Modelo para escolha de método de coleta de dados em pesquisas de opinião pública

Abstract

This study presents an analysis of data collection methods in public opinion research, ranging from traditional methods to current practices incorporating emerging technologies. It highlights the relevance of public opinion research, particularly its contribution to understanding societal behavior within a democratic context and to public policy formulation. The study aims to assist in selecting the best data collection method for a specific problem. To this end, the FITradeoff (Flexible and Interactive Tradeoff) multicriteria decision method was employed. FITradeoff, part of the family of compensatory multicriteria methods, is applied in various contexts; its key benefits include flexibility, interactivity, and reduced cognitive load. The research is classified as applied, bibliographic, and exploratory, utilizing a combined qualitative and quantitative approach. A systematic literature review was conducted, with sources selected using the PRISMA 2020 flow diagram. Public opinion polls significantly influence political decisions, underscoring the need for an ethical and responsible approach to data collection to ensure the legitimacy of results and the representativeness of public opinion. Traditional methods, such as face-to-face interviews and telephone surveys, remain in use due to their representativeness, despite higher costs and slower execution. Interactions with the developed model enabled comparisons between alternatives, allowing for the ranking of the most suitable options for each analyzed problem through a structured tool. The empirical application of the method demonstrated the feasibility of using FITradeoff in public opinion research, highlighting its ability to structure the decision problem from a multicriteria perspective. Thus, this study aims to facilitate the selection of the most appropriate data collection method for each problem using FITradeoff, thereby yielding more robust and reliable results. The model contributes to a more systematic, transparent, and well-founded decision-making process by allowing for the simultaneous consideration of various criteria when selecting a data collection method.