customer satisfaction and loyalty

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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 Passiante

e-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 customepurchase 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 firms 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 and

loyalty has made considerable progress within the last years

(Szymanski and Henard, 2001; Oliver, 1999). Customer

loyalty is seen to be crucial to the success of business

organizations, since attracting new customers is far more

expensive than retaining existing ones (Dick and Basu, 1994;

Saren and Tzokas, 1998; Fournier, 1998). It has been

suggested by many authors that loyal customers are a

competitive asset and that a way of increasing customer

retention is through secure and collaborative relationship

between buyers and sellers (Chaudhuri, 1999; Chaudhuri and

Holbrook, 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; Slywotzky

and Shapiro, 1993), and not all customers generate

acceptable cost and revenue streams (Carroll, 1991;

Storbacka et al., 1994). It has been suggested, therefore,

that the firm should actively develop relationships with

profitable customers and try to end relationships withunprofitable customers (Jones and Sasser, 1995; Peppers

and Rogers, 1993; Shapiro et al., 1987; Slywotzky and

Shapiro, 1993). Tailoring marketing efforts to segments that

differ in current and/or future profitability makes a firms

strategy more effective, by identifying profitability customer

tiers, and offer products and services customized for the

specific 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 consistently

favourable set of stated beliefs towards the brand purchase),customer loyalty behaviours (in terms of his pattern of past

purchases) and profitability. To this end, customer loyalty, its

antecedents and outcomes, and, thus, the links between

customer satisfaction, customer loyalty and profitability have

been analyzed at a customer level. Specifically, the study has

focused 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 firms customer base? Is

there any model that can assess customer loyalty based on

specific variables and indexes? Do characteristics exist

which determine whether customers attain high levels of

customer loyalty?

Our approach is based on a framework put forward by

Costabile (2001) to analyse the relationship existing between

the act of purchase of the customer, his satisfaction, his trust

and commitment and, at the end, his loyalty. In this study, we

have extended the single act of purchase to the complete

purchase behaviour of the customer, and we have also

explored the relationship existing between the customer

loyalty and his profitability.

The paper is organized as follows. The first section presents

the theoretical framework and the main hypotheses. The

second section illustrates the method adopted. The main

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

www.emeraldinsight.com/0736-3761.htm

Journal of Consumer Marketing

23/7 (2006) 445457

q Emerald Group Publishing Limited [ISSN 0736-3761]

[DOI 10.1108/07363760610712993]

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results are described and discussed in section three. The final

section presents conclusions and a future research agenda.

Theoretical framework and main hypotheses

Customer loyalty: antecedents and outcomes

Customer loyalty is a concept that has enjoyed wide currency

and usage within the field of consumer behaviour for manyyears. Dick and Basu (1994) viewed customer loyalty as the

strength of the relationship between an individuals relative

attitude towards an entity (brand, service, store, or vendor)

and repeat patronage. Three conceptualizations of customer

loyalty 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); and

3 buying moderated by the individuals attitudes.

Loyalty as primarily an attitude that leads to a relationship withthe brand

Researchers argue that there must be a strong attitudinal

commitment 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 taking

the form of a consistently favourable set of stated beliefs

towards the brand purchased. These attitudes may be

measured by asking people how much they like the brand,

feel committed to it, will recommend it to others, and have

positive beliefs and feelings about it relative to competing

brands (Dick and Basu, 1994). The strength of these attitudes

is the key predictor of a brands purchase and repeat

patronage. This is what Oliver (1997, p. 392) has in mind

when he defines customer loyalty as: A deeply held

commitment to re-buy or re-patronize a preferred product/

service consistently in the future, thereby causing repetitive

same-brand or same brand-set purchasing despite situational

influences and marketing efforts having the potential to causeswitching behaviour. In the fields of advertising and brand

equity research this model received some support (e.g. Aaker,

1996; de Chernatony and McDonald, 1998). The approach

also appealed to many practitioners in advertising and brand

management because it is empathetic with the search for

strategies to enhance the strength of consumers attitudes

towards a brand.

Ahluwalia et al. (1999) have shown that attitudinally-loyal

customers are much less susceptible to negative information

about the brand than non-loyal customers. Also, where loyalty

to a brand increases, the revenue-stream from loyal customers

becomes more predictable and can become considerable over

time 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 relationships

with some of their brands. A good example of this perspective

is provided by Fournier (1998), who sees loyalty as a

committed and affect-laden partnership between consumers

and brands. It is a partnership that will be even stronger when

supported by other members of a household or buying group,

and where consumption is associated with community

membership or identity. Examples include Skoal smokeless

tobacco among some North American cowboys, loyalty to

particular European soccer teams (Arnould et al., 2002), the

Beanie Babies craze (Morris and Martin, 2000), Jeep brand

fests (McAlexander et al., 2002), and the classic case o

Harley-Davidson bikers (Schouten and McAlexander, 1995)

Despite the psychological and sociological richness of the

attitudes drive behaviour and relationship approaches to

understand customer loyalty, these conceptualizations o

loyalty are not without drawbacks (e.g. Dowling, 2002). They

are thought to be less applicable for understanding the buying

of low-risk, frequently-purchased brands, or when impulsebuying or variety seeking is undertaken, than for important or

risky decisions (Dabholkar, 1999). Also, as Oliver (1999) has

noted, there is little systematic empirical research to

corroborate or refute this perspective of customer loyalty

The examples above are isolated cases, often cited as

illustrative of the revenue-effects that might be achieved

rather than the profit impacts that have been achieved.

Loyalty mainly expressed in terms of revealed behaviour

This conceptualisation is arguably the most controversial but

the best supported by data. The controversy comes out

because loyalty is defined mainly with reference to the pattern

of past purchases with only a secondary interest in consumer

motivations 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 data

about these purchase patterns over many years across

dozens of product categories and for many diverse countries

(Uncleset al., 1994). They have found that few consumers are

monogamous (100 percent loyal) or promiscuous (no

loyalty 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 ongoing

propensity 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 are

purchase amount and frequencies, repeat-buying for a

defined period).Stochastic modelling techniques describe the observed

patterns of customer buying. Given these descriptions, loyalty

is inferred to operate in the following manner: through trial

and error, a brand that provides a satisfactory experience is

chosen.

Loyalty to the brand (measured by repeat purchase) is the

result of repeated satisfaction that in turn leads to weak

commitment. The consumer buys the same brand again, not

because of any strongly-held prior attitude or deeply-held

commitment, but because it is not worth the time and trouble

to search for an alternative. If the usual brand is out of stock

or unavailable for some reason, then another functionally

similar (or substitutable) brand (from the portfolio) will be

purchased (e.g. East, 1997; Ehrenberg et al.

, 1997, 2004)There is little reason to spend much effort weighing up the

alternatives 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 of

empirical evidence, controversy persists. Those who subscribe

to the attitudes drive behaviour and relationship

approaches expressly rule out revealed behaviour as a

dominant measure of loyalty. That, they argue, may merely

reflect happenstance. Even combined measures of revealed

behavior 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 individuals attitudes

This conceptualisation argues that the best conceptualization

of loyalty is to allow the relationship between attitude and

behaviour to be moderated by time. The reasons for

incorporating buyers attitudes into a definition of loyalty

have been put forward by various authors over the past 20

years are two:

1 Distinguishing between attitudinally loyalty and

non-attitudinally loyal customers is useful because it

indicates who and how many customers are vulnerable to

a change in the spurious environmental causes of their

loyal behaviour. Hence, it gives an indication of how long

customers are likely to stay loyal.

2 A purely behavioural definition of loyalty fails to explain

the causes of loyal behaviour.

The dynamic approach is based on a dynamic model that has

been defined in order to interpret the customer-firm

relationship life-cycle as a continuum, along which cognitive

and behavioural constructs overlap. In this way through

successive sedimentation the multidimensional construct of

customer 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, its

determinants and consequences (Iacobucci et al., 1992;

Oliver, 1997); empirical evidence on trust, as well as studies

that are the connection with the propensity to repurchase and

the consolidation of the relationship (Bitner, 1995; Blois,

1999); and the studies of the relationship life-cycle and the

different forms of loyalty, whose basic configuration is simple

repurchase, but with an evolution path towards true loyalty

on the base of the attitudinal constructs interacting with the

behavioural one (Jacoby and Chestnut, 1973, 1978; Ford,

1980, 1998; Iacobucci and Zerrillo, 1997). In Figure 1, thedynamic model of customer loyalty is described. The anchor

points are customer trust and customer commitment.

In this model, satisfaction with past purchases, and any

consequential habit formation, explains most of a persons

ongoing propensity to buy one or a product from a specific

firm. All these patterns profile customers, not brands per se

that is, consumers of a firms products could be distributed

across segmentation criteria with respect to their loyalty level

to a brand/firm.

As shown in Figure 1, trust is considered as an outcome of

customer satisfaction and as antecedent of customer

commitment and customer loyalty. The reason why manyauthors regard trust as an antecedent of customer loyalty is

underlined by Moorman et al. (1993). According with Schurr

and Ozanne (1985) trust has been defined as the belief that a

partys word or promise is reliable and that a party will fulfi

his/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 and

management 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 so

important to relational exchange . . . because relationships

characterized by trust are so highly valued that parties wil

desire to commit themselves to such relationships.

Conceptualising customer profitability

Customer profitability is a customer-level variable which

refers to the revenues which one particular customer

generates over a given period of time. Customer profitability

appears in two temporal forms in marketing literature. First, it

appears as an historical record. In this sense, a customer

profitability analysis is similar to the firms analysis of its

profits and losses. The main difference is that a customer

profitability 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 to

calculate the contribution margin (gross contributionmargin), based on sales revenue less all product-related

expenses for all products sold to an individual customer

during one particular period of time (cf. Wang and Splegel

1994). Then, depending on the availability of data, sales

general and administrative expenses traceable to the

individual customer are subtracted (Cooper and Kaplan

1991; Howell and Soucy, 1990). The result of this calculation

is the operating profit generated by the customer. An

extension of this line of thinking is the computation o

customer return on assets, i.e. customer profitability

divided by, e.g. the sum of accounts receivable and

inventory (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 is

sometimes referred to as the lifetime value of a customer

(cf. Heskett et al., 1997; Peppers and Rogers, 1993; Petrison

et al., 1993; Rust et al., 1996). It has been defined, for

example, as the stream of expected future profits, net of costs,

on a customers transactions, discounted at some appropriate

rate 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 customers volume of purchases, margin per

unit of purchase and acquisition, development and retention

costs traceable to this customer (Blattberg and Deighton, 1996;

Figure 1A dynamic model of customer loyalty





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Wayland and Cole, 1997). Several authors have also noted that

customers generally vary in terms of profitability (Cooper and

Kaplan, 1991; Peppers and Rogers, 1997; Shapiro et al., 1987;

Slywotzky and Shapiro, 1993). It has been argued that one

particular customer does not generate the same costs and

revenues over time as another customer. Moreover, not all

customers generate acceptable cost and revenue streams. For

example, in retail banking, some 50-60 percent of customersmay be unprofitable (Carroll, 1991; Storbacka et al., 1994). It

has been suggested, therefore, that the firm should actively

encourage relationships with profitable customers and attempt

to terminate relationships with unprofitable customers (Jones

and Sasser, 1995; Peppers and Rogers, 1997; Shapiro et al.,

1987; Slywotzky and Shapiro, 1993).

Customer profitability and customer loyalty

An increased focus on profitability at the customer level is a

reflection of a movement within the marketing discipline

towards a less aggregate view of markets. In other words, the

individual customer rather than segments of customers is

increasingly stressed as the unit of analysis. This movement

has given birth to labels such as one-to-one marketing and

micro marketing. Seen from this perspective, customer

profitability is emerging as an important dimension in which

each (unique) customer can be described.

A focus on customer-level profitability can also be

conceived of as a reflection of marketings changing role

within the firm (cf. Webster, 1992). An important aspect of

the new role is that marketing is too important to be left to

the marketing department. Consequently, at least in

marketing literature, other departments are encouraged to

deal with marketing issues. This can be seen particularly in

terms of cost control, in the sense that marketing performance

measures are being introduced in cost accounting literature

and practice. For example, activity-based costing and

balanced scorecard techniques often include dimensions

which are highly relevant to marketing (cf. Cooper andKaplan, 1991; Kaplan and Norton, 1992). In this context, it

is worth noting that marketing has traditionally lagged behind

other functional areas of business with respect to the

implementation of cost control systems (Dunne and Wolk,

1977; Morgan and Morgan, 1980). Another factor behind the

interest in customer profitability (and its links to behaviour

and attitudes) is the development of information technology,

e.g. in terms of data warehouses, which allows for a detailed

analysis of each customer.

Despite the growing interest in customer profitability,

identifying profitable customers is likely to be easier said than

done for most firms. The main reason is that few firms have an

internal accounting system which allows for an analysis of

profitability 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 which

facilitate an analysis of customer profitability are commercially

available on the market, there are reasons to believe that

practitioners are experimenting with such data to an extent that

is not yet reported in academic journals. In any case,

profitability data on the customer level are generally not

collected in empirical studies carried out by marketing

scholars. This is not likely to advance marketing theory. After

all, profitability lies at the heart of the marketing concept

(Kohli and Jaworski, 1990; Narver and Slater, 1990). Similarly,

marketings link to profitability is stressed in the definitions of

marketing offered by the Chartered Institute of Marketing and

the American Marketing Association (cf. Buttle, 1996)

However, attention in the marketing literature has instead

been focused on other customer-level variables than customer

profitability which provide marketers and market researchers

with an easier access to data, particularly in terms of customer

surveys, and are assumed to be carriers of information aboutcustomer profitability. Customer satisfaction and custome

loyalty are a variable of this type. The attention devoted to

these particular variables can be seen in the light of the current

interest in relationship marketing. It is assumed, in brief, that it

is more profitable to keep existing customers than to attrac

new customers, and it is commonly assumed that custome

satisfaction serves as a particularly important antecedent o

customer 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, the

nature of the satisfaction-loyalty-profitability link has rarely

been analyzed in empirical terms.

Hypotheses development

Figure 2 presents the model that guided our hypothesesdevelopment. Following the Bagozzi (1974) holistic construal,

the conceptual meaning of our focal concept (loyalty) is

obtained through specification of antecedents (purchase

behaviour, satisfaction, trust, commitment) and the

outcomes (profitability).

As shown in Figure 2, following Blattberg and Deighton

(1996), Wayland and Cole (1997), we consider customer

profitability as a performance outcome (from the suppliers

point of view) of customers purchase behaviour. We assume

customers purchase behaviour to affect profitability by effects

on both revenues and costs. First, as the customer continues

to purchase from the same supplier, the suppliers revenues

increase. In addition, as the purchases continue, the customer

may discover, and purchase, additional products in thesuppliers assortment. In other words, the potential for cross-

selling may increase over time which affects revenues

positively (Kalwani and Narayandas, 1995). Second, a high

level of repeated purchases is likely to go hand in hand with

having 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, the

University of Michigan found that for every percentage

increase in customer satisfaction, there is an average increase

of 2.37 percent of return on investment (Keiningham andVavra, 2001). Moreover, the cost of gaining a new customer is

ten 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 about

influencing factors of customer satisfaction on loyalty has

made considerable progress within the last years (Fournier

and Mick, 1999; Oliver, 1999; Anderson et al., 1994; Buttle,

1996; Rustet al., 1995; Szymanski and Henard, 2001; Oliver,

1999). Indeed, the most commonly applied conceptua

models of loyalty begin from the well-established notion that

customers who have satisfying experiences with products wil





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buy those products or will intend to buy them again (Jacoby

and Kyner, 1973; Szymanski and Henard, 2001; Jacoby and

Chestnut, 1973, 1978; Ford, 1980, 1998; Iacobucci and

Zerrillo, 1997).

Finally, we hypothesize that, as the customer loyalty

enhances, customer profitability increases (Reichheld and

Sasser, 1990; Kohli and Jaworski, 1990; Narver and Slater,

1990). Improvements in customer loyalty and retention by

even a few percentage points have in some cases increased

profits 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 be

consequences of customer satisfaction and predictors of

profitability, as they have been suggested by the literature

(Costabile, 2001; Garbarino and Johnson, 1999; Anderson

et al., 1994; Peppers and Rogers, 1997; Reichheld, 1996).

Variables are trust and commitment that influence reciprocity

and co-operation between the firm and its customers (Stern

and El Ansary, 1992; Bucklin and Sengupta, 1993; Bitner,1995; Blois, 1999). We have added to the previous hypotheses

the analysis of trust and commitment as determinants that

develop as customers gain experience and adopt relational

orientations, and their connection with the customer

propensity to repurchase and to consolidate of the

relationship, 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 an

antecedent 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 are

positively and significantly related to purchase

behaviour.

Research method

In order to test our hypotheses, we have conducted an

empirical study in the agri-food sector. The point of departure

for the case study was to match customer satisfaction andcustomer loyalty attitude data (at the customer level) with

purchase behaviour and profitability data (also at the

customer level). The first step has been to identify a firm

which had kept track of costs and revenues over time at a

customer level, and was willing to provide access to this data

We identified one firm. For confidentiality issues we cannot

name it.

The firm is based in Italy and sells food products (pasta

olive oil, wine, vegetables, bread, sauces, cakes, honey and

other typical foods) through direct marketing activities. Its

current range consists of about 50 different items. Most

relevant sales channels used are: telephone, internet

television, catalogue mail. The most important direc

marketing instrument is based on the telephone, whichdevelops alone 52 per cent of sales purchase. Television

instrument develops 27 per cent of sales, catalogue mail 18

per cent of sales, and internet just 3 per cent of sales. The

customer base is spread throughout the national territory

Products are delivered through a national courier directly to

the houses of its customers. The cost accounting system

allows for a detailed analysis of customer behaviour, as well

as analyses of profitability at several levels (customers

products, sales persons, etc). This technology has been

complemented with a telephone survey submitted to the

customers.

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





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Data collection

The data used in this study have been derived from two

sources: a telephone survey of the firms customers; and the

firms 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 on

balanced five-point Likert-type scales, ranging from stronglydisagree to strongly agree, where 1 strongly disagree and

5 strongly agree.The telephone survey was chosen because

of its relevant advantages such as monitoring of interviews for

improved quality control, higher response rates, less bias due

to non-response, shorter time requirements for completion,

reasonably low cost (Dutka, 1993; Leland and Bailey, 1995).

Customer satisfaction was measured as the weighted mean of

three items[1] defined during a previous the market survey,

based on global satisfaction, congruence between expected

and perceived value, value perception. Customer Loyalty

Attit ude was measured with nine items adapted from

Morgan and Hunt (1994), Moorman et al. (1992, p. 82),

Pearson (1996), Schijns and Schroder (1996), Anderson and

Narus (1984, p. 66), Selnes (1993), Crosby et al. (1990),

Anderson and Weitz (1989). Two main dimension of

customer loyalty attitude were investigated: customer trust

and customer commitment. Customer Trust was measured

with 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 Kahles (1988)

brand commitment scale. In particular, the following most

relevant dimensions of customer commitment were examined:

exclusive purchase intention, word-of-mouth[2], expectation

of continuity, price sensitivity.

Indicators and items capturing customer satisfaction and

the attitudinal dimensions of customer loyalty are described in

Table I.

Data on customer purchase behaviour and profitability werecollected from the firm database. Thus, the behavioural

dimension of customer loyalty was measured by ten indicators

as shown in Table II.

Data on purchase behaviour and customer profitability were

collected from the firm database. The firm provided us the

access to its records for the period December 2002-June

2004. The sample selection was based on the firms retained

customers (those customers who made at least one purchase

annually after the initial sale), who participated to thetelephone survey with a useful response rate (in total, 4,397

customers). Data from these records were then entered into

the same database as the survey responses. The client code

was the key to matching the purchase behaviour and

profitability records kept by Firm A on each customer with

the survey responses. Several attempts were made to examine

the quality of measurements. Internal consistency of the scales

used was ascertained by both calculating Cronbachs

coefficient alpha and conducting an item analysis (through

item-whole and inter-item correlation, as suggested by

Spector, 1992).

First, Cronbachs alpha results were largely higher than

Malhotras (1993, p. 308) 0.60 limit for acceptable reliability

in terms of internal consistency. The customer attitudina

loyalty measure, consisting of nine items, has an alpha value

of 0.910. The customer satisfaction measure, consisting of

three items, has an alpha value of 0.798. The customer

purchase behaviour measure, consisting of ten items, has an

alpha value of 0.92. Content validity for the customer loyalty

attitude, customer satisfaction, customer behaviours and

customer profitability measures was ascertained by examining

the scale composition throughout measure purification. The

resulting scales demonstrate good reliability, as evidenced by

Table III, in addition to being content valid.

Data analysis

The data gathered from the customer survey (data capturing

attitudinal loyalty and customer satisfaction) and the firms

data 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 Surveys items

Attitudinal Trust Trust attitude (1-5) I feel that I completely t rust this firm act ivities 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 buy

product from this firm

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

firm/branda

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

this 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 time

Price sensitivity (1-5) As a consumer to this brand, I feel that I am prepared to pay more for higher

quality products

Loyalty perception (1-5) I feel very l ittle loyalty to this firm/branda

Satisfaction Satisfaction Global satisfaction (1-5) I am completely satisfied with the products of firm A

Congruence between expected and perceived

value (1-5)

Performance expectations after purchasing firm As products exceed

expectations prior to the purchase

Value perception (1-5) Firm As products benefits are more important with respect to the costs and

sacrifices related to the product purchase

Note: a Reverse coded items





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then analyzed using the Statistical Package for the Social

Sciences (SPSS). Factor analysis, cluster analysis, ANOVA,

canonical correlation analysis, multiple regression, path

analysis, and t-tests were employed to test the research

hypotheses on the relationships among the variables.

A logistic regression analysis was used in order to identifythe stronger predictors of customer profitability and customer

loyalty, using all available measures, including both

behavioural and attitudinal variables. The regression

coefficients of each model equation related to the main

hypothesis were elaborated. A particular attention was given

to standardised coefficients calculation. This, because the

magnitude of a regression coefficient isnt necessary related to

how good a predictor the variable is, since the size of the

coefficient depends in large part on the units of the measure

for the variable. One way to make the coefficients easier to

compare is to compute what are known as standardised

coefficients (Beta coefficients).

ANOVA analysis summarized the results of variances

analysis. The sum of squares and mean square were analysed,

for two sources of variation, regression and residual. Theoutput for Regression displayed useful information about the

variation accounted for by each model. The output for

Residual displayed information about the variation that was

not accounted for by each model. R, R squared, adjusted R

squared, and the standard error were analysed. Among the

initial hypothesis, the model that accounted for most o

variation in the dependent variable, with a good large

regression sum of squares in comparison to the residual sum

of 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 the

introduction. That is to say, customers clearly do vary in

terms of the profitability they generate. For example, in this

case study, the top ten customers (2.4 per cent of the sample)

who ranked highest in terms of customer profitability

generated 20 per cent of the total customer profitability in

the sample. This is in line with most relevant theoretica

approaches and empirical evidences. Second, the analysis of

the most relevant behavioural loyalty variables (customer nof

orders and sales purchases value) reveals a positive and strong

correlation with customer profitability that has been

confirmed by the Beta coefficients computation. The

detailed results of these computations are summarised in

Table 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 in

inbound way (the client contact the firm for the order)

9. Loyalty programs 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 be

based 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 was

operationalised for each customer in the sample as sales revenue all product related expenses for allproducts sold to an individual customer during one particular period of time, sales, general and administrative

expenses 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 customer

consist 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; Kahnet al., 1986; Rao, 1969Carman, 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 0.42

Customer loyalty attitude 9 0.910 4,397 0.54

Customer purchase behaviour 10 0.92 4,397 3.9

Customer profitability 1 0.944 4,397 4.2

Notes:n number of items; a = Cronbachs alpha; N number of cases;Std dev. standard deviation





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As shown in Table IV, all the hypotheses of conceptual

framework were confirmed by the empirical results.

Discussion: the governance of customer loyaltyThe results showed support for all but one of the five

hypotheses, the exception being H2.

Purchase behaviour (behavioural dimension of customer

loyalty) was found to be positively and significantly associated

with customer profitability. This result was confirmed by t

statistics method results, that identified sales purchase value

and number of orders as some of the best predictors of

customer profitability.

Customer satisfaction was found to be positively associated

with customer profitability, but it was considered not statically

significant. The results confirm what was claimed about this

variable in the introduction: customer satisfaction (a mental

state) 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 of

the customer, which may follow from a certain level of

satisfaction, trust and commitment that affects customer

profitability.

Customer loyalty attitude was found to be positively and

significantly associated with customer profitability. Our model

then relates customer attitudinal loyalty measures (intent to

repurchase, willingness to recommend and other probable

market actions) to the expected profitability of each customer:

estimating the customer expected profitability, basing on his

attitudinal loyalty level, could be extremely useful for a

manager for setting-up a customized marketing strategy, such

as maintaining a price advantage and/or providing additiona

services to offer value. To this end, in the literature some

categorization of customers are suggested, useful for

identifying, 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 the

variance of the latter. However, multiple linear regression and

ANOVA analysis have shown that the model fails to explain a

lot of the variation in the dependent variable, and it needs for

additional factors that help account for a higher proportion of

the variation in the dependent variable. This is in line with

many theoretical approaches that highlighted how apparent

high levels of satisfaction may not result in a behaviour

characterised by high loyalty due to the many intervening

variables of customer loyalty development process (Jones and

Sasser, 1995; Oliver, 1999).

Satisfaction, trust and commitment were found to be

positively and significantly associated with purchase

behaviour. Three variables were entered the model, but two

of them resulted most relevant according with t statistic

method: customer trust and customer commitment. Figure 3

shows the links between purchase behaviour and the main

customer loyalty attitude enablers.

Customer trust and customer commitment resulted the

most important variables positively and significatively related

to purchase behaviour. In particular, customer commitment,

with the large tstatistics value, resulted to be the main driver

for customer purchase behaviour.

Table IV Results of the computations

Unstandardized

coefficients Standardized coefficients

B Std error Beta t Sig.

H1

Dependent variable: profitability

(Constant) 0.015 0.007 2.164 0.031

Customer purchase behaviour (REGR factor score 1 for analysis 1) 0.736 0.015 0.964 48.329 0.000

H2


(Constant) 0.431 0.010 45.308 0.000

Customer satisfaction 0.446 0.007 0.684 62.010 0.000

H3


(Constant) 0.018 0.021 0.875 0.381

Customer loyalty attitude (REGR factor score 1 for analysis 2) 0.325 0.035 0.822 10.022 0.000

H4

Dependent variable: loyalty attitude

(Constant) 0.015 0.002 6.138 0.021


H5

Dependent variable: purchase behaviour

(Constant) 2.386 0.500 212.430 0.000

Customer trust 0.230 0.060 0.760 12.208 0.000

Customer commitment 1.254 0.023 0.823 32.342 0.000






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Our study has identified several significant associations

between variables in the customer satisfaction-customer

loyalty attitude-purchase behaviour (behavioural loyalty)-

customer profitability chain. The associations between the

two latter types of variables should not be surprising, since it

is the actual acts by customers, not their attitudes that affect

the firms performance (cf. Storbacka et al., 1994). However,the results of our analysis show that customer loyalty variables

are related to what customers do in terms of purchase

behaviour: these relationships are commonly missing in many

parts of the marketing literature. Segmentation literature, and

particularly the literature on segmentation of business

markets, is one area in which these results are relevant.

Many segmentation variables have been described as

candidates for the segmentation of business markets, but

they are generally related to other characteristics of the buyer

than customer loyalty (cf. Shapiro and Bonoma, 1984;

Webster, 1984). 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/orpsychographic variables, should take into account also

loyalty measurement models.

Literature review and empirical results have also shown cost

savings associated with a loyalty building strategy in at least

six 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 to

measure and manage customer loyalty effectively, by using

both leading and lagging indicators:. Attitudinal measures, such as customer commitment

(intent to repurchase, willingness to recommend and

other probable market actions) provide the basis for

developing leading indicators of customer loyalty.. Behavioural measures, such as repeat purchasing, volume

or frequency of purchasing, returns, debt, complaints and

interactions, customer retention and longevity, furnish key

lagging indicators of customer loyalty.

As suggested by Kaplan and Norton (1992), without effective

leading indicators, it may be difficult to establish how

outcomes are achieved. Moreover, an organization lacking

leading indicators of key performance outcomes or results has

no 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 is

too late. The link between the attitudinal and behavioura

indicators pointed out in this paper allow to use attitudinal

measures for the purpose of estimating future results, as wel

as developing models that enable an organization to examine

alternative what-if scenarios.

Conclusions

In this paper we have explored links between variables

concerning the customer satisfaction the customer

attitudinal loyalty the customer behavioural loyalty the

customer profitability chain.We have included both attitudinal (such as intent to

repurchase, willingness to recommend and other probable

market actions have been included in order to provide the

basis for developing leading indicators of customer loyalty)

and behavioural measures (such as repeat purchasing, volume

or frequency of purchasing, returns, debt, complaints and

interactions, customer retention and longevity, have been

included as lagging indicators of customer loyalty).

Our model also has verified some relations existing between

attitudinal measures and behavioural measures, in order to

use attitudinal measures for estimating the customer expected

profitability; this estimation can be used for setting-up a

customized marketing strategy, such as maintaining a price

advantage 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 that

of agri-food. While useful in controlling for potentia

extraneous influences unrelated to the study, the limitation

involved in studying a single industry constrains the possibility

to generalize these findings. Future research should seek to

replicate the study into different firms and business sectors in

order to assess whether the linkages identified here still exist

in different industrial and consumer populations. Another

limitation is related to the time periods used in the study. It is

not clear to what extent the time periods have provided a

Figure 3Links between customer loyalty attitude enablers and purchase behaviour





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proper context for an analysis of the relationships between

attitudinal variables and behavioural variables. However, it

does seem clear that attitudinal variables such as customer

satisfaction do not remain constant over time (cf. Peterson

and Wilson, 1992). Future research should seek to replicate

the study into different period of time, more than one. It

means, among other things, that the timing of the survey

becomes 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 to

which one particular customer is profitable (cf. Reichheld,

1996).

Notes

1 Items capturing customer satisfaction have been adapted

from Pearson (1996), Oliver (1993), Holbrook (1999),

Costabile (2001), Westbrook and Oliver (1991).

2 Word-of-mouth can be defined as oral, person-to-person

communication between a receiver and a communicator

(Arndt, 1967, p. 189).

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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: [email protected]

Paola 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.





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