markets: an investigation of the financial services industry. Mark Colgate. Senior Lecturer, Department of Marketing, The University of. Auckland, New Zealand.
An executive sum m ary for m anagers and executive readers can be found at the end of this article
Switching barriers in consumer markets: an investigation of the financial services industry Mark Colgate Senior Lecturer, Department of Marketing, The University of Auckland, New Zealand
Bodo Lang Lecturer, Department of Marketing, The University of Auckland Business School, Auckland, New Zealand
Keywords Consumer behaviour, Services marketing, Barriers, Financial services Abstract Much research looks at why customers switch service organizations but there has been less focus on why customers do not switch service organizations, even though they have seriously considered doing so. In light of this, we present an analysis of the literature and develop a list of potential switching barriers. These switching barriers are then empirically tested within two financial services industries. Results from over 400 consumers enable us to ascertain not only the importance of each switching barrier but also to develop a more parsimonious understanding of these barriers, through factor analysis. The results reveal similar patterns in the two industries in respect to switching barriers. The first of the four factors contains reasons related to apathy, the second factor contains negative reasons for customers staying with their current service provider, the third factor relates to relationship variables and the final factor relates to service recovery. Results clearly indicate that the first two factors are far more important than the latter two in terms of why customers stay even when they seriously considered leaving.
Introduction Much research looks at why customers switch service organizations (Keaveney, 1995; Levesque and McDougall, 1996; Zeithaml et al., 1996) and its importance (Fornell and Wernerfelt, 1987; Mittal and Lassar, 1998; Reichheld and Sasser, 1990). Yet there has been little research that looks at why customers do not switch service organizations. This is an important area of research for several reasons. Point of view
First, from an academic point of view a comprehensive understanding of the switching process requires not only an understanding of why consumers switch but also an awareness of why they do not switch. That is, consumers frequently go through a cognitive process where they decide to either stay or leave a service organization, what we call a ``switching dilemma’’. This research looks at the decision to stay and the reasons behind it. In this respect we are focusing on a missing element in consumer research in a services context. Second, for those firms which have many prospective switchers as part of their customer base it is important to understand why these customers stay and to what extent such firms can further discourage such customers from leaving (in both positive and negative ways). Finally, for those services firms which are looking to attract these prospective switchers (e.g. new entrants into the market), an understanding of why customers do not switch is important, as it will enable them to develop strategies to overcome these switching barriers and gain market share. The research register for this journal is available at http://www.mcbup.com/research_registers The current issue and full text archive of this journal is available at http://www.emerald-library.com/ft
3 32
JO U R N A L O F C O N SU M E R M A R K E T IN G , V O L . 1 8 N O . 4 2 00 1, pp . 332 -347 , # M C B U N IV E R S IT Y PR E S S , 0 736 -376 1
A two-stage research process was developed to ascertain the reasons why consumers decide to stay with their current service provider even though they have seriously considered switching to another provider. Initially, a literature review was undertaken to unearth the constructs that other researchers have suggested act as switching barriers. The second stage explores, through empirical research, the underlying structure of these barriers and their importance in respect of a consumer’s decision to stay with their service provider. The idea behind this stage is to validate empirically the switching barriers proposed within the literature but which have not been tested. The paper then concludes with implications for both academics and managers alike. Sw itching barriers
Literature review The aim of the literature review was to identify switching barriers and synthesise these to develop broad categories in respect to why consumers stay with service organizations even though they have seriously considered switching. Both the product and services literature are analysed to develop a comprehensive understanding of consumer behavior in this area. Relationship investment Relationship marketing has received increasing attention from both academics and practitioners due to the potential benefits for both firms and their customers (Colgate and Danaher, 2000). Due to the potential benefits a body of literature has emerged indicating that investment into a relationship may be one reason consumers stay with their service provider. For example, Gwinner et al. (1998) argue that consumers will commit themselves to establishing, developing, and maintaining relationships with a service provider that provide superior valued benefits. They discovered that consumers receive many benefits from developing relationships and that these benefits could be classified into confidence, social, and special treatment benefits. Gwinner et al. (1998) found that even if a consumer perceives the core service attributes as being less than optimal, they may remain in a relationship if they are receiving important relational benefits.
Relationship-specific investm ents
Berry and Parasuraman (1991) also suggest that effective relationshipspecific investments increase customers’ dependency because they raise the costs of switching to competitors. By switching to a competitor, the customer would lose the benefits from the relationship-specific investments not readily available from the competitors. Jones et al. (2000) also discovered an indirect empirical link between interpersonal relationships and repurchase intentions. This link suggested that, in situations of low customer satisfaction, strong interpersonal relationships positively influence the extent to which customers intend to repurchase. These results suggest that relationships do act as a barrier to switching. Switching costs Switching costs are another category of switching barriers that emerge from an analysis of the literature. These costs are defined as the cost of changing services in terms of time, monetary and psychological costs (Dick and Basu, 1994; Guiltinan, 1989; Sengupta et al., 1997). Switching costs can also create a dependence of the consumer on the provider (Morgan and Hunt, 1994). Switching costs may come in the form of termination costs from the current service provider to joining costs with the alternative service provider.
JO U R N A L O F C O N S U M E R M A R K E T IN G , V O L . 18 N O . 4 20 01
3 33
Gronhaug and Gilly (1991) argue that a dissatisfied customer may remain ``loyal’’ because of high switching costs. For example, moving to a new service provider requires investing effort, time and money, which acts as a significant barrier to a consumer taking action when dissatisfied with the current service provider. Ping (1993) examined the relationship between switching costs and customer loyalty, and discovered that when customers perceive the switching costs associated with leaving the current relationship and establishing the alternative to be high they tend to be ``loyal’’. Perceived risk
Switching costs also relate to perceived risk, which is defined as ``the consumer’s perception of the uncertainty and adverse consequences of buying a product [or service]’’ (Dowling and Staelin, 1994, p. 119). This is conceptualised as the likelihood of negative consequences (i.e. danger, loss, etc.). Perceived risk represents consumers’ uncertainty about loss or gain in a particular transaction and has six components (e.g. Murray, 1991; Murry and Schlacter, 1990): financial, performance, social, psychological, safety, and time/convenience loss. We can see that these are similar to the time, monetary and psychological switching costs, referred to earlier, when safety, social and performance risk are included under the broader psychological descriptor. Clearly, switching costs seem to be an important reason not to switch service providers as many researchers have proposed the existence and significance of these barriers. Hence, they form an integral part of this study. Availability and attractiveness of alternatives The number of alternative providers, as perceived by the consumer, may also influence a decision to remain with a service provider. First, there may not be many or any alternatives due the structure of the industry, e.g. monopoly. Second, consumers may perceive that there are few alternatives in the market because of the fact that many of the alternatives are not in their evoked set. This is supported by Bendapudi and Berry (1997) who propose that consumers might remain in a relationship because they perceive no alternative. Therefore, repeat purchase behaviour may not indicate loyalty from consumers, but merely a lack of alternatives or no perceived differences between alternatives (e.g. Bejou and Palmer, 1998; Ping, 1993; Andreasen, 1985; Szmigin and Bourne, 1998). This perception may mean that it may not be considered worthwhile switching from one service provider to another.
Service provider
Anderson and Narus (1990) also suggest that a consumer might be dependent on a service provider because of the lack of superior competition in the marketplace. So even though consumers are not satisfied with their current provider they stay because it is still better than the alternatives. In summary, it seems likely that the presence of alternatives, some of which need to be at least as good as the current provider, may play a major role in a consumer’s decision to stay or leave. Service recovery The final category unearthed in the literature, which relates to reasons why customers may stay with their current service provider is service recovery. Service recovery includes all the activities and efforts employed by a service organization to rectify, amend, and restore the loss experienced by the customer following a service failure (GroÈnroos, 1988). Consumers may stay with a service provider after they have experienced a problem with them because they were satisfied with the service recovery process after they had complained. This is the optimal situation for service
3 34
JO U R N A L O F C O N S U M E R M A R K E T IN G , V O L . 18 N O . 4 20 01
providers who encounter a complaining customer (Zemke, 1993). A service recovery strategy is recognised as a crucial element in achieving long-term customer satisfaction for services firms (Tax et al., 1998). Customers who have experienced a problem will usually be dissatisfied, although this level of dissatisfaction varies based on the severity of the problem. Successful service recovery can reverse this dissatisfaction and can sometimes lead to the customer being more satisfied than prior to the problem, a phenomenon called the ``service recovery paradox’’ (Smith and Bolton, 1998). In this way, good service recovery can lead to customers changing their mind about switching from their service provider. Hence, service recovery is included as an important switching barrier in this study. Individual issues
Summary of literature None of above literature has sought to classify why customers do not switch (after a switching dilemma) into one overall study. Rather, research has focused on individual issues (such as relationship investment) and few studies are empirically based. Importantly, no research has asked consumers the reasons for staying with a service provider after they have seriously considered switching (i.e. after they have been through a switching dilemma). Asking consumers why they might not switch before they have considered doing so may lead to reliability problems. For example, Jones et al. (2000) ask ``if you were thinking of switching what would stop you from switching’’, which leads customers to speculate rather than identifying the real reasons that prevent customers from switching providers. In light of this gap, this paper has analysed the literature and drawn out four major categories: relationship investment, switching costs, availability of alternatives and service recovery. These four categories are then examined through responses from consumers who have recently seriously considered switching from their current service provider. This leads to the following research questions: (1) To what extent are the four major categories of switching barriers (relationship investment, switching costs, availability of alternatives and service recovery) substantiated across these two service industries? (2) What is the relative importance of these categories in respect to why customers do not switch, even though they have seriously considered doing so?
Cross-sectional survey
Methodology Design A cross-sectional survey design was adopted which questioned respondents from two industries; the retail insurance industry and retail banking industry within New Zealand. Each survey was sent out to two separate samples as the questionnaires were tailored to the unique aspects of the industry. Respondents received two items; a booklet and a reply-paid envelope making it easier for consumers to respond. The booklet consisted of eight pages, the first page being a cover letter explaining the relevance of the survey and what to do with the completed survey. The remainder of the booklet contained a self-completion questionnaire including instructions on how to fill out the questionnaire. One section of the survey was used to investigate only those respondents who had previously ``seriously considered switching’’ from their main[1] insurance company or bank but had decided to stay, and the reasons for this decision. This section enabled the investigation of this study’s two research questions.
JO U R N A L O F C O N S U M E R M A R K E T IN G , V O L . 18 N O . 4 20 01
3 35
Sample To select respondents, a proportionally stratified probability sampling method was used. This method carries several advantages. First, stratified sampling is a very efficient method, resulting in lower standard deviations and higher confidence in any estimated values. Second, employing this method ensures that different regions of New Zealand (sub-populations) were represented. Within each sub-population a systematic sampling method (i.e. select every ``nth’’ data point), was used to select consumers. Questionnaires
M ajor objective
The details of 4,456 consumers were acquired from an electronic version of all New Zealand telephone books. From the 4,456 questionnaires sent out, 263 (9.8 per cent) were returned as ``return to sender’’ in the banking industry and 175 (9.8 per cent) in the insurance industry. This left 2,425 valid questionnaires for the banking industry and 1,593 for the insurance industry that were sent out. To reduce non-response bias, a second mailing was made to non-respondents from the first mailing. In total 1,346 usable banking questionnaires were received, resulting in a response rate of 55.5 per cent and 580 (36.4 per cent) for the insurance industry. The difference in response rates is attributable to two factors. First, although penetration of insurance products is high (around 85 per cent of all New Zealanders have at least one insurance product) it is not as high as bank accounts, where 96 per cent of the population has a cheque account. Second, banking seems to generate higher levels of involvement. For example, in this study the average involvement score for Zaichowsky’s (1994) five-point scale was 2.24 (out of 7, where 1 is highly involved) for banking and 3.04 for insurance. It is reasonable to assume that consumers are more likely to respond to surveys on services they are more involved in. Measurements The major objective of the study was to identify the reasons why consumers decide not to switch from their main bank or insurance company, even though they seriously considered moving. Therefore, respondents were asked whether they ``have ever seriously considered moving from their main bank (insurance company) but ended up staying’’. This question and its wording is important as it enables us to create a sample of ``considered switchers’’ and it also avoids any behavioural intention issues. That is, this group has considered switching and it is not, therefore, a reflection of what they plan to do in the future. Research that asks consumers what they plan to do in the future has been proven to be a less than accurate reflection of what customers actually do (cf. Zeithaml et al., 1996). This study investigates those customers who have actually seriously considered switching ± but stayed ± so that it reflects past, not future, behaviour. The word ``serious’’ was an important inclusion in the question as it ensures that the people included in the sample have spent time consciously considering switching. Respondents in this sample were then asked how long ago they seriously considered moving, why they considered moving (i.e. what triggered this decision process) and, most importantly, why they did not move. This final question contained 11 categories as to why a consumer may not move after they have seriously considered doing so, and also an additional open-ended category for those respondents whose answers did not fit the closed-ended questions. The 11 categories were based on the above literature review and contained five questions on relational investment (social bonds, confidence benefits and special treatment), three questions on switching costs (psychological, financial and time), one on service recovery and two
3 36
JO U R N A L O F C O N S U M E R M A R K E T IN G , V O L . 18 N O . 4 20 01
questions on the attractiveness of alternatives. The actual questions used in the survey can be seen in Table I.
Retail banking industry
Results Descriptive analysis The results from the retail banking industry reveal that 41 per cent (549) of the total sample has seriously considered leaving their main bank at some stage and 22 per cent (295) did so in the last year. It was decided that only those customers who had seriously considered leaving their bank in the last year would be used, as past research has shown that more recent events have more accurate levels of recollection (Sudman and Bradburn, 1973). This resulted in a reduced but still adequate sample of 295 respondents. In the insurance industry 27 per cent of respondents (154 of those sampled) had seriously considered switching their main insurance company at any stage, 9 per cent (52) in the last year, 10 per cent (57) 1-2 years ago and the rest (8 per cent or 45) over two years ago. The sample used in the insurance industry for the subsequent analysis are those customers who have seriously considered moving in the last two years, not the last year as in the banking sample. Although it would have been preferable to use only those who have considered switching in the last year, this sample was too small and thus the first two categories were combined to give a sample of 109 respondents. Analysis of those customers who have seriously considered switching insurance companies compared to those who have not indicated that there are no differences in terms of age, gender, income, education level or ethnicity. However, those customers who have seriously considered moving banks tended to be younger (Chi square = 44.43, p = 0.00), had higher incomes (Chi square = 37.32, p = 0.00) and a higher level of education (Chi square = 23.186, p = 0.01) than those who had not seriously considered moving.
Prospective sw itchers
These prospective switchers also exhibit extreme levels of dissatisfaction compared to those who have not seriously considered moving. For example only 4 per cent of those customers who have not seriously considered moving in the retail-banking sample are dissatisfied and 81 per cent satisfied, compared to 39 per cent and 22 per cent respectively for those customers who have seriously considered moving in the last year. A comparison of the two groups in the insurance industry reveals similar findings. Only 2 per cent Switching barrier categories
Switching barrier variables
Relational investments
I have confidence that my bank/insurance company provides the best deal My bank/insurance company knows my needs Staff know me I receive preferential treatment from my main bank/insurance company I feel a sense of loyalty to my main bank/insurance company
Switching costs
Too much bother in terms of time and effort I was concerned about negative financial outcomes I feel locked in because of the products I have with the bank/ insurance company
Service recovery
A complaint that I had was resolved
Attractiveness of alternatives
All banks/insurance companies are the same I was uncertain of the outcome if I changed
Table I. Switching barrier variables used in survey JO U R N A L O F C O N S U M E R M A R K E T IN G , V O L . 18 N O . 4 20 01
3 37
of those insurance customers who have not seriously considered moving at all are dissatisfied and 82 per cent satisfied, compared to 12 per cent and 51 per cent respectively. Those customers who have seriously considered leaving their main bank also tended to search actively for information about alternatives. Over 35 per cent of those customers who had considered switching collected material to compare prices and information about the competition. Another 28 per cent asked friends and family and other acquaintances for advice about alternatives. The rest just considered switching but did not actively seek information about what to do next. The results were similar for retail insurance customers but with 52 per cent comparing information from different companies, and 19 per cent asking friends and family for advice. Decision-making process
These results and the fact that consumers were asked to state whether they seriously considered switching suggests that respondents had begun to go through a decision-making process, and collecting information was a first step in this process, and were not just thinking of leaving in passing. This indicates an active, rather than passive, state of mind. This increases confidence in the validity of the responses to the main questions this research sought to answer. Why do consumers not switch service providers, how can we classify these reasons and how important are these different reasons? Classification of switching barriers Banking industry Exploratory factor analysis was used to assess the dimensionality of the reasons why customers do not switch banks and thus determine the relevance of categories unearthed in the literature. A common factor analysis with Varimax rotation was undertaken for the 11 items in the retail banking survey. Evaluation of the Eigenvalues and screeplot indicated a four-factor solution, which explained 67 per cent of variation in the items. Tests suggested that the overall factor solution adequately accounted for the underlying structure of the data (Bartlett’s Test of Sphericity p-value = 0.000, KMO statistic = 0.671). The final factor solution is represented in Table II. Problems
Factor 1
I receive preferential treatment from my main bank/insurance company I feel a sense of loyalty to my main bank/ insurance company I have confidence that my bank/insurance company provides the best deal My bank/insurance company knows my needs I was concerned about negative financial outcomes I feel locked in because of the products I have with the bank/insurance company I was uncertain of the outcome if I changed Too much bother in terms of time and effort All banks/insurance companies the same A complaint that I had was resolved
Factor 2
Factor 3
Factor 4
0.624 0.718 0.856 0.867 0.660 0.828 0.558 0.819 0.698 0.846
Note: ``Staff know me’’ variable was deleted due to insufficient loading
Table II. Rotated factor solution for retail banking respondents 3 38
JO U R N A L O F C O N S U M E R M A R K E T IN G , V O L . 18 N O . 4 20 01
The first factor accounted for 24 per cent of the variation in the data, and related to relationship issues such as loyalty, staff knows my needs, preferential treatment and receiving the best deal, and very much fits with the Gwinner et al. (1998) relationship classification. In light of this it was labelled ``relationship investment’’ as it relates to the fact that some customers are not willing to leave due to the effort that has been made in developing the relationship between themselves and their bank. ‘‘N egativity’’
The second factor was named ``negativity’’, and explained 15 per cent of the variance. Items in this factor were all related to negative reasons as to why customers might stay ± such as being locked in, being concerned about negative financial consequences and uncertainty about the outcome of switching to another provider. The third factor also explained 15 per cent of the variation and was labelled ``apathy’’ as it was made up of two variables relating to the fact that the status quo seemed more appealing. These variables were ``all banks are the same, so no better off’’ and ``too much bother in terms of time and effort’’. The final factor accounted for 13 per cent of the variance and is concerned with one variable only ± satisfactory handling of a customer complaint. Thus, this factor is called ``service recovery’’. The variable ``staff know me’’ did not load on any factor (the cut-off was 0.5 for factor loading, as Hair et al. (1995) suggest this is a reasonable cut-off for a sample size of over 100) and was thus deleted.
Retail insurance industry
Insurance industry In terms of the retail insurance industry data a Varimax rotation on the 11 items was also undertaken. Evaluation of the Eigenvalues and screeplot indicated a four-factor solution, which explained 69 per cent of variation in the items. Tests suggested that the overall factor solution was adequately accounting for the underlying structure of the data (Bartlett’s Test of Sphericity p-value = 0.000, KMO statistic = 0.678). The final factor solution is represented in Table III. Overall, the factor structure and its components are very similar to the retail banking industry data. The first factor accounted for 23 per cent of the variation in the data, and related to the same relationship issues contained in the first factor of the Problems I feel a sense of loyalty to my main bank/ insurance company I have confidence that my bank/insurance company provides the best deal My bank/insurance company knows my needs Staff know me I was concerned about negative financial outcomes I feel locked in because of the products I have with the bank/insurance company I was uncertain of the outcome if I changed A complaint that I had was resolved Too much bother in terms of time and effort All banks/insurance companies the same
Factor 1 Factor 2 Factor 3 Factor 4 0.760 0.782 0.819 0.605 0.813 0.704 0.806 0.898 0.619 0.876
Note: ``I receive preferential treatment’’ from my main bank/insurance company variable was deleted
Table III. Rotated factor solution for retail insurance respondents JO U R N A L O F C O N S U M E R M A R K E T IN G , V O L . 18 N O . 4 20 01
3 39
retail banking analysis. The only difference was the addition of the ``staff know me’’ variable and the deletion of the variable ``preferential treatment’’ as it did not load on any factor. Due to its similarity to the equivalent factor in the banking sample this factor was also named ``relationship investment’’. The second factor was also named ``negativity’’ and explained 19 per cent of the variance. Items in this factor were identical to the second factor in retail banking data. The third factor accounted for 13 per cent of the variance and is identical to the fourth factor in the retail banking results; hence it is called ``service recovery’’. The final factor also explained 13 per cent of the variation and was labelled ``apathy’’ as it was akin to the third factor in the retail banking data. Sw itching barriers
Although creating a classification of the switching barriers is useful, and it is interesting to note similar factor structures in both industries, an understanding of the importance of these categories is also valuable. This is because it enables us to assess the relative significance of the factors in relation to the reasons prohibiting consumers from leaving their service provider. In order to determine the relative importance of the derived factors on a consumer’s decision not to switch, the mean importance rating was derived for each factor. These importance scores were calculated by averaging the mean scores of the items within each factor. This technique has previously been adopted in research assessing the importance weightings of factors in other service contexts (Gwinner et al., 1998). Tables IV and V provide the mean importance ratings for each of the four factors and for their component items.
‘‘Apathy’’
As the tables show in both markets, the ``apathy’’ factor was the largest switching barrier, with ``too much bother’’ being the biggest single reason within this factor and also the joint most important reason out of the 11 items in the insurance market and second most important single reason in the banking market. Clearly, therefore, customer inertia is a major barrier for Problem factors
Mean
Factor 1: Relationship investment Feel loyalty towards bank Receive preferential treatment Bank knows needs Confidence of best deal
1.95 2.02 1.77 2.02 1.98
Factor 2: Negativity Concerned about negative outcomes Feel locked in Uncertainty if changed
2.74 2.91 2.68 2.64
Factor 3: Apathy All banks same Too much bother
2.82 2.74 2.90
Factor 4: Service recovery Complaint resolved
1.97 1.97
Note: Means based on a scale of relative importance weighting (1 = strongly disagree to 4 = strongly agree)
Table IV. Comparison of factor means: retail banking 3 40
JO U R N A L O F C O N S U M E R M A R K E T IN G , V O L . 18 N O . 4 20 01
Problem factors
Mean
Factor 1: Relationship investment Feel loyalty towards insurance company Staff know me Insurance company knows needs Confidence of best deal
2.31 2.28 2.13 2.37 2.46
Factor 2: Negativity Concerned about negative outcomes Feel locked in Uncertainty if changed
2.48 2.77 2.12 2.55
Factor 3: Service recovery Complaint resolved
2.07 2.07
Factor 4: Apathy All insurance companies same Too much bother
2.69 2.61 2.77
Note: Means based on a scale of relative importance weighting (1 = strongly disagree to 4 = strongly agree)
Table V. Comparison of factor means: retail insurance
service organizations to overcome if they are looking to attract customers away from a poor performing competitor. The second most important factor in both industries was ``negativity’’ ± the potential for the customer to lose in some way if they switched firms. Being concerned about financial negative outcomes drove this factor and was also the biggest single reason in both markets. Uncertainty of change was also prominent in this factor. Finally, ``feel locked in’’ was a less significant variable in the retail insurance industry compared to the retail banking industry. This is probably to do with the fact that the barriers to exit are much lower for an insurance policy than for switching banks, given the potential complexity and time involved (e.g. changing salary details, direct debits, etc.). Relationship investm ent
The third most important factor in the insurance industry and the last (by a small margin) in the banking industry was relationship investment. There are clearly differences between the two markets here with insurance customers believing that a much larger relationship investment has been made with their company than bank customers. In particular, insurance customers seemed to believe that they received the best deal with their current company, but bank customers believed this to be less true. Bank customers also believed that their bank did not understand their needs as well. Regardless of the differences between the two markets, relationship investment is still a much less important reason to stay for consumers in both of these markets, relative to the negative and apathy factors. Finally, service recovery did not seem to be a major switching barrier; this could be due to three reasons: some consumers may not have a reason to complain; not every customer complains when they receive a service failure; and even when they do complain they may not necessarily receive a satisfactory resolution. Discussion The above results are of significance as they raise some important academic and managerial issues. First, the way the literature has described barriers to
JO U R N A L O F C O N S U M E R M A R K E T IN G , V O L . 18 N O . 4 20 01
3 41
switching contrasts with a customer-centric description of the reasons why consumers don’t switch, as presented in this paper. For example, lack of alternatives, time and effort in terms of switching are revealed as one ``apathy’’ category in this paper, rather then the separate categories proposed in the literature. Moreover, this factor was deemed the most important from the customer’s perspective, indicating that change that seems too difficult, and potentially fruitless, is a significant barrier to switching. From a managerial perspective this issue seems critical in these industries ± how do competing organizations overcome this consumer apathy that seems so prevalent? What strategies and tactics can be used to move customers from the passive state of mind (i.e. considering switching but staying) to the active (i.e. actually switching). Research into this area by both managers and academics seems vital if this barrier is to be understood and overcome. Negative consequences
Another category not found within the literature is ``negativity’’, this factor essentially relates to the possibility of negative consequences if the customer switches firms. This factor contains psychological (such as uncertainty and feeling locked in) and financial consequences. This is similar to the switching costs category identified in the literature but more focused on the negative outcomes typically associated with switching providers. This factor was the second most important and highlights the value of managers accentuating the positive and reducing uncertainty, when looking to attract consumers. The negative financial outcomes may be more difficult to overcome unless firms can give new customers price breaks as an enticement. One category of switching barriers that was consistent with the literature was the relationship category. This was prominent in the literature and a clear factor emerged within the analysis that contained only relationship elements. Interestingly, this factor was not considered as important by customers as a reason not to switch (particularly for banking consumers) ± negative factors and apathy were much more important. This is notable given the multitude of research that supports the relationship approach (cf Cram, 1994; Payne, 1994; Rust et al., 1994; Shani and Chalasani, 1992; Webster, 1994). It may well be that the industries under analysis are particularly poor at developing relationships and this reduces this barrier’s significance. Alternatively, consumers have seriously considered leaving because the relationship has dissolved and hence it is a reason to leave rather than stay. Finally, it may be that relationships are not as important to consumers as we first thought and other factors ``tie’’ the consumer to the organization. Clearly more research is required here.
Service recovery factor
3 42
Similarly, the service recovery factor is also consistent with the literature but not rated as important. This factor suggests that when consumers seriously consider leaving, service recovery does not really mediate the switching process. Overall, it seems to play only a minor role. Undoubtedly one of the reasons for this is that service recovery is not common, it is likely that only a handful of situations will require service recovery. For example, in some circumstances customers do not often complain (e.g. dissatisfaction with a price increase) hence service recovery may not be required. However, other factors could also be at work, such as poor complaint handling. This would not be picked up in these results. The customer may have complained but received poor service recovery and, hence, this did not influence their decision to stay. It is likely that a combination of these factors is at work. JO U R N A L O F C O N S U M E R M A R K E T IN G , V O L . 18 N O . 4 20 01
Further research may also be useful here in ascertaining exactly why service recovery was not a more prominent factor. Conclusion Customers’ switching behaviour and the reasons behind it have received considerable attention in the past. This paper set out to investigate the reverse of this phenomenon: the reasons why consumers, who have seriously considered switching their service provider, stayed. There are many reasons why this paper is important. First, empirically testing the reasons why customers do not switch providers aids our understanding of consumer switching behaviour. By identifying what factors reduce the likelihood of switching we gain a better understanding of when customers are more or less likely to switch service providers. Factors
Second, this research is not only the first empirical effort to validate the numerous variables that are believed to have an impact on customer switching behaviour but also combines these variables into factors. By doing so, we have been able to validate the significance of certain variables, such as perceived lack of alternatives and switching costs. While factor analysis has enabled us to condense a large number of variables into a more manageable number of categories, this process has also provided us with insights into the underlying patterns of why customers do not switch providers. Importantly, this paper has revealed the importance of a new factor, termed ``negativity’’, relating to the potential negative outcomes of the switching process for the consumer. Third, this paper has made a significant contribution by prioritising the four factors that prohibit customers from switching service providers. Similar patterns emerged in both industries. Interestingly, ``apathy’’ was found to be the most important in both the retail bank and retail insurance context. Second most important was the newly-found factor, ``negativity’’, further underlining the academic contribution of this study.
Limitations
Despite best intentions, there are limitations to this research. First, the industries under analysis are similar in many respects and this may limit the generalisability of results. Research in dissimilar industries such as doctors, dentists, Internet service providers (ISPs) is strongly encouraged. Similarly, studies in other countries would also be valuable to ascertain whether the results are country specific. Finally, the categories that were used in this study were taken from the literature and, even though there was an openended question prompting respondents for further categories, it may be that these categories were not exhaustive and alternative barriers may exist. Overall, many parties should be interested in the above results. Organizations that have low levels of customer satisfaction, and hence need to reinforce barriers to switching, will hopefully start to understand the factors that encourage customers to stay and build on them. Given that apathy and negativity seem to be the most significant switching barriers, it seems reasonable to recommend that these organizations need to build more switching barriers such as financial barriers or increasing the number of products customers hold, thus increasing the feeling of being ``locked in’’. This strategy is unlikely to be sustainable in the long term, however, as having a large number of customers who feel ``trapped’’ is likely to lead to more negative word of mouth, lower acceptance of new products, less ability to cross-sell, and many other negative outcomes relating to having ``terrorist’’ customers (Jones and Sasser, 1995). A more sustainable approach
JO U R N A L O F C O N S U M E R M A R K E T IN G , V O L . 18 N O . 4 20 01
3 43
would be to understand why relationships are not barriers to switching and build stronger relationship values, such as trust. Managers from services organizations looking to attract customers away from competitors will also benefit from an understanding of what keeps potentially dissatisfied customers with a firm. Knowledge that apathy and negative factors drive this decision will help these managers build appropriate strategies to increase levels of customer acquisition. For example, reducing the time it takes customers to switch or offering financial incentives to switch could be more important than first thought. Academ ic perspective
From an academic perspective, this seems an under-researched area. This research alone suggests that the numbers of consumers who seriously consider switching but stay on an annual basis is large (22 per cent in the banking example). Hence this topic is potentially as important as understanding switching itself. The authors see more research that creates a greater understanding of the switching barriers across additional industries as being critical to the advancement of consumer marketing theory. Note 1. A main bank was defined as the bank that respondents would use for most of their transactions. A main insurance company was defined in terms of the company where the customer had most policies. This was deemed necessary to ensure valid responses from respondents, as they were likely to have a stronger impression of their main company compared to a company they did little business with. References Anderson, J.C. and Narus, J.A. (1990), ``A model of distributor firm and manufacturer firm working partnerships’’, Journal of Marketing, Vol. 54 No. 1, pp. 42-58. Andreasen, A.R. (1985), ``Consumer responses to dissatisfaction in loose monopolies’’, Journal of Consumer Research, Vol. 12, September, pp. 135-41. Bejou, D. and Palmer, A. (1998), ``Service failure and loyalty: an exploratory empirical study of airline customers’’, Journal of Services Marketing, Vol. 12 No. 1, pp. 7-22. Bendapudi, N. and Berry, L.L. (1997), ``Customers’ motivations for maintaining relationships with service providers’’, Journal of Retailing, Vol. 71 No. 3, pp. 223-47. Berry, L.L. and Parasuraman, A. (1991), Marketing Service: Competing through Quality, The Free Press, New York, NY. Colgate, M. and Danaher, P. (2000), ``Implementing a customer relationship strategy: the asymmetric impact of poor versus excellent execution’’, Journal of the Academy of Marketing Science, Vol. 28 No. 3, pp. 375-87. Cram, T. (1994), The Power of Relationship Marketing: Keeping Customers for Life, Pitman Publishing Ltd, London. Dick, A.S. and Basu, K. (1994), ``Customer loyalty: toward an integrated conceptual framework’’, Journal of the Academy of Marketing Science, Vol. 22 No. 2, pp. 99-113. Dowling, G. and Staelin, R. (1994), ``A model of perceived risk and intended risk-handling activity’’, Journal of Consumer Research, Vol. 21 No. 1, pp. 119-34. Fornell, C. and Wernerfelt, B. (1987), ``Defensive marketing strategy by customer complaint management: a theoretical analysis’’, Journal of Marketing Research, Vol. 24, November, pp. 337-46. Gronhaug, K. and Gilly, M.C. (1991), ``A transaction cost approach to customer dissatisfaction and complaint actions’’, Journal of Economic Psychology, Vol. 12, pp. 165-83. GroÈnroos, C. (1988), ``Service quality: the six criteria of good perceived service quality’’, Review of Business, Vol. 9 No. 3, pp. 10-13. Guiltinan, J.P. (1989), ``A classification of switching costs with implications for relationship marketing’’, in Childers, T.L., Bagozzi, R.P., Peter, J.P. (Ed.), 1989 AMA Winter Educators’ Conference: Marketing Theory and Practice, American Marketing Association, Chicago, IL, pp. 216-20.
3 44
JO U R N A L O F C O N S U M E R M A R K E T IN G , V O L . 18 N O . 4 20 01
Gwinner, K.P., Gremler, D.D. and Bitner, M.J. (1998), ``Relational benefits in services industries: the customer’s perspective’’, Journal of the Academy of Marketing Science, Vol. 26 No. 2, pp. 101-14. Hair, J.F., Anderson, R.E., Tatham, R.L. and Black, W.C. (1995), Multivariate Data Analysis, Prentice-Hall, Inc., Englewood Cliffs, NJ. Jones, M.A., Mothersbaugh, D.L. and Beatty, S. (2000), ``Switching barriers and repurchase intentions in services’’, Journal of Retailing, Vol. 76 No. 2, pp. 259-74. Jones, T. and Sasser, E. (1995), ``Why satisfied customers defect’’, Harvard Business Review, November-December, pp. 88-96. Keaveney, S.M. (1995), ``Customer switching behaviour in service industries: an exploratory study’’, Journal of Marketing, Vol. 59, April, pp. 71-82. Levesque, T.J. and McDougall, G.H.G. (1996), ``Customer dissatisfaction: the relationship between types of problems and customer response’’, Canadian Journal of Administrative Sciences, Vol. 13 No. 3, pp. 246-76. Mittal, B. and Lassar, W.M. (1998), ``Why customers switch? The dynamics of satisfaction versus loyalty’’, Journal of Services Marketing, Vol. 12 No. 3, pp. 177-94. Morgan, R. and Hunt, S. (1994), ``The commitment-trust theory of relationship marketing’’, Journal of Marketing, Vol. 58, July, pp. 20-38. Murray, K.B. (1991), ``A test of services marketing theory; consumer information acquisition activities’’, Journal of Marketing, Vol. 55, January, pp. 10-25. Murray, K.B. and Schlacter, J.L. (1990), ``The impact of services versus goods on consumers’ assessment of perceived risk and variability’’, Journal of the Academy of Marketing Science, Vol. 18 No. 1, pp. 51-65. Payne, A. (1994), ``Relationship marketing: making the consumer count’’, Managing Service Quality, Vol. 4 No. 6, pp. 29-31. Ping, R.A. Jr (1993), ``The effects of satisfaction and structural constraints on retailer exiting, voice, loyalty, opportunism, and neglect’’, Journal of Retailing, Vol. 69 No. 3, pp. 320-52. Reichheld, F.W. and Sasser, W.E. (1990), ``Zero defections: quality comes to services’’, Harvard Business Review, Vol. 68 No. 5, pp. 105-10. Rust, R.T., Zahorik, A.J. and Keiningham, T.L. (1994), Return on Quality; Measuring the Financial Impact of Your Company’s Quest for Quality, Probus Publishing Company, Chicago, IL. Sengupta, S., Krapfel, R.E. and Pusateri, M.A. (1997), ``Switching costs in key account relationships’’, Journal of Personal Selling & Sales Management , Vol. 17 No. 4, pp. 9-16. Shani, D. and Chalasani, S. (1992), ``Exploiting niches using relationship marketing’’, Journal of Services Marketing, Vol. 6 No. 4, pp. 43-52. Smith, A. and Bolton, R. (1998), ``An experimental investigation of customer reactions to service failure and recovery encounters: paradox or peril?’’, Journal of Service Research, Vol. 1 No. 1, pp. 65-81. Sudman, S. and Bradburn, N. (1973), ``Effects of time and memory factors on response in surveys’’, Journal of the American Statistical Association, December, pp. 805-15. Szmigin, I. and Bourne, H. (1998), ``Consumer equity in relationship marketing’’, Journal of Consumer Marketing, Vol. 12 No. 6, pp. 544-57. Tax, S.S., Brown, S.W. and Chandrashekaran, M. (1998), ``Customer evaluations of service complaint experiences: implications for relationship marketing’’, Journal of Marketing, Vol. 62, April, pp. 60-76. Webster, F. Jr (1994), Market Driven Management of Marketing, John Wiley and Sons, Inc., New York, NY. Zaichkowsky, J.L. (1994), ``The personal involvement inventory: reduction, revision and application to marketing’’, Journal of Advertising, Vol. 23 No. 4, pp. 59-70. Zeithaml V.A., Berry, L.L. and Parasuraman, A. (1996), ``The behavioural consequences of service quality’’, Journal of Marketing, Vol. 60, April, pp. 31-46. Zemke R. (1993), ``The art of service recovery: fixing broken customers ± and keeping them on your side’’, in Scheuing, E. and Christopher, W. (Ed.), The Service Quality Handbook, Amacom, pp. 463-76.
&
JO U R N A L O F C O N S U M E R M A R K E T IN G , V O L . 18 N O . 4 20 01
3 45
This summ ary has been provided to allow managers and executives a rapid appreciation of the content of this article. Those with a particular interest in the topic covered m ay then read the article in toto to take advantage of the more comprehensive description of the research undertaken and its results to get the full benefit of the material present
Executive summary and implications for managers and executives I really can’t be bothered to change my bank It’s all too much hassle. The bank may give lousy service but we’re not changing banks because it means sorting out dozens of direct debits, arranging for changes to the payroll at work, cancelling cheques and dealing with the old bank who aren’t about to rush about trying to help. And what’s worse, we can’t be sure the new bank will give us any better service. So we don’t change and we put up with the queues, mistakes and unhelpfulness of our current bank. Colgate and Lang reveal that this ``apathy’’, as they term it, is the biggest barrier to people switching supplier ± at least in the financial services industry. There are other factors involved but this ``apathy’’ is the biggest influence keeping people from changing. As marketers we need to consider how this finding should influence the way in which we communicate and serve our customers. In addition we should look at ways to reduce the hassle involved in switching, thereby allowing customers to join us from a competitor. However, the other factors that influence the decision not to switch ± financial or psychological negatives, the strength of relationships and the firm’s ability to recover from service failure ± also need to be incorporated into our marketing activities. Service quality and good communications Good service and the right communications are the first line of defence against customers leaving. It is self-evident that the service performance of a firm affects the relationship with customers and, where that performance is good, the customer has less reason to look elsewhere to receive that service. However, we cannot overlook the importance of communication with customers as part of the service . The face-to-face contact over the bank counter may be great but if we send poorly written letters we’re undermining that good service. It is the complete service that matters, not just the individual contacts with the customer. A strong relationship makes for a better chance of keeping the customer ± but it’s not enough on its own. Alongside the service and relationship elements, firms also create barriers to switching by imposing financial penalties on switchers and through the psychological barriers implicit in a long relationship. These barriers are very significant and competitors have to overcome them if they are to succeed in attracting customers to switch. Indeed, some companies do use the tactic of paying financial penalties where they exist for switching customers. Apathy ± why should I bother, it’s not that important? Removing the inertia that keeps people from switching ± and maintaining that apathy ± represents the heart of switching or anti-switching strategies. Put simply, encouraging customers to take the easy route and stay is a sensible approach for firms. And, where we want to encourage people to change, we need to take away the hassle and make the switch really easy. Recently, I changed suppliers for gas and electricity. Why? Because my new supplier not only was cheaper but offered to do all the leg work, sorting out direct debits, billing and meter reading. All I had to do was sign the form. If
3 46
JO U R N A L O F C O N S U M E R M A R K E T IN G , V O L . 18 N O . 4 20 01
this company had not given that service I wouldn’t have switched suppliers, since I cannot spare the time to get all the details sorted out. This approach ± removing the hassle barrier ± must bring advantages to the ``poacher’’. And the current supplier has little defence, assuming that there is no financial barrier to the switch. The only protection is a sense of loyalty ± or at least inertia ± or a lack of trust in the potential new supplier. Indeed, Colgate and Lang suggest that raising the level of trust that consumers have in the firm presents an additional defence against switching. At the same time as we consider our response to switching customers we should examine the profitability of those customers and the costs of keeping them set against the costs of losing them. There is no reason to keep customers when those customers do not provide a significant benefit to the business. In some cases we might even be better off without them! Customers will leave ± just don’t make it easy for them In the end we have to accept that customers will leave. And also that this departure is not always our fault ± our service might have been great but it’s no good if the customer’s moving to the other end of the country. Nevertheless, we shouldn’t make it easy for the customer to go and we should make some effort to keep the customer. We need to consider all the elements discussed above ± building barriers through the structure of the product, in the complexity of the relationship and in the service we provide. We need to offer more reasons to stay, so as to counteract firms that will seek to ``buy’’ new customers through ``payingoff’’ the barriers. The longer we hold on to a customer and the more effort we put into our relationship with that customer, the less likely it is that their desire to switch will overcome the inertia and apathy that keep them with us. (A preÂcis of the article ``Switching barriers in consumer markets: an investigation of the financial services industry’’. Supplied by Marketing Consultants for MCB University Press.)
JO U R N A L O F C O N S U M E R M A R K E T IN G , V O L . 18 N O . 4 20 01
3 47
