Residential Consumers’ Lifestyle Energy Usage and Energy Efficiency in Selected States in Malaysia. (2023)

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Author(s): Salina Daud [1,2,3]; Wan Noordiana Wan Hanafi (corresponding author) [1,2,3,*]; Bamidele Victor Ayodele [4]; Jegatheesan Rajadurai [1,2,3]; Siti Indati Mustapa [1,2,3]; Nurul Nadiah Ahmad [1,3]; Wan Mohammad Taufik Wan Abdullah [3,5]; Siti Norhidayah Toolib [1,3]; Maryam Jamilah Asha’ari [1,2,3]; Harni Aziera Afsarizal [1,3]

Keywords; consumer lifestyle; residential; energy efficiency; energy

1. Introduction

Energy demand and consumption have been increasing rapidly over the past few decades because of the disruptive changes in energy industries and services as well as changes in people’s lifestyles around the world. The world is currently consuming about 9000 Mega Tonnes of Oil Equivalent (MTOE) energy, which has doubled in the last three decades [1]. In recent years, the residential sector in Malaysia has been responsible for 20.7% of energy consumption. The National Electrical Board (NEB) of the government works closely with electricity markets to balance the nation’s energy supply and demand. Market forecasting is used to predict future electricity demands and their distribution across power stations. Real-time estimation of the demand profile is performed throughout the day for the residential, commercial, and industrial sectors [2].

It is predicted that domestic power consumption in Malaysia will increase as a result of an increase in the possessing of appliances, an improvement in economic conditions, and a change in lifestyle [3]. The residential sector’s need for energy has skyrocketed in recent years as a result of rising demand as well as improvements in people’s quality of life, which has given rise to concerns on the part of policymakers. According to [4], consumer activities directly influence energy use (e.g., housing and private transport) and account for more than 43.0% of the total world energy use. Breaking habits can be difficult but not impossible. In fact, lifestyle changes are what is required to drive a net-zero carbon future.

It is now a new goal of household energy management to improve users’ energy habits, reduce electricity costs, and promote the efficient use of new energy equipment. To accomplish this goal, it is critical to collect energy consumption data, such as how much power is used, how long it is used, and what type of energy is used, as well as analyse users’ energy consumption patterns [5].

The behaviour of general residential customers in terms of energy use varies significantly depending on their lifestyle or how they live. As a result, electric power companies must create and offer appropriate services customised to energy user behaviour. Additionally, knowing one’s own inclination for energy consumption is useful information for customers when making decisions regarding tariff selection, purchasing household appliances, and the everyday use of household equipment.

Improving energy efficiency is important for reducing Malaysia’s energy demand, achieving sustainability goals, and improving the environment. However, monitoring energy usage in the residential sector, which is the largest energy consumer, is challenging due to the complexity of energy usage patterns. Comprehensive models are needed to study residential energy consumption effectively.

A study by Bin and Dowlatabadi [6] and Feng et al. [7] utilised the Consumer Lifestyle Approach (CLA) to understand the relationship between consumer behaviour, energy use, and CO[sub.2] emissions. However, the results from these studies were not accurate in predicting household energy consumption behaviour due to limitations in the data. Other studies that looked at household energy decision behaviours focused on income [8] and price elasticity [9] using household data.

Studies in developed countries have analysed the impact of lifestyle factors on energy demands, but there are few studies in developing countries such as Malaysia, where converging lifestyles could pose a challenge. This study aims to investigate energy efficiency behaviour based on residential consumers’ lifestyles, which include housing, mobility, consumption, diet, leisure activities, and information. The limited studies on this topic in developing countries emphasise the need for further research in this area.

2. Literature Review

2.1. Energy Efficiency

Energy efficiency is considered a cornerstone of a comprehensive energy policy. Both solutions must be developed simultaneously in order to stabilise and reduce emissions of carbon dioxide and other pollutants. Inasmuch as efficient energy consumption is crucial and impedes the growth of energy demand, increased supplies of pure energy may result in substantial reductions in the usage of fossil fuels [10].

Additionally, energy efficiency is acknowledged on a global scale as the most effective and economical means of achieving sustainable development objectives. Through an awareness campaign, building legislation, and building energy rules, the Malaysian government has been aggressive in introducing energy efficiency for buildings. The Malaysian Energy Policy emphasises a three-pronged strategy for managing the nation’s energy supply, use, and environment. It aims for prudent management of energy supply and use while minimising the impact of energy production in an effort to protect the environment.

The 11th National Energy Efficiency Action Plan (NEEAP) 2016–2025 of Malaysia outlines the methods necessary to accomplish coordinated and cost-effective energy production and consumption [11]. The 11th NEEAP emphasises improving the penetration of energy-efficient instruments and consumer conservation. Nonetheless, inconsistent results have been observed for Malaysian consumers’ responsible energy consumption. Malaysia is in the process of transitioning from its current energy production mix to a renewable energy mix, in which hydro and solar power will be the primary energy resources [12].

Energy efficiency has become a headline issue for governments around the world. Rinkinen et al. [13] emphasised that energy efficiency is defined as using less energy to produce the same amount of a good or service. This paper defines energy efficiency as “using energy wisely and economically to sustain everyday life, live comfortably, and support wellbeing” [14]. In addition, energy-efficient appliances consume less electricity than inefficient appliances [15]. Air conditioners, light bulbs, washer–dryers, refrigerators and freezers, washing machines, water heaters, tumble dryers, electric ovens, and dishwashers are examples of Energy-Efficient Appliances (EEAs) [16].

2.2. Residential Energy Behaviour

Residential energy behaviour refers to the energy consumption patterns and habits of individuals in their homes. This can include factors such as the type and energy efficiency of appliances used, heating and cooling practices, water usage, and other energy-related activities. Understanding residential energy behaviour is important for reducing energy consumption and promoting energy efficiency [17]. Residential consumers have been identified by researchers as a crucial target market for energy conservation. It was also stressed by Abrahamse and Shwom [18] and Wang et al. [19] that households play a critical role in energy consumption and conservation, and their energy usage is more difficult to regulate compared to other sectors such as industry. This is due to the challenge of influencing individual behaviour in households. This highlights the importance of understanding and addressing residential energy behaviour in promoting energy efficiency and reducing energy consumption [20].

According to Twerefou and Abeney [21], home energy consumption constitutes a significant portion of energy demand and greenhouse gas emissions in the residential sector in Indonesia [22]. Thus, increasing the energy efficiency of housing is a crucial strategy for mitigating climate change globally, as housing has a large impact on energy requirements [23]. There have been many studies on various aspects of residential energy use, with space heating being one of the most researched topics due to its high energy consumption. Space heating costs can vary based on factors such as the size of the area being heated, equipment efficiency, and utilization [24].

2.3. Consumer Lifestyle

Lifestyle research is not limited to a single field but has developed greatly in sociology and marketing. Lifestyle was first presented in marketing by Anderson and Golden [25], who described it as “the patterns that arise and emerge from the daily dynamics of a community”. The early study was successful in identifying lifestyle characteristics within patterns of consumer behaviours in domains such as travel, job, home leisure activities, and service use [26].

Along these lines, empirical studies that have been conducted over the past two decades have revealed that income, education, family size, number of people living in the home, number of hours a home is occupied, size and type of dwelling, and stage of life cycle (for example, young singles, young families, families with teenagers, empty-nesters, and retired households) are important indicators of household energy consumption. These factors all play a role in determining how much energy a household uses [27].

However, consumers’ lifestyle perspectives should be considered in the context of their personal, professional, and cultural backgrounds, values, and beliefs. Energy consumption is relevant to any activity that directly or indirectly uses energy or requires energy-intensive products or services [28]. To understand the relationship between energy consumption and lifestyle, individual behaviour and equipment use data need to be transformed into indicators for identifying energy lifestyle groups. The consumer’s lifestyle influences their views, choices, and behaviours towards energy-related items and services. Therefore, examining the lifestyle perspectives of consumers is crucial in understanding and promoting energy efficiency.

Household energy use and conservation actions can also be influenced by habits, rituals, and social practices [29]. A variety of factors influence customer energy usage behaviour. Among the most explored elements are socioeconomics, demography, housing/dwelling, household attitudes, household lifestyle, and technological advances [30,31]. Bird and Schwarzinger [32] divided the consumer energy lifestyle group into six separate areas of life: housing, mobility, consumption, diet, leisure activities, and information. All six consumer lifestyles were adapted from Schwarzinger and Bird [28] and are explained below.

2.3.1. Housing

Energy efficiency and energy consumption are closely related, where an increase in energy efficiency can result in significant reductions in energy consumption use [33]. This is aside from being a critical lifestyle domain. Housing is also considered a vital part of many people’s lives. It provides them with various basic needs such as shelter and recognition [34]. According to Chen, Wang [35], and other researchers, demographic and household factors can affect the energy consumption of households. For instance, younger households tend to use more electricity than older ones. This is because elderly households are replacing major electric appliances such as televisions, air conditioners, washing machines, and refrigerators, which are already widespread in developed countries periodically. Due to the increasing number of households that are replacing their old electric appliances, the demand for energy-efficient products is expected to rise. This can help lower household energy consumption [36]. According to Matsumoto [37], many households have expressed their concerns about the high cost of energy services. However, they tend to focus on the overall cost of these services rather than the individual consumption of energy.

A study by Frederik et al. [38] examined the determinants of household energy consumption and found that socio-demographic and psychological factors (such as income, employment status, type/size of dwelling, home ownership, household size, and phase of the family life cycle) influenced household energy consumption. These socio-demographic and psychological factors include beliefs and attitudes, motives, and intentions, perceived behavioural control, cost–benefit trade-offs, and personal and social norms that influence household energy consumption. However, the impact of these two characteristics varies widely across studies [39]. Several studies have also focused on identifying factors related to household electricity consumption and the household’s perception towards resource efficiency at home [40]. Based on the literature, the following hypothesis is proposed:

Hypothesis 1(H1).

There is a positive relationship between housing and energy efficiency.

2.3.2. Mobility

Due to its high energy use, heavy reliance on oil products, and high emissions, the transportation sector is getting increasing attention in the consideration of climate change and sustainable development. The sustainable and energy-efficient transportation of passengers and goods has become the main concern of politicians around the world. However, transportation’s reliance on fossil fuels has resulted in it being a major contributor to greenhouse gas emissions, and it is one of the few industrial sectors where emissions are still increasing [41,42]. Eder and Nemov [43] evaluated the energy consumption levels of automobiles in various nations throughout the world and assessed the major trends in energy consumption. According to the report, transportation regulations have a direct impact on energy consumption and GHG emissions, and they can result in a significant modal shift toward more energy-efficient modes of transportation, such as public transportation, walking, and cycling [44,45,46]. Furthermore, the various behaviours of the routing schemes according to the mobility and traffic load caused a different pattern in energy consumption. Based on the literature, the following hypotheses are proposed:

Hypothesis 2(H2).

There is a positive relationship between mobility and energy efficiency.

2.3.3. Consumption

The growth of residential sectors, as well as an increased dependence on electric appliances such as refrigerators, washing machines, air conditioning, water heaters, lights, and entertainment goods, has contributed to an increase in the use of electricity [47]. It is necessary for tropical regions to have data on the elements that affect energy consumption. This will allow for the development of specific electricity-saving strategies for reducing electricity consumption based on factors connected to the characteristics of individual households. In contrast to other sectors, such as the industrial sector, it is more difficult to limit the amount of energy that is consumed by households through the application of regulations or legislation that are applied to other sectors. This is due to the fact that families comprise individuals, and it is fairly difficult to compel individuals to comply with restrictions that are related to the consumption of energy [48]. Therefore, effective resource management at home needs to be addressed in order to guarantee that the country will be able to meet its energy requirements in the future [17]. Based on the literature, the following hypothesis is proposed:

Hypothesis 3(H3).

There is a positive relationship between consumption and energy efficiency.

2.3.4. Diet

Every living organism has a daily energy requirement that food provides. This is due to eating a wide variety of foods. Each food group, such as beans, provides a specific amount of the fuel known as food energy (in kcal). The food has an efficiency-related indicator I in kg per kcal) and an emission factor (Efi in g CO[sub.2]-eq per kilogramme) to produce the needed number of legumes [49]. Food consumption accounts for a sizable portion of indirect energy use. Mealtime activities are used as an example since the quantity of energy consumed can range from zero (preparing a cold meal) to low (microwaving food) (such as cooking using an electric oven). Choosing foods produced using less energy-intensive ways (i.e., climate-friendly agriculture) or switching to foods that provide comparable nutritional value (i.e., calorie or protein content) but release less greenhouse gas emissions are examples of indirect efficiency behaviours [10]. According to a prior study, food production accounts for a significant share of total energy consumption. For example, depending on how the borders of the energy input analysis of the food are formed, estimates of the total amount of energy used in the production of food in the United States can range from 8% to 16% (higher estimates include energy consumed by consumers who drive to buy food). Based on the literature, the following hypothesis is proposed:

Hypothesis 4(H4).

There is a positive relationship between diet and energy efficiency.

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2.3.5. Leisure Activities

Leisure activities in this study refer to indoor activities that are related to (1) relaxation, (2) distraction, or (3) increasing knowledge and spontaneous social interaction. For instance, watching television or video, listening to the radio, making recordings, and using a computer [50]. Daily human activities influence energy consumption patterns, with particular forms of energy usage behaviour forming clusters in specific spatial and temporal locations [51]. These activities can include work, home, and leisure activities, all of which have an impact on the city’s energy-saving potential in different sectors [52]. Meeting demand during peak periods in many countries necessitates the use of less efficient, more carbon-intensive generation units, making energy provision particularly costly, both economically and environmentally during these times [53]. A number of academic and policy studies have attempted to better understand which everyday activities contribute to residential peak demand, with the goal of identifying the degree of temporal flexibility that may exist when activities normally associated with energy consumption are carried out [53,54,55,56]. Based on the literature, the following hypothesis is proposed:

Hypothesis 5(H5).

There is a positive relationship between leisure activities and energy efficiency.

2.3.6. Information

In this study, information is defined as the availability and quality of information on current energy consumption levels and trends based on metering level, the information content of utility bills, and households’ willingness and ability to analyse this information [57]. Information plays a critical role in improving energy efficiency in households. This is supported by previous studies that discovered a favourable relationship between these two aspects (information [58] and energy efficiency [59]). The information available to households, such as energy usage, energy conservation opportunities, and the energy performance of technology affects the adoption of energy-efficient devices. The extent of metering, the information content of utility bills, and families’ willingness and aptitude to analyse this information all influence the availability and quality of information on current energy usage levels and patterns [57]. Based on the literature, the following hypotheses is proposed:

Hypothesis 6(H6).

There is positive relationship between information and energy efficiency.

3. Method

The research process flowchart is illustrated in Figure 1.

3.1. Research Design

Research design can be defined as the set of frameworks and structures used for the purpose of conducting research where it is useful to collect and analyse data to answer the research questions and solve research problems [60]. In accordance with the research objective, this study employs (1) quantitative, (2) descriptive, and (3) cross-sectional research designs to investigate energy consumption based on the residential consumers’ lifestyles.

Quantitative research places a premium on the collecting and analysis of numerical data and places an emphasis on reasonably large and representative data sets [61]. The hypotheses that were presented in the conceptualised model that addressed the objective of this research will be put to the test through the use of a survey, since the quantitative research method was used.

Descriptive analysis is provided by frequencies, measures of central tendency, and dispersion. The purpose of frequency is to demonstrate the values such as the numbers and percentages for the different categories of a single categorical variable [62]. In this study, after the samples are collected, the samples of descriptive statistics are used to make conclusions about the characteristics of the entire population [63].

Cross-sectional studies are those in which data are gathered once, during a period of days, weeks, or months [64]. Many cross-sectional studies are exploratory or descriptive in purpose [65]. This study used cross-sectional which would help in generating the hypothesis on which further research may be based on.

3.2. Sampling Technique

The sampling technique used in this study is the multistage sampling technique. In the first stage, the study area was divided into four clusters based on regions: South, Central, North, and East. In the second stage, all four clusters were then categorised based on state, in which Selangor, Putrajaya, Melaka, Kedah, and Pahang were selected randomly. In the third stage, 10 to 15 respondents were selected randomly within each state.

3.3. Survey Developments

From the very beginning, the survey instrument was developed together with the help of an expert. Establishing the content validity of a scale involves systematic but subjective assessments of a scale’s ability to measure what it is supposed to measure [66]. Content validity was established through a panel of 10 experts in the field of energy and research, who reviewed the questionnaire and made recommendations for improvement.

This panel was selected based on their experience in the field of energy, their knowledge of research work, as well as their familiarity with the subject. Based on experts’ comments and recommendations, the questionnaire was modified by eliminating vague statements, improving flow and structure, and increasing relevance and clarity. Overall, the panel’s response reveals that the instrument survey is a suitable instrument.

A focus group discussion was then conducted with research practitioners and stakeholders to further check the content of the questionnaire for relevance, clarity, and ease of completion. The results of the expert review and focus group discussion indicate that the survey instrument is a suitable tool for measuring energy efficiency in the Malaysian context.

3.4. Questionnaire Survey

The study used a survey by distributing self-administered questionnaires to residential consumers. The survey was administered to heads of households or housewives, as they are responsible for paying utility bills and managing household energy use. The data were collected through a face-to-face interview, which was preferred over other techniques such as telephonic interviews or email. This method provided the greatest scope for detailed questions and answers, according to Aborisade [67].

The study adopted measurement items for various constructs from past research, as follows: housing was adopted from Ruotsalainen et al. [4] and Kong et al. [5]; leisure activities from Bin and Dowlatabadi [6]; information from Kong et al. [5]; mobility from Feng et al. [7] and Zhang et al. [8]; consumption from Zhou and Teng [9]; diet from Zhou and Teng [9]; and energy efficiency from Gembicki [10]. The questionnaires with a Likert scale anchored on 1 “strongly disagree” and 6 “strongly agree”. The survey was divided into three sections. Section A to Section B included questions for measuring consumer lifestyles and energy efficiency, respectively, while Section C consisted of questions measuring the demographic profile of the respondents.

3.5. Pilot Study

A pilot study is a preliminary study conducted using a small sample to determine the validity, understandability, and answerability of the question [68]. The pilot study was carried out to identify any issues with the questionnaire and to make sure the participants understood the questions. The researcher met with the participants, explained the questions, and made sure they understood what the variables were. In this study, a pilot study was conducted with 50 respondents from Selangor, Putrajaya, Melaka, Kedah, and Pahang, with a sample size of 10–15 respondents per state. A comment box was provided at the end of the survey for participants to provide feedback on the questionnaire.

3.6. Data Analysis

This study used Structural Equation Modelling (SEM) with a focus on partial least squares structural equation modelling (PLS-SEM) to test the relationship between dependent and independent variables. The data analysis was conducted using a two-stage approach, and PLS-SEM was also used to test the validity and reliability of variables [69]. Reliability and validity are two important aspects of measurement in research. Reliability refers to the consistency and stability of the measurement, while validity refers to the accuracy and meaningfulness of the measurement.

In the first stage, the reliability and validity of the measurements were tested. In this case, composite reliability was used to assess the reliability of the measurements, and convergent and discriminant validity were used to assess the validity. The convergent validity was used to determine if the items measured the same concepts, while the discriminant validity was used to determine if the items were different from other constructs. The hetero-trait and mono-trait ratios (HTMT) were used to assess the discriminant validity [69]

In the second stage, the correlations of constructs of the structural model were assessed [70]. Validating the structural model can help the researcher to evaluate systematically whether the hypotheses expressed by the structural model are supported by the data [71]. The structural model results were evaluated by using path coefficients, coefficient of determination (R[sup.2]), and effect size (f[sup.2]), as recommended by Hair and Alamer [69] and Ramayah et al. [72].

4. Findings

4.1. Respondent Profile

The study was conducted on 50 respondents, of whom 26 were male and 24 were female. As presented in Figure 2, the average age of the respondents was between 36 to 59 years old, with 27 respondents having a Master’s/Ph.D. degree. In terms of occupation, the majority of the respondents were full-time workers (44 respondents). As for the housing area, 35 of the respondents were from urban areas, and 15 respondents were from rural areas. Out of the eight types of houses analysed in the study: bungalow, terrace, semi-detached, low-cost house, flat house, low-cost flat house, apartment/condominium, and village house. The terrace house was the highest, as there were 12 respondents who lived in a terrace house.

The focus of Figure 3 is on household income and average monthly electricity bills. A total of 30 respondents had a total household income of less than RM 5000. The average monthly electricity bills was between RM 51 and RM 100 for 15 respondents and between RM 101 and RM 250 for another 15 respondents.

4.2. Descriptive Analysis

The means and standard deviations for the variables are presented in Table 1. The mean scores for the variables on a six-point Likert scale were 3.801 and 4.955, with stand-ard deviation scores of 1.001 and 1.250 for housing, leisure activities, mobility, consumption, information, diet, and energy efficiency. The results suggest that the participants generally agreed with the survey questions, and the mean value can be used as a representative score for each item in the data set.

4.3. Measurement Model Analysis

Convergent and discriminant validity need to be established in the study before the measurement model is further tested. The outer loadings, Average Variance Extracted (AVE), and Composite Reliability (CR) are analysed in order to determine whether or not convergent validity has been achieved.

From Table 1, it was observed that all the items measuring a particular variable were greater than 0.50 on those particular variables and less than 0.50 on the other variable, thus confirming construct validity. Previous researchers suggested that the cut-off value for factor loadings should exceed 0.50 [73]. Following these criteria, items with factor loadings less than 0.50 were removed. Table 1 shows the outer loadings of all items for all variables in the initial and modified measurement model. According to these results, two items were removed from housing (P8 and P9), whereas three items were dropped from leisure activities (AKT4, AKT5, and AKT8), two items from information (SI3 and SI4), four items were removed from mobility (MO1, MO2, MO3, and MO4), four items were removed from consumption (PEE6, PEE7, PEE8, and PEE9), five items were removed from diet (D5, D6, D7, D8, and D9), and five items were removed for energy efficiency (KT7, KT8, KT9, KT10, and KT12). In total, 25 items were removed. After removing items with loading less than the recommended value, all measurement items loaded significantly between 0.564 and 0.893.

The reliability of the reflective measurement model was checked by using composite reliability. Composite reliability is preferred over Cronbach’s alpha as it takes into account different loadings for the indicators [74]. Composite reliability can be interpreted similarly to Cronbach’s alpha, with values ranging from 0 to 1, where higher values indicate higher reliability [75]. The composite reliability values reflect the level to which construct indicators reveal the latent variables, and they should be greater than 0.70 [76]. As shown in Table 1, all variables displayed composite reliability between 0.813 and 0.892, which is well above the threshold value of 0.70.

The validity of the study was assessed using convergent validity and discriminant validity. Convergent validity measures the extent to which a measure positively correlates with other measures of the same construct. The convergent validity of the constructs in this research was examined using Average Variance Extracted (AVE) values, as suggested by Fornell and Larcker (1981) [77]. AVE reflects the average variance shared between a construct and its measures relative to the amount of measurement error. As shown in Table 1, the AVE values for all variables were between 0.539 and 0.666, which are higher than the prescribed value of 0.50 [78]. This indicates that a construct explains more than 50% of the variance among the scale indicators, establishing convergent validity. Therefore, the results support the existence of convergent validity for the constructs in this study.

Table 1 summarizes each variable in the measurement model, all of which demonstrate satisfactory reliability and convergent validity.

Next, Table 2 lists the discriminant validity outcomes using the conservative heterotrait–monotrait (HTMT) ratio approach [79]. The HTMT approach shows the estimation of the true correlation between two latent variables and helps to examine the discriminant validity. A threshold value of 0.90 has been suggested, and it suggests a lack of discriminant validity if the HTMT values are above 0.90 [79]. The results in Table 2 show that the measurement model meets this criterion, as the HTMT values are below 0.90 and the confidence interval does not involve the value of 1, indicating the discriminant validity of the measurement model.

4.4. Structural Model Evaluation

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The structural model in PLS-SEM was assessed after the measurement model was found to be valid and reliable. Hypotheses were tested through the structural model to answer research questions [69]. The assessment of the structural model included the significance of the path coefficients, coefficient determination (R[sup.2]), and effect size (f[sup.2]). Before testing the hypotheses, multicollinearity was checked by assessing the variance inflation factors (VIFs) of the exogenous variables. The result showed that the VIFs were less than 3.33, indicating no multicollinearity issues.

4.4.1. Path Coefficient

In accordance with [49], all hypotheses were tested with 5000 bootstrap samples through a one-tailed test. The PLS-bootstrapping results in Table 3 reveal that mobility (ß = 0.0280, t-value = 0.143), diet (ß = 0.024, t-value = 0.175), and leisure activities (ß = -0.068, t-value = 0.431) each has a non-significant effect on energy efficiency. Therefore, H2, H4, and H5 are not supported. However, Table 3 also indicates a significant effect between housing (ß = 0.278, t-value = 1.693), consumption (ß = 0.387, t-value = 2.162), and information (ß = 0.262, t-value = 1.883) on energy efficiency. As such, H1, H3, and H6 are supported.

4.4.2. Coefficient of Determination

The results from Table 4 show that customer lifestyle variables explain 63.7% of the total variance of energy efficiency, which is considered substantial according to the criteria proposed by Chin [80]. A value of R[sup.2] of 0.19 is considered weak, 0.33 is average, and a value of 0.50 R[sup.2] is considered substantial. The results from Table 4 indicate that customer lifestyle variables (housing, leisure activities, mobility, information, consumption, and diet) account for 63.7% of the total variance of energy efficiency. The model, therefore, possessed substantial explanatory power.

4.4.3. Effect Size (f[sup.2])

The evaluation of the effect size (f[sup.2]) is the third criterion for assessing a structural model based on the R[sup.2] values of the independent variable. Cohen [81] stated that the f[sup.2] values of 0.020, 0.105, and 0.350 represent weak, moderate, and strong impacts, respectively. Regarding home consumer energy efficiency, consumption had an effect size of 0.035, while diet, leisure activities, and mobility each had effect sizes of 0.015, 0.019, and 0.006, indicating small effects (Refer to Table 4). Housing (effect size = 0.257) and information (effect size = 0.200) had a moderate effect on energy efficiency.

5. Discussion

In this study, a questionnaire survey was administered to investigate energy efficiency based on the energy consumption of the residential consumers’ lifestyles. The results from this study showed mixed findings for the hypotheses concerning consumer lifestyle and energy efficiency. The statistical analysis indicated that only three factors had significant effects on energy efficiency from the six consumer lifestyle behaviours: consumption, housing, and information.

The first hypothesis (H1) focuses on the relationship between housing and energy efficiency. The hypothesis aims to determine how improvements in these areas can lead to reduced energy use and increased energy efficiency, which can have positive impacts on both the environment and households. Consistent with previous research [38,39], the result indicated a positive significant relationship with (ß = 0.278, t-value = 1.693). These findings also align with previous research which suggests that improved housing can have positive impacts on health and wellbeing [48]; boost development, especially in low-income countries [82]; and help achieve environmental goals through reduced energy consumption [83].

The second hypothesis (H2) is on the relationship between mobility and energy efficiency. The result is different from the finding by Gembicki [10], as it indicates as non-significant (ß = 0.028, t-value = 0.143). However, more study is needed in this area as mobility and energy efficiency are closely linked as transportation is one of the major sources of energy consumption. Improving energy efficiency in transportation can greatly reduce the overall energy consumption of a household. This can be achieved through the use of fuel-efficient vehicles, public transportation, and alternative modes of transportation such as biking or walking. Encouraging low-carbon mobility options and reducing vehicle use can also help mitigate the impact of transportation on the environment.

The third hypothesis (H3) is on the relationship between consumption and energy efficiency. The result indicated a significant relationship (ß = 0.387, t-value = 2.162). It is important to understand the main factors that impact household energy consumption. According to Wiesmann et al. [84], it is crucial to consider the energy sources and the energy requirements of households to gain insight into energy choices and consumption patterns. The significant relationship shows that the energy sources from the appliance characteristics (air conditioners, refrigerators, freezers, heaters, vacuums, rice cookers, kettles, irons, televisions, and other electrical appliances) are contributing factors towards energy efficiency.

The study also discusses the relationship between diet and energy efficiency as proposed in hypothesis four (H4). It is worth noting that diet has a non-significant relationship with energy efficiency (ß = 0.024, t-value = 0.175). However, the results of analysis by Schwarzinger and Bird [28] indicate a significant relationship. The relationship between diet and energy efficiency can be seen in the way that the production, transportation, and preparation of food require energy inputs. Increasing energy efficiency can help to improve sustainability.

The relationship between leisure activities and energy efficiency was also tested as proposed in hypothesis five (H5). The structural model analysis indicated a non-significant relationship between leisure activities and energy efficiency (ß = -0.068, t-value = 0.431). Leisure activities are an important consumer lifestyle as they could play a role in energy efficiency, as they often involve the use of energy-consuming devices such as televisions, gaming consoles, and computers. Encouraging energy-saving practices during leisure activities, such as using power-saving modes on electronics, can help reduce household energy consumption and improve energy efficiency.

Lastly, hypothesis six (H6) indicates a significant relationship between information and energy efficiency (ß = 0.262, t-value = 1.883). The findings are supported by Santos and Borges [85], who, in their study, suggested that feedback and detailed information are effective ways to influence behaviour. Mills and Schleich [57] also indicated that household information on energy consumption, conservation opportunities, and the energy performance of technologies are expected to affect energy efficiency. The use of information technology and communication systems can help improve energy efficiency by enabling more effective monitoring and control of energy use, as well as facilitating the exchange in information about energy-saving practices and technologies. Additionally, the production and use of information technology also consume energy, thus there is a need for energy efficiency in the information technology sector as well.

6. Conclusions

Improving the energy efficiency of our houses is a wonderful way to minimise greenhouse gas emissions and boost thermal comfort. The study focused on the relationship between energy efficiency and consumer lifestyle behaviours in the residential sector. The results showed that only three factors (consumption, housing, and information) had a significant impact on energy efficiency. The findings suggested that Malaysia’s energy-saving policy, which emphasises the adoption of energy-saving appliances, has been effective. These results highlight the importance of consumer behaviour in driving energy efficiency and reducing greenhouse gas emissions.

The findings also indicated that three other consumer lifestyle attributes have a non-significant effect on energy efficiency: diet, leisure activities, and mobility. The outcomes of the analysis suggest the necessity of providing comparable but distinct policies or programmes to different groups in order to boost their domestic energy efficiency. In addition to extensive consumer education programmes that encourage users to shift or reduce the amount of time spent on energy-intensive activities in order to conserve energy, these resources may include the replacement of energy-intensive appliances, the promotion of energy storage devices, and the implementation of more cost-reflective tariffs.

According to the findings, residents should optimise their energy efficiency in accordance with their current energy lifestyles in order to reduce their large energy use. More research is needed, however, to understand the disparities in consumer groups’ lifestyles that affect energy efficiency. Following an assessment of residential users’ energy efficiency, energy-saving recommendations and services can be supplied to them. This can help power organisations maximise power package services based on user characteristics, support governments in formulating energy-saving and emission-reduction plans, and serve as a reference for the dispatching work of electric power companies.

The findings given in this research have several limitations that must be highlighted. For instance, as this is a pilot study with a small sample size, it can be expanded to a larger sample size in generalising the results of consumer energy lifestyles in Malaysia. Secondly, the study can use demographic factors to moderate the relationship between consumers’ energy lifestyle factors and energy efficiency.

Finally, from the literature search, this is the first study that investigates energy efficiency behaviour based on the six residential consumers’ lifestyles (housing, leisure activities, information, mobility, consumption, and diet) in Malaysia; thus, this topic deserves further research. Additionally, future studies are encouraged to expand the sample size to derive a more reliable and robust construct.

Author Contributions

Conceptualization, S.D., J.R., S.I.M., N.N.A. and W.M.T.W.A.; Methodology, S.D., J.R. and S.I.M.; Data analysis, W.N.W.H., S.D. and J.R.; Data collection, S.D., J.R., S.I.M., N.N.A., W.M.T.W.A., M.J.A., W.N.W.H., S.N.T. and H.A.A.; Writing—original draft preparation, W.N.W.H., S.N.T. and H.A.A.; Writing—review and editing, S.D., B.V.A., M.J.A. and W.N.W.H. All authors have read and agreed to the published version of the manuscript.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.


1. M.N. Akroush; M.I. Zuriekat; H.I. Al Jabali; N.A. Asfour Determinants of purchasing intentions of energy-efficient products: The roles of energy awareness and perceived benefits., 2019, 13,pp. 128-148. DOI:

2. S. Joshi How Coronavirus Measures Have Changed Electricity Demand.. Available online: <date-in-citation content-type="access-date" iso-8601-date="2023-02-04">(accessed on 4 February 2023)</date-in-citation>.

3. Ministry of Energy, Green Technology and Water, Ministry of Energy, Green Technology and Water (KeTTHA): Putrajaya, Malaysia, 2017,

4. J. Ruotsalainen; J. Karjalainen; M. Child; S. Heinonen Culture, values, lifestyles, and power in energy futures: A critical peer-to-peer vision for renewable energy., 2017, 34,pp. 231-239. DOI:

5. X. Kong; S. Zhu; X. Huo; S. Li; Y. Li; S. Zhang A household energy efficiency index assessment method based on non-intrusive load monitoring data., 2020, 10, 3820. DOI:

6. S. Bin; H. Dowlatabadi Consumer lifestyle approach to US energy use and the related CO2 emissions., 2005, 33,pp. 197-208. DOI:

7. Z.-H. Feng; L.-L. Zou; Y.-M. Wei The impact of household consumption on energy use and CO2 emissions in China., 2011, 36,pp. 656-670. DOI:

8. J. Zhang; F. Teng; S. Zhou The structural changes and determinants of household energy choices and energy consumption in urban China: Addressing the role of building type., 2020, 139,p. 111314. DOI:

9. S. Zhou; F. Teng Estimation of urban residential electricity demand in China using household survey data., 2013, 61,pp. 394-402. DOI:

10. J. Gembicki Energy efficiency in the agricultural and food industry illustrated with the example of the feed production plant., 2016, 10,p. 00138. DOI:

11. P. Phrakhruopatnontakitti Energy consumption, economic growth and environmental degradation in 4 Asian Countries: Malaysia, Myanmar, Vietnam and Thailand., 2020, 10,pp. 529-539. DOI:

12. Z. Zulkifli Malaysia country report., Energy Commission of Malaysia: Putrajaya, Malaysia, 2012,pp. 170-190.

13. J. Rinkinen; E. Shove; G. Marsden, Routledge: Oxfordshire, UK, 2020,

14. R. McAndrew; R. Mulcahy; R. Gordon; R. Russell-Bennett Household energy efficiency interventions: A systematic literature review., 2021, 150,p. 112136. DOI:

15. K.A. Agyarko; R. Opoku; R. Van Buskirk Removing barriers and promoting demand-side energy efficiency in households in Sub-Saharan Africa: A case study in Ghana., 2020, 137,p. 111149. DOI:

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16. C.-S. Tan; H.-Y. Ooi; Y.-N. Goh A moral extension of the theory of planned behavior to predict consumers’ purchase intention for energy-efficient household appliances in Malaysia., 2017, 107,pp. 459-471. DOI:

17. A. Azlina; M. Kamaludin; E.S.Z.E. Abdullah; A. Radam Factors influencing household end-use electricity demand in Malaysia., 2016, 22,pp. 4120-4123. DOI:

18. W. Abrahamse; R. Shwom Domestic energy consumption and climate change mitigation., 2018, 9,p. e525. DOI:

19. S.S. Wang; D.Q. Zhou; P. Zhou; Q. Wang CO2 emissions, energy consumption and economic growth in China: A panel data analysis., 2011, 39,pp. 4870-4875. DOI:

20. D.K. Twerefou; J.O. Abeney Efficiency of household electricity consumption in Ghana., 2020, 144,p. 111661. DOI:

21. J. Heinonen, Aalto University: Espoo, Finland, 2012,

22. D. Wiedenhofer; M. Lenzen; J.K. Steinberger Energy requirements of consumption: Urban form, climatic and socio-economic factors, rebounds and their policy implications., 2013, 63,pp. 696-707. DOI:

23. U. Surahman; D. Hartono; E. Setyowati; A. Jurizat Investigation on household energy consumption of urban residential buildings in major cities of Indonesia during COVID-19 pandemic., 2022, 261,p. 111956. DOI: PMID:

24. J. Stragier; L. Hauttekeete; L. De Marez; R. Brondeel Measuring energy-efficient behavior in households: The development of a standardized scale., 2012, 4,pp. 64-71. DOI:

25. W.T. Anderson; L.L. Golden Lifestyle and psychographics: A critical review and recommendation., 1984, 11,pp. 405-411.

26. L. Schipper; S. Bartlett; D. Havk; E. Vine Linking life-styles and energy use: A matter of time?., 1989, 4,pp. 273-320. DOI:

27. L. Lutzenhiser; S. Lutzenhiser Looking at lifestyle: The impacts of American ways of life on energy/resource demands and pollution patterns.,

28. S. Schwarzinger; D.N. Bird; T.M. Skjølsvold Identifying consumer lifestyles through their energy impacts: Transforming social science data into policy-relevant group-level knowledge., 2019, 11, 6162. DOI:

29. E. Shove; M. Pantzar; M. Watson, Sage: Newcastle upon Tyne, UK, 2012,

30. N.A. Chik; K.A. Rahim; A. Radam; M.N. Shamsudin CO2 emissions induced by households lifestyle in Malaysia., 2013, 14,p. 344.

31. K. Hwang; B. Lee Pride, mindfulness, public self-awareness, affective satisfaction, and customer citizenship behaviour among green restaurant customers., 2019, 83,pp. 169-179. DOI:

32. D. Bird; S. Schwarzinger; D. Kortschak; M. Strohmaier; G. Lettmayer, The ECHOES Consortium: Brussels, Belgium, 2019,

33. L. Xie; H. Yan; S. Zhang; C. Wei Does urbanization increase residential energy use? Evidence from the Chinese residential energy consumption survey 2012., 2020, 59,p. 101374. DOI:

34. J. Thøgersen Housing-related lifestyle and energy saving: A multi-level approach., 2017, 102,pp. 73-87. DOI:

35. J. Chen; X. Wang; K. Steemers A statistical analysis of a residential energy consumption survey study in Hangzhou, China., 2013, 66,pp. 193-202. DOI:

36. S. Matsumoto; K. Mizobuchi; S. Managi Household energy consumption., 2022, 24,pp. 1-5. DOI:

37. S. Matsumoto Daily Habits and Energy Consumption: Go to Bed Earlier for Environmental Protection., 2019, 8,p. 54. DOI:

38. E.R. Frederiks; K. Stenner; E.V. Hobman Household energy use: Applying behavioural economics to understand consumer decision-making and behaviour., 2015, 41,pp. 1385-1394. DOI:

39. J. Urban; M. Šcasný Exploring domestic energy-saving: The role of environmental concern and background variables., 2012, 47,pp. 69-80. DOI:

40. S.S.S. Ali; M.R. Razman; A. Awang; M. Asyraf; M. Ishak; R. Ilyas; R.J. Lawrence Critical determinants of household electricity consumption in a rapidly growing city., 2021, 13, 4441. DOI:

41. F. Creutzig; P. Jochem; O.Y. Edelenbosch; L. Mattauch; D.P.V. Vuuren; D. McCollum; J. Minx Transport: A roadblock to climate change mitigation?., 2015, 350,pp. 911-912. DOI: PMID:

42. C.N. Businge; S. Viani; N. Pepe; M. Borgarello; C. Caruso; G. Tripodi; S. Soresinetti Energy efficiency solutions for sustainable urban mobility: Case study of the Milan metropolitan area., 2019, 182,pp. 151-163.

43. L. Eder; V.Y. Nemov Forecast of energy consumption of vehicles., 2017, 28,pp. 423-430. DOI:

44. P. Poudenx The effect of transportation policies on energy consumption and greenhouse gas emission from urban passenger transportation., 2008, 42,pp. 901-909. DOI:

45. D. Ogilvie; M. Egan; V. Hamilton; M. Petticrew Promoting walking and cycling as an alternative to using cars: Systematic review., 2004, 329,p. 763. DOI:

46. R. Scarinci; F. Rast; M. Bierlaire Needed reduction in mobility energy consumption to meet the goal of a 2000-watt society., 2017, 101,pp. 133-148. DOI:

47. J. Jailani; N. Mohamad; M.A. Omar; A. Hauashdh; N.H. Abas Energy Consumption Pattern of Residential Buildings: Case Study of Residential Area in Batu Pahat, Johor., 2020, 12,pp. 052-058. DOI:

48. P. Howden-Chapman; H. Viggers; R. Chapman; K. O’Sullivan; L.T. Barnard; B. Lloyd Tackling cold housing and fuel poverty in New Zealand: A review of policies, research, and health impacts., 2012, 49,pp. 134-142. DOI:

49. M. Hadler; B. Klösch; S. Schwarzinger; M. Schweighart; R. Wardana; D.N. Bird, Springer Nature: Berlin/Heidelberg, Germany, 2022,

50. A. Veal Joffre Dumazedier and the definition of leisure., 2019, 42,pp. 187-200. DOI:

51. J.A. Fonseca; A. Schlueter Integrated model for characterization of spatiotemporal building energy consumption patterns in neighborhoods and city districts., 2015, 142,pp. 247-265. DOI:

52. N. Mohammadi; J.E. Taylor Recurrent Mobility: Urban Conduits for Diffusion of Energy Efficiency., 2019, 9,pp. 1-12. DOI: PMID:

53. M.J. Lorincz; J.L. Ramírez-Mendiola; J. Torriti Impact of time-use behaviour on residential energy consumption in the United Kingdom., 2021, 14, 6286. DOI:

54. I. Glorieux; I. Mestdag; J. Minnen The coming of the 24-h economy? Changing work schedules in Belgium between 1966 and 1999., 2008, 17,pp. 63-83. DOI:

55. I. Glorieux; I. Laurijssen; J. Minnen; T.P. van Tienoven In search of the harried leisure class in contemporary society: Time-use surveys and patterns of leisure time consumption., 2010, 33,pp. 163-181. DOI:

56. M. Hellgren Extracting more knowledge from time diaries?., 2014, 119,pp. 1517-1534. DOI:

57. B. Mills; J. Schleich Residential energy-efficient technology adoption, energy conservation, knowledge, and attitudes: An analysis of European countries., 2012, 49,pp. 616-628. DOI:

58. K. Ek; P. Söderholm The devil is in the details: Household electricity saving behavior and the role of information., 2010, 38,pp. 1578-1587. DOI:

59. S. Hori; K. Kondo; D. Nogata; H. Ben The determinants of household energy-saving behavior: Survey and comparison in five major Asian cities., 2013, 52,pp. 354-362. DOI:

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60. D.M.I. Akhtar Research design., 2016,. Available online: <date-in-citation content-type="access-date" iso-8601-date="2023-02-04">(accessed on 4 February 2023)</date-in-citation>.

61. L. Blaxter; C. Hughes; M. Tight, McGraw-Hill Education: Maidenhead, UK, 2010,

62. W.G. Zikmund; B.J. Babin; J.C. Carr; M. Griffin, 7th ed. edition; Thomson/South-Western: Mason, OH, USA, 2003,

63. W.G. Zikmund; B.J. Babin; J.C. Carr; M. Griffin, 9th ed. edition; Cengage Learning: Boston, MA, USA, 2013,

64. U. Sekaran; R. Bougie, John Wiley & Sons: Hoboken, NJ, USA, 2016,

65. P. Ghauri; K. Gronhaug, Pearson Education: London, UK, 2005,

66. R.G. Netemeyer; J.S. Boles; R. McMurrian Development and validation of work–family conflict and family–work conflict scales., 1996, 81,p. 400. DOI:

67. O.P. Aborisade Data collection and new technology., 2013, 8,p. 48. DOI:

68. E. Van Teijlingen; V. Hundley The importance of pilot studies., 2002, 16,p. 33. DOI:

69. J. Hair; A. Alamer Partial Least Squares Structural Equation Modeling (PLS-SEM) in second language and education research: Guidelines using an applied example., 2022, 1,p. 100027. DOI:

70. J.F. Hair; J.J. Risher; M. Sarstedt; C.M. Ringle When to use and how to report the results of PLS-SEM., 2019, 31,pp. 2-24. DOI:

71. N. Urbach; F. Ahlemann Structural equation modeling in information systems research using partial least squares., 2010, 11,pp. 5-40.

72. T. Ramayah; J. Cheah; F. Chuah; H. Ting; M. Memon Partial least squares structural equation modeling (PLS-SEM) using SmartPLS 3.0., Pearson: London, UK, 2018,

73. J.F. Hair; C.M. Ringle; M. Sarstedt Partial least squares structural equation modeling: Rigorous applications, better results and higher acceptance., 2013, 46,pp. 1-12. DOI:

74. J. Henseler; C.M. Ringle; R.R. Sinkovics The Use of Partial Least Squares Path Modeling in International Marketing., Emerald Bingley: Bingley, UK, 2009, Volume 20,pp. 277-320.

75. J.F. Hair; M. Sarstedt; L. Hopkins; V.G. Kuppelwieser Partial least squares structural equation modeling (PLS-SEM)., 2014, 26,pp. 106-121. DOI:

76. R.P. Bagozzi; Y. Yi On the use of structural equation models in experimental designs., 1989, 26,pp. 271-284. DOI:

77. C. Fornell; D.F. Larcker Evaluating structural equation models with unobservable variables and measurement error., 1981, 18,pp. 39-50. DOI:

78. J.F. Hair; M.C. Howard; C. Nitzl Assessing measurement model quality in PLS-SEM using confirmatory composite analysis., 2020, 109,pp. 101-110. DOI:

79. J. Henseler; C.M. Ringle; M. Sarstedt A new criterion for assessing discriminant validity in variance-based structural equation modeling., 2015, 43,pp. 115-135. DOI:

80. W.W. Chin How to write up and report PLS analyses., Springer: Berlin/Heidelberg, Germany, 2010,pp. 655-690.

81. J. Cohen A power primer., 1992, 112,p. 155. DOI:

82. L. Aldieri; A. Gatto; C.P. Vinci Evaluation of energy resilience and adaptation policies: An energy efficiency analysis., 2021, 157,p. 112505. DOI:

83. V. Haines; V. Mitchell; B. Mallaband, Loughborough University: Loughborough, UK, 2010,

84. D. Wiesmann; I.L. Azevedo; P. Ferrão; J.E. Fernández Residential electricity consumption in Portugal: Findings from top-down and bottom-up models., 2011, 39,pp. 2772-2779. DOI:

85. J. Santos; A.S. Borges; T. Domingos Exploring the links between total factor productivity and energy efficiency: Portugal, 1960–2014., 2021, 101,p. 105407. DOI:

Figures and Tables

Figure 1: Research Process. [Please download the PDF to view the image]

Figure 2: Respondent profile (a) gender, (b) age, (c) area, (d) occupation, (e) education level, and (f) type of house. [Please download the PDF to view the image]

Figure 3: Respondent profile (a) household income and (b) average monthly electricity bills. [Please download the PDF to view the image]

Table 1: Measurement Model—Reliability and Convergent Validity Result.

VariableItem CodeInitial ModelModified ModelMSDCRAVE

































































































































Leisure Activities



































































Energy Efficiency









































Note: M = Mean, SD = Standard Deviation, CR = Composite Reliability, AVE = Average Variance Extracted.

Table 2: Discriminant Validity Results—HTMT.

ConsumptionDietEnergy EfficiencyHousingInformationLeisure ActivitiesMobility




Energy Efficiency












Leisure Activities













Table 3: Path coefficient and Hypotheses.

Path Coefficients (ß)Standard Deviationt-ValueDecision

H1: Housing -> Energy Efficiency





H2: Mobility -> Energy Efficiency





H3: Consumption -> Energy Efficiency





H4: Diet -> Energy Efficiency





H5: Leisure Activities -> Energy Efficiency





H6: Information -> Energy Efficiency





Table 4: VIF, f[sup.2], and R[sup.2] Results.















Leisure Activities






Author Affiliation(s):

[1] College of Business Management and Accounting, Universiti Tenaga Nasional, Muadzam Shah 26700, Pahang, Malaysia

[2] Institute of Energy Policy and Research (IEPRe), Universiti Tenaga Nasional, Putrajaya Campus, Jalan Ikram-Uniten, Kajang 43000, Selangor, Malaysia

[3] UNITEN R&D Sdn Bhd (URND), Universiti Tenaga Nasional, Jalan Ikram-Uniten, Kajang 43000, Selangor, Malaysia

[4] Department of Chemical Engineering, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Perak, Malaysia

[5] Teaching & Learning Centre (TLC), Universiti Tenaga Nasional, Putrajaya Campus, Jalan Ikram-Uniten, Kajang 43000, Selangor, Malaysia

Author Note(s):

[*] Correspondence:

DOI: 10.3390/en16083514

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Copyright 2023 Gale, Cengage Learning. All rights reserved.


How much energy does residential use in Malaysia? ›

The average electricity consumption for residential was 345 kWh per month based on the survey of 348 samples in Malaysia [2].

What is the energy efficiency program in Malaysia? ›

THE Sustainability Achieved via Energy Efficiency (SAVE) 3.0 programme has received overwhelming response from the public since its inception. The programme was launched in January 2022 by the Sustainable Energy Development Authority (SEDA) Malaysia.

What is the primary energy consumption of Malaysia? ›

Energy consumption

Petroleum and other liquids and natural gas are the primary energy sources consumed in Malaysia, with estimated shares of 37% and 36%, respectively, in 2019. Coal meets about 21% of the country's energy consumption. Renewable energy accounts for 6% of total consumption (Figure 7).

What is Malaysia main source of energy? ›

Coal is the main energy source used to generate electricity. After the electricity is generated at a power plant, it goes by wire to a transformer that “steps up” the voltage. The electricity is then sent on a nationwide network of transmission lines made of aluminum.

Is Malaysia self sufficient in energy? ›

Per capita this is an average of 4,470 kWh. Malaysia could be self-sufficient with domestically produced energy. The total production of all electric energy producing facilities is 163 bn kWh, which is 109 percent of the country's own usage. Despite this, Malaysia trades energy with foreign countries.

What is Malaysia new energy policy? ›

By 2040, the NEP aims to reach an energy mix of 4% bioenergy, 4% solar, 9% hydropower, 27% oil products, 39% natural gas and 17% coal compared to 2018 numbers of 1% bioenergy, 0% solar, 6% hydropower, 30% oil products, 41% natural gas and 22% coal.

How can we reduce energy consumption in Malaysia? ›

  1. Turn off lights and fans before leaving the house. ...
  2. Clean the area around your air conditioner. ...
  3. Open up to natural light to save energy. ...
  4. Setting a timer on your air conditioner. ...
  5. Use Energy Star appliances and equipment.

What is the energy rating system developed by Malaysia? ›

The Green Building Index (GBI) is a first-generation rating tool for energy efficient buildings in Malaysia.

What are the most suitable renewable energy sources for Malaysia? ›

5 Types of Renewable Energy Sources in Malaysia
  • Solar Energy.
  • Hydro Energy.
  • Wind Energy.
  • Geothermal Energy.
  • Biomass Energy.
Nov 22, 2022

Why do we need renewable energy in Malaysia? ›

Renewable energy is currently contributing 23 per cent to Malaysia's energy mix[4] dominated by hydropower generation. As such, renewable energy plays one of the most important roles in reducing greenhouse gas emissions. It is one of the few clean, safe, and viable forms of alternative resources to fossil fuels.

What is the important of renewable energy in Malaysia? ›

Pursuing the energy transition pathway will save Malaysia up to USD 13 billion annually, reduce its emissions significantly, and diversify its energy supply. Kuala Lumpur, Malaysia, 09 March 2023 – New report confirms Malaysia's ability to meet its net zero goal with increased use of local and affordable renewables.

What is Malaysia consumer consumption? ›

KUALA LUMPUR (Jan 19): Real household spending in Malaysia is expected to grow by 5% year-on-year (y-o-y) in 2023 to reach RM1. 1 trillion, slowing down from 11.8% y-o-y growth in 2022, as recovery effects fade and growth returns to a new normal trajectory similar to that of pre-pandemic figures, said Fitch Solutions.

What is the consumption growth rate of Malaysia? ›

GDP records slowest increase since Q1 2022 in the fourth quarter. GDP growth moderated to 7.0% year on year in the fourth quarter, from 14.2% in the third quarter.

What is the total energy demand in Malaysia? ›

Total Energy Consumption

In 2020, consumption per capita was 2.8 toe. This is higher than neighbouring countries. Electricity consumption per capita has increased from 3 900 kWh per capita in 2010 to 4 700 kWh in 2020.

What are the top 3 natural resources in Malaysia? ›

Crude oil, refined petroleum, and, more recently, liquefied natural gas together account for a major portion of the country's commodity export earnings.

What are 3 renewable energy in Malaysia? ›

Malaysia has many renewable energy sources that can be developed such as solar, wind, biomass, hydro, geothermal and tidal wave.

What resources does Malaysia need? ›


Malaysia's most economically significant natural resource is tin; its tin deposits are the most extensive in the world. Other important natural resources are bauxite, copper, gold, iron ore, natural gas, petroleum, and timber.

Is Malaysia a self-sufficient country? ›

The country is not self-sufficient for many food items, and the situation is worsening. As a result, Malaysia is depending even more on imports, and the intake of proteins and micronutrients remains inadequate.

What are the energy security issues in Malaysia? ›

This study has identified two major issues concerning energy supply security in Malaysia, namely over-dependency to fossil fuel and increasing of energy import dependency.

What is an example of sustainable energy in Malaysia? ›

There are two (2) major types of renewable natural resources currently consumed in Malaysia; hydropower and solar energy. These average from 5-6% of the country's energy consumption source in the past 5 years.

Is Malaysia doing enough to ensure we have sustainable energy and transport system? ›

Malaysia is still a developing country and should not be compared to developed countries who are major powerhouses. Considerable progress has been made in Malaysia when it comes to renewable energy, but there are some challenges in the implementation of clean energy.

How to reduce global warming in Malaysia? ›

Invest in, generate electricity from clean energy

Electricity generation is the largest single contributor to greenhouse gas (GHG) emissions almost everywhere across the world, including Malaysia, driven by a reliance on fossil fuel inputs such as coal and natural gas.

What are energy efficiency initiatives measures taken up by Malaysia to promote energy efficiency? ›

5.1 Overview of Key Initiatives and Programmes. Key initiative 1: Promotion of 5-Star Rated Appliances. Key initiative 2: Minimum Energy Performance Standards (MEPS) Key initiative 3: Energy Audits and Energy Management in Buildings and Industries.

What is the power rating in Malaysia? ›

In Malaysia the standard voltage is 240 V and the frequency is 50 Hz. You can use your electric appliances in Malaysia, if the standard voltage in your country is in between 220 - 240 V (as is in the UK, Europe, Australia and most of Asia and Africa).

Who is the energy regulator of Malaysia? ›

Roles and Responsibilities. The Energy Commission is the regulator for the electricity and gas supply industry based on the powers provided by the Energy Commission Act 2001 and other related acts.

What is Malaysia's target for renewables? ›

KUALA LUMPUR, March 9 (Reuters) - Malaysia will need to double its investments in renewable energy transition to at least $375 billion in order to achieve its ambitious goal of carbon neutrality by 2050, the International Renewable Energy Agency (IRENA) said on Thursday.

What percentage of Malaysia energy is renewable? ›

Malaysia's renewable energy supply now at 25pct, on right track to achieve 2025 target. KUALA LUMPUR: Renewable energy (RE) supply in Malaysia is now at 25 per cent, the Dewan Rakyat was told today.

What is the first renewable energy in Malaysia? ›

Kuala Lumpur, 25 August 2022 – Clean energy specialist, Solarvest Holdings Berhad (“Solarvest” or the “Group”) has launched Malaysia's first renewable energy financial technology (“fintech”) platform, which is complementary to its solar financing solution – Powervest.

What is the energy sustainability policy in Malaysia? ›

Malaysia aims to increase renewables, excluding hydropower, to 20 percent of the generation mix by 2025. As part of the process, Malaysia is expected to expand renewable capacity from 6 to 14GW, rising from 18 to 30 percent of the generation mix.

Why wind energy is not popular in Malaysia? ›

Malaysia is generally known to experience a low wind speed area as compared to other countries. As Malaysia's mean annual wind speed is low at no more than 2 m/s, wind energy has not been successfully harnessed since most of wind turbines need a minimum speed of 4 m/s for electricity generation.

Why is green technology important in Malaysia? ›

The green technology agenda in Malaysia consists of a range of initiatives and policies which aim to increase the use of environment-friendly approaches in every sector to reduce the reliance on fossil fuels and environmental impact.

What is an example of a big project on renewable energy in Malaysia? ›

The solar PV power plant, located in Mukim Tanjung 12, Kuala Langat, Selangor, averts 76 000 tons of CO2 equivalent emissions per year, akin to an equivalent fuel displacement of about 36,000 cars off the Malaysian roads.

What is Malaysia renewable energy roadmap? ›

About MyRER

This target supports Malaysia's global climate commitment is to reduce its economy-wide carbon intensity (against GDP) of 45% in 2030 compared to 2005 level. Realization of the Government's vision is crucial in supporting the nation to achieve its Nationally Determined Contributions (NDC) targets.

What are the advantages of using solar energy in Malaysia? ›

Pros and Cons of Solar Energy
Advantages of Solar EnergyDisadvantages of Solar Energy
Renewable Energy SourceCost
Reduces Electricity BillsWeather Dependent
Diverse ApplicationsSolar Energy Storage is Expensive
Low Maintenance CostsUses a Lot of Space
1 more row
Apr 13, 2023

How is consumer protection in Malaysia? ›

If you are not satisfied with the price or even quality of goods and services you received, you can lodge a complaint with the Ministry of Domestic Trade, Co-operatives and Consumerism. As a consumer, you are protected under the Consumer Protection Act 1999.

What do Malaysians spend on? ›

Malaysians are spending almost 70% of their monthly income on goods, housing and transport, said Domestic Trade and Consumer Affairs Minister, Datuk Seri Saifuddin Nasution Ismail. A report by the World Bank Group has revealed that the three components also make up a bulk of the cost of living of the average Malaysian.

Why is there a growing consumer market in Malaysia? ›

This is thanks in part to strong purchasing power, supported by an expanding middle class and rising household income. As shown in the chart below, retail sales have grown at a high single‑digit rate for each of the past two years.

What is the main economy of Malaysia? ›

Manufacturing has a large influence in the country's economy, accounting for over 40% of the GDP. Malaysia is also the world's largest Islamic banking and financial centre.

What is Malaysia biggest economy? ›

According to the World Bank, Malaysia is an upper-middle income country. The manufacturing sector, including electronics, has emerged as the leading economic sector, followed by agriculture (agriculture, livestock, forestry and fisheries), and the retailing and hospitality sectors.

How much consumption does Malaysia have in economy? ›

Malaysia Private Consumption accounted for 56.7 % of its Nominal GDP in Dec 2022, compared with a ratio of 59.4 % in the previous quarter. Malaysia Private Consumption contribution to Nominal GDP ratio is updated quarterly, available from Mar 1991 to Dec 2022, with an average share of 48.0 %.

What is the primary energy consumption in Malaysia? ›

Energy consumption

Petroleum and other liquids and natural gas are the primary energy sources consumed in Malaysia, with estimated shares of 37% and 36%, respectively, in 2019. Coal meets about 21% of the country's energy consumption. Renewable energy accounts for 6% of total consumption (Figure 7).

What is the average electricity usage per day in Malaysia? ›

The measurement results showed that the average energy consumption is 25.8 kWh/day during weekend and 21.9 kWh/day during weekdays with 11.5 kWh/day for the air conditioner only.

What percentage of energy use is residential? ›

In 2021, the U.S. residential sector consumed 20.9 quadrillion Btu of primary energy, 22% of U.S. primary energy consumption.

How much energy is used in residential? ›

In 2021, the average annual electricity consumption for a U.S. residential utility customer was 10,632 kilowatthours (kWh), an average of about 886 kWh per month.

What is the household electricity consumption per capita in Malaysia? ›

This is higher than neighbouring countries. Electricity consumption per capita has increased from 3 900 kWh per capita in 2010 to 4 700 kWh in 2020.

How much electricity is consumed in Malaysia? ›

Amount of electricity consumed in Malaysia 2014-2021

In 2021, the amount of electricity consumed in Malaysia totaled more than 145 billion kilowatt hours (kWh), an increase compared to the previous year.

Which residential usage consumes the largest amount of energy? ›

More than half of energy use in homes is for heating and air conditioning.

How does residential energy use affect climate change? ›

Burning fossil fuels for electricity is one of the largest sources of heat-trapping greenhouse gas emissions in the United States (see the U.S. Greenhouse Gas Emissions indicator). The opposite effect could take place with winter heating.

What consumes the most energy at home? ›

Top five energy consuming home appliances
  • Wet appliances. Washing machines, dishwashers and tumble dryers account for 14% of a typical energy bill, taking the top spot in our list. ...
  • Cold appliances. ...
  • Consumer electronics. ...
  • Lighting. ...
  • Cooking.
Jan 14, 2022

What four factors affect the amount of energy a household uses? ›

4 Factors That Affect Your Home's Energy Efficiency
  • Harsh Weather Conditions. Seasonal changes and fluctuating temperatures can take a toll on energy efficiency, especially if your home is not well-maintained. ...
  • Humidity. ...
  • Drafts. ...
  • Insulation.
Jan 17, 2023

How can we calculate how much energy we use at home? ›

To calculate consumption, you multiply the power in kW by the hours you use the devices per day, per week or per month. For example, let's examine the consumption at the home of Agnes and Roman: The TV has a power of 200 W, that is, 0.2 kW. They have it on for 2 hours a day, so their daily consumption is 0.4kWh.

How much energy does a household use over time? ›

Since 1980, per-household energy consumption has been reduced 16.7 percent, while a 13.5 percent increase in households has been observed.

What is the household power supply in Malaysia? ›

Malaysia operates on a 240V supply voltage and 50Hz.

What is the household consumption data in Malaysia? ›

It excludes purchases of dwellings but includes imputed rent for owner-occupied dwellings.
Household expenditure per capita in Malaysia from 2008 to 2020 (in constant 2010 U.S. dollars)
CharacteristicHousehold consumption per capita in constant 2010 U.S. dollars
9 more rows
Oct 5, 2022

How much does household electricity cost in Malaysia? ›

How do we calculate it?
First 200 kWh (1-200 kWh) per month:( * 38.00)/100= RM 76.00
Next 300 kWh (301-600 kWh) per month:( * 51.60)/100= RM 76.00
Next 300 kWh (601-900 kWh) per month:( * 54.60)/100= RM 76.00
Next 901 kWh onwards per month:( * 57.10)/100= RM 76.00
Estimated Bill:=
1 more row


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