From sustainability constraints to innovation: Enhancing innovation by simultaneously attending to sustainability and commercial imperatives

The purpose of this paper is to connect the literatures on sustainability, innovation and paradox to suggest that sustainability constraints – simultaneously addressing commercial and sustainability goals – will increase organizational innovation.

Drawing from the literatures on paradox, innovation and sustainability, the authors develop theory about how managers can deliberately enhance the generation and implementation of creative ideas within their organizations.

The authors build on the existing literature that suggests sustainability considerations should be strategically and deeply integrated elements of business activity by developing arguments about how such integration improves organizational performance. The authors argue sustainability considerations, by creating unique forms of constraints, improve organizational success by enhancing creative idea generation and implementation.

Even strategic leaders espousing to only maximize economic efficiency face the challenge of effectively managing sustainability constraints. The discrepancy between what they should do and the problems they face means strategic leaders often have fewer tools to manage and reflect on their own decision-making than is available in the management literature. This paper presents arguments from diverse research that describes potential decision processes and their outcomes.

This paper highlights an important shift in how sustainability constraints are fundamental drivers of long-term organizational performance.

Extant literature treats the simultaneous attention to sustainability concerns and commercial success as difficult accomplishments of clever strategic leaders. Instead, the authors propose that simultaneous attention to sustainability and commercial imperatives is fundamental to long-term organizational success, because it is a powerful determinant of new products, services and business models.