Thesis-2009-Gennari.pdf (16.19 MB)
A general system planning methodology - G.S.P.M. - applied to national airport system planning - N.A.S.P. - in middle income and economically active countries - M.I.E.A.C.
thesisposted on 2015-02-11, 15:52 authored by Henrique S. Gennari
A General System Planning Methodology (G.S.P.M.) has been proposed in this dissertation with the objective to promote planning practices improvements regardless to the characteristics of the planning context and to the nature of the planning field where it may be applied. The G.S.P.M. is a normative planning methodology based on procedural theory of planning, and it is addressed mainly to the multi-disciplinary planning actors dealing with the multi-objective planning context. The G.S.P.M. has been given a "procedural framework" supported by two Axiomatic Theories, and three objectives of planning have been selected to express simultaneously the G.S.P.M. effectiveness and the aimed Planning Improvement, and they are; Planning Adequacy, Planning Flexibility and Planning Continuity. The National Airport System Planning (N.A.S.P.) has been selected to be the planning field test for the G.S.P.M. and two different planning contexts have been selected to be respectively, the investigation field and the application field for the G.S.P.M. test. A sample of five developed countries have been chosen to represent the investigation field as follows; Norway, U.S.A., United Kingdom, Federal Republic of Germany, and Canada. A sample of four Middle Income and Economically Active Countries(M.I.E.A.C.) have been chosen as the application field, and Brazil has been selected the prime country with three further Brazilian Scenarios designed with the help of Developmental Scenarios Writing to represent that sample. A Multiple Cross System Analysis Matrix(M.C.S.A.M.) has been designed to be an instrument for the G.S.P.M. operational process within the application test in the N.A.S.P. of the two sample of countries. The M.C.S.A.M. is a bidimensional assessment matrix supported by planning theories and operated by multi-disciplinary planning actors to select the preferred aspects of planning which have been used to identify the characteristics of the planning context and planning environment. The M.C.S.A.M. has been designed to select also the preferred planning factors and goals which may represent the potentially most effective planning factors and goals within the given planning context. A Developed Countries Realist N.A.S.P. Methodology Model has been identified within the investigation field which would express the common N.A.S.P. framework within the developed countries, representing the "emphatical understanding" from which we supposed to learn their planning practices. A M.I.E.A.C. N.A.S.P. Realist Methodology Model has been identified within the application field which would express the common N.A.S.P. framework within the M.I.E.A. Countries. This realist model which has been obtained from the Brazilian Scenarios has been also called the Brazilian Planned Scenario N.A.S.P. which is supposed to be the ideal planning context hypothetically designed to improve the actual Brazilian N.A.S.P. practices, as a planning exercise of "predictable understanding". The comparative analyses of the two N.A.S.P. Realist Methodology Models has defined a Tailoring Process of Planning where the adequate planning method can be identified with the appropriate level of technology to the identified planning context.
- Aeronautical, Automotive, Chemical and Materials Engineering
- Aeronautical and Automotive Engineering
Publisher© Henrique Salles Gennari
Publisher statementThis work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/
NotesA Doctoral Thesis. Submitted in partial fulfilment of the requirements for the award of Doctor of Philosophy of Loughborough University.
EThOS Persistent IDuk.bl.ethos.328833