The Relationship Between Internal Reference Price and Three Aspects of Dealing Patterns: Frequency, Depth, and Depth Variation

ABSTRACT - This paper is an extension of Kalwani and Yim (1992) that includes depth-variation in addition to depth and frequency, as factors in dealing patterns that affect the internal reference price. It also investigates the interaction effects among the three factors. Depth-variation indicates whether deals over a certain period are conducted with constant or mixed depths. Results showed that the internal reference price was higher when consumers observed a mixed- rather than a constant-depth pattern. In addition, the depth effect appeared more pronounced when consumers observed a constant- rather than a mixed-depth pattern and when observing a high rather than a low frequency pattern.

Citation:

Miyuri Shirai (2005) ,"The Relationship Between Internal Reference Price and Three Aspects of Dealing Patterns: Frequency, Depth, and Depth Variation", in AP - Asia Pacific Advances in Consumer Research Volume 6, eds. Yong-Uon Ha and Youjae Yi, Duluth, MN : Association for Consumer Research, Pages: 299-302.

Asia Pacific Advances in Consumer Research Volume 6, 2005      Pages 299-302

THE RELATIONSHIP BETWEEN INTERNAL REFERENCE PRICE AND THREE ASPECTS OF DEALING PATTERNS: FREQUENCY, DEPTH, AND DEPTH VARIATION

Miyuri Shirai, Yokohama National University, Japan

ABSTRACT -

This paper is an extension of Kalwani and Yim (1992) that includes depth-variation in addition to depth and frequency, as factors in dealing patterns that affect the internal reference price. It also investigates the interaction effects among the three factors. Depth-variation indicates whether deals over a certain period are conducted with constant or mixed depths. Results showed that the internal reference price was higher when consumers observed a mixed- rather than a constant-depth pattern. In addition, the depth effect appeared more pronounced when consumers observed a constant- rather than a mixed-depth pattern and when observing a high rather than a low frequency pattern.

INTRODUCTION

The importance of consumers’ internal reference price (IRP) in their purchase decisions has been recognized in a significant number of previous studies (for an early review, see Kalyanaram and Winer 1995). IRP is defined as a standard price stored in consumers’ memories and recalled to evaluate the validity or attractiveness of retail prices. The underlying premise is that consumers judge a retail price comparatively. That is, consumers perceive a retail price as cheap if it is lower than IRP and perceive it as expensive if it is higher. Thus, the higher the IRP, the better the price judgments consumers generate. IRP is not static and is updated as occasions demand since it is formed mainly on prices that individual consumers have observed previously. Accordingly, one series of research regarding IRP has been to investigate marketing tools that influenced it. As a result, some marketing tools have been found to affect IRP. IRP is influenced by advertised reference prices (e.g., Biswas and Blair 1991; Urbany et al. 1988), price discounts (e.g., Diamond and Campbell 1989; Kalwani and Yim 1992), and coupons (Folkes and Wheat 1995; Raghubir 1998).

Although many marketing tools that are capable of influencing IRP have been revealed, the effect of dealing patterns considered over multiple periods has not been fully investigated. Unless price discounts are offered infrequently or a products’ purchase interval is very long, it is important to investigate the effects of deals within a certain period, rather than at one time. Consumers’ tendency to rely on those memories increase in the opposite situation. So far, the only study that focuses on this type of promotion has been that of Kalwani and Yim (1992). They investigated the effect of frequency (1, 3, 5, and 7 discounts) and depth (10%, 20%, 30%, and 40%) of irregular dealing patterns set over 10 weeks. [Frequency refers to how often discounts are given in a certain period and depth indicates, in percentage terms, how deep discounts are.] Their experimental results indicated that IRP decreased as the frequency and depth increased; however, the functional relationship between IRP and frequency was sigmoid, but concave for depth. This study, therefore, extends that of Kalwani and Yim by including an additional component to dealing patterns: depth-variation. Depth-variation indicates whether deals over time are conducted with constant depth (constant-depth pattern) or with varied depths (mixed-depth pattern). Given the fact that many products are generally offered with different discount depths over time, this aspect deserves attention and investigation of this effect is considered important. Also, we hypothesize the interactive effects of these dealing components. The interactive relationship between frequency and depth was not found in Kalwani and Yim’s study. However, we argue that theoretically, it does exist. Similar to Kalwani and Yim, we focus on irregular dealing patterns (i.e., variation in the time between each deal). When regular patterns are offered, consumers can learn them much more easily than irregular ones. This implies that the effect on IRP is more obvious for regular patterns than for irregular patterns. Thus, it is more interesting to focus on irregular patterns whose effects are more uncertain. Besides, irregular patterns were more common, especially for convenience goods.

HYPOTHESES

Here, we consider three aspects of dealing patterns: depth-variation, depth, and frequency. However, as for the main effect, we only present a hypothesis on the effect of depth-variation on IRP. As explained earlier, the main effect of depth and frequency has already been confirmed by Kalwani and Yim(1992). We then present hypotheses about two-way interactive relationships among the three aspects.

Depth Variation

Here we compare two types of dealing patterns: a mixed-depth pattern and a constant-depth pattern. For simplicity, we consider the case where there are two discount depths in the mixed-depth pattern. We assume that the depth in the constant-depth pattern is equal to the average depths in the mixed-depth pattern; this assumption is necessary in order to compare the effect of the two patterns. We also assume that depths in the mixed-depth pattern do not differ largely from the depth in the constant-depth pattern. This treatment allows us to investigate a more pure effect of depth-variation by excluding the effect of depth difference.

If consumers have observed mixed discount prices over time, then IRP will depend on how they take those discount prices into account, i.e., on which discount depth they use as an anchor. The larger discount price might be more salient initially, but we argue that it will be treated more like a special deal and will be downplayed. That is, the larger discount depth will be segregated from normal promotional activities as special events and have less effect on the formation of IRP (similar to the Thaler’s (1985) silver lining principle). Therefore, the smaller discount price will have more weight as an anchor for IRP. For example, if depths of 30% and 40% were observed in the mixed-depth pattern, 30% will be the anchor. For consumers who have seen only one constant discount depth, 35%, the anchor should be constant depth. Since, IRP will be formed on the anchor, IRP is expected to be higher when a mixed-depth pattern was observed rather than a constant-depth pattern. Hence, we propose:

Hypothesis 1: IRP should be higher when the observed dealing pattern is a mixed-depth pattern as opposed to a constant-depth pattern.

Interactive Effects

We first consider the interaction between depth-variation and depth. We argue that the impact of depth varies depending on the depth-variation. In general, consumers can learn simple dealing patterns more easily as opposed to complex ones because the former can be described in terms of fewer symbols than the latter (Simon and Kotovsky 1963). Accordingly, we predict that the depth effect on IRP would be larger when consumers observed a constant-depth pattern rather than a mixed-depth pattern because the former is simpler than the latter and consumers are able to generate an extra symbol related to the depth. In other words, the difference in IRP between large and small-depth patterns should be larger for the constant-depth pattern than for the mixed. As demonstrated by Kalwani and Yim 1992, the larger the depth, the lower the IRP. Thus, we expect IRP should be lowest when consumers observed a large and constant-depth dealing pattern. Hence, we present:

Hypothesis 2: The effectiveness of depth will likely be more pronounced when the observed dealing pattern is a constant-depth pattern as opposed to a mixed-depth pattern.

We next consider the interaction between depth-variation and frequency. We argue that frequency should influence the effect of depth-variation on IRP. As consumers observe more deals they become more familiar with them and would better learn the pattern. Cacioppo and Petty (1979) showed that message repetition enhances the opportunity to process the content of information. Also, Simon and Kotovsky (1963) argued that the shorter the pattern, which implies a higher frequency, the easier it is to understand. Thus, the impact of depth-variation on IRP should become larger when a high number of deals are observed as opposed to low. As demonstrated by Kalwani and Yim (1992), the higher the frequency, the lower the IRP. And, as in Hypothesis 1, IRP is expected to be lower for a constant-depth pattern than a mixed. Thus, we predict that IRP will be lowest when consumers observe a high number of deals with a constant-depth pattern. Thus,

Hypothesis 3: The effectiveness of depth-variation will likely be more pronounced when the observed dealing pattern is a high-frequency pattern as opposed to a low-frequency pattern.

We considered the interaction between depth and frequency. This effect was not revealed in Kalwani and Yim (1992). However, we argue that the depth effect should depend on the deal frequency. As discussed in Hypothesis 3, a high frequency of deals enables consumers to better learn about the dealing pattern. Thus, the depth effect should become larger when consumers observed a high rather than a low number of deals. Since IRP decreases as the depth and frequency increases (Kalwani and Yim 1992), we expect that IRP becomes lowest when consumers observed a high number of deals with a large-depth pattern. Therefore,

Hypothesis 4: The effectiveness of depth will likely to be more pronounced when the observed dealing pattern is a high-frequency pattern as opposed to a low-frequency pattern.

METHOD

Study Design

This study was a controlled experiment designed to test our hypotheses. We created a hypothetical shampoo brand, Brand X. The study manipulated the three components of a dealing pattern for Brand X set over 18 weeks and involved 2 (depth-variation) x 2 (depth) x 2 (frequency) full factorial between-subjects design. The two levels of depth-variation were a mixed-depth pattern (two different depths) and a constant-depth pattern (one depth), the two levels of depth were a large pattern (35%) and a small pattern (15%), and the two levels of frequency were a low pattern (two times) and a high pattern (six times). Levels of depth-variation and depth were related so that when the depth-variation was mixed, the two depths were 10% and 20% for the small-depth condition and 30% and 40% for the large. The order of these two discount depths was randomized.

Each subject was randomly assigned to one of the eight treatment conditions. The regular price and container size of Brand X were determined to be consistent with actual levels in the shampoo market, with an average level of JY798 (=US$6.65) and 550ml chosen respectively. Deals were presented as " % OFF" in red text.

Sample and Procedure

Three hundred and forty three undergraduate students participated in a classroom setting. All the experimental materials were contained in a booklet distributed to each subject. The first page of the booklet provided a general description of the study. It noted that the study concerned supermarket prices and that participants would be exposed to the price of a hypothetical brand of shampoo, Brand X, for 18 consecutive weeks, starting from the following pages. Then they were encouraged to treat the observed prices as if they actually observed them in the store and to deliberate as much as they normally would in a retail store. Finally, a description of Brand X was provided. From the next page of the booklet, the subjects observed each week’s retail price and promotional information (if any) over 18 consecutive weeks. These prices were presented on a separate page for each week, and they were not allowed to go back to the previous pages once they had turned the next page. The final page of the booklet contained questions that measured IRP, their purchase experience for shampoo, brand loyalty, perceived price expensiveness of the shampoo category, frequency of use a week, and demographics. Subjects turned the pages and answered the required questions at their own pace.

Dependent Variable

IRP was operationalized as expected price. Expected price was demonstrated to be one of the common IRPs that consumers used across many products (Shirai 2003). It was assessed by asking subjects to answer the following open-ended question: "Based on the prices you have seen, what do you expect the price of Brand X to be this week?"

RESULTS

Manipulation Checks

Perception of depth and frequency were evaluated in order to check whether the respective manipulation was successful or not. Both measures were evaluated on a 5-point scale from (1) Very much to (5) Not at all from the following question: "Do you think that the discount depths offered are large?" for the depth and "Do you think that the number of offered deals are high?" for the frequency. T test indicated that perceived depth differed significantly between large and small depth conditions (T=9.9, p<.0001). The means score was 2.3 for the large depth condition and 3.4 for the small. Also, T test indicated that perceived frequency differed significantly between high and low frequency conditions (T=12.2, p<.0001). The mean score was 1.2 for the high frequency condition and 2.8 for the low. Thus, the manipulation we employed was considered to have worked effectively.

Analysis

We conducted ANOVA to test the hypotheses. The first hypothesis predicted that the IRP would be higher for a mixed-depth pattern than a constant-depth pattern. A significant effect was revealed (F (1, 333)=3.9, p<.05). The mean value for the constant-depth pattern was JY750.8 and for the mixed-depth pattern JY768. Therefore, Hypothesis 1 is supported. Here, we additionally note that the main effect of depth and frequency were also revealed (F (1, 333)=17.9, p<.0001 for depth and F (1, 333)=12.3, p<.001 for frequency), consistent with Kalwani and Yim (1992). The mean value for the large-depth pattern was JY741, for the small-depth pattern was JY777.8, for the high-frequency pattern was JY 744.1, and for the low-frequency pattern was JY 774.7. The depth generated the largest impact, frequency the second, and depth-variation the third.

FIGURE 1

THE EFFECT OF DEPTH-VARIATION AND DEPTH ON INTERNAL REFERENCE PRICES

FIGURE 2

THE EFFECT OF DEPTH AND FREQUENCY ON INTERNAL REFERENCE PRICE

Hypothesis 2 stated that depth-variation and depth interactively affected IRP. ANOVA showed that the effect was significant (F (1, 333)=6.9, p<.01). Figure 1 shows the mean IRP for the different conditions. As predicted, the difference between a small-depth pattern and a large one was larger for a constant-depth pattern than for a mixed-depth pattern. Also, IRP was lowest when the dealing pattern was a large and constant depth. Hence, Hypothesis 2 is supported.

Hypothesis 3 predicted that there was a significant interaction effect between depth-variation and frequency. The ANOVA showed the effect in the predicted direction, but it was not significant (F (1, 333)=1.5, n.s.). Hypothesis 3 is not supported.

As predicted in Hypothesis 4, there was a significant interaction effect between depth and frequency on IRP (F (1, 333)=4.7, p<.05). Figure 2 shows the mean IRP for different conditions. As predicted, the difference between small and large-depth patterns was larger for a high-frequency pattern than a low. Also, IRP was lowest when the dealing pattern was a large-depth pattern with a high frequency of deals.

DISCUSSION

This paper investigates the impact of dealing patterns on consumers’ IRP. It essentially expands Kalwani and Yim’s (1992) study that showed the effect of depth and frequency on IRP. In addition to depth and frequency, we focused on another important component of dealing patterns, depth-variation and the interaction effects among the three components as well. Depth-variation refers to whether deals over that time are conducted with a constant depth (constant-depth pattern) or with varied depths (mixed-depth pattern).

Through a laboratory experiment, we found the effect of depth-variation was that IRP was higher when consumers observed a mixed-depth pattern rather than a constant one. Thus, when deals were planned to offer several discount depths with equal frequency over time, consumers had a tendency to use a smaller depth, rather than a larger as an anchor for forming IRP. However, the impact of depth-variation was not as large as depth or frequency. Next, we found two interaction effects (depth-variation vs. depth, depth vs. frequency). The effectiveness of depth was more pronounced when consumers observed the constant-depth pattern than the mixed-depth pattern. Also, the effectiveness of depth was more pronounced when consumers observed a high frequency of deals than low.

Several implications can be derived from these results. First, several depths should be used in dealing patterns if keeping IRP at a higher level is a major concern. Second, the effect of depth becomes more important when planning to offer a constant depth pattern. Third, the effect of depth becomes more important when planning to offer a higher number of deals. Overall, manufacturers and retailers are likely to obtain better responses from consumers when deals are considered over time and when frequency, depth, and depth-variation are considered at the same time.

There are several limitations in this study. First, the study design does not replicate the real world; it has been suggested we employ field survey methodology in future studies. Second, the study did not use actual brands; the use of an actual brand name should lead to further understanding of consumer responses to deals. Third, the study used only student subjects and needed to conduct the same analysis using other population groups. Finally, only one product, shampoo, was examined here and it will be necessary to target more product classes to better generalize the findings.

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