CONTENTS 1. INTRODUCTION

2

CONTENTS

2. ANALYSIS OF RDS AS A PROBABILISTIC SAMPLING METHOD 2.1. Introduction to RDS

2.1.1. Evolution of sampling methods of hidden populations 2.1.2. Introduction of terminology

2.1.3. RDS: a borderline probability sampling method

2.2. Estimators and theoretical foundations of the method

2.2.1. RDS I

2.2.2. Estimation of transition probabilities 2.2.3. Estimation of mean group degrees 2.2.4. Proportions weight in RDS 2.2.5. Markov equilibrium 2.2.6. Homophily 2.3. RDS II 2.3.1. RDS II estimator 2.3.2. Comparison of RDS I and RDS II 2.3.3. Variance of RDS II 2.3.4. Using bootstrap in RDS

2.4. Analysis of the hypotheses of probabilistic sampling

3. STUDY OF ESTIMATORS VARIABILITY: MONTE CARLO SIMULATIONS 3.1. Introduction of theoretical context and of objectives of the study

3.2. General settings of simulations 3.3. Simulations and data analysis

3.3.1. Simulation 1: correlation between study variable and degree 3.3.2. Simulation 2: variability of estimations on varying of sample size

3

3.3.3. Simulation 3: Variability of estimations on varying of individual degrees

3.3.4. Simulation 4: Required sample size on varying of parameters

3.4. Conclusions and benefits of analysis

4. APPLICATION OF RDS TO CONSUMER BEHAVIOR STUDIES IN MARKETING

4.1. Sampling scheme: information and hypotheses 4.2. Target population and sampling frame in RDS 4.3. Sampling and data analysis

4.3.1. Selection of seeds 4.3.2. Selection of incentives

4.3.3. Instructions and filter questions 4.3.4. Data analysis

4.4. Benefits and limitations of RDS for consumer behavior studies

5. ANALYSIS OF THE GAP BETWEEN ATTITUDE AND BEHAVIOR OF SUSTAINABLE CONSUMPTION IN ITALY

5.1. Introduction of the problem and of the objectives of study 5.2. Benefits of RDS for the study

5.3. Target population and sampling frame

5.4. Definition of the sample and of its characteristics

5.5. The model of study of sustainable consumption behavior

5.5.1. The principle of product specificity 5.5.2. Analysis of existing models

5.5.3. Construction of survey

5.6. Data analysis

5.6.1. Analysis of recruitments and of sample structure 5.6.2. Analysis of survey data

5.6.3. Analysis of the gap between attitude and behavior and construction of profiles

4 6. CONCLUSIONS

6.1. Conclusions related to the statistical research 6.2. Conclusions related to the marketing research

References

Appendix 1 Appendix 2