Customer retention, loyalty, and satisfaction in the german

*Corresponding author. Tel.: #49-203-379-3109; fax: #49-203-379-2656.E-mail addresses: [email protected] (T.J. Gerpott), [email protected] (W. Rams), andreas.schin-

[email protected] (A. Schindler).

Telecommunications Policy 25 (2001) 249}269

Customer retention, loyalty, and satisfaction in the Germanmobile cellular telecommunications market

Torsten J. Gerpott��*, Wolfgang Rams�, Andreas Schindler�

�Telecommunications Management, Department of Business Administration, Gerhard-Mercator-University Duisburg,Lotharstr. 65, D-47057 Duisburg, Germany

�Deutsche Telekom AG, Friedrich-Ebert-Allee 140, D-53133 Bonn, Germany�Deutsche Telekom MobilNet GmbH, Landgrabenweg 151, D-53227 Bonn, Germany

Received 1 September 2000; received in revised form 4 December 2000; accepted 8 December 2000

Abstract

Customer retention (CR), loyalty (CL), and satisfaction (CS) are important (intermediate) goals fortelecommunication network operators on their way to superior economic success in the liberalised Germanmarket. Therefore, drawing on a sample of 684 residential customers of digital cellular network operators inGermany this study tests hypotheses suggesting that CR, CL, and CS should be treated as di!erentialconstructs which are causally inter-linked. LISREL analyses support a two-stagedmodel in which overall CShas a signi"cant impact on CL which in turn in#uences a customer's intention to terminate/extend thecontractual relationship with his mobile cellular network operator ("CR). Mobile service price andpersonal service bene"t perceptions as well as (lack of) number portability between various cellular operatorswere identi"ed as supply-related variables with the strongest e!ects on CR. Mobile network operators'perceived customer care performance had no signi"cant impact on CR. The "ndings suggest that an importantlever for regulators to promote competition in cellular markets is the enforcement of e$cient numberportability procedures between mobile network operators. � 2001 Elsevier Science Ltd. All rights reserved.

Keywords: Customer loyalty; Customer retention; Customer satisfaction; Mobile communications; Number portability;Telecommunications marketing

1. Background

Since the 1990s, the telecommunications sector has become a dynamic key area for the economicdevelopment of industrialised nations. This is the result of enormous technical progress as well as of

0308-5961/01/$ - see front matter � 2001 Elsevier Science Ltd. All rights reserved.PII: S 0 3 0 8 - 5 9 6 1 ( 0 0 ) 0 0 0 9 7 - 5

�See, for instance, the article collections edited by Bruhn and Homburg (1998), and Simon and Homburg (1997), inwhich customer retention, customer loyalty, and customer satisfaction are discussed as success criteria for marketingstrategies in a wide range of di!erent industries.

�For reviews of relevant management research see Gerpott (2000), Homburg and Bruhn (1998), Homburg andRudolph (1997), and Dick and Basu (1994).

the increased number of network operators and the intense competition that has developed. Thesefactors, in turn, are a consequence of the removal of monopoly rights, which were mainly enjoyedby state-owned operators of public telecommunication networks. The increasing economic import-ance of telecommunications companies inspired many management scholars to devote moreteaching and research attention to this sector (see Szyperski & Loebbecke, 1999, pp. 485}486).Speci"cally in the "eld of marketing strategies for telecommunications services it is frequentlypointed out that once customers have been acquired and connected to the telecommunicationsnetwork of a particular operator, their long-term links with the focal operator are of greaterimportance to the success of the company in competitive markets than they are in other industrysectors (see Wilfert, 1999, pp. 198}199; Gerpott, 1998, pp. 213}221; Knauer, 1998, pp. 510}511;Harter, Ripsam, & Ruhl, 1997, p. 15; Booz. Allen & Hamilton, 1995, pp. 55}60). Nevertheless, thereis a dearth of empirical research into the extent of customer retention or the supply side retentiondrivers in particular telecommunications markets. Therefore, this paper examines di!erences andcommonalties between the constructs `customer retentiona, `customer loyaltya, and `customersatisfactiona and what supply side factors in#uence them both conceptually and empirically for theGerman mobile communications market using data from a sample of 684 residential mobilecommunications users.This type of analysis is not only of interest to cellular network operators/service providers but

also to other industries for at least two reasons. First, a discussion of how customer retention,customer loyalty, and customer satisfaction can be di!erentiated and how the three variables areinter-linked is of general importance to corporate management. This is because without respect tothe industry concerned all three are (intermediate) objectives on the way to ensuring a company'ssales success which can be in#uenced by management action.� Second, to date managementresearch on customer retention and satisfaction� has been concerned almost exclusively withover-the-counter goods sold in unconnected individual transactions in mature markets. In themobile communications market, however, usage-dependent and service-like contract goods aresold. By focusing the analysis on this type of market a less `made-to-order "eld of researcha isinvestigated.The remainder of this paper is structured as follows: In Section 2, a brief description of

the German mobile communications market is provided. In Section 3, we explicate the conceptsof customer retention, customer loyalty, and customer satisfaction * "rst in general, andthen with reference to the mobile communications market in particular. Further, we develophypotheses on supply side determinants of these three constructs within the mobilecommunications market. These hypotheses are then tested in an empirical study reportedin Section 4. Finally, in Section 5, we discuss implications of the empirical "ndings fornumber portability regulation in mobile markets and for competitive strategies of mobile networkoperators.

250 T.J. Gerpott et al. / Telecommunications Policy 25 (2001) 249}269

�For a general discussion of contractual/continuous vs. single/discrete transactions, see Oevermann (1996, p. 30) andJeschke (1995, p. 14).

2. Pro5le of the German mobile cellular market

Mobile communications markets can be divided by the type of services provided and by thetelecommunications networks used for `productiona into the sub-markets for cellularradiotelephony, paging, trunked mobile radio access, and satellite services and networks (seeGerpott, 1998, p. 220; Knauer, 1998, p. 509; Stoetzer & Tewes, 1996, p. 304). In terms of salesrevenues and number of customers involved, the mobile cellular telephony market is by far themost important sub-market for mobile communications. Thus, this study concentrates on thispart of the mobile market in Germany. In keeping with common practice, the terms `cellularmarketa and `mobile (communications) marketa will be used synonymously. The "rst non-militarypublic mobile communications network was introduced in 1958 into Germany. By the end of1991, however, only 0.53 million radiotelephone access lines had been sold (see Gerpott, 1999,pp. 60}61; Wilfert, 1999, pp. 188}189; Stoetzer & Tewes, 1996, p. 305). This was due to the highprices of terminals and services, and to technical shortcomings of the analogue network genera-tions used at the time (e.g., frequently no radio coverage within buildings.) Demand only started totake-o! when digital mobile networks based on the GSM standard replaced analogue networks,and Deutsche Telekom's monopoly in the "eld of mobile cellular networks and services wasdissolved.Competition between four GSM operators promoted high network availability and the fast

introduction of user-friendly terminals. It also prompted considerable marketing e!orts. Thesefactors and others led to a dramatic increase in the number of mobile access lines in Germany* from 0.92 million at the end of 1992 to 23.32 million at the end of 1999. In the 12 months fromthe end of 1998 to the end of 1999 alone, the number of cellular access lines in Germany increasedby 9.46 million or by 68%. At the end of 1999, there were four network operators sharing themarket. These were Mannesmann/Vodafone with a customer market share of 42%, DeutscheTelekom/T-Mobil with 40%, E-Plus with 15%, and VIAG Interkom with 3%. Because the fouroperators use a network technology based on a common standard, the services they o!er are verysimilar. As a result, the German mobile communications market has the structure of a narrowoligopoly. In this oligopoly market, at least up to the end of 1999 none of the four networkoperators adopted a very aggressive let alone a cutthroat competitive style (cf. Wilfert, 1999,pp. 189}190; Gerpott, 1998, p. 220; Stoetzer & Tewes, 1996, p. 307).Studies of customer retention, loyalty, and satisfaction have typically analysed markets for

over-the-counter goods sold in single discrete transactions (e.g., motor cars). In comparison, themobile communications market has two special features. First, access to a cellular network and thehandling of calls over that network represent a continuous contractual transaction carried out overa long period.� During this period, the buyer cannot be certain that the network operator willalways provide the promised service quality to the full extent. The contractual transaction isnormally structured in such a way that customers pay a basic monthly fee for the opportunity touse the mobile communications network through access that has been provided for the purpose. Inaddition, they pay ex post call charges in accordance with the amount of minutes they actually use

T.J. Gerpott et al. / Telecommunications Policy 25 (2001) 249}269 251

�Since 1997, operators of mobile communications networks in Germany have been o!ering their customers analternative contractual model, namely the ability to pay in advance for speci"c use of the network (such as 100min ofoutgoing calls) over a speci"ed period (for instance six months). (These are the so-called `pre-paid access cardsa). Buteven this business model involves a contractual transaction in which the network operator has an (even greater) interestin motivating the customer actively to renew the contractual relationship (`reloading of the pre-paid cardsa). This isbecause the relationship will otherwise be brought to an end automatically when the mobile communications access isdeactivated once the contractual period has expired. For this reason, no further distinction will be made here betweenpre-paid customers and conventional mobile communications customers, whose contracts are implicitly extended unlessexplicitly terminated by at least one of the parties.

the network.� As far as network operators are concerned, continuing the contractual relationshipwith a current customer is more important with this sort of business structure than with transac-tions in purchase goods. The reason is that marginal income from the customer increases the longerthe business relationship lasts, because the incremental costs for each customer/cellular access lineand period are much lower than the basic access fee paid by the customer within the period.The second special feature is that the German mobile communications market is still relatively

young. Apart from rapid growth in the number of customers, another general feature of youngmarkets is that the service category exchanged there is new, both for sellers and buyers (cf. Laker,Pohl, & Dahlho!, 1999, pp. 88}93; Gerpott, 1998, pp. 215}216). For instance, none of the fournetwork operators had had any experience in competition with other providers of mobile net-works, when they entered the German market between 1992 and 1998. Likewise, the large numberof new customers acquired by the four networks were predominantly (private) accounts who havenot used a mobile terminal before. Consequently, the level of uncertainty among prospectivecustomers in the mobile communications market may be higher* or their level of trust may belower * than in fully developed markets.On the demand side, the mobile communications market is divided into residential and business

customers. Our own research excludes the market for business customers who mainly use mobilecommunications services to earn income. Unlike residential customers, business users often do notthemselves make the decision to sign or extend a mobile subscription contract. Instead, there arespecial purchasing departments within their companies that are responsible for doing this. In themobile communications market, therefore, there should be a clear distinction between the pro-cesses used to retain business accounts and those used to retain residential customers. To reducecomplexity, therefore, we restrict our analysis to the residential customer segment.

3. Customer retention, customer loyalty, and customer satisfaction: di4erentiation of the constructs,their causal links, and their determinants

3.1. General research status

The phenomenon of customer retention encompasses a degree of `fuzzinessa since it representsa theoretical construct which cannot be observed directly. There is considerable variance in theways in which customer retention is speci"ed conceptually and empirically by scholars andpractitioners. There are also great di!erences in the manner in which it is more or less separated


from related constructs such as `customer loyaltya, `customer satisfactiona, `customer enthusi-asma, `customer trusta, and `customer obligationa (for similar views see Bliemel & Eggert, 1998,p. 38; Diller, 1996, p. 81). Therefore, for the sake of clarity we must point out that we follow thetheoretical arguments of Homburg and Bruhn. They suggest distinguishing between the constructsof customer retention, customer loyalty, and customer satisfaction which they see as linked bya two-stage causal chain (cf. Homburg & Bruhn, 1998, pp. 8}10). Accordingly, customer satisfac-tion is a direct determining factor in customer loyalty, which, in turn, is a central determinant ofcustomer retention. Each of the three constructs mentioned is a!ected by other factors, which canbe divided into those on the side of the potential customer (e.g., need for variety) and those on theside of the supplier of a product. On the provider side, companies have a direct in#uenceon construct determinants (e.g., the marketing mix). On the customer side, companies can, atmost, in#uence factors (e.g., demographic and psychographic features of the potential customer)indirectly by selecting their target markets. Therefore, customer side factors are not analysed in thispaper.If one, "rst of all, speci"es the customer retention construct at the end of the causal links

postulated by Homburg and Bruhn, it is possible to identify the following common core in thewide-ranging de"nitions suggested in the literature: Customer retention (CR) is concerned withmaintaining the business relationship established between a supplier and a customer. This can beachieved in two ways. The "rst is by subsequent purchases, or by extending the customer's contractwith the supplier over a speci"ed period of time (ex post perspective). The second is by the intentionof the customer to make future purchases from the provider, or to refrain from quitting the contract(ex ante consideration) (cf. among others, Herrmann & Johnson, 1999, p. 583; Bliemel & Eggert,1998, pp. 38}39; Me!ert, 1998, p. 119; KruK ger, 1997, pp. 19}22; Peter, 1997, p. 7; Diller, 1996,pp. 83}84). It is not possible to derive clear threshold values * either for the frequency ofsubsequent purchases, the continuation of contracts, or the intention to abandon a provider* thatcould be used to classify a customer as `retaineda when they were exceeded or not reached. Theretention of a customer by a supplier therefore is represented by a continuous variable which cantake di!erent values over time (see in agreement Homburg & Bruhn, 1998, p. 10; Me!ert, 1998, pp.119, 129; KruK ger, 1997, p. 27; Diller, 1996, p. 84).On the one hand, a business relationship may be maintained involuntarily because a customer is

prevented by mobility barriers from changing suppliers or dispensing with a category of service(cf. Herrmann & Johnson, 1999, pp. 585}586; Bliemel & Eggert, 1998, pp. 41}43; Me!ert, 1998,pp. 127}128; Diller, 1996, p. 88). On the other hand, a customer may carry out subsequenttransactions because she has a favourable attitude towards the provider and the services hesupplies, and because he therefore wants to keep the business relationship going to their mutualbene"t. Customer loyalty (CL) is the term used when business relationships are continued in thelatter way (cf. Bliemel & Eggert, 1998, pp. 39}41; Homburg & Bruhn, 1998, pp. 8}9; Weinberg,1998, p. 49; KruK ger, 1997, pp. 20}21; Diller, 1996, pp. 88}89; Dick & Basu, 1994, p. 101). From thisdistinction it follows that, although CL and CRmay be strongly related in terms of cause and e!ect,the existence of mobility barriers and mobility intensi"ers means that they are not completelycongruent.The construct of customer satisfaction that comes at the beginning of the causal links assumed

by Homburg and Bruhn (1998) can be conceptually speci"ed as follows: Customer satisfaction (CS)is an experience-based assessment made by the customer of how far his own expectations about the


�For a discussion of the meaning of `customer satisfactiona, see Herrmann and Johnson (1999, pp. 582}583),Homburg, Giering and Hentschel (1999, pp. 175}176), KruK ger (1997, pp. 43}48), and Woodru! (1997, pp. 142}143).

� In view of the distinction made here between CR, CL, and CS, the following point must be noted. The cross-tabulations shown in Fig. 1 di!er frommatrices in the previous literature that, at "rst glance, appear similar, but in whichCR and CL or CL and CS are not analysed separately (see e.g. Herrmann & Johnson, 1999, p. 585; Homburg, Fa{nachtand Werner (1998, p. 406); Dick & Basu, 1994, p. 101).

�For a general discussion of the competitive relevance of mobile network operator number portability, see Gerpott(1998, pp. 75, 244).

individual characteristics or the overall functionality of the services obtained from the providerhave been ful"lled. Satisfaction is higher or lower with respect to the extent to which what wasactually provided exceeds or falls short of what was expected.� In the literature CS is discussed asone important factor in determining CL which is not conceptually identical with CL. This isbecause CL is also essentially in#uenced by the future conxdence of customers in the capabilities ofa supplier or his sales objects, and by their assessment of owers by competitors relative to thosewhich they experienced from their present vendor (cf. Herrmann & Johnson, 1999, p. 586;Homburg, Fa{nacht, & Werner, 1999, p. 186; Bliemel & Eggert, 1998, p. 40; Weinberg, 1998,pp. 48}49; Dick & Basu, 1994, pp. 101, 104).The theoretical di!erentiation of CR, CL, and CS that can be derived from the literature, and the

two-staged causal links between these constructs will next be considered with regard to theirspeci"c relevance for the German mobile communications market.

3.2. Hypotheses on interrelationships between CR, CL, and CS and their determinantsin the German mobile market

3.2.1. Customer retention and its determinantsThe matrix in Fig. 1 displays four ideal combinations of CR and CL values as pertinent for the

German mobile communications market (cf. Diller, 1996, p. 88, Fig. 5).� Accordingly, there are twostandard situations covering the following cases. First, that in which customers want to terminatethe contractual relationship with their mobile carrier and, from the point of view of their loyalty,will distance themselves from their provider (see the customer type `wanderersa in Fig. 1). Second,that in which customers want to maintain the contractual relationship and have a positive attitudeto the provider (see the customer type `loyal customersa in Fig. 1). In addition, it may happen,however, that although customers do not feel any loyalty towards their network operator, theynevertheless do not wish to terminate the contractual relationship (see the customer type `captivecustomersa in Fig. 1). The main reason for this may be that customers in Germany are not able totake their assigned cellular phone numbers with them to another network operator with whomthey would like to enter into a new contract once they have terminated their contract with theirpresent carrier (cf. Schwarz-Schilling & Stumpf, 1999, pp. 3}10, 37}65; Mellewigt, 1997, p. 576).�Customers, then, have to pay a price for `inconveniencea if a new mobile communications numberis assigned to them when they change providers. This is because (1) other persons in theirenvironment have to be informed of the new number so that contact is not lost, and (2) newbusiness cards, writing paper, address labels, etc. may have to be revised (see Berke, 1999, p. 94;Knauer, 1998, pp. 516}517).


Fig. 1. Ideal combinations of customer retention and loyalty, and customer loyalty and satisfaction in the mobilecommunications market.

Non-standard types of customers are the `advantage maximisersa and the `bad buyersa (seeFig. 1). Although these credit their network operator with providing a thoroughly `respectabletechnical servicea and have a positive attitude towards him, they nevertheless intend to terminatetheir business relationship with the operator. A literature review and anecdotal insights which weobtained over a 5-year period in consulting projects for cellular operators suggest that this low CRin spite of high CL can be explained by three complementary lines of argument:

� In the German mobile communications market, it is common practice for customers to be soldmobile handsets at a low price when they conclude a contract with a provider. This terminalprice is well below the one that has to be paid when no mobile subscription contract is involved.The aim is to lower the barrier for new customers entering the young mobile communications


market. In return, the providers require that their customers sign a long-term access line contract(typically for two years) to make up what they have lost on the terminal through the revenuesobtained from a customer (see Wilfert, 1999, pp. 198}199; Knauer, 1998, pp. 513}514; Booz.Allen & Hamilton, 1995, p. 52). The result of this practice could be that after the minimumcontractual period has expired a substantial number of customers terminate their contract sothat they can once again obtain a subsidised terminal (see Wilfert, 1999, p. 199). Accordingly, thestrong desire of mobile communications customers to obtain a new terminal, irrespective of theirloyalty to their network operator, can have a negative e!ect on CR.

� Many residential customers only use mobile communications services for the xrst time after theyhave signed a network access contract. Because of their lack of experience with such services, it ispossible that customers may overestimate the bene"ts they expect to obtain. Furthermore, therequirements of potential customers can change to the extent that the reasons that led toa contract in the "rst place no longer apply. In both cases, the reduced personal bene"ts thata mobile communications connection brings can lead customers to change their intention ofcontinuing with the contract. This low CR level does not necessarily have to go hand in handwith a negative attitude towards the network operator; for the customers may recognise andacknowledge that the important reason for wanting to terminate the business relationship hasnothing to do with their contractual partner.

� The costs that customers have to pay for the use of mobile communications access are di$cult toestimate when a contract is being signed. This holds particularly for customers who have noexperience of cellular services. For this reason, it could turn out that a customer has under-estimated how much he/she will have to pay. Thus, there may be a large number of cellularcustomers who, as a result of having to pay more than their threshold value, intend to terminatethe contractual relationship with their network operator to completely withdraw from themarket ("low CR). Nevertheless, because of the similar prices charged by all the competitors inthe German mobile communications market, these customers express complete loyalty to theircurrent business partner ("high CL).

To sum up, based on Fig. 1 and the preceding three paragraphs, we expect CR to be stronger inthe German mobile communications market when

� CL is also high (Hypothesis H�), although there will also be a considerable number of customers

who, with strong (weak) bondings to a network operator, show a low (high) degree of CL(Hypothesis H

�);

� it is important for customers to retain their mobile access number over a long period (HypothesisH

�);

� fewer customers wish to obtain a new mobile terminal (Hypothesis H�);

� customers rate highly the bene"t they obtain from the services supplied by their own mobilecommunications provider (Hypothesis H

�);

� customers favourably rate the prices charged by their own mobile communications provider forthe services supplied (Hypothesis H

�).

3.2.2. Customer loyalty and its determinantsIn the literature (cf. Herrmann & Johnson, 1999, pp. 584}587; Homburg et al., 1999, p. 178; Dick

& Basu, 1994, p. 104) it is emphasised frequently that there is a signi"cantly positive correlation


On the importance of trust and the perception of competitors as factors determining CL, see also Peter (1997, pp.121}124) in addition to Herrmann and Johnson (1999, p. 586), Homburg et al. (1999, p. 186), Bliemel and Eggert (1998, p.40), Weinberg (1998, pp. 48}49), and Dick and Basu (1994, pp. 101, 104).

For a general theoretical treatment of the customer value notion, see Woodru! (1997).

between CS and the loyalty that customers feel towards a "rm, but that a high degree of CL doesnot always have to go hand in hand with a high degree of CS. Here, it is usually assumed that CLand CR can be equated. However, it has just been shown that CS has only an indirect e!ect on CRvia CL. It is therefore necessary to have separate discussions about typical ideal combinations ofCL and the overall satisfaction of customers (see the bottom half of Fig. 1). Accordingly, there is thestandard case of `disappointed customersa who are dissatis"ed with the services provided by theirnetwork operator, and who consequently make a negative assessment of this provider with regardto the future (see Fig. 1, standard case A). Similarly, we have a standard case of `impressedcustomersawho are very satis"ed with the performance of their network operator to date, and whotherefore place great trust in him with regard to the future as well (see Fig. 1, standard case B). Inaddition, however, there are plausible explanations for the occurrence of two rarer cases. First,a network operator can have `optimistic customersa who are not really satis"ed with the servicessupplied to date, but who nevertheless trust that their provider will improve his performance in thefuture. Alternatively, they see him as a `lesser evila in comparison with his competitors (see Fig. 1,atypical case A). Second, there may be `pessimistic customersa who are satis"ed with the servicesthey have received from their network operator, but who nevertheless expect, or assume, that itmight be possible to obtain better services from his competitors. Our arguments derived fromconceptual CR/CS studies can be condensed in the form of three hypotheses:

� CS has positive e!ects on CL (Hypothesis H�).

� CS does not determine CL completely. There is, indeed, a considerable number of customerswho have a high (low) degree of CL while at the same time demonstrating a low (high) degree ofCS (Hypothesis H

).

� The more positive the image that customers have of their network operator's competitors, theweaker will be the CL to their current contractual partner (Hypothesis H

).

3.2.3. Customer satisfaction and its determinantsUp to now, CS has been characterised here as an overall retrospective judgement about how far

expectations with regard to a service have been ful"lled in use situations. This qualitativeperception is in turn based on evaluative perceptions by the customer with regard to individualpurchase-relevant features or value drivers which facilitate or block the achievement of service-related personal goals of the customer. As far as mobile communications services are concerned,previous research suggests the following four individual features as key drivers of the customervalue of cellular services (see Wilfert, 1999, pp. 191}194; Bolton, 1998, pp. 54}55; Gerpott, 1998,pp. 282}283; Danaher & Rust, 1996, pp. 67}69; Booz. Allen & Hamilton, 1995, pp. 57}58):

� the network quality, which is re#ected in excellent indoor and outdoor coverage and in the clarityof voice reproduction without any connection break-downs;

� the price paid for obtaining access to and using the network;


� the features summarised under the rubric of **customer care++, namely the quality of the exchangeof information between customer and supplier (1) in response to customer (telephone) enquiriesand (2) in the course of interactive activities initiated by the network operator (e.g., presentationof an invoice).

Another point to be taken into account is that the overall satisfaction of customers with mobilecommunications services is also in#uenced by how far they perceive these services to be of bene"tto them personally. Even if a customer has a positive (negative) view of the services provided by hisnetwork operator, his overall satisfaction may still be adversely (favourably) a!ected by the factthat he rates the general value of the range of services to meet his needs * in other words, theidiosyncratic bene"t he obtains from them* as low (high). Overall, then, it is to be expected thatCS will increase hand in hand with the positive assessment of network quality (Hypothesis H

��),

mobile communications prices/costs (Hypothesis H��), customer care (Hypothesis H

��), and the

personal bene"t obtained from mobile communications services (Hypothesis H��).

There is one "nal point that remains to be made from a practical point of view. What is of greatinterest is not just the mere existence of e!ects of di!erent variables on CR, CL, and CS, but ratherthe relative size e!ect of the various supplier side factors linked to the three focal criteria.

4. Empirical methods and results

4.1. Sample

Data for the present study were collected by an established market-research company. Weinstructed this "rm to carry out a standardised telephone survey among customers of mobilenetwork operators in Germany. The following groups of individuals were excluded from thesurvey:

� Customers of the network operator VIAG Interkom because this company only had a 0.2%share of the customer market at the time the data were collected (January 1999). Furthermore,the small number of VIAG customers had very little experience with the services supplied bytheir operator, since the VIAG network had only been launched three months before.

� Customers of T-Mobil who are still using the analogue `C-Netza because `C-Netza only hada 2.5% share of the customermarket in January 1999, and was due to be shut-down by the end of2000. Questions about CR were therefore of little signi"cance in this context.

In order to obtain a random sample of about 700 residential customers layered in proportion tothe market shares of the three established mobile operators in Germany phone numbers weredrawn at random from all the "xed-network telephone numbers in Germany. If the interviewersfound that one person in a household was a customer of a mobile network operator, the personconcerned was asked there and then, or when contacted later, to participate in the survey. Thosewho agreed to do so were asked if they were able to o!set their mobile communications costsagainst tax, and whether they used their mobile communications principally for business purposes.Only those who answered `noa to both questions were classi"ed as residential customers, and werethen included in subsequent analyses.


�� In mid-January 1999 the distribution of all customers of the three German operators of mobile communicationsnetworks mentioned was as follows: Mannesmann 44.2%; T-Mobil (without `C-Netza) 40.8%; and E-Plus 15.0%. Asa consequence, E-Plus customers are somewhat over-represented, and those of Mannesmann and T-Mobil somewhatunderrepresented. A �� test revealed that network-operator shares in our sample and in the market as a whole di!ersigni"cantly at the 5% level, but not at the 1% level (��"8.09; df"2).

��For measurement/indicator variables of dependent (independent) constructs to be explained (not to be explained),we use the abbreviation y

�(x

�). If a construct is measured by several indicators, the following notation holds:

y��

(x��)"measurement variable z to capture the endogenous (exogenous) latent variable y

�(x

�).

Following this procedure, a total of 684 residential customers were interviewed by phone. Ofthese, 41.1% were customers of Mannesmann, 39.9% of T-Mobil, and 19.0% of E-Plus.�� Therespondents' age ranged between 15 and 76, with a mean of 36.89 years (S"13.34; n"680). 69.9%of the respondents were men. In 51.2% of the cases, the net monthly income in the household of theinterviewee exceeded DM 4000. The monthly mobile bill of the respondents was between DM 10and DM 1000, with a mean value of DM 80.05 (S"66.81; n"639). For the German cellularmarket data on the socio-demographic structure of all the residential customers are not publiclyavailable. However, we obtained such data from one mobile network operator. We were thereforeable to analyse with regard to the four socio-demographic variables reported above, to what extentthere were signi"cant deviations between the sub-sample of the customers of this operator includedin our survey and the total population of all customers of this provider. Appropriate tests revealedno di!erences at the 10% level of statistical signi"cance.

4.2. Measurement of variables

4.2.1. Customer retention, customer loyalty, and customer satisfactionFollowing earlier work (for instance, Grund, 1998; Joho, 1996; Keaveney, 1995; Rust & Zahorik,

1993), to measure CR, interviewees were asked, whether they would `terminate their contract [withthe relevant network operator] as soon as possiblea ("indicator y

�).��Answers had to be given on

a 5-point scale ranging from `completely righta (coded 1), to `partly righta (coded 3), to `not at allrighta (coded 5). Table 1 informs about the distribution of the CR indicator in our sample.According to this, 59.8% of the respondents can be classi"ed as closely linked to a networkoperator (scale level of 5), and 12.6% as only slightly linked or highly willing to quit the contract(scale levels of 1 and 2).To measure CL, previous research has mainly employed items that re#ect an individual's

intention to repurchase and his willingness to recommend a product to others (cf. Herrmann& Johnson, 1999; KruK ger, 1997; Peter, 1997). Therefore, the residential customers were asked towhat extent, on the basis of their experience, they would

� reselect the same network operator or another provider (y��

),� recommend their own or another network operator to friends or acquaintances (y

��).

Participants were provided with "ve answer categories ranging from `de"nitely opt for/recom-mend another network operatora (coded 1), to `undecideda (coded 3), to `de"nitely re-select/recommend the present network operatora (coded 5). As expected, both items were stronglycorrelated (r"0.74). Consequently, they were averaged on a single CL scale with item weights


Table 1Distribution of answers for the variables customer retention, customer loyalty, and customer satisfaction

Percentage frequency of answers for scale level�

(Low&&&&&&&&&&&&&&&&&&�High)Variables 1 2 3 4 5 M� S n

1. Customer retention (y�) 8.9 3.7 11.3 16.3 59.8 4.14 1.28 674

2. Customer loyalty (y�) 4.3 8.6 12.4 51.2 23.5 3.95 0.99 652

3. Customer satisfaction (y�) 1.8 4.5 18.2 47.5 28.0 3.95 0.90 682

�Customer loyalty was measured with two items using the average of the factor-weights of the items to calculate the`customer loyaltya scale score. Possible intermediate values that are not whole numbers were rounded o! to simplify thepresentation of the distribution of `customer loyaltya answers. In all other statistical analyses, the exact, non-roundedcustomer loyalty scale scores were used.�M"arithmetic mean value; S"standard deviation; n"number of valid answers received.

��For CR and CL: r"0.57 (n"645); for CL and CS: r"0.57 (n"651); for CR and CS: r"0.47 (n"674).

taken from their loadings in a factor analysis. This scale had an acceptable factor reliability of 0.89(see Fig. 2). As can be deduced from Table 1, the CL mean was 3.95. In other words, the averageresidential respondents showed a relatively high degree of loyalty to their mobile operator.To measure (overall) CS with their mobile communications network participants were asked to

comment on the statement `I am completely satis"ed with my current mobile communicationsnetworka (y

�), using a 5-point scale anchored with the reply options `completely righta (coded 5)

and `completely not righta (coded 1). It can be seen from Table 1 that only 6.3% of the respondentswere slightly satis"ed, or not satis"ed at all, with their mobile communications network (scale levelsof 1 and 2), and 28.0% were completely satis"ed (scale level of 5).There were signi"cantly positive associations between the three endogenous variables.��At 0.57,

the correlation between CL and CS reached approximately the order of magnitude found in earlierstudies of other markets with similar variable measurements (see, for example, Herrmann &Johnson, 1999, p. 594; Peter, 1997, p. 221). An explorative factor analysis con"rmed the expectedthree-factorial structure of the four items y

�, y

��, y

��, and y

�. Consequently, hypotheses H

�, H

�,

H�, and H

formulated in Sections 3.2.1 and 3.2.2 cannot be classi"ed as statements already refuted

by an initial rough analysis. Therefore, subsequent con"rmatory detailed analyses can begin withthe assumption that the variables CR, CL, and CS represent overlapping but not identical constructs.

4.2.2. Other supply side determinants of the focal criteriaThe three potential CR determinants phone number constancy, acquisition of a new terminal at

a favourable price, and personal benext from the mobile communications network of the currentcontractual partner of a customer were each measured by single item questions. Their wording andanswer scales are shown in Table 2 (see variables x

�, x

�, and x

�in Table 2). As the fourth supply side

factor determining CR and CS, assessment of mobile communications prices was operationalisedwith two items that are marked as indicators x

��and x

��in Table 2. An interviewee's perception


Table 2Measurement of supply side variables expected to in#uence the focal three criteria

Variable name Measurement

Phone number constancy Ìt is important for me to be able to keep my present mobile phone numberonce my contract with2has expired.a (x

�)

Five answer categories, for `completely righta ("5), to `partly righta ("3), to`not at all righta ("1)

New terminal Ìt is important for me to obtain a new mobile phone at a very reasonable priceonce my contract with 2 comes to an end.a (x

�)

Five answer categories, as shown above for item x�

Personal bene"ts `What personal bene"t does the 2 network have for you?a (x�)

Five answer categories, from `very substantial bene"ta ("5), to `mediumbene"ta ("3), to `no bene"ta ("1)

Assessment of prices `How do you assess the prices, tari!s, and conditions of your 2 access?a (x��

)`How do you assess the prices charged for connecting from your 2 access tothe "xed network?a (x

��)

Five answer categories, from èxtremely gooda ("5), to `gooda ("3), to `bada("1)

Image of competitors Ì will present a number of statements to you that may describe providers ofmobile phone services. For each one, please indicate whether it applies parti-cularly to 2[competitor of the interviewee's own provider].a

Customer orientation (x��

): Total of the statements marked as particularlyapplicable ìs fair to his customersa, ìs customer-friendlya, and ìs nicea

Reliability (x��

): Total of the statements marked as particularly applicableìs seriousa, ìs reliablea, and `provides securitya

Modernity (x��

): Total of the statements marked as particularly applicableìs technically up to datea, ìs a modern "rma, and ìs dynamicaSum of the three image elements x

��, x

��, and x

��to form an overall image

score with higher values representing a better competitor imageAssessment of network quality `How do you assess the quality of the 2 network, based on your overall

experience in using the 2 network for phone calls?a (x��

)`How do you assess the call quality of the 2 network ?a (x

��)

Five answer categories, as shown above for items x��

and x��

Assessment of customer care `How do you assess the quality of the customer care services of the 2 net-work?a (x

��)

`How do you assess the e!orts of your network operator to keep you up todate? These e!orts include #yers sent with your bill, letters to customers, andbrochures.a (x

��)

Five answer categories, as shown above for items x��

and x��

of the network operator's competitors (image of the competitors) was investigated by presenting ninepotentially positive characteristics of operators of mobile communications networks. Respondentswere then asked to indicate the extent to which these characteristics applied to a particularcompetitor. Factor analyses revealed that the image of the competitors comprised the threedimensions `customer orientationa, `reliabilitya, and `modernitya (see variables x

��, x

��, and

x��

in Table 2). These could, in turn, be aggregated to an overall scale image of competitors with an


Fig. 2. Completely standardised solution of the empirical causal model.

acceptable measurement reliability (see Section 4.3). Finally, the CS determinants of perceivednetwork quality and customer care performance were each measured with two items for which detailscan also be found in Table 2 (see there variables x

��, x

��, x

��, and x

��).


��Methodological introductions of statistical causal analysis techniques can be found in Homburg and Baumgartner(1995, pp. 163}165), and Homburg and Hildebrandt (1998, pp. 16}43 and the sources quoted there).

��LISREL stands for Linear Structural Relationships.��The threshold values for the various quality criteria discussed below are also established there.

4.3. Analysis of causal links

4.3.1. Quantixcation and quality assessment of the postulated causal modelThe hypotheses put forward in Section 3.2 can be interpreted as a model with multi-stage causal

links. In this model, CR is in#uenced by CL and by the supply side variables of `phone numberconstancya, `new terminala, `personal (service) bene"ta, and `service pricesa. CL, in turn, is dependenton CS and the image of the competitors. Finally, CS is a function of the assessment of price, networkquality, customer care, and the personal bene"t provided by the services of a mobile communicationsoperator. To wit, CS works indirectly through CL on CR, but does not a!ect CR directly.Causal analysis methods can be used to test this multi-stage causal model. In causal analyses,

simultaneous tests are performed to see how far the following three models correspond to theempirical data: (1) a measurement model designed to capture the (indicator-based latent) variablesaddressed in the research's cause and e!ect hypotheses; (2) a structural equations model intended tore#ect the cause and e!ect relationships between the latent variables; and (3) an overall modelconsisting of the measurement model and the structural equations model.�� Therefore, the presentstudy employed a con"rmatory causal analysis test of the system of causal relationships de"ned byhypotheses H

�}H

��using the LISREL 8 software package.�� To estimate the models, we selected

the `Generally Weighted Least Squares (WLS)a method because it typically provides validparameter estimates, even if* as in our study* a normal distribution of the indicators cannot beassumed in the underlying population, and if the indicators have to be regarded as ordinal-scaledrather than interval-scaled (cf. JoK reskog & SoK rbom, 1996, p. 240).Fig. 2 gives details of the structural equation model calculated in accordance with our 13 e!ect

assumptions. It also gives details of the factorial measurement model on which it is based. Latentvariables are indicated by ellipses and measurement variables by rectangles. The arrows pointingfrom the latent constructs to the measurement variables reveal the factor loading of the indicatoron the construct. The arrows pointing `from outsidea to the indicators quantify the residual partfor the relevant indicator that cannot be explained by the measurement model. Thearrows/standardised path coe$cients between the two latent variables represent the causal rela-tionship between the two constructs.Before the individual path coe$cients in Fig. 2 can be interpreted, the "t (1) of the measurement

model, (2) of the structural equation model, and (3) of the entire causal model with our data must bechecked (see Homburg & Baumgartner, 1995, pp. 162, 171}172).�� To be acceptable, an LISRELmeasurement model has to ful"l the following criteria: (a) the reliability for each indicator must be*0.4; (b) each factor reliability must be *0.6, and (c) the average factor variance explained mustbe *0.5. Our measurement model meets requirement (a) for 15 of 16 indicators (the exception isvariable x

��) and requirement (b) without restriction. Requirement (c) is met by four of the "ve

latent variables in Fig. 2 that are measured by at least two indicators. Only for the construct`assessment of customer carea (x

�) does the average explained variance of the variables for the

factor fail, with 0.46, to reach the aforementioned threshold value. Overall, then, the quality of ourmeasurement model can be said to be at least satisfactory, if not very good.


The quality of structural equation models is classi"ed as acceptable if the squared multiplecorrelation for each endogenous variable (to be explained)* in other words, for CR, CL, and CS inour model* is *0.4. In our sample, the squared determination coe$cients of the model shown inFig. 2 are 0.78 for CR, 0.64 for CL, and 0.65 for CS. This means that our structural equation modelexhibits a good "t with the empirical data.Common test criteria for an overall model are the following (see for details Homburg &

Baumgartner, 1995, pp. 165}172):

1. a root mean squared error of approximation (RMSEA) that should not be above 0.05;2. a ratio of �� model-"t statistics by degrees of freedom that should not exceed 2.5;3. goodness of "t indices, and particularly (a) the goodness of "t index (GFI), (b) the adjusted

goodness of "t index (AGFI), and (c) the comparative "t index (CFI), each of which has to exceeda threshold value of 0.9 if a model is to be classi"ed as "tting the data well.

As can be seen from Fig. 2, the "rst two or the last three quality criteria for our overall model arewell below the highest recommended value or above the minimum suggested values. This meansthat the overall model in Fig. 2 can be classi"ed as "tting the data very well.A critical aspect in our theoretical reasoning is the separation of/ability to separate CL and CS.

Therefore, in spite of the good "t of the data with the causal model shown in Fig. 2, we tested howmuch better would be an alternative model in which these two variables or the three indicatorsy��

, y��

, and y�were combined to form a new construct `customer tiesa, "tted to the data. This

alternative model was compared against the theoretically expected model in Fig. 2: Its RMSEAvalue was 35% higher ("worse) and its ��/degree-of-freedom ratio was 33% higher ("worse)than the benchmark model values. Further, the revised model did not explain the CR construct aswell as our initial model. Therefore, it is both possible and necessary to retain the proposedseparation of the constructs CL and CS.

4.3.2. Discussion of factors inyuencing CR, CL, and CSIn line with H

�, the empirically derived causal model (see Fig. 2) suggests that the willingness of

mobile communications customers to continue the contractual relationship with their networkoperator is strongly in#uenced by the extent to which they have a positive perception of him* inother words by CL. At the same time, however, CL does not in any way fully explain the CRvariance in our sample. Thus, the data also support H

�. Further signi"cant direct determinants of

the degree of CR were the desire to leave one's phone number unchanged, the assessment of thepersonal bene"t obtained from the services supplied by one's own mobile communicationsprovider, and his service prices (see Fig. 2). Our analyses therefore also con"rm H

�, H

�, and H

�.

Contrary to H�, the strength of preference for the acquisition of a new terminal at a favourable

price did not have any signi"cant (negative) e!ect on CR.With regard to possible determinants of CL, it can be seen from Fig. 2 that the causal links

postulated in H�}H

are in line with the empirical observations. Thus, for instance, an increase in

CS by one unit leads to a highly signi"cant increase in CL by 0.75 units (support of H�).

Nevertheless, although there is no doubt that mobile communications CS has an outstandingin#uence on CL to their network operator, the CS variable cannot by any means completelyexplain the CL variance. Consequently, it is reasonable to preserve the conceptual distinctionbetween CL and CS as suggested by H

. In our sample, a second signi"cant factor determining CL


proved to be the image that the customer had of his network operator's competitors. The morepositive this image was, the lower the degree of CL (support of H

). This indicates, then, that the

degree of CL depends partly on processes in which customers compare their perceptions of theirown network operators with the perceptions they have of his competitors.Our analyses supported the hypothesised two-stage causal link in which CS has only an indirect

e!ect on CR via CL: CS had a strong indirect e!ect of 0.375 (0.75�0.50) on CR, but its e!ect on CRwas completely mediated by the CL variable. Furthermore, three of the four remaining hypotheseson determinants of CS could be maintained in our sample. As can be seen in Fig. 2, the perceivednetwork quality (H

��), the assessment of mobile prices (H

��), and the assessment of personal

bene"t obtained from mobile communications services (H��) were detected as signi"cant direct

determinants of the overall satisfaction of mobile customers. Contrary to H��, we did not "nd

a signi"cant relationship between CS and perceived quality of customer care.If the direct and indirect e!ects of the factors explaining the di!erences in CR in Fig. 2 are

summarised, it can be seen that CL is the strongest determinant of CR with a standardised e!ect of0.50. But the overall CR e!ect of a customer's assessment of mobile communication prices amountsto 0.44 (0.28#0.41�0.75�0.50) and is thus only slightly weaker. Following CS, perceivedpersonal bene"t obtained from mobile communications services from one's own provider had thefourth-strongest impacts on CR with a total of 0.30 (0.20#0.25�0.75�0.50). The 47% di!erencein the e!ect produced by the factors `pricea and `personal bene"ta can be explained by thefollowing consideration: Because of technological standardisation in digital mobile networks, it isdi$cult for mobile operators to di!erentiate their services once a comprehensive regional coverageof their networks has been achieved. As a consequence, a customer's perception of the personalbene"t obtained from the services of his own network provider could not be attributed to theperformance of the company concerned in particular, but to all providers in general. Therefore, inturn, the personal bene"t obtained from services supplied by the customer's own contractualpartner has a weaker e!ect on CS and on CR with just that partner.With an overall e!ect of 0.22, the mobility barrier caused by the lack of network operator

portability of mobile access numbers was the "fth-strongest determinant of CR. This barrier helpsnetwork operators to `motivatea customers to continue their contractual relationship even ifthey do not have a very positive attitude towards their mobile communications provider and/orare not satis"ed with the services he supplies. With an e!ect size of 0.17 (0.46�0.75�0.50),the sixth-strongest determinant of CR was the perceived quality of the network. Customersappear to consider quality to be a feature that `can be taken for granteda. Therefore, thisvariable does not have an outstanding e!ect on CR. Finally, the desire of a mobile communicationscustomer to obtain a new terminal and perceived quality of an operator's customer care processeshad practically no e!ect on the CR criterion. Customer care can therefore be taken torepresent a peripheral service feature that is of little importance in shaping CR compared to thecore service.

5. Implications for competitive strategies of mobile network operators

The purpose of this study was to analyse levels, di!erences, and causal links of the threeconstructs CR, CL, and CS, using a sample of 684 residential mobile communications customers in


Germany. Overall, respondents scored relatively high on the three focal constructs. The resultsfurther indicate that it is conceptually justi"able, empirically tenable, and practically helpful for thecontract business under consideration if CR is not equated with CL and/or CS. Instead, a two-stage causal mechanism should be assumed in which CS drives CL which in turn has impacts onCR. To illustrate the need to distinguish between the three focal variables, respondents weredivided along the median values of the three target constructs in the sample in cases with a low ora high value on a particular construct. Cross-tabulations of the CR}CL or the CL}CS answercombinations of the respondents revealed that 34 or 31% of the customers belong to the atypicalcases 1 and 2 or A and B shown in Fig. 1. In other words, these individuals had opposite CR andCL or CL and CS variable values.A prerequisite for the di!erentiation between the three target constructs also having practical

relevance is that it should help to identify supply side management variables that only selectivelya!ect the three target constructs. In our study, such parameters were the variables `phone numberconstancya, `image of competitorsa, and `network qualitya (see Fig. 2 and Table 2). In particular,a lack of number portability between operators of mobile communications networks appears to actas a barrier that prevents customers from terminating the contract with their network operator,even if their loyalty or satisfaction is low. This is because they would lose their current number ifthey were to change to another provider. For operators of mobile communications networks witha large customer base, this "nding implies that they should organise professional political lobbyingactivities in every national market that help to reduce competitive pressures by perpetuatinga regulation that does not enforce portability of phone numbers in current GSM networks and inthe next generation of technology for mobile communications networks (UMTS/IMT-2000). InGermany such lobbying activities of mobile operators were recently unsuccessful since the Germanregulatory authority RegTP decided to enforce complete number portability between operators ofmobile communications networks in February 2002. According to our "ndings this change is likelyto increase considerably the intensity of competition in Germany at a stage of market developmentwhere the number of new "rst-time customers is declining and where acquisition of old customersfrom their competitors will become an increasingly important ingredient of mobile operators'competitive strategies.In order to develop sound competitive and marketing strategies, it would seem advisable for

mobile network operators not just to rely on general indicators of CL and CS when analysing thethreat of migration by their existing customers. They should rather seek to improve theirmeasurements of customers' perceptions of characteristics of the core services they themselves o!er.There are two elements that provide the most important early-warning signals for the degree of CRand which also act as a `levera to motivate customers to continue their contractual relationshipwith a provider. These are, "rst, the customer assessment that the prices charged by their supplierare `good and faira (compared against competitors), and, second, the customer perception of thefunctional bene"t of mobile communications services. The use of pricing policies to achieve positiveCR e!ects is especially di$cult for operators of mobile communications networks because, up tonow, competitors were very quick in neutralising temporary advantages in price level or pricestructure by introducing modi"ed pricing schemes of their own (see for details Wilfert, 1999, p. 197;Gerpott & KnuK fermann, 1998, pp. 144}147; Stoetzer & Tewes, 1996, p. 307). However, customer-speci"c discounts* somewhat similar to `bonus milesa in aviation* can be made dependent onthe duration of a contract and on the amount that services are used. Operators of mobile networks


who "rst succeed in creating the complex billing procedures for this type of pricing strategies andwho manage to communicate these plans in a way that a!ects the mass market, will be able tostrengthen the ties of their residential customers to their "rm because such strategies have hardlybeen used in the past in Germany (cf. Gerpott, 1998, pp. 213}214, 294; Knauer, 1998, pp. 515}516).Perceived personal bene"t obtained from mobile communications services has considerable

direct and indirect e!ects on CR. This suggests that mobile operators within the residentialcustomer market in Germany ought to strive to become pioneers in service innovations thatimprove the core functionalities of mobile communications services (fast, simple, and trouble-freetransfer of all types of information from any place at any time). More speci"cally, if, between 2001and 2004, an operator of mobile communications networks in Germany is the "rst provider tointroduce functioning fast(er) mobile data services and the next mobile network generation withbroadband multimedia services onto the market he will have the opportunity to forge stronger tieswith residential customers as well.Finally, it should be noted that two `non-"ndingsa have practical implications for competitive

strategies of mobile operators in the residential customer market. First, there appear to exist onlya few residential customers who terminate the contract with their network operator because theywant to obtain a new terminal at a low price by switching to another provider once their contractcomes to an end. Consequently, it may not be necessary for mobile operators to o!er their existingresidential customers up-to-date models of terminals at a price that is below the initial cost of thedevice. Second, the quality of customer care * whether provided over the phone by call centreservice agents, or by a continuous supply of written product or company information * has nosigni"cant direct or indirect e!ect on CR. To wit, popular claims of consultants (for others, seeHarter et al., 1997, pp. 160}162; Heidemann & Zynga, 1997, pp. 19}21) that, even in the case ofstandard telecommunications services for the mass market, customer care is a very importantvariable for network operators in improving customer acquisition and CR were not substantiated.This "nding may be taken to indicate that the quality of care for residential customers in the case ofstandard telecommunication services represents a `hygiene factora: If customer care is poor, it willcontribute to dissatisfaction; but if it is good, it will not improve CS. Accordingly, mobile operatorswould be well advised to maintain the telco industry standard in customer care processes, butshould not attempt to obtain a competitive strategic advantage by providing an extraordinary levelof customer care.

6. Implications for future research

Directions for future research on retention, loyalty, and satisfaction of cellular service buyers inparticular and of buyers of service-like innovative contract goods in general follow from four majorlimitations of the present study. First, our analysis relies on cross-sectional data. Thus, to providean even more convincing case for causal interpretations of variable correlations, additionallongitudinal research is needed in which exogenous factors are captured before data on endogenouscriteria are collected. Second, in the present study the focal constructs CR and CL were measuredby questionnaire items asking for behavioural intentions and attitudes related to service o!eringsof cellular operators. New research can help by expanding this measurement approach to includeindicators of actual customer usage behaviours such as number of months passed since a customer


"rst signed the contract with her cellular operator, customer air time minutes/revenues per year ornumber of times a customer recommended her operator to another person within a speci"edperiod.Third, our work did not take into account observations made by Bolton (1998, pp. 52}62) in the

US cellular residential market, which suggest that the magnitude of correlations between cellularservice attributes and CS on the one hand and CL and CR on the other hand may be contingent onthe past duration of the contractual relationship between a customer and his cellular serviceoperator. As a consequence, additional studies are needed exploring CR and CL determinants invarious residential customer sub-samples which di!er in terms of the duration of their previousrelationship with a mobile operator. Fourth, the present investigation placed a deliberate focus onsupply side mobile service attributes a!ecting CR, CL, and CS. Therefore, further research shouldinclude customer side variables re#ecting speci"c individual customer goals and motivations inusing cellular services as well as general psychological constructs such as need for variety whichpast work discussed in the context of repeat purchase behaviours. Similarly, empirical researchexploring determinants of CR, CL, and CS in other telecommunications service market segments (e.g.,dial-up internet access) would be bene"cial to learn to what extent our "ndings can be generalisedbeyond the cellular market.To sum up, given the paucity of previous research on CR, CL, and CS in competitive (mobile)

telecommunications service markets there exists ample opportunity for management scholars andpractitioners alike to contribute towards improved carrier pro"tability by expanding our under-standing of antecedents and consequences of the duration of an operator's contractual relationshipwith his mass market customers.

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