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  • 1.
    Awan, Salman Ahmad
    et al.
    Wuhan Univ Technol, Sch Management, Wuhan 430070, Peoples R China..
    Said, Muzafar
    Karlstad University, Faculty of Arts and Social Sciences (starting 2013), Karlstad Business School.
    Roos, Inger
    Karlstad University, Faculty of Arts and Social Sciences (starting 2013), Service Research Center.
    Improve the Communication Quality by Understanding Switching Behavior2015In: PROCEEDINGS OF THE 12TH INTERNATIONAL CONFERENCE ON INNOVATION AND MANAGEMENT / [ed] Wang Yingming, Xu Hongyi, WUHAN UNIV TECHNOLOGY PRESS , 2015, p. 62-73Conference paper (Refereed)
    Abstract [en]

    Instant paper aims to analyze telecom customer relationship by delving into customer switching behavior and identifying preferred communication type to help companies in designing appropriate communication in order to prevent the customer switching and enhancing customer loyalty. Two staged qualitative research has been conducted by interviewing 13 telecom customers who had experienced telecom service provider switching and data is analyzed by coding technique. Findings reveal that telecom customers chose distinctive sources of information while making switching decision. Active customers chose newsletter based on rich content including innovative services information whereas passive customers chose newsletter primarily based on competitive prices. Managers can communicate active and passive customers according to the respective communication preferences. Moreover, marketers can study switching determinants, triggers and sources of information in order to design the customized communication so as to prevent triggers from happening in the first place, thereby enhancing customer loyalty. This paper synthesizes insights from the extant literature on relationship marketing, customer switching behavior and contemporary communication channels to develop comprehensive customer-driven loyalty enhancing communication.

  • 2.
    Edvardsson, Bo
    et al.
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration. Karlstad University, Faculty of Economic Sciences, Communication and IT, The Service and Market Oriented Transport Research Group.
    Friman, Margareta
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Psychology. Karlstad University, Faculty of Economic Sciences, Communication and IT, The Service and Market Oriented Transport Research Group.
    Roos, Inger
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Emotions and Stability in Telecom-customer Relationships2009In: Journal of Service Management, ISSN 1757-5818, E-ISSN 1757-5826, Vol. 20, no 2, p. 192-208Article in journal (Refereed)
  • 3.
    Edvardsson, Bo
    et al.
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration. Karlstad University, Faculty of Economic Sciences, Communication and IT, The Service and Market Oriented Transport Research Group.
    Friman, Margareta
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Psychology. Karlstad University, Faculty of Economic Sciences, Communication and IT, The Service and Market Oriented Transport Research Group.
    Roos, Inger
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Service Quality Grounded in Customer Experiences, Affect and Relationships2007In: Service Excellence als Impulsgeber, 2007Chapter in book (Refereed)
  • 4.
    Edvardsson, Bo
    et al.
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration. Karlstad University, Faculty of Economic Sciences, Communication and IT, The Service and Market Oriented Transport Research Group.
    Gustafsson, Anders
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Roos, Inger
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Comparing Switching Patterns in Competitive and Non-competitive Markets-Customer Preferences and Behavior in Five Service Industries2002Conference paper (Refereed)
    Abstract [en]

    ABSTRACT

    This article is about behavioral change in customer relationships. Changes in customer behavior are compared in five different service industries. The changes are manifested as switching behavior, which is at the same time the reference point for customer expressions on the paths that lead to switching. Switching barriers and the competitive industrial situations in the comparison between industries also revealed changes in behavior in an industrial monopoly in which switching to alternative external service providers was not an option. This kind of switching was articulated as internal switching. The behavioral change was therefore assessed in terms not only of frequency, but also of type of change. Switching was reflected as a configuration including the ability to cause behavioral change on different levels. The switching ability called configuration energy even caused a change in behavior at the highest level in a non-competitive industry in which there was a lack of switching alternatives. Total change was considered to be a result of the higher energy level driving the switching configuration than when the change was partial.

    Keywords: Customer switching, customer relationships, behavioral change, competitive and non-competitive service industries.

  • 5.
    Edvardsson, Bo
    et al.
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration. Karlstad University, Faculty of Economic Sciences, Communication and IT, The Service and Market Oriented Transport Research Group.
    Gustafsson, Anders
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Roos, Inger
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Customer Clubs in Telecommunications - A Relationship Marketing Perspective2003Conference paper (Refereed)
  • 6.
    Edvardsson, Bo
    et al.
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration. Karlstad University, Faculty of Economic Sciences, Communication and IT, The Service and Market Oriented Transport Research Group.
    Gustafsson, Anders
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Roos, Inger
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Improving the Prerequisites for Customer Satisfaction and Performance: A Study of Policy Deployment in a Global Truck Company2010In: International Journal of Quality and Service Sciences, ISSN 1756-669X, E-ISSN 1756-6703, Vol. 2, no 2, p. 239-258Article in journal (Refereed)
  • 7.
    Edvardsson, Bo
    et al.
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration. Karlstad University, Faculty of Economic Sciences, Communication and IT, The Service and Market Oriented Transport Research Group.
    Gustafsson, Anders
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Roos, Inger
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Service Portrays and Service Constructions ' A Critical Review Through the Lens of the Customer, International2005In: Journal of Service Industry Management (2005)Article in journal (Refereed)
    Abstract [en]

    Service definitions and service characteristics have played a key role in establishing service research as an academic field. In this article we discuss service portraits. We believe that discussions regarding definitions of services and service characteristics are important when understanding value creation through services. Our aim is to contribute to the discussion about the future of service research by means of a literature overview and empirical results from a study among scholars who have shaped this area of research. This discussion is motivated by criticism from service scholars who question the foundations for the discourse. The critique focuses on how services have been defined and operationalized in generic service characteristics. By portraying service, we view service as a perspective on value creation. We put emphasis on the lens of the customer and the value that is co-created with customers

  • 8. Edvardsson, Bo
    et al.
    Gustafsson, Anders
    Roos, Inger
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Service Portrays and Service Constructions: A Critical Review Through the Lens of the Customer2004Conference paper (Refereed)
    Abstract [en]

    The concept service has been defined in many different ways. Most scholars put forward that services are activities, deeds or processes and interactions (Solomon et al, 1985; Lovelock, 1991; Zeithaml and Bitner, 2000). Most definitions also focus on the customer and that ser-vices are provided as solutions to customer problems (Grönroos, 2000). Does it capture the essence of services? Does it form a fruitful basis for managing services and for the creation of value through services?

    In service research some fundamental truths about services have for a long time been re-ferred to and used in scholarly studies. In the beginning of services research, a common way was to portray services as something different from goods. The intangibility, heterogeneity, inseparability and perishability (IHIP) characteristics served as guiding principles in several academic battles to establish the research field of services (Bateson, 1979; Parasuraman, Zeithaml, and Berry 1985; Shostack, 1977).

    Service research has reached a point when the relevance of established truths and concepts are discussed. The critic comes from established and pioneering scholars within service research such as Christian Grönroos, Chris Lovelock and Evert Gummesson. During the 2002 Service Frontiers conference in Maasricht and the 2003 AMA ServSig conference in Reims, some service scholars expressed disappointment with the development within the discipline. The relevance of the IHIP characteristics has been questioned, especially when it comes to intan-gibility. The argument is that the characteristics do not reflect what services really are and value creation through services.

    A discussion has started focusing on the foundations for service research. This paper is a con-tribution to that discussion. Our focus is on one research question: How is the phenomenon Service defined and portrayed within service research? The aim is to critically examine how (1) the concept service is defined, (2) the service characteristics as an expression of the concept service and (3) value-creation through services. The three themes will be dealt with through the lens of the customer. The paper is based on a literature search and the ambition is to contribute to the ongoing discussion on the foundations for and future direction of service research.

  • 9.
    Edvardsson, Bo
    et al.
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration. Karlstad University, Faculty of Economic Sciences, Communication and IT, The Service and Market Oriented Transport Research Group.
    Gustafsson, Anders
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Roos, Inger
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    The Effect of Triggers in Customer Relationships2002Conference paper (Refereed)
    Abstract [en]

    In the research literature trigger is used in several different meanings and ways. The application in relationship marketing has traditionally been connected to critical incidents with implication for relationships between customers and service providers. The behavioural consequences of triggers have accordingly had a limited and narrow association with relationships. In this article we include triggers in a switching-intention model that gives not only the connection between trigger and critical incidents, but includes also the context to the behavioural consequences of triggers. The model reflects a dynamic switching path that describes on ongoing process of customer sensitiveness for switching. In other words, the trigger divides the customers due to their sensitivity for switching into customer groups indicating differing levels regarding the strength of their relationship with a certain service provider.IntroductionIn a longer time perspective as in the relationship view customers seem to fluctuate in their evaluation of their service providers. The fluctuation may be considered as changes in their perceptions of the service providers. The reasons for the changes differ regarding factors that are important for the relationship continuation. The changed perceptions again are likely to influence the stability of the relationships regardless of the seemingly existing maintenance of the relationship. Therefore, the real state of the relationship temperature regarding true stability and thus the reasons and motivation for the change becomes essential. Recent marketing literature suggests that a discrimination of switching customers from continuers deepens the understanding concerning the matter of fluctuating perceptions in customer relationships (Ganesh et al. 2000; Keaveney and Parhasarathy 2001). The authors of those articles imply further that the effect of customer relationships history on future customer perceptions of relationships is possible to discern by distinguishing the continuers from switchers. Nevertheless, the awareness of fluctuating perceptions during the distance between the initiation of and switching from relationships put pressure on the slow progress in marketing literature on the subject of deepening understanding of customer relationships. This article sets focus on triggers that influence customer relationships in order to fill the gap of lacking understanding of the deceptively and irregularly perception changes among customers. Improvement concerning the understanding of differing perception sensitivity among customers may be considered as a response to the request in recent literature regarding behavior changes and segments. Schultz (2002) indicates that customer segmentation has stagnated to reflect only physical properties, attitude or finite measures. In order to maintain behavioural data for segmentation an increased understanding of behavior changes is needed.Accordingly, those kinds of basic differences among customers have implications for their sensitivity for episodes that challenge their current relationships. In this article we propose a loyalty-predicting model with ultimate focus on switching intentions. The model includes sensitising factors labelled triggers. The role of the trigger is defined according to Roos (1999; 2002: Edvardsson et al. 2002), where the energy and direction of the trigger influence describes a switching path. The trigger effect described here is on top of and affects the relationships when customers have perceived or constantly perceive situational, influential or reactional factors that they in some way relate to the relationship with their service provider. Consequently, the source of the influencing factors does not have to be directly related to the relationship, also the context has established its noticeable and additional significance as trigger source and contributor (Edvardsson et al. 2002). In sum, the trigger effect on customer perceptions is in this study accordingly defined as factors with sensitising and directing influences on customers evaluations processes with behavioral consequences for the relationship (Roos 1999; 2002: Edvardsson et al. 2002).In this paper, we also report the results from an empirical study of a large Swedish telecommunication company, where a loyalty-predicting model has been tested. The results show differences among customers concerning the evaluation of service providers depending on whether customers are on switching paths or not. We find that the models built for customers that are on the switching path have a larger R2 indicating that the models fit better for them. The implication is that these customers are more critical towards the service provider and are better at evaluating the company compared to customers that does not have a trigger.The triggerThe literature describes triggers of varying nature. Generally the trigger concept is used in psychological literature indicating the causal factor of a change of the conditional state or in medical literature as the final reason for breaking down the defence against deceases (Eby et al. 1999; Karpa 2000; Supphellen and Nelson 2001). In the financial literature trigger is used, although rarely, as the articulation of explanations for prompt capital outflows and rapid deterioration of stable economies (Paasche 2001). In marketing literature trigger is most frequently given the role of alarm clocks (Gardial et al. 1996), where the function concentrates on energy to provide signals for further actions either in organisations (Schindehutte et el. 2000) or in perception processes (Roos and Strandvik 1997; Edvardsson and Strandvik 2000). Such view on triggers was edified by Olsen (1992) as triggers were characterized equal to critical steps in an episode of a customer relationship. The trigger was seen as the source of the critical incident with energy to influence the progress of the incident. However, literature does not usually use trigger significance in the way it is used in the present article where the trigger function is seen as a change of the relationship character caused by typical factors with long-lasting effect. The effect on the specific customer is a change to more conscious and sensitive approaches to all perceptions of the relationship (Edvardsson et al. 2002). Therefore, the triggered customers have distinct and different characters concerning their awareness of their service providers services and products compared to those customers who have not perceived a trigger. Based on the logic of satisfaction it has been suggested in the literature (Day 1976; Woodruff 1993; Gardial et al. 1996) that the triggering effect causing behavioural changes on the relationship has to be associated with critical incidents. It is therefore crucial to define the difference between critical incidents and criticality. Day said nearly 30 years ago: In general, something out of the ordinary must occur either prior to the purchase process, during the purchase process, or during the consumption phase to alert the consumer or call his attention to some aspect of the purchase situation (italics added: Day 1976). That definition represents the traditional view on critical incident with no outspoken implication for customer relationships.Gardial et al. (1996) again consider triggers as events with five different kinds of responses among customers. One response is categorised as Change in Behavior or Product use, another is Change in Evaluation followed by Re-evaluation, Change in Standards Level and Emotional Response. That categorization reflects the authors view on the consequences of the events. The static view on the consequences of the events makes their categories appear as detached elements of a relationship. When customers describe their actual switching behavior as a process (Roos ), for example, they include emotions and changes in perceptions as factors of their switching paths. The factors of the paths only describe the progress and the character of the switching paths, the paths characterize the customers and their sensitiveness for switching. In a switching perceptive we follow therefore the definition of criticality that pays attention to actual change of behavior with implication for the relationship (Roos 1999; Edvardsson and Strandvik 2000). Accordingly, when a change in behavior occurs the reason of the change is revealed and derived, not only from traditional critical incidents but also from other factors both in the typical relationship and in the context of it. The traditional association between critical incidents and the change in behavior becomes thus included in the trigger definition used for this article. In other words, the defintion of triggers is thereby extended from a precise location associated to some critical incident causing immediate change in perception, evaluation or behavior to a more long-standing effect that not always has direct influence on the relationship. In sum, in this article the trigger effect is defined and analysed as: Situational, Influential and Reactional triggers, which gives not only the distinctive relationship definition but also simultaneously prompts the segmenting function. The segmenting effect of the trigger The segmenting effect of triggers is embedded in the customer description of switching paths. Triggers are divided in: Situational, Influential and Reactional. The categorization is made due to a numerous qualitative studies and a method labelled SPAT. We are not going to present and deliberate SPAT any further in this study, because that particular tool for qualitative analysing of actual switching behavior has been previously published (Roos 1999; 2002; Edvardsson et al. 2002 a and b).Customer sensitiveness regarding their evaluation of service providers are divided into groups labelled: Situational Influential Reactional.The situational, influential and reactional characteristics identify the sensitiveness that labels the respective switching path. According to Roos (1999; 2002) and Edvardsson et al. (2002 a and b) situational customers perceive increased sensitiveness towards the service provider because of changes in their own lives or in something affecting their own lives. Such matters can be represented by demographic changes in the family, changes in job situations or the economic situation of the particular customer or the family. Situational customers have a comprehensive approach to price issues concerning the relationship. Influential customers again follow the price campaigns of the competitors without a deep elaboration of costs and benefits, specially concerning the efforts of new actors aiming in to the market. Influential customers follow the business including the competitors actions and have not a comprehensive approach to price issues. Reactional customers are those customers that traditionally were included in literature (Gardial et al. 1996) as having perceived critical incidents. Reactional customers have perceived a critical incident or perceive that the business of the service provider has deteriorated or is constantly deteriorating. Price increase that is perceived to be unfair in the meaning that they either becomes to high compared to others or are considered to much at one time may also place a reactional customer on the switching path. Mostly the increased sensitiveness of a reactional customer is, however, related in some respect to the personnel or the overall service. Reactional customers are less-price sensitive than the other two segments perceiving increased sensitiveness towards the service provider.Once customers have perceived the trigger they enter the switching path. When customers are on switching paths they are more sensitive to all concerns of the particular company. The consequence of that is that the sensitiveness is not increased only regarding the source of the trigger, but regarding the whole company. Customers become more aware and they seem to be better at evaluating the companys business that those customers that have not perceived any trigger. From that perspective we propose a model that enables the differences among customers regarding the relationship strength. Thus, when customers are more sensitive towards the company they simultaneously seem to be more aware of the switching option. The respective switching path again describes more in detail the character of each customer group and the level of their switching disposition. The modelThe model (Edvardsson et al. 2002) describes loyalty ? in terms of customers being or not being on switching paths. Additionally, the trigger effect, the reasons for being on switching paths, divides customers into segments based on the kind of trigger influencing the switching path. Customers commitment to their service providers sets furthermore apart the customer evaluation of the service providers as being either calculative or affective. The factors of the model are included embedding their typical functions for the dynamism of the process. The loyalty model depicts accordingly loyalty as on ongoing process. Figure 1 displays a model that is the result of a range of qualitative studies on actual switching behavior (Edvardsson et al. 2002a and b). The dynamic model is divided into four different stages: The triggers, The process, The return reasons and The outcome. The outcome of the model is switching intentions forming the possible end of a switching path. On the switching path the customers form their perceptions of the company. The factors included in the perception of the company were derived from longitudinal qualitative studies on actual switching behavior of telecommunications (Edvardsson et al. 2002b). More detailed, the perceptions form the focus of the customer expressions during their relationships and on their switching paths. Figure 1. The loyalty model.The Triggers were found to have a sensitising effect (Roos 1999) on customer perceptions throughout the relationships and are separately analysed from the angle of their particular trigger character. The dynamic switching intention model has accordingly not only the potential to describe a switching path but features also a segmenting capacity.In social psychology, involvement has been used in persuasion research as an important variable affecting attitude change (Park and Mittal 1985). Commitment to service providers occurs during certain circumstances of involvement, regardless of what kind of industry the service provider operates in. Although, some industries may be argued to have more committed customers due to the character of their products being durables or non-durables, customers themselves decide on whether they are committed to their service provider or not depending also on other and complementary factors. The reasons for commitment is in Figure 1 looked at as being either affective or calculative. In other words, the repeated behavior in the model is not only regarded as committed or not committed, it is additionally distinguished by argumentation. Being viewed as customer communication, either with other people or with themselves, customers change their behavior also by changing their attitudes towards the service provider. The categorization into affective and calculative cuts through all categories suggested by Park and Mittal (1985). Their categorization is based on how argumentation influences affect and behavior. In some cases, however, the change of behavior must not be an antecedent of attitudinal change, which is paid attention to in Figure 1.The methodThe resultsDiscussionReferences:Day 1976Eby, Lillian T., Deena M. Freeman, Michael C. Rush and Charles E. Lance (1999), Motivational Bases of Affective Organizational Commitment: A Partial Test of An Integrative Theoretical Model, Journal of Occupational and Organizational Psychology, Vol. 72, No. 4, pp. 463-483.Edvardsson, Bo and Tore Strandvik (2000), Is a Critical Incident Critical for a Customer Relationship?, Managing Service Quality, Vol. 10, No. 2, pp. 82-91.Edvardsson, Bo, Anders Gustafsson and Inger Roos (2002a),Understanding the Trigger Effect on Customers Maturity Processes in Telecommunication, QUALITY IN SERVICES (QUIS 8), The Eighth International Research Symposium on Service Quality, Victoria, British Columbia, Canada, June 11-14, 2002.Edvardsson, Bo, Anders Gustafsson and Inger Roos (2002b), Comparing Switching Patterns in Competitive and Non-competitive markets Customer Preferences and Behavior in Five Service Industries, 11th Annual AMA Frontiers in Services Conference Maastricht, The Netherlands, June 27-29, 2002.Ganesh, Jaishankar, Mark J., Arnold and Kristy E. Reynolds (2000), Understanding the Customer Base of Service Providers: An Examination of the Differences between Switchers and Stayers, Journal of Marketing, Vol. 64, No. 3, pp. 65-87.Gardial, Sarah Fisher, Daniel J. Flint and Robert B. Woodruff (1996), Trigger Events: Exploring the Relationships between Critical Events and Consumers Evaluations, Standards, Emotions, Values and Behavior, Journal of Consumer Satisfaction, Dissatisfaction and Complaining Behavior, Vol. 9, pp. 35-51.Karpa, Kelly Dowhower (2000), The Assault on Allergies: From Diagnostics to Treatments, Drug Topics, pp. 12-17.Keaveney, Susan M. and Madhavan Parhasarathy (2001), Customer Switching Behavior in Online Services: An Exploratory Study of the Role of Selected Attitudinal, Behavioral, and Demographic Factors, Journal of the Academy of Marketing Science, Vol. 29, No. 4, pp. 374-390.Paasche, Bernhard (2001), Credit Constraints and International Financial Crisis, Journal of Monetary Economics, Vol. 48, No. 3, pp. 623-650.Roos, Inger (1999), Switching Processes in Customer Relationships, Journal of Service Research, Vol. 2, No. 1, pp. 68-85.Roos, Inger (2002), Methods of Investigating Critical Incidents: A Comparative Review, Journal of Service Research, Vol. 4, No. 3, February, pp. 193-204.Roos, Inger and Tore Strandvik (1997),Diagnosing the Termination of Customer Relationships, Three American Marketing Association Special Conferences, Relationship Marketing, Dublin, Ireland, 12-15 June 1997, pp. 617-631, 1997.Schindehutte, Minet, Michael H. Morris and Donald F. Kuratko (2000), Triggering Events, Corporate Entrepreneurship and the Marketing Function, Journal of Marketing Theory and Practice, Vol. 8, No. 2, pp. 18-30.Schultz, Don E. (2002), Behavior changes; do your segments?, The American Marketing Asssociation: Marketing News, July 22, p. 6, 2002.Supphellen, Magne and Michelle R. Nelson (2001), Developing, Exploring, and Validating a Typology of Private Philanthropic Decision, Journal of Economic Psychology, Vol. 22, No. 5, pp. 573-603.Woodruff 1993

  • 10.
    Edvardsson, Bo
    et al.
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration. Karlstad University, Faculty of Economic Sciences, Communication and IT, The Service and Market Oriented Transport Research Group.
    Gustafsson, Anders
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Roos, Inger
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Understanding the Customers' Maturity Process - A Telecommunication Case2002Conference paper (Refereed)
    Abstract [en]

    Understanding the Customers Maturity Process

    A telecommunication case



    Bo Edvardsson

    Anders Gustafsson

    and

    Inger Roos



    Telecommunication represents the characteristic of a fierce-competitive, dynamic and rapid-growing industry. Through merger mania in a turbulent market telecommunication companies try to improve their control over as many customers as possible (Sumner-Smith and Sumner 1999; Borna 2000; Cobbett and Matthews 2000). These companies are trying to achieve the ultimate attribute of relationship marketing, i.e. long-term relationships with their customers (Grönroos 1989; 2000; Berry 1995; Colgate and Stewart 1998), the application in this industry, however, with disloyal, frequently switching customers seems challenging. Even more difficult is the situation for the companies in the wireless part of the industry with no barriers what so ever to prevent customers from switching. One of the major challenges for the telecom companies is to identify the specific factors appealing to customers willingness to switch between different operators. A longitudinal approach to analysing customers switching processes puts forward and distinguishes the most decisive factors in terms of disloyal behavior. The emerging pattern from that mapping indicates the focus of customer perceptions. That focus is in this study defined as maturity agents. The maturity agents again form the maturing market of a specific market, here telecommunications. Maturing market is hence viewed from the customers perspective in line with the relationship logic. The indicators of the maturing market are per definition instable over time and need therefore to be supported and updated by repeated mapping of customers switching behavior.

    This paper is based on two empirical studies recently carried out in a large Swedish telecommunication company. The first study was a combined complaint and switching behaviour study (Edvardsson and Roos 2001). Findings of the first study are in this paper compared to findings of the second study consisting of process mapping of the customers switching behavior in the same company. Based on this comparison, factors and combinations of factors were found to work as maturity agents in the customers processes. The purpose of the study is to build a model with the capability to establish and generalise maturity agents and their influence on switching intention. Empirical results of the quantitative study are presented.

    In sum, a maturity-agent model is presented and quantitatively measured results presented. The maturity-agent model is grounded in the two empirical studies made in the telecommunication company, here labelled The Company, the maturity agents are defined as the factors, which embed the potential to communicate the change of customer perceptions, including both The Company and the context. The maturity agents are likely to change over time accordingly. The identification of these maturity agents may facilitate and support the sharpness of marketing activities carried out in order to build and maintain long-term customer relationships.

    References:

    Berry, Leonard (1995), Relationship Marketing of Services - Growing Interest, Emerging Perspectives, Journal of the Academy of Marketing Science, Vol.23, No. 4 (Fall), 236-245.

    Edvardsson, Bo and Inger Roos (2000): Customer Complaints and Switching Behavior A Study of relationship dynamics in a telecommunication company. Journal of Relationship Marketing, forthcoming 2001.

    Borna, Claude, 2000. Combating Customer Churn. Telecommunications, Americas Ed. Vol. 34, No. 3, 83-85.

    Grönroos, Christian (1989a): Defining Marketing: A Market-Oriented Approach. European Journal of Marketing, Vol. 23. No. 1, pp. 52-50.

    Grönroos, Christian (2000): Grönroos, Christian (2000), Relationship Marketing: The Nordic School Perspective. Jagdish N. Sheth and Atul Parvatiyar, eds, Handbook of Relationship Marketing, London, Sage Publications, 95-118.

    Sumner-Smith, David and Ian Sumner, 1999. The free-access revolution. Marketing, Vol. 4, March, 29-30.

    Cobbett, Ray and Mike Matthews, 2000. Its your call. Supply Management, Vol.5, No. 14, 34-35.

  • 11.
    Edvardsson, Bo
    et al.
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration. Karlstad University, Faculty of Economic Sciences, Communication and IT, The Service and Market Oriented Transport Research Group.
    Roos, Inger
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Comparing Customers and providers perspectives on customer relationships Implications for the value perception2009Conference paper (Refereed)
  • 12.
    Edvardsson, Bo
    et al.
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration. Karlstad University, Faculty of Economic Sciences, Communication and IT, The Service and Market Oriented Transport Research Group.
    Roos, Inger
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Customer Complaints and Switching Behavior: A Study of relationship dynamics in a telecommunication company2000Conference paper (Refereed)
  • 13.
    Edvardsson, Bo
    et al.
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration. Karlstad University, Faculty of Economic Sciences, Communication and IT, The Service and Market Oriented Transport Research Group.
    Roos, Inger
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Customer Complaints and Switching Behavior- A study of relationship dynamics in a telecommunication company2003In: Journal of Relationship Marketing, accepted for issue 2 or 3 in 2003Article in journal (Refereed)
  • 14.
    Edvardsson, Bo
    et al.
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration. Karlstad University, Faculty of Economic Sciences, Communication and IT, The Service and Market Oriented Transport Research Group.
    Roos, Inger
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Gustafsson, Anders
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Understanding the Trigger Effect on Customers' Maturity Processes in Telecommunications2002In: QUIS 8: Quality in Services: Crossing Boundaries / [ed] Tax, S; Stuart, I; Brown, S W; Edvardsson, B; Johnston, R; Scheuing, EE,, Victoria, B.C., Canada: University of Victoria , 2002, p. 256-265Chapter in book (Refereed)
    Abstract [en]

    Telecommunication represents the characteristic of a fierce-competitive, dynamic and rapid-growing industry. Through merger mania in a turbulent market telecommunication companies try to improve their control over as many customers as possible (Sumner-Smith and Sumner 1999; Borna 2000; Cobbett and Matthews 2000). These companies are trying to achieve the ultimate attribute of relationship marketing, i.e. long-term relationships with their customers (Grönroos 1989; 2000; Berry 1995; Colgate and Stewart 1998), the application in this industry, however, with disloyal, frequently switching customers seems challenging. Even more difficult is the situation for the companies in the wireless part of the industry with no barriers what so ever to prevent customers from switching. One of the major challenges for the telecom companies is to identify the specific factors appealing to customers willingness to switch between different operators. A longitudinal approach to analysing customers switching processes puts forward and distinguishes the most decisive factors in terms of disloyal behavior. The emerging pattern from that mapping indicates the focus of customer perceptions. That focus is in this study defined as maturity agents. The maturity agents again form the maturing market of a specific market, here telecommunications. Maturing market is hence viewed from the customers perspective in line with the relationship logic. The indicators of the maturing market are per definition instable over time and need therefore to be supported and updated by repeated mapping of customers switching behavior.This paper is based on two empirical studies recently carried out in a large Swedish telecommunication company. The first study was a combined complaint and switching behaviour study (Edvardsson and Roos 2001). Findings of the first study are in this paper compared to findings of the second study consisting of process mapping of the customers switching behavior in the same company. Based on this comparison, factors and combinations of factors were found to work as maturity agents in the customers processes. The purpose of the study is to build a model with the capability to establish and generalise maturity agents and their influence on switching intention. Empirical results of the quantitative study are presented.In sum, a maturity-agent model is presented and quantitatively measured results presented. The maturity-agent model is grounded in the two empirical studies made in the telecommunication company, here labelled The Company, the maturity agents are defined as the factors, which embed the potential to communicate the change of customer perceptions, including both The Company and the context. The maturity agents are likely to change over time accordingly. The identification of these maturity agents may facilitate and support the sharpness of marketing activities carried out in order to build and maintain long-term customer relationships. References:Berry, Leonard (1995), Relationship Marketing of Services - Growing Interest, Emerging Perspectives, Journal of the Academy of Marketing Science, Vol.23, No. 4 (Fall), 236-245.Edvardsson, Bo and Inger Roos (2000): Customer Complaints and Switching Behavior A Study of relationship dynamics in a telecommunication company. Journal of Relationship Marketing, forthcoming 2001.Borna, Claude, 2000. Combating Customer Churn. Telecommunications, Americas Ed. Vol. 34, No. 3, 83-85.Grönroos, Christian (1989a): Defining Marketing: A Market-Oriented Approach. European Journal of Marketing, Vol. 23. No. 1, pp. 52-50.Grönroos, Christian (2000): Grönroos, Christian (2000), Relationship Marketing: The Nordic School Perspective. Jagdish N. Sheth and Atul Parvatiyar, eds, Handbook of Relationship Marketing, London, Sage Publications, 95-118.Sumner-Smith, David and Ian Sumner, 1999. The free-access revolution. Marketing, Vol. 4, March, 29-30.Cobbett, Ray and Mike Matthews, 2000. Its your call. Supply Management, Vol.5, No. 14, 34-35.

  • 15.
    Gustafsson, Anders
    et al.
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Johnson, M. D.
    Roos, Inger
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    The Effects of Customer Satisfaction, Relationship Commitment Dimensions and Triggers on Customer Retention2005In: Journal of Marketing, p. 210-218Article in journal (Refereed)
    Abstract [en]

    Abstract

    In a study of telecom services the authors examine the effects customer satisfaction, affective commitment, and calculative commitment on retention. The study further examines the potential for situational and reactional trigger conditions to moderate the satisfaction-retention relationship. The results support consistent effects of customer satisfaction, calculative commitment and prior churn on retention. Prior churn also moderates the satisfaction-retention relationship. The results have implications for both customer relationship managers and researchers using satisfaction surveys to predict behavior.



    Keywords: Customer Retention, Relationship Management, Customer Satisfaction, Affective Commitment, Calculative Commitment, Triggers, Heterogeneity

  • 16.
    Gustafsson, Anders
    et al.
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Johnson, M.
    Roos, Inger
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Managing Customer Satisfaction, Brand Image, and Strength of Relationship across Switching Paths2003Conference paper (Refereed)
    Abstract [en]

    Managing Customer Satisfaction, Brand Image, and Strength of Relationship across Switching Paths

    The importance that customers place on attributes as drivers of customer satisfaction and loyalty is a critical input to a firms resource allocation strategy and quality improvement efforts. The priority setting process requires two key inputs. One is the relative importance of the various attributes and benefits toward improving customer satisfaction. The other is performance data on the attributes and benefits. These inputs can then be used in an importance-performance analysis, also known as a strategic satisfaction matrix, which determines where a firm should concentrate its resources to improve performance (Martilla and James 1977). The essential aspects to improve are those where importance is high and performance is low. This effectively focuses resources where they have the greatest impact on satisfaction and subsequent loyalty. Those aspects where performance and impact are both high illuminate a firms competitive advantage. Clearly, when both importance and performance are low, customers are telling us not to waste resources improving these areas. The low importance/high performance category may be areas where resources have been wasted in the past because the improvements were not important to customers. Alternatively, these may be drivers of satisfaction that customers consider basic and necessary. This importance-performance logic usually assumes that we measure and model benefits that a company provides to customers. These benefits are then the primary antecedents of customer satisfaction as a type of overall evaluation of the consumption experience. This satisfaction, in turn, influences customers behavioral intentions in the form of a predisposition to repurchase the product or service again (loyalty). The model can be quite elaborate when it comes to benefits and their attributes, but it is the assumed that only customer satisfaction effects loyalty.

    We are now at a time were companies talk about building relationships with their customers and seek a better understanding of how brand equity affects business results. Consequently, there are some new approaches to improving ones Return on Customers (Rust, Zeithaml and Lemon 2000) and customer loyalty modeling (Johnson et al. 2001) that have moved beyond just customer satisfaction to include the effects of brand image or reputation, affective relationship commitment, and calculative relationship commitment on loyalty. In this expanded loyalty model the implications of the importance-performance logic are not so clear. For example, if brand or strength of relationship has a high impact and a low performance, does it make more sense to improve them directly or indirectly via customer satisfaction? The point is that there are more strategic considerations and implications that emerge from a loyalty matrix vis-à-vis a simple satisfaction matrix.

    Furthermore, recent research on switching paths (Roos 1999) shows how a variety of triggering events put customers on a switching path (such as influential triggers, reactional triggers, and situational triggers). These triggers serve as a natural segmentation scheme for companies managing a comprehensive loyalty matrix. What we propose to do in this paper is to merge the two previously mentioned research fields to examine new types of loyalty models for telecom service customers with very different potential switching paths and explore the strategic implications of this more comprehensive analysis. We find that different triggers systematically influence the effect that satisfaction, brand image, and relationship commitment have on loyalty and, as a result, the management different switching paths.

  • 17.
    Gustafsson, Anders
    et al.
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Roos, Inger
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Edvardsson, Bo
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration. Karlstad University, Faculty of Economic Sciences, Communication and IT, The Service and Market Oriented Transport Research Group.
    Customer Clubs in Telecommunications - A Relationship Marketing Perspective2004In: Managing Service Quality 14(2/39), pp 157-168Article in journal (Refereed)
    Abstract [en]

    Abstract

    Similar to most industries telecommunications has introduced customer or loyalty clubs to their customers during a number of years. Customer clubs occurred as negations of the consequences the deregulated market initiated. Customer clubs are a recognizable part of most CRM strategies, their effect on customer loyalty are, however, not obvious. This study presents result on the fact that the majority of the customers included in clubs do not consider their participation to engage them more than before regarding the telecom service provider. In comparison, excluded customers reflect, however, differently on their telecom relationship. This article evaluates two qualitatively conducted studies, in which customer experiences are contrasted against customer switching processes. Based on the qualitative studies some evidence has been quantified regarding responses to customer clubs. The roles of customer experiences as reasons for switching telecom providers are hence revealed and confronted with the customer-club maintenance function on relationships.

    Customers connect loyalty more and more to customer-club programs in their minds because of the offer frequency to them of varying memberships in order to receive benefits of all kinds for being a company-regular customer. Literature suggests different definition of loyalty and retention (Johnson and Gustafsson 2000) specifying that loyalty embeds an extended behavioral loyalty including also attitudinal aspects (Oliver 1997), while retention more is a customer maintenance measure as differing actions for keeping customers (Stauss et al. 2001). McGoldrick and Andre (1997) point out that loyalty should be a long-term strategic goal, and not the subject of a series of short-term tactical schemes . The reason of their statement is that customer preferences change over time and that it is important to be able to include the changes in the definition on loyalty. Oliver (1997) indicates following the same line that loyalty is a deeply held commitment to rebuy or repatronize a preferred product or service consistently in the future, despite situational influences and marketing efforts having the potential to cause switching behaviour (Oliver 1997, p. 392). Such definition disagrees, however, with the relationship perspective. Relationships have been considered dynamic with changing character and the interaction with customers is therefore suggested to be close in order to know the customer Gummesson 1995; Grönroos 1996). Recently, relationships are deliberately suggested to need new forms of reflecting tools in order to capture the dynamism (Roos 2002; Edvardsson et. al 2002). The influence of the context is assigned a considerable significance (Bolton et al. 2000), the competitors, for example, are by the authors established to have a complex impact on customer-relationship dynamism and even cause switching.

    Customer clubs can be argued to be a part of or a way to perform relationship marketing. Relationship marketing was in its early shape a tool for keeping customers instead of continuously focusing on new customers (Berry 1983; Grönroos 1983). In this article we use that original statement and nature of relationship marketing as our basis. However, we do know that tools were lacking for introducing relationship-marketing procedures into companies strategies as the procedures were introduced in the literature. Personnel were considered key factors (Gummesson 1993) and moment-of-truth the marketplace of the mission for learning to know the customer. At the moment, it seems to be more a question of devising schemes. All customers are regular customers of several companies. The main problem is that customers not always are always aware of the difference being a regular customer included in the customer club or just being a customer.

    The purpose

    The purpose of this paper is to deliberately study how customers in a Swedish telecommunication company perceive and identify the customer-club membership in terms of effect on loyalty and retention.

    The role of satisfaction in customer clubs

    An important question regarding satisfaction and customers included in customer clubs is: do these kinds of programs increase customer satisfaction? Bolton et al. (2000) emphasize the importance of understanding the role of satisfaction regarding customer clubs. According to literature (Jones and Sasser 1995; Bolton and Lemon 1999; Bolton 1998) customer clubs have a longitudinal effect on customer relationships if customers perceive the experiences satisfactory. In other words, the usage level become crucial in customer clubs, otherwise customers are not able to build there perceived satisfaction particularly on experiences.

    Bolton (1998) carried out in the cellular communication industry. She argues that constant failures, even if recovery is perceived by customers as satisfactory, decrease the duration of the relationship. In other words, customers update their relationships according to an anchoring and adjustment process. The adjustment process is motivated by the impact of new information, and customers with a long relationship consequently have higher cumulative satisfaction and fewer perceived losses. Those with many perceived losses normally do not have long relationships, according to this study. Therefore, she suggests that service providers should understand early indicators of switching.

    Loyalty

    Concepts such as retention and re-purchasing are frequently used as indicators of loyalty (Dufer and Moulins 1989; Reichheld and Sasser 1990; Bolton and Drew 1991; Cronin and Taylor 1992; Denison and Knox 1993; Reichheld 1996).

    The link between usage, satisfaction and loyalty is in this article highlighted by introducing the influence of comparability of attributes on switching (Keaveney 1995; Bolton 1998; Roos 1999). When alternatives decreases, the likelihood for perceiving the evaluated attributes more satisfactory increases, which in turn has effect on re-purchase (choice) intention. In telecommunication it seems to be crucial to understand the process behind satisfactory perceived experiences. Srinivasan (1987) argues, for example, that customers do not evaluate the technology itself, because it is too complicated for most of them. They only process the technology-change perception, and are not able to evaluate it. Simonson and Tversky (1992) put it in the following way: performance defines the goal of a purchase. Price, for example, which is central in telecommunication-customer perceptions, is merely considered to be a tool with which to achieve the goal. As a consequence, whereas the experience may be perceived of as more important than price, and thus may affect choice probability, the price may affect the extent of choice. Performance uncertainty, which may appear as uncertainty related to possible wrong choices, needs to be reduced in order to facilitate choice. Customers need to feel safe in their purchasing. Nowlis and Simonson (1996) discuss the topic in terms of how different kinds of attributes compete intrinsically based on the ease of comparison. In sum, in order to build strong customer relationships in a business where the products as in telecommunications is rather similar among competitors and additionally difficult to evaluate in terms of rare contacts to the company, satisfactory experiences become important. Therefore it seems necessary and useful to stress the usage of the products both in terms of frequency and up sell. Then the possibility for partly switching (Roos 1999) to a competitor may be reduced and the prerequisite for satisfactory experiences increased.

    The procedure of the qualitative study

    The qualitative part of our study was designed to include both interviews as well as focus groups. The reason for including two different kinds of tools for collecting qualitative data was to achieve appropriate richness regarding understanding the variables behind customers evaluation of the telecommunication companys customer club.

    The basis for the strategic sample was that the included customers had to reach a set volume of telecommunication traffic. Among the 800 customers that met the established conditions we randomly chose 12 customers with customer-club membership and 12 customers representing not members. We interviewed altogether 30 customers of the telecommunication company.

    Additionally to 24 interviews among member and not members of the customer club, ordinary customers were collected for focus groups interviews. The logic behind the two-part qualitative study was partly the maturity regarding richness of variables communicating important issues regarding customer clubs and partly the opportunity it served being able to include customers belonging to differing interest groups. The customers of the focus groups were chosen with the special request of being capable to both describe their membership properly, but also to compare their membership of the telecommunication customer club with other clubs and membership. Therefore, the age became important and customers between 30-55 years were applied for. They had to have a membership of at least 6 months to telecommunication club and additionally one or more other memberships of customer clubs.

    Results

    The overall impression is that customers do not perceive the customer-club membership to add relevant value to their relationship with the telecommunication company. It appears, however, obviously that on the whole, customers in the club differ regarding their evaluation of the telecommunication company. However, there is no clear distinction between perception of customers included in the customer club and customers that have not signed up for a membership. Accordingly, the customer club seems to indirectly add value to the relationship rather than influence retention.

    Verification

    A survey telephone was carried out in order to verify that the variables captured in the previous qualitative studies were relevant. In all the survey covered 898 respondents and the used sample was a representative sample with regards to age and geographical spread of all of The Companys customers. The respondents were asked to rate a number of issues on a 10-grade scale.

    In the sample (Table 1) there were 135 (15%) respondents that stated they were members and 566 (63%) that stated that they were non-members. It was interesting to find that in our sample 197 stated that they did not know whether or not they were members.

    There are 600 000 members for 4 200 000 customers (14 %).

    Table 1. Members and not members of the customer club

    n Percentage

    Member 135 15%

    Non-member 566 63%

    Do not know 197 22%



    If the loyalty club were to have the effects that it was originally intended to have, we would expect that the customers that are members would have higher ratings for the intended loyalty compared to non-members. The measures for intended loyalty that we use in this study can be found in Table 2.

    Given the art of the service, i.e. that the customers do not chose the service provider every time. In the telecom business a customer has the same service provider until he chooses another. The first two measures in Table 2 of intended loyalty is appropriate in this service context. The measures are whether or not the customer would stay on as a customer and that the customers have no reason to switch from the service provider. Generally the members score higher for these questions on intended loyalty. But the differences are only significant for the first measure and not the second one.



    One question measures the intention to switch, and two questions can be considered as measures of intended loyalty. That is if they were choosing today would they chose Telia again. Finally one question measures how faithful they are towards Telia, meaning if they could be a customer to more than one supplier simultaneously.

    If we study Table 2 we find that this is generally the case but the differences between members and non-members are not large enough in order to be significant which in turn makes us question how well the loyalty program actually works. One of the really interesting questions in the quantitative study is whether the respondent or not the respondents could consider having more than one operator at the same time, which is a clear indicator concerning how loyal the respondents really are. The differences between members and non-members are really small for this question.

    Table 2. Satisfaction and differences between members and non-members

    Member Non-member Sig

    Loyalty Continue as a customer to the company 8.14 7.59 0.032

    No reason for switching 7.14 6.69 0.144

    Can consider having more than one operator 6.82 6.88 0.854

    Likelihood of speaking favorably about the company to others 6.46 6.19 0.336

    Likelihood of choosing The company again 6.98 6.69 0.288

    Customer Satisfaction Overall satisfaction 7.37 6.75 0.003

    Performance versus the customers ideal service provider in the category 7.23 6.84 0.055

    Expectancy disconfirmation 6.62 6.50 0.541



    Apart from loyalty we also included attitude questions in the form of customer satisfaction measures in the quantitative study. Since we are working from a relationship perspective we think of customer satisfaction an overall evaluation of the consumption experience. Cumulative customer satisfaction as such is usually measured through three survey measures: overall satisfaction, expectancy-disconfirmation, and performance versus an ideal product or service in the category (Johnson et. al., 2001).

    As can be seen from Table 2 we actually do find significant differences between members and non-members for the customer satisfaction measures, which in turn implies that the loyalty program actually has some effect. Members are overall more satisfied with Telia as a service provider and they are closer to an ideal service provider. There are, however, no difference between the to groups when Telias performance is compared to the respondents expectations.

    The results from this exploratory study both confirm and disconfirm the effects of loyalty programs. The proofs against the loyalty program is that a large share of the population is uncertain whether or not they actually are members in the program, which makes it questionable how attractive a membership really is. Members of the loyalty program does not seem particularly loyal to Telia, although some of the ratings for the loyalty questions are higher it is not significantly higher. The proof in favor of the loyalty program is that the members actually seem to have higher satisfaction ratings which implies that the loyalty program actually has some effect on the members attitude toward Telia.

    References



    Berry, Leonard L. (1983): Relationship Marketing. Emerging Perspectives on Services Marketing. Ed. Leonard L. Berry, Texas A&M University, G. Lynn Shostack, Bankers Trust Company and Gregory D. Upah, Young and Rubicam, pp. 25-28. Chicago: American Marketing Association.

    Bolton, Ruth N. (1998), A Dynamic Model of the Duration of the Customers Relationship with a Continuous Service Provider: The Role of Satisfaction. Marketing Science, Vol. 17, No. 1, 1998, pp. 45-65.

    Bolton, Ruth N. and James H. Drew (1991), A Multistage Model of Customers` Assessments of Service Quality and Value. Journal of Consumer Research, Vol. 17, March.

    Bolton, Ruth N. and Katherine N. Lemon (1999), A Dynamic Model of Customers Usage of Services: Usage as an Antecedent and Consequence of Satisfaction, Journal of Marketing Research, 36 (2), pp. 171-186.

    Bolton, Ruth N., P. K. Kannan and Matthew D. Bramlett (2000), Implications of Loyalty Program Membership and Service Experiences for Customer Retention and Value, Journal of the Academy of Marketing Science, Vol. 28, No. 1, pp. 95-108.

    Cronin, Joseph J., Jr and Steven A. Taylor (1992), Measuring Service Quality: A Re-examination and Extension. Journal of Marketing, Vol. 56, July, pp. 55-68.

    Dufer, Jean and Jean-Louis Moulins (1989), La Relation Entre la Satisfaction du Consommateur et Sa Fidélité à la Marque: Un Examen Critique. Recherche et Application en Marketing, Vol. 4, No 2, pp. 21-36.

    Edvardsson, Bo, Anders Gustafsson och Inger Roos (2002), Understanding the Trigger Effect on Customers Maturity Processes in Telecommunications. In, Service Quality in Service: Crossing Boundaries. Ed. Tax, S, Ian Stuart, Stephen W. Brown, Bo Edvardsson, Robert Johnston and Eberhard E. Scheuing. Canada, Victoria: University of Victoria, Printing and Duplicating Services, pp. 256-265.

    Grönroos, Christian (1983): Marknadsföring i tjänsteföretag. Stockholm: Liber förlag.

    Grönroos, Christian (1996b): Relationship Marketing Logic, The Asia-Australia Marketing Journal. Vol. 4, No. 1, pp. 7-18.

    Gummesson, Evert (1993): Case Study Research in Management. Methods for Generating Qualitative Data. Stockholm: Stockholm University, Department of Business Administration, December 1993, Sweden.

    Gummesson, Evert (1995): Relationsmarknadsföring: Från 4P till 30R (Relationship Marketing: From 4Ps to 30 Rs). Malmö: Liber-Hermods.

    Johnson, Michael D. and Anders Gustafsson (2000), Improving Customer Satisfaction, Loyalty, and Profit. An Integrated Measurement and Management System, Jossey Bass, Inc., San Francisco, California.

    Johnson, Michael D., Anders Gustafsson, Tor Wallin Andreassen, Line Lervik and Jaesung Cha (2001), The Evolution and Future of National Customer Satisfaction Index Models, Journal of Economic Psychology, 22 (2). Pp 217-245.

    Jones, Thomas O. and W. Earl Sasser Jr. (1995), Why Satisfied Customers Defect, Harward Business Review, Vol. 73, November-December 1995.

    Keaveney, Susan M. (1995): Customer Switching Behavior in Service Industries: An Exploratory Study. Journal of Marketing, Vol. 59, April, 1995, pp. 71-82.

    McGoldrick, Peter J., and Elisabeth Andre (1997), Consumer Misbehavior. Promiscuity or Loyalty in Grocery Shopping, Journal of Retailing and Consumer Services, Vol. 4, No. 2, pp. 73-81.

    Nowlis, Stephen M. and Itamar Simonson (1996): The Effect of New Product Features on Brand Choice. Journal of Marketing Research, Vol. XXXIII, February 1996, pp. 36-46.

    Oliver Richard L. (1997), Satisfaction. A Behavioral Perspective on the Consumer, USA: McGraw-Hill.

    Reichheld, Frederick F (1996): The Loyalty Effect: The Hidden Force Behind Growth, Profits, and Lasting Value/Frederick F. Reichheld with Thomas Teal. Boston: Harvard Business School Press.

    Reichheld, Frederick F. and W. Earl Sasser, Jr. (1990), Zero Defections: Quality Comes to Services. Harvard Business Review, Vol. 68, September-October, pp. 105-11.

    Roos, Inger (1999), Switching Processes in Customer Relationships, Journal of Service Research, Vol. 2, No. 1, August 1999, pp. 68-85.

    Roos, Inger (2002), Methods of Investigating Critical Incidents: A Comparative Review, Journal of Service Research, 4, 3, February, 193-204.

    Simonson, Itamar and Amos Tversky (1992): Choice in Context: Tradeoff Contrast and Extremeness Aversion. Journal of Marketing Research, Vol. XXIX, August 1992, pp. 281-295.

    Srinivasan, T., C. (1987): An Integrative Approach to Consumer Choice. Advances in Consumer Research, Vol. XIV, pp. 96-100.

    Stauss, Bernd, Klaus Chojnacki, Alexander Decker and Frank Hoffmann (2001), Retention Effects of a Customer Club, International Journal of Service Industry Management, Vol. 12, No. 1, pp. 7-19.

  • 18. Liljander, Veronica
    et al.
    Roos, Inger
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Customer Relationship Levels-From Spurious to True Relationships2001Conference paper (Refereed)
    Abstract [en]

    Relationship marketing (RM) is usually posited as the opposite of transactional marketing, which is marketing at arms-length without any interaction between producers and individual buyers. Its opposite RM has been seen as the revival of old customs, when buyers and producers were known to each other, and close buyer-seller relations were common practice (Grönroos 1990; Sheth and Parvatiyar 2000). Long-term relationships are believed to be beneficial to both the firm and its customers because it increases the companys productivity and profits (Reicheld 1996) while providing customers with individualised service, customised goods and other relationship benefits that follow from gaining more knowledgeable about customers needs (Berry 1995; Gwinner, Gremler and Bitner 1998).

    Doubts have been raised regarding its applicability for all types of consumer products (Crosby and Stephens 1987; Grönroos 1990), and its desirability by all customers (Berry 1995; Grönroos 2000; Fournier et al. 1998), but it is believed to be specifically well suited for services marketing because of the direct interaction between customers and service providers (Berry 1995; Grönroos 2000). Companies may also need to implement both transaction and RM strategies for different customer segments (Berry 1995).

    RM strategies can vary considerably between services industries and companies, and little is known about which relationship levels lead to positive customer responses and enhance company profitability. Sheaves and Barnes (1996, p 216) note that Many companies have embraced this [RM] concept and have set out to establish customer relationships. Yet, there appears to be little consensus on what it actually means to have a relationship with a customer or how the concept should be implemented. Companies implement it on different levels and separate strategies may be used within the same firm for different customer segments, such as key accounts (Cannon and Narayandas 2000). Berry and Parasuraman (1991) divided RM into three levels, depending on the bonds which are created between the firm and its customers. The lowest level, which is based on financial bonds, offers little competitive advantage to the firm. Parvatyiar and Sheth (2000) also note that RM has been interpreted both narrowly as the implementation of loyalty programs and data base marketing, and more broadly as including information sharing and joint development of goods and services that are in the customers best interest.

    However, customers of different services desire different forms of relationships (Sheaves and Barnes 1996). For instance, highly involved customers of services with credence properties (Sheth and Parvatiyar 1995; Sharma and Patterson 1999) may be especially inclined to form close long-term relationships with one service provider. Hence, RM has to be looked upon as a continuum, with various possible implementations. It is essential to identify different types of customer relationships and investigate their effect on company profitability, customer satisfaction and commitment. By taking a customer perspective, we propose that customer relationships can be described along a continuum ranging from spurious to true relationships, depending on the customers level of satisfaction, trust and commitment.

    Trust and commitment are central in business relationships (Morgan and Hunt 1994), but they are also crucial for understanding customer service relationships (Garbarino and Johnson 1999; Sharma and Patterson 1999; Singh and Sirdeshmukh 2000; Tax et al 1998). Relationships foster trust (Gwinner et al. 1998; Sheth and Parvatiyar 2000), but also cannot develop without a build up of trust between the parties (Berry 1995, Sheaves and Barnes 1996). Trus is especially important for services that are characterised by high performance ambiguity, significant consequentiality and high interdependence between the parties, such as medical service and car repair (Singh and Sirdeshmukh 2000). The intangibility and heterogeneousness of services, combined with a spread of consumer distrust in companies, positions trust as perhaps the single most powerful relationship marketing tool available to the company (Berry 1995, p. 242). This sentiment is echoed by Hart and Johnson (1999), who advocate the absence of trust defects as the most important factor in explaining customer commitment to service companies.

    Trust in services is built by continuously experiencing high process and outcome quality (Sharma and Patterson 1999), as well as by frequent and open, two-way communication between the parties (Berry 1995; Sharma and Patterson 1999). The importance of communication for relationship strength has been stressed in industrial buyer-seller relationships (Morgan and Hunt 1994) while it has been largely ignored as a value-adding component in RM (Crosby and Stephens 1987).

    In this paper we look at RM from the customers point of view. The purpose of the paper is to show that customer relationships may exist at different levels, ranging from spurious to true relationships. We do this with a literature review that emphasises trust and commitment. Empirical research is needed to identify relationship levels for different services and customer groups and to evaluate the success of RM strategies. However, the present paper is limited to a preliminary theoretical framework for conducting future research.

    First, a distinction is made between two extreme relationship levels, spurious and true relationships. Next, customer commitment and trust will be discussed in some detail, while service satisfaction and communication effectiveness will be given less attention. Last, relationship levels will be related to levels of trust and commitment.

  • 19. Liljander, Veronica
    et al.
    Roos, Inger
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Two Strategies and Their Effect on Consumer Trust, Satisfaction and Commitment2000Conference paper (Refereed)
  • 20.
    Roos, Inger
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Methods of Investigating Critical Incidents: A Comparative Review2002In: Journal of Service Research, Vol. 4, No. 3, February, pp. 193-204Article in journal (Refereed)
    Abstract [en]

    ABSTRACT

    The methods used for analysing customer relationships have traditionally focused exclusively on service encounters. Recently, researchers have presented these service encounters as a flow or process, although without taking time into account. Both of these perspectives on customer relationships have provided the means for developing a process-based method that does take time into account. This makes it possible to analyze and describe a customer relationship in which effects and consequences can be represented, and the influenced and influencing factors prioritized. Given that the domain for analyzing the customer relationship is a switch from one service provider to another, the consequence is clear. The switch is identical to the consequence. The consequence, again, defines the criticality. Criticality and context are key concepts in the search for a deeper understanding of customer relationships, and efforts are made to include them in the development of the methods put forward in this article.

    Keywords: SPAT, method development, critical incidents, customer relationships, switching behavior

  • 21.
    Roos, Inger
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration. Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center.
    Segmentering av kunder i ett byteperspektiv2012In: Marknadsföring i tjänsteekonomin / [ed] Per Echeverri & Bo Edvardsson, Gylling: Naryana Press och Lund: Studentlitteratur , 2012, 2Chapter in book (Other academic)
  • 22.
    Roos, Inger
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    SPAT-Switching Path Analysis Technique2001Conference paper (Refereed)
    Abstract [en]

    Abstract



    Critical incidents have been acknowledged as embedding useful information concerning customer behavior during decades of research. Knowledge of customer switching gained from critical incidents has been approached from different angles. Concepts such as service quality, complaining behavior and service recovery have been used as a basis, and the implications for relationships have been inferred (LaBarbera and Mazursky 1983; Simonson and Tversky 1992; Headly and Miller 1993; Heskett et al. 1994; Strandvik and Liljander 1994; Zeithaml et al. 1996; Rust et al. 1997; Stauss and Neuhaus 1997; Grönroos 1990; Singh 1990; Bolton and Drew 1991; Oliva et al. 1992; Blodgett et al. 1995; Jones and Sasser 1995; Reichheld 1996; Oliver 1997; Bejou and Palmer 1998; Edvardsson and Roos 2001). The methods applied in the studies have followed the tradition of the original literature. It is only recently that switching behavior has been specifically focused on. The static and episodic focus in this study, however, is on relationship dynamics and a new method was required. The CIT technique (Flanagan 1954; Edvardsson 1992; Bitner, Booms and Tetreault 1989; Stauss 1993; Keaveney 1995; Bansal and Taylor 1999) has developed into SPAT- The Switching Path Analysis Technique (Roos 1999a and b). It succeeds in reflecting both the process of customer switching from one service provider to another and the dynamism on the switching path. The use of SPAT resulted in a Catalytic Switching Model, which revealed deliberate changes of behavior in customer relationships.

    From a managerial standpoint, understanding customer switching paths establishes a basis for being able to see individuals among customers. They form customer segments that are firmly and fundamentally based on the particularities embedded in every service provider and industry. Customer switching paths provide information of a certain nature. They show a preference change by the customer that is related to both the industry and the customers own life. The industry change involves both competitors and trends, while the personal-life change includes shifts in economic and demographic circumstances. The customer-switching path is based on actual behavior, and is updated through an anchoring and adjustment process in terms of customer-perceived changes in their own living and their perceptions of the service provider.

    The instruments of The Switching Path Analysis Technique

    The analysis of a switching path focuses on; The trigger, The initial state, The process and The outcome. The outcome stage includes the kind of switching a customers behavior indicates. The process describes the switching-determinant configuration. The initial state describes the relationship length, thus touching on customer involvement and commitment. The trigger indicates the sensitive factors influencing customer-behavior change. The tools included in SPAT are an interview guide, analysis (code system), and techniques for reporting the findings.

    1. The interview guide was put together with the objective of giving the interviewees the opportunity to tell their switching stories with minimum influence from the interviewer.

    2. The analyse stage in SPAT could begin by identifying whether the customer has made a revocable, a conditional revocable or an irrevocable switching decision (Re path, ReC path or Ir path. These switching paths indicate whether the customer aims to go back to the switched-from service provider or not. The switching paths differ according to the kind of trigger, in combination with the switching-determinant configuration directing the customer on the path. A situational trigger is something outside the switched-from service provider that has increased the sensitivity of the situation, frequently involving changes in the demographic or economic circumstances of the customer. An influential trigger operates when conditions in the switched-to service provider act as a comparison standard for the switching customer. The reactional trigger influences the customers sensitiveness to matters inside the switched-from service provider.

    Switching determinants are of three kinds: a pushing determinant, a swayer, and a pulling determinant.

    Switching-determinant configuration

    In the switching-determinant configuration the switching determinants appear distinct. In such a configuration the dynamism of the switching path means its energy and direction. This is not fuelled by only one switching determinant, but frequently by all three kinds: a pusher, a swayer and a puller. The change over time, and the energy and direction, are connected to the trigger, which in turn provides the configuration with energy and direction. This energy may appear as customer complaints, for example, which may cause customer emotions. A change in the trigger may imply that a new switching-determinant configuration is advancing the switching path.

    The pushing determinant is defined as the switching determinant that is perceived by the customer as the reason for switching to another service provider.

    A swayer does not cause switching by itself. It has no power of its own to provoke switching or returning. It only mitigates or strengthens the switching decision, and may be positive or negative. In other words, it may strengthen the switching or mitigate it.

    The pulling determinant explains why customers go back to the service provider from which they have recently switched.

    Other switching-paths factors include the length of the relationship, the length of the switching decision, emotions and complaining. The value of such factors is that they reveal customer involvement and commitment (Roos 1999c), which has implications in the categorization of customer paths into Re, ReC and Ir paths.

    Triggers segmenting customers according to their switching behavior

    Three kinds of trigger were distinguished: the situational, the interactional and the reactional. The following three customer segments characterized by actual behavior on the switching path, were formed. (1) Something happened to the customers which they found difficult, almost impossible, to influence: Situational customers. (2) Customers were influenced by something which made it easier for them to patronise a certain service provider: Influential customers. (3) Customers reacted to some kind of deterioration which was connected to the service provider: Reactional customers.

    Situational customers are made perceptive to switching by something outside the service that has increased the sensitivity of the situation within it. This may not be immediately connected to the service, or to the service provider.

    Influential customers are sensitive to conditions by the switched-to service provider and act as comparison standards. An influential trigger may be connected to purchasing, or it may be a new alternative in the form of a competitor, or a competitor who has changed or improved its concept. A credit card or a loyalty card may also constitute an influential trigger.

    Reactional customers declare their sensitiveness to matters inside the firm. This may be related to deterioration in the service quality or in the range of goods. At some stage during this process of deterioration, the customer wakes up and takes stock of the situation.

    Identifying customer-switching paths seems to produce new information on customer behavior. The switching perspective deepens our knowledge of the relationship between customers and their service providers. The reason why these deeper insights emerge may be connected with the dynamic approach to studying actual behavior. This unique combination was realized following the modification of a method. We should not neglect careful reconsideration of methods and their potential for providing new results when we adopt new approaches.

    References:

    Bansal, Harvir S. and Shirley F. Taylor (1999): The Service Provider Switching Model (SPSM). A Model of Consumer Switching Behavior in the Service Industry. Journal of Service Research, Vol.2, No. 2, November 1999, pp.200-218.

    Bejou, David and Adrian Palmer (1998): Service failure and loyalty: an exploratory empirical study of airline customers. Journal of Services Marketing, Vol. 12, No. 1, pp. 7-22.

    Bitner, Mary Jo, Bernard H. Booms and Mary Stanfield Tetreault (1989): Critical Incidents in Service Encounters, Designing a Winning Service Strategy, Mary Jo Bitner and Lawrence A. Crosby, eds. Chicago: American Marketing Association, pp. 89-99.

    Blodgett, Jeffrey G. and Wakefield, K., L., and Barnes, J., H., (1995): The effects of customer service on consumer complaining behavior. Journal of Service Marketing, Vol. 9, No 4 1995 pp. 31-42.

    Bolton, Ruth N. and James H. Drew (1991), A Multistage Model of Customers` Assessments of Service Quality and Value. Journal of Consumer Research, Vol. 17, March.

    Edvardsson, Bo (1992): Service Breakdowns, A Study of Critical Incidents in an Airline. International Journal of Service Industry Management, Vol. 3, No.4, 17-29.

    Edvardsson, Bo and Inger Roos (2001): Customer Complaints and Switching Behavior A Study of relationship dynamics in a telecommunication company. Journal of Relationship Marketing, forthcoming 2001.

    Flanagan, John C. (1954), The Critical Incident Technique, Psychological Bulletin, Vol. 51, No. 4, pp.327-358.

    Grönroos, Christian (1990), Service Management and Marketing. Toronto: Lexington Books.

    Headley, Dean E. and Stephen J. Miller (1993), Measuring Service Quality and its Relationship to Future Consumer Behavior. Journal of Health Care Marketing, Winter 1993, Vol. 13, No. 4, pp. 32-39.

    Heskett, James L., Thomas O. Jones, Gary W. Loveman, W. Earl Sasser, Jr. and Leonard A. Schlesinger (1994), Putting the Service-Profit Chain to Work. Harvard Business Review, March-April 1994, pp. 164-174.

    Jones, Thomas O. and W. Earl Sasser Jr. (1995), Why Satisfied Customers Defect, Harward Business Review, Vol. 73, November-December 1995, pp. 88-99.

    Keaveney, Susan M. (1995), Customer Switching Behavior in Service Industries: An Exploratory Study. Journal of Marketing, Vol. 59, April, 1995, pp. 71-82.

    LaBarbera, Priscilla A. and David Mazursky (1983), A Longitudinal Assessment of Consumer Satisfaction/Dissatisfaction: The Dynamic Aspect of the Cognitive Process. Journal of Marketing Research. November 1983.

    Oliva, Terence A., Richard L. Oliver and Ian C. MacMillan (1992), A Catastrophe Model for Developing Service Satisfaction Strategies. Journal of Marketing, Vol. 56, July 1992, pp. 83 - 95.

    Oliver, Richard L. (1997), Satisfaction. A Behavioral Perspective on the Consumer. USA: McGraw-Hill.

    Reichheld, Frederick F (1996), The Loyalty Effect: The Hidden Force Behind Growth, Profits, and Lasting Value/Frederick F. Reichheld with Thomas Teal. Boston: Harvard Business School Press.

    Roos, Inger (1999a), Switching Paths in Customer Relationships. Doctoral Dissertation, Publications of the Swedish School of Economics and Business Administration, No. 78, Helsinki, Finland.

    Roos, Inger (1999b), Switching Processes in Customer Relationships. Journal of Service Research, Vol. 2, No. 1, August 1999, pp. 68-85.

    Rust, Roland T., J. Jeffery Inman and Jianmin Jia (1997), Customer Expectation Distributions: A Dynamic Model, Theoretical Implications, and Empirical Evidence. Paper presented at Frontiers in Service Conference, USA, Nashville TN, October 2-4, 1997, organized by the Center for Service Marketing at Vanderbilt University and American Marketing Association.

    Simonson, Itamar and Amos Tversky (1992), Choice in Context: Tradeoff Contrast and Extremeness Aversion. Journal of Marketing Research, Vol. XXIX, August 1992, pp. 281-295.

    Singh, Jagdip (1990), Voice, Exit, and Negative Word-of-Mouth Behaviors: An Investigation Across Three Service Categories. Journal of the Academy of Marketing Science, Vol. 18., No 1, pp. 1-15.

    Stauss, Bernd (1993): Using the Critical Incident Technique in Measuring and Managing Service Quality. In E Scheuing, and William F. Christopher (eds.) The Service Quality Handbook, New York: American Management Association, pp. 408-427.

    Stauss, Bernd and Patricia Neuhaus (1997), The Qualitative Satisfaction Model, International Journal of Service Industry Management, Vol. 8, No. 3, pp. 236-249.

    Strandvik, Tore and Veronica Liljander (1994), Relationship Strength in Bank Services. Proceedings from the 1994 Research Conference on Relationship Marketing: Theory, Methods and Applications. Jagdish N. Sheth, Atul Parvatiyar, eds. June 11-13, 1994, Atlanta, Georgia.

    Zeithaml, Valarie, Leonard L. Berry and A. Parasuraman (1996), The Behavioral Consequences of Service Quality. Journal of Retailing, Vol. 60, April, pp. 31-46.

  • 23.
    Roos, Inger
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    The Nature of Customer Support Service2007Conference paper (Refereed)
    Abstract [en]

    Regardless of whether companies consider themselves as manufacturing or service producing companies, today nearly every company offers customer support in some form. Despite the frequent presence of customer-support service in companies the understanding of how customers experience the use of it in their interactions with companies is vague. In recent studies where service has been discussed (Grönroos 2006; Edvardsson et al. 2005; Lovelock and Gummesson 2004; Vargo and Lusch 2004a; 2004b), one important aspect has been to stress context specific and even company specific issues. Therefore it is relevant to examine a specific service related to a specific industry. Such a service is what most industries have included in their offerings and most customers have experienced; customer support service.

    The purpose of this article is to understand the applicable mechanism of customer support service as it is perceived by the customers, i.e. its development and appearance from the customers point of view. The relationships strength is the departure and the dynamic picture including the core service and customer support service the focus.

    Customer support service was studied from the customers perspective by interviewing 70 telecom customers about what role the support service has in their relationships in comparison with the core service/product. The results indicate that customers assessments of customer-support service drive surprisingly often the relationships whereas the core service, correspondingly, has a minor role for the relationship continuation. It looks like the dynamism of the customer perceptions of the core and support service dimensions needs to be understood in order to capture the customers reality. The dynamism was revealed by applying a modification of the SPAT method (Switching Path Analysis Technique), SPAT-mechanism, to the 70 interviews and contrasted to a static content analysis of 1900 customers support-service contacts in order to learn from the differences between the two approaches and their result generating capabilities.

    The contribution of the study is that customers do not carry a static picture of the core and support service configuration. On the contrary, according to their frame of references and for its situational purpose customers experience a dynamic entity. Despite the presence of customer support service in almost all companies it has rarely been focused on in marketing research. Contiguous studies again often separate the support dimension from the overall picture of service in the same way as do the company organizations generally; thus, separate functions in separated departments or units.

    Based on the results of the analysis using the SPAT-mechanism and by emphasizing the customers perceptive, the following was confirmed; the definition of customer support service in telecom was possible to establish as to both its nature and its role in the relationships consequently for the strength. In order to make a comparison that either verifies or challenges such an assumption, a comparison study based on a static content analysis was carried out in order to compare the results of a dynamic analysis to the static. If a method had been used excluding the option of considering the relationship dynamism and strength, the results show that it might neither have been possible to define the dynamism of the customer support service nor determine its role for relationship strength. However, by applying the dynamic mechanism the contribution regarding the understanding of customer-support service in telecom was broadened. Support service has no static definition from the customers point of view; it rather is embedded in the core product and highly related to customers value-in-use (Bitner and Brown 2006). The comprehension of the results of the present study has implication for how companies should design their support service in order to really support the customers.

    References:

    Bitner, Mary Jo and Stephen W. Brown (2006), The Evolution and Discovery of Service Science in Business Schools, Communication of the ACM, (July), 73-78.

    Edvardsson, Bo, Anders Gustafsson and Inger Roos (2005, Service Portraits in Service Research - A Critical Review, International Journal of Service Industry Management 16 (1), 107-121.

    Grönroos, Christian (2006), Adopting a Service Logic for Marketing, Marketing Theory, 6 (3), 317-111.

    Lovelock, Christopher and Gummesson, Evert (2004) Whither Services Marketing? In Search of a New Paradigm and Fresh Perspectives, Journal of Service Research, 7 (1), 20-41.

    Vargo, S. L. and Lusch, R. F. (2004a) Evolving to a New Dominant Logic of Marketing, Journal of Marketing 68 (January 2004), 1-17.

    Vargo, S. L. and Lusch, R. F. (2004b) The Four Service Marketing Myths Remnants of a Goods-Based, Manufacturing Model, Journal of Service Research 6 (4), 324-335.

  • 24.
    Roos, Inger
    et al.
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Edvardsson, Bo
    Comparing Customer and Service Provider Perspectives of Customer Relationships Implications for Value Perception,2009Conference paper (Refereed)
    Abstract

    Abstract

    Recent findings in telecom studies indicate that traditional customer-relationship research has omitted the fact that customers and service-providers perspectives on relationships often do not coincide regarding the contents, boundaries and continuation. Findings in two studies on emotions indicate that customers experiences and perceptions in their current relationships to some extent stem from their earlier and switched-from relationships (Ganesh et al. 2000; Roos et al. 2008; 2009). This knowledge is based on studies of individual relationships over time (longitudinal study) including the customers switches from service providers and initiations of new relationships during seven years. In the same way a longitudinal study on frequent switchers show that the relationship history on the individual level follow a given pattern indicating the connection between the relationships in terms of loyalty (Roos and Gustafsson 2007). The information carried by customers between relationships are labeled triggers and defined as holding the sensitivity of customer relationships (ibid.). Consequently, the triggers harboring the sensitivity for both perceptions and behavior (Roos and Gustafsson 2007) are likely to play an important role when looking for differences in perspectives on customer relationships.

    The aim of this paper is to empirically define and analyze differences regarding customers and service providers scopes and perceptions of the focal relationships.

    The study has three main contributions. First, the differences in perspectives between service providers and customers are demonstrated through empirical results. Second, the point of interest concerning the difference is identified and defined as triggers. Third, the importance of understanding the difference is put forward. For example, triggers are perceptible by customers while service providers do not possess this ability, which means that customers perceive the sensitivity in relationships while service providers do not. The implication of the difference is that concepts related to perceptions such as value are seen in a new light. A question rises regarding whether customers or service providers value perceptions have been applied in traditional studies on value.

  • 25.
    Roos, Inger
    et al.
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Edvardsson, Bo
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration. Karlstad University, Faculty of Economic Sciences, Communication and IT, The Service and Market Oriented Transport Research Group.
    Customer support service: A relationship perspective2008In: Managing Service Quality, Vol. 18, No. 1, pp. 87-107Article in journal (Refereed)
    Abstract [en]

    Extended Abstract

    Purpose: The purpose of this article is to describe customers perception of customer support service related to the core service in telecom customer relationships. The customers perceptions of the support-service stem from their contacts with the support service and are related to the importance for the relationship with the telecom provider.

    Approach/Methodology: We used a modified version of SPAT (Switching Path Analysis Technique) in our analysis to create the necessary data for carrying out a dynamic analysis - in other words customers experiences of the customer-support service over time in their relationship with the service provider. The modification, called the SPAT mechanism, only focused on the difference between driving and non-driving factors related to the relationship strength.

    Findings: From the service perspective we found that some of the customers in the present study were particularly focused on the customer-support, which made it dominate the relationships. At that special time, their telecom service predominantly comprised customer support, which was more important than the core service. At other times, when the support-service focus was not as strong, the priority was likely to be different. Consequently, the composition of the telecom service and the core service is according to customers expressions dynamic and only the customer perspective has the authority to define it.

    Research limitations: Research on service has been going on for several decades, and thus offers a great variety of findings from cross-sectional studies. Therefore, the present studys presentation of only one kind of service could be considered limited.

  • 26.
    Roos, Inger
    et al.
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Edvardsson, Bo
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration. Karlstad University, Faculty of Economic Sciences, Communication and IT, The Service and Market Oriented Transport Research Group.
    Gustafsson, Anders
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Customer Switching Patterns in Competitive and Non-competitive Service Industries2004In: Journal of Service ResearchArticle in journal (Refereed)
  • 27.
    Roos, Inger
    et al.
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Edvardsson, Bo
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration. Karlstad University, Faculty of Economic Sciences, Communication and IT, The Service and Market Oriented Transport Research Group.
    Wägar, Karolina
    Ravald, Annika
    Extending Understanding of Customer Relationship Stability: The Concept of The Blind Spot in Service Research2011Conference paper (Refereed)
    Abstract

    ABSTRACT

    This paper introduces the blind spot as a concept in service research. In the customer-relationship context the blind spot refers to the service providers inability to grasp the divergence between the customers patronage behavior, relationship perceptions and relational mode, and the temporal lability inherent in them. Consequently, the service provider makes a misestimation of the stability of the customer relationship. This constitutes a major challenge for service providers in their efforts to create customer value and develop relationships in order to maintain a loyal customer base. In addressing the challenge the writers develop the notion of blind spots in customer relationships, assess their consequences and propose a set of guidelines in order to reduce their effects.

  • 28.
    Roos, Inger
    et al.
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Friman, Margareta
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Psychology. Karlstad University, Faculty of Economic Sciences, Communication and IT, The Service and Market Oriented Transport Research Group.
    Emotional Experiences in Customer Relationships: a Telecommunication Study2008In: International Journal of Service Industry Management, Vol. 19, No. 3, pp. 281-301Article in journal (Refereed)
    Abstract [en]

    Abstract

    Purpose: This study aims at deepening understanding of the role of emotion in customer switching processes and identifying the relative frequency of negative discrete emotions in terms of different triggers.

    Approach/Methodology: Customers of Swedish telecommunications services were interviewed about their switching processes. The interviews were analyzed according to SPAT (Switching Path Analysis Technique), which divides relationships into different stages in accordance with their relevance to the relationship strength. The ultimate focus is on self-reported emotions embedded in the switching process.

    Findings: The main finding was that the identified emotions was located in the trigger part of the relationship, and was expressed by the respondents during the switching process in form of Annoyance, Anxiety, Disappointment, Dissatisfaction, Distress, Depression, Rage, Stress and Tension.

    Research limitations: The empirical study is conducted within the telecom industry which may influence the switching frequency because of the deregulations in the beginning of this decade. Our interpretation of valence and activation was based on theoretical assumptions about where various discrete emotions are located on a continuum.

  • 29.
    Roos, Inger
    et al.
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Friman, Margareta
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Psychology. Karlstad University, Faculty of Economic Sciences, Communication and IT, The Service and Market Oriented Transport Research Group.
    Edvardsson, Bo
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration. Karlstad University, Faculty of Economic Sciences, Communication and IT, The Service and Market Oriented Transport Research Group.
    Emotions and Stability in Telecom-customer Relationships2008Conference paper (Refereed)
  • 30.
    Roos, Inger
    et al.
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Friman, Margareta
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Psychology. Karlstad University, Faculty of Economic Sciences, Communication and IT, The Service and Market Oriented Transport Research Group.
    Edvardsson, Bo
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration. Karlstad University, Faculty of Economic Sciences, Communication and IT, The Service and Market Oriented Transport Research Group.
    Emotions and Stability in Telecom-customer Relationships2008In: Journal of Service ManagementArticle in journal (Refereed)
  • 31.
    Roos, Inger
    et al.
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Friman, Margareta
    Edvardsson, Bo
    Perceived Affective Feelings in Service Relationships: A Study of Triggers in Switching Processes2006Conference paper (Refereed)
    Abstract [en]

    ABSTRACT

    This study deals with the challenging area of customer reactions, in service research labelled customers emotional reactions in relationships. The impact of emotions on customer relationships has occurred sporadically in service research for about two decades. In this study, affective feelings are connected to customer switching processes in telecom relationships. However, not many empirical studies have been carried out. The combination of affective feelings and switching processes has been neglected in the literature. Affective feelings, however, may be a major potential addition to our understanding of customer relationships, in terms of their stability. Customers affective feelings related to actual switching behavior may reveal new insights into different categories of switching processes. Affective feelings may also deepen our knowledge of similar switching-process categories in cases where different emotions are expressed. Accordingly, the emotion-related knowledge can be of significance to subsequent behavior in customer relationships. In other words, our understanding of the stability function of the relationships may benefit from the findings.



    Keywords: Service relationships, Switching process, Trigger, Affective feelings

  • 32.
    Roos, Inger
    et al.
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Friman, Margareta
    Edvardsson, Bo
    Perceived Affective Feelings in Service Relationships: A Study of Triggers in Switching Processes2006Conference paper (Refereed)
    Abstract [en]

    ABSTRACT

    This study deals with the challenging area of customer reactions, in service research labelled customers emotional reactions in relationships. The impact of emotions on customer relationships has occurred sporadically in service research for about two decades. In this study, affective feelings are connected to customer switching processes in telecom relationships. However, not many empirical studies have been carried out. The combination of affective feelings and switching processes has been neglected in the literature. Affective feelings, however, may be a major potential addition to our understanding of customer relationships, in terms of their stability. Customers affective feelings related to actual switching behavior may reveal new insights into different categories of switching processes. Affective feelings may also deepen our knowledge of similar switching-process categories in cases where different emotions are expressed. Accordingly, the emotion-related knowledge can be of significance to subsequent behavior in customer relationships. In other words, our understanding of the stability function of the relationships may benefit from the findings.



    Keywords: Service relationships, Switching process, Trigger, Affective feelings

  • 33.
    Roos, Inger
    et al.
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Grönroos, Christian
    The Service Quality Path: A Longitudinal Service Quality Study with Implications for Image and Relationship Marketing2000Conference paper (Refereed)
    Abstract [en]

    Inger Roos and Christian Grönroos



    Abstract



    Customer perceptions concerning service quality are traditionally measured on technical or functional dimensions, tangibles, reliability, responsiveness, assurance and empathy. The same dimensions are suggested also by the literature of Image and Relationship marketing. Lately studies on service quality related to customer relationships have been presented. These studies, however, have rarely been able to distinguish between priorities of quality dimensions concerning the effect on relationships. In a switching perspective, however, customer perception on the relationship is seen as expressed reasons for leaving it. These reasons occur as dynamic configurations of customer switching behaviour connected to influencers who are considered important for customers changed behaviour. In this article, customer actual switching behaviour is compared to customer-quality perceptions. Based on this comparison customers are suggested to constantly being on a service quality path. Such a path organises the concepts of Image and Relationship marketing into a comprehensive dialogue with the customers. The service quality path comprises the concepts of Image and Relationship by delegating different missions to the same dimensions.



    Keywords: Service quality, Switching behaviour, Service-quality path, Image, Relationship marketing, Customer-perception configurations,

  • 34.
    Roos, Inger
    et al.
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Gustafsson, Anders
    Active and Passive Customers2008Conference paper (Refereed)
    Abstract [en]

    Active and Passive Customers in Customer Relationships

    Inger Roos and Anders Gustafsson

    Activity and Passivity in customer relationships has to our knowledge not been studied to date in the marketing field of research. Some customers actively search for new alternatives, while others seem to passively linger in their current relationships but are still ready to switch as soon as they are contacted by a competitor. The knowledge embedded in the difference and nature of Active and Passive customers may add both to the immediate knowledge of customer relationships and loyalty. Recent research (Roos and Gustafsson 2007) has in a qualitative study put forward the importance of knowing the difference between activity and passivity regarding switching customers for their subsequent behavior. The purpose of this article is to analyze customer-switching processes regarding their differences between whether the customers were active or passive during the cognitive processes leading to either stability or instability in their individual customer relationships.

    In the psychology literature, it is widely accepted that cognitive processes and states can be unconscious, occurring below awareness, or implicit, occurring without attention or intention (Winkielman and Berridge 2004). People unconsciously process information that can impact their judgments, motivations, choices, behaviors, and feeling (Dijksterhuis et al. 2005; Simonson 2005). Considerable research attention has been devoted to aspects of choice that are conscious, while limited attention has been paid to those that lie outside of conscious awareness (Fitzsimmons et al. 2002). Active customers seem to make deliberate switches that generate stability in new relationships while the situation for the future when passive customers switch is unstable new relationships.

    Crucial and unique for research communities is access to longitudinal data, i.e., customer switching behavior over a long period of time which is the situation for our research team and departure point for the present study. The possibility of following 128 customers switching processes on an individual level regarding the development of relationships, their switching behavior, their initiating of new relationships, and the new relationships development after the switches enables patterns to show. The present study focuses on quantitative analyses of the data for finding an understanding of the relationship flow and development on the individual level over a longer period of time. Not only the relationship between one telecom operator and the customers is analyzed, we study switching at an individual level across a number of operators and determine differences in the process leading to either stability or instability in the customer relationships. In sum, the differences between whether customers cognitive processes are conscious or unconscious may have a great impact on the stability of customer relationships. However, unconscious processes may be better understood through the comparison of customer assessments of the service provider affected of either conscious or unconscious processes.

    Dijksterhuis, Ap, Pamela K. Smith, Rick B. van Baaren, and Daniel H. J. Wigboldus (2005), "The Unconscious Consumer: Effects of Environment on Consumer Behavior," Journal of Consumer Psychology, 15 (3), 193-202.

    Fitzsimmons, Gavan J., J. Wesley Hutchinson, Patti Williams, Joseph W. Alba, Tanya L. Chartrand, Frank K. Kardes, Geeta Menon, Priya Raghubir, J. Edward Russo, Baba Shiv, and Nader T. Tavassoli (2002), "Non-Conscious Influences on Consumer Choice," Marketing Letters, 13 (3), 269-79.

    Roos, Inger and Anders Gustafsson (2007), "Understanding Frequent Switching patterns - a Crucial Element in Managing Customer Relationships, accepted for Journal of Service Research, August 2007.

    Simonson, Itamar (2005), "In Defense of Consciousness: The Role of Conscious and Unconscious Inputs in Consumer Choice," Journal of Consumer Psychology, 15 (3), 211-17.

    Winkielman, Piotr and Kent C. Berridge (2004), "Unconscious Emotion," Current Directions in Psychological Science, 13 (3), 120-23.

  • 35.
    Roos, Inger
    et al.
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Gustafsson, Anders
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Deepening the Understanding of Switching Paths ' Redefining the Influential Trigger2005Conference paper (Refereed)
  • 36.
    Roos, Inger
    et al.
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration. Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center.
    Gustafsson, Anders
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    The influence of active and passive customer behaviour on switching in customer relationships2011In: Managing Service Quality, ISSN 0960-4529, E-ISSN 1758-8030, Vol. 21, no 5, p. 448-464Article in journal (Refereed)
    Abstract [en]

    Purpose – The purpose of this study is to examine the relationship between active/passive customer behavior and loyalty (responses to switching triggers) in customer relationships.

    Design/methodology/approach – A longitudinal study (seven years) is undertaken of the roles of various triggers and active/passive customers in analyzing the processes that lead to customers changing their service provider in the context of the Swedish telecommunications retail industry.

    Findings – Triggers affect customers' evaluations of service in different ways and cause varying kinds of behavior, depending on whether the customers are active or passive in their customer relationships.

    Originality/value – The study offers new insights into the difference between active and passive customers, which facilitates the design of loyalty-enhancing communications between providers and their customers.

  • 37.
    Roos, Inger
    et al.
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Gustafsson, Anders
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Understanding Frequent Switching Patterns - a Crucial Element in Managing Customer Relationships2007In: Journal of Service ResearchArticle in journal (Refereed)
    Abstract [en]

    Given the growing competition in the global market, it is becoming increasingly important for companies to retain their existing customers, i.e., to pre-empt frequent switching. A fruitful way of gaining more knowledge about customers switching behavior is to examine the role of various factors in their switching processes. This qualitative study, based on data from telecom operators, offers new insights by identifying and defining the role of prejudice in customers rationale for leaving one telecom operator in favor of another. The research also identifies whether the customers are actively or passively engaged in the switching process, which seems to be important in terms of linking prejudice to frequent switching. The findings have important implications for the successful management of customer relationships since they point to instability in customer populations

  • 38.
    Roos, Inger
    et al.
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Gustafsson, Anders
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Edvardsson, Bo
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration. Karlstad University, Faculty of Economic Sciences, Communication and IT, The Service and Market Oriented Transport Research Group.
    Defining Relationship Quality for Customer-driven Business Development - a Housing-mortgage Company Case,2006In: International Journal of Service Industry ManagementArticle in journal (Refereed)
  • 39.
    Roos, Inger
    et al.
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Gustafsson, Anders
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Edvardsson, Bo
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration. Karlstad University, Faculty of Economic Sciences, Communication and IT, The Service and Market Oriented Transport Research Group.
    Defining Service Quality for a Customer-Driven Busines development ' A House-Mortage Company Case2005In: Paper presented at the ServSig conference in Singapore June 2 – 4, 2005Article in journal (Refereed)
  • 40.
    Roos, Inger
    et al.
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Gustafsson, Anders
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Edvardsson, Bo
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration. Karlstad University, Faculty of Economic Sciences, Communication and IT, The Service and Market Oriented Transport Research Group.
    Defining Service Quality for Business-Driven Service Development - A Housing Mortage Company Case2005Conference paper (Refereed)
  • 41.
    Roos, Inger
    et al.
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Gustafsson, Anders
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Edvardsson, Bo
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration. Karlstad University, Faculty of Economic Sciences, Communication and IT, The Service and Market Oriented Transport Research Group.
    The Role of Customer Clubs in Recent Telecom Relationships2004Conference paper (Refereed)
    Abstract [en]

    In a qualitative study of telecommunications customers we unexpectedly found that they combined only certain elements of their whole customer-club interest in their stay-or-leave relationship deliberations. The results of this study suggest a twofold role, the affective and the calculative, in the keeping function of the customer club. Only the affective role showed immediate implications for loyalty. Both roles serve the stability of the relationships, but in categorically different ways. Quite apart from this twofold effect on loyalty, the club seems to have an additional function, attracting, that customers use when they communicate and articulate it more generally. Conceptually, the findings made us re-consider the frequency concept. Frequency that has traditionally been connected to routinized-response behavior was redefined and included in the calculative definition of customers commitment to the customer club in a relationship perspective

  • 42.
    Roos, Inger
    et al.
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Gustafsson, Anders
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Edvardsson, Bo
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration. Karlstad University, Faculty of Economic Sciences, Communication and IT, The Service and Market Oriented Transport Research Group.
    The Role of Customer Clubs in Recent Telecom Relationships2005In: International Journal of Service Industry ManagementArticle in journal (Refereed)
  • 43.
    Roos, Inger
    et al.
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Gustafsson, Anders
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Edvardsson, Bo
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration. Karlstad University, Faculty of Economic Sciences, Communication and IT, The Service and Market Oriented Transport Research Group.
    Landmark, Peter
    Should we Differentiate Between Business and Private Customers?2010In: Management Research and Practice, ISSN 2067-2462, Vol. 2, no 3, p. 249-263Article in journal (Refereed)
  • 44.
    Roos, Inger
    et al.
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Gustafsson, Anders
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Edvardsson, Bo
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration. Karlstad University, Faculty of Economic Sciences, Communication and IT, The Service and Market Oriented Transport Research Group.
    Landmark, Peter
    Should we Differentiate Between Business and Private Customers?2010Conference paper (Refereed)
    Abstract

    Abstract

    The question we pose in this paper is how similar or different really private and business customers are? There are several potential differences among these two groups. It can be assumed that the private customers generally are more free to make their own choices based on what best fits their needs. While a business customer may have more limits and can be more bound by company policies and contracts when selecting a service provider. The context we have chosen for this study is air travel. The context is relevant since business and private customers make similar choices; they need to go from one location to another. The results are based on qualitative studies.

    It turned out that the business customers were not as bound by company policies as we first thought. The findings showed a partially different decision-process character where the private costs in terms of family and personal needs occurred as being the most important aspects of the relationships between business customers and the airport service and flights in comparison. The results show that in companies not only job matters such as possibility to work decide the way of travelling but equally important are the clearly private aspects in the choice situations such as time with family. Time is accordingly an important asset for business customers, which was assumed, but it is not time in combination with companys strategies or programs that decide but pure private motives that act basis when departure and arrival occur in the business-traveling customers week programs.

    Price was found to be important but not as important as was customers possibilities to work or time with the family. The implication is that in a theoretical perspective the function of the consideration sets (Srinivasan 1987; Nedungadi 1990; Heide and Weiss 1995; Grewal et al. 1999) of private and business customers appears to look the same, only the features differ. In comparison with the complex service-purchasing process models (Valk and Rozemeijer 2009) of the business-relationship literature the procedure seems not always to occur in a structured way and in accordance with the company strategies. The implication is that airline companies build their programs on premises that are not used by business customers.

  • 45.
    Roos, Inger
    et al.
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Gustafsson, Anders
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Edvardsson, Bo
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration. Karlstad University, Faculty of Economic Sciences, Communication and IT, The Service and Market Oriented Transport Research Group.
    Nelsson Etzell, Anna
    SPAT (Switching Path Analysis Technique) - a Method to Understand Switching Paths and Future Behavior2011Conference paper (Refereed)
    Abstract

    ABSTRACT

    The longitudinal application of SPAT- Switching Path Analysis Technique- to different industries showed gradually interesting results relevant for filling identified gaps in the literature on customer decision making. The basis of the process method SPAT was the traditional CIT technique, with its focus on critical incidents. However, soon the development of SPAT changed the focus into the strength of the customer relationships. After one decade of empirical studies using SPAT, the deepened knowledge about customer relationships comprehended not only the possible categorization of the driving factors of the customer relationships according to their caused sensitivity for switching, but also according to their predictability for both staying or switching. In other words, it was possible to tell something about the outcome state that not only included the state as such but the stability, which had been pointed out to have beeen neglected in the literature on decision processes. The use of SPAT (Roos 1999) adds thereby theoretically and empirically to the Fishbein and Ajzenss model (1975) by describing unconscious thought processes and to Ajzen (1991) by extending the The theory of planned behavior model. The addition do not only distinguish between conscious and unconscious thoughts for behavior, but does specifically focus on the stability of the outcome behavior, which by Sheppard et al. (1988) was said to has been obeyed in the Fishbein and Ajzenss model (1975). This article demonstrates the longitudinal empirical studies regarding results relevant for the method development, and suggests a decision model including the stability indicating outcome state.

  • 46.
    Roos, Inger
    et al.
    Karlstad University, Faculty of Arts and Social Sciences (starting 2013), Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Löfgren, Martin
    Karlstad University, Faculty of Arts and Social Sciences (starting 2013), Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Edvardsson, Bo
    Karlstad University, Faculty of Arts and Social Sciences (starting 2013), Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Customer-Support Service from a Relationship Perspective: Best Practice for Telecom2013In: Management Research and Practice Journal (MRP), ISSN 2067-2462, Vol. 5, no 2, p. 5-21Article in journal (Refereed)
  • 47.
    Selos, Erno
    et al.
    Hanken school of economics.
    Laine, Teemu
    Hanken school of economics.
    Pitkänen, Lauri
    Hanken school of economics.
    Suomala, Petri
    Hanken school of economics.
    Roos, Inger
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration. Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center.
    Active/passive Customer Behavior in the Business-to-Business Supplier Switches: Extending SPAT to B-to-B Context2012In: / [ed] Jocob Mickelsson & Anu Helkkula, 2012Conference paper (Refereed)
  • 48. Selos, Erno
    et al.
    Teemu, Laine
    Roos, Inger
    Karlstad University, Faculty of Arts and Social Sciences (starting 2013), Service Research Center.
    Suomala, Petri
    Pitkänen, Lauri
    Applying SPAT for understanding B-to-B supplier switching processes2013In: Managing Service Quality, ISSN 0960-4529, E-ISSN 1758-8030, Vol. 23, no 4, p. 321-340Article in journal (Refereed)
    Abstract [en]

    Purpose: This study aims to focus on the switching path analysis technique (SPAT) application to enlarge the understanding of customer switching from the business to consumer (B-to-C) context to the processes of business-to-business (B-to-B) supplier switches. Design/methodology/approach: The paper is a theory extension of SPAT, with nine (9) supplier switching cases in different B-to-B settings. The cases shed light also on the actual triggers and determinants of the B-to-B switches. Findings: The study proves the applicability of SPAT in B-to-B settings. The B-to-B context adds complexity, forming a relationship flow where many driving factors act for switching. Thus, the findings suggest that a comprehensive analysis of the triggers and determinants is required to understand the switching processes. In particular, the characteristics of the active/passive behaviour should be analysed separately in the customer and in the old and new suppliers. Research limitations/implications: The empirical findings are exploratory in nature. Further research should refine the characteristics of active and passive behaviour at the levels of the relationship, the companies and the individuals to comprehend the notion of the influential trigger in SPAT. Further research should also address the wider topic of the patterns of certain triggers and determinants that actually lead to unstable supplier relationships. Practical implications: The B-to-B supplier switches appear to be complex processes. The supplier should be able to be constantly aware of the major changes in the customer’s business. Based on this awareness, the supplier may actively affect the development of the relationship to avoid unwanted switches. Originality/value: The paper combines the relatively mature research stream of B-to-C supplier switches and access to B-to-B supplier-switching cases. The theory contribution of the paper is the extension of the theory to the B-to-B context, with relevant research implications.

  • 49. Taylor, A. Gail
    et al.
    Hamer, Lawrence
    Roos, Inger
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Customer Reactions to Involuntary Switching2004Conference paper (Refereed)
  • 50.
    Wägar, Karolina
    et al.
    Hanken School of Economics, Vaasa, Finland.
    Roos, Inger
    Karlstad University, Faculty of Arts and Social Sciences (starting 2013), Service Research Center. Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Business Administration.
    Ravald, Annika
    Hanken School of Economics, Vaasa, Finland.
    Edvardsson, Bo
    Karlstad University, Faculty of Economic Sciences, Communication and IT, Service Research Center. Karlstad University, Faculty of Arts and Social Sciences (starting 2013), Karlstad Business School.
    My Customers Are in My Blind Spot: Are They Changing and I cannot See It?2012In: Journal of Service Research, ISSN 1094-6705, E-ISSN 1552-7379, Vol. 15, no 2, p. 150-165Article in journal (Refereed)
    Abstract [en]

    It is clearly recognized that service providers often have an incomplete and fragmentary understanding of their customers' relationship behaviors. Although it is clear that this incomplete understanding has serious implications for customer relationship management, and might even constitute a strategic risk, there have been no explicit attempts to analyze the phenomenon. The authors therefore introduce and develop the concept of the blind spot as a metaphor referring to situations where a service provider's visual field is obscured. The authors examine the phenomenon of blind spots in a temporal and a relational context, determine their consequences, and outline the implications for customer relationship management. A number of blind spot scenarios are presented in order to illustrate how blind spots obstruct the service provider's ability to make correct interpretations of customer relationships, and thereby also correct estimations of relationship stability. The conceptualization of blind spots as outlined in this article sheds light on the underlying mechanisms that drive customer behavior in terms of relationship stability and hence offers a deeper understanding of the dynamic nature of customer relationships. From a managerial point of view, proper monitoring systems and routines for analyzing relevant customer information play essential roles in understanding and managing blind spots.

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