Skip to content
Licensed Unlicensed Requires Authentication Published by De Gruyter March 3, 2017

Bias and Size Effects of Price-Comparison Platforms: Theory and Experimental Evidence

  • Aurora García-Gallego EMAIL logo , Nikolaos Georgantzís , Pedro Pereira and José C. Pernías-Cerrillo

Abstract

We analyze the impact on consumer prices of some information characteristics of price-comparison search platforms. An equilibrium model where vendors compete in prices and consumers do not observe prices, but can obtain price information through a search platform, is developed. The model generates several predictions about the impact on the price distribution of: (i) the size of the search platform’s sample, (ii) whether the search platform’s sample is random, and (iii) the number of vendors in the market. The model’s predictions are tested experimentally. The results confirm the predictions about (ii) and (iii), but reject the model’s predictions about (i).

JEL Classification: C91; D43; D83; L13

Corresponding author: Prof. Aurora García-Gallego, LEE and Economics Department, Universitat Jaume I, Av. Sos Baynat s/n, 12006-Castellón, Spain, Phone: +34-964387631

Acknowledgments

The authors gratefully acknowledge financial support by the NET Institute and the Spanish Ministerio de Economía y Competitividad (project ECO2015-68469-R). P. Pereira acknowledges financial support from Fundação para a Ciência e a Tecnologia and FEDER/COMPETE (grant UID/ECO/04007/2013). This paper benefited from helpful comments by H. Raff, J. Brandts, J. Bröcker, T. Cason, S. Hoernig and M. Sefton.

Appendix A. Proofs

A Nash equilibrium is a n-tuple of cumulative distribution functions over prices, {F1(·), …, Fn (·)}, such that for some Πj on 0+, and j=1, …, n: (i) Πj(p)=Πj, for all p on the support of Fj (·), and (ii) Πj(p)Πj, for all p.

When vendors are identical we focus on symmetric equilibria, in which case: Fj (·)=F(·), pj =p, p̅j =p̅ and Πj=Π, for all j.

Denote by p^j the minimum price charged by any indexed vendor other than vendor j, and denote by m^j the number of indexed vendors that charge p^j. The profit function of vendor j when it charges price pj is:

πj(pj;τ)={pj[λn+(1λ)ϕjτ]if pj<p^j1pj[λn+1λm^jϕjτ]if pj=p^j1pjλnif p^j<pj10if 1<pj.

The next Lemma states some auxiliary results.

Lemma 1For all j: (i) ljτp_jp¯j1; (ii) Fjτis continuous on[ljτ,1]; (iii) p̅j =1; (iv) Πj=λn; (v) p_j=ljτ; (vi) Fjτhas a connected support.

Proof of Lemma 1. For τ=s and j=k+1, …, n the proofs are obvious, so consider: (a) τ=s and j=1, …, k, and (b) τ=c, u.

  • For any j, any price pj<ljτ or pj >1 is strictly dominated by pj =1;

  • Suppose not, i.e. suppose that Fjτ has a mass point at price p. Let ε>0 be arbitrarily small and such that no mass point exists at price pε. The expected profits of firm j are:

    Πj(pε)=(pε)λn+(pε)(1λ)ϕjτProb[pε<p^j]+(pε)(1λ)ϕjτProb[pεp=p^j],

    and

    Πj(p)=pλn+p(1λ)ϕjτProb[p<p^j]+p(1λ)ϕjτm^jProb[p=p^ij].

    Subtracting the second expression from the first and taking the limit as ε approached zero, one obtains

    limε0[Πj(pε)Πj(p)]=p(1λ)ϕjτ(m^j1m^j)Prob[p=p^j]>0.

    Hence, vendor j would increase profit by shifting mass from p to an ε neighborhood below p. But this implies that it cannot be an equilibrium strategy to maintain a mass point at p;

  • Suppose not, i.e. suppose p̅j <1. Then

    Πj(p¯j)=p¯jλn+p¯j(1λ)ϕjτ[1F(p¯j)]k1=p¯jλn,

    since from (ii) there are no mass points at p¯jλn. However, the payoff from setting a price equal to 1 is λn>p¯jλn;

  • Follows from (ii) and (iii);

  • Parts (ii) and (iv) imply that p_jλn+p_j(1λ)ϕjτ=Πj(p_j)=λn. Hence p_j=ljτ;

  • Suppose not, i.e. suppose there is an interval [pl , ph ] satisfying ljτpl<ph1 such that F(pl )=F(ph ). Suppose also that pl is the infimum of all prices p, ljτp1. Then pl is in the support of F(·) and, from (ii) Πj=Πj(pl)=plλn+pl(1λ)ϕjτ[1F(pl)]k1<phλn+ph(1λ)ϕjτ[1F(ph)]k1=Πj(ph), a contradiction.□

Proof of Proposition 1. We show constructively that equilibrium exists. Alternatively, existence follows from theorem 5 of Dasgupta and Maskin (1986). (i) Use Lemma 1(iv) to set Πj(p)=pλn+p(1λ)ϕjτ[1F(p)]k1=λn. Solving for F(p) the result follows; (ii) Obvious.□

Proof of Remark 1. (i) Follows from the fact that all firms are indifferent between any equilibrium price and the monopoly price. (ii) Follows directly from the definition of μc=lc+lc1(1Fc)ndp and εc=lc+lc1(1Fc)dp.

Theorem 1 (i) εc (n)<εc (n+1); (ii) μc (n)>μc (n+1).◆

Proof of Theorem 1. (i) See Morgan et al. (2006); (ii) Follows from (i) and Remark 1(i).      □

Proof of Corollary 1. Obvious.      □

Proof of Proposition 2. (i) Obvious; (ii) Follows from Corollary 1 and the Theorem 1; (iii) Obvious.      □

Proof of Corollary 2. (i) Obvious; (ii) Follows from Corollary 1 and the Theorem 1.      □

Proof of Proposition 3. (i) Obvious; (ii) Follows from (i); (iii) Obvious; (iv) Follows from (iii).      □

Proof of Corollary 3. (i) Obvious; (ii) Obvious; (iii) Follows from (ii); (iv) Follows from (ii).      □

Appendix B. Instructions for Subjects (Translated From Spanish)

  • The purpose of this experiment is to study how subjects take decisions in specific economic contexts. This project has received financial support by public funds. Your decision making in this session is going to be of great importance for the success of this research. At the end of the session you will receive a quantity of money in cash which will depend on your performance during the session.

  • The environment in which the experiment takes place is an industry. This industry has the following characteristics:

    • a price comparison search platform like the ones on the Internet,

    • 3 firms, (Treatments 48: 6 firms),

    • 1200 consumers.

    Each firm in the industry produces a homogeneous product, and this product is the same for all firms.

  • Transactions will take place in UMEX (our lab’s Experimental Monetary Units).

  • This session will consist of 50 rounds.

  • You are one of the 3 firms (Treatments 48: 6 firms) in the industry. Your production costs are zero. Therefore, your profits are equal to your revenue.

  • Each round, you and the rest of the firms in the industry have to decide the price at which you want to sell the product. Price is your only decision variable.

  • (Treatments 1 and 4) Each period, a Price search platform lists the prices of all firms in the industry.

  • (Treatments 2, 5 and 7) Each period, a Price search platform lists the prices of 2 firms (Treatment 5: 4 firms) in the industry. More precisely, each round, the price comparison search platform randomly chooses 2 firms (Treatment 5: 4 firms), whose price will be included in its price list. The identity of the firms whose price will be included in the list of the price search platform, will be announced publicly to the members of the industry after the firms’ prices are posted.

  • (Treatments 3, 6 and 8) Each period, a Price search platform lists the prices of 2 firms (Treatment 6: 4 firms) in the industry. More precisely, each round, the price comparison search platform randomly chooses 2 firms (Treatment 6: 4 firms), whose price will be included in its price list. The identity of the firms whose price will be included in the list of the price search platform, will be announced publicly to the members of the industry before the firms’ prices are posted.

  • Each consumer wants to buy one unit of the product per round. The maximum willingness to pay of each consumer for a unit of the product is 1000 UMEX. That is, if the price you fix is higher than 1000 UMEX, nobody will buy from you.

  • There are two types of consumers. Half of them, i.e. 600 consumers, will read the list of price created by the search platform. The other half do not actually read the list of prices of the search engine (maybe because they are not able to do so).

  • The consumers who read the price list of the search platform will buy, each period, from the firm whose price for that period is the lowest among all prices included in the price list, if such price does not exceed 1000 UMEX. In case of a “tie” (i.e. several firms fix the same minimum price) the consumers are distributed evenly among the firms with the same minimum price.

  • The consumers who do not read the search platform’s price list will buy “randomly” from any vendor, so that this group of consumers will be distributed evenly among all firms in the industry.

  • In each round, 3 firms (Treatments 48: 6 firms) forming (together with you) the same industry, will be randomly drawn among the 18 participants of this session. Therefore, the probability of competing with the same 2 firms (Treatments 48: 5 firms) in 2 different periods is very low (less than 10%).

  • Once the participants have been assigned to the industries, you must set your price. The master program in the computer will simulate the consumers’ reactions. At the end of each round, you will see on your screen the information about your own sales, your earnings and the prices fixed by your competitors in the market.

  • At the end of the session you will be paid in cash. Your reward will be determined taking into account the earnings you accumulate over 10 (randomly selected) out of the total 50 periods. The exchange rate will be: 1,000,000 UMEX=10 €.

Thank you very much for your participation. Good luck!

References

Armstrong, M., V. Vickers and J. Zhou (2009) “Prominence and Consumer Search,” RAND Journal of Economics, 40(2):209–233.10.1111/j.1756-2171.2009.00062.xSearch in Google Scholar

Arnold, M., C. Li, C. Saliba and L. Zhang (2011) “Asymmetric Market Shares, Advertising, and Pricing: Equilibrium with an Information Gatekeeper,” Journal of Industrial Economics, 59(1):63–84.10.1111/j.1467-6451.2011.00446.xSearch in Google Scholar

Athey, S. and G. Ellison (2011) Position Auctions with Consumer Search. Quarterly Journal of Economics, 126(3):1213–1270.10.3386/w15253Search in Google Scholar

Bagwell, K. and G. M. Lee (2014) “Number of Firms and Price Competition.” Research Collection School Of Economics, Singapore Management University.Search in Google Scholar

Baye, M. and J. Morgan (2001) “Information Gatekeepers on the Internet and the Competitiveness of Homogeneous Product Markets,” American Economic Review, 91(3):454–474.10.1257/aer.91.3.454Search in Google Scholar

Baye, M., D. Kovenock and C. Devries (1992) “It takes Two to Tango: Equilibria in a Model of Sales,” Games and Economic Behavior, 4:493–510.10.1016/0899-8256(92)90033-OSearch in Google Scholar

Benaïm, M., J. Hofbauer and E. Hopkins (2009) “Learning in Games with Unstable Equilibria,” Journal of Economic Theory, 144:1694–1709.10.1016/j.jet.2008.09.003Search in Google Scholar

Bradlow, E. and D. Schmittlein (1999) “The Little Engine that could: Modeling the Performance of World Wide Web Search Engines,” Marketing Science, 19(1):43–62.10.1287/mksc.19.1.43.15180Search in Google Scholar

Brown, J. and A. Goolsbee (2002) “Does the Internet make Markets more Competitive? Evidence from the Life Insurance Industry,” Journal of Political Economy, 110(3):481–507.10.1086/339714Search in Google Scholar

Brynjolfsson, E. and M. Smith (2000) “Frictionless Commerce? A Comparison of Internet and Conventional Retailers,” Management Science, 46(4):563–585.10.1287/mnsc.46.4.563.12061Search in Google Scholar

Burdett, K. and K. Judd (1983) “Equilibrium Price Dispersion,” Econometrica, 51:955–969.10.2307/1912045Search in Google Scholar

Cason, T. N. and D. Friedman (2003) “Buyer Search and Price Dispersion: A Laboratory Study,” Journal of Economic Theory, 112:232–260.10.1016/S0022-0531(03)00135-0Search in Google Scholar

Chen, Y. and M. Riordan (2008) “Price-Increasing Competition,” RAND Journal of Economics, 39(4):1042–1058.10.1111/j.1756-2171.2008.00049.xSearch in Google Scholar

Clay, K., R. Krishnan, E. Wolff and D. Fernandes (2002) “Retail Strategies on the Web: Price and Non-Price Competition in the Online Book Industry.” The Journal of Industrial Economics, 50(3):351–367.10.1111/1467-6451.00181Search in Google Scholar

Clemons, E., I. Hann and L. Hitt (2002) “Price Dispersion and Differentiation in Online Travel: An Empirical Investigation,” Management Science, 48(4):534–549.10.1287/mnsc.48.4.534Search in Google Scholar

Corniere, A. and G. Taylor (2014) “Integration and Search Engine Bias,” RAND Journal of Economics, 45(3):576–597.10.2139/ssrn.2190953Search in Google Scholar

Dahlby, B., D. West (1986) “Price Dispersion in an Automobile Insurance Market,” Journal of Political Economy, 94(2):418–438.10.1086/261380Search in Google Scholar

Dasgupta, P. and E. Maskin (1986) “The Existence of Equilibrium in Discontinuous Economic Games, I: Theory,” Review of Economic Studies, 53:1–26.10.2307/2297588Search in Google Scholar

De los Santos, B., A. Hortacsu and M. Wildenbeest (2013) “Testing Models of Consumer Search Behavior using Data on Web Browsing and Consumer Purchases,” American Economic Review, 102(6):2955–2980.10.1257/aer.102.6.2955Search in Google Scholar

Dinlersoz, E. and P. Pereira (2007) “On the Diffusion of Electronic Commerce,” International Journal of Industrial Organization, 25(3):541–574.10.1016/j.ijindorg.2006.05.008Search in Google Scholar

Ellison, G. and S. Ellison (2009) “Search, Obfuscation, and Price Elasticities on the Internet,” Econometrica, 77(2):427–452.10.3386/w10570Search in Google Scholar

Ellison, G. and A. Wolitzky (2012) “A Search Cost Model of Obfuscation,” RAND Journal of Economics, 45(3):417–441.10.3386/w15237Search in Google Scholar

Fischbacher U. (2007) “z-Tree: Zurich Toolbox for Readymade Economic Experiments,” Experimenter’s manual. Experimental Economics, 10(2):171–178.10.1007/s10683-006-9159-4Search in Google Scholar

Fonseca, M. A. and H. T. Normann (2008) “Mergers, Asymmetries and Collusion: Experimental Evidence,” The Economic Journal, 118:387–400.10.1111/j.1468-0297.2007.02126.xSearch in Google Scholar

Frank, R. and D. Salkever (1997) “Generic Entry and the Market for Pharmaceuticals,” Journal of Economic and Management Strategy, 6:75–90.10.1162/105864097567039Search in Google Scholar

García-Gallego, A., N. Georgantzís, A. Jaramillo-Gutiérrez, P. Pereira and J. C. Pernías (2014) “Monopolistic Product Line Competition with Ex Post Consumer Heterogeneity,” Journal of Business Research, 67(5):795–801.10.1016/j.jbusres.2013.11.047Search in Google Scholar

Grabowski, H. and J. Vernon (1992) “Brand Loyalty, Entry and Price Competition in Pharmaceuticals after the 1984 Drug Act,” Journal of Law and Economics, 35:331–350.10.1086/467257Search in Google Scholar

Guimarães, P. (1996) “Search Intensity in Oligopoly,” Journal of Industrial Economics, 44:415–426.10.2307/2950523Search in Google Scholar

Hagiu, A. and B. Jullien (2011) “Why do Intermediaries Divert Search?” RAND Journal of Economics, 42(2):337–362.10.1111/j.1756-2171.2011.00136.xSearch in Google Scholar

Harrison, G. and P. Morgan (1990) “Search Intensity in Experiments.” Economic Journal, 100:478–486.10.2307/2234134Search in Google Scholar

Hopkins, E. and R. Seymour (2002) “The Stability of Price Dispersion under Seller and Consumer Learning,” International Economic Review, 43:1157–1190.10.1111/1468-2354.t01-1-00052Search in Google Scholar

Huck, S., Normann, H. T. and J. Oechssler (2004) “Two are few and Four are Many: Number Effects in Experimental Oligopolies,” Journal of Economic Behavior and Organization, 53:435–446.10.1016/j.jebo.2002.10.002Search in Google Scholar

Iyer, G. and A. Pazgal (2000) “Internet Shopping Agents: Virtual Co-Location and Competition,” Marketing Science, 22:85–106.10.1287/mksc.22.1.85.12842Search in Google Scholar

Janssen, M. C. W. and J. L. Moraga-González (2004) “Strategic Pricing, Consumer Search and the Number of Firms,” Review of Economic Studies, 71:1089–1118.10.1111/0034-6527.00315Search in Google Scholar

Lach, S. (2002) “Existence and Persistence of Price Dispersion: An Empirical Analysis,” The Review of Economics and Statistics, 84(3):433–444.10.3386/w8737Search in Google Scholar

Lawrence, S. and C. Giles (1998) “Searching the World Wide Web,” Science, 280(3):98–100.10.1126/science.280.5360.98Search in Google Scholar

Lawrence, S. and C. Giles (1999) “Accessibility of Information on the Web,” Nature, 400:107–109.10.1038/21987Search in Google Scholar

Morgan, J., H. Orzen and M. Sefton (2006) “An Experimental Study of Price Dispersion,” Games and Economic Behavior, 54:134–138.10.1016/j.geb.2004.07.005Search in Google Scholar

Orzen, H. (2008) “Counterintuitive Number Effects in Experimental Oligopolies,” Experimental Economics, 11(4):390–401.10.1007/s10683-007-9174-0Search in Google Scholar

Orzen, H. and M. Sefton (2008) “An Experiment on Spatial Price Competition,” International Journal of Industrial Organization, 26:716–729.10.1016/j.ijindorg.2007.05.007Search in Google Scholar

Pereira, P. (2005) “Do Lower Search Costs Reduce Prices and Price Dispersion?” Information Economics and Policy, 17(1):61–72.10.1016/j.infoecopol.2004.03.001Search in Google Scholar

Rosenthal, R. (1980) “A Model in which an Increase in the Number of Sellers Leads to a Higher Price,” Econometrica, 48:1575–1579.10.2307/1912828Search in Google Scholar

Samuelson, L. and J. Zhang (1992) “Search costs and Prices,” Economics Letters, 38:55–60.10.1016/0165-1765(92)90161-QSearch in Google Scholar

Schotter, A. and Y. Braunstein (1981) “Economic Search: An Experimental Study,” Economic Inquiry, 19(1):1–25.10.1111/j.1465-7295.1981.tb00600.xSearch in Google Scholar

Seade, J. (1980) “On the Effects of Entry,” Econometrica, 48(2):479–489.10.2307/1911111Search in Google Scholar

Sorensen, A. (2000) “Equilibrium Price Dispersion in Retail Markets for Prescription Drugs,” Journal of Political Economy, 108(4):833–850.10.1086/316103Search in Google Scholar

Stahl, D. (1989) “Oligopolistic Pricing with Sequential Consumer Search,” American Economic Review, 79:700–712.Search in Google Scholar

Stigler, G. (1961) “The Economics of Information,” Journal of Political Economy, 69(3):213–225.10.1007/978-3-642-51565-1_86Search in Google Scholar

Tang, Z., M. Smith and A. Montgomery (2010) “The Impact of Shopbot use on Prices and Price Dispersion: Evidence from Online Book Retailing,” International Journal of Industrial Organization, 28:579–590.10.1016/j.ijindorg.2010.03.014Search in Google Scholar

Varian, H. (1980) “A Model of Sales,” American Economic Review, 70:651–659.Search in Google Scholar

White, A. (2013) “Search Engines: Left Side Quality Versus Right Side Profits,” International Journal of Industrial Organization, 31(6):690–701.10.1016/j.ijindorg.2013.04.003Search in Google Scholar

Published Online: 2017-3-3
Published in Print: 2017-5-24

©2016 Walter de Gruyter GmbH, Berlin/Boston

Downloaded on 4.6.2024 from https://www.degruyter.com/document/doi/10.1515/rne-2016-0015/html
Scroll to top button