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Extending the prevalent consumerloyalty modelling: the role of habit

strengthSvein Ottar Olsen

Troms Business School, University of Troms, Troms, Norway

Ana Alina Tudoran and Karen BrunsAarhus School of Business and Social Sciences, Aarhus University,

Denmark, and

Wim VerbekeGhent University, Ghent, Belgium

Abstract

Purpose This study aims to address the role of habit strength in explaining loyalty behaviour.

Design/methodology/approach The study uses 2,063 consumers data from a survey inDenmark and Spain, and multigroup structural equation modelling to analyse the data. The paperdescribes an approach employing the psychological meanings of the habit construct, such asautomaticity, lack of awareness or very little conscious deliberation.

Findings The findings suggest that when habits start to develop and gain strength, less planningis involved, and that the loyalty behaviour sequence mainly occurs guided by automaticity and inertia.A new model with habit strength as a mediator between satisfaction and loyalty behaviour provides asubstantial increase in explained variance in loyalty behaviour over the traditional model withintention as a mediator.

Originality/value This study contributes to the existent literature by providing an extension of

the prevalent consumer loyalty theorizing by integrating the concept of habit strength and bygenerating new knowledge concerning the conscious/strategic and unconscious/automatic nature ofconsumer loyalty. The study derives managerial implications on how to facilitate habit formation andhow to influence habit-based versus intention-based loyalty behaviour. The external validity of thisstudy is assured by nationwide representative samples in two countries.

Keywords Intention, Habit strength, Loyalty,Structural equationmodelling, Food,Consumer behaviour,Customer loyalty

Paper typeResearch paper

1. IntroductionResearch on marketing argues that strategies to gain consumer loyalty and to preventconsumers from switching to a competitive product are essential business questionstoday (Reinartzet al., 2005). The need to understand what drives consumer loyalty hasspawned a number of publications examining the determinants and mediators ofconsumer loyalty behaviour (Ballet al., 2004; Chiou and Droge, 2006; Evanschitzky andWunderlich, 2006; Gustafssonet al., 2005; Yi and La, 2004).

The current issue and full text archive of this journal is available at

www.emeraldinsight.com/0309-0566.htm

This work was performed within the EU FP6 Integrated Project SEAFOODplus, contract no.FOOD-CT-2004-506359. The financing of the work by the European Union is gratefullyacknowledged.

The first two authors contributed equally to this study.

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Received 8 June 2010Revised 20 February 2011

Accepted 6 May 2011

European Journal of Marketing

Vol. 47 No. 1/2, 2013

pp. 303-323

q Emerald Group Publishing Limited

0309-0566

DOI 10.1108/03090561311285565


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Past research on the psychological process that drives loyalty behaviour has mainlyfocused on the deliberate or goal-directedness intentions mechanism (Oliver, 1999;Pritchardet al., 1999). For example, Olivers (1999) model assumes that product loyaltyis the outcome of active planning, which starts with episodes of positive cognition and

affect towards a product or brand, and ends with a strong commitment (intention)directed towards repeatedly purchasing the same product/brand. While plausible inthe case of less frequent behaviours or in the initial stages of product adoption, thisassumption may not be applicable to continued behaviours or behaviourscharacterised by frequent purchases (such as food and drink purchasing andconsumption), as it ignores the fact that frequently performed behaviours in stablecontexts become habitual and thus automatic over time (Limayemet al., 2007; Ouelletteand Wood, 1998). As argued by Webb and Sheeran (2006) and others, when behaviouris performed in stable contexts and for low-involvement and frequent purchases,consumers behaviour can be initiated and executed without needing the personsconscious intent and guidance (Webb and Sheeran, 2006, p. 261). Consumers tend tobuy the same brands of products across different shopping episodes, the same amountat a given retail store across repeat visits, and consume similar types of foods in a mealacross days (Wood and Neal, 2009). Habits but not intention hide the most commonform of repeat purchase or repeat consumption (Triandis, 1980). Habits develop andgain strength by satisfactory repetition, and over time become automatic, so thatrepeated behaviour can occur without awareness and self-instruction (Wood and Neal,2009). Therefore, ignoring the habit-persistence effects may systematicallyoverestimate the intentional product/brand loyalty (Seetharaman, 2004).

The overall objective of this work is to investigate the key role of habit strength inloyalty behaviour in the context of food consumption behaviour. More specifically, theobjectives are:

. to introduce the most prevalent consumer loyalty model in the field of marketing

(Oliver, 1999), highlighting its strengths and shortcomings, and to extend thecurrent theorizing on loyalty by integrating the notion of habit strength as amediator between cumulative satisfaction and loyalty behaviour; and,respectively

. to test this extended model empirically and compare its predictive ability withthe original model in the field of food consumption.

No explicit study to the authors knowledge takes this approach. A few studiesasserting the role of habit in loyalty behaviour present four major shortcomings. First,these studies lack a properly rigorous argument and substantiated theoretical base(Limayem et al., 2007). Second, there is a lack of precision in relation toconceptualisation and measurement of the habit notion. The habit construct is

typically conceived as past behavioural frequency or consecutive product purchase(Jolley et al., 2006; Ouellette and Wood, 1998; Seetharaman, 2004). The majority ofstudies omit the key aspects of habit, such as automaticity, lack of awareness or verylittle conscious deliberation (Verplanken and Orbell, 2003). Third, most of the previousstudies do not include actual behaviour in their models to test it empirically. Forinstance, Trafimow (2000) analyses the relationship between habit and intention tobehave as a proxy for actual behaviour, suggesting that future research shouldexamine these effects for actual behaviour. Fourth, habit is usually considered to be a

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negative construct both in daily life, e.g. referred to in a context of bad habits oraddiction (Lindblad and Lyttkens, 2002), as well as in some parts of the loyaltyliterature (Dick and Basu, 1994). The reason for this is the assumption that habit orinertia is something passive, convenient, a non-conscious form of retention associated

with spurious loyalty and different from true loyalty as an active, planned andconscious component of decision-making processes (Dick and Basu, 1994). However,habit can be a positive trait or outcome for consumers and businesses. People develophabits for convenience in order to save cognitive effort and time (Wood and Neal, 2009),which is not negative per se. Without habits, people would be doomed to plan, guideconsciously and monitor every action (Nealet al., 2006). Buying a brand or product orgoing to a particular restaurant out of habit may be a consequence of satisfied actionsover time (Triandis, 1980). On the other hand, the reason why individuals performactive planning, compare and evaluate may be because they lack skills and knowledgeof the product or because they became less satisfied over time and continue to considerand evaluate additional alternatives. Thus, buying, consuming or using a brand orproduct out of habit may be something businesses want to encourage, even though

over time it is less driven by active planning and a decision to act.Overall, the present study aims to address these limitations. The study contributes

to the marketing literature and practice by:

. providing an extension of the prevailing consumer loyalty theorizing byintegrating the concept of habit strength into the traditional Olivers (1999)model;

. by generating new knowledge concerning the conscious/strategic andunconscious/automatic nature of consumer loyalty behaviour; and

. by proposing managerial implications or guidelines on how to enable habitformation and how to influence habit-based versus intention-based loyaltybehaviour.

The external validity of this study is strengthened by the use of two representativesamples of consumers in two countries with different food consumption cultures(Denmark and Spain).

2. Overview of the frameworkOlivers (1999) hierarchical model of loyalty seeks to explain consumers behaviour torepurchase or repatronize a preferred product/service consistently over time (Oliver,1999). Olivers model positively relates satisfaction to loyalty behaviour through themediator role of intention. This perspective is in accordance with the traditionalattitude-intention-behaviour approach in social psychology (Ajzen, 1991), suggestingthat intention is the main causal mechanism behind the enactment of behaviour. In themarketing literature, most studies rely on hierarchical mediation through intention topredict consumer loyalty behaviour (Chiou and Droge, 2006; Evanschitzky andWunderlich, 2006; Han et al., 2008). However, Olivers model cannot account for thepossibility that long-practised behaviour may no longer be under motivationalconscious control, but rather influenced by antecedents other than intention. Toovercome this limitation and improve the explanatory power of the model further, weincorporate the habit-strength construct as an alternative less conscious automaticcause explaining loyalty behaviour. In developing our study, we begin with a brief

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discussion of the fundamental concepts. Next, we turn to discuss Olivers model (Model1 in Figure 1) and the proposed model (Model 2 in Figure 1) in more detail.

2.1 Satisfaction

Satisfaction is the consumers fulfilment response and the degree to which the level offulfilment is pleasurable (Oliver, 1999). Satisfaction is a key to building and retaining aloyal base of long-term consumers (Limayem et al., 2007). For satisfaction to affectloyalty behaviour, consumers should experience frequent or cumulative satisfactionepisodes (Oliver, 1999). Repeated satisfaction with a product, service or brand becomesaggregated over time and forms consumer cumulative global satisfaction with theproduct, service or brand (Johnson et al., 1995).

2.2 Loyalty intentionsLoyalty intention is a deeply held commitment to repurchase a specific product, serviceor brand (Oliver, 1999). Intention captures different motivational factors that influencehuman behaviour (Eagly and Chaiken, 1993). According to Ajzen (1991), intention is anindicator of how hard people are willing to try how much effort they are planning toexert to perform the behaviour. Loyalty intention is often used as a substitute forloyalty behaviour or as the ultimate dependent variable in satisfaction-loyalty studies(exceptions include, e.g. Gustafsson et al., 2005; Seiders et al., 2005). Mittal andKamakura (2001) question this practice and argue that intention and behaviour aredifferent constructs.

2.3 Loyalty behaviourLoyalty behaviour is the consumers tendency to patronize a product, revealed throughbehaviour (action) that can be measured and that impacts directly on sales (Worthingtonet al., 2010). Businesses pursue loyalty behaviour because such behaviour in consumers

can secure profitability and long-term sustainability (Reinartz et al., 2005). Marketingliterature defines and measures loyalty behaviour as the self-reported frequency ofpurchases/consumption over time (Gustafssonet al., 2005; Pritchard et al., 1999; Yi and

Figure 1.A conceptual frameworkfor examining themediating role of habitstrength on thesatisfaction-loyaltyrelation

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(1999) model. Oliver proposes a temporal approach to loyalty behaviour formation andargues that consumers go through different phases from cognitive loyalty and affectiveloyalty (satisfaction) through loyalty intention (commitment) before being committedto loyalty behaviour. Hence, loyalty intention acts as mediator between satisfaction

and loyalty behaviour. Different empirical studies on consumer loyalty areconceptually built on Olivers loyalty model (Chiou and Droge, 2006; Evanschitzkyand Wunderlich, 2006; Han et al., 2008).

A limitation of Olivers model is that it does not explain consumers loyaltybehaviour once loyalty behaviour has been installed and for frequently performedbehaviours in stable environments. The model implicitly entails every single initiationof behaviour being directly preceded by deliberative intentions regarding the course ofaction. However, many actions are simply resumptions of activities that individualsstarted some time before, and forming the underlying intention is thereforeunnecessary in most situations (Wilson et al., 2000). Consistent with modernpsychological theories (Wilson et al., 2000), the attitude behaviour link may notnecessarily depend on planned, explicit attitudes. Rather, individuals may act based onthe automatic, implicit attitudes that are stored in their memory. Automatic behaviouroccurs when the attitudes towards the behaviour are easily accessed and retrievedfrom the memory and evidence exists that attitudes are highly accessible underhabitual behaviours (Verplanken and Aarts, 1999). In an attempt to fill this gap, thepresent study proposes habit strength as a mediating variable between satisfactionand loyalty behaviour. We further present more arguments on how habits aredeveloped though repeated performance and positive affect (satisfaction) in stablecontexts.

Triandiss (1980) theory of interpersonal behaviour states that behaviour is afunction of intentions, facilitating conditions and habit strength. While novelbehaviours are primarily determined by intentions, repeated behaviours are primarily

determined by habit. Habits form slowly in stable contexts where the behaviour isfrequently practised (daily to several times a week) (Ouellette and Wood, 1998).According to Wood and Neal (2009), habit formation is originally anintention-dependent process where goals provide the initial outcome-orientedimpetus for response repetition. During the process of habit formation, individualsgradually learn the associations between the behaviour and the characteristics of thecontext in which the behaviour is performed (Wood and Neal, 2009). Once habits areformed, perception of contexts governs the associated behaviour without awareness ofthe underlying goal-directed intentions (Verplanken and Wood, 2006). Recognizingthat habits may originate in goal pursuit (intention-dependent), some scholars arguethat habits are a form of goal-dependent automaticity which emerge when contextactivates a goal (Verplanken and Aarts, 1999), whereas other researchers argue that

habit context-response associations are completely independent of goals (Wood andNeal, 2009).

Habits also may arise when cues in the performance context are associated withpositive affect (i.e. satisfied repetitions) over time (Triandis, 1980). In this case, contextstrigger habit formation as they signal opportunities to obtain the rewarding experience(Wood and Neal, 2009). Research on the neurotransmitter systems in the brain hasshown that the context reliably associated with positive response outcome can promotehabit performance (Wood and Neal, 2009). Additional evidence from the marketing

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literature has shown a significant correlation between affect or satisfaction andperceived habit strength in the area of recycling behaviour (Knussenet al., 2004), fruitconsumption behaviour (De Bruijn et al., 2007) and information-systems-relatedbehaviour (Limayem et al., 2007). Similarly, in the present study, we position

cumulative satisfaction as a driver of habit strength based on the consumers positiveexperience with the consumption of the product.

In summary, Olivers model (Model 1, Figure 1) relies primarily on the deliberate orgoal-directedness intentions mechanism to explain customer loyalty behaviour (asmeasured by the frequency of behaviour). The extended model (Model 2, Figure 1)proposes a mediating effect of habit (habit strength) in the relationship betweensatisfaction and loyalty behaviour. Consistent with previous arguments, as the habitsdevelop and gain strength through satisfactory execution of the behaviour, the loyaltybehaviour is less likely to depend on a rational statement (loyalty intentions) andmainly depends on the automaticity of habit.

3. Methodology3.1 Focus on product category loyaltyTraditionally scholars have associated consumer loyalty exclusively with brands(Chiou and Droge, 2006; Evanschitzky and Wunderlich, 2006; Oliver, 1999). Recentstudies (Nijssen et al., 2003; Pritchard et al., 1999) have associated loyalty also withproduct categories, services, stores, persons or geographic region. Evidence suggeststhat consumers decision-making and loyalty may form at different levels of theproduct hierarchy from product categories to brands. For example, when decidingwhat to have for dinner, consumers choose among multiple food categories, classes, ortypes of products before reaching decisions among brands. In addition, some productcategories lack strong brands (e.g. fresh fruits, unprocessed meat and fresh seafood aremostly sold unbranded). Product category loyalty is similar to brand loyalty because

the same rules that govern brand competition may also be applied to product categorycompetition. For example, fish competes with meat and butter competes withmargarine as much as Coca-Cola competes with Pepsi and other soft drink brands.This study deals with consumer loyalty towards a product category (Chadet al., 2005)and in particular consumers loyalty towards the consumption of fish as the main mealprotein in an in-home context.

3.2 SampleTwo representative household samples from Denmark (DK) (n 1110) and Spain (SP)(n 953) form the basis of the present analysis. The two-sample analysis was aimed toprovide conceptual and statistical support for the investigated approach and to verifywhether specific parameters of the models are (in)variant across the countries. The

countries were selected based on expected differences in fish consumption. Spain ranksas one of the highest consumers of fish in Europe (approximately 42 kg/capita/year cf.FAOSTAT, 2006). Denmark in turn presents a relatively low level of total fishconsumption in Europe (approximately 24 kg/capita/year cf. FAOSTAT, 2006).

The fieldwork and pre-testing were sub-contracted to local market researchagencies. Households were selected randomly. In each household, the person mainlyresponsible for food shopping and cooking was elected as the respondent. Thisprocedure influenced the distribution of gender in favour of females (77 per cent of the

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total number of respondents). Otherwise, the samples were representative of thedifferent countries, in terms of basic socio-demographics such as age, education, townsize and region.

3.3 MeasuresPilot interviews were conducted in order to pre-test the questionnaire. Only smallrevisions were necessary. The respondents were clearly informed that this studyfocused on fish as a product category, and not on shellfish or other seafood products.All the questions were framed with regard to consuming fish as the main meal/dinnerin their home environment, in accordance with the principle of compatibility (Ajzen,1991) and with the notion that habit is performed in relatively stable contexts (Ouelletteand Wood, 1998).

Satisfaction was measured by three seven-point semantic-differential items: Wheneating fish for the main meal/dinner at home: I feel bad-good, unsatisfied-satisfied,unpleasant-pleasant. This scale is frequently used to assess consumer satisfaction(Limayem et al., 2007; Seiders et al., 2005).

Intended loyalty was assessed with three indicators: Please indicate how likely it isthat you expect/plan/want to eat fish at home for your main course/dinner in the nearfuture? These items are frequently used to measure intention as a reflective constructwithin the expectancy-value theory (Armitage and Conner, 2001), and have beenadapted to the loyalty literature in different ways (Evanschitzky and Wunderlich,2006). The respondents were given the opportunity to mark their intention on a scalefrom one very unlikely to seven very likely.

Habit strength was measured by three items from the self-report index of habitstrength scale (Verplanken and Orbell, 2003). We reduced the number of items becausesome items in the original scale covered other dimensions, such as frequency andidentity. Thus, our scale of habit strength focused on measures to assess lack of

aware ne ss /c on sci ou sne ss , and was me as ured b y th re e se ve n- poin tsemantic-differential items: Eating fish as a main course/dinner at home issomething: I have been doing for a long time (a routine); I have no need to think aboutdoing; I do without thinking too much (automatically).

Finally, loyalty behaviour was measured by one item, How often do you eat fish asa main course/dinner at home?, which was to be answered on a nine-point frequencyscale ranging from never to every day or almost every day. Self-reportingbehavioural frequency in cross-sectional surveys serves as a good proxy for actualconsumption (Pritchard et al., 1999; Yi and La, 2004).

4. Analysis and results4.1 Analytical procedures

The analyses include an examination of the reliability and validity of the constructs byestimating a confirmatory factor analysis (CFA) model individually for each model andeach sample. Next, we apply structural equation modelling to test the proposed Model1 and Model 2 for each individual sample. The traditional chi-square fit test is reported;however, because it has been recognised as an inappropriate test for a large sample size(Byrne, 2001), six other indices, considered to be robust indicators of model fit, areincluded: the Comparative Fit Index (CFI), Normed Fit Index (NFI), Relative Fit Index(RFI), Incremental Fit Index (IFI), TuckerLewis Index (TLI) and Root Mean Square

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Error of Approximation (RMSEA). An acceptable model fit is indicated by CFI, NFI,RFI, IFI and TLI values exceeding 0.90 and RMSEA values below 0.08 (Byrne, 2001).

4.2 Construct reliability and validity

CFA was estimated as a preliminary step to confirm the factor structure and to providean initial test of reliability and validity of the factors (Anderson and Gerbing, 1988). Weran a CFA for each of the two models (Model 1 and Model 2). However, for spacereasons, only the results for Model 2 (including all the constructs) are shown in Table I.On the basis of the model fit indices the CFA model appeared to fit the data adequately.Without exception, every individual item loading on the predicted constructs washighly significant with values ranging from 0.71 to 0.98, hereby providing evidence ofthe items convergent validity (Anderson and Gerbing, 1988). The reliabilitycoefficients (Cronbach alpha, composite reliability and variance extracted) weresatisfactory, ranging from 0.72 to 0.95. The intercorrelations between the constructsare displayed in Table II. All the correlations appeared to be significant and below 0.70,attesting to discriminant validity. Furthermore, to confirm the discriminant validity,

Country Denmarka Spainb

Construct/item Loading a CR VE Loading a CR VE

Satisfaction 0.847 0.907 0.767 0.918 0.948 0.859Feel bad/Feel good 0.81 0.90Unsatisfied/Satisfied 0.94 0.90Unpleasant/Pleasant 0.91 0.85

Loyalty intentions 0.935 0.958 0.885 0.977 0.985 0.957Plan 0.93 0.98Expect 0.96 0.98Want (desire) 0.85 0.95

Habit strength 0.809 0.886 0.723 0.814 0.889 0.729I have been doing for a longtime 0.75 0.71I have no need to think aboutdoing 0.84 0.74I do without thinking(automatically) 0.78 0.87

Loyalty behaviourHow often did you eat fish athome? 1.00 (fixed) 1.00 (fixed)

Model fit statisticsx

2 175.24 141.81

df 30 30p-value 0.000 0.000CFI 0.98 0.99NFI 0.98 0.98TLI 0.96 0.97RMSEA 0.06 0.06

Notes: an 1,110; bn 953; a Alpha Cronbach; CR Composite Reliability; VE Varianceextracted

Table I.Results of the CFA,

country-specific analysis

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the procedure recommended by Bagozzi et al. (1991) was followed. A series ofone-factor and two-factor confirmatory models was run for each pair of constructs inthe study, and a chi-square difference test was then conducted. The results revealedthat, for all the pairs of constructs, the two-factor solution was better than the

one-factor solution (p , 0:

01). Overall, the data show that the measures of the proposedconstructs achieve high reliability and sufficient convergent and discriminant validityacross the two individual CFA models.

4.3 Common method biasAs common method bias may have confounding effects on the observed relationshipsbetween the predictor and the criterion variables, particularly when data areself-reported (a single source), we estimated next the single-common-method factorapproach, devised by Podsakoffet al.(2003), to check whether a common method biasis present. The measurement model was estimated with a single-method first-orderfactor added to the indicators of the four variables. It should be noted that the

measurement properties (fit indices), under the common method factor model, slightlyimproved in comparison with the basic model (CFI 0:996 vs 0.980; NFI 0:996 vs0.979; RMSEA 0:053 vs 0.061). However, the correlation estimates between thevariables remained almost unchanged between the two models. On the basis of thisanalysis, common method bias appeared not to be an issue in this research.

4.4 Estimation of the proposed modelsThe following step in the analysis was to estimate the two proposed structural models.We carried out the estimation following a hierarchical process. First, consistent withOlivers model, we tested Model 1 to determine the effect of satisfaction and themediating role of loyalty intention on loyalty behaviour. Then we introduced thevariable habit strength as a mediator in the relationship between satisfaction andloyalty behaviour (Model 2). On the other hand, to verify the mediating effect of theproposed variables, i.e. loyalty intention and habit strength, a number of conditionsmust hold (Baron and Kenny, 1986):

. Satisfaction should have a significant effect on loyalty intentions and habitstrength.

. Loyalty intentions and habit strength should have a significant effect on loyaltybehaviour (these first two conditions are examined in Model A).

Denmarka Spainb

Variable/country S Li H Lb S Li H Lb

Mean 5.82 4.31 4.59 5.16 5.85 4.22 5.41 6.75Std dev. (1.34) (2.30) (1.81) (1.82) (1.25) (2.10) (1.40) (1.29)Satisfaction (S) Loyalty intentions (Li) 0.39 0.39 Habit strength (H) 0.49 0.36 0.65 0.39 Loyalty behaviour (Lb) 0.44 0.46 0.54 0.43 0.31 0.56

Notes: a n 1,110; b n 953; Correlation coefficients are given in the non-diagonal elements

Table II.Construct estimatedmeans, standarddeviations andcorrelations

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. Satisfaction should have a significant direct effect on loyalty behaviour (Model B).

. The direct effect of satisfaction on loyalty behaviour should become smaller inabsolute value when the path between the mediators (loyalty intentions andhabit strength) and loyalty behaviour is opened (Model C).

4.4.1 Loyalty intentions as a mediator towards loyalty behaviour. Table III shows thatthe conditions are present for the existence of a clear mediating effect of loyaltyintentions (Oliver, 1999). According to Model A, the relationships satisfaction loyaltyintentions and, respectively, loyalty intentions-loyalty behaviour are significant forboth samples. The direct effects of satisfaction on loyalty behaviour are significant inModel B, while they decrease in Model C, where the relation between loyalty intentionsand loyalty behaviour is admitted. An additional Sobel test (Sobel, 1982) confirms thesignificance of the mediation effect of loyalty intentions on loyalty behaviour (Model 1confirmed).

4.4.2 Habit strength as an alternative route towards loyalty behaviour. In discussing

the habit-strength construct, we provided a theoretical basis for positioning habitstrength as a mediating variable similar to the loyalty intentions in the traditionalcognitive-based hierarchy. Table III (Model 2) reports the results of the estimation ofthe three models after introducing habit strength as an alternative mediating variablebetween satisfaction and loyalty behaviour. First, Model D, the model reflecting thefirst condition in the mediating role of habit strength, was tested. Looking at the resultsof the estimation, it can be confirmed that satisfaction is significantly correlated withhabit strength, and in the expected direction, while habit strength itself has a positiveand significant effect on the loyalty behaviour. Satisfaction acts indirectly on loyaltybehaviour through habit strength. It appears that the first condition for habit strengthto exert a mediating effect in the loyalty process is fulfilled. Model E presents asignificant chi-square statistic and goodness-of-fit indicators that are slightly worse

than those of Model D. Moreover, since the difference between the chi-square values ofthe two models (Dx2(0)DK 61.21 and Dx

2(0) SP 98.98) is significant and Model Dsexplanation is clearly better, we deduce that the mediating-effect model (Model D:satisfaction-habit strength-loyalty behaviour) is superior to the direct-effect one (ModelE: satisfaction-loyalty behaviour). Next, Model F (combining the effect of satisfactionwith the mediating effect of loyalty intentions and habit strength) was compared withModel D. Of the two models, Model F presents the best goodness-of-fit indicators andthe differences in the chi-square statistic are significant (Dx2(1)DK 29.38 andDx

2(1)SP 4.14). By transitivity, if Model D is better than Model E and Model F isbetter than Model D, than Model F is better than Model E. Hence Model F is the modelthat best fits the data, and hence the one that best represents the loyalty behaviourprocess.

We note that the effect of habit strength on loyalty behaviour is greater that theeffect of loyalty intentions on loyalty behaviour in each of the two samples. Thisfinding is especially notable given that the countries examined differ considerably onthe fish consumption and habit dimensions. On the other hand, in Spain, the inclusionof the mediating effect of habit strength almost cancels out the direct effect ofsatisfaction on loyalty behaviour (b 0:09; t 1:96). In Denmark, in turn, satisfactionaffects the loyalty behaviour through loyalty intentions and habit strength (mediation),although it continues to have a significant direct effect as well.

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Model1

Model2

Relationships

M

odelA

ModelB

ModelC

ModelD

ModelE

ModelF

Denmarka

S-Li

0.39

(12.4

4)

0.4

0

(12.8

2)

0.3

9

(12.2

9)

0.4

1

(12.8

9)

0.4

1

(12.8

6)

0.40

(12.8

1)

Li

Lb

0.47

(16.7

2)

0.3

5

(11.8

8)

0.3

0

(11.2

4)

0.3

4

(11.4

2)

0.27

(9.3

0)

S-Lb

0.4

5

(14.8

6)

0.3

0

(9.9

4)

0.3

2

(10.4

9)

0.18

(5.2

4)

SH

0.4

3

(13.8

4)

0.5

1

(14.4

0)

0.50

(14.2

5)

HLb

0.5

2

(14.7

5)

0.33

(9.7

5)

Modelfit:

x

2

(df)

162.53

(13)

197.2

6

(13)

64.0

3

(12)

297.9

8

(32

)

359.1

9

(32)

268.60

(31)

CFI

0.97

0.9

7

0.9

9

0.9

6

0.9

6

0.97

NFI

0.97

0.9

7

0.9

9

0.9

6

0.9

6

0.97

TLI

0.94

0.9

3

0.9

8

0.9

4

0.9

3

0.94

RMSEA

0.10

0.1

1

0.0

6

0.0

9

0.1

0

0.07

R2

Li

0.15

0.1

6

0.1

5

0.1

7

0.1

6

0.16

R2

H

0.2

7

0.2

6

0.25

R2

Lb

0.22

0.2

0

0.2

9

0.3

7

0.3

0

0.41

Spainb

S-Li

0.41

(12.5

2)

0.4

1

(12.6

6)

0.4

0

(12.4

6)

0.4

1

(12.7

9)

0.4

1

(12.8

0)

0.41

(12.7

9)

Li

Lb

0.30

(9.4

1)

0.1

5

(4.4

4)

0.1

1

(3.8

3)

0.1

3

(4.0

4)

0.10

(3.1

3)

S-Lb

0.4

3

(13.5

6)

0.3

6

(10.6

4)

0.3

9

(11.4

2)

0.09

(1.9

6)

SH

0.6

6

(17.0

0)

0.6

6

(17.1

6)

0.65

(16.8

4)

HLb

0.5

2

(14.3

2)

0.46

(9.9

5)

Modelfit:

x

2

(df)

145.13

(13)

55.1

7

(13)

35.8

2

(12)

106.1

1

(32

)

205.0

9

(32)

101.97

(31)

CFI

0.98

0.9

9

1.0

0

0.9

9

0.9

8

0.99

NFI

0.98

0.9

9

0.9

9

0.9

9

0.9

8

0.99

TLI

0.96

0.9

9

0.9

9

0.9

8

0.9

6

0.98

RMSEA

0.10

0.0

6

0.0

5

0.0

5

0.0

8

0.05

R2

Li

0.16

0.1

7

0.1

6

0.1

7

0.1

7

0.17

R2

H

0.4

3

0.4

4

0.43

R2

Lb

0.09

0.1

8

0.2

0

0.3

3

0.2

1

0.39

Notes:an

1,1

10;n

953;Satisfaction(S),Loyaltyintention

s(Li),Habitstrength(H),Loyaltybeh

aviour(Lb)

Table III.Results of Model 1 andModel 2

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Finally, in line with Byrne (2001) and Steenkamp and Baumgartner (1998), wecompared the value of coefficients between countries in a multi-group cross-countryanalysis[1]. A constrained model, in which the structural relationships were fixedbetween country samples, was first estimated. Next, the constrained structural model

was compared with an unconstrained model in which all the relationships were set freebetween the two samples. The differences in the chi-square values between the modelsdetermine whether the variable country acts as a moderating variable; that is, asignificant decrease in the chi-square from the constrained model to the unconstrainedmodel implies that the country variable has a significant influence on the structuralrelationship (Byrne, 2001).

The results (Table IV) show significant differences between the two countries. Forthe relationships that were moderated, the paths from loyalty intention to loyaltybehaviour and from satisfaction to loyalty behaviour were consistently higher forDenmark than for Spain. Specifically, the coefficient from loyalty intentions to loyaltybehaviour was more than twice as strong for the Danish consumers than for theSpanish ones (0.26, p 0:000 versus 0.10, p 0:01). As regards the path between

satisfaction and loyalty behaviour, it was significantly weaker for the Spanish sample(0.09, p 0:05). In turn, the link from habit strength to loyalty behaviour wasconsistently higher for Spain (0.48, p 0:000) than for Denmark (0.35, p 0:000).

5. DiscussionLoyalty behaviour has guided marketing research for many years. Olivers (1999)model proposes a model of loyalty behaviour formation that infers that individualsintentions are a full mediator between satisfaction and loyalty behaviour. However, thequestion of the present work is whether the course of action associated with consumerloyalty is always planned and mediated by loyalty intentions or whether an alternativeroute exists between satisfaction and loyalty.

We have introduced and tested an extended model in an attempt to delineate twodistinct phenomena explaining loyalty behaviour. Although variants of theseapproaches exist in the literature, there is a lack of studies that integrate the twophenomena and discuss the implications of this extended model (Limayem et al., 2007).Taking Olivers model as a starting point, individuals settled intentions mediate thesatisfaction-loyalty behaviour in the initial stage of product adoption and in laterbehaviour maintenance associated with unstable contexts (Ajzen, 2002). However, in

Relationship/country Denmarka SpainbMulti-groupcomparisonsc

Satisfaction-Loyalty intentions (b1) 0.41 (23.40) * * 0.43 (23.40) * * DK * * SP * *

Loyalty intentions-Loyalty behaviour (b2) 0.26 (12.33) * * 0.10 (3.55) * DK * * . SP * *Satisfaction-Loyalty behaviour (b3) 0.17 (7.04) * * 0.07 (1.62)ns DK * * . SPns

Satisfaction-Habit strength (b4) 0.49 (26.13) * * 0.67 (26.13) * * DK * SP * *

Habit strength-Loyalty behaviour (b5) 0.35 (11.19) * * 0.48 (10.48) * * DK * * , SP * *

Notes: a n 1110; bn 953; cComparisons across countries were made based on unstandardisedcoefficients; nsNot significant; *Significant at p 0:01; * * Significant at p , 0:001; Model fit:x2 577:25; df 114; p 0:000; CFI 0:98; NFI 0:98; RFI 0:96; IFI 0:98; TLI 0:97;RMSEA 0:04; Standardised regression coefficients are reported; t-values in parentheses

Table IV.Results of Model 2

cross-countrycomparisons

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later behaviour performed frequently in stable contexts, consumer behaviour isautomatic and less guided by plans and deliberations, which are represented by theformation of intentions. Once habit starts to develop and gain strength throughsatisfactory execution of the behaviour, the satisfaction-action loyalty sequence may

occur automatically, through habit strength and thus less guided by behaviouralintention.

The results from our study in a food consumption in-home context corroborateprevious arguments. Habit strength has proved to be a relevant mediator in the twosamples analysed, regardless of their differences in habits of fish consumption. Theonly difference across countries was registered in the magnitude of the coefficientestimators. For more habituated individuals in fish consumption (Spanish fishconsumers who are among the heaviest fish consumers in Europe), behaviouralintention was a weaker antecedent of loyalty behaviour when compared with lesshabituated individuals (Danish fish consumers whose fish consumption is only half theone as observed in Spain). That is, consistent with the conceptual argument, Spanishconsumers, as the high fish consumption country, were more likely to undertake lessplanned and more intuitive or inertia-based responses with regard to the buying orconsumption of the involved product category.

The inclusion of a cognitive measure of habit strength in Olivers model led to anotable increase in the explanatory power of the proposed model from 0.29 to 0.41 inDenmark, and from 0.20 to 0.39 in Spain, respectively. Based on the Cohen f2 effect sizemeasure for hierarchical multiple regression, the habit strength had an effect size of0.203 in Denmark and respectively 0.311 in Spain, which represents a medium effect inboth samples (Cohen and Cohen, 1983). The model in which habit is proposed tomediate the link between cumulative satisfaction and loyalty behaviour possesses asignificantly higher explanatory power than the traditional model.

The overall findings of this research have shown that for the fish consumption

behaviour in an in-home context, habit strength can have a stronger effect on loyaltybehaviour than loyalty intentions. Consumers intentions were found to be significantbut relatively weaker in mediating consumer satisfaction in each sample. Theindividual country analysis produced a similar pattern of results, hereby providingvalidation of the findings. Overall the current study provides evidence of theappropriateness of a model of loyalty behaviour that distinguishes between intentionsand an automatic process outside conscious intentions.

6. Managerial implicationsIn view of this discussion and with regard to studying the role of habits inunderstanding and managing consumer loyalty in the context of food marketing, theresults suggest several implications. The dominant approach of consumer loyalty

behaviour in a business-to-consumer context has been to see loyalty behaviour as aplanned, conscious process based on consumer intentions, deliberation andcommitment towards the product category or brand (Oliver, 1999). While we do notinquire into the mediating effect of intention on loyalty behaviour, we argue that insome circumstances (such as later behaviour performed in stable environments andbehaviours characterised by frequent purchases, relatively little involvement andintense competition due to the availability of many substitutes across product category

such as food products), this effect is partially or almost entirely suppressed by

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habituation (Limayemet al., 2007). The fact that intention is not the only antecedent ofbehaviour loyalty confirms the previous findings by Mittal and Kamakura (2001) andothers showing poor correlation between intention and behaviour loyalty. Therefore,this study advocates that scholars evaluating food consumption behaviour and

practitioners in food marketing and other fast-moving consumer goods shouldconceive consumers loyalty behaviour as an action governed by two distinctivephenomena: intentions when referring to loyalty behaviour formation and habits whenevaluating loyalty behaviour persistence. Intention-loyalty consumers act from theirintention, which is a product of cognitive deliberation, planning and commitment,while habit-loyalty consumers act from their habit in a less-planned, more inertial orautomatic mode.

In a highly competitive market with low-differentiated products of comparablequality and satisfying similar needs or goals, businesses are keenly interested instrategies designed to strengthen consumer loyalty for an incumbent product orproduct category, or to break consumers loyalty to competing products and productcategories. Based on this study, and considering different scenarios, specific strategiesfor managing different types of product category loyalty through marketing activitiescan be built, that focus either on influencing consumer motivation through intentionloyalty or by influencing their habits.

In general and consistent with the previous literature, managing consumer loyaltytowards low frequency-of-purchase product categories (such as, various categories ofconsumer durables) requires the fostering and maintaining of attribute beliefs aboutthe product and product category as well as satisfactory experience with the product tointention loyalty formation and further loyalty behaviour maintenance.Intention-based loyalty formation can be accomplished by focusing oninformation-based communications that encourage consumers to evaluate andbalance the benefits and costs (exclusive value) of the incumbent product and

commit consumers to choice. In this traditional scenario, consumer goal-directednessintention mechanisms play a mediating role in consumer loyalty formation. Bycontrast, for product categories characterised by high frequency-of-purchase (as in thisstudy), managing consumer loyalty requires additional strategies.

First, building consumer loyalty in the initial phases of product adoption forfrequently purchased products (such as various categories of food products) initiallyrequires the fostering of awareness and attribute beliefs about the product and productcategory and satisfactory experience with the product. In that sense, actions haveusually focused on information-based communications about the product andsatisfactory episodes with the product in order to strengthen the beliefs and affect(satisfaction) associated with the product consumption or usage (Webb and Sheeran,2006). For instance, linked to our empirical case, the fostering of beliefs about the

health qualities of fish and continuous satisfaction with the fish products should bepositively correlated with individuals intentions to adopt the fish category in theirdaily consumption. In this scenario, consumer intention plays a mediating role inconsumer loyalty formation.

Second, maintaining consumer loyalty for a product in circumstances characterisedby high purchase frequency (consumables) and intense competition can be obtained byfostering habit-based loyalty based on stable contexts, cumulative satisfaction andfrequent performance. The habits of purchase or consumption that consumers form

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over time (inertia) are a natural phenomenon that happens to a product or productcategory. Consumers fall into such a state of inertia because the cognitive effortrequired while buying the product is minimal when compared with a novel alternativethat requires self-control resources. Thus, in a stable context and for frequent

behaviours marketing strategies should focus on inciting consumers to developquickly the habit of using the desired product (Limayemet al., 2007). Specific actions tofostering habit formation for fish consumption may include cumulative satisfactionand repeat purchase of the fish products in stable contexts in order to createassociations in the memory between the features of the environment and the product inquestion (for instance, a fish stand positioned every Saturday at the supermarketentrance in order to create a habit in a stable buying context, ready fish dinners tocreate a consumption habit and coupons and bonuses to encourage frequentpurchasing). Marketers should pay more attention to actions focused on developingconsumers habit of purchasing and consuming the product, as consumers are oftenacting automatically and are more likely to maintain their old behaviours (habits)given the demands of everyday life such as time pressure, cognitive load andregulatory depletion (Wood and Neal, 2009). Additionally, by locking-in consumersinto the habit of consuming an incumbent product category, businesses may preventloyalty behaviour formation for a competitive product category. Hence, the habit-basedstrategy complements the intention-based strategy in which fish marketers want toprevent consumer loyalty for another product category (e.g. turkey meat) bycommunicating the exclusive nutritive value of fish when compared to the meatcategory and thus fostering loyalty formation based on logical thinking andcomparisons.

Finally, businesses may be interested in strategies designed to break consumerhabit-based loyalty for an incumbent product category characterised by high purchasefrequency (e.g. meat). While it can be beneficial to promote the benefits of the targeted

product category (fish), this is not always sufficient to offset consumers behaviour.Habits are deeply embedded in consumers minds and less sensitive to (new)information (Verplanken and Wood, 2006) . Consequently, traditionalinformation-based interventions communicating the benefits of the fish productcategory may be less effective in breaking the old habits. In order to influence thechoice of habitual-loyal consumers for a competitive product category (such as fish),the companies should consider changing the context that activates the existing habitsfor an incumbent product (i.e. meat) and thus automatically directing habitperformance (Wood and Neal, 2009). For example, changing the physicalsurroundings in which consumers purchase habitually (e.g. product placement onthe shelf, store displays, introducing a similar packaging design) may change theconsumer choice of products. Changing the context breaks the purchasing habit by

suppressing the link between the context and the incumbent product in the memory(Wood and Neal, 2009). An in-store experiment for instance showed that consumers aresignificantly less likely to purchase potato chips if they are placed on top and bottomshelves than if they are placed on the middle shelf (Sigurdsson et al., 2009). With regardto the physical context, it is important to note that it might be extremely difficult tochange (particularly when retailers exert considerable influence on the way theproducts are located on shelves and in stores). However, a closer co-operation betweenproducers and retailers (Fornariet al., 2009) may break consumers habits for specific

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products and product categories. Persuasive interventions based on information aboutthe benefits of an alternative product would be less effective for habit-loyaltyconsumers without breaking the context or the physical surrounding link (Verplankenand Wood, 2006). This is because, for frequent behaviours, a significant portion of

purchasers or consumers fall into such a state of inertia that the cognitive activity theyengage in while buying is minimal, and consumers do not consider the expectedbenefits and costs of changing the current product for a rival alternative (Limayemet al., 2007; Verplanken and Aarts, 1999). In support of this idea, a meta-analysis ofdifferent interventions designed to change individuals behaviour through differentinformation-based strategies (persuasive communication, social encouragement, socialpressure, social support and information regarding behaviour and outcome) revealedcorresponding changes in behaviour only for intentional-based behaviour but not forhabitual-based behaviour (Webb and Sheeran, 2006).

In summary, the current results convey that approaches to identifying loyalconsumers or customers should focus on both intention and habit-dependent views ofloyalty. If understanding the nature of habit and differentiating between a controlledand a less-controlled dimension of loyalty behaviour were to be implementedsuccessfully in business settings, this could be of value for preventing, strengtheningor breaking the old habits and loyalty to an incumbent product category or brand.

7. Limitations and further researchThe present study faces some limitations. The study employs cross-sectional data;therefore, causal effects can only be inferred. Although the authors based theirarguments on Jaccard and Blanton (2005), according to whom, for stable behaviours,cross-sectional data can be as informative as longitudinal data, prospectivelongitudinal studies are recommended to verify and validate the present findings.

Second, this study did not directly assess real action (factual behaviour); rather, theauthors built their hypotheses on individuals self-reported opinions about their pastbehaviour. Optimistic biases might have affected participants responses, because ofthe prevailing recommendations to increase fish consumption for its nutritional andhealth benefits. Therefore, a future research agenda requires replications involvingnew marketing objects (brands, stores, services), other product categories that havemore negative connotations and higher loyalty ratings (such as snacks, confectionery,fast foods) or various categories of consumer durables. New studies also require acombination of different methodologies (quantitative and qualitative) and moreobjective methods of data collection (experiments and neuroimaging techniques) tounderstand and capture consumers habits and loyalty behaviour in different contexts(in-home vs out-of-home, own country vs abroad). Qualitative designs, such as focus

groups, in-depth interviews or observations at the point of purchase, or a combinationof these, could be an approachable challenge for future research. For example, it wouldbe beneficial to combine verbal protocols with direct observation in order to studyconsumers decision-making process in stable and unstable buying and consumptioncontexts, or for relative new and current incumbent products with the same level ofsatisfaction. These qualitative techniques combined with more advancedneuroimaging techniques on consumer sub-conscious action ( Jonides, 2004) couldhelp to determine the real drivers of consumer loyalty behaviour.

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Note

1. The invariance of the measurement model (i.e. factor loadings) was initially assessed.Although the chi-square difference between the unconstrained model and the constrainedmodel (fixed loadings across groups) was statistically significant (delta chi-square 74:7;

p , 0:

01), the TLI indicated a negligible change in fit (delta TLI , 0:

001). The metricinvariance between the two groups was therefore accepted (Byrne, 2001). The constrainedmodel was used in the subsequent structural invariance analysis (Steenkamp andBaumgartner, 1998).

References

Ajzen, I. (1991), The theory of planned behaviour, Organizational Behaviour and HumanDecision Processes, Vol. 50 No. 2, pp. 179-211.

Ajzen, I. (2002), Perceived behavioural control, self-efficacy, locus of control, and the theory ofplanned behaviour, Journal of Applied Social Psychology, Vol. 32 No. 4, pp. 665-83.

Anderson, J.C. and Gerbing, D.W. (1988), Structural equation modeling in practice: a review and

recommended two-step approach, Psychological Bulletin, Vol. 103 No. 3, pp. 411-23.

Armitage, C.J. and Conner, M. (2001), Efficacy of the theory of planned behaviour:a meta-analytic review,British Journal of Social Psychology, Vol. 40 No. 4, pp. 471-99.

Bagozzi, R.P., Yi, Y. and Phillips, L.W. (1991), Assessing construct validity in organizationalresearch, Administrative Science Quarterly, Vol. 36 No. 3, pp. 421-58.

Ball, D., Coelho, P.S. and Machas, A. (2004), The role of communication and trust in explainingcustomer loyalty: an extension to the ECSI model, European Journal of Marketing, Vol. 38Nos 9/10, pp. 1272-93.

Baron, R.M. and Kenny, D.A. (1986), The moderator-mediator variable distinction in socialpsychological research: conceptual, strategic and statistical considerations, Journal of

Personality and Social Psychology, Vol. 51 No. 6, pp. 1173-82.

Byrne, B.M. (2001), Structural Equation Modeling with AMOS Basic Concepts, Applications,and Programming, Lawrence Erlbaum Associates, Mahwah, NJ.

Chad, W., MacDonald, S., Lingras, P. and Adams, A. (2005), Relationship between product basedloyalty and clustering based on supermarket visits and spending patterns,International

Journal of Computer Science & Applications, Vol. 2 No. 2, pp. 85-100.

Chiou, J.-S. and Droge, C. (2006), Service quality, trust, specific asset investment and expertise:direct versus indirect effects in a satisfaction-loyalty framework,Journal of the Academyof Marketing Science, Vol. 34 No. 4, pp. 1-15.

Cohen, J. and Cohen, P. (1983), Applied Multiple Regression/Correlation Analysis for theBehavioural Sciences, Lawrence Erlbaum Associates, Hillsdale, NJ.

De Bruijn, G.-J., Kremers, S.P.J., De Vet, E., De Nooijer, J., Van Mechelen, V. and Brug, J. (2007),Does habit strength moderate the intention-behaviour relationship in the theory of

planned behaviour? The case of fruit consumption,Psychology and Health, Vol. 22 No. 8,pp. 899-916.

Dick, A.S. and Basu, K. (1994), Customer loyalty: toward an integrated conceptual framework,Journal of Academy of Marketing Science, Vol. 22 No. 2, pp. 99-113.

Eagly, A. and Chaiken, S. (1993),The Psychology of Attitudes, Harcourt Brace Jovanovich, FortWorth, TX.

Evanschitzky, H. and Wunderlich, M. (2006), An examination of moderator effects in thefour-stage loyalty model, Journal of Service Research, Vol. 8 No. 4, pp. 1-16.

EJM47,1/2

320


19/21

FAOSTAT (2006), Food and Agriculture Organization statistical database, United Nations,available at: http://faostat.fao.org/default.aspx (accessed 5 November 2009).

Fornari, D., Grandi, S. and Fornari, E. (2009), The role of management of product innovation inretailer assortment: evidence from the Italian FMCG market,The International Review of

Retail, Distribution and Consumer Research, Vol. 19 No. 1, pp. 29-43.Gustafsson, A., Johnson, M.D. and Roos, I. (2005), The effects of customer satisfaction,

relationship commitment dimensions and triggers on customer retention, Journal ofMarketing, Vol. 69 No. 4, pp. 210-8.

Han, X., Kwortnik, R.J. Jr and Wang, C. (2008), Service loyalty: an integrative model andexamination across service contexts, Journal of Service Research, Vol. 11 No. 1, pp. 22-42.

Heskett, J.L. (2002), Beyond customer loyalty,Managing Service Quality, Vol. 12 No. 6, pp. 355-7.

Honkanen, P., Olsen, S.O. and Verplanken, B. (2005), Intention to consume seafood: theimportance of habit strength,Appetite, Vol. 45 No. 2, pp. 161-8.

Jaccard, J. and Blanton, H. (2005), The origins and structure of behaviour: conceptualizingbehaviour in attitude research, in Albarracn, D., Johnson, B.T. and Zanna, M.P. (Eds),

Handbook of Attitudes and Attitude Change, Lawrence Erlbaum Associates, Mahwah, NJ,pp. 125-72.

Johnson, M.D., Anderson, E.W. and Fornell, C. (1995), Rational and adaptive performanceexpectations in a customer satisfaction framework, Journal of Consumer Research, Vol. 21No. 4, pp. 128-40.

Jolley, B., Mizerski, R. and Olaru, D. (2006), How habit and satisfaction affects player retentionfor online gambling, Journal of Business Research, Vol. 59 No. 6, pp. 770-7.

Jonides, J. (2004), How does practice makes perfect?, Nature Neuroscience, Vol. 7, pp. 75-9.

Knussen, C., Yule, F., MacKenzie, J. and Wells, M. (2004), An analysis of intentions to recyclehousehold waste: the roles of past behaviour, perceived habit, and perceived lack offacilities, Journal of Environmental Psychology, Vol. 24 No. 2, pp. 237-46.

Limayem, M., Hirt, S.G. and Cheung, C.M.K. (2007), How habit limits the predictive power ofintention: the case of information systems continuance, MIS Quarterly, Vol. 31 No. 4,pp. 705-37.

Lindblad, E. and Lyttkens, C.H. (2002), Habits versus choice: the process of decision-making inhealth related behaviour,Social Science & Medicine, Vol. 55, pp. 451-65.

Mittal, V. and Kamakura, W.A. (2001), Satisfaction, repurchase intent, and repurchase behavior:investigating the moderating effect of customer characteristics, Journal of Marketing

Research, Vol. 38 No. 2, pp. 131-42.

Neal, D.T., Wood, W. and Quinn, J.M. (2006), Habits: a repeat performance, Current Directionsin Psychological Science, Vol. 15 No. 4, pp. 198-202.

Nijssen, E., Singh, J., Sirdeshmukh, D. and Holzmueller, H. (2003), Investigating industry contexteffects in consumer-firm relationships: preliminary results from a dispositional approach,

Journal of the Academy of Marketing Science, Vol. 31 No. 1, pp. 46-60.Oliver, R.L. (1999), Whence customer loyalty?, Journal of Marketing, Vol. 63, pp. 33-44.

Ouellette, J. and Wood, W. (1998), Habit and intention in everyday life: the multiple processes bywhich past behaviour predicts future behaviour, Psychological Bulletin, Vol. 124 No. 1,pp. 54-74.

Podsakoff, P.M., MacKenzie, S.B., Lee, J.-Y.Y. and Podsakoff, N.P. (2003), Common methodbiases in behavioural research: a critical review of the literature and recommendedremedies, Journal of Applied Psychology, Vol. 88 No. 5, pp. 879-903.

Consumerloyalty

modelling

321


20/21

Pritchard, M.P., Havitz, M.E. and Howard, D.R. (1999), Analyzing the commitment-loyalty linkin service context, Journal of Academy of Marketing Science, Vol. 27 No. 3, pp. 333-48.

Reinartz, W., Thomas, J.S. and Kumar, V. (2005), Balancing acquisition and retention resourcesto maximize customer profitability,Journal of Marketing, Vol. 69 No. 1, pp. 63-79.

Seetharaman, P.B. (2004), Modeling multiple sources of state dependence in random utilitymodels: a distributed lag approach, Marketing Science, Vol. 23 No. 2, pp. 263-71.

Seiders, K., Voss, G.B., Grewal, D. and Godfrey, A.L. (2005), Do satisfied customers buy more?Examining moderating influences in a retailing context, Journal of Marketing, Vol. 69No. 4, pp. 26-43.

Sigurdsson, V., Saevarsson, H. and Foxall, G. (2009), Brand placement and consumer choice:an in-store experiment, Journal of Applied Behavior Analysis, Vol. 42, pp. 741-5.

Sobel, M.E. (1982), Asymptotic confidence intervals for indirect effects in structural equationsmodels, in Leinhart, S. (Ed.), Sociological Methodology, San Francisco, CA, pp. 290-312.

Steenkamp, J.-B.E.M. and Baumgartner, H. (1998), Assessing measurement invariance incross-national consumer research,Journal of Consumer Research, Vol. 25 No. 1, pp. 78-90.

Trafimow, D. (2000), Habit as both a direct cause of intention to use a condom and as amoderator of the attitude-intention and subjective norm-intention relations, Psychologyand Health, No. 15, pp. 383-93.

Triandis, H.C. (1980), Values, attitudes and interpersonal behaviour, in Howe, H.E. and Page,M.M. (Eds), Nebraska Symposium on Motivation: Beliefs, Attitudes and Values, Vol. 27,University of Nebraska Press, Lincoln, NE, pp. 195-259.

Verplanken, B. and Aarts, H. (1999), Habit, attitude, and planned behaviour: is habit an emptyconstruct or an interesting case of automaticity?, European Review of Social Psychology,Vol. 10, pp. 101-34.

Verplanken, B. and Orbell, S. (2003), Reflections on past behaviour: a self-report index of habitstrength, Journal of Applied Social Psychology, Vol. 33 No. 6, pp. 1313-30.

Verplanken, B. and Wood, W. (2006), Interventions to break and create consumer habits,

Journal of Public Policy and Marketing, Vol. 25 No. 1, pp. 90-103.

Webb, T.L. and Sheeran, P. (2006), Does changing behavioral intentions engender behaviorchange? A meta-analysis of the experimental evidence, Psychological Bulletin, Vol. 132No. 2, pp. 249-68.

Wilson, T.D., Lindsey, S. and Schooler, T.Y. (2000), A model of dual attitudes, PsychologicalReview, Vol. 107 No. 1, pp. 101-26.

Wood, W. and Neal, D.T. (2009), The habitual consumer, Journal of Consumer Psychology,Vol. 19, pp. 579-92.

Worthington, S., Russell-Bennett, R. and Hartel, C. (2010), A tri-dimensional approach forauditing brand loyalty, Journal of Brand Management, Vol. 17, pp. 243-53.

Yi, Y. and La, S. (2004), What influences the relationship between customer satisfaction and

repurchase intention? Investigating the effects of adjusted expectations and customerloyalty, Psychology and Marketing, Vol. 21 No. 5, pp. 351-73.

About the authorsProfessor Svein Ottar Olsen has carried out research in consumer behaviour and marketingresearch with focus on consumer psychology and consumption behaviour. Professor Olsen haspublished articles in leading marketing and international business journals in the area ofperceived quality, consumer satisfaction and loyalty, survey methodology in international

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research, and use of marketing information. Svein Ottar Olsen is the corresponding author andcan be contacted at: [email protected]

Dr Ana Alina Tudoran has carried out research and published articles in international andnational business journals in the area of brand equity, perceived quality, consumer satisfaction

and the role of information on consumer behaviour. Dr Tudorans current research interests arein the area of behavioural economics and quantitative methods.Dr Karen Bruns has carried out research on consumer behaviour and she is author of

numerous scientific publications on marketing and consumer behaviour in relation to food. Inparticular Dr Bruns has researched food-related lifestyles across Europe, and has worked withthe implementation of results in food companies.

Dr Wim Verbeke has carried out research on consumer attitudes, perceptions and acceptanceof agricultural and food production technologies and products. In particular, Dr Verbeke isauthor of numerous scientific publications on the impact of information, food labelling and therole of individual characteristics and individual difference variables on food consumptiondecisions.

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