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IIMA INDIA<br />

Research and publications<br />

the internet boom years <strong>of</strong> the late 1990s, Mercata.com developed a pricing structure that encourages<br />

consumers <strong>to</strong> buy as a group rather than as individuals. In this transaction system, multiple consumers<br />

congregated in cyberspace at one point in time at one place <strong>to</strong> <strong>to</strong>gether buy large numbers <strong>of</strong> a single<br />

item. If, for example, up <strong>to</strong> 5 people register <strong>to</strong> buy a Palm VIIx, they pay $299 each; if between 5 and<br />

8 people register, the price drops <strong>to</strong> $269. For 9 or more people the price drops <strong>to</strong> $249. The ‘sale’<br />

ended at a designated time; the price paid by a cus<strong>to</strong>mer was a function <strong>of</strong> the number <strong>of</strong> cus<strong>to</strong>mers<br />

who registered <strong>to</strong> buy the product. This transaction system encouraged cus<strong>to</strong>mers <strong>to</strong> buy as a group<br />

and at the same point in time.<br />

Similarly, Procter & Gamble’s move in the early 1990’s from high-low pricing <strong>to</strong> ‘value<br />

pricing,’ an EDLP structure ran contrary <strong>to</strong> the expressed preferences <strong>of</strong> market players and helped<br />

reduce the forward buying and s<strong>to</strong>ckpiling behavior <strong>of</strong> retailers as well consumers. As is well known,<br />

penetration pricing not only can help expand market size but, in its extreme form, also alter market<br />

structure by driving out competi<strong>to</strong>rs. Such preda<strong>to</strong>ry pricing is, <strong>of</strong> course, illegal in the U.S., but<br />

underscores the power <strong>of</strong> pricing structures in driving markets. At a more tactical level, a firm can use<br />

price-matching refund policies <strong>to</strong> discourage the extent <strong>of</strong> price search that would otherwise have<br />

been conducted by a consumer (Srivastava and Lurie 2001). Firms can also increase purchase rates<br />

by restricting the consumer’s flexibility through an expiring discount that reduces the time available<br />

<strong>to</strong> make a decision for an <strong>of</strong>fer (Amir 2002).<br />

A third form <strong>of</strong> staking behavior entails what may be termed enlightened ‘planned<br />

cannibalization.’ For example, Intel periodically introduces new generations <strong>of</strong> microprocessors with<br />

new features and functionalities and encourages cus<strong>to</strong>mers <strong>to</strong> migrate <strong>to</strong> these by educating them<br />

about the new functionalities and their criticality (see also Sethi 1979). A fourth form <strong>of</strong> staking<br />

behavior entails designing products in a manner that lowers the risk for market players. For example,<br />

by modularizing a product’s components, a firm can reduce the time taken <strong>to</strong> repair the product,<br />

thereby reducing cus<strong>to</strong>mers’ perceived risk and encouraging them <strong>to</strong> adopt the product (see also<br />

Garud and Kumaraswamy 1993).<br />

Physical context setting behaviors aim <strong>to</strong> drive markets by altering the physical context or<br />

environment <strong>of</strong> market players. For example, the use <strong>of</strong> congruent music and fragrance in s<strong>to</strong>res<br />

W.P. No. 2013-05-07 Page No. 11

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