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Telecommunications Policy 25 (2001) 249}269

Customer retention, loyalty, and satisfaction in the German mobile 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 for telecommunication network operators on their way to superior economic success in the liberalised German market. Therefore, drawing on a sample of 684 residential customers of digital cellular network operators in Germany this study tests hypotheses suggesting that CR, CL, and CS should be treated as di!erential constructs which are causally inter-linked. LISREL analyses support a two-staged model in which overall CS has a signi"cant impact on CL which in turn in#uences a customer's intention to terminate/extend the contractual relationship with his mobile cellular network operator ("CR). Mobile service price and personal service bene"t perceptions as well as (lack of) number portability between various cellular operators were 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 important lever for regulators to promote competition in cellular markets is the enforcement of e$cient number portability 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 economic development of industrialised nations. This is the result of enormous technical progress as well as of

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

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the increased number of network operators and the intense competition that has developed. These factors, in turn, are a consequence of the removal of monopoly rights, which were mainly enjoyed by state-owned operators of public telecommunication networks. The increasing economic importance of telecommunications companies inspired many management scholars to devote more teaching 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 frequently pointed out that once customers have been acquired and connected to the telecommunications network of a particular operator, their long-term links with the focal operator are of greater importance to the success of the company in competitive markets than they are in other industry sectors (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, there is a dearth of empirical research into the extent of customer retention or the supply side retention drivers in particular telecommunications markets. Therefore, this paper examines di!erences and commonalties between the constructs `customer retentiona, `customer loyaltya, and `customer satisfactiona and what supply side factors in#uence them both conceptually and empirically for the German mobile communications market using data from a sample of 684 residential mobile communications 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 are inter-linked is of general importance to corporate management. This is because without respect to the industry concerned all three are (intermediate) objectives on the way to ensuring a company's sales success which can be in#uenced by management action. Second, to date management research on customer retention and satisfaction has been concerned almost exclusively with over-the-counter goods sold in unconnected individual transactions in mature markets. In the mobile communications market, however, usage-dependent and service-like contract goods are sold. By focusing the analysis on this type of market a less `made-to-order "eld of researcha is investigated. 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 concepts of customer retention, customer loyalty, and customer satisfaction * "rst in general, and then with reference to the mobile communications market in particular. Further, we develop hypotheses on supply side determinants of these three constructs within the mobile communications market. These hypotheses are then tested in an empirical study reported in Section 4. Finally, in Section 5, we discuss implications of the empirical "ndings for number portability regulation in mobile markets and for competitive strategies of mobile network operators.

See, for instance, the article collections edited by Bruhn and Homburg (1998), and Simon and Homburg (1997), in which customer retention, customer loyalty, and customer satisfaction are discussed as success criteria for marketing strategies in a wide range of di!erent industries. For reviews of relevant management research see Gerpott (2000), Homburg and Bruhn (1998), Homburg and Rudolph (1997), and Dick and Basu (1994).

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2. Pro5le of the German mobile cellular market Mobile communications markets can be divided by the type of services provided and by the telecommunications networks used for `productiona into the sub-markets for cellular radiotelephony, paging, trunked mobile radio access, and satellite services and networks (see Gerpott, 1998, p. 220; Knauer, 1998, p. 509; Stoetzer & Tewes, 1996, p. 304). In terms of sales revenues and number of customers involved, the mobile cellular telephony market is by far the most important sub-market for mobile communications. Thus, this study concentrates on this part of the mobile market in Germany. In keeping with common practice, the terms `cellular marketa and `mobile (communications) marketa will be used synonymously. The "rst non-military public mobile communications network was introduced in 1958 into Germany. By the end of 1991, 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 high prices of terminals and services, and to technical shortcomings of the analogue network generations used at the time (e.g., frequently no radio coverage within buildings.) Demand only started to take-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 was dissolved. Competition between four GSM operators promoted high network availability and the fast introduction of user-friendly terminals. It also prompted considerable marketing e!orts. These factors 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 from the end of 1998 to the end of 1999 alone, the number of cellular access lines in Germany increased by 9.46 million or by 68%. At the end of 1999, there were four network operators sharing the market. These were Mannesmann/Vodafone with a customer market share of 42%, Deutsche Telekom/T-Mobil with 40%, E-Plus with 15%, and VIAG Interkom with 3%. Because the four operators use a network technology based on a common standard, the services they o!er are very similar. As a result, the German mobile communications market has the structure of a narrow oligopoly. In this oligopoly market, at least up to the end of 1999 none of the four network operators 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, the mobile communications market has two special features. First, access to a cellular network and the handling of calls over that network represent a continuous contractual transaction carried out over a long period. During this period, the buyer cannot be certain that the network operator will always provide the promised service quality to the full extent. The contractual transaction is normally structured in such a way that customers pay a basic monthly fee for the opportunity to use the mobile communications network through access that has been provided for the purpose. In addition, they pay ex post call charges in accordance with the amount of minutes they actually use

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

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the network. As far as network operators are concerned, continuing the contractual relationship with a current customer is more important with this sort of business structure than with transactions in purchase goods. The reason is that marginal income from the customer increases the longer the business relationship lasts, because the incremental costs for each customer/cellular access line and 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 young markets 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 four network operators had had any experience in competition with other providers of mobile networks, when they entered the German market between 1992 and 1998. Likewise, the large number of new customers acquired by the four networks were predominantly (private) accounts who have not used a mobile terminal before. Consequently, the level of uncertainty among prospective customers in the mobile communications market may be higher * or their level of trust may be lower * 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 mobile communications services to earn income. Unlike residential customers, business users often do not themselves make the decision to sign or extend a mobile subscription contract. Instead, there are special purchasing departments within their companies that are responsible for doing this. In the mobile communications market, therefore, there should be a clear distinction between the processes used to retain business accounts and those used to retain residential customers. To reduce complexity, 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 represents a theoretical construct which cannot be observed directly. There is considerable variance in the ways in which customer retention is speci"ed conceptually and empirically by scholars and practitioners. There are also great di!erences in the manner in which it is more or less separated

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

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from related constructs such as `customer loyaltya, `customer satisfactiona, `customer enthusiasma, `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 the theoretical arguments of Homburg and Bruhn. They suggest distinguishing between the constructs of customer retention, customer loyalty, and customer satisfaction which they see as linked by a two-stage causal chain (cf. Homburg & Bruhn, 1998, pp. 8}10). Accordingly, customer satisfaction is a direct determining factor in customer loyalty, which, in turn, is a central determinant of customer retention. Each of the three constructs mentioned is a!ected by other factors, which can be divided into those on the side of the potential customer (e.g., need for variety) and those on the side of the supplier of a product. On the provider side, companies have a direct in#uence on construct determinants (e.g., the marketing mix). On the customer side, companies can, at most, 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 this paper. 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 the wide-ranging de"nitions suggested in the literature: Customer retention (CR) is concerned with maintaining the business relationship established between a supplier and a customer. This can be achieved in two ways. The "rst is by subsequent purchases, or by extending the customer's contract with the supplier over a speci"ed period of time (ex post perspective). The second is by the intention of 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; Kruger, 1997, pp. 19}22; Peter, 1997, p. 7; Diller, 1996, K pp. 83}84). It is not possible to derive clear threshold values * either for the frequency of subsequent purchases, the continuation of contracts, or the intention to abandon a provider * that could be used to classify a customer as `retaineda when they were exceeded or not reached. The retention of a customer by a supplier therefore is represented by a continuous variable which can take di!erent values over time (see in agreement Homburg & Bruhn, 1998, p. 10; Me!ert, 1998, pp. 119, 129; Kruger, 1997, p. 27; Diller, 1996, p. 84). K 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 subsequent transactions because she has a favourable attitude towards the provider and the services he supplies, and because he therefore wants to keep the business relationship going to their mutual bene"t. Customer loyalty (CL) is the term used when business relationships are continued in the latter way (cf. Bliemel & Eggert, 1998, pp. 39}41; Homburg & Bruhn, 1998, pp. 8}9; Weinberg, 1998, p. 49; Kruger, 1997, pp. 20}21; Diller, 1996, pp. 88}89; Dick & Basu, 1994, p. 101). From this K distinction it follows that, although CL and CR may be strongly related in terms of cause and e!ect, the existence of mobility barriers and mobility intensi"ers means that they are not completely congruent. 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

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individual characteristics or the overall functionality of the services obtained from the provider have been ful"lled. Satisfaction is higher or lower with respect to the extent to which what was actually provided exceeds or falls short of what was expected. In the literature CS is discussed as one important factor in determining CL which is not conceptually identical with CL. This is because CL is also essentially in#uenced by the future conxdence of customers in the capabilities of a supplier or his sales objects, and by their assessment of owers by competitors relative to those which 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 their speci"c relevance for the German mobile communications market. 3.2. Hypotheses on interrelationships between CR, CL, and CS and their determinants in the German mobile market 3.2.1. Customer retention and its determinants The 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 two standard situations covering the following cases. First, that in which customers want to terminate the 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 attitude to 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, they nevertheless do not wish to terminate the contractual relationship (see the customer type `captive customersa in Fig. 1). The main reason for this may be that customers in Germany are not able to take their assigned cellular phone numbers with them to another network operator with whom they would like to enter into a new contract once they have terminated their contract with their present 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 number is assigned to them when they change providers. This is because (1) other persons in their environment have to be informed of the new number so that contact is not lost, and (2) new business cards, writing paper, address labels, etc. may have to be revised (see Berke, 1999, p. 94; Knauer, 1998, pp. 516}517).

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), Kruger (1997, pp. 43}48), and Woodru! (1997, pp. 142}143). K In view of the distinction made here between CR, CL, and CS, the following point must be noted. The crosstabulations shown in Fig. 1 di!er from matrices in the previous literature that, at "rst glance, appear similar, but in which CR and CL or CL and CS are not analysed separately (see e.g. Herrmann & Johnson, 1999, p. 585; Homburg, Fa{nacht and 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).

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

Non-standard types of customers are the `advantage maximisersa and the `bad buyersa (see Fig. 1). Although these credit their network operator with providing a thoroughly `respectable technical servicea and have a positive attitude towards him, they nevertheless intend to terminate their business relationship with the operator. A literature review and anecdotal insights which we obtained over a 5-year period in consulting projects for cellular operators suggest that this low CR in spite of high CL can be explained by three complementary lines of argument: E In the German mobile communications market, it is common practice for customers to be sold mobile handsets at a low price when they conclude a contract with a provider. This terminal price 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

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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 revenues obtained 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 minimum contractual period has expired a substantial number of customers terminate their contract so that they can once again obtain a subsidised terminal (see Wilfert, 1999, p. 199). Accordingly, the strong desire of mobile communications customers to obtain a new terminal, irrespective of their loyalty to their network operator, can have a negative e!ect on CR. E Many residential customers only use mobile communications services for the xrst time after they have signed a network access contract. Because of their lack of experience with such services, it is possible that customers may overestimate the bene"ts they expect to obtain. Furthermore, the requirements of potential customers can change to the extent that the reasons that led to a contract in the "rst place no longer apply. In both cases, the reduced personal bene"ts that a mobile communications connection brings can lead customers to change their intention of continuing with the contract. This low CR level does not necessarily have to go hand in hand with a negative attitude towards the network operator; for the customers may recognise and acknowledge that the important reason for wanting to terminate the business relationship has nothing to do with their contractual partner. E The costs that customers have to pay for the use of mobile communications access are di$cult to estimate when a contract is being signed. This holds particularly for customers who have no experience of cellular services. For this reason, it could turn out that a customer has underestimated how much he/she will have to pay. Thus, there may be a large number of cellular customers who, as a result of having to pay more than their threshold value, intend to terminate the contractual relationship with their network operator to completely withdraw from the market ("low CR). Nevertheless, because of the similar prices charged by all the competitors in the German mobile communications market, these customers express complete loyalty to their current business partner ("high CL). To sum up, based on Fig. 1 and the preceding three paragraphs, we expect CR to be stronger in the German mobile communications market when E 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 ); E it is important for customers to retain their mobile access number over a long period (Hypothesis H ); E fewer customers wish to obtain a new mobile terminal (Hypothesis H ); E customers rate highly the bene"t they obtain from the services supplied by their own mobile communications provider (Hypothesis H ); E customers favourably rate the prices charged by their own mobile communications provider for the services supplied (Hypothesis H ). 3.2.2. Customer loyalty and its determinants In 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

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between CS and the loyalty that customers feel towards a "rm, but that a high degree of CL does not always have to go hand in hand with a high degree of CS. Here, it is usually assumed that CL and CR can be equated. However, it has just been shown that CS has only an indirect e!ect on CR via CL. It is therefore necessary to have separate discussions about typical ideal combinations of CL and the overall satisfaction of customers (see the bottom half of Fig. 1). Accordingly, there is the standard case of `disappointed customersa who are dissatis"ed with the services provided by their network operator, and who consequently make a negative assessment of this provider with regard to the future (see Fig. 1, standard case A). Similarly, we have a standard case of `impressed customersa who are very satis"ed with the performance of their network operator to date, and who therefore place great trust in him with regard to the future as well (see Fig. 1, standard case B). In addition, 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 services supplied to date, but who nevertheless trust that their provider will improve his performance in the future. 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 services they have received from their network operator, but who nevertheless expect, or assume, that it might be possible to obtain better services from his competitors. Our arguments derived from conceptual CR/CS studies can be condensed in the form of three hypotheses: E CS has positive e!ects on CL (Hypothesis H ). E CS does not determine CL completely. There is, indeed, a considerable number of customers who have a high (low) degree of CL while at the same time demonstrating a low (high) degree of CS (Hypothesis H ). E The more positive the image that customers have of their network operator's competitors, the weaker will be the CL to their current contractual partner (Hypothesis H ). 3.2.3. Customer satisfaction and its determinants Up 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 qualitative perception is in turn based on evaluative perceptions by the customer with regard to individual purchase-relevant features or value drivers which facilitate or block the achievement of servicerelated 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 customer value 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): E the network quality, which is re#ected in excellent indoor and outdoor coverage and in the clarity of voice reproduction without any connection break-downs; E the price paid for obtaining access to and using the network;

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).

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E the features summarised under the rubric of **customer care++, namely the quality of the exchange of information between customer and supplier (1) in response to customer (telephone) enquiries and (2) in the course of interactive activities initiated by the network operator (e.g., presentation of an invoice). Another point to be taken into account is that the overall satisfaction of customers with mobile communications services is also in#uenced by how far they perceive these services to be of bene"t to them personally. Even if a customer has a positive (negative) view of the services provided by his network operator, his overall satisfaction may still be adversely (favourably) a!ected by the fact that he rates the general value of the range of services to meet his needs * in other words, the idiosyncratic bene"t he obtains from them * as low (high). Overall, then, it is to be expected that CS 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 great interest is not just the mere existence of e!ects of di!erent variables on CR, CL, and CS, but rather the 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. We instructed this "rm to carry out a standardised telephone survey among customers of mobile network operators in Germany. The following groups of individuals were excluded from the survey: E 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 by their operator, since the VIAG network had only been launched three months before. E Customers of T-Mobil who are still using the analogue `C-Netza because `C-Netza only had a 2.5% share of the customer market in January 1999, and was due to be shut-down by the end of 2000. 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 to the market shares of the three established mobile operators in Germany phone numbers were drawn at random from all the "xed-network telephone numbers in Germany. If the interviewers found that one person in a household was a customer of a mobile network operator, the person concerned was asked there and then, or when contacted later, to participate in the survey. Those who agreed to do so were asked if they were able to o!set their mobile communications costs against 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 were then included in subsequent analyses.

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Following this procedure, a total of 684 residential customers were interviewed by phone. Of these, 41.1% were customers of Mannesmann, 39.9% of T-Mobil, and 19.0% of E-Plus. The respondents' 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 the interviewee exceeded DM 4000. The monthly mobile bill of the respondents was between DM 10 and DM 1000, with a mean value of DM 80.05 (S"66.81; n"639). For the German cellular market data on the socio-demographic structure of all the residential customers are not publicly available. However, we obtained such data from one mobile network operator. We were therefore able to analyse with regard to the four socio-demographic variables reported above, to what extent there were signi"cant deviations between the sub-sample of the customers of this operator included in our survey and the total population of all customers of this provider. Appropriate tests revealed no di!erences at the 10% level of statistical signi"cance. 4.2. Measurement of variables 4.2.1. Customer retention, customer loyalty, and customer satisfaction Following 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 [with the 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 all righta (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 network operator (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; Kruger, 1997; Peter, 1997). Therefore, the residential customers were asked to K what extent, on the basis of their experience, they would E reselect the same network operator or another provider (y ), E 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/recommend another network operatora (coded 1), to `undecideda (coded 3), to `de"nitely reselect/recommend the present network operatora (coded 5). As expected, both items were strongly correlated (r"0.74). Consequently, they were averaged on a single CL scale with item weights

In mid-January 1999 the distribution of all customers of the three German operators of mobile communications networks mentioned was as follows: Mannesmann 44.2%; T-Mobil (without `C-Netza) 40.8%; and E-Plus 15.0%. As a consequence, E-Plus customers are somewhat over-represented, and those of Mannesmann and T-Mobil somewhat underrepresented. A test revealed that network-operator shares in our sample and in the market as a whole di!er signi"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: G G y (x )"measurement variable z to capture the endogenous (exogenous) latent variable y (x ). G X G X G G

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Table 1 Distribution of answers for the variables customer retention, customer loyalty, and customer satisfaction Percentage frequency of answers for scale level (Low&&&&&&& & & & & &&&&&&& High) 1 2 3 4 5 8.9 4.3 1.8 3.7 8.6 4.5 11.3 12.4 18.2 16.3 51.2 47.5 59.8 23.5 28.0

Variables 1. Customer retention (y ) 2. Customer loyalty (y ) 3. Customer satisfaction (y )

M 4.14 3.95 3.95

S 1.28 0.99 0.90

n 674 652 682

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 the presentation of the distribution of `customer loyaltya answers. In all other statistical analyses, the exact, non-rounded customer loyalty scale scores were used. M"arithmetic mean value; S"standard deviation; n"number of valid answers received.

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 average residential 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 communications networka (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 respondents were slightly satis"ed, or not satis"ed at all, with their mobile communications network (scale levels of 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 earlier studies 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 expected three-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 with the assumption that the variables CR, CL, and CS represent overlapping but not identical constructs. 4.2.2. Other supply side determinants of the focal criteria The 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 current contractual partner of a customer were each measured by single item questions. Their wording and answer 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 operationalised with two items that are marked as indicators x and x in Table 2. An interviewee's perception

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).

T.J. Gerpott et al. / Telecommunications Policy 25 (2001) 249}269 Table 2 Measurement of supply side variables expected to in#uence the focal three criteria Variable name Phone number constancy Measurement

261

New terminal

Personal bene"ts

Assessment of prices

Image of competitors

Assessment of network quality

Assessment of customer care

`It is important for me to be able to keep my present mobile phone number once my contract with2has expired.a (x ) Five answer categories, for `completely righta ("5), to `partly righta ("3), to `not at all righta ("1) `It is important for me to obtain a new mobile phone at a very reasonable price once my contract with 2 comes to an end.a (x ) Five answer categories, as shown above for item x `What personal bene"t does the 2 network have for you?a (x ) Five answer categories, from `very substantial bene"ta ("5), to `medium bene"ta ("3), to `no bene"ta ("1) `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 to the "xed network?a (x ) Five answer categories, from `extremely gooda ("5), to `gooda ("3), to `bada ("1) `I will present a number of statements to you that may describe providers of mobile phone services. For each one, please indicate whether it applies particularly to 2[competitor of the interviewee's own provider].a Customer orientation (x ): Total of the statements marked as particularly applicable `is fair to his customersa, `is customer-friendlya, and `is nicea Reliability (x ): Total of the statements marked as particularly applicable `is seriousa, `is reliablea, and `provides securitya Modernity (x ): Total of the statements marked as particularly applicable `is technically up to datea, `is a modern "rma, and `is dynamica Sum of the three image elements x , x , and x to form an overall image score with higher values representing a better competitor image `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 `How do you assess the quality of the customer care services of the 2 network?a (x ) `How do you assess the e!orts of your network operator to keep you up to date? These e!orts include #yers sent with your bill, letters to customers, and brochures.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 nine potentially positive characteristics of operators of mobile communications networks. Respondents were then asked to indicate the extent to which these characteristics applied to a particular competitor. Factor analyses revealed that the image of the competitors comprised the three dimensions `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

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

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

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4.3. Analysis of causal links 4.3.1. Quantixcation and quality assessment of the postulated causal model The 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 number constancya, `new terminala, `personal (service) bene"ta, and `service pricesa. CL, in turn, is dependent on CS and the image of the competitors. Finally, CS is a function of the assessment of price, network quality, customer care, and the personal bene"t provided by the services of a mobile communications operator. 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 the empirical data: (1) a measurement model designed to capture the (indicator-based latent) variables addressed in the research's cause and e!ect hypotheses; (2) a structural equations model intended to re#ect the cause and e!ect relationships between the latent variables; and (3) an overall model consisting of the measurement model and the structural equations model. Therefore, the present study employed a con"rmatory causal analysis test of the system of causal relationships de"ned by hypotheses 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 valid parameter estimates, even if * as in our study * a normal distribution of the indicators cannot be assumed in the underlying population, and if the indicators have to be regarded as ordinal-scaled rather than interval-scaled (cf. Joreskog & Sorbom, 1996, p. 240). K K 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. Latent variables are indicated by ellipses and measurement variables by rectangles. The arrows pointing from the latent constructs to the measurement variables reveal the factor loading of the indicator on the construct. The arrows pointing `from outsidea to the indicators quantify the residual part for the relevant indicator that cannot be explained by the measurement model. The arrows/standardised path coe$cients between the two latent variables represent the causal relationship between the two constructs. Before the individual path coe$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 be checked (see Homburg & Baumgartner, 1995, pp. 162, 171}172). To be acceptable, an LISREL measurement 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 must be *0.5. Our measurement model meets requirement (a) for 15 of 16 indicators (the exception is variable 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 our measurement model can be said to be at least satisfactory, if not very good.

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.

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The quality of structural equation models is classi"ed as acceptable if the squared multiple correlation for each endogenous variable (to be explained) * in other words, for CR, CL, and CS in our model * is *0.4. In our sample, the squared determination coe$cients of the model shown in Fig. 2 are 0.78 for CR, 0.64 for CL, and 0.65 for CS. This means that our structural equation model exhibits 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 exceed a 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 are well below the highest recommended value or above the minimum suggested values. This means that 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 how much better would be an alternative model in which these two variables or the three indicators y , 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 RMSEA value 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 as well as our initial model. Therefore, it is both possible and necessary to retain the proposed separation of the constructs CL and CS. 4.3.2. Discussion of factors inyuencing CR, CL, and CS In 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 network operator is strongly in#uenced by the extent to which they have a positive perception of him * in other words by CL. At the same time, however, CL does not in any way fully explain the CR variance 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 the personal bene"t obtained from the services supplied by one's own mobile communications provider, 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 outstanding in#uence on CL to their network operator, the CS variable cannot by any means completely explain the CL variance. Consequently, it is reasonable to preserve the conceptual distinction between CL and CS as suggested by H . In our sample, a second signi"cant factor determining CL

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proved to be the image that the customer had of his network operator's competitors. The more positive 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 their own 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 CR was completely mediated by the CL variable. Furthermore, three of the four remaining hypotheses on determinants of CS could be maintained in our sample. As can be seen in Fig. 2, the perceived network 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 of 0.50. But the overall CR e!ect of a customer's assessment of mobile communication prices amounts to 0.44 (0.28#0.41;0.75;0.50) and is thus only slightly weaker. Following CS, perceived personal bene"t obtained from mobile communications services from one's own provider had the fourth-strongest impacts on CR with a total of 0.30 (0.20#0.25;0.75;0.50). The 47% di!erence in the e!ect produced by the factors `pricea and `personal bene"ta can be explained by the following consideration: Because of technological standardisation in digital mobile networks, it is di$cult for mobile operators to di!erentiate their services once a comprehensive regional coverage of their networks has been achieved. As a consequence, a customer's perception of the personal bene"t obtained from the services of his own network provider could not be attributed to the performance of the company concerned in particular, but to all providers in general. Therefore, in turn, the personal bene"t obtained from services supplied by the customer's own contractual partner 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 helps network operators to `motivatea customers to continue their contractual relationship even if they do not have a very positive attitude towards their mobile communications provider and/or are 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. Customers appear to consider quality to be a feature that `can be taken for granteda. Therefore, this variable does not have an outstanding e!ect on CR. Finally, the desire of a mobile communications customer to obtain a new terminal and perceived quality of an operator's customer care processes had practically no e!ect on the CR criterion. Customer care can therefore be taken to represent a peripheral service feature that is of little importance in shaping CR compared to the core 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 three constructs CR, CL, and CS, using a sample of 684 residential mobile communications customers in

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Germany. Overall, respondents scored relatively high on the three focal constructs. The results further indicate that it is conceptually justi"able, empirically tenable, and practically helpful for the contract business under consideration if CR is not equated with CL and/or CS. Instead, a twostage causal mechanism should be assumed in which CS drives CL which in turn has impacts on CR. To illustrate the need to distinguish between the three focal variables, respondents were divided along the median values of the three target constructs in the sample in cases with a low or a high value on a particular construct. Cross-tabulations of the CR}CL or the CL}CS answer combinations of the respondents revealed that 34 or 31% of the customers belong to the atypical cases 1 and 2 or A and B shown in Fig. 1. In other words, these individuals had opposite CR and CL 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 selectively a!ect the three target constructs. In our study, such parameters were the variables `phone number constancya, `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 act as 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 if they were to change to another provider. For operators of mobile communications networks with a large customer base, this "nding implies that they should organise professional political lobbying activities in every national market that help to reduce competitive pressures by perpetuating a regulation that does not enforce portability of phone numbers in current GSM networks and in the next generation of technology for mobile communications networks (UMTS/IMT-2000). In Germany such lobbying activities of mobile operators were recently unsuccessful since the German regulatory authority RegTP decided to enforce complete number portability between operators of mobile communications networks in February 2002. According to our "ndings this change is likely to increase considerably the intensity of competition in Germany at a stage of market development where the number of new "rst-time customers is declining and where acquisition of old customers from 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 the threat of migration by their existing customers. They should rather seek to improve their measurements 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 CR and which also act as a `levera to motivate customers to continue their contractual relationship with a provider. These are, "rst, the customer assessment that the prices charged by their supplier are `good and faira (compared against competitors), and, second, the customer perception of the functional bene"t of mobile communications services. The use of pricing policies to achieve positive CR e!ects is especially di$cult for operators of mobile communications networks because, up to now, competitors were very quick in neutralising temporary advantages in price level or price structure by introducing modi"ed pricing schemes of their own (see for details Wilfert, 1999, p. 197; Gerpott & Knufermann, 1998, pp. 144}147; Stoetzer & Tewes, 1996, p. 307). However, customerK speci"c discounts * somewhat similar to `bonus milesa in aviation * can be made dependent on the duration of a contract and on the amount that services are used. Operators of mobile networks

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who "rst succeed in creating the complex billing procedures for this type of pricing strategies and who manage to communicate these plans in a way that a!ects the mass market, will be able to strengthen the ties of their residential customers to their "rm because such strategies have hardly been 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 residential customer market in Germany ought to strive to become pioneers in service innovations that improve the core functionalities of mobile communications services (fast, simple, and trouble-free transfer of all types of information from any place at any time). More speci"cally, if, between 2001 and 2004, an operator of mobile communications networks in Germany is the "rst provider to introduce functioning fast(er) mobile data services and the next mobile network generation with broadband multimedia services onto the market he will have the opportunity to forge stronger ties with 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 only a few residential customers who terminate the contract with their network operator because they want to obtain a new terminal at a low price by switching to another provider once their contract comes to an end. Consequently, it may not be necessary for mobile operators to o!er their existing residential customers up-to-date models of terminals at a price that is below the initial cost of the device. Second, the quality of customer care * whether provided over the phone by call centre service agents, or by a continuous supply of written product or company information * has no signi"cant direct or indirect e!ect on CR. To wit, popular claims of consultants (for others, see Harter et al., 1997, pp. 160}162; Heidemann & Zynga, 1997, pp. 19}21) that, even in the case of standard telecommunications services for the mass market, customer care is a very important variable 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 of standard telecommunication services represents a `hygiene factora: If customer care is poor, it will contribute to dissatisfaction; but if it is good, it will not improve CS. Accordingly, mobile operators would be well advised to maintain the telco industry standard in customer care processes, but should not attempt to obtain a competitive strategic advantage by providing an extraordinary level of customer care.

6. Implications for future research Directions for future research on retention, loyalty, and satisfaction of cellular service buyers in particular and of buyers of service-like innovative contract goods in general follow from four major limitations of the present study. First, our analysis relies on cross-sectional data. Thus, to provide an even more convincing case for causal interpretations of variable correlations, additional longitudinal research is needed in which exogenous factors are captured before data on endogenous criteria are collected. Second, in the present study the focal constructs CR and CL were measured by questionnaire items asking for behavioural intentions and attitudes related to service o!erings of cellular operators. New research can help by expanding this measurement approach to include indicators of actual customer usage behaviours such as number of months passed since a customer

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"rst signed the contract with her cellular operator, customer air time minutes/revenues per year or number of times a customer recommended her operator to another person within a speci"ed period. 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 cellular service attributes and CS on the one hand and CL and CR on the other hand may be contingent on the past duration of the contractual relationship between a customer and his cellular service operator. As a consequence, additional studies are needed exploring CR and CL determinants in various residential customer sub-samples which di!er in terms of the duration of their previous relationship with a mobile operator. Fourth, the present investigation placed a deliberate focus on supply side mobile service attributes a!ecting CR, CL, and CS. Therefore, further research should include customer side variables re#ecting speci"c individual customer goals and motivations in using cellular services as well as general psychological constructs such as need for variety which past work discussed in the context of repeat purchase behaviours. Similarly, empirical research exploring 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 generalised beyond 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 and practitioners alike to contribute towards improved carrier pro"tability by expanding our understanding of antecedents and consequences of the duration of an operator's contractual relationship with his mass market customers.

References

Berke, J. (1999). Oligopol sprengen: Mehr Wettbewerb im Mobilfunk. Wirtschaftswoche, 53(41), 94. Bliemel, F. W., & Eggert, A. (1998). Kundenbindung * die neue Sollstrategie? Marketing, 20, 37}46. Bolton, R. N. (1998). A dynamic model of the duration of the customer's relationship with a continuous service provider: The role of satisfaction. Marketing Science, 17, 45}65. Booz Allen, & Hamilton (1995). Mobilfunk. Frankfurt/M.: IMK. Bruhn, M., & Homburg, C. (Eds.). (1998). Handbuch Kundenbindungsmanagement. Wiesbaden: Gabler. Danaher, P. J., & Rust, R. T. (1996). Indirect "nancial bene"ts from service quality. Quality Management Journal, 3(2), 63}75. Dick, A. S., & Basu, K. (1994). Customer loyalty: Toward an integrated conceptual framework. Journal of the Academy of Marketing Science, 22, 99}113. Diller, H. (1996). Kundenbindung als Marketingziel. Marketing, 18, 81}94. Gerpott, T. J. (1998). Wettbewerbsstrategien im Telekommunikationsmarkt (3rd ed.). Stuttgart: Scha!er-Poeschel. K Gerpott, T. J. (1999). Strukturwandel des deutschen Telekommunikationsmarktes. In D. Fink, & A. Wilfert (Eds.), Handbuch Telekommunikation und Wirtschaft (pp. 49}75). Munchen: Vahlen. K Gerpott, T. J. (2000). Kundenbindung * Konzepteinordnung und Bestandsaufnahme der neueren empirischen Forschung. Die Unternehmung, 54, 23}42. Gerpott, T. J., & Knufermann, M. (1998). Mobilfunk * Entwicklung des liberalisierten deutschen Markts. BetriebswirtK schaftliche Blatter, 47, 140}150. ( Grund, M. A. (1998). Interaktionsbeziehungen im Dienstleistungsmarketing. Wiesbaden: Gabler. Harter, G., Ripsam, T., & Ruhl, M. (1997). Customer care * Kundenbindung zum Nulltarif. In Booz. Allen, & Hamilton (Eds.), Telekommunikation in der Welt von morgen (pp. 151}166). Frankfurt/M.: IMK.

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

269

Heidemann, D., & Zynga, A. M. (1997). Wettbewerbsvorteile im Telekommunikationsmarkt durch `World-Class Customer Carea. Telekom Praxis, 74(2), 18}22. Herrmann, A., & Johnson, M. D. (1999). Die Kundenzufriedenheit als Bestimmungsgro{e der Kundenbindung. K Schmalenbachs Zeitschrift fur betriebswirtschaftliche Forschung, 51, 579}598. ( Homburg, C., & Baumgartner, H. (1995). Beurteilung von Kausalmodellen. Marketing, 17, 162}176. Homburg, C., & Bruhn, M. (1998). Kundenbindungsmanagement * Eine Einfuhrung in die theoretischen and praktiK schen Problemstellungen. In M. Bruhn, & C. Homburg (Eds.), Handbuch Kundenbindungsmanagement (pp. 3}35). Wiesbaden: Gabler. Homburg, C., Fa{nacht, M., & Werner, H. (1998). Operationalisierung von Kundenbindung and Kundenzufriedenheit. In M. Bruhn, & C. Homburg (Eds.), Handbuch Kundenbindungsmanagement (pp. 389}410). Wiesbaden: Gabler. Homburg, C., Giering, A., & Hentschel, F. (1999). Der Zusammenhang zwischen Kundenzufriedenheit and Kundenbindung. Die Betriebswirtschaft, 59, 174}195. Homburg, C., & Hildebrandt, L. (1998). Die Kausalanalyse. In L. Hildebrandt, & C. Homburg (Eds.), Die Kausalanalyse (pp. 16}43). Stuttgart: Scha!er-Poeschel. K Homburg, C., & Rudolph, B. (1997). Theoretische Perspektiven zur Kundenzufriedenheit. In H. Simon, & C. Homburg (Eds.), Kundenzufriedenheit (2nd ed.) (pp. 31}54). Wiesbaden: Gabler. Jeschke, K. (1995). Nachkaufmarketing. Frankfurt/M: Lang. Joho, C. (1996). Ein Ansatz zum Kundenbindungsmanagement fur Versicherer. Bern: Haupt. ( Joreskog, K. G., & Sorbom, D. (1996). Lisrel 8: User's reference guide. Chicago: SSI. K K Keaveney, S. M. (1995). Customer switching behavior in service industries. Journal of Marketing, 59(2), 71}82. Knauer, M. (1998). Kundenbindung in der Telekommunikation: Das Beispiel T-Mobil. In M. Bruhn, & C. Homburg (Eds.), Handbuch Kundenbindungsmanagement (pp. 507}522). Wiesbaden: Gabler. Kruger, S. M. (1997). Proxtabilitatsorientierte Kundenbindung durch Zufriedenheitsmanagement. Munchen: FGM. K ( K Laker, M., Pohl, A., & Dahlho!, D. (1999). Neue Markte: Kunden gewonnen * Was kommt dann? In H. H. K Hinterhuber, & K. Matzler (Eds.), Kundenorientierte Unternehmensfuhrung (pp. 85}97). Wiesbaden: Gabler. ( Me!ert, H. (1998). Kundenbindung als Element moderner Wettbewerbsstrategien. In M. Bruhn, & C. Homburg (Eds.), Handbuch Kundenbindungsmanagement (pp. 115}133). Wiesbaden: Gabler. Mellewigt, T. (1997). Kommentar zu A 43 TKG. In W. Buchner, J. Ehmer, M. Geppert, B. Kerkho!, H.-J. Piepenbrock, K R. Schutz, & F. Schuster, (Eds.), Beck'scher TKG-Kommentar (pp. 556}578). Munchen: Beck. K K Oevermann, D. (1996). Kundenbindungsmanagement von Kreditinstituten. Munchen: FGM. K Peter, S. I. (1997). Kundenbindung als Marketingziel. Wiesbaden: Gabler. Rust, R. T., & Zahorik, A. J. (1993). Customer satisfaction, customer retention, and market share. Journal of Retailing, 69, 193}215. Schwarz-Schilling, C., & Stumpf, U. (1999). Netzbetreiberportabilitat im Mobilfunkmarkt (Report of the WIK for RegTP, ( hectograph manuscript, VI#68pp.). Simon, H., & Homburg, C. (Eds.). (1997). Kundenzufriedenheit (2nd ed.). Wiesbaden: Gabler. Stoetzer, M.-W., & Tewes, D. (1996). Competition in the German cellular market? Telecommunications Policy, 20, 303}310. Szyperski, N., & Loebbecke, C. (1999). Telekommunikationsmanagement (TKM) als betriebswirtschaftliche Spezialdisziplin. Die Betriebswirtschaft, 59, 481}495. Weinberg, P. (1998). Verhaltenswissenschaftliche Aspekte der Kundenbindung. In M. Bruhn, & C. Homburg (Eds.), Handbuch Kundenbindungsmanagement (pp. 39}53). Wiesbaden: Gabler. Wilfert, A. (1999). Der Wettbewerb auf dem Mobilfunkmarkt in Deutschland. In D. Fink, & A. Wilfert (Eds.), Handbuch Telekommunikation und Wirtschaft (pp. 187}202). Munchen: Vahlen. K Woodru!, R. B. (1997). Customer value: The next source for competitive advantage. Journal of the Academy of Marketing Science, 25, 139}153.

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