Journal of Consumer MarketingCustomer satisfaction and loyalty in a digital environment: an empirical test

Jean Donio' Paola Massari Giuseppina Passiante

Article information:To cite this document:Jean Donio' Paola Massari Giuseppina Passiante, (2006),"Customer satisfaction and loyalty in a digital environment: anempirical test", Journal of Consumer Marketing, Vol. 23 Iss 7 pp. 445 - 457Permanent link to this document:

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Customer satisfaction and loyalty in a digitalenvironment: an empirical test

Jean Donio’University of Paris II, Paris, France

Paola Massari and Giuseppina Passiantee-Business Management School, ISUFI, University of Lecce, Lecce, Italy

AbstractPurpose – The purpose of this paper is to explore the links between customer loyalty attitude, customer loyalty behaviours (measured by customerpurchase behaviours) and profitability. The aim is to define a conceptual framework within which to analyse the relationships between attitudes,behaviour, and profitability of the customers.Design/methodology/approach – Reference was made to earlier studies which argued that loyal customers constitute competitive asset of businessorganizations. Several authors noted that customers generally vary in terms of loyalty behaviours and attitudes and highlighted that differences aboutcustomers’ loyalty levels affect a firm’s profitability results. Customer loyalty, its antecedents and outcomes, and the links between customersatisfaction, customer loyalty and profitability have been analyzed at a customer level.Findings – The results showed support for all but one of the five hypotheses, the exception being H2.Originality/value – The results of the study provide evidence that a Loyalty Index can give managers an adequate support for market segmentation.This means that actual market segment strategies, based on geographical, demographical and/or psychographic variables, should take into account alsoloyalty measurement models.

Keywords Customer satisfaction, Customer loyalty, Electronic commerce, Customer relations, Marketing intelligence

Paper type Research paper

Introduction

Research on factors that influence customer satisfaction andloyalty has made considerable progress within the last years(Szymanski and Henard, 2001; Oliver, 1999). Customerloyalty is seen to be crucial to the success of businessorganizations, since attracting new customers is far moreexpensive than retaining existing ones (Dick and Basu, 1994;Saren and Tzokas, 1998; Fournier, 1998). It has beensuggested by many authors that loyal customers are acompetitive asset and that a way of increasing customerretention is through secure and collaborative relationshipbetween buyers and sellers (Chaudhuri, 1999; Chaudhuri andHolbrook, 2001; Fournier, 1998; Oliver, 1999).Several authors pointed out that customers generate

different levels of profitability (Cooper and Kaplan, 1991;Peppers and Rogers, 1993; Shapiro et al., 1987; Slywotzkyand Shapiro, 1993), and not all customers generateacceptable cost and revenue streams (Carroll, 1991;Storbacka et al., 1994). It has been suggested, therefore,that the firm should actively develop relationships withprofitable customers and try to end relationships withunprofitable customers (Jones and Sasser, 1995; Peppersand Rogers, 1993; Shapiro et al., 1987; Slywotzky andShapiro, 1993). Tailoring marketing efforts to segments that

differ in current and/or future profitability makes a firm’sstrategy more effective, by identifying profitability customertiers, and offer products and services customized for thespecific tier, and therefore capturing its financial value.The purpose of this empirical study is to explore the links

existing between customer loyalty attitude (as his consistentlyfavourable set of stated beliefs towards the brand purchase),customer loyalty behaviours (in terms of his pattern of pastpurchases) and profitability. To this end, customer loyalty, itsantecedents and outcomes, and, thus, the links betweencustomer satisfaction, customer loyalty and profitability havebeen analyzed at a customer level. Specifically, the study hasfocused on the following issues:. What are the main antecedents and outcomes of customer

loyalty?. What are the links between customer satisfaction,

customer loyalty and profitability?. How can loyalty be evaluated in a firm’s customer base? Is

there any model that can assess customer loyalty based onspecific variables and indexes? Do characteristics existwhich determine whether customers attain high levels ofcustomer loyalty?

Our approach is based on a framework put forward byCostabile (2001) to analyse the relationship existing betweenthe act of purchase of the customer, his satisfaction, his trustand commitment and, at the end, his loyalty. In this study, wehave extended the single act of purchase to the completepurchase behaviour of the customer, and we have alsoexplored the relationship existing between the customerloyalty and his profitability.The paper is organized as follows. The first section presents

the theoretical framework and the main hypotheses. Thesecond section illustrates the method adopted. The main

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

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Journal of Consumer Marketing

23/7 (2006) 445–457q Emerald Group Publishing Limited [ISSN 0736-3761]

[DOI 10.1108/07363760610712993]

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results are described and discussed in section three. The finalsection presents conclusions and a future research agenda.

Theoretical framework and main hypotheses

Customer loyalty: antecedents and outcomesCustomer loyalty is a concept that has enjoyed wide currencyand usage within the field of consumer behaviour for manyyears. Dick and Basu (1994) viewed customer loyalty as “thestrength of the relationship between an individual’s relativeattitude towards an entity (brand, service, store, or vendor)and repeat patronage”. Three conceptualizations of customerloyalty have been identified in the literature:1 loyalty as primarily an attitude that sometimes leads to a

relationship with the brand;2 loyalty mainly expressed in terms of revealed behaviour

(i.e. the pattern of past purchases); and3 buying moderated by the individual’s attitudes.

Loyalty as primarily an attitude that leads to a relationship withthe brandResearchers argue that there must be a strong “attitudinalcommitment” to a brand for true loyalty to exist (Day, 1969;Jacoby and Chestnut, 1978; Foxall and Goldsmith, 1994;Mellens et al., 1996; Reichheld, 1996). This is seen as takingthe form of a consistently favourable set of stated beliefstowards the brand purchased. These attitudes may bemeasured by asking people how much they like the brand,feel committed to it, will recommend it to others, and havepositive beliefs and feelings about it – relative to competingbrands (Dick and Basu, 1994). The strength of these attitudesis the key predictor of a brand’s purchase and repeatpatronage. This is what Oliver (1997, p. 392) has in mindwhen he defines customer loyalty as: “A deeply heldcommitment to re-buy or re-patronize a preferred product/service consistently in the future, thereby causing repetitivesame-brand or same brand-set purchasing despite situationalinfluences and marketing efforts having the potential to causeswitching behaviour”. In the fields of advertising and brandequity research this model received some support (e.g. Aaker,1996; de Chernatony and McDonald, 1998). The approachalso appealed to many practitioners in advertising and brandmanagement because it is empathetic with the search forstrategies to enhance the strength of consumers’ attitudestowards a brand.Ahluwalia et al. (1999) have shown that attitudinally-loyal

customers are much less susceptible to negative informationabout the brand than non-loyal customers. Also, where loyaltyto a brand increases, the revenue-stream from loyal customersbecomes more predictable and can become considerable overtime – as shown in analyses of cases such as Federal Express,Pizza Hut franchises, and Cadillac dealerships (Gremler andBrown, 1999). An extension of the “attitudes define loyalty”perspective is to suggest that consumers form relationshipswith some of their brands. A good example of this perspectiveis provided by Fournier (1998), who sees loyalty as acommitted and affect-laden partnership between consumersand brands. It is a partnership that will be even stronger whensupported by other members of a household or buying group,and where consumption is associated with communitymembership or identity. Examples include Skoal smokelesstobacco among some North American cowboys, loyalty toparticular European soccer teams (Arnould et al., 2002), theBeanie Babies craze (Morris and Martin, 2000), Jeep brand

fests (McAlexander et al., 2002), and the classic case ofHarley-Davidson bikers (Schouten and McAlexander, 1995).Despite the psychological and sociological richness of the

“attitudes drive behaviour” and “relationship” approaches tounderstand customer loyalty, these conceptualizations ofloyalty are not without drawbacks (e.g. Dowling, 2002). Theyare thought to be less applicable for understanding the buyingof low-risk, frequently-purchased brands, or when impulsebuying or variety seeking is undertaken, than for important orrisky decisions (Dabholkar, 1999). Also, as Oliver (1999) hasnoted, there is little systematic empirical research tocorroborate or refute this perspective of customer loyalty.The examples above are isolated cases, often cited asillustrative of the revenue-effects that might be achieved,rather than the profit impacts that have been achieved.

Loyalty mainly expressed in terms of revealed behaviourThis conceptualisation is arguably the most controversial butthe best supported by data. The controversy comes outbecause loyalty is defined mainly with reference to the patternof past purchases with only a secondary interest in consumermotivations or commitment to the firm (Ehrenberg, 1988;Fader and Hardie, 1996; Kahn et al., 1988; Massy et al.,1970). Researchers have gathered impressive amounts of dataabout these purchase patterns over many years – acrossdozens of product categories and for many diverse countries(Uncles et al., 1994). They have found that few consumers are“monogamous” (100 percent loyal) or “promiscuous” (noloyalty to any brand). Rather, most people are “polygamous”(i.e. loyal to a portfolio of brands in a product category).From this perspective, loyalty is defined as “an ongoingpropensity to buy the brand, usually as one of several”(Ehrenberg and Scriven, 1999).These researchers tend to adopt a market focus as opposed

to an individual focus (e.g. key performance measures arepurchase amount and frequencies, repeat-buying – for adefined period).Stochastic modelling techniques describe the observed

patterns of customer buying. Given these descriptions, loyaltyis inferred to operate in the following manner: through trialand error, a brand that provides a satisfactory experience ischosen.Loyalty to the brand (measured by repeat purchase) is the

result of repeated satisfaction that in turn leads to weakcommitment. The consumer buys the same brand again, notbecause of any strongly-held prior attitude or deeply-heldcommitment, but because it is not worth the time and troubleto search for an alternative. If the usual brand is out of stockor unavailable for some reason, then another functionallysimilar (or substitutable) brand (from the portfolio) will bepurchased (e.g. East, 1997; Ehrenberg et al., 1997, 2004).There is little reason to spend much effort weighing up thealternatives when all are likely to be satisfactory. However,over repeated purchases a weak commitment to the (limited)number of brands bought in a product category can form.All these studies are grounded in considerable amounts of

market research data and analysis. But, despite the weight ofempirical evidence, controversy persists. Those who subscribeto the “attitudes drive behaviour” and “relationship”approaches expressly rule out revealed behaviour as adominant measure of loyalty. That, they argue, may merelyreflect happenstance. Even combined measures of revealedbehavior and satisfaction may not probe deeply enough for us

Customer satisfaction and loyalty in a digital environment

Jean Donio’, Paola Massari and Giuseppina Passiante

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to be sure there is true loyalty (Arnould et al., 2002; Oliver,1999).

Buying moderated by the individual’s attitudesThis conceptualisation argues that the best conceptualizationof loyalty is to allow the relationship between attitude andbehaviour to be moderated by time. The reasons forincorporating buyers’ attitudes into a definition of loyaltyhave been put forward by various authors over the past 20years are two:1 Distinguishing between attitudinally loyalty and

non-attitudinally loyal customers is useful because itindicates who and how many customers are vulnerable toa change in the “spurious” environmental causes of theirloyal behaviour. Hence, it gives an indication of how longcustomers are likely to stay loyal.

2 A purely behavioural definition of loyalty fails to explainthe causes of loyal behaviour.

The dynamic approach is based on a dynamic model that hasbeen defined in order to interpret the customer-firmrelationship life-cycle as a continuum, along which cognitiveand behavioural constructs overlap. In this way throughsuccessive sedimentation the multidimensional construct ofcustomer loyalty is defined.The model is founded on empirical evidence and

experiments realized in the different fields of study.Specifically, it refers to: studies on customer satisfaction, itsdeterminants and consequences (Iacobucci et al., 1992;Oliver, 1997); empirical evidence on trust, as well as studiesthat are the connection with the propensity to repurchase andthe consolidation of the relationship (Bitner, 1995; Blois,1999); and the studies of the relationship life-cycle and thedifferent forms of loyalty, whose basic configuration is simplerepurchase, but with an evolution path towards “true loyalty”on the base of the attitudinal constructs interacting with thebehavioural one (Jacoby and Chestnut, 1973, 1978; Ford,1980, 1998; Iacobucci and Zerrillo, 1997). In Figure 1, thedynamic model of customer loyalty is described. The anchorpoints are customer trust and customer commitment.In this model, satisfaction with past purchases, and any

consequential habit formation, explains most of a person’s

ongoing propensity to buy one or a product from a specificfirm. All these patterns profile customers, not brands per se;that is, consumers of a firm’s products could be distributedacross segmentation criteria with respect to their loyalty levelto a brand/firm.As shown in Figure 1, trust is considered as an outcome of

customer satisfaction and as antecedent of customercommitment and customer loyalty. The reason why manyauthors regard trust as an antecedent of customer loyalty isunderlined by Moorman et al. (1993). According with Schurrand Ozanne (1985) trust has been defined as “the belief that aparty’s word or promise is reliable and that a party will fulfilhis/her obligation in an exchange relationship”.Commitment expresses the extent to which a partner is

willing to maintain a valued relationship (Moorman et al.,1992), and similarly to trust, is “critical to the study andmanagement of customer loyalty” (Morgan and Hunt, 1994,p. 31). Trust is seen as a key determinant to commitment (e.g.Morgan and Hunt, 1994; Gruen, 1995; Geyskens et al.,1996). Morgan and Hunt (1994) state that “trust is soimportant to relational exchange . . . because relationshipscharacterized by trust are so highly valued that parties willdesire to commit themselves to such relationships”.

Conceptualising customer profitabilityCustomer profitability is a customer-level variable whichrefers to the revenues which one particular customergenerates over a given period of time. Customer profitabilityappears in two temporal forms in marketing literature. First, itappears as an historical record. In this sense, a customerprofitability analysis is similar to the firm’s analysis of itsprofits and losses. The main difference is that a customerprofitability analysis refers to one particular customer,whereas a profit and loss statement refers to all customers.A history-oriented customer profitability analysis can be

made at several levels. A common point of departure is tocalculate the contribution margin (gross contributionmargin), based on “sales revenue less all product-relatedexpenses for all products sold to an individual customerduring one particular period of time” (cf. Wang and Splegel,1994). Then, depending on the availability of data, sales,general and administrative expenses traceable to theindividual customer are subtracted (Cooper and Kaplan,1991; Howell and Soucy, 1990). The result of this calculationis the operating profit generated by the customer. Anextension of this line of thinking is the computation of“customer return on assets”, i.e. customer profitabilitydivided by, e.g. the sum of accounts receivable andinventory (Rust et al., 1996).Second, customer profitability is also referred to in a future

sense in the literature. In this case, it often takes the form ofthe output from a net present value analysis. The output issometimes referred to as the “lifetime value” of a customer(cf. Heskett et al., 1997; Peppers and Rogers, 1993; Petrisonet al., 1993; Rust et al., 1996). It has been defined, forexample, as the stream of expected future profits, net of costs,on a customer’s transactions, discounted at some appropriaterate back to its current net present value (Peppers and Rogers,1997, p. 32).A similar concept is “customer equity” which is seen as a

function of the customer’s volume of purchases, margin perunit of purchase and acquisition, development and retentioncosts traceable to this customer (Blattberg and Deighton, 1996;

Figure 1 A dynamic model of customer loyalty

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Wayland and Cole, 1997). Several authors have also noted thatcustomers generally vary in terms of profitability (Cooper andKaplan, 1991; Peppers and Rogers, 1997; Shapiro et al., 1987;Slywotzky and Shapiro, 1993). It has been argued that oneparticular customer does not generate the same costs andrevenues over time as another customer. Moreover, not allcustomers generate acceptable cost and revenue streams. Forexample, in retail banking, some 50-60 percent of customersmay be unprofitable (Carroll, 1991; Storbacka et al., 1994). Ithas been suggested, therefore, that the firm should activelyencourage relationships with profitable customers and attemptto terminate relationships with unprofitable customers (Jonesand Sasser, 1995; Peppers and Rogers, 1997; Shapiro et al.,1987; Slywotzky and Shapiro, 1993).

Customer profitability and customer loyaltyAn increased focus on profitability at the customer level is areflection of a movement within the marketing disciplinetowards a less aggregate view of markets. In other words, theindividual customer – rather than segments of customers – isincreasingly stressed as the unit of analysis. This movementhas given birth to labels such as “one-to-one marketing” and“micro marketing”. Seen from this perspective, customerprofitability is emerging as an important dimension in whicheach (unique) customer can be described.A focus on customer-level profitability can also be

conceived of as a reflection of marketing’s changing rolewithin the firm (cf. Webster, 1992). An important aspect ofthe new role is that “marketing is too important to be left tothe marketing department”. Consequently, at least inmarketing literature, other departments are encouraged todeal with marketing issues. This can be seen particularly interms of cost control, in the sense that marketing performancemeasures are being introduced in cost accounting literatureand practice. For example, activity-based costing andbalanced scorecard techniques often include dimensionswhich are highly relevant to marketing (cf. Cooper andKaplan, 1991; Kaplan and Norton, 1992). In this context, itis worth noting that marketing has traditionally lagged behindother functional areas of business with respect to theimplementation of cost control systems (Dunne and Wolk,1977; Morgan and Morgan, 1980). Another factor behind theinterest in customer profitability (and its links to behaviourand attitudes) is the development of information technology,e.g. in terms of “data warehouses”, which allows for a detailedanalysis of each customer.Despite the growing interest in customer profitability,

identifying profitable customers is likely to be easier said thandone for most firms. The main reason is that few firms have aninternal accounting system which allows for an analysis ofprofitability at the individual customer level. At least this iswhat many academicians claim (Howell and Soucy, 1990;Myer, 1989; Reichheld, 1996; Slywotzky and Shapiro, 1993).However, given that several computerized systems whichfacilitate an analysis of customer profitability are commerciallyavailable on the market, there are reasons to believe thatpractitioners are experimenting with such data to an extent thatis not yet reported in academic journals. In any case,profitability data on the customer level are generally notcollected in empirical studies carried out by marketingscholars. This is not likely to advance marketing theory. Afterall, profitability lies at the heart of the marketing concept(Kohli and Jaworski, 1990; Narver and Slater, 1990). Similarly,

marketing’s link to profitability is stressed in the definitions ofmarketing offered by the Chartered Institute of Marketing andthe American Marketing Association (cf. Buttle, 1996).However, attention in the marketing literature has insteadbeen focused on other customer-level variables than customerprofitability which provide marketers and market researcherswith an easier access to data, particularly in terms of customersurveys, and are assumed to be carriers of information aboutcustomer profitability. Customer satisfaction and customerloyalty are a variable of this type. The attention devoted tothese particular variables can be seen in the light of the currentinterest in relationship marketing. It is assumed, in brief, that itis more profitable to keep existing customers than to attractnew customers, and it is commonly assumed that customersatisfaction serves as a particularly important antecedent ofcustomer retention and thus long-term customer relationships(cf. Anderson et al., 1994; Buttle, 1996; Rust et al., 1995).However, due to the lack of data on customer profitability, thenature of the satisfaction-loyalty-profitability link has rarelybeen analyzed in empirical terms.

Hypotheses developmentFigure 2 presents the model that guided our hypothesesdevelopment. Following the Bagozzi (1974) holistic construal,the conceptual meaning of our focal concept (loyalty) isobtained through specification of antecedents (purchasebehaviour, satisfaction, trust, commitment) and theoutcomes (profitability).As shown in Figure 2, following Blattberg and Deighton

(1996), Wayland and Cole (1997), we consider customerprofitability as a performance outcome (from the supplier’spoint of view) of customer’s purchase behaviour. We assumecustomer’s purchase behaviour to affect profitability by effectson both revenues and costs. First, as the customer continuesto purchase from the same supplier, the supplier’s revenuesincrease. In addition, as the purchases continue, the customermay discover, and purchase, additional products in thesupplier’s assortment. In other words, the potential for cross-selling may increase over time – which affects revenuespositively (Kalwani and Narayandas, 1995). Second, a highlevel of repeated purchases is likely to go hand in hand withhaving contacts with the supplier at several occasions.H1. Customer purchase behaviour is positively and

significantly related to customer profitability.

As pointed out by several authors (Jones and Sasser, 1995;Chaudhuri and Holbrook, 2001; Fournier, 1998; Oliver,1999), we suggest that customer satisfaction (a mental state)can have an impact on customer profitability: indeed, theUniversity of Michigan found that for every percentageincrease in customer satisfaction, there is an average increaseof 2.37 percent of return on investment (Keiningham andVavra, 2001). Moreover, the cost of gaining a new customer isten times greater than the cost of keeping a satisfied customer(Gitomer, 1998).Following Costabile (2001) we consider satisfaction as a

possible antecedent of customer loyalty. Research aboutinfluencing factors of customer satisfaction on loyalty hasmade considerable progress within the last years (Fournierand Mick, 1999; Oliver, 1999; Anderson et al., 1994; Buttle,1996; Rust et al., 1995; Szymanski and Henard, 2001; Oliver,1999). Indeed, the most commonly applied conceptualmodels of loyalty begin from the well-established notion thatcustomers who have satisfying experiences with products will

Customer satisfaction and loyalty in a digital environment

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buy those products or will intend to buy them again (Jacobyand Kyner, 1973; Szymanski and Henard, 2001; Jacoby andChestnut, 1973, 1978; Ford, 1980, 1998; Iacobucci andZerrillo, 1997).Finally, we hypothesize that, as the customer loyalty

enhances, customer profitability increases (Reichheld andSasser, 1990; Kohli and Jaworski, 1990; Narver and Slater,1990). Improvements in customer loyalty and retention byeven a few percentage points have in some cases increasedprofits by 25 per cent or more (Griffin, 1995).H2. Customer satisfaction is positively and significantly

related to customer profitability.H3. Customer loyalty attitude is positively and significantly

related to customer profitability.H4. Customer satisfaction is positively and significantly

related to customer loyalty attitude.

We have also included two variables, which are assumed to beconsequences of customer satisfaction and predictors ofprofitability, as they have been suggested by the literature(Costabile, 2001; Garbarino and Johnson, 1999; Andersonet al., 1994; Peppers and Rogers, 1997; Reichheld, 1996).Variables are trust and commitment that influence reciprocityand co-operation between the firm and its customers (Sternand El Ansary, 1992; Bucklin and Sengupta, 1993; Bitner,1995; Blois, 1999). We have added to the previous hypothesesthe analysis of trust and commitment as determinants thatdevelop as customers gain experience and adopt relationalorientations, and their connection with the customerpropensity to repurchase and to consolidate of therelationship, following the suggestions of Bitner (1995),Blois (1999) and Garbarino and Johnson (1999).More specifically, trust has been considered as an outcome

of customer satisfaction (Schurr and Ozanne, 1985) and as anantecedent of customer commitment and customer loyalty(e.g. Morgan and Hunt, 1994; Gruen, 1995; Geyskens et al.,1996; Scheer and Stern, 1992).

H5. Customer satisfaction, trust and commitment arepositively and significantly related to purchasebehaviour.

Research method

In order to test our hypotheses, we have conducted anempirical study in the agri-food sector. The point of departurefor the case study was to match customer satisfaction andcustomer loyalty attitude data (at the customer level) withpurchase behaviour and profitability data (also at thecustomer level). The first step has been to identify a firmwhich had kept track of costs and revenues over time at acustomer level, and was willing to provide access to this data.We identified one firm. For confidentiality issues we cannotname it.The firm is based in Italy and sells food products (pasta,

olive oil, wine, vegetables, bread, sauces, cakes, honey andother typical foods) through direct marketing activities. Itscurrent range consists of about 50 different items. Mostrelevant sales channels used are: telephone, internet,television, catalogue mail. The most important directmarketing instrument is based on the telephone, whichdevelops alone 52 per cent of sales purchase. Televisioninstrument develops 27 per cent of sales, catalogue mail 18per cent of sales, and internet just 3 per cent of sales. Thecustomer base is spread throughout the national territory.Products are delivered through a national courier directly tothe houses of its customers. The cost accounting systemallows for a detailed analysis of customer behaviour, as wellas analyses of profitability at several levels (customers,products, sales persons, etc). This technology has beencomplemented with a telephone survey submitted to thecustomers.

Figure 2 Predicted links between customer loyalty attitude, purchase behaviour and customer profitability

Customer satisfaction and loyalty in a digital environment

Jean Donio’, Paola Massari and Giuseppina Passiante

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Data collectionThe data used in this study have been derived from twosources: a telephone survey of the firm’s customers; and thefirm’s customers’ database.In order to collect data on customer satisfaction and

customer loyalty attitude, a telephone survey was developed.The scales used by respondents have been measured onbalanced five-point Likert-type scales, ranging from “stronglydisagree” to “strongly agree”, where 1 ¼ strongly disagree and5 ¼ strongly agree. The telephone survey was chosen becauseof its relevant advantages such as monitoring of interviews forimproved quality control, higher response rates, less bias dueto non-response, shorter time requirements for completion,reasonably low cost (Dutka, 1993; Leland and Bailey, 1995).Customer satisfaction was measured as the weighted mean ofthree items[1] defined during a previous the market survey,based on global satisfaction, congruence between expectedand perceived value, value perception. Customer LoyaltyAttitude was measured with nine items adapted fromMorgan and Hunt (1994), Moorman et al. (1992, p. 82),Pearson (1996), Schijns and Schroder (1996), Anderson andNarus (1984, p. 66), Selnes (1993), Crosby et al. (1990),Anderson and Weitz (1989). Two main dimension ofcustomer loyalty attitude were investigated: customer trustand customer commitment. Customer Trust was measuredwith one item adapted from Hess (1995) and Moorman et al.(1992). Customer Commitment was measured using a multi-item scale adopted and modified from Mowday et al.’s (1979)Organizational Questionnaire, and Beatty and Kahle’s (1988)brand commitment scale. In particular, the following mostrelevant dimensions of customer commitment were examined:exclusive purchase intention, word-of-mouth[2], expectationof continuity, price sensitivity.Indicators and items capturing customer satisfaction and

the attitudinal dimensions of customer loyalty are described inTable I.Data on customer purchase behaviour and profitability were

collected from the firm database. Thus, the behavioural

dimension of customer loyalty was measured by ten indicatorsas shown in Table II.Data on purchase behaviour and customer profitability were

collected from the firm database. The firm provided us theaccess to its records for the period December 2002-June2004. The sample selection was based on the firm’s retainedcustomers (those customers who made at least one purchaseannually after the initial sale), who participated to thetelephone survey with a useful response rate (in total, 4,397customers). Data from these records were then entered intothe same database as the survey responses. The client codewas the key to matching the purchase behaviour andprofitability records kept by Firm A on each customer withthe survey responses. Several attempts were made to examinethe quality of measurements. Internal consistency of the scalesused was ascertained by both calculating Cronbach’scoefficient alpha and conducting an item analysis (throughitem-whole and inter-item correlation, as suggested bySpector, 1992).First, Cronbach’s alpha results were largely higher than

Malhotra’s (1993, p. 308) 0.60 limit for acceptable reliabilityin terms of internal consistency. The customer attitudinalloyalty measure, consisting of nine items, has an alpha valueof 0.910. The customer satisfaction measure, consisting ofthree items, has an alpha value of 0.798. The customerpurchase behaviour measure, consisting of ten items, has analpha value of 0.92. Content validity for the customer loyaltyattitude, customer satisfaction, customer behaviours andcustomer profitability measures was ascertained by examiningthe scale composition throughout measure purification. Theresulting scales demonstrate good reliability, as evidenced byTable III, in addition to being content valid.

Data analysisThe data gathered from the customer survey (data capturingattitudinal loyalty and customer satisfaction) and the firm’sdata base (data capturing customer behaviours andprofitability) were entered into a computer database and

Table I Variables and items capturing attitudinal loyalty and customer satisfaction

Variables Indicators Survey’s items

Attitudinal Trust Trust attitude (1-5) I feel that I completely trust this firm activities and its products

Loyalty Commitment Willingness to invest in the relationship (1-5) As a consumer to this firm/brand, I am willing to put in extra effort to buyproduct from this firm

Exclusive purchase intention (1-5) As long as the product is similar I could just as well be buying from a differentfirm/branda

Word-of-mouth attitude (1-5) I am proud to tell others that I buy product from this firm. I would recommendthis brand to others

Exclusive purchase Intention (1-5) For me, this brand is the best alternativeExpectation of continuity (1-5) I expect to stay with this brand for a long period of timePrice sensitivity (1-5) As a consumer to this brand, I feel that I am prepared to pay more for higher

quality productsLoyalty perception (1-5) I feel very little loyalty to this firm/branda

Satisfaction Satisfaction Global satisfaction (1-5) I am completely satisfied with the products of firm ACongruence between expected and perceivedvalue (1-5)

Performance expectations after purchasing firm A’s products exceedexpectations prior to the purchase

Value perception (1-5) Firm A’s products benefits are more important with respect to the costs andsacrifices related to the product purchase

Note: a Reverse coded items

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then analyzed using the Statistical Package for the SocialSciences (SPSS). Factor analysis, cluster analysis, ANOVA,canonical correlation analysis, multiple regression, pathanalysis, and t-tests were employed to test the researchhypotheses on the relationships among the variables.A logistic regression analysis was used in order to identify

the stronger predictors of customer profitability and customerloyalty, using all available measures, including bothbehavioural and attitudinal variables. The regressioncoefficients of each model equation related to the mainhypothesis were elaborated. A particular attention was givento standardised coefficients calculation. This, because themagnitude of a regression coefficient isn’t necessary related tohow good a predictor the variable is, since the size of thecoefficient depends in large part on the units of the measurefor the variable. One way to make the coefficients easier tocompare is to compute what are known as standardisedcoefficients (Beta coefficients).

ANOVA analysis summarized the results of variance’sanalysis. The sum of squares and mean square were analysed,for two sources of variation, regression and residual. Theoutput for Regression displayed useful information about thevariation accounted for by each model. The output forResidual displayed information about the variation that wasnot accounted for by each model. R, R squared, adjusted Rsquared, and the standard error were analysed. Among theinitial hypothesis, the model that accounted for most ofvariation in the dependent variable, with a good largeregression sum of squares in comparison to the residual sumof squares, was highlighted.Some observations should be made before we examine the

outcome with regard to the hypotheses.First, the standard deviations for customer profitability

confirm what was claimed about this variable in theintroduction. That is to say, customers clearly do vary interms of the profitability they generate. For example, in thiscase study, the top ten customers (2.4 per cent of the sample)who ranked highest in terms of customer profitabilitygenerated 20 per cent of the total customer profitability inthe sample. This is in line with most relevant theoreticalapproaches and empirical evidences. Second, the analysis ofthe most relevant behavioural loyalty variables (customer n oforders and sales purchases value) reveals a positive and strongcorrelation with customer profitability that has beenconfirmed by the Beta coefficients computation. Thedetailed results of these computations are summarised inTable IV.

Table II Variables and items capturing customer purchase behaviour and profitability

Variables Definitiona

1. Sales purchases value (1-5) The amount of sales purchases (Euros) during a period of time of 18 months

2. N. of orders (1-5) The number of orders during a period of time of 18 months

3. Frequency of purchases (1-5) The frequency of purchase, expressed in days (n. orders/days)

4. Returns (1-5) The percentage of products returns with respect to overall sales purchase value (returns/total sales purchasevalue expressed in %)

5. Debt (1-5) The % of debt with respect to overall sales purchase

6. Interactions (1-5) All kind of interaction with the firm, intended ad communications, compliments, complaints

7. Way of payment (1-5) The way of payment usually chosen by the customer (credit card, anticipated to the courier, at moment of delivery,anticipated through the bank, after 30/60 days)

8. Way of order (1-5) The order could be done in outbound way (the firm contact the client, during a direct marketing campaign) or ininbound way (the client contact the firm for the order)

9. Loyalty program’s membership (1-5) The client shares some personal information with the firm in order to participate in Loyalty Programs

Composition of purchase (1-5) The composition of purchase, expressed in %, could be based more on special offers and discount or could bebased more on purchase with normal conditions of price

Customer profitability (1-5) According with Cooper and Kaplan (1991) and Howell and Soucy (1990), customer profitability wasoperationalised for each customer in the sample as “ þ sales revenue – all product related expenses for allproducts sold to an individual customer during one particular period of time, – sales, general and administrativeexpenses traceable to the individual customer for the same period of time”. The currency is EU currency (Euro)and a period of 18 months is included in the analysis. Thus, the profitability observations for each customerconsist of the operating profit generated by each customer during this period of time

Note: a Variables definition is based on literature review (Kelley, 1967; Raj, 1982; Tate, 1961, Farley, 1968; Fournier and Yao, 1997; Kahn et al., 1986; Rao, 1969;Carman, 1970; Enis and Paul, 1970; Goldman, 1977-1978; Jacoby and Chestnut, 1978; Cooper and Kaplan, 1991; Howell and Soucy, 1990; Kaplan and Norton,2004) and on the results of an Expert Analysis (survey to 30 managers of the agri-food sector)

Table III Scale summary

Constructs scale n a N Std dev.

Satisfaction 3 0.798 4,397 0.42Customer loyalty attitude 9 0.910 4,397 0.54Customer purchase behaviour 10 0.92 4,397 3.9Customer profitability 1 0.944 4,397 4.2

Notes: n ¼ number of items; a = Cronbach’s alpha; N ¼ number of cases;Std dev. ¼ standard deviation

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As shown in Table IV, all the hypotheses of conceptualframework were confirmed by the empirical results.

Discussion: the governance of customer loyalty

The results showed support for all but one of the fivehypotheses, the exception being H2.Purchase behaviour (behavioural dimension of customer

loyalty) was found to be positively and significantly associatedwith customer profitability. This result was confirmed by tstatistics method results, that identified sales purchase valueand number of orders as some of the best predictors ofcustomer profitability.Customer satisfaction was found to be positively associated

with customer profitability, but it was considered not staticallysignificant. The results confirm what was claimed about thisvariable in the introduction: customer satisfaction (a mentalstate) has not any direct impact on customer profitability.Thus, our results seem to confirm the hypotheses of Fournierand Mick (1999) and Oliver (1999) that it is the behaviour ofthe customer, which may follow from a certain level ofsatisfaction, trust and commitment that affects customerprofitability.Customer loyalty attitude was found to be positively and

significantly associated with customer profitability. Our modelthen relates “customer attitudinal loyalty” measures (intent torepurchase, willingness to recommend and other probablemarket actions) to the expected profitability of each customer:estimating the customer expected profitability, basing on hisattitudinal loyalty level, could be extremely useful for amanager for setting-up a customized marketing strategy, such

as maintaining a price advantage and/or providing additionalservices to offer value. To this end, in the literature somecategorization of customers are suggested, useful foridentifying, motivating, serving a customer according to his/her expected differential levels of profits (e.g. Zeithaml et al.,2001)Customer satisfaction was found to be positively related to

customer loyalty attitude, explaining 43 per cent of thevariance of the latter. However, multiple linear regression andANOVA analysis have shown that the model fails to explain alot of the variation in the dependent variable, and it needs foradditional factors that help account for a higher proportion ofthe variation in the dependent variable. This is in line withmany theoretical approaches that highlighted how apparenthigh levels of satisfaction may not result in a behaviourcharacterised by high loyalty due to the many interveningvariables of customer loyalty development process (Jones andSasser, 1995; Oliver, 1999).Satisfaction, trust and commitment were found to be

positively and significantly associated with purchasebehaviour. Three variables were entered the model, but twoof them resulted most relevant according with t statisticmethod: customer trust and customer commitment. Figure 3shows the links between purchase behaviour and the maincustomer loyalty attitude enablers.Customer trust and customer commitment resulted the

most important variables positively and significatively relatedto purchase behaviour. In particular, customer commitment,with the large t statistics value, resulted to be the main driverfor customer purchase behaviour.

Table IV Results of the computations

Unstandardizedcoefficients Standardized coefficients

B Std error Beta t Sig.

H1Dependent variable: profitability(Constant) 0.015 0.007 2.164 0.031Customer purchase behaviour (REGR factor score 1 for analysis 1) 0.736 0.015 0.964 48.329 0.000

H2Dependent variable: profitability(Constant) 0.431 0.010 45.308 0.000Customer satisfaction 0.446 0.007 0.684 62.010 0.000

H3Dependent variable: profitability(Constant) 0.018 0.021 0.875 0.381Customer loyalty attitude (REGR factor score 1 for analysis 2) 0.325 0.035 0.822 10.022 0.000

H4Dependent variable: loyalty attitude(Constant) 0.015 0.002 6.138 0.021Customer satisfaction 0.058 0.005 0.725 0.039 0.000

H5Dependent variable: purchase behaviour(Constant) 2.386 0.500 212.430 0.000Customer trust 0.230 0.060 0.760 12.208 0.000Customer commitment 1.254 0.023 0.823 32.342 0.000Customer satisfaction 20.061 0.054 0.621 1.778 0.000

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Our study has identified several significant associationsbetween variables in the customer satisfaction-customerloyalty attitude-purchase behaviour (behavioural loyalty)-customer profitability chain. The associations between thetwo latter types of variables should not be surprising, since itis the actual acts by customers, not their attitudes that affectthe firm’s performance (cf. Storbacka et al., 1994). However,the results of our analysis show that customer loyalty variablesare related to what customers do in terms of purchasebehaviour: these relationships are commonly missing in manyparts of the marketing literature. Segmentation literature, andparticularly the literature on segmentation of businessmarkets, is one area in which these results are relevant.Many segmentation variables have been described ascandidates for the segmentation of business markets, butthey are generally related to other characteristics of the buyerthan customer loyalty (cf. Shapiro and Bonoma, 1984;Webster, 1984). The results of the study provide evidence thata Loyalty Index can give managers an adequate support formarket segmentation. This means that actual market segmentstrategies, based on geographical, demographical and/orpsychographic variables, should take into account alsoloyalty measurement models.Literature review and empirical results have also shown cost

savings associated with a loyalty building strategy in at leastsix areas (Reichheld, 1996):1 reduced marketing costs – customer acquisition costs

more;2 lower transaction costs, such as outbound efforts and

order processing;3 reduced customer turnover expenses (fewer lost

customers to replace);4 increased cross-selling success, leading to larger share of

customer;5 more positive word of mouth; and6 reduced failure costs (reduction in returns, debt, claims

and complaints).

To obtain these cost savings, we believe that is necessary tomeasure and manage customer loyalty effectively, by usingboth leading and lagging indicators:. Attitudinal measures, such as customer commitment

(intent to repurchase, willingness to recommend andother probable market actions) provide the basis fordeveloping leading indicators of customer loyalty.

. Behavioural measures, such as repeat purchasing, volumeor frequency of purchasing, returns, debt, complaints and

interactions, customer retention and longevity, furnish keylagging indicators of customer loyalty.

As suggested by Kaplan and Norton (1992), without effectiveleading indicators, it may be difficult to establish howoutcomes are achieved. Moreover, an organization lackingleading indicators of key performance outcomes or results hasno early warning mechanism to signal the need for correctiveaction. By relying exclusively on outcomes or results,organizations may not detect the need for action until it istoo late. The link between the attitudinal and behaviouralindicators pointed out in this paper allow to use attitudinalmeasures for the purpose of estimating future results, as wellas developing models that enable an organization to examinealternative “what-if” scenarios.

Conclusions

In this paper we have explored links between variablesconcerning the customer satisfaction – the customerattitudinal loyalty – the customer behavioural loyalty – thecustomer profitability chain.We have included both attitudinal (such as intent to

repurchase, willingness to recommend and other probablemarket actions have been included in order to provide thebasis for developing leading indicators of customer loyalty)and behavioural measures (such as repeat purchasing, volumeor frequency of purchasing, returns, debt, complaints andinteractions, customer retention and longevity, have beenincluded as lagging indicators of customer loyalty).Our model also has verified some relations existing between

attitudinal measures and behavioural measures, in order touse attitudinal measures for estimating the customer expectedprofitability; this estimation can be used for setting-up acustomized marketing strategy, such as maintaining a priceadvantage and/or providing additional services to offer value.As a conclusion, some limitations of our study should be

emphasised. Firstly, data were collected in one single firm.Secondly, the study focused on a single industry, namely thatof agri-food. While useful in controlling for potentialextraneous influences unrelated to the study, the limitationinvolved in studying a single industry constrains the possibilityto generalize these findings. Future research should seek toreplicate the study into different firms and business sectors inorder to assess whether the linkages identified here still existin different industrial and consumer populations. Anotherlimitation is related to the time periods used in the study. It isnot clear to what extent the time periods have provided a

Figure 3 Links between customer loyalty attitude enablers and purchase behaviour

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proper context for an analysis of the relationships betweenattitudinal variables and behavioural variables. However, itdoes seem clear that attitudinal variables such as customersatisfaction do not remain constant over time (cf. Petersonand Wilson, 1992). Future research should seek to replicatethe study into different period of time, more than one. Itmeans, among other things, that the timing of the surveybecomes a key issue. One may consider as time unit “theyear”, but if customer relationships are viewed as investments,a longer period may be needed to determine the extent towhich one particular customer is profitable (cf. Reichheld,1996).

Notes

1 Items capturing customer satisfaction have been adaptedfrom Pearson (1996), Oliver (1993), Holbrook (1999),Costabile (2001), Westbrook and Oliver (1991).

2 Word-of-mouth can be defined as “oral, person-to-personcommunication between a receiver and a communicator”(Arndt, 1967, p. 189).

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Crosby, L.A. and Stephens, N. (1987), “Effects ofrelationship marketing on satisfaction, retention, andprices in the life insurance industry”, Journal of MarketingResearch, Vol. 24 No. 4, pp. 404-11.

Customer satisfaction and loyalty in a digital environment

Jean Donio’, Paola Massari and Giuseppina Passiante

Journal of Consumer Marketing

Volume 23 · Number 7 · 2006 · 445–457

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Dowling, G.R. and Uncles, M.D. (1997), “Do customerloyalty programs really work?”, Sloan Management Review,Vol. 38 No. 4, pp. 71-82.

Ehrenberg, A.S.C., Mark, D.U. and Goodhardt, G. (2004),“Understanding brand performance measures: usingDirichlet benchmarks”, Journal of Business Research.,Vol. 57 No. 12, pp. 1307-25.

Fournier, S. (1996), “The consumer and the brand: anunderstanding within the framework of personalrelationships”, working paper 97-024, Harvard BusinessSchool, Boston, MA.

Heskett, J.L., Jones, T.O., Loveman, G.W., Sasser, W.E. andSchlesinger, L.A. (1994), “Putting the service profit chainto work”, Harvard Business Review, Vol. 72 No. 2,pp. 164-74.

O’Brien, L. and Jones, C. (1995), “Do rewards really create

loyalty?”,Harvard Business Review, Vol. 73 No. 3, pp. 75-82.

About the authors

Jean Donio’, is a Full Professor at the University of Paris II,

France. He is the corresponding author and can be contacted

at: jdonio@easynet.frPaola Massari is a Researcher at e-Business Management

School, ISUFI, University of Lecce, Lecce, Italy.Giuseppina Passiante is a Full Professor of Innovation

Management at the e-Business Management School, ISUFI,

University of Lecce, Lecce, Italy.

Customer satisfaction and loyalty in a digital environment

Jean Donio’, Paola Massari and Giuseppina Passiante

Journal of Consumer Marketing

Volume 23 · Number 7 · 2006 · 445–457

457

To purchase reprints of this article please e-mail: reprints@emeraldinsight.com

Or visit our web site for further details: www.emeraldinsight.com/reprints

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