A systems approach to examining the drivers and barriers of renewable energy technology adoption in the hotel sector in Queensland, Australia

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Abstract

The adoption of renewable energy technology (RET) in the hotel sector is low, despite the technology's potential to reduce a hotel's energy consumption and carbon emissions. Previous research has explored selected aspects of RET adoption in hotels, but a comprehensive and systemic analysis is missing. This research uses a systems approach, which allows examination of a wide range of dynamics and complexities, including feedback mechanisms that influence system behaviour over time. The model was developed using the structural analysis method and causal loop diagramming in conjunction with theories of diffusion and patterns of innovation. The aim was to enhance our understanding of the hotel energy system, with a focus on drivers and barriers to RET adoption in the sector. The results demonstrate that the uptake of RET by hotels reflects an interplay between incentive policy, hotel owner/manager perceptions of RET, tourists' behaviour, technology advancement and electricity grid price. The analysis also uncovers the dynamics of key drivers that, under different circumstances, can also become barriers. The insights generated from the analysis validate the use of systems thinking to capture the complexities and dynamics of interactions.

Introduction

The hotel sector has the potential to reduce its greenhouse gas emissions by investing into their own renewable energy technology (RET) system to generate electricity (hereafter, RET adoption). Hotels rank among the largest energy-intensive commercial buildings, which require 24-h air conditioning, space and water heating, and many other energy services (Karagiorgas, Tsoutsos, & Moiá-Pol, 2007). By adopting RET, hotels could respond to tourists’ increasing demand for green hotels (Yusof & Jamaludin, 2013), and reduce energy costs subject to RET investment cost and grid electricity price (Gross, Blyth, & Heptonstall, 2010). Whilst there are no data regarding hotel adoption of RET globally, earlier work by Karagiorgas et al. (2006) indicates that uptake is quite low, except for thermal solar. This presents an opportunity to promote RET adoption in the hotel sector. This research contends that understanding what drives and hinders the hotel sector from adopting RET can promote a better uptake by hotels. The hotel sector in this research refers to commercial tourist accommodation providers excluding private home rentals or other small-scale hosted accommodation.

There is a paucity of research which examines drivers and barriers to RET adoption in the hotel context. Gash, Carter, and Miller (2013) argue that the barriers to adopting RET include expert advice against RET, lack of funding, inadequate RET operational knowledge in a specific environment, and high maintenance cost. Mahachi, Mokgalo, and Pansiri (2015) identify driving forces for RET adoption in hotels as political leadership, financial benefits, the availability of green programs, and strong environmental values. These factors are similar to those that influence the adoption of other environmental measures, which has been the focus of a growing body of research. For example, E. S. W. Chan, Okumus, and Chan (2018) identified barriers to adoption of environmental technologies in hotels, which are: (1) product-related barriers such as immaturity of the technology and long payback period; (2) external barriers such as inconvenience caused by government and tourists' acceptance of environmental technologies; and (3) internal barriers such as a limitation on the hotel's ability and a lack of owner initiative to adopt environmental technologies. Similarly, Wang, Font, and Liu (2019) identified market needs, managers' attitudes towards the environment, and the demand from stakeholders as the antecedents of willingness to adopt eco-practice in a hotel.

This research asserts that the adoption of RET warrants its own examination, mainly because there has been relatively limited uptake in the hotel industry, despite some obvious benefits of reducing costs long term. The low adoption rate contradicts Namasivayam, Enz, and Siguaw (2000) findings that technology is revenue positive is usually adopted faster than technology that improve employee productivity and guest services. Low RET adoption in the hotel sector does not reflect the government policies that are particularly favourable to RET adoption, such as: (1) increasing RET competitiveness by internalising carbon prices of non-renewable energy, (2) providing RET investment funds (Solangi, Islam, Saidur, Rahim, & Fayaz, 2011); and (3) increasing RET consumption rates through feed-in tariffs (FITs), whereby owners of RET equipment can sell excess electricity back to the grid (Poruschi, Ambrey, & Smart, 2018). Moreover, research outside the hotel literature indicates factors influencing RET adoption are context-related and are beyond individual or organizational control, such as consumer reliance on grid distribution and the availability of a specifically trained workforce to maintain RET hardware (Pável Reyes-Mercado, 2017; Sen & Ganguly, 2017).

The above factors from different perspectives including policies, technology and the hotel sector highlight an interrelated and complex system. Thus, the overall RET system must be examined to understand low RET adoption in the hotel sector by considering such complexity. A systems approach provides a suitable platform to explore the RET adoption dynamics (Negro, Alkemade, & Hekkert, 2012). This research presents the system elements of potential RET adoption in the hotel sector in Queensland, Australia. The three objectives are: (1) identifying variables, their roles and relationships, related to RET adoption in the hotel sector; (2) illustrating the variable interactions with a causal loop diagram (CLD) explaining the past and current pattern of RET adoption; and (3) using the CLD to understand the dynamics of the system and the role of drivers as potential enablers or barriers shaping hotels’ uptake of RET. This research presents a systems approach for hoteliers and policy makers to understand the (un)intended consequences of their decisions, and to identify interventions that can modify system behaviour favourably.

Section snippets

Renewable energy synopsis

RET uses energy obtained from replenishing natural resources such as solar, wind, hydro, bioenergy, and geothermal, to produce energy (ARENA, 2017b). As global fossil fuel-related emissions increase, RET is an alternative electricity resource to reduce global greenhouse gas emission from energy use (IEA, 2019). A decade-long growth in RET as an electricity-generation choice is observable globally (IRENA, 2019). RET investment is often driven by financial incentives such as FIT, quotas and

Energy policy environment

The Australian federal government sets a 20% Renewable Energy Target by 2020 and funds RET projects and R&D through the Australian Renewable Energy Agency (ARENA, 2017b). At the state level, the Queensland Government incentivizes solar photovoltaic (PV) installation through the feed-in tariff (FIT) policy. However, FIT has been criticized for: 1) levying Queensland households (whether they install RET or not) and providing monetary benefits to solar PV owners (Nelson, Simshauser, & Nelson, 2012

Systems approach

The systems approach is suitable to analysing the interactions of key variables influencing RET adoption (Negro et al., 2012). RET adoption decisions are not ‘isolated’ ones but form a ‘system’ of components connected in a non-linear fashion. Changes in one factor may have an unintended consequence. For example, FIT or higher tourist in-room electricity consumption may influence hotels to consider adopting RET; and an increasing RET demand may improve the technology over time. Exploring RET

Variables related to RET adoption in the hotel

The MICMAC results indicate 38 variables related to the hotel sector and RET adoption in Queensland, representing nine roles with different levels of influence and dependence as identified by stakeholders (summarised in Fig. 3). Six responses with two each from hotel engineers, operation managers and accountants were aggregated using geometric mean (see Appendix B). The low response rate could due to a long time required (>60 min) to complete the matrix. Small sample size is acceptable as

Conclusion

This research applied a systems approach to better understand the complex system of hotel RET adoption, involving multiple dimensions of technology, government incentives, tourist behaviour and hotel management. This research combined three established, yet thus far not integrated, innovation theories, namely: (1) Brown (1981)'s marketing system; (2) Sahal (1981)'s potential demand and technological feasibility of the product; and (3) Rogers (2003)'s process for consumer adoption or resistance.

Declaration of competing interest

None.

Acknowledgements

The authors are grateful to anonymous reviewers for their valuable suggestions which helped to improve this manuscript.

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