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The effects of the trustworthiness of an online shop on the goals of the ecrm:

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1 The effects of the trustworthiness of an online shop on the goals of the ecrm: with special consideration of the transactional and relational customer value. INAUGURAL DISSERTATION to obtain the title of Doctor rerum oeconomicarum of the Faculty of Economics and Social Sciences of the University of Bern presented by ROGER SEILER from Basel-Stadt 2013 Original document saved on the web server of the University Library of Bern This work is under a Creative Commons attribution-No commercial use-No processing 2.5 Switzerland license agreement licensed. To view the license, please go to or send a letter to Creative Commons, 171 Second Street, Suite 300, San Francisco, California 94105, USA.

2 Copyright notice This document is licensed under a Creative Commons Attribution-Noncommercial-NoDerivs 2.5 Switzerland license. You may: reproduce, distribute and make publicly available this work. Subject to the following conditions: Attribution. You must state the name of the author / rights holder in the manner specified by him (which, however, must not give the impression that you or your use of the work are rewarded). No commercial use. This work may not be used for commercial purposes. No editing. This work may not be edited or changed in any other way. In the event of distribution, you must inform others of the license conditions under which this work falls. Any of the aforementioned conditions can be waived if you receive the consent of the rights holder. This license does not affect moral rights under Swiss law. A detailed version of the license agreement can be found under ii

3 The Faculty of Business and Economics at the University of Bern published this work on at the request of the reviewer Prof. Dr. T. Myrach and Prof. Dipl.-Ing. Dr. H. Schauer accepted as a dissertation without commenting on the views expressed in it. Bern, the date of the doctoral degree iii

4 Dedication to My Parents. iv

5 Acknowledgments to Prof. Dr. I thank T. Myrach for the support and for the suggestions on theoretical and methodological aspects of the work. Prof. Dipl.-Ing. Dr. I thank H. Schauer for taking over the submission. I thank Mr. J. Ebert for his advice on the empirical part. My heartfelt thanks go to Angela. I would also like to thank all test persons whose cooperation made the empirical part of the work possible. Bern, v

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7 Contents 1 Introduction Introduction Structure of the thesis Question Research contribution of this thesis Theoretical frame of reference CRM / eCRM Customer loyalty Customer satisfaction Customer value Conclusion Customer loyalty and customer value Methods for measuring customer value ABC analysis Customer Lifetime Value Customer contribution calculation (KDBR) Customer portfolio RFM method (Scoring method) Delimitation CRM / eCRM levels of CRM Conclusion Definition of areas of responsibility of CRM / eCRM Objectives CRM / eCRM Classification of goods typology New institutional economics Introduction Basic assumptions Property rights theory Transaction cost theory Principal agent theory Trust Introduction Trust objects Types of trust Generalized trust vii

8 Table of contents Specific trust System trust vs. personal trust Swift and initial trust Economics Sociology Psychology Differentiation of trust and hope Demarcation of trustworthiness phases of trust Conclusion Technology Acceptance Model (TAM) TRA TPB TAM Risk of right of return Contract revocation of general terms and conditions (GTC) of right of return Swiss mail order company Analysis of return modalities Conclusion Right of return Company forms Empirical research status Data mining Data warehousing Web mining Classification Hypotheses Trustworthiness measures Website properties Trust disposition Objectives electronic Customer Relationship Management (ecrm) Customer satisfaction Customer value Relational customer value Transactional customer value Customer acquisition Method Research design Design of this work Design theory viii

9 Table of contents Survey design experiment Structural Equation Modeling (SEM) Formative and reflective specification of latent variables Variance and covariance analysis approach PLS approach Selection of the approach Selection of the software Modeling path models Procedure for model development Quality criteria of covariance-based analyzes Quality criteria of variance-based analyzes Overview of the quality criteria used Operationalization Constructs procedure Items Measurement models of the latent constructs Operationalization Structural equation model Infrastructure Objectives Implementation Procedure of the experiment Differentiation Survey design Components Invitation test person information Soft online shops Survey software Data processing tool Server Trustworthiness measures Best seller (gold / silver / bronze) User ratings Stars / text PCtipp Stiftung Warentest GTC SSL encryption Payment method Data protection References ix

10 Table of contents About us Company form Operationalized return policy Conclusion Trustworthiness measures Call center modifications CMS rating PCtipp Return policy Stiftung Warentest SSL and payment methods Added content Cross / up-sell proposal Modifications Survey software Identification of missing answers Integration modifications Carrying out a pre-test General examination Test subjects (response) Composition Sample results Manipulation check Comparison of manifestations of the manipulations Sample parallelization (precondition comparison) Average value comparisons Shop A / Shop B Factor analysis Mediation analysis Structural equation model Review of the model Reflective constructs Indicator reliabilities Factor reliabilities Formative constructs VIF Discriminant validity Determination measure Predictive relevance Framework conditions x Conclusion

11 Table of contents Main model Model variants Trustworthiness measures Website properties Trust disposition Customer satisfaction Customer value Customer acquisition Final part Interpretation of the results Theory implications Practice implications Outlook Summary List of figures 163 List of tables 167 List of abbreviations 169 Bibliography 171 A Glossary 201 B Questionnaire 207 C Declaration of independence 213 1

12 Table of Contents 2

13 1 Introduction "We have been discussing economic models in which trust is important." [Akerlof 1970, p. 500] The introduction of the present work contains an introduction to the topic, gives an overview of the structure of the work, illuminates the question and the research contribution of this work. 1.1 Introduction The number of studies dealing with the topic of trust has risen since the mid-1990s from less than twenty articles per year to 109 articles in 2003. Since then, the publications have remained well above the level of 1994 (cf. Ebert [2007, p. 3ff.]). Ebert [ibid., P. 4] attributes this to the international orientation of companies, which was recorded by Rugman and Collinson [2006, p. 33]. The resulting competitive pressure moved companies to joint ventures and cooperations [Ebert 2007, p. 4]. He also cites e-commerce as the reason for the increase in publications. Ebert postulates an increase in the probability that customers will change companies in e-commerce because e.g. Price information is more easily available. Therefore, the topic of customer loyalty, which can curb such a change, is also becoming more topical. This task can be assigned to Customer Relationship Management (CRM) or the ecrm. It is therefore not surprising that technology-based customer care (CRM and ecrm) is receiving widespread attention, because its use can lower costs and better bond profitable customers to the company. Hannich [2009] examined the uses and trends of CRM in Swiss companies. 332 decision-makers from Swiss SMEs across all sectors were surveyed [ibid., P. 7]. He notes that customer value has emerged as a constant topic in the last three years [ibid., P. 4]. Furthermore, the emotionalization of CRM as a trend, which achieved 60.7% approval among the respondents, is dominant [ibid., P. 5]. 85.1% of the companies surveyed set themselves the goal of wanting to build trust [ibid., P. 5]. The widespread use of this goal can be seen as an indicator of the practical relevance as well as the topicality of this topic with regard to the question of the present work. 3

14 1 Introduction Another perspective for this study is the turnover. Online orders are the trend. In the Swiss mail order business, sales generated online rose by 17% in 2008 [Kessler and Hochreutener 2009, p. 1]. In Switzerland, CHF 4.65 billion of goods were sold online [ibid., P. 1]. The sales generated in the B2C sector have not only increased, but in 2009 they even exceeded offline sales in the mail order business for the German market [BVH 2010, p. 14]. Current forecasts for the B2B sector indicate that this situation will also occur in Switzerland [Kessler and Hochreutener 2009, p. 2]. According to the study by the Swiss Mail Order Association (VSV), 41% of orders in the B2C area are processed online [ibid., P. 1]. In the B2C sector in Switzerland, there is still a 9% shortfall so that online sales in mail order business exceed those in offline trading. 1.2 Structure of the thesis The main part of this thesis consists of a theoretical and an empirical part. The theoretical part particularly introduces the definitions and basics (customer value, customer loyalty and customer satisfaction). The concept of trust is distinguished from this. In addition, economic theories that provide an explanation for the topic of trust in the ecrm are presented. On the basis of this basis, the hypotheses of this work are derived and then the method used is explained. The empirical part discusses the quantitative results of an experiment on the trustworthiness of an online shop and its effects on customer loyalty, customer value and customer satisfaction. The interpretation of the results, theoretical and practical implications, an outlook and the summary of the work are in the final part of this work. Figure 1.1: Structure of this dissertation 4

15 1.3 Issue 1.3 Issue This thesis examines the effects that the trustworthiness of an online shop can have on selected goals of the ecrm. The focus is specifically on customer loyalty and customer value, which are seen as central goals of the ecrm. In order to be able to study these effects, trust-building strategies in online shops are necessary. The question focuses on the business-to-customer (B2C) online shopping area in the Swiss online shopping market. 1.4 Research contribution of this thesis This thesis makes an empirical contribution to the analysis of the effects of the trustworthiness of an online shop on customer loyalty, customer value and customer satisfaction. The investigation is carried out by means of an experiment in order to present test persons with a realistic shopping environment and to examine their behavior (intentions) as well as the actual behavior of test persons. Strategies are used to increase the trustworthiness of an online shop, which make use of the technical possibilities of an online shop to reduce information asymmetries and uncertainties on the part of the buyer. 5

16 1 Introduction 6

17 2 Theoretical frame of reference In this chapter the theoretical frame of reference is defined and relevant terms are explained in more detail. The terms customer loyalty, customer value, CRM and ecrm are examined in more detail below. Furthermore, methods for measuring customer values ​​are presented. The tasks and goals of CRM and ecrm are also examined in more detail. Finally, this work is classified, taking into account the terms introduced. 2.1 CRM / eCRM customer loyalty Bruhn and Homburg [2008, p. 8] define customer loyalty based on Diller [1996] and Meyer and Oevermann [1995] as follows: also to positively shape the actual behavior of a customer towards a provider or his services in order to stabilize or expand the relationship with this customer for the future. According to Meffert [1999, p. 251], this definition corresponds to the management-related view of customer loyalty. The purchasing behavior-related perspective focuses on customer behavior and, according to Diller [1996, p. 83], can include willingness to buy again. Bruhn [2007] divides the construct of customer loyalty into two dimensions. One dimension includes the behavioral intentions of customers and includes repurchase, cross-buying, recommendation and acceptance of price increases. The factual behavior represents the second dimension and, in contrast to the behavioral intention, comprises the actual behavior of the customers. The dimensions are congruent except for the distinction between the intention and the actual behavior. Trust affects the intention to buy again, recommend to others and buy additional items [Kirchgeorg and Lorbeer 2006] and lead to more loyal customers [Bauer et al. 2006]. Trust influences both dimensions and their aspects and therefore plays a role in binding customers to a company. When using customer loyalty strategies, however, care must be taken that they do not undermine customer trust, otherwise the effectiveness of this strategy through the negative impact on trust and the associated negative 7

18 2 Theoretical frame of reference Figure 2.1: Conceptualization of customer loyalty based on Bruhn [2007, p. 112] Effects on customer loyalty is reduced. Bliemel and Eggert [1998] cite two basic customer loyalty strategies and differentiate between loyalty and loyalty strategies [cf. ibid., p. 44]. The customer cannot change when they are connected and they do not want to change when they are connected. 1. A relationship strategy can, for example, be implemented through first-class customer service, which is intended to ensure satisfied customers. As a result, customers buy again from this company out of satisfaction. The bond can therefore represent barriers to change via lock-in effects, which prevent the customer from switching to competitors. According to Bliemel and Eggert [ibid., P. 40], the bond is made up of the customer's attitude to satisfaction and trust. The authors see the connected strategy as a more advantageous strategy in highly competitive markets. The strategy of bondage is unsuitable with regard to customer loyalty by means of trust, since the latter has a voluntary character (cf. Ripperger [1998, p. 46]; Picot et al. [2001, p. 125]; Kirchgeorg and Lorbeer [2006, p. 440] ). Furthermore, the loyalty strategy is risky, since in the initial phase of the customer relationship the trustworthiness of the homepage first builds trust and the next competitor only needs a mouse click (cf. [Hof et al. 1998]) 1 For a detailed comparison [cf. Bliemel and Eggert 1998, p. 44], [Eggert 2000, p. 119] or more generally [cf. Kotler and Bliemel 2001, p. 85]. 8th

19 2.1 CRM / eCRM is removed. If the new customer recognizes the loyalty strategy, there is a risk that he will choose another provider. On the other hand, positive references from existing customers are an element of the trust strategy in this work. Because the loyalty strategy binds customers to the company by means of lock-in effects, there is a possibility that they will be dissatisfied but still not be able to change. This situation could lead to negative customer references, which would torpedo the chosen trust strategy. For these reasons, the loyalty strategy is preferred to the loyalty strategy in this thesis and the measures of customer loyalty through trust are assigned to the loyalty strategy. The complete conceptualization that is used in the experiment can be seen in Figure 2.1. Because the experiment concentrates on the initial phase of the relationship and no longitudinal investigation is carried out, the intention to repurchase had to be used with regard to repurchase and price increase acceptance. Customer satisfaction Homburg and Koschate [2007, p. 846] define customer satisfaction as the result of psychological comparison processes. Homburg and Stock [2003, p. 19] refer to the importance of customer satisfaction when it comes to analyzing customer behavior. For an overview of the operational procedure in a company, reference is made to Homburg and Werner [1997, p. 56 ff.], Who explain the use of a customer satisfaction index. They explicitly point out that one of the deficits in companies is the equation of customer satisfaction and customer loyalty [ibid., P. 17]. This deficit is reduced in the present study by considering customer satisfaction and customer loyalty (in this study the term customer value will be used later) 2 as separate constructs. Homburg and Stock [2003, p. 24] provide an overview of various concepts that are associated with customer satisfaction. They highlight the C / D paradigm, which is widespread and states that customer satisfaction results from an actual / target comparison of the perceived performance.According to this paradigm, satisfied customers arise when the perceived performance corresponds to their expectations. If expectations are not met, customers are correspondingly dissatisfied. The authors place the theories on customer satisfaction in the C / D paradima 3 for an overview of the effect relationships. This provides the conceptual framework, but the operationalization must take place via a measurement. Therefore, these measurement methods are examined more closely. A graphical overview 2 See section See Churchill and Surprenant [1982] for the determinants of customer satisfaction according to this principle. 9

20 2 Theoretical frame of reference can be found in Figure 2.2. Figure 2.2: Overview of measurement methods for customer satisfaction. Beutin [2003, p. 118] differentiates between objective and subjective measurement methods. The former measure e.g. monetary parameters such as market share and have the advantage that they are not influenced by subjective perception. A further distinction can be made between feature-based and event-based methods [Bauer et al. 2000, p. 26]. The quality of a service can be measured with the feature-based method of the SERVQUAL 4 approach from Parasuraman et al. [1988] can be measured. The SERVQUAL approach compares the expected performance with the perceived performance and is therefore based on the C / D paradigm. The dimensions of environment, reliability, responsiveness, performance competence and empathy are taken into account in the SERVQUAL approach. Criticisms of this approach are that the model cannot be used across industries, its very static character and the difficulty of using it when several services are used, as happens in department stores, for example [Bauer et al. 2000, p. 27 ff.]. Event-related approaches focus on a specific event. One method of this approach is the Critical Incident Technique [ibid., P. 28]. With this approach, a specific event (e.g. a customer complaint) is analyzed in more detail. The problem with this approach is that customers tend to remember positive or negative examples [ibid., P. 29]. The authors Bauer et al. [ibid., p. 33] therefore focus their attention on the transaction process and the current satisfaction with a process. Furthermore, Beutin [2003, p. 120] differentiates between implicit and explicit 4 combinations of the terms service and quality. 10

21 2.1 CRM / eCRM process. The first rely on the customer's complaint behavior. As a result, the company assumes satisfied customers if no customer complaints are noticed [ibid., P. 120 f.]. The explicit methods record customer satisfaction directly [ibid., P. 122]. A further distinction can be made between one-dimensional and multi-dimensional processes [ibid., P. 122]. The question of calculation arises for the multidimensional indices. Arzenheimer and Hippner [2000, p. 226 ff.] Subdivide the indices according to three mathematical operators. The additive indices add the features together [ibid., P. 226], with the weighted indices the features can have different effects on the index [ibid., P. 227] and with the multiplicative indices the features are multiplied together [ibid., P. 227]. , P. 227]. The point in time provides a further possibility of classification and leads to the ex ante and ex post procedures [Beutin 2003, p. 123]. The effects of customer satisfaction work on the concepts of customer loyalty and customer value. According to Homburg and Koschate [2007, p. 845] and Huber et al. [2008, p. 71] satisfied customers make more use of the company's services and increasingly respond to cross-selling. Homburg and Koschate [2007, p. 845] also observe increased word-of-mouth advertising. It therefore makes sense to include a customer satisfaction construct in this study. After a detailed analysis of the literature, DeLone and McLean [1992] set up a model which postulates an effect between user satisfaction and the use of a system [ibid., P. 87]. The effect can be based on user satisfaction on usage or it can also occur in the opposite direction [ibid., P. 83]. An analysis of the research on their model over a period of 10 years comes to the conclusion that the postulated model should be retained [DeLone and McLean 2003, p. 23]. They only add the dimension of service quality to the original model and replace individual and organizational effects with a net benefit construct [ibid., P. 24]. They explicitly emphasize the relevance of their model in connection with e-commerce [ibid., P. 17]. Such a mode of operation makes it possible to consider the use of a system as a proxy variable 5 for customer satisfaction. The use of a system can be viewed as representative of satisfaction. Krafft and Götz [2007, p. 337] come to the conclusion that customer satisfaction is to be assessed as a relatively unexplored area. They also emphasize that so far no method for operationalizing and measuring customer satisfaction has become established in science. Therefore, the question arises of how customer satisfaction should be operationalized. This investigation focuses on new customers in the initial phase of the 5. A proxy variable is understood to be a variable that can serve as a proxy for another to measure it. 11

22 2 Theoretical frame of reference for customer relationships. Because the survey takes place immediately after the experiment, a comprehensive construct seems unsuitable, as the customers have not yet received the product and therefore have no direct experience with the product in the online shop. Therefore, the approach of the authors around Bauer [2000, p. 33] is used and customer satisfaction is considered based on the purchase process. In order to avoid a one-dimensional construct, customer satisfaction is conceptualized on the basis of the dimensions of satisfaction with the purchase and satisfaction with the ordering process. Customer value The customer value is (...) the measure of the overall economic importance of a customer for the company [Rudolf-Sipötz 2001 , P. 4]. It is important to note that customer value is not an absolute figure [ibid., P. 22]. Günter and Helm [2006] refer to Cornelsen [2000, p. 38], who, in his comprehensive analysis, lists both monetary and non-monetary contributions. Model 6 by Cornelsen [ibid., P. 199] explicitly takes into account the reference value which is used in this work for customer acquisition and which can play an essential role in terms of trust. The terms customer value, customer value (CV), customer net benefit (KNN), customer lifetime value (CLV) and customer equity (CE) require explanation because language barriers and synonymous usage could cause confusion. In the English-language literature, customer value is referred to as customer value. There is basically a provider and a customer perspective on this term (cf. Günter and Helm [2006, p. 7]; Krafft [2007, p. 44]). The perspective from the customer's point of view corresponds, for example, to the preference of a certain product because it brings the customer a specific benefit. Kumar and Reinartz [2006], Eggert [2000], Woodruff [1997] or Zeithaml [1988]. In German-speaking countries, the term customer net benefit is associated with customer value. This term is often used as a synonym for the CV Vogel [2006, p. 13] and also takes the customer's perspective. According to Kotler and Bliemel [2001, p. 58], the customer benefit is even used for the purchase decision and leads to the fact that the customer tends to buy with the highest value gain. This gain in value is formed from the difference between the sum of benefits and the sum of expenses [ibid., P. 58] 8. The supplier perspective, which calls the value of the customer from a company 6 REVAL [Cornelsen 2006, p. 196] 7 Holbrook [1999, p. 7 ff.] Uses the term consumer value, which refers more clearly to the perspective of the end customer. 8 Eggert [2006, p. 48] refers to Cornelsen [2000, p. 294], who combines the concepts of customer net benefit and customer value by arguing that a high customer value increases the average purchase quantity and thus also the customer's turnover. 12th

23 2.1 CRM / eCRM considered, is used in particular by Wittkötter and Steffen [2002, p. 74]. The authors believe that the customer value from the customer's point of view, understood as the difference between the perceived costs and the perceived benefit, cannot be a sensible starting point for CRM. You admit that it is necessary, but should rather be seen as a secondary condition (...) of CRM. Rather, they emphasize that customer value is not only determined by monetary factors alone, but that non-monetary determinants are also relevant and therefore use the company perspective of customer value as a starting point for CRM. Figure 2.3: Conceptualization of customer value based on Tomczak and Rudolf-Sipötz [2006, p. 132] The customer value from the provider perspective can be divided into a direct and indirect dimension (cf. Neckel and Knobloch [2005, p. 189ff.]; Cornelsen [2006]). The authors Neckel and Knobloch [2005] cite the recommendation, information and cooperation potential for indirect contributions and refer to the tolerance to price increases and larger quantities of goods as direct contributions to customer value. Both the direct and the indirect contributions to customer value are taken into account in this work by 13

24 2 Theoretical frame of reference, the price increase tolerance as well as up- and cross-selling are examined in the experiment. Figure 2.4: Conceptualization of customer value based on Hippner [2006, p. 27] The CLV and the CE are viewed from the provider perspective. Neckel and Knobloch [2005, p. 17] believe that the CLV tries to show future development potential. CE was introduced according to Krafft [2007, p. 17] by Blattberg and Deighton [1996]. CE represents the aggregation of the discounted CLVs for current and future customers (cf. [Bauer et al. 2003, p. 49]; Rust et al. [2004, p. 110];). The authors Berger and Nasr [1998, p. 27] additionally differentiate CE from CLV by taking the acquisition costs into account in the CE calculation. The CE perspective is a more abstract and aggregated view compared to the CLV perspective, which is focused in detail on individual customers (see section). Krafft [2007, p. 44] explains that CE is used to describe the economic value of customers, segments or business relationships. It is clear from the explanation that this must be the supplier perspective of customer value. Tomczak and Rudolf-Sipötz [2006, p. 132] convert this provider perspective into a market and resource potential 14

25 2.1 CRM / eCRM subdivided (see Figure 2.3). A subdivision that differentiates between non-monetary and monetary determinants of customer value comes from Hippner [2006]. He speaks of the relationship and transaction potential (see Figure 2.4) of customer value [ibid., P. 27]. Because this work also contains non-monetary components that can be assigned to the relational potential, the above-mentioned, more precise division of [ibid.] Was chosen. A recommendation of a product by a customer can be cited as an example. This recommendation clearly represents a non-monetary parameter for the company. Conclusion: customer loyalty and customer value The concept of customer loyalty and that of customer value are of central importance for the present work and should be compared. If one compares the two concepts, then a similarity can be noted, because both concepts focus on the customer. Nevertheless, one could differentiate and split the customer relationship in two with regard to the actors. On the one hand there is the company and on the other its customers. If you take these two actors as a starting point for a closer look, you can come to the conclusion that customer value is to be classified on the customer side. This classification would also be consistent with the theoretical conceptualizations, since customer value is about the economic importance [Rudolf-Sipötz 2001] of monetary and non-monetary values ​​[Günter and Helm 2006] of the customer. A division of the customer value into a transaction and a relation potential [Hippner 2006] focuses on the behavior of customers. Likewise, one could justify the classification using the concept of the provider perspective, which e.g. von Wittkötter and Steffen [2002], because the company looks at its customers and thus implies that the customer value is to be found in the customer and not in the company. Although customer value is of great importance to the company, the starting point of customer value remains with the customer. Customer loyalty could be classified with regard to the division according to actors on the company side, because according to the definition by Bruhn and Homburg [2008], this concept includes all measures that are used by the company to bind customers to them. Bliemel and Eggert [1998] speak of customer loyalty strategies and differentiate between loyalty and loyalty strategies. Both strategies represent approaches that aim at the loyalty of customers to the company. The strategies are based on the actor in the company and have an impact on the customers, who can generate value for the company. The argumentation just given shows that the concept of customer loyalty can be assigned to the side of the company, 15

26 2 Theoretical frame of reference while that of customer value can be attributed to the customer side. Ultimately, both concepts aim at similar, in numerous conceptualizations even congruent behavior or intentions of customers, which represent an economic contribution to the company. In the present work these economic contributions are to be examined in more detail and therefore it makes sense to search on the customer side. Consequently, in operationalization (see Section 4.2), the construct of customer value is used and measured in order to analyze the effect of trust measures.Methods for measuring customer value The following section presents methods for measuring customer value ABC analysis The ABC analysis is used often defined on the basis of annual sales. It is easy to use and easy to create because the data for this can be taken from the accounting department (cf. Köhler [2003, p. 397]; Krafft and Rutsatz [2006, p. 278]; Krafft [2007, p. 77] ). In this process, customer sales are compared to customer shares and customers are divided into categories [Krafft and Rutsatz 2006, p. 279]. The conclusion is that a few high-turnover customers are to be regarded as more valuable than those who make up a large proportion of the customer base but generate little turnover. As a rule of thumb, A customers justify more intensive support [Köhler 2003, p. 398]. The process is particularly widespread in the capital goods industry (cf. Krafft and Rutsatz [2006, p. 279]). As an improvement, Krafft and Rutsatz [ibid., P. 279] and Krafft [2007, p. 78] propose to carry out the ABC analysis based on the customer contribution. This goes back to the suggestion of Mulhern [1999]. Krafft [2007, p. 78] is of the opinion that the sales-based ABC analysis represents a segmentation approach that should be supplemented by others. The ABC analysis is clearly a monetary approach (applies to customer classification according to sales and contribution margins) and therefore does not take into account potential, such as the reference potential. In addition, the ABC analysis is based on annual sales and is therefore only suitable to a limited extent for evaluating new customers. A new customer with little turnover can very well be satisfied with the purchase in the online shop and be interesting for the company through a recommendation, as this recommendation could result in the purchase of an additional customer. Therefore, this recommendation represents a value for the company, which is not captured by the monetary approach of the ABC approach. Because this and other aspects of customer value are not captured by the ABC analysis, this is 16

27 2.1 CRM / eCRM unsuitable for customer segmentation in this thesis. The CLV method, on the other hand, offers the possibility of taking the reference potential into account and therefore illuminates this blind spot of the ABC analysis Customer Lifetime Value The CLV concept is often viewed as a monetary view of the customer and is used by Bauer et al. [2003, p. 49] defined as a supplier-oriented point of view as the customer's economic value to the company. With the CLV, the expected cash flows of a customer are generally totaled and then the fair value of these payment flows is calculated [Berger and Nasr 1998, p. 18 ff.]. The CLV approach covers the entire life cycle of the customer relationship. By discounting the cash flows, the CLV method has features of the concept of the net present value method (NPV) from the dynamic investment calculation (cf. Thommen [2002, p. 864 ff.]), Which calculates the time value of accumulated future pensions by adding them discounted at a discount rate 9. Jackson [1989] 10 differentiates between two types of industrial customers, lost-for-good and always-a-share customers. This distinction is adopted by Dwyer [1997, p. 9 ff.] In order to develop a customer retention model for the first case and a customer migration model for the second case. Reinartz and Kumar [2000, p.17 et seq.] Add that the CLV is relatively easy to calculate in contractual relationships, provided that the duration of the contract, such as for mobile phone subscriptions, is known. On the other hand, the CLV is much more difficult to calculate for unbound customers in the mail order business because it makes sense to assume that new purchases can be made even with longer buying intervals [ibid., P. 18]. In the present work, the latter case is relevant, since no contractual commitment is entered into with the purchase. Bauer et al. [2003, p. 49 ff.] Divide the concepts of the CLV into three approaches. The first category is occupied by the concepts that ignore the customer loyalty rate 11. Concepts that take the customer loyalty rate into account (cf. Dwyer [1997]; Reinartz and Kumar [2000]), but ignore cross-selling and references [Bauer et al. 2003, p. 50], form the second category. As the last and third category, concepts are used which correct the deficiencies of the first two categories and are assessed as comprehensive [ibid., P. 50]. Bauer et al. [ibid., p. 54] propose a CLV, which can be viewed as comprehensive, since it takes into account the up- and cross-selling income (see Figure 2.5) as well as the reference value of a customer. The comprehensive consideration is opposed to the more general one by Venkatesan and Kumar [2004, p. 108], which of future returns the 9 The term is also used as a discount factor. 10 Dwyer [1997, p. 8] refers to [Jackson 1989] as the founder of this classification. 11 Retention rate, the probability that a customer will remain loyal [Bauer et al. 2003, p. 50]. 17th

28 2 Theoretical frame of reference subtracts and discounted future costs to calculate the CLV. A common distinction between the concepts differentiates between a retrospective (past-related) and a prospective (future-related) category. The CLV concepts with potential estimates belong to the latter category. According to Krafft and Rutsatz [2006, p. 279], it is precisely the prospective part of the CLV that is responsible for considerable inaccuracies and is to be regarded as the reason for the lack of establishment of the CLV. At this point it should be noted that the different perspectives are justified. The aspects examined in this thesis concern the monetary (up- / cross-sell) as well as the non-monetary perspective (e.g. reference value) of the CLV. Figure 2.5: The CLV model according to Bauer et al. [2003, p. 54] In contrast to the CLV, which records an individual customer value, Customer Equity (CE) relates to the entire customer base and not to the value of an individual [Rust et al. 2004, p. 110]. Rust et al. [ibid.] expand the view of the CE even to the potential clientele by using CE 18

29 2.1 Define CRM / eCRM as: (...) the total of the discounted lifetime values ​​summed over all of the firm s current and potential customers. [ibid., p. 110]. You go one step further as a farmer and others. [2003, p. 56]. The consideration of potentials can also flow into the CLV [Gelbrich and Wünschmann 2006, p. 586 ff.] Therefore, a calculation of the CE in the broader sense would also be possible, which takes the relational potential into account in order to determine the CE. The CLV approaches see the customer relationship from the investment perspective. In contrast, there are approaches that use the contribution margin as a basis for calculation. This method is called customer contribution margin calculation (KDBR). Customer contribution margin calculation (KDBR) is used to determine the profitability of a customer relationship [Bruhn 2009, p. 278]. The basic principle is that sales are compared with the relationship costs of a customer [Köhler 2003, p. 399]. This calculation principle is derived from the product contribution margin calculation [Schirmeister and Kreuz 2006, p. 313]. Because this procedure deals with the interrelationships between costs and operational performance, according to Meyer [1996, p. 171] it is assigned to the operational accounting and represents a further development of financial accounting [ibid., P. 172]. A distinction is made between direct and indirect (also called overhead costs) costs (cf. Leimgruber and Prochinig [1994, p. 93]; Meyer [1996, p. 181]). The direct costs can be clearly assigned to the individual product, the overhead costs, however, are incurred for several products and must be assigned proportionally [ibid., P. 181]. According to Köhler [2003, p. 400], the customer contribution margin calculation takes place in three stages. On the first, the sales deductions are deducted from the gross customer sales, which results in the net sales per customer. The variable unit costs are then deducted from what provides the 1st customer contribution margin. If the clear order costs are deducted from this key figure, you get the 2nd customer contribution. As the last and thus third level, the clearly customer-related and other individual costs are deducted. This results in the 3rd customer contribution margin. For a simplified two-stage version, Schirmeister and Kreuz [2006, p. 314ff.] Can be used, which make a direct comparison of the product and customer calculations. The shortening comes about in the first stage, since Schirmeister and Kreuz [2006] start directly with the product contribution margin. Köhler [2003, p. 401] takes the process perspective (e.g. dispatch of goods) for customer-oriented success determination. Regardless of the perspective, these methods have certain limitations. On the one hand, a solid database from accounting is required, which can provide the figures tailored to the customer relationship. This is not 19

30 2 Theoretical frame of reference, of course, since accounting has the task of period and product-related income statements [Schirmeister and Kreuz 2006, p. 313]. In addition to the data refinements, there are facts and effects that are not included in the customer contribution margin calculation. For example, if customer A recommends a product to customer B, the sales will be attributed to customer B [Köhler 2003, p. 400], although customer A is the source of the sales. Because the relationship potentials of customers play a role in the present work, the customer contribution margin calculation can lead to relevant distortions. Customer portfolio The idea of ​​assigning customers to two dimensions goes back to Markowitz [1959, pp. 3ff.]. Reinecke and Keller [2006, p. 266] refer to a portfolio that classifies its customers according to the dimensions of customer attractiveness and the company's competitive position with customers. This classification goes back to Lessing [1982, p. 57]. For the attractiveness dimension, Reinecke and Keller [2006, p. 265] see sales, customer value or the development of contribution margins as possible key figures. If the portfolio is created with the dimensions of sales and relative market share, the portfolio is also known under the name BCG 12 matrix. This matrix provides take-away, skimming, question mark and star customers. This form of representation Figure 2.6: Customer portfolio with sales and relative market share (BCG matrix) 12 BCG stands for Boston Consulting Group. 20th

31 2.1 CRM / eCRM is clear and can be used by corporate management to develop a customer processing strategy [ibid., P. 266] RFM method (scoring method) The RFM method goes back to Hughes [2006] and segments the customer base by means of time (Recency ), Frequency and monetary value [cf. ibid., p. 104 f.]. The frequency criterion makes it clear that this method can only be used to a limited extent for the segmentation of new customers, since the frequency of new customers is only manifested through purchases. The criteria taken into account also make it clear that this method does not record non-monetary values ​​of a customer. In particular, customer reviews can be valuable contributions online, which should not be missing when considering the customer value with the trustworthiness of an online shop as a background. Therefore, from this perspective, methods are preferred which offer the possibility of taking into account values ​​which can be beneficial to the trustworthiness of an online shop. Therefore, the CLV procedure and the customer portfolio are to be preferred for evaluating a customer including his non-monetary values. Delimitation CRM / eCRM CRM stands for customer relationship management and is called customer relationship management according to Bruhn and Homburg [2008, p.7]. You emphasize that it often refers to the information technology framework of this management [ibid., P.7]. Hippner [2006] interprets the term more holistically and with an information technology focus as a concept: CRM is a customer-oriented corporate strategy that tries to achieve long-term profitable customer relationships with the help of modern information and communication technologies through holistic and individual marketing, sales and service concepts to build up and consolidate (cf. Hettich et al. [2000, p. 1346]; Hippner [2006, p. 18]). However, numerous authors point out that there is still no established definition for CRM (cf. e.g. Gerdes [2008, p. 448] or Bruhn [2009, p. 13]). Eggert and Fassott [2001] come to the same conclusion for the term ecrm, which stands for electronic customer relationship management and can be defined as follows: ecrm includes the process of creating customer relationships with the help of electronic media or channels (especially the Internet) [Staack 2004, p. 26]. 13 The fact that the concepts of CRM and ecrm are close to one another can also 13 Cf. also Payne [2006, p. 24]: The Term e-crm refers to the use of e-commerce tools or electronic channels in CRM. 21

32 2 Theoretical frame of reference Schulze [2002, p. 54]. He formulates: Basically the goals for ecrm and CRM are identical; the only difference between the two approaches is the type of interactions between the company and its customers. It should be noted that both terms refer to the design of the customer relationship. This design can be more precisely divided into three business processes, which relate to the marketing, sales and service processes of a company. Link [2001] describes these processes in a more general way, but with a technical reference and process character: CRM can be defined as the information technology-based production, maintenance and use of customer relationships [ibid., P.3]. Schulze [2002] mentions the following components that are necessary to automate marketing, sales and service of a portal application. With the exception of the technical integration, which is not used due to the absence of legacy systems, all components (cf. Section 4.3) according to Schulze [ibid., P. 54] are used in this work: Customer registration: Collection of personal data Customer identification: ID / password Use: Use of business logic Technical integration: Connection of the portal to legacy systems CRM and ecrm are used to design customer-specific business processes, namely marketing, sales and service. The concepts differ, however, in the type of channel selected and, in particular for the Internet channel, a clear assignment to the ecrm should be permissible. Swift [2001, p. 12] expresses the concrete intentions and goals of the CRM approach as well as the influencing intention behind the measures more clearly by mentioning the influencing of consumer behavior in his definition: enterprise approach to understanding and influencing customer behavior through meaningful communications in order to improve customer acquisition, customer retention, customer loyalty, and customer profitability. CRM not only relates to different business processes, but, since it is oriented towards the customer, the customer lifecycle and its phases come into focus. Hippner [2006] includes potential, current and lost customers with his CRM perspective. In addition, Figure 2.7 shows that customer relationship management only relates to current customers. The CRM is more broadly defined and, as already mentioned in Link [2001] and Swift [2001], is also geared towards potential and lost customers [Hippner 2006]. The visualized delimitation by Hippner [ibid.] Can be seen in Figure 2.7. Schumacher and Meyer [2004, p. 19] focus more on the goals of CRM: CRM generally refers to the comprehensive design of the supplier-customer relationship between a company and its 22nd

33 2.1 CRM / eCRM Figure 2.7: Conceptual classification and delimitation according to Hippner [ibid., P. 20] customers and interested parties understood. CRM is seen as a customer-oriented approach to corporate management. It includes the alignment of entrepreneurial activity on the interests, requirements and preferences of customers, with the aim of optimally designing long-term, partnership-based customer relationships in order to generate economic benefits. In addition, they introduce the concepts of customer satisfaction and customer loyalty, which CRM does not neglect so that a holistic character can manifest itself: In addition to the corporate goal of profit, the realization of customer satisfaction and competitiveness through customer loyalty is a primary goal of CRM-oriented companies. 14 The mentioned customer relationship can be divided into phases or stages (cf. Krafft et al. [2002]) CRM stages Krafft et al. [ibid., p. 42] define three levels of CRM: customer (re-) acquisition, retention / intensification and the termination of the customer relationship. The classification with the definitions and perspectives of e.g. Link [2001], Swift [2001] and Hippner [2006] compatible. The first two stages of this classification can be identified in this work as follows. The customer acquisition is assigned to the 1st stage. Selling complementary products (cross-selling) and animating the purchase of a more expensive product (up-sell) can be assigned to the 2nd level, as these represent an intensification of the relationship in terms of the customer's financial commitment. 14 References to Wenzel [1998, p. 45] and Macharzina [1993, p] 23

34 2 Theoretical frame of reference Conclusion Definition It can be seen from the various definitions that CRM can basically be seen as a holistic corporate strategy that aims to positively influence customer relationships using communication technologies. This strategy applies to potential, current and lost customers. In addition, the customer relationship should be designed to be as long-term, profitable and individual as possible. In this context, the concepts of customer loyalty (see section 2.1.1) and customer value (see section 2.1.3) are also mentioned. If the electronic communication channels are used in this approach, the term ecrm is used. The areas of responsibility of CRM / eCRM CRM and ecrm, by definition, relate to many areas of a company. Therefore, a more detailed breakdown is shown at this point in order to classify this work more precisely. Theoretical treatises on CRM often differentiate between operative, analytical and communicative CRM (cf. Hettich et al. [2000, pp.] Schumacher and Meyer [2004, p. 21] 15, Hilbert [2008, p. 1 fig. 1], Kreuz et al [2001, p. 10 ff.] or Neckel and Knobloch [2005, p. 45 fig. 1-15]). Some authors introduce the concept of collaborative 16 CRM into this three-way division of the task areas (cf. Payne [2006, p. 23]; Uebel et al. [2004, p. 10]; Stokburger and Pufahl [2002, p. 10]). Collaborative CRM is about enabling interaction between the individual channels as well as between customers, the company and their employees [Payne 2006, p. 23]. According to [ibid.], The concept of collaborative CRM includes the coordination of communication channels and customer communication. This could lead to ambiguities, especially when examining communication. Schumacher and Meyer [2004, p. 47] specify the concept of collaborative CRM as measures that serve to standardize corporate CRM activities. A collaborative character can be ascribed to the multi-channel management, which according to Schumacher and Meyer [ibid., P. 47] is described as the technical and procedural coordination of different communication channels. Hippner et al. [2006, p. 48 ff.] Divide the task areas of CRM in two by only differentiating between operational and analytical CRM and classifying the communicative CRM tasks with the operational ones. There is no division of the task area for this work, as the operational tasks cannot be separated from the communicative ones. Because the present 15 refers to Kehl and Rudolph [2001] for the subdivision of operative and analytical CRM (see Kehl and Rudolph [ibid., P. 257 ff.]). 16 The ecrm uses collaborative filtering to personalize offers. Amazon makes e.g. Book suggestions based on suggestions from analytical CRM using collaborative filtering. 24

35 2.1 CRM / eCRM investigation mainly concerns the communication channel Internet, the three-part breakdown of CRM is preferred, which communicative CRM explicitly mentions. In the area of ​​communicative CRM, it is important to illuminate the call center more precisely. The call center is used to contact customers [ibid., P. 65]. If the customer calls, the inbound functionality of the call center is used. If the company contacts the customer, this is assigned to the outbound functionality [ibid., P. 65]. The communication medium of the telephone is used in the call center. If several channels are integrated, one speaks of a Customer Interaction Center (CIC) [Hettich et al. 2000, p. 1362].The present work has implemented such a call center (see Section 4.3.8) to give customers the opportunity to contact the company. In the experiment, no calls were made to customers, so the call center is only designed for inbound functions. Goals CRM / eCRM Improving customer acquisition, customer loyalty and increasing profitability are also the goals of customer relationship management [Schulze 2002, p 14]. A central task of CRM is therefore to identify and maximize the value of a customer and thus to contribute to increasing the company's value [Wittkötter and Steffen 2002, p. 82]. Staack [2004, p. 50 ff.] Uses the customer perspective to subdivide the ecrm's goals into customer-related (effective and efficient acquisition of profitable new customers, establishment and expansion as well as deepening of profitable customer relationships and avoidance of the migration of profitable customers) and cross-customer (process-related 17th , strategic and financial) goals. These explicitly named goals coincide with the conceptual goals that emerge from the definitions of CRM and ecrm (see section 2.1.6). Classification It should and cannot be the goal at this point to set up a further definition of CRM and ecrm. Rather, clarity should be created about the classification of this work in the broad field of CRM and ecrm. With regard to the CRM process, as Link [2001] understands it, the present work is to be classified in the production as well as the use of the customer relationship and can also be used with the 1st and 2nd level according to Krafft, among others [2002] (see section). Because this takes place via the electronic channel of the Internet (cf. definition by Staack [2004]), the work is assigned to the ecrm. 17 As an example: Improving the efficiency / effectiveness of marketing, sales and service. 25th

36 2 Theoretical frame of reference 2.2 Typology of goods The typology of goods, borrowed from the information economy, is relevant with regard to a customer's purchase decision, since a different information asymmetry can arise when purchasing, depending on the type of goods. This asymmetry could have trust-related effects. Therefore, in this work, the goods are divided into the following categories: Search goods (e.g. printer paper with 80 g / m 2) Experience goods (e.g. TFT monitor) Trust goods (e.g. antivirus software) The subdivision into search and experience goods goes to Nelson [1970, P. 312 ff.]. He argues that search goods can in principle be assessed before buying, while with experience goods in most cases a purchase is inevitable in order to be able to assess the product. This subdivision was expanded by Darby and Karni [1973, pp. 68 ff.] To include the typology of trustworthy goods. These goods can usually not be fully assessed even after they have been purchased. 18. The assignment of a product to these types of goods depends on various factors and on the experience and level of knowledge of the customer with regard to the product. Arnthorsson et al. [1991, p. 218] even introduce the situation as a factor which can have an influence on the assignment of the product. With regard to these properties of products, the present work also speaks of the search, experience and trust character of the products in order to emphasize the dominant type of goods. Meffert [2000, p. 56] sees this classification as suitable for marketing measures that aim to reduce the purchase risk. This statement on the purchase risk in connection with the types of goods leads to the conclusion that an investigation that examines the trustworthiness of an online shop should not disregard the types of goods. 2.3 New institutional economics This section deals with the theories of the new institutional economics, because they provide a theoretical background for the need for trust in online shopping and contribute to an understanding of the selected measures of the online shop experiment. 18 Credence qualities are those which, although worthwile, cannot be evaluated in normal use. [Darby and Karni 1973, pp. 68 ff] 26

37 2.3 New Institutional Economics Introduction The classical school of economics, in which Smith [1776] examines the division of labor and introduces the invisible hand as an explanation for the coordination of individuals [ibid.], Has been replaced by neoclassical schools, which have competitive markets with supply and demand as central theoretical concepts include [Picot et al 2008, p. 35]. The New Institutional Economy extends the neoclassical constructs to include the behavior of individuals [Höll 2009, p. 149]. These individuals are recognized by institutions that are supposed to be sanctionable expectations related to the behavior of one or more individuals [Picot et al. 2008, p. 10], coordinated and motivated [ibid., P. 10]. Picot et al. [ibid.] list laws, rights or corporative structures (companies) as examples of institutions and point out that the New Institutional Economics is not a uniform theoretical structure, but should be viewed as methodologically related approaches [ibid., p. 46] and can be subdivided into three sub-streams: Property rights theory Transaction costs theory Principal-agent theory Basic assumptions The theory of New Institutional Economics includes basic assumptions, some of which must first be presented before the three sub-streams can be discussed individually. The first assumption to be mentioned is methodological individualism, which regards people as different with different and diverse preferences and goals [Richter and Furubotn 1996, p. 3]. The second assumption is individual benefit maximization, which assumes that every person maximizes their individual benefit (cf. Höll [2009, p. 149]; [Picot et al. 2008, p. 46]). Richter and Furubotn [1996] use the term Maximand in this context (cf. Furubotn and Pejovich [1972, p. 1138]). The two assumptions show that the focus is no longer on a company as a whole, but on individuals and their actions within a company [ibid., P. 1138]. This consideration leads to the assumption of perfect and imperfect individual rationality. Richter and Furubotn [1996] note that there are two views among theorists. Those who adhere to the neoclassical conception of perfect individual rationality and are predominant in the Prinpal-Agent theory [ibid., P. 4]. Imperfect individual rationality 19 is represented by the other group, which, for example, 19 The terms objective and limited rationality are also used for perfect or imperfect individual rationality (cf. [Picot et al. 2008, p. 32]). 27

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