Consumers evaluate the convenience of changing their products according to the price paid as well as the technology (quality) level. When the consumers wish to capitalize the products residual value, they should return them as early as possible. Accordingly, we develop a model of Closed-loop Supply Chain (CLSC) where consumers seek to gain as much as possible from their returns and the return rate is a function of both price and quality. We model a two-period Stackelberg game to capture the dynamic aspects of a CLSC, where the manufacturer is the channel leader. We investigate who, namely, manufacturer or retailer, should collect the products in the market. Thus, we identify the best CLSC structure to adopt when the return rate is both price-and quality-dependent. Our results demonstrate that it is always worthwhile for companies to collect products and adopt an active return approach for returns. We investigate the eect of retail competition in both forward and backward channels and show the impact of eliminating the double marginalization on market outcomes.
The performance of many of the technologies used in physical protection systems that guard high-value assets are heavily influenced by weather and visibility conditions as well as intruder capabilities. This complicates the already difficult problem of optimizing the design of multi-layered physical protection systems. This paper develops an optimization model for the automatic design of these systems with explicit consideration of the impact of weather and visibility conditions as well as intruder capabilities on system performance. An illustrative case study is provided.
Within a Closed-loop Supply Chain (CLSC) framework we study several consumer return behaviors for the used products which are based on the product prices and rebates. Consumers evaluate the rebate they receive as well as the price of the new product before deciding whether to dump a return. Therefore, the number of used products returned is examined under two types of rebates: a …xed rebate and a variable rebate. We search for the optimal rebate mechanism and …nd that the CLSC pro…ts are higher under an variable rebate policy. This …nding justi…es the industry practices that employ a rebate mechanism based on both the value and the price of used item. We o¤er two types of solution concepts to the CLSC games: open-loop Stackelberg solution and Markov perfect Stackelberg solution, which are commonly employed in the dynamic games literature. While we mainly employ Markovian equilibrium, we also allow …rms to utilize open-loop strategies so as to assess the impact of precommitment on the market outcomes. Therefore, we o¤er a comprehensive analysis of all possible market equilibrium solutions under di¤erent strategic considerations and the commitment deliberations. We show that under the …xed rebate regime open-loop solution coincides with Markov perfect solution. Furthermore, we show how consumer return behavior impacts the dynamic nature of the game. We …nd that the time frame is irrelevant if …rms o¤er a …xed rebate. In contrast, the game will be fully dynamic when …rms o¤er a variable rebate.
Abstract. The concept of a supply function equilibrium (SFE) has been widely used to model generators' bidding behavior and market power issues in wholesale electricity markets. Observers of electricity markets have noted how generation capacity constraints may contribute to market power of generation firms. If a generation firm's rivals are capacity constrained then the firm may be pivotal; that is, the firm could substantially raise the market price by unilaterally withholding output. However the SFE literature has not properly analyzed the impact of capacity constraints nor has it considered the impact of pivotal firms on equilibrium predictions. We characterize the set of symmetric supply function equilibria when firms are capacity constrained and show that this set is increasing as capacity per firm rises. We also provide conditions under which asymmetric equilibria exist and characterize these equilibria.
Abstract. The concept of a supply function equilibrium (SFE) has been widely used to model generators' bidding behavior and market power issues in wholesale electricity markets. Observers of electricity markets have noted how generation capacity constraints may contribute to market power of generation firms. If a generation firm's rivals are capacity constrained then the firm may be pivotal; that is, the firm could substantially raise the market price by unilaterally withholding output. However the SFE literature has not properly analyzed the impact of capacity constraints and pivotal firms on equilibrium predictions. We characterize the set of symmetric supply function equilibria for uniform price auctions when firms are capacity constrained and show that this set is increasing as capacity per firm rises. We provide conditions under which asymmetric equilibria exist and characterize these equilibria. In addition, we compare results for uniform price auctions to those for discriminatory auctions, and we compare our SFE predictions to equilibrium predictions of models in which bidders are constrained to bid on discrete units of output.
This paper studies several stochastic programming formulations of dynamic oligopolistic games under uncertainty. We argue that one of the models, namely games with probabilistic scenarios (GPS), provides an appropriate formulation. For such games, we show that symmetric players earn greater expected profits as demand volatility increases. This result suggests that even in an increasingly volatile market, players may have an incentive to participate in the market. The key to our approach is the so-called scenario formulation of stochastic programming. In addition to several modeling insights, we also discuss the application of GPS to the electricity market in Ontario, Canada. The examples presented in this paper illustrate that this approach can address dynamic games that are clearly out of reach for dynamic programming, a common approach in the literature on dynamic games. r
This paper studies the impact of some innovation-led lean programs in a Closed-loop Supply Chain (CLSC) setting. We use a game-theoretic approach to model a CLSC composed of one supplier and one manufacturer. The supplier sets the wholesale price of an intermediate product while the manufacturer sets the selling price of a nal product. Further, the manufacturer invests in innovation-led lean practices to entail both a strategic eect and a process innovation eect. The strategic eect consists of responsiveness involving the CLSC's capacity to properly respond to consumers' needs and leading to increase in sales. Further, the strategic eect enhances sustainability as consumers align their behavior to the CLSC's attitude of reducing the waste through lean, thus using their products for longer time period and entirely exhausting their residual value. Innovation-led lean practices also generate a process innovation eect, which consists of the marginal production cost abatement. Our ndings indicate that lean practices leading to both strategic and process innovation are protable for the manufacturer and sponsor sustainability. When only one of those can be presented, CLSCs should prefer the adoption of a strategic lean program. From its side, the supplier is much less sensitive to environmental benets, thus it focuses on sales and operational matters. Furthermore, in a centralized CLSC, the preferences for strategic vs. process innovation lean follow the same path of the decentralized CLSC. Nevertheless, we pinpoint that the manufacturer in the decentralized CLSC has a larger incentive to adopt a strategic lean program than in the centralized CLSC. Also, the supplier always obtains larger economic benets in the decentralized CLSC under any type of innovation-led lean program.
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