Relative explanatory power of agency theory and transaction cost analysis in German salesforces

ResearchPaperNo. 1421

RelativeExplanatory Powerof AgencyTheoryand Transaction CostAnalysis in German Salesforces

ManfredKrafftRajiv Lal

SonkeAlbers

December1996

GraduateSchool of BusinessStanfordUniversity

Manfred Krafft is Assistant Professorof Marketing, University of Kiel,Germany.

Rajiv Lal is Professorof Marketing and ManagementScience,GraduateSchoolof Business,StanfordUniversity.

SonkeAlbers is Professorof Marketing andManagementScience,Universityof Kiel, Germany.

RelativeExplanatory Powerof Agency Theory and

TransactionCost Analysis in German Salesforces

December1996

Manfred Krafft*, Rajiv Lal** and Sonke Albers***

* AssistantProfessorof Marketing, University of Kid, Germany.

** Professorof Marketing and ManagementScience,GraduateSchool of Business,

Stanford University.

~ Professorof Marketingand ManagementScience,University of Kiel, Germany.

Key words: Agency Theory, TransactionCost Analysis, SalesforceCompensation

Plans,Direct vs Reps, Germany.

OneLine Abstract: How complementaryareAgencyTheoryandTransactionCost

Analysis?

Abstract

In this paperwe takean integratedview of TransactionCost AnalysisandAgency

Theory to study the direct vs rep decisionand the design of compensationplans

in Germansalesforces.While we attempt to investigatethe generalizabilityof the

findings in the U.S.A. to thosein Germany,we also developa set of new hypotheses

in the context of both thesedecisionsand report new effects. Finally, we assess

the complementarityof thesetwo approachesby estimatingthe relativeexplanatory

powerof the two frameworksfor eachof thesedecisions.

We report that while almostall the findings with respectto the designof com-

pensationplans in the U.S.A. aregeneralizableto Germany,thefindings with respect

to the direct vs. rep decisionare not equally generahizable.We also find that while

Agency Theory doesnot add much to explain the decisionof direct vs. ~p in our

data,TransactionCost Analysis is equally limiting in helping understandthe design

of salesforcecompensationplans.

1. INTRODUCTION

The benefitsof effectively managinga salesforcehave neverbeengreater.For almost

all firms, salesis the only revenuegeneratingpart of the organization,while every-

thing elseis acost center. Moreover,with increasingemphasison marketorientation

in today’s environment,the role of salesforcehasassurfiedan increasedimportance.

However, the costs of using a direct salesforceare escalatingby the day with the

averagecost of making a personalsalescall beingcloseto $250 in the U.S.A. (Dart-

nell Survey 1994) and DM 150 in Germany(Mueller 1992). Furthermore,the total

cost of the personalselling effort in the U.S.A. exceeds$140 billion annually (more

than is spenton any otherpromotionaleffort) throughthe employmentof 8 million

individuals in salesand relatedoccupations(Kotler 1994). It is thereforeimperative

that this assetbe usedin the most effectiveand efficient manner.

An important aspectof managinga salesforceis relatedto its design. Depend-

jug on the tasks that needto be performedby the salesforceincluding, prospecting,

communicating,selling, servicingand informationgathering,a firm needsto decide

whetherit shouldhavea companysalesforce(direct) or utilize independentsalesrep-

resentatives(reps). Furthermore,if a companydecidesto employ a direct salesforce,

it needsto designthecontrol andrewardsystemsso asto achievethebestutilization

of its salesforce’sefforts.

By now it is well recognizedthat a salesperson’sperformancedependsnot only on

individual specificfactorsbut alsoon therewardsystemusedto motivatea salesforce

(seeChurchill, Ford and Walker 1993). Hencemanyefforts have beenmadetowards

the studyof salesforcecompensationplansin the more recentsalesforcemanagement

literature(seeWeinberg1975, Basu,Lal, SrinivasanandStaelin 1985,Lal andStaelin

1986, John and Weitz 1989, Deardenand Lilien 1990, Coughlanand Narasimhan

1992,Lal andSrinivasan1993, Lal, OutlandandStaeliii 1994andJosephandKaiwani

)

1995). Seealso the reviews by Coughlanand Sen (1989), Coughlan(1993)and Albers D

(1996).

Two of the most popular theoreticalframeworks used to study the decisionof

repsvs. companyownedsalesforceand designof compensationplansareTransaction

Cost Analysis (TCA) and Agency Theory(AT). While researcherssuchas Anderson

(1985) use TCA to study the choice betweensalesrepsand direct salesforce,John 3

and Weitz (1989) useTCA to study the designof compensationplans. On the other

hand,Basu,Lal, Srinivasanand Staelin (1985),Lal & Staelir~(1986) arid Rao (1990)

apply Agency Theory to study the designof compensationplans.

In this paper, we also focuson thesetwo aspectsof salesforcemanagementbut )

in a context outsidethe U.S.A., namely Germany,which is amongthe three largest

economiesin the worl(l. One of our goals here is to investigatethe generalizabihity

of the empirical findings reportedin the literature to countriesoutside the U.S.A.

This is important since it is known that different culturesfavor different attitudes

towardswork, usedifferent typesof communicationsand operatein varying legal cmi-

vironments(Albers,Krafft and Bielert 1996). Hofstede(1980), using datafrom over

hundredthousandIBM employeesin 66 subsidiariesfinds that culturesfavor differ-

ent attitudestoward work on the following dimensions: powerdistance,uncertainty

avoidance,individualism/collectivismand rnasculini’ty/femininity. In particularhis

analysis.showsthat Germansare more collectivistsand score higheron uncertainty

avoidance,as comparedto their U.S.A. counterparts.Finally, while many aspects

of an employmentcontractbetweenthe salespersonand the firm can be negotiated

in the U.S.A., Germanlaws imposesignificant constraintson this relationship.This

leadsto less useof repsand a higheraverageproportionof salary to total paywhen

comparedto theU.S.A. (Albers,Krafft andBielert 1996). Thus, it is notobvious that

the findings reportedin the literature areequally applicableto the Germancontext.

4

V~ethereforeinvestigatethe usefulnessof theabovementionedtheoreticalframeworks

to internationalcontexts.

Our secondand more importantobjectiveis to comparethe relativeusefulnessof

Agency Theory and TransactionCost Analysis in the context of eachof thesetwo

(le(:isions. Although thesetwo frameworksappearto be complementary,our investi-

gation is motivatedby the fact that TCA was originally advancedto understandand

study issuesrelatedto the boundariesof thefirm (for example,makeor buy decisions

of a firm), while AT hasbeenproposedto understandthe contractualarrangements

betweena firm and its employees.Thus one wonderswhetherTCA shouldprovide a

relatively better understandingof the direct vs. rep decisionwhile AT may be more

appealingin the (:OnteXt of compensationplans. Finally, we proposeand test the

validity of severalnew hypbthesesrelated to the issuesof vertical integrationand

designof compensationplans.

2. LITERATURE REVIEW

In thus section,we briefly review the publishedTCA and AT basedwork on how

to organizea salesforce(usea direct salesforcevs. reps)and designsalesforcecom-

pensationplans. The mostcomprehensivestudy to dateof thedirect vs. rep decision

is providedby Anderson(1985). In this study, AndersonusesTCA to developa setof

hypothesesfor when the selling function should be vertically integratedratherthan

farmedout to a rep organization.By integratingher hypotheseswith thosealready

availablein the salesforcemanagementliteraturesheattemptsto explain broad ob-

servablepatternsof industry usageof salesreps. She confronts thesehypothesesto

datafrom theelectronicscomponentsindustry andfinds significantsupportfor many

of her hypotheses.More specifically, shefinds that firms usea direct salesforcewhen

the product requiresconsiderablelearning, when the firm .hasto reveal damaging

5

(:onflderltial information in employingsalesreps amid when it is difficult to evaluate

time performanceof a salesperson.Furthermore,shealsoreports that aspredictedby

TCA, while environmentaluncertaintyhasno impact on this decision, the greater

the combination of transactionspecific assetsand environmemital unpredictability,

the higherthe likelihood of integration. In summary,Andersonprovidesa conceptual

framework based0mm TCA to study the problem of direct vs. repsand finds empirical

supportfor someTCA based!hypothesesin datacollectedfrom electronicscomponent

industry.

Thestudy of salesforcecompensationplanshasbeenapproachedvia both Agency

Theory and TransactionCost Analysis. In addition. the salesforcemanagementlit— )

eratimreoffers a more intuitive Way. to study this problem. The literature basedon

AT originates with the work of Basu, La!, Srinivasan amid Staelin (1985) (BLSS).

Herein, the authorshypothesizethe impact of increasein uncertainty,marginalcost

of productionand attractivenessof alternative.joh opportunitieson time proportion

of salary to total compensationchanges. More recently, Lal and Srinivasan(1993)

extend the BLSS analysis to salespeopleselling more than one product. Lal and

Srinivasan’stheoreticalanalysissuggeststhat while BLSS’s resultscontinueto hold,

the proportionof salary to total compensationcan he expectedto decreasewith an

increasein the effectivenessof the salespersonand/or a decreasein risk aversion.

Although manyAT basedhypotheseshavenot beentesteddirectly, the empirical

findings in the literatureare consistentwith manyof thesepredictions. For example,

Coughlanand Narasimhan(1992) find supportfor thepredictionthat the proportion

of salary decreaseswith increasingeffectivenessof the salespersonas measuredby

seniority.’ The most direct confirmationof this hypothesisis found in Lal, Outland

‘This effect is observedonly if industrypay is not includedin the analysis(see Column 2, Table )6, in CoughianandNarasimhan1992).

6

and Staeliri (1994) where the proportionof salary is seento he (!ecreasinigwith in-

creasingability of thesalespersonasreportedby his/hersalesmanager.With respect

to the uncertaintyhypothesis,Lal, Outland and Staelin.(1994) find that the fraction

of salary in total compensationincreaseswith increasein environmentaluncertainty

and/orquotauncertainty. Josephand Kalwani (1995) also find supportfor this hy-

pothesiswhereuncertaintyis measuredby the coefficient of variationof dollarsales.2

Finally, Josephand Kaiwani (1995) are the only authorsto find supportfor the risk

aversionhypothesis.Theytestandfind supportfor thepredictionthat theproportion

of incentivepay increaseswith risk tolerance.

John and Weitz (1989) useTCA to study the role of salary and incentives in

structuringsalesforcecompensationplans. To achievethesegoals, they considerthe

two controlmechanismsidentified by Williamson (1975,1981, 1985)and proposethat

in the salesforcecontext, while bureaucraticcontrol corresponds“to the useof su-

pervision to implementcOmpensationplans emphasizingsalary , market control

mechanismscorrespondto plans emphasizingincentives.” Using this analogy, they

hypothesizethat the proportionofsalaryshould increasewith increasein transaction

specific assets,thedifficulty to evaluatesalespeople’sperformance,environmentalun-

certainty facing salesmanagersand the size of the salesforce.The authorsintegrate

thesehypotheseswith those in the salesmanagementliterature and validate their

frameworkusing a sampleof 161 salesmanagersand salesvice-presidentsin manu-

facturingfirms. The empiricalanalysisoffers somesupport for the hypothesesbased

on TCA. While easeof replacingsalespeopleandits interactionwith environmental

uncertaintyhave a significant impacton salary as predicted, “other key constructs

are not significantly relatedto salary.”3 Finally, the authorsalso find support

2Studiesby JohnandWeitz (1989) and CoughianandNarasimhan(1992) do not find supportfor thishypothesis.

3While neitherreplaceabilitynor its interactionwith transactionspecific assetsis significant due

7

)

for someof the hypothesesprovidedin the salesforcenrlanagementliterature.

Thus we see that there is no single study that attemptsto test the predictions

of both frameworks(TCA and AT) on one dataset. The goals of our study are to

test the generalizahilityof theseframeworksto internationalcontexts,dievelop and

testsome new hypotheses,and most importantly estimatethe explanatorypowerof

these two frameworks in the context of the above mentioneddeeisions. The next

sectiondevelopsand identifies the set of hypothesestestedin our study. Section 4

presentsa descriptionof the researchdesign,measuresemployedand the findings of

our study. Section 5 offers a comparisonof the explanatorypower of TCA and AT

for the vertical integrationand compensationdesign decisionsand we close with a

summaryand directionsfor future research.

3. HYPOTHESES DEVELOPMENT )

In this section,we developa set of hypotheseswith respectto both the decisionto

employ a reporganizationvs. direct salesforceand the structureof the compensation

plan.

3.1. Direct Salesforcevs. Reps

Our intent here is to integratethe predictionsof Agency Theory and Transaction

Cost Analysis. As in themost prominentstudy to dateusingTransactionCost Anal-

ysis (Anderson1985),we include factorssuchastransactionspecific assets,difficulty

in evaluatingperformance,environmentalunpredictability,and travel requirements.

We next state a set of hypothesesbased on AT. AT has beenproposedto study

the optimalcontractualarrangementsbetweena principal and an agent,taking into

accountthe motivationalaspectsof any sucharrangement.While AT hasnot been

to multicollinearity, eachconstructis significant at p < 0.10 whenit aloneappearsin the model.

8

explicitly usedto investigatethe direct vs. rep decision,one may wonderwhich orga-

nizationaldesignmayhe betterftom a motivationalviewpoint for a particularselling

context. The motivationalargumentsbecomemoreevidentwhenone recognizesthat,

repsare connpensatedsolely throughcommissionswhile a directsalesforce’scompen-

sation must consist of a salary component,to be consistentwith the labor laws in

Germany. Thus one would arguethat if control issuesas describedin transaction

cost approachesfavor a rep organization,this decisionmay be modified if thereare

sufficient motivationalreasonsfor including a salaryin the compensationplan.

Hence we hypothesizethat since an increasein uncertaintyin the selling envi-

ronmentand/or a higherminimum utility requirementresultsin a higherfraction of

salary, suchchangescan he expectedto favor a direct salesorganization. Similarly,

sincean increasein effi~ctivenessof salespeopleresultsin amore incentivesbasedplan,

it is hypothesizedthat moreeffectivesalespeoplearemorelikely to be associatedwith

a rep organization.Thesehypothesesare in addition to thosealready identified by

Anderson (1985),arid a completeset of the predictionsarid correspondingempiriéal

findings to dateis presentedin Table la. While thesehypotheseshavebeendeveloped

and testedin time U.S.A., we believe that the findings should generalizeto German

salesforces.However,sincerepsare less frequentlyusedin Germany,somevariables

with less explanatorypower may turn out to be insignificant in our data. Further-

more,sinceGermansrankhigheron uncertaintyavoidance,the effect of this variable

mayhave a higherlikelihood of beingsignificant in our data.

3.2. CompensationPlans

Given the rich literature on the salesforcecompensationplans,we integrateAT and

TCA in this study. As hypothesizedin AT we include the following factors: envi-

ronmentaluncertainty,effectivenessof the salesperson,attractivenessof alternative

9

employmentopportunities,ability to measureinputs, arid adequacyof outputsas a

measureof performance.While the impactof the first threefactorshasbeemi i(lelltifie(l

in other empiricalstudiesusing AT, the last two factorsneedsomeelaboration.

AT proposesthat incentiveplansshould be usedonly if it is difficult to measure

time inputs provided by the salesperson.Otherwise, the most cost effective way of

compensatinga salespersonis throughthe useof salary and monitoring the efforts

of a salespersonthat are expectedto heconsistentwith prespecifledgoals. However,

if this is difficult to measure,incentive plans basedon output measuresshould he

coniSidlered. In such circumstances,AT proposesthat the emphasison incentives

should! be commensuratewith the ability in assessingthe efforts of a salesperson

throughoutputmeasures.In summary,only whenit is difficult to measuretheinputs

of a salesperson,increasingemphasisshould he placedon incentiveswith increasein

the adequacyof outputsas an indicatorof inputs. )

Finally, while mostof the work on salesforcecompensationplansusing AT focuses

on time salesgeneratingaspectsof a salesperson’seffort, we know that a part of time

salesperson’seffort mayhe nonproductivein theshort runor evenin thelong run. For

example,servicingcustomers,call preparationand handling ordersdo not generate

salesin the short, run, however, they are essentialto the viability of the firm in the

long run. In contrast,travel time is a lossof productivetime and doesnot result

in any. payoff even in the long run. AT predicts that the proportion of salary to

total compensationshould increasewith increasein nonproductiveactivities, such

as travel time, desiredof the salesperson. Similarly, if salespeoplehave to spend

more time taking orders,servicingaccountsetc., againrelatively more emphasison

salary is desirablein the short run. Since our empirical study includesobservations

from a variety of different industries,differencesalongthesedimensionscould play

an importantrole in explainingthe variancein proportionof salaryto total pay.

10

The TCA factorsusedin this Studly areeasein replacingsalespeople,transaction

specificassets,al)ilitv to assessperformanceaccurately,uncertaintyfacingsalesmami—

agers, interactionbetweenreplaceabilityand uncertainty,and size of time salesforce.

All thesefactorsareconsideredin John and Weitz (1989). With respectto theability

to assesssalesperson’sperformance,TCA does not distinguish betweeninput and

output measures.Johnand Weitz (1989) arguethat if outputmeasuresarehelpful

in assessinga salesperson’sperformance,incentivesplansshould he used. However,

unavailabilityof such outputmeasuresshould leadto moresalary and monitoringof

the salesperson.Thus in contrastto AT, where incentivesshould not be usedwhen

input measuresare available,TCA proposesthat incentivesshould be usedas long

asoutputmeasurescanprovide an accurateassessmentof a salesperson’sactivities.

The differencein the two hypothesescan he better understoodwhen one recog-

nizes that while AT’s objective is to help design the most profitable compensation

plan to motivate a salesperson,the goal of TCA is to help minimize the cost of

comutrollinig/transactingwith a salesperson.In other words, if output measurescan

provide an accurateassessmentof a salesperson’sactivities,TCA proposesthat no

further costs be incurred in motivating a salesperson.On the other hand, if input

measuresare accurate,AT proposesthat salespeoplecan be motivated and profits

maximizedwithout resortingto the useof outputmeasures.

In summary,we seekto validatemanyof thehypothesesidentifiedin prior studies

of compensationplans, validatea new hypothesiswith regardsto the effect of non-

selling activities and, test the competinghypothesesput forward by AT and TCA

with respectto the adequacyof assessinga salesperson’sperformancebasedon input

andoutputmeasures.A summaryof thesehypothesesand empiricalfindings to date

is presentedin Table lb. Again, thoughthesehypotheseshavebeendevelopedand

tested in the U.S.A., there is no reasonto believe that they would not generalize

11

)

to Gernianmcontexts. However,as the proportionof salary to total pay in Germmiany )

is substantiallyhigher and thereforeshows less variation than in the U.S A., some

variableswith less explanatorypower may turn out to he non-significantfor German

salesforces.Furthermore,the relatively higheremphasison avoiding uncertaintyin

Germany again gives rise to the possibility of finding a significant impact of this

variablein our data.

4. RESEARCH DESIGN

‘To test the hypothesesdescrihedin the previoussection,we maileda questionmiaire

to 1099 chiefsalesexecutivesof Germansalesforces,noting the fact that firms mostly

useonly one compensationschemefor the whole salesforce..Ini this way, we seek to

capturetime perceptionsof chief salesexecutiveswho are involved in the designof

salesforcesand their incentiveplans. The questionnairewas developedarid pretested

throught,he direct help of 10 top salesexecutives.Severalefforts were madeto solicit

time responseof the chief salesexecutives. The initial mailing wa.s followed imp by a

secondmailingafter 4-6 weeks. Furtherefforts to improvetheresponserateweremade

througha contactby fax and promiseof sharingtheresultsof ourstudy. The survey

wascompleteabout twelve weeksafter the first mailing and resultedin a response

rate of about 25 %. Of the 270 respondingfirms, 61 firms usedrepresentativesonly,

173 useda direct salesforceand 36 useda hybrid organization. ‘~ A comparisonof

our samplewith other Germanstudiesis reportedin Table 2 and a comparisonof

the different characteristicsof the empirical studiesinvestigatingthe direct vs. rep

decisionand the designof compensationplans is presentedin Table 3.

4Thereasonsfor the existenceof a hybrid organizationseemto be rather arbitraryand includesalesforcesin transition, vacantterritoriesbeing temporarilyassignedto repsand reps being usedas a threat to companysalespeopleto improve their performance.

12

4. 1. 11’!easures

The two dependentvariablesin ourstudy are, thekind of salesforce(direct salespeo-

ple or reps)and the proportion of salaryto total pay in caseof the direct salesforce.

Thefirst dependentvariablewasmeasuredby askingeachrespondentaboutthe num-

ber of salespeopleemployedin the salesforceand also the numberof salesrepsin the

salesorganization.Thesequestionswere deemedappropriatesincesomesalesforces

employboth direct salespeopleandreps. To measurethe proportionof salaryto total

pay,eachrespondentprovidedestimatesof the percentageof salespeoplecompensated

by straightsalary,straight commissionsand a combinationplan. Furthernnore,they

provided an estimateof the variableincomein a combinationplan. Although most

salesforceswere compensatedthrough mainly one type of plan, we multiply the re-

ported estimateof the proportionof variable incomeby the percentageof salesforce

compensatedby army one of the variableplans (salaryplus commissions,salaryplus

bonusand salaryplus commissionsplus bonus) to determinethe variableportion of

the total packagefor time salesforce. Details of the questionsusedto measurethe

dependentvariablesare providedin AppendixI.

The independentvariablesidentified in Tables la and lb were measuredusing

multi-item scalesas describedin Appendix II. Thesevariablescan be categorized

into groupsdescribingthe stateof Market Failure, the Selling Environment, the

Salespeopleand CompanySpecifics.

Market Failure

Réplaceability A three item scalewas used to measurethe easein hiring the

kind of salespeopledesiredby the firm.

TransactionSpecific AssetsWe measuredthe uniquenessof companyproce-

duresandtime neededto learnaboutthe uniqueaspectsof the firm’s customersand

13

)

products. Since TCA (healswith the cost of conitrol mechaniisnmi,we choseto employ )

a (1011am rmieasumrewhich was constructedby multiplying the total costof training new

salespeople(reportedin DM) with thefractionof training time neededto developcus-

tomerspecific, companyspecific and productspecific knowledge. This is in contrast

to the multi-item agree/disagreescalesusedin the literature.

Ease of measuring inputs This constructis nmieasured through a four-item

agree/disagreescaleas in Johnand Weitz (1989).

Inadequacyof Output as a Performance MeasureThis constructis mea-

sured!through a three-itemagree/disagreescale. In this way we usea moreelaborate

scalethan in John andWeitz (1989).

Selling Environment

Uncertainty This constructhasbeenapproachedthrougha varietyof measures

in theliterature,whereeachmeasurecapturesa somewhatdifferent dimensionof this )

overall construct.In ourstu(ly we includeitemsusedin previousstudiesbut also mea-

sure the numberof customersper salespersonto capturethe possibility of avoiding

uncertaintythrough dliversification of the selling effort (Porter 1980). A confirma-

tory factor analysisof theseitems resultedin threedifferent factors,Environmental

Uncertainty, SalesVolatility and Diversification of Risk, asshown in Appendix II.

The Salespeople

EffectivenessThis constructwas measuredthrough averageselling experience

(in years)beforejoining the firm asin Coughianand Narasimhan(1992).

Minimum Utility Requirement This constructreflectsthe attractivenessof

alternativeemploymentopportunitiesfor the salespersonand was measuredby esti-

matingtheaverageindustryincomefrom theinformationprovidedby therespondents

abouttotal incomepaid by thefirm to an averagesalesperson.Moreover,the average

14

level of educationin the salesforceis also usedto measurethis construct.We also use

tenure with the commipariv as a mnmeasureof opportunity cost of time. All thesemea—

sures,Tenure,Educationand AverageIndustry Income,have beenusedby Coughlan

arid Narasinihan(1992).

Company Specifics

We also measurethe Sizeof the Salesforcein termsof the numberof salespeople,

Travel R,eqi.iircmentsfor the salespeoplevia the percentageof time spent traveling

amid numberof hotel stays,and Importanceof Selling Activities by the amount of

time devotedto selling.

4.2. Estimation.

Time irnipact of the independentvariables on the decisiomm to employ a (hrect sales—

force rather than reps is estimatedwith time help of logistic regressionwhich usesa

maximumlikelihood procedure(as in Anderson 1985).

The relationshipbetweensalary asa proportion of total payand the independent

variablesis estimatedvia ordinaryleast-squaresregression,wherethedependentvari-

able hasbeentransformedto its logit (in ~, wherex is the dependentvariable).

This logit transformationis requiredto satisfy the normality assumptionsof ordi-

nary leastsquareswhen the dependentvariable is constrainedbetween0 and 1, as

indicatedby John and Weitz (1989).

4.3. Results

Direct vs Reps The resultsof ouranalysisof the directvs rep decisionaredisplayed

in Table 4a. In ourstudy the TCA and AT variablesexplain a significantportion of

the variance. Sinceno measureis availablein Logistic regression,we report the

15

Log Likelihood of —42.52 and a model x2 of 68.762. Given the degreesof freedom.

both theseare highly sigmmificant an.l the mnmo(lel y2 is better than that reportedby

Atidersomi (1985), who reportsa Log Likelihood of —74.16 arid a mnodlel ~ 2 of 46.38.

With respectto the hypothesizedeffects,we find supportfor the hypothesesthat

a direct salesforceis more likely to he employed with increasingtransactionspecific

assets,decreasingamountof time (levoted to sellimig, decreasingtravel requirements,

increasinguncertaintyin time selling environment,(lecreasingnumberof customersper

salespersonarid decreasinmgeffectivenessof the salespeople.Only the effect of size of

the salesforceis contrary to the predicteddirection and resultsin a higher likelihood

of a rep organizationwhena larger numberof salespeopleare employed. This find- )

ing can he justified throughShapiro’s(1977) observationthat adnministrativecontrol

rrmechanm.isrnsbecomeinmcreasinmglycostly with sizeof time organizatiomi Anotherexpla-

nation could lie in the unavailability of a largeenougim qualified pool of salespeople )

to employ.

With respectto time generalizabilityof the findings in time U.S.A., we note (in

Table 4h) that our findlimmgs are consistemmtwith those reportedin Anderson (1985) )

with respectto the effectsof transactionspecific assetsand emphasison non-selling

activities. On the otherhand,while the effectsof companysize, travel requirements

and uncertaintywere found to be insignificant in Anderson’sstudy, we find signifi-

cant effects in our data. Finally, we were unableto replicate the significant impact

of difficulty of evaluatingperformanceasreportedby Anderson (1985). Hence, we

conclude that the findings in the U.S.A. with respectto direct vs. rep decisiondo

not generalizeto Germanyeasily. Also, it is worth noting that Germansare ranked

higher on uncertaintyavoidanceand a direct effect of uncertaintyis found in our

data,as predicted.

In thisstudy we alsodevelopeda seriesof new hypotheseswith respectto replace-

16

abilit,, effectivemmessof salespeoplearid mninimmium utihit.y reqi1ir.~enieImts.However, only

the effect of effectivenmessof salespeopleis found to be significantand in the pre(hi(:te(l

direction.

Finally, with respectto the conflicting hypothesesaboutuncertaintyand travel

requirements,ourdatalendssupport to the AT basedpredictionfor uncertaintybut

rejectsthat for travel requiremnrents.Taking all theseeffectsinto account,we find that

variablesderived from both TCA and AT havesignificant inipacton the decisionto

integratethe salesforce.

Salary vs IncentivesThe resultsof the analysisof salaryas a percentageof total

compensationare displayedin Table 5a. 1mm our study, the AT and TCA variables

explain 36.3 % of the variance arid the immodel is significant at the 0.001 level (F

value= 4.212). The explanatorypower of thesevariablescolnmpamesfavorably with

other cross-sectionalstudiesof salesforcecommmpensationplamms.

With respectto the hypothesizedeffectswe find the datato supporttime following

hypotheses:theemphasison salaryincreaseswith increasinginadequacyof outputas

a measureof performance,increasingamount of time devotedto selling, diecreasing

effectivenessof salespeopleand increasingminimum utility requirementsasmeasured

by tenureand education.We also find that uncertaintyperse doesnot impact the

designof compensationplans asproposedby Johnand Weitz (1989)using the TCA

framework.

Our dataalso reject the hypothesesthat compensationplans should emphasize

salarywith increasingdifficulty in replacingsalespeople,increasinguncertainty(as

measuredby thenumberofcustomerspersalesperson)andincreasingminimumutility

requirement(asmeasuredby theaverageindustryincome). Theseobservationscanbe

explainedin the following manner. Our finding on replaceabilitycan be understood

b~noting the fact that compensationplans which aremore gearedtowardssalary

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attractthe lesseffectivesalespeopleamid thesesalespeoplecan bemoreeasilyreplaced.

Similarly, while amm increasein the numberof customersper salespeopleis Presumed

to decreasethe uncertainty in the selling environment, it might be time casethat

if all customersneedsome minimum level of attention in the formn of servicing an

account, arm increasein the number of accountsresults in a higher amount of norm-

selling activity which leadsto an increasein the emphasison salaryasevidencedin

thedata. Finally, we conjecturethat averageindllistry incommie nray riot he anaccurate

measurefor minimunmutility. This is because,thenmmeasure(loesnot capturedisutility

from effort. In fact it may bea proxy for skill of asalesperson,in which caseAT based

modelspredict a negativeimpacton the proportionof salary to total compensation. )

We now compareour empirical findings to thosereportedimm the U.S.A. (seeTa-

ble Sb). Our findings with respectto the effect of effectivenessof salespeople,amid

nminimumutility requiremmmenitsareconsistentwith thosein Couigiilanm amid Narasirnhanr )

(1992) and Lal, Outlandand Staehin (1994). The impact of factorssuch as timnme de-

voted to selling, easeof measuringinputs and inadequacyof output as measureof

performanceis also consistentwith the effects reportedin John and Weitz (1989).’~

Similarly, theinsignificanteffect of uncertaintyobservedin ourdatais consistentwith

the findings in othercross-sectionalstudiessuchasCoughlanand Narasinmhaim(1992)

and Johnand Weitz (1989). In contrast,the effect of easein replacingsalespeople

in our datadoes not support the findings in John and Weitz (1989). In thisway

we areableto documentthat mostof the findings reportedfor Americansalesforces

generalizeto Germany.

While one canoften provide ex-postrationalizationsfor discorifirming results, it

is importantto note that oneof the more importanthypothesesof AT with regards

5While Johnand Weitz (1989) reporta direct andsignificant impactof this variable,the effectof this variableis significant only throughits interactionwith time devotedto selling in our data.

18

to uncertaintYhuts riot found significantsupport in any empirical study using cross—

sectionaldata. Tins is particularly interestimmgsince other stuidlies usimig imidividual

level (lata (Lal, OutlandandStaelin 1994 and .Josephand Kalwarmi 1995) have found

support for this hypothesis. To investigatethis issue, we interviewed some of the

executivesin oursample.Theseinterviewsleadus to believethat executivesreact to

uncertaintysomewhatdifferently thanassumedin AT basedanalyses.1mm particular,

since uncertainty is beyond the control of the firm, the managementtreats it as

sonmmethirmgthat the salesforceshould beable to dealwith, amid if not, salesexecutives

prefer to find salespeoplewho can. In order to he ableto do so, a sufficient increase

imi uncertainty is accompaniedby higher commissions.Salespeoplewho are unable

to dealwith uncertaintywill find suchcontractsto be unattractivearid thereforenot

want to stay with time company; while those who can, get rewardedthrough a plami

that consistsof a higherfractionofincentivebased!cOmnj)ensation.Hence,we conmcli.mde

that while the AT literatureon salesforcecompensationplans(leals with umicertainty

only through the design of compensationplans, managersin our sampleseem to

dealwith uncertaintyby offering the right incentivesto signal the higheruncertainty

in the selling environmentand attract an appropriatelyskihledi salesforce. This is

especiallytrue of Germanywhere the legal restrictionsmake it extremelydifficult

to fire salespeople,as a consequencethe hiring decisionis of much more importance

than in the U.S.A.

Among themoreuniqueaspectsof ourstudy is the inclusionof theconstructtime

devotedto selling and its interactionwith easeof measuringinputs. We find that

while the hypothesiswith respectto time devotedto selling is supportedin ourdata,

the hypothesiswith respectto easeof measuringinputs is also supported,although

indirectly through the interactionwith time devotedto selling. In other words, we

find that for any level of time devotedto selling, the proportionof salaryincreases

19

with um(:m’ease in easeof nmeasurimmginputs, as preilicteni. On time other hanni, the

relationshipbetweenthe fraction of salary ann! time devoted to selling (iCpCuIds on

the easeof mneasurringinputs. III particular,we find that if it, is sufficiently difficult

to measureinputs, theeffect on conmpensationplansis dominatedby the direct effect

of time time devotedto selling; and includesa higher percentageof incentiveswith

immcreasimmgtime devotedto selhimmg. However, if inputs are rather easy to measure,

therm the net effect on the cornipemmsationmplan is (line to easeof measuringinputs andh

resultsin a higherpercentageof salary with increasingeaseof measuringinpnmts for

any level of time (levoted to selling. The inclusion of thesevariablesseemsto he

important given that. the ~3-coefficientsfor thesevariablesare relatively high. )

Finally, ourstudy providesa strict testof the competinghypotheseswith respect

to input and output mnmeasuresin AT and TCA frameworks. Recall that AT P1~Ol)O5e5

that when it is easy to measureinputs, compensationplans should consist mainly

of salary;however if immputs are difficult, to measure,the conipenisatiomiilanm should

increasinglyemphasizeincentiveswith increasein adequ.iacyof outputsas a measure

of performance.We thereforetest thesepredictiomis by specifyingeaseof measuring

inputs as a main effect and include an interactionterm that picks up the effect of

inadequacyof output measureswhen inputs are difficult to measure(see AT model

in Table Sc). In contrast,TCA suggeststhat the designof compensationplan should

focus more on the outputs. However, if output is an inadequatemeasureof per-

formance,TCA hypothesizesthat compensationplans should include an increasing

fraction of salarywith increasingeasein measuringinputs. We testthesepredictions

by specifyinga model where adequacyof output measuresis a main effect and the

interactiontermcapturesthe effect of useof measuringinputswhenoptputmeasures

areinadequate.Finally, thesetwo constrainedmodelscan be comparedwith a model

wherewe include easeof measuringinputs and adequacyof outputsas a measureof

20

J)erformnanceas ummain effects in addition to time interaction ternim (hetweemi thesetwo

main effects).6 The resultsare presentedin Table Sc. It is observedthat while the

interactionbetweendifficulty in measuringinputs andoutputasa measureof perfor-

manceis highly significantand in the hypothesizeddirection in the AT model, the

interactionbetweenoutput beinga bad measureof performanceand easeof measur-

ing inputsis insignificant in theTCA model. Thusour resultslendsupport to the AT

framework. Furthermore,the resultsof an F-testindicatethat thereis no loss in the

explanatorypowerof the AT and TCA models(constrainedmodels)whencomparedl

with that of the unconstrainedmodel.

In summary,we have provided the first empirical investigationof both AT and

TCA basedconstructsthrougha single diata source. We providea testof the com-

peting hypotheseswith respectto input arid outputfactors amid find support for the

predictionsbasedon Agency Theory. Furthermore,while manyfindings in the com-

pensationliteratureareconfirmedand thereforegeneralizeto Germany,we also offer

somenew findings in theform of rejectingsomehypothesesandsupportingnew ones.

The main conclusionwith respectto rejecting thesehypothesesis that someof time

operationahizationsmaynot bevalid; but moreimportantly, our findings suggestthat

an importantconsiderationhasbeenleft out in modelingcompensationplans. While

the extant literature investigatesthe impact of changesin the environmenton the

designof compensationplans holding everythingelse constant(with the exception

of Lal and Staelin1986), salesexecutivesseemto dealwith different selling environ-

mentsthroughnot only the designof compensationplansbut alsoby attractingthe

right type of salespeople.In otherwords, the practiceof salesmanagementsuggests

an interactionbetweendesignof compensationplansandrecruitment/selectionwhile

the theoreticalliterature treatstheseissuesindependently.

6We aregrateful to ProfessorRichardStaelin for his help in developingthe appropriatetestforthesehypotheses.

21

5. EXPLANATORY POWER OF TCA AND A~ENCYTHEORY

Time more recent theoreticaland the empirical salesforcemaumagemnentliterature

has benmefitted inmmensely from two different theoreticaldevelopmnemitsimm the ceo—

imomnics literature, namely TransactionCost Analysis andi Agency Theory. While

sonicauthorshaveusedAgencyTheory as time fommdat.ionifor their investigation,oth-

ershavefocusedon TransactionCost Analysis. Theseseparateinvestigationssuggest

that both thesetheoreticalapproaciresprovidesignificant insightsinto the issi.re of

compositionof salaryandincentivesin salesforceconmpensationplansand theclecisiomi

to emnmploy a direct salesforcein lieu of salesrepresentatives.With this asthe moti-

vationm we conductedour study b’~rimmtegratingconstructsprovided by both Agency

Theoryamid TCA.

Our study provides time first direct evidenceof supportfor both thesetheoretical

approacheswheni tested! sinmultaneouslyin time samime data set. However, a mmatural

dluestiOn that arisesfronmm theseempirical studies is: Whether Agenmcy Timeory and

TCA competewith eachother on’ complementeachother ‘? 1mm theeconionmicsliterature,

thesetheorieshavebeeni traditionally viewed asseparatetheoriesaddressimmgdiffenenit

sets of issues. TCA was developedoriginally to investigatethe boundariesof the firm

and was extensivelyused in understandingissuesregardingvertical integrationvs.

arms length transactions(Williamson 1975). Later,Agency Theorywasdevelopedto

addressissuesrelatedto theinternalorganizationof the firm. More recently,TCA has

also beenappliedto choiceofinternal controlmechanisms(Johnand Weitz 1989) and

AgencyTheoryhasalsobeenusedto studycoordinationand interactionbetweentwo

separateeconomicentities (Lal 1990). The prevailingview in economicsis that the

boundariesof thefirm arenot aswell definedasoriginally thoughtandthesetheories

are viewed ascomplementingeachother rather thancompetingwith eachother. In

the marketingliteratureon designof salesforcecompensationplans, while the early

77

applications of these theoriesviewed them as competingframeworks.more recent.

applicationsare suggestiveof complenmmentingeachother. \‘Vith this hackgroumnid,we

investigatetime explanatorypowerof thesetwo approachesfor the two decisiomms.

To addressthis issue, we estimatethe additional varianceexplainedby Agency

Theoryspecific variablesamid! the TCA specific variables in the decisionto employ

a direct salesforce.This underlinesthe fact that thesetwo theoriesalso havesome

common variables/constructssuchasuncertainty,easeof’ measuringinputs, adequacy

of output as performammcemeasure. We first recognizethe five Agency Theoryspe-

cific constructsto he: time devotedto selling, selling experience,tenure,education

andaverageinmdustr’y inconne. Likewise, we recognizefour TCA specific constructstO)

be size of thesalesforce,rejilaceahility, transaction—specificassetsann! the inmteractioim

betweenuncertaintyand replaceability. Time additional explanatory power of these

two setsof variablesareestimatedthrougha nested-model.The resultsaredisplayed

in Table Ca. We seethat while the imprOvementof the ‘node! x2 is highly significant

from the inclusiomi of TCA specific variables,the improvementof themodel x2 is not

significant from the inclusion of Agency Theoryspecific variables, In other words,

while theTCA specific variablesadda significant explanatorypower in time investiga-

tion of the decisionto havea direct salesforcevs. reps, the Agency Theoryvariables

do not haveany sucheffect. This suggeststhat theinvestigationof thedirect vs. rep

decisioncanbe adequatelyaddressedthrough the TCA framework.

We now reportthefindingsof asimilar investigationfor thedesignof compensation

plans. In this casethe TCA specific constructsand the Agency Theory specific

constructsare the sameas above. In addition, as discussedearlier, we identify the

interactionbetweeneaseof measuringinputs and time devotedto selling as being

AgencyTheoryspecificwhile that betweenuncertaintyand replaceabilityto beTCA

specific. The additional explanatorypower of these two sets of variablesis again

23

estimatedthrough a nested—model.The resultsof this analysisaredisplayedin Table

6b. We see that while the F-value for the change in the sumnm of errors is higimhv

significant from the inclusion of Agency Timeory specific variables, the F-value for

the changein the sum of errorsis not significant from the inclusiomi of TCA specific

variables.In otherwords, while theAgencyTheoryspecificvariablesadd a significant

explanatory power in the investigation of the designof compensationplans, TCA

specific variablesdo not. This suggeststhat the study of the proportion of salary

in the compensationplan can be adequatelyaddressedthrough the Agency Theory

framework. Thus one may conclude that in our study of sahesforcemanagement

decisions,the two theories,Agency Theory and TCA, are less likely to be viewed as )

comniplemnientingeachother.

Our resultsshould he interprettedmm the German context wherewe find strong

legal differencesbetweenthe natureof compensationplaim and termination clauses

for direct and representativesalespeople(ascomparedto the U.S.A., where the dif-

ferencesmnmay riot be as stark). Thereforethe interchangeabilityof TCA and AT in

other countriesmay decreasewhen we observestrongstructuraldifferencesbetween

repsand direct salespeople.

6. SUMMARY AND DIRECTIONS FOR ‘FUTURE RESEARCH

In this study we provide the first testof an integratedset of factorsfrom Trans-

action Cost Analysis and Agency Theory through a dataset collectedoutside the

U.S.A. We therebyprovide the first testof both theseframeworkson a single data

base. Moreover, by collecting the datain Germany,we are ableto addressthe issue

of generalizabilityof the findings in the U.S.A. Indeed, sincemany of our findings

are consistentwith those reportedin studiesbasedon datacollectedin the U.S.A.,

24

we can conclul(1ethat theseframeworkscan be applied also) to situationsoutsidethe

U.S.A.; althoughm less so in the caseof time decisionto employ adirect salesfor’ce.

Among thenew findings in ourstudy, we documentthe impactof somenew vari-

ables and provide evidenmcedisconfirmnungthe effects observe.cl1mm the U.S.A. .More

specifically,we hmmdl timat aspredicted,increasingefiectiveumessof salespeopleincreases

the likelihood of’ employinga reporganization.With respectto thedesignof compen-

sation plamms, we find that time devotedto non-sellingactivities hasa direct positive

imimpact on the proportionof salaryin the total comnlpemisationplanand more interest—

ingly, it also hasan indirect effect throughthe easeof measuringinputs.

We also find (lisconfimminmg evidencefor severalhypothesesthat were either sup-

ported1or not disconfirmedin time U.S.A. Stuidhies. For exanmple,we fimudi that (:()mmipeni—

sationplansinclude ahigher fraction of’ salarywhen salespeoplear easilyreplaceable.

This is in conmtrastwith the insignificanteffectsfound in Johnand Weitz (1989). Sim-

ilarly, the hypothesizedeffect of uncertainity (as mnmeasuredby number‘of custonmers

per salesperson)is rejectedi in our dataset, while the results from the U.S.A. either

support or do not reject this hypothesis. With respectto the direct vs. rep dieci—

sion we find significant disconfirmingeffect of size of the salesferceand significant

confirmingeffectsof travel requirementsand uncertainty. This is in d!irect contrast

with non-significantresultsreportedby Anderson(1985)with respectto eachof these

threevariables.

Finally, the most important finding in our study is from a test of competing

hypothesesbasedon AT and TCA frameworks with respectto the effectsof ease

of measuringinputs andoutput being an adequatemeasureof performanceon the

designof compensationplans. Thesepredictionsarefundamentalto thebasicideasin

the two theoriesand while ourdatasupportthe predictionsfrom AT, thepredictions

from TCA arenot supported.

25

We furthier investigatethecomplementarymratureof thesetwo theoriesin Gernnmanmy

by assessingthe explammatorypowerof thesetwo theoriesfor time two decisions,direct

vs. repsand proportionof salary in the compensationplan. We find that while one

theory is better for explainingone phenomemmon,the other is adequatein explaining

the secondphenomenon.More precisely, while TCA specific variablesdo not add

to explanatorypowerof the Agency Theory specific variablesin the salarydecision,

the Agency Theory specific variablesdo not add to explanatorypower of the TCA

specific variablesin the decisionto employ a direct salesforce. We therefore think

that one has to be cautiousin treatingAT andTCA ascomplimentarytheories.

With respectto directionmsfor future research,thmis is the ‘first study to assess

the generalizabilityof the findings in the U.S.A. to other countriesand cultures;

givemm our findings it is useful to further investigatethe impactof differencesmm legal

environments,commnunicationstyles and! work ethicson the generalizahihityof the

TCA andi AT frameworks. With respectto the usefulnessof AgencyTheory to studly

thedesignof compensationplans,we find that theexisting analysisbasedon a model

of homogeneoussalesforceneedsto be extended.In environmentswheresalespeople

differ alongseveraldimensions.,the interactionbetweenthe choice of compensation

plan and the hiring decisioncan no longer be neglected.In otherwords, the choice

of compensationplanneedsto takeinto accountnot only the motivationalaspectsof

this decisionbut also the kind of salespeoplethat will be attractedto the company

by the designof the compensationplan. A first suchattempthasbeenoffered in Lal

and Staehin(1986) and Rao (1990).

26

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29

APPENDIX I: Description of DependentVariables

DependentVariable, Operationatization, Re,nark.s

Kind of salesforce(direct salespeopleor manufacturer representatives)How many salespeople(employed and independentrepresentatives)are primarily working for your salesorganization (without satesmanagement)?

salespeopleNumber of independentsalesrepresentativesworking in your salesOrganization(A comparisonof thefirst and secondquestionreveals, whethera company uses representatives only, adirect salesJt~rce01(1 hybrid)

Proportion of salary to total pay *)How niany of your salespeopleare compensatedby the following plans ?• Straight Salary %• Straight Commission %• A Combination Plan, such as

- Salary plus Comniission(SALCOM) %- Commissionand Drawing Account %- Salary plus Bonus (SALBON) %- Commissionplus Bonus %- Salary plus Commissionplus Bonus(SACOBO) %

If you are offering combination plans, what level doesthe proportion of variable inconie to total pay typically reach? (VARPERC)

(The variablepropornon wascomputedvia the followingformula: (VARPERC*(( SALCOM÷SALBON+SACOBO)/100)).The dependemitvariable is th,e,i thecomplementto 100%).

*) There is nosinglecompany in the ‘direct salesforce’subsamplethat uses~commissiouanddrawingaccount’or ‘commissionplus bonus’ plans.Thereforetheformula hasbeen simplified and only containscombination plans with somesort of salary.

APPENDIX II: Description of IndependentVariables

Construct (Cronbachs a), Operationalizations, Remarks

Market (market failure)

Salespeoplehardly replaceable(a = .64)When a salespersonquits, wecan easily hire a good replacementOur products can be explainedeasily toward our accounts,such that salespeoplecould sell all of our products already after a short trainingi rile

The products offered by our salespeoplearecomplex

Transaction specificassets(productof ‘total costs’amid ‘percentageof customem;productandcompanyspecificknow-hon‘)

What are the total costsfor training new salespersons(costsof training, compensationof the salesperson)?about DM per salespersonHow much timeof the training is neededfor

% customerspecific know-how,% product specific know-how,% company specific know-how,% know-how of general selling techniques,% other’ ?

Ouput is bad performancemeasure(a = .72)Using outcome measures(i.e. overall sales)how preciselydo they represent the actual effort?How preciselycan you infer the actual individual selling effort from the outcomemeasures?How many factors beyond the control of your salespersonsdo influence the selling outcome?

Easeof measuring inputs (a = .69)It is just not possibleto superviseour salespeoplecloselyIt is difficult to evaluatehow much effort any individual in this group really puts into his jobThesesalespeopletravel somuch that closesupervision is impossibleIt is easy for thesesalespeopleto turn in falsified salescall reports if they want to

Source

John/Weitz(1989)new

new

new

new

similar to Anderson (1985)similar to Anderson (1985)

new

John/Weitz (1989)-John/Weitz (1989)John/Weitz (1989)JohnfWeitz (1989)

Company(frequency of transaction)Sizeof the salesforce

How many salespeople(employedand independentrepresentatives)are primarily working for your salesorganization (without salesmanagement)? salespeople .

John/Weitz (1989)

Time devotedto sellingOf their total working time your salespeopleuse % for salescalls new

Travel requirementsHow many nights do your salespersonsspend in a hotel in atypical month? about nights Anderson (1985)

Environment

Environmental uncertainty (a = .64)How often do you or one of your competitors introduce competitive new products’? (seldom - often)How fast doesthe environment of yourcompanychange (i.e. technology,intensity of competition’?(slowly - fast)How strong do you perceivethe intensity of competition in your market (segment)‘?(low - high)

Salesvolatility (a = .73)How much did the market volume of your industry vary on averageover the last five years?How much did overall salesof your entire salesforcevary on averageover the last five years’!How much did your actual overall salesdiffer from your expectedoverall sales’?

Diversification of riskOne salespersonis on averageresponsiblefor about accounts

similar to Anderson (1985)similar to Anderson (1985)similar to Anderson(1985)

John/Weitz (1989)John/Weitz (1989)JohnfWeitz(1989)

new

Salesperson

EffectivenessSellingExperience:

.41’in imnuili utility requirementTenure:

How many of your salespeopledid prior to the job in your company have• less than three years %• threeto sevenyears %• more than sevenyears % experiencein selling?

How many of salespeoplehave worked in your salesorganization for% lessthan one year,% one to less than three years,% three to lessthanfive years,% five to less than, ten years, resp.% ten yearsor longer

How many of your salespeoplehave receivedtheir highest degree from% Hauptschule(9 yea,-shig/ischiool),

% Mittlere Reife (10yearshighschool),% Abitur (13yearsspecialtrack of highschool),% college-degree,% university-degree’?

Education:(weightedindex)

new

CoughlanfNarasimhan (1992)

Coughlan/Narasimhan (1992)

Coughlan/Narasimhan(1992)Averageindustry income: What is the annual total pay (salary + variable income), that your industry offers an averagesalesperson’?________ DM

Table La.’ Hypothesesandfindingson the vertical integrationissue

Variable

Hypotheses

TCA AT

Anderson

(1985)

Hyp. Supported:V

Not supported:f.

Market (market failure)

- Salespeopleeasilyreplacable

- Transactionspecificassets(TSA)• Product-specificknow-how• Confidentialinformation• Customerloyalty

- Difficultiness in evaluatingperformance

• Output is badperformancemeasure

• Easeof measuringinputs

—

.

+

+

+

+

+

.

+

+

+ *+ ‘~‘~‘

— ~

+

,

V

v”f.

~“

.

Company (frequency of transaction)

- Sizeofthesalesforce

- Time devotedto selling

- Travel requirements

+

—

—

+

n.s.

— **

fl.S.

“

Sellingenvironment

- Uncertainty• Environmentaluncertainty

• Salesvolatility• Diversificationof risk

- Environmentaluncertainty* TSA

000+

.

+

+

n.s.

+ **

..

V

Silesperson

- Effectiveness• Selling experience

- Minimum utility• Tenure• Education• Averageindustry income

—

+

+

+

+~—]: The higher the variable thehigher[lower] is theprobabilityof choosingemployedsalespeople*: significant at the 10%level **: significant at the5% level

***: significant at the 1% level n.s.: not significant

Table lb.’ Hypotheses(1/1(1Findings Regam’dingSaIa,’y asa Percemitageof’ Total Compensation

VariableHypothesesTCA AT

John/Weitz

(1989)1 Lal/Outland!

Staelin (1994)CouglanfNara-sirnhan (1992)

Joseph/Kalwani(1995)

Overall

findingsMarket (market failure)- Salespeopleeasilyreplacable

- Transaction specific assets- In vestment in training- Output is a had performancemeasure- Easeof measuring inputs * time devoted to selling- Difficultiness of measuring inputs

+

+

+

—

+

+

—

— * a)

n.s.n.s.

+ * V

+ * f.

V

f.

Company (frequencyoftransaction)- Sizeof the salesforce- Time devoted to selling- Travel requirements

+

—

—

÷

— ** f.— *** V

— * f fV

Sellingenvironment- Uncertainty

• Environmentaluncertainty• Salesvolatility• Quota achievement• Diversification of risk• Uncertainty* Replaceability

0000

÷

+

÷+

—

n.s.

+ * a)

+ l”I”l’ V

+ ~,“ V

— * f.

+ *** V mixed

~./

Salesperson- Risk aversion- Effectiveness

• Sellingexperience• Age

• Salesper call- Minimum utility requirement

• Tenure• Education• Average industry income

+

—

—

—

+

+÷

.

— *** V

,

— ~ b)

, n.s.

+ ** f.

+ *** V

+ *** V— ~ b)

+ ‘~~‘~‘ V V

f

V

V

R2 (adjusted) I ‘ .22 .68 LR: .15 not reported

+~—j: The higher the influence of the variable the higher (smaller) should be the proportion of salary of the employedsalespeople***:significantat the 1% level**: significant at the 5% level *: significant at the IO% level n.s.: not significant V hypothesis supported f: hypothesis getsno supporta)~Variables are multicolhinear. If included separatelyeach variable is significant(p < .10). When both are included their combined effects are significant.b): Variables are multicollinear. Each construct is significant whenit alone appearsin the model (p < .01) with ‘selling experience’ in the right and ‘average

industiy income’ in the wrong direction. Both are insignificant whe1i introduced into the model at the sametime.

Table2.’ Comparisonofthesample(direct salespeopleonly) with commercialcompensationstudies

Characteristics Kienbaum Krafft/Lal/Albers MUller

Numberofemployees 872 2,081

Annual salesin Million DM 207 315

Annual salesper salesperson 5,857,000DM 2,893,000DM

Salesforcesize(mode) 30 23

Tenure of salespeople(in years) 8.0 7.98

Averageageof salespeople 42.0 41.31

Total pay in DM 95,000 91,200 81,217

Percentageof fixed salary 73.0 % 76.2 % 84.6%

Source: KienbaumVergutungsberatung(1993),pp. 9ff., Verlag NorbertMUller (1992),pp. 10ff.

Table3: Characteristicsof empirical investigationsof Transaction Cost Analysis(TCA) and Age/icy Theory (AT) hypothesesregarding thevertical integration issueand theproportion ofsalaty

Study

Characteristics

Anderson(1985)

JohnlWeitz

(1989)Lal/OutlandlStaelin

(1994)CoughlanfNarasimhan

(1992)JosephlKalwani

(1995)KrafftlLal/Alhers

(1996)

Researchissue.

VerticalIntegration

Proportion ofSalary

Proportion ofSalary

Proportion of Salary Proportion ofSalary

Vertical IntegrationProportion of Salary

Theory tested TCA TCA ‘ AT AT AT TCA and AT

Unit of research SalesDistricts Companies Representatives,Superiors

Companies Companies Companies

Type of SalesForceOrganization

.

Representatives,EmployedSalespeople,Hybrids

Representatives,EmployedSalespeople

EmployedSalespeople

Representatives,EmployedSalespeople,Hybrids

.

EmployedSalespeople

Vertical Integration:Reps vs. EmployedSalespeopleProportion of Salary:EmployedSalespeople

Respondents

.

159 regional salesmanagersfrom 13companiesof theelectronic compo-nents industry

161 manufacturingfirms with annualsalesexceeding$50 million

77 representativesfrom 3 salesforcesof a companysellingcomputersand services

233 companiesfrom39 industries

266companiesfrom a varietyof industries

270companies

Responserate 43.3%.

60.5% (firstmailing: 2 1.5%)

50% (salespeople)90% (superior)

unknown 33% 24.6%

Methodology Mail survey Mail survey Mail survey Secondarydata fromDartnell Corporation

Mail survey Mail survey

Investigation Period 1981 1984-85 1989 1986 1993 1992-93

Investigation Area USA . USA USA USA USA Germany

Table4a.’ Findingson thevertical integration issue

Variable

Hypotheses

TCA AT

Coefficients Empirical

(Logistic regression) findings

Market (market failure)

- Salespeopleeasilyreplaceable

- Transaction specificassets

- Difficultiness in evaluatingperformance

• Output is bad performance measure

• Easeofmeasuringinputs

—

+

+

+ +

— 0.05100 n.s.

0.00006 ~

0.641 10 n.s.

— 1.68490 n.s.

V

Company (frequency of transaction)- Sizeof the salesforce- Time devotedto selling- Travel requirements

+

—

—

+

— 0.00560 ~

—0.04170 ~—0.2 1950 ~

fV

V (TCA)

Selling environment- Uncertainty

• Environmental uncertainty• Salesvolatility• Diversification of risk

000

+

+

—

.

0.16080 ~— 0.04890 n.s.—0.00120 ~

V,

V

Salesperson

- Effectiveness• Selling experience

- Minimum utility• Tenure• Education• Averageindustryincome

—

+++

.

— 0.24320

—0.00960 n.s.0.00490 n.s.

— 0.00001 n.s.

V

Constant 3.28390 n.s.

Model Statistics:Log Likelihood

Model x2Goodnessof Fit

—42.52068.762

107.960

df significance151 1.0000

14 0.0000151 0.9968

+~—]: The higher the variable the higher [lower] is the probability of choosingemployedsalespeople*: significant at the 10% level **: significant at the 5% level ***: significant at the 1% leveln.s.: not significant V: hypothesissupported f: hypothesisnot supported

Table 41,: Comparisonof’Anderson‘.v andourfindings on the vertical integration issue

Variable

Hypotheses

TCA AT

Anderson

(1985)

Our

findings

Market (market failure)

- Salespeopleeasily replacable

- Transactionspecificassets(TSA)• Product-specific know-how• Confidential information• Customer loyalty

- Difficultiness in evaluating performance

• Output is bad performance measure

• Easeof measuring inputs

—

+++

+

+

+

+

+ *

+ ~

—

+

n.s.

***

n.s.

n.s.

Company (frequency of transaction)

- Sizeof the salesforce

- Time devotedto selling

- Travel requirements

+

—

—

+

n.s.

—

n.s.

—

—

—

Selling environment

- Uncertainty

• Environmentaluncertainty• Salesvolatility• Diversification of risk

- Environmental uncertainty * TSA

000+

+

+

—

.

n.s.

+ **

+ ~

n.s.—

Salesperson

- Effectiveness• Selling experience

- Minimum utility• Tenure• Education• Averageindustryincome

.

—

~++

+

—

n.s.n.s.n.s.

+~—]: The higherthe variable the higher [lower] is the probability of choosingemployedsalespeople

*: significant at the 10% level**: significant at the 5% level ***: significant at the 1% leveln.s.: not significant V: hypothesissupported f: hypothesisnot supported

)

)

)

)

Variable

Hypotheses 13 coefficients

TCA AT (Logit regression)

one-tailed

p-values

Empirical

findings

Market (market failure)

- Salespeopleeasily replaceable

- Transactionspecificassets

- Difficultiness in evaluating performance

• Output is bad performance measure• Input easy* time devotedto selling• Easeof measuring inputs

—

+

+

+

+

+

+

0.452

0.022

, 0.1590.4080.003

0.094 *

0.406 n.s.

0.027 ‘~

0.003 ‘~‘~‘~‘

0.485 n.s.

f

•

VV

Company (frequency oftransaction)- Sizeof the salesforce

- Time devotedto selling

+

—

— 0.056

— 0.469

0.244 n.s.

0.001 ~ V

Selling environment

- Uncertainty• Environmental uncertainty• Salesvolatility• Diversificationof risk• Uncertainty * Replaceability

000—

+

+

—

0. 1020.0750,192

—0.326

0.280 n.s.0.204 n.s.0.022 *~*

0.187 n.s.

f

Salesperson

- Effectiveness• Selling experience

- Minimum utility• Tenure• Education• Averageindu~tryincome

I V

Model Statistics:R2

adjustedR2

F

—

+

+

+

— 0.125

0.2410.313

—0.152

.

0.064 *

0.003 ***

0.002 ***

0.070 *

V

.

V

Vf

0.3630.2774.212 (127 cases)

Note: To investigate if uncertainty and the interaction term are not significant due to multicollinearity,we ran regressionswith only one of thesethree variables (uncertainty, replaceability, interaction term) andfind that only replaceability is significant, albeit at a higher significance level (lower p-value).

Table5a: Findingson .ralary as’ a percentageof total compensation

n.s.:

The higher the variable the higher [lower] the percentageof salary should besignificant at the 10% level **: significant at the 5% level ***: significant at the 1% levelnot significant v’: hypothesissupported f: hypothesisnot supported

Table5b: Comparisonof Our FindingsRegardingSalaryasa PercentageofTotal Compensationwith RecentStudies

VariableHypothesesTCA AT

John!Weitz(1989)

Lal/Outland!Staelin(1994)

Couglan/Nara-sii’nhan (1992)

Joseph/Kalwani(1995)

Ourfindings

Market (market failure)- Salespeopleeasily replacable

- Transaction specificassets- Investment in training- Output is a bad performance measure- Ease of measuring inputs * time devotedto selling- Difficultinessof measuringinputs

—

+

++

—

+

+

—

— * a)n.s.n.s.

+ * V

+ * f.

+ *

n.s.

+ **

+ ~

n.s.Company (frequencyof transaction)-Sizeofthesalesforce- Time devoted to selling- Travel requirements

+

—

—

±

— ** f.— *** V

— * f. n.s.—

Sellingenvironment- Uncertainty

• Environmental uncertainty• Salesvolatility• Quota achievement• Diversification of risk• Uncertainty* Replaceability

0000+

+++—

n.s.

+ * a)

+ ~ V

+ ~

— * f. + ‘~‘l’~ V

~n.s.

n.s.

+ **

~.

Salesperson- Risk aversion- Effectiveness

• Sellingexperience• Age• Salesper call

- Minimum utility requirement• Tenure• Education• Average industry income

+

—

—

—

++±

.

— *** V

.

— b)

n.s.+ ** f.

+ *** V

+ ~— ~ b)

+ *** V

— *

.

+ ~

+ ~— *

R2 (adjusted) .22 .68 LR: .15 not reported .28

+~—]: The higher the influence of the variable the higher (smaller) should be the proportion of salary of the employedsalespeople***:significantat the 1% level**: significant at the 5%level *: significant at the 10%level n.s.: not significant V hypothesissupported f: hypothesisgetsno supporta): Variables are multicollinear. If included separately eachvariable is significant (p < .10). When both are included their combined effects are significant.b). Variables are multicollinear. Each construct is significant when it alone appeal’s in the model (p < .01) with ‘selling experience’in the right and ‘average

industry income’ in the wrong direction. Both areinsignificant whenintroducedinto themodel at the sametime.

Table5c: Finding.s’ wit/i unconstrainedand‘INPUT*OUTPUT’

*: significantatthe 10% level***: significantat the 1% level

**: significant at the 5%leveln.s.: not significant

con.s’trained coefficient.v of INPUT, OUTPUT and

VariableUnconstrained(~3coefficients)

AT model(13 coefficients)

TCA model(~3coefficients)

Market (market failure)

- Salespeopleeasilyreplaceable

- Transactionspecificassets

- Difficultiness in evaluating performance

• (1 — Output is bad performance measure)• Inputeasy‘~ time devotedto selling• (1 — Output bad) * Inputeasy• (1 — Inputeasy) * Output bad• Output bad * Input easy• Easeof measuring inputs

0.526 *

0.036

— 0.1740.438 ~‘f’~*

+ 0.006

— 0.019

0.605

0.042

‘

0.462 ~

+ 0. 194 *

+ 0. 141 *

0.530 *

0.036

— 0.179 ‘~

0.439

— 0.018

Company (frequency of transaction)- Size of the salesforce

- Time devotedto selling— 0.058

— 0.502 *~*~*

— 0.064

— 0.515 ~

— 0.058

— 0.502 ~

Selling environment

- Uncertainty• Environmentaluncertainty• Salesvolatility ‘

• Diversificationof risk• Uncertainty* Replaceability

0.1290.0630.167 *~*

— 0.384

0.1700.0680.157 ‘~“I~

— 0.466

0.1310.0630.166 ‘K’~~

— 0.388

Salesperson

- Effectiveness• Sellingexperience

- Minimum utility• Tenure• Education• Averageindustry income

—0.124 *

0.261 ~

0.272 ~

— 0.087

—0.118 *

0.254 ***

0.269 ‘~‘~

— 0.080

—0.123 *

0.261 ~0.272 ~‘K

— 0.086

Model Statistics:R2

adjustedR2

F

0.3720.2814.072

0.3680.2834.314

0.3720.2874.383

Table6a: Explanatorypower of TCA andAT spec~ficvariablesfor the decision to employdirectsale~forcevs. independentrepresentatives

Total modelTotal model withoutAT-specific variables

Total model withoutTCA-~pecificvariables

Numberof variables 14, 9 * 11 ~

—2Log Likelihood(d.f./significance)

ModelX2

(d.f. / significance)

85.040(151/1.000)

68.762(14 / 0.000)

93.265(156/ 1.000)

60.537(9 / 0.000)

107.514(154/0.998)

46.288(11 / 0.000)

Improvementx2-testofthe —2LL-changeagainstthetotal model if theory-specificvariablesareremoved

Improvementx2: 8.225Significance 0.1443

Improvement x2: 22.474Significance 0.0001

*: The five variables not included are ‘Time devoted to selling’, ‘Selling experience’, ‘Tenure’,‘Education’, and ‘Average industry income’

t: The three variables not included are ‘Salespeopleeasily replaceable’, ‘Transaction specificassets’,and ‘Size of the salesforce’

Totalmodel

Total model withoutAT-specific variables

Total model withoutTCA-specific variables

Number of variables 15 9 * 11

R2

adjusted R20.3630.277

0.1470.082

0.3410.278

Partial F-test of the R2 changeagainst the total model if theory-specific variables are removed

F-to-change: 6.268Significanceof F-to-change

<0.000

F-to-change: 0.951Significanceof F-to-change

0.438

*: The six variables not included are‘Input easy* time devotedto selling’, ‘Time devotedtoselling’, ‘Selling experience’,‘Tenure’, ‘Education’,and ‘Average industry income’

t: The four variables not included are ‘Salespeopleeasily replaceable’, ‘Transaction specificassets’,‘Size of the salesforce’,and ‘Uncertainty * Replaceability’

)

)

Table6b: Explanatorypower of TCA and AT spec~flcvariablesfor salary as a percentageof totalcompensation