Analogical Reasoning About New Product Introductions By Experts and Novices

ABSTRACT - A study was conducted to examine the processes by which expectations for future introductory patterns are developed for novel (new-to-the-world) high-tech products. Our findings indicate that high-tech novices and high-tech experts differ significantly. Specifically, novices appear to base expectations for a novel product on observations about a familiar product that shares salient attributes with the novel product. Experts, on the other hand, are unlikely to be influenced by the observed history of such a product.



Citation:

Michelle L. Roehm, Derrick S. Boone, and Harper A. Roehm, Jr. (1999) ,"Analogical Reasoning About New Product Introductions By Experts and Novices", in E - European Advances in Consumer Research Volume 4, eds. Bernard Dubois, Tina M. Lowrey, and L. J. Shrum, Marc Vanhuele, Provo, UT : Association for Consumer Research, Pages: 161-165.

European Advances in Consumer Research Volume 4, 1999      Pages 161-165

ANALOGICAL REASONING ABOUT NEW PRODUCT INTRODUCTIONS BY EXPERTS AND NOVICES

Michelle L. Roehm, Wake Forest University, U.S.A.

Derrick S. Boone, Wake Forest University, U.S.A.

Harper A. Roehm, Jr., Wake Forest University, U.S.A.

ABSTRACT -

A study was conducted to examine the processes by which expectations for future introductory patterns are developed for novel (new-to-the-world) high-tech products. Our findings indicate that high-tech novices and high-tech experts differ significantly. Specifically, novices appear to base expectations for a novel product on observations about a familiar product that shares salient attributes with the novel product. Experts, on the other hand, are unlikely to be influenced by the observed history of such a product.

Prior research suggests that a consumer’s decision to buy a high-tech product is influenced by expectations about when a new version of the product will be introduced (Balcer and Lippman 1984). Thus, for example, a consumer’s decision to buy a palmtop computer may be affected by his/her expectations for when the next new model is likely to become available. More specifically, when a consumer believes that the time until the next generation will be short, the likelihood of purchasing the current version is lower than when the time is estimated as fairly long. Several explanations for this behavior are that a short time estimate imlies that the current version will soon be obsolete, that it will be difficult to obtain replacement parts for or that there may be decreased technical assistance.

Given the pivotal role of consumers’ "intergenerational timing" expectations in the purchase/delay purchase decision, it is not surprising that these inferences have begun to attract research attention. In particular, recent studies have explored development processes for these expectations (Cripps and Meyer, 1994). An intuitive finding in this research is that such expectations can develop from observations about past introductory patterns (Boone, Lemon and Staelin, 1999). That is, individuals tend to form expectations about future introductory timings by projecting out past introductory patterns for the same product. This implies that, for instance, expectations for a palmtop computer’s next introduction will often be based on a sense of how long the intergenerational time span has been for this product in previous iterations.

A question that remains to be addressed is how expectations are formed when there is no historical information available. For example, for the first generation of a new product in a new product categoryCfor which previous intergenerational timelines are nonexistentChow does a consumer develop timing expectations? This is the central issue of the present research. For guidance, we turn to a contemporary theory of how expectations, in general, are formed for novel items.

Learning by Analogy

When developing expectations for a novel product, consumers may often attempt to apply knowledge that they already have about some other product. When this occurs, the consumer is learning by analogy (Gregan-Paxton and Roedder John 1997). Although numerous circumstances may call for analogical reasoning, it seems especially likely to take place when consumers are curious about characteristics that cannot be observed in an initial encounter with the novel product. For example, imagine that a consumer is shopping in an electronics store and encounters an E-Book (electronic book) for the first time. While some characteristics, such as physical features and price, may be obvious from a simple visual examination of the product, other characteristics cannot be observed. An example of such a characteristic would be the length of time before the current E-Book model will be replaced with a new version.

To learn about this characteristic, the consumer may apply analogical reasoning. In so doing, he or she would transfer over information about the intergenerational timing of some other product with which he or she is more familiar. For example, perhaps the consumer who encounters the E-Book has some knowledge of palmtop computers. This knowledge base might include information about how often new versions become available. By activating this knowledge base, the introductory timing of the palmtop can be projected onto the E-book to create an expectation for the intergenerational timing that will be associated with the E-Book.

Recent research provides insights into the multi-stage process by which knowledge is transferred analogically from a known product such as the palmtop computer to an unknown product such as an E-book (for summaries of this literature see Gentner and Markman 1997 and Gregan-Paxton and Roedder John 1997). First, an individual who is exposed to an unknown product accesses some known product (called a "base" in the analogy literature) that may provide information to transfer to the unknown product (termed the "target"). Prior research suggests that the base products that are most likely to be accessed are those that share salient attributes with the target (Gentner, Ratterman and Forbus 1993; Ross 1987). Thus, upon viewing an E-book (unknown target), a consumer might access knowledge of palmtop computers, because palmtops share attributes such as size, shape, color, and so on.

Next, the consumer attempts to map known characteristics of the base product (palmtop) onto the novel product (E-Book) to verify their smilarity. For example, perhaps the consumer’s knowledge base for palmtops includes their approximate weight and price range. By activating this information, the consumer can map it to what can be observed about the E-Book. The objective in this stage is to verify that observed characteristics of the E-Book correspond to those known for palmtops. Such a correspondence causes the mapping to seem sound, and to thus permit transfer of further information about the palmtop to the E-Book. For instance, if the weight and price range that are known for the palmtop seem similar to those observed for the E-Book, then other information that cannot be observed for the E-BookCsuch as the intergenerational timing between product versionsCmay also be inferred to be true of the E-Book.

Reflecting on this theory of analogical learning, it seems that purchase likelihood for a new product is at the mercy of the expectations for products that look like it. Such products are, after all, what are most likely to be accessed as an information source and used as a basis of transfer. However, this assumes that the mapping phase produces verification of similarity of the base and target products. If, on the other hand, serious inconsistencies are identified during mapping, the match between the base and the target will seem insufficient to support the transfer of further information.

The Moderating Role of Expertise

Recent research suggests that the probability of identifying inconsistencies that would interrupt transfer of expectations from a known base (palmtop) to an unknown target (E-Book) may relate to expertise with the base product. Specifically, base experts may be more likely than base novices to recognize discrepancies that will interrupt transfer.

Experts’ knowledge structures are richer than novices. Importantly, the expert structure is likely to contain both attributes and deeper functional information about the base product (Alba and Hutchinson 1987; Pennington 1987; McKeithen, Reitman, Reuter and Hirtle 1981). Hence a palmtop expert should not only know the typical size, shape, color, weight, price and the general frequency with which new versions are introduced, but also functional aspects of a palmtop such as that it can process spreadsheet formulas and connect with the internet.

With new-to-the-world products of the type we are studying, this deeper knowledge seems likely to lead to recognition of discrepancies between a base and a target. If a novel product shared attributes and functions with extant products, it would not be truly novel. In many cases, such as with the E-Book, the really new product is introduced specifically to offer a heretofore unavailable combination of functions. Hence, when a palmtop expert attempts to map functions such as spreadsheet processing to the E-Book, a mismatch will be identified. When this occurs, transfer should be interrupted.

In contrast, novices are less well-equipped with the kind of knowledge that may bring such discrepancies to light. By definition, the base knowledge structure of the novice should be relatively impoverished. Although it may include attribute information that is salient about the base, it is unlikely to include deeper functional information (Alba and Hutchinson 1987; Murphy and Wright 1984; Schoenfeld and Hermann 1982). Hence, novices with respect to palmtops may know certain attributes, such as their typical size, shape, color, weight, price and the general frequency with which new versions are introduced. However, novices are unlikely to understand functional aspects of a palmtop such as its capability to process spreadsheet formulas and connect with the internet.

With primarily an attribute-based knowledge structure, a novice is unlikely to uncover substantial differences between the base and the target. In theory, the base (palmtop) was retrieved because it does share some salient attributes with the target (E-Book). As a result, differences that novices could identify are virtually eliminated at the outset. Further, if novices are unlkely to notice differences between a new-to-the world product and an existing product that shares surface attributes, then novices are likely to complete the transfer of knowledge and expectations from the known base (palmtop) to the unknown target (E-Book).

On the basis of the foregoing discussion, we predict that when considering a purchase of a novel product, novices will be influenced by intergenerational timing for a familiar product that has similar salient attributes. When the familiar product’s introductory time frames seem relatively long, the novice will estimate the novel product’s future intergenerational time spans as longer than when the familiar product’s time frames seem relatively short. Consequently, novices’ purchase intentions should vary according to these estimates. Specifically, the purchase intentions should be higher when the expected intergenerational time are relatively long than when they are relatively short.

Experts, on the other hand, will be unlikely to be influenced by time frames observed for products that share attributes, if there are differences between the products at a deeper functional level. Thus, there should be no difference in experts’ expectations for a novel product’s future intergenerational time frames, regardless of whether they believe a physically similar product has a history of relatively long or relatively short intergenerational periods. It follows that purchase likelihood should correspondingly not vary for experts.

These observations are consistent with research that has been conducted by Novick (1988). She exposed both expert and novice problem solvers to practice problems and trial problems that shared attributes but not deeper functional solution principles. Novices tended to incorrectly transfer the solution from the practice problem to the trial problem on the basis of the attribute similarity between problems. Experts, in contrast, tended not to transfer the solution, presumably because of differences that were noted at the deeper level and implied that further transfer was inappropriate.

STUDY

An exploratory study was conducted to examine our hypotheses. During the experiment, subjects were incidentally exposed to information about intergenerational time frames for a "leading palmtop computer." The times given were manipulated such that half of our participants were exposed to times that were relatively long, and half were exposed to times that were relatively short. This manipulation of perceived palmtop intergenerational times was combined with an expertise variable to investigate the effect on purchase intentions for a novel product with attribute resemblance to a palmtop computer. In keeping with the current theorizing, we anticipated that novices’ purchase intentions for the novel product would vary as a function of perceived intergenerational timing for the palmtop, but that experts’ intentions would not vary thusly.

Subjects and Procedures

Subjects were 40 MBA students who participated in the study during a regular class period. Our entire study was broken into two parts, which were represented to subjects as two independent and unrelated experiments. Part One ("Experiment 1") was intended to incidentally expose subjects to product introduction timing information for a typical palmtop computer. In such a way, we hoped to unobtrusively make available information that could be applied to a physically similar new product in Part Two ("Experiment 2").

"Experiment 1" was introduced as an investigation of the methods that consumers use to remember detailed information about products. Instructions for the experiment informed subjects that they would be presented with some product information and later tested on the accuracy of thir recall for this information.

The product information they were given was a listing of introduction dates and intergenerational timings for a palmtop. Two versions of this listing were developed for the experiment. Half of the subjects were given a listing with relatively short time spans, where the average time between generations was 11 months. The second half of subjects were given a listing with a relatively longer time span, in which the average time between generations was 18 months (see Appendix for an example). The two versions of the information were meant to encourage perceptions of short or long times between palmtop computer introductions.

Subjects were encouraged to study this information and to use their favorite memorization method to learn as many of the given product details as possible. In keeping with the alleged purpose of "Experiment 1", subjects were then asked to list as much of the information as they could and to write a short description of the method they’d used to commit the information to memory. This concluded "Experiment 1."

"Experiment 2" was then introduced. To support the cover story that two different studies were being conducted, the booklet for "Experiment 2" was formatted differently from "Experiment 1," using differently colored paper, different text fonts, and different page layouts.

Preliminary instructions for "Experiment 2" were to read an ad for a brand new product, the E-Book. This ad showed a picture of the product, which physically resembles a palmtop computer. The ad also included brief copy that highlighted key attributes and benefits of the new item. For example, these claims included "Lightweight at only 14 oz" and "Small and convenient to hold." After reading the ad, subjects turned the page to find two questions relating to their interest in purchasing and likelihood of purchasing an E-Book if money were no object. Subjects responded on 1-7 semantic differential scales anchored by not interested/very interested and not likely/very likely.

Next, two questions were presented regarding the anticipated time span before the next generation of E-books would be introduced. The first of these items asked subjects to indicate how long they thought would be before a new E-Book is introduced on a 1-9 scale anchored by short time/long time. The second question asked for an estimate in months of the time between generations of E-Books. These two items allowed us to investigate whether differences in purchase interest and likelihood corresponded to differences in expected intergenerational times for the E-book.

Subjects then encountered a quiz that asked them to define as many of the following high-tech terms as they could: LAN, Java, Perl, modem, ethernet, dongle, universal serial bus, HTML, FTP, proxy server. It was expected that high-tech experts would be able to define more terms than high-tech novices, and therefore that this quiz would allow us to separate our subjects into groups of relative novices and relative experts. Those who defined more than the median (6.0) number of words were deemed Experts, and those who defined fewer than the median number of words were designated as Novices.

Finally, subjects received a question measuring perceived times between palmtop introductions. This was intended to serve as a check on the adequacy of the introductory timing prime at producing perceptions of relatively long or relatively short intergenerational times for palmtops. Subjects provided an estimate of the length of time for palmtops between introductions on a 1-7 scale anchored by short time/long time.

Analysis

Prior to conducting the analyses of primary interest, an analysis of variance (ANOVA) was conducted on the expectations for palmtop computer introduction time frames. This step allowed us to perform a check on the manipulation of perceptions regarding the palmtop computer. A two-way full-factorial ANOVA was run with high-tech expertise (high vs. low) and palmtop introducton timing (long vs. short) primed by the product information in "Experiment 1" (this variable is hereafter referred to as "priming condition"). The dependent variable consisted of responses to the survey question about time between palmtop introductions. If the manipulation were successful, then those subjects who saw the list with relatively long time spans should estimate palmtop intergenerational time frames as being longer than those who saw the list with relatively short time spans. Results of the analysis were consistent with our predictions. The only significant effect was a main effect for priming condition (F (1, 36)=28.58, p<.001). Means on the dependent variable suggest that subjects in the long-time priming condition expected a significantly longer time between palmtop introductions (X=4.92) than subjects in the short-time priming condition (X=3.60). This result implies that the priming manipulation was successful in producing differences in the perceived intergenerational time frames for palmtops.

The key hypotheses of interest were that whereas novices would apply expectations for the palmtop to expectations for the E-Book and vary their purchase intentions accordingly, experts would not apply palmtop expectations to the E-Book and thus would not vary their purchase intentions. As a first step toward testing these hypotheses, a two-way full factorial ANOVA was conducted on responses to each question related to interest in and likelihood of purchasing the E-Book. Independent variables for these analyses were expertise (expert, novice) and priming condition (long time, short time). It was anticipated that novices would be significantly more interested in and likely to purchase an E-Book when the palmtop introductions seemed relatively long than when they seemed relatively short. Experts, on the other hand, were predicted to be no more or less interested in and likely to purchase an E-Book after having seen the long-time priming list or the short-time priming list.

Significant interactions between expertise and priming condition were observed for both the interest (F (1, 36)=3.82, p<.058) and likelihood of purchase (F (1, 36)=4.04, p<.052) dependent variables. Follow-up contrasts demonstrate that these interactions were driven by a greater interest in (X=5.89 vs. 4.73; F( 1, 36)=8.35, p<.007) and likelihood of purchase (X=6.00 vs. 5.09; F( 1, 36)=4.70, p<.037) among novices when the primed palmtop introduction timing was long than when it was short. In contrast, experts did not differ in interest (X=5.27 vs. 5.22; F( 1, 36)=0.02, p<.901) or purchase likelihood (X=5.28 vs. 5.56; F( 1, 36)=0.46, p<.504) as a function of priming.

These findings support a relationship between perceived palmtop introductory time frames and purchase intentions for E-Books for novices but not experts. However, one facet of our theory remains to be tested, namely the intervening assumption that novices’ (but not experts’) expectations for the E-Book were influenced by expectations for the palmtop. To examine this hypothesis, we conducted two additional ANOVAs. Responses to the two items (a scale rating and an estimate in months) measuring expected E-Book introductory time frames were subjected to ANOVAs with expertise and priming condition as independent variables. In each case, a two-way interaction between the independent factors was observed (scale rating: F(1,36)=7.00, p<.012); months estimate: F (1, 36)=3.70, p<.056). Follow-up contrasts indicated that novices expected a longer time between E-Book generations when the palmtop priming condition was long (scale rating: X=7.44; months estimate: X=17.0) than when it was short (scale rating: X=6.00; F (1,36)=8.84, p<.005; months estimate X=12.09; F (1,36)=9.34, p<.004). Conversely, experts’ expectations for the E-Book did not vary according to the palmtop priming condition (scale rating: X=6.18 vs. 6.56; F (1, 36)=0.59, p<.447; months estimate: X=15.09 vs. 14.67; F (1,36)=.07, p<.793).

Further, as Figure 1 demonstrates, the pattern of means for the E-Book introductory timing expectations mirrors that of the interest in and likelihood of purchase ratings for the E-Book. Such parallel patterns are consisent with our prediction that palmtop introductory timing would be analogically transferred to E-Books by novices but not by experts.

DISCUSSION

Taken together, the results of our study provide evidence for differences in new product introduction expectations for experts and novices. The findings also suggest a connection between these expectations and purchase interest and likelihood. Importantly, although experts and novices in our study began with similar expectations for the intergenerational timing of palmtop computers, only novices seemed willing to apply those expectations to developing expectations for a novel product resembling the E-Book.

Theoretically speaking, our data contribute to the developing literature on new product purchase decisions. More broadly, the current findings add to our still-growing knowledge of differences in information processing strategies between experts and novices (e.g., Alba & Hutchinson 1987; Sujan 1985) and provide further evidence of the importance of consumer expectations in purchase decisions.

With respect to the analogical reasoning literature, the current study adds to emerging evidence that use of the analogical process often differs for experts and novices (e.g., Gregan-Paxton and Roedder John 1997). Recent research has, for example, suggested that when given analogical comparisons between items that share few surface attributes but do share deeper functional similarities, experts are more likely to complete the analogy than novices (Roehm and Sternthal 1999). Conversely, the present research suggests that when an analogical comparison holds primarily at the level of surface attributes, novices are more likely than experts to complete the transfer of information.

Looking forward, future research is needed to more closely examine the expectation formation process of experts. While our results are enlightening with regard to novices, experts remain something of a mystery at this point. An additional, and important, future direction is to examine cultural influences on the expectation process. Does, for instance, the past- versus future-orientation of a culture serve as a qualifier of the current findings?

FIGURE 1

E-BOOK PURCHASE INTENTION AND TIMING EXPECTATIONS

APPENDIX

TIME LISTINGS IN "EXPERIMENT 1"

REFERENCES

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Balcer, Yves and Steven A. Lippman (1984), "Technological Expectations and Adoption of Improved Technology," Journal of Economic Theory, 34, 292-318.

Boone, Derrick S., Katherine N. Lemon and Richard Staelin (1999), " The Impact of Expectations of Future Product Introductions on Consumer Purchase Decisions," manuscript under review.

Cripps, John D. and Robert J. Meyer (1994), "Heuristics and Biases in Timing the Replacement of Durable Products," Journal of Consumer Research, 21, (September), 304-318.

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Gentner, Dedre and Arthur B. Markman, (1997) "Structure Mapping in Analogy and Similarity," American Psychologist, 52 (1), 45-56.

Gentner, Dedre, Mary Jo Ratterman and Kenneth Forbus(1993), "The Roles of Similarity in Transfer: Separating Retrievability from Inferentil Soundness," Cognitive Psychology, 25, 524-575.

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McKeithen, Katherine B., Judith S. Reitman, Henry H. Rueter and Stephen C. Hirtle (1981), "Knowledge Organization and Skill Differences in Computer Programmers," Cognitive Psychology, 13, 307-325.

Murphy, Gregory L. and Jack C. Wright (1984), "Changes in Conceptual Structure with Expertise: Differences between Real Work Experts and Novices," Journal of Experimental Psychology: Learning Memory and Cognition, 10 (1), 144-155.

Novick, Laura R. (1988), "Analogical Transfer, Problem Similarity and Expertise," Journal of Experimental Psychology, Learning Memory and Cognition, 14, 510-520.

Pennington, Nancy (1987), "Stimulus Structures and Mental Representations in Expert Comprehension of Computer Programs," Cognitive Psychology, 19, 295-341.

Roehm, Michelle L. and Brian Sternthal (1999), "Analogy, Mood and Judgment," manuscript under review.

Ross, Brian (1987), "This is Like That: The Use of Earlier Problems and the Separation of the Similarity Effects," Journal of Experimental Psychology: Learning , Memory and Cognition, 13 (4), 629-639.

Schoenfeld, Alan H. and Douglas J. Hermann (1982), "Problem Perception and Knowledge Structure in Expert and Novice Mathematical Problem Solvers," Journal of Experimental Psychology: Learning Memory and Cognition, 8 (5), 484-494.

Sujan, Mita (1985), "Consumer Knowledge: Effects on Evaluation Strategies Mediating Consumer Judgments," Journal of Consumer Research, 12 (June), 31-46.

----------------------------------------

Authors

Michelle L. Roehm, Wake Forest University, U.S.A.
Derrick S. Boone, Wake Forest University, U.S.A.
Harper A. Roehm, Jr., Wake Forest University, U.S.A.



Volume

E - European Advances in Consumer Research Volume 4 | 1999



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