Literature Reviews: Modern Methods for Investigating Scientific and Technological Knowledge

ISBN-13: 9783030757243 / Angielski / Miękka / 2022

Ana Paula Cardoso Ermel;D. P. Lacerda;Maria Isabel W. M. Morandi

Opis

This book begins by introducing the topic of knowledge in literature, including its scientific foundations. Due to the ever-increasing number of scientific publications, literature reviews are becoming more and more essential to stay updated. Literature Reviews describes an innovative system for creating systematic literature reviews, through reviewing, analyzing, and synthesizing scientific and technological literature.It then discusses systematic literature reviews, content analysis, and literature synthesis separately, before presenting the methodology to combine them in one process. It showcases computational tools to aid in this technique and offers examples of the method in action. Finally, the book takes a new of future developments in the subject.This book is of interest to graduate students, as well as researchers and academics, helping them to deepen insights and improve skills needed to conduct thorough literature reviews.

Spis treści

Introduction.- Scientific Contribution of Systematic Literature Reviews: Fundamentals in Karl Popper.- Systematic Literature Review.- Literature Analysis.- Literature Synthesis.- Literature Ground Theory (LGT).- Computational Tools For Literature Review, Analysis, and Synthesis.- What to Consider in a Systematic Literature Review: Three Examples from Design Science Research.- Future Perspectives.

O autorze

Ana Paula Cardoso Ermel holds a Master's degree in Production and Systems Engineering (UNISINOS) and a Bachelor's degree in Mechanical Engineering (URI). She has extensive knowledge in the implementation of quality management systems in the metalworking industry and holds the position of a permanent researcher at the Research Group on Modeling for Learning (GMAP | UNISINOS).

Daniel Pacheco Lacerda holds a Doctoral degree in Production and Systems Engineering (COPPE/UFRJ) and Master’s and Bachelor’s degree in Business Administration (UNISINOS and SJT). He is a permanent researcher and associate professor in the Graduate Program of Production and Systems Engineering at UNISINOS University. In this same institution, he coordinates the Undergraduate Program of Production and Systems Engineering, and the Research Group on Modeling for Learning (GMAP | UNISINOS). Over the last ten years, he accumulated a list of academic recognitions within and outside Brazil and has been recently identified as the 12th most prolific author on the Theory of Constraints worldwide. He has published numerous journal articles and eighteen books.

Maria Isabel Wolf Motta Morandi holds Doctoral and Master’s degrees in Production and Systems Engineering (UNISINOS), a Bachelor’s degree in Chemistry Engineering (UFRGS), and Specializations in Management and Logistics (FGV). She is a permanent researcher and coordinator at the Research Group on Modeling for Learning (GMAP | UNISINOS) and an associate professor in the Undergraduate Program of Production and Systems Engineering at UNISINOS University. She also has 18 years of experience as an executive in the chemical industry, 13 years of experience in specialized consultancies for multinational companies, as well as extensive knowledge in applied research regarding systems thinking, systems dynamics, discrete-event simulation, and mathematical modeling.

Leandro Gauss holds a Master's degree in Production and Systems Engineering (UNISINOS) and a Bachelor's degree in Industrial Design and Mechanical Engineering (ULBRA). For more than seventeen years, he has been working on the design process of capital goods for manufacturing environments within and outside Brazil, and since 2018 integrates the Research Group on Modeling for Learning (GMAP | UNISINOS) as a permanent researcher. He is also an assistant professor in the Undergraduate Program of Production and Systems Engineering at UNISINOS University,  and in the last two years received awards for best article and dissertation at master's level from the two most renowned Production Engineering Associations in Brazil (ANPEPRO and ABEPRO).