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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : International Journal of Research in Marketing, Volume 28, Issue 4, December 2011, Pages 309–318
Potential customers' willingness to pay (WTP) for a new product can be affected by their observing a posted price and this can be modeled in terms of an anchoring mechanism. A theoretical argument and mathematical proof are developed, showing that if customers use an asymmetric WTP anchoring mechanism, it will normally be optimal for firms to price higher than otherwise. Experimental evidence is provided supporting the notion that an asymmetric anchoring mechanism can be involved in purchase decisions.
Marketers often tell the story of a Native American jewelry shop that had trouble selling an allotment of turquoise jewelry to its customers, who were mainly tourists in Arizona. After trying several other promotions, the owner of the store left her assistant a note with instructions stating, “Mark down the items by 1/2.” Misunderstanding the note, the assistant instead doubled the price of each piece…and sold out (Cialdini, 1985). A critical factor in this story is that the vacationing customers who bought the assortment were unfamiliar with turquoise jewelry. If they had a well-formed idea of how much this jewelry was actually worth, then they never would have responded as they did. Because they were unfamiliar with the product, they were strongly influenced by its price. Based on their behavior, we infer that these customers must employ a rationale for their purchasing decision different from the traditional rationale in which customers make their subjective valuation of a product independently of the product's listed price. In these situations, customers are forced to make purchasing decisions regarding unfamiliar new products. In such cases, the listed price can be an important determinant of the customer's willingness-to-pay (WTP), which is defined as the maximum amount that a customer is willing to pay for a product. Just as the jewelry shop owner did not consider the influence of the price on her customers' WTP, the most common new product pricing strategies rarely consider the possibility that price setting can affect customers' WTP. For new products in which WTP plays a key price-setting role, the two main pricing strategies are skimming and penetration. Businesses that employ a skimming strategy price their products higher than the average customer's WTP. By doing so, the businesses first attract early adopters, who presumably have relatively inelastic demand. After setting the initial price at a higher level, the businesses could attract later customers with lower WTP by reducing their prices. Businesses that utilize the penetration strategy price their new products low enough that the initial offer price is less than the WTP of a large number of potential customers. Both of these strategies set prices for products by assuming that customer WTP is fixed. This assumption may be based on a well-established method for estimating WTP, such as conjoint modeling or the contingent valuation method (CVM). However, these methods will fail to provide an accurate estimate of customer WTP if a customer's WTP is not fixed but influenced by the listed price. We contend that customers are normally unsure about their original WTP for a new product and are likely to modify this value after observing the listed price. This claim leads us to our central contribution to the literature. Specifically, we develop and evaluate new pricing models that show how a customer's awareness of the listed price affects his or her WTP. In addition, we provide companies with a suggestion regarding their price-setting strategies for their new products. Another key feature of our approach is that we treat a customer's uncertainty regarding WTP as a probability distribution from which the customer draws a random WTP at the time of the purchase. Furthermore, the customer can consider the observed market price as one indicator of the probability distribution of the other customers' WTP. Our proposed models assume that a customer's WTP is semi-endogenous in that the customer's original WTP is formed independently of the price but is influenced and changed by the price at the final purchasing stage. More specifically, in our model, customers do not simply compare the original WTP with the listed price but also adjust their original WTP to accommodate the additional information presented by the observed price. Then, they compare the adjusted WTP with the price in the final purchasing decision. Our ideas are similar to those of Wathieu and Bertini's (2007) study, where the listed price is not simply compared with the WTP but also stimulates the customers to reconsider their WTP. However, our study utilizes a different assumption with regard to whether the WTP is affected by the observed price. Our model assumes that the listed price affects the customers' WTP while they reconsider their decision, whereas in their model, the WTP remains unaffected by the observed price at this point. We postulate that customers go through one of two adjustment mechanisms that yield different purchasing decisions in which their WTPs are presumed to be modified by the listed price. Whereas in the first adjustment mechanism (i.e., the One-step Anchoring Mechanism (AM1)), the customers adjust their WTP symmetrically in both upward and downward directions; in the second mechanism (i.e., the Two-step Anchoring Mechanism (AM2)), the customers only adjust their WTP in an upward direction. Under the AM2, companies can justifiably set prices higher than they would if the WTP were determined exogenously (i.e., without considering the reaction of the customers to the listed market price). According to the AM2, if customers see a listed price that is lower than their WTP, then they automatically purchase the product. However, if the listed price is higher than their WTP, then they modify their WTP instead of simply forgoing the purchase, as suggested by the conventional purchasing mechanism. Essentially, we argue that a higher-than-WTP price provides a customer with an opportunity to revalue his or her WTP such that the new WTP reflects a higher level of quality or scarcity, which the customer would have missed at the first evaluation stage because of risk aversion but which the other customers had recognized.3 Based on this new information, the customer draws a new WTP from the revised WTP probability distribution. This distribution is asymmetrically modified, which means that the ex post distribution is shifted upward, increasing the probability that the new WTP drawn from this distribution will be higher than the listed price. The remainder of the paper is organized as follows. Section two reviews the relevant literature, section three introduces our theoretical model, section four provides some empirical support for our model, section five describes the managerial implications, and section six provides our conclusions, the practical implications, the limitations of the paper, and our proposals for future research.
نتیجه گیری انگلیسی
In this study, we developed two mechanisms for describing how customers adjust their WTP for new products. We presume that customers anchor their WTP by calculating the weighted average of their subjective WTP and the market WTP. In a One-step Anchoring Mechanism (AM1), the customer directly compares the observed price with his or her anchored WTP. In a Two-step Anchoring Mechanism (AM2), the customer first compares his or her subjective WTP with the observed price and then (if necessary) compares his or her anchored WTP with the listed price. We provided logical arguments for these mechanisms, showed how they relate to the findings of prior research, and then developed a series of propositions that followed from the mechanisms. Then, we provided experimental evidence in support of AM2. Lastly, we examined the pricing implications for firms that desire to maximize profits. As our study and prior research on anchoring and adjustment have shown, a firm that uses well-proven methods to research its customers' subjective WTP before it sets the price for new products may still price its offering below the profit-maximizing level because these methods do not usually account for the anchoring and adjustment effect described in this paper. Note that we are not suggesting that such methods be dropped altogether. However, we do suggest that prices based on such methods be adjusted upwards and retested in realistic environments that allow for anchoring and adjustment effects to be observed. These findings will be of interest to firms that develop or sell innovative products. Pricing these types of products is a major concern for these firms, and our findings suggest that firms using “skim” pricing strategies stand to benefit from the upward adjustment in the WTP that their customers experience at the time of the purchase. To develop our model, we imposed many distributional assumptions, such as the assumption that both the subjective WTP and the market WTP have the same type of distributions. In addition, our model can be developed in many ways by relaxing the distributional assumptions. For example, by relaxing the assumption of identical variance, we can develop a model that captures the relationship between pricing and the degree of uncertainty associated with the subjective WTP. Our logic suggests that if customers have more ill-formed notions of their WTP for new products, then we should find higher prices in the marketplace, but we know of no research that has evaluated the relationship between pricing and WTP variance. Moreover, future scholars can probably find evidence suggesting that different types of customers have different WTP distributions, which may lead to certain opportunities for legal price discrimination across the isolated customer segments. Finally, our model can also be expanded to a multi-period model that explains a customer's repeated purchasing behavior. A multi-period model based on our models will help explain how customer WTP evolves as new products become established in the marketplace and will also help account for the differences in the price elasticities between repeat purchasers and first-time buyers.