXP: total non-interest expense divided by total assets (annualized).

  10. 10.

    LABOREXP: salary and benefits expense divided by total assets (annualized).

  11. 11.

    FTES: number of full-time-equivalent employees divided by total assets.

  12. 12.

    WAGE: salary and benefits expense divided by FTES (annualized).

  13. 13.

    PREMEXP: expense on premises and equipment divided by total assets (annualized).

  14. 14.

    OTHEREXP: all “other” (i.e., non-labor and non-premises) non-interest expenses divided by total assets (annualized).

  15. 15.

    OVERHEAD: book value of physical assets divided by total assets.

  16. 16.

    EQUITY: book value of equity divided by total assets.

  17. 17.

    GROWTH: asset growth rate (annualized).

  18. 18.

    BADLOANS: nonperforming loans divided by total assets.

1.2 Appendix 2: Exogenous variables

  1. √

    %BUSSINESS: commercial and industrial loans divided by total loans.

  2. √

    %REALSTATE: real estate loans divided by total loans.

  3. √

    LOANS: total loans.

  4. √

    LOAN LOSS ALLOWANCE: allowance for loan and lease losses.

  5. √

    UNEMPLOYMENT: US rate of unemployment.

  6. √

    QUARTER: seasonal dummy variable.

1.3 Appendix 3

See Table 4.

Table 4 Panel data results sample: 2002/Q1–2010/Q4
Full size table

Rights and permissions

Reprints and permissions

About this article

Cite this article

Momparler, A., Climent, F.J. & Ballester, J.M. The impact of scale effects on the prevailing internet-based banking model in the US. Serv Bus 6, 177–195 (2012). https://doi.org/10.1007/s11628-011-0126-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11628-011-0126-6

Keywords

Search

Navigation