Examining energy saving behaviors in student dormitories using an expanded theory of planned behavior

Highlights

• An expanded theory of planned behavior (TPB) model is proposed to explain energy saving behaviors.

• 290 postgraduates were surveyed with results analyzed using structural equation modeling.

• All indicators were found significantly related to intention except subjective norm.

• Personal moral norm was found to have enhanced explanation power of the TPB model.

• Gender differences were observed to exist in the energy saving behaviors.

Abstract

Buildings contribute to over one third of global energy-related carbon emissions, on which occupant behavior attains a significant impact. Occupant behavior is influenced by both internal and external factors, such as psychological and social factors, equipment properties. However, there is a marked lack of knowledge about the internal factors that influence occupant behaviors in buildings, in particular student dormitories. This paper aims to investigate energy saving behaviors using student dormitories as the case from a social psychological perspective. First, a theoretical framework was proposed based on the Theory of Planned Behavior (TPB) integrated with a new variable “personal moral norm”, to identify significant indicators of energy saving behaviors. Second, a questionnaire was conducted with 290 students to obtain data for model fitting. Third, the proposed framework was tested using two-step Structural Equation Modeling. Results show that students’ energy saving intentions are positively related to their behaviors. Personal moral norm has the greatest impact on energy saving intention, followed by perceived behavioral control and attitude, while the impact of subjective norm is insignificant. The additional variable “personal moral norm” significantly increases the explanation power of the TPB model. Moreover, gender and thermal sensation moderate the impact of energy saving intention on behavior. Finally, energy saving intervention strategies are suggested for student dormitories. The findings contribute to a better understanding of energy use behaviors in student dormitories and add to the existing body of knowledge about social psychological indicators of energy saving behaviors by confirming the role of moral beliefs.

Introduction

Buildings are important energy end-users, demanding around 3060 Mtoe each year, which accounts for 36% of global final energy use and 28% of global energy-related CO₂ emissions (2018) (IEA, 2019). Despite improvements in building design and construction, and having more efficient appliances, the total energy demand of buildings continued rising during 2016–2018 (OECD/IEA, 2019). Energy-related CO₂ emissions of buildings has increased from 7.7 Gt in 2000 to 9.6 Gt in 2018 (IEA, 2019). With increasing income and higher comfort requirements, occupants have raised their expectation of building services, which accelerates the growing energy demand of existing buildings and the insatiable demand for new buildings. Two key international agreements, the Paris Agreement on climate change and the Montreal Protocol on ozone depletion, are targeting energy efficiency in buildings as measures to achieve broader goals at sustainability (OECD/IEA, 2017).

It is believed that buildings have massive energy saving potential. According to IEA (2019), near-zero energy constructions and deep energy renovations could potentially reduce the sector's energy needs by nearly 30% by 2050 in the faster transition scenario. However, “technology alone does not guarantee low energy use in buildings” (D'oca et al., 2018) and human dimensions should be considered carefully when addressing higher performance of buildings (Qin & Pan, 2020; Xu et al., 2013; Zhou et al., 2016). Jareemit and Limmeechokchai (2019) stated that annual household energy use could decrease by 7%–15% or 484–1038 kWh with favorable energy saving behaviors in Bangkok, Thailand. Sun and Hong (2017) stated that occupant behavior caused an up to 20% difference in energy savings, depending on how different technologies were used. As buildings become smarter and people require a more comfortable living environment, the impact of occupants on building energy use will undoubtedly increase (IEA-EBC, 2019).

However, two research gaps are identified in the literature. First, there is a lack of exploration into the internal factors that motivate occupant behaviors. Researchers have tried to delve into the ‘black box’ of occupant behaviors, but this has proved to be very complex (IEA-EBC, 2013, IEA-EBC, 2018). Occupant behavior is somehow uncertain and stochastic, influenced by both internal factors, such as biological, psychological and social factors, and external factors like building and equipment properties, the physical environment and time. These social concerns, economic concerns, comfort concerns etc. are all important for understanding how occupants use buildings (Day & O’brien, 2017; Gou et al., 2017). However, compared to research outcomes about external factors affecting occupant behavior (Hong et al., 2015; Wang et al., 2016; Wagner et al., 2018; Sikram et al., 2019), studies on internal factors, especially the psychological factors, are limited and challenging. More effort is required to find behavior models and social-psychological constructs (see Appendix A for the definition of construct) which can explain and predict energy-related behaviors effectively (Ding et al., 2018).

The second research gap has to do with behavior models in specific types of buildings, e.g. student dormitories. An empirical study in a university dormitory in the US proved that living in green dorms positively affected pro-environmental behaviors of the student residents (Watson et al., 2015). Energy conservation activities in student dormitories are believed to not only guide pro-environmental behaviors and harvest energy savings, but also impose a prolonged impact on the sustainable development when students start to play a role in the society (Ding et al., 2019; Sintov et al., 2016). It is estimated that there will be 377 million students enrolled for higher education globally by 2030 (Calderon, 2018). Thus, it is necessary to promote energy conservation in student dormitories. However, the determinants of energy saving behaviors by student residents remain largely unknown. The absence of argumentation on social psychological constructs prevents us from exploring the underlying reason for energy savings. For example, Peschiera et al. (2010) reported that, based on an experiment in a student dormitory in the USA, a significant reduction in electricity use was only achieved by students who were informed of not only their individual bill but also the average bill of the building and the bills of their peer network. Interestingly, Anderson et al. (2017) had a slightly different finding in Korea compared to that in the USA, that the normative feedback messages did not achieve any significant energy reduction among students with a low concern for social norms. However, it was still uncovered why the same energy saving measure performed differently in the two case studies or why the normative feedback message only worked for the students with high concern for social norms. More social psychological surveys among different groups and cultures are therefore necessary to achieve reliable conclusions.

This paper thus aims to contribute to a better understanding of energy saving behaviors in student residential buildings from the perspective of behavior theories in social psychology. The research was guided by three questions: (1) What are the significant internal factors affecting energy saving behaviors and behavioral intentions? (2) How do these factors shape the behaviors of student residents? (3) What are effective human-in-the-loop approaches to motivating and enhancing energy conservation? This paper, in Section 2, first establishes a theoretical framework based on classic behavior theories, and then develops a list of hypotheses. In Section 3 the paper then explains the multiple research methods employed for data collection and analysis, including a questionnaire survey and two-step structural equation modeling. In Section 4 the results and analyses are reported, followed by a discussion in Section 5 and the conclusions in Section 6.