herman et al

Introduction

Bundling of products, product components,and services is an important consideration formanufacturers, retailers, and service providersbringing their goods and services to market.Bundling typically takes one of two forms: pureor mixed (Adams and Yellen, 1976). Purebundling refers to a strategy in which only abundle of items or components is available forpurchase; in other words, buyers must purchasethe bundle, they do not have the option of pur-chasing individual components. In contrast,mixed bundling gives buyers the option ofpurchasing either the bundle, or any or all of theindividual components.

To differentiate their products and servicesfrom the competition, manufacturers, retailers,and service providers often use bundling strate-gies (e.g. automobile option packages,stereo/compact disk/tape deck packages, travelpackages that vary in their comprehensivenessof room, board and entertainment coverage,and automobile service centers that offer pack-ages that vary on their maintenance coverage).Recent work on bundling has provided impor-tant insights with regard to bundling (Guiltinan,1987), consumers’ evaluation of multi-productbundles (Gaeth, Levin, Chakraborty and Levin,1990), their perceptions of savings when theyevaluate bundle offers (Yadav and Monroe,1993), and their evaluation of bundles thatinclude different anchor products, as well asdifferent numbers of products (Yadav, 1994).Nonetheless, many questions about consumers’evaluations of product and service bundlesremain unanswered. Of note, Yadav and Monroe (1993) suggest future research shouldfocus on the joint effects of price and non-priceinformation in consumers’ bundle evaluations.

The purpose of this paper is to examine fourfactors expected to affect consumers’ intentionsto purchase product and service bundles. Thesefactors include: whether the bundle is pure ormixed, the price discounts of a pure bundle incomparison to the sum of the components of amixed bundle, the functional complementarityof the components in the bundle, and the number of components in the bundle. Specifi-cally, we are interested not only in the effects ofeach factor on purchase intention, but also thecombined effects of these factors. We begin by

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Product and servicebundling decisions andtheir effects on purchaseintention

Andreas HerrmannFrank Huber andRobin Higie Coulter

The authorsAndreas Herrmann is Professor of Marketing at the Schoolof Business Administration, University of Mainz, Germany.Frank Huber is Doctoral Student at the School of BusinessAdministration, University of Mannheim, Germany.Robin Higie Coulter is Associate Professor of Marketing,School of Business Administration, University of Connecticut,Storrs, Connecticut, USA.

AbstractExamines the effects of four factors (the bundle: pure ormixed, the price discount, the functional complementarity ofbundle components, and the number of bundle components)on consumers’ intentions to purchase product and servicebundles. The findings were relatively consistent acrossproduct (automobile) and service (automotive service)contexts, and illustrate that pure bundles are preferred tomixed bundles, and a greater price discount is preferred to alesser one. The results also indicate that five componentbundles generate greater purchase intention than eitherthree or seven component bundles, and that “very related”bundle components result in greater purchase intention thaneither moderately or not related components. Additionally,several interactions are present.

Pricing Strategy & PracticeVolume 5 · Number 3 · 1997 · pp. 99–107© MCB University Press · ISSN 0968-4905

reviewing these factors as related to bundlingand intention to purchase, and then, describe astudy of bundling in the context of automobilechoice and automotive service choice. Ourresults provide implications for managerialdecisions related to bundle pricing and composition.

Pricing pure and mixed bundlesThe typical pricing strategy with bundles is tooffer a pure bundle at a discount as an incentivefor consumers to purchase a package rather thanto purchase individual components of the pack-age. Consider the following example. An auto-motive manufacturer offers a sporty package(e.g. a three-pronged steering wheel, sportyseats, tachometer, and four aluminum wheelrims) as a pure bundle for $2,400, or as a mixedbundle, in which case the sum of the compo-nents is $3,000. In the former case, the con-sumer receives all of the components at a 20percent discount; in the latter case, the individ-ual can choose from the components in thebundle (e.g., select only the tachometer and thealuminum wheel rims) but will pay a higherprice per component than would be the case ifhe purchased the pure bundle.

Research suggests that consumers tend to usethe individual component prices for a mixedbundle as their reference price in judging thevalue of a pure bundle that includes the sameitems (Yadav and Monroe, 1993). Thus, con-sumers perceive the pure bundle as providingmore value for the dollar than the mixed bundle,and hence are more likely to purchase the purerather than the mixed bundle.

Number of components in a bundleThe number of components is another concernto those responsible for constructing bundles(Ansari, Siddarth and Weinberg, 1996). Lawless(1991) argued that, from a strategic perspective,the more products (or services or components)that a firm includes in a bundle, the more diffi-cult it is for the competition to duplicate thebundle. Nonetheless, from an informationprocessing perspective, it is important to consid-er just how many bundle componentsconsumers can process and/or factor into theirdecisions. Research suggests that consumersprocess and value information about a set ofattributes, until the amount of information

exceeds their cognitive capacity. This line ofreasoning suggests that more components in abundle is better, i.e. results in greater purchaseintention, until the number exceeds processingcapacity, at which point information overloadoccurs and purchase intention decreases.

Functional relationship among bundlecomponentsIdentification and inclusion of the “optimal” setof components in a bundle is another key con-cern of manufacturers, retailers and serviceproviders. Should a multi-component bundleconsist of functionally-related, complementaryattributes (e.g. a centralized lock system and analarm system) or functionally-unrelated attrib-utes (e.g. a centralized lock system and a sun-roof)? From the seller’s perspective, comple-mentary bundle components simplify cross-selling, post-sales support, and potentiallyincrease consumer loyalty (Lawless, 1991;Paun, 1993). Gaeth et al. (1990) found thatconsumers evaluate bundles consisting of func-tionally-related products differently than theyevaluate bundles consisting of functionally-unrelated products. In our context, one mightargue that on scanning components of a bundle,consumers will perceive a bundle that has com-plementary attributes as more favorable (andhence, more willing to purchase) than a bundlethat is comprised of functionally-unrelatedattributes.

Methodology

We conducted two studies, one in the context of aproduct choice (i.e. likelihood of buying a car)and the other in the context of a service choice(i.e. likelihood of purchasing an automotivemaintenance service package). The componentsunder consideration were the same for the prod-uct and service experiments, they included: typeof bundling (two levels: pure or mixed), pricediscount for the pure bundle in comparison to thesum of the prices for the individual components(three levels: 0 percent, 10 percent, 20 percent),functional complementarity of the components(three levels: very complementary, somewhatcomplementary, not at all complementary), andnumber of components or elements included inthe bundle (three levels: 3, 5, 7).

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Product and service bundling decisions and their effects on purchase

Andreas Herrmann, Frank Huber and Robin Higie Coulter

Pricing Strategy & Practice

Volume 5 · Number 3 · 1997 · 99–107

We conducted two (2 × 3 × 3 × 3) full factori-al experiments in November and December1994 in Munich, Germany. A total of 540 sub-jects (car owners who were in the market to buya new car) from a panel participated in thestudy. The sample, in terms of socio-economicvariables, was representative of the Germanpopulation. Each person was randomly assignedto one of the 54 cells (ten subjects per cell) ineach experiment; thus, it was unlikely that thesubject was assigned to the same cell in bothexperiments. Experiment 1 assessed purchaselikelihood for an automobile and Experiment 2assessed purchase likelihood for an automotiveservice package. Experiment 1 preceded Experi-ment 2 for all subjects.

Based on the cell to which the subjects wereassigned in Experiment 1, they received a sheetthat included information on each of the factorswe manipulated: type of bundle, price discount,functional complementarity and number ofcomponents. Each description contained infor-mation about a standard automobile completelyassembled by a German car manufacturer and apicture of the car’s exterior; this part of thedescription was constant across all 54 cells. (Theexact description of the car is not included in thisdocument, due to the proprietary nature of theresearch.) The description contained two pack-ages, one a pure bundle (with 3, 5, or 7 compo-nents) with a quoted price (i.e. the 0 percent, 10percent, or 20 percent discount compared withthe sum of the individual components), and onea mixed bundle (with the same number of attrib-utes as the pure bundle) with the respectiveprices of the component parts. Functional com-plementarity was operationalized by designingbundles that had functionally-related attributes(e.g. the safety package included: a centralizedsecurity system, an alarm system and a passen-ger-side airbag), and bundles that includedunrelated attributes (e.g. a centralized securitysystem, a sun roof and aluminum wheel rims).Additionally, a statement about whether thecomponents could be purchased only as a purebundle or were available individually (i.e. as amixed bundle) was included on the informationsheet. Tables I and II illustrate three of the 54stimuli for Experiment 1 (the automobile) andExperiment 2 (the service package), respectively.After reviewing the information sheet, subjectsindicated their intention to purchase the

described bundle on a seven point scale in which1 is “Not at all likely to purchase” and 7 is “Verylikely to purchase”.

Findings

Individual effectsOur results indicate main effects for each of thefour bundle factors for both product and servicepurchase intention. First, we found a pricediscount main effect for both the automobile(F2/486 = 138.87; p < 0.001) and the automotiveservice (F2/486 = 35.37; p < 0.001). As might beexpected, as the price discount for the bundleincreased from 0 percent to 20 percent, con-sumers were more likely to report an intention topurchase the product or service bundle (TableIII provides the purchase intention means for theindependent variables). In the product context,the price discount effect size, ω2, explained thegreatest percentage of variance (28); in theservice context, ω2 was 9 percent.

As research suggests, we found that a purebundle resulted in greater purchase intentionthan a mixed bundle for both the automobile(F1/486 = 20.34; p < 0.001) and automotiveservice (F1/486 = 11.25; p < 0.01). The ω2 in theproduct and service contexts was 2 percent and1 percent, respectively.

Our results indicated a main effect for num-ber of components in the bundle for the auto-mobile (F2/486 = 16.29; p < 0.001) and theautomotive service (F2/486 = 15.80; p < 0.001).The ω2 for the product and service bundles,respectively, was 3 percent and 4 percent. Forthe automobile, we found a curvilinear relation-ship; the quadratic term was significant (F1/537 =15.99; p < 0.001), as was the contrast betweenfive attributes and three and seven attributes(t537 = 4.00; p < 0.001). The automotive serviceresults were similar; the quadratic term (F1/537 =23.04; p < 0.001) and the contrast (t537 = 4.80;p < 0.001) were significant. As shown in Figure 1, purchase intention was greatest forboth the automobile and the automotive servicewhen the bundle had five, rather than three orseven, components.

Also, as might be expected, the greater thefunctional complementarity among the compo-nents or elements of a bundle, the greater thelikelihood of purchase of the automobile (F2/539= 44.17, p < 0.001) and the automotive service

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(F2/539 = 44.62; p < 0.001). As the relationshipamong the components increased from “not atall related,” to “somewhat related,” to “veryrelated,” intention to purchase also increased.Again, Table III shows the purchase intentionmeans for the three levels of functional comple-mentarity; “very related” components generat-ed significantly greater purchase intention thanthe other two manipulations. Functional com-plementarity, with an effect size of 11 percent,explained the greatest percentage of variance inthe automotive service purchase intention, andaccounted for 9 percent of the variance in theautomobile purchase intention.

Interaction effectsIn addition to the main effects, we found threesignificant interaction effects for the productand service choices. First, we found a price

discount by functional complementarity inter-action for both the automobile (F4/539 = 7.23; p < 0.001) and the automotive service (F4/539 =4.86; p < 0.01) purchase intention. In general,the findings indicated that the more functionallycompatible the components and the greater theprice discount, the greater the intention topurchase. Post hoc Scheffé analyses (p < 0.05)for the automobile indicated mean purchaseintention for a “very related” component bundlepriced at a 20 percent discount (x– = 5.08) wassignificantly greater than purchase intention forother complementarity-price discount combi-nations. For “very related” and “somewhatrelated” component bundles, a 20 percentdiscount resulted in significantly greater pur-chase intention than a 10 percent discount andno discount; there was, however, no significantdifference in the purchase intention generated

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Table I Examples of product bundle composition

Information about product bundlesStandard model 1* Standard model 2 Standard model 54

Model Standard equipped German Standard equipped German Standard equipped German manufacturer’s car model manufacturer’s car model manufacturer’s car model

Bundle Automatic locking system Automatic locking system RadioAlarm system Alarm system Metallic paintPassenger airbag Passenger airbag Passenger airbag

Sun roofAutomatic locking systemAlarm systemVelour seats

Price DM 2,130 DM 2.130 DM 5.264

Price for individual items Auto locking system DM 750 Auto locking system DM 750 Radio DM 740Alarm system DM 530 Alarm system DM 530 Metallic paint DM 1,260Passenger airbag DM 850 Passenger airbag DM 850 Passenger airbag DM 850

Sun roof DM 1,490Auto locking system DM 750Alarm system DM 530Velour seats DM 960

Total for individual items DM 2,130 DM 2,130 DM 6,580

Available in bundle? Components are available Components are not available Components are not available only in the bundle in the bundle, only individually in the bundle, only individually

Note:*Standard model 1 represents a pure bundle at no discount with three “very related” (security/safety) components

by no discount and a 10 percent discount (seeFigure 2 and Table IV). For “not related” com-ponent bundles, there was no significant differ-ence between a 20 percent and a 10 percentdiscount, but both generated significantlygreater purchase intention than no discount.

For the automotive service, the “very related”component bundle priced at a 20 percent dis-count generated a significantly greater purchaseintention than the “somewhat related” compo-nent bundles priced at a 10 percent discount andat no discount and for all “not related” bundles.For “very related” component bundles, therewas no significant difference in the purchaseintention generated by no discount, a 10 percentdiscount and a 20 percent discount (see Figure 2and Table IV). For less compatible (somewhatand not related) components, there was nodifference in the purchase intention generated bya 20 percent and 10 percent discount; the 10percent discount resulted in significantly greaterpurchase intention than no discount for the “not

related” service bundle, but not for the “some-what related” service bundle.

Second, we found a functional complemen-tarity by type of bundle interaction for the auto-mobile product (F2/539 = 6.66; p < 0.001) andthe automotive service (F2/539 = 3.11; p < 0.05) purchase intention. For both productand service, post hoc Scheffé analyses (p < 0.05)indicated that the pure bundle with “very relat-ed” components generated significantly greaterpurchase intention than each of the other bundletype-functional complementarity combinations.

Third, we found a price discount by numberof components interaction (F4/539 = 4.08; p < 0.01) for the automobile purchase inten-tion. Post hoc Scheffé analyses (p < 0.05) sug-gested that bundles with three, five and sevencomponents at a 20 percent discount generat-ed the same level of purchase intention, andthat they generated greater purchase intentionthan bundles (regardless of the number of

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Table II Examples of service bundle composition

Information about service bundlesService bundle 1 Service bundle 2 Service bundle 54

Description Oil change Oil change Oil changeBrake and brake fluids test Brake and brake fluids test Brake and brake fluids testBattery test Battery test Battery test

CO2 testFan belt test

Change tiresRotate tires

Price DM 320 DM 320 DM 416

Price for individual items Oil change DM 120 Oil change DM 120 Oil change DM 120Bake/brake fluids test DM 140 Bake/brake fluids test DM 140 Bake/brake fluids test

DM 160Battery test DM 60 Battery test DM 60 Battery test DM 30

CO2 test DM 90Fan belt test DM 20Change tires DM 70Rotate tires DM 30

Total for individual services DM 320 DM 320 DM 520

Available in bundle? Services are available Services are not available in Services are not available in only in the bundle the bundle, only individually the bundle, only individually

Note:Service bundle 1 represents a pure bundle at no discount with three “very related” (“regular maintenance”) services

components) priced at a 10 percent or nodiscount. For three and five component bundles, there was no significant differencebetween the purchase intention resulting fromno discount and a 10 percent discount; howev-er, for seven component bundles, a 10 percentdiscount generated a significantly greaterpurchase intention than no discount.

Finally, our results for the automotive ser-vice bundle indicated an interaction betweenthe number of components and functional

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Table III Mean intention to purchase values for main effect results*

Manipulated Automobile Automotive variable bundle service bundle

Price discount0 percent 2.69 a,b 2.67 a,b

10 percent 3.24 a,c 3.14 a,c

20 percent 4.29 b,c 3.62 b,c

BundlePure 3.59 3.30Mixed 3.23 2.99

Number of componentsThree 3.36 a 2.99 a

Five 3.71 a,b 3.51 a,b

Seven 3.16 b 2.93 b

Functional complementarityRelated components 3.91 a,b 3.69 a,b

Somewhat related 3.29 a 3.12 a,c

Not at all related 3.02 b 2.62 b,c

Note:* Mean values are based on a 1 to 7 scale in which 1 is “Not at all likelyto purchase” and 7 is “Very likely to purchase”. Within columns (i.e. forthe product or for the service) and by manipulated variables, meanswith the same superscript differ significantly based on Scheffé compar-isons (p < 0.05). For example, with regard to the automobile bundle andthe price discount manipulated variable, the 0 percent discount resultedin significantly lower purchase intention than the 10 percent pricediscount (represented by the a) and the 20 percent price discount(represented by the b), and the 10 percent discount resulted in signifi-cantly lower purchase intention than the 20 percent price discount(represented by the c).

5

4

3

2

1

0

Purchase intention

3 5 7Number of components

KeyProductService

Figure 1 Purchase intention means for the number of components in productand service bundles

7

6

5

4

3

2

1

0

Purchase intention

Non-related Very related

Functional complementarity of components

Automobile

7

6

5

4

3

2

1

0

Purchase intention

Non-related Very related

Functional complementarity of components

Automotiveservice

Key0 per cent disc10 per cent disc20 per cent disc

Key0 per cent disc10 per cent disc20 per cent disc

Figure 2 Purchase intention means for the functional complementarity by pricediscount interaction

complementarity (F4/539 = 4.50; p < 0.001).Post hoc Scheffé analyses (p < 0.05) indicatedthat five “very related” components resulted ingreater purchase intention than any othernumber of components-functional complemen-tarity combination.

Managerial implications and recommendations

Our findings suggest that manufacturers, retail-ers, and service providers considering abundling strategy should pay attention to thefour variables we considered, since each had aneffect on purchase intention, and several inter-actions were present. Our findings were relative-ly consistent across product (automobilechoice) and service (automotive service choice)contexts, and in general, they illustrated thatpure bundles are preferred to mixed bundles,and a greater price discount is preferred to a

lesser one. Our results also indicated that fivecomponent bundles generate greater purchaseintention than either three or seven componentbundles, and that “very related” bundle compo-nents result in greater purchase intention thaneither moderately or not related components.For the automobile, price discount explained 28percent of the variance in purchase intention,and functional complementarity explained ninepercent. For the automotive service, the func-tional complementarity of componentsexplained 11 percent of the variance, and pricediscount explained nine percent.

Product bundlingOur results suggest that manufacturers andretailers should be sensitive to interaction effectsbetween bundle factors, particularly with regardto the price discount. First, managers need toconsider the functional complementarity ofbundle components when establishing pricediscounts. Our recommendations regardingpricing discounts for the varying levels of func-tional complementary bundles are based on twoassumptions:(1) relatively equal costs and mark-ups for each

of the three types of functional complemen-tarity bundle packages; and

(2) an overall increase in revenue because theincreased cost of a higher discount is offsetby a greater increase in demand (i.e. pur-chase intention).

Thus keeping in mind these assumptions, ourresults for “very related” and “somewhat relat-ed” component bundles suggest offering a 20percent discount because it resulted in signifi-cantly greater purchase intention than a 10percent discount and no discount. The value ofa 10 percent discount for these two levels offunctional complementarity, however, warrantsconsideration, because offering a 10 percentdiscount (rather than no discount) does notresult in increased purchase intention. For “notrelated” component bundles, a 10 percentdiscount is recommended because it resulted inthe same level of purchase intention as a 20percent discount, yet exceeded the purchaseintention generated by no discount.

The price discount by number of compo-nents interaction also has pricing implications.Regardless of the number of components (three,

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Table IV Mean intention to purchase values for functional complementarity byprice discount results*

Manipulated Automobile Automotive variable bundle service bundle

Not at all related components0 percent 2.23 a,b 1.90 a,b

10 percent 3.15 a 2.90 a

20 percent 3.67 b 3.62

Somewhat related components0 percent 2.53 a 2.53 a

10 percent 3.22 b 3.1520 percent 4.12 a,b 3.67 a

Very related components0 percent 3.30 a 3.5710 percent 3.35 b 3.3820 percent 5.08 a,b 4.13

Note:* Mean values are based on a 1 to 7 scale in which 1 is “Not at all likelyto purchase” and 7 is “Very likely to purchase”. Within columns (i.e. forthe product or for the service) and by manipulated variables, meanswith the same superscript differ significantly based on Scheffé compar-isons (p < 0.05). For example, with regard to the automobile bundle andthe “not related” components level of functional complementarity, the0 percent discount resulted in significantly lower purchase intentionthan the 10 percent price discount (represented by the a) and the 20percent price discount (represented by the b)

five or seven) in a product bundle, a 20 percentdiscount resulted in a greater purchase intentionthan no discount or a 10 percent discount.Thus, three, five and seven component bundlesshould be priced at a 20 percent discount. Ifresources preclude offering a 20 percent dis-count for three or five component bundles, nodiscount is recommended (since no discountand a 10 percent discount result in the samelevel of purchase intention). For seven compo-nent bundles, a 10 percent discount (comparedwith no discount) is justified because it doesaffect purchase intention.

Finally, when constructing product bundlesdesigned to generate purchase intention, a purebundle with “very related” components gener-ates greater purchase intention than other func-tional complementarity-bundling combinations.

Although our results do not indicate a four-way significant interaction among the variablesunder investigation, a pure bundle with five“very related” components with a 20 percentdiscount achieved the highest purchase inten-tion (on a seven-point scale) for the automobile(x– = 6.3). Other product combinations with thepurchase intention greater than or equal to 5included:(1) a pure bundle with seven “very related”

components at a 20 percent discount;(2) a pure bundle with three “very related”

components at a 20 percent discount; and(3) a mixed bundle with five “very related”

components at a 20 percent discount.

Service bundlingOur results also indicate that service providersshould be attentive to interaction effectsbetween bundle factors, particularly those withregard to functional complementarity. First andsimilar to the product context finding, serviceproviders need to consider the functional com-plementarity of bundle components whenestablishing the price discount. Our resultsindicated that a 10 percent discount generatedthe same level of purchase intention as a 20percent discount. For a bundle with “very relat-ed” components, offering a discount (either 10percent or 20 percent) results in no greaterpurchase intention than no discount. For“somewhat related” component bundles, thereis no significant difference in the purchaseintention generated by no discount and a 10

percent discount. For “not related” componentbundles, the 10 percent discount results insignificantly greater purchase intention than nodiscount. Making the same cost/demandassumptions as for products, our findings indi-cate that service providers must carefully assessthe value of pricing “very related” service bun-dles at a discount because there is no differencein the purchase intention generated from thethree tested discount levels. For “somewhatrelated” and “not related” component servicebundles the recommended price discount is 10percent.

Two other functional complementarityinteraction effects (with the type of bundle andthe number of components) have implicationsfor service providers’ bundle construction. Aswas the case with product manufacturers,service providers should establish pure servicebundles with “very-related” components(rather than other functional complementarity-bundling combinations) to achieve greaterpurchase intention. Further, constructing abundle with five “very related” componentsshould achieve greater purchase intention thanother functional complementarity-number ofcomponents combinations.

Although our results do not indicate a signifi-cant four-way interaction among the examinedvariables, similar to the automobile findings, apure bundle with a 20 percent discount thatincludes five “very related” components achievedthe highest purchase intention (on a seven-pointscale) for the automotive service (x– = 5.9). Noother service combination had a purchase inten-tion with a scale value of five or more.

Summary and future researchThis study examined the individual and com-bined effects of four bundle factors on productand service purchase intention. Price discountand complementarity of bundle componentsappear to be key drivers of purchase intention forboth the automobile and automotive servicebundles. Moreover, the interaction between thetwo factors suggests that there is a threshold levelof discounting necessary to affect purchase inten-tion. For “very related” component productbundles, the 20 percent discount results ingreater purchase intention than the 10 percentdiscount and no discount; there is no differencebetween the 10 percent and no discount in terms

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of generating purchase intention. For “veryrelated” component service bundles, the threediscount levels (0 percent, 10 percent and 20percent) resulted in the same level of purchaseintention. Thus, it appears that a 20 percentdiscount is effective in generating purchase inten-tion for the “very related” component productbundle, whereas no discount or a 10 percentdiscount may suffice for the service bundle.

For the “somewhat related” componentproduct bundle, a 20 percent discount results inthe greater purchase intention than a 10 percentdiscount and no discount. For the “somewhatrelated” component service bundle, the 20percent discount generated greater purchaseintention than no discount, but not greater thana 10 percent discount. Again, it appears that a 20percent discount and a 10 percent discount areeffective in generating purchase intention for theproduct bundle and service bundle, respectively.

For unrelated component product and ser-vice bundles, a 20 percent discount resulted inthe same level of purchase intention as a 10percent discount, and both generated greaterpurchase intention than no discount. Thus, a 10percent discount appears to be a cost effectivemeans of achieving purchase intention for boththe product and service unrelated componentbundle.

Future research should continue to investi-gate the individual and combined effects ofbundle components for other service and prod-uct choices. From a managerial and cost evalua-tion perspective, it is important that researchalso investigate the cost per bundle-price dis-count and price discount-demand relationshipsto ascertain the added value of discounts in

increasing purchase intention. Studies mightalso examine bundle factor effects not only onpurchase intention, but also on other consumerinformation processing variables. Additionally,the effects of these bundle factors might beinvestigated with regard to consumer productand service loyalty, as well as with regard tostrategies for effectively communicating bundleinformation to consumers.

References

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Ansari, A., Siddarth, S. and Weinberg, C.B. (1996), “Pricing abundle of products or services: the case of nonprofits,”Journal of Marketing Research, Vol. 33, February, pp. 86-93.

Gaeth, G.J., Levin, I.P., Chakraborty, G. and Levin, A.M.(1990), “Consumer evaluation of multi-productbundles: an information integration analysis,” Marketing Letters, Vol. 2 No. 1, pp. 47-57.

Guiltinan, J.P. (1987), “The price bundling of services: anormative framework,” Journal of Marketing, Vol. 51,April, pp. 74-85.

Lawless, M.W. (1991), “Commodity bundling for competitiveadvantage: strategic implications,” Journal of Management Studies, Vol. 28, May, pp. 267-80.

Paun, D. (1993), “When to bundle or unbundle products,”Industrial Marketing Management, Vol. 22, February,pp. 29-34.

Yadav, M.S. (1994), “How buyers evaluate product bundles: amodel of anchoring and adjustment,” Journal ofConsumer Research, Vol. 21, September, pp. 342-53.

Yadav, M.S. and Monroe, K.B. (1993), “How buyers perceivesavings in a bundle price: an examination of a bundle’stransaction value,” Journal of Marketing Research, Vol. 30, August, pp. 350-8.

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