Switching Costs, Network Effects, and Networking Equipment: Compatibility and Vendor Choice in the Market for LAN Equipment

Transcription

1 Assocaton for Informaton Systems AIS Electronc Lbrary (AISeL) ICIS 2002 Proceedngs Internatonal Conference on Informaton Systems (ICIS) December 2002 Swtchng Costs, Network Effects, and Networkng Equpment: Compatblty and Vendor Choce n the Market for LAN Equpment Chrs Forman Carnege Mellon Unversty Follow ths and addtonal works at: Recommended Ctaton Forman, Chrs, "Swtchng Costs, Network Effects, and Networkng Equpment: Compatblty and Vendor Choce n the Market for LAN Equpment" (2002). ICIS 2002 Proceedngs Ths materal s brought to you by the Internatonal Conference on Informaton Systems (ICIS) at AIS Electronc Lbrary (AISeL). It has been accepted for ncluson n ICIS 2002 Proceedngs by an authorzed admnstrator of AIS Electronc Lbrary (AISeL). For more nformaton, please contact elbrary@asnet.org.

2 SWITCHING COSTS, NETWORK EFFECTS, AND NETWORKING EQUIPMENT: COMPATIBILITY AND VENDOR CHOICE IN THE MARKET FOR LAN EQUIPMENT Chrs Forman Carnege Mellon Unversty Pttsburgh, PA USA Abstract Ths paper examnes the mportance of compatblty on buyer behavor n the market for LAN equpment over the perod 1996 through I provde evdence that swtchng costs drve frm establshments to purchase LAN equpment from ncumbent vendors. Because LAN equpment s a networked good, ncumbency affects vendor choce both when t occurs at the same establshment and/or at other establshments wthn the same frm. Moreover, compatblty across dfferent product lnes wthn the same vendor also nfluences vendor choce. Ths manfests tself n a buyer tendency to purchase routers and swtches from the same vendor. These propostons are explored n data on purchases of LAN equpment utlzng open standards such as the Ethernet networkng protocol, and represent the frst econometrc measurement of compatblty effects wthn products utlzng open standards. These fndngs show that there are strong economc ncentves to offer broad product lnes, and provde some ratonale for the acquston strateges of major vendors. 1 INTRODUCTION A key component of the strateges of many manufacturers of computng networkng equpment has been to offer broad product lnes. Csco Systems, Nortel Networks, and Lucent Technologes all pursued aggressve acquston strateges n the latter half of the 1990s to become a one stop shop of networkng gear. These frms beleved the ablty to provde a full lne of routers, swtches, and other networkng gear would provde them wth a compettve advantage over ther compettors. In partcular, Csco has aggressvely acqured other networkng frms, most notably n the multbllon dollar acqustons of frms lke StrataCom ($4.7 bllon), Cerent Corporaton ($6.9 bllon), and Arrow Pont Communcatons ($5.7 bllon), among others. For such a strategy to be successful, several condtons must hold. Frst, t requres that ncompatbltes across the products of dfferent vendors create swtchng costs (Klemperer 1995) for buyers. Second, broad product lne strateges depend on networkng equpment beng a network good that exhbts network externaltes. The combnaton of swtchng costs and network externaltes mples that legacy nvestments wll affect not only a buyer s vendor choce for smlar hardware, but also affects purchasng decsons across other products, so that, for example, an nstalled base n routers also nfluences swtch vendor choce. Moreover, unlke most goods that exhbt swtchng costs, legacy nvestments across an entre organzaton nfluence vendor choce at a partcular establshment n the frm. Despte the mportance of swtchng costs and networkng externaltes on product choce n hardware and software, there have been relatvely few emprcal papers that examne ths phenomenon. Greensten (1993) and Breuhan (1997) examne the role of swtchng costs on product choce n manframes and PC software. Gandal (1994) and Brynjolfsson and Kemerer (1997) examne the effects of network externaltes on spreadsheet prces, whle Kauffman et al. (2000) examne how network externaltes can create swtchng costs that nhbt adopton of a new electronc network n bankng. More recently, several papers have examned 2002 Twenty-Thrd Internatonal Conference on Informaton Systems 685

3 swtchng costs and brand loyalty wthn the context of consumer behavor n electronc markets (e.g., Brynjolfsson and Smth 2001; Chen and Htt 2001; Johnson et. al. 2000; Moe and Fader 2000). Ths paper examnes how product compatblty affects vendor choce n the market for routers and swtches, two major classes of local area network (LAN) equpment. Ths paper contrbutes to the exstng emprcal lterature on swtchng costs and network externaltes n three ways. Frst, the paper demonstrates how an exstng nstalled base n one product can spll over and affect purchasng decsons n another. Prevous work had examned swtchng costs n only a sngle-product envronment. In partcular, ths work shows that as swtches dffused wdely throughout the late 1990s, the combnaton of swtchng costs and network externaltes drove frms to purchase swtches from ther ncumbent router vendor. Second, the paper shows that, wthn the context of mult-establshment frms, ncumbency affects vendor choce both when t occurs at the same establshment and/or at other establshments at the same frm. These frst two fndngs show that n networked nformaton systems, the legacy problem s much more severe than commonly thought. Lock-n can occur due to pror nvestments of completely dfferent products, or from the nvestments of other establshments wthn the same frm. Fnally, the paper shows how ncumbency can nfluence vendor choce n a key component to IS nfrastructure. LAN equpment has facltated the rapd growth n the use of personal computers and the exploson n popularty of the Internet. Moreover, these products employed so-called open standards lke TCP/IP or Ethernet protocols that are commonly supposed to facltate nteroperablty across heterogeneous products. Ths research rases a cauton flag for optmsts who beleve Internet protocols wll greatly allevate nteroperablty problems. These hypotheses are tested by estmatng a nested logt model of vendor choce. In ths model, the probablty of choosng a partcular vendor s made a functon of buyer characterstcs and the extent of prevous buyer-vendor nteracton. To estmate these models, data from the Harte Hanks CI Technology database s used. The data set ncludes over 28,000 observatons from frms n the fnance and servces sectors over the perod 1996 through As wth most papers attemptng to measure the mportance of past behavor on current purchase decsons, ths paper faces the econometrc dentfcaton problem of dsentanglng the effects of state dependence versus unobserved heterogenety. 1 Buyers may contnue to purchase from the same vendor ether because of vendor lock-n or because that vendor s product s partcularly well suted to the buyer. Ths problem wll be mtgated somewhat when cross-product ncumbency effects are examned; unobserved heterogenety s more lkely to drve persstence n buyer behavor wthn rather than across products. 2 TECHNICAL BACKGROUND Routers dffused wdely wth the foundng of Csco Systems n the 1980s. Routers are used to drect packets of nformaton across a network; however, they also have functonalty that also enables them to montor and manage network traffc effcently. Ths added functonalty comes at a cost n the form of the addtonal tme t takes for routers to route packets. Swtches were ntroduced n the md-1990s n part as a soluton to the cost and latency problems of routers. Lke routers, swtches are used to drect packets of nformaton across a network. Ther desgn often results n faster packet forwardng and lower hardware prces than routers, but wthout the added functonalty of routers. Because routers and swtches perform the same basc functon, routng data packets, they are sometmes used as substtute products. Despte relatvely rapd dffuson of swtches, few adopters of swtchng technology abandoned routers entrely. Most buyers of swtches mantaned some routers n ther network, and most purchased routers concurrently wth ther swtches. Ths s because the network management and securty features of routers remaned necessary. Routers, because of ther added functonalty, form the brans of the network. Thus, routers and swtches are also commonly employed as complements. 1 Ths problem has been examned extensvely elsewhere; for example, see Heckman (1981) Twenty-Thrd Internatonal Conference on Informaton Systems

4 3 THEORETICAL BACKGROUND AND RESEARCH HYPOTHESES Klemperer (1995) descrbes how a buyer s desre for compatblty between exstng systems and new purchases can lead to swtchng costs when changng vendors. Swtchng costs can cause buyers to exhbt brand loyalty and so ncrease the lkelhood of repeat purchases from ncumbent vendors. Klemperer lsts several types of such swtchng costs, although n the market for LAN equpment they are most lkely to arse from two sources: (1) need for compatblty wth exstng equpment and (2) costs of learnng new brands. Klemperer also notes the potental effects of swtchng costs n multproduct competton. If buyers value varety and prefer to purchase systems consstng of multple components and f there are swtchng costs to purchasng products from dfferent vendors, then vendors that sell sngle products only may be at a dsadvantage to those who produce a full product lne and who can enable buyers to avod swtchng costs n multproduct purchases. 2 Ths theory leads us to expect several patterns of buyer behavor. The frst hypothess s that we expect buyers wth an nstalled base of routers at the establshment to be more lkely to purchase new routers from the ncumbent vendor. Smlarly, we expect swtch ncumbency at the establshment to affect a buyer s choce of swtch vendor. Hypothess 1: Buyers face costs n changng router vendors. Buyers wll be more lkely to purchase from a router vendor wth ncumbency at the establshment, relatve to an dentcal buyer wthout ncumbency. Hypothess 2: Buyers face costs n changng swtch vendors. Buyers wll be more lkely to purchase from a swtch vendor wth ncumbency at the establshment, relatve to an dentcal buyer wthout ncumbency. When buyers that are part of mult-establshment frms purchase networkng equpment, they must be concerned not only wth the local nstalled base of equpment at the buyer s establshment but also wth the nstalled base of networkng gear used throughout the frm. Thus, the second set of hypotheses s that nstalled base external to the ste but wthn the frm wll nfluence vendor choce. Hypothess 3: Buyers face costs n choosng a router vendor dfferent from that nstalled n other establshments throughout the same frm. Buyers wll be more lkely to purchase from a router vendor wth ncumbency throughout the frm, relatve to an dentcal buyer wthout ncumbency. Hypothess 4: Buyers face costs n choosng a swtch vendor dfferent from that nstalled n other establshments throughout the same frm. Buyers wll be more lkely to purchase from a swtch vendor wth ncumbency throughout the frm, relatve to an dentcal buyer wthout ncumbency. The next two hypotheses relate to the effects of compatblty across products wthn the same vendor. Hypothess fve states that nstalled base n routers wll nfluence the choce of swtch vendor. Hypothess 5: Buyers face swtchng costs n choosng dfferent router and swtch vendors. Buyers wll be more lkely to purchase from a swtch vendor wth router ncumbency at the ste or throughout the frm, relatve to an dentcal buyer wthout ncumbency. Along the same lnes, the costs of swtchng supplers should nfluence vendor choce among buyers purchasng multple products smultaneously, ndependent of nstalled base effects. Hypothess 6: Buyers face swtchng costs n choosng dfferent router and swtch vendors. Buyers purchasng routers and swtches smultaneously wll face costs of purchasng from dfferent vendors. 2 Buyers may value varety f, for example, a vendor s products are horzontally dfferentated heterogeneously across segments of the router and/or swtch markets Twenty-Thrd Internatonal Conference on Informaton Systems 687

5 4 STRUCTURE OF THE MODEL Buyers n ths model are assumed to be ndvdual stes wthn a frm. All stes assocate some utlty wth a choce j, U j. Utlty takes the form of a random utlty model (e.g., McFadden 1981), U = u + ε. Thus, a ste s utlty for a choce s decomposed nto two components: (1) a determnstc component term ε j u j j j j that s a resdual that captures the effects of unmeasured varables. that s a functon of ste as well as choce characterstcs and (2) an error A choce n the model conssts of (1) a 0/1 decson of whether to purchase a router; (2) a 0/1 decson of whether to purchase a swtch; (3) f a router s purchased, a choce of router vendor; and (4) f a swtch s purchased, a choce of swtch vendor. Buyers choose a router or swtch vendor rather than a partcular model of networkng equpment. Ths s due to lmtatons wth the data set, for the data do not dentfy model. In ths paper, the assumpton s that utlty s addtvely separable nto components that vary wth the decson to purchase a router (r), the decson to purchase a swtch (s), the choce of router vendor (v), and the choce of swtch vendor (w). Each decson j can be ndexed by a quadruple subscrpt (r,s,v,w). Under these assumptons the utlty functon can be wrtten as U = α R + β S + γ V + δ W + ε j r r, s r, s, v r, s, v, w r, s, v, w where α, β, γ, and δ represent parameters to be estmated and the vectors Rr, Sr, s, Vr, s, v, and Wr, s, v, w represent varables affectng the decson to purchase a router and swtch and the decsons of router and swtch vendor, respectvely. Followng the lterature on the nested logt model (e.g., McFadden 1981), we assume that the error term ε rsvw,,, follows a generalzed extreme value dstrbuton. I further assume that the decson process can be nested accordng to Fgure 1. The jont probablty of a partcular choce j n ths model wll be P = P P P P j r sr vsr, wvsr,, where P s the jont probablty of choosng a partcular (r,s,v,w) combnaton, represents the margnal probablty of j P r P s r P vs, r purchasng a router, s the probablty of purchasng a swtch condtonal on router choce, s the condtonal probablty of purchasng from a partcular router vendor, and P wv, s, r s the condtonal probablty of purchasng from a swtch vendor. The generalzed extreme value dstrbuton mples that gven choces (r,s,v), the condtonal probablty of makng a choce of * swtch vendor w takes the followng form: P w* v, s, r = exp( δ W ) w Cvsr,, rsvw,,, * Wrsvw,,, exp( δ ) [1] where C vsr,, denotes the set of choces avalable to the buyer at the node defned by (v,s,r). At the next level up, the probablty of choosng router vendor * v wll be P * v s, r = exp( γ V + λi ) v Crs, * * rsv,, rsv,, Vrsv,, + λirsv,, exp( γ ) [2] Twenty-Thrd Internatonal Conference on Informaton Systems

6 Do Not Purchase Router Purchase Router Do Not Purchase Purchase Do Not Purchase Purchase Swtch Swtch Swtch Swtch Router Model Router Model Swtch Model Swtch Model 100 Fgure 1. Networkng Gear Choce Model where Irsv,, = log exp( δ Wrsvw,,, ) s the nclusve value, the expected aggregate value of choce v. The coeffcent w Crsv,, on the nclusve value, 8, measures the dssmlarty of alternatves avalable to the buyer gven dfferent choces v. McFadden (1981) has shown that the choce structure gven by Fgure 2 s consstent wth expected utlty maxmzaton f and only f the nclusve value parameter n [2] les wthn the unt nterval. The choce probabltes Ps r and P r are constructed analogously to [2], wth nclusve values from lower levels of the tree servng as components of the expected utlty of upper level choces. I estmate the model usng sequental maxmum lkelhood. Percent Com Bay Csco Other Routers Swtches Notes: Sample s Shows condtonal probablty of purchasng from ncumbent vendor n a year, among those stes purchasng routers and swtches. Other ncludes all vendors besdes 3Com, Bay Networks, and Csco (ncludng Cabletron). Fgure 2. Loyalty Rates for Routers and Swtches 2002 Twenty-Thrd Internatonal Conference on Informaton Systems 689

7 5 DATA 5.1 Sample Data on technology usage was obtaned from the CI Technology Database (hereafter CI database) over the perod 1995 through The unt of observaton n the CI database s a ste. 3 To keep the analyss of manageable sze, data was obtaned from the CI database on SIC codes (Fnance, Insurance, and Real Estate), 73 (Busness Servces), 87 (Engneerng, Research, Management, and Accountng), and 27 (Prntng and Publshng). The sample contans data on all stes of over 100 employees from the CI database over the sample perod. All stes are from the Unted States. An observaton n the database contans the stock of technology goods nstalled at the ste. To nfer purchase decsons, the change n quantty nstalled from year to year for each vendor s calculated. Unfortunately, the data do not contan model nformaton on LAN equpment, so the partcular model purchased cannot be dentfed. Because of mssng data, many observatons had to be dropped. Stes that were not n the database for two consecutve years and for whch nferences on purchase quanttes could not be made were dropped. For many smaller vendors n the database, the number of purchase observatons was too small to estmate the effects of nstalled base; stes purchasng from or who had an nstalled base from these smaller vendors were dropped. The vendor decson of frms that purchased routers from 3Com, Bay Networks, and Csco and that purchased swtches from 3Com, Bay Networks, Cabletron, and Csco were examned. 5.2 Varables Varables n the model can be dvded nto three categores: (1) those nfluencng the vendor decson drectly and that ndcate the degree of pror buyer/vendor nteracton; (2) those nfluencng the vendor decson drectly and that control for buyer heterogenety; and (3) those nfluencng the decson of whether to purchase a router or swtch. 4 Ths secton descrbes the frst set of varables. Descrptons of the second set of control varables are ncluded n Table 1. 5 The varables IRTR and ILSW are dummy varables ndcatng that the ste has an nstalled base of routers and swtches from a partcular vendor. These varables wll measure the mportance of ncumbency at the ste level. If prevous buyer-vendor nteracton has an mportant effect on vendor choce, then we expect that the coeffcents on these varables wll be postve. The varables PCLSW and PCRTR are defned as the percentage of a partcular vendor s swtches and routers nstalled throughout a frm. Thus, these varables test whether frm-wde (as opposed to ste-wde) nstalled base effects are mportant. The varable RSCOMP measures potental effects of compatblty wthn a vendor s product lne. RSCOMP s an ndcator varable that s one when a choce ncludes the same router and swtch vendor. If product compatblty across routers and swtches s mportant to buyers when makng a vendor choce, then we should expect the coeffcent on ths varable to be postve f there are costs to havng dfferent router and swtch vendors. 3 See secton 6 for a descrpton of ste. 4 Unfortunately, nformaton on router lst or transacton prce s not avalable. Varatons n prce, as well as any ncentves vendors may provde to reduce buyer swtchng costs, wll be absorbed n the vendor-specfc constant. They wll nfluence the unobserved component of the model only nsofar as relatve prce vares across products or ncentves vary across customers for a partcular vendor. 5 To conserve space, descrptve statstcs on the thrd set of varables, those descrbng the decson to purchase, are not ncluded. These varables ncluded nformaton on the sze of nstalled base of routers and hubs, the change n the number of network nodes, the types of Internet applcatons used, dummes ndcatng used of advanced networkng technologes (e.g., FDDI or fast Ethernet), ndustry dummes, and year dummes. Also, the results from the frst and second stages of the model that estmate factors determnng whether the ste wll purchase are not reported Twenty-Thrd Internatonal Conference on Informaton Systems

8 Table l. Means, Standard Devatons, Mnmums, and Maxmums for Sample Descrpton Mean Standard Devaton Mnmum Maxmum Varables measurng prevous buyer/vendor nteracton IRTR Indcates nstalled base of routers at ste ILSW Indcates nstalled base of swtches at ste PCRTR Percentage of vendor s routers nstalled n frm PCLSW Percentage of vendor s swtches nstalled n frm RSCOMP Indcates choce of dentcal router and swtch vendor Varables measurng buyer heterogenety DHQ Indcates ste s frm-wde or regonal frm headquarters STIME Indcates second-tme purchaser of networkng gear TOTNODES Total network nodes ,691 TOTPROT Total network protocols Source: Harte Hanks Market Intellgence and author s calculatons 6 RESULTS 6.1 Unvarate Statstcal Evdence Fgure 2 shows the loyalty rates of corporate stes that are purchasng routers and swtches. A ste represents an ndvdual geographc locaton wthn a frm, and s smlar to the concept of establshment used n government statstcs. A loyalty rate shows the condtonal probablty of purchasng from the ncumbent vendor, gven that the ste s purchasng routers or swtches that year. For each of the Bg Three vendors of 3Com, Bay Networks, and Csco, loyalty rates for routers and swtches are qute hgh, rangng from 47.8 percent to 83.5 percent n routers and from 67.3 percent to 76.5 percent n swtches. Loyalty rates for routers of other vendors are low; many of ther buyers eventually mgrated to Csco. Loyalty rates for swtches of other vendors are hgher. 6 In all, smple unvarate analyss suggests buyer patterns are consstent wth hypotheses 1 and 2. Table 2 shows the dstrbuton of vendor choces for buyers who jontly purchase routers and swtches, and provdes some evdence for hypothess 6. 7 The table shows that among stes purchasng from one router vendor and one swtch vendor, roughly 46 percent buy from the same vendor. 8 6 The varance n loyalty rates for routers s greater than that for swtches because some establshments wth an nstalled base n Bay, 3Com, or other routers mgrated to Csco over the sample perod. Ths was n part because many of the vendors n the other category exted the market. 7 To be precse, the table shows the dstrbuton of purchases from buyers purchasng one router and one swtch. Results from stes purchasng from multple router and swtch vendors are qualtatvely smlar, however are dffcult to dsplay n tabular form. 8 Note that ths 46 percent s less than the percentage of observatons along the dagonal because some purchases n the other category may nclude vendors dfferent than the vendor the establshment has n ts nstalled base Twenty-Thrd Internatonal Conference on Informaton Systems 691

9 Table 2. Frequency of Vendor Choce Among Frms Makng Jont Router and Swtch Choces, Router/ Swtch Vendor 3Com Bay Csco Other 3Com % 3.6% 0% 7.1% Bay % 72.8% 8.6% 11.1% Csco % 17.5% 38.4% 26.8% Other % 18.9% 5.7% 41.5% Source: Harte Hanks Market Intellgence and author s calculatons Notes: Frst row of lne provdes frequency. Second row of lne shows probablty of purchasng from swtch vendor condtonal on concurrently purchasng from router vendor. 6.2 Parameter Estmates Table 3 presents the parameter estmates of the nested logt model. 9 To conserve space, only the results from the router and swtch vendor decson are presented. These results depct the vendor decson, condtonal on the decson to buy routers and/or swtches. The coeffcents on the varables measurng pror buyer-vendor nteracton are allowed to vary based on whether the buyer s a standalone ste or part of a larger frm. The model s estmated over the entre sample perod. 10 The mddle column of Table 3 shows the parameter estmates from the lowest level of the nested logt model, the one that ndcates swtch vendor choce. The presence of an ncumbent swtch vendor appears to have an mportant effect on a buyer s decson, provdng support for hypothess 2. Frm-wde ncumbency may also play a role n the swtch vendor decson, as shown by the varable PCLSW, however the effects are weaker and just barely nsgnfcant at the 10 percent level. Thus, the coeffcent estmates provde some support for hypothess 4. Hypothess 5 suggests that the presence of an ncumbent router vendor may also have an effect on the swtch vendor decson. The effect of router vendor ncumbency at a ste (IRTR) s sgnfcant; however, t s less powerful than the effects of swtch ncumbency. Frm-wde router ncumbency (PCRTR) appears not to be mportant n determnng a ste s swtch vendor. Because frm branches are most lkely to connect to other stes and to the outsde world through routers (rather than swtches), the nsgnfcance of frm-level effects on swtch vendor choce are unsurprsng. Further confrmng the mportance of vendor product-lne compatblty and provdng evdence n support of hypothess 6 s the coeffcent on the varable RSCOMP. RSCOMP shows that stes purchasng routers and swtches smultaneously are lkely to purchase them from the same vendor. The varable s a one-way measure of the mportance of compatblty,.e., router vendor choce may feed nto the smultaneous decson of swtch vendor but not the other way around. However, because of the structured way n whch networks are commonly bult, ths lmtaton s not a major concern. 9 A potental problem wth use of the nested logt model s that the order n whch decsons are nested determnes the error process and can affect estmaton of the parameters. The model was estmated accordng to an alternatve nestng structure n whch router decsons are nested beneath swtch decsons, however one of the nclusve value parameters was outsde of the range consstent wth utlty maxmzaton. Based on ths evdence and because strong prors exst that the error structure consstent wth Fgure 1 s the correct one for ths model, the results from the baselne model of Fgure 1 are presented. The results of the model wth ths alternatve nestng were also consstent wth hypotheses 1 through Year dummes are ncluded n the frst two stages of the model Twenty-Thrd Internatonal Conference on Informaton Systems

10 Table 3. Results from Demand Estmaton: Choce of Router and Swtch Vendor Varable Swtch Vendor Router Vendor Varables measurng pror vendor nteracton: standalone stes ILSW **... (0.4224)... IRTR ** ** (0.2693) (0.4617) RSCOMP **... (0.2158)... Varables measurng pror vendor nteracton: mult-establshment frms ILSW **... (0.3506)... PCLSW (0.2682)... IRTR ** ** (0.2787) (0.2660) PCRTR ** (0.2726) (0.2023) RSCOMP **... (0.1712)... Varables measurng buyer heterogenety DBAY (0.2965) (0.3345) DCAB **... (0.3744)... DCIS ** ** (0.3152) (0.2811) DBAY TOTNODES ** * (0.0206) (0.0242) DCAB TOTNODES *... (0.0235)... DCIS TOTNODES ** * (0.0194) (0.0223) DBAY TOTPROT (0.1739) (0.1971) DCAB TOTPROT (0.1954)... DCIS TOTPROT (0.1647) (0.1629) DBAYS TIME ** (0.2471) (0.3624) DCABS TIME **... (0.3055)... DCISS TIME * ** (0.2794) (0.2987) DBAY DHQ (0.2950) (0.3739) DCAB DHQ (0.3520)... DCIS DHQ (0.3045) (0.3321) 2002 Twenty-Thrd Internatonal Conference on Informaton Systems 693

11 Varable Swtch Vendor Router Vendor INCL VALUE ** (0.3270) N 28,088 28,088 Log-Lkelhood Source: Harte Hanks Market Intellgence and author s calculatons. Notes: *Indcates sgnfcance at 10% level. **Indcates sgnfcance at 5% level. Mssng varables n router decson because there s no Cabletron nteracton term. The parameter estmates from the thrd level of the model, ndcatng router vendor choce, are depcted n the far rght column of Table 3. In ths level, varables measurng the effects of swtch nstalled base on router purchases are not ncluded. The reason s that because routers are more complcated than swtches, the expectaton s that product compatblty ssues arsng from an nstalled base of swtches wll be relatvely unmportant. 11 Router ncumbency appears to have had an mportant mpact on the router vendor decson. Among standalone stes, the mportance of router vendor ncumbency was strong and sgnfcant. Vendor ncumbency at the ste was sgnfcant although somewhat less mportant for stes that were part of a larger corporaton; however, combned wth frm-wde ncumbency effects (PCRTR), the mpact of vendor ncumbency was very smlar (2.438 vs for stes wthn frms that have an nstalled base comprsed completely of one vendor). Thus, there s strong support for hypothess 1. Frm-wde ncumbency also appears to have an mportant effect on router vendor choce, provdng support for hypothess 3. Because branch offce routers must be able to frequently communcate wth other stes wthn the frm, ths result s expected. 6.3 The Effects of Compatblty The effects of ncumbency vary wth a ste s characterstcs. To measure the effects of ncumbency whle controllng for ste heterogenety, the parameter estmates of the above model are used to smulate the probablty of choosng a partcular router and swtch vendor wth and wthout vendor ncumbency at the ste level. Thus, the smulatons show the mpact of changng one factor ste-level vendor ncumbency on vendor choce. These smulatons are performed for all stes purchasng routers and/or swtches; stes that do not purchase networkng gear are not ncluded n the smulatons. Tables 4 and 5 present the sample means of these smulatons. Both tables examne the effects of ncumbency when the ste s and s not jontly purchasng routers and swtches. Table 4 examnes the effects of ste-level ncumbency on the router vendor decson. It shows that, dependng on the crcumstances, vendor ncumbency ncreases the probablty of purchase from 14 percent to over 25 percent. Csco ncumbency at a ste vrtually ensures that a buyer wll purchase Csco agan. Smulatons showng frm-level effects (not ncluded) showed smlar results. Table 5 shows the effects of ste-level ncumbency on swtch purchases. Smulatons showng frm-level effects showed smlar results. The effects of ncumbency on vendor choce are dramatc. The smallest mean ncrease n probablty assocated wth ncumbency s 27.4 percent. In most cases, the ncrease n probablty s above 34 percent. Table 5 shows somethng else of note. The dstrbuton of swtch market shares dffers wdely dependng on whether a ste s concurrently purchasng a router. 12 Frms concurrently purchasng a router are much more lkely to purchase from Csco and less lkely to purchase from other vendors. Cabletron n partcular fares poorly among stes smultaneously purchasng routng gear. 13 Ths result suggests that broad product lnes are mportant, and s consstent wth the strategy of major vendors to obtan swtchng 11 Ths hypothess was affrmed emprcally n regressons that ncluded the effects of swtch nstalled base. 12 Strctly speakng, of course, these probabltes do not represent true market shares, as they only represent probabltes of purchasng from a partcular vendor, and do not nclude the effects of quantty or value at all. Stll, they represent an mportant pont. 13 The low lkelhood of Cabletron swtch purchase among frms purchasng routers s compounded by the fact that observatons n whch frms purchased Cabletron routers were dropped. However, because the number of such observatons was so low (see footnote 8), the bas created should be small Twenty-Thrd Internatonal Conference on Informaton Systems

12 Table 4. Effects of Incumbency at Ste Level on Router Purchases A. Stes not concurrently purchasng swtch Vendor Probablty wth Incumbency Probablty wthout Incumbency 3Com Bay Networks Csco B: Stes concurrently purchasng swtch Vendor Probablty wth Incumbency Probablty wthout Incumbency 3Com Bay Networks Csco Source: Harte Hanks Market Intellgence and author s calculatons. Notes: Probabltes calculated for stes purchasng routers n the gven perod. Probabltes represent sample means of probablty of purchasng from vendor gven that the ste does and does not have an nstalled base wth the vendor n queston. Table 5. Effects of Incumbency at Ste Level on Swtch Purchases A: Stes not concurrently purchasng router Vendor Probablty wth Incumbency Probablty wthout Incumbency 3Com Bay Networks Cabletron Csco B: Stes concurrently purchasng router Vendor Probablty wth Incumbency Probablty wthout Incumbency 3Com Bay Networks Cabletron Csco Source: Harte Hanks Market Intellgence and author s calculatons. Notes: Probabltes calculated for stes purchasng swtches n the gven perod. Probabltes represent sample means of probablty of purchasng from vendor gven that the ste does and does not have an nstalled base wth the vendor n queston Twenty-Thrd Internatonal Conference on Informaton Systems 695

13 technology through acquston. The results of Table 5 suggest that such frms may have been correct n ther assessment of the mportance of havng a broad product lne. 7 CONCLUSION Ths paper examnes the effects of compatblty on buyer choce n the market for LAN equpment. It shows that even controllng for buyer heterogenety, the presence of an nstalled base of equpment affects the choce of vendor when purchasng routers and swtches. Pror research s extended by showng that swtchng costs can assume a partcularly harmful form when combned wth network externaltes. In such an envronment, swtchng costs not only nfluence wthn-product choces at an establshment, but also reach across establshments and across product lnes. Moreover, the paper shows that the use of open standards such as Ethernet or TCP/IP has done lttle to mtgate ths problem. Ths fndng confrms the demand-sde ncentve for the aggressve acquston strateges pursued by some networkng vendors. For IS executves, t also has potentally worrsome consequences for the future of the legacy problem n a networked world. These ntal results suggest several potental avenues for future research. One aspect of the buyer-vendor relatonshp left unexplored n ths paper s the role of thrd-party network managers and IT outsourcng on vendor choce. IT outsourcng may strengthen the effects of ncumbency f thrd-party frms are assocated wth partcular vendors; alternatvely, thrd-party network managers or desgners may be able to help ther clents overcome swtchng costs. Another potental course would be to examne the effects of swtchng costs on the dffuson of swtchng technology. The framework and data used here are well-suted to address these questons. 8 ACKNOWLEDGMENTS Ths paper was derved from Chapter 3 of my Northwestern Unversty dssertaton. I am very grateful to Shane Greensten for hs gudance and support. I thank Davd Besanko, Ranjay Gulat, Mke Mazzeo, and Mark Doms for helpful dscussons. I thank the General Motors Strategy Center and the Kellogg School of Management for fnancal support, and Harte Hanks Market Intellgence for provdng essental data. 9 REFERENCES Breuhan, A. Innovaton and the Persstence of Technologcal Lock-In. Unpublshed Doctoral Dssertaton, Stanford Unversty, Brynjolfsson, E., and Kemerer, C. Network Externaltes n Mcrocomputer Software: An Econometrc Analyss of the Software Market, Management Scence (42), 1996, pp Brynjolfsson, E., and Smth, M. D. Consumer Decson-Makng at an Internet Shopbot: Brand Stll Matters, Journal of Industral Economcs (49), 2001, pp Chen, P-Y., and and Htt, L. Measurng Swtchng Costs and Ther Determnants n Internet-Enabled Busnesses: A Study of the Onlne Brokerage Industry, Workng Paper, Wharton School School of Busness, Unversty of Pennsylvana, Gandal, N. Hedonc Prce Indexes for Spreadsheets and an Emprcal Test of the Network Externaltes Hypothess, RAND Journal of Economcs (25), 1994, pp Greensten, S. M. Dd Installed Base Gve an Incumbent Any (Measurable) Advantages n Federal Computer Procurement?, RAND Journal of Economcs (24), 1993, pp Heckman, J. J. Heterogenety and State Dependence, n S. Rosen (ed.), Studes n Labor Markets. Chcago: Unversty of Chcago Press, Johnson, E., Moe, W., Fader, P., Bellman, S., and Lohse, J. On the Depth and Dynamcs of Onlne Search Behavor, Workng Paper, Wharton School of Busness, Unversty of Pennsylvana, Kauffman, R. J., McAndrews, J., and Wang, Y-M. Openng the Black Box of Network Externaltes n Network Adopton, Informaton Systems Research (11), 2000, pp Klemperer, P. Competton When Consumers Have Swtchng Costs: An Overvew wth Applcatons to Industral Organzaton, Macroeconomcs, and Internatonal Trade, Revew of Economc Studes (62), 1995, pp McFadden, D. Econometrc Models of Probablstc Choce, n C. F. Mansk and D. McFadden (eds.), Structural Analyss of Dscrete Data wth Econometrc Applcatons. Cambrdge, MA: MIT Press, Moe, W., and Fader, P. Capturng Evolvng Vst Behavor n Clckstream Data, Workng Paper, Wharton School of Busness, Unversty of Pennsylvana, Twenty-Thrd Internatonal Conference on Informaton Systems