Complexity and the triple bottom line: an information-processing perspective.

Abstract

The purpose of this paper is to empirically investigate the impact of complexity on the triple bottom line by applying information-processing theory. Specifically, the paper assesses the impact of internal manufacturing complexity on environmental, social, and financial performance. Furthermore, the paper assesses the moderating role of connectivity and shared schema in reducing the potential negative impact of complexity on performance. Multi-country survey data collected through the Global Manufacturing Research Group were utilized to test the hypotheses. The authors used structural equation modeling to test the measurement and initial structural model. Furthermore, to test the proposed moderating hypotheses, the authors applied the latent moderated structural equations approach. The results indicate that while complexity has a negative impact on environmental and social performance, it does not significantly affect financial performance. Furthermore, this negative impact can be reduced, to some extent, through connectivity; however, shared schema does not significantly impact on the complexity-performance relationship. This study presents a comprehensive analysis of the impact of complexity on sustainability. Furthermore, it provides managerial applications as it proposes specific tools to deal with the potential negative influences of complexity.