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The Effect of Triggers in Customer Relationships
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.ORCID iD: 0000-0003-2705-0836
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.ORCID iD: 0000-0001-8278-1442
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.
2002 (English)Conference 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

Place, publisher, year, edition, pages
2002.
National Category
Business Administration
Research subject
Business Administration
Identifiers
URN: urn:nbn:se:kau:diva-24382OAI: oai:DiVA.org:kau-24382DiVA: diva2:598149
Conference
Marketing Track of Decision Sciences Institute, 33rd Annual Meeting, San Diego, California, USA, 23-26 November
Available from: 2013-01-22 Created: 2013-01-22 Last updated: 2015-06-02Bibliographically approved

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