Comparing Qualitative Analysis Techniques for Construction Engineering and Management Research: The Case of Arctic Water Infrastructure

Abstract

Construction is a dynamic sociotechnical process, consisting of ongoing interdependencies between people and the built environment. Accordingly, finding solutions to construction challenges when they arise requires understanding the interactions between social and technical factors. Over the past three decades, qualitative methods have been increasingly applied in construction engineering and management (CEM) research to understand challenges within this industry. However, there remains a lack of resources in the CEM literature on qualitative method selection and implementation specifically applicable to this domain. Without such guidance, it can be challenging to choose the most appropriate research methods, which can limit theoretical and practical contributions. To begin to address this gap, this paper offers an overview and comparison of three qualitative data analysis techniques—ranging in their use of induction, prevalence in CEM research, and ability to answer different types of research questions. These analysis techniques are applied to the same semi-structured interview data drawn from a case study on water infrastructure in rural Alaska. Insights gained from each method are compared to illustrate the utility of each technique. To the authors’ knowledge, this study is the first qualitative method-comparison paper published for a CEM audience. Based on the comparison findings, choosing a deductive content analysis can allow for full characterization and quantification of a data set and discussion of results in relation to a predefined framework, such as a framework based on design and construction standards. A hybrid content analysis can expose new, detailed insights for an existing framework by allowing emergent themes to arise and be quantified. Conversely, a constant comparative analysis can reveal emergent trends and uncover the reasons why these trends occur based on connections between prominent themes, which can help CEM researchers develop new theories. Overall, this study helps advance the sociotechnical side of CEM research by enabling the discipline to better address the industry’s complex challenges.