Literature grounded theory: método de pesquisa para investigação sobre o conhecimento científico e tecnológico

Abstract

The continuous growth in the number of publications promotes science advances, meanwhile, it becomes more difficult to map the already published researches in a given field, or even in specific topics. For this reason, it is important to discuss alternatives for literature mapping. The main objective of this master thesis is to propose a research method, named Literature Grounded Theory – LGT, to generate theory and hypothesis by mapping the existent scientific and technological knowledge. The Design Science Research supported the present research. The proposed method was developed in two stages. The first one combined theoretical concepts with revision procedures, and literature analysis and synthesis. The implementation of the Systematic Literature Review allowed for criticizing the current procedures, resulting in internal and external requirements of the LGT method. Besides, it helped to identify the tools used to accomplish each step and to suggest best practices. The concrete result of the first stage was the first revision of the LGT method. The second stage comprehends interviews with specialists in the field, used to validate the proposed method. The interview results were analyzed by means of the content analysis technique, with the statistical Fleiss’ Kappa method, and the Krippendorff`s Alpha to evaluate the agreement between the respondents. The interview was essential to identify improvement opportunities in the method’s first revision, while it reinforced the relevance of the present work. Regarding the research results, there are pieces of evidence of the possibility of generating new theories by investigating already published scientific and technological knowledge. For this purpose, structuring the literature synthesis techniques, as well as the Qualitative Meta-analysis technique contribute to the generation of the new knowledge. Moreover, associating the scientific and technological knowledge supports the strategical decision-taking in the organizations.