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View of Consumer-Related Food Waste from the Perspectives of Selected Demographic Variables


Academic year: 2023

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Consumer-Related Food Waste from the Perspectives of Selected Demographic Variables

1* Cheam Chai Li

Faculty of Business and Management,

Universiti Teknologi MARA Kelantan, 18500 Machang, Kelantan, Malaysia

*Corresponding Author Email: chailicheam@uitm.edu.my

Received: 5th September 2022 Accepted: 14th October 2022 Published: 17th January 2023 ABSTRACT

Human reactions to food waste are significant and diverse. A sociodemographic factor whose effects on food waste have received extensive attention in the scientific literature. To reduce consumer-related food waste, it is essential to have a thorough understanding of consumer demographics and factors that affect food waste. In light of this, the primary goal of the study is to understand the issues associated with respondents' demographics (gender, education levels, marital status and residential areas), as well as the consumer food waste key variables (behaviour, ethic, knowledge, Covid19, and festival) using independent t-test and Chi Square. The test of differences revealed significant differences in festival scores between men and women as well as significant ethical differences across educational levels and marital status. On the other hand, a cross-sectional study revealed a relationship between respondents' weekly meal plans and residential areas, but not gender. Because negative externalities occur across the whole food lifecycle and have a detrimental influence on the economy, social, and environment, reducing and preventing food waste is crucial and demands for immediate action. The attempts to reduce per capita global food waste at the consumer level will only be successful with the support and cooperation of consumers themselves, the food industry, and the government. It is hoped that the study's findings, conclusions, and recommendations would provide policymakers with some ideas for developing an effective strategy to raise awareness of food waste and minimize it at consumer level.

Keywords: Demographics, food waste behaviour, knowledge, covid19, ethics OPEN ACCESS


Human reactions to food waste are significant and diverse.

According to research, consumers are the single largest contributor to the total volume of food waste generated, surpassing waste made during the harvesting, processing, and distribution of food (Griffin, Sobal, & Lyson, 2009). This is supported by a study conducted by Aschemann-Witzel (2015), which revealed consumer-related food waste to be a complicated and diverse issue. In other words, cultural, social, political, economic, and geographic forces, as well as cognitive, motivational, and structural elements, food-related behaviours, and food habits, are said to have an impact on food waste.

Generally, food waste is closely linked to both the behaviour of the food service provider and the behaviour of the consumers (Segrè, 2014). It's a global problem that exemplifies the unsustainable food production and consumption system (Silva, 2016). This level of food waste is significant not only in terms of monetary loss to households, but also in terms of natural resource waste, food supply in underdeveloped nations, and greenhouse gas emissions (Stuart, 2009). Improper waste management, particularly food waste, can have an impact on a country's environmental

quality (Lai, Lim, Teh, & Yeap, 2017). If this continues, the country may find itself with an overwhelming food waste problem that endangers both the environment and the people who live nearby. This is due to the fact that when food is thrown away, the water and energy used to cultivate, harvest, transport, and package it are also wasted. Methane, a greenhouse gas that is substantially more potent than carbon dioxide, is emitted as food decomposes in landfills. There are 2.5 kg of greenhouse gases released for every 1 kg of food that is dumped in a landfill. The environmental effects of food waste are undeniable, as every meal that ends up in a landfill produces CO2 that contributes to pollution. With the food system accounting for more than 11% of all greenhouse gas (GHG) emissions, food waste is currently one of the major causes of GHG emissions worldwide. In turn, this leads to more serious problems including climate change, air pollution, and water contamination (Azureen 2022). According to the United Nations, food waste is a social issue that is relevant to everyone because it threatens the economic and environmental sustainability of the food supply chain, causes food insecurity, and exacerbates social injustice (Parfitt et al., 2010). All the negative effects of reducing food waste may be eliminated, leaving only 6% to 8% of all greenhouse gas emissions attributable to human activity.



One-third of all food produced worldwide is lost or discarded, which highlights how important the problem of food waste is in the modern world (Blakeney, 2019). Malaysia has not escaped the wrath of the international community. With a population of more than 32 million people, Malaysia has experienced significant economic expansion during the last five decades.

Malaysia is ranked 41st out of 113 nations in the world for food security, according to the Global Food Security Index.

Malaysia is regarded as a culinary paradise by both residents and tourists. Despite these successes, the Solid Waste Management and Public Cleansing Corporation (SWCorp) estimates that Malaysians wasted 16,688 tonnes of food every day in 2017 (Mohd Sharif, 2018). During the holiday season, the quantity of food waste could increase by 15% to 20%. The big issue with some wasted food is that it is still edible, and it has been discovered that there is enough food waste to feed 12 million people. As such, a thorough analysis of consumer demographics and food waste-related variables is essential when focusing on minimising consumer-related food waste.

Due to its serious environmental consequences, food waste is viewed as one of the sustainability issues that has to be addressed (Aschemann-Witzel, et al. 2015).

Sociodemographic elements like gender and employment position may have an impact on food provisioning behaviours, leading to food waste (Koivupuro et al. 2012). Evidence, however, indicates that sociodemographic characteristics can only predict a small amount of food waste (Stancu et al., 2016 and Falasconi et al. 2019). For instance, in the previous studies, it was found that socio-demographic factors only explain for 7–13% of the variation in the intention to minimise and perceived behavioural control to prevent household food waste (Visschers et al. 2016 and Van derWerf et al. 2019).

Purchasing more food than they need, then throwing it away, costs consumers millions of Ringgit per year. According to the then housing and local government minister, each household in Malaysia spends roughly RM210 per month, or RM2,600 annually, to dispose of food that is wasted. By 2025, it was anticipated that processing food waste will cost households between RM160 and RM400, up from the present range of RM60 to RM150 (Azureen, 2022). It's unfair, damaging, and almost always preventable. Typically, consumer behavior—

which is influenced by perception—leads to food waste at the individual consumer level. Even though food waste is a major ethical concern, it is also difficult for even experienced customers to use their knowledge on a regular basis due to ignorance (Porpino et al. 2016). Additionally, as a result of store panic buying and restaurant closures in response to the Covid-19 outbreak, there may be an increase in domestic food waste at a time. Therefore, it's also critical to determine whether Covid-19-related changes in food shopping and consumption patterns have had a major impact on household food waste. According to the GM of the nonprofit The Lost Food Project (TLFP) Food waste decreased at times, particularly after the first Movement Control Order (MCO) in 2020. This is supported by SWCorp data, which revealed that Malaysia averaged roughly 1.7 tonnes of waste per day in April 2020 (once MCO was in full force), down from an average of about 2.1 tonnes in March 2020. However, once the restrictions were removed, the numbers increased once more

around June to July, reaching about 2.2 to 2.3 tonnes everyday (Azreen 2022).

Based on the aforementioned, it can be seen that food waste is unacceptable in terms of behaviour, ethics, knowledge, festivals, and COVID19. This is congruent with Martin-Rios et al. (2018) s’ moral, socioeconomic, and environmental perspective. Therefore, a thorough understanding of its underlying causes at the individual level is important to prevent food waste (Fanelli, 2019). Moreover, Malaysia pledged last year to achieve emission reductions by 2050 and to lower the GDP's intensity of greenhouse gas emissions by 45% through 2030. Therefore, it is important to reduce foodwaste throughout all levels. The expense of food waste and its detrimental impact on the environment make it necessary to determine the factors that influence it. By analysing respondents' demographics (gender, educational attainment, marital status and residence locations) and the key variables (behaviour, ethic, knowledge, Covid19, and festivals), the study aims to provide some insight into the issues of consumer food waste.


In our lives, food serves a range of purposes, from supplying energy to fostering social bonds. Therefore, customers should refrain from throwing away these meals in the first place. Food waste can be defined as the food that was meant for human consumption but was instead composted, fed to animals, recycled, or treated for energy recovery (WRAP UK, nd).

While food waste responsibility is described as the deliberate process of becoming aware of the potential for food waste and adopting preventative measures to avoid it. Understanding food's date labels, conserving leftovers for later meals, and creating a shopping plan are a few categories of activities that can be used to promote "positive" food waste behaviour (Mond ejar-Jim enez et al., 2016).

Aschemann-Witzel et al. (2015) provided a fascinating model of the factors influencing consumer behaviour with regard to food waste. The model includes socio-demographic and psychological components, all of which are crucial for understanding consumer behaviour with respect to food waste. The concept heavily relies on psychological elements, including motivation based on financial rewards, ethical reasons, religious, and environmental concern. The authors emphasised that household type and size had an impact on attitudes toward food waste, while giving socio-demographic indicators less significance. Based on a few studies on behaviour, von Kameke and Fischer (2018) discovered that young people are more likely to change their behaviour to conserve food, O'Brien (2008) contended that food waste is directly related to the routines that develop under particular conditions, and Steg and Vlek (2009) discovered that people's homes, neighbourhoods, and communities can have a big impact on how sustainably they behave.

Food waste knowledge is defined as people's awareness, understanding, or information about food waste gained via experience or research. Consumers' lack of knowledge about food waste has led to a lack of awareness and behaviour when it comes to managing food waste (Aschemann-Witzel et al., 2015). As a result, the issue of food waste has drawn attention



to the fact that a lack of knowledge and skills frequently affects household behaviour (Radzyminska, 2016). People are less likely to engage in waste prevention activities if they are unaware of the issue of food waste (Miafodzyey, 2013). It has been suggested that education and communication are the most effective methods for changing behaviour (Whitehair et al., 2013). This concurred with Wu et al's (2019) theory that people might acquire the skills necessary to prevent food waste through education. Barr (2007) found that people are more likely to refrain from wasting food if they have a solid awareness of the problems associated with it. The unfortunate fact is that people may be aware of some ways to manage food in their homes to prevent food waste, but they may not act on that knowledge (Aschemann-Witzel, et. al, 2015).

As mentioned previously, food waste can be tackled from a variety of perspectives, including ethically. When it comes to food waste ethics, people's acceptance of food waste is dependent on their own set of values, guiding principles, and societal norms. The degree to which people are aware of, understand, and embrace the ethical views around food waste can lead to a shift in behaviour, and therefore a transition to a more sustainable, socially responsible way of life.

Due to economic instability brought on by changes in food prices and the Covid19 pandemic, food waste will probably increase in the severe circumstances (Akter, 2020). People rushed to hoard food and essential items during the COVID19 epidemic, which resulted in a sharp increase in demand at grocery stores (Garbe et al., 2020). Additionally, it is known that during the crisis with movement restrictions have been put in place by the government, more food would likely be cooked and consumed at home, and there is a tendency for food preparation waste (Quested and Murphy, 2014). However, as individuals become more accustomed to food preparation and preservation methods with more time and practice (Amicarelli and Bux, 2020 ; Roe et al., 2020 ), there is also a possibility that less food will end up on plates (Roe et al., 2018). Given the conflicting consumer responses that may both raise and decrease waste through various mechanisms, the relationship between behaviour changes caused by the pandemic and ultimate food waste creation has not been adequately examined (Ikiz et al., 2021).

Previous research has shown relationships between the post- consumer food waste factors. Also important and deserving of investigation are consumer sociodemographic characteristics.

First, different gender interpretations were offered with respect to food waste. According to one study, women waste less food than males do (Cicatiello, Secondi, & Principato, 2019;

Schmidt, 2016), although other literature sources claim that gender has no effect on how much food is wasted (Porpino et al., 2015). In comparison to female students, male students waste less staple food (Wu et al., 2019). When comparing male and female customers, males were more likely to finish their meal (Zhao and Manning, 2019). In Silvennoinen et al., (2014) and Koivupuro et al., (2012) studies, they claimed that single women generate greater food waste than single men or couples. Several studies (Baker, Fear and Denniss, 2009;

Williams, Wilkstrom, Otterbring, Lofgren and Gustavsson, 2012) have found that when the number of family members increases, the average amount of food wasted per person

reduces. However, several research did not discover a significant link between education level and food waste (Hair, Sarstedt, Ringle, & Mena, 2012). Some literature revealed a link between employment and the amount of food waste. In terms of residential locations, Kambo et al. (2017a) and Osmani and Kambo (2018) discovered a number of socioeconomic characteristics, including education level and age, that affect how much food is wasted in Albanian. In fact, they discovered a link between residential area, age, and the amount of food waste. With respect to ethics, research reveals that women frequently feel guilty when they waste food because they see it as a sign that they are ineffectively running the home and aren't providing for their family (Lyndhurst, 2007). Qi and Roe's (2016) study, which discovered that women are more likely to feel guilty when they had to throw food away, came to similar conclusions.


Convenient sampling was performed in June and July, 2021 to collect the sample for this research. A link to an online survey was provided to the respondents after they were contacted via Whatapp groups. In 2020, there were around 22.3 million people in Malaysia who are working age (16 to 64) (DOSM, 2020). The study’s sampling frame, however, only included respondents with tertiary education and who were between the ages of 31 and 41. On the basis of this, Krejcie and Morgan (1970) determined that the sample size was roughly 384. 32 responders were dismissed, however, when their responses were examined for blank spaces and straight lines. As a result, 552 responses from the survey were usable.

The first part of the questionnaires covered demographics, the subsequent parts covered knowledge, behaviour, ethics, Covid19 pandemic and festive seasons. The last several parts used Likert scales, which range from 1 for very strongly disagreeing to 7 for very strongly agreeing. The questionnaires were modified and incorporated from previous studies, such as those by Adriana Burlea-Schiopoiu et al.

(2020) on food waste behaviour, ethics, and the Covid19 epidemic; Abdelradi (2018) and Dalilawati and Khana (2019) on knowledge, and Aktas et al. (2019) on festivals.

The Statistical Package for Social Sciences for Windows was used to complete the data analysis (SPSS, v24.0). To begin, the Kaiser-Meyer-Olkin Measure (KMO) test was used to determine factor analysis applicability. It was determined that it was significant, thus factor analysis was carried out. The use of factor analysis to analyse and validate the internal structure of instruments is one of the most useful ways (Nunnally 1978, Henson & Roberts 2006). Next, the instruments were investigated using principal components analysis with varimax rotation. The data was evaluated for reliability using Cronbach's alpha test after the instruments were confirmed.

This is done to guarantee that all of the questions in a variable are measuring the same underlying characteristics. These significant variables were also subjected to a normality test using kurtosis and skewness. The skewness and kurtosis rules of thumb are 1 and 7, respectively. In addition, descriptive statistics (frequency) were employed to describe the sociodemographic of respondents as well as the mean scores for the main factors.



The first analysis of the study was to compare the means of major variables (such as knowledge, behaviour, ethics, covid19 and festival) and demographic variables (gender, education and marital status) using test of differences. For instance, male and female (gender subgroups) were compared for the mean scores associated with the main variables to see if they were scored differently, and then the effect size was calculated (eta squared). Eta squared shows how much of the variance of the dependent variable is explained by the independent variable (Pallant, 2001). Cohen (1988) standards were utilised in the study to determine the significance of the effect size. Next, Chi square tests were used to see whether a person's weekly plan to reduce food waste for both gender and residential area were related.


Table 1 summarizes the demographic profile of the respondents. In summary, respondents range in age from 31 to 40 years old, and the sample size is 552. It was female- dominated at 71.2% (393). Majority of them (90.4%, 499) were single and more than half of them were holding Bachelor’s degree (62.1%, 343). Regardless, more than half (63%, 348) of the respondents expressed that they planned their weekly meals to avoid food waste.

Table 1: demographic of respondents

Frequency percentage Gender


female 159

393 28.8

71.2 Marital status


Married 499

53 90.4

9.6 Highest education qualification

Bachelor’s degree

Diploma / certificate 343

209 62.1

37.9 Residential area


Rural 303

249 54.9

45.1 Do you plan your weekly meals

to avoid food waste?


No 348

204 63.0

37.0 The descriptive analysis of the research was displayed in Table 2. The individuals were marginally more likely to avoid food waste based on knowledge (M=5.58, SD=0.99), behaviour (M=5.55, SD=1.14), ethics (M=6.07, SD=0.96), and Covid19 (M=4.55, SD=0.94). When it came to food waste, participants' assessment on the Festive (M=4.21, SD=1.63) was slightly higher than average.

These significant variables were also subjected to a normality test. Table 2 shows the univariate skewness and kurtosis results, where the skewness and kurtosis of knowledge, behaviour, ethics, covid19, and festive were all within ±1 and

±7. As a result, all five key variables in the study were found to be normally distributed.

Table 2: Descriptive and Normality for the Major Variables

Variable Mean SD Skewnes

s Kurtosis

KNOW 5.58 0.988 -0.420 -0.250

BHV 5.55 1.138 -0.485 -0.512

ETH 6.07 0.956 -1.088 1.425

COVID 4.55 0.940 0.731 0.451

FES 4.21 1.620 -0.193 -0.814

The major variables were then subjected to reliabilities tests.

Nunnally (1978) estimates that established scales have a reliability of 0.8-0.9. The study's Cronbach alpha was greater than 0.7, with 0.881, 0.775, and 0.746 for festive, ethnics, and knowledge, respectively, as indicated in Table 3. The behaviour and covid scales, on the other hand, were both between 5 and 6 (0.636 and 0.556, respectively). The following items were eliminated: three for factor behaviour, two for covid19, and one each for the ethical and festive variables.

The paragraphs that follow explained the results of the factor analysis. The Kaiser-Meyer-Olkin Measure of Sampling Adequacy (KMO) was originally explained in the study. The KMO method was used to assess the data's appropriateness for factor analysis. The KMO number was 0.830, and since it was higher than 0.50, it suggested a meritorious index, indicating that the study's KMO met the requirement.

Simultaneously, Barlett's test revealed a result of 7849.84 with a significance of 0.001. This revealed that the variables were not correlated, allowing for factor analysis. After these two tests, the researcher felt secure enough to proceed with factor analysis.

The variance in observed variables explained by a common cause is referred to as communalities. Exploratory Factor Analysis (EFA) is mainly concerned with communality. Table 3 shows that 14 of the items evaluated met the communality criterion with extraction values greater than 0.5. The tighter the association between the variable and the specified parameters, the higher the communalities value. If KN1 has a value of 0.791, for example, it can explain 79.1% of the factor.

Similarly, all of the other components have a value greater than 0.5, indicating that they can all adequately explain the factor.

Measures of Sampling Adequacy (MSA) were used to determine anti-image correlation, with the value acquired by looking at the diagonal value with the 'a' alphabet next to each value in SPSS. 14 of the 21 items examined met the MSA criteria (above 0.5), while the remaining 7 were found to be less than 0.5. As a result, the low factor value entries were removed from the list, leaving 14 items out of the original 21.

Further factor analysis was possible with these 14 items.

Factor determination was the final stage in factor loading. The loadings were checked using a rotating component matrix to determine which item belongs to which factor (show the correlation between items and the construct). Principal Components Extraction and Varimax Rotation were used because the data set was without independent and dependent variables. The loading and cross loading were both more than



0.5, according to the findings (refer Table 3). It revealed the loading factor coefficients of 14 items in 1, 2, 3, 4, and 5 factors, which corresponded to Rotated Component Matrix (exhibited in Table 3). Items FES1, FES2, and FES3 were found to be linked with factor 1, with values ranging from 0.839 to 0.876. ETH1, ETH2, and ETH3 were linked with factor 2 with values of 0.794, 0.854, and 0.726 correspondingly. Factor

3 was linked with KN1, KN2, KN3, and KN4 with values of 0.791, 0.792, 0.587, and 0.644 respectively. BEV2 and BEV4 were connected with factor 4 with values of 0.789 and 0.822, respectively, and the remaining two items, COV1 and COV2, were correlated with factor 5 with values of 0.627 and 0.675, respectively.

Table 3: Factor Analysis Results

items 1 2 3 4 5 Communalities Anti-image

correlation KN1


.856 .876 .839

.794 .854 .726

.791 .792 .587 .644

.789 .822

.627 .675

.680 .666 .603 .650 .697 .727 .689 .751 .607 .645 .725 .736 .783 .712

.865 .873 .901 .855 .755 .811 .832 .805 .876 .897 .930 .775 .733 .791 Cronbach 0.881 0.775 0.746 0.636 0.556

Eigenvalue 3.871 2.621 1.415 1.004 0.761

% of variance 27.653 18.723 10.108 7.169 5.435

An independent sample t-test was performed to examine the key components' mean scores for gender, education, and marital status. The research findings are summarised in Table 4. First, the gender and major factors mean values are compared. In terms of festival, males (M=4.53, SD=1.551) and females (M=4.07, SD=1.631; t(550)=3.040, p<0.01) scored considerably differently. The magnitude of the changes in the means, on the other hand, was quite small (eta square=0.016), indicating that gender could account for 2% of the variance for the variable festival. Overall, the mean scores for the other four major variables—knowledge, behaviour, ethics, and covid19—were not substantially different based on gender.

When the averages of diploma and degree were evaluated against the primary factors, it was discovered that the ethic variable had substantially different mean scores for Degree

(M=6.13, SD=0.918) and Diploma (M=5.96, SD=1.008;

t(550)=2.030, p<0.05). The differences in mean scores were relatively tiny (eta square=0.00744). Overall, based on educational levels, the mean scores for the other four major categories—knowledge, behaviour, COVID19, and festival—

were not significantly different.

When the mean marital status scores were compared to the major variables, the mean ethical scores for single (M=6.04, SD=0.942) and married (M=6.30, SD=1.053; t(550)=-1.891, p<0.1) were substantially different. On the other hand, the size of the changes in the means was minimal (eta square=0.006).

However, there were no significant differences in mean evaluations for the other key factors, namely knowledge, behaviour, covid19, and festival, when it came to marital status.

Table 4: Differences in the major variables by Gender, Education and Marital Status

Knowledge Behaviour Ethics Covid19 Festival


Male 5.61 5.47 6.11 4.61 4.53

Female 5.57 5.58 6.05 4.52 4.07

t-value 0.394 -1.02 0.666 0.895 3.04

p-value 0.694 0.308 0.506 0.372 0.002*


Degree 5.61 5.56 6.13 4.5 4.15

Diploma 5.53 5.54 5.96 4.62 4.29

t-value 0.886 0.153 2.03 -1.421 -0.973



p-value 0.372 0.879 0.043** 0.156 0.331

Marital status

Single 5.59 5.54 6.04 4.56 4.21

Married 5.53 5.65 6.30 4.44 4.13

t-value 0.341 -0.662 -1.891 0.844 0.246

p-value 0.702 0.509 0.059*** 0.399 0.739

Note: P<0.1***, p<0.05**, p<0.01*

Last but not least was the results of the cross-tabulation analysis. The study's purpose was to see if both gender and residential area had any relation on respondents' weekly meal plans in order to prevent food wastage. Table 5 shows that 16.8% of males said yes to weekly meal planning to reduce food waste, compared to 46.2 % of females. According to the chi square value of 1.722, there were no differences in respondent weekly meal plans for gender. When it was examined if the residential location and the weekly plan to avoid food waste are related, the results in Table 6 reveal that 36.6% of those in the urban region say yes to weekly meal planning to avoid food waste, while only 26.4% of those in the rural area say yes. The chi square value of 3.448 is significant and this indicates that the weekly food plans and residential areas of respondents are related at 10% significant level.

Table 5: Cross tabulation between gender and Plan weekly meals to avoid food waste

Variable N Chi Square

No Yes

Gender Female 25 46.2 393 1.722 (0.189) Male 12 16.8 159

Table 6: Cross tabulation between residential area and Plan weekly meals to avoid food waste

Variable N Chi

Square No Yes


area Urban 18.3 36.6 303 3.448 (0.063)***

Rural 18.7 26.4 249

***P<0.1 5. CONCLUSION

Food waste is a major source of concern in Malaysia these days, since it leads to market inefficiencies, social injustice, and pollution, all of which threaten the planet's long-term survival. As a result, this research was conducted and the purpose of the study is to shed some insight on the issue of consumer food waste by reporting the findings and discussing respondents' demographics, such as gender, residential areas, marital status and educational levels, as well as the study’s major variables (behaviour, ethic, knowledge, Covid19, and festival).

The findings suggest that there were substantial disparities in festival scores between males and females for test of differences. However, the differences are minor, with both

genders being more accepting of festive factor that affect food waste. Besides, there were also differences for education and marital status on ethics with respect to food waste behaviour.

Education can help people understand how to prevent food waste, claim Wu et al (2019). While Williams et al. (2012) said that the average amount of food wasted per person decreases as the number of family members rises. The educated individuals and married couples with bigger family size probably believe that wasting food when so many people can't afford to eat is unethical.

When the study looked at cross-sectional data, however, there were no differences in respondent weekly meal plans and gender. According to Lee and Paik (2011), gender has little influence on food separation or recycling behaviour. This is in line with the findings of Stancu, et al. (2016) and Falasconi, et al. (2019), who found that socioeconomic determinants have minimal predictive power for food waste. On the other hand, the study discovered a relation between respondents' weekly meal plans and their living areas, this is consistent to the study by Steg and Vlek (2009). This was most likely owing to the fact that the expense of living in cities is higher than in rural areas.

As a result, folks who live in cities are more resilient when it comes to food, resulting in less food waste.

All parties involved, including consumers, the food industry, and the government, must act rapidly to address the issue of food waste given that it has an immediate impact on the economy, social, and environment. This will help to reduce per capita global food waste at the consumer level. First of all, consumers must value foods and adjust their attitudes and behaviours when it comes to eating. The easiest method to reduce food waste is to plan their meals ahead of time by developing a shopping list especially during festive seasons.

If they have to eat outside, they must do so wisely and ethically. On a daily basis, consumers can practise the three Rs at home namely reduce, reuse, and cycle. In addition, Individual customers can compost their own food waste at home using leftovers. Cleaning detergents and soil fertilizers are among the products of composting and it, too, might enable a family to save money. Hunger claims the lives of more people every year. As a results, industries' feeding the hungry initiatives has been introduced. The food and beverages industries such as restaurants, hotels, bakeries, and other businesses related to food and beverage can help the community by donating excess food to feed the hungry and reduce food waste. Some non-governmental organisations (NGOs) and the government have begun to implement a scheme known as food banks in some parts of Malaysia. The non-profit organization would gather excess cooked, non-perishable food as well as uncooked, raw food and distribute it to orphanages, welfare homes, and the poor.



As government initiatives to raise public awareness and foster a culture of environmental concern, The Lost Food Project (TLFP) was able to increase the number of partners who donated food as a result of the Food Donor's Bill (Malaysian Food Donors Protection Act 2020) being introduced in 2019 and then gazetted in 2021. Many people in the food industry were persuaded to donate their excess without worrying about the consequences. This demonstrates how policies have an impact on this issue. Besides, tax incentives for food donors could be another modification in policy that may be made, as in-kind donations currently are not rewarded in the same way that monetary donations are (Azreen 2022).

It is hoped that the study's findings, conclusions and recommendations would provide policymakers with some suggestions for developing a sound strategy to raise consumer awareness of food waste and minimize it at the source.


Abdelradi, F. Food waste behaviour at the household level: A conceptual framework. Waste Management 2018, 71, 485-493.

Abe, K. and Akamatsu, R. (2015), Japanese children and plate waste:

contexts of low self-efficacy, Health Education Journal, 74 (1), 74-83, doi: 10.1177/0017896913519429.

Adriana Burlea-Schiopoiu, Radu Florin Ogarca, Catalin Mihail Barbu, Liviu Craciun, Ionut Cosmin Baloi, Laurentiu Stelian Mihai, (2021) The impact of COVID-19 pandemic on food waste behaviour of young people, Journal of Cleaner Production, 294, https://doi.org/10.1016/j.jclepro.2021.126333.

Akter, S., (2020). The impact of COVID-19 related ‘stay-at-home’ restrictions on food prices in Europe: findings from a preliminary analysis. Food Secur. 12, 719–725. doi: 10.1007/s12571- 020- 01082- 3 . Amicarelli, V., Bux, C., (2020). Food waste in Italian households during the

Covid-19 pandemic: a self-reporting approach. Food Secur. 1–13. doi:

10.1007/s12571- 020- 01121- z .

Aschemann-Witzel, J., de Hooge, I., Amani, P., Bech-Larsen, T., & Oostindjer, M. (2015). Consumer-Related Food Waste: Causes and Potential for

Action. Sustainability, 7(6), 6457–6477.


Azreen Hani, (2022, Feb 15) Malaysia throws away 17,000 tonnes of food daily. The Malaysian Reserve. Available at https://themalaysianreserve.com/2022/02/15/malaysia-throws-away- 17000-tonnes-of-food-daily/

Baker, D., J. Fear, and R. Denniss. 2009. What a waste—An analysis of household expenditure on food. Policy Brief No. 6. www.tai.

org.au/sites/defualt/files/PB6Whatawastefinal_7.pdf. Accessed 11 February 2017

Barr, S., (2007), Factors influencing environmental attitudes and behaviours:

a UL case study of household waste management, Environment and Behavior, 39(4), 435-473.

Bernama (2022, April 26) Malaysian households lose RM210m a month in food waste disposal – minister, Bernama. Available at retrieved https://www.malaysiakini.com/news/619269

Bisogni, C. A., Connors, M., Devine, C. M., & Sobal, J. (2002). Who we are and how we eat: A qualitative study of identities in food choice. Journal of Nutrition Education and Behavior, 34(3), 128–139.

Blakeney, M. (2019). Food Loss and Food Waste: Causes and Solutions.

Cheltenham, UK: Edward Elgar Publishing.

Bojanic, D. and Xu, Y. (2006). An investigation of acculturation and the dining- out behavior of Chinese living in the United States. International Journal of Hospitality Management, 25(2), 211-226.

Boulet, M., Wright, B., Williams, C. and Rickinson,M. (2019), Return to sender:

a behavioural approach to reducing food waste in schools, Australasian Journal of Environmental Management, (26), 4, 328-346, doi: 10.1080/14486563.2019.1672587.

Cicatiello, C., Secondi, L., & Principato, L. (2019). Investigating consumers’

perception of discounted suboptimal products at retail stores.

Resources, 8(3), 129-134. doi:


Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum Associates, Publishers.

Essay Sauce (n.d) Correlation between food waste and different ethnic

groups. retrieved on jan 2021 at



Falasconi, L.; Cicatiello, C.; Franco, S.; Segrè, A.; Setti, M.; Vittuari, (2019) M. Such a shame! A study on self-perception of household food waste.

Sustainability, 11, 270.

Fanelli, R.M (2019). Using Causal Maps to Analyse the Major Root Causes of Household Food Waste: Results of a Survey among People from Central and Southern Italy. Sustainability, 11, 1183.

Garbe, L., Rau, R., Toppe, T., (2020). Influence of perceived threat of Covid- 19 and HEXACO personality traits on toilet paper stockpiling. PLoS One 15, e0234232. doi: 10.1371/journal.pone.0234232.

Graham-Rowe, E., Jessop, D.C., Sparks, P., (2015), Predicting household food waste reduction using an extended theory of planned behaviour, Resources, Conservation and Recycling, 101, 194-202.

Griffin, M., Sobal, J., & Lyson, T. A. (2009). An analysis of a community food waste stream. Agriculture and Human Values, 26(1–2), 67–81.

Hair, J. F., Sarstedt, M., Ringle, C.M., &Mena, J. A. (2012). An assessment of the use of partial least squares structural equation modeling in marketing research. Journal of the Academy of Marketing Science, 40(3), 414–433.

Henson, R. K and J. Kyle Roberts (2006), Use of Exploratory Factor Analysis in Published Research: Common Errors and Some Comment on Improved Practice. Educational and Psychological Measurement.

66(3), 393-416

Ikiz, E., Maclaren, V.W., Alfred, E., Sivanesan, S., (2021). Impact of COVID- 19 on household waste flows, diversion and reuse: the case of multi- residential buildings in Toronto. Canada. Resources, Conservation &

Recycling, 164, 105111. doi: 10.1016/j.resconrec.2020.105111.

Izumi, B.T., Akamatsu, R., Shanks, C.B. and Fujisaki, K. (2020), An ethnographic study exploring factors that minimize lunch waste in Tokyo elementary schools, Public Health Nutrition, (23), 6, 1142-1151, doi: 10.1017/S136898001900380X.

Jackson, P., Del Aguila, R.P., Clarke, I., Hallsworth, A., De Kervenoael, R.

and Kirkup, M., (2006). Retail restructuring and consumer choice 2.

Understanding consumer choice at the household level. Environment and Planning A, 38(1), 47-67.

Jackson, P.A., Rowlands, M. and Miller, D., 2005. Shopping, place and identity. Routledge.

Kambo A., Keco R., Tomori I. (2017a). An empirical investigation of the determinants of food waste generation in urban area at household level in Albania. International Journal of Economics, Commerce and Management 5(5), 487-497

Koivupuro, H.-K., Hartikainen, H., Silvennoinen, K., Katajajuuri, J.-M., Heikintalo, N., Reinikainen, A., Jalkanen, L., (2012), Influence of socio- demographical, behavioural and attitudinal factors on the amount of avoidable food waste generated in Finnish households. International Journal of Consumer Studies, 36(2), 183-191.

Krejcie, R.V., & Morgan, D.W., (1970). Determining Sample Size for Research Activities. Educational and Psychological Measurement.

Lai, K., Lim, S., Teh, P., & Yeap, K. (2017). An Artificial Neural Network Approach to Predicting Electrostatic Separation Performance for Food Waste Recovery. Polish Journal of Environmental Studies, 26(4), 1921–1926. https://doi.org/10.15244/pjoes/68963

Lee, S., Paik, H.S., (2011), Korean household waste management and recycling behaviour, Building and Environment, 46, 1159-1166.

Luckstead, J., Nayga, R.M., Snell, H.A., (2020). Labor issues in the food supply chainmamid the COVID-19 pandemic. Appl. Econ. Perspect.

Policy aepp 13090. doi: 10.1002/aepp.13090.

Lyndhurst, B., (2007), WRAP food behaviour consumer research – Findings from the qualitative phase, WRAP.

Marais, M.L., Smit, Y., Koen, N. and Lötze, E. (2017), Are the attitudes and practices of foodservice managers, catering personnel and students contributing to excessive food wastage at Stellenbosch university?

South African Journal of Clinical Nutrition, 30 (3), 60-67, doi:


Martin-Rios, C., Demen-Meier, C., Gössling, S., & Cornuz, C. (2018). Food waste management innovations in the foodservice industry. Waste Management, 79, 196-206.

Miafodzyeva, S., & Brandt, N. (2013). Recycling behaviour among householders: synthesizing determinants via a meta-analysis. Waste and Biomass Valorization, 4(2), 221–235.

Mohd Sharif (2018, December 18), Amount of food wasted by Malaysians enough to feed 12 million people a day', News Straight Time. retrieved

on 20 Jan 2022

https://www.nst.com.my/news/nation/2018/12/441882/amount-food- wasted-malaysians-enough-feed-12-million-people-day

Mondéjar-Jiménez, J.A., Ferrari, G., Secondi, L. and Principato, L. (2016), From the table to waste: an exploratory study on behaviour towards



food waste of Spanish and Italian youths, Journal of Cleaner Production, 138(1), 8-18.

Nunnally, J. C. (1978). Psychometric theory (2nd ed.). New York: McGraw- Hill.

O’Brien, M., 2008. A Crisis of Waste? Understanding the Rubbish Society.

Routledge, New York.

Osmani M. and Kambo A. (2018). Food waste factors of urban Albanian consumers – A Multinomial Econometric approach. European Scientific Journal 14(3), 11-30.

Pallant, J. (2001). SPSS survival manual: A step by step guide to data analysis using SPSS for Windows version 10. Buckingham: Open University Press.

Parfitt, J., Barthel, M. and Macnaughton, S. (2010), Food waste within food supply chains: quantification and potential for change to 2050, Philosophical Transactions of the Royal Society B: Biological Sciences, (365), 554, 3065-3081.

Pellegrini, G., Sillani, S., Gregori, M. and Spada, A. (2019), Household food waste reduction: Italian consumers’ analysis for improving food management, British Food Journal, (121), 6, 1382-1397.

Porpino G, Wansink B, Parente J (2016) Wasted positive intentions: the role of affection and abundance on household food waste. J Food Prod

Mark 22(7):733–751.


Porpino, G., (2016), Household food waste behavior: Avenues for future research, Journal of the Association for Consumer Research, 1(1), 41- 51.

Porpino, G., Parente, J., & Wansink, B. (2015). Food waste paradox:

Antecedents of food disposal in low-income households. International Journal of Consumer Studies, 39(6), 619–629. Doi https://doi.org/10.1111/ijcs.12207

Priefer, C., Jorissen, J., Brautigam, K.-R., 2016. Food waste prevention in Europe–A cause-driven approach to identify the most relevant leverage points for action. Resour. Conserv. Recycl. 109, 155–166.

Qi, D., Roe, B.E., (2016), Household food waste: Multivariate regression and principal components analysis of awareness and attitudes among U.S.

consumers. PLoS ONE, 11(7), e0159250.

Quested, T.E., Marsh, E., Stunell, D., Parry, A.D., (2013). Spaghetti soup: the complex world of food waste behaviours. Resour. Conserv. Recycl.

79, 43–51. doi: 10.1016/j.resconrec.2013.04.011.

Radzyminska, M., Jakubowska, D., & Staniewska, K. (2016). Consumer attitude and behavior towards food waste. Journal of Agribusiness and Rural Development, 1(39), 175–181.

Roe, B.E., Apolzan, J.W., Qi, D., Allen, H.R., Martin, C.K., (2018). Plate waste of adults in the United States measured in free-living conditions. PLoS One 13. doi: 10.1371/journal.pone.0191813.

Schanes K., Dobernig K., Gözet B. (2018). Food waste matters - A systematic review of household food waste practices and their policy implications.

Journal of Cleaner Production 182, 978-991. DOI: 10.1016/j.


Schmidt, K. (2016). What a waste! developing the food waste-preventing behaviors scale - A useful tool to promote household food waste- prevention. International Journal of Food and Nutritional Science, 3(3), 1–14. doi: https://doi.org/10.15436/2377-0619.16.936

Secondi, L., Principato, L., Laureti, T., (2015), Household food waste behaviour in EU-27 countries: A multilevel analysis, Food Policy, 56, 25-40.

Segrè, A., Falasconi, L., A., P., & Vitturari, M. (2014). Background paper on the economics of food loss and waste. Working Paper (FAO), 1–83.

Silva, J. G., (2016). SAVE FOOD: Global Initiative on Food Loss and Waste Reduction. Retrieved from FAO.org: http://www.fao.org/save- food/news-and-multimedia/news/news-details/en/c/429182/

Silvennoinen, K., Katajajuuri, J.-M., Hartikainen, H., Heikkila, L., Reinkainen, A., (2014), Food waste volume and composition in Finnish households, British Food Journal, 116(6), 1058-1068.

Slocum, R. (2011). Race in the study of food. Progress in Human Geography, 35(3), 303–327.

Stancu, V.; Haugaard, P.; Lähteenmäki, L. (2016) Determinants of consumer food waste behaviour: Two routes to food waste. Appetite, 96, 7–17.

Steg, L., Vlek, C., 2009. Encouraging pro-environmental behaviour: an integrative review and research agenda. J. Environ. Psychol. 29 (3), 309–317.

Stuart, T. (2009). Waste: Uncovering the global food scandal. Penguin Books Valentine, G., 1999. Eating in: Home, consumption and identity. Sociological

Review, 47 (3), 491-524.

Van derWerf, P.; Seabrook, J.A.; Gilliland, J.A. (2019) Food for naught: Using the theory of planned behaviour to better understand household food wasting behaviour. Canadian Geographer, 63(3), 1-16.


The_Canadian_Geographer___Le_G-ographe_canadien.pdf Visschers, V.H.M., Wickli, N., Siegrist, M., (2016), Sorting out food waste

behaviour: A survey on the motivators and barriers of self-reported amounts of food waste in households, Journal of Environmental Psychology, 45, 66-78.

Von Kameke C. and Fischer D. (2018). Preventing household food waste via nudging: An exploration of consumer perceptions. Journal of Cleaner Production 184, 32-40. DOI: 10.1016/j.jclepro.2018.02.131 Whitehair, K.J., Shanklin, C.W. and Brannon, L.A. (2013), Written messages

improve edible food waste behaviors in a university dining facility, Journal of the Academy of Nutrition and Dietetics, (113), 1, 63-69, doi:


Williams, H., Wikstrom, F., Otterbring, T., Lofgren, M. & Gustavsson, A.

(2012). Reasons for household food waste with special attention to packaging. Journal of Cleaner Production, 24,141-148.

WRAP UK (nd). Why take action: legal/policy case. Available at http://www.wrap.org.uk/content/why-take-action-legalpolicy-case Wu, Y., Tian, X., Li, X., Yuan, H. and Liu, G. (2019), Characteristics,

influencing factors, and environmental effects of plate waste at university canteens in Beijing, China, Resources, Conservation and Recycling, 149, 151-159, doi: 10.1016/j.resconrec.2019.05.022.

Xue, L.; Liu, G.; Parfitt, J.; Liu, X.J.; Van Herpen, E.; Stenmarck, Å.; O’Connor, C.; Östergren, K.; Cheng, S.K. (2017) Missing food, missing data? A critical review of global food losses and food waste data. Environ. Sci.

Technol. 51, 6618–6633.

Yaffe-Bellany, D , Corkery, M. , (2020). Dumped Milk, Smashed Eggs, Plowed Vegetables: Food Waste of the Pandemic. New York Times.

Zainal, D., & Hassan, K.A. (2019). Factors Influencing Household Food Waste Behaviour in Malaysia. International Journal of Research in Business, Economics and Management, 3(3), 56-71

Zhao, X. and Manning, L. (2019), Food plate waste: factors influencing insinuated intention in a university food service setting, British Food Journal, (121), 7, 1536-1549, doi: 10.1108/BFJ-07-2018-0481.



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