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Hotel Rankings of Online Travel Agents, Channel Pricing and Consumer Protection

No 300 Hotel Rankngs of Onlne Travel Agents, Channel Prcng and Consumer Protecton Matthas Hunold, Renhold Kesler, Ulrch Latenberger September 2018 IMPRINT DICE DISCUSSION PAPER Publshed by düsseldorf unversty
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No 300 Hotel Rankngs of Onlne Travel Agents, Channel Prcng and Consumer Protecton Matthas Hunold, Renhold Kesler, Ulrch Latenberger September 2018 IMPRINT DICE DISCUSSION PAPER Publshed by düsseldorf unversty press (dup) on behalf of Henrch Hene Unverstät Düsseldorf, Faculty of Economcs, Düsseldorf Insttute for Competton Economcs (DICE), Unverstätsstraße 1, Düsseldorf, Germany Edtor: Prof. Dr. Hans Theo Normann Düsseldorf Insttute for Competton Economcs (DICE) Phone: +49(0) , e mal: DICE DISCUSSION PAPER All rghts reserved. Düsseldorf, Germany, 2018 ISSN (onlne) ISBN The workng papers publshed n the Seres consttute work n progress crculated to stmulate dscusson and crtcal comments. Vews expressed represent exclusvely the authors own opnons and do not necessarly reflect those of the edtor. Hotel Rankngs of Onlne Travel Agents, Channel Prcng and Consumer Protecton Matthas Hunold, Renhold Kesler and Ulrch Latenberger September 2018 Abstract We nvestgate whether onlne travel agents (OTAs) assgn hotels worse postons n ther search results f these set lower hotel prces at other OTAs or on ther own webstes. We formally characterze how an OTA can use such a strategy to reduce prce dfferentaton across dstrbuton channels. Our emprcal analyss shows that the poston of a hotel n the search results of OTAs s better when the prces charged by the hotel on other channels are hgher. Ths s consstent wth the hypothess that OTAs alter ther search results to dscplne hotels for aggressve prces on competng channels, and by ths reduce search qualty for consumers. Keywords: Consumer protecton, free-rdng, hotel bookng, onlne travel agents, rankng, search bas. JEL Class: D40, L42, L81 Frst verson: February Fnancal support by the State Government of Baden-Württemberg, Germany, through the research program Strengthenng Effcency and Compettveness n the European Knowledge Economes (SEEK) s gratefully acknowledged. We thank three anonymous referees and an anonymous edtor for extremely careful and constructve feedback. We thank the partcpants at the MaCCI Annual Conference 2017, the 9th ICT Conference at Télécom ParsTech 2017, the 15th ICT Conference at the ZEW 2017, the 19th ZEW Summer Workshop for Young Economsts, the EARIE Conference 2017 n Maastrcht, the German Economc Assocaton Annual Meetng 2017 n Venna, the 4th IO n the Dgtal Economy Workshop n Lège, semnars at the Unverstes of Bergen, Dortmund, Düsseldorf, Palma and Zürch, the Workshop on E-Commerce and Platforms at CREST, the 15th Dgtal Economcs Summer School n Montpeller, and n partcular Apostolos Flppas, Vcente Lagos, Martn Petz, Johannes Muthers, Chrstoph Schottmüller, Chengs Wang and Julan Wrght for helpful comments. Henrch-Hene-Unverstät Düsseldorf, Düsseldorf Insttute for Competton Economcs (DICE), Unverstätsstr. 1, Düsseldorf, Germany; Centre for European Economc Research (ZEW), MaCCI Mannhem Centre for Competton and Innovaton, Address: L7,1, Mannhem, Germany; Télécom ParsTech, 46 Rue Barrault, Pars, France, and ZEW (as above); 1 1 Introducton Onlne travel agents (OTAs) have become mportant ntermedares for hotels and consumers. 1 They pool the offers of dfferent hotels and help consumers to fnd a hotel room offer. A consumer searchng for a hotel room at an OTA typcally retreves a lst wth offers from varous hotels. The rankng of these offers affects whch hotels consumers are lkely to book (Ursu (2018)). Consumers may often beleve that offers wth hgher match values have been ranked hgher accordng the consumer s own needs. Indeed, the labels on major OTAs default rankngs are consstent wth ths thnkng. Expeda labels ts default rankng Recommended and uses the terms Our top pcks and The best selecton for busness travelers. 2 More suspcous mnds may argue that OTAs charge the hotels commsson fees per bookng, such that OTAs beneft when offers wth a hgh lkelhood of a bookng at the OTA are made the most vsble. In addton, OTAs say they fear free-rdng because they provde hotel search and comparson servces for free, but consumers would ultmately book elsewhere f there s a lower prce, leavng the OTA wthout the per-bookng commsson. 3 In the context of narrowng down ts Prce Party Clauses (PPCs) n Europe, commtted to varous natonal competton authortes to not drectly condton the rankng on prce party across channels. Indeed, hotelers have voced the concern that OTAs would reduce ther vsblty, ncludng the rankng, when they have more compettve prces on competng sales channels. We dscuss ths and more nsttutonal background n detal n secton 3. In ths artcle we nvestgate both theoretcally and emprcally the queston of whether OTAs condton ther rankngs of search results on the hotel prces at other OTAs or on the hotels webstes. In the theory part (secton 4), we frst establsh a reference rankng of hotel offers accordng to the expected match values for consumers ( best match rankng ). We then show that an OTA whch maxmzes ts short-term profts may have ncentves to present offers wth a hgher bookng lkelhood on the OTA webste more promnently, to the detrment of the matchng qualty (search bas). We show that ths can create a relatonshp between the rankng and the hotel prces on other sales channels. Through ths relatonshp the OTA can nfluence the hotels n ther prcng across dstrbuton channels wthout drectly condtonng the rankng on the prce dfferentals across channels. Moreover, we show that n order to maxmze long-term profts, an OTA 1 See European Hotel Dstrbuton Study 2018 (last accessed August 31, 2018). 2 Labels last checked on August 31, The term for busness travelers s translated from the German webste verson. 3 See, for nstance, s arguments as dscussed n the German Federal Cartel Offce s decson prohbtng s narrow prce party clauses (last accessed August 31, 2018). 2 may also employ a polcy whereby t condtons the rankng drectly, and possbly more drastcally, on whether a hotel s offerng lower prces on competng channels. In the emprcal sectons 5 to 7, we nvestgate how changes of a hotel s prces on competng sales channels affect the hotel s poston n the default rankngs that appear n response to a search query va and Expeda. We use data of () and () Expeda, as well as () the meta-search ste Kayak. 4 The data comprses daly search results for 250 ctes n 13 countres, mostly from Europe, between July 2016 untl January Thus, we can track the lstngs and prces of the same hotel room offers on dfferent onlne channels of more than 18,000 hotels. We use addtonal nformaton to solate the effect of a lower prce on competng sales channels on the rankng poston from other factors that mght affect the overall rankng. These nclude promotonal actvtes for specfc hotel offers, as reported by the OTA, as well as nformaton on whether hotels pad addtonal fees to the OTA n order to mprove ther rankngs. We measure hotel qualty wth the average user ratng, the number of user ratngs, the number of stars and other factors such as breakfast ncluded and free cancellaton. In secton 7 we conduct our emprcal analyses. We use both lnear panel estmatons wth hotel fxed effects and rank-ordered logt regressons. We fnd that for a gven hotel prce at an OTA, a lower prce at the other OTA or on the hotel s webste leads to a worse rankng poston. Ths suggests that the OTA condtons ts recommended rankng on factors that are relevant for the OTA to maxmze ts proft, but arguably not to maxmze the match value of consumers. We run further robustness checks n subsecton 7.2. We fnd ths relatonshp both n countres wth and wthout PPC clauses. It s also robust to dfferent functonal forms of the prce dfferences and sgnfcant for both downward and upward devatons. It s more pronounced for substantal prce dfferences of around 10% and above. When usng specfcatons wth lags and leads of the prce dfferences across channels, we do not see a systematc pattern of sgnfcant correlatons between prce dfferences n the future wth rankngs today (a possble ndcaton of reverse causalty). Fnally, we also fnd that hotels prce dfferentate n a plausble way (subsecton 7.3). For nstance, hotels set the drect channel prce lower f demand s hgh and the travel date s close to the bookng date. In the concludng secton 8, we dscuss whether the observed rankng patterns are part of normal proft maxmzaton and whether consumer protecton mght be needed n such cases. 4 The webste of the meta-search ste Kayak looks smlar to that of an OTA such as, but dfferent from an OTA presents prce offers of the dfferent OTAs and the hotel webstes. 3 2 Related lterature Our work relates to the lterature on ntermedares who can decde whch product to present frst or partcularly promnently (Raskovch, 2007; Inderst and Ottavan, 2012; Hunold and Muthers, 2017; Shen and Wrght, 2018). Hagu and Jullen (2011, 2014) specfcally analyze bases n the rankngs of search engnes. In a settng where customers have heterogeneous search costs and the platform has a per-clck payment scheme, Hagu and Jullen (2011) predct dstortons n the rankng n the sense that the less sutable product s dsplayed frst to generate addtonal revenue from the product provders. Moreover, they also consder the stuaton that producers know the result of the rankng algorthm before settng prces. De Cornere and Taylor (2014) show that vertcally ntegrated search engnes dstort search results, but the overall welfare effect s unclear because, for example, the ntegrated search engne can have a strong ncentve to generate demand. To our knowledge, there are not yet any emprcal research artcles that analyze the relaton between the poston of hotels n an OTA s search results and the hotel s prces on competng sales channels. Yet, there s lterature whch hghlghts the mportance of OTA rankngs for the bookng choces of consumers. Chen and Yao (2016), De los Santos and Koulayev (2017), Koulayev (2014), and Ghose et al. (2012, 2014) study how rankngs affect consumer onlne choces n the hotel market resultng n poston effect estmates of up to $35 n De los Santos and Koulayev (2017). Ursu (2018) explots a random varaton n the rankng of the OTA Expeda to study the effect of rankngs on search and bookng behavor. She fnds that rankngs affect the search costs of consumers and that better rankng postons are assocated wth more clcks on the partcular offer: the hgher an offer s ranked, the hgher the probablty s that consumers wll clck on the offer n order to obtan more detaled nformaton. However, she fnds that once a consumer has clcked on an offer, the probablty for a bookng s not nfluenced by the rankng poston. Lu et al. (2015) study the relatonshp between the prcng of ntermedares, such as physcal travel agents, and the ntroducton of a new onlne drect sales channel of a hotel chan. Usng data of hotel room transactons from 2001 to 2007, they analyze the ntroducton of the drect onlne sales channel n 2002 and fnd a sgnfcant reducton of the ntermedares prce prema. Ths result suggests that there s competton between dfferent forms of hotel dstrbuton channels. Our work s related to the recent theoretcal lterature on the (ant-)compettve effects of prce party clauses (PPCs) of ntermedares, such as OTAs (Edelman and Wrght, 2015; Bok and Corts, 2016; Johnson, 2017; Wang and Wrght, 2017; Johansen and Vergé, 2017; 4 Wals and Schnkel, 2018). 5 To ths lterature we add the nsght that non-contractual measures, such as rankng the search results on factors other than maxmzng consumer matches, can have smlar effects as PPCs. Ths artcle also relates to the growng emprcal lterature on the effects of prce party clauses by onlne bookng platforms, such as Hunold et al. (2018) and Mantovan et al. (2017). Hunold et al. (2018) study the PPCs of OTAs usng meta-search prce data of hotels. They fnd that PPCs nfluence the prcng and avalablty of hotel rooms across onlne sales channels. In partcular, the abolton of s narrow PPC s assocated wth the hotels drect channel beng the prce leader more often. Moreover, they fnd that hotels make rooms more often avalable at when t does not use the narrow PPC. These fndngs ndcate that prcng across channels s mportant for hotels and also rase the queston of whether non-contractual measures that am at the OTA s prces beng lowest have become more mportant n jursdctons where contractual measures, n partcular prce party clauses, were restrcted. 3 Industry background: Onlne hotel bookng Dstrbuton channels. One can book hotels through varous channels. Tradtonally, a large share of consumers books ther room drectly at the hotel, both offlne by telephone or walk-n, and onlne va the hotel webste and e-mal. Accordng to the European hotel assocaton HOTREC, these channels make up 50 percent of all bookngs, the latter comprsng 14 and 16 percent, respectvely. 6 In the last decade, OTAs became very mportant for hotels as a dstrbuton channel. Whle the share of hotel bookngs through OTAs was already 22 percent n 2013, ths number steadly ncreased to 29 percent n 2017, comprsng around 75 percent of all webste-based bookngs of hotel rooms. The OTA ndustry s hghly concentrated n 2017 and Expeda accounted for more than 80 percent of those bookngs n Europe, wth havng, on average, a share of more than 60 percent. Rankng of hotel offers at OTAs. OTAs are ntermedares that pool offers of dfferent hotels and help consumers to fnd a hotel room. In response to a search request, consumers retreve a lst of recommended offers. The label for ths default lst s Our 5 Wth a prce party clause an OTA contractually oblges a hotel to not charge lower prces on (certan) competng sales channels, such as other OTAs and the drect channel of the hotel. They are also called best prce clauses and (retal) most favored naton (MFN) clauses. 6 Ths and the followng data s taken from the European Hotel Dstrbuton Study 2018 (last accessed August 31, 2018). 5 top pcks at and Recommended at Expeda. 7 Despte the ablty of consumers to refne ther search through flters (sortng by prce, locaton, etc.), there s evdence that a sgnfcant share of consumers reles on default rankngs. Usng a dataset from the Wharton Customer Analytcs Intatve, Ursu (2018) shows that only 34 percent of consumers sort or flter hotel search results at an undsclosed OTA. 8 The rest makes use of the default rankng, and as Ursu (2018) shows, hgh-ranked hotels receve more clcks (and hence more bookngs). De los Santos and Koulayev (2017) report for a prce comparson webste that more than 50 percent of users rely on the default rankng. Smlarly, Blake et al. (2016) report that on ebay between 67 and 85 percent of search requests on ebay have the default rankng. Although OTAs do not reveal ther default rankng algorthm, Expeda provdes a general dea of the typcal crtera. 9 Frst, the rankng depends on a prce-to-value benchmark, whch s based on crtera lke prce, ratngs, locaton, etc. Second, t depends on how well a hotel partners wth the OTA, e.g., by comparng room rates offered on the platform to those offered on other channels, or by assessng how much nformaton the hotel provdes on the platform. Thrd, a hotel s rankng poston s affected by the commsson rate t pays to the OTA. s rankng s stated to be dependent on nformaton provded by the hotelers and customers ncludng among others converson, avalablty, and prcng data. 10 Prcng. Most OTAs today use the agency model, where hotels sgn up at the OTA, provde detals regardng ther offers, and set retal prces on ther own. Any offers that match a specfc search request are lsted n the correspondng search output. Whle sgnng up s usually free of charge, the OTA demands a commsson for each bookng on ts webste. has used ths model for a long tme and we understand that Expeda also typcally uses ths model n Europe. 11 The commsson s a share of the hotel prce. 12 Base commsson rates are around 10 to 15 percent for both and Expeda and have remaned constant n recent years. However, effectve commsson rates can be sgnfcantly hgher. 13 offers a Vsblty Booster that allows hotels to pay hgher commssons n exchange for better rankng postons on specfc dates, and the 7 Labels last checked on August 31, See Ursu (2018), page 6 of the Onlne Appendx B, for detals (last accessed August 31, 2018). 9 See, for nstance, a communcaton by Expeda that targets hotelers (last accessed August 31, 2018). 10 See the respectve help page for hotelers on (last accessed August 31, 2018). 11 See the annual reports of and Expeda as well as the artcle Expeda and TrpAdvsor Separately Kll 2 Brands That Were Once Sster Companes (last accessed August 31, 2018). 12 See the respectve help page for hotelers on (last accessed August 31, 2018). 13 See Hunold et al. (2018), Onlne Appendx VIII, for references and detals. 6 Preferred Partner Program, whch also nvolves payng a hgher commsson for extra vsblty, among other thngs. 14 Expeda offers a smlar servce called Accelerator through whch hotels can mprove ther rankng poston by payng a hgher commsson. 15 The addtonal commsson pad for such servces can be as hgh as 10 to 15 percent. 16 Prce party clauses (PPCs). A major concern for OTAs s free-rdng, where consumers use the platform s search and comparson servce, but ultmately book through a cheaper channel, leavng the OTA wthout the commsson. As free-rdng s ncentvzed by lower prces on other channels, many OTAs have used, and partly stll use, prce party clauses (PPCs) n order to mtgate aggressve prcng. There are manly two types of PPCs to dstngush. Under a wde PPC, an OTA oblges the hotel not to charge a hgher prce on the OTA than on any other onlne (and partly offlne) bookng channel, whch n partcular ncludes other OTAs and the hotel s own drect sales channels. Narrow PPCs prohbt the hotel from offerng lower prces on ts drect onlne sales channels than at the OTA that mposes the clause, but do not contractually restrct the hotel s room prces at other OTAs. 17 These PPCs n the contracts between OTAs and hotels dffer fundamentally from prce matchng polces, where OTAs guarantee customers the lowest avalable prce for an offer. Both and Expeda had a prce matchng polcy n place durng the perod of observaton, wth Expeda restrctng ths guarantee to regstered users n late Natonal competton law enforcement or new natonal laws typcally target the contracts between the OTAs and the hotels n the respectve jursdcton. Varous natonal competton authortes n Europe consdered that (wde) PPCs could restrct competton between OTAs wth respect to commsson rates, whch s the man theory of harm (see the dscusson n secton 2). Fgure 1 shows a tmelne of polcy changes regardng PPCs. In December 2013, the German competton authorty prohbted the German ncumbent OTA HRS from applyng PPCs. 19 In Aprl 2015, followng jont nvestgatons, competton authortes n Sweden, France, and Italy smultaneously accepted commtments from to only mpose narrow PPCs. Subsequently, n June announced an extenson of these 14 See s webste on the Preferred Partner Programme (last accessed August 31, 2018). 15 See Expeda s webste on Vsblty (last accessed August 31, 2018). 16 See the artcle Frst Look at Expeda Accelerator Program for Improvng Hotel Placement (last accessed August 31, 2018). 17 See Hunold (2017) for detals and a comparson of dfferent decsons wth respect to PPCs n Europe. 18 See the archved webstes of and Expeda respectvely (last accessed August 31, 2018). 19 See German Federal Cartel Offce s decson prohbtng HRS to apply prce party clauses (last accessed August 31, 2018). 7 commtments to the rest of Europe. 20 Expeda reacted to ths n July 2015 by announcng that t would also abolsh ther wde PPCs n Europe. 21 Fgure 1: Polcy actons aganst prce party clauses (PPCs) of onlne travel agents (OTAs) Tmelne France, Italy, Sweden Competton Authortes Only Narrow PPCs for France Parlament No PPCs Austra Parlament N
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