儿童感冒发烧Profiting from Demand Uncertainty: Pricing Strategies in Advance Selling
Xuying Zhao
Mendoza College of Business, University of Notre Dame, Notre Dame, IN 46556, xzhao1@nd.edu
Zhan Pang
Department of Management Science, Lancaster University, Lancaster, LA1 4YX, United Kingdom, z.pang@lancaster.ac.uk
Is demand uncertainty a devil? A conventional thought is that demand uncertainty hurts a ller’s profit. However, we show that demand uncertainty could favor a ller if the pricing mechanism is designed properly. Specifically, we study the optimal pricing strategy in advance lling with both consumer demand and valuation uncertainties. Three strategies are considered and compared: dynamic pricing (DP), price commitment (PC), and pre-order price guarantee (PG). We show that consumer valuation and demand uncertainties in the advance lling period play important roles in determining the optimal pricing strategy. When pre-order demand uncertainty or consumer valuation uncertainty is high, a ller should u PG, which enables the ller to profit from demand uncertainty. Otherwi, PC is the optim
听不到吉他谱al strategy. Furthermore, PG, while increasing a ller’s profits, reduces consumer surplus, which may lead to a lower social welfare compared to the other two strategies. Key words : Advance lling, pricing strategies, strategic consumer behavior History : This paper was first submitted in June, 2011.
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违章举报Introduction
With the development of Internet and new technologies, advance lling has been adopted by a variety of product and rvice providers as an important marketing strategy. A special form of advance lling is pre-order for new to-be-relead products. Under advance lling strategy, a ller encourages consumers to pre-order a new product before its relea date to receive guaranteed prompt delivery on the relea date. For example, both Amazon and Barnes & Noble u the advance lling strategy for most new to-be-relead products such as novels, softwares, movie DVDs, music albums, game consoles, and video games. Through pre-orders, consumers are guaranteed to receive the new product on its relea date. This is especially valuable to consumers in anticipation of the stock-out risk after the relea. For instance, Apple’s iPad 2 was sold out in ma
配件仓库管理ny stores on its relea date after stoking hours-long lines (Dilger 2011). In mid 2006, llers announced that no Wii game consoles would be available without a pre-order until 2007 (Martin 2006, Li and Zhang 2011). In general, an advance lling scheme involves two periods. The first period is the advance lling
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Electronic copy available at: /abstract=1866765
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Zhao and Pang: Pricing Strategies in Advance Selling Article submitted to Management Science; manuscript no. (Plea, provide the mansucript number!)
桶包period before a product is relead. At the beginning of the first period, a ller determines the advance lling price. The cond period is the (spot) lling ason after the product is relead. Before the lling ason starts, the ller determines the inventory to hold for the lling ason and announces the (spot) lling price. In practice, advance lling can be implemented with different pricing strategies. We are interested in three pricing strategies that are commonly obrved
in practice: dynamic pricing (DP), price commitment (PC) and pre-order price guarantee (PG). Dynamic pricing (DP) is the most prevailing and easy-to-implement strategy under which a ller only specifies the advance lling price in the first period. The lling ason price is announced at the beginning of the lling ason. Under DP, consumers arriving in the advance lling period are uncertain about future spot price. They may hesitate to buy early becau prices may fall right after products are relead. It is often obrved in practice that many products were charged a high price in the advance lling ason and then have a significant price cut after the relea. For instance, the pre-order price for Amazon Kindle 2 was $359 and then dropped to $299 after the relea (Carnoy 2009, Li and Zhang 2011). Best Buy accepts pre-orders for Motorola Xoom tablet at the price of $1,199 and the lling ason price is slashed to $599 (or $799 for an advanced model) on the relea date (Ronberg 2011). Price commitment (PC) is another commonly obrved pricing strategy in advance lling. Under PC, a ller announces the advance lling price and lling ason price simultaneously at the beginning of the first period. When the lling ason price is committed higher than the advance lling price, PC removes consumer incentive to wait for price cut after relea. For example, conferences such as INFORMS and POMS annual meetings usually announce early registration fees for each time period, which exhibit a pattern of increasing fees when time is clo to the conferences. However, in practice, the pricing path under PC may not nece
ssarily be low-to-high. The lling ason price could also be lower than the advance lling price. For example, llers such as Filene & Bament (Bell and Starr 1994), Lands End, and Syms clearly announce their prices and future price discounts for some of their products (Aviv et al. 2009). A potential risk associated with an upfront committed prices is the loss of ability to react to sales realization at the end of the advance lling period and the potential market changes in the lling ason. Another issue for PC is the credibility of a ller. It may be difficult for consumers to trust a small ller’s commitment on future price. We focus on situations where reputation effects or other factors allow llers to credibly commit to their preannounced lling ason prices, i.e., the ller has exogenous creditability (Xie and Shugan 2001). For example, a big ller such as Amazon is credible to keep its commitment on spot price if it would adopt PC, considering that the spot prices are obrvable online to every one.
Electronic copy available at: /abstract=1866765
Zhao and Pang: Pricing Strategies in Advance Selling Article submitted to Management Science; manuscript no. (Plea, provide the mansucript number!)
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Pre-order price guarantee (PG), also called pre-order price protection, is a more sophisticated strategy than the previous two. Under PG, a ller dynamically charges the price in the lling ason, while committing to refund the price difference to pre-order consumers if the spot price is lower than the pre-order price. For instance, Amazon implements PG for all of its pre-orders. AT&T offered price protection (refunds) for consumers who purchad iPhone 3GS about one month early before its price reduction (Ziegler 2010). PG provides multiple benefits to a ller. First, it attracts consumers to buy early, especially tho hesitating to buy early becau of potential price change in the future. Second, it helps a ller to increa the pre-order price without driving consumers away becau of the hope of getting refunds later. However, under PG, a ller may also risk to lo some profit in the advance lling period when price matching happens in the lling ason. This paper compares the aforementioned three pricing strategies in advance lling, taking into account strategic consumer behavior. We aim to address the following rearch questions: What are the optimal pre-order and spot prices under the pricing strategies? What are the profit and social welfare implications under the strategies? What are the roles of valuation and demand uncertainties on a ller’s profit and choice among the three pricing strategies? To address our rearch questions, we develop a stylized model which captures the important characteristics of advance lling where both consumer demand and consumer valuation of the product are uncertain.
A consumer’s product valuation is uncertain when making early purcha decision. For example, when a consumer pre-orders a new to-be-relead product, she gives up the opportunity to evaluate the product during the purcha period, such as browsing the new novel, or sampling the new CD, or trying out the new video game in a local store and then decide whether to buy it or not. Recent rearch (Shugan and Xie 2000, 2005, Xie and Shugan 2001, Prasad et al. 2011, Zhao and Stecke 2010, Fay and Xie 2010) has shown that consumer valuation uncertainty is an important feature in advance lling. To capture consumer valuation uncertainty, we follow Xie and Shugan (2001) to assume that consumer valuation follows a two-point Bernoulli distribution before the lling ason starts. That is, there is a probability for consumers to realize a high valuation. If such a probability is high or low, then consumer valuation uncertainty is low. In addition to consumer valuation uncertainty, we also consider demand uncertainty. Zhao and Stecke (2010) and Prasad et al. (2011) show that demand uncertainty further facilitates advance lling becau of the prence of stockout risk. To capture demand uncertainty, we assume demand in each period follows a general distribution. It is important to note that our rearch questions cannot be answered by existing pricing strategy and advance lling literature. Most studies in advance lling literature focus on the question whether or not a ller should ll in advance. Very few papers consider and compare different
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Zhao and Pang: Pricing Strategies in Advance Selling Article submitted to Management Science; manuscript no. (Plea, provide the mansucript number!)
pricing strategies after a ller decides to ll in advance. Among the few papers that do compare different pricing strategies, the extant models in pricing strategies do not allow for consumer valuation uncertainty and the extant models in advance lling do not allow for consumer demand uncertainty. Figure 1 summarizes the positioning of this paper. To the best of our knowledge, ours reprents the first attempt to examine the impact of both consumer valuation uncertainty and demand uncertainty on pricing strategies in advance lling.
YES
Consider Consumer Valuation Uncertainty
NO我的发现
Consider Demand Uncertainty
Consider Demand Uncertainty
桑葚酒的功效与作用
YES
NO
YES
The Current paper
Recent study on advance lling. (e.g., Xie and Shugan 2001)
Figure 1
Recent study on pricing strategy to deal with strategic consumers. (e.g., Aviv, Levin, and Nediak 2009, Li and Zhang 2011, Su and Zhang 2008, Lai et al. 2010)
Paper Positioning
Our analys reveal that consumer valuation uncertainty and demand uncertainty play the key roles in determining the optimal pricing strategy in advance lling. Especially, we find that PG enables a ller to profit from pre-order demand uncertainty. The higher the pre-order demand uncertainty, the
higher the ller’s expected profit. Our main findings are as follows. 1. In terms of profits, PC is always better than or equal to DP. In particular, if the probability for a consumer to realize a high valuation is neither too high nor too low, i.e., consumer valuation uncertainty is high, PC generates more profits than DP. Otherwi, the two pricing strategies have the same expected profits. 2. In terms of profits, the performance of PG not only relies on consumer valuation uncertainty, but also on demand uncertainty during the advance lling period. When consumer valuation uncertainty is high, i.e., the probability for a consumer to realize a high valuation is neither too high nor too low, PG dominates the other two strategies if there exists first period demand uncertainty. Otherwi, the statement is reverd. When it is highly probable that consumers may realize a
点读机女孩
Zhao and Pang: Pricing Strategies in Advance Selling Article submitted to Management Science; manuscript no. (Plea, provide the mansucript number!)
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high valuation, a ller is indifferent among the three pricing strategies. At the other end, when consumers are very likely to realize a low valuation, PG dominates the other two strategies if the first period demand uncertainty is high. Otherwi, the statement is reverd. 3. In terms of social welfar
e, DP is the best among the three strategies, while it is not the best among three in terms of expected profits. We also show that none of the three pricing strategies maximizes social welfare. We provide characteristics of a social welfare maximizing strategy.
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Literature Review
This paper is cloly related to the study on strategic consumer behavior where a consumer anticipates future price and stocking out risks to decide whether to “buy now” or “wait”. In the area of strategic consumer behavior, the four main issues examined in this paper are: (i) dynamic pricing, (ii) price commitment, (iii) pre-order price guarantee, and (iv) consumer valuation uncertainty in advance lling. There are veral streams of related literature, each addressing different subts of the issues. Recent studies in DP explicitly model consumers’ decisions regarding when to buy. See Shen and Su (2007) for a comprehensive review. Aviv and Pazgal (2008) analyze DP with strategic consumers, a fixed initial inventory (capacity), and a single price reduction at a fixed time. Elmaghraby et al. (2008) also focus on a markdown mechanism in which prices decrea in steps according to a pre-announced schedule. Different from the above two papers, some studies, includin
g Su (2007) and our paper, find that markups or markdowns may be optimal under different situations. Another stream of literature studies the role of PC on counteracting consumer strategic behavior. For example, Besanko and Winston (1990) show that PC has an advantage over DP with strategic consumers, given a deterministic number of consumers, and without a fixed capacity constraint. That is, with DP, consumers may expect and wait for a significant price cut in the future. However, with PC, a ller is able to preannounce prices to show that there is actually no substantial price markdown in the future. When demand is uncertain and capacity (inventory) is fixed, Dasu and Tong (2010) and Aviv and Pazgal (2008) find that there is no domination relationship between DP and PC, and the performance gap between them is generally small. Next, Liu and van Ryzin (2008), Su and Zhang (2008), Su and Zhang (2009), and Yin et al. (2009) study how to u capacity and inventory availability information to change a strategic consumer’s behavior, given that a ller adopts PC. The above papers capture consumers concern over price risk (e.g., reluctance to buy now becau prices may drop substantially in the future) and availability risk (e.g., purcha intentions fueled by stocking out risks in the future). In the current work, we also consider fit risk. That is, “consumers are uncertain over their valuations, so there may be product misfit if valuations turn out to be low” (See Su 2009a for discussion about the three risks for consumers). In this ca, we find that PC is always better than or equal to DP in terms of profit.
