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Marketing Performance Measures:

History and InterrelationshipsBruce H. Clark

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To cite this article: Bruce H. Clark (1999): Marketing Performance Measures: History andInterrelationships, Journal of Marketing Management, 15:8, 711-732

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Journal of Marketing Management 1999, 15, 711-732

Bruce H. ClarkI

Northeastern

University

Introduction

Marketing Performance Measures:

History and Interrelationships

This article reviews the history of measuring the peifonnance of marketing in the fimJ, organised

around three themes: the movement from financial tononfinancial output measures, the expansion frommeasuring only marketing outputs to measuring

marketing inputs as well, and the evolution fromunidimensional to multidimensional measures of

peifonnance. Evaluation of this history suggests a

need for the marketing community to develop a set of

measures small enough to be manageable but large

enough to be comprehensive. The paper examines the

interrelationships among four important measures

and suggests research issues and approaches to aid in

UJistask.

Measuring marketing perfom1ance is attracting academic and managerialattention with an urgency and scope previously unprecedented in the field's

history. This represents the convergence of four trends. First after a decade of

downsizing, major corporations are reaching the point of diminishing retums onincreasing profits by reducing headcount and increasing operational efficiency.This has led to a refocusing on marketing as a driver of future sales, and

therefore profit growth (Sheth and Sisodia 1995). Second, there has been

increasing demand from investors for infonnation related to the quality of the

marketing effort which traditionally has been both under- and poorly reported in

finn financial statements (Mavrinac and Siesfeld 1997; Haigh 1998). Third, popular new overall conceptions of business perfonnance measurement such as

the Balanced Scorecard (Kaplan and Norton 1992) have attracted attention tothe issue of which marketing measures should be included in overall

assessments of business perfonnance. Finally, senior marketing managersthemselves have become fmstrated with traditional perfom1ance measures that

they believe, undervalue what they do, leading to calls for research from a variety

of quarters (e.g.Marketing Science Institute 1998).The purpose of this paper is to layout the history of marketing perfom1ance

measurement at a very broad level, and to suggest that what marketing as a field

1 Correspondence: Bruce Clark, Assistant Professor, Marketing Group, 202 Hayden Hall,Northeastern University, Boston, MA 02115 USA, Phone: 1-617-373-4783, FAX: 1-617-373-8366, e-mail: [email protected]

ISSN0267-257X/99/080711 +21 $12.00/0 Westbum Publishers Ltd.

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712 Bruce H. Clark

needs is fewer measures and more understanding of the interrelationshipsamong those measures. I identify three discernible historical trends and their

consequences, explore the interrelationships among four key marketing

perfonnance measures, and discuss the search for a few good leading indicatorsof marketing perfom1ance, with implications for research and practice.

A History

Marketing perfom1ance measurement has, of course, been practiced and studiedfor decades. A review of this history suggests marketing performance measureshave moved in three consistent directions over the years: first from financial to

non-financial output measures; second, from output to input measures; and

third, from unidimensional to multidimensional measures (see Figure 1 andTable 1 for summary views).

Table 1. Literature Review Summary

Single Financial Output Measures

Profit Goodman (1970, 1972), Sevin (1965)Sales Revenue Feder (1965)

CashFlow

Buzzell and Chussil (1985), Day and Fahey (1988) Non-financial Measures

Market Share

Quality ofServices

Adaptability

Customer

Satisfaction

Customer Loyalty

Buzzell and Gale (1987), Jacobson (1988), Szymanski,

Bharadwaj, and Varadarajan (1993)

Bucklin (1978)

Bhargava, Dubelaar, and Ramaswami (1994), Walker and

Ruekert (1987)

Anderson and Sullivan (1993), Anderson, Farnell, and Rust

(1997), Danaher and Matson (1994), Farnell (1992), Farnell,

Johnson, Anderson, Cha, and Bryant (1996), Halstead,

Harbnan, and Schmidt (1994), Hauser, Simester, and

Wernerfelt (1994), Oliva, Oliver, and MacMillan (1992),

Peterson and Wilson (1992), Piercy and Morgan (1995),

Seines (1993), Spreng, MacKenzie, and Olshavsky (1996),

Teas (1993), Teas and PalanI997), Voss, Parasuraman, and

Grewal (1998), Yi (1990)

Anderson and Sullivan (1993), Dick and Basu (1994),

Farnell, Johnson, Anderson, Cha, and Bryant (1996), Jones

and Sasser (1995), Oliva, Oliver, and MacMillan (1992),

Reichheld (1994), SeInes (1993)

Confd/ ...

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Marketing Performance Measures 713

Non-fmancial Measures Cont'd/ ...

Brand Equity Aaker and Jacobson (1994), Ambler and Barwise (1998),

Barwise (1993), Keller (1993, 1998), Haigh (1998), Lassar,Mittal, and Shanna (1995), SeInes (1993), Simon andSullivan (1993)

Piercy (1986), Srivastava, Shervani, and Fahey (1998)

Brownlie (1993, 1996), Kotler, Gregor, and Rodgers (1977),Rothe, Harvey, and Jackson (1997)Bonoma (1985, 1986), Bonoma and Crittenden (1988)

Effectiveness

Multivariate

~Q!ysis

MarketingImplementation

MarketOrientation

Day and Nedungadi (1994), Deshpande and Farley (1998a,1998b), Han, Kim, and Srivastava (1998), Kohli and

Jaworski (1990), Kohli, Jaworski, and Kumar (1993), Jaworski

and Kohli (1996), Narver and Slater (1990, 1998), Slaterand Narver (1994), Wrenn (1997)

Multiple Measures

Efficiency Bonoma and Clark (1988), Dunn, Norbum, and Birley(1994), Kotler

(1977), Sheth and Sisodia (1995), Walker and Ruekert(1987)

Bhargava, Dubelaar, and Ramaswami (1994), Spriggs (1994)

Input Measures

Marketing Assets Marketing Audit

Moving from Financial to Non-Financial Output Measures

Early work in the finn-level measurement of marketing perfonnance was

largely directed at examining the productivity of a finn's marketing efforts at

producing positive financial outputs. These studies typically were designed to

provide guidance to managers regarding how to best allocate their marketingresources, drawing on both marketing knowledge and perspectives from finance

and accounting.One branch of this literature developed extensive profitability analyses of

marketing efforts. Sevin (1965) and Goodman (1970, 1972) are classics in thisfield, laying out in great detail how to relate financial outputs to marketing

inputs. Feder (1965) borrowed from the marginal revenues-marginal costs

concept in microeconomics to suggest how to allocate marketing resources most

efficiently.Later work expanded from using profitability as an output to use more

sophisticated measures from the finance literature, examining cash flows and thenet present value of different marketing strategies (Buzzell and Chussil, 1985;

Day and Fahey, 1988). In their review of finn-level marketing productivity studies,

Bonoma and Clark (1988) found that the most frequent measures of output

were, in order, profit, sales (unit and value), market share, and cash flow.

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714 Bruce H. Clark

Figure 1. The Expanding Domain of Marketing Performance Measures

Non-Financial

Measures

CustomerSatisfaction

Customer Loyalty

Brand Equity

Single Financial

Output Measures

Profit

Sales Cash Flow

Input Measures Multiple Measures

Marketing Audit Marketing Audit Marketing Efficiency/

Implementation Effectiveness

Market

Multivariate

Orientation Analysis

The 1980s brought an expanded conception of output that included non-financial measures. This was partly driven by the realization that what hassometimes been called "the black box" (e.g. Piercy, 1997) of mediating factors between marketing inputs and financial outputs is itself worthy of study. Bonomaand Clark (1988) uncovered many moderating factors in the marketing

productivity literature, suggesting that the process of transformation betweenmarketing inputs and outputs is highly contingent on other variables.Market share attracted tremendous attention as an output variable in this

period. Work by consultants at the Boston Consulting Group (Henderson, 1973)and academics working on the Profit Impact of Market Strategies (PIMS)project(Buzzell and Gale, 1987) concluded that market share was a strong predictor of

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Marketing Perfomlance Measures 715

cash flow and profitability. This, combined with the spectacular success at thetime of Japanese finns that emphasized market share as a perfonnance measure,drove much examination of market share as the best measure of marketing

perfonnance. Unfortunately, in retrospect the market share-profitabilityrelationship has proven both controversial and complicated Qacobson, 1988;Szymanski, Bharadwaj, and Varadarajan, 1993).

Aside from market share, other non-financial measures advocated as outputsincluded services and level of new product development/innovation. Bucklin

(1978) is particularly adamant in his claim that the quality of services providedmust be included in any marketing productivity measure. Rather than consideronly the benefit to a customer of using a product, Bucklin attempts to account

for the services that add to simple foml utility, discussing logistical services (e.g.

delivery),infonnational services (e.g.product infonnation), and product functionalservices (e.g.warranties, packaging).

Adaptability or innovativeness of a finn's marketing has received continuousattention as a perfonnance measure (Bhargava, Dubelaar, and Ramaswami,1994; Walker and Ruekert, 1987). Typically cast in tenns of the finn's new

product or marketing innovations, the idea behind measuring adaptability as anoutput of marketing is that in the face of a changing environment, finns that are

unable to adapt will fail (Walker and Ruekert, 1987).In the last 10 years, three new non-financial output measures have attracted

extensive research attention: customer satisfaction, customer loyalty, and brandequity. I will briefly review each measure in tum.

Customer Satisfaction.Perhaps no recent measure of business perfonnance has attracted as much

attention as customer satisfaction. With a large and continuing academicresearch stream (see Halstead, Hartman and Schmidt, 1994 and Vi, 1990 for

reviews) and substantial adoption by industry (the 1997 Marketing NewsCustomer Satisfaction Research Directory listed over 200 research fimls with

satisfaction practices), customer satisfaction measures have become important

benchmarks in many industries. .

The traditional disconfimlation paradigm of customer satisfaction proposes

that customers have prepurchase expectations about the products they buy, and

are more satisfied depending on how well the consumption experience exceeds(disconfin11S)those expectations. Having a satisfied customer base is considered

an important marketing asset because it should lead to increased loyalty,with its

consequent revenue implications and lower marketing costs.

While straightforward in theory, customer satisfaction measurement in

practice has proven more complex. First, at least in North America, most

customers are satisfied. Peterson and Wilson (1992) review a large number ofstudies where the distribution of customer satisfaction responses is highly

skewed towards the positive. This finding presents two problems. Managerially, a

high satisfaction rating may have little' consequence if customers are equally

satisfied with competing products; if everyone gets an 85% score, then no finn

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716 Bmce H. Clark

has a competitive advantage. Methodologically, Peterson and Wilson (1992)

observe that the highly skewed distribution reduces the likelihood that asignificant correlation between satisfaction and other perfonnance variables will

be observed; low variance in the satisfaction measure makes it unlikely that anyclear relationship with other variables will be revealed.

Empirical research evidence regarding the disconfinnation paradigm has also been quite mixed, leading to a proliferation of satisfaction frameworks (e.g.Anderson and Sullivan, 1993; Teas, 1993; Voss, Parasuraman and Grewal, 1998).

The expectations constmct has proven particularly problematic, in that differentstudies appear to define it differently (Teas and Palan, 1997), leading one to

wonder exactly what managers should be measuring. Recent research also

suggests that there may be multiple satisfaction processes (Spreng, MacKenzie

and Olshavsky, 1996) and that one should consider measuring satisfaction on anattribute-by-attribute basis (Donaher and Mattson, 1994; Halstead, Hartman andSchmidt, 1994).

Further, satisfaction measurement programs appear particularly difficult to

implement. Piercy and Morgan (1995) note substantial internal barriers to the

measurement process. Measures also appear more subject to manipulation than

objective items such as unit sales. Once customer contact personnel (e.g.

salespeople) or organizations (e.g. retailers) know they will be graded on

satisfaction ratings, there is a tremendous incentive to manipulate the findings

(Hauser, Simester, and Wernerfelt, 1994).

Customer Loyalty.Partly in response to problems with customer satisfaction as a measure,

customer loyalty measures have attracted increasing attention as a measure of

good marketing. Behavioural measures of brand purchase and repurchase have

existed for years in the marketing literature (e.g. Uncles, Ehrenberg and

Hammond, 1995), but there has been a recent emphasis on expanding beyond

purely behavioural conceptions of loyalty (Dick and Basu, 1994). Advocates of

loyalty note that financial perfonnance ultimately reflects whether customers

repurchase from a firnl over time, regardless of satisfaction. One of the most

prominent spokespersons for this position, Frederick Reichheld (I994), suggests

that good marketing attracts the right customers: ones whose loyalty the finn is

able to earn and keep. A loyal customer base, it is argued, should increase

revenue per customer as satisfied customers buy more volume, a broader range

of products, and/or pay a premium for the company's products. It also should

lower marketing costs; current customers are cheaper to retain, and word-of-

mouth from current customers should make new customers easier to acquire. A

common financially-based measure of the worth of a loyal customer base is tocalculate the "lifetime value" of the customers in this base (Wyner, 1996).

Brand Equity.Many researchers and managers believe that a powerful brand (one with high

"equity") is among the greatest marketing assets a finn can have (see Barwise,

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Marketing PerfOnllanCe Measures 717

1993; Keller, 1998 for reviews). Strong brands, it is argued, (1) allow finns tocharge price premiums over unbranded or poorly branded products; (2) can beused to extend the company's business into other product categories; and (3)

reduce perceived risk to customers (and, perhaps, investors).There have been two approaches to measuring brand equity. The behavioural

approach looks at customer response to the brand, either in tenns of perceptions

or purchase. One definition of behaviourally-based brand equity is the differentialeffect of brand knowledge on customer response to marketing of the brand(Keller, 1993). Customers in these studies typically respond more favourably tostrong brands than to unbranded or poorly branded products. The financialapproach to brand equity attempts to divine the financial value of the brand to

finns and their investors. A widely cited approach in this area was developed by

Simon and Sullivan (1993), who define brand equity as the incremental cashflows that accme to branded products over and above the cash flows that would

result from the sale of unbranded products.

There is little question that brands can make a powerful difference in how

customers respond to brands and brand extensions (Barwise, 1993; Keller, 1998).

There is growing evidence that brand equity has an influence on investors as well

(Aaker and Jacobson, 1994; Simon and Sullivan, 1993), which has led to changes

in financial reporting ntles in the UK (see Ambler and Barwise, 1998 for adiscussion of brand valuation and brand equity). Barwise (1993) notes, however,

that we actually know relatively little about the impact of a brand on the branded product's long-tenn profitability. Further, the relationship between the behavioural and financial approaches to brand equity are at present not well-

integrated (see Ambler and Barwise, 1998 for a discussion of definitions). Finally,while brand equity appears a powerful measure of perfonnance, it also is one

that is hard to use as a short-tenn perfonnance measure for managers. It cantake years and huge marketing expenses to create a powerful brand; conversely,this asset can take substantial time to dissipate even in the face of reduced

marketing support

Moving from Output to Input Measures

Recent emphasis on measures such as customer satisfaction, customer loyalty

and brand equity is part of a general move away from ultimate financial outputmeasures such as profit and sales and toward measures earlier in the input-to-

output sequence. In particular, one can look at initial marketing activities (inputs)

that lead to intennediate outcomes such as the three measures above that in

tum lead to financial outputs. The intenllediate outcomes can be thought of asthe marketing assets (Piercy, 1986; Srivastava, Shervani and Fahey, 1998) that

are leveraged to produce superior financial perfonnance.

One of the earliest attempts to assess the underlying marketing inputs thatlead to superior perfOnllanCe was the marketing audit concept (see Brownlie,

1993; Rothe, Harvey, and Jackson, 1997 for reviews). The goal of a marketing

audit is to systematically evaluate the appropriateness of the actjvities and assets

a finn uses in its marketing, given the finll'S situation. While initially conceived in

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718 Bruce H. Clark

the 1950s, the audit was strongly popularized by Kotler and his colleagues

(Kotler, Gregor, and Rodgers, 1977). They advocate an evaluation of the

environment, to understand the situation the finn is in, and then examination of

strategy, organization, systems, and productivity of marketing. Further work canthen be focused on specific marketing functions. While an area of much researchand successful case studies, it is unclear how widespread audits are in practice.

They also typically do not result in exact perfon11ance measures so much asdiagnoses for organizational improvement (Brownlie, 1996).

Bonoma (1985, 1986) also weighs in on the question of what constitutes good

marketing practices. He focuses on the finn's marketing skills and marketingstructures (e.g. systems and procedural support), and argues that good marketing

is the product of the interaction between the two.

The most recent systematic evaluation of the quality of marketing inputs hasresulted from the market orientation concept This perspective - also variouslydescribed as marketing-oriented and market-driven (see Jaworski and Kohli,

1996; Wrenn, 1997 for reviews) - measures activities that develop and use

intelligence about the market While definitions across studies vary (e.g. Day and

Nedungadi, 1994; Kohli and Jaworski, 1990; Narver and Slater, 1990), common

components of being market oriented include systematic gathering, analysis,

dissemination and use of market infonnation within the organization. Day and

Nedungadi (1994) in particular note the importance of maintaining a balanced perspective between customers and competitors.

Empirical evidence suggests that being good at generation. dissemination andapplication of market infom1ation within the organization can be a significant

advantage (e.g. Day and Nedungadi, 1994; Jaworski and Kohli, 1993; Narver and

Slater, 1990), but overall findings on the relationship between market orientation

and perfonnance have been mixed (Han, Kim and Srivastava, 1998). This has led

to a search for moderators or new explanatory factors in the relationship (e.g.Han et aI., 1998; Slater and Narver, 1994). Aside from affecting business

perfom1ance, Wrenn (1997) reviews studies suggesting marketing orientation

also positively affects both customer and employee perceptions of the finn.

As with brand equity, the variety of operationalizations of market orientation

make it difficult to use as a perfonnance measure in practice. As many of the

measures of orientation list specific organizational activities (e.g. 'We have

interdepartmental meetings at least once a quarter to discuss market trends and

developments," Kohli, Jaworski, and Kumar, 1993), one may wonder if a focus on

measuring market orientation as a perfonnance measure might lead to ritual

activities that allow fin11Sto "tick the box" without realizing the true benefits. This

relates to the issue of whether market orientation represents a behaviour or a

culture (Deshpande and Farley, 1998a; Narver and Slater, 1998).

Moving to Multidimensional Measures

Early in the history of measuring marketing perfom1ance, it was common to

use one or a handful of financial or volume measures to track the output of

marketing. This changed in the, 1970s, beginning with the multidimensional

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Marketing Perforn1ance Measures 719

marketing audit (e.g. Kotler, Gregor and Rodgers, 1977). In the 1980s, Bonomaand Clark (1988) and Walker and Ruekert (1987) independently suggestedschemes of marketing perfonnance measurement tl1at assessed marketing

efficiency and effectiveness. Bonoma and Clark (1988) described tl1e fonner as a productivity measure, comparing outputs to inputs, and tl1e latter as acomparison of outputs to goals, drawing on Dmcker's (1974) distinction betweenefficiency as "doing tl1ings right" and effectiveness as "doing the right tl1ing."Walker and Ruekert (1987) added a measure of adaptability to changes in tl1e

environment, while Bonoma and Clark (1988) included a measure of tl1e hostilityof tl1e external environment.

Paradigms from tl1e management literature have influenced tl1e move to

multidimensional measures as well. Kumar, Stem and Achrol (1992) draw on

four perspectives from tl1e organizational effectiveness literature to researchreseller perfonnance. Kotler's dimensions of marketing effectiveness (Kotler,1977) have been incorporated into rigorous empirical studies (e.g. Dunn,

Norburn and Birley, 1994). Multivariate data analysis techniques such as factor

analysis and Data Envelopment Analysis have been adopted to identify tl1eunderlying dimensions of perfonnance (e.g. Bhargava, Dubelaar and Ramaswami,1994; Spnggs, 1994). While multiple measures are clearly psychometrically

desirable to obtain tl1e most complete picture possible of marketingperfom1ance, tl1eyraise difficult issues for managers, a point to which I will return

below.

Evaluating the Trends

Having seen evidence regarding tl1e historical trends in marketing perfonnance

measures, one can ask if tl1ese trends are good for scholars, managers or botl1.The answer appears to be a qualified yes for both audiences.

That we have moved as a field to examine non-financial measures as well as

financial is clearly an improvement. The asset-based marketing perspective in

particular (e.g. Piercy, 1986) demonstrates tl1e inadequacy of financial outputs astl1e sole measure of marketing perforn1ance. Indeed, tl1e reason non-financial

measures were adopted in tl1e first place was tl1e instinct of managers and

academics tl1at some important elements of marketing perfonnance (e.g. brand

strengtl1) were left uncaptured by traditional financial measures. Areas such as

customer satisfaction and brand equity have been unusual in tl1at scholarly

research and practitioner interest have coincided far more powerfully tl1an is

usual in our discipline. This is all to the good.

Deeper understanding of tl1e quality of marketing inputs in the fonn of

marketing processes has had less clear impact. Inherently difficult to study

because of tl1e complexity of processes and tl1e large number of external andinternal constituencies involved, defining "good marketing activities" has more

often been tl1e subject of conceptual or qualitative treatments (e.g. Bonoma,

1985; Bonoma and Crittenden, 1988) tl1an rigorous statistical research. Concepts

such as tl1e marketing audit and market orientation, while powerful in tl1eory,

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720 Bruce H. Clark

appear difficult to transfer to the managerial realm. Both ideas have empiricalstudies backing up a link to overall business perfonnance, but, as noted above,this link is by no means a simple linear relationship, depending rather on a

variety of potential moderating factors. Further, it is difficult to tell howwidespread either practice is because some finns may adopt elements of eitherapproach without ever using the words "marketing audit" or "market orientation."

In sum, this trend has led to richer, deeper understanding of marketing process, but compared to objective financial measures its complexity makes it relatively

intractable for managers and more statistically-inclined researchers.The trend toward multidimensional measures has arguably been wonderful

for researchers and horrible for practitioners. Psychometrically and theoretically,

researchers know that a multidimensional model of marketing perfonnance is

likely to be more "true" in that it will capture more facets of perfonnance thanany single dimension can. Unfortunately, successively more complicated schemesdramatically increase the burden on managers attempting to measure

perfomlance in the world. Given bounded rationality, any individual manager can

only juggle so many concepts in his or her mind at once. Yet organizations are

finding themselves overwhelmed with measures. Meyer (1998) notes that it is

common for corporations to have fiftyto sixty "top-level" perfomlance measures

(p. xvi). In the marketing context, .Ambler and Kokkinaki (1998) conclude that

"marketing is already assessed against plenty of measures," (p. 35) but that the

weighting of measures is incorrect Figuring out which of many measures are"really important" may drive the conscientious manager to despair. While one

might be able to reduce these measures to a more manageable set by means of

multivariate statistical techniques, these techniques seem unlikely to be part of

everyday management More generally, it is not clear that management is

interested in elegant multidimensional schemes. Ambler and Kokkinaki (1998)

find that financial measures dominate UK executives' assessment of marketing

perfonnance; Clark (1999) finds sales the most frequent measure used among

US executives. Even in our own field, researchers who use perfonnance as a

dependent variable most frequently rely on sales and market share (Ambler andKokkinaki, 1997). One of the original appeals of the balanced scorecard

approach to total business perfonnance measurement was that it organized

measures under a small set of dimensions of business perfonnance with which

any manager can work (Kaplan and Norton, 1992). Marketing scholars must

similarly present management with a handful of measures that are simple

enough to be usable but comprehensive enough to give an accurate perfonnance

assessment

Understanding Interrelationships among Measures

Much work in recent years on non-financial measures has been to understand

their relationship to financial measures (e.g. Han et a!., 1998; Anderson, Fomell

and Rust, 1997). The presumption behind many of these non-financial measures

is that they are leading indicators of long-nm shareholder value (e.g.Srivastava et

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Marketing Perfonnance Measures 721

aL, 1998). A powerful brand, for example, should not only generate profits on thecurrent accounting statements, but will help generate future profits.

A question one may ask in this context is whether we need all the non-

financial measures proposed. For example, if a fim1 has good customersatisfaction measures, does it also need loyalty measures? The key to developing

a comprehensive but usable set of measures must be to understand theinterrelationships among the various marketing perfonnance measures proposed.To the extent different measures are all correlated with profit or sales, that theyare uncorrelated with one another seems unlikely. If, on the other hand,

measures are highly correlated, they then can be collapsed into multipleindicators of a single constmct (Churchill, 1979). Perhaps most likely is the

situation where various measures are independent but correlated, with causal

relationships among them.At a relatively simple level, consider the interrelationships among four

concepts that have drawn research attention in the last 10 years: market

orientation, customer satisfaction, customer loyalty and brand equity. Each has

been proposed as an important indicator of marketing perfonnance that shouldin tum affect overall business perfonnance. Following is a brief summary of whatwe as a field know about the interrelationships among these four, with an eye

toward future research that might indicate which measures are most valuable toparticular finns.

Market Orientation and Customer Satisfaction

Jaworski and Kohli (1996) observe that market orientation should be

positively related to customer satisfaction. Gathering and responding to good

market intelligence should lead to products that do a better job of meetingcustomer needs. Unfortunately, they note, there is little empirical study tosupport this proposition. If market orientation does improve overall business

perfonnance, customer satisfaction would be a logical mediating variable throughwhich such a relationship would occur. Indeed, such a mediating relationship

might explain why the direct effect of market orientation on business

perfonnance has been difficult to document consistentJy. In the long nm, onemight see negative feedback from customer satisfaction to market orientation

through perfonnance: a company with a satisfied customer base might havesuccess, which in tum might lead to complacency and a dulling of the fim1's

market orientation (see Miller, 1994 on the perils of success).

Market Orientation and Customer Loyalty

Fundamentally, the same logic as under the market orientation-satisfaction

link should apply here. The question is whether the link would be direct or

indirect through satisfaction. As loyalty in the absence of satisfaction may occuronly in the absence of competitive alternatives (see below), the indirect link

seems more likely.

Market Orientation and Brand Equity

No one, to my knowledge, has proposed a causal link between market

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722 Bruce H. Clark

orientation and brand equity, but speculation suggests that some positiverelationship might exist A market oriented finn, with good knowledge of

customers, presumably can design and support a stronger brand than an

internally-focused, ignorant firn1. While this effect may be indirect throughsatisfaction, one can argue that a direct link might exist before purchase as the

well-designed brand is attractive and affects customer behaviour even prior toany satisfaction experience. Once again, a disconnection may occur between brand equity and market orientation if high brand equity leads to complacency

and a lower market-orientation.

Brand Equity and Customer Satisfaction

Looking at brand equity from a psychological perspective, a brand name

evokes a particular set of knowledge about the brand from memory (Keller,1993). This knowledge structure (e.g. image, associations, attitudes) will differamong brands and between branded and non-branded products, with

consequences for customer behaviour.It seems straightforward that customer satisfaction in one period should affect

brand equity in the next A satisfying experience with a brand should increase the

favourability of the associations a customer has to the brand. Interestingly, SeInes(1993) finds this relationship in only one of the four industries he examines.

Another intriguing possibility is that brand equity in one period may affectcustomer satisfaction in the next period, both through its impact on expectations

and on perceived experience with the brand. Regarding expectations, brandknowledge should affect the expectations aspect of customer satisfaction in two

dimensions: certainty and level. First, a strong brand will probably produce well-

defined expectations, because the knowledge structure about the brand will be

elaborate. By comparison, a product with a weak brand or no brand will evoke

little knowledge and thus more uncertain expectations. Measures of satisfaction

with strong brands should be more reliable than with weak brands, because the

expectations construct will be more clearly defined. Second, a brand, however

strong, will produce some level of expectations about the product Keller(1993)

defines positive brand equity as that evoking more favourable responses than a

corresponding unbranded product A strong brand might influence expectations

in a higher direction, making satisfaction more difficult to achieve.

Regarding experience, favourable brand equity may have an influence on

perceived experience with using the brand; one might rate more highly an

experience with a well-liked brand than one would with a corresponding

unbranded product, simply because the accumulated (positive) experience with

the brand outweighs any single experience. A positive expectation created by a

strong brand may also influence the perceived experience through an

assimilation effect, such that perceived quality adjusts slightly in the direction of

expectations (cf.Anderson and Sullivan, 1993).

Brand Equity and Customer Loyalty

Favourable brand equity should affect customer loyalty. Customers are

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presumably more loyal to well-regarded brands than to poorly-regarded ones;whether this link is direct or mediated by customer satisfaction is open toquestion (see below). Seines (1993) found a direct positive link across four

industries (see also Lassar, Mittal and Shanna, 1995). Behaviourally, Fader andSchmittlein (1993), found that brands with high market shares exhibited much

greater brand loyalty than did brands with low market shares.

It seems less likelythat simple loyalty in the fonn of consistent repurchase has

an effect on the favourability of brand equity. Rather, loyalty should reinforce

whatever level of brand equity already exists. Every purchase incident shouldreinforce (and possibly elaborate) the current knowledge structure the customerholds regarding the brand, making it more accessible in memory. The only

influence on the level might occur through an exposure effect, such that

familiarity increases liking (Bomstein, 1989).

Customer Satisfaction and Customer Loyalty

Unlike some of the other links, this link has received extensive researchattention, the conclusion of which is that customer satisfaction has a positive

direct impact on customer loyalty (Fornell, 1992; Seines, 1993; Anderson andSullivan, 1993; Jones and Sasser, 1995; Fornell, Johnson, Anderson, Cha andBryant, 1996). There is evidence, however, that the fonn and strength of this link

varies across industries. Some analysts suggest that the strength of thisrelationship may vary by the degree of competitiveness within the industry, such

that the relationship is stronger in more competitive industries (Fornell, 1992;Jones and Sasser, 1995). Seines (1993) suggests the ambiguity of the product

may moderate this relationship. In products where evidence about the quality of

a product experience is ambiguous, brand may matter more and satisfaction lessin detemlining loyalty because the satisfaction j~ldgments will be poor. Thisrelationship has also been posited to be nonlinear, both overall and varying by

industry (Oliva, Oliver and MacMillan, 1992; Anderson and Sullivan, 1993). Less

well-documented is the idea that loyalty may affect satisfaction through familiarity

with the product Halstead et al. (1994) observe that some level of familiarity is

necessary before a customer can fonn expectations about a product

Looking for a few Good Leading Indicators

When measuring marketing perfonnance began, financial output measuresdominated the field. As marketing perfonnance measures evolved, we added a

host of non-financial and input measures to the measurement mix. Financial

outputs will probably always be used as indicators of marketing perfonnance, but

they are snapshots of the present and say little about the marketing health of the

company in the future. Unfortunately, the proliferation of potential leadingindicators is managerially problematic; for example, the American Marketing

Association's, 1999 Customer Satisfaction and Quality Measurement Conference

is entitled "Making Sense of Multiple Measurements."

Looking for a few good leading indicators suggests two research agendas. On

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724 Bruce H. Clark

a micro level, one should attempt to reduce the number of items used tomeasure particular constnlCts, while still retaining enough for reliability.Psychometrically, there are a variety of standard data reduction techniques

available for this endeavor, such as factor analysis. In a structural equationmodeling context, Baumgartner and Homburg (1996, p. 144) suggest that three

items per latent constnlct is a minimum standard for reliable measurement.

Regarding the number of constructs managers should attempt to track, simple psychological limits on the number of items people can juggle in memory

suggests seven is a plausible maximum (Miller, 1956; Lynch and Srull, 1982) -below I will suggest four specific measures.

Beyond this, the academic community sometimes encourages proliferation of

measurement schemes, as each scholar suggests his or her own items for a

particular constnlct. For some constructs, we have enough of a history that weshould be moving in the opposite direction: using a standard set of measuresrather than inventing new measures for each study. Research developing parsimonious syntheses of larger sets of measures would be particularly useful,

both for managers and for academics who might be measuring multipleconstructs in a single study. Deshpande and Farley (1998b), for example,

examine three different sets of measures of the market orientation construct and

develop a short synthesized inventory that incorporates the core infonnation

researchers and managers need to capture. More of this kind of research is

needed.On a more macro level, the challenge for marketing scholars is to understandthe nature of causality among multiple constructs, both for advancement of

theory and to advise managers regarding which measures will be most useful for

their businesses. Regarding the four constructs discussed in the previous section,

Figure 2 summarizes the hypothesized relationships. These, and other constnlcts,

should be examined jointly to detennine their relationship and mutual influence

(see SeInes, 1993, for example).

The challenges in this endeavor are fourfold. First one must establish the

direction of causal relationships. Second, one must identify the fonn of the

relationship Oinear, nonlinear, etc,), Third, one must establish the strength of the

relationships in practical tenns. Finally, one must understand the temporal

relationships among these measures to truly use them as predictors of overall

business health.

In tenns of research approaches, to tndy demonstrate these causal links,

researchers will need to model systems of equations using longitudinal data.

Stnlctural equations modeling is a technique that may be useful in this context

(Diamantopoulos, 1994). One likely source of data would be customer databases

in transaction-intensive industries such as finance, telecommunications, or airtravel. Companies could be assessed on market orientation scales, and customers

could be interviewed or surveyed regarding customer satisfaction and brand

equity. Customer loyalty would be available through the database records. Using

this kind of data, scholars can examine the direction, shape, and dynamics of the

relationships.

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Marketing Perfonnance Measures

Figure 2. Hypothesized Interrelationships among Key Measures

725

Market

Orientation

Brand

Equity

---- ~~ causal relationships

..- - - - - - - - feedback relationships

Regarding shape, in several cases nonlinear or contingent relationships have

been identified, with consequences for both academic modelling and managerial

measurement Economics certainly suggests the general principle that any effect

eventually suffers diminishing returns (i.e. a concave function), but research in

customer satisfaction suggests that in certain competitive situations one may see

increasing returns to satisfaction (e.g.Jones and Sasser, 1995). Another possible

nonlinear fom1 would be an s-shaped relationship.Regarding dynamics, to identify leading indicators one is interested in the

speed with which an effect occurs in the presence of a causal agent, and the

speed with which an effect diminishes when the causal agent is removed. For

example, how quickly does customer satisfaction affect customer loyalty? If

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726 Bruce H. Clark

customer satisfaction subsequently declines, how long will it be before customerloyalty diminishes as well? Speed here may depend on interpurchase times.Someone who has just purchased a car is not likely to be in the market again for

a few years, while a customer's relationship with a financial institution mayinvolve multiple transactions in the course of a year. In the fonner case, the effectof satisfaction on loyalty will not be seen for years, while in the latter it may

appear within months.Cross-industry studies will be important both to identify contingent factors

and to better infonn managers in particular industries which measures may be

most useful. Industry competitiveness appears a particularly likely moderatingvariable in relationships among measures (e.g. Fornell, 1992; Slater and Narver,

1994). Because of the importance of temporal relationships, research should

look for feedback loops among the measures, as shown in Figure 2; it is likelythat A may cause B in one period, but B may influence A in the next.

Finally, aside from the econometric approach, experimental studies may also

be useful in examining some relationships. The relationship between satisfaction

and brand equity could probably be approached in this fashion. One might also

incorporate repurchase intention as a measure of loyalty in experimental

approaches, but market orientation will be harder to approach in this fashion.

What Do I Do While I'm Waiting?

The previous sections suggest a substantial research agenda that will eventually

bear fruit for managers. The question naturally arises, what should managers do

while they are waiting for this research?

Allowing that we still have much to learn, it seems clear that managers should

continue to track financial measures such as sales and profits. Publicly-traded

finns are required to report these measures, and internally, one is more likely to

receive budgets from financially-oriented managers if one can show previous

financial success.

Beyond this, I believe satisfaction and loyalty measurement are the areas in

which most managers should concentrate in the near tenn. Satisfaction assesses

customer perceptions of the finn's offerings, while loyalty tracks actual customer

purchasing behaviour. Between these two measures, finns should get at least a

rough indication of competitive strengths and weaknesses and future financial

return on marketing efforts.

Satisfaction should be assessed relative to customers' satisfaction with

competing products. Rather than overall satisfaction, finns should measure

satisfaction with each of the different attributes/benefits customers value. A

weighted sum of these items, based on the importance customers place onattributes, will produce a more reliable composite than simple overall items, and

should also identify competitive strengths and weaknesses in the finn's offerings.

One fiml I have worked with grades customer satisfaction (A, B, C, etc.)

depending on how its customer satisfaction scores compare to the scores of

competitors. Piercy (1997) has a number of helpful suggestions on how to

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Marketing Performance Measures 727

measure and use customer satisfaction within the organization.

Regarding loyalty, surveys of repurchase intention can be beneficial, but,

where possible, finns should assess loyalty through a database of transactions.

For companies with many customers, a good summary measure of loyalty is the percentage of customers lost in a time period. For companies with fewer

accounts, salespeople often have good infonnation on loyalty. This cansometimes be quantified in terms of number of rebids lost Other transaction-

based elements of a loyalty constmct might include frequency, recency, andamount of purchase, and breadth of purchase in a finn's line.

For both of these measures it is critical to compare the summary measures totwo referents. First, what are the trends over time in customer satisfaction and

loyalty? As Dickson (1997, p. 12) observes, the change or "delta" in measures is

often far more infonnative in tenns of managing marketing than looking atmeasures on a stand-alone basis. Second, each of these measures should be

broken out by market segment Averages taken across segments can mask

significant differences in the threats and opportunities facing managers. For agiven market segment, then, one would hope to see a chart or table with fournumbers measured over time: sales, profit, relative customer satisfaction, andcustomer loyalty. These, in tum, can identify areas for further research or

marketing efforts.

Conclusion

This paper has attempted to layout what we know about the history and

interrelationships among key marketing measures. The three historical trendsidentified - toward non-financial output measures, marketing input measures,and multiple measures - have improved our understanding of marketing perfomlance. The challenge left for further research is to identify the few good

leading indicators that managers can track for the future.

Acknowledgments

The history portion of this paper benefited from comments on a paper presented

at the, 1998 Conference on Business Perfonnance Measurement at CambridgeUniversity. This paper has also benefited from the comments of two anonymous

reviewers.

References

Aaker, David A and Jacobson, Robert (1994), 'The Financial Information

Content of Perceived Quality", ]oumal of Marketing Research, 31, May, 191-

201.

Ambler, Tim and Barwise, Patrick (1998), "The trouble with brand valuation",

The ]oumal of Brand Management 5, 5, 367-377.Ambler, Tim and Kokkinaki, Flora (1997), "Measures of Marketing Success",

Down




19/23

728 Bntce H. Clark

Joumal of Marketing Management 13,665-678.Ambler, Tim and Kokkinaki, Flora (1998), "Marketing Perfom1ance

Measurement: Which Way is Up?", In: AD. Neely and D.B. Waggoner, Eds.

Peifomwnce Measurement--Theory and Practice, Volume 1,31-38, Centre forBusiness Perfom1ance, Cambridge University,Cambridge, UK.

Anderson, Eugene W., Fomell, Claes and Rust, Roland T. (1997), "CustomerSatisfaction, Productivity and Profitability. Differences Between Goods andServices",Marketing Science, 16, 2, 129-145.

Anderson, Eugene W. and Sullivan, Mary W. (I 993), "The Antecedents andConsequences of Customer Satisfaction for Finns", Marketing Science, 12, 2,125-143.

Barwise, Patrick (I 993), "Brand equity: Snark or Boojum?" lntemational Joumal

ofResearch in Marketing, 10, 93-104.Baumgartner, Hans and Homburg, Christian (1996), "Applications of stntctural

equation modeling in marketing and consumer research: A review,lntemational Joumal ofResearch in Marketing, 13, 139-161.

Bhargava, Mukesh, Dubelaar, Chris and Ramaswami, Sridhar (1994), "ReconcilingDiverse Measures of Perfom1ance: A Conceptual Framework and Test of aMethodology", Joumal of Business Research, 31, 235-246.

Bonoma, Thomas V. (I985), The Marketing Edge: Making Strategies Work, FreePress, New York.

Bonoma, Thomas V. (1986), "Marketing Subversives", Harvard Business Review,64, November-December, 113-118.

Bonoma, Thomas V. and Clark, Bntce H. (1988), Marketing PeifonnanceAssessment, Harvard Business School Press, Boston.

Bonoma, Thomas V. and Crittenden, Victoria L. (1988), "Toward a Model ofMarketing Implementation", Sloan Management Review, 29, 2, 7-14.

Bomstein, Robert F. (I989), "Exposure and Affect: Overview and Meta-analysis of

Research, 1968-1987", Psychological Bulletin, 106, 265-289.Brownlie, Douglas (1993), ''The Marketing Audit: A Metrology and Explanation",

Marketing Intelligence and Planning, 11, 1,4-12.Brownlie, Douglas (1996), "Marketing AuditS and Auditing: Diagnosis Through

Intervention", Joumal of Marketing Management 12,99-112.Bucklin, Louis P. (I 978), Productivity in Marketing, American Marketing

Association, Chicago.

Buzzell, Robert D. and Chussil, Marc 1. (1985), "Managing for Tomorrow", Sloan

Management Review, 26,4,3-14.Buzzell, Robert D. and Gale, Bradley T. (1987), The PIMS Principles: Linking

Strategy to Peifomwnce, Free Press, New York

Churchill, Gilbert A (1979), "A Paradigm for Developing Better Measures ofMarketing Constntets", Joumal of Marketing Research 16, Febntary, 64-73.

Clark, Bruce H. (1999), "Managerial Perceptions of Marketing Perfonnance:Efficiency,Adaptability, Effectiveness, and Satisfaction", working paper, College

of Business Administration, Northeastern University.Day, George S. and Nedungadi, Prakash (1994), "Managerial Representations of

Down




20/23


Competitive Advantage",Journal of Marketing, 58, April, 31-44.Day, George S. and Fahey, Liam (1988), "Valuing Market Strategies", Journal of

Marketing, 52, 3, 45-57.

Deshpande, Rohit and Farley, John (1998a), "The Market Orientation ConstmctCorrelations, Culture, and Comprehensiveness", Journal of Market-Focused

Management 2, 3, 237-239.Deshpande, Rohit and Farley, John (1998b), "Measuring Market Orientation:

Generalization and Synthesis", Journal of Market-Focused Management 2, 3,213-232.

Diamantopoulos, A (1994), "Modelling with LISREL: A Guide for the

Uninitiated", Journal of Marketing Management 10, 105-136.Dick, Alan S. and Basu, Kunal (1994), "Customer Loyalty:Toward an Integrated

Conceptual Framework", Journal of tile Academy of Marketing Science, 22, 2,99-113.

Dickson, Peter R (1997), Marketing Management 2nd edn. The Dryden Press,Fort Worth, TX

Donaher, Peter J. and Mattson, Jan (1994), "Customer Satisfaction During the

Service DeliveryProcess", European Journal of Marketing, 28, 5, 5-16.Dunn, Mark G., Norburn, David and Birley, Sue (1994), "The Impact of

Organizational Values, Goals, and Climate on Marketing Effectiveness",

Journal ofBusiness Research, 30, 131-141.

Dmcker, Peter (1974), Management: Tasks, Responsibilities, Practices, Harperand Row,New York.

Fader, Peter S. and Schmittlein, David C. (1993), "Excess Behavioural Loyalty forHigh-share Brands: Deviations from the Dirichlet Model for Repeat

Purchasing", Journal of Marketing Research, 30, 4, 478-493.Feder, Robert A (1965), "How to Measure Marketing Perfonnance", Hmvard

Business Review, 43, May-June, 132-142.Fornell, Claes (1992), "A National Customer Satisfaction Barometer. The Swedish

Experience", Journal of Marketing, 56, 1, 6-21.

Fornell, Claes, Johnson, Michael D., Anderson, Eugene W., Cha, Jaesung, andBryant, Barbara Everitt (1996), "The American Customer Satisfaction Index:

Nature, Purpose, and Findings",Journal of Marketing, 60, 4, 7-18.Goodman, Sam R (1970), Techniques of Profitability Analysis, Wiley-

Interscience, New York.

Goodman, Sam R (1972), Tile Marl\.eting Controller, AMR International, NewYork.

Haigh, David (1998), "The future of brand value reporting", Brand Finance

Limited.

Halstead, Diane, Hartman, David and Schmidt Sandra L. (1994), "MultisourceEffects on the Satisfaction Fonnation Process", Journal of the Academy of

Marketing Science, 22, 2,114-129.Han, Jin K, Kim, Namwoon, and Srivastava, Rajendra K (1998), "Market

Orientation and Organizational Perfonnance: Is Innovation a Missing Link?"

Journal of Marketing, 62, 4, 30-45.

Down




21/23

730 Bruce H. Clark

Hauser, John R, Simester, Duncan I. and Wemerfelt, Birger (1994), "Customer

Satisfaction Incentives", Marketing Science, 13,4,327-350.Henderson, Bruce D. (1973), ''The Experience Curve Revisited: IV. The Growth

Share Matrix of the Product Portfolio", Boston Consulting Group, Boston.Jacobson, Robert (1988), "Distinguishing Among Competing Theories of the

Market Share Effect", ]oumal of Marketing, 52, 4, 68-80.Jaworski, Bernard]. and Kohli, Ajay K. (1993), "Market Orientation: Antecedents

and Consequences", ]oumal of Marketing, 57, 3,53-70.Jaworski, Bernard ]. and Kohli, Ajay K. (1996), "Market Orientation: Review,

Refinement, and Roadmap", ]oumal of Market-Focused Management 1, 119-135.

Jones, Thomas O. and Sasser, Earl W. (1995), 'Why Satisfied Customers Defect",

Harvard Business Review, 73, 6, 88-99.Kaplan, Robert S. and Norton, David P. (1992), ''The Balanced Scorecard-

Measures that Drive Perfomlance", Harvard Business Review, 70, 1,71-79.Keller, Kevin L. (1993), "Conceptualizing, Measuring, and Managing Customer-

Based Equity, ]oumal of Marketing, 57, 1, 1-22.Keller, Kevin L. (1998), Strategic Brand Management Prentice-Hall, Upper

Saddle River,NJ,USAKohli, Ajay K., and Jaworski, Bernard ]. (1990), "Market Orientation: The

Construct, Research Propositions, and Managerial Implications", ]oumal of

Marketing, 54, 2, 1-18.Kohli, Ajay K, Jaworski, Bernard ]., and Kumar, Ajith (1993), "MARKOR A

Measure of Market Orientation", ]oumal of Marketing Research 30, November, 467-477.

Kotler, Philip (1977), "From Sales Obsession to Marketing Effectiveness",

Harvard Business Review, 55, 6, 67-75.Kotler, Philip, Gregor, William, and Rodgers, William (1977), ''The Marketing

Audit Comes of Age", Sloan Management Review, 18, 2, 25-43.Kumar, Nirnlalya, Stem, Louis W., and Achrol, Ravi S. (1992), "Assessing Reseller

Perfornlance from the Perspective of the Supplier", ]oumal of MarketingResearch, 29, May,238-253.

Lassar, Walfried, Mittal, Banwari, and Shamla, Arun (1995), "Measuring

Customer-Based Brand Equity", ]oumal ofConsumer Marketing, 12,4, 11-19.Lynch, John G. Jr. and Srull, Thomas K. (1982), "Memory and Attentional Factors

in Consumer Choice: Concepts and Research Methods", ]oumal ofConsumerResearch, 9, June, 18-37.

Marketing Science Institute (1998), "1998-2000 Research Priorities: A Guide to

MSI Research Programs and Procedures", Marketing Science Institute,

Cambridge, MA,USAMavrinac, Sarah and Siesfeld, Tony (1997), "Measures that Matter. An

Exploratory Investigation of Investors' Infomlation Needs and Value

Priorities", working paper, Ivey School of Business, University of Western

Ontario.

Meyer, Marshall W. (1998), "Finding Perfonnance: The New Discipline in

Down




22/23


Management", In: AD. Neely and D.B. Waggoner, Eds. Perfornwnce Measurement-Theory and Practice, Volume 1, xiv-xxi, Centre for BusinessPerfonnance, Cambridge University,Cambridge, UK

Miller, Danny (I 994), 'What Happens After Success: The Perils of Excellence", journal of Management Studies, 31, 3, 325-358.

Miller, George A (I 956), "The Magical Number Seven, Plus or Minus Two: Some

Limits on Our Capacity for Processing Infonllation", Psychological Review, 63,81-97.

Narver, John C. and Slater, Stanley F. (1990), 'The Effect of Market Orientation

on Business Profitability", journal of Marketing, 54, October, 20-35. Narver, John C. and Slater, Stanley F. (1998), "Additional Thoughts on the

Measurement of Market Orientation: A Comment on Deshpande and Farley,

journal of Market-Focused Management, 2, 3, 233-236.Oliva, Terence A, Oliver, Richard L., and MacMillan, Ian C. (1992), "A

Catastrophe Model for Developing Service Satisfaction Strategies", journal ofMarketing, 56, 3, 83-95.

Peterson, Robert A and Wilson, William R (1992), "Measuring CustomerSatisfaction: Fact and Artifact", Journal of tile Academy of Marketing Science,20, 1, 61-71.

Piercy, Nigel (1986), "Marketing Asset Accounting: Scope and Rationale",

European Journal of Marketing, 20, 1, 5-15.

Piercy, Nigel (I 997), Market-Led Strategic Change, Butterworth-Heinemann,Oxford.

Piercy, Nigel and Morgan, Neil (1995), "Customer Satisfaction Measurement and

Management A Processua] Analysis", Journal of Marketing Management 11,817-834.

Reichheld, Frederick E. (1994), "Loyalty and the renaissance of marketing",Marketing Management, 2, 4, 10-21.

Rothe, James T., Harvey, Michael G., and Jackson, Candice E. (1997), 'The

Marketing Audit Five Decades Later', Journal of Marketing Theory and

Practice, 5, Summer, 1-16.SeInes, Fred (1993), "An Examination of the Effect of Product PerfOnllanCe onBrand Reputation, Satisfaction and Loyalty", European journal of Marketing,27, 9, 19-35.

Sevin, Charles H. (I 965), Marketing Productivity Analysis, McGraw-Hili, NewYork

Sheth, Jag N. and Sisodia, Raj S. (1995), "Feeling the Heat", Marketing

Management, 4, 2, 8-23.Simon, Carol J. and Sullivan, Mary W. (1993), 'The Measurement and

Detenninants of Brand Equity: A Financial Approach", Marketing Science, 12,1,28-52.

Slaver, Stanley F. and Narver, John C. (1994), "Does Competitive Environment

Moderate the Market Orientation-Perfonnance Relationship?" Journal of

Marketing, 58, 1,46-55.Spreng, Richard A, MacKenzie, Scott 8., and Olshavsky, Richard W. (1996), "A

Down




23/23

732 Bruce H. Clark

Reexamination of the Detenninants of Customer Satisfaction", ]oumal of

Marketing, 60, 3, 15-32.

Spriggs, Mark T. (1994), "A Framework for More Valid Measures of Channel

Member Perfom1ance", ]oumal of Retailing, 70, 4, 327-343.Srivastava, Rajendra K, Shervani, Tasadduq A, and Fahey, Liam (1998), "Market-

based assets and shareholder value: A framework for analysis", ]oumal of

Marketing, 62, 1, 2-18.

Szymanski, David M., Bharadwaj, Sundar G., and Varadarajan, P. Rajan (1993),

"An Analysis of the Market Share-Profitability Relationship", ]oumal of

Marketing, 57, 3, 1-18.

Teas, R Kenneth (1993), "Expectations, Perfom1ance Evaluation, and

Consumers' Perceptions of Quality", ]oumal of Marketing, 57,4, 18-34.

Teas, R Kenneth and Pal an, Kay M. (1997), "The Realms of Scientific MeaningFramework for Constmcting Theoretically Meaningful Nominal Definitions of

Marketing Concepts", ]oumal of Marketing, 61, 2, 52-67.

Uncles, Mark, Ehrenberg, Andrew and Hammond, Kathy (1995), "Patlems of

Buyer Behaviour. Regularities, Models, and Extensions", Marketing Science,

14,3, G71-G78.

Voss, Glenn B., Parasuraman, A, and Grewal, Dhruv (1998), "The Roles of Price,

Perfonnance, and Expectations in Detem1ining Satisfaction in Service

Exchanges", ]oumal of Marketing, 62, 4, 46-61.

Walker, Orville C. and Ruekert, Robert W. (1987), "Marketing's Role in theImplementation of Business Strategies: A Critical Review and Conceptual

Framework", ]oumal of Marketing, 51, 3, 15-33.

Wrenn, Bruce (1997), ''The Market Orientation Construct: Measurement and

Scaling Issues", ]oumal of Marketing Theory and Practice, 5, Summer, 31-54.

Wyner, Gordon A (1996), "Customer valuation: Linking behaviour and

economics", Marketing Research, 8, 2, 36-38.

Vi, Youjae (1990), "A Critical Review of Customer Satisfaction", In: VA Zeithaml,

Ed. Review of Marketing 1990, 68-123, American Marketing Association,

Chicago.

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