# Formalizing a Two-Step Decision-Making Process in Land Use: Evidence from Controlling Forest Clearcutting Using Spatial Information

^{1}

^{2}

^{3}

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## Abstract

**:**

## 1. Introduction

#### 1.1. Literature Overview

#### 1.1.1. Standard Decision-Making Methods

#### 1.1.2. Blackwell Contribution to Decision Making

#### 1.1.3. Entropy Analysis under Uncertainty

#### 1.2. Article Objective

= Optimal expected profit under additional information − Optimal initial expected profit

#### 1.3. Why Choosing a Forest Clear-Cut Control

- i.
- Find the most powerful information structures.
- ii.
- Determine the optimal action in terms of payoffs.

#### 1.4. Article Outline

## 2. Materials and Methods

#### 2.1. Theoretical Model

#### 2.1.1. Blackwell Approach

**Theorem**

**1.**

**Remark**

**1.**

#### 2.1.2. Entropy Approach

**Definition**

**1.**

**Definition**

**2.**

#### 2.2. Case Study

#### 2.2.1. Data Collection and Analysis

#### 2.2.2. Case Description

## 3. Results

#### 3.1. Entropy Results

#### 3.2. Blackwell Results

**Remark**

**2.**

## 4. Discussion

**Step****1.**- The choice of the two most powerful information structures, based on level one results. Once the information structure is ranked according to their informative input, the decision maker may eliminate the other possible alternatives, hence making the decision process easier.
**Step****2.**- The assessment of the information power: the two structures should be assigned with their informative power in the sense of Blackwell.
**Step****3.**- The computation of the optimal action: the action with the maximum expected payoff.

## 5. Conclusions

## Author Contributions

## Funding

## Informed Consent Statement

## Conflicts of Interest

## References

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Date (2019) | Region (France) | Number of People Interviewed |
---|---|---|

May | Occitanie/Nouvelle Aquitaine | 26 |

June | Île de France/Centre Val de Loire | 17 |

July | Pays de la Loire/Bretagne–Normandie | 25 |

September | Hauts de France/Grand Est | 22 |

October | Bourgogne–Franche–Compté | 12 |

November | Auvergne–Rhône–Alpes/Provence–Alpes Côte d’Azur | 14 |

Factors | Amount per Unit |
---|---|

Fuel | 0.17 EUR/km |

Technician salary | 2700 EUR/month i.e., 150 EUR/day |

Engineer salary | 4750 EUR/month i.e., 250 EUR/day |

Average number of working days | 19 days/month |

Fine due to ${s}_{3}$ | 4000 EUR |

Fine due to ${s}_{4}$ | 160,000 EUR |

Number of Days/Engineer | Number of Days/Technician | Average Distance (km) | Fine (€) | |
---|---|---|---|---|

$\left({a}_{1},{s}_{1}\right)$ | 0.5 | 0 | 150 | 0 |

$\left({a}_{1},{s}_{2}\right)$ | 1 | 0 | 150 | 0 |

$\left({a}_{1},{s}_{3}\right)$ | 15 | 15 | 300 | 4000 |

$\left({a}_{1},{s}_{4}\right)$ | 15 | 15 | 300 | 160,000 |

${\mathit{s}}_{1}$ | ${\mathit{s}}_{2}$ | ${\mathit{s}}_{3}$ | ${\mathit{s}}_{4}$ | |
---|---|---|---|---|

${a}_{1}$ | $-150.5$ | $-275.5$ | $2051$ | $\mathrm{153,949}$ |

${a}_{2}$ | $0$ | $0$ | $0$ | $0$ |

${\mathit{s}}_{1}$ | ${\mathit{s}}_{2}$ | ${\mathit{s}}_{3}$ | ${\mathit{s}}_{4}$ | |
---|---|---|---|---|

${b}_{1}={a}_{1}$ | $-150.5$ | $-275.5$ | $2051$ | $\mathrm{153,949}$ |

${b}_{2}={a}_{2}$ | $0$ | $0$ | $-4000$ | $-\mathrm{160,000}$ |

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**MDPI and ACS Style**

Jabbour, C.; Hoayek, A.; Salles, J.-M. Formalizing a Two-Step Decision-Making Process in Land Use: Evidence from Controlling Forest Clearcutting Using Spatial Information. *Land* **2023**, *12*, 15.
https://doi.org/10.3390/land12010015

**AMA Style**

Jabbour C, Hoayek A, Salles J-M. Formalizing a Two-Step Decision-Making Process in Land Use: Evidence from Controlling Forest Clearcutting Using Spatial Information. *Land*. 2023; 12(1):15.
https://doi.org/10.3390/land12010015

**Chicago/Turabian Style**

Jabbour, Chady, Anis Hoayek, and Jean-Michel Salles. 2023. "Formalizing a Two-Step Decision-Making Process in Land Use: Evidence from Controlling Forest Clearcutting Using Spatial Information" *Land* 12, no. 1: 15.
https://doi.org/10.3390/land12010015