Journal of Financial Services Marketing

, Volume 17, Issue 2, pp 120–134 | Cite as

Pricing financial services innovations

Original Article

Abstract

The number of innovative financial solutions introduced to markets has grown considerably in the past decade owing to emerging digital technologies, deregulation and market fragmentation. Examples are abundant in the worldwide markets for insurance, credit products and transaction processing services. A question of growing interest is how firms should price these innovations. The optimal introductory pricing of financial innovations may vary as a function of factors such as price sensitivity of the market and competitors’ ability to introduce competing financial solutions. In this article, we examine the role of these factors in the optimal pricing of a financial innovation. Using an agent-based simulation framework, introductory pricing strategies that maximize profitability under various market conditions are identified. Results indicate that lower levels of market price sensitivity and longer time horizons for competitive entry create pricing opportunities for financial innovators. However, the relationship becomes more complex as market price sensitivity increases or competitive market entry becomes more immediate. Detailed recommendations for optimal pricing of financial innovations under various market conditions are provided, and the article concludes with strategic recommendations for pricing innovative financial services.

Keywords

pricing innovations financial services diffusion agent-based modeling and simulation 

References

  1. Amini, M., Wakolbinger, T., Racer, M. and Nejad, M.G. (2012) Alternative supply chain production–sales policies for new product diffusion: An agent-based modeling and simulation approach. European Journal of Operational Research 216 (2): 301–311.CrossRefGoogle Scholar
  2. Bass, F. (1969) A new product growth model for consumer durables. Management Science 15 (5): 215–227.CrossRefGoogle Scholar
  3. Bass, F. (2004) Comments on ‘a new product growth for model consumer durables’. Management Science 50 (12): 1825–1832.CrossRefGoogle Scholar
  4. Bijmolt, T., Van Heerde, H. and Pieters, R. (2005) New empirical generalizations on the determinants of price elasticity. Journal of Marketing Research 42 (2): 141–156.CrossRefGoogle Scholar
  5. Casalo, L., Flavian, C. and Guinaliu, M. (2008) The role of satisfaction and website usability in developing customer loyalty and positive word-of-mouth in the e-banking services. International Journal of Bank Marketing 26 (6): 399–417.CrossRefGoogle Scholar
  6. Chandrasekaran, D. and Tellis, G. (2007) A critical review of marketing research on diffusion of new products. In: N.K. Malhotra (ed.) Review of Marketing Research. Armonk: M.E. Sharpe, pp. 39–80.CrossRefGoogle Scholar
  7. Chen, Y., Wang, Q. and Xie, J. (2011) Online social interactions: A natural experiment on word of mouth versus observational learning. Journal of Marketing Research 48 (2): 238–254.CrossRefGoogle Scholar
  8. Davis, J., Eisenhardt, K. and Bingham, C. (2007) Developing theory through simulation models. Academy of Management Review 32 (2): 480–499.CrossRefGoogle Scholar
  9. Dawes, J., Mundt, K. and Sharp, B. (2009) Consideration sets for financial services brands. Journal of Financial Services Marketing 14 (3): 190–202.CrossRefGoogle Scholar
  10. Dusansky, R. and Koc, C. (2010) Implications of the interaction between insurance choice and medical care demand. Journal of Risk and Insurance 77 (1): 129–144.CrossRefGoogle Scholar
  11. Estelami, H. (1999) The profit impact of consumer complaint solicitation across market conditions. Services Marketing Quarterly 20 (1): 165–195.CrossRefGoogle Scholar
  12. Estelami, H. (2005) A cross-category examination of consumer price awareness in financial and non-financial services. Journal of Financial Services Marketing 10 (2): 125–139.CrossRefGoogle Scholar
  13. Estelami, H. (2006) Marketing Financial Services. Indianapolis, IN: Dog Ear Publishing.Google Scholar
  14. Estelami, H. (2009) Cognitive drivers of suboptimal financial decisions: Implications for financial literacy campaigns. Journal of Financial Services Marketing 13 (4): 273–283.CrossRefGoogle Scholar
  15. Fortin, D. and Uncles, M. (2011) The first decade: Emerging issues of the twenty-first century in consumer marketing. Journal of Consumer Marketing 28 (7): 472–475.CrossRefGoogle Scholar
  16. Ghoreishi Nejad, M. (2011) The role of influentials in the diffusion of new products: PhD dissertation, University of Memphis, Memphis, TN, USA.Google Scholar
  17. Gladwell, M. (2002) The Tipping Point: How Little Things Can Make a Big Difference. San Francisco, CA: Back Bay Books.Google Scholar
  18. Goldenberg, J., Libai, B., Moldovan, S. and Muller, E. (2007) The NPV of bad news. International Journal of Research in Marketing 24 (3): 186–200.CrossRefGoogle Scholar
  19. Goldenberg, J., Libai, B. and Muller, E. (2002) Riding the saddle: How cross-market communications can create a major slump in sales. Journal of Marketing 66 (2): 1–16.CrossRefGoogle Scholar
  20. Gounaris, S., Stathakopoulos, V. and Athanassopoulos, A. (2003) Antecedents to perceived service quality: An exploratory study in the banking industry. International Journal of Bank Marketing 21 (4/5): 168–190.CrossRefGoogle Scholar
  21. Harrington, J. (2011) Customer satisfaction dips for banks, soars for credit unions. Tribune Business News, 13 December: 8.Google Scholar
  22. Harrison, J.R., Zhiang, L.I.N., Carroll, G.R. and Carley, K.M. (2007) Simulation modeling in organizational and management research. Academy of Management Review 32 (4): 1229–1245.CrossRefGoogle Scholar
  23. Hogan, J., Lemon, K.N. and Libai, B. (2003) What is the true value of a lost customer? Journal of Service Research 5 (3): 196.CrossRefGoogle Scholar
  24. Jiang, Z., Bass, F. and Bass, P. (2006) Virtual Bass model and the left-hand data-truncation bias in diffusion of innovation studies. International Journal of Research in Marketing 23 (1): 93–106.CrossRefGoogle Scholar
  25. Krishnan, T., Bass, F. and Kumar, V. (2000) Impact of a late entrant on the diffusion of a new product/service. Journal of Marketing Research 37 (2): 269.CrossRefGoogle Scholar
  26. Lehmann, D. and Esteban-Bravo, M. (2006) When giving some away makes sense to jump-start the diffusion process. Marketing Letters 17 (4): 243–254.CrossRefGoogle Scholar
  27. Libai, B., Muller, E. and Peres, R. (2009) The diffusion of services. Journal of Marketing Research 46 (2): 163–175.CrossRefGoogle Scholar
  28. Libai, B., Muller, E. and Peres, R. (2010) Sources of Social Value in Word-of-Mouth Programs. in MSI Working Paper Series. Report no.10–103.Google Scholar
  29. Lilien, G.L., Rangaswamy, A. and Van den Bulte, C. (2000) Diffusion models: Managerial applications and software. In: V. Mahajan, E. Muller and Y. Wind (eds.) New-product Diffusion Models. New York: Kluwer Academic Publishers.Google Scholar
  30. Lowenstein, G. and Thaler, R. (1989) Anomalities: Intertemporal choices. Journal of Economic Perspectives 3 (4): 181–193.CrossRefGoogle Scholar
  31. Manning, R. (2001) Credit Card Nation: The Consequences of America's Addiction to Credit. New York: Basic Books.Google Scholar
  32. Mesak, H. and Darrat, A. (2002) Optimal pricing of new subscriber services under interdependent adoption processes. Journal of Service Research 5 (2): 140–153.CrossRefGoogle Scholar
  33. Muller, E., Peres, R. and Mahajan, V. (2010) Innovation Diffusion and New Product Growth. Cambridge, MA: Marketing Science Institute.Google Scholar
  34. Murray, K. (1991) A test of services marketing theory: Consumer information acquisition activities. Journal of Marketing 55 (1): 10.CrossRefGoogle Scholar
  35. Murthi, B., Steffes, E. and Rasheed, A. (2011) What price loyalty? A fresh look at loyalty programs in the credit card industry. Journal of Financial Services Marketing 16 (1): 5–13.CrossRefGoogle Scholar
  36. North, M. and Macal, C. (2007) Managing Business Complexity. New York: Oxford University press.CrossRefGoogle Scholar
  37. Oliver, R. (2009) Satisfaction: A Behavioral Perspective on the Consumer. New York: M.E. Sharpe.Google Scholar
  38. Panther, T. and Farquhar, J. (2004) Consumer response to dissatisfaction with financial services providers: An exploration of why some stay while others switch. Journal of Financial Services Marketing 8 (4): 343–353.CrossRefGoogle Scholar
  39. Richards, J. (2009) Common fallacies in law-related consumer research. Journal of Consumer Affairs 43 (1): 174–180.CrossRefGoogle Scholar
  40. Rogers, E. (2003) Diffusion of Innovations, 5th edn. New York: Free Press.Google Scholar
  41. Shleifer, A. (2000) Inefficient Markets: An Introduction to Behavioral Finance. New York: Oxford University Press.CrossRefGoogle Scholar
  42. Sultan, F., Farley, J.U. and Lehmann, D.R. (1990) A meta-analysis of applications of diffusion models. Journal of Marketing Research 27 (1): 70–77.CrossRefGoogle Scholar
  43. Tellis, G. (1998) The price elasticity of selective demand: A meta-analysis of econometric models of sales. Journal of Marketing Research 25 (4): 331–341.CrossRefGoogle Scholar
  44. Toubia, O., Goldenberg, J. and Garcia, R. (2008) A New Approach to Modeling the Adoption of New Products: Aggregated Diffusion Models. MSI Working Paper Series, 08 (001), pp. 65–81.Google Scholar
  45. Van den Bulte, C. and Wuyts, S. (2007) Social Networks and Marketing. Cambridge, MA: Marketing Science Institute.Google Scholar
  46. Walker, O., Mullins, J. and Boyd, H. (2010) Marketing Strategy: A Decision Focused Approach. New York: McGraw-Hill.Google Scholar
  47. Warren, E. (2008) Product safety regulation as a model for financial services regulation. Journal of Consumer Affairs 42 (3): 452–460.CrossRefGoogle Scholar

Copyright information

© Palgrave Macmillan, a division of Macmillan Publishers Ltd 2012

Authors and Affiliations

  1. 1.Graduate School of Business Administration, Fordham UniversityNew YorkUSA

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