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Russell-Bennett, Rebekah, Mulcahy, Rory, Little, Jo, & Swinton, Tim(2018)Money or mind? What matters most in influencing low-income earners tobe energy efficient?Journal of Social Marketing, 8(1), pp. 2-23.

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2

Money or Mind? What matters most in influencing low-income earners to be energy

efficient?

To Cite: Russell-Bennett, R., Mulcahy, R., Little, J. and Swinton, T., (2018) Money or Mind? What matters most in influencing low-income earners to be energy efficient? Journal of Social Marketing, Vol 8(1): 2 – 23

Rebekah Russell-Bennett

School of Advertising, Marketing and Public Relations

Queensland University of Technology

Brisbane, Queensland

Australia

Rory Mulcahy

School of Business

University of Sunshine Coast,

Sippy Downs, Queensland

Australia

Jo-Anne Little

Marketing Program Manager

Reduce Your Juice

CitySmart

Australia

Tim Swinton

Project Manager

Reduce Your Juice

CitySmart

Australia

3

Rebekah Russell-Bennett is a professor in the QUT Business School and is the immediate past president of the Australian Association of Social Marketing. Rebekah undertakes research in social marketing with a technology or services focus. Rebekah has published more than 150 peer-reviewed articles and is considered an international leader in the field of social marketing. She is also the co-editor of the Journal of Services Marketing, an A ranked journal in the ABDC list. Rory Mulcahy is a lecturer of marketing at the University of Sunshine Coast. Rory just recently completed his PhD in 2015 and has published articles and conference papers in the Journal of Social Marketing, ANZMAC, the World Social Marketing Conference and International Social Marketing Conference. His research interest include serious games, digital marketing and the micro-celebrity endorsement. Jo-Anne Little is the Marketing Project Manager for the Reduce Your Juice project at CitySmart. She is a marketing professional with over 15 year’s industry experience across a variety of brands and organisations. Specialising in digital and social marketing, she has an interest in the application of digital marketing and gamification techniques for social good.

Tim Swinton is the Commercial Projects Manager at CitySmart. He has delivered a range of innovative energy efficiency programs producing tangible environmental, social and commercial outcomes across the residential and business sectors. Tim is a graduate of the QUT Business School and completed a Graduate Certificate in Built Environment and Engineering.

Acknowledgement: This Activity has received funding from the Australian Government. The views expressed herein are not necessarily the views of the Commonwealth of Australia, and the Commonwealth does not accept responsibility for any information or advice contained

herein

Money or mind? What matters most in influencing Australian young adult low-income

earners to be energy efficient?

Abstract

Purpose of the study: Designing a social marketing intervention for Australian young adult

low-income earners requires an understanding of the key motivations. As part of the Low-

Income Earner Energy Efficiency Program (LIEEP), this study investigates the key factors

that influence energy behaviours amongst Australian young adult low-income earners as part

of the Reduce Your Juice social marketing program. We also investigate the effect of gender.

Method: An online survey of 753 low-income renters was conducted using validated

measures. The data were analysed using structural equation modelling.

4

Findings: The two factors that had the highest influence on intentions for energy saving

behaviours were the ‘mind’ factor of self-efficacy and ‘money’ factor of price concern.

There were gender differences in the effect of bill control and price concern on intentions for

different energy efficiency behaviours.

Practical implications: This study provides guidance on the key factors to emphasise when

designing an energy efficiency program for Australian young adult low-income earners.

Social implications: This study provides evidence for different motivations amongst

Australian young adult low-income earners for energy efficiency programs and that a ‘one-

size-fits-all’ approach may not be effective.

Originality/Value: While there is high interest in the public sector for motivating Australian

young adult low-income earners to change their energy behaviours little is known about the

key factors that motivate intentions to engage in these behaviours.

5

Introduction

Social marketing is continually finding new behaviours and market segments where

behaviour change needs to be achieved. In this article we investigate electricity saving in

Australian young adult low-income earners and the factors which influence their electricity

saving behaviour. There have been numerous electricity efficiency programs in Australia to

stimulate a reduction in usage at both the upstream and downstream levels. Further reductions

are necessary if Australians are to live more sustainably (Council of Australian Governments,

2010), thus indicating that past programs have not achieved the level of reduction desired.

In the past social marketing has investigated vulnerable or hard-to-reach consumers

(Gordon et al., 2006) and more recently there have been calls to investigate low-income

earners (Hamilton and Catterall, 2005; Hamilton, 2012). Research shows low-income earners

are often at risk in regard to poor health outcomes and diminished lifestyles (MacAskill et al.,

2002; Scott and Higgins, 2012). One area social marketers can provide assistance to low-

income earners is in the management of electricity consumption. Research into the ability of

social marketing to assist Australian young adult low-income earners is in its infancy, with

only one empirical study investigating the customer value of electricity saving behaviours for

older consumers (60+ years) (Butler et al., 2016). Therefore, there is an opportunity to gain

greater insight into how social marketers can encourage Australian young adult low-income

earners to engage in electricity saving behaviours.

The current energy saving behaviour literature draws predominately from the theory

of planned behaviour (TPB), both explicitly and implicitly (Gadenne et al., 2011; Wang et

al., 2011). However, many of these studies assume energy saving behaviour occurs as a result

of consumers’ environmental concerns or preference for environmental conservation

(Murtagh et al., 2013). This limits their capacity to reflect non-attitudinal motivations, for

instance financial savings (Butler et al., 2016) and temperature comfort (Huebner et al.,

2013). However, the research that has used the TPB ignores other key factors identified in the

energy literature that motivate consumers. Furthermore, research shows males and females

are motivated to conserve energy by different factors (Cotton et al., 2015); however, social

marketers are yet to understand how this applies to a young adult low-income market

segment. As such, this research examines an extended TPB model and draws on both the

energy and psychology literature to include attitudinal (mind) and financial (money) factors

which may explain Australian young adult low-income earners’ energy saving behaviours,

and the gender differences which may exist.

6

This research contributes to the social marketing literature in three ways: first, we test

an extended TPB model; second, we contribute to the social marketing and energy literature

by testing narrower operationalisations of electricity saving attitudes and behavioural

intentions, including switch (turning light switches and electronic devices off at the wall),

wash (using a clothes rack rather than a dryer) and cool (using temperature controlling

devices to an optimal setting); and third, as this study specifically focuses on Australian

young adult low-income earners, we extend social marketers’ understanding of this market

segment. The paper is organised as follows. First, a brief discussion of low-income earners is

presented. A review of extant literature on energy saving and related behaviours is then

presented, along with the hypotheses to be tested. The research methodology is then

described, followed by the presentation of the results. Finally, the implications of the research

are discussed.

Low-income earners

Low-income earners have previously been neglected by marketers (Hamilton and Catterall,

2005; Hamilton, 2012). Scholars argue this is based upon the misconceptions of low-income

earners as “living miserable lives” and being less profitable (Hamilton, 2012; Hamilton and

Catterall, 2005; Paicentini and Hamilton, 2013). Recent research challenges previous

perceptions of low-income earners. For example, studies have found that low-income earners

can be equally driven to possess the material trappings of success (Gbadamosi, 2009; Soman

and Cheema, 2011). This could be attributed to low-income earners wishing to avoid the

stigmatisation and visibility of belonging to this socio-economic group. Furthermore, more

recently there has been an increasing recognition of the importance of understanding the

psychology of the poor (Schilbach et al., 2016) and marketing to better the lives of those who

live closer to the ‘bottom of the pyramid’ (Paicentini and Hamilton, 2013; Blocker et al.,

2013).

Social marketing is interested in low-income earners from a different perspective to

commercial marketers in that the goal is to improve quality of life rather than generate profit

(Hampson et al., 2009, MacAskill et al., 2002). Current social marketing research on low-

income earners has investigated behaviours such as smoking (MacAskill et al., 2002),

encouraging consumption of fruit and vegetables (Hampson et al., 2009) and, more recently,

electricity efficiency in older low-income earners (Butler et al., 2016). This study aims to

further the understanding of social marketing’s ability to assist low-income earners,

particularly those who are young adults, in the context of electricity saving behaviours. It is

7

important to understand what influences Australian young adult low-income earners to

perform electricity saving behaviours, as it this encourages behaviours that can form habits

and carried through into older adulthood. Young adults are also the parents of the future

therefore will be influential in socialising their children about electricity use. Thus, by

gaining this understanding, this research begins to address calls in the literature to better

understand low-income earners and how social marketers can assist them in saving electricity

(Butler et al., 2016).

There are difficulties in researching low-income earners, with one of the key

complications being in creating a generalisable definition of what constitutes an individual or

group being classified as low-income. Laderchi and colleagues (2003) and Blocker and

colleagues (2013) point out that whilst there is world-wide agreement on poverty reduction

there is little agreement on the definition. Laderchi and colleagues (2003) go further,

outlining four approaches to classifying “poor” or “low-income”: monetary, capability, social

exclusion and participatory. For the purposes of this research we adopt the monetary

approach, which identifies poverty or low-income based upon shortfalls in consumption

and/or income based on a standard of income. There again is minimal agreement in the

literature on a standard monetary threshold, as standard incomes differ across countries

(UNESCO, 2016). Therefore, given this research is Australian, we adopt the income

thresholds relevant to that country. In Australia the bottom two quintiles of income earners

are considered low-income and the monetary income threshold for this is AU$41,5001 per

annum individual income (Australian Bureau of Statistics, 2013). Thus, this monetary income

threshold was additionally used as eligibility criteria to participate in Reduce Your Juice and

this study.

What influences electricity saving behaviour?

Studies of consumers’ intentions to save energy (Gadenne et al., 2011; Wang, Yin and

Zhang, 2011) or conserve resources (Chan and Bishop, 2013; Fielding et al., 2008; Greaves

et al., 2013) typically employ models such as the TPB. Studies, such as Greaves and

colleagues (2013), have shown the TPB to be a strong predictor of office workers behavioural

intentions for workplace environmental behaviours, with variances of over 50% being

explained. Whilst the TPB has been proven to be a useful model to research energy saving

1 This is the equivalent of US$30,452.00 and £25,844

8

behaviour, and other behaviours related to this research, key limitations in previous research

exist.

One limitation is that the majority of energy studies take an environmental

conservation perspective and study samples outside of Australia such as China (Wang, Yin

and Zhang, 2011) or older Australian populations (Gadenne et al., 2011). These studies take

the viewpoint that consumers’ environmental concerns will drive their intentions and

behaviour to conserve energy. For instance, Gadenne and colleagues (2011) examine energy

saving behaviours of Australian consumers aged 35 years and older of a ‘green’ business and

operationalise TPB factors using environmental conservation measures. Accordingly,

scholars have critiqued the findings of pro-environmental attitude studies, suggesting the

results may be a result of pro-environmental bias, whereby the participant wishes to be seen

as more environmentally conscious (Murtagh et al., 2013).

Another limitation in current energy saving research appears to be the additional

missing factors outside of the TPB which may influence consumers’ electricity behaviours

and their limited focus on young adult low-income earners. For example, Huebner and

colleagues (2013) and Shove and colleagues (2014) argue that domestic electricity

consumption and electricity saving is influenced by temperature comfort needs. However,

their studies are limited in the context of this research, particularly Huebner and colleagues

(2013) whose study had a mean age of 64 years for participants. Other studies also argue

financial saving or over-expenditure as key drivers of energy use and saving (Barr, et al.,

2005), particularly for the elderly (Butler et al., 2016). It therefore appears current energy

saving studies may have overemphasised the environmental concern of consumers, as well as

missed other additional factors which may drive consumers’ energy saving behaviours.

Furthermore, the majority of studies have focused on older populations or broader sample

demographics, which makes it difficult to determine their findings applicability to social

marketing campaigns such as Reduce Your Juice targeted at Australian young adult low-

income earners. We therefore extend upon previous research by using the TPB and other

factors identified in the literature as being drivers of energy saving behaviour to investigate

Australian young adult low-income earners’ electricity saving behaviours. For this research

we group these factors in the categories of financial (money) and attitudinal (mind).

9

Financial factors

Financial or economic factors such as monetary savings or current financial conditions have

been shown to be good predictors of electricity usage behaviours (Barr et al., 2005; Seligman

et al., 1979) and important to low-income earners (Butler et al., 2016). For example, a study

by Butler and colleagues (2016) found economic value to be the most important driver for

electricity efficient behaviours in Australian older low-income earners. This is consistent with

other research, which finds that individuals under conditions of scarcity will attempt to use

trade-offs to benefit their welfare (Shah et al., 2015; Roux et al., 2015). Research shows this

is particularly the case for low-income earners, who focus their budgets on limiting the risks

of overspending (Homburg et al., 2010). Given the focus of this study, saving a scarce

resource such as financial resources may also extend to Australian young adult low-income

earners’ electricity saving behaviours. For this study we conceptualise financial factors to

consist of two factors: price concern and bill control. Price concern refers to an individual’s

level of worry that they will struggle to pay their electricity bill and that efforts to save

electricity will result in a considerable financial saving (Seligman et al., 1979). Bill control

refers to the level of influence an individual perceives they have over reducing their bill in

comparison to other entities such as an electricity provider (Schindler, 1998). For this study

we hypothesise the following:

H1. Australian young adult low-income earners’ price concern will be positively

associated with intentions for electricity saving behaviours.

H2. Australian young adult low-income earners’ bill control will be positively

associated with intentions for electricity saving behaviours.

Attitudinal factors

The TPB is a useful attitudinal framework to analyse individuals’ behaviour; however, it

often needs extension to account for additional factors relevant to the context under

investigation (Chan and Bishop, 2013). For this research we include the additional factor of

temperature comfort, along with the TPB factors of self-efficacy (also referred to as perceived

behavioural control), attitude and social norms (also referred to as subjective norms).

Temperature comfort refers to the level of perceived temperature comfort an individual

desires (Becker et al., 1981). Research reports temperature comfort as possessing high

explanatory power for energy (including electricity) consumption, particularly in countries

with cold climates (Hueber et al., 2013). This means that when consumers place high

10

importance on temperature comfort they are more likely to use electricity to maintain this

comfort e.g. keeping the air conditioning at lower temperatures to stay cool or setting the heat

high to stay warm. Studies also suggest a cold-to-hot empathy gap, whereby individuals often

underestimate or overestimate the impact of their desired state on their own future behaviour

(Loewenstein, 2005). For instance, Loewenstein (2005) comments that people often

overestimate their own behaviour and preferences when in a “hot” state. When applied to the

context of this research a similar overestimation of desired temperature preferences may take

place, whereby individuals overuse temperature-controlling appliances to reach their desired

temperature state. Therefore, based upon the prior research in electricity and the cold-to-hot

empathy gap it is hypothesised:

H3. Australian young adult low-income earners’ need for temperature comfort will

be negatively associated with intentions for electricity saving behaviours.

Research has shown perceived behaviour control or self-efficacy – the belief an

individual has in their ability to perform a behaviour – to both directly and indirectly

influence intentions to perform behaviours (Chan and Bishop, 2013). Studies have reported

factors conceptually similar to self-efficacy, such as autonomy (Sweeney et al., 2014) and

functional value (Butler et al., 2016), to be important for electricity saving. Research also

shows the higher perceived levels of ease in the task of saving electricity, the more likely

individuals are to perform electricity saving behaviours (Butler et al., 2016; Thøgersen and

Grønhøj, 2010). Self-efficacy therefore appears to be an important factor in electricity saving

behaviours and the following is hypothesised:

H4. Australian young adult low-income earners’ self-efficacy will be positively

associated with intentions for electricity saving behaviours.

Social norms refers to the comparisons individuals make with others regarding

electricity efficiency based upon saving money and the amounts of electricity consumed

(Dwyer et al., 2015). Social norms has been well established as a key factor which drives

conservation behaviour (Goldstien et al., 2008), particularly in electricity (Dwyer et al.,

2015; Gadenne et al., 2011). For example, findings of Dwyer and colleagues’ (2015) study

put forward that electricity conservation can be encouraged by signalling social norms to

people. Therefore, for this research we hypothesise:

H5. Low-income earners’ perceived social norms will be positively associated with

intentions for electricity saving behaviours.

11

Past empirical studies on electricity behaviour suggest attitude is a key factor which

influences behaviour (Murtagh et al., 2013). Conceptualisations and the operationalisation of

attitudes across studies vary depending on the study’s focus, which can include general pro-

environmental or green attitudes (Abrahamse and Steg, 2011; Ngo et al., 2009) and attitudes

towards electricity reduction (Murtagh et al., 2013; Gadenne et al., 2011). However, most

studies are yet to investigate behaviour-specific attitudes, such as attitudes towards switching

lights off which are not being used and setting temperature controlling appliances to efficient

settings. One exception is Gadenne and colleagues (2011), who measured and examined the

influence of attitudes for three workplace conservation behaviours on intentions in three

separate models. The current study, however, aims to examine general attitudes towards

saving electricity and three specific electricity saving attitudes, along with behaviours

relevant to the context of this study, in a singular model. This is because Reduce Your Juice

aimed to encourage Australian young adult low-income earners to perform all three specific

electricity saving behaviours and therefore by examining general attitudes and specific

attitudes to electricity saving behaviours a better representation of what influences intentions

to saving electricity can be achieved. Furthermore, general attitudes to saving electricity was

chosen as this was a key measure used as part of the LIEEP program. The three electricity

saving behaviours chosen were cooling (keeping air-conditioner to the optimal temperature of

24 degrees), washing (using a clothes line rather than dryer) and switches (turning appliances

off at the power switch when not being used), based upon a review of electricity saving

behaviours Australian young adult low-income earners would be capable of modifying

(www.reduceyourjuice.com.au). The following hypothesis will therefore be tested in this

study:

H6. Australian young adult low-income earners’ attitudes will be positively

associated with intentions for electricity saving behaviours.

Gender differences

Gender differences have been noted in the electricity literature as an area which merits

attention (Paço and Varejão, 2010). Recent studies have begun to address these calls, in

particular Cotton and colleagues (2015) report differences between collective actions and

barriers to electricity-saving behaviour for males and females. Huang’s (2015) study also

finds gender differences, with male-headed households found to be more likely to consume

higher volumes of electricity than female-headed households. Another study by Nisiforou and

12

colleagues (2012) notes gender differences in energy usage and habits, with females more

dissatisfied with room temperature than males.

Studies outside of electricity saving behaviour also present findings relevant to

potential gender differences which could be found in this study. In the context of

environmental and sustainable behaviours females have been shown to have higher intentions

to perform behaviours than males (Bhatnagar and McKay-Nesbitt, 2016; Brough et al.,

2016). More specifically, females have been found to have higher environmental concerns

and reactions (Bhatngar and McKay-Nesbitt, 2016; Laroche et al., 2001) and are more likely

to embrace sustainable behaviours than men due to their feminine nature (Brough et al.,

2016). Other research finds men are more likely to take responsibility for managing the utility

bills in the division of labour within the household (Hargreaves et al., 2010). Therefore, the

following hypotheses will be investigated:

H7a. The influence of financial factors for electricity saving intentions will be

significantly different between male and female Australian young adult low-income

earners.

H7b. The influence of attitudinal factors for electricity saving intentions will be

significantly different between male and female Australian young adult low-income

earners.

Method

In order to investigate the factors that influence Australian young adult (18–35 years) low-

income earners’ electricity behaviour intentions an online survey was conducted with 753

low-income renters. Potential respondents were identified via a number of methods, including

low-income earner community services, an online consumer panel and referrals. To be

eligible to participate as an Australian young adult low-income earner participants were

required to be aged 18–35 years and report their weekly income in a screening question (only

those who earned under AU$41,500, the threshold in Australia, were eligible to participate).

This question was also used to screen participants in the related social marketing program,

PROGRAM X.

13

Sample

Despite seeking a gender balance in responses the sample had a skew towards females

(73.6%). The sample was evenly split for highest level of education completed, with 30.5%

reporting TAFE (technical and further education training) as their highest level, followed by

University (27.2%) and High School Year 12 (26.0%). The largest percentage (17.1%) of the

sample earned between AU$400–$599 per week and, on average, participants had four

people in their household, with the majority living with their partner and children (33.3%).

The descriptive results of the sample provided some interesting insights into electronic goods

ownership of low-income earners, particularly those of an entertainment or communication

nature. In terms of computer ownership, 49.2% had two or more laptops. A large majority

(74.9%) had a tablet in their household (30.1% had two or more), which is higher than the

Brisbane average of 73% (Colmar Brunton and Energex, 2013). Interestingly, 78.2% had two

or more smartphones in their house, which is comparatively higher than the Brisbane average

of 76% (Colmar Brunton and Energex, 2013). The majority (76.9%) had at least one gaming

console in their household, which is slightly above the Brisbane average of 76%.

Measures

Previously validated items were adapted for the context of this study. The measures for

financial factors were price concern (Seligman et al., 1979) and bill control (Schindler,

1998), with the measures for psychological factors being temperature comfort (Becker et al.,

1981) and self-efficacy (Schwarzer and Jerusalem, 1995). We measured attitudes at both the

general and specific level to facilitate a comparison of effectiveness in predicting intentions.

General attitudes to electricity were sourced from the Commonwealth Scientific and

Industrial Research Organisation (CSIRO), the Australian Government’s corporate research

entity. The items for general attitudes were generated by the CSIRO and used in this program

along with other sister programs to use as a baseline for evaluating the comparative

effectiveness of programs. On the other hand, social norms and attitudes to the behaviours of

cool, wash and switch were adapted from Tonglet and colleagues (2004). Behavioural

intention measures often examine intentions to perform the behaviour as well as the intention

to tell others (Zainuddin et al., 2013). In this study two items were adapted to measure

participants’ intentions to perform as well as discuss cool, wash and switch. All scales were

measured using 5 point likert scales, with the exception of bill control which was measured

using a semantic differential scale. The final items are provided in the Appendix.

14

Analysis

The analysis technique used in this paper to test the hypothesised relationships was structural

equation modelling (SEM). SEM was deemed an appropriate analysis technique as it has

shown to be a powerful technique to investigate the influence of multiple independent

variables onto a singular dependent variable (Hair et al., 2006) and is useful in social

marketing research (Parkinson et al., 2012). To test the differences between males and

females we conducted a multi-group analysis of structural invariance, following the

procedures of Dagger and O’Brien (2010). This method was chosen because multi-group

SEM is a suitable approach for testing invariance. First, the unconstrained baseline model

was examined (CMIN/DF=2.75 CFI=.93 RMSEA=.048), which demonstrated good fit. We

then tested for invariance by comparing the structural weights between males and females.

Results

The descriptive statistics are summarised in Table 1. The results indicate low levels of

willingness to sacrifice temperature comfort for electricity efficiency (M=3.05) and moderate

levels of price concern (M=3.85) and self-efficacy (M=3.53). Attitudes to electricity were

low (M=2.17), whereas attitudes to cool (M=4.13), switch (M=4.68) and wash (M=4.57)

were high. Intentions were also high for cool (M= 3.77), switch (M=4.22) and wash

(M=4.17). These scores indicate this sample is concerned by the price of paying for

electricity and have a high level of intention to perform behaviours which will help reduce

their electricity use. Interestingly, the general attitude to electricity efficiency was low to

moderate.

<Insert Table 1 about here>

Measurement model

Prior to testing relationships in the structural model, the validity of the items was assessed

using confirmatory factor analysis on the measurement model. The results indicate the

measurement model fitted well with the data CMIN/DF=2.46 CFI=.94 RMSEA=.04. Further,

the reliability of the items met and exceeded the recommended thresholds of .60 and Average

Variance Extracted (AVE) scores also exceeded .50 (with the exception of social norms and

intentions to wash) as recommended in the literature (Anderson and Gerbing, 1988). Further,

all factor loadings of the individual items for the constructs were significant, with loading

scores of between .62 and .91. These results demonstrate convergent reliability and validity

across constructs in the measurement model. The squared correlations between each of the

15

items were also below the AVE score, which indicates discriminant validity is present in the

data.

Structural model and hypothesis testing

After the measurement model was confirmed the structural model was tested. The structural

model produced a good fit to the data CMIN/DF=2.64 CFI=.92 RMSEA=.04. Standardised

co-efficients (B) were used to determine the direct effects of the hypothesised relationships

(see Table 2 and Figure 1). Twelve of the 19 relationships were significant in the model, with

32% of variance explained for behavioural intentions for switch and wash, and 52%

explained for cool. The results indicate bill control significantly influences intentions to

switch, supporting H1a. Price concern significantly influences intentions to switch and wash

supporting H2a and H2c. The results indicate the temperature comfort hypothesis was

supported (H3). Self-efficacy was found to be a significant predictor of intentions to cool and

wash, supporting H4b and H4c. Social norms was found to significantly influence all three

electricity saving behaviour intentions, supporting H5a, H5b and H5c. Attitudes for switch,

cool and wash were found to be significant predictors of intentions to perform those

behaviours, supporting H6b, H6c and H6d.

A competing model was also run to test general attitudes as a second-order factor with

three specific attitudes (cool, wash and switch). The structural model produced a poor fit to

the data, CMIN=3.01, CFI=.79, RMSEA=.50, and general attitudes still did not significantly

influence intentions to cool (b=.04, p=.422), wash (b=.03, p=.288) and switch (b=.01

p=.086). Three competing models were run with each of the three specific electricity

behaviours as a sole dependent variable. The structural models for each behaviour, cool

(CMIN=4.87, CFI=.640, RMSEA=.70), wash (CMIN=3.68, CFI=.736, RMSEA=.60) and

switch (CMIN=4.35, CFI=.677, RMSEA=.67), also produced poor fits to the data.

Invariance testing

The model was then tested using multi-group analysis testing for invariance between males

and females (Dagger and O’Brien, 2010) (see Table 2 and Figures 1 and 2). The analysis was

conducted for paths in the total sample model for both genders. Each path was individually

constrained and chi-square difference tests conducted. Further, if the path was significant for

only one gender it was also deemed to stronger. The relationship between bill control and

intentions for cool, price control and intentions for switch were stronger for males. Bill

control and intentions for switch, comfort and cool intentions, self-efficacy and switch and

16

wash intentions, general attitudes and switch was stronger for females. Therefore, both H7a

and H7b were partially supported.

<Insert Table 2 and Figures 1 and 2 about here>

Post-hoc testing

A series of post-hoc tests were conducted using independent sample t-tests to gain further

insight into the differences which may exist between males and females. Independent t-tests

were conducted for all of the constructs tested in the structural model (see Table 3). Of the

constructs analysed using an independent sample t-test, self-efficacy, price concern, wash

attitude and switch attitude were found to have significant differences. For self-efficacy,

males reported significantly higher levels of self-efficacy (M=3.70, SD=.59) than females

(M=3.46, SD=.69). Males also reported significantly higher levels of price concern (M=2.42,

SD=1.01) than females (M=2.10, SD=.93). In contrast, females reported significantly higher

levels of wash attitude (M=4.64, SD=.56) than males (M=4.36, SD=.77). Females also

reported significantly high levels of switch attitude (M=4.70, SD=.52) than males (M=4.63,

SD=.58).

<Insert Table 3 about here>

Discussion

The purpose of this research was to address the research question, what is the relative effect

of financial and psychological factors on electricity saving intentions in Australian young

adult low-income earners? The results show in a singular model that both mind and money

factors influence electricity use behavioural intentions; price concern and self-efficacy have

the largest number of influential relationships with behavioural intentions which contribute to

saving electricity. Finding financial factors, such as price concern, as significant predictors of

intentions to save electricity is consistent with past research in electricity (Butler et al., 2016;

Becker, 1981; Seligman et al., 1979). Likewise, past research in electricity and social

marketing has found self-efficacy to be a strong predictor of intentions (Thøgersen and

17

Grønhøj, 2010; Parkinson et al., 2012). The finding of the influence of temperature comfort is

a new finding for an extended TPB model. While this is consistent with past electricity

saving research, which has found heating appliances and temperature comfort are key drivers

of electricity consumption (Huebner et al., 2013), prior research has not investigated

temperature comfort in a hot climate where cooling is important.

This study also investigated gender differences in the influence of money factors on

electricity saving intentions. The results suggest men are influenced by bill control, self-

efficacy, social norms and attitude, whereas females are less concerned with price and more

influenced by the other factors to save electricity. Furthermore, post-hoc testing shows males

have higher levels of self-efficacy and price-concern than women. In contrast, females have

significantly higher levels of wash and switch attitude. This is consistent with past studies in

electricity which have found differences between male and female electricity saving

behaviour (Cotton et al., 2015). Furthermore, females are more likely to take part in

conservation behaviours (Bhatnagar and McKay-Nesbitt, 2016; Brough et al., 2016).

The descriptive results regarding the ownership of entertainment electrical appliances

of Australian young adult low-income earners provides a new perspective on low-income

earners. The sample had high ownership levels of non-essential goods, such as smartphones,

tablets and gaming consoles, which were comparable to the general population. These results

demonstrate that whilst Australian young adult low-income earners have smaller disposable

incomes in comparison to other socio-economic groups they are willing to spend their money

on non-essential items which increase their electricity bill.

Theoretical implications

This study highlights the value of incorporating additional financial and attitudinal factors

into a modified TPB model for understanding electricity saving behaviours. The study shows

that when considering electricity savings in a low-income context, both money and mind

factors are important. This research also contributes to social marketing’s theoretical

understanding of the Australian young adult low-income earner. Research focusing on low-

income earners has often described this group as less likely to own the same level of

appliances and material possessions as higher social classes (Hamilton, 2012). This research,

however, has found Australian young adult low-income earners can potentially have

ownership of goods equal to the general population. This was particularly the case for

entertainment or communication appliances, such as gaming consoles, smartphones and

18

tablets. This is consistent with more recent discussions about low-income earners’

consumption of goods and services in an attempt to belong to other socio-economic groups

(Ordabayeva and Chandon, 2011). Prior studies have found that a household’s economic

situation can have an inverse effect on consumption through aspiration level and social

comparison (Karlsson et al., 2004). Consequently, Australian young adult low-income

earners may be purchasing multiple electrical appliances and devices to reflect their aspired

status, leading to increased or higher levels of electricity consumption.

Another contribution of the study is the further insight into the measurement of

attitudes and behavioural intentions. While all the factors in the model significantly influence

one of the three sub-dimension behaviours of electricity saving, the significant effect of each

factor on all three differs. This finding lends further support to research (Greaves et al., 2013)

demonstrating the importance of understanding and investigating specific behaviours which

make up a larger and more complex behaviour, such as electricity saving. Further, drawing

on the results of competing attitude models, we argue that social marketers need to

investigate lower-order factors of behaviours that are specific to the context, rather than seek

relationships at higher levels.

Practical implications

The findings of this research reveal the importance of both financial and psychological

factors for influencing intentions of electricity saving behaviours and, in particular, the

gender differences in these factors. This research offers implications for social marketers by

indicating that both financial and psychological factors should be used to motivate and

influence Australian young adults to engage in electricity saving behaviours. Thus,

campaigns need to include both appeals to the mind (self-efficacy) and the monetary situation

of the household to avoid excluding consumers. The lack of relationship between general

electricity saving attitudes and intentions directs social marketers to create campaigns with

specific behaviours to be performed by consumers.

Further, this research demonstrates the complexity of electricity saving behaviours to

practising social marketers. The high predictive ability of behaviour-specific attitudes

indicates that social marketers should focus their interventions or components of

interventions on specific electricity saving behaviours, such as turning appliances off at the

wall, keeping temperature appliances to efficient settings and electricity-efficient washing

19

behaviours. As such, social marketers targeting electricity saving should ensure they

effectively increase the perceived impact and benefits of performing each of the three specific

electricity saving behaviours (Joireman et al., 2004).

Finally, Australian young adult low-income earners are very digitally-connected, with

high ownership of smartphones, tablets and gaming consoles in comparison to the general

population. Digital approaches are being investigated by social marketers in other segments,

such young adults with mental health issues (Schuster et al., 2013) and high school students

(Mulcahy et al., 2015). The findings of this research suggest that digital approaches using

games and smartphones may be an appropriate avenue to encourage the young adult low-

income segment to uptake electricity saving behaviours.

Limitations and future research directions

The current research has some limitations which will now be acknowledged, along with

opportunities for future research. The sample used within this study was skewed towards

females and limited to an Australian young adult low-income earners aged 18–35 years.

Future research studies should aim to investigate if the findings of this study are generalisable

to other market segments. For example, examining differences amongst different ages,

income, household sizes and household relationship structures (e.g. family and share

household) may provide further insight. A limitation of this study is its cross-sectional nature

and measurement of behavioural intentions as an outcome. Future research should use

longitudinal research designs and attempt to gain behavioural data, such as electricity

metering, to gain further insight and extend the findings of this research. Additional research

investigating lower-order factors which conceptualise electricity saving behaviour is also

warranted.

This study focused on three electricity saving behaviours relevant to the geographical

area of this sample, such as cooling rather than heating for temperature comfort. Furthermore,

a limitation exists in the differences in wording and measurement of general attitudes to

saving energy and the specific electricity saving attitudes. It is possible that the different

wording for the general attitude scale and specific electricity saving attitudes may explain the

non-significant influence of general attitudes on behavioural intentions. Future studies should

attempt to use a general attitude scale with more neutral wording, or similar wording to the

specific electricity saving behaviours, to examine if the findings of this study hold. Future

research of young adult low-income consumers should also attempt to gain insight into

20

background characteristics (Thøgersen and Ölander, 2006), such as their family of origin and

their ownership of electronic appliances. For example, electronic goods owned by young

adults may be hand-me-downs or gifts from family or friends, which may explain the high

ownership of multiple electrical appliances and their electricity saving behaviours. Finally,

future research may also seek to investigate if individuals use electricity for other comfort

reasons aside from temperature control. For instance, individuals may keep lights or TVs on

for security or social comfort.

21

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Appendix –Scale Items

Construct Original Scale Adapted Items

Bill Control Schindler (1998)

Is your electricity bill something you believe is in your control or out

of your control? (Very much in my control/Very much out of my

control)

Is the amount of your electricity bill due to something about you or the

electricity provider? (Very much me/Very much the electricity

provider)

Is the amount of your electricity bill something that you believe is

controllable by you or is it something you believe is controllable by

your electricity provider? (Very much controllable by me/Very much

controllable by the electricity provider)

Price Concern Seligman et al.

(1979)

Trying to save a few dollars a day by reducing electricity use is just

not worth it.

I would only save electricity if I was struggling to pay my electricity

bills.

Temperature

Comfort

Becker et al. (1981)

It is too uncomfortable to have my indoor temperature more than 24°

in the summer months.

While others might tolerate having hotter air conditioning settings in

summer, my own need for being cool is high.

It’s not worth having the house warmer in the summer just to try and

save a little money.

I would be very uncomfortable in the summer if I turned my daytime

air conditioner settings up to 24°.

Self-Efficacy Schwarzer and

Jerusalem (1995)

I can always manage my electricity use if I try hard enough.

It is easy for me to stick to my aims and accomplish my goals for

saving electricity.

I am confident that I could deal efficiently with unexpected events that

affect my electricity use.

Thanks to my resourcefulness, I know how to handle unforeseen

situations that affect my electricity use.

I can solve most electricity use problems if I invest the necessary

effort.

I can remain calm when facing difficulties about electricity use.

When I am confronted with a high electricity bill, I can usually find

several solutions.

26

Construct Original Scale Adapted Items

If I am having trouble with managing my electricity use I can usually

think of a solution.

Social Norms Tonglet et al. (2004) Most people would approve of me saving electricity.

I would feel guilty if I did not save electricity.

Saving electricity is consistent with the principles of my community.

Everybody should share the responsibility to save household

electricity.

Attitude to Energy Energy efficiency is too much hassle.

Energy efficiency means I have to live less comfortably.

My quality of life will decrease when I reduce my energy use.

Energy efficiency will restrict my freedom.

Energy efficiency is not very enjoyable.

*Attitude to Cool,

Wash & Switch Tonglet et al. (2004) Using X rather than X is bad/good.

Using X rather than X to is not useful/useful.

Using X rather than X is not sensible/sensible.

Using X rather than X is not responsible/responsible.

*Intentions to Cool,

Wash & Switch Zainuddin et al.

(2013)

I intend to use X rather than X.

I intend to recommend to someone else to use X rather than X.

Note: Replace X and X for Cool “using temperature controlling devices to an optimal setting”, for Wash “using a clothes rack rather than a dryer” and for Switch “using turning light switches and electronic devices off at the wall”.

27

Table 1: Descriptive statistics, mean, AVE scores and correlations Factor M (AVE) 1 2 3 4 5 6 7 8 9 10 11 1.Bill Control

4.48 .69 (.87)

2.Price Concerns

3.85 .54 .21** (.70)

3.Comfort 3.05 .50 .16** .44** (.79) 4.Self-efficacy

3.53 .50 .36** -.13**

.07* (.84)

5. Social Norms

3.87 .48 .08* .32** .16** .36** (.67)

6.Attitude to Electricity

2.17 .64 -.24**

-.49**

-.29**

-.24**

-.21**

(.89)

7.Attitude to Switch

4.68 .68 .15** .25** .13** .16** -.20**

.30** (.85)

8.Attitude to Cool

4.13 .69 .11** .26** .29** .17** -.26**

.27** .42** (.88)

9.Attitude to Wash

4.57 .65 .11** .26** .15** .09* -.22**

.31** .57** .47** (.89)

10.Intentions Switch

4.22 .54 .04 .25** .-.11**

.21** -.30**

.27** .36** .18** .20** (.77)

11. Intentions to Cool

3.77 .63 .09* .25** .-.32**

.25** .-30**

.23** .19** .56** .19** .41** (.60)

12. Intentions to Wash

4.17 .45 .07 .20** -.14**

.19** -.27**

.22** .16** .22** .40** .32** .34** (.70)

*Significant at 0.01 level; ** significant at 0.05 level, Cronbach Alpha’s in brackets

28

Figure 1. Structural Model Results for Full Sample

Note: Only significant results shown; Alternative models were examined; 1) with attitude to energy as a second-order factor; 2) separate models for each behaviour (switch, cool and wash), but all had significantly worse fit.

Bill Control

Price Concern

Temperature Comfort

Self-Efficacy

Attitude to Energy

Attitude to Switch

Attitude to Cool

Attitude to Wash

Intentions Switch

Intentions Cool

Intentions to Wash

R2 Intentions to Switch: .32 R2 Intentions to Cool: .52 R2 Intentions to Wash: .32

Social Norms

29

Figure 2: Male and Female Model Comparison

Bill Control

Price Concern

Temperature Comfort

Self-Efficacy

Attitude to Energy

Attitude to Switch

Attitude to Cool

Attitude to Wash

Intentions Switch

Intentions Cool

Intentions to Wash

R2 Intentions to Switch: .32 R2 Intentions to Cool: .71 R2 Intentions to Wash: .43

Social Norms

Bill Control

Price Concern

Temperature Comfort

Self-Efficacy

Attitude to Energy

Attitude to Switch

Attitude to Cool

Attitude to Wash

Intentions Switch

Intentions Cool

Intentions to Wash

R2 Intentions to Switch: .32 R2 Intentions to Cool: .47 R2 Intentions to Wash: .30

Social Norms

Males Females