Tesis doctorales de Economía


EVOLUÇÃO E PERSPECTIVAS DO COMÉRCIO INTERNACIONAL DE AÇÚCAR E ÁLCOOL

Eduardo Fernandes Pestana Moreira




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Anexo II. Mactor Report

Atores Açúcar e Álcool

ACTOR PRESENTATION

• LIST OF ACTORS

1. Organização Mundial do Comércio (OMC)

2. Governo dos USA (USA)

3. Governo da União Européia (UE)

4. Grupo dos Países em Desenvolvimento (G-20)

5. Países da Ásia, Pacífico e Caribe (ACP)

6. Governo da China (China)

7. Governo da Índia (India)

8. Organizações Ambientalistas Internacionais (ONG-I)

9. Indústria Automobilística Mundial (AUTO)

10. Mercosul (Msul)

11. Organização dos Países Produtores de Petróleo (OPEP)

12. Governo da Rússia (Rússia)

13. União da Agroindústria Canavieira (UNICA)

14. Governo do Brasil (BRASIL)

15. Grupos Estrangeiros com Negócios no Brasil (IDE)

16. Governo do Japão (JAPÃO)

• OBJECTIVE PRESENTATION

• LIST OF OBJECTIVES

1. Reduzir Subsídios (REDSUBSID)

2. Segurança Energética (SEGENERGIA)

3. Proteção à Produção Interna (PROTPROD)

4. Preferências Tarifárias (PREFTARIF)

5. Redução da Poluição Atmosférica (POLUIÇAOAR)

6. Proteção das Florestas (FLORESTA)

7. Sustentar Preços do Petróleo (PREÇOPETRO)

8. Sustentar Preços do Açúcar (PREÇOAÇUC)

9. Reduzir Barreiras ao Comércio Bens Agrícolas (LIBAGRI)

10. Liberalizar Fluxo de Capitais (LIBCAP)

• DATA INPUT MATRICES

• MATRIX OF DIRECT INFLUENCES (MDI)

The Matrix of Direct Influences (MDI) Actor X Actor created from the actors' strategies table, describes the direct influences actors have on each other.

Influences are graded from 0 to 4 according to the importance of the actor's possible jeopardy:

0: No influence

1: Operating procedures

2: Projects

3: Missions

4: Existance

• VALUED POSITION MATRIX (2MAO)

The matrix of valued positions Actor X Objective (2MAO) provides information on the actor's stance on each objective (pro, against, neutral or indifferent) and the hierarchy of its objectives.

The sign indicates whether the actor is likely to reach objective or not.

0: Objecive has a bleak outcome

1: Objective jeopardises the actor's operating procedures (management, etc...) / is vital for its operating procedures

2: Objective jeopardises the success of the actor's projects / is vital for the success of its projects

3: Objective jeopardises the accomplishment of the actor's mission / is indispensible for its missions

4: Objective jeopardises the actor's existence / is indispensible for its existence

• RESULTS OF THE STUDY

• DIRECT AND INDIRECT INFLUENCES

• Matrix of Direct and Indirect Influences (MDII)

The MDII matrix determines the direct or indirect influences of order 2 between actors. The utility of this matrix is its more complete vision of the games of competitiveness (an actor can reduce the number of choices of another by influencing it through an intermediary actor). The "sum" operation used to calculate the MDII does not produce (in this new matrix) the same scale of intensities adopted to evaluate direct influences in MDI. Despite this, values in MDII are a good indicator of the importance of direct and indirect influences actors have on each other. Two indicators are calculated from the MDII:

- The degree of direct and indirect influence of each actor (Ii, by summing rows).

- The degree of direct and indirect dependence of each actor (Di, by summing columns).

Values represent direct and indirect influences between actors:

The higher the value, the more influence the actor has on the other.

• Map of influences and dependences between actors

Map of influence and dependence between actors is a graphic representation of actors' positions with respect to influences and dependences (direct or indirect: Di and Ii) between each other. Positions are calculated automatically by the Mactor software.

• Net scale of influences (NS)

The net scale of direct and indirect influences measures, for every couple of actors, the distance between the direct and indirect influence. Each actor exerts (receives) direct and indirect influences of order 2 (from) each actor. The net influence scale will indicate for each couple of actors the surplus influence either exerted or received. If the scale is positive (+ sign), actor i (rows of NS matrix) has more direct and indirect influence on actor j (columns of NS matrix) than it receives from this actor. This is the opposite when the scale has a negative ( - ) sign. The next step is to calculate for each actor the total difference of direct and indirect influences by adding up the net influence scales on the rest of the actors.

Values are relative whole numbers:

The (+) sign indicates the actor exerts more influence than it receives.

The (-) sign indicates the actor exerts less influence than it receives.

• MDII competitiveness

MDII competitiveness vector

The Matrix of Direct an Indirect Influences (MDII) provides two types of useful information:

- The direct and indirect influences actor i has on actor j (MDII)ij where i!=j and are equivalent, by definition, to the direct and indirect dependence actor j has with respect to actor i.

- The indirect influences actor i has on itself coming through an intermediary actor. This is called retroaction (MDII)ii. When an actor is more competitive so will be its influence, but its dependence and retroaction will be quite weak. It is foolish to think that only the actor's influence measures its competitiveness. An actor can be very influential, be also very dependent and at the same time be very retroactive: this would result in a weak competitiveness. However, an actor being moderately influential, and having no dependence or retroaction will be very competitive.

Ri* is the competitiveness of actor i considering its max: influences; direct and indirect dependence; and feedback.

Histogram of MDII's competitiveness

The MDII competitiveness histogram is created from the MDII competitiveness vector.

• ACTORS OBJECTIVES RELATIONSHIP

• Order 1 relationship

Simple position matrix (1MAO)

The simple position 1MAO matrix shows the valency of each actor with respect to every objective (likely, unlikely, neutral, or indifferent). This matrix, result of Mactor's phase 3, is not made up of the initial data entries. Mactor recalculates it from 2MAO.

-1: actor unlikely to achieve objective

0: Neutral position

1: actor likely to achieve objective

• Order 2 relationship

n) Valued position matrix (2MAO)

The 2MAO matrix specifies the actor's position on each objective (pro, against, neutral or indifferent). This matrix is the initial information given by the user and also presents marginalities.

The sign indicates whether the actor is likely to reach objective or not.

0: Objecive has a bleak outcome

1: Objective jeopardises the actor's operating procedures (management, etc...) / is vital for its operating procedures

2: Objective jeopardises the success of the actor's projects / is vital for the success of its projects

3: Objective jeopardises the accomplishment of the actor's mission / is indispensible for its missions

4: Objective jeopardises the actor's existence / is indispensible for its existence

Histogram of actor's implication towards its objectives 2MAO

This histogram is produced from the valued relationship matrix (order 2) between actors and objectives, 2MAO. It represents the actor's objectives mobilisation. The histogram is used to identify for each actor, the extent of its position with respect to the defined objectives, e.g. pro or against.

• Order 3 relationship

Weighted valued position matrix (3MAO)

The weighted (with respect to competitiveness) valued position matrix (3MAO) describes each actor's position on every objective. This is taking into account its degree of opinion on every objective, its objective hierarchy and competitiveness between actors.

Positive values represent the actor's mobilisation towards its objectives.

Negative values represent the rate of opposition.

Histogram of actor's mobilisation towards its objectives 3MAO

This histogram is produced from the valued relationship matrix (order 3) between actors and objectives, 3MAO. It represents the actions taken by actors towards objectives. The histogram is used to identify for each actor, the extent of its position with respect to the defined objectives, e.g. pro or against.

Weighted valued position matrix (3MAO)

Positive values represent the actor's mobilisation towards its objectives.

Negative values represent the rate of opposition.

• CONVERGENCE BETWEEN ACTORS

• Order 1 convergence

Convergence matrix (1CAA)

The Matrix of objectives convergences between actors or simple Convergences Actor X Actor (1CAA) identifies for a couple of actors the number of common positions they have on objectives (pro or against). This would identify the number of possible alliances. "Neutral" and "indifferent" positions (coded as "0") are not taken into consideration. This is a symmetrical matrix.

The values represent the degree of convergence: the higher the intesity, the more actors have common interests

• Order 2 convergence

Valued convergence matrix (2CAA)

The valued convergence matrix or Valued Convergence Actors X Actors (2CAA) is related to the Matrix of valued positions Actors X Objectives (2MAO). This calculates the average convergence intensity between two actors, when these have the same degree (pro or against the objective). The values in this matrix do not measure the number of potential alliances (as in 1CAA), but the alliance intensity with the objectives hierarchy (preferences) of the couple of actors. This is a symmetrical matrix.

The values represent the degree of convergence: the higher the intesity, the more actors have common interests

• Order 3 convergence

Weighted valued convergence matrix (3CAA)

The weighted valued matrix of convergences or weighted valued Convergences Actors X Actors (3CAA) is related to the weighted valued position matrix Actors X Objectives (3MAO). It identifies for a couple of actors the number of common positions they have on objectives (pro or against). This would identify the number of possible alliances also taking into account the actors' preferences in terms of objectives and their competitiveness. This is a symmetrical matrix.

The values represent the degree of convergence: the higher the intesity, the more actors have common interests

• DIVERGENCE BETWEEN ACTORS

• Order 1 divergence

Divergence matrix (1DAA)

The Matrix of divergences of objectives between actor or simple Divergences Actors X Actors (1DAA) identifies for each couple of actors the number of objectives on which these actors do not hold the same position (one actor is pre the objective and the other is against it). In other words it describes the number of potential conflicts. "Neutral" and "indifferent" positions (with code "0") are not taken into consideration. This is a symmetrical matrix.

The values represent the degree of divergence: the higher the intesity, the more actors have diverging interests

• Order 2 divergence

Valued divergence matrix (2DAA)

The Matrix of valued divergences or valued Divergences Actors X Actors (2DAA) is related to the Matrix of valued positions Actors X Objectives (2MAO). It identifies for each couple of actors the number of objectives for which these actors do not hold the same position (one actor is pro the objective and the other is against it). The values in this matrix do not measure the number of potential conflicts (as in 1DAA), but rather the conflict intensity with the objectives hierarchy (preferences) of the couple of actors. This is a symmetrical matrix.

The values represent the degree of divergence: the higher the intesity, the more actors have diverging interests

• Order 3 Divergence

Weighted valued divergence matrix (3DAA)

The weighted valued matrix of divergences or weighted valued Divergences Actors X Actors (3DAA) is related to the weighted valued position matrix Actors X Objectives (3MAO). It identifies for each couple the average divergence intensity for those two actors who do not hold the same position (one actor is pro the objective and the other is against it). The values of this Matrix measure the conflict intensity with, for every couple, their objectives hierarchies (preferences) and their competitiveness. This is a symmetrical matrix.

The values represent the degree of divergence: the higher the intesity, the more actors have diverging interests

• ACTOR AMBIVALENCE

• Actor's ambivalence matrix

Two actors can share both converging and diverging positions on different objectives. Hence, we call this couple of actors ambivalent. If they wish to become allies, they have to work only on those common objectives, and put aside their diverging objectives. Actor ambivalence is calculated with three equilibrium indicators using their simple, valued, then valued and weighted positions.

This indicator varies from 1 (very ambivalent actors) to 0 (not ambivalent actors).

• Histogram of actor's ambivalence

This histogram is produced from the actor ambivalence vector.

• NET DISTANCE BETWEEN OBJECTIVES

• Map of net distances between objectives

This map is used to identify objectives on which actors take the same position (either pro or against). It hence enables to isolate groups of objectives where there is a strong convergence (when objectives are close together) or divergence (when objectives are far apart) on the part of actors' opinion. It also maps objectives with respect to the net scale (the difference between the valued convergence matrix and the valued divergence matrix, respectively 2COO and 2DOO).

• NET DISTANCES BETWEEN ACTORS

• Map of net distances between actors

The map of net distances between actors is used to recognise potential alliances while taking into account divergences and convergences between actors of order 2.


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