Dynamic Pricing and Inventory Management Under Fluctuating Procurement Costs
Dynamic Pricing and Inventory Management Under Fluctuating Procurement Costs

Author: Guang Xiao

Publisher:

Published: 2015

Total Pages: 38

ISBN-13:

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We consider a periodic review joint pricing and inventory control model in which a firm faces both stochastic demand and fluctuating procurement costs. To address procurement cost fluctuation, the firm adopts a dual-sourcing strategy, under which it procures from a spot market with immediate delivery and through a forward-buying contract with postponed delivery. Our analysis offers the unique insight that a risk-neutral firm may earn higher expected profit under a more volatile procurement cost process. This is because the firm makes its pricing and sourcing decisions in response to the realized cost in each period. Moreover, we characterize how the firm should dynamically adjust its pricing and sourcing decisions in accordance to cost evolution. For example, if sourcing through the forward-buying contract is less expensive than sourcing directly from the spot market, the optimal safety stock is decreasing in the current spot market purchasing cost. However, the optimal order quantity through the forward-buying contract is, in general, not monotone in the current spot-purchasing cost. Finally, we conduct extensive numerical experiments to show that dynamic pricing and dual-sourcing may be either strategic complements or substitutes in the presence of fluctuating procurement costs and uncertain demand. This is because dynamic pricing mitigates demand uncertainty risk and exploits procurement cost fluctuation, while dual-sourcing may either intensify or dampen demand risk.

Purchasing Raw Material in a Fluctuating Market
Purchasing Raw Material in a Fluctuating Market

Author: Jose Trevino

Publisher:

Published: 1964

Total Pages: 110

ISBN-13:

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A class of situations is considered where the usual techniques of operations research do not indicate the possibility of reducing to a common unit all the operating characteristics of a system caused by some decision and thus defining a criterion function. A special example of this class is furnished by the management of raw materials inventory in the face of fluctuation prices in the raw material market. Statistically reliable explanatory models of the random behavior of price are constructed, and decision rules are defined as transformation of appropriately chosen state variables. Some functionals of the random outcomes of decisions are computed as functions of the undetermined parameters open in the decision rule. Trade-offs between such functionals or system characteristics are analyzed with a view to obtain a basis for the selection of 'good' values of the parameters. Theoretical results are compared against simulated systems using actual series as inputs. (Author).

Optimization and Inventory Management
Optimization and Inventory Management

Author: Nita H. Shah

Publisher: Springer Nature

Published: 2019-08-31

Total Pages: 470

ISBN-13: 9811396981

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This book discusses inventory models for determining optimal ordering policies using various optimization techniques, genetic algorithms, and data mining concepts. It also provides sensitivity analyses for the models’ robustness. It presents a collection of mathematical models that deal with real industry scenarios. All mathematical model solutions are provided with the help of various optimization techniques to determine optimal ordering policy. The book offers a range of perspectives on the implementation of optimization techniques, inflation, trade credit financing, fuzzy systems, human error, learning in production, inspection, green supply chains, closed supply chains, reworks, game theory approaches, genetic algorithms, and data mining, as well as research on big data applications for inventory management and control. Starting from deterministic inventory models, the book moves towards advanced inventory models. The content is divided into eight major sections: inventory control and management – inventory models with trade credit financing for imperfect quality items; environmental impact on ordering policies; impact of learning on the supply chain models; EOQ models considering warehousing; optimal ordering policies with data mining and PSO techniques; supply chain models in fuzzy environments; optimal production models for multi-items and multi-retailers; and a marketing model to understand buying behaviour. Given its scope, the book offers a valuable resource for practitioners, instructors, students and researchers alike. It also offers essential insights to help retailers/managers improve business functions and make more accurate and realistic decisions.

Comparative Statics Analysis of Inventory Management Model with Dynamic Pricing, Market Environment Fluctuation, and Delayed Differentiation
Comparative Statics Analysis of Inventory Management Model with Dynamic Pricing, Market Environment Fluctuation, and Delayed Differentiation

Author: Nan Yang

Publisher:

Published: 2021

Total Pages: 0

ISBN-13:

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We consider a general joint pricing and inventory management model with delayed differentiation, in which a firm serves a market with multiple products made from a generic one. The firm holds inventory for the generic product which is produced using multiple resources. Moreover, the market size, the attractiveness of each product, the firm productivity, and the procurement cost of each resource all evolve over the planning horizon driven by an exogenous Markov process. Comparative statics analysis is essential for studying this model, offering insights on the impact of market environment fluctuation upon the firm's optimal pricing and inventory policy. Hence, we propose a new approach that combines the advantages of implicit function theorem (IFT) and monotone comparative statics (MCS) approaches to perform comparative statics analysis in our joint pricing and inventory management model under market environment fluctuation. The new approach applies to our model where the standard IFT and MCS methods are not easily amenable. Using our new comparative statics approach, we characterize the optimal pricing and production policy of the firm, and offer insights on how the firm should adaptively respond to market environment fluctuations.