How to launch a high-tech product successfully: An analysis of marketing managers' strategy choices

HOW TO LAUNCH A HIGH-TECH PRODUCT SUCCESSFULLY: AN ANALYSIS OF

MARKETING MANAGERS’ STRATEGY CHOICES

ERIK JAN HULTINK Derft University of Technology

JAN P.L. SCHOORMANS De@ University of Technology

The launch strategy for a new product is a crucial decision issue for marketing managers. Little agreement exists however about the content of a launch strategy and about the individual and combined effects of its constituent parts on new- product success. In this study, the relative importance of some launch strategy tactics (pricing, promotion, product assortment and competitive advantage) on the expected success of the new product is investigated by using a one-third fractional conjoint- analysis design. All respondents (N=28) were product and marketing managers in the Dutch consumer electronics industry. The results of the study showed that two clusters of managers can be identified with distinct preferred launch strategies. The first cluster of managers preferred a penetration pricing strategy, a small product assortment and a customer oriented promotional campaign. The second cluster of managers preferred a skimming strategy while keeping the product assortment small. We discuss criteria for assigning managers to one of the two clusters and discuss implications of the study for further research.

THE LAUNCH STRATEGY AS A DETERMINANT OF NEW-PRODUCT SUCCESS

In the last decades, much research has been done on the determinants of new-product success and failure. Studies by Rothwell, Freeman, Horsley, Jervis, Roberson, and

Direct all correspondence to: E.J. Hultink, Delft University of Technology, Faculty of Industrial Design

Engineering, Jaffalaan 9, 2628 BX Delft, The Netherlands.

The Journal of High Technology Management Research, Volume 6, Number 2, pages 229-242. Copyright @ 1995 by JAI Press, Inc. All rights of reproduction in any form reserved. ISSN: 1047-8310.

230 THE JOURNAL OF HIGH TECHNOLOGY MANAGEMENT RESEARCH Vol. ~/NO. 2/ 1995

Townsend (1974) Cooper (1979), and Maidique and Zirger (1984) have shown that

seven factors are especially important for new product success. These factors are product

advantage, market knowledge, technological synergy, marketing synergy, market

potential, top management involvement, and the launch strategy. In this study we will

focus on the launch strategy.

Some controversy exists about the content of a launch strategy. Green and Ryans

(1990) state that the launch strategy comprises the actions that determine the initial

positioning of the product in the market-place and contribute to the product’s long-

term success or failure. Biggadike (1979) divides the launch strategy decisions that

determine this initial position in the market into strategic and tactical launch decisions.

Biggadikes’ strategic launch decisions include the relative innovativeness of the new

product, the degree of relative forward and backward integration and the production

entry scale. Choffray and Lilien (1984), Easingwood and Beard (1989) and Ryans (1988)

mention the selection of target markets. Yoon and Lilien (1985) Ryans (1988) and Green

and Ryans (1990) also include the timing of market entry as strategic launch decisions.

Biggadike (1979) considers pricing, promoting and distributing the new product as

tactical launch decisions. We refer to a launch strategy as a particular combination

of launch tactics.

The importance of the market launch for new-product success has been mentioned

by several authors. Empirical research by Cooper and Kleinschmidt (1986) indicated

that the frequency of both strategic and tactical launch activities (e.g., trade shows,

promotional effort, seminars for customers) showed significant differences between

successful and unsuccessful products. Apparently, launch activities were much better

handled in successful projects. Yoon and Lilien (1985) found that the long run success

of “original” new products (i.e., technological breakthroughs) increased with a higher

“degree of expertise in marketing strategy”. In other terms, this means that a proper

launch strategy can increase the chances of success of a new product considerably. Green

and Ryans (1990) have stated that: “the launch strategy provides the platform from which competitive advantage must be gained and sustained throughout the product Zife cycle.” We agree with Green and Ryans (1990) that the launch strategy for a new

product or service is a crucial decision issue.

THE IMPACT OF TACTICAL LAUNCH DECISIONS ON NEW-PRODUCT SUCCESS

Although many authors agree that the launch strategy is crucial to new product success,

it is less understood how specific tactical launch decisions are related to new-product

success. In this study, it was not our aim to deal with all possible tactical launch decisions

exhaustively but rather to find out whether or not the relative importance of some tactical launch aspects on new-product success can be determined empirically. Studies

by Link (1987) Simon (1986), and Traynor and Traynor (1989) and our own qualitative

research with marketing managers in the Dutch industry indicated that especially pricing, promotion, competitive advantage and product assortment choices were

considered relevant launch tactics. In the present study, we will focus on the effect of

these four tactical launch decisions on new-product success.

Launching Successful High Tech Products 231

Pricing Strategy. Especially two pricing strategies are considered important for new products: penetration pricing and skimming. The first strategy refers to using low prices

as the principal instrument for penetrating mass markets early, whereas the latter refers to a policy of high initial prices followed by lower prices (Dean, 1’950). Kotler (1991)

gives some general conditions in which each pricing strategy can be applied best. Kotler states that a penetration price is optimal when:

1) the market is highly price sensitive; 2) production and distribution costs fall with accumulated production experience;

and 3) a low price discourages actual and potential competition.

A skimming strategy is optimal when:

1) a sufficient number of buyers have a high current demand;

2) the high price does not attract more competitors; and

3) the high price supports the image of a superior product.

Some researchers have studied the individual effect of different pricing strategies (e.g., skimming and penetration) on new-product success. In these studies the success of the new product was usually operationalized as the rate and extent of diffusion. Dean (1950), Dolan and Jeuland (198 I), Bass and Bultez (1982) and Kalish (1983) have given normative pricing strategy recommendations from this diffusion perspective. Dolan and

Jeuland (1981) showed that if early adopters have a strong effect on later adopters the pricing strategy is optimal when the price increases at introduction, then peaks, and

decreases later on. Bass and Bultez investigated the optimal pricing policies when costs decline with experience. They concluded that the new product’s price should decline

monotonically.

Maidique and Zirger (1984) and Choffray and Lilien (1984) tested the effect of different pricing strategies on new product success empirically. Maidique and Zirger

(1984) found that success was likely to be greater when a product yields a high- contribution margin to the firm (i.e., skimming). Choffray and Lilien (1984) investigated

the impact of product innovativeness on the type of pricing strategy employed. They

found that original new products (i.e., breakthroughs and new lines) tend to use penetration pricing, apparently considering the long term positive effect of cumulative production on cost (the experience effect), whereas reformulated products (i.e., line extensions and modifications) rely more on skimming strategies, because of the value added by reformulation.

Promotion Strategy. Two promotion strategies have received extensive treatment in

the marketing literature: push and pull promotion. A push promotion strategy involves manufacturer marketing activities directed at channel intermediaries to induce them to carry the product and promote it to end users; whereas a pull promotion strategy is directed at end users to induce them to ask intermediaries for the new product. For example, Davidow (1986), Wind and Mahajan (1987), Eliashberg and Robertson (1988),

Hisrich and Peters (1991) and Kotler (1991) have dealt with these promotion strategies for new products. Hisrich and Peters (1991) stress the importance of customer (pull) promotion because awareness needs to be created for the new product. Levy, Webster


and Kerin (1983) Davidow (1986) and Beard and Easingwood (1991) state that dealer promotion (push) is a very important strategy for marketers, especially in the case of

high-tech products, where dealers are often needed to educate the customer about the

new product.

Product Assortment Strategy. In this study product assortment strategy refers to the

breadth of the product line one year after the introduction of the new product. Traynor

and Traynor (1989) Lambkin (1988) and Hisrich and Peters (1991) dealt with the

impact of the breadth of the product line on new-product performance. Traynor and

Traynor (1989) reported that the completeness of the product line was among the most

important marketing tools for high-technology marketers. Lambkin (1988) found that

the breadth of the product line was associated with the market share achievement of

new firms. Hisrich and Peters (199 1) argue that offering many versions of the same

product to a single segment might actually confuse the customer, especially in the case

of high-tech products. However, by differentiating an innovative product and targeting

the alternatives at different marketing segments, firms can increase their competitive

space. Pioneers and early entrants may even preempt the competition in this way.

Competitive Advantage. The new product’s competitive advantage has repeatedly

been found to be one of the major success factors in new product development. This

competitive advantage can originate from, for example, a better design, a higher quality,

or being more innovative (Cooper, 1984; Cooper & Kleinschmidt, 1987a; Johne &

Snelson, 1988). However, it is still unclear from the literature which competitive

advantage can best be communicated for a new high-tech product. In the present

research we will address this question.

Research Question. In this study we refer to a launch strategy as a particular

combination of launch tactics. The four launch tactics mentioned above have a certain

relationship with new-product success. In the past, these correlations were studied on

a one to one basis. In this study, we are interested in the relative influence of these

launch tactics on new product success. By using a conjoint measurement study, these

relative effects are assessed by their relative importances. This importance can be measured by relating the score given to a certain launch strategy to the composition

of that launch strategy (the specific launch tactics) by a number of experts. The experts

we refer to can be found among marketing managers, who commonly make these kind

of decisions. This leads to the following research question:

How do marketing managers perceive the relative importances of the tactical launch decisions @ricing, promotion, product assortment and competitive advantage) on new product success?

METHOD

Respondents. All respondents (N=28) were product or marketing managers, representing 19 well known companies in the Dutch consumer electronics industry. We

chose these marketing managers because they had experience in launching new high-

tech products. About half of the respondents were approached at the Firato (the Dutch consumer electronics fair) in September 1992. The other half of the respondents were recommended by people who already joined the experiment. These respondents were


contacted by phone and if they agreed to join the experiment, they were sent the postal questionnaire afterwards.

Measuring the Success of a New Product. Measuring new-product performance in

terms of success or failure is not an easy nor a straightforward task. First of all, for

measuring new-product success, many performance measures are available (Cooper &

Kleinschmidt, 1987b; Griffin & Page, 1993; Hart & Craig, 1993). For example, Griffin and Page (1993) identified 75 different measures of new-product success and failure currently being used by academics and by practitioners in the US industry. Cooper

(1984) identified three independent dimensions of new-product success (i.e., financial performance, success rate and market impact). This means that new-product success

is a multi-dimensional concept. To overcome this problem, an overall measure of new- product success was used in this study. Although this measure may seem rather general, Dess and Robinson (1984) found that managers’ global overall perceptions of

performance correlated strongly with more specific objective performance criteria. In this study we used expectations about overall success instead of an actual overall

success measure. In most studies on new-product performance, success is measured in

hindsight. The method relying on managerial hindsight may not be the most valid one

to use because measuring success in hindsight has some serious problems and drawbacks. First, managers often do not remember exactly what strategy was used for

the product (Golden, 1992). Secondly, it is uncertain whether success or failure of the new product is the result of the chosen launch strategy or due to external factors which

occurred between the launch and the measurement of success (Green & Ryans, 1990).

Finally, asking people in hindsight for the reasons of success or failure, as is done frequently in this kind of research, is highly sensitive to attribution errors (Curren,

Folkes, & Steckel, 1992). In this research project, overall expected success of a new high-tech product (the

Photo-CD) was the dependent variable. Overall expected success was defined as the

degree to which one expects the product’s profits to exceed or fall short of the firm’s acceptable profitability criteria for new product investments. This variable was

measured on a 9-point scale, ranging from a complete failure to a very high success. Choosing the New Product: The Photo-CD. Not all new products are the same.

Kleinschmidt and Cooper (1991), using Booz-Allen and Hamilton’s (1982) category scheme, classify new products in relation to products already existing in the market.

Kleinschmidt and Cooper (1991) make a distinction between low innovative products (modifications, revisions, cost improvements and repositions), moderately innovative products (less innovative new lines, new items to existing lines) and highly innovative

products (new-to-the-world products and innovative new lines). This distinction is important because launch decisions are dependent on the newness of the new product.

Hisrich and Peters (1991) for example, state that the introduction stage of the new product’s life cycle will be much longer for a highly innovative product than for a low innovative product because of the likelihood of the consumer’s lack of understanding of the new product. The launch strategy for a highly innovative product should reflect this possible lack of understanding.

In the present research project, marketing managers rated the expected success of different launch strategies for the Photo-CD. We chose this particular new product for two reasons. First, we wanted to study the influence of launch strategies on the expected success of a new-to-the-world high tech product. The Photo-CD (“a


revolutionary electronic photo album”, Philips 1992) can in our view, especially at the

time we collected our data, best be classified as such a highly innovative product.

Watching pictures on a TV screen with the ability to manipulate (e.g., to pan, rotate

and zoom in) is a new-to-the-world product (Urrows & Urrows, 1991). Secondly, we

chose the Photo-CD because the launch of the Photo-CD started at the Firato (The

Dutch consumer electronics fair), where we collected most of our data. This enhanced the realism of the task. Although one may argue that the selection of the Photo CD,

instead of multiple products, can influence the results of the study, we think this is

less of a problem. All respondents were experts in launching new high-tech products

and were familiar with the Photo CD. We chose only one product because we were more interested in marketing managers’ strategy choices when they have to introduce

a certain high-tech product than in how they usually launch their own new products. Conjoint Measurement Task. As indicated before, four launch tactics were selected:

pricing, product assortment, promotion and product’s competitive advantage. In this

study, the launch tactics will be referred to as launch attributes. We use this term because

attribute is the common term in conjoint analysis. For the launch attribute pricing, we included two levels: penetration pricing and skimming. The second launch attribute, product assortment strategy, refers to the breadth of the product line one year after

introduction. In this study we distinguished two levels: introducing a small assortment (3 models) into the market and introducing a large assortment (10 models) into the

market. The third launch attribute refers to the promotion strategy employed for the new product. For this attribute two levels were distinguished: promotion aimed at the

trade or at the consumer (i.e., push versus pull promotion. The last attribute referred to the competitive advantage communicated for the new product). We distinguished

three levels of competitive advantage: a higher quality, a better design, and being more

innovative.

In Table 1 the different launch attributes and levels are shown. In total 24 (2*2*2*3)

different launch attribute combinations are possible. This number of combinations is

regarded as being too large and too time-consuming for respondents. This was especially the case for our sample of marketing managers who were on a tight schedule at the

consumer fair. Therefore, we used Conjoint Designer (Bretton-Clark, 1986) to get a one-third fractional factorial design, resulting in eight different combinations. These combinations represented the experimental launch strategies. A disadvantage of such

TABLE 1 Launch Attributes and Levels

Launch Attribute Levels

Pricing Strategy

Product Assortment Strategy

Promotion Strategy

Competitive Advantage

- Skimming

- Penetration Pricing

- Small Assortment (3 models)

- Large Assortment (10 models)

- Push (Trade)

- Pull (Customer)

- Higher Quality

- Better Design

- More Innovative

Launching Successful High Tech Producrs 235

a fractional design is that it only allows for the estimation of main effects. Each

respondent evaluated the same eight strategies. To avoid order-effects and fatigue, the

different strategies were presented in randomized order by using four different standard

latin squares (Maxwell 8z Delaney, 1990).

Procedure. All respondents were given a self-explanatory questionnaire with written

instructions. The respondents had to imagine that they were being hired as a launch

specialist by a mid-size Dutch consumer electronics company. They had to advise the

company on the appropriateness of eight different launch strategies selected by the

company. This company would be the third company to enter the Photo-CD market.

In a few years, there would be eight competitors altogether on the market. The market

for the Photo-CD was expected to grow in the years to come. Each respondent rated

each of the eight different strategies on its chances of success on a 9-point rating scale.

In order to be able to elaborate on the motivations for the responses, some of the

respondents were interviewed after the task. These interviews were also a check to find

out whether or not the respondents had understood the task.

RESULTS

The Conjoint and Cluster Analysis. Conjoint analysis estimates part-worths for each

attribute level per respondent. The relative importance of a particular attribute on the

overall preference for a launch strategy is determined by calculating the largest absolute

difference in the part-worths of the attribute, the sensitivity (Green & Srinivasan, 1978;

Wittink & Cattin, 1989). In order to check the homogeneity of the sample of 28

managers, a cluster analysis was carried out on the part-worths of the individual

respondents. Two clusters of managers could be identified with different part-worth

patterns. In the cluster analysis, one respondent formed a cluster on its own. We decided

to exclude this respondent from further analysis. The average results (part-worths and

sensitivities) for the two remaining clusters are shown in Table 2.

The sensitivities in Table 2 show that pricing strategy is considered to be the most

important launch attribute in obtaining new-product success in both clusters. The two

clusters differ in the expectations with respect to the successfulness of the particular

price-attribute level. In Cluster 1 the penetration strategy is valued most heavily, whereas

in Cluster 2 the skimming strategy is preferred most.

The first cluster is characterized by penetration pricing, a small product assortment

and pull promotion. This indicates that the managers in Cluster 1 prefer a combination

of a penetration pricing strategy and a small assortment with a promotion strategy aimed

at customers (pull). The expected value of emphasizing competitive advantage is limited

in this cluster. We label Cluster 1 the penetration cluster.

The second cluster is characterized by skimming and a small product assortment.

This means that managers in Cluster 2 prefer a skimming strategy and a small product

assortment for achieving new-product success. Promotion strategy and emphasizing competitive advantage were of relatively little importance. We label Cluster 2 the skimming cluster.

Between both clusters, agreement exists on the breadth of the product assortment. The positive values for the part-worths on this attribute show that managers in both


TABLE 2 Part-Worths and Sensitivities of Strategy Attributes

Strategy Attribute

Cluster 1 (N=14) Cluster 2 (N=13)

Part- Worths Sensitivities Part- Worths Sensitivities

Pricing

Penetration

Skimming

Promotion

Push (trade)

Pull (customer)

Product Assortmeni

Small (3)

Large

Competitive Advantage

Quality

Design

Innovative

1.18 2.38 -0.70 1.40

-1.18 0.70

-0.96 1.92 -0.22 0.44

0.96 0.22

0.18 0.36 0.41 0.82 -0.18 -0.41

-0.02 0.22 -0.26 0.69

0.12 -0.17

-0.10 0.43

clusters believe that the breadth of the product line for a new high-tech product should be small.

We calculated the total utility values of all possible launch strategies for both clusters

by adding up the individual part-worths for all combinations. The launch strategies

were rank-ordered by giving the launch strategy with the highest utility value in both clusters, rank one (see Table 3). Rank-order correlation made clear that the two groups

of managers prefer significantly different but not completely opposite strategies

(Spearman correlation coefficient = -0.54, p = 0.0061). The rank orders show that launch strategies with a very high rank in the first cluster do not have a very low rank in the second cluster, while launch strategies with a very high rank in the second cluster do not correspond to a very low rank in the first cluster.

The Effect of Company Characteristics. The 27 managers in the two clusters represent 18 well known multi-national companies from all over the world. Twelve companies

are represented by one manager. Seven companies are represented by two and one company by four managers. Respondents from the same company were generally not

members of the same cluster. This result indicates that a single overall company-specific strategy does not seem to exist.

Therefore, we analyzed the relationship between cluster membership (i.e., type of launch strategy chosen) and company characteristics. The company characteristics are derived from the annual reports of each of the companies involved. The following two company characteristics are taken into account: (a) The core industry, being consumer electronics or non-consumer electronics (e.g., the computer and photography industry); and (b) The geographical regions of company-head quarters, like Japan, USA and Europe.

We chose these company characteristics because they were objective, easy to interpret and available in the annual reports. The results of this analysis are shown in Table 4.


TABLE 3 The Estimated Preferences for All 24 Launch Strategies

Launch Strategies

Cluster 1 Cluster 2

Penetration Skimming Utility* Rank Utility* Rank

Penetration/ Consumer/ Small/ Design 2.43 1 -0.33 16 Penetration/consumer/Small/Quality 2.28 2 -0.23 15

Penetration/ Consumer/ Small/ Innovat. 2.21 3 0.36 9 Penetration/ Consumer/ Large/ Design 2.07 4 -1.16 22

Penetration/ Consumer/ Large/ Design 1.93 5 -1.06 21 Penetration/ Consumer/ Large/ Quality 1.85 6 -0.46 17

Penetration/Trade/Small/Design 0.51 7 -0.77 19 Penetration/Trade/Small/ Design 0.37 8 -0.73 18

Penetration/Trade/Small/Innovative 0.29 9 -0.08 12

Penetration/ Trade/ Large/ Design 0.16 10 -1.60 24

Skimming/ Consumer/ Small/ Design 0.08 11 -1.50 23 Penetration/Trade/ Large/Quality 0.01 12 -0.90 20

Penetration/ Trade/ Large/ Innovative -0.05 13 1.07 4

Skimming/Consumer/Small/Quality -0.06 14 1.17 3 Skimming/Consumer/Small/Quality -0.13 15 1.76 1 Skimming/Consumer/Large/Design -0.27 16 0.24 I1 Skimming/ Consumer/ Large/ Quality -0.42 17 0.34 10 Skimming/ Consumer/ Large/ Innovative -0.48 18 0.94 5

Skimming/ Trade/ Small/ Design -1.84 19 0.63 7 Skimming/Trade/Small/Quality -1.97 20 0.73 6 Skimming/ Trade/ Small/ Design -2.05 21 1.32 2

Skimming/Trade/ Large/ Design -2.37 22 -0.20 14 Skimming/Trade/Large/Quality -2.51 23 -0.10 13 Skimming/ Trade/ Large/ Innovative -2.58 24 0.50 8

Nofe: * The utility value equals the sum of part worths of a strategy combination

TABLE 4 Company Characteristics and Launch Strategy Clusters

Cluster I Cluster 2 Company Characteristics Penetration Skimming Total

Core Industry*

Consumer Electronics

Non Consumer Electronics 7 11 18 7 2 9

Region Head Quarters**

Japan 5 7 USA 6 1 Europe 3 5

14 13

Notes: * x2 = 3.63, df = I, p = 0.057 (before Yates-correction), Fisher Exact test p = 0.066

** x2 = 4.39, df= 2,~ = 0.111

12

7

8

27


Table 4 shows that the relationship between cluster membership and core industry came close to significance (x2 = 3.63, df = 1, p = 0.057). This trend can be considered conceptually significant. There are some strong indications that managers in the non-

consumer electronics industry are more likely to belong to the penetration cluster.

Although almost all managers in the U.S. companies belong to the penetration cluster,

Table 4 shows that the relationship between cluster membership and region head quarters was not statistically significant (x2 = 4.39, df = 2, p = 0.111).

DISCUSSION

In this study, two major groups of managers with different preferred launch strategies

have been identified. The two groups of managers were labeled the penetration and the skimming cluster. Although for both clusters we started out with four launch tactics, in the penetration cluster only the importances of penetration pricing, a small product

assortment and pull promotion proved to be relevant. In the second cluster skimming and a small product assortment were considered relevant. It seems that for the marketing

managers in both clusters, launch strategies concentrate on two critical decisions: pricing and the breadth of product assortment. In the penetration cluster also promotion is

considered important. In the penetration cluster marketing managers preferred a penetration-pricing

strategy with a customer-oriented promotion and a small assortment. The skimming

cluster emphasized a skimming pricing strategy with a small assortment. The major difference between both clusters is the choice of the pricing strategy. From the qualitative follow-up interviews, a tentative interpretation could be derived with respect to the

managers’ pricing preferences. Managers in the penetration cluster probably rated the

different strategies more according to market share and sales objectives, while managers in the skimming cluster seemed to be more interested in financial success objectives,

like return on sales and profitability. One may conclude that either pricing strategy can be succesfull. This choice may however be dependent on the objectives for the new

product launch (i.e., sales or profit). While some results in our study agree with previous findings, other results were

inconsistent with earlier work. For example, Choffray and Lilien (1984) found that

original new products (breakthroughs and new lines), like the Photo-CD, tend to use penetration pricing. Beard and Easingwood (1991) found that skimming the market

should be considered, especially when the technology of the new product is unique. Our results can possibly refine this discussion. The question is probably not whether penetration pricing or skimming should be used. Instead, our results suggest that either strategy is possible. Penetration pricing should however be combined with a customer- oriented promotion and a small assortment, whereas skimming should be used with

a small assortment and maybe innovativeness as the competitive advantage. Managers in the penetration cluster preferred a pull strategy aimed at the customer.

This finding agrees with previous studies which stressed the importance of a large promotional effort aimed at the customer when the market is unaware of the new product (Barczak, Bello, & Wallace, 1992; Beard & Easingwood, 1991; Kotler, 1991). Especially in the case of a high-tech product, many customer barriers for adoption exist (Sheth & Ram, 1987). Moriarty and Kosnik (1989) mention the high level of market


uncertainty in these industries. It is therefore necessary to have a large promotional campaign aimed at the customer to break these barriers and decrease uncertainties by providing information and education about the new product. Managers in the skimming cluster did not consider the promotion strategy to be important. It is possible that these

managers thought that the market they aimed at was already aware of the existence

of the new product because two competitors were already on the market.

Managers in both clusters believe that the breadth of the product assortment should be small. This finding supports Hisrich and Peter’s (1991) suggestion that especially in the introduction stage of a new-to-the-world product one only confuses the customer

and the dealer with a large assortment. Moreover, one might argue that a large assortment may add to the perceived complexity of the new product and therefore

reduces the chances for new-product success (Rogers, 1983). One of the most important findings from the empirical studies on new-product success

or failure was that new products should have a competitive advantage to be successful

(Cooper & Kleinschmidt, 1987a). This finding was hardly supported in our study. In

the skimming cluster, the attribute level “being more innovative” came close to significance. The importance of being more innovative in the skimming cluster supports

Kleinschmidt and Cooper’s (1991) study on the impact of product innovativeness on

performance. They found that highly innovative products had major product advantages, because more innovative products simply offer greater opportunities for

differentiation. In the penetration cluster, competitive advantage played a minor role

although a design premium was most preferred. It is surprising that the attribute “competitive advantage” played such a minor role. A possible explanation for this finding may be that respondents considered it too difficult to differentiate among the three competitive advantage attribute levels. If the range among the attribute levels was too low, this may have resulted in a low range of part-worths (i.e., a low sensitivity).

Another possible explanation we can think of, is the impact of the exclusion of the intrinsic value of the new product (the physical performance parameters) from our

research design. Although we did this on purpose because we expected the importance of this attribute to dominate all other importances, it may have effected the results on

the competitive advantage attribute. It is possible that respondents formed a global

opinion about the Photo CD instead of opinions on the different levels of the competitive advantage attribute. This may have resulted in small importances attached

to the competitive advantage levels. A third reason may be the newness of the product. This newness, which implies the creation of a totally new market, means that it may be rather difficult for respondents to assess the competitive advantage for the new product because no competing products were in the market yet.

In choosing a launch strategy, marketing managers formulate explicit or implicit expectations about the contribution of the various marketing-mix elements to the future

success of the new product. For high-tech new-to-the-world products it is almost impossible to formulate reliable, numerically specified expectations. Therefore, we want to argue that for a new high-tech product, qualitative expectations are formulated. This process will be influenced by product, market and respondent characteristics. The influence of product characteristics were kept at a minimum in this study because all respondents had to launch the same new product. The fact that managers from consumer electronics and non-consumer electronics companies differ with respect to the launch strategy chosen indicates that market characteristics play a role. Possible


respondent characteristics that may be important in this respect are experience with

the product category, experience with the market and experience in launching new

products in general. The influence of these personal factors on preferred launch

strategies will be an interesting and relevant topic for further research. Another topic

for further research may be the influence of order of entry. In our research the company

was the third company to enter the market. It is still unclear however what the most

appropriate launch strategy should look like when the company is the pioneer of the

new product.

Discussion of the Methodology

In our study only 28 respondents participated. The results of the study, however,

can be considered representative for managers in the Dutch consumer electronics

industry, because a large percentage of the population of marketing managers in that

industry participated. In most studies on the determinants of new-product success and

failure, managers were asked their opinions in hindsight. We chose to measure

expectations about success instead of measuring success in hindsight. This choice was

valuable for two reasons. First, managers in the real world also work with expectations

about success when taking their decisions. Secondly, the relationship between the launch

strategy variables and new-product success was not contaminated by other factors that

typically occur between the launch of a product and the measurement of success when

success is measured in hindsight.

The method of conjoint analysis proved to be a valuable tool in assessing the

preferences for and choices of large numbers of alternative launch strategies. An

advantage of the use of conjoint analysis is that evaluations can be measured in a more

indirect, valid and efficient way. A fractional factorial design was used to make it

possible to collect data at the consumer electronics fair. However, this data collection

procedure inhibited the testing of interaction effects, whereas the use of full factorial

designs does make it possible to test interaction effects as well. This fact should be taken

advantage of in future research with respondents who are on a less tight time schedule.

The combination of the use of expectations and conjoint analysis minimized the

problem of attribution errors. The respondents did not have to attribute success or

failure to a given set of attributes. Instead a score had to be givenfor this set of attributes.

This reason enhances the validity of the results of this study.

A disadvantage of only using expectations is that a comparison with actual results is not possible. In a more refined complex longitudinal research design expectations

should be followed by an assessment of actual results. Despite this disadvantage, we think that working with expectations in an experimental approach has much to offer

for future high-technology launch strategy research.

ACKNOWLEDGMENTS

The authors are greatful to Walle Oppedijk van Veen, Henry Robben, Dirk Snelders,

Herman Brusselmans, Abbie Griffin, and Rudy Moenaert for their helpful comments

on earlier versions of this manuscript.


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How to launch a high-tech product successfully: An analysis of marketing managers' strategy choices