AUTHOR=Tshivhase Lelo , Bisschoff Christo 

TITLE=A conceptual model to measure and manage the implementation of green initiatives at South African public universities

JOURNAL=Frontiers in Sustainability

VOLUME=4

YEAR=2023

URL=https://www.frontiersin.org/journals/sustainability/articles/10.3389/frsus.2023.1237514

DOI=10.3389/frsus.2023.1237514

ISSN=2673-4524

ABSTRACT=<sec><title>Introduction</title><p>The growing need for environmental awareness accentuated the importance of green and sustainable business practices. This is also true for universities that modernly expanded their green training and research to engage in green operational practices.</p></sec><sec><title>Methods</title><p>This article summarises the main principles and factors of implementing green initiatives. Firstly, a generic theoretical approach conceptualizes implementing green initiatives at universities. The investigation analyses existing and current green initiatives at the universities, considers the benefits and barriers of implementing green initiatives, and develops a theoretical model for implementing green initiatives at South African public universities. An adapted conceptual model consisting of twenty significant literature antecedents (<italic>p</italic> ≤ 0.05) and 13 latent variables (factors) could be hypothesized. This model was tested empirically with reliable data (α = 0.749) from a five-point Likert scale questionnaire administered to 144 responding green managers at eight selected South African public universities.</p></sec><sec><title>Results</title><p>Although the regression model explains satisfactory variance (R<sup>2</sup> = 0.862; R<sup>2</sup> adjusted = 0.841), only five of the 20 antecedents in the theoretical model are significant. They are <italic>Cost of green products</italic> (<italic>r</italic> = 0.527; <italic>p</italic> ≤ 0.05), <italic>Lack of awareness and training</italic> (<italic>r</italic> = 0.435; <italic>p</italic> ≤ 0.05), <italic>Managerial attitude and commitment</italic> (<italic>r</italic> = 0.369; <italic>p</italic> ≤ 0.05), <italic>Digitisation</italic> (<italic>r</italic> = 0.552; <italic>p</italic> ≤ 0.05), and <italic>Management Committee</italic> (<italic>r</italic> = 0.451; <italic>p</italic> ≤ 0.05). Further analysis revealed that the data possess embedded intelligence. Resultantly, 13 factors were identified, explaining a cumulative variance of 61.8%. However, only six factors are reliable and, therefore, usable (α ≥ 0.57). They are <italic>F1</italic>: <italic>Convenience and efficient workflow, F2</italic>: <italic>Personnel cooperation, F3</italic>: <italic>Efficient use of resources, F5</italic>: <italic>Learning and improvement, F6</italic>: <italic>Delegation of authority</italic>, and <italic>F7</italic>: <italic>Improved management attitude</italic>. Cumulatively, the six usable factors explain a cumulative variance of 45.5%.</p></sec><sec><title>Discussion</title><p>The model aspires to demonstrate and measure the implementation of green initiatives at public universities. Although the theoretical model is detailed, the empirical study showed that not all of the antecedents are usable for measuring and managing the implementation of green initiatives at South African public higher institutions. This study validated five of the antecedents and six factors for immediate use. The model's unvalidated antecedents and unreliable factors require empirical revalidation before operationalizing it fully. Researchers and scholars exploring this avenue of green initiatives implementation models can also benefit from this article.</p></sec>