مزایای سود قیمت گذاری بسته بندی محصولات تکمیلی
کد مقاله | سال انتشار | تعداد صفحات مقاله انگلیسی |
---|---|---|
1863 | 2011 | 7 صفحه PDF |
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Journal of Retailing and Consumer Services, Volume 18, Issue 4, July 2011, Pages 355–361
چکیده انگلیسی
In an attempt to provide a framework that can help firms find optimum bundling product categories and pricing strategies that maximize their profits, this study develops a profit-maximization model. The results indicate that optimum bundles and price strategies exist; specifically, if a firm uses a bundling strategy to sell its products, it should combine highly complementary products and charge a relatively lower price. The value of a bundling strategy always increases with the size of market and price sensitivity. Managers can use the provided model framework and related advice and examples to plan their bundling strategies.
مقدمه انگلیسی
A common marketing strategy bundles complementary products and services, though the pricing of these bundles remains an extremely challenging task. Firms must consider various issues, including segmented customer demand, product-specific costs, and consumers' multiple options. Furthermore, bundling decisions have significant implications for monopoly power, level of welfare, and marketing strategies especially as integrated, unique solutions become more common as firms' central market offering. Finally, bundling can minimize consumer costs from 18% to 57%, depending on the number of items bundled, the value of those items, and the level of the variations (Estelami, 1999). Because complementary product bundling can offer economies of scale, bundle choices and sizes are significant for both consumers and suppliers. Moreover, because the cross-elasticity of demand for complementary goods is negative – that is, demand for one complementary good creates demand for the other – firms can gain additional marketing power through bundling, and vendors can obtain optimal prices. For example, if they price the base good at a relatively low price, consumers are more likely to consider the secondary product. Various examples of complementary product bundling describe the different approaches that firms have taken to this strategy. Michelin may be the pioneer of bundling; when it started publishing the Michelin guide, it provided tourists with information about gas stations, hotels, and restaurants, as well as maps and driving directions. But it also encouraged the use of automobiles, which boosted its tire business, making tourist guides and automobile tires seemingly strange complements. More conventionally, DVD players and disks clearly are complementary and function as a system, just as computer hardware and software or season tickets and sporting events are. A perfect complement must be consumed with its complement; for example, demand for hot dogs creates parallel demand for buns, as well as for ketchup, mustard, and other related items. These widespread actual examples have prompted various research models, though none of these models addresses optimal pricing and profit maximization for complementary products. We therefore propose a model in which the optimal price for complementary products depends on the degree of complementarity between the two products. A higher degree of complementarity produces a unique symmetric equilibrium, such that all consumers simultaneously buy both products. When the degree of complementarity is lower, asymmetric equilibrium exists, the firm behaves as a monopolist, and some consumers buy only the monopoly product while others always buy both. At intermediate complementarity levels, both types of equilibria exist. In this context, the degree of complementarity should influence the advantages of bundling products and thus the optimum bundling that allows the firm to maximize its profit. According to Cournot (1938), if joint consumption is mandatory, firms should set a price based on the value of the joint consumption. Economides (1996) confirms this view by showing that a firm can charge higher prices by selling complementary products to customers who prefer the composite goods. The firm's sale therefore depends on the price of the bundle and the degree of product complementary. We propose a profit-maximization model to address three main research questions: What is the optimal pricing strategy when there is no bundling? What is the optimum product and pricing strategy when the firm uses bundling? What is the value of a bundling strategy to the firm if the market is large and consumers are sensitive to price? In the next section, we summarize relevant literature before we present our profit-maximization model with two different scenarios, depending on whether the firm uses or does not use a bundling strategy. The main results pertain to optimal policies and a sensitivity analysis; we also present the results of a numerical analysis that we conducted to provide further insights for firms. We end with some conclusions and managerial implications.
نتیجه گیری انگلیسی
Our study contributions are both theoretical and substantive. Specifically, we demonstrate that optimum product categories and pricing strategies exist for a firm that sells complementary products through a bundling strategy. We first derive a pricing strategy for no bundling and bundling scenarios, then use comparative statistics to determine optimal strategy decisions. The results indicate that a firm using bundling to sell its products should offer a larger discount and charge a lower price when the degree of complementarity between the two products is high. Furthermore, a bundling policy is always valuable for the marketer when the products are close complements, and the value of the bundling policy always increases with market size and bundling discount price sensitivity. Our numerical examples further illustrate and confirm our analytical findings, which in turn offer key managerial implications. Our findings can help firms identify the values of different product categories and the corresponding optimum pricing strategy for their bundling policy. In addition, companies can use the insights from our research to improve their marketing decisions and thus improve their profits. Many firms use or plan to use bundling strategies to sell products to consumers. As bundling becomes more and more popular, it is of increasing managerial relevance to develop an optimal strategy for marketers. We employ a profit-maximization model to confirm this intuition objectively, using optimum bundling product categories and pricing strategies. If it strategically implements such strategies, a firm can maximize its profit efficiently. For example, retailers, who sell complementary products, such as computers and speakers, should offer a generous discount policy and charge a lower price for bundled products. The business market contains several examples, including Best Buy, Babies “R” Us, and Kohl's, that have successfully applied these strategies. We also suggest several extensions to this research. First, we have assumed that firms have perfect information about the market, but additional research should explore the optimal bundles of products and pricing strategies in an incomplete information setting. Second, our analysis is based on a single-period model. Research that examines these issues in a dynamic multiperiod environment would add to our understanding of bundling. Third, our model is based on the demand for a single firm. Competition might be incorporated explicitly into our model to support an analysis of demand for not only a single firm but also with regard to competitive decisions.2 Fourth, the effect of mixed bundling on firm performance may be an interesting research topic in the future.3 Finally, we assumed a linear theoretical demand function in this paper for analytical tractability. While the linear theoretical demand models have been used extensively in economics and marketing, we can further examine whether the derived qualitative implications generalize to other demand functions, such as non-linear demand functions and more flexible empirical regression models, as avenues of future research.