Unravelling The Complexities Of Retail Price Discounts And Perceived Quality Uncertainty: Impact On Consumer Behavior And Online Reviews
Sep 17, 2023 | Sathvika Kanuri
A consumer's perception of a product's quality is formed when they decide whether to buy it. However, given the difficulty in gathering and processing all the necessary information, he/she is likely to be unsure about the perceived quality. In the pricing literature, it is clearly outlined. A consumer's perception of a product's quality is formed when they decide whether to buy it. However, given the difficulties in gathering and processing all the necessary information, she is likely to be unsure about the perception of quality. However, there is still a great deal of confusion regarding the connection between the retail price discount and the quality perception uncertainty (represented by the variance of quality perception).
The article aims to investigate this connection and show how it has managerial ramifications. Researchers suggest an inverted-U relationship between quality perception uncertainty and the depth of a retail price discount based on our analysis of the research that is currently available.
In particular, customers are more prone to blame price promotion on elements unrelated to product quality at low discount levels. As a result, there is little doubt about the quality they perceive because their past quality assumptions, created based on the usual pricing, are not much altered.
At a high discount level, however, customers are more likely to link price promotion to quality-related issues, specifically poor quality. As a result, individuals may confidently feel that the promoted product is of low quality, and in such a situation, there is little uncertainty over their sense of quality.
Theoretically, researchers primarily add to the body of knowledge regarding the informational impact of retail price discounts on customer quality assessments before purchase. This is the first study that, to our knowledge, has examined how perceived quality uncertainty is affected by the level of price discounts and how this influences consumer purchasing decisions. The link between price discount depth and perceived quality uncertainty is an inverted U shape, as opposed to the monotonic relationship between price discount depth and perceived (mean) quality. Although perceived quality uncertainty does not directly mediate price discount and consumer purchase, it does lessen the mediation effect of perceived quality (based exclusively on price cue) on buy intention when price cue is the only quality cue.
Price can be both a measure of financial sacrifice and a measure of quality. The cognitive trade-off between these two impressions leads to the perception of value, which affects purchasing decisions. We are primarily interested in the consumer's price-based quality learning process in a price promotion setting, in contrast to the existing literature on the price-quality link conducted in a non-promotion situation. When a price discount is given, the consumer bases their perception of the quality of the product not only on the original price but also on the depth of the discount. The diagnosticity of pricing signals (the original price plus a price discount) may vary directly when consumers assign price discounts to various variables, which decreases the mediation impact of perceived quality (based just on the original price).
Customers frequently receive the current discounted price when there is a price promotion. We only refer to the initial price and price discount as the primary pricing signals influencing customer quality views because the current price is influenced by the original price and price discount.
Hypothesis 1: When the discount depth is high (vs. low), consumers are more likely to ascribe retail price discounts to quality-related (vs. quality-unrelated) reasons; but, when the discount depth is intermediate, consumers are unable to clearly distinguish between the two causes.
Hypothesis 2: There is an inverse-U relationship between perceived quality uncertainty and the extent of the retail price reduction. Consumer quality uncertainty is lowest when the discount depth is low, increases as the discount depth rises, and then decreases once more when the discount depth falls.
Impact of retail price discount depth on the usage of additional non-price quality cues
Contrary to perceived mean quality, which highlights the general trend of consumers' views of quality, perceived quality uncertainty reveals the degree of variation in those perceptions. Consumer purchasing intentions may not be directly impacted by perceived quality uncertainty brought on by a retail price drop for risk-neutral consumers. The use of other high-quality cues for high-quality learning, which in turn affects consumer purchasing decisions, may be impacted. The weights of other quality cues included in quality learning will alter if the level of quality uncertainty perceived by consumers increases with discount depth. We will gain a better understanding of the effect of discount depth on the use of additional non-price quality indicators by examining the relationship between retail price discounts and perceived quality ambiguity.
Given the aforementioned inverted U-shaped relationship between retail price discount depth and uncertainty in quality perception, we expect that the effects of other non-price quality cues on perceived quality are non-monotonically moderated by price discount depth. When the discount depth increases from low to moderate, the level of uncertainty about the quality judgment based on the price cues also increases. Thus, consumers will rely more on additional information to modify their prior quality perceptions based only on price cues. In contrast, when the discount depth changes from moderate to high, they perceive a lower level of quality uncertainty and rely less on other cues. Since perceived mean quality positively affects purchase intention, we also expect that the effects of other non-price quality cues on consumer purchase are non-monotonically moderated by discount depth.
Methods and Results
Study 1: consumer attribution for the retail price discount
To prove that consumer attribution for retail price discounts varies with the discount depth, researchers employed three discount groups (low vs. moderate vs. high) and used fresh fruit as the stimulus. One hundred and twenty-one undergraduate students (50.4% male, 49.6% female) participated for monetary compensation and were randomly assigned to one of the three conditions. We asked the participants to imagine that they were planning to buy some cherries online and presented a webpage (without giving the exact name of the website) containing a picture of the product, a brief description of its attributes, the original price, and the discount (20% vs. 50% vs. 80%) (See online appendix E). We told all participants that the original price was the regular online price.3 Next, we asked them to write down the most likely reason for the price discount. Finally, as a manipulation check, we asked them to indicate their perceptions about the price discount using a seven-point scale (“What do you think of the magnitude of price discount? 1 = extremely small, 7 = extremely large”). We kept all other factors that might affect their attributions, such as product introduction, product picture, and return policy, the same across the three groups.
Consumers are more likely to attribute retail price discounts to quality-related (vs. quality-unrelated) factors when the discount depth is high (vs. low) and cannot unambiguously discriminate between the two causes when the discount depth is moderate. When the discount level was either high or low, consumers overwhelmingly attributed price discounts to a certain cause, clearly defining the relationship between product quality and price discount. Thus, the level of uncertainty in their quality perceptions is relatively low.
Study 2: the relationship between retail price discount depth and perceived quality uncertainty
In this experiment, researchers employed three discount depths (low vs. moderate vs. high) and one control group without a price discount. Two hundred undergraduate students (49% male, 51% female) participated for monetary compensation and were randomly assigned to one of the four conditions. They asked participants to imagine that they were planning to buy some kiwi fruit online, and we presented a webpage (without giving the exact name of the website) containing the product description, the original price, and the discount (20% off vs. 50% off vs. 80% off) (See Online Appendix E). In addition, we told all participants that the original price was the regular online price. All other factors that might affect quality evaluation, such as product introduction, product picture, and return policy, are the same across the four groups.
Manipulation Check. As expected, the participants in the four groups (no discount vs. 20% off vs. 50% off vs. 80% off) perceived significant differences among the various selling prices (F [3, 196] = 36.744, p < .01). As price discount increased, they perceived lower selling price (Meanno = 5.240, Mean Low = 4.760, Meanmoderate = 4.240, Mean High = 2.900, Meanno, low = 0.480, p < .05; Mean Low, moderate = 0.520, p < .05; Mean Moderate, high = 1.340, p < 0.01), suggesting that our manipulation was effective.
This conditional process model contains a mediation process (price discount → perceived mean quality → purchase intention) combined with the moderation of the path from perceived mean quality to purchase intention by perceived quality uncertainty. The results showed that the interaction effect of perceived mean quality and perceived quality uncertainty on purchase intention was significant and negative (β = −0.085, p = .078), which suggests the effect of perceived mean quality on purchase intention is stronger at a lower level of perceived quality uncertainty.
In addition to serving as an economic incentive, retail price discount fulfills an informational function as a quality indicator. Compared with the extant literature that focuses on the impact of price discounts on the mean of consumers’ quality perceptions, we mainly focus on another outcome variable, uncertainty in perceived quality, which refers to the variance of consumers’ quality perceptions.
Unlike the monotonic relationship between price discount depth and perceived quality, the relationship between price discount depth and perceived quality uncertainty is an inverted “U” shape. Consumers are more likely to attribute price discounts to quality-related (vs. quality-unrelated) factors when price discount is high (vs. low). They are unable to discriminate between the two causes when the price discount is moderate. Thus, the level of uncertainty in perceived quality is low when the price discount is either low or high, but high when the price discount is moderate.
Future research can extend our study to explore the boundary conditions for the inverted-U-shaped relationship between price discount depth and perceived quality uncertainty. For example, an interesting extension is to investigate whether the inverted-U-shaped relationship between retail price discount depth and perceived quality uncertainty holds for categories that provide standard and storable goods, for consumers with sufficient purchase experience or expertise, or in the presence of a dominant non-price quality cue.
In light of our current work, the reason may be that when assessing quality for packaged grocery goods, consumers perceive a national brand signaling good quality is less diagnostic than a store brand signaling inferior quality. Therefore, consumers perceive higher uncertainty and rely more on other quality cues such as ingredients for quality learning when provided with a national brand (vs. store brand). Future research can extend to cover more different types of quality cues and consumer learning behavior.
Understanding the subtleties of consumer behavior is essential for businesses to succeed as the online retail industry continues to develop. The two articles' research findings provide insight into the nuances of retail price reductions, perceived quality uncertainty, and the effect of repurchase intentions on online reviews. By achieving the ideal balance between alluring discounts and perceived value and by utilizing the persuasive power of repurchase intentions, businesses may dramatically influence customer behavior and achieve favorable results in the cutthroat digital market.