An Analysis of Multi-Dimensional Internal Reference Prices

>ABSTRACT - This study examines the number and type of multiple internal reference prices (IRPs) consumers utilized for evaluating an offered price for three products that differed in perceived price expensiveness and product involvement. Findings are as follows. First, the number of IRPs utilized increases in tandem with perceived price expensiveness and product involvement. Second, the combination of multiple IRPs utilized is similar, but the most important IRP varies among consumers. Third, the type of IRP utilized varies among products, although there are some commonalities. Our additional investigation pertaining to the impact of deviations from IRPs is also reported.

Citation:

Miyumi Shirai (2003) ,"An Analysis of Multi-Dimensional Internal Reference Prices", in NA - Advances in Consumer Research Volume 30, eds. Punam Anand Keller and Dennis W. Rook, Valdosta, GA : Association for Consumer Research, Pages: 258-263.

Advances in Consumer Research Volume 30, 2003     Pages 258-263

AN ANALYSIS OF MULTI-DIMENSIONAL INTERNAL REFERENCE PRICES

Miyumi Shirai, Yokohama National University

>ABSTRACT -

This study examines the number and type of multiple internal reference prices (IRPs) consumers utilized for evaluating an offered price for three products that differed in perceived price expensiveness and product involvement. Findings are as follows. First, the number of IRPs utilized increases in tandem with perceived price expensiveness and product involvement. Second, the combination of multiple IRPs utilized is similar, but the most important IRP varies among consumers. Third, the type of IRP utilized varies among products, although there are some commonalities. Our additional investigation pertaining to the impact of deviations from IRPs is also reported.

INTRODUCTION

Importance of internal reference price (IRP) in consumers’ decision making has found a consensus among marketing researchers through a considerable amount of empirical evidence for a review, see Kalyanaram and Winer 1995). Also, IRP effects are well grounded in several psychological theories such as adaptation-level theory, assimilation-contrast theory, and prospect theory (for a review, see Sawyer and Dickson 1984). The IRP is defined as a standard price which consumers utilize for evaluating a product offer price. Its formation is based mainly on prices that individual consumers have observed previously; it is stored in memory, recalled, and reevaluated as occasions demand.

Although IRP has been addressed by past research, there is a specific void in those studies. Given the multi-dimensional nature of IRP, no specific suggestion is offered to marketers as to which price concept should receive focus when they choose to use IRP for more effective price communications toward consumers. Multi-dimensionality suggests that the IRP may differ among consumers and products; also, consumers may use more than one IRP per purchase occasion. As for those multiple IRPs, Winer (1988) presented five operational IRPs: fair price, reservation price, lowest acceptable price, expected price, and perceived price. Fair price taps notions of what a product 'ought to cost’. Reservation price is the most a consumer is 'willing to pay’ for a product. Lowest acceptable price is the lowest price level at which a consumer does not 'suspect poor quality’ and hence would pay for a product. Expected price is the price a consumer thinks she will have to pay for a product 'in the future’. Perceived price is the current perceived or estimated price, which incorporates an amalgamation of the price most frequently charged, last price paid, price of the brand usually bought, and the average price of similar products. Various other operational IRPs have been used: reasonable price (Folkes and Wheat 1995), lowest market price (Biswas and Blair 1991), average price (Bearden et al. 1992; Diamond and Campbell 1989), and evoked price (Rao and Gautschi 1982).

Although each IRP concept differs, previous research has found that many of these prices were similar. For instance, Folkes and Wheat (1985) demonstrated that the reservation, fair, expected, and reasonable prices were highly correlated for an electric ice-cream maker and oil stain (Cronbach’s alpha=.92). In a study by Diamond and Campbell (1989), levels of the expected, average, most frequent, fair, and reservation prices were very similar for liquid laundry detergent. Bearden et al. (1992) showed that, excepting fair price, the normal, expected, average, and reservation prices were correlated for apartment rents (mean score of correlation coefficients=0.75). These previous research efforts elucidate how similar the level of some IRPs can be, but not which type of IRPs that consumers use. As mentioned earlier, that latter information is crucial for marketers because recognizing corresponding IRPs leads to focus and emphasis of appropriate IRPs in price communications toward consumers.

One exception is a study by Chandrashekaran and Jagpal (1995) which showed that four IRPs (fair price, reservation price, normal price, and lowest price seen) would not be combined into an overall unitized IRP upon evaluating an offered price; instead, respective IRPs directly influenced evaluation. They also found that consumers’ use of IRPs was product-specific. For a compact disc stereo player, fair price and reservation price affected evaluations similarly and were highly correlated (phi=.71). For running shoes, fair price and lowest price seen affected evaluations to a similar degree and were significantly correlated (phi=.58).

This study also investigates consumer use of multiple IRPs, but employs a different approach from Chandrashekaran and Jagpal. Instead of measuring the level of multiple IRPs, we attempt to rank these prices based on perception of usability for price evaluations. This approach may lead to more accurate measurement in terms of relative importance of multiple IRPs. We argue that consumers may use multiple internal prices; however, these prices are not used simultaneously. In other words, multiple IRPs are used separately in some order of importance. For example, one consumer may first use expected price, the most relevant IRP for him, for price evaluation. If he feels that more price evaluation is necessary, he may next recall purchased price, his second-most relevant IRP, for subsequent evaluation. If he is not yet satisfied, he then recalls his third-most relevant IRP for further evaluation, and so on. This process continues until the consumer reaches a certain level of price-evaluation satisfaction. Hence, measuring multiple IRPs by asking consumers to indicate their level all at once, as in previous research, seems to be rather unnatural. Consumers are not able to differentiate innate levels of respective IRPs in that way. This may explain why levels of different IRPs were very similar in previous studies.

This study examines which IRP consumers generally use upon evaluating an offered price for several different product classes; those classes would differ in their respective level of consumers’ perceived price expensiveness and product involvement. Product involvement is defined here as the individual’s level of interest in a product. It is found to affect many aspects of consumer response, such as attention to a stimulus, depth of stimulus processing, cognitive response, and search behavior (e.g., Celsi and Olson 1998; Moore and Lehmann 1980; Petty et al. 1983). In addition, we look at a situation where actual offered prices deviate from consumers’ IRPs (e.g., Winer 1986; Kalwani et al. 1990). We attempt to examine whether the direction of deviation from IRP (DIRP) influences consumers’ intentions for conducting an additional price search and intentions of using market prices observed in the price search as an IRP for future price evaluations. If the effects are significant, it would imply that IRP is influenced not only by manufacturer’ or retailers’ past pricing activities, but also by consumers’ past price search behaviors resulting from DIRP. Previous research has revealed the direct effect of DIRP on consumers’ choice decisions, but not its indirect effect on future price evaluations. Therefore, we wish to take this opportunity to investigate these potential effects as well. We point out that our focus for DIRP is strictly on its direction, not on its size.

HYPOTHESES

We begin by developing hypotheses regarding the number and type of multiple IRPs that consumers use for price evaluation. Our next set of hypotheses relates to the effect of DIRP direction on intention of conducting an additional price search and of using observed market prices for future price evaluations.

Consumers are likely to evaluate offered prices of a product more carefully and seriously when it is perceived to be relatively expensive since perceived sacrifice engendered by expenditure is large and consumers’ needs and motivation for reaching the right decision increase. Also, consumers are likely to generate more careful price evaluations when their involvement toward a product is high. Previous research found that their attention, processing depth, and cognitive responses to stimulus are high when consumers’ involvement toward a stimulus is high; their recall ability is also enhanced because it leads to more retrievable, more accurate, and stronger memory traces (e.g., Leavitt et al. 1981; Petty et al. 1983). We argue that a more careful and serious price evaluation leads to use of more IRPs because those consumers are bound to examine offered price validity from every possible aspect. Hence,

H1: The number of IRPs that consumers utilize are larger for products for which consumers’ perceived price expensiveness and product involvement are high than for products for which they are low.

Following the same argument, we assert that the type of IRPs used for price evaluation also differs among products that have different levels of perceived price expensiveness and product involvement. In particular, we predict that the use of reservation price and fair price would be very product specific. Reservation price plays a vital role for a product for which perceived sacrifice of expenditure is high since it reflects the most consumers are willing to pay. For such products, reservation price is formed with close reference to a consumer’s budget. Fair price also plays an important role for such products; consumers would be encouraged to justify expenditure on the product. Fair price is the best IRP to meet this need because it denotes what a product ought to cost. High perceived sacrifice on expenditure relates to high perceived price expensiveness and engenders high product involvement. Hence,

H2: The type of IRPs that consumers utilize is product specific. In particular, the relative importance of reservation price and fair price as IRPs increases as perceived price expensiveness and product involvement increase.

Previous research found that consumers’ price knowledge and accuracy of recalled past prices were low in general (Dickson and Sawyer 1986, 1990). We argue that consumers are aware that their recall of previously purchased prices is inaccurate and somewhat ambiguous, especially for less-frequently purchased products. Thus, they may use historical purchase prices for a price evaluation, but do not appraise them highly. We also argue that this tendency becomes more pronounced as purchase frequency decreases or inter-purchase periods lengthen. This is because some technological innovation or product changes might be expected; alternatively, the same product is likely to be off the market and consumers’ memories of purchase prices fade over time.

H3: Importance of purchased prices as an IRP is relatively low. Importance decreases as purchase frequency decreases.

We now hypothesize relationships between DIRP and intention for additional price search and of using observed market prices as an IRP for future price evaluations. Previous studies found consistently that consumers do relatively little pre-purchase search and price comparison for durable goods (e.g., Beatty and Smith 1987) despite reported importance of price to consumers’ purchase decisions (Rothe and Lamount 1973). We argue that the price search intention varies depending on the direction in which DIRP occurs. We predict that a higher intention for conducting an additional price search will be derived when offered prices are higher than expected (negative DIRP) than when they are lower than expected (positive DIRP). While positive DIRP leads to pleasure, negative DIRP leads to discomfort or shock. Consumers with negative DIRP will be more motivated to examine whether this negative DIRP is due to their inappropriate price knowledge or not; therefore, their needs and motivation for an additional price search increases. If a positive DIRP occurs, consumers merely enjoy pleasure and perceive low benefit for the search. Hence, the following hypothesis is proposed:

H4: A consumer’s intention to conduct an additional price search is higher when a negative DIRP arises than when a positive DIRP arises.

The same argument can be applied to intention toward using market prices observed in the price search for future price evaluation. Negative DIRP should make consumers more knowledgeable of product market prices, as hypothesized in H4. Thus, the intention of using those market prices as IRPs for future evaluations is higher for consumers with a negative DIRP than for those with a positive DIRP. Moreover, consumers with a negative DIRP are likely to engrave the fact of inaccurate price expectation more deeply and clearly in their minds. This forces them to pay more attention to new price-related information such as market prices. Thus, we propose:

H5: A consumer’s intention of using market prices obtained in a price search for future price evaluations is higher when a negative DIRP arises than when a positive DIRP arises.

METHOD

The study was a 2 x 3 factorial between-subjects design. Crossing DIRP with products developed six versions of experimental booklets. The two levels of DIRP conditions were positive and negative; three products were a personal computer (PC), a cellular phone (cell-phone), and shampoo. [Through an interview with 15 students, product involvement and perceived price expensiveness were found to be generally high for PC, moderate for cell-phone, and low for shampoo. Also, a pilot study was conducted to investigate whether IRP use was plausible for the three products. A questionnaire asked 46 students to rate price importance and describe the rating rationale. Results revealed that price is important for these products, but the extent and reason of importance is product specific. Therefore, we conclude that the role of IRP should be vital for these products.]

On a voluntary basis, 341 undergraduate student subjects participated in this study; of them, 297 were useful for analyses. (111 for PC, 116 for cell-phone, and 70 for shampoo).

Procedure

The experimental booklet comprised four consecutive hypothetical scenarios. The first scenario asked subjects to imagine the following:

You are currently thinking of buying a PC (cell-phone, shampoo). You are about to visit a store to buy it. You have no strong preference on which brand to buy; thus, price becomes one of the attributes you pay attention to. Your product checking also includes price checking. Checking of price validity is conducted by comparing an offered price to standard prices you refer to. This is the list of prices typically representing a standard.

Then, the nine IRPs were presented to subjects. The IRPs were fair price (FP), reservation price (RP), lowest acceptable price (LAP), lowest-observed price (LOP), highest-observed price (HOP), average-observed price (AOP), normal price (NP), expected price (EP), and purchased price (PP). [No price levels were labeled on these price terms since we did not attempt to investigate the effect of having access to price information upon price evaluations.] Each of these nine prices was described specifically so subjects could easily differentiate them. Subjects were encouraged to ask questions if they found difficulties differentiating them. The order of presenting these prices was alternated. Subjects were asked to select only those prices they would consider using as a reference for evaluating validity of an offered price; they were asked to rank selected prices by order of precedence from highest to lowest. Then, subjects received the second scenario:

Now, you are in the store to buy a PC (cell-phone, shampoo). When you checked on several offered prices in the store, the overall price of the product class was higher ("lower" for the positive DIRP condition) than expected. You realized that your price expectation was not consistent with actual levels.

After reading the scenario, subjects assessed their level of intention for conducting an additional price search. Then, the subjects received the third scenario, in which they decided to conduct a price search to understand typical and appropriate price levels of the product in the market. Next, they selected information sources that they would seriously consider seeking information from: "check more prices in the store", "visit other stores", "read magazines", "search on the internet", "ask acquaintances", and "ask store clerks". Finally, the last scenario was provided. It asked subjects to imagine that they had gained a good amount of knowledge about the product price through price searching. Then they rated their intention of using the three market prices (highest-market price, lowest-market price, and intermediate-market price) obtained from their price search for future price evaluations. In the end, they assessed their product involvement, perceived price expensiveness of the product class in general, and supplied demographic data.

Measures

Price search intention was measured using a 4-point scale anchored by "Very much" and "Not at all" with the question, "Do you search for more price information by checking prices of the product?" Intention of utilizing each of three market prices (highest, lowest, and intermediate prices) obtained from the price search on future price evaluations were measured by a 5-point scale from "Very much" to "Not at all" for the question, "How much do you intend to use the highest (lowest, intermediate) price observed in the price search for price evaluations in the future?"

RESULTS

Data checks

We needed to verify that subjects’ assessment on perceived price expensiveness and product involvement actually differed among the three products. Perceived price expensiveness was measured by a 5-point scale anchored with "Very much" and "Not at all" on the question: "Do you feel that a PC (cell-phone, shampoo) is generally an expensive product?" The mean score was 2.2 for PC, 3.1 for cell-phone, and 4.6 for shampoo (F(2, 289)=246.5, p<.01). Tukey test indicated that all contrasts were significant at alpha=.05. Product involvement was measured by a 3-point scale anchored with "Very much" and "Not at all" on the question: "Are you generally interested in a PC (cell-phone, shampoo)?" The mean score was 1.6 for PC, 2.0 for cell-phone, and 2.9 for shampoo (F(2, 288)=58.2, p<.01). Tukey test indicated that all contrasts were significant at alpha=.05. These results indicate that perceived price expensiveness and product involvement were both high for PC, moderate for cell-phone, and low for shampoo. Accordingly, those two characteristics are comparable among the three products.

Hypothesis tests

Hypothesis 1 stated that the number of IRPs utilized increased as perceived price expensiveness and product involvement increased. The mean score of a number of selected IRPs was 5.7 for PC, 4.8 for cell-phone, and 2.4 for shampoo (F(2, 292)=68.9, p<.01). Tukey test indicated that all contrasts were significant at alpha=.05. Figure 1 shows the proportion of subjects selecting each IRP with the intent to use it as an IRP. For PCs, RP (71%), LAP (78%), AOP (74%), NP (87%), and EP (83%) received relatively high scores. For cell-phones, NP (74%) and EP (73%) received high scores. For shampoo, only NP (74%) received a high score. These suggest that as perceived price expensiveness and product involvement increase, IRPs utilized by consumers increase, supporting H1.

Hypothesis 2 predicted that importance of RP and FP as an IRP increased as perceived price expensiveness and product involvement increased. Proportions of those using RP and FP were 71% and 64% for PC, 65% and 46% for cell-phone, and 44% and 36% for shampoo; FP use was lower than RP use. Chi-square test showed that the use of RP and FP differed significantly by product type (Chi² (2)=11.5, p<.01 for RP and Chi² (2)=14.6, p<.001 for FP). The average ranks of RP and FP were 2.7 and 2.8 for PC, 3.4 and 3.9 for cell-phone, and 4.1 and 4.1 for shampoo (F(2, 180)=5.2, p<.01 for RP, F(2, 146)=3.3, p<.05 for FP; PC and shampoo differed significantly at alpha=.05 for both IRP). These data concur with H2.

As for other IRPs, use of LAP was particularly product specific (Chi² (2)=20.6, p<.0001) and use of AOP and PP were fairly product specific (Chi² (2)=6.9 and 6.3, p<.05). Figure 1 also shows that NP, EP, LOP and HOP share commonalities across the three products. That is, subjects strongly regard NP and EP (Chi² (2)=6.0 and 5.7, p<.1), and weakly regard LOP and HOP (Chi² (2)=2.7 and 3.6, n.s.). Additionally, the proportion of subjects ranking each IRP first in terms of their intent to use it as an IRP differed by product as shown in Figure 2: LAP received the highest proportion for PC (21%), RP for cell-phone (19%), and EP for shampoo (17%). These proportions are not high, suggesting that the most important IRP that consumers use varies among consumers even though the combination of multiple IRPs they use tends to be similar.

Hypothesis 3 predicted that importance that consumers assigned to PP for price evaluation was lower; this tendency strengthened with decreased purchase frequency. Among the three products, purchase frequency was low for PC, moderate for cell-phone, and high for shampoo. [A pretest conducted with 19 students indicated that the average inter-purchase period was 3.4 years for PC, 2 years for cell-phone, and .2 years for shampoo (F(2, 54=6.20, p<.01)., Tukey test showed that all contrasts were significant at alpha=.05.] Figure 1 shows that the proportion of subjects who selected PP was 48% for PC, 63% for cell-phone, and 61% for shampoo. Chi-square test showed that PP use differed by product type (Chi² (2)=6.2, p<.05). The average rank was 4.3 for PC, 3.4 for cell-phone, and 2.8 for shampoo (F(2, 166)=6.3, p<.01; two contrasts (PC vs. phone, PC vs. shampoo) were significant at alpha=.05). These data indicated that consumers use PP for price evaluations; however, its extent is relatively low and becomes even lower for less-frequently purchased products. Thus, H3 is supported.

FIGURE 1

PROPORTION OF EACH IRP

FIGURE 2

PROPORTION OF #1 RANKED IRP

Next, we examine the effect of DIRP on an additional price search as proposed in Hypothesis 4. Two price search aspects were investigated: intention to conduct price search and the number of information sources sought for use in that search. The former aspect reflects the amount while the latter reflects the depth of the price search. The extent of price search intention was significantly different between positive DIRP and negative DIRP for cell-phone (T(122)=2.2, p<.05), with more search for the negative DIRP than positive DIRP (M_positive=2.0 vs. M_negative=1.6). The effect on search intention for PCs and shampoo was not significant. The effect of DIRP on the number of information sources intended for use was significant for PC (T(112)=2.1, p<.05), with more sources for negative DIRP than positive DIRP (M_positive=2.4 vs. M_negative=3.1). When a negative DIRP arose, most subjects similarly intended to use "visit other stores" and "ask acquaintances" highly (77% and 74%), but when a positive DIRP arose, "check more prices in the store" loomed larger (87%). The effect for cell-phones and shampoo was not significant. Thus, we conclude that negative DIRP leads to more price search than positive DIRP; still, the effect depends on product type, partially supporting H4. We also note here that intention for an additional price search and number of information sources used for that price search varies significantly among the products (F(2, 285)=33.8, p<.01 for extent, F(2, 285)=39.8, p<.01 for source). The higher the perceived price expensiveness and product involvement, the more and deeper the additional price search.

Hypothesis 5 stated that the effect of DIRP on intention of using market prices observed in a price search for future price evaluations was greater for negative DIRP than for positive DIRP. For PCs, the effect of DIRP on the extent of using highest-market price was only marginally significant (T(112)=1.7, p<.1, M_positive=3.2 vs. M_negative=2.8). For cell-phones, the effect on the extent of using highest-market price was only marginally significant (T(122)=1.7, p<.1, M_positive=3.1 vs. M_negative=2.7). For shampoo, the effect on the extent of using intermediate-market price was significant (T(82)=2.0, p<.05, M_positive=2.3 vs. M_negative=1.8). Thus, we observed a propensity to use more market prices when a negative DIRP arose rather than when a positive DIRP arose; here again, the type of market prices used and extent of using them depended on product type. These results partially support H5. Notably, comparison of the products revealed that the intention of using intermediate-marketprice differed significantly among them (F(2, 284)=4.5, p<.05, M_computer=1.7, M_phone=2.0, and M_shampoo=2.1), indicating that PC shoppers regarded intermediate-market price highest. Moreover, the intention to use each market price was significantly different among the three market prices (F(2, 854)=77.0, p<.01, M_highest=3.1, M_intemediate=1.9, and M_lowest=2.2), indicating that intermediate-market price would be used most and highest-market price would be used least.

DISCUSSION

Although the multidimensional nature of IRP is well-accepted among marketing researchers, few studies address which IRP should be used in price communication strategies toward consumers. This paper examined the number and type of multiple IRPs consumers used in general evaluation of offered prices. Nine IRPs that commonly appeared in previous research were used in this study: fair price, reservation price, lowest acceptable price, lowest-observed price, highest-observed price, average-observed price, normal price, expected price, and purchased price. We examined consumer use of multiple IRPs for three products that differed in consumers’ perceived price expensiveness and product involvement: a PC (high level), a cell-phone (moderate level), and shampoo (low level). Results from our experimental design indicated substantial heterogeneity with respect to number and type of IRPs that consumers utilize for price evaluations. Consumers used more IRPs as perceived price expensiveness and product involvement of products increased. As for type of IRPs, the combination of multiple IRPs used was similar, but the most important IRP varied among consumers. When perceived price expensiveness and product involvement were high, shoppers regarded RP, LAP, AOP, NP, and EP highly. When they were moderate, NP and EP were regarded highly. When they were low, NP became a key for evaluation. Particularly, the extent of using FP, RP, and LAP differed highly among the products; FP and RP gained importance when perceived price expensiveness and product involvement were high. However, three commonalities were revealed among the products. First, NP and EP were regarded highly as an IRP. Second, LOP and HOP were regarded less as an IRP. Third, among the nine IRPs, use of PP was lower; this propensity became stronger as purchase frequency decreased or inter-purchase period lengthened.

We conducted an additional investigation to see whether variations in the level of IRPs among consumers were due partially to the direction in which actual price deviated from IRP (DIRP). Results showed that when price expensiveness and product involvement were higher, consumers with negative DIRP showed a tendency to conduct additional price search in terms of extent and number of information sources utilized, in contrast to those with positive DIRP. Also, consumers intended to use market prices obtained from the price search more for future evaluations when negative DIRP arose than when positive DIRP arose. Furthermore, among various market prices, the intermediate-market price was the most important IRP. The highest-market price was least important, although importance increased as negative DIRP arose. Thus, depending on the direction of DIRP consumers experience, the level of IRPs used for future price evaluations is likely to vary; negative DIRP may lead to more accurate IRPs.

Implication

For effective market competition, marketing managers should develop price communication strategies in consideration of consumer use of multiple IRPs. Some adjustments in strategy by considering target product characteristics are appropriate. For products with high perceived price-expensiveness and high product involvement, it is effective to emphasize RP, LAP, AOP, NP, and EP in price communication. Focusing on a solitary IRP in strategy may not be effective because the most important IRP varies among consumers. Messages should be informative. For example, listing similar products with price (affecting AOP, NP, and EP), emphasizing product value by contrasting them (affecting RP), providing information about similar and more expensive products (affecting RP and EP), and about less valued and lower priced products (relates to LAP) on a simultaneous and consistent basis may raise or hold IRPs at desirable level. For products with low perceived price expensiveness and product involvement, messages should be clear and compact and emphasize NP. In addition, providing information about highest-market price in messages should be avoided for all product types since consumers tend to disregard such information. Finally, a concern about the effect of FP on consumers’ choice is not necessary as long as a product is not sold at an outrageous price; FP is used, but is not a determinant for price evaluation. We believe that FP importance increases only on special occasions, such as when consumers are informed about changes in the cost of raw materials.

Research Extensions

Several extensions should be conducted to overcome limitations of this study. First, other methods to measure multiple IRP use should be sought. Implicit measurements may be more appropriate since IRP is memory based. Second, other product classes should be targeted. Especially, analyzing frequently purchased products (e.g., foods) and durables with a longer product lifecycle (e.g., microwave ovens) will broaden implications of this study. Third, the sample of respondents should be expanded to include consumers who are unfamiliar with a product. Those consumers are likely to use different IRPs than consumers with high familiarity. For example, they may use prices of different product classes that have some similarity with the target product class. Using population groups other than student convenience samples should be included in this extension. Fourth, examination of whether consumers use multiple IRPs serially should be conducted. Fifth, analysis at the brand level is required to see whether IRPs differ among brands. Difference will likely be found between private and national brands since consumers’ expectations toward these brands differ (e.g., Hock and Banerji 1993; Richardson et al. 1994). Brand image may be another factor; Biswas and Sherrell (1993) found that high-image brands induce higher IRPs than low-image brands. Sixth, examination of interaction between store image or store type and IRPs would expand results presented in this study since IRP is known to be influenced by store type (Thaler 1985). Finally, our study design does not replicate the real world in all aspects; therefore, field experiments are necessary to confirm results.

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