Inventories Control, State Regulations, and the Amplitude Model (TAM)

Inventories Control, State Regulations, and the Amplitude Model (TAM)

José G. Hernández R. (Minimax Consultores C.A., Venezuela), María J. García G. (Minimax Consultores C.A., Venezuela) and Gilberto J. Hernández G. (Minimax Consultores C.A., Venezuela)
DOI: 10.4018/978-1-5225-3232-3.ch023
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The contribution of this chapter is to relate the control of inventories and the regulations that on it the state can exercise, with the decision making under uncertainty, represented by The Amplitude Model (TAM) and making use of the area Inventory of the Logistic Model Based on Positions (MoLoBaC). Inventory control is one of the fundamental tasks of business logistics and the company as a whole. But there are situations where this inventory control is affected by state regulations. It wants to analyze this delicate situation from the perspective of the models of decision making under uncertainty, in particular TAM. From the all above the general objective of this paper emerges: Make use of the Inventories area, of the Logistics Model Based on Positions and with The Amplitude Model, to analyze the possible actions to take, to confront the consequences of the restrictions imposed by the state, which affect the inventory control.
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The presence and management of inventories in the industrial field can be seen from different perspectives, starting from the information that can be shared along the supply chain (Du et al., 2012) to the environmental effect and costs of carbon emissions (Hovelaque & Bironneau, 2015) and even incorporating, in addition to environmental aspects, the quality (Kazemi et al., 2016) and passing by the bullwhip effect (Nagashima et al., 2015) and the analysis of multiple levels in the supply chain (Salas et al., 2016). Or by the effect of the four seasons (Hudnurkar, Jakhar & Rathod, 2014) and the deterioration of the products (Khedlekar, Shukla & Namdeo, 2016; Sana, Panda & Modak, 2015), by the impact of the restrictions of the carbon footprint in the inventory management (Tao, Fan & Lai, 2016), by the time of lead time and a better customer service (Glock, 2012; Sarkar & Moon, 2014) and even considering aspects, such as the delay in payments (Aljazzar, Jaber & Goyal, 2016; Banu & Mondal, 2016).

This great relevance of the inventories makes that there are many works that study the importance of the inventory control (Cárdenas-Barrón, Cheng & Treviño-Garza, 2014; García et al., 2017; Schwarz et al., 2016). These first authors focus their study on the model of Economic Order Quantity (EOQ) of which model has derived another great amount of works (De & Mahata, 2016; De & Sana, 2015; Kazemi, Olugu et al., 2016; Mishra, 2016; Shekarian et al., 2016). And even some of them on approaches to those previously mentioned, such as carbon emissions (Qin, Bai & Xia, 2015; Yang et al., 2016).

For their part García et al. (2017) and Schwarz et al. (2016) have focused, as well as Tao, Fan & Lai (2016) in aspects that have to do with restrictions on the control of inventories, but in their case when restrictions are imposed by the state.

The subject of the intervention of the state is of old data, as they comment García et al. (2017) and although it is a central theme in economics studies (Aguilera et al., 2011; Clift, 2012; Voss & Williams, 2012) and the marketing studies (Timm, 2014) it has also been studied from other points of view, such as sociology (Liow, 2012) and the socio-economic vision (Fine, 2016).

Key Terms in this Chapter

MoLoBaC Inventories Area: In the Logistical Model Based on Positions (LoMoBaP [MoLoBaC]) is one of the two areas of the stage Production. In the Inventories area are grouped three positions, the Inventory Model manager, the Spare and Equipment manager and the General Inventory manager, or simply Inventory manager, who is the supervisor of the previous two.

Inventory Control: One of the most relevant and delicate tasks of logistics. It is related to all the components that are needed in the production process, whether they are a direct part of the final product or are necessary for the proper operability of the organization. Through the control of inventories, it must be ensured that each of these components must be available at the time and in the quantities required, so that production does not stop.

Logistics Models: Those created, explicitly or accidentally, to justify and understand business logistics. In particular for this chapter is of interest four qualitative-quantitative models created to explain the logistics: Logistics of Supply, Production, Distribution and Inverse (LSPDI [LAPDI]); Logistics Model Based on Positions (LoMoBaP [MoLoBaC]); Logistics, Strategic, Tactical, Operational with Inverse Logistics Model (STOILMo [MoLETOI]) & Logistics Model Based on Indicators for Positions (LoMoBaIPo [MoLoBaICa]).

Enterprise Logistics: Centered in searching and achieving a greater satisfaction, present and future of the final costumer, and includes socio-environmental and ethical-legal aspects, organization planning, execution and control of all related activities related to the attainment, flow, gathering and maintenance of materials, products and services, since the raw material source, including there the costumers through inverse logistics, to the sale point of the finished product local or international, massive or enterprise, in a more effective and efficient, maximizing performance and the expected quality, minimizing waste, times and costs and using modern information technologies.

Logistics Model Based on Positions (MoLoBaC): Studies enterprise logistic through the functions relative to the positions. It is shaped by forty four positions which are grouped in twelve areas that meet in six stages.

Amplitude Model: A new model to be applied in decision making under uncertainty, in its beginnings was created to reinforce two of the traditional methods most used: Hurwicz and Laplace, but, because of its applicability, it took on a life of its own. The main characteristic that distinguishes it from traditional models is that it takes into account the dispersion of data. This does it through the amplitude, hence its name.

Negative State Intervention: In economics there are abundant studies of the intervention of the state in the economy of the nations. In some cases these interventions are positive and contribute to the aggrandizement of nations. However, on many occasions, deep interventions by the state, which directly affects the operability of companies, become disastrous interventions of the state. In general these harmful interventions of the state, not only affect the companies, but they end up affecting the society as a whole. And in most cases they produce an opposite effect to the desired one, deepening, thus, the problem that was intended to solve.

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