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    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, USAb

    Sigmund 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 Eggerts 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,

    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;

    0019-8501/$ see front matterD 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).

    Industrial Marketing Management 33 (2004) 675687

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    5. finally, empirically test and validate Ulaga and Eggerts

    (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 ofCarter (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

    Fig. 1. Customer values main model.

    J.M. Spiteri, P.A. Dion / Industrial Marketing Management 33 (2004) 675687676

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    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 customerthe medical professional.

    Therefore, the spectrum of personal selling activities is

    viewed as central to the relationship marketing efforts ofthe 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 IIused 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,

    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),

    Table 1

    Antecedents of customer value

    Antecedents Findings Author(s)

    Market orientation Directs firm to focus on gathering and

    dissemination of customer value information

    Slater & Narver, 2000; Woodruff & Gardial, 1996

    Learning Positively linked to implementation of

    customer value information

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

    Slater & Narver, 1995

    Competence/expertise Linked to customer value Doney & Cannon, 1997; Smith & Barclay, 1997

    Communication Linked to customer value Anderson & Weitz, 1989; Gronroos, 1990

    Alignment of sales compensation to value Linked to customer value Anderson et al., 1994

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

    relationships

    Gundlach & Murphy, 1993; Tax, Brown,

    & Chandrashekaran, 1998

    Forbearing opportunistic behavior Linked to success of buyer/seller

    relationships

    Morgan & Hunt, 1994

    Ethical acts Linked to success of buyer/seller

    relationships

    Boedecker, Morgan, & Stoltman, 1991;

    Lagace et al., 1991

    Shared values Linked to success of buyer/seller

    relationships

    Morgan & Hunt, 1994

    Promotional investments Add customer value or perceived value Woodruff & Gardial, 1996

    Relational investments Add customer value or perceived value Berry, 1995; De Wulf et al., 2001; Goff et al., 1997

    Innovations Add customer value or perceived value Dickson, 1992; Ghemawat, 1986; Jacobson, 1992

    Total quality management Add customer value or perceived value Buzzell & Wiersema, 1981; Capon, Farely, & Hoenig, 1990

    Seeking sustainable competitive

    advantage

    Lead to acceptance of customer value

    as competitive advantage

    Christopher et al., 1991; Porter, 1985;

    Treacy & Wiersema, 1995

    Process efficiencies Lead to acceptance of customer value

    as competitive advantage

    McKenna, 1991; Porter, 1985

    Cost-cutting initiatives Lead to acceptance of customer value

    as competitive advantage

    Cannon & Homburg, 2001

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    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 toinclude financial factors so that the customers 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 fororganizations 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 superiorcustomer 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 organizations

    customers, considering what they want and believe that

    they can get from buying and using a sellers 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 termsutility, worth, benefits, and qualityto 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?

    Fig. 2. Components of customer perceived product value.

    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

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    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-

    pliers 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 suppliers offering as perceived by key

    decision-makers in the customers 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 Eggerts (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 satisfactionThe 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).

    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 Europes pharmaceutical

    market (Scharitzer & Kollarits, 2000) showed physicians

    subjective customer value assessments of certain pharma-

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

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    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 satisfactionmodel 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.

    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 marketprofessionals.

    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 foranother 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 studys

    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 Cronbachs 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

    Table 3

    H1H3: There are positive relationships between perceived customer

    value and overall buyers satisfaction (H1), end-user brand and

    company loyalty (H2), and market performance (H3).H4H6: There are positive relationships between perceived

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

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

    H7H9: There are positive relationships between perceived

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

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

    H10H12: There are positive relationships between perceived strategic

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

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

    H13H15: There are negative relationships between perceived relationship

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

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

    H16H17: 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

    buyers satisfaction and end-user loyalty (H19).

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

    strategic benefits and perceived sacrifices, overall buyers satisfaction,

    and end-user loyalty (H20).

    H21: There is a linear relationship customer value and overall buyers

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

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

    strategic benefits and perceived sacrifices, overall buyers 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).

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    referenced and computed Cronbachs alpha values for thescales.

    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.

    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-

    Table 4

    Cronbachs alpha values of present and previous studies

    Perceived independent,

    mediator, and dependent

    variables

    Items Sample item Referenced/computed

    Cronbachs alpha

    References

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

    Strategic-related benefits 4 Please rate product brand onsharing 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

    Table 5

    Summary of tests of hypotheses

    Hypotheses Independent variable(s) Dependent variable Pearsons correlation Significance level (P)

    H1 Customer value Overall satisfaction .22 .004

    H2 Customer value End-user loyalty .23 .000

    H3 Customer value Market performance .04 .690

    H4 Product benefits Overall satisfaction .62 .000

    H5 Product benefits End-user loyalty .50 .000

    H6 Product benefits Market performance .19 .016

    H7 Personal benefits Overall satisfaction .42 .000

    H8 Personal benefits End-user loyalty .37 .000

    H9 Personal benefits Market performance .056 .469

    H10 Strategic benefits Overall satisfaction .50 .000

    H11 Strategic benefits End-user loyalty .45 .000

    H12 Strategic benefits Market performance .01 .854

    H13 Relationship sacrifices Overall satisfaction .09 .242

    H14 Relationship sacrifices End-user loyalty .04 .591

    H15 Relationship sacrifices Market performance .03 .723H16 Overall satisfaction End-user loyalty .52 .000

    H17 End-user loyalty Market performance .22 .005

    H18 Overall satisfaction Market performance .04 .593

    H19 Customer value and overall satisfaction End-user loyalty R2 =29% F= 33.5, P= .000

    H20 Perceived product, personal, strategic,

    benefits, perceived sacrifices, and overall

    satisfaction

    End-user loyalty R2 = 36.1% F= 18.2, P= .000

    H21 Customer value, overall satisfaction, and

    end-user loyalty

    Market performance R2 = 8.5% F= 5.05, P= .002

    H22 Perceived product, personal, strategic,

    benefits, perceived sacrifices, overall

    satisfaction, and end-user loyalty

    Market performance R2 = 13.5% F= 4.16, P= .001

    H23a Main model Model did not load on SEM.

    H23b Alternate model GFI=.992 (a very good fit), v2 = 4.49 (6 df), P=.661

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    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 variablespractice types, geographic

    spread, and dispensed/vetall 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

    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 fourfactors, which were theoretically the three benefits and

    one sacrifices proposed in Ulaga and Eggerts (2002)

    scale.

    4.3. Measurement properties

    The computed Cronbachs 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 122 using

    correlation and regression are presented. Hypothesis 23 was

    tested using a structural equation modeling approach and is

    presented below.

    Fig. 4. Customer values alternate model.

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    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 theinclusion 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.

    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 scales component influence on

    market performance also appears to be direct and not

    through the roles of mediating variables like the business

    buyers 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 proposedantecedents, 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. Whilethe 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 scales

    items.

    The research also confirmed the importance of end-

    user loyalty, particularly in this hybrid marketing situa-

    tionmanufacturer 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 researchthat 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 practitioners 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 Eggerts (2002)

    customer value scale. Nevertheless, the practitioners re-

    quired specific language particularly for the strategic

    benefits components. For example, one strategic benefit

    Relationship Estimate S.E. Critical

    value

    Significant

    PersonalpProduct 0.236 0.073 3.232 yes

    StrategicpPersonal 0.770 0.045 17.127 extremely

    StrategicpProduct 0.183 0.044 4.156 yes

    SatisfactionpProduct 0.803 0.095 8.434 very

    LoyalpSatisfaction 0.242 0.085 2.833 just

    LoyalpStrategic 0.366 0.114 3.211 yes

    LoyalpProduct 0.403 0.124 3.242 yes

    Market performance

    pLoyal

    772.809 241.10 3.205 yes

    Market performance

    pSatisfaction

    904.159 273.94 3.301 yes

    Market performance

    pProduct

    1169.40 404.34 2.892 just

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    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 orinstructions of what this general wording specifically

    means to the responder. For example, to a clinics 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 andsacrifices 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 adecision 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 makesthe 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 consumerhas 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 Eggerts (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 ofcustomer 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 benefitsthe 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

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    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 customers 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 futureresearch.

    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.

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