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Isolating the Internet Price Effect. Bill Brunger , SVP, Network, Continental Airlines (ret.) and Doctoral Candidate, Case Western Reserve University. Motivation: So What Has Happened? (Some level of causality seems obvious). Industry Structure obviously changed….

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isolating the internet price effect

Isolating the Internet Price Effect.

Bill Brunger,

SVP, Network, Continental Airlines

(ret.) and

Doctoral Candidate,

Case Western

Reserve University

industry structure obviously changed
Industry Structure obviously changed…

Domestic US Low Cost Carrier growth.

easier to see by taking southwest and america west out
Easier to See by Taking Southwestand America West Out…

Rise of Internet

Wave I

Wave II

Domestic US Low Cost Carrier growth (No WN,HP).

most customers believe that airline pricing behavior changed
Most customers believe that Airline Pricing Behavior Changed
  • But I’m not sure…
  • We still match and go on sale and run off-peak sales and amuse ourselves with our alphabet soup of fares and restrictions…
  • And DCA3 and PFS et al. limited “Internet-only” and channel-specific activity…
  • There have been relatively few innovations: Priceline/Hotwire, weekly specials, clubs,…
distribution became more concentrated
Distribution Became More Concentrated!!!!

We Had Expected Fragmentation

preliminary qualitative study
Preliminary Qualitative Study
  • Method
    • 15 open-ended interviews; all referrals; mixed demography and geography, and
    • All were “Experienced travelers”
      • All had purchased in the pre-Internet time
      • Limitation: homogeneity of age; all between about 30 and 60.
      • Advantage: Perspective; Most previous studies have been on students (who never used a TA) or clients of a particular firm
  • Data
    • Analyzed using Glaser and Strauss
    • Initial set of codes from literature (11): search duration, dynamics, range, timing, fare levels, fit, loyalty, and adjectives and descriptors of control, trust, choice and cooperation; evidence of co-production
    • Final set (50) cluster into 6 categories

weatherhead.case.edu/edm/archive/details.cfm?id=10288&topic=23

Or Google: Brunger Impact Airline

five findings
Five Findings
  • Switch was not perceived primarily about lower fares; about control & transparency/search breadth.
  • Unexpectedly, the actual search protocols that most respondents perform are quite simple.

- Effects of trip type, FFP status & demography?

  • Some formed new levels of “involvement” with the Search. Some became “search enthusiasts”.
  • For some, enabled, facilitated, reinforced rich new set of traditional (and web) social interactions.

5.  Change with respect to timing, specifically the decision about when to purchase the ticket.

& They Believe that They Find Lower Fares

can we see evidence of the change
Can We See Evidence of the Change?

But this is primarily a market segmentation effect…

what am i going to look at next
What am I going to look at next?

Customers who use Internet/OnlineTravel Agencies (OTAs) to purchase leisure trips pay significantly less (11.5% in our sample) for similar itineraries in the same markets than those who purchase through traditional travel agencies even though the fares and inventory offered by the airlines are identical. The purpose of this study is to examine this Internet Price Effect (IPE).

other than transparency effects what could account for 11 5 differential in the ipe
Other than Transparency Effects, what could account for 11.5% differential in the IPE?
  • Trip characteristics
  • Customer differences
  • Market structure
  • The “Value” of the seat
  • Then the question is, controlling for these attributes, does IPE persist?
slide16
What do I

expect to find???

Using My Regression Equation:

FP= ß0 + ß1*DC + ß2*TC+ ß3*CD + ß4*MS + ß5*OpV + ε

previous regression based studies of airlines and distribution
Previous Regression-based Studiesof Airlines and Distribution
  • Borenstein, S., and Rose, N. 1994. Competition and Price Dispersion in the U.S. Airline Industry. Journal of Political Economy, 102 (4): 653-682.
  • Clemons, E., Hann, I., and Hitt, L. 2002. Price dispersion and differentiation in online travel: An empirical investigation. Management Science, 48 (4), April: 534-549.
  • Granados, N., Gupta, A., Kauffman, R. 2006. Internet-enabled Market transparency: Impact of price elasticity of demand in the air travel industry. Working paper, Carlson School of Management, University of Minnesota, May 8, 2006.
  • Lane, L. 2003. Price Discrimination in the U.S. Domestic Airline Industry: The Effect of the Internet. Unpublished Third Year Research Project, EDM Program, Weatherhead School of Management, Case Western Reserve University.
  • Sengupta, A., and Wiggins, S. 2006. Airline Pricing, Price Dispersion and Ticket Characteristics On and Off the Internet. Working paper #06-07, NET Institute, Texas A&M University, November, 2006.
  • Stavins, J. 2001. Price Discrimination in the Airline Market: The Effect of Market Concentration. Review of Economics and Statistics, 83, February: 200-202.
some very early findings
Some Very Early Findings…
  • Continental’s Top-25 Markets
  • June,2006, every nonstop simple roundtrip
  • Only “clearly leisure”
  • OTA and Traditional Agencies (No CO.com)
  • Group size < 9; Coach cabin only
  • CO “shipped” the same Fares and Inventory to all channels!
regression coefficients
Regression Coefficients

DV = fare paid as percent of mean; All coefficients significant at .01 level except the red