Online loyalty and its interaction with switching barriers

Dilip Mutum a,n, Ezlika Mohd Ghazali b,1, Bang Nguyen c,2, David Arnott d,3

a Nottingham University Business School, The University of Nottingham Malaysia Campus, Jalan Broga, 43500 Semenyih, Selangor, Malaysiab Department of Marketing and Information Systems, Faculty of Business and Accountancy, University of Malaya, 50603 Kuala Lumpur, Malaysiac East China University of Science and Technology, 130 Meilong Road, Xuhui, 200237 Shanghai, Chinad Warwick Business School, The University of Warwick, CV4 7AL Coventry, UK

a r t i c l e i n f o

Article history:Received 30 April 2013Received in revised form26 August 2014Accepted 27 August 2014Available online 20 September 2014

Keywords:Online switching barriersOnline switching inducementsOnline loyalty

a b s t r a c t

The results of empirical research on online retail switching tendencies is quite mixed and only a fewhave specifically examined the presence, frequency or impact of switching barriers and switchinginducements in the context of online services. Empirical evidence shows that there is “stickiness tocertain sites” experienced by online customers and that they do less comparative shopping than mightbe expected. This paper conceptualises online switching behaviour as the interaction of barriers andinducements (both real and perceived) using Oliver's four-stage loyalty model. It also highlights the needto re-examine the concept of online loyalty and its interaction with switching barriers and inducementsin the online context.

& 2014 Elsevier Ltd. All rights reserved.

1. Introduction

The online retail market is a very important channel of choicefor customers worldwide. According to a report by the BostonConsulting Group (2012), the internet economy of the G20countries is expected to grow at more than 10 percent annuallyfor the next five years and contribute US $4.2 trillion to thecombined GDP of these countries in 2016. Thus, it is not surprisingthat there is a huge interest in enhancing the understanding offactors involved in building online customer retention. Out ofthese, switching barriers (SBs) have emerged as one of the mostimportant factors for online retailers to consider.

Unlike the physical brick and mortar shops, where there is agreater opportunity for building relationships (Bansal et al., 2004),retaining customers online is considered more difficult due to thenon-personal and transaction-based nature of the interactions.Varadarajan et al. (2008) notes that the relative ease of switchingonline accentuates the importance of building and maintainingSBs. However, the findings emerging from empirical research ononline switching behaviour is quite mixed. For example, Joneset al. (2000) found that switching barriers were important factors

influencing customers repurchase intentions under certain cir-cumstances. On the other hand, Holloway (2003) concluded thatswitching costs (one of the categories of SBs) are unimportant andnegligible.

Even though the concept of SBs has been discussed quiteextensively in marketing literature with commendable attemptsto explore the influence of SBs in the online market environment(Balabanis et al., 2006; Goode and Harris, 2007; Holloway, 2003; Liet al., 2007; Tsai and Huang, 2007; Yang and Peterson, 2004), thereis still a lack of consensus in terms of its definition, categories andeven measurement of the constructs. Furthermore very little effortwas made to identify and measure SBs specific to the onlineservices sector. In view of this, it was considered important toexamine consumer switching behaviour from an online servicessector perspective from both academic and practical perspectives.There is also a widespread assumption that switching barriers arealmost negligible in the online shopping context (Bakos, 1997). Thepopularity of online shopping is supposed to have created a levelplaying field where ‘competitors are just one click away’. Whilemost retailers acknowledge that having a loyal online customerbase is important and beneficial, a large number of online retailerslack a knowledge of the strategies required to retain customersand develop loyalty (Wilcox and Gurau, 2003). This indicates thatdeveloping loyalty is not as straightforward as some studies havesuggested.

This paper attempts to integrate past studies into a theoreticalframework for understanding and to classify customer switchingbehaviour, which is conceptualised in this paper as the interactionbetween SBs and the four-stages of loyalty based on Oliver's (1997)

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journal homepage: www.elsevier.com/locate/jretconser

Journal of Retailing and Consumer Services

http://dx.doi.org/10.1016/j.jretconser.2014.08.0120969-6989/& 2014 Elsevier Ltd. All rights reserved.

n Corresponding author. Tel.: þ6 03 8725 3754.E-mail addresses: dsmutum@gmail.com (D. Mutum),

ezlika.ghazali@gmail.com (E. Mohd Ghazali), bang.london@gmail.com (B. Nguyen),david.arnott@wbs.ac.uk (D. Arnott).

1 Tel.: þ6 03 7967 3972.2 Tel.: þ86 13761689258.3 Tel.: þ44 24 765 24487.

Journal of Retailing and Consumer Services 21 (2014) 942–949

model. It is expected to contribute to a clearer understanding ofthe role of switching barriers and the link to online customerloyalty.

2. Customer loyalty

Marketing practitioners and academics alike have emphasisedthat the most important goal of marketers is to generate custo-mers who are committed repeat-purchasers – in other words,customers who are loyal. This is crucial for the success of a firmbecause loyal customers enhance the firm's profitability(Reichheld and Teal, 1996), market share (Chaudhuri andHolbrook, 2001) and increase shareholder value (Sindell, 2000).Oliver (1999) described customer loyalty as the overall attachmentand deep commitment to product, brand, organisation or retailer.

The different phases of loyalty have been explored in quitesome detail (Jacoby and Chestnut, 1978; Dick and Basu, 1994).According to Harris and Goode (2004), one of the most compre-hensive appraisals of loyalty construct was provided by Oliver(1997) who conceptualised loyalty as developing in four phases,namely, cognitive loyalty, affective loyalty, conative loyalty andaction loyalty. It was postulated (but not empirically tested) thatloyalty is not achieved until a customer shows high consistencythroughout the four distinct phases of loyalty (Oliver, 1997). Thereis a need to examine the four phases, namely, cognitive loyalty,affective loyalty, conative loyalty and action loyalty from an onlinemarketing perspective.

2.1. Cognitive loyalty

Cognitive loyalty (loyalty based on cognition only) refers to thebelief that a particular online retailer is preferable to others, abelief based solely on the information that customers have about aretailer's functional characteristics, such as costs and benefits(Oliver, 1997; Harris and Goode, 2004). In this phase customersare mostly exercising rational switching behaviour, weighing thecosts and benefits of both firms and competitors' offerings. Oliver(1997) argues that customers operating only at a cognitive level ofloyalty will be highly vulnerable to competitors' inducements. Thisis more so in the online market context where agent-basedservices such as shop-bots exist, which aggregate information onproducts and competitors, and which make switching decisionseasier for cognitive loyal customers (Pedersen and Nysveen, 2001).

2.2. Affective loyalty

Affective loyalty involves a liking for or a favourable attitudetowards a brand, based on cumulative episodes of experiencedsatisfaction. Attitude is a function of cognition, so affective loyaltyis stronger than cognitive loyalty and is based on the customers'cumulative experience of satisfaction that leads to a positiveattitudinal shift (Oliver, 1997). Customers can develop a highrelative attitude (‘like’) to an online retailer whilst still remainingreceptive to other competitors' overtures. A study looking at theantecedents of customer loyalty towards e-mail service providers,found that emotions indirectly influence affective loyalty. Theauthors concluded that customer loyalty could be enhanced byinvesting in customer emotions and e-trust (Ranganathan et al.,2013).

2.3. Conative loyalty

Conative loyalty refers to customer's behaviour al intention tokeep purchasing a brand in the future. Having a favourableattitude towards a brand (effectively loyal) may not necessarily

lead to intention to buy (conatively loyal) the brand in the future.Although conative loyalty is stronger than affective loyalty, custo-mers may still consider alternative offerings (Oliver, 1999). How-ever, the likelihood of buying due to other online competitors'inducements is lower when compared to cognitive and affectiveloyalty.

2.4. Action loyalty

This is the final phase of loyalty, which relates to transformingintention into action, and the readiness of the customer to over-come obstacles to purchasing a brand. Similar to physical marketenvironment, the behaviour of customers online will becomeroutine after some time as they become accustomed to purchasewith a particular site. Once that happens, the decision processbecomes ‘habitual’ (Fornell, 1992). Oliver (1997) further arguesthat this habit or ‘routinised response behaviour’ of action-loyalcustomer means that they are almost immune to competitors'inducements to switch, as they will engage less (if not at all) in anysearch for and evaluation of competitors' marketing communica-tion. In the online context, the vast majority of online customersbookmark their favourite retailers' websites and visit them morethan those of competitors (Anderson and Srinivasan, 2003). Overtime, as trust is established, the positive influence of satisfactionon loyalty will increase significantly and the customer will transitfrom problem solving to relying on well-established habitualpurchasing behaviour (Johnson et al., 2003). In other words, thebehaviour of customers online will become routine after sometime as they become accustomed not only to purchasing through aparticular retailer's website, but also to navigating around it.

3. Switching barriers

The concept of SBs has been discussed quite extensively inmarketing literature. However, there is a lack of consensus interms of its definition, categories and even measurement of theconstructs (Balabanis et al., 2006; Goode and Harris, 2007;Holloway, 2003; Li et al., 2007; Tsai and Huang, 2007; Yang andPeterson, 2004). A synthesis of past empirical research of SBs inthe online environment context is provided in Table 1.

It is obvious from the table that there are almost as manyperspectives of switching barriers as there are researchers.Although most authors agree that switching barriers is concep-tually a multidimensional construct encompassing several cate-gories and dimensions, some authors utilise only one globalmeasure of switching barriers (Ranaweera and Prabhu, 2003;Shin and Kim, 2008). Fornell (1992) argued that a direct measureof switching barriers is difficult to obtain as switching barriersinclude all costs associated with deserting one supplier in favourof another. Thus, SBs constitute all the reasons that prevent orhinder customers from switching to competitors. On the otherhand, SBs were defined by Jones et al. (2000) as “any factor thatmakes it more difficult or costly for consumers to change provi-der”. Specifically, it is the extent to which customers experience asense of being locked into the relationship with a service providerbecause of the economic, social and psychological costs associatedwith switching (Allen and John, 1990; Tsai and Huang, 2007). Dueto the perceived extra costs of switching, these barriers reduce thelikelihood of customers leaving the service provider, althoughcertain factors like below-average service performance mayencourage this (Jones et al., 2000). This paper has adopted SBsbased on Jones et al. (2002), who has divided customer perceivedSBs into three major components, namely, perceived switchingcost, attractiveness of available alternatives and interpersonalrelationships. However, an examination of customers who shop

D. Mutum et al. / Journal of Retailing and Consumer Services 21 (2014) 942–949 943

online would require modifications and adaptations in terms ofmeasurements.

Customers' perceptions of SBs will influence their behaviour,not objective barriers (Morgan and Hunt, 1994) and as such SBs inthis paper specifically refer to SBs as perceived by customers. Someof the barriers identified in previous literature include perceivedswitching costs (Burnham et al., 2003; Jones et al., 2002), per-ceived risks (Fornell, 1992), interpersonal relationships (Joneset al., 2000), the attractiveness of alternatives (Jones et al.,2000), switching inducements (Grace and O'Cass, 2001;Keaveney, 1995) and so on.

The concept of switching barriers is well established and hasstarted to attract interest in recent years. There have been somecommendable attempts to explore the influence of SBs in theonline market environment (Balabanis et al., 2006; Goode andHarris, 2007; Holloway, 2003; Li et al., 2007; Tsai and Huang, 2007;Yang and Peterson, 2004). These include few studies have alsolooked at online SBs by incorporating variables which had beenidentified in earlier (offline) studies into their overall conceptual

frameworks. For instance, Goode and Harris (2007), while lookingat the factors which influences and moderates online behaviour alintentions, found that switching barriers and inducements moder-ate the link between all the antecedents studied. Furthermore, Tsaiet al. (2006) found that SBs mediate the links between theantecedents of several types of switching behaviour and customerretention in the online environment. However, the review of theliterature revealed several conceptualisation and operationalisationissues with respect to switching barriers, prompting the focus inthis study on further exploration of the very nature of the conceptand its role in promoting online customer retention. Furthermore,very little effort was made to identify and measure SBs specific tothe online service environment.

By looking at the interaction between loyalty and switchingbarriers, several studies confirm the relationship between SBsand customer retention (Balabanis et al., 2006; Goode andHarris, 2007; Jones et al., 2000; Li et al., 2007; Tsai et al., 2006).There is some evidence that switching barriers are positivelyrelated to loyalty (Ping, 1993, 1997) and Fornell (1992) was one

Table 1Empirical research on switching behaviour in the online service environment.

Researcher Switching barriersmeasured

Context andfindings

Primary contributions Findings

Zhanget al.(2008)

� Attractivealternative

� Sunk costs

Blog service Examining switching barriers of blog service providersbased on Bansal et al.'s (2005) push-pull-mooringframework

Attractive alternative is a strong factor affectingintention to switch

Goode andHarris(2007)

� Switching costs� Switching

inducements

Research agencydatabase:consumers of onlinebook website

Examining the antecedents of behavioural intentionswith both switching costs and switching inducementsas moderators

� Switching inducement moderates therelationship between (a) ‘favourableinterpretation of firm's banner advertisements’and (b) ‘perceived online security’ and conativeloyalty

� Switching costs moderate the linkagesbetween (a) ‘perceived online reputation’ and(b) ‘favourable interpretation of firm's banneradvertisements’ and conative loyalty

Li et al.(2007)

� Comparison level ofalternative

� Non-retrievableinvestment

Internet users:student subjects

Distinguish stayers and switchers along fiverelationship dimensions according to Wilson's (1995)model

The decision to stay or leave a website depends onthe level of commitment, trust, satisfaction,comparison level of alternative non-retrievableinvestment

Tsai et al.(2006)

� Expected value-sharing

� Perceivedswitching costs

� Community-building

Customers of ane-retailer in Taiwan

Testing a conceptual framework that considers theantecedents of switching barriers and overallsatisfaction, and their roles as drivers of onlinecustomer retention

Perceived switching costs and communitybuilding exert the greatest impact on repurchaseintentions through switching barriers and overallsatisfaction

Balabaniset al.(2006)

Convenience, economics,emotional, speed,familiarity, unawareness,parity

Online shoppers:student subjects

Examines switching barriers and satisfaction as theantecedents of online loyalty

Impact of switching barriers varies at differentlevels of customer satisfaction. What customerconstitutes a switching barrier also differs atdifferent levels of satisfaction

Yang andPeterson(2004)

� Switching costs Online financial andretailing services

Examines the moderating effects of switching costs oncustomer loyalty through satisfaction and perceivedvalue

The moderating effects of switching costs on theassociation of loyalty and satisfaction andperceived value are significant when the level ofsatisfaction or perceived value is above average

ThatcherandGeorge(2004)

� Artificial costs� Learning costs� Transaction costs

GVU datasets of webusers

Exploring the direct influence of switching coststoward web shoppers' commitment

Vendor may foster commitment if strategies arefocused on increasing transaction costs andsatisfaction. Vendor may be vulnerable to newentrants when focusing on artificial costs

Chen andHitt(2002)

� Relationshipservice –

personalisation� Overall costs

Online brokerage Measures the level of switching costs and brandloyalty for online service providers using randomutility modelling framework

Online consumers' system usage and the breadthand quality of alternative online service providerswere significant predictor of switching behaviour

Mathwick(2002)

� Switching effort� Contract barriers� Continuity barriers

GVU datasets:experience onlineshoppers

Exploring the perceived magnitude of switching costson four groups of online shoppers

The stronger the exchange norms governingonline interaction, the higher the real or perceivedswitching costs created through contract,continuity barriers, or perceived switching effort

D. Mutum et al. / Journal of Retailing and Consumer Services 21 (2014) 942–949944

of the pioneers to consider SBs as an important factor besidessatisfaction, in influencing customer loyalty. Hirschman (1970)also argues that the loyalty tendency will increase when there arelimited options to exit a relationship and when the SB is high.Intuitively, there should be some distinction in the nature ofloyalty when a customer ‘wants’ to stay with a relationshipbecause of firm's service superiority as compared to a customer‘having’ to stay because of firm's monopoly or market power (seeHirschman, 1970; Julander and Söderlund, 2003). Thus, followingthe reasoning provided by Jones et al. (2007), we divide SBs intotwo, namely, negative barriers and positive barriers.

3.1. Attractiveness of available alternatives

According to Oliver (1997, p. 395), consumers operating at thecognitive level are hypothesised to be more susceptible to switch-ing caused by marketing overtures. The attractiveness of availablealternatives (AAA) construct is defined as the customer perceptionswith regards to the extent to which viable competing alternativesare available in the marketplace (Jones et al., 2000). This constructis based on the customer's perception of other available companieswho could alternatively provide the product or service in question.As such, it is not a measure of actual intensity of competition butrather the attractiveness of possible alternatives as perceived bycustomers (Holloway and Beatty, 2003).

Past research on channel relationships has shown that per-ceived AAA is positively associated with exit and negatively withloyalty (Ping, 1993; Rusbult et al., 1982). In addition, the traditionaleconomics model of buying behaviour has classically posited thatcustomers will always base their decision on the costs and benefitsrelative to other competing alternatives that are available in themarket, that is when the perception of available alternatives is low,the perceived benefits of changing provider are also low, therebyleading to retention. Furthermore, Colgate and Norris (2001)suggested that a lack of perceived differences between alternativescan also act as a switching behaviour. They found that thosecustomers who switch providers tend to perceive greater differ-entiation between different firms. AAA has also been defined byGoode and Harris (2007) as “switching inducement”. It is in thislight that AAA is seen as a barrier to switching. The AAA constructis central in online exchange research as it has been argued that,developing online loyalty by reducing the perceived AAA, shouldbe an important goal of online firms (Rigby et al., 2002). This isbecause online shoppers are more susceptible to switching

inducement than offline shoppers (Goode and Harris, 2007). Inline with Oliver's (1997) argument that cognitive loyal customerswill be more susceptible to switching due to competitors' induce-ment in terms of benefits, such as lower cost and higher quality,we assume that the relationship between cognitive loyalty andaffective loyalty will be weaker under the situation of attractivealternatives. Moreover, Oliver (1997) also argues that the dete-rioration of customer commitment to a brand would impact theconative stage of loyalty. One of the primary reasons of erodingcommitment is an increased attractiveness of competitors' brand(Sambandam and Lord, 1995). On the other hand, the less theperception of competitors' attractiveness, the more committed thecustomers with the current provider, which translate to purchaseintention. Thus, we assume that AAA will moderate the relation-ship between cognitive and affective loyalty. In other words, as theAAA increases, the relationship between cognitive loyalty andaffective loyalty will be weaker and vice versa. This leads to ourfirst proposition, namely

Proposition 1. As the AAA increases, the relationship betweencognitive loyalty and affective loyalty will be weaker.

Oliver (1997) also put forward that the deterioration of custo-mer commitment to a brand would impact the conative stage ofloyalty. One of the primary reasons of eroding commitment is anincreased attractiveness of competitors' brand (Sambandam andLord, 1995). On the other hand, the lesser the perception ofcompetitors' attractiveness, the more committed the customerswould be with their current provider, which would translate topurchase intention. Therefore we propose that

Proposition 2. As the AAA decreases, the relationship betweenaffective loyalty and conative loyalty will be stronger.

4. Perceived switching costs

Porter (1980) defines switching costs as the “one-time costsfacing the buyer of switching from one supplier's product toanother's”. There is some confusion between the terms ‘switchingcosts’ and ‘switching barriers’ (Balabanis et al., 2006), with someauthors using the terms interchangeably (e.g. Mathwick, 2002)(see Table 1). Goode and Harris (2007, p. 157) pointed out thatthere are “subtle differences between switching barriers andcosts” but failed to describe any clear differences. Differentcategories of switching costs have also emerged. Fornell (1992)

Phase 3Phase 2

Phase 1

Loyalty

Cognitive(belief)

Affective(liking/feel)

Conative(behavioural

intention)

Action(habit/inertia)

Attractiveness of Available Alternatives

Artificial Cost

Time & Effort Barrier

Relational Bond

Uncertainty Cost

Perceived switching costs Perceived switching inducements

Fig. 1. Conceptual framework.

D. Mutum et al. / Journal of Retailing and Consumer Services 21 (2014) 942–949 945

for instance describes switching costs as “all costs (financial,psychological, learning, etc.) associated with deserting one sup-plier in favour of another”. He contends that switching costs mayinclude search costs, transaction costs, learning costs, cognitiveeffort, emotional costs, loyalty discounts, customer habit and thefinancial, social and psychological risks experienced by the custo-mer when deciding to change provider. These costs can either bereal or perceived and monetary or non-monetary. Switching costsin this paper refers to perceived switching costs. In this paper,perceived switching costs is classified under four different dimen-sions, namely, artificial cost, uncertainty cost, relational bond and‘time and effort’ barrier (refer to Fig. 1). The dimensions aredescribed in detail below.

4.1. Artificial switching costs

These switching costs are mentioned in the literature as thecosts that arise due to actions initiated by a supplier in order toretain customers and make it more costly to switch suppliers(Klemperer, 1987). Artificial cost is also roughly equivalent toBurnham et al.'s (2003) financial dimension and Jones et al.(2002) ‘loss benefit cost’ dimension. They are the perceived costsrelated to the potential loss of special discounts and uniquebenefits if the consumer switches from her or his current serviceprovider to another. In the online context, the closest examples arefrequent flyer programs and repeat purchase discounts. Switchingsuppliers means that customers will lose these loyalty rewards.

Past studies on brand switching behaviour have demonstratedthat customers who switch to a firm because of extrinsic factors(such as points accumulations or coupons or even price) mayexhibit lower levels of satisfaction and less future purchaseintention as compared to customers who switch because ofinternal factors (such as dissatisfaction or desire to try a newbrand) (Mazursky et al., 1987). Therefore, we can assume that thelink between cognitive loyalty and affective loyalty is weakerwhen the customer decides not to switch (stay) because ofartificial costs as the customer is attached to the brand only atthe rational level. Therefore we posit that

Proposition 3. As the perceived artificial cost increases, the linkbetween conative and action loyalty will become stronger.

In addition, past research has shown that loyalty cards do notaffect customer loyalty by enhancing perceived performance orsatisfaction, but they do strengthen the relationship betweenbuying intention (conative loyalty) and the actual buying beha-viour (action loyalty) (Evanschitzky and Wunderlich, 2006). Thus,it is highly likely that as the perceived artificial cost increases, thelink between conative and action loyalty will become stronger.

Proposition 4. As the perceived artificial cost increases, the linkbetween conative and action loyalty will become stronger.

4.2. Uncertainty costs

These costs refers to the customer's perception of the costs orpotential losses associated with accepting the risk of potentialnegative outcomes when switching to an untested provider aboutwhich the customer has little or insufficient information (Colgateand Lang, 2001; Guiltinan, 1989; Klemperer, 1995). This constructis roughly equivalent to “economic risk costs” (Burnham et al.,2003). Risk and uncertainty are higher when there is a lack of face-to-face interaction of the internet market. Thus uncertainty costsshould be more important in service over the internet wheresecurity and privacy issues and delivery service are highly essen-tial (Zeithaml et al., 2002). Reasons preventing online customersfrom re-registering with too many websites are not only due to the

hassle factor but also due to the security and privacy risk issues(Balabanis et al., 2006). Jones et al. (2002) postulated thatcustomers' perceptions of risk and uncertainty are higher whenservices are heterogeneous (differentiated) in nature and thevalue of offering is difficult to judge. They also suggested thatcumulative positive experience with a service provider willaccentuate the perceptual uncertainty to switch. This suggeststhat as perceived uncertainty cost increases, the link betweencognitive and affective loyalty will become stronger. Furthermore,the link between affective and conative loyalty will becomestronger as well. In line with these arguments we put forth thefollowing:

Proposition 5. As perceived uncertainty cost increase, the linkbetween cognitive and affective loyalty will become stronger.

4.3. Relational bond

This dimension can be further differentiated into interpersonalrelationships and brand relationship loss costs. Jones et al. (2000)proposed interpersonal relationship with the supplier's employeesas a SB. Due to the self-service nature of online shopping, theabsence of direct human contacts deems interpersonal relation-ship between customer and firm's employee to be very minimal.Following the recommendation of Yen and Gwinner (2003), therelationship and perception of friendship is re-conceptualised inthis paper as the interpersonal relationship between shoppers orusers of the website. Some companies (e.g. Amazon.com) havecreated online communities that can foster relationships betweenthe website users. Therefore, the interpersonal relationshipbetween users can act as SB and prevent a customer from leavingthe service provider. On the other hand, Brand relationship losscosts Burnham (1998) has identified the feeling of loss in leaving abrand as one dimension of relational cost that can stop customerfrom defecting. Based on Porter (1980) and few others, he refers tothis cost as the customer's perception of “psychological lossesassociated with breaking the bonds of identification that havebeen formed with the brand or company with which the customerhas associated”. It should be noted that brand commitment comesfrom emotional involvement represented by relational switchingbarriers. In line with Oliver's (1997) arguments that affectiveloyalty contains some involvement by the customer and thisaspect is more salient at the conative stage of loyalty. In otherwords, as the perceived relational bond increases, the linkbetween affective and conative loyalty will become stronger. Thisleads to our next proposition.

Proposition 6. As the perceived relational bond increases, the linkbetween affective and conative loyalty will become stronger.

4.4. Time and effort barrier

The time and effort barrier is the last dimension of perceivedswitching costs in the conceptual framework. This dimension ismade up of various costs including pre-switching search cost,post-switching learning cost, setup cost and sunk cost.

4.4.1. Search costShapiro and Varian (1999) have identified search costs as a type

of switching costs and as a potential reason for customer lock-in.By examining the literature, two components of Pre-switchingsearch cost have been identified in this paper, namely, physicalsearch cost and cognitive search cost (Johnson et al., 2003).Physical search cost refers to the perception of the time and effortrequired to seek the information necessary to make an informedswitching decision, while cognitive search cost refers to the

D. Mutum et al. / Journal of Retailing and Consumer Services 21 (2014) 942–949946

perception of time and effort expended in making sense ofinformation sources and analysing the information that has beencollected (Johnson et al., 2003). Some researchers call this the‘evaluation cost’ (Burnham et al., 2003; Jones et al., 2002).

It is more difficult, inefficient and time consuming for custo-mers to search for viable competing alternatives offline as com-pared to the online environment where product informationacquisition is much easier. Shopbots and search engines have alsomade information searching and comparisons simpler andquicker for customers. However, Johnson et al. (2004) has demon-strated that the internet does not produce a high amount ofsearching. In fact, online customers engage in fewer comparisonsand tend to remain attached to the websites that they arefamiliar with (Smith, 2002). For example, the results of a locked-in study showed that online customers displayed short-termorientation that leads them to select a favourite site to userepeatedly even though this choice may not result in the lowestprice for the sought product (Johnson, 2003). Even if theoverall level of physical search cost is reduced, a previously usedwebsite still holds a relative cost advantage that influencesswitching behaviour (Zauberman, 2003). This brings us to thesecond type of search cost, the cognitive search cost. The low entrybarrier of firms operating online has produced huge amounts ofinformation. Balabanis et al. (2006) described cognitive search costas being related to the perception of time and effort needed toanalyse and verify the credibility of large quantities of onlineconsumer reports, reviews and forums that may sometime beinconsistent, or to comprehend the technical specifications orjargon in the absence of expert advice. New information isprocessed only when it is felt to be significant and/or relevant(Lee et al., 2000) in coping with the problem of informationoverload.

4.4.2. Learning costAnother cost which makes up the time and effort barrier

dimension is learning cost (Burnham, 1998) should also beexamined. On the other hand, Klemperer (1987) describes learningcosts as any costs (including time) that are needed in learning touse one firm's product line or brand (Guiltinan, 1989). Thisincludes all the costs associated with customers having to adaptto and familiarise themselves with conducting transactions on anunfamiliar website, such as the time and effort expended inacquiring customer know-how as customers adapt to the newprovider (Burnham et al., 2003; Jones et al., 2002). According toJohnson et al. (2003), customers stay with a website to avoid theinconvenience and hassle of learning to navigate a new one.Having learned to use the website increases the attractiveness ofthe website as compared to alternative sites and thus raises thecost of switching to another. The more experience the customergains of a site over time the stronger will be the ‘cognitive lock-in’of that customer (Johnson et al., 2003, 2004). Just as a firm canlock in a customer with high physical cost in the offline market, itis expected that firms can lock in customers with high cognitivecost similarly in the online market place.

4.4.3. Setup costSetup cost was described in the past literature as the cost of

beginning or initiating a relationship with a new provider(Burnham, 1998). In the internet environment, if customisation ishigh, the customer may seek to avoid change due to the set-upcosts often incurred when switching to a new e-retailer. Balabaniset al. (2006) also found that internet shoppers dislike registeringto too many internet stores due to the hassle of doing that.

4.4.4. Sunk costSeveral researchers have identified that prior investment in an

exchange relationship as one barrier to switching (Bendapudi andBerry, 1997; Ping, 1997). This represents customer perception of allthe irrecoverable time, effort, and money invested to establish andmaintain a relationship and is similar to the sunk costs of Joneset al. (2002). Although it may be economically irrelevant, sunkcosts represent a prior investment and psychologically importantfor customers in their decision to stay or leave (Guiltinan, 1989).Each facets of switching cost that have been identified, willbecome sunk after the customer switch to another provider. Forinstance, the past time and effort involved in going through alengthy registration process, learning how to navigate a site andpersonalising a site may prevent a customer from changing serviceproviders. Degeratu et al. (2000) also found that there is less brandswitching online, especially when online consumers utilise theirpre-set personal list to make a purchase.

The inertia brought by information overload and time pressureexperienced by customers on the internet (Zauberman, 2003)impede searching and evaluating alternative stores and reduceswitching. According to Oliver (1997), under the condition ofaction loyalty, customers will not engage in search and evaluationand therefore they can be considered as immune to competitors'inducements. Further, he holds that action loyalty includes routi-nised and habit behaviour. Oliver (1997) also argues that the keysustainers of action loyalty towards current provider are sunkcosts where actual purchase will be more likely for customers whofaced sunk costs. In line with all these arguments, it is highly likelythat as the perceived time and effort cost increases, the linkbetween conative and action loyalty will become stronger. Thuswe have the final proposition:

Proposition 7. As the perceived time and effort cost increased, thelink between conative and action loyalty will become stronger.

5. Discussion and avenues for future research

Despite the growing volume of research related to the concept ofswitching costs and barriers, the SBs that online customers face andtheir actual impact on them remain largely misunderstood. Previousresearch has shown that satisfaction may not be the best predictor ofcustomer loyalty and that the presence (or lack) of switching barriersmay be the reason a customer stays with (or leaves) a firm.

Oliver's four-stage loyalty model was further expanded to includeonline switching (refer to Fig. 1: conceptual framework). This paperconceptualises switching behaviour in the online context in terms ofthe relations between various SB dimensions and the various transi-tion phases of the four-stage loyalty model of Oliver (1997). Further-more, past studies on switching behaviour have failed to distinguishbetween consumers at various levels of loyalty by assuming that theyare all similar. Online switching is seen as the interaction of barriersand inducements (both real and perceived) and specifically, attractive-ness of available alternatives and perceived switching costs (refer toFig. 1: Conceptual Framework).

A summary of the various propositions in this paper is furtherpresented in Table 2.

It is anticipated that future empirical testing of the effects ofbarriers and inducements on the online loyalty development processwill add to our understanding of both the conceptual and practicalaspects of loyalty and switching behaviour in various online market-places. In order to stimutate thought for future research, four potentialareas of scholarly enquiry have been identified.

1. Future research should examine whether the various barriersand inducements moderate the three transition phases as

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customers move from cognitive (belief) to action (habit orinertia). For example, two specific research questions includea. Does AAA moderate the relationships between conative and

action loyalty?b. Does the time and effort barrier moderate the relationship

between affective and conative loyalty?2. There are two main types of online retailers: pure-play online

retailers and retailers with both online and offline operations(brick-and-click retailers). While increasing emphasis inresearch and publications has been placed on issues relatingto online customer retention in recent years, most of thesestudies have not empirically differentiated between issuesaffecting pure-play internet companies and bricks-and-clickcompanies. It is expected that different types of online retailerwill affect satisfaction and customer retention to a certainextent. Holloway (2003) concludes that the customer relation-ship with bricks-and-click retailers is stronger than withretailers with only a virtual store-front. Failing to differentiatebetween these two types of online retailers in a loyalty studymay distort the result or lead to over-estimation of relation-ships in a research model. This is because the brand name,physical presence and tangibility of the retailer's offlinebranches are likely to enhance a customer's familiarity withits online counterparts as well as the brand equity of the onlinestore (Pan et al., 2002). Furthermore, most of the studies onswitching behaviours have looked at traditional offline contextsand with online studies frequently using samples consisting ofa mixture of customers from brick-and-click (with both offlineand online stores) and pure-player internet (internet only)firms. It would be interesting to see whether there are anydifferences between brick-and-click and pure-player internetfirms with regards to switching behaviours.

3. Past studies in the area of consumer behaviour, have generallyassumed that habit or inertia and spurious loyalty are analo-gous (Dick and Basu, 1994) because both types of behaviouroccur, by and large, without a clear motive or intention (Ji andWood, 2007; Wood and Neal, 2009). Further studies can alsoexamine whether this is true in the online service contextas well.

4. Drivers of habit formation. Finally, the role of habit in theonline context has rarely been tested empirically in consumerbehaviour literature and future studies should examine thedrivers of habit formation and the role of satisfaction in theprocess.

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Table 2Summary of propositions.

No. Proposition

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