customer value, overall satisfaction, end-user loyalty, and market ... · customer value, overall...

Industrial Marketing Management 33 (2004) 675–687

Customer value, overall satisfaction, end-user loyalty, and market

performance in detail intensive industries

Joseph M. Spiteria, Paul A. Dionb,*

a6255 RFD, Long Grove, IL 60047, USAbSigmund Weis School of Business, Susquehanna University, 514 University Avenue, Selinsgrove, PA 17870, USA

Received 21 October 2003; received in revised form 15 February 2004; accepted 28 March 2004

Available online 14 July 2004

Abstract

The objective was to test a customer value variable, as operationalized by a modification of Ulaga and Eggert’s scale, as a direct

explanatory concept in predicting satisfaction, loyalty, and market performance in a hybrid veterinary pharmaceuticals market. The market

was considered to be a hybrid because physicians purchase on behalf of their clients. The scale proved to be reliable and valid in a detail

intensive market using 220 veterinary physicians as respondents. To achieve an acceptable structural equation modeling fit, the customer

value variable had to be dropped. The final model indicated a direct influence by product, strategic, and personal benefits as well as perceived

sacrifices on the dependent variables. Management implications of the study are described.

D 2004 Published by Elsevier Inc.

Keywords: Customer value; Satisfaction; Ulaga–Eggert scale; Veterinary pharmaceuticals

1. Introduction

Marketing academics have identified customer value as

one of the top research agendas. The Marketing Science

Institute has consistently included customer value in its list

of research priorities. The Institute for the Study of Business

Markets at the Pennsylvania State University and the Center

for Business and Industrial Marketing at Georgia State

University have also integrated research on customer value

and view it as a key research program. Customer value is on

the mission statements of many large corporations (Exxon)

and has become a sought after source of competitive advan-

tage. Now that the first scale for the operationalization of this

concept has been published (Ulaga & Eggert, 2002), research

into customer value can become a more empirical area of

inquiry. The needed theoretical areas of research for custom-

er value include ‘‘. . .major antecedents, mediating variables,

and consequences’’ (Ulaga & Eggert, 2002, p.15) and ‘‘to

investigate relationship customer-value concepts closely

related to the construct such as commitment, satisfaction,

0019-8501/$ – see front matter D 2004 Published by Elsevier Inc.

doi:10.1016/j.indmarman.2004.03.005

* Corresponding author. Tel.: +1-570-372-4034.

E-mail address: [email protected] (P.A. Dion).

and trust.’’ Methodologically, there is also a need to inves-

tigate how robust this new scale is outside its original setting

of French industrial purchasing managers. The purpose of

this study was to empirically investigate the model shown

below in Fig. 1. This model was synthesized from several

available research efforts.

Additionally, as the new consumer value scale of Ulaga

and Eggert (2002) has neither been revalidated nor tested for

its predictive effectiveness in a new marketing setting, this

newly developed scale was validated and then empirically

tested in a detail intensive industry (DII) setting. In sum-

mary, the research objectives were to:

1. empirically investigate the effect of perceived product

benefits, perceived strategic benefits, perceived personal

benefits, perceived sacrifices, and perceived relationship

benefits on the construct of customer value;

2. empirically link the measurement of customer value to

outcome measures, such as overall satisfaction, end-user

loyalty, and market performance;

3. empirically investigate the role of overall satisfaction in

the model;

4. empirically investigate the effects of relationship benefits

and sacrifices on market performance;

Fig. 1. Customer values’ main model.

J.M. Spiteri, P.A. Dion / Industrial Marketing Management 33 (2004) 675–687676

5. finally, empirically test and validate Ulaga and Eggert’s

(2002) customer value scale in a DII market setting.

The research context employed here is veterinary pharma-

ceuticals. The industry that comprises ethical pharmaceut-

icals for both humans and animals is often called ‘‘detail

intensive industries’’ because of its reliance on detailers

(another name for ethical pharmaceuticals salespersons). DII

offers one of the most salient examples of all the elements of

business-to-business exchanges with product marketing sit-

uations that involve intense relationship-building activities

by manufacturers’ representatives with the medical profes-

sional. This and other interesting aspects of DII have long

attracted marketing academics (Krishnamurthi & Zoltners,

1994).

The theoretical underpinnings for this research into cus-

tomer value in DII begin with the work of Carter (1997), who

researched the importance of relationship marketing activi-

ties in the human pharmaceutical market. Carter asserted that

given the importance of detailing (presenting information on

J.M. Spiteri, P.A. Dion / Industrial Marketing Management 33 (2004) 675–687 677

drugs) ‘‘if there is no personal contact, then the chances that

the customer will purchase the product is small.’’ It is

through the personal selling activity that a long-term rela-

tionship between the manufacturer and their representative is

maintained with the customer—the medical professional.

Therefore, the spectrum of personal selling activities is

viewed as central to the relationship marketing efforts of

the firm and one of the critical sets of antecedents to

customer value. Recently, drug manufacturers have invested

in direct-to-consumer advertising (DTC), which is changing

the dynamics and the relative importance of detailing and

other relationship-building activities to DTC. DII have also

become examples of business to consumer marketing. In-

deed, DII is now a good example of a hybrid of business-to-

business and business-to-consumer.

The research was conducted in three phases. Using a

Delphi methodology on 22 respondents, Phase I tested the

language or wording adaptation of the perceived strategic

benefits indicators variable in the veterinary market. Phase II

used a sample of 100 multi-informants to test the importance

of the items of benefits and sacrifices found in the scale of

customer value. Based on the findings of the two earlier

phases, Phase III consisted of fielding the final version of the

full questionnaire to a random sample of 623 respondents.

2. Literature and theory background

The literature review begins with a conceptual presenta-

tion of the antecedents to the customer value construct,

Table 1

Antecedents of customer value

Antecedents Findings

Market orientation Directs firm to focus on gathering

dissemination of customer value in

Learning Positively linked to implementation

customer value information

Competence/expertise Linked to customer value

Communication Linked to customer value

Alignment of sales compensation to value Linked to customer value

Equity/fairness in exchange Linked to success of buyer/seller

relationships

Forbearing opportunistic behavior Linked to success of buyer/seller

relationships

Ethical acts Linked to success of buyer/seller

relationships

Shared values Linked to success of buyer/seller

relationships

Promotional investments Add customer value or perceived v

Relational investments Add customer value or perceived v

Innovations Add customer value or perceived v

Total quality management Add customer value or perceived v

Seeking sustainable competitive

advantage

Lead to acceptance of customer va

as competitive advantage

Process efficiencies Lead to acceptance of customer va


Cost-cutting initiatives Lead to acceptance of customer va


followed by the processes that lead to the construct of

customer value. These processes include the assessment of

product quality and price and how they lead to the concept

of customer value followed by a look at the construction of

a recently released scale. After the antecedents and process

are presented, the literature is reviewed for possible out-

comes to customer value. They are overall buyer satisfac-

tion, end-user loyalty, and market performance. Finally,

there is an examination of marketing issues in DII.

2.1. Antecedents of customer value

There are many legitimate antecedents to the compre-

hensive and complex concept of customer value. There are

16 such influences documented in the literature. A detailed

discussion of each would be too lengthy to include in this

article but Table 1 gives a summary of the influences and

references findings.

2.2. Processes of customer value

Quality models comprise a large research stream in

marketing thought. However, recently, quality models have

been criticized for not explicitly including the effect of

perceived price or cost on the customers’ judgment of quality

(Iacobucci, Grayson, & Ostrom, 1994) and for not consi-

dering sustainable competitive advantage (Butz&Goodstein,

1996). Since the continued search for competitive advantage

has been directed toward delivering superior customer value

(Band, 1991; Day, 1990; Gale, 1994; Naumann, 1995),

Author(s)

and

formation

Slater & Narver, 2000; Woodruff & Gardial, 1996

of Day, 1994a, 1994b; Kohli & Jaworski, 1990;

Slater & Narver, 1995

Doney & Cannon, 1997; Smith & Barclay, 1997

Anderson & Weitz, 1989; Gronroos, 1990

Anderson et al., 1994

Gundlach & Murphy, 1993; Tax, Brown,

& Chandrashekaran, 1998

Morgan & Hunt, 1994

Boedecker, Morgan, & Stoltman, 1991;

Lagace et al., 1991

Morgan & Hunt, 1994

alue Woodruff & Gardial, 1996

alue Berry, 1995; De Wulf et al., 2001; Goff et al., 1997

alue Dickson, 1992; Ghemawat, 1986; Jacobson, 1992

alue Buzzell & Wiersema, 1981; Capon, Farely, & Hoenig, 1990

lue Christopher et al., 1991; Porter, 1985;

Treacy & Wiersema, 1995

lue McKenna, 1991; Porter, 1985

lue Cannon & Homburg, 2001

Table 2

Definitions for customer value

Benefits Costs or sacrifices Researcher(s)

Maximize rewards Minimize costs Bagozzi, 1974

Utility of what is received What is given Zeithaml, 1988,

p. 14

Quality and benefits Relative to sacrifices Monroe, 1991,

p. 46

Five categories of value:

functional, social,

emotional, epistemic,

and conditional value

Sheth, Newman,

& Gross, 1991

Worth of set of economic,

technical, service, and

social benefits

Exchanged for price

of product

Anderson, Jain,

& Chintagunta,

1993, p. 5

Product value, value-in-use,

possession value, and

overall value

Burns, 1993

Perceived quality Relative prices Gale, 1994

Emotional bond between

customer and producer

Butz & Goodstein,

1996


frameworks and tools have now been developed for manag-

ing toward customer-focused competitive advantage (Clem-

ons & Woodruff, 1992; Day, 1990; Day & Wensley, 1988;

Slater & Narver, 1995). In traditional quality models, product

quality precedes customer satisfaction (Parasuraman, Zei-

thaml, & Berry, 1988). Iacobucci et al. (1994) claim that the

traditional quality model needs a simple modification to

include financial factors so that the customer’s evaluation

can take into consideration ‘‘what they paid for what they

got.’’

Product quality has also not been sufficient as a sustain-

able competitive advantage (Butz & Goodstein, 1996).

Organizations have earnestly pursued internal changes in

the process of quality control, such as downsizing, restruc-

turing, and reengineering. However, although the way

organizations work may change, these steps have not always

had the desired impact on the bottom line (Hall, Rosenthal,

& Wade, 1993). Consequently, the search for competitive

advantage goes on. One direction has been the call for

organizations to direct the pursuit of competitive advantage

toward delivering superior customer value (Band, 1991;

Day, 1990; Gale, 1994; Naumann, 1995).

Ulaga and Chacour (2001) conceptualized customer

value as being derived from the concept of product quality,

as depicted in Fig. 2.

Subsequent to this work, Ulaga and Eggert (2002) went

on to develop a scale for measuring customer value, which

is discussed in the next section.

2.3. The concept of customer value

The term value is used in many different contexts in

marketing. One perspective in organizational strategy main-

tains that creating and delivering superior customer value to

high-value customers will increase the value of an organi-

zation (Slywotzky, 1996). High-value customers have their

monetary worth as individual customers to the organization

quantified, whereas value of an organization quantifies the

worth to its owners (stakeholders). On the other hand,

customer value takes the perspective of an organization’s

Fig. 2. Components of customer

customers, ‘‘considering what they want and believe that

they can get from buying and using a seller’s product’’

(Woodruff, 1997). This research deals with this latter

concept.

There are many diverse meanings and perspectives for

the concept of customer value. These are summarized in

Table 2.

The definitions have similarities and differences. Con-

sensus is seen in the linking of customer value to some

product and/or service. Further, at the core of customer

value is the perspective of the customer and not of the seller.

Finally, the perception of customer value involves a tradeoff

between what the customer receives (e.g., quality, benefits,

worth, utilities) and what they give up (prices, sacrifices) to

acquire the product. Divergence is seen in the reliance on

other terms—utility, worth, benefits, and quality—to con-

struct the definitions, but these terms are not all well

developed or defined. Hence, it becomes difficult to com-

pare concepts: Is customer value as quality the same as

customer value as utility?

perceived product value.

Fig. 3. Customer value indicators and links to benefit.

arketing Management 33 (2004) 675–687 679

2.4. Customer value scale

Recently, customer value has been defined and a psy-

chometrically sound scale for measuring the concept in

business-to-business markets has been developed (Ulaga

& Eggert, 2002). Four customer-value components emerged

from their study: product-related benefits, strategic benefits,

personal benefits, and relationship sacrifices. These were

aggregated into the higher-order construct of customer

value. As has been stressed earlier, the literature contains

a variety of definitions of customer-perceived value. In these

definitions, Eggert and Ulaga (2002) identified three com-

mon elements:

1. Customer-perceived value is a trade-off between bene-

fits and sacrifices perceived by the customer in a sup-

plier’s offering (Monroe, 1990, p. 46; Zeithaml, 1988,

p. 14).

2. Value perceptions are subjective (Kortege & Okonkwo,

1993).

3. Competition is important, because value is relative to

competition.

Ulaga and Eggert (2002) define customer value in business

markets as the trade-off between the multiple benefits and

sacrifices of a supplier’s offering as perceived by key

decision-makers in the customer’s organization and taking

into consideration the available alternative suppliers’ offer-

ings in a specific use situation. The perceived benefits are

some combination of physical attributes, service attributes,

and technical support available relative to the particular

use of the product as well as the purchase price and other

indicators of perceived quality (Ravald & Gronroos, 1996).

Additionally, a complexity is that an individual may

evaluate the same product differently on different occa-

sions.

Ulaga and Eggert’s (2002) scale covers the indicators of

the variables of perceived ‘‘relationship benefits’’ and ‘‘sac-

rifices.’’ These indicators (in parentheses) and their con-

structs are shown in Fig. 3.

2.5. Consequence of customer value

2.5.1. Overall satisfaction

The concept of customer value is related to, but different

from, both concepts of satisfaction (Woodruff & Gardial,

1996). The literature identifies two types of satisfactions:

transactional and overall satisfaction (or cumulative satis-

faction). Transactional satisfaction is defined as the post-

choice evaluative judgment of a specific purchase occasion

(Hunt, 1977; Oliver, 1980, 1993), whereas cumulative

customer satisfaction is an overall evaluation based on the

total experience (Fornell, 1992; Johnson & Fornell, 1991).

Because relationship marketing is long term, the more

appropriate variable to measure is ‘‘overall satisfaction’’

(Ravald & Gronroos, 1996).

J.M. Spiteri, P.A. Dion / Industrial M

The concept of customer value has a strong relationship

to customer satisfaction. Both concepts describe evaluation

and judgments of products in use situations. In fact, per-

ceived value may lead directly to the formation of overall

satisfaction feelings (Churchill & Surprenant, 1982). Alter-

natively, they may be compared with one or more other

standards (Clemons & Woodruff, 1992; Woodruff, Schu-

mann, Clemons, Burns, & Gardial, 1990).

2.5.2. End-user loyalty

The concepts of quality, brand and/or company equity,

customer satisfaction, and customer value are interrelated.

Customer satisfaction is one of the most important criteria

for customer loyalty (Heskett, Sasser, & Schlesinger,

1997). Howard and Sheth (1969). Several studies discuss

and/or observe a strong link between customer satisfaction

and loyalty (Anderson & Sullivan, 1993; Bearden & Teal,

1983; Boulding, Staelin, Kaira, & Zeithaml, 1993; For-

nell, 1992; Oliver & Swan, 1989). Reichheld and Sasser

(1990) discuss why increasing customer loyalty should

lead to higher profitability. However, recent studies have

demonstrated mixed results in analyzing the relationship

between satisfaction and loyalty. These studies suggest

that satisfied customers may not be sufficient to create

loyal customers (e.g., Cronin & Taylor, 1992; Fornell,

1992).

2.5.3. Market performance

An empirical study conducted in Europe’s pharmaceutical

market (Scharitzer & Kollarits, 2000) showed physicians’

subjective customer value assessments of certain pharma-

Table 3

J.M. Spiteri, P.A. Dion / Industrial Marketi680

ceutical companies lead to the market success of a product.

The construct of ‘‘customer loyalty’’ is at the interface

between subjectively observed and objectively measured

dimensions of enterprise performance. They also found a

link between perceived service quality and economic suc-

cess. In that study, the pharmaceutical companies used

relationship-marketing activities, such as personal selling,

for building long-term relationships. Rust and Zahorik

(1993) empirically demonstrated the relationship between

customer satisfaction and profitability for a health care

organization and also found that although firms see an initial

strong relationship between satisfaction scores and perfor-

mance, this relationship declines over time. Ravald and

Gonroos (1996) found that ‘‘loyalty’’ was linked to mutually

profitable relationships. In fact some studies have indicated

that satisfied clients can also be just as disloyal (Lowenstein,

1997).

Several additional industry-related researches include

Scharitzer and Kollarits (2000), who used a satisfaction

model to support the link between perceived service

quality and economic success. In that study, the pharma-

ceutical companies used relationship-marketing activities,

such as personal selling, for building long-term relation-

ships. Rust and Zahorik (1993) empirically demonstrated

the relationship between customer satisfaction and profit-

ability for a health care organization, and also found that

although firms see an initial strong relationship between

satisfaction scores and performance, this relationship

declines over time.
H1–H3: There are positive relationships between perceived customer
value and overall buyers’ satisfaction (H1), end-user brand and

company loyalty (H2), and market performance (H3).

H4–H6: There are positive relationships between perceived

product benefits and overall buyers’ satisfaction (H4), end-user brand

or company loyalty (H5) and market performance (H6).

H7–H9: There are positive relationships between perceived

personal benefits and overall buyers’ satisfaction (H7), end-user brand

or company loyalty (H8), and market performance (H9).

H10–H12: There are positive relationships between perceived strategic

benefits overall buyers’ satisfaction (H10), end-user brand or company

loyalty (H11), and market performance (H12).

H13–H15: There are negative relationships between perceived relationship

sacrifices and overall buyers’ satisfaction (H13), end-user brand or

company loyalty (H15), and market performance (H16).

H16–H17: There are positive relationships between overall buyers’

satisfaction and end-user or company loyalty (H16) and a positive

relationship between end-user loyalty and market performance (H17).

H18: There is a positive relationship between overall buyer satisfaction and

market performance (H18).

H19: There is a linear relationship between customer value and overall

buyer’s satisfaction and end-user loyalty (H19).

H20: There is a linear relationship among perceived product, personal,

strategic benefits and perceived sacrifices, overall buyer’s satisfaction,

and end-user loyalty (H20).

H21: There is a linear relationship customer value and overall buyer’s

satisfaction, end-user loyalty, and market performance (H21).

H22: There is a linear relationship among perceived product, personal,

strategic benefits and perceived sacrifices, overall buyer’s satisfaction,

end-user loyalty, and market performance (H22).

H23a: That is, the main model in Fig. 1 is a theoretically better fit than any

other alternate models and is, therefore, more parsimonious (H23).

3. Study method

The study was conducted in three phases, with data

drawn from a randomly selected panel of 1200 veterinar-

ians who participated in a monthly buyer panel and

responded by mail. Telephone reminders were used to

increase the response rate.

1. In Phase I, 22 respondents checked the wording

changes to the original instrument of Ulaga and Eggert

to adapt it to the present research context. This panel

consisted of five academicians, seven industry con-

sultants, four sales professionals, and six market

professionals.

2. Phase II of the study tested the new wording and new

items on a pilot sample of 100 that excluded the 623 used

for the full questionnaire. The purpose was to investigate

if the originally worded indicators in the customer value

scale were important to the purchasing decision-makers

in DII.

3. Phase III implemented a complete rollout to 623

qualified panelists (those who have been panelists for

at least 3 years) whose purchase histories and profiles are

known and have established relationships with the

various suppliers.

3.1. Sample selection

The 623 sample respondents were chosen from 427

clinics in a monthly panel of 1200 American Veterinary

Medical Association (AVMA) members. Potential clinics

were randomly chosen and invited to the panel, if they

refused; the clinic was replaced and was available for

another draw. To insure representativeness responders were

statistically compared with nonresponders and the AVMA

universal demographics universe.

3.2. Statement of research hypotheses

The hypotheses were directed at testing the study’s

theoretical framework outlined in Fig. 1. They are summa-

rized in Table 3.

3.3. Measurement of research variables

The five-point low (1) and high (5) response scales for

each construct were evaluated using Cronbach’s alpha and

exploratory and confirmatory factor analysis. After minor

modifications for double-loading and nonloading items,

measures were only included after they demonstrate accept-

able levels validity and reliability. Table 4 presents both the

ng Management 33 (2004) 675–687

Table 4

Cronbach’s alpha values of present and previous studies

Perceived independent,

mediator, and dependent

variables

Items Sample item Referenced/computed

Cronbach’s alpha

References

Product-related benefits 4 Please rate product quality. .82/.79 Ulaga & Eggert, 2001

Strategic-related benefits 4 Please rate product brand on

sharing their knowledge or

expertise with you.

.82/.93 Ulaga & Eggert, 2001

Personal benefits 4 Please rate product brand on

how pleasant the working

relationship is with you.

.84/.94 Ulaga & Eggert, 2001

Relationship sacrifices 3 Please rate the product brand

on how much time they cost you.

.90/.65 Ulaga & Eggert, 2001

Buyer’s customer loyalty 3 Product, brand, or company loyalty .57/.78 Butaney & Wortzel, 1988

Overall satisfaction 3 Please rate how satisfied you or

your clinic are with using the

product brand.

.87– .94/.82 Crosby & Stephens, 1987


referenced and computed Cronbach’s alpha values for the

scales.

The relationship benefits variable was computed using

factor weights from the product, strategic, and personal

benefits. The perceived customer value variable was com-

puted as a ratio of relationship benefits to relationship

sacrifices. Market performance was computed as the 3-year

average of the monthly doses dispensed.

Table 5

Summary of tests of hypotheses

Hypotheses Independent variable(s) Dependent va

H1 Customer value Overall satisf

H2 Customer value End-user loy

H3 Customer value Market perfo

H4 Product benefits Overall satisf

H5 Product benefits End-user loy

H6 Product benefits Market perfo

H7 Personal benefits Overall satisf

H8 Personal benefits End-user loy

H9 Personal benefits Market perfo

H10 Strategic benefits Overall satisf

H11 Strategic benefits End-user loy

H12 Strategic benefits Market perfo

H13 Relationship sacrifices Overall satisf

H14 Relationship sacrifices End-user loy

H15 Relationship sacrifices Market perfo

H16 Overall satisfaction End-user loy

H17 End-user loyalty Market perfo

H18 Overall satisfaction Market perfo

H19 Customer value and overall satisfaction End-user loy

H20 Perceived product, personal, strategic,

benefits, perceived sacrifices, and overall

satisfaction

End-user loy

H21 Customer value, overall satisfaction, and

end-user loyalty

Market perfo

H22 Perceived product, personal, strategic,

benefits, perceived sacrifices, overall

satisfaction, and end-user loyalty

Market perfo

H23a Main model

H23b Alternate model

4. Study findings

4.1. Sample characteristics

A total of 220 usable responses were received for a

35.5% response rate. The vets/clinic variable shows that the

sample is almost identical to the universe (2.12 vs. 2.13),

but there is a difference when compared with the non-

riable Pearson’s correlation Significance level ( P)

action .22 .004

alty .23 .000

rmance � .04 .690

action .62 .000

alty .50 .000

rmance .19 .016

action .42 .000

alty .37 .000

rmance � .056 .469

action .50 .000

alty .45 .000

rmance .01 .854

action .09 .242

alty � .04 .591

rmance .03 .723

alty .52 .000

rmance .22 .005

rmance � .04 .593

alty R2 = 29% F = 33.5, P= .000

alty R2 = 36.1% F = 18.2, P= .000

rmance R2 = 8.5% F = 5.05, P= .002

rmance R2 = 13.5% F = 4.16, P= .001

Model did not load on SEM.

GFI=.992 (a very good fit), v2 = 4.49 (6 df), P=.661


responders. Larger clinics seemed to respond more, most

probably because they are better staffed and more likely

have office staff to help with the clinics purchase function;

they are thus better targets of the multi-informant method-

ology. All the other variables—practice types, geographic

spread, and dispensed/vet—all show good representation of

the sample with the universe and nonresponders.

4.2. Phase II findings on importance of scale indicators

The 100 multi-informant Phase II research tested the

importance of all the scales indicators to confirm that

these benefits and sacrifices applied to DII setting. The

results showed that they were all important and meaning-

ful, of course, to varying degrees, and that an open-ended

request for more or different benefits and sacrifices

provided no additional items. Weighting analysis showed

that the highest weights were given to product benefits

(34%), followed by relationship sacrifices or costs (27%),

strategic benefits (21%), and finally personal benefits

(18%). Ranking of the individual items ranged from

product reliability (item 1), the new/specific item product

safety (item 2), product quality (item 3), and all the way

to personal value (item 14) and personal recognition (item

15). It is noteworthy that the relationship building benefits

Fig. 4. Customer values

and indicators are ranked lowest. The mean ratings ranged

from 4.97 for the highest individual items to the lowest

2.98 out of a scale of 1–5 for the lowest to 5 at the

highest, implying that even the lowest was only slightly

lower than the average in the scale. Confirmatory factor

analysis validated the Phase II scale and just over 68% of

the variance in the indicators was explained by four

factors, which were theoretically the three benefits and

one sacrifices proposed in Ulaga and Eggert’s (2002)

scale.

4.3. Measurement properties

The computed Cronbach’s scores are reported in Table 2

and all exceed .6 (Hair et al., 1995, p. 88). A confirmatory

factor analysis of the indicator variables loaded onto factors

representing relationship benefits, sacrifices, satisfaction,

and loyalty.

4.4. Tests of research hypotheses

In Table 5, the results of tests of Hypotheses 1–22 using

correlation and regression are presented. Hypothesis 23 was

tested using a structural equation modeling approach and is

presented below.

’ alternate model.


Hypothesis 23: The main model presented in the intro-

duction was tested using a SEM (AMOS 4.01) approach.

While the main model did not load at all, the results for the

alternate model (see Fig. 4) were acceptable. However, it

was necessary to drop the customer value variable to

achieve an acceptable GFI. Because the customer value

was a ratio of relationship benefits to sacrifices the relation-

ship benefits variable was dropped because it was derived

from product benefits, strategic benefits, and personal ben-

efits using factor weights and would introduce a latent

variable into the model. The alternate model gave the

following: GFI=.992, adjusted GFI=.964, v2 = 4.49 (6 df ),

and P=.661. These results imply that this is an acceptably

fitting model. Thus, the alternate model is a more acceptable

and a better goodness-of-fitting model than the main model.

While better fitting models were obtainable, each required

the omission of model variables for only marginal increases

in better fit. However, these more parsimonious models

were not as well supported by the theory that argued for the

inclusion of the variables, such as market performance and

relationship costs (which provided the best fitting mode

with the omission of these variables: GFI=.999). The results

for the specific relationships in the model are presented

below. They provide support for the alternate model in that

all the relationships were found to be statistically significant.

Relationship Estimate S.E. Critical

value

Significant

Personalp Product 0.236 0.073 3.232 yes

Strategicp Personal 0.770 0.045 17.127 extremely

Strategicp Product 0.183 0.044 4.156 yes

Satisfactionp Product 0.803 0.095 8.434 very

Loyalp Satisfaction 0.242 0.085 2.833 just

Loyalp Strategic 0.366 0.114 3.211 yes

Loyalp Product 0.403 0.124 3.242 yes

Market performance

pLoyal

772.809 241.10 3.205 yes

Market performance

p Satisfaction

� 904.159 273.94 � 3.301 yes

Market performance

p Product

1169.40 404.34 2.892 just

5. Conclusions and managerial implications

This study empirically tested and supported a large

part of a postulated framework of antecedents, processes,

and outcomes of customer value. However, the SEM did

not support the use of a higher order construct of

customer value, as proposed in the earlier theory first

by Monroe (1991) and then by Ulaga and Eggert

(2002).

Most of the influence on the product selection process

is through the direct effects of the customer value

components rather than through the indirect effect of

the higher order construct. Acting directly, these individ-

ual customer value benefits and sacrifices also have more

impact on the overall satisfaction and end-user loyalty

outcome measures than on market performance, most

likely because of the time dependent promotional lagged

effects. Moreover, the scale’s component influence on

market performance also appears to be direct and not

through the roles of mediating variables like the business

buyer’s overall satisfaction and end-user loyalty. There-

fore, the alternate model had higher goodness-of-fit than

the main model. Nevertheless, the research did confirm

the general structure proposed—antecedents, dimensions

of or higher order customer value construct, linked to the

three outcome measures of overall satisfaction to end-user

loyalty to market performance.

The research also confirmed both the validity and

reliability of all the measures used, including the new

scale of Ulaga and Eggert (2002). The language of the

items in the instrument was also sufficiently generic that

they were used in a new DII setting with only minimal

use of questionnaire instructions and directions. While

the literature-supported conceptual antecedents to custom-

er value were not all empirically researched, key ante-

cedents arising from sales-force activities and efforts

were found to be positively linked to both personal

and strategic benefits. Additionally, the results from the

100 multi-informant Phase II part of this research em-

pirically confirmed the importance of all of the scale’s

items.

The research also confirmed the importance of end-

user loyalty, particularly in this hybrid marketing situa-

tion—manufacturer selling to business buyer who, in turn,

sells to the consumer. This points to the influence of a

brand message in business-to-business (e.g., the promo-

tion of ‘‘Intel Inside’’). In these cases, the business buyer

must consider the influence of the ultimate consumer in

making their product selection decisions between viable

alternatives.

The link between end-user loyalty and market perfor-

mance was positive but weak. Most probably, this is due

to the many promotional lagged effects that are present

when looking at present time cross-sectional data obtained

from current ratings when compared with the longitudi-

nally impacted product usage or market performance.

While this was one of the limitations of the study, the

current results did set up a benchmark for future research

that may consider these lagged effects.

It is highly desirable for a marketing scale to be

sufficiently generic so that it is theoretically grounded

and generalizable. However, from a practitioner’s perspec-

tive, it is strategically desirable that the instrument used is

sufficiently specific so as to provide managerially action-

able insights. These two goals are often in conflict. In this

study, the results supported the general acceptance of the

generic language used in Ulaga and Eggert’s (2002)

customer value scale. Nevertheless, the practitioners re-

quired specific language particularly for the strategic

benefits components. For example, one strategic benefit


indicator was ‘‘Please rate Supplier 1 and Supplier 2 on

helping you or your clinic to develop and maintain your

strategic advantages.’’ Many of the respondents proffered

suggestions on language that made it clear what ‘‘strategic

advantages’’ meant for medical practitioners. This re-

search balanced these two needs (theoretically generic

vs. practitioner specific) by providing ‘‘explanations’’ or

‘‘instructions’’ of what this general wording specifically

means to the responder. For example, to a clinic’s owner,

strategic advantages ‘‘include attracting, maintaining, and

educating pet owners about animal health products and

veterinary professional.’’

Since the original responders of the customer value

scale (Ulaga & Eggert, 2002) were French industrial

buyers, it could not be assumed, without further testing,

that the items or indicators were important and hence

meaningful to the DII setting. Accordingly, the 100 multi-

informant Phase II research tested the importance of all

the scales indicators to confirm that these benefits and

sacrifices applied to DII setting.

The studies proposed antecedents have implications for

managing toward customer-focused competitive advantages

by assisting organizations to match internal quality man-

agement capabilities with an external strategic focus. This is

accomplished by gathering customer value-oriented infor-

mation necessary to make decisions that improve the cus-

tomer value delivery process. This leads to organizational

learning to align the internal organizations with what the

customers value. Management can, therefore, improve the

customer value rating by increasing the effectiveness of the

appropriate research confirmed antecedents. While a gener-

alizable instrument serves the purpose of establishing the

importance of customer value research in a particular

setting, a specific instrument is then needed for strategic

alignment and implementation.

Support for the structure of the alternate research model

implies that increasing the overall customer value rating by

increasing specific components will improve all three-out-

come measures. Managerially, the insight is that suppliers

would do better by concentrating on measuring the effec-

tiveness of improving the individual components rather than

indexing them into the higher order construct, such as

customer value. A possible explanation for the ineffective-

ness of the higher order construct is this: When reaching a

decision on optimal value, buyers are assumed to mentally

calculate a ratio of customer benefits to customer sacrifices

(this is termed the index method). As this is rather a

sophisticated calculation, it may not be realistic in every

industrial buying setting. But since the research on the actual

mental model or decision-making mechanism is not yet

available, it is speculation at this point.

The roles of overall satisfaction and end-user loyalty

follow from the established theory and are necessary for

product selection or preference decisions. This study rein-

forced the notion that end-user loyalty is a better predictor

of market performance than either overall satisfaction or

customer value. It also found that overall satisfaction is a

better predictor of end-user loyalty than customer value.

However, in this research, there is an important difference

in the foci of these variables that was not investigated in

previous research. The customer of the buyer (the pet

owner, in this case) influences the perceptions of the buyer

on the end-user loyalty ratings. However, the buyer makes

the customer value and overall satisfaction ratings deci-

sions. The theoretical implication of this is that industrial

purchase decisions must consider the responses of the

customers of the product. There are many buying busi-

ness-buying decisions that have brand loyalty implications.

For example, the ‘‘Intel Inside’’ branding message cited

before. Clearly, generic components in computers or auto-

parts would not have applicable branding messages, but

many products in DII have been increasingly promoted as

DTC brand messages. The medical professional manager

now has to contend with a marketing manager directly

influencing the consumer. This implies that the consumer

has become more powerful in brand selection. Interestingly,

this sets up potential conflict as to what the buyer may

consider to be ‘‘value’’ (discounted price or deal) but on a

product that the consumer does not prefer. Therefore, the

measurements of customer value in business-to-business

must now consider what the consumer also ‘‘values.’’

Ulaga and Eggert’s (2002) scale does not provide for the

influence of the consumer. However, in this research the

combined scale includes the ‘‘pull power’’ of the end-user,

leading to interesting insights. This has changed the dy-

namics of marketing in DII industries, where the old theory

that stressed the importance of the sales-force efforts, is

now supplemented with the increased importance of end-

user request for products spurred on by DTC adverting

messages.

End-user loyalty was found to have a more direct link to

market performance, and would probably be a stronger link

if lagged effects are taken into account. Overall satisfaction

explains more of the variance of end-user loyalty than

customer value. So the question this raises is: ‘‘Do we

really need the customer value construct?’’ Iacobucci et al.

(1994) were the first to observe that all customer satisfaction

research needs is the inclusion of price. Certainly, the

implication of this study is that traditional customer satis-

faction could accomplish the same end as the components of

customer value. However, the focus on what the customer

values would need to guide what product attributes or uses

are included in the scale.

In the DII hybrid marketing situation, this research on

the importance of the individual components demonstrated

that the product benefits are more important than personal

or strategic benefits—the relationship-marketing dimen-

sion, which loaded onto one variable. When they are

combined, they aggregate to 39%, which is higher than

the product benefits. The implication is that the compet-

itive advantage has shifted to the strategic benefits, which

is where the impact for DTC is seen. This supports the


notion that ‘‘despite the growing focus on customer

service in business-to-business marketing, when it comes

to perception of customer perceived value, product quality

has a greater impact on customer’s perceived value than

service value.’’

6. Limitations and recommendation for future research

The limitations of the study were the following:

1. Many of the antecedents have not been empirically

tested or confirmed and there is no consensus yet on

their specification or conceptualization. This study has

offered one possible set and researched several of them

to provide a plausible basis for the indicators. Future

research should empirically investigate more.

2. Mediator variables, such as trust, commitment, and

satisfaction, have not been fully modeled or empiri-

cally tested and so are also fruitful areas for future

research.

3. Within the model structure, the new customer value

scale has only been shown to apply to DII. Hence,

hypotheses testing and inferences are limited to DII

and may not be generalizable to other marketing

settings. Future research could also be directed at

proving the model and scale also apply in other market

settings.

4. No attempt has been made to fully include the impact of

time as a variable, although a 3-year average of market

performance was used as a measure. The findings

indicate that the low variance explained for the market

performance outcome maybe due to the time-lagged

effects of promotions. Again, this is a fruitful area for

future research, where a longitudinal study can be

performed with the results of this study used as a

benchmark.

5. Limitations with the definitions of customer value also

concern the lack of treatment of the time dimension. As

changes in the perception of value come from successive

purchase and use of the product, time will impact

customers’ perception of value. Furthermore, time will

certainly influence the positive or negative development

of the relationship with the company and/or its

representatives. The time or circumstance dependent

information needed to deal with the above dynamic has

not been considered.

6. Finally, the last limitation is that by using panel cross-

sectional data, this may result in bias due to common

method variance and spurious cause–effect inferences.

These are known to inflate correlation measures,

resulting in overestimations of the influence of hypoth-

esized predictors. Recognizing that drawing cause–

effect inferences from cross-sectional data maybe

tenuous, a longitudinal study is recommended to confirm

any established hypothesized sequence of effects.

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Joseph Spiteri, the president of a company that does research on markets for

veterinary medical products, earned a DBA from the Wayne Huizenga

School of Business in Fort Lauderdale, FL.

Paul Dion, an associate professor of management at the Sigmund Weis

School of Business at Susquehanna University, researches business-to-

business marketing and purchasing performance, marketing logistics, and

research methodology and statistics.

customer value, overall satisfaction, end-user loyalty, and market ... · customer value, overall...

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