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The purpose of this paper is to investigate the level of energy saving behaviour between green and conventional office buildings in Malaysia to determine if people in green buildings perform better energy saving behaviour than people in conventional buildings. The paper specifically focused on use of technology, computer usage and potential energy savings from that use. The paper then examines what strategies are used to encourage energy saving behaviour for building occupants.

Questionnaires were distributed to occupants in the buildings to evaluate the extent of energy saving behaviour practiced, and identify potential strategies to encourage energy saving behaviour.

The findings show better energy saving behaviour practice in green buildings and the paper show why this is the case. The recommended strategies to encourage energy saving behaviour are discussed, and include means of raising education awareness on energy efficiency among the occupants. This can be done through distribution of guidelines, posters, pamphlets and e-mails. Occupants can also be given live updates on the energy usage of the building. Briefing on the objectives and goals of the organisation’s commitment to energy efficiency can be given to newly employed staff. As seen in this paper, these multiple strategies have shown to be successful in encouraging energy saving behaviours.

To date, energy saving behaviour has been given less focus in improving green building performance. There is limited research that compares energy saving behaviour between green and conventional commercial buildings in Malaysia. The findings provide a better understanding on occupants’ behaviour in energy conservation and suggest strategies for future recommendation.

The purpose of this paper is to examine the predictable effect of economic and non-economic factors regarded as the most important to stimulate stakeholders’ behavioural intentions to adopt green building.

The primary data was collected from 106 green building accredited professionals in both the public and private sectors registered with the Green Building Council of South Africa. The data analysis techniques adopted include descriptive and inferential statistics, namely, factor analysis and logistic regression model (LRM).

The LRM results revealed five predictors and two control variables made a unique statistically significant contribution to the model. The strongest predictor to enhance the intention to adopt green building was a financial benefit (FB), recording an odds ratio of 9.1, which indicates that the likelihood to adopt is approximately 9.1 times more if FBs is evident.

It is anticipated that the most significant facilitators/enablers identified by built environment stakeholders will create an enabling environment to enhance the adoption of green building.

This research has contributed to the existing knowledge by developing a decision support model. The decision support model provides predictive indicators for clients, consultants and contractors to harness their resources and identify significant parameters to improve their decision-making in adopting green building.