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This chapter covers three main concepts: it provides an overview of supply chain management (SCM), introduces the concepts of procurement and what is entailed within this function, and explains how inventory is managed. In the first section, SCM is considered broadly but also in the context of hospitality. The key roles and objectives of SCM as well as the significance of supply chain risk and disruption are considered. In the second section, the concept of sourcing is discussed. Sourcing is a critical function in any organization: without this, an organization would cease to operate. The importance of supplier selection is explored, with methods to make the most appropriate selection and for subsequently managing suppliers. Finally, the third section focuses on how inventory management can be optimized. Concepts such as economic order quantity (EOQ) and ABC analysis are explored, along with alternatives to traditional inventory management methods.

This chapter discusses a collaborative strategy for noncompetitive small- and medium-sized enterprises (SME's) aiming to reduce their logistics costs by means of a joint replenishment of multiple items. The proposed approach is an extension of the classical joint replenishment problem, named as a Stochastic Collaborative Joint Replenishment problem (S-CJRP) because it considers stochastic demand, warehouse and transport capacity constraints, and multiple buyers and vendors. Operating this method implies three main challenges: (1) determining the frequency with which each buyer should replenish the products; (2) allocating investments and benefits between partnering buyers; and (3) deciding whether to coordinate the supply chain internally or outsource its coordination. The S-CJRP is solved through a heuristic approach, which deals with uses of the Shapley Value Function to allocate the investments and benefits, and it explores the coordination through several simulation scenarios, all of which exhibit prospective cost reductions in inventory management. Preliminary results show that third-party logistics providers could be a valuable resource in coordinating SMEs along a supply chain.

The purpose of this chapter is to develop a new perspective model of well-balanced information economy.

The methodological tools of this work are based on application of the method of comparative analysis for comparing the old and the new model of information economy, modeling of socio-economic systems, simplex-method as an algorithm for solving the optimization task of linear programming, related to improvement of the conceptual model of information economy, and the method of formalization for graphical presentation of a new model of information economy.

The developed and presented author’s perspective model of information economy envisages balancing in four main directions: infrastructural possibilities and readiness for their practical usage by society and business; state regulation and market self-management; existing and new information; and external information exchange. Despite the clarity and strictness of conceptual settings, the new model is peculiar for increased flexibility and adaptation to the peculiarities of the socio-economic practice of economic system. Thus, the new model of well-balanced information economy allows overcoming all drawbacks – logical mismatches and contradictions – of the existing (old) model of information economy.

Due to optimization of the conceptual model, its practical implementation in economic activities of modern socio-economic systems becomes possible – as a result of which, with accumulation of experience, it will be possible to assess true value of the idea of information economy’s formation for humanity and the global economic system.

In this chapter, inventory and sales data from a small business with seven showrooms are evaluated to forecast future sales and maximize total profits. In each showroom, three major brands of ceiling fans are sold and a limited amount of products from each brand are displayed. Each showroom varies in their sales volume, display capacity, and profit margins. Using historical data, the optimal display configuration was determined for each showroom; that is, the proportion of products from each brand to display in the limited display grid, while acknowledging existing constraints. Next using the optimal displays, profit for the next year is forecasted. Finally a comparison is made between actual and forecasted results and profits pre and post the optimal product display.