This chapter shows how to make an enterprise diagnosis and how, with the right tools, a better management of dynamic knowledge can be established. The chapter begins by examining the Logistic Model Based on Positions (LoMoBaP) and using the position of Customer Services Manager to perform an enterprise diagnosis. The results of this are then expressed through a Matrixes Of Weighing (MOW). The general objective of the chapter is to show how by making the diagnosis of a company through the Customer Services Manager, which is one of the positions of the Logistic Model Based on Positions, and expressing this diagnosis through Matrixes Of Weighing, a dynamic knowledge base that will allow the company an efficient knowledge management, specifically for the most important management aspects, is generated.
The main contribution of this chapter is the study of the generation and management knowledge, emphasizing the social aspects, from an area of the Logistic Model Based on Positions (LoMoBaP). The area to use is the Inverse logistics, which is integrated for the Reverse logistics manager, the Compilation and Reception manager and the Classification and use manager. The analysis will be done via dynamic knowledge, studying the upward spiral of knowledge creation, tacit to explicit to tacit. To do this will be constructed tables where the functions of these three positions will be identified and will be discussed, as these functions are involved in the process of management and generation of knowledge, following the processes of Socialization, Externalization, Combination and Internalization, simultaneously that are located in the Ba and knowledge assets are analyzed: Experimental, Conceptual Systemic and Routine Knowledge.
Immediately after the catastrophes that affected Venezuela at the end of 1999, especially the flood of the State of Vargas, a group of investigators of a consultancy company and of a private university of Caracas Venezuela, started working in decisions support systems (DSS) that could be useful in the moment of a catastrophe, helping to minimize the impact of its three principal stages: Pre-catastrophe, Impact and Post-catastrophe. Clearly, for the development of these DSS, it was indispensable to construct mathematical models to support them. The objective of this chapter is to disclose this experience by presenting some of these mathematical models and its conversion in DSS that supports decision making in the case of catastrophes.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.