do services marketers' success measures match their strategies?

Journal of Services MarketingEmerald Article: Do services marketers' success measures match their strategies?Michael T. Manion, Joseph Cherian

Article information:

To cite this document: Michael T. Manion, Joseph Cherian, (2009),"Do services marketers' success measures match their strategies?", Journal of Services Marketing, Vol. 23 Iss: 7 pp. 476 - 486

Permanent link to this document: http://dx.doi.org/10.1108/08876040910995266

Downloaded on: 12-10-2012

References: This document contains references to 36 other documents

To copy this document: [email protected]

Access to this document was granted through an Emerald subscription provided by RICE UNIVERSITY

For Authors: If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service. Information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information.

About Emerald www.emeraldinsight.comWith over forty years' experience, Emerald Group Publishing is a leading independent publisher of global research with impact in business, society, public policy and education. In total, Emerald publishes over 275 journals and more than 130 book series, as well as an extensive range of online products and services. Emerald is both COUNTER 3 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation.

*Related content and download information correct at time of download.

Do services marketers’ success measures matchtheir strategies?

Michael T. Manion

School of Business & Technology, University of Wisconsin-Parkside, Kenosha, Wisconsin, USA, and

Joseph CherianLiautaud Graduate School of Business, University of Illinois at Chicago, Chicago, Illinois, USA

AbstractPurpose – The paper seeks to show that the strategic types of service marketers (e.g. Prospectors, Defenders or Analyzers) match the types of successmeasures that they use to evaluate new services.Design/methodology/approach – A theory is developed to show why service marketers of different strategic types use different success measuresfor the evaluation of new services. Using responses from 202 financial services marketers, strategic types are shown to relate in theoretically expectedways with the importance ratings of the categorized success measures.Findings – Notable relationships among strategic types and their success measure are identified. Prospectors, for example, attach greater importanceto growth performance measures, consistent with the growth orientation of their service development programs. Defenders, on the other hand, attachmore importance than Prospectors to efficiency performance measures, which relate to their programs’ efficiency orientation. Analyzers, interestingly,place more emphasis on objectives-based performance measures, including strategic fit, than Prospectors.Research limitations/implications – The sampling frame purposely contains only US financial services firms; as such, future research may build uponthis single-industry, single-country study.Practical implications – Academic success literature generally disregards the strategic types of respondents in measuring the success of servicedevelopment programs. Practitioners, however, seek performance measures that are consistent with their firm’s business strategy. This study provides acategorization of the most important success measures as appropriate to different strategic types.Originality/value – The service success literature has often dealt with the question of “what causes success?” and has rarely confronted, head-on,the question of “what is success?”. This paper addresses this critical research gap.

Keywords Services marketing, Financial services, Marketing strategy, Performance measures

Paper type Research paper

An executive summary for managers and executivereaders can be found at the end of this article.

Introduction

Services marketers (SMs) care about the success of theirservice development programs (Fitzsimmons andFitzsimmons, 2000) and are increasingly aware that theirorganizational performance relates to the success of their newservices programs (Avlonitis et al., 2001; Easingwood andStorey, 1993; Edgett, 1994; Johne, 1999; Johne and Storey,1998; Lievens and Moenart, 2000; Martin and Horne, 1993;Syson and Perks, 2004; Vermeulen, 2004). Their servicedevelopment (SD) programs include a variety of SD projects,which may range from the most innovative in the world to themost mundane of modifications. In the case of bankingservices, this range may be seen in leading-edge innovationsthat enable customers to make secure funds transferswirelessly to cost-reducing conversions from paper to

electronic statement delivery. As such, SD programs are adirect expression of SMs’, strategic type and are directed atproducing very different types of success. This leads to thequestion of whether all SMs should use the same successmeasures for their SD programs, as the success literatureseems to do. Shouldn’t SMs’ strategic types drive which SDprogram performance measures they consider moreimportant?Our study theorizes that the SMs’ strategic type should

significantly affect which SD program success measures theyconsider more important, because each type seeks to succeedin different ways. This theory is grounded in researchconducted by the Product Development and ManagementAssociation (PDMA), an association of product developmentpractitioners and academics (Griffin and Page, 1996). ThePDMA research suggested, for example, that Prospectors, thestrategic type most likely to introduce new products to newmarkets, should place greater importance on programperformance measures that are consistent with theirorientation toward growth. Defenders, on the other hand,the strategic type most likely to maintain stable service linesfor existing markets, should place greater importance onperformance measures that are consistent with theirorientation toward efficiency.

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

www.emeraldinsight.com/0887-6045.htm

Journal of Services Marketing

23/7 (2009) 476–486

q Emerald Group Publishing Limited [ISSN 0887-6045]

[DOI 10.1108/08876040910995266]

Received: January 2007Revised: August 2007Accepted: September 2007

476

Although the PDMA study was not specifically formulatedfor the services industries, our expert interviews with servicesmarketers indicated that each of the specific strategy andperformance concepts cataloged is equally appropriate andapplicable in the services context. Furthermore, numerousstudies support the notion that firm strategy has a significantimpact on the marketing and development of services (Fox-Wolfgramm et al., 1998; James and Hatten, 1995; McKeeet al., 1989; Smith and Fischbacher, 2005).The issue of different performance measures for different

strategic types is especially critical because SD successliterature has largely used the same measures for differenttypes. Edgett (1994) and Martin and Horne (1993) use onecommon performance measure – the success rate of projectsattempted – for all types of respondents, though this metricmay not be appropriate for the more risk-taking type SMs.Storey and Easingwood (1998) and Easingwood and Storey(1993) use another common measure – future opportunitiesor market standing – for all types of respondents, though itmay not be appropriate for less market-sensitive type SMs.The logic that performance measures for programs shouldmatch SM strategy is inescapable (Griffin and Page, 1996).The orientation of SD programs, constituting the collectiveefforts of SMs in executing their market entry and service linestrategies, should differ by their strategic types. To the point,if SMs have different SD program orientations, based on theirstrategic type, shouldn’t the SD success literature usedifferent measures for different strategic types?Hence the principal domain of our study is the strategy of

SMs and the performance measures of their SD programs.The research question addressed in this paper is whetherstrategic type affects the perceived importance to SMs ofdifferent SD program performance measures. While SMsincreasingly realize the necessity to relate their SD efforts totheir business strategies, the literature to date provides littleguidance on which SD performance measures should beemphasized to determine success. Therefore, our study of SDprogram measures is intended to be current and relevant bothto service industry professionals and for academic researchers.We advance the theoretical question in the context of financialservices marketed to corporate customers by SMs and findsupport.We propose that the specific study of SM strategy and SD

program performance measurement deserves greateracademic attention than it has previously received. Weshould note that the new product and service developmentliterature is often presented without specific differentiation.And, while a limited number of studies focus on SD, thefindings for physical products are often found to be applicableto services (Storey and Easingwood, 1998). However, thoughthe study of service development often draws uponmanufacturing firms’ strategies and new productperformance measures, we must regard differences carefully.Because services providers may differ from productmanufacturers, we address specific questions to confirm theapplicability of firms’ strategic types and product successconcepts to our SM and SD program research. We proposethat academicians should apply those performance measures,which are consistent with SMs’ actual business strategies, inorder to accurately portray SD success.

Theory development

The following sections address three specific questions:1 Do services marketers vary by strategic type?

2 Do services marketers’ strategic types relate to their SDprogram orientations?

3 Does the perceived importance of SD performancemeasures vary by program orientation?

Confirming answers to these questions, we can proceed to testwhether SD program performance measures vary by strategictype. Following this introductory discussion, we describe thehypotheses, methods, findings, and conclusions.

Services marketers’ strategic typesFirst, do services marketers vary by strategic type? Clearly, theMiles and Snow (1978, 1994) (MS) strategic typologyapplies. Miles and Snow (1978, 1994) state that four strategictypes can describe firms’ strategies. Though originallydeveloped for manufacturing firms, the MS typology hasbeen applied to market and product development strategiesfor service industries generally, and often to financial servicesfirms. SMs’ strategic types determine the elements of successof their development programs (Slater and Mohr, 2006). TheMS concepts have proven valid for financial servicesmarketers (Fox-Wolfgramm et al., 1998; McDaniel andKolari, 1987; McKee et al., 1989). The Appendix providesthe full survey text for the four MS strategic types and the tenSD performance measures included in this study.The MS typology includes four strategic types (i.e.

Prospectors, Defenders, Analyzers, and Reactors), which aredefined by their core business problems. Within the MSstrategic typology, the first three types (Prospectors,Analyzers, and Defenders) are considered stable in theiradherence to their strategies. Prospectors, the first strategictype, seek to be the “first-in” to new markets with new servicelines. According to the MS typology, Prospectors’ corebusiness problem is “seeking new opportunities in newmarkets”. These “first movers” seize opportunities, take risks,and expect to reap monopolistic profits (Lamkin, 1988).Prospectors respond to early market signals, continually turnover their service lines, and frequently develop services inorder to produce new revenues and profits (Narver et al.,2004).Defenders, the second strategic type, seek to maintain a

secure niche in narrower service and market domains, servingonly specific customer types with a limited range of services.According to the MS typology, the Defender’s core businessproblem is to “seal off” their markets by efficient productionof low cost services. They penetrate existing markets with highquality, superior services, and greater value. They rely onexperienced management teams and do not attempt initiativesthat lack a high likelihood of success. The PDMA researchsuggests that Defenders, more than Prospectors, will pursuedevelopment programs with an efficiency orientation.Analyzers, the third stable strategic type in the MS

typology, are more likely to exhibit two distinct behaviors:1 developing new services for existing customer segments;

and2 marketing existing services to new customer segments.

Their core business problem is maintaining “balance”, intheir market strategy, between leadership and penetrationand, in their services strategy, between promising and stablelines. They tend to monitor new markets and to be the “earlyfollowers”; that is, they are often “second in” behindProspectors, but offer enhanced services. However, they arerarely “first in” to a new market with new services. ThePDMA research suggests that Analyzers, when compared to

Do services marketers’ success measures match their strategies?

Michael T. Manion and Joseph Cherian


Volume 23 · Number 7 · 2009 · 476–486

477

Prospectors, will pursue development programs with anefficiency orientation.The typology includes a fourth type, Reactors, who are

considered unstable in their adherence to their strategies; thisis because it is difficult to specify a priori what they react to.Therefore, consistent with most research using the MStypology (Hambrick, 1984; James and Hatten, 1995) weinclude the Reactor type in our results, but do not conductdetailed analysis or attempt to draw conclusions regardingtheir organizational characteristics.In a recent review of the value of the MS typology,

Hambrick (2003) framed the contribution as having a“profound effect” on several disciplines and guiding scholarsand consultants in their practice. Furthermore, although their“ideas have stimulated an abundance of research and practicalinsight over more than two decades, scholars are still drawn tothem today” (p. 116). Numerous studies over two decadeshave affirmed the validity and reliability of the MS strategictypology (DeSarbo et al., 2005; Hambrick, 1984; James andHatten, 1995). Therefore, we used the MS strategic typologyto frame and derive our propositions regarding the perceivedimportance of success measures in SD.

Services marketers’ strategy and SD program

orientationSecond, do SMs’ strategic types relate to their SD programorientations? The firm characteristics provided in the MStypology may be readily interpreted into SD programorientations. In the terms of the MS typology, Prospectors’core business problem is seeking new opportunities in newmarkets, so they are continuously “re-positioning” forchanging markets and technologies. They compete byresponding to early market signals, replacing revenues frommaturing services, and earning monopolistic profits as the“first in”. The PDMA research suggests that Prospectors,more than other strategic types, will pursue developmentprograms with a growth orientation.On the other hand, Defenders’ core business problem is to

“seal off” their markets by maintaining efficient,technologically stable environments. They compete byrelying on management experience, employing rigorousscreening protocols, planning for longer service life cycles,and maximizing returns on larger capital investments.Analyzers’ programs are also, assumedly, more efficiency-oriented than Prospectors.Therefore, the MS typology descriptions indicate that

Prospectors will have more growth-oriented SD programs. Onthe other hand, Defenders, and to some degree Analyzers, willhave more efficiency-oriented SD programs. We have noexpectations of Reactors, as the unstable “reactive” type.

SD program orientation and perceived importance of

performance measuresThird, does the perceived importance of performancemeasures vary by SD program orientation? We find supportthat program performance measures are consistent with eithergrowth or efficiency program orientations. To begin, weconfirm that SMs do have development program performancemeasures, and that these vary in perceived importance tothem. Further, we find that the measures reported in thePDMA survey are consistent with those found to be in use infinancial services (Storey and Kelly, 2001).The PDMA research findings suggest a general hypothesis

that the perceived importance to SMs of the two different setsof performance measures varies by strategic type. The PDMA

research determines the perceived importance of performancemeasures by the expert opinions of its respondents, and oursurvey determines the perceived importance of those SDperformance measures to experts in services. While thePDMA research did not formally suggest a direct relationshipamong strategic types and the perceived importance of sets ofprogram performance measures, when combined with ourpreliminary expert interviews, we can suggest such a “biggerpicture”.We employ a well-recognized framework of program

performance measures for our analysis. This catalog ofmeasures was compiled and validated through a publishedsurveyof development practitioners and academics (Griffin andPage, 1996). The research includes eight measures that areconsidered most important and useful to members of theProductDevelopment andManagement Association (PDMA).These eight program performance measures, which areincluded among ten in our survey, are commonly used indevelopment research (Griffin, 1997; Griffin and Page, 1993;Hart and Craig, 1993; Page, 1993). The PDMA research alsoindicates that development managers and academics sharesimilar perceptions, if not precise common definitions, of theseprogram performance measures. Consistent with generalconclusions drawn by Griffin and Page (1996) about theireight performance measures, we add two global measures, –firm growth and firm efficiency. The resulting ten programmeasures are listed and defined in Table I.The PDMA research finds that firms associate different

performance measures with different strategy orientations.That is, some firms placed greater importance on the (three)performance measures consistent with a growth orientationand other firms placed greater importance on the (five)performance measures consistent with an efficiencyorientation. We interpret the PDMA research to indicatethat firms’ emphasis on different performance measures isconsistent with and because of their “type-induced” growth orefficiency strategies. We find through preliminary expertinterviews that SMs are able to rate the perceived importanceof measures on a scale, which facilitates operationalization ofthe variable. We also confirm that SMs understand thestrategy-based rationale for placing greater importance ondifferent program performance measures. We present thestrategy-based rationales for each program measure asdescribed by SMs in Table I.We use these program measures as the best foundation

available for our research, but we note that the measures havenot been tested empirically. Empirical research with these SDperformance measures can only advance the knowledgegained from the previous PDMA research. The concept of“importance” of performance measures is also introduced bythe PDMA research. The PDMA survey findings suggest astrong correlation between perceived importance and actualusefulness of measures (Griffin and Page, 1996). Therefore,we follow this line of thinking in our model and incorporateits usefulness in evaluating SD program success into theperceived importance of a program measure to the SM. ThePDMA research suggests that the perceived importance ofdevelopment measures varies among firms and ourpreliminary expert interviews confirm that the perceivedimportance of SD program measures does indeed vary amongSMs.The “bigger picture” is that the strategic types and the SD

program performance measures fit into an overall patternconsistent with program orientation. For example,Prospectors appear to place greater importance on growth-




Volume 23 · Number 7 · 2009 · 476–486

478

oriented measures of performance, while the two other typesplace greater importance on efficiency-oriented measures. Weexamine the findings of the PDMA research and observe thatthe respondents more often associate three growth-orientedmeasures with Prospectors and five efficiency-orientedmeasures with Defenders and Analyzers. Although thePDMA research does not formally suggest that businessstrategy affects the perceived importance of different sets ofSD program performance measures, we observed a clearrelationship in the findings.

Grounding theory in practiceGriffin and Page (1996) recommend that researchers in thedevelopment disciplines present theories to experiencedpractitioners in the field to ascertain concept validity beforeempirically testing. Therefore, before finalizing our researchmodel and hypotheses, we confirmed the PDMA researchfindings by means of preliminary interviews with industryexperts in services marketing and development. Preliminaryinterviews were held at a national conference in Chicago withten leading financial service providers and 12 corporatetreasury practitioners who are acknowledged thought leadersin the discipline. Each interviewee held a senior position intheir organization and had at least ten years of experience inthe industry. The unstructured interviews addressed theprogram performance measures and the proposed programorientations of services marketers.

The expert interviews supported the PDMA survey findingsthat three of our program measures are growth-oriented andfive are efficiency-oriented. More specifically, the expertsrationalized that the growth-oriented measures should bemore important to Prospectors given their core businessproblem of seeking new opportunities in new markets.Therefore, Prospectors’ strategic responses and the growthorientation of their SD programs determine that an importantset of performance measure will include the futureopportunities created, the new sales and new profitsgenerated. To this performance measurement set we addedthe fourth more global measure of firm growth.The SM experts further rationalized that the five efficiency-

oriented measures should be more important givenDefenders’ core business problem of “sealing off” theirmarket niches by maintaining efficient, technologically stableenvironments. Therefore, Defenders’ strategic responses totheir core problems and their efficiency-oriented SDprograms should determine that their more importantperformance measure factor will include strategic fit,management opinion, five-year objectives, success rate, andprogram return on investment (ROI). To this performancemeasurement set we added the sixth more global measure offirm efficiency.Further, the efficiency-oriented measures should be more

important for the Analyzers’ alternative strategies to be eithermarket “followers” with enhanced services or early marketentrantswithexisting service lines.Analyzers’programsarealso,

Table I Summary of program performance measures

Program orientations and performance

measures (Griffin and Page, 1996, p. 490)

Definitions of performance measures (Griffin

and Page, 1996, Appendix 2, p. 496)

Strategy-based rationales for two

orientations extracted from preliminary

expert interviewsa

Growth orientationFuture opportunities Degree to which today’s new products lead to

future opportunities

“Responding to early signals before competitors

see potential”

New sales Percentage of sales provided by products less than

n years old

“Replacing revenues from maturing services and

increased competition”

New profits Percentage of profits provided by products less

than n years old

“Earning monopolistic profits as ‘first in’ to new

markets”

Firm growthb Global measure of firm growth added to three

other measures

“‘Re-positioning’ continuously for changing

markets and technologies”

Efficiency orientationStrategic fit Degree to which this year’s new products fit the

business strategy

“‘Balancing’ stable and changing elements in

service and market strategies”

Five-year objectives Degree to which the program hit our five-year new

product objectives

“Planning over time horizon of service life cycles”

Management opinion Overall success of the product development

program (subjective)

“Relying on management experience and

expertise”

Success rate Success/failure rate (number of successes/total

projects)

“Employing rigorous project screening and

selection protocols”

Program ROI Return on investment for the new product

development program

“Maximizing returns on large capital investments

in technology”

Firm efficiencyb Global measure of firm efficiency added to five

other measures

“Maintaining niche in technologically stable

environment”

Notes: PDMA research results are reported in Griffin and Page (1996). Eight important program performance measures and two orientations as reported inPDMA research. Three measures are identified as growth-oriented and five measures are identified as efficiency-oriented (Griffin and Page, 1996, p. 490).aStrategy-based rationales for program orientations extracted from preliminary expert interviews. bTwo global measures for firm growth and firm efficiency areadded based on Griffin and Page (1996)




Volume 23 · Number 7 · 2009 · 476–486

479

assumedly, more efficiency-oriented than those of Prospectorsand, therefore, they will attach greater importance thanProspectors to the efficiency-oriented measures.Our ten program measures are presented according to their

expected growth- or efficiency-program orientations inTable I. Table I provides strategy-based rationales for theseassociations, which we derived from our preliminary expertinterviews. The PDMA research results and our preliminaryexpert interviews provide us with a framework to testempirically the relationship between these SD programmeasures and strategic type. We propose that the perceivedimportance of two sets of program performance measuresvaries due to SMs’ strategic type. We find clear and groundedtheoretical support that SD program performance measuresshould be consistent with SMs’ strategy.

Research modelThe conceptual research model includes the major constructsof strategic types and the perceived importance of SDprogram measures of perceived importance. The fourstrategic types comprise the categorical independent variableand the perceived importance of ten performance measures,which reflect two SD program orientations are the Likert-scaled dependent variables in our study. The three stablestrategic types are the subject of our hypotheses and detailedanalysis. Reactors are defined as strategically unpredictable,and therefore hypotheses may not be developed based on theirunpredictable behavior. This is consistent with the previouslycited precedents in the application of the MS typology (Jamesand Hatten, 1995).The SD program measures of perceived importance are

considered as two distinct sets, based on the PDMA researchand preliminary interviews. The hypotheses relate to growth-oriented and efficiency-oriented program measures.

HypothesesWe state our general research question, which is theoreticallybased on the generally accepted MS typology of firm strategyand the PDMA definitions of program performance measuresin the 1996 survey, conceptually grounded by our expertinterviews:

RQ1. Does strategic type match the perceived importance ofthe SD program performance measures?

Four general hypotheses follow from the general researchquestion:

H1. The perceived importance of growth-orientedperformance measures will be greater for Prospectorsthan for Analyzers.

H2. The perceived importance of growth-orientedperformance measures will be greater for Prospectorsthan for Defenders.

H3. The perceived importance of efficiency-orientedperformance measures will be greater for Analyzersthan for Prospectors.

H4. The perceived importance of efficiency-orientedperformance measures will be greater for Defendersthan for Prospectors.

We expect that the set of performance measures, associatedwith growth-oriented programs, will be more positivelyrelated to the Prospectors than to Analyzers or Defenders.These findings will indicate support, respectively, for H1 andH2. Compared to Prospectors, we further expect that theother set of performance measures associated with efficiency-oriented programs will be more positively related to

Analyzers, indicating support for H3, and to Defenders,indicating support for H4.

Methods

We defined the variables in our research model based on priorresearch. A validated typology (i.e. MS strategic types) and agenerally accepted instrument and metrics from previousresearch (i.e. PDMA survey and measures) operationalize thetwo major constructs in our study. The financial servicesindustry is appropriate for this investigation of developmentsby service marketers (Akamavi, 2005). The financial servicesindustry, specifically, has been studied successfully using theMS typology (Fox-Wolfgramm et al., 1998; James andHatten, 1995; McDaniel and Kolari, 1987; McKee et al.,1989). As in previous research involving the MS typology, weuse self-descriptive paragraphs to determine SMs’ strategictypes. Each MS paragraph describes a Gestalt that surveyrespondents readily recognize as their SMs’ strategies (Jamesand Hatten, 1995).

Validation of survey instrumentWe base our survey instrument and data collection method onprevious research, preliminary expert interviews, and ourpersonal professional experiences in the industry. Whilepreparing the actual survey instrument, we held preliminaryinterviews, following the PDMA research format of usingstrategy-based scenarios, and then we measured perceivedimportance at a national conference in Chicago with tenleading treasury service providers who are recognized sourcesin the area of financial service development.The data collection methods that appear in the SD

literature tend to be interview-based self-assessments (Hartand Craig, 1993; Johne and Snelson, 1988). Quantifying theperceived importance of performance measures requires thesubjective opinions of knowledgeable SM respondents. Weconfirmed through the preliminary expert interviews that SMmiddle managers and relationship managers understand themeaning of the strategic types and the performance measuresand are able to respond readily to survey questions about eachconcept. The preliminary interview findings resonate with thefindings in the four other services studies cited above.

Financial services marketing firms as unit of analysisFinancial services marketers (SMs) are the principal unit ofanalysis for our study. We sought the most expert opinionsavailable on the subjects of organizational strategy andperformance measurement within each state-level bank ornon-bank SM. We directed our survey to senior officers atleading US financial service providers that market treasurymanagement services to their corporate customers. Theindividual survey recipients hold titles of Vice President orabove and have management or marketing responsibility fortreasurymanagement services at their SMs.We rely on themostsenior individual respondent’s opinion about the organization’sstrategic type and new service performance measures. Weobserved that, as expected, individuals at this level of seniorityare able to express informed opinions about the organizations’strategic types and new service performance.To identify target survey respondents, we referred to the

annual directory ofmarketers of treasurymanagement services,published by the Association for Financial Professionals(Foreman and Shafer, 2003), which lists 75 leadingcommercial US banks. The directory also provides name andaddress information for the most senior contact individuals




Volume 23 · Number 7 · 2009 · 476–486

480

responsible formarketing treasurymanagement services in theirorganizations. These individuals are often Senior VicePresidents and above and may oversee multiple bankingfunctions, including marketing, account management,product management, and operating services, which relate toproviding treasury management services. We sent electronicquestionnaires, in two waves, to these 75 senior individuals andreceived responses from23 (30.7 percent response rate) of themor their designated subordinates.We also surveyed officers and members of the 28 regional

affiliates of the Association for Financial Professionals. Wesent packages of hard copy questionnaires in time for monthlymembership meetings in two waves. We received responsesfrom 199 AFP officers and members employed by SMs. Thebankers in this response group generally held titles of VicePresident and above. Non-bank respondents generally heldtitles of Manager, Director, or Partner. This net response toour paper surveys from 148 bankers and 31 other SMs is 23.2percent of the estimated 773 officers of the 28 regional AFPaffiliates.

Findings

The 202 US service marketers in our study are represented bysenior mangers who are employed by 171 single-statecommercial banks and 31 non-bank SMs. The 171commercial banks include single-state bank subsidiaries andbank service corporations of 95 multi-state, multi-bankholding companies (MBHCs). Each of the 95 MBHCsemploys 1.80 of our survey respondents, on average, rangingfrom one to five respondents. For example, USBank, a largemulti-state, multi-bank holding company, employs five of therespondents in five different single-state banks and servicecorporations. The most senior respondent is chosen torepresent each of the 171 single-state bank subsidiaries orservice corporations. Twenty bank respondents, whose single-state banks are already covered by the electronic surveyresponses, are eliminated in this process. The 31 other SMsinclude investment advisors, commercial credit companies,and financial consultants. There is only one respondent foreach of the 31 non-bank SMs.

Strategic type of respondentsThe survey respondents identify their employer firms asProspectors (25.2 percent), Analyzers (35.1 percent),Defenders (31.7 percent), and Reactors (7.9 percent).Consistent with previous applications of MS typology, wereport our findings and analysis for all four strategic types,and our hypotheses and conclusions for the three stable types– Prospectors, Analyzers, and Defenders.

Perceived importance ratings of SD program

performance measuresWe asked all respondents to rate the perceived importance ofthe ten program performance measures on a Likert scaleranging from 5 as very important to 1 as very inimportant.Three of the ten measures studied rate at least a 4.25 on the5.00 importance scale. The three more important measuresinclude strategic fit (4.41), future opportunities (4.28), andnew profits (4.23). One less important measure rates less than3.75 on the 5.00 importance scale – program return oninvestment (3.73). The other six program performancemeasures rate between 4.00 and 4.25 on the 5.00importance scale. These six important measures are firmefficiency (4.20), new sales (4.18), five-year objectives (4.17),

firm growth (4.13), success rate (4.12), and managementopinion (4.11). The mean importance scores for all tenmeasures are reported in Table II.

Program performance measurement factorsWe hypothesized, based on the PDMA survey andpreliminary interviews, that the ten performance measurescould be categorized by importance as growth- or efficiency-oriented. Therefore, we conducted a factor analysis of the tenmeasures, using principal component analysis with Varimaxrotation and Kaiser normalization. The factor analysis of theten program measures reveals three distinct, interpretabledimensions for program measurement, as reported in TableII. The three program performance measurement factors arelabeled for further analysis as “growth”, “objectives”, and“efficiency”.The growth factor emerged as expected with the four

growth-oriented measures (27 percent variance explained,a . 0:78). An efficiency factor emerged (24 percent varianceexplained, a . 0:78). However, only two of the six expectedefficiency-oriented measures loaded on it – success rate andfirm efficiency.An unexpected “objectives” factor emerged (21 percent

variance explained, a . 0:80). Three of the six expectedefficiency-oriented measures loaded on it: strategic fit, five-year objectives, and management opinion. One measure,program return on investment, failed to load on any one of thethree factors and is dropped from further analyses.

Correlations among importance of program

performance measurement factors and strategic typesThe first statistical test confirms correlations among strategictypes and the importance of the three program performancemeasurement factors.The correlations are reported inTable III.First, Prospectors correlate positively and significantly

(p , 0:01) to the growth factor, as expected. The finding thatDefenders correlate negatively and significantly (p , 0:01)withthe growth factor also provides support for H2.Second, Defenders correlate positively and significantly

(p , 0:01) with the efficiency factor, as expected. The findingthat Prospectors correlate negatively and significantly(p , 0:01) with the efficiency factor also provides support forH4.Third, analyzers correlate positively and significantly

(p , 0:01) with the unexpected objectives factor.Prospectors correlate negatively and significantly (p , 0:01)with the objectives factor.

Analysis of variance of performance measurement

factors among strategic typesThe second statistical test is to compare the means of theperceived importance of each performance measurementfactor among the strategic types. We do this by analysis ofvariance (ANOVA) tests using SPSSw statistical software(Norusis, 2002). We find that the factor scores for the threeprogram performance measures vary significantly amongstrategic types, at the p , 0:01 level. The ANOVA results arereported in Table IV.The data support significant (p , 0:05) differences in

means between pairs of stable strategic types on the threeperformance measurement factors. Prospectors’ andDefenders’ mean factor scores differ significantly (p , 0:05)for the growth factor and the efficiency factor. These findingsprovide added support that Prospectors place significantlymore importance on the growth factor and Defenders place




Volume 23 · Number 7 · 2009 · 476–486

481

significantly more importance on efficiency factor (H2 and

H4, respectively).However, the data does not support the two hypotheses

regarding Analyzers (i.e. H1 and H3). Analyzers do not place

significantly less importance on the growth factor than

Prospectors, nor significantly less importance on the

efficiency factor than Prospectors. In this way, Analyzers

demonstrate their tendency to be a “hybrid” strategic type.

Interestingly, Analyzers place more importance on the

objectives factor than Prospectors, but not significantly

more importance than Defenders. None of the three stabletypes (i.e. Prospectors, Analyzers, and Defenders) differssignificantly from the strategically unstable Reactors on any ofthe three performance measurement factors.

Conclusions

Our general conclusion is that SD Program performanceshould be measured in terms of growth, efficiency, andobjectives. SMs should match the importance that they place

Table II Level of importance of program performance measures and factor analysis by program orientation

Importance of program performance measures

(15 very unimportant, 55 very important)

Mean

(SD)

(n5 202)

“Growth”

measurement factor

“Objectives”

management factor

“Efficiency”

measurement factor

Growth-oriented measuresFuture opportunities 4.28 (0.71) 0.593

New sales 4.17 (0.63) 0.918

New profits 4.23 (0.66) 0.852

Firm growth 4.12 (0.56) 0.675

Efficiency–orientedmeasures

Strategic fit 4.41 (0.62) 0.757

Five-year objectives 4.17 (0.72) 0.814

Management opinion 4.11 (0.86) 0.827

Success rate 4.12 (0.65) 0.843

Firm efficiency 4.20 (0.62) 0.889

Program ROI 3.73 (0.65) 20.697 .380

Eigenvalue 2.43 2.15 1.89

Percentage of variance explained 26.99 23.86 21.00

Cumulative percentage explained 26.99 50.85 71.85

Factor reliability (a) 0.782 0.783 0.801

Notes: Principal component analysis using Varimax rotation and Kaiser normalization. Factor loadings less than 0.300 are suppressed for clarity of presentation

Table III Correlations of strategic types and importance of program performance measurement factor scores

Importance of program performance

measurement factors

Prospector

(n5 51)

Analyzer

(n5 71)

Defender

(n5 64)

Reactor

(n5 16)

Growth factor 0.309 * * 0.053 20.193 * * 20.109

Objectives factor 20.231 * * 0.223 * * 20.159 20.029

Efficiency factor 20.183 * * 20.060 0.296 * * 20.042

Notes: n ¼ 202. * *Correlation is significant at the p , 0:01 level. Bold values indicate significant positive correlations, as hypothesized

Table IV ANOVA of strategic types and importance of program performance measurement factor scores

Importance of program performance

measurement factor

Differences among types

F-test/significance(n5 202)

Prospector

(n5 51)

Analyzer

(n5 71)

Defender

(n5 64)

Reactor

(n5 16)

Growth factor 11.49 * * 0.538 a 0.071a,b 20.402b 20.368b

Objectives factor 5.40 * * 20.402a 0.302b 0.005a,b 20.098a,b

Efficiency factor 5.77 * * 20.319a 20.081a,b 0.371 b 20.141a,b

Notes: Bold values indicate significant differences between stable types at the p , 0:05 level, as hypothesized. Homogeneity of variance assumed based onLevene’s t-test at the p , 0:05 level. Tukey’s b post hoc test: group sizes are unequal, harmonic mean sample size is 39.73. aDifferent superscript letters indicatea significant difference between two types at the p , 0:05 level. * *Differences among types as indicated by F-test are significant at the p , 0.01 level




Volume 23 · Number 7 · 2009 · 476–486

482

on each of these three measurement factors to firm strategy.SMs’ different core business problems and SD programorientations are clearly related to different programperformance measures. Therefore, all SMs need not use thesame SD success measures. Prospectors, Defenders, and,interestingly, even “hybrid” Analyzers should contextualizetheir success in SD programs based on their unique strategictypes. This conclusion resonates with Montoya-Weiss andCalantone’s (1994) findings that “strategy” or strategic fit is akey determinant of success, though it is, unfortunately, notincluded consistently in performance research. We cantherefore challenge the implicit assumption in themainstream of SD success literature that performance canbe determined and measured without regard to strategy.Certainly, different sets of metrics are appropriate fordifferent strategic types.Our general conclusion also resonates with the strategic

rationales for the perceived importance of programperformance measure to SMs, as suggested by the PDMAresearch and our preliminary expert interviews (Table I).Prospectors perceive the growth factor, which indicatessuccess with early market entry and new service linestrategies, as more important. Defenders perceive theefficiency factor, which indicates success with secure marketniches and narrower service lines, as more important.Remarkably, even Analyzers perceive the objectives factor,which indicates success in strategically balancing expansion ofnew and existing markets and service lines.

Conclusions regarding program performance

measurement factorsThe elements of the growth factor reflect Prospectors’ successin solving their core problem of “seeking new opportunities innew markets”. Prospectors, more than the other two strategictypes, measure their performance in future opportunities,because their strategy is to respond to early market signalsbefore competitors and to react to changing markets andtechnologies. Prospectors place greater importance on thegrowth measures of new sales and new profits because theirstrategy is to replace maturing services with new ones and toreap monopolistic profits for being first to market.The elements of the efficiency factor reflect Defenders’

success in solving their core problem of “sealing off” theirmarkets – that is, maintaining a secure niches in narrowermarket and service domains, serving only specific customertypes with a limited range of services. Defenders measuresuccess rate because they seek to ensure a high likelihood ofreward and a low likelihood of risk with their few newservices.The elements of the objectives factor reflect Analyzers’

pursuit of strategies to balance the stable and changingelements in their market entry and service lines. Theytherefore measure success by strategic fit and five-yearobjectives. Analyzers watch the competitive environmentcarefully and respond judiciously to the “right” opportunities,recognizing the importance of management opinion.

Conclusions regarding individual elements of program

performance measurement factorsTwo specific elements – i.e. future opportunities and newprofits – of the growth factor are perceived to be of greaterimportance by respondents across all strategic types. Futureopportunities may be important to most SMs because servicesare flexible and may be adjusted quickly in response to futurecustomer needs. New profits may be important to most SMs

because competitors can easily duplicate new services, andtherefore earning early monopolistic profits is a necessaryreward.One expected efficiency-oriented measure, program return

on investment, is perceived to be of less importance torespondents across all types and it did not load onto theefficiency factor, or any other factor. This may be becausemost SD programs do not often involve large capitalinvestments. Furthermore, the returns on necessarytechnology investments may be measured more readily atthe SD project than program level.Strategic fit is perceived to be of greater importance than

any other element across all strategic types. This findingresonates with the theme of this paper.

Managerial implications

Our findings suggest that SMs could be more effective andefficient in evaluating their SD programs by matchingmeasures to strategies. The use of strategy-basedperformance measures may provide better feedback toservice marketers, enhance the program evaluation process,and contribute to overall program success. SMs are advised tochoose performance measures consistent with their businessstrategies to evaluate their SD programs. Prospectors, forexample, are advised to emphasize the growth factorassociated with their growth-oriented strategy, as indicatedin the PDMA survey. On the other hand, Defenders maychoose the efficiency factor associated with their businessstrategy in evaluating their program. Analyzers may placegreatest importance on the objectives factor, as discovered inour study. This strategic refinement to SMs’ evaluationprocesses may actually improve the likelihood of overall SDprogram success.Furthermore, SMs, regardless of strategic type, may better

evaluate their SD programs by focusing on the moreimportant individual performance measures (i.e. strategic fit,future opportunities, and new profits). other less importantperformance measures (i.e. program return on investment)may be deferred or dropped, so that the evaluation processmay be more concise and timely (Hart et al., 2003). Anotheroption is for SMs to evaluate their SD programs assigninggreater weights to their more important strategic measures.

Academicians may wish to align success measures with

practiceAcademicians may enhance the validity of their performancestudies by aligning their success measures with thoseperceived to be important by SMs. Future SD research maybe more relevant and rigorous by focusing on the performancemeasures that are more important and more consistent withSMs’ strategic types. Academicians may be guided in theirselection of SD performance measurement factors when theyconduct research in industries dominated by certain strategictypes (e.g. growth factor in the consulting industry, or theefficiency factor for the utilities industry, or the objectivesfactor for the banking industry).In general, we recommend that all SD program

performance studies include strategic fit as a successmeasure. This clearly resonates with the recommendationthat Montoya-Weiss and Calantone (1994) made on theessential role of strategy as a determinant of success.This study has certain limitations, which may be overcome

by future research. The opportunity exists for research into




Volume 23 · Number 7 · 2009 · 476–486

483

other service industries and in other countries to test thesefindings regarding strategic SD measures.Perhaps most importantly, we conclude that SD success

may take many forms. Academicians should apply thoseperformance measures that are consistent with SMs’ actualbusiness strategies in order to accurately portray SD success.

References

Akamavi, R.K. (2005), “A research agenda for investigationof product innovation in the financial services sector”,Journal of Services Marketing, Vol. 19 Nos 6/7, pp. 359-78.

Avlonitis, G.J., Papastathopoulou, R.G. and Gounaris, S.P.(2001), “An empirically-based typology of productinnovativeness for new services: success and failurescenarios”, Journal of Product Innovation Management,Vol. 18, pp. 324-42.

DeSarbo, W.S., Di Benedetto, C.A., Song, M. and Sinha, I.(2005), “Revisiting the Miles and Snow strategicframework: uncovering the interrelationships betweenstrategic types, capabilities, environmental uncertainty,and firm performance”, Strategic Management Journal,Vol. 26, pp. 47-74.

Easingwood, C.J. and Storey, C.D. (1993), “Marketplacesuccess factors for new financial services”, Journal ofServices Marketing, Vol. 7 No. 1, pp. 41-54.

Edgett, S.J. (1994), “The traits of successful new servicedevelopment”, Journal of Services Marketing, Vol. 8,pp. 40-9.

Fitzsimmons, J.A. and Fitzsimmons, M.A. (2000), NewService Development: Creating Memorable Experiences, SagePublications, Thousand Oaks, CA.

Foreman, L. and Shafer, D.L. (2003), “Directory of treasurymanagement services”, AFP Exchange, Vol. Fall, pp. 104-32.

Fox-Wolfgramm, S.J., Boal, K. and Hunt, J.G. (1998),“Organization adoption of institutional change inProspector and Defender banks”, Administrative ScienceQuarterly, Vol. 43, March, pp. 87-126.

Griffin, A. (1997), “PDMA research on new productdevelopment practices: updating trends and benchmarkingbest practices”, Journal of Product Innovation Management,Vol. 14 No. 6, pp. 429-58.

Griffin, A. and Page, A.L. (1993), “An interim report onmeasuring product development success and failure”,Journal of Product Innovation Management, Vol. 10 No. 4,pp. 291-308.

Griffin, A. and Page, A.L. (1996), “Success measurementproject: recommended measures for product developmentsuccess and failure”, Journal of Product InnovationManagement, Vol. 13, pp. 478-96.

Hambrick, D.C. (1984), “Taxonomic approaches to studyingstrategy: some conceptual and methodological issues”,Journal of Management, Vol. 10 No. 1, pp. 27-41.

Hambrick, D.C. (2003), “Academic commentary: On thestaying power of Defenders, Analyzers, and Prospectors”,Academy of Management Executive, Vol. 17 No. 4, pp. 115-8.

Hart, S. and Craig, A. (1993), “Dimensions of success in newproduct development”, in Baker, M.J. (Ed.), Perspectives onMarketing Management, Wiley, London, pp. 207-41.

Hart, S., Hultink, E., Tzokas, N. and Commandeur, H.R.(2003), “Industrial companies’ evaluation criteria in newproduct development gates”, Journal of Product InnovationManagement, Vol. 20 No. 1, pp. 22-36.

James, W.L. and Hatten, K.J. (1995), “Further evidence onthe validity of the self-typing paragraph approach: Miles

and Snow strategic archetypes in banking”, StrategicManagement Journal, Vol. 16, pp. 161-8.

Johne, F.A. (1999), “Successful market innovation”, EuropeanJournal of Innovation Management, Vol. 2 No. 1, pp. 6-11.

Johne, A. and Snelson, P. (1988), “Success factors in productinnovation: a selected review of the literature”, Journal ofProduct Innovation Management, Vol. 5 No. 2, pp. 100-10.

Johne, A. and Storey, C.D. (1998), “New servicedevelopment: a review of the literature and annotatedbibliography”, European Journal of Marketing, Vol. 32 Nos3/4, pp. 184-251.

Lamkin, M. (1988), “Order of entry and performance in newmarkets”, Strategic Management Journal, Vol. 9, pp. 127-40.

Lievens, A. and Moenart, R.K. (2000), “Communicationflows during financial service innovation”, European Journalof Marketing, Vol. 34 Nos 9/10, pp. 1078-110.

McDaniel, S.W. and Kolari, J.W. (1987), “Marketing strategyimplications of Miles and Snow strategic typology”, Journalof Marketing, Vol. 51, October, pp. 19-30.

McKee, D.O., Varadarajan, P.R. and Pride, W. (1989),“Strategic adoptability and firm performance: a market-contingent perspective”, Journal of Marketing, Vol. 53 No. 3,pp. 21-35.

Martin, C.R. and Horne, D.A. (1993), “Service innovation:successful versus unsuccessful firms”, International Journalof Services Marketing, Vol. 4 No. 1, pp. 49-65.

Miles, R.E. and Snow, C.C. (1978), Organizational Strategy,Structure, and Process, McGraw-Hill, New York, NY.

Miles, R.E. and Snow, C.C. (1994), Fit, Failure, and the Hallof Fame: How Companies Succeed or Fail, The Free Press,New York, NY.

Montoya-Weiss, M. and Calantone, R. (1994),“Determinants of new product performance: a review andmeta-analysis”, Journal of Product Innovation Management,Vol. 11, pp. 397-417.

Narver, J.C., Slater, S.F. and MacLachlan, D.L. (2004),“Responsiveness and proactive market orientation and newproduct success”, Journal of Product InnovationManagement, Vol. 21 No. 5, pp. 35-52.

Norusis, M.J. (2002), SPSS 10.5 Guide to Data Analysis,Prentice-Hall, Upper Saddle River, NJ.

Page, A.L. (1993), “Assessing new product developmentpractices and performance: establishing crucial norms”,Journal of Product Innovation Management, Vol. 10,pp. 273-90.

Slater, S.F. and Mohr, J.J. (2006), “Successful developmentand commercialization of technological innovation: insightsbased on strategy type”, Journal of Product InnovationManagement, Vol. 23, pp. 26-33.

Smith, A.M. and Fischbacher, M. (2005), “New servicedevelopment: a stakeholder perspective”, European Journalof Marketing, Vol. 39 Nos 9/10, pp. 1025-48.

Storey, C.D. and Easingwood, C.J. (1998), “Types of newproduct performance: evidence from the consumer financialservices sector”, Journal of Business Research, Vol. 43,pp. 76-86.

Storey, C.D. and Kelly, D. (2001), “Measuring theperformance of new service development”, The ServicesIndustry Journal, Vol. 21 No. 2, pp. 71-90.

Syson, F. and Perks, H. (2004), “New service development: anetwork perspective”, Journal of Services Marketing, Vol. 18No. 4, pp. 255-66.

Vermeulen, M. (2004), “Managing product innovation infinancial services firms”, European Management Journal,Vol. 22 No. 1, pp. 43-50.




Volume 23 · Number 7 · 2009 · 476–486

484

Appendix

About the authors

Michael T. Manion is an Associate Professor in the School ofBusiness & Technology at the University of Wisconsin-Parkside, where he teaches marketing and strategy in theMBA and undergraduate business programs. He has 20 yearsof experience in marketing consulting and banking services.

Michael T. Manion is the corresponding author and can be

contacted at: [email protected] Cherian is an Associate Professor of Marketing in

the Liautaud Graduate School of Business at the University of

Illinois at Chicago, where he teaches marketing at the MBA

and PhD levels.

Figure A1 Survey questions




Volume 23 · Number 7 · 2009 · 476–486

485

Executive summary and implications formanagers and executives

This summary has been provided to allow managers and executivesa rapid appreciation of the content of the article. Those with aparticular interest in the topic covered may then read the article intoto to take advantage of the more comprehensive description of theresearch undertaken and its results to get the full benefit of thematerial present.

It takes different strokes for different folks, so they say. Whatis actually meant by that is a bit uncertain but it’s true to saythat different people have different requirements, tastes,preferences and beliefs, and that individualism, rather thangeneralization, is often a better option in understandingsomeone or something.While service marketers care about the success of their

service development programs and are increasingly aware thattheir organizational performance relates to the success of theirnew services programs, they’re all different “types”, so itshouldn’t be surprising to discover that they have differentways of assessing that success. In fact, service development(SD) programs are a direct expression of service marketers’(SMs’) strategic type and are directed at producing verydifferent sorts of success. Indeed, according to MichaelT. Manion and Joseph Cherian in “Do services marketers’success measures match their strategies?”, the logic thatperformance measures for programs should match servicemarketers’ strategy is inescapable as each type seeks tosucceed in different ways.They suggest that SMs could be more effective and efficient

in evaluating their SD programs by matching measures tostrategies. The use of strategy-based performance measuresmay provide better feedback to service marketers, enhance theprogram evaluation process, and contribute to overallprogram success.Referring to previous research by the Product Development

and Management Association (PDMA), an association ofproduct development practitioners and academics, theauthors note that a first strategic type – “Prospectors” –seek to be the “first-in” to new markets with new service lines.Prospectors’ core business aim has been labelled as “seekingnew opportunities in new markets”. These “first movers”seize opportunities, take risks, and expect to reapmonopolistic profits. They respond to early market signals,continually turn over their service lines, and frequentlydevelop services in order to produce new revenues and profits.The second strategic type – “Defenders” – seek to

maintain a secure niche in narrower service and marketdomains, serving only specific customer types with a limitedrange of services. Defenders try to “seal off” their markets byefficient production of low-cost services. They penetrateexisting markets with high-quality, superior services, andgreater value. They rely on experienced management teamsand do not attempt initiatives that lack a high likelihood ofsuccess. The PDMA research suggests that Defenders, more

than Prospectors, will pursue development programs with anefficiency orientation.The third strategic type – “Analyzers” – are more likely to

exhibit two distinct behaviors:1 developing new services for existing customer segments;

and2 marketing existing services to new customer segments.

They try to maintain “balance” in their market strategy,between leadership and penetration and, in their servicesstrategy, between promising and stable lines. They tend tomonitor new markets and to be the “early followers”; that is,they are often “second in” behind Prospectors, but offerenhanced services. However, they are rarely “first in” to a newmarket with new services. The PDMA research suggests thatAnalyzers, when compared with Prospectors, will pursuedevelopment programs with an efficiency orientation.Although the PDMA study was not specifically formulated

for the services industries, the present study indicates thateach of the specific strategy and performance conceptscatalogued is equally appropriate and applicable in theservices context.Prospectors, for example, are advised to emphasize the

growth factor associated with their growth-oriented strategy.On the other hand, Defenders may choose the efficiencyfactor associated with their business strategy in evaluatingtheir program. Analyzers may place greatest importance onthe objectives factor. This strategic refinement to SMs’evaluation processes may actually improve the likelihood ofoverall SD program success.Furthermore, SMs, regardless of strategic type, may better

evaluate their SD programs by focusing on the moreimportant individual performance measures (i.e., strategicfit, future opportunities, and new profits). Other lessimportant performance measures (i.e. program return oninvestment) may be deferred or dropped, so that theevaluation process may be more concise and timely. Anotheroption is for SMs to evaluate their SD programs assigninggreater weights to their more important strategic measures.A general conclusion is that SD program performance

should be measured in terms of growth, efficiency, andobjectives. SMs should match the importance that is placedon each of these three measurement factors to firm strategy.SMs’ different core business aims and SD programorientations are clearly related to different programperformance measures. Therefore, all SMs need not use thesame SD success measures. Prospectors, Defenders, and,interestingly, even “hybrid” Analyzers should contextualizetheir success in SD programs based on their unique strategictypes.The authors challenge the assumption that performance

can be determined and measured without regard to strategy.

(A precis of the article “Do services marketers’ success measuresmatch their strategies?”. Supplied by Marketing Consultants forEmerald.)




Volume 23 · Number 7 · 2009 · 476–486

486

To purchase reprints of this article please e-mail: [email protected]

Or visit our web site for further details: www.emeraldinsight.com/reprints

do services marketers' success measures match their strategies?

Documents