Social Licence to Operate: The Contextual Role of Culture and the Dominance of Attitudinal and Regulatory Factors in New Wind Energy Installation

Abstract

This study investigated the factors influencing the social licence to operate (SLO) for new wind-farm installations, focusing on the roles of community attitudes, regulatory environment and local cultural values and beliefs. Using survey data collected from 226 community members across Australia, multiple linear regression analysis was conducted to examine how these factors influence community acceptance of wind energy development. The findings reveal that positive community attitudes towards wind energy and trust in the regulatory environment significantly enhance the SLO. In contrast, local cultural values and beliefs were not significant predictors. The findings suggest that acceptance of wind energy projects is driven more by perceptions of regulatory fairness and individual attitudes than by cultural norms. Interestingly, community members appear to base their support primarily on perceived economic and social benefits, underpinned by strong trust in the regulatory environment rather than cultural values and beliefs. Theoretically, the study refines SLO frameworks by empirically demonstrating the context-specific nature of cultural influences and the dominant role of attitudinal and regulatory factors. Practically, the study highlights the need for transparent governance and proactive community engagement strategies to strengthen public confidence and foster renewable energy transitions.

Keywords

Social licence to operate wind energy positive attitudes regulatory environment sustainable energy transition

Introduction

Global wind energy production in 2018 was 600 gigawatt (GW) and accounted for about 6% of world electricity demand (Australian Renewable Energy Agency, 2025). Projections indicate continued growth in wind energy in both global and Australian electricity markets. In Australia alone, 94 operational wind farms generated about 16 GW of energy in 2018 (Australian Renewable Energy Agency, 2025). The rapid expansion highlights not only the increasing importance of wind energy as a key component of a sustainable electricity mix, but also the need for and importance of securing social licence to operate (SLO). Although offshore wind farms in Australia are projected to have operational turbines by 2032, this timeline appears ambitious, given reported investor hesitation and withdrawal of project development support (Stock, 2025). As wind projects grow in number and scale, understanding and addressing public perceptions about new wind energy installations is critical to ensuring the successful development and long-term viability of wind energy initiatives.

In addition to rising costs, the transition to offshore wind energy development in Australia and globally has been slowed by regulatory hurdles, challenges with grid integration and concerns related to SLO (Hammond, 2025). Public opposition to wind farms often stems from concerns that they negatively impact wildlife, reduce property values and contribute to environmental pollution (Bessette & Mills, 2021). Although wind farms are not inherently a threat, these perceptions can generate strong resistance among communities (D’Souza & Yiridoe, 2014). To address such concerns and secure long-term, sustainable investment, the onshore wind energy industry must actively seek SLO, which involves gaining community approval and trust. Government policy is important in this process, acting as a facilitator by providing clear regulatory frameworks, ensuring fair consultation and supporting initiatives that demonstrate the social and environmental benefits of wind energy. By addressing both community concerns and regulatory requirements, developers can enhance public acceptance and foster a more supportive SLO and develop wind energy systems.

The SLO is a relatively new concept in renewable energy development. It refers to the approval granted to developers by stakeholders in the communities impacted by projects. This study adopts Hall’s (2014) definition of SLO as the ongoing approval of a development project by a community and relevant stakeholders. When such approval is absent, the diffusion of innovations often falters, as community resistance can hinder acceptance and implementation (Hall, 2014). The rate at which innovations diffuse varies considerably and depends on two primary factors influencing adoption: the degree of innovativeness and the presence of favourable public attitudes (Rogers & Jain, 1968).

According to Rogers (1995), the public is more likely to embrace an innovation when it is perceived to generate positive net benefits or enhance overall utility. In the context of wind energy, the perceived financial benefit of lower energy costs serves as a key trade-off that supports public acceptance and accelerates diffusion. Other factors that are relevant include policy and regulatory frameworks (Baumber, 2018; Hall, 2014; Hall et al., 2015) and local cultural values and beliefs (Barich et al., 2022; Firestone et al., 2015; Goggins et al., 2022; Prno & Slocombe, 2012). A transparent and fair regulatory policy framework builds trust and legitimacy by ensuring that projects comply with ethical norms and legal requirements, while weak or inefficient regulations can erode community confidence. Similarly, respecting local cultural values and beliefs fosters moral legitimacy and social acceptance by aligning project goals with community identities, traditions and expectations (D’Souza & Yiridoe, 2014). Together, these factors influence perceptions of fairness, trust and shared values, which are essential for sustaining a social licence.

Social Systems

Rogers’s (2003) concept of social systems helps explain the social dynamics that influence the acceptance or rejection of new ideas, technologies or projects, making it relevant for understanding the SLO. In Rogers’s (2003) diffusion of innovations theory, a social system is the network of individuals, groups and institutions whose norms, values and communication patterns shape how innovations are perceived and adopted. The SLO depends on the collective attitudes, trust in regulation and cultural values within a community (Glasson et al., 2022; Liu et al., 2025; Pixley et al, 2022; Rodolaki & Barakos, 2023; Stephens & Robinson 2021). Using Rogers’s (2003) social systems framework allows analysts to see how opinions about a project, such as a wind farm or mining operation, spread through local networks and how influential actors like community leaders or regulatory bodies influence acceptance. The social systems framework demonstrates that gaining a social licence is not only about compliance, but also about how well an organization aligns with existing social structures, values and communication processes (Lesser et al., 2023).

Rogers (1995) argues that the selection of change agents should be tailored to the characteristics of the social system in which an innovation is introduced. Social systems can be classified as heterophilous, where individuals have little social identification with one another or homophilous, where members share strong social ties and identification. Such social systems may be further described as ‘localite’ or ‘cosmopolite’ (Rogers & Jain, 1968). Within the context of innovation diffusion, social systems are defined as ‘a set of interrelated units engaged in joint problem solving to accomplish a common goal’ (Rogers, 1995, p. 23). Understanding the structure and cohesion of these systems is essential, as it influences how effectively innovations spread and how change agents can influence adoption and the SLO.

Innovation adoption decisions can take three forms: individuals may decide independently, decisions may be made collectively within a social system or decisions may be guided by authoritative sources with recognized expertise or power (Rogers, 1995). In the context of wind energy, such decisions are closely tied to the SLO, as public acceptance and stakeholder approval often depend on the interdependent choices of individuals within the social system (Orr, 2003). The socio-political system, comprising key stakeholders, policymakers, technology developers and relevant regulations and frameworks, plays a crucial role in shaping these decisions (Wüstenhagen et al., 2007). Understanding these dynamics is essential for securing and maintaining SLO, as coordinated support and informed decision-making among stakeholders strengthen trust, reduce uncertainty and enhance the likelihood of successful wind energy adoption.

Achieving both socio-political and community acceptance, which are central to SLO, requires careful consideration of local cultural values and beliefs, the types of innovation decisions and the potential consequences of new technologies. Securing such acceptance depends on cooperation both at the societal level and within individual projects, which is influenced by the distribution of power and decision-making within the social system; in particular, whether decisions are made democratically or through more centralized, command-and-control approaches. Moreover, social systems that are most responsive to innovation and capable of securing social acceptance tend to foster creativity, encourage collaborative problem-solving and maintain relatively flat hierarchies with strong leadership to guide implementation (Sanson-Fisher, 2004). Consequently, the structure and dynamics of the social system play a critical role in obtaining and sustaining SLO, as they influence the speed, legitimacy and durability of community and stakeholder support.

Social Licence to Operate

Beyond challenges such as skilled labour shortages, policy responses to new wind energy developments are influenced by considerations of the SLO (Briggs et al., 2022). Power et al. (n.d.) proposed using the SLO framework to capture the level of social licence directly from the community, rather than relying on a binary acceptance or rejection dichotomy, allowing for a nuanced measurement of the relationship between developers and community members. The framework can assess social licence at the individual level or aggregate it to reflect the broader community. The SLO framework of Thomson and Boutilier (2011) proposes four dimensions: economic legitimacy, socio-political legitimacy, interactional trust and institutional trust.

Building on existing literature, this study examines three factors that influence SLO, thereby linking these variables to these dimensions of social licence to capture how community support is shaped towards new wind energy development. The study considered three areas in relation to new wind energy that influence SLO: attitudes, regulatory environment and local cultural values and beliefs. These three factors are critical in shaping public perceptions and, consequently, in influencing the degree of social acceptance for wind energy projects.

Against this backdrop, the objectives of the study are:

To evaluate the strength and direction of relationships between predictors (i.e., regulatory environment, local cultural values and community attitudes) and the outcome variable related to wind energy development (i.e., community support for social licence to operate).

To determine which predictors have the most significant impact on the support for new wind energy projects within communities.

To provide evidence-based policy and practitioner insights for improving and strengthening community trust and project acceptance towards the social licence to operate.

Research Hypotheses

In this section, hypotheses are developed and used to investigate the relationships between community attitudes, government regulatory environment, local cultural values and beliefs and the SLO for new wind-farm installations. The empirical findings are discussed later in relation to the hypotheses, highlighting the supported and unsupported relationships.

Attitudes

Attitudes are shaped by how much a community trusts that a developer will act responsibly, engage transparently and address community concerns. High trust strengthens positive attitudes, thereby enhancing SLO. Communities with favourable attitudes towards wind energy development are more likely to engage constructively in consultation processes and offer input rather than outright opposition, which signals a higher SLO. From the perspective of social judgement theory, individuals rely on existing attitudes as a frame of reference to evaluate new information about innovations (Sherif & Hovland, 1961). Consequently, public attitudes towards social or technological issues influence the extent to which different positions are deemed acceptable. Importantly, these attitudes are not static; they can be shaped and refined through knowledge. Individuals who have knowledge about wind farms are better able to appreciate their environmental and economic benefits, thereby fostering greater social acceptance (D’Souza & Yiridoe, 2014). Awareness of factors such as renewable energy technologies (RETs), turbines and wind energy system size, fixed and operating costs, installation and maintenance requirements, energy generation potential and connection to existing utility grids all contribute to forming more favourable attitudes towards wind energy. In Australia, public awareness campaigns for small wind systems have not been pursued on the same scale as those for solar power, resulting in relatively limited knowledge and understanding of wind energy technologies (Clean Energy Council, 2011). Residents living in close proximity to wind farms are a group most likely to take action to oppose a proposed wind farm and are also the most likely to withhold the SLO in the preplanning and planning stages (Corscadden et al., 2012; D’Souza & Yiridoe, 2014). However, this NIMBY (not in my backyard) opposition may dissipate as the project moves through the post-planning stages (Power et al., n.d.).

In general, diffusion tends to be slower when unfavourable attitudes towards an innovation exist or when the innovation itself is perceived to have inherent uncertainty. Early survey research on consumer attitudes towards wind energy generally suggests strong public support for wind technology (Bond, 2008; Bosley & Bosley, 1988; Dimitropoulos & Kontoleon, 2009). For instance, Bond (2008) reported that 94% of respondents in Australia described wind energy as ‘interesting’, while 74% regarded wind power as ‘graceful’. Similarly, a survey of 1,027 consumers commissioned by the Australian Wind Energy Association (AWEA) found that about 95% of respondents supported the construction of wind farms and 91% agreed that developing wind farms in rural Australia was important for generating electricity from renewable sources (AWEA, 2003). Although there was strong support, a small proportion, about 1.7%, opposed wind energy developments after construction (Bond, 2008). More recent research reports lingering opposition towards wind farms (Winter et al., 2024), suggesting that public controversy surrounding wind energy has intensified, and may influence acceptance of the SLO. In summary, positive attitudes act as an enabler that transforms into informed confidence, strengthening public support. Thus, it is hypothesized that:

H₁: Positive attitudes about wind energy influence the SLO new wind-farm installations.

Regulatory Environment

Regulatory environment uncertainty can influence the SLO wind energy projects. In Australia, the energy market is highly complex, with multiple stakeholders, including regulators, government agencies, private landowners and local communities, involved in wind farms and energy development. For example, there is regulatory variation by local and regional authorities in the Australian state of Victoria (Akimov et al., 2023), while the Australian Energy Regulator determines allowable expenditure and consumer pricing. In addition, land-use governance varies across regions, creating ambiguity for project planning and implementation. Local planning schemes further complicate energy development, imposing restrictions on wind-farm development in Public Conservation and Resource Zones, state parks, coastal areas and other environmentally sensitive landscapes (Chen, 2019). Although coastlines in many countries and regions are particularly valuable sites and have resources (e.g., tides, waves and offshore winds) for renewable energy systems (Gill, 2005), in the early 2000s, in the Australia state of Victoria, for example, regulations and restrictions excluded nearly 43% of the coastline from potential wind energy development (Wawryk, 2004). Such overlapping regulations and variable land-use arrangements heighten environmental uncertainty, making it more difficult for communities and stakeholders to anticipate impacts and for developers to demonstrate responsible management. The resulting uncertainty undermines stakeholder confidence and can weaken the SLO, highlighting the need for transparent engagement, clear communication and proactive strategies to address environmental concerns.

Other regulatory schemes address concerns related to noise and potential damage to plant and animal species and habitats (Sander et al., 2024). Regulations include provisions to minimize the environmental impact of wind energy facilities on flora, fauna and their habitats through careful turbine siting and design measures during the project planning stage (Ruoso et al., 2024). While these regulations are intended to mitigate environmental risks, they also impose constraints on the construction and expansion of wind energy projects. Such limitations can influence community perceptions and stakeholder confidence and highlight the role of environmental management in securing and maintaining SLO. If regulations are not clear, are inconsistent or are subject to sudden and unexpected change, communities may have higher risks in the project. This uncertainty can also reduce trust in a developer’s ability to comply with regulations, thereby weakening SLO. By demonstrating proactive measures to protect ecosystems, developers can strengthen public trust and facilitate greater social acceptance, which is critical for the community’s SLO wind-farm installations. Based on the above discussion, it is hypothesized that:

H₂: Perceived uncertainty associated with the regulatory environment reduces a community’s willingness to grant SLO for new wind-farm developments.

Local Cultural Norms and Values

Wind power projects are embedded within the social and cultural contexts of their locations, and their success depends on securing SLO (Velasco-Herrejón et al., 2024). Cross-cultural factors influence an innovation’s compatibility with the values, beliefs and past experiences of individuals within a social system (Rogers, 2003, p. 15). As such, wind energy project acceptance can vary significantly depending on local community values and norms. A critical consideration is how new RETs, such as wind projects, interact with the historical and cultural settings of a location (Diesendorf, 2005).

Cultural dimensions, impacted by social location and shaped by belief and values systems, among other factors, can influence public perceptions and acceptance of wind energy projects (Velasco-Herrejón et al., 2024). Psycho-social factors, such as political orientation, perceived environmental impacts, environmental attitudes and place attachment, can also affect stakeholder support (Devine-Wright, 2007). Besides energy generation, wind farms in Australia provide opportunities for public education and rural tourism, enhancing community engagement and fostering broader social acceptance (Bond, 2008). These social and cultural considerations imply that securing and maintaining SLO requires understanding and integrating local values, beliefs and experiences into project planning and communication strategies.

In summary, communities are more likely to support wind projects that align with their cultural values, traditions and ways of life. Projects perceived as conflicting with these norms may face opposition and reduce SLO. Based on the above overview, it is proposed that:

H₃: Local cultural norms and values influence community acceptance of new wind-farm installations, thereby influencing SLO.

Research Methods

The survey was administered by a professional market research firm, minimizing potential researcher bias during data collection and ensuring respondent confidentiality. This study forms the third component of a larger research initiative examining community attitudes towards renewable energy developments in Australia (D’Souza & Yiridoe, 2014, 2019). The larger project consisted of three separate but interconnected parts. The third phase, reported in this article, focuses on the SLO for wind-farm projects in rural communities. Participants were selected using purposive sampling, targeting residents and stakeholders who were directly affected by wind farms, as determined by residential location. Ultimately, a sample of 226 respondents participated in the Australia-wide survey. The study participants resided in rural areas in five states in Australia, namely New South Wales, South Australia, Tasmania, Victoria and Western Australia.

A five-point Likert-scale (ranging from 1‘strongly disagree’, to 5 ‘strongly agree’) was used to elicit responses to the following statements: (a) to what extent do your feelings on cultural values and beliefs influence any new installations of wind turbines in your area; (b) environmental regulatory frameworks influencing the new wind-farm installations; and (c) attitudes about new wind-farm installations. The outcome or dependent variable, the perceived effect of new wind-farm installation on the community, was measured in terms of the effect of the new wind-farm installation on the community on residents. This was measured on a 5-point Likert scale, where 1 = I would not care, 2 = I would oppose this new installation, 3 = I am neutral on the situation, 4 = I might agree and 5 = I would fully agree to the new wind-farm installation. Each construct was measured using a single five-point Likert item (1 = strongly disagree to 5 = strongly agree), which was treated as a continuous variable for analysis. Although Likert-scale items are ordinal, research indicates that parametric methods are robust to departures from interval scaling when data approximate a normal distribution (Carifio & Perla, 2008; Norman, 2010).

A pilot survey with 20 participants residing in locations relevant to the focus of this study demonstrated that the survey instrument was clear, relevant and reliable. Multiple linear regression (MLR) using SPSS version 29 was used to analyse the data. The econometric analysis investigated the significant determinants of predictors of the SLO for new wind-farm installations, including measurement constructs for: community attitudes, the regulatory environment and local cultural values and beliefs on the dependent variable. This approach is appropriate because it allows for the evaluation of both the individual (unique) and collective effects of multiple predictors on a continuous outcome variable.

MLR also allows for evaluating the relative strength and direction of each predictor, while controlling for the influence of other factors (Tabachnick & Fidell, 2001). This is particularly important when investigating SLO, where factors such as attitudes, regulations and cultural norms are interrelated and may jointly influence community acceptance. By using MLR, the study can determine which factors have the most significant impact on SLO while accounting for potential confounding effects. Furthermore, MLR is suitable when the aim is to test theoretically derived hypotheses about causal relationships among variables, as it provides estimates of the magnitude and statistical significance of each predictor. The regression methods used in this study allowed for empirically testing the conceptual model grounded in social systems and social licence frameworks. Diagnostic tests (i.e. multicollinearity and normality) were conducted to ensure that the assumptions of MLR were satisfied, thereby enhancing the robustness and validity of the results.

Findings

Normality was assessed using the Shapiro–Wilk test, histogram and normal P–P plot. The P–P plot showed that data points closely followed the diagonal line, indicating that the normality assumption was not violated. The normal P–P plot of regression standardized residuals revealed slight deviations from the diagonal line, particularly at the tails (Figure 1). This suggests some departure from normality in the residuals. However, given that regression analysis is robust to moderate deviations from normality, it was reasoned that this deviation is unlikely to substantially affect the validity of the model estimates (Hair et al., 2017).

Figure 1.

Normal P-P Plot of Regression Standardized Residual.

Survey Sample Characteristics

Important demographic characteristics of the survey participants are summarized in Table 1. The majority of participants (58.5%) were in the age category of 18–54 years, indicating that survey responses were obtained primarily from people who are potentially likely to be economically active and socially engaged members of their communities. The age distribution suggests that the sample is largely made up of individuals likely to have direct or indirect exposure to discussions and decisions regarding renewable energy developments.

Table 1.

Demographic Characteristics of Survey Respondents.

Item	Count (and Percentage)
Age categories
18–34	46 (20.4)
35–44	37 (16.4)
45–54	49 (21.7)
55–59	27 (11.9)
60–64	26 (11.5)
65+	41 (18.1)
Total	226 (100)
Education
Year 11	27 (11.9)
Year 12	39 (17.3)
Trade certificate or diploma	67 (29.6)
University degree	57 (25.2)
Postgraduate degree or higher	23 (10.2)
Other (please specify)	13 (5.8)
Total	226 (100)
Occupation
Full time	70 (31)
Part-time/Casual	47 (20.8)
Self-employed	13 (5.8)
Retired	55 (24.3)
Unemployed	8 (3.5)
Home duties	19 (8.4)
Students	10 (4.4)
Volunteer	2 (0.9)
Other	2 (0.9)
Total	226 (100)
Annual Income bracket (before tax)
Less than $20,000	23 (10.2)
$20,000–$49,999	68 (30.1)
$50,000–$79,999	64 (28.3)
$80,000+	71 (31.4)
Total	226
Gender
Male	82 (36.2)
Female	143 (63.3)
Other	1 (0.5)
Total	226

In terms of educational attainment, a relatively high proportion of respondents reported holding either a trade qualification (30%) or a university degree (25%), reflecting a generally well-educated sample. This educational profile is important as higher education levels are often associated with greater awareness of environmental issues and more informed attitudes towards RETs. The majority of participants reported having full-time employment (31%), compared with 3.5% being unemployed. In addition, about 6% were self-employed. The employment profile suggests a predominantly economically working population. This profile has the potential to influence perceptions about wind energy projects, as financial security can influence how individuals evaluate potential community and environmental benefits.

Annual household income levels varied across respondents, with a significant proportion (30%) earning between AUS$20,000 and AUS$49,000 annually (before tax), and another 28.3% reporting annual income (before tax) between AUS$50,000 and AUS$79,000. This household income variation indicates a diverse socio-economic composition within the sample studied, providing a balanced representation of middle-income earners who are likely to weigh both economic and environmental considerations when assessing community projects. Gender distribution showed a higher representation of female participants compared to males. This gender imbalance is not uncommon in community-based surveys, as women are often more engaged in local environmental and social issues. The higher participation of adult women may also reflect a greater interest in sustainability and community well-being, which are central to the concept of SLO.

In summary, the demographic characteristics of the survey sample reflect socially and economically active study participants with moderate to high levels of education and income, providing a suitable basis for examining perceptions of wind energy development and the factors influencing SLO.

Factors Influencing SLO

Results of the regression analysis of significant determinants of factors which influence SLO are reported in Table 2. The R² statistic indicates that about 41% of the variance in community support for the new wind-farm installation can be explained by the predictors included in the model. This suggests that the three independent variables of interest collectively account for a considerable portion of the variation in how communities perceive or respond to the establishment of a new wind farm, while the remaining 59% of the variance is attributable to other factors not captured in the model. In the multiple regression model, the ANOVA results demonstrate that the model was statistically significant, F-statistic (3, 222) = 15.271, p < .001, indicating that the predictors meaningfully explain variation in community responses to new wind-farm installations.

Table 2.

Regression Analysis.

Model		Unstandardized Coefficients		Std Coefficients	t	Sig.	95.0% Confidence Interval for B		Collinearity Statistics
Model		B	Std. Error	Beta	t	Sig.	Lower Bound	Upper Bound	Tolerance	VIF
1	(Constant)	2.269	0.366		6.206	0.001	1.549	2.990
	Attitudes	0.377	0.071	0.345	5.352	0.001	0.239	0.516	0.897	1.114
	Regulatory env	−0.174	0.083	−0.134	−2.089	0.038	−0.337	−0.010	0.907	1.103
	Cultural beliefs	0.040	0.070	0.036	0.570	0.569	−0.098	0.178	0.941	1.062

Tests for multicollinearity indicated no concern, with tolerance values well above the acceptable threshold (TOL less than 0.10) and corresponding VIF values above 10. This suggests that the predictors were largely independent and did not exhibit multicollinearity problems. Mahalanobis distance values were examined to identify potential multivariate outliers. Four cases exceeded a distance of 16.27 in a sample of 226 participants. However, these values were within the acceptable χ² threshold for the number of predictors and sensitivity analyses showed no substantial change in results when these cases were excluded. Therefore, all cases were retained for subsequent analyses (Tabachnick & Fidell, 2001). Cook’s distance values were examined to assess the influence of individual cases on the regression model. All values were well below the recommended threshold (maximum Cook’s D = 0.05 < 1), indicating that no cases exerted undue influence on the model estimates (Tabachnick & Fidell, 2001).

Social Licence to Operate

The findings indicate that positive attitudes about wind energy influence the SLO for new wind-farm installations (H₁) (β = 0.345, significant at p < .001). This suggests that residents and community members with favourable views about wind energy and RETs are more likely to support and legitimize the establishment of new wind farms in their neighbourhoods. Positive attitudes contribute to greater trust, perceived benefits and acceptance, which in turn strengthen a project’s SLO.

Perceived uncertainty within the regulatory environment reduces a community’s willingness to grant an SLO for new wind-farm developments (H₂). This suggests that the regulatory environment has a significant negative effect on the community’s SLO (β = −0.134, p < .03). This suggests that stricter or poorly communicated regulatory processes may reduce community support for new wind-farm installations, highlighting the need for transparent, inclusive and locally responsive governance.

Although cultural values and beliefs are theoretically expected to positively influence community acceptance of new wind-farm installations and support the SLO, the effect in this study was not statistically significant. This suggests that, within this sample, cultural values and beliefs did not have a measurable impact on community support for new wind-farm projects (H₃).

Discussion and Conclusions

The findings of the study are discussed in relation to the research objectives and hypotheses. The discussion highlights the policy and practitioner implications of the findings and areas where targeted interventions can enhance community trust, improve communication strategies and strengthen the SLO for future wind energy initiatives.

The analysis indicates that the relationship hypothesized in H₁ was significant, consistent with previous literature, which suggests that public acceptance of wind power largely stems from positive attitudes towards its broader environmental benefits, such as reducing carbon emissions and promoting sustainability (Hall, 2014). Similarly, studies suggest that attitudes and local acceptance of wind farms are generally positive across all three development phases, that is, high in the initial stage, lower during planning and construction and increasing again once the facility is operational (Wolsink, 2007). This pattern reflects the dynamic nature of the SLO, where community support fluctuates depending on perceived benefits, trust and engagement throughout the project lifecycle. Positive attitudes, particularly related to the operational phase, reinforce the SLO by demonstrating renewed community approval and confidence in the project’s long-term environmental and social value. Attitudes towards wind energy projects and other RETs are influenced by multiple factors, including perceived costs, risks and benefits, as well as emotional responses to the technology. In addition, levels of trust, perceptions of procedural fairness in decision-making and the perceived fairness of benefit distribution all influence public acceptance and support (Ellis & Ferraro, 2016).

The findings from this study indicate a positive and significant relationship between community attitudes and the SLO for new wind-farm developments. Attitudes towards wind energy projects and other RETs are influenced by factors such as perceived costs, risks and benefits, as well as emotional responses to the technology. Moreover, trust, procedural fairness in decision-making and the perceived fairness of benefit distribution play crucial roles in shaping these attitudes (Ellis & Ferraro, 2016). Residents and communities who perceive wind projects as fair, transparent and beneficial tend to have stronger positive attitudes towards such projects, thereby enhancing the SLO. This finding reinforces the view that favourable community perceptions and fair engagement practices are essential to sustaining long-term acceptance and support for renewable energy initiatives.

The findings also indicate that perceived uncertainty associated with the regulatory environment negatively influences the community’s willingness to grant a SLO for new wind-farm installations (β = −0.138, p < .03) (H₂). This finding is consistent with Hall (2014), who concluded that regulatory environments that lack clarity or inclusivity heighten public concern and erode trust in both developers and governing institutions, thereby weakening the SLO. Greater regulatory uncertainty, perceived lack of transparency or overly complex approval processes can undermine community trust and confidence in wind energy projects (Corscadden et al., 2012). When regulations are viewed as inconsistent, inaccessible or driven by external interests rather than community input, residents may feel excluded from the decision-making process. Such perceptions can reduce procedural fairness and legitimacy, the two core components of the SLO. Consequently, even if the project offers potential environmental or economic benefits, the absence of clear, predictable and participatory regulatory mechanisms may lead to resistance or hesitation in granting social approval. The results suggest that enhancing the certainty of the regulatory environment for wind energy is important to encourage innovation (Ellis & Ferraro, 2016).

Although local cultural values and norms were not statistically significant, consideration of these factors offers important insights into the dynamics of community acceptance (H₃). Cultural values and practices influence attitudes towards development projects. In addition, other factors such as perceived environmental benefits, trust in developers, fairness of decision-making and risk–benefit perceptions, may play more decisive roles in determining social approval for wind energy projects. This does not imply that cultural factors are unimportant; rather, in the context of renewable energy infrastructure, communities may prioritize tangible outcomes and procedural transparency over alignment with local cultural norms. Developers may regard this as an indication that proactive engagement, clear communication of benefits and fair processes are needed as elements of effective strategies for securing the SLO rather than attempting to address cultural expectations alone.

Bidwell (2013) reported that community members’ support for wind energy development is less dependent on environmental or cultural values and more closely tied to underlying values related to economic and social outcomes. Specifically, community acceptance seems to hinge on the belief that commercial wind farms can provide tangible economic benefits, such as local employment and infrastructure development. These beliefs are reinforced by altruistic values, reflecting concern for the broader community and are diminished by conservative values emphasizing traditionalism and resistance to change. Bidwell (2013) suggested that opposition to commercial wind energy projects may be more accurately conceptualized as grounded in general conservatism rather than in a local environmental ethic. Consequently, while cultural values in the narrow sense did not directly predict SLO, the findings highlight the nuanced ways in which broader social and economic value orientations influence community responses to wind energy projects, offering a richer understanding of the factors underlying both support and opposition.

Limitations and Future Research

Further research is needed to better understand public knowledge and perceptions of the benefits associated with wind farms, as well as to investigate whether shifting individual beliefs and cultural values could influence overall acceptance (Stewart et al., 2021). Findings from studies for other countries about the effects of public opinion and cultural values on renewable energy projects are not entirely consistent with the patterns observed in Australia. While opinion surveys often report generally positive cultural values towards wind farms, this has not necessarily translated into a corresponding increase in the number of wind projects. Moreover, the extent to which negative opinions or concerns impact the development and approval of wind farms remains unclear.

A key limitation in establishing and maintaining SLO lies in managing uncertainty, which was beyond the scope of this research, and can be considered in future research. Another limitation of this study is the use of MLR, which assumes linear relationships, normality of residuals and independence among variables. While the analysis identifies associations between predictors and the SLO, it does not establish causation (Tabachnick & Fidell, 2001). Additionally, MLR may not capture complex interactions or non-linear effects, potentially underestimating the influence of factors such as cultural values. The hypotheses can be examined further, and the findings can be validated in larger studies.

Theoretical and Practical Implications

The results of this study provide both theoretical and practical insights into factors which influence the SLO for new wind-farm installations. Theoretically, the findings indicate that while community attitudes and the regulatory environment significantly influence SLO, local cultural values and beliefs were not significant predictors. This challenges the commonly held assumption in SLO literature that culture is a universal determinant of community acceptance. Instead, the findings of this article suggest that the influence of cultural factors may be context-dependent, and that influence varies according to the type of technology being considered, perceived risks and regulatory conditions. By highlighting the primacy of attitudes and regulatory trust over cultural norms in this context, the study refines SLO theory, emphasizing the need for models that account for situational moderators rather than assuming uniform cultural effects across communities.

From a practical standpoint, these findings offer guidance for policymakers, developers and community engagement practitioners. Given the strong effect of the regulatory environment, ensuring transparent, consistent and trustworthy regulatory processes is essential to fostering community acceptance. Initiatives that enhance positive attitudes towards wind energy, such as educational campaigns, participatory engagement and highlighting local benefits, can further strengthen the SLO. Conversely, cultural values were not statistically significant, which suggests that extensive cultural tailoring of engagement strategies may not be necessary in similar contexts, allowing resources to be allocated more effectively towards regulatory communication and attitude-shaping interventions. Overall, the study formalizes the importance of strategic focus on regulatory trust and community perceptions as primary levers for obtaining and maintaining SLO for innovative energy projects.

Footnotes

Acknowledgements

The authors thank the participants in this research for sharing their insights and perspectives.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Ethics Approval

This research received ethics approval from La Trobe University, Ethics number HEC 35/13R.

Funding

The authors received no financial support for the research, authorship and/or publication of this article.

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