Leveraging Customer Information for Competitive Advantage.

Transcription

1 Leveragng Customer Informaton for Compettve Advantage. Raj Srnvasan and Gary Llen The Pennsylvana State Unversty ISBM Report Insttute for the Study of Busness Markets The Pennsylvana State Unversty 402 Busness Admnstraton Buldng Unversty Park, PA (814) or (814) Fax

2 Abstract Internet and database technologes enable marketers to collect ever more extensve nformaton on ther customers needs, preferences and past behavors, but marketers often clam that they are challenged to make effectve use of the nformaton. Despte the substantal lterature on market nformaton utlzaton, the topc of customer nformaton has receved lmted attenton from marketng researchers. Does the generaton and use of customer nformaton lead to hgher levels of customer satsfacton and mproved frm performance? And do these relatonshps hold n general, or are there any envronments under whch these relatonshps are dfferent? We seek to address ths gap n the lterature by ) developng the customer nformaton management construct and ) studyng the effects of customer nformaton management on customer satsfacton and frm performance. In ths paper, we also examne the moderatng effects of a frm s customer envronments on the relatonshp between customer nformaton management and customer satsfacton and performance respectvely. Data from a natonal survey of 218 marketng executves provdes strong support for a postve relatonshp between customer nformaton management and customer satsfacton and frm performance that s robust to contexts characterzed by varyng levels of customer heterogenety and customer relatonshp ntensty. In sum, ths research suggests that customer nformaton s a knowledge asset that can be leveraged to mprove frm performance. Key Words Market nformaton Customer nformaton Knowledge Management

3 INTRODUCTION Internet and database technologes enable marketers to collect ever more extensve nformaton on ther customers needs, preferences and past behavors, but marketers often clam that they are challenged to make effectve use of the nformaton. Indeed, marketers mplctly assume that f they have extensve nformaton about ther customers and use that nformaton to gude ther actons, then they wll be rewarded n the marketplace wth greater market share, hgher profts and the lke. But s ths assumpton true? Does the generaton and use of customer nformaton lead to hgher levels of customer satsfacton and mproved frm performance? And do these relatonshps hold n general, or are there any envronments under whch these relatonshps are dfferent? Despte the substantal lterature (Deshpande, Farley and Webster 1993; Kohl and Jaworsk 1990; Jaworsk and Kohl 1993; Moorman 1995; Narver and Slater 1990; Snkula 1994) on market nformaton utlzaton, the use of customer nformaton has not receved academc attenton 1. Ths paper addresses the relatonshp between customer nformaton management and frm performance. Consstent wth past research on organzatonal utlzaton of nformaton (Menon and Varadarajan 1992; Moorman 1995), we defne customer nformaton management to nclude both the generaton and use of customer nformaton. We model the lnk between customer nformaton management, customer satsfacton and frm performance and examne how these relatonshps are modfed by two aspects of the frm s envronment customer heterogenety and customer relatonshp ntensty. The paper s structured as follows. We frst defne the customer nformaton management construct. We then suggest a conceptual framework and a related set of models lnkng customer 1

4 nformaton management, customer satsfacton and frm performance. Based on ths framework, we develop hypotheses about the effects of customer nformaton management on customer satsfacton and frm performance and the moderatng effects of customer envronment characterstcs on these lnkages. Followng that, we descrbe the sample, methodology and the results of the tests of hypotheses. We conclude wth a dscusson of the manageral mplcatons and then dentfy the lmtatons of ths research and outlne future research opportuntes n ths area. Our results show that customer nformaton management has a strong drect postve effect both on customer satsfacton and frm performance. Our data also provdes support for a strong ndrect postve effect of customer nformaton on frm performance, through ts effect on customer satsfacton. These relatonshps show no sgnfcant contngences, suggestng that our results are robust to varyng levels of customer heterogenety and customer relatonshp ntensty. CUSTOMER INFORMATION MANAGEMENT DEFINED We defne customer nformaton as nformaton 2 about the atttudes and behavors of the frm s current, past and prospectve customers. The term customer n ths defnton ncludes both end-users of the products and servces and channel members ncludng dstrbutors, wholesalers and retalers (Jaworsk and Kohl 1993). Customer nformaton may be collected and used ether at the aggregate market level, at the segment level or at the level of the ndvdual customer. Consder, Staples Drect, a dvson of Staples Inc., the offce products superstore, whch targets small to medum szed-frms wth between 5 and 50 employees. Although, the company s prvate label credt card and call center make t possble to know each customer ndvdually, the frm manages customer nformaton at the segment level because of the small economc value of each 2

5 customer. However, Staples Natonal, another dvson amed at large corporate procurement departments has average account szes n excess of $ 1 mllon and manages customer nformaton at the ndvdual account level. The extant lterature conceptualzes organzatonal nformaton actvtes as a seres of processes that nclude ) nformaton generaton (Kohl and Jaworsk 1990; Moenaert and Souder 1996; Moorman 1995) and ) nformaton utlzaton (Menon and Varadarajan 1992). Consstent wth past research, we conceptualze the construct of customer nformaton management at the organzatonal level as a two-dmensonal construct that ncludes both customer nformaton generaton and customer nformaton utlzaton. Customer nformaton generaton A frm must generate customer nformaton before t can use the nformaton. Some researchers suggest that f more nformaton s avalable, then executves are more lkely to use t (Shrvastava 1987). However, usablty assessments of nformaton must be made pror to ts utlzaton and these assessments are mportant n affectng the usage of nformaton (Day 1994; Menon and Varadarajan 1992; Moenaert and Souder 1996). Hence, we defne customer nformaton generaton to nclude: 1) customer nformaton avalablty and 2) customer nformaton nterpretaton. Informaton avalablty refers to the avalablty of nformaton n an organzaton and encompasses the two processes of nformaton acquston and nformaton transmsson (Kohl and Jaworsk 1990; Moorman 1995). The frm must have the necessary nformaton systems to collect nformaton about ts customers at the rght tme and at the rght level of aggregaton for subsequent use. 3

6 Informaton nterpretaton refers to processes by whch nformaton s gven meanng (Daft and Weck 1984). Extant emprcal research on nformaton utlzaton n organzaton (Moenaert and Souder 1996) suggests that nformaton s assessed on the bass of 1) relevance 2) comprehensblty and 3) tmelness and 4) accessblty before t s ncorporated n manageral decson makng. Customer nformaton utlzaton Customer nformaton utlzaton 3 s the extent to whch customer nformaton s used to gude marketng strateges and decsons (John and Martn 1984). Menon and Varadarajan (1992) and Moorman (1995) proposed a mult-dmensonal conceptualzaton of nformaton utlzaton ncludng drect (nstrumental) use and ndrect (conceptual) use of nformaton 4. Instrumental use of customer nformaton refers to the use of customer nformaton n problem solvng and operatons (Caplan, Morrson and Stambaugh 1975). For example, customer nformaton may be used n order to customze product offerngs to customers based on customer preferences and needs. Conceptual use of customer nformaton refers to the ndrect use of nformaton for general understandng that has an ndrect nfluence on manageral decson makng (Menon and Varadarajan 1992; Moorman 1995). For nstance, customer nformaton that s generated and avalable to a frm s managers may be used n less drect ways to stmulate the plannng of new product platforms or to help understand and react to general market trends. In the next secton, we present our conceptual framework, develop our hypotheses and present a model of the proposed relatonshps between customer nformaton management, customer satsfacton and frm performance. 4

7 CONCEPTUAL FRAMEWORK, HYPOTHESES AND MODEL Conceptual Framework and Hypotheses We examne the relatonshp between customer nformaton management (.e. generaton and usage of nformaton) and customer satsfacton and frm performance wthn a conceptual framework as shown n Fgure 1. In the followng paragraphs, we descrbe the relatonshps n ths framework and formally state our hypotheses. (Fgure 1 here) Effect of Customer Informaton Management on Customer Satsfacton Usng customer nformaton, a frm can develop and mplement better targeted marketng programs for ts dfferent customer segments (or ndvdual customers) n terms of customzed product offerngs, communcatons, prcng and dstrbuton. For example, Staples Natonal uses customer nformaton at the level of the ndvdual customer to desgn customzed product offerngs, prcng and delvery terms for each account based on customer preferences. These targeted offerngs should result n hgher customer satsfacton among Staple Natonal s customers. Frms that do not use customer nformaton, on the other hand, wll be more lkely to mplement a common marketng strategy across all customers resultng n lower customer satsfacton. Hence, H1: The greater the level of customer nformaton management n an organzaton, the more satsfed ts customers. Drect Effect of Customer Informaton Management on Frm Performance Accordng to the resource-based vew of the frm (Peteraf 1993; Wernerfelt 1984), resources are frm-specfc assets that are dffcult to mtate. Knowledge assets are strategc resources that are 5

8 sources of economc profts to the frm (Itam and Roehl 1987; Teece, Psano and Shuen 1997). Therefore, a frm s customer nformaton management capablty s a resource that potentally represents a source of compettve advantage. For e.g. Staples Drect, uses the customer nformaton t has on dfferent customer segments to determne the deployment of marketng resources for acquston, development and retenton strateges. Hence, all other thngs equal, a frm that uses a dfferentated marketng strategy should perform better than a frm that uses a one product/prce fts all approach. Secondly, the bonds between the marketer that effectvely uses customer nformaton and ts customers can create an nformatonal barrer to entry aganst compettors who do not have access to the same customer nformaton base (Glazer 1991; p. 15). However, some researchers (Chrstensen 1997; Hamel and Prahalad 1991, p. 83) argue that excessve customer orentaton can cause myopa resultng n a tyranny of the served market so that these frms may mss opportuntes/threats from outsde ther served market. For example, Chrstensen (1997) argues that frms n the dsk drve ndustry were so focused on meetng exstng customer needs that they mssed new product opportuntes because these new products dd not orgnally meet the needs of ther exstng customers. Hence, accordng to ths vew, usng customer nformaton may negatvely affect frm performance. On net, however, we hypothesze a drect postve relatonshp between a frm s customer nformaton management capablty and ts busness performance. Hence, H2: The greater the level of customer nformaton management n an organzaton, the better ts busness performance. 6

9 Indrect Effect of Customer Informaton Management on Frm Performance through Customer Satsfacton In addton to the drect effect of customer nformaton on frm performance (H2), we hypothesze that customer nformaton wll have an ndrect postve effect on frm performance medated through customer satsfacton. The greater the satsfacton of a frm s customers, the more loyal ts customers (Gale 1994). Further, the costs to the frm of servng repeat customers are lower than the costs of acqurng new customers (Blattberg and Deghton 1996). Hence, H3: The hgher the level of customer satsfacton of a frm s customers, the better ts busness performance. In sum, we hypothesze the man effects of customer nformaton management on frm outcomes of customer satsfacton and frm performance n the followng three ways (Table 1): 1. Customer nformaton management wll be postvely related to customer satsfacton (H1). 2. Customer nformaton management wll be postvely related to frm performance (H2). 3. Customer nformaton management wll have an ndrect postve effect on performance medated by customer satsfacton (H3). (Table 1 here) Moderatng Effects of Customer Envronments The envronmental context of an organzaton s lkely to nfluence ts structure, conduct and consequences (Bourgeos 1980; Slater and Narver 1994). It s therefore lkely that customer nformaton management may have a stronger postve effect on frm outcomes of customer satsfacton and frm performance under some envronmental condtons than others may. 7

10 Specfcally, we consder the effects of two characterstcs of the frm s customer envronment, the extent of customer heterogenety and the ntensty of customer relatonshps as factors that may moderate the relatonshp between a frm s use of customer nformaton and ts customer satsfacton and performance. As the drect effects of these varables are not the man focus of ths research, we consder only nteracton effects n our model 5. Customer heterogenety s the extent to whch the customers of a gven frm are dfferent from each other. We consder two sources of customer heterogenety. Frst, customers dffer n terms of ther needs and preferences for the frm s products, so that the frm s product offerngs may vary across dfferent customers. Second, customers dffer n terms of ther sze and proft potental to the frm. The greater the extent of customer heterogenety, the greater the need for the frm to acqure more nformaton about ts dfferent customers (who are more dfferent from each other) and the greater the lkelhood that the use of customer nformaton wll lead to superor customer value and hgher frm performance. On the other hand, the returns to usng customer nformaton n a frm whose customers are homogenous wll be lower because of the ntrnscally lower need for nformaton. Hence, the use of customer nformaton s lkely to be more strongly related to customer satsfacton n frms that have greater customer heterogenety than n frms that have lower customer heterogenety. By smlar reasonng, frms wth greater customer heterogenety that use customer nformaton are more lkely to have superor performance than frms wth lower customer heterogenety. Hence, H4a: The greater the heterogenety of a frm s customers, the stronger the relatonshp between customer nformaton management and the satsfacton of ts customers. H4b: The greater the heterogenety of a frm s customers, the stronger the relatonshp between customer nformaton management and ts busness performance. 8

11 Customer relatonshp ntensty s the extent of transacton ntensty n a frm s relatonshp wth ts customers. Frms dffer n the extent of ther transacton ntensty wth ther customers. Some frms have hgh transacton-ntensty n ther customer relatonshps so that the frm s sales revenue s generated from many transactons wth many customers coverng many products (Glazer 1991). On the other hand, some frms generate ther sales value from a narrow product range, servng few customers through a small number of busness transactons. In frms wth hgh customer relatonshp ntensty, each transacton s an opportunty for the frm to collect nformaton about ts customers. The frm can use the customer nformaton t has thus collected to mprove both customer and frm value n subsequent transactons over the customer s lfetme. If the customer relatonshp ntensty s low, then there are fewer occasons for the frm to both generate and use customer nformaton. Hence, we hypothesze that the effects of customer nformaton utlzaton on both frm outcomes of customer satsfacton and busness performance wll be hgher n organzatons that have hgher customer relatonshp ntensty. Hence, H5a: The greater the frm s customer relatonshp ntensty, the stronger the relatonshp between customer nformaton management and the satsfacton of ts customers. H5b: The greater the frm s customer relatonshp ntensty, the stronger the relatonshp between customer nformaton management and ts busness performance. Model Specfcaton Man Effects As our sample ncludes frms spannng a number of dfferent ndustres and markets wth dfferent compettve envronments, we nclude control varables to account for dfferences that may exst n the customer satsfacton and performance standards of dfferent ndustres. Strategy 9

12 researchers (Porter 1985) argue that frm performance s nfluenced, n part, by the characterstcs of the compettve envronment. We nclude control varables characterzng the frm s envronment that have been consdered by past lterature to be mportant determnants of performance (Bouldng and Staeln 1990; Jacobson and Aaker 1987; Jaworsk and Kohl 1993). Because factors relatng specfcally to the compettve market envronment are lkely to affect customer satsfacton levels n ndustres, we nclude compettve ntensty (CINT) and buyer power (BPOWER) n the relatonshp between customer nformaton management and customer satsfacton. The control varables suppler power (SPOWER), barrers to entry (B2E), pressure from substtute products (SUBST) and product qualty (PQ) are ncluded n the relatonshp between customer nformaton usage and frm performance. Gven that these sx varables are beng ncluded only as controls n the model and do not consttute the varables of substantve nterest, we consder only ther addtve effects and do not consder the nteracton terms between these varables and customer nformaton management. Hence, the proposed relatonshp between customer nformaton management and customer satsfacton and frm performance s expressed as follows: CSAT = α + α CIM + α CINT + α BPOWER + ε (1) where PERF = β + β CIM β SPOWER + β SUBST + β PQ + β CSAT + β B2E ε 2 (2) CSAT = customer satsfacton measure for the th frm CIM = customer nformaton management measure for the th frm 10

13 PERF = performance of the th frm CINT = compettve ntensty of the th frm BPOWER = buyer power of the th frm SPOWER = suppler power of the th frm B2E = barrers to entry of the th frm SUBST = substtutablty from compettors products of the th frm PQ = qualty of products of the th frm ε 1 and ε 2 = error terms and αs and βs are coeffcents to be estmated. We specfy the relatonshps outlned n Fgure 1 as a system of lnear equatons. Our path dagram n Fgure 1 forms a recursve system of equatons wth only one-way causal flows n the system. Recursve models wth the assumpton of ndependent errors, fulfll the rank and order condtons for dentfcaton wth no addtonal restrctons 6 (Land 1973, p. 31 provdes a formal proof). We thus obtan consstent parameters of estmates n each equaton. We tested several nonlnear specfcatons and found no support for those functonal forms n our data. We tested hypotheses H1-H3 usng the procedure recommended by Baron and Kenny (1986) by studyng the medatng effects of customer satsfacton on the relatonshp between customer nformaton management and frm performance. Hence, we estmated the followng regresson equatons: 1) regress customer satsfacton on customer nformaton management 2) regress frm performance on customer nformaton management and 3) regress frm performance on customer 11

14 nformaton management and customer satsfacton. Thus, n addton to Eqs. (1) and (2), we wll also regress frm performance on customer nformaton as shown n Eq. (3). PERF = γ γ CIM 1 + γ B2E γ SUBST + γ PQ + ε γ SPOWER 3 + (3) ε 3 s the error term and γs are coeffcents to be estmated. Our three hypotheses are supported f the followng condtons hold: ) customer satsfacton must depend on customer nformaton management n Eq.(1) ) customer nformaton management must affect frm performance n Eq. (3) ) customer satsfacton and customer nformaton management must affect frm performance n Eq. (2). To nvestgate the extent to whch customer nformaton management explans varance n frm outcomes of customer satsfacton and frm performance above that provded by ndustry and market control varables, we perform model comparson usng baselne models for customer satsfacton and frm performances wth only control varables as follows: CSAT = η + η CINT + η BPOWER + ε (4) PERF = µ µ 1SPOWER + µ 2B2E + µ 3SUBST + µ 4PQ ε 5 (5) where ε 4 and ε 5 are error terms and the ηs, and µs are coeffcents to be estmated. Interacton Effects We tested the moderatng effects of customer heterogenety and customer relatonshp ntensty usng moderator regresson analyss (MRA) wthn a regresson framework (Pedhazur 1997) by creatng an nteracton term that s a multplcatve product of each of the moderator varables 12

15 and the explanatory varables. Followng accepted gudelnes (Aken and West 1991, p. 12), we also ncluded the man effects of the explanatory varables and the moderators n addton to the nteracton effects. The MRA analyss of the relatonshp between customer nformaton management and customer satsfacton nvolved fve predctors (customer nformaton management, customer heterogenety, customer relatonshp ntensty, customer nformaton management customer heterogenety, customer nformaton management customer relatonshp ntensty) and two control varables. Lkewse, the MRA analyss of the relatonshp between customer nformaton management and frm performance nvolved the same fve predctors and four control varables. All the varables were mean-centered before we constructed the nteracton terms to reduce the potental effects of collnearty (Cronbach 1987). The nteracton effects between the customer envronmental varables of customer heterogenety and customer relatonshp ntensty on the relatonshp between customer nformaton management and customer satsfacton and frm performance respectvely are specfed n the followng equatons: CSAT = λ + λ CIM λ ( CHET * CIM 7 + λ CHET + λ CRI + ) + λ ( CRI λ CINT + λ BPOWER + ε * CIM ) + (6) PERF = φ + φ CIM φ ( CHET φ B2E 6 1 * CIM 7 + φ CHET 2 ) + φ ( CRI + φ SPOWER 5 + φ CRI 8 3 * CIM + + φ SUBST ) + + φ PQ 9 + ε 7 (7) where CHET = customer heterogenety of the th frm CRI = customer relatonshp ntensty of the th frm 13

16 ε 6 and ε 7 are error terms and the λs, and φs are coeffcents to be estmated. All other varables are as defned n Eqs. (1) and (2). In the next secton, we descrbe the method used to collect data and the results of our analyss. METHOD Data collecton We collected data for ths research as part of a Customer Informaton Benchmarkng Study jontly conducted by Penn State s Insttute for the Study of Busness Markets (ISBM) and the Drect Marketng Assocaton n Summer We drew the sample randomly from a lst of member frms from ISBM and a database from Dun and Bradstreet. We found no sgnfcant dfferences between companes from the two dfferent lsts on key varables of the study. Researchers from a professonal marketng research frm called heads of marketng department to request ther partcpaton n the study. Informants were promsed a summary of the results n return for ther partcpaton. All questons regardng the organzaton used the dvson or strategc busness unt (SBU) as the organzatonal unt of analyss frms were contacted out of whch 217 frms responded resultng n a response rate of 8%. Non-response analyss showed no dfferences n the demographc characterstcs of companes of managers who declned to partcpate from those that partcpated n the study. Callbacks ndcated that the man reason for non-partcpaton was lack of tme. Measurement We developed scales for the study usng a mult-phase, teratve procedure. Frst, we generated a large pool of tems measurng each of the study s constructs. From ths pool of tems, we selected a subset usng the crtera of unqueness and the ablty to convey dfferent aspects of 14

17 meanng to nformants (Churchll 1979). We reverse coded some tems to offset response set bas. Responses were recorded on a 5-pont Lkert scale wth 1 ndcatng strong dsagreement wth the statement and 5 ndcatng strong agreement. We pre-tested tems for the dfferent scales n three phases: 1) face-to-face ntervews wth 4 academc experts and 2 practtoner managers n a drect marketng company 2) telephone ntervews wth 4 managers of marketng nformaton systems and 3) a plot survey of 8 managers. At each stage, partcpants were asked to dentfy tems that were confusng, tasks that were dffcult to perform and any other problems that they encountered. We revsed or elmnated tems that were problematc. The tems used n the scales are provded n the Appendx. A bref descrpton of the scale tems follows. Customer nformaton management (CIM) was measured by a 9-tem scale. Fve tems pertaned to customer nformaton generaton and four tems pertaned to customer nformaton utlzaton. Representatve tems ncluded Customer nformaton s accessble to all managers who need to use t (customer nformaton generaton) and Customer nformaton s a central nput n our busness plannng (customer nformaton utlzaton). Customer heterogenety (CHET) and customer relatonshp ntensty (CRI) were measured by two tem and three tem scales respectvely. The tems for customer heterogenety assessed the heterogenety of the frm s customers both n terms of ther preferences and the sales and proft potental to the frm. Customer relatonshp ntensty scale assessed the extent of transacton ntensty n a frm s relatonshps wth ts customers. Representatve tems were Our customers are very dfferent from each other n terms of needs and preferences (customer heterogenety) and Once we get a customer, we do not have to nvest a great deal of effort and tme n managng our customer relatonshps (reverse-coded for customer relatonshp ntensty). 15

18 Busness performance (PERF) was measured usng a 2-tem scale of judgmental measures (Jaworsk and Kohl 1993; Slater and Narver 1994). Because the frms n our samples covered a number of dfferent ndustres characterzed by dfferent performance standards, we used subjectve measures of performance. Prevous studes n frm performance have found a strong correlaton between subjectve assessments and ther objectve counterparts (Dess and Robnson 1984; Slater and Narver 1994). The judgmental measure asked nformants for ther assessments of the overall performance of the busness and ts performance relatve to ts major compettors, rated on a fve-pont scale rangng from poor to excellent. Customer satsfacton (CSAT) was also measured usng a 2-tem scale of subjectve measure. The judgmental measure asked nformants for ther assessment of the overall customer satsfacton of a frm s customers and the customer satsfacton of ts customers relatve to major compettors on a fve-pont scale rangng from poor to excellent. The sx control varables of compettve ntensty (CINT), buyer power (BPOWER), suppler power (SPOWER), entry barrers (B2E), substtutablty pressure from compettors products (SUBST) and product qualty (PQ) were measured usng subjectve sngle-tem measures adapted from Jaworsk and Kohl (1993). RESULTS Relablty Analyss We assessed the relablty of each mult-tem scale by computng ts coeffcent alpha (Table 2). We elmnated tems that exhbted low nter-tem correlatons to mprove the nternal consstency of the scales. The refned scales generally have good relablty coeffcents that exceed the levels of 0.70 recommended by Nunnally (1978) for exploratory research except for 16

19 customer heterogenety and customer relatonshp ntensty measures that had relablty coeffcents of 0.61 and 0.58 respectvely. Gven the need to test for moderatng effects, we retaned these scales despte ther lower relabltes. (Table 2 here) The two components of customer nformaton management customer nformaton generaton and customer nformaton utlzaton have relablty coeffcents of 0.81 and 0.74 respectvely. Further, exploratory factor analyss of the customer nformaton management construct showed a clear loadng of the tems on 2 dstnct factors - customer nformaton generaton and customer nformaton utlzaton (Table 3) provdng support for the two-dmensonalty of the customer nformaton management construct. The correlaton between the two sub-factors of customer nformaton generaton and customer nformaton usage was (Table 3 here) Gven that both customer nformaton generaton and customer nformaton usage are essental aspects of the customer nformaton management construct, we computed the scores for the customer nformaton management measure (and other mult-tem scores) by addng the correspondng tem scores 7. The mean score of customer nformaton management was wth a standard devaton of 6.05 and a range of 15 to 45 (out of a possble range of 9 to 45). The coeffcent alpha for the customer nformaton management scale ncludng the two components of customer nformaton generaton and customer nformaton usage s good at Table 4 contans the descrptve statstcs and the correlaton matrx of the dfferent constructs used n the research. (Table 4 here) 17

20 Hypotheses Testng The results of the regresson for customer satsfacton ndcate that customer nformaton management s postvely related (α 1 = 0.080, t = 4.25) to customer satsfacton n Eq. 1 provdng support for H1 8 (Table 5). We fnd that customer nformaton management has a sgnfcant drect postve effect on frm performance n equaton 3 (γ 1 = 0.086, t = 4.30) (Table 7) provdng support for H2. Further, customer satsfacton has a sgnfcant postve effect on frm performance n equaton 2 (β 2 = 0.552, t = 9.36) (Table 6) supportng H3. Thus, our data support all our three hypotheses H1, H2 and H3. (Table 5, 6 and 7 here). When both customer satsfacton and customer nformaton management are ncluded n the model for frm performance (Table 6), the coeffcent for CIM drops from (γ 1 = 0.086, t = 4.30) (Table 7) to (β 1 = 0.051, t = 3.00), ndcatng that customer satsfacton partally medates the relatonshp between customer nformaton management and frm performance. These results suggest that customer nformaton has two effects on frm performance - a drect postve effect and an ndrect postve effect medated through customer satsfacton. The total effect of customer nformaton management on frm performance ncludng both the drect and ndrect effects s ( % = 0.130). Not surprsngly, the drect effects of customer satsfacton on frm performance are larger (β 2 = 0.552) than the effect of customer nformaton management on frm performance (combned drect and ndrect effect = 0.130). (Table 8 here) 18

21 We conducted model comparsons between models ncludng customer nformaton over baselne models wth only the control varables to check whether the ncluson of customer nformaton management s able to explan a sgnfcantly larger proporton of varance. The R-square for the model for customer satsfacton (Eq. 1) mproves by more than 100% over the baselne model (Eq. 4) (from to 0.116) and the results of the F-tests of dfference n ft (Pedhazur 1997; p. 108) are sgnfcant (p< 0.01) (Table 8). We obtan smlar results for the F-test of the dfference n fts between the model for frm performance that ncludes customer nformaton management (Eq. 3) and a baselne model wth only the control varables (Eq. 5) (R-sq. ncreases from to 0.141; p < 0.01). Fnally, a model of frm performance that ncludes both customer nformaton management and customer satsfacton (Eq. 2) provdes a consderably mproved ft over a baselne model wth only control varables (Eq. 5) (R-sq. ncreases from to 0.391; p < 0.01). (Table 9 and 10 here) The tests of the hypotheszed moderatng effects of customer heterogenety and customer relatonshp ntensty on the lnkage between customer nformaton management and customer satsfacton (Hypotheses H4a, H5a) (Table 9) and frm performance (Hypotheses H4b, H5b) (Table 10) are not sgnfcant (p < 0.05). Results of a dfferental F-test shows (p < 0.05) that ncludng the nteracton effects of customer heterogenety and customer relatonshp ntensty (Eqs. 6 and 7) does not provde any explanatory power n the model over a model that ncludes customer nformaton management and the control varables. (Eqs. 4 and 5) (Table 8). In other words, the postve relatonshps between customer nformaton management and frm outcomes of customer satsfacton and busness performance appear to be robust across 19

22 envronments characterzed by varyng levels of customer heterogenety and customer relatonshp ntensty. DISCUSSION Manageral Implcatons Our results have mportant mplcatons for practce. Frst, our results suggest that customer nformaton management s a two-dmensonal construct coverng customer nformaton generaton and customer nformaton utlzaton. The two-dmensonal nature of the construct suggests that t s not only mportant for managers to nvest n the generaton of customer nformaton, but also to ensure that systems exst to ensure the effectve utlzaton of customer nformaton. Second, the tests of hypotheses suggest that customer nformaton management of a frm s related to two mportant frm outcomes customer satsfacton and busness performance. Hence, all thngs beng equal, frms that mplement customer nformaton management are lkely to not only have more satsfed customers, but are also lkely to perform better than those that do not. Fnally, the null results of the tests of moderatng effects suggest that the postve relatonshp between customer nformaton management on frm outcomes are robust and generally applcable regardless of the two characterstcs, customer heterogenety and customer relatonshp ntensty of the frm s customer envronment. Lmtatons and Future Research Drectons In ths secton, we dscuss the study s lmtatons and dentfy some opportuntes for future research. 1. Methodologcal lmtatons. The cross-sectonal nature of data n our study restrcts conclusons to those of assocaton, not of causaton. Hence, a frutful extenson of ths 20

23 research would be a longtudnal study where customer nformaton usage n perod 1 s related to outcome measures n perod 2. Such a methodology wll more strongly establsh causalty between customer nformaton usage and busness performance. Addtonally, a longtudnal study wll provde a more rgorous test of our hypotheses as t may be argued that effects of customer myopa, f any, are more lkely to be observed on long term frm performance measures that are better captured n data from a longtudnal study. Second, the data for our study s provded by a sngle nformant, the head of marketng, and therefore suffers from lmtatons of sngle-source data (Kumar, Stern and Anderson 1993). Hence, future researchers may try to use multple nformants that may mprove the overall relablty of the analyses and enhance confdence n theory testng. 2. Antecedents of customer nformaton management system. In ths study we dd not dentfy the antecedents of a effectve customer nformaton management system. For example, what should frms do n order to ensure that customer nformaton s beng generated and used n ther frms? It s mportant for managers to know the factors that lmt or enhance customer nformaton generaton and usage f they are to develop optmal customer nformaton management strateges. Future research could examne the manageral varables that facltate or hnder customer nformaton management systems. 3. Relatonshp between customer nformaton avalablty and customer nformaton usage. In ths research, we dd not examne the relatonshp between customer nformaton generaton and customer nformaton utlzaton. In other words, do frms that use customer nformaton generate customer nformaton or do frms that generate customer nformaton use t? It may be mportant for managers to dsentangle the causalty between customer nformaton 21

24 generaton and customer nformaton utlzaton because resource mplcatons for generaton and usage of customer nformaton are dfferent. Conclusons In ths research, we defne the construct of customer nformaton management and develop a relable measure for t and emprcally valdate the measure among a sample of managers. We demonstrate emprcally that customer nformaton management s postvely related to two frm outcomes of customer satsfacton and busness performance. Further, the null results of the tests of the moderatng effects of the frm s customer heterogenety and customer relatonshp ntensty suggest that the effects of customer nformaton management on customer satsfacton and busness performance are robust across dfferent customer envronments. In sum, ths research provdes evdence that customer nformaton s a knowledge asset that can be leveraged to mprove busness performance. 22

25 References Aken, Leona S. and Stephen G. West (1991), Multple Regresson: Testng and Interpretng Interactons. Newbury Park, CA: Sage Publcatons. Baron, Reuben M. and Davd A. Kenny (1986), The Moderator-Medator Varable Dstncton n Socal Psychologcal Research: Conceptual, Strategc and Statstcal Consderatons, Journal of Personalty and Socal Psychology, Vol. 51(6), Blattberg, Robert C. and John Deghton (1996), Manage Marketng by the Customer Equty Test, Harvard Busness Revew, Vol. 74(4), Bouldng, W. and Staeln, R. (1990), Envronment, Market Share and Market Power, Management Scence, 36, Bourgeos, Leonard Jay, III (1980), Strategy and Envronment: A Conceptual Integraton, Academy of Management Journal, 1 (January), Caplan, Nathan, Andrea Morrson and Russell Stambaugh (1975), The Use of Socal Scence Knowledge n Polcy Decsons at the Natonal Level. Ann Arbor, MI: Insttute for Socal Research. Chrstensen, Clayton M. (1997), Innovators Dlemma. Boston, MA: Harvard Busness School Press. Churchll, Glbert, A., Jr. (1979), A Paradgm for Developng Better Measures of Marketng Constructs, Journal of Marketng Research, 16 (February), Cronbach, Lee J. (1987), Statstcal Tests for Moderator Varables: Flaws n Analyses Recently Proposed, Psychologcal Bulletn, 1(3), Daft, Rchard, L. and Karl E. Weck (1984), Toward a Model of Organzatons as Interpretaton Systems, Academy of Management Revew, 9 (Aprl),

26 Day, George S. (1994), The Capabltes of Market-Drven Organzatons, Journal of Marketng, 58 (October), Deshpande, Roht, John U. Farley and Frederck E. Webster (1993), Corporate Culture, Customer Orentaton and Innovatveness n Japanese Frms: A Quadrad Analyss, Journal of Marketng, 57 (January), Dess, G.G. and Rchard B. Robnson, Jr. (1984), Measurng Organzatonal Performance n the Absence of Objectve Measures: The Case of the Prvately held Frm and Conglomerate Busness Unt, Strategc Management Journal, 5(July-September), Gale, Bradley T. (1994), Managng Customer Value. New York, NY: The Free Press. Glazer, Rash (1991), Marketng n an Informaton-Intensve Envronment: Strategc Implcatons of Knowledge as an Asset, Journal of Marketng, 55 (October), Hamel, Gary and C. K. Prahalad (1991), Corporate Imagnaton and Expedtonary Marketng, Harvard Busness Revew, July-August, 1991, Itam, Hroyuk and Thomas W. Roehl (1987), Moblzng Invsble Assets. Cambrdge, MA: Harvard Unversty Press. Jacobson, Robert and Davd A. Aaker (1987), The Strategc Role of Product Qualty, Journal of Marketng, 51(4), Jaworsk, Bernard J. and Ajay K Kohl (1993), Market Orentaton: Antecedents and Consequences, Journal of Marketng, 57 (July), John, George and John Martn (1984), Effects of Organzatonal Structure of Market Plannng on Credblty and Utlzaton of Plan Output, Journal of Marketng Research, 21 (May),

27 Kohl, Ajay. K. and Jaworsk, Bernard J. (1990), Market Orentaton: The Construct, Research Propostons, and Manageral Implcatons, Journal of Marketng, 54 (Aprl), Kumar, Nrmalya, Lous W. Stern and James C. Anderson (1993), Conductng Interorganzatonal Research usng Key Informants, Academy of Management Journal, Vol. 36(6), Land, Kenneth (1973), Identfcaton, Parameter Estmaton and Hypothess Testng n Recursve Socologcal Models, n Structural Equaton Models n the Socal Scences, Arthur S. Goldberger and Ots D. Duncan, eds. New York: Semnar Press Inc., Menon, Anl and Rajan P Varadarajan (1992), A Model of Marketng Knowledge Use Wthn Frms, Journal of Marketng, 56 (October), Moenaert, Rudy. K. and Wllam E. Souder (1996), Context and Antecedents of Informaton Utlty at the R&D/Marketng Interface, Management Scence, 42(November), Moorman, Chrstne (1995), Organzatonal Market Informaton Processng: Cultural Antecedents and New Product Outcomes, Journal of Marketng Research, 32 (August), Narver, John, C. and Stanley F.Slater (1990), The Effect of a Marketng Orentaton on Busness Proftablty, Journal of Marketng, 54 (October), Nunnally, Jm C. (1978), Psychometrc Theory. 2 nd ed. New York, NY: McGraw-Hll. Pedhazur, Elazar (1997), Multple Regresson n Behavoral Research: Explanaton and Predcton. 3 rd ed. Orlando, FL: Harcourt Brace Publshers. Peppers, Don and Martha Rogers (1996). The 1:1 Future: buldng relatonshps one customer at a tme. New York: Bantam Doubleday Publshng Group Inc. 25

28 Peteraf, Margaret, A. (1993), The Cornerstones of Compettve Advantage: A Resource-Based Vew, Strategc Management Journal, 14 (March), Pne, B. Joseph, Don Peppers and Martha Rogers (1995), Do You Want to Keep Your Customers Forever, Harvard Busness Revew, (March/Aprl), Porter, Mchael, (1985), Compettve Advantage. New York, NY: The Free Press. Shrvastava, Paul (1987), Rgor and Practcal Usefulness of Research n Strategc Management, Strategc Management Journal, 8 (January-February), Snkula, James, M. (1994), Market Informaton Processng and Organzatonal Learnng, Journal of Marketng, 58 (January), Slater, Stanley F. and John C. Narver (1994), Does Compettve Envronment Moderate the Market Orentaton-Performance Relatonshp? Journal of Marketng, 58 (January), Teece, Davd, J., Gary Psano and Amy Shuen (1997), Dynamc Capabltes and Strategc Management, Strategc Management Journal, 18(7), Wayland, Robert E. and Paul M. Cole (1997). Customer Connectons: New Strateges for Growth. Boston, MA: Harvard Busness School Press. Wernerfelt, Brger (1984), A Resource-Based Vew of the Frm, Strategc Management Journal, 5 (March),

29 Fgure 1- Effects of Customer Informaton Management on Customer Satsfacton and Frm Performance Customer Informaton Customer Satsfacton Frm Performance Customer Envronments Customer Heterogenety Customer Relatonshp Intensty Industry and 27

30 Table 1 Summary of Hypotheses Hypotheses Relatonshp Sgn Support from the Lterature H1 Customer nformaton Postve - management on customer satsfacton H2 Customer nformaton management on frm performance Postve Glazer 1991; Itam and Roehl 1987; H3 H4a,H4b H5a, H5b Customer satsfacton on frm performance Moderatng effects of customer heterogenety on the relatonshp between customer nformaton management and customer satsfacton and frm performance Moderatng effects of customer relatonshp ntensty on the relatonshp between customer nformaton management and customer satsfacton and frm performance Postve Postve - Postve - Blattberg and Deghton 1996; Gale 1994; 28

31 Table 2 Relabltes of Mult-tem Scales used n the Study Measures Customer Informaton Management (CIM) Customer nformaton generaton (CIG) Comprehensveness Accuracy Accessblty Relevant Perceved qualty Customer nformaton usage(ciu) Used for managng operatons Well-ntegrated nto operatons Used n plannng Usage relatve to compettors Frm performance (PERF) Overall Relatve to compettors Customer satsfacton (CSAT) Overall Relatve to compettors Customer heterogenety (CHET) Dfference n sales and proft to frm Dfference n preferences and needs Customer relatonshp ntensty (CRI) Customer servcng calls for ongong effort Investments n managng customer relatonshps Customer relatonshps requre ongong communcatons Relablty Coeffcent (Cronbach s Alpha)

32 Table 3 Exploratory Factor Analyss of Customer Informaton Management Showng Two Factors of Customer Informaton Generaton (CIG) and Customer Informaton Utlzaton (CIU) Varable Factor 1 Factor 2 Customer Informaton Generaton (CIG) Comprehensveness Accuracy Accessblty Relevance Perceved qualty Customer Informaton Usage (CIU) Used for managng operatons Well-ntegrated nto operatons Used n plannng Usage relatve to competton

33 Table 4: Correlaton Matrx of Measures Used n the Research Range Means (sd) CIM PERF CSAT CHET CRI CINT BPOWER SPOWER B2E SUBST PQ 1. Customer Informaton Management (CIM) (6.047) Performance (PERF) 3. Customer Satsfacton (CSAT) (1.766) (1.483) Customer heterogenety (CHET) (2.043) Customer relatonshp ntensty (CRI) (2.410) Compettve ntensty (CINT) (1.213) * * 0.165* Buyer power (BPOWER) (1.180) * Suppler power (SPOWER) (1.111) Barrers to entry (B2E) (1.285) Pressure from substtute products (SUBST) (1.249) * Product qualty (PQ) (0.760) * * denotes sgnfcant at p < All others sgnfcant at p <

34 Table 5 Regresson Analyses showng the Effects of Customer Informaton Management on Customer Satsfacton (Equaton 1) Varables Parameter t-value estmates (se) Customer nformaton 0.080(0.019) 4.25 Management (CIM) (α 1 ) Compettve ntensty (CINT) (α 2 ) (0.119) 1.71 Buyer power (BPOWER) (α 3 ) (0.119) R-sq

35 Table 6 Regresson Analyses Showng the Effects of both Customer Informaton Management and Customer Satsfacton on Performance (Equaton 2) Varables Customer nformaton management (CIM) (β 1 ) Parameter t-value estmates (se) 0.051(0.017) 3.00 Customer satsfacton (CSAT) (β 2 ) 0.552(0.059) 9.36 Barrers to entry (B2E) (β 3 ) (0.096) Suppler power (SPOWER) (β 4 ) 0.018(0.098) 0.18 Substtutablty of products 0.009(0.098) 0.09 (SUBST) (β 5 ) Product qualty (PQ) (β 6 ) 0.009(0.105) 0.09 R-sq

36 Table 7 Regresson Analyses Showng the Effects of Customer Informaton Management on Performance (Equaton 3) Varables Customer nformaton management (CIM) (γ 1 ) Parameter t-value estmates (se) 0.086(0.020) 4.30 Barrers to entry (B2E) (γ 2 ) 0.004(0.114) 0.04 Suppler power (SPOWER) (γ 3 ) (0.115) Substtutablty of products 0.086(0.116) 0.74 (SUBST) (γ 4 ) Product qualty (PQ) (γ 5 ) 0.350(0.117) 2.99 R-sq

37 Table 8 Model Comparsons to Examne the Explanatory Power of Customer Informaton Management on Customer Satsfacton and Frm Performance showng Improved Performance over a Baselne Model that Includes only Control Varables Model (Equaton no.) R- square Customer Satsfacton Only control varables (4) Customer nformaton management +control varables (1) Customer nformaton management +control varables +nteracton effects of envronmental varables (6) Frm Performance Only control varables (5) Customer nformaton management +Control varables (3) Customer nformaton management + Customer satsfacton + Control varables(2) Customer nformaton management +control varables +nteracton effects of envronmental varables(7) Overall F Degrees of freedom , 215 Results of Dfferental F-test (F and p values) , (0.01) (Eq. 1 vs. Eq. 4) , , (Eq. 6 vs. Eq. 1) , (0.01) (Eq. 3 vs. Eq. 5) , (0.01) (Eq. 2 vs. Eq. 5) , (Eq. 7 vs. Eq. 3) 35

38 Table 9 Interacton Effects of Customer Heterogenety and Customer Relatonshp Intensty on the Relatonshp between Customer Informaton Management and Customer Satsfacton (Equaton 6) Varable Customer Informaton Management (CIM)(λ 1 ) Customer Heterogenety (CHET) (λ 2 ) Customer Relatonshp Intensty (CRI) (λ 3 ) Parameter t-value Estmate (se) 0.083(0.020) (-0.072) (0.063) (0.012) Customer Informaton Management Customer Heterogenety (CIM CHET) (λ 4 ) Customer Informaton 0.004(0.007) 0.57 Management Customer Relatonshp Intensty (CIM CRI) (λ 5 ) Compettve Intensty (CINT) (0.128) (λ 6 ) Buyer power (BPOWER) (λ 7 ) (0.125) R-sq

39 Table 10 Interacton Effects of Customer Heterogenety and Customer Relatonshp Intensty on the Relatonshp between Customer Informaton Management and Frm Performance (Equaton 7) Varable Customer Informaton Management (CIM) (φ 1 ) Customer Heterogenety (CHET) (φ 2 ) Customer Relatonshp Intensty (CRI) (φ 3 ) Customer Informaton Management Customer Heterogenety (CIM CHET) (φ 4 ) Parameter Estmate t-value (se) (0.021) (0.071) (0.058) (0.011) (0.007) 0.86 Customer Informaton Management Customer Relatonshp Intensty (CIM CRI) (φ 5 ) Barrers to entry (B2E) (φ 6 ) (0.118) Suppler Power (SPOWER) (φ 7 ) (0.119) Substtutablty of Products 0.088(0.116) 0.76 (SUBST)(φ 8 ) Product qualty (PQ) (φ 9 ) 0.348(0.118) 2.95 R-sq

40 Appendx Items of Scales Used n the Research I. Customer Informaton Management (CIM) (α=0.84) Customer Informaton Generaton (CIU) (α =0.81) 1. Our customer nformaton s detaled, comprehensve and relable. 2. Our customer nformaton s accurate and up-to-date. 3. Our customer nformaton s accessble to all managers who need to use t. 4. We have relevant and necessary nformaton about our customers. 5. The qualty of our customer nformaton s not good (R). Customer Informaton Utlzaton (CIU) (α =0.74) 1. We use customer nformaton for managng our current busness operatons. 2. Our customer nformaton system s well-ntegrated nto our busness systems and forms the backbone of our busness operatons. 3. Our customer nformaton s a central nput n our busness plannng. 4. The ntegraton of customer nformaton n our busness processes and plannng s better than that of our major compettors. II. Frm Performance (PERF) (α = 0.74) 1. Overall performance of our busness unt. 2. Performance of our busness unt relatve to that of our major compettors. III. Customer satsfacton (CSAT) (α =0.76) 1. Overall satsfacton of our busness unt s customers. 2. Satsfacton of our busness unt s customers wth us, relatve to ther satsfacton wth our major compettors. IV. Customer heterogenety (CHET) (α =0.61) 1. Our customers dffer substantally from each other n terms of sales and proft potental to us. 2. Our customers are very dfferent from each other n terms of needs and preferences. V. Customer relatonshp ntensty (CRI) (α =0.58) 1. The servcng of our customers calls for ongong sellng and marketng effort on our part. 2. Once we get a customer, we do not have to nvest a great deal of effort and tme n managng our customer relatonshps (R). 3. Transactons wth our busness unt s customers requres a lot of ongong communcatons. 38