Enterprises’ sustainability orientation: A natural language processing approach
Sustainability in business is widely viewed as a strategic orientation decision. However, comparatively, little is known about assessing sustainability orientation and its drivers and implications for enterprises. This thesis examines sustainability orientation from a diverse perspective and focuses on sustainability orientation using corporate narratives. Specifically, this thesis harnesses the power of natural language processing (NLP) techniques, which is a field of artificial intelligence (AI), as a tool for research in extracting insights from textual communication. The thesis comprises three studies along with a cohesive synthesis of their implications. First, I begin by drawing on the vast literature on corporate social sustainability (CSR) to explore contextual factors that drive enterprises' behaviour towards sustainability. Specifically, the results illustrate that CSR practices are associated with external constituents' scrutiny levels. It is strongly related to political factors and social visibility and partially to media exposure. In addition, the study provides evidence to illustrate that positive influences on CSR practices may have been short-lived when a longer time horizon is considered. Second, by exploring small and middle-sized enterprises (SMEs), I elucidated the implications of a communicated sustainability orientation strategy on enterprises' economic performance. I used the communication of social values as a signal of sustainability orientation and explored its impacts, also considering social actions as an additional signal of sustainability orientation. The findings suggest that the effect of communicating social values on economic performance varies between social enterprises and traditional commercial enterprises. Unlike traditional commercial enterprises, social enterprises do not achieve economic performance advantages by communicating social values. Instead, it is the social actions of social enterprises that positively influence economic performance. Third, I explore sustainability orientation through the Sustainable Development Goals (SDGs) lenses. The last empirical study explores the effect of a communicated SDG orientation strategy on the economic performance of traditional commercial enterprises and social enterprises. The results demonstrated a positive relationship between the communication of a narrow set of SDGs and enterprises' economic performance. The extent of this effect is similar between social and traditional commercial enterprises. The results take on the meaning that stakeholders might appreciate an enterprise's SDG orientation strategy that concentrates on a narrow set of SDGs within distinct purpose-driven institutional contexts. This thesis is an effort to increase transparency about critical aspects of enterprises' sustainability orientation: its assessment, influential factors and implications for economic performance. This doctoral thesis provides significant practical and theoretical contributions to understanding the complex dynamics between sustainability orientation and business context. By focusing on the evolutionary nature of social norms, this research provides an aggregated view of how environmental pressures affect an enterprise's practices towards sustainability. This thesis also offers an initial step in examining the relationship between a communicated sustainability orientation strategy and enterprises' economic performance. It highlights that social enterprises and traditional commercial enterprises experience different external pressures and should tailor their sustainability orientation strategies to their specific context. Moreover, this thesis reinforces that innovative NLP approaches can overcome challenges in measuring sustainability orientation.
sustainability orientation, social enterprises, economic performance, natural language processing
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