Interdisciplinary Advances in Technology, Engineering, and Applied Sciences

Abstract

This study used a mixed-methods, multi-disciplinary research design to investigate the role that interdisciplinary collaboration between technology, engineering and applied science played in innovation and problem-solving. The participants included 185 engineering, computer science, information technology, environmental studies, biotechnology and other applied science professionals and researchers identified through purposive sampling based on prior interdisciplinary projects or research experience. A structured questionnaire was used to gather quantitative data on the dimensions of interdisciplinary collaboration, knowledge integration, technological capability, research collaboration, innovation performance and real-world problem-solving capacity, with a sub-sample of 18 interviewees following this with semi-structured interviews to elicit information on how knowledge was being shared and integrated across disciplines. Descriptive statistics, Pearson correlation, and multiple regression were used to analyse the quantitative data, and Braun and Clarke's thematic analysis framework was used to analyse the data from the qualitative interviews, with the results from the two strands then combined. The quantitative findings revealed that innovation performance and problem-solving ability were positively and significantly related to interdisciplinary collaboration, knowledge integration, technological capability, and research collaboration, with interdisciplinary collaboration, and knowledge integration having the highest beta coefficient values in the regression model. Structured collaborative platforms, boundary spanning communication practices, shared conceptual frameworks, trust-based relationship building, and institutional support structures were identified as the five recurring mechanisms that support cross-disciplinary knowledge sharing identified through thematic analysis of the interview data. Analysis of quantitative and qualitative results showed that the structural opportunities for interdisciplinary collaboration need to be supported by the relational and cognitive integration mechanisms that enable interdisciplinary engagement to lead to outcomes of innovation and applied problem solving. The results show the importance of intentional multi-disciplinary design and support systems in driving technology, engineering and applied-science innovation.