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Marketing Metrics Use in a Transition Economy: TheCase of VietnamJohn U. Farley a , Scott Hoenig b , Donald R. Lehmann c & Hoang Thuy Nguyen da The Tuck School of Business , Dartmouth College , Hanover, NHb School of Economics and Business Sciences , University of the Witwatersrand ,Johannesburg, South Africac Graduate School of Business , Columbia University , New York, NYd Center for International Cooperation and Training , The University of Banking , Hanoi,VietnamPublished online: 11 Oct 2008.

To cite this article: John U. Farley , Scott Hoenig , Donald R. Lehmann & Hoang Thuy Nguyen (2008) MarketingMetrics Use in a Transition Economy: The Case of Vietnam, Journal of Global Marketing, 21:3, 179-190, DOI:10.1080/08911760802151811

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Marketing Metrics Use in a Transition Economy:The Case of Vietnam

John U. FarleyScott Hoenig

Donald R. LehmannHoang Thuy Nguyen

ABSTRACT. This article explores the use of marketing metrics by a sample of Vietnamese firms,providing an example of the use of marketing metrics in a “transition” economy as it grows andbecomes more market and marketing driven. The analysis reports usage frequency and then develops aset of “correlation chains” linking firm characteristics, metric use, and various indicators of performance.Vietnamese managers generally report that several types of metrics are used. Ownership structure andindustry also impact which metrics are utilized. An initial assessment of chains relating metric use tofirm performance indicates that the impact is complex and indirect.

KEYWORDS. Marketing metrics, ownership structure, market and competitive conditions, metricchains, firm performance, Vietnam

Assessing the productivity of marketing ingeneral and marketing metrics in particular hasbeen a critical focus in the U.S. (Clark, 1999),the UK (Ambler, 2003), and other developedeconomies, including France, Japan, and Ger-many (Barwise & Farley, 2004). In the last fourtwo-year research priority-setting cycles of theMarketing Science Institute, marketing produc-tivity and marketing metrics together have beenhigh priority topics, sometimes the highest. Sim-ilarly, a McKinsey survey of CEOs (Webster,Malter, & Ganesen, 2003) found that market-ing productivity/efficiency and growth were thetwo key jobs of marketing. Consequently, thereis increased need for marketing to demonstrate

John U. Farley is C. V. Starr Distinguished Senior Research Fellow at The Tuck School of Business,Dartmouth College, Hanover, NH. Scott Hoenig is affiliated with the School of Economics and BusinessSciences, University of the Witwatersrand, Johannesburg, South Africa. Donald R. Lehmann is the GeorgeE. Warren Professor of Marketing at the Graduate School of Business, Columbia University, New York,NY. Hoang Thuy Nguyen is Vice-Director of the Center for International Cooperation and Training, TheUniversity of Banking, Hanoi, Vietnam.

Address correspondence to John U. Farley, The Tuck School of Business, Dartmouth College, Hanover,NH 03755. E-mail: john.u.farley@dartmouth.edu

productivity, especially in difficult environmentslike those encountered in developing economiesand in economies transitioning from commandstructures to structures based on market forces.

Firms use metrics to manage key areas ofmarketing performance—customer satisfactionand retention, retailer and wholesaler satisfac-tion and retention, branding, advertising, andnew products. As well as providing valuable in-formation about performance in each area, met-ric use also provides a window into the types ofprocesses and capabilities a firm is likely to de-velop and employ. We analyze marketing metricsfrom a sample of 200 businesses from Vietnam,a developing and transitioning economy in the

Journal of Global Marketing, Vol. 21(3), 2008Available online at http://jgm.haworthpress.com

C© 2008 by The Haworth Press. All rights reserved.doi: 10.1080/08911760802151811 179

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180 JOURNAL OF GLOBAL MARKETING

Southeast Asian part of the world, which hasbeen relatively under-researched.

We address four research questions:

� RQ1: How often are different metricsused in the developing economy setting ofVietnam?

� RQ2: How does metric use relate to per-formance?

� RQ3: Can relatively simple correlationalchains be helpful for examining the com-plex relationships found among firm char-acteristics, metrics use, and performance?

� RQ4: How does metrics use in this settingvary with characteristics such as indus-try served, firm size, ownership structure(state-owned versus private), and marketcharacteristics such as industry growth andindustry competition?

BACKGROUND

Published studies to date have mostly con-sidered the relationships of metrics to financialperformance as well as the interrelationshipsamong the metrics themselves (Clark, 1999).Much of the thrust behind the focus on market-ing metrics comes from increasing pressure onmarketing managers by senior management tomake marketing “value relevant,” i.e., to linkit to financial performance. This is not a newissue (Kirpalani & Shapiro, 1973; Bonoma &Clark, 1988). The thrust is rooted in a desireby management to evaluate business on a sortof “balanced scorecard” (Kaplan & Norton,1992; Ambler & Kokkinaki, 1997; Bhargava,Dubelaar, & Ramaswami, 1994; Clark, 2001;Feder, 1965; Ittner, Larcker, & Randall, 2003).Much of the relevant work in the marketingarea is relatively recent and includes conceptualwork by Srivastava, Shervani, and Fahey (1997,1998) and Rust, Zahorik, and Keiningham(1995). Morgan, Clark, and Gooner (2002)present a theoretical rationale for the underlyingrelationship between metrics and performance.

Researchers have generally focused on partic-ular metrics such as: (1) customer lifetime value(Blattberg & Deighton, 1996; Blattberg, Getz,& Thomas, 2001; Gupta, Lehmann, & Stuart,

2004); (2) satisfaction (Fornell, 1992); (3) brandequity (Ailawadi, Neslin, & Lehmann, 2003;Keller, 1993; Park & Srinivasan, 1994; Simon& Sullivan, 1992; Aaker & Jacobson, 2001); (4)channel satisfaction (Lambert & Pohlem, 2001);and (5) new product success (Ambler & Kokki-naki, 1997; Clark, 2001; Feder, 1965). Ambler(2001, 2003) and Ambler and Kokkinaki (1997)provide an exhaustive set of metrics with partic-ular emphasis on the brand.

Substantial work has assessed the actualimpact of specific metrics on financial per-formance. These include satisfaction (Ander-son, Fornell, & Lehmann, 1994; Blattberg &Deighton, 1996), new product introductions(Chaney, Divinney, & Winer, 1991), and mar-keting orientation (Slater & Narver, 1992). Mar-keting capabilities have been critical factors indetermining company success ( Bhargava, Dube-laar, & Ramaswami, 1994; Day & Wensley,1988; Ittner, Larcker, & Randall, 2003). Impor-tantly, this result has been observed in the tran-sitional economies of Russia (Farley & Desh-pande, 2005) and China (Deshpande & Farley,2000), as well as in earlier work in Vietnam(Deshpande & Farley, 1999a). Similar resultswere found in South Africa (Farley, Hoenig,& Ismail, 2008), where economic transition istightly linked to massive changes in the nature ofthe labor force (Chipp, Farley, & Hoenig, 2006).

The Research Environment: Vietnamunder Doi Moi

Socialism is whatever brings happiness tothe people.

General No Nguyen Gap, 1995

We are not afraid of capitalist enterprises,but of not being able to supervise and con-trol them.

Party Leader Do Muoi, 1996

Like China (Deshpande & Farley, 2000), Viet-nam is emerging from central planning and intoa form of market socialism. In comparison tofive other diverse Asian countries (Deshpande,Farley, & Bowman 2004), Vietnam has a low

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Farley et al. 181

per-capita income, which places it among the40 “low income countries” in World Bank clas-sification. While Vietnam also has a relativelyrural population and low savings rate, it has arelatively high literacy rate.

Relatively rapid transformation of plannedeconomies into more market-orientedeconomies has, of course, depended onvisible changes in government policy on suchmatters as ownership of assets and controlof revenue streams. However, transformationhas also depended heavily on more subtle andless visible success of firms—old and new,private and public sector—in responding to thenew economic environment. Under “Doi Moi”(variously translated as renovation, change, andnewness, and related policies oriented towarda market economy), indications are that thecountry of 75 million may ultimately enjoyeconomic growth like that experienced by manyof its Asian neighbors (Hiebert, 1996).

Marketing in Vietnam

This study of marketing metrics extends otherwork on Vietnamese marketing managementthat did not explicitly deal with marketingmetrics or their impact. Deshpande and Farley(1999a) studied Vietnamese management inthe framework of a modified competing valuesmodel. Providing face validity for their results,the Vietnamese managers questioned believesin perseverance, protecting face, and tradition,as well as Confucian values involving groupand family (Tan & Farley, 1987). Vietnamesefirms which were more entrepreneurial, market-oriented, and innovative performed better(Deshpande & Farley, 1999b). Unlike the West,where innovativeness tends to be most importantin terms of performance (Deshpande, Farley, &Webster, 1993), market orientation was moreimportant in Vietnam. Despite the fact that gov-ernment corporations tend to be headquarteredin Hanoi, there were no significant differencesbetween firms in Hanoi and Ho Chi Minh City.Further, there were only minor differencesamong three types of firms (government, co-operative, and private), and no industry-relateddifferences—consistent with results in a dozenother countries (Deshpande & Farley, 2004a).

Deshpande and Farley (1999a) also found a veryhigh level of bureaucracy in Vietnam, althoughChina was about the same—probably residualfrom central economic planning. Vietnam alsohad significantly lower values for consensualculture (Japan was highest, as expected) andcompetitive corporate culture. Both marketorientation and innovativeness were average inVietnam. (China was higher in both, perhapsindicating that it is farther ahead in transition ofthe economy.)

METHOD

We surveyed managers from 200 differentstrategic business units (SBUs) in 76 memberfirms of the government-sponsored VietnameseAdvertising Association. The firms operate ina variety of industries and have a wide rangeof firm sizes, industry growth, and competitionlevels (Table 1). It was provided as part ofroutine data collection requested from mem-bers of the association, using printed surveyquestionnaires sent to and returned by eachmanager, with a virtually 100% response rate.Respondents were guaranteed anonymity forthemselves and their companies, and promiseda report of the results as an additional incentiveto participate in the study. Approximately halfof the firms were headquartered in the Northand half in the South. Overall, the firms arefairly small in terms of number of employees(most under 1000). Many are joint ventures orgovernment-related entities. The metrics usecharacteristics are shown in Table 2.

The survey consisted of four major compo-nents. First, we measured frequency of metricuse on 6-point scales ranging from never todaily. For this purpose, a list of metric measureswas chosen, partly based on the set in Amblerand Koklenaki (1997). These measures fall intofive major categories: customers, channel andretailers, brand, new products and services,and advertising and promotions. Second, werequested information regarding the 12-monthchange in performance related to each of the22 metrics using a 5-point scale. Third, firmperformance in term of various measures ofprofitability, market share, and growth with

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TABLE 1. Characteristics of 200 Respondents and Their Companies

Industry Title of Executive Number of Employees

Advertising 9 Associate Brand Manager 1 1–10 17Automobiles 4 Business Development Executive 2 11–25 29Banking 6 Business Officer 2 26–100 28Beverages 5 CEO 11 101–1000 69Building contractor 15 Chairman 1 1000+ 57Ceramics 6 Deputy Director of Marketing 1 OwnershipComputer 4 Deputy Director of Sales 1 Private organization 63Concrete 3 Executive Manager 5 Government department 48Consumer goods 19 Manager of Accounting 1 Wholly owned multinational 19Design architecture 1 Manager of Accounting & Finance 1 Joint venture (foreign firm 13

has majority ownership)Education 3 Manager of Strategy 1 Joint venture (Foreign firm 13

has minority ownership)Electrics 3 Marketing Executive 102 State-owned enterprise 40Garments 19 Marketing Manager 15 Unknown 4Home furniture & appliances 13 Manager of Production 2 Number of competitorsHotel 6 Planning Officer 1 1–3 10Logistic 17 President 4 4–5 17Motorbike 2 Sales Executive 41 6–9 41Plastics 2 Vice Director 1 10–19 53Real estate 9 Vice Director of Marketing 2 20+ 79Restaurant 9 Vice President 5 Industry growth (yearly)Services 11 ≤ 3% 3Textiles 16 4–5% 19Trading 15 6–9% 70Water 3 10–29% 89

30%+ 19

respect to competitors (Buzzell & Gale, 1987;Deshpande & Farley, 2004a) was collected,using 5-point scales. Finally, information wascollected regarding firm characteristics—size,ownership structure, and industry served, andindustry characteristics of market growth andcompetitive levels. These measures, shown inTable 2, were based on those in Deshpande,Farley, and Webster (1993, 2000) and onmeta-analysis (Capon, Farley, & Hoenig, 1990,1996), which outlined that these are the metricsmost commonly used to measure performance.

RESULTS

Use of Metrics

Table 2 outlines the metrics used by Viet-namese firms on at least a yearly basis. Morethan half of the firms used at least one met-ric from each metric group—new product,customer, channel, branding, and advertising

metrics. This indicates an active interest in mon-itoring marketing performance. It is interestingto note that the more traditional marketing met-rics (channels, advertising, and new products)are used the most. The more recently developedmetrics, which involve more intangible assetssuch as lifetime customer value and brand eq-uity, are used much less.

Patterns of Metrics and Performance

Earlier work relating metrics to performance(Barwise & Farley, 2004; Ambler, 2001; Desh-pande & Farley, 2004b) in various settings in-cludes Thailand, which found rather low mea-sures of fit in multiple regressions, but did findconsistent patterns of positive relationships be-tween measures of metric use and various mea-sures of performance. This was the case in Viet-nam as well. Of 66 correlations of use of the22 metrics and the three performance measures(growth, share, and profit):

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Farley et al. 183

TABLE 2. Marketing Metrics and Firm Performance Measures Used by Vietnamese Firms

Percent Using at LeastMarketing Metrics One in the Category Firm Performance3

New Product and Services Metrics1,2 85% ProfitNumber of new products launched Profit relative to industrySales from new products Sales growth in last 5 yearsNew product sales/R&D Sales growth relative to industry% launched considered innovations Share in most important marketROI on new products∗ Share across markets% profitable within specified time∗

Customer Metrics1,2 62% Share relative to industryCustomer satisfactionNumber of new customers acquiredProfit margin per customer or segment∗Sales by customer or segment∗Loyalty∗Lifetime customer value

Branding Metrics1,2 51%Brand price premium paid by final customersBrand recognition by final customersBrand image by final customers∗

Channel Metrics1,2 85%Number of new channels or retailers acquiredChannel satisfactionProfit margin per channel and retailer∗Loyalty (retention rate)∗

Advertising and Promotion Metrics1,2 81%Attitudes towards product/service purchaseAdvertising or promotion to sales ratioAdvertising or promotion awareness

Note. 1Metrics frequency of measurement used 6-point scale ranging from 0 = never to 5 = daily.2Metrics performance change over 12 months used 5-point scale ranging from 1 = significant decrease to 5 = significant increase in thelast 12 months.3Performance measurements used 5-point scale. All appear in correlational chains discussed later.∗Metric does not appear in correlation chains discussed later.

� 7 are positive and significantly differentfrom zero, ranging from 0.14 to 0.20;

� 49 are positive but not significantly differ-ent from zero, ranging from 0.00 to 0.13;

� 10 are negative but not significantly differ-ent from zero, ranging from –0.01 to –0.12;and

� none are negative and significantly differ-ent from zero.

Based on a sign test of randomness, there are sig-nificantly more positive relationships and signif-icantly fewer negative relationships than wouldoccur by chance.

Metrics Chains as an InteractionMechanism

The relatively noisy patterns of the correla-tions indicate some characteristics that hindermultivariate analysis. First, respective goodness-of-fit measures (R2) in the three multiple regres-sions relating each performance measure to all ofthe metrics are relatively small (profit R2 = 0.17,sales growth R2 = 0.16, and market share R2 =0.16). Factor analysis of the 22 measures of met-ric use did not show systematic loading patternssimilar to the five groupings of the metric mea-sures shown in Table 2. The factor scores for theeight-factor model had very low goodness-of-fit

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184 JOURNAL OF GLOBAL MARKETING

measures in regressions on performance (profitR2 = 0.03, sales growth R2 = 0.08, and marketshare R2 = 0.03).

Based on these results, we can see thatmerely measuring, say, sales from new productsis unlikely to directly and significantly increaseROI. To help uncover the structure of metric use-performance relationships, we created a series offive “metric chains,” one for each group of met-rics: new products, customer metrics, branding,channel metrics and advertising, and promotion.The logic of such a “chain of effects” is laidout in Rust, Ambler, Carpenter, Kumar andSrivastava (2004). Various firm characteristics,including industry growth, number of competi-tors, and state vs. private ownership, are linkedto use of particular metrics, then to intermediateoutcomes (generation of new customers, forexample), and finally to overall measures of firmperformance (profitability, growth in sales, andmarket share). We only report links included ineach chain that have significant Pearson correla-tions. Metrics whose use do not have a significantcorrelation on at least one link are excludedfrom the chains. The items used in at least oneof the chains are indicated Table 2. The chainsin Figure 1 through Figure 5 can be viewed asa kind of “alpha version” of an attempt to par-simoniously convert a “metrics dashboard” ofthe sort described by Kaplan and Norton (1992)into a performance chain of the type describedby Ambler (2003) and Lehmann and Reibstein(2006).

The New Products Metrics Chain: Bewareof Competitors

Competition drives new product metric use(Figure 1), which in turn drives new prod-uct launches, the percent of new products thatare profitable, and new product sales, and, ofcourse, means lower shares. By contrast, indus-try growth leads to lower use of new productmetrics, possibly because there is less pressureto develop new products. Metrics use increasesnew product launches and the percent of prod-ucts that are successful. However, new productmetrics are not positively related to overall prof-its or share, suggesting a “necessity is the motherof new products” explanation. In other words,

FIGURE 1. New Products Chain

srotitepmoC fo rebmuNtnedecetnA

Metrics Use

-.19-.32

New Product Metrics Use

.23

New Products Launched

.14 .14

.19

-.12

.15 .17 -.16

Firm Growth Last Profitable Profit Relative Share Share

Performance 5 Years Business to Industry Most Across

Important Markets

Market

Intermediate Results

Industry Growth

-.13

% Profitable

.16

NewProduct Sales

-.21

NewProduct Sales/R&D

-.19

new product metric use helps performance but islikely to occur when performance is hamperedby competition.

The Customer Metrics Chain: MarketInformation in Action

Customer-type metrics (Figure 2) which relyon internal data (primarily customer records) andexternal data (primarily market research) are reg-ularly used by marketers. Private firms are morelikely to use such metrics, probably reflecting ahigher level of market orientation.

The negative relationship between industrygrowth and customer metrics use (similar to thatfor the new product metrics) probably reflectsthe fact that as long as the firm is growing, pres-sure for analysis may be low. Customer met-rics use is positively related to both customersatisfaction and customer acquisition. Customer

FIGURE 2. Customer Metrics Chain

Industry Growth

-.23

Customer Metrics Use

.21.19

CustomerSatisfaction

Number ofNew Customers

-.18

-.25 -.21

.14 .13.21 .17 .19

Antecedent

Metrics Use

Intermediate Results

Change in:

Firm Performance

Market Share inMost ImportantMarket

Market ShareAcrossMarkets

Profitable Business Sales Growth

GrowthLast 5 Years

Private Ownership

.22

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Farley et al. 185

FIGURE 3. Branding Metrics Chain

Antecedent Number of Competitors

Metrics Use Branding Metrics Use

.25

Brand Recognition Price Premium

.15

.12 .14

Firm Growth Last Share Profitable Share in Share

Performance 5 Years Relative Business Most Important Across

to Industry Market Markets

Intermediate Results

Change in:

-.32 -.19.19

satisfaction in turn relates positively to profitsbut not share. A non-monotonic relationship be-tween share and satisfaction was found by For-nell (1992). More new customers relates posi-tively to both profit and sales growth, reflectingthe truism that customers are the key to businesssuccess. Overall, metrics users have higher lev-els of satisfaction and greater customer loyalty—particularly among new customers.

The Branding Metrics Chain: Equityof Brands

The considerable effort focused on brand eq-uity over the past two decades (Keller, 1993;Keller & Lehmann, 2006) suggests that thereis a metrics link between branding and perfor-mance. Having more competitors is related togreater use of brand metrics (Figure 3), similarto the case for customer and new product met-rics. The use of brand metrics in turn relatespositively to brand recognition. Recognition re-lates to relative share and price premiums relateto a more profitable business.

The Channels Metrics Chain: Necessity isthe Mother of Metrics Use

Having more competitors is related to the useof channel metrics (Figure 4). Channel metricsuse in turn is positively related to channel satis-faction. The fact that it is negatively related tosales growth again suggests metrics use is lowerwhen things are going well. Having more com-petitors is by definition related to lesser share.

FIGURE 4. Channel Metrics Chain

srotitepmoC fo rebmuNtnedecetnA

Metrics Use Channel Metrics Use

.28

Channel Satisfaction

.20

erahSerahS elbatiforP selaS tsaL htworGmriF

Performance 5 Years Growth Business Most Across

Important Markets

Market

Intermediate Results

Change in:

-.16-.17-.32 -.19

Number of

New Channels

-.13

-.19

The Advertising Metrics Chain: AnOutlier

Private firms are more likely to use advertisingmetrics (Figure 5). However, unlike the generalpatterns in the other figures, use of advertisingmetrics has no relationship with logical conse-quences of advertising—advertising awareness,for example. Their use is also greater when prof-its are lower, reinforcing a “necessity”-basedmotivation.

Firm Characteristics and Metrics Use

In most cases of an economy in transition to amore market-driven economic structure (includ-ing Vietnam), the transition involves developinga mixture of ownership types. These may includea public sector group made up of state-ownedfirms and government departments, a private sec-tor group that is owned locally or by multina-tional firms, and some mixture of foreign and

FIGURE 5. Advertising Metrics Chain

Antecedent

Metrics Use

Advertising

Metrics Use

Awareness

-.12

Firm Growth Profits Relative Share in Most Profitable

Performance Last 5 Years to Industry Important Market Business

Intermediate Results

-.19 .13

Advertising &Promotion /SalesAttitude

-.19 -.12

PrivateOwnership

.12

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186 JOURNAL OF GLOBAL MARKETING

local ownership. Different ownership structuresmay lead to emphasis on different metrics. Otherfactors such as firm size or industry participationmay also have an impact on the use of metrics,as they can impact the amount and type of re-sources available to a firm (Barney, 1991), whichcan in turn impact firm operation and subsequentperformance. Larger firms generally have accessto a broader array of resources, both internallyand externally, and this could allow for a broaderuse of internal monitoring mechanisms. In addi-tion, different types of industry-standards andsupport-service norms can exist, and these cancause variations in factors such as metrics use.We examine the links between firm and indus-try characteristics and metrics using a series ofMANOVAs.

Ownership

A MANOVA of ownership (Table 3) showssome differences in metrics use in the Viet-namese firms based on ownership, but use ofonly five of the 22 individual metrics are sig-nificantly different by ownership. In all fivecases, foreign-owned firms use metrics more fre-quently. An analogous pattern of differences inthe use of HRM practices between state corpo-rations and foreign subsidiaries has been foundin China (Farley, Hoenig, & Yang, 2002).

Firm Size

With respect to size, the MANOVA showslittle relationship of size to the use of metrics,with only two of the 22 metrics showing anysignificant differences. While this result may besurprising, Capon, Farley, and Hoenig (1996)also found that firm size had little systematicimpact on various measures of firm performancefor large U.S. firms.

Industry

Ten of 22 uses of metrics indicators differsignificantly by industry. These include some ineach of the five categories of metrics, indicatingthat the external industry factors (competitionand customers) may be a significant driver ofthe types of information firms use to monitortheir operations.

DISCUSSION

More innovative and more marketing-oriented firms in Vietnam perform better—a re-sult found in other developing markets includingRussia, China, and India, as well as in somedeveloped markets (the U.S., Japan, Britain,France, and Germany).

There was little indication that marketingmanagers of firms in transition economiesin general and in Vietnam in particular facethe sort of pressure that is common on mar-keting managers in industrial economies to“justify” marketing (Barwise & Farley, 2005)with metrics. Nonetheless, most managers inVietnamese firms appear to have embraced theuse of marketing metrics as management tools.Up to 22 different metric measures were foundto be used regularly by managers to monitortheir marketing operations (RQ1). Further,use of metrics has a systematic (althoughnot necessarily direct or universal) link tomultiple measures of performance in Vietnam(RQ2). Simple chains help capture useful anddiscernable patterns among antecedents, metricsuse, and performance (RQ3). In terms of firmcharacteristics (RQ4), competition (particularlythe number of competitors), type of industry,and growth play an important role.

While each of the correlational metric chainshad specific characteristics, there are some com-mon features:

Competition matters. Competition has a con-sistent negative relationship with performance—a fact which produces some face validity for thegeneral approach. More related to the main topicof this paper, competition tends to be positivelyrelated to the use of metrics. Combined with thelink to sales growth, this suggests that, to someextent, metrics use is a reaction to a difficultbusiness environment.

Advertising metrics use may not be critical.The advertising results are ambiguous at best.Even though advertising has tended to be almostsynonymous with marketing in the relativelyshort history of the transition economies (Batra,1999), there were no clear antecedents orconsequences of the use of advertising metrics.This suggests the possibility that some firms

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TABLE 3. Metric Use by Firm Ownership, Size, and Industry

P-level for Overall ANOVA Number of Metrics Individual MetricTest of Equality (Based Significantly Different Significantlyon Wilks Lambda) over Ownership Types Different Highest Use by

Ownership type(private,government, orforeign-owned)

.02∗ (Wilks lambda = .63) 5 of 22 Number of newcustomers

Sales per customerCustomer loyaltyBrand recognition %

of productslaunched

Foreign-ownedForeign-ownedForeign-ownedForeign-ownedPrivate

Size (5-point scalebased on numberof employees)

.25 (Wilks lambda = .50) 2 of 22 Lifetime customervalue

Channel loyalty

Medium-sizedMedium-sized

Industry (24categories basedon listing inTable 1)

.00∗ (Wilks lambda = .00) 10 of 22 Customersatisfaction

Number of newcustomers

Sales per customerChannel satisfactionChannel loyaltyLifetime customer

valueBrand price

premiumNew product sales

% of newproductslaunched

Advertising/sales

Plastics, hotelsHome furnishings and

appliancesEducation, building,

advertisingEducationMotorbikesCeramics, garmentsPlastics, motorbikesEducation, ceramics,

buildingEducation, motorbikesConsumer goods

Note. ∗Significantly different, p = .05.

are more concerned about advertising than theyneed to be.

The metrics relationships are subtle. While allof the correlations discussed in detail earlier aresignificant, they are consistently in the range of.1 to .3 in absolute value. While it is important toremember that this application is in a transitioneconomy, this suggests that the relationships arerelatively weak, i.e., there is no “silver bullet”metric whose use guarantees success.

Traditional industrial organization researchconsidering more developed economies has of-ten focused on relationships among industrygrowth, competitive levels, and type of firm own-ership. In these settings, it has been found thathigher growth and less competition, along withprivate ownership, will generally lead to higherprofitability (Capon, Farley, & Hoenig, 1990). Itis not a coincidence that we have found similarrelationships in Vietnam.

Explanations for the exact mechanism of howthese relationships hold are still the subject ofhigh inquiry and range across various formsof structural, strategic, and organization culturalalignment. The setting of Vietnam provides uswith a different structural example, i.e., one ofan economy changing quickly in these charac-teristics, which have a wide range of variabilityacross industries. Here we can study the interac-tion of one particular mechanism, which is theuse of marketing metrics, as a moderator mech-anism that enhances performance.

Considering the specific results for this devel-oping country setting, we see:

1. The impact of metrics does not appear tobe direct;

2. The use of the metrics is impacted by theclassical industry characteristics of marketcompetition, growth, and ownership; and

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3. Somehow management has recognizedthe need to use metrics in order to gaincompetitive advantage.

Further Research and Limitations

While use of metrics appears to increase aseconomies advance, we still do not fully under-stand the process of adoption needed as levelsof competition, growth, and ownership changerapidly in a setting such as this. For example,which metrics are more important to use in earlygrowth stages, and which ones need to be im-plemented later as growth factors set in? Ques-tions such as this may be key to differentiatingthe needs of management focus in developingcountries.

Even though the metric chain methodologyused here meets the stated goal of parsimony,more sophisticated models should be tested. Un-fortunately, our experiments with multivariatemethods indicated that the relatively low cor-relations caused estimation problems. Issues ofdirection of causality (endogeneity) and omit-ted variable bias, therefore, still need to beexamined.

The analysis of performance in this article hasfocused on mean values of performance mea-sures and of metrics. Some research suggeststhat formal planning (Capon, Farley, & Hulbert,1988) and some types of marketing decisionsmay also impact the variance of returns (e.g.,cash flows; Srivastava, Shevani, & Fahey, 1997).It may be that metrics use has more impact onthe variance of performance than on its mean.

This study is of one country at one point oftime. While the results of the exercises of creat-ing the metrics chains show some promise, theseresults need replication in time and place (Bar-wise & Farley, 2004, 2005). The role of meta-analysis of the growing literature on metricsshould be examined (Farley & Kopalle, 2006).

Finally, like much of the research on market-ing metrics, the results are based on self-reportsand questionnaires. Use of other methods, suchas focus groups, might enrich the results and pro-vide more insights into the processes that governprivate and public firms in transition economies.Similarly, objective measures (for example, con-tent analysis of annual reports or government

oversight proceedings when they become pub-licly available) might add additional insights.Hopefully, the results reported here, while notconclusive, will be sufficient to encourage fur-ther research in these directions.

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