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Article Excerpt
1. Introduction
"Companies must be flexible to respond rapidly to competitive and market changes." --Michael Porter (1996)
Contemporary businesses face uncertainty due to a variety of factors, such as increasing globalization, proliferation in product varieties, disruptive changes in technology, and most importantly, uncertain demands from customers. In this context, approaches to incorporate operational flexibility in a firm's supply chain, to better match supply and demand, have received considerable attention. One such approach is delayed differentiation or postponement. Using delayed differentiation, a firm delays or postpones the final customization of a related bundle of products (and/or the shipment of a product to different geographical markets) to the extent possible, pending more accurate product- and market-specific demand information. This is a form of risk pooling across markets.
Delayed differentiation is well illustrated by the celebrated example of Hewlett-Packard (HP) (see Lee et al. 1993). HP manufactured the Deskjet-Plus printers in its Vancouver, Washington facility, and shipped the printers to three distribution centers in North America, Europe, and Asia. The transit time by sea to the two non-U.S. distribution centers was about a month. Depending on the eventual destination country, different power-supply modules had to be installed in the printers to accommodate local voltage, frequency, and plug conventions. The manuals and labels also had to be localized due to language differences. HP redesigned the printer so that the power module could be added as a simple plug-in, manufactured a generic Deskjet-Plus printer in the United States (sans power-supply module, manual, and labels), and later localized the generic product in Europe--based on observed demand conditions. Restructuring its printer-production process in this fashion enabled HP to maintain the same service levels with an 18% reduction in inventory and saving millions of dollars (Lee et al. 1993). A recent survey across a number of industries including aerospace, automotive, education, health care, retail, high-tech, and telecommunications found that 9% of the firms, employed some form of postponement (Mathews and Syed 2004).
The main model in this paper builds on Anand and Mendelson (1998) and extends their research to a competitive setting. In Anand and Mendelson (1998), a monopolist firm's supply chain consists of a production facility, a distribution center, and two differentiated markets. Demand information is used to mitigate the effects of uncertainty in the output markets. They compare a firm's performance under two alternative supply chain configurations--early and delayed differentiation, to quantify the value of postponement. They compute the optimal shipping and production policies in a dynamic (multiperiod) setting, and study the drivers of the value of postponement.
In the current study, we model delayed differentiation as a decision variable in a competitive scenario. Each firm in our duopoly model chooses between two different supply chain configurations: delayed differentiation or early differentiation. We derive the equilibrium choices of supply chain configurations, and analyze the corresponding sales, production, consumer surplus, welfare, and profits for each firm. Although the conventional risk-pooling benefits of the monopoly models persist in our setup, we additionally identify strategic consequences of the supply chain configuration employed. We show that for a wide variety of demand parameters, firms may prefer to deploy early rather than delayed differentiation even under cost parity between the two options. Further, under plausible conditions, we find a dominant-strategy equilibrium in early differentiation, i.e., each firm's dominant strategy (independent of the other firm's choice) is to employ early differentiation. We observe this even when all cost and demand parameters are identical under early and delayed differentiation. To understand the drivers of these results, we parse the profits of each firm into two additively separable components. The first is the risk-pooling premium that favors delayed differentiation and drives the results in a monopoly setting. It is a function of the demand variances and coefficients of correlation across the different markets. We term the second component, unique to our competitive setting, the strategic premium. This component is a function only of the size of the market in which the two firms compete, and is higher under early differentiation. As the demand variances fall, the correlations between a firm's markets increase, or the size of the competitive market increases and the strategic premium begins to dominate the risk premium; leading to the results discussed above.
We extend the analysis to a variety of relaxations of the original model, including heterogeneous markets and retailers ([section]6), and alternative market structures ([section]7), and find that our results are consistent. A unilateral increase in the mean demand of the competitive market (keeping everything else constant) favors early differentiation, although such an increase in the size of any of the monopoly markets has no impact on either firm's choice of supply chain configuration--the absolute profits under early or delayed differentiation obviously change but their relative ordering does not. Thus, the degree of competition (the relative size of the competitive and monopolistic markets) is an important determinant of the optimal supply chain configuration. Similarly, the impact of a change in the demand correlation between a firm's markets is unambiguous: A unilateral decrease in this correlation increases the risk-pooling premium and favors delayed differentiation for the firm, irrespective of the other firm's supply chain configuration. It is important to emphasize that, in our models, the relative disadvantage of delayed differentiation with respect to early differentiation does not arise out of different process costs, but is purely due to endogenous strategic effects.
The rest of this paper is organized as follows. Section 2 reviews the related literature, and [section]3 describes our modeling framework. Section 4 derives and compares the equilibrium production, sales, and profits under each possible supply chain configuration. In [section]5, we characterize the equilibrium choices in supply chain configurations. In [section]6, we relax the assumption of identical distribution of market demands and further extend the model and analysis by allowing for completely general distributions of demand. Next, we examine the implications of the clearance and market structure assumptions of the main model of [section][section]3-5, by relaxing these assumptions in analytical models (in [section][section]7.1 and 7.2, respectively). We demonstrate that our central message--that early differentiation is often the dominant strategy for firms under competition, on account of the strategic premium; and that the choice of supply chain configuration must take the industry structure into account--is robust to all the relaxations analyzed in [section][section]6 and 7. Concluding remarks are in [section]8.
2. Related Literature
In addition to the studies of HP's use of postponement by Lee and colleagues, there is an extensive stream of operations research on postponement under monopoly settings. The interested reader is referred to the comprehensive reviews of this literature in Anand and Mendelson (1998) and Swaminathan and Lee (2003). A second stream of research, mostly in economics, on early-mover commitment also relates to our competitive setting.
Military lore is replete with stories of generals gaining commitment for battle from their troops by cutting off their retreat options--by burning the transport ships or bridges they used to reach enemy lines (from which the idiom "burning one's bridges" derives) or by "nailing one's colors to the mast" in Naval warfare. Troops must then win or die. Schelling (1960) provides other examples; his citation for the 2005 Nobel Prize in Economics read, in part, "Schelling showed that a party can strengthen its position by overtly worsening its own options." Similarly, under competition, a player who commits first to a course of action or (equivalently) restricts his own options in a manner convincing to his opponents may gain a strategic advantage, as in Stackelberg (1934). Hamilton and Slutsky (1990) and Rabah (1995) show that the signs of the slopes of the best-response functions drive players' preferences for the order of moves in a game: Each player prefers his simultaneous Nash payoff to his Stackelberg follower payoff if and only if the best-response curves are downward sloping. Stackelberg's (1934) equilibrium arises in multistage production games in Saloner (1987), Pal (1991), and Maggi (1996). Capital investments can play a similar role. A player might invest in capacity to gain a strategic advantage in the subsequent Cournot (quantity-setting) competition (Dixit 1980, Spence 1977) or second-stage price competition (Allen et al. 1995). Vives (2000) provides a good overview of this literature.
The literature on dedicated versus flexible manufacturing technologies under competition is of particular interest from an operations perspective (Roller and Tombak 1993, Boyer and Moreaux 1997, Goyal and Netessine 2007). The main finding is that employing dedicated production technology can have commitment value under competition. Roller and Tombak (1993) analyze a two-stage game, in which firms chose between a flexible and a less-flexible technology in the first stage and decide on production quantities in the second stage. In equilibrium, adoption of flexible technologies is more likely in concentrated markets. Boyer and Moreaux (1997) extend the analysis to consider the effect of volatility and market size on the choice of production technology. Goyal and Netessine (2007) formally prove the existence and the uniqueness of an equilibrium in the stage games under general conditions, and characterize the restrictions that lead to specific equilibrium outcomes.
In our study, the trade-off between commitment and flexibility arises from choosing the point of differentiation of an intermediate good into related end products. Our results demonstrate that the rich literature on delayed differentiation arguing its superiority over early differentiation under cost minimization or profit maximization was predicated very strongly on the monopoly assumption. Under competition, the strategic premium plays a pivotal role, leading to early differentiation as a dominant strategy under a broad range of parameters, even under cost parity with delayed differentiation. Our paper demonstrates the vital importance of the link between operations and industry structure. In optimizing its operations, it is imperative for a firm to take its industry structure into account.
3. Model Setting
3.1. Competitive Structure
Two competing firms seek to maximize their individual expected profits under demand uncertainty. Each firm sells two related products; for concreteness, we will assume that each product is sold in a distinct product market. Each firm is the monopoly supplier in one of its two markets, which we call the monopoly market (denoted by the superscript M). The two firms compete in their other market (the competitive market, denoted by the superscript C). (1)
The model reflects a common situation wherein a firm is a strong player--a near monopolist--in one market (e.g., its home market), and faces strong competition from local players in overseas markets. For example, in the case of inkjet printers (discussed above), HP was a dominant player in the United States, a competitive force in Europe, and a marginal presence in Japan, due to strong competition from companies like Epson. (2)
3.2. Market Model
Following Anand and Mendelson's (1998) monopoly model, each market faces a linear and downward-sloping demand curve p(q) = a - q, (3) where the intercept a is random, and drawn from a distribution with mean...
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