Abstract
Purpose
This study aims to extend the Theory of Planned Behavior (TPB) with the Norm Activation Theory (NAT) and apply these two theories to explain Gen Z’s intention to reduce household food leftovers.
Design/methodology/approach
Primary data were collected online from 386 respondents, selected through a convenience sampling technique from June to August 2023. Established indicators measured each construct adequately, and hypotheses were examined by using a structural equation model with robust maximum likelihood estimation.
Findings
Attitude toward behavior, perceived behavioral control and personal norms built by awareness of consequences and ascription of responsibility were proven to be able to form the intention to reduce household food leftovers. Extending the TPB with the NAT revealed that intention was built based on attitudinal belief, control belief and a feeling of moral obligation that activates personal norms.
Research limitations/implications
Respondent validity needs to be strengthened; injunctive and descriptive norms are still integrated, and the translation of intention into action is yet to be examined
Practical implications
Social marketers boosted behavior change campaigns among Zoomers by emphasizing moral responsibility, promoting awareness and favorable behavioral beliefs through tailored messages and highlighting the ease of reducing household food leftovers.
Originality/value
This study bridged existing research gaps by extending the TPB with the NAT in the context of household routine consumption practices. It offered valuable insights for promoting responsible consumption and reducing household food leftovers among the youth.
Keywords
Citation
Setiawan, B., Purwanto, P., Ikasari, W.S.D. and Suryadi, S. (2024), "An inclusive extension of the Theory of Planned Behavior for explaining household food leftover reduction intention among Gen Z", Journal of Social Marketing, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/JSOCM-09-2023-0210
Publisher
:Emerald Publishing Limited
Copyright © 2024, Emerald Publishing Limited
Introduction
The problem of food waste is a critical issue occurring in many countries worldwide. Annually, tons of food are wasted, resulting in severe environmental and economic repercussions. A report from the United Nations Environment Programme (2021) states that in 2019, 17% of the global food production, amounting to 931 million tons, was discarded, as written in the Food Waste Index Report 2021. This wastage was dispersed across different sectors, with households, food service and retail accounting for 11%, 5% and 2%, respectively. These statistics emphasize the significance of Sustainable Development Goal (SDG) 12.3, which aims to halve food waste and loss by 2030 (United Nations, 2020). Throughout the entire food supply chain, from the initial stages of production to the final consumption by consumers, significant quantities of food are lost or wasted (Barone et al., 2019; Habib et al., 2023; Wharton et al., 2021). This includes losses during harvesting, processing, distribution, retail and consumer level. Addressing food waste comprehensively demands collaborative efforts across all food supply chain sectors, encompassing producers, distributors, retailers, policymakers and consumers.
Issues related to responsible consumption, food and food waste are critical recommendations for future studies agenda in social marketing topics (Salgado Sequeiros et al., 2022). Social marketing is the application of marketing concepts and techniques to create mutually beneficial exchanges for individuals and society, aiming to influence desired behaviors for social good or community well-being (Kotler and Lee, 2011; Lee and Kotler, 2019). Efforts to reduce the generation of food waste can be initiated by using a social marketing approach, corresponding to the action suggestions provided by Lee (2020). Nevertheless, addressing food waste through social marketing encounters various challenges in its implementation (Sutinen, 2022). Food waste is a complex and multidimensional sustainability issue that is difficult to resolve (Beachcroft-Shaw and Ellis, 2020). This condition is highly susceptible to generating misconceptions, leading to inappropriate problem-solving approaches. The suboptimal handling of the food waste issue through social marketing is also attributed to the limited theoretical foundations of scholars (Carvalho and Mazzon, 2019).
In social marketing, theories play a central role, as they guide the understanding of reality, consumers and how behavioral changes benefiting society can occur. Social marketing must remain open to diverse approaches concerning human behavior and social transformation to fulfill its primary objective, underscoring the significance of socio-cultural context (Sutinen, 2022). The intended success of the behavior goal can involve the norm aspect in assessing the achievement of short-term social marketing intervention. This aspect has a significant role in increasing the awareness and engagement of the targeted group (Akbar et al., 2023). Therefore, the effort to build society’s intention to reduce food leftovers in the household must include norms as the individual guide in behaving. The Theory of Planned Behavior (TPB) (Ajzen, 1985, 1991) is a fundamental theory involving the norm aspect as an essential part of the socio-cultural approach to explain individual behavior in various contexts. The TPB has been widely used in behavior about food waste with various levels of predictive power (Srivastava et al., 2023). In the context of reducing food waste, several recent studies extend the use of TPB by completing the norm aspect inclusively. For example, Chen (2023), Elhoushy and Jang (2021) and Kim et al. (2020) studies completed the TPB norm aspect by incorporating another norm factor that comes from the individuals’ internal side. This norm can be explained well through the personal norm, the core factor of the Norm Activation Theory (NAT) (Schwartz, 1977), which is built because of the awareness of consequences of behavior and the ascription of responsibility. Adding personal norms from NAT to TPB increases the model’s ability to explain the intention and display one’s pro-environmental behavior (Setiawan et al., 2020). Therefore, this inclusive extension will reveal what specific norm can encourage an individual’s intention to reduce food leftovers.
The household per capita food waste generation is substantially similar across income groups in different countries (United Nations Environment Programme, 2021). Consequently, addressing food waste has become a significant concern for developed and emerging economies (Amicarelli et al., 2021; Ardra and Barua, 2023; Aydin and Yildirim, 2021). Indonesia is a developing country with a population of more than 270 million in 2020 (BPS – Statistics Indonesia, 2021). It represents approximately 3.51% of the world’s population, positioning it among the five most populous countries. The substantial population growth in the country has led to increased demand for food, causing various environmental issues, such as food leftovers. This condition aligns with the idea that human actions are critical in causing wastage (Kim et al., 2022; Thapa et al., 2023). In 2022, Indonesia generated 34,611,111.65 tons of waste, implying that each resident of Indonesia produces 128.09 kilograms of waste per year. Food waste has the highest proportion (40.4%) of the total waste composition of various waste types. Furthermore, households contribute the highest volume of 36.33% to the national waste generation (Ministry of Environment and Forestry Republic of Indonesia, 2024). Indonesia has experienced an economic deficit of around IDR 213–551tn per year between 2000 and 2019 because of the generation of food loss and waste, accounting for 4%–5% of the country’s GDP (Ministry of National Development Planning/Bappenas Republic of Indonesia, 2021). Indonesia has committed to integrating the SDGs’ objectives, aims and benchmarks into its Medium-Term National Development Plan. Hence, using Indonesia as the context for studies examining consumer-generated food waste is highly pertinent.
Although in general research on food waste increases, research focusing on the intention to reduce food leftovers in the context of the routine practice of household consumption has received little attention (Schanes et al., 2018). Specifically, in recent research that has used both TPB and NAT constructs, either partially or in combination, research focuses on the practice of planning and shopping routines (Chen, 2023; Elhoushy and Jang, 2021; Romani et al., 2018; T’ing et al., 2021), preparing and cooking (Abu Hatab et al., 2022; Elhoushy and Jang, 2021), eating out (Coşkun and Özbük, 2020; Iriyadi et al., 2023; Kim et al., 2020, 2022; Wang et al., 2022) and disposition (Romani et al., 2018; Talwar et al., 2022). Previous studies have identified specific gaps that trigger further exploration. First, a notable gap exists regarding the comprehensive implementation of the TPB and the NAT constructs. Combining these frameworks thoroughly is essential to examine how an individual’s internalized and externalized values can elucidate the intention to reduce food leftovers. Second, previous studies have not yet focused on the intention to reduce food leftovers in the practice of routine consumption in the household. Therefore, this study fills in the gaps by combining entirely the TPB and the NAT constructs. It focuses on Gen Z’s intentions to reduce food leftovers through more responsible consumption while eating within their household.
Referring to the background explanation and identified research gap, the main research question is how effective the inclusive extension of TPB is in explaining the intention to reduce household food leftovers among Gen Z. By combining all constructs from NAT into TPB, this study has the potential to address the challenges of social marketing implementation complexity because of limited theoretical foundations, as highlighted by Carvalho and Mazzon (2019) and Sutinen (2022). The remaining segments of the paper are organized as follows. Section 2 examines the NAT and the TPB literature review and establishes the foundational rationale for developing the study hypothesis. Section 3 outlines the methods, including specific measurements, primary data collection and statistical analysis procedures. Section 4 displays the outcomes of the statistical analysis, consisting of descriptive statistics, confirmatory factor analysis and the structural test. Section 5 discusses the results of the analysis, the theoretical and practical implications and the study’s limitations. Furthermore, this section indicates recommendations for future studies. Section 6 encapsulates the study’s conclusions.
Literature review and theoretical framework
Food waste in daily household practice
Household routine practices (planning, shopping, pre-consumption, consumption and disposition) are essential in determining food supply and the potential for food leftover generation (Principato et al., 2021; Schanes et al., 2018). During planning, busy consumers may not check their fridges before shopping, leading to buying items they already have. The impact of this behavior is the accumulation of excessive food supplies in the refrigerator. This condition may lead to wastage as these items become unused and eventually discarded (Aloysius et al., 2023; Gimenez et al., 2023). Therefore, consumers must allocate time to check their existing food supplies before shopping, enabling them to avoid over-purchasing and waste.
Meanwhile, in the shopping routine, consumers might buy more food than necessary because of sales promotions offered (Van Lin et al., 2023; Wu and Honhon, 2023). When consumers purchase more food than they need, some of it will go unused and potentially end up in the trash. Therefore, consumers must be more prudent when buying food, even with enticing sales promotions. They need to create a well-planned shopping list and purchase only the amount of food that meets their needs. By doing so, consumers can help reduce the amount of food waste and minimize waste of valuable resources. In the pre-consumption routine, many consumers do not store food properly, overcook and use large plates, leading to food leftovers (Gimenez et al., 2023). Only a few studies examine how eating habits contribute to food waste generation (Schanes et al., 2018). Varied food preferences and unpredictable appetites within families are significant factors causing individuals not to finish leftover foods (Principato et al., 2021). While leftovers can often be repurposed and still edible, serving such food to children or family guests may not be well-received in some cases.
Norm Activation Theory
NAT focuses on how individuals’ awareness and sense of moral responsibility influence their norms regarding specific social or environmental problems, encouraging the formation of pro-social behavior (Schwartz, 1977). NAT is one of the critical concepts in behavioristic psychology, often used to describe various pro-social and pro-environmental activities (Obuobi et al., 2022). It also provides insight into how people’s internal values, moral convictions and awareness of the consequences of their actions shape the willingness to participate in behaviors that contribute to the betterment of society and the environment. Furthermore, this theory has been applied in various domains, such as encouraging sustainable behaviors, promoting charitable actions and understanding how to motivate people to address social issues. The core factor of NAT is the presence of personal norms, which represent a feeling of responsibility and moral obligation. Individuals with strong moral responsibility, guided by their norms, were more likely to engage in pro-environmental actions (Talwar et al., 2022). The behavior of reducing food waste is considered both pro-environmental and pro-social behavior. It is influenced by individual psychological factors (Elhoushy and Jang, 2021; Wang et al., 2018), the environment (Abu Hatab et al., 2022) and personality traits (Kutlu, 2022). This altruistic behavior is driven by a moral obligation to provide positive benefits for others and the environment (Talwar et al., 2022). In NAT, this moral obligation is known as a personal norm, activated by awareness of consequences and ascription of responsibility. NAT can effectively explain the intention to reduce food waste in the context of eating out (Iriyadi et al., 2023). Thus, NAT is believed to have the same effectiveness in routine household consumption.
Personal norm activation begins with an awareness of consequences. For instance, individuals realize that food waste could lead to severe environmental pollution, ecological damage and resource wastage (Wang et al., 2019, 2018). This awareness shapes their belief regarding the potential impact of their actions. Such awareness is often linked to an instrumental behavior, considering the balance between benefits and costs (Setiawan et al., 2021; Wan et al., 2017). Awareness of consequences is crucial in shaping the personal norms associated with the endeavor to curtail food waste (Attiq et al., 2021; Filimonau et al., 2023; Fraj-Andrés et al., 2023; Iriyadi et al., 2023). This facet of understanding the repercussions of actions has become a pivotal influencer, intertwining with an individual’s ethical framework. By comprehending the broader effects of their choices, people can establish a deeper connection between their values and behaviors. This awareness bridges the abstract notion of personal norms and the tangible reality of minimizing food leftovers. It also instills a sense of responsibility, fostering a more profound commitment to sustainable practices and responsible consumption (Kim et al., 2022; T’ing et al., 2021; Wang et al., 2022). Therefore, the first hypothesis of this study is as follows:
Gen Z’s awareness of the positive consequences of responsible consumption behavior in the household positively influences personal norms.
In addition to the awareness of consequences, the activation of personal norms is influenced by the consideration of responsibility (ascription of responsibility) as a consequence of behavior (Kim et al., 2022; Schwartz, 1977; Shin et al., 2018; Wang et al., 2022). Activation of personal norms occurs when individuals acknowledge their accountability for the detrimental impacts of food leftovers. Meanwhile, it remains inactive when there is individuals’ denial to be responsible (Kim et al., 2022; Obuobi et al., 2022; Schwartz, 1977; Setiawan et al., 2021; Wang et al., 2022). This argument serves as the fundamental basis for the presumption that feeling responsible shapes personal norms to reduce food waste (Filimonau et al., 2023; Fraj-Andrés et al., 2023; Iriyadi et al., 2023). Therefore, the second hypothesis of this study is as follows:
The ascription of responsibility from Gen Z about responsible consumption behavior in the household positively influences personal norms.
Personal norm is a pivotal element in NAT that becomes an individual’s intrinsic moral compass toward specific beneficial behaviors (Schwartz, 1977). This internal compass drives people toward choices and actions aligned with their deeply ingrained beliefs of right and wrong. This indicates that the personal norm is an ethical driver, intricately woven into human behavior and decision-making, fostering a unique blend of conscience and action. Furthermore, it serves as an intrinsic pressure that influences attitudes in response to awareness of social or environmental issues (Kim et al., 2022; Wang et al., 2022). Personal norms play a vital role in developing the intention for pro-environmental behavior in waste management (Alsuwaidi et al., 2022; Filimonau et al., 2023; Fraj-Andrés et al., 2023; Iriyadi et al., 2023; Long et al., 2024; Setiawan et al., 2021; Talwar et al., 2022; T’ing et al., 2021). The findings from previous studies show that personal norm is a crucial intrinsic factor that supports pro-environmental behavior. Therefore, the third hypothesis of this study is as follows:
Gen Z’s personal norm of responsible consumption behavior in the household positively influences the intention to reduce food leftovers.
Theory of Planned Behavior
In the TPB, the intention to behave predicts future individual behavior. TPB is based on the Theory of Reasoned Action (TRA), which states that personal beliefs and social pressure shape intention. Furthermore, it complements TRA by considering situations where the behavior cannot be entirely under individual control. In TPB, behavior is influenced by both intention and perceived behavioral control, with attitude toward behavior, subjective norm and perceived behavioral control predicting intention (Ajzen, 1985, 1991). The TPB model has generally demonstrated its significance reliably when tested in predicting various sustainable behaviors (Nik Masdek et al., 2023). Attitude toward behavior refers to evaluating the expected consequences of a specific behavior (Ajzen, 1985, 1991; Fishbein and Ajzen, 2011). In the context of reducing food waste, several studies showed a positive linkage between attitude toward behavior and the intention to reduce food waste (Bhatti et al., 2023; Elhoushy and Jang, 2021; Kim et al., 2020; T’ing et al., 2021). These results indicate that individual positive attitudes are reflected by the perceived benefits of reducing food waste, such as saving money and avoiding food shortages. Therefore, it significantly explains individual intention. Therefore, the fourth hypothesis of this study is as follows:
Gen Z’s attitude toward responsible consumption behavior in the household positively influences the intention to reduce food leftovers.
A subjective norm represents an individual’s social pressure to engage or refrain from a particular behavior (Ajzen, 1985, 1991; Fishbein and Ajzen, 2011). This social pressure is based on the perception of what certain people or groups consider the appropriate attitude. Individuals are motivated to act in ways that are approved by those they consider to be important, such as family, relatives and colleagues (Elhoushy and Jang, 2021; Fishbein and Ajzen, 2011; Kim et al., 2020; Setiawan et al., 2021). Empirical evidence supports that subjective norms positively impact the intention to reduce food waste (Elhoushy and Jang, 2021; Kim et al., 2020). Therefore, the fifth hypothesis of this study is as follows:
The subjective norm positively affects Gen Z’s intention to reduce household food leftovers.
Perceived behavioral control refers to a person’s perception of the level of easiness and difficulties in a particular behavior. Based on this construct, it is assumed to be the act of reflecting on past experiences and the anticipation of obstacles that could possibly appear. Therefore, this is related to the perception of the extent to which a person is able or has control over specific behavior (Fishbein and Ajzen, 2011). In the context of the intention to reduce food waste, perceived behavior control significantly affects consumers’ intention to reduce food waste (Bhatti et al., 2023; Kim et al., 2020; Romani et al., 2018; T’ing et al., 2021). Therefore, the sixth hypothesis of this study is as follows:
The perceived behavioral control positively affects Gen Z’s intention to reduce household food leftovers.
Methods
The focus of this study is on individuals belonging to Gen Z, commonly referred to as Zoomers, within the age range of 18–26 years old. Gen Z are chosen as the study subjects for several reasons. First, Gen Z constitutes a significant portion of Indonesia’s population, with 71,509,082 individuals, accounting for 26.5% of the total population. Given their prevalence, this group has the potential to contribute substantially to household food waste. Second, recent studies on food waste have increasingly targeted younger demographics (Bhatti et al., 2023; Bravi et al., 2020). The respondents were selected through a convenience sampling technique. An online questionnaire was created using the Google Forms platform. It was distributed through instant messaging applications from June to August 2023 among students attending private universities in Jakarta and its surrounding areas to ensure a representative sample from the target demographic.
The online questionnaire comprised six parts, with the first part serving as an introduction, explaining the study’s purpose and expecting the respondent’s willingness to participate. In the second part, respondents were asked to consent voluntarily to participate in filling out the study questionnaire. For those who declined to participate, the online questionnaire ended. However, respondents who agreed to participate proceeded to the third part, which consisted of a screening process to ensure they fell within the age range of Gen Z (18–26 years old). The fourth part provided information on the definition of food leftovers and included visual examples. The fifth part consisted of statement items measuring each latent variable of the study, while the last part asked for a brief profile of the respondents.
The three fundamental constructs in NAT, namely, Awareness of Consequences (AWCONSE), Ascription of Responsibility (ARESPON) and Personal Norms (PNORM), were measured by referring to the definitions provided by Schwartz (1977) and the operationalization conducted by T’ing et al. (2021). AWCONSE was evaluated using four indicators given as follows:
the benefit to everyone (awc1);
the enhancement of everyone’s welfare quality (awc2);
the promotion of a better environment (awc3); and
the adverse impact on residents (awc4) (presented as a reversed question).
Meanwhile, ARESPON was examined through five indicators given as follows:
the belief that everyone should reduce food leftovers (are1);
the expectation that each person in society should reduce food leftovers (are2);
the persistence of self-willingness to reduce food leftovers despite others’ actions (are3);
the sense of responsibility for the negative effects of food leftovers (are4); and
the acknowledgment of responsibility for the ecological consequences of food leftovers (are5).
PNORM was analyzed through six indicators, which included:
experiencing remorse when food was wasted while others lacked access to it (pn1);
striving to be a better person by minimizing food leftovers (pn2);
feeling unsettled by the quantity of discarded food (pn3);
feeling compelled to reduce food leftovers (pn4);
believing in the moral duty to avoid food wastage while consuming (pn6); and
feeling morally obligated to reduce food leftovers regardless of external viewpoints (pn7).
The three foundational constructs in TPB, which serve as antecedents of intention, namely, Attitude toward behavior (ATTITUDE), Subjective norm (SNORM) and Perceived behavioral control (PBCONTRO), were assessed by referring to the definitions provided by Ajzen (1985, 1991) and developed based on measurement indicators from T’ing et al. (2021) and Coşkun and Özbük (2020). ATTITUDE was evaluated using five indicators, specifically:
highly advantageous (att1);
logical (att2);
fun (att3);
good (att4); and
pleasant (att5).
SNORM was examined through five indicators including:
significant people urge to reduce food leftovers (sn1);
key individuals in life ask to reduce food leftovers (sn2);
key individuals in life hope for reducing food leftovers (sn3);
social pressure to reduce food leftovers (sn4); and
people with characters like mine ought to reduce food leftovers (sn5).
PBCONTRO was measured using five indicators given as follows:
able to predict the right portion of food according to needs at home (pbc1);
easily determine food portions at home (pbc2);
easy to finish all the food placed on the plate (pbc3);
full authority to finish all the food at home (pbc4); and
no significant obstacles in finishing the food consumed at home (pbc5).
The intention construct (INTENT) was operationalized for measurement with reference to Ajzen (1985, 1991) as follows:
intending to finish all the food placed on the plate (int1);
intending to take only the amount of food that can be consumed (int2);
intending to seriously reduce food leftovers as much as possible (int3); and
intending to minimize food leftovers (int4).
Each measurement item within every latent variable was assessed using a five-point Likert scale from 1 (strongly disagree) to 5 (strongly agree). This study conducted confirmatory factor analysis (CFA) before performing structural equation modeling (SEM), as outlined by Jöreskog et al. (2001) and Hair et al. (2014). CFA ensured the validity and reliability of the measurement model, a key component of SEM. By starting with CFA, this study evaluated the alignment of observed indicators (questions, items, measurements) with the underlying constructs, confirming that the chosen indicators accurately captured the intended measurements. In the CFA process, item validity was determined by the standardized loading factor (SLF), requiring a minimum threshold of > 0.5, and > 0.7 was preferred (Hair et al., 2014).
Furthermore, the construct reliability test was conducted, and the results showed that the Construct reliability (CR) was greater than 0.6 and the Average variance extracted (AVE) was greater than 0.5. The threshold parameters concerning SLF, CR and AVE are referred to the recommendations from Jöreskog et al. (2001) and Hair et al. (2014). Subsequently, a goodness-of-fit test was performed to confirm the alignment between the collected empirical data and the formulated study model. SEM analysis was employed to assess the hypothesized relationships. The utilization of the computer software LISREL 8.8 aided in conducting the data analysis. The estimation technique used is a maximum likelihood when the assumption of multivariate normality is successfully achieved. However, when this assumption fails, the estimation technique will use the robust maximum likelihood technique.
Findings
Respondents profile
A total of 397 individuals responded to the online questionnaire link circulated, of which 386 met the inclusion criteria. From a gender perspective, a majority of respondents were females (69.2%), with an average age of 21.45 years and a standard deviation of 2.5 years. In terms of their residence, the respondents were distributed across Bogor (49.7%), Jakarta (40.2%), Depok (7%) and other peripheral areas of the capital city (3.1%). Educational attainment varied, with 51.8% being high school graduates, 9.6% holding diplomas, 34.2% holding bachelor’s degrees and 4.4% holding postgraduate degrees. Regarding meal patterns when all core family members are at home, the results showed that 17.4% consistently ate together, 29% ate together more often, 35% alternated between eating together and separately, 9.8% tended to eat separately and 8.8% consistently ate separately. Most respondents (66.3%) indicated that they did not have income-generating employment, with 56.2% being students, 10.1% job seekers and the remainder choosing not to respond. Respondents with self-generated income were primarily engaged in private sector employment (46.2%), entrepreneurship (27.7%), creative professions (12.3%) and various other occupations. The distribution of respondents’ income was as follows: less than IDR 5m for 41.5%, IDR 5–7m for 25.4%, IDR 8–10m for 25.4% and more than IDR 10m for 7.7%.
Descriptive statistics
This study used a descriptive statistical analysis through computations of mean, standard deviation, skewness and kurtosis coefficients for each construct. This analysis was based on the mean scores of respondents’ answers to all measurement items within each construct. The outcomes revealed that the subjective norm concept received the lowest average score (Mean = 3.69), while the intention concept garnered the highest average score (Mean = 4.21). The assessment for each measurement item ranged from 1 to 5. With three approval level categories (low, moderate, high), an interval value of 1.33 [(5 – 1)/3] was used. Therefore, all constructs displayed an aggregate average score falling into the high agreement level (3.67–5.00).
Regarding standard deviation, the awareness of consequences exhibits the most consistent data distribution (standard deviation = 0.69), suggesting that respondents’ answers to this construct are more homogeneous. A majority of variables display negatively skewed distributions, indicating a bias toward lower values. The kurtosis values vary, with some distributions having heavier tails than a normal distribution (positive kurtosis) while others are flatter (negative kurtosis). The distribution of “SNORM” is nearly symmetric, with skewness and kurtosis values approximating zero. The results of the descriptive statistical tests are presented in Table 1.
Conducting a multivariate normality test by examining the skewness and kurtosis is essential. The amalgamation of these two factors, assessed through the chi-square test, shows that a higher chi-square value signifies a more pronounced disparity between the distribution of the data and the standard normal distribution. The data analysis results show a chi-square value of 26974.453 and a p-value of 0.000, underscoring exceptionally high statistical significance (Table 2). The outcomes from the two tests suggest that the assessed data’s distribution deviates from a normal pattern. Evident dissimilarities between the observed data distribution and the anticipated normal distribution signify the data set’s non-fulfillment of normality assumptions. Consequently, the used estimation technique is the robust maximum likelihood, following the recommendation by Jöreskog et al. (2001).
Confirmatory factor analysis
In the initial CFA iteration, it was observed that items awc4 and sn4 exhibited SLF values lower than the established threshold of SLF < 0.7 (awc4 = 0.312; sn4 = 0.629). Consequently, these two items were excluded from the model, leading to a subsequent CFA test iteration. The comprehensive outcomes are presented in Table 3, whereby the result identified that all of the measurement units had good validity and reliability (SLF > 0.5; CR > 0.6; and AVE > 0.5) as recommended by Jöreskog et al. (2001) and Hair et al. (2014). The modification indices procedure was executed to improve data compatibility with the established study model. The modification correlated with the error covariance score from two observed variables belonging to the same construct (Table 4). After the modification indices analysis, a measurement model was obtained, which fulfilled the goodness of fit indices criteria (Table 5). These findings robustly supported the conduct of a structural test. Furthermore, this study employs Harman’s single-factor test to detect and mitigate common method variance (CMV) issues. The analysis reveals no CMV in the data, with one factor accounting for 47.656% of the variance, below the recommended threshold of 50%.
Structural test
A fit analysis for the structural model was carried out before hypothesis testing (Table 5). After confirming the structural model’s fit with the goodness-of-fit criteria, this study conducted structural tests to assess the study hypotheses (Table 6 and Figure 1). From the NAT perspective, Gen Z’s awareness of the positive consequences of responsible household consumption is proven to have a positive effect on personal norms. Gen Z’s ascription of responsibility regarding responsible household consumption has also been proven to positively affect the personal norm. This result is followed by the significance of the positive effect of Gen Z’s personal norm toward the intention to reduce household food leftovers. From the TPB perspective, Gen Z’s attitude toward responsible consumption behavior in the household has been proven to positively affect the intention to reduce food leftovers. Unfortunately, the subjective norm does not significantly affect Gen Z’s intention to reduce household food leftovers. Furthermore, perceived behavioral control has positively affected Gen Z’s intention to reduce household food leftovers. Overall, it has been revealed that only one of the six hypotheses, namely, H5, is not supported by data.
Discussion
This study extends the TPB with NAT to understand Gen Z’s intentions to reduce household food leftovers. Through the lens of NAT, Gen Z realizes that irresponsible consumption behavior at home can potentially cause food waste, which can have negative environmental implications if not managed properly. By recognizing the adverse effects of food waste, Gen Z contributes to everyone’s benefit and significantly enhances the welfare quality of the entire community. Their efforts in reducing household food waste are crucial in promoting a better environment, leading to a more sustainable future. These findings support previous studies indicating that younger generations are becoming aware of the negative consequences of food leftovers at home, both environmentally and economically (Bravi et al., 2020; Zepeda and Balaine, 2017). Therefore, this awareness motivates the younger generation to engage in food waste reduction efforts (Attiq et al., 2021; Bravi et al., 2020), acts as internal pressure and successfully becomes a catalyst for activating personal norms that guide their behavior (Attiq et al., 2021; Filimonau et al., 2023; Fraj-Andrés et al., 2023; Iriyadi et al., 2023).
In addition to being aware of the consequences, Gen Z feels responsible and believes everyone should contribute to reducing food leftovers. This sense of responsibility activates personal norms as behavioral guidelines (Attiq et al., 2021; Kim et al., 2022; Obuobi et al., 2022; Schwartz, 1977; Setiawan et al., 2021; Wang et al., 2022). This finding provides empirical evidence of the importance of the ascription of responsibility in activating the personal norms of Gen Z. Therefore, this is a crucial indication that reducing food waste requires communal action from individuals who are aware and feel responsible for environmental preservation (Iriyadi et al., 2023; Kim et al., 2022; Obuobi et al., 2022; Wang et al., 2022). The roles of these two constructs cannot be separated from each other. Combining both constructs plays a vital role in activating personal norms, as a moral obligation for Gen Z. This deep sense of responsibility and awareness underscores their commitment to sustainability and responsible consumption.
From the TPB perspective, the results indicate that attitudes and perceived behavioral control significantly affect Gen Z’s intentions to reduce household food leftovers. For Gen Z, this behavior is considered beneficial and logical. Enjoying meals at home provides emotional satisfaction, which motivates them not to leave any food on their plates. These findings align with previous studies that highlight the crucial role of attitude in explaining intentions to reduce food waste (Bhatti et al., 2023; Elhoushy and Jang, 2021; Kim et al., 2020; T’ing et al., 2021). In addition to positive attitudes, intentions are also formed when Gen Z feel capable of taking action. Predicting the portion of food that can be consumed and having full authority to consume it shapes intentions significantly. These results are consistent with previous research indicating that perceived behavioral control supports the formation of consumer intentions to reduce food waste (Bhatti et al., 2023; Elhoushy and Jang, 2021; Kim et al., 2020; Romani et al., 2018). Regarding norms, internal motivation among Gen Z plays a more dominant role than external social pressure. These findings confirm previous studies, which reveal that subjective norms still lack sufficient empirical support in explaining intentions (Bhatti et al., 2023; Fraj-Andrés et al., 2023). Strengthening internal motivation can be a more effective strategy to reduce household food leftovers than relying on social pressure from the surrounding environment.
The findings of this study carry important practical implications. Social marketers can design communications using language that is easily understood and relevant to the daily lives of Gen Z. Messages are delivered through interactive digital content, using social media platforms trending among Gen Z. The digital content posted on social media requires positive reinforcement to achieve the desired behavioral outcomes (Ong et al., 2023). Social marketers create content featuring scenes of young individuals dining at home. Furthermore, these individuals convey that not leaving food behind is an enjoyable and easily achievable activity by showcasing cheerful and enthusiastic faces. The digital content concludes with a closing statement emphasizing that reducing household food leftovers is everyone’s responsibility, including the younger generation. Another practical implication is that social marketers can collaborate with educational institutions. Gen Z are in their productive age range, generally attending high school and university. Therefore, social marketers can partner with academic institutions through integrated curriculum education programs. By instilling sustainability values in the educational environment, the younger generations become agents of change, driving environmentally friendly practices in society.
The study’s findings have significant theoretical implications in social marketing literature as solutions to address food waste complexity, as emphasized by Sutinen (2022). Responsible food consumption behaviors in households can help minimize the emergence of food waste potential. For Gen Z, the intention to reduce household food leftovers is explained better with personal norms, attitudes and perceived behavioral control. Subjective norms lack adequate empirical support and thus play a minor role in explaining intentions. In this context, Gen Z prioritizes individual freedom and self-expression more. This circumstance explains their inclination to reduce food leftovers based on personal values rather than societal pressures. Therefore, extending TPB with NAT to explain Gen Z’s intention to reduce food waste is necessary. Social marketing scholars who want to predict the young generation’s behavioral intention regarding responsible consumption practices can consider this extension. As an implication, the crucial role of intentions can be successfully realized in actual behavior.
This study has several limitations that can be addressed through future studies. First, although exact procedures are established to ensure survey respondents’ appropriateness, the validity has yet to be objectively measured. Further studies may consider objective measuring respondent validity using Rasch model measurement analysis. This approach yields a model with good objective validity regarding measurement instruments and respondents simultaneously. Second, from a normative perspective, further studies could consider a more detailed measurement of two separate constructs: injunctive and descriptive norms. It is essential to explore further what social pressures would successfully shape intentions, whether they originate from what others say or think or from what has been exemplified. Third, this study does not consider testing the realization of intentions into actual behavior in a follow-up survey. Therefore, subsequent studies could test the realization of intentions into actual behavior. Furthermore, further studies can consider situational factors that moderate the functional relationship between intentions and actual behavior.
Conclusion
This study aimed to extend the TPB with the NAT and apply the two theories to explain Gen Z’s intention to reduce household food leftovers. From the NAT perspective, the personal norm plays an essential role as a core factor supporting the formation of intentions. The empirical data provide sufficient support for consumers’ awareness of consequences and ascription of responsibility. From the TPB perspective, attitude and perceived behavioral control are constructs with sufficient empirical support. Therefore, the extended TPB model finds that Gen Z’s intention to reduce household food leftovers is built from the fully activated personal norm, positive attitude and sufficient perceived behavioral control. The insufficient empirical support for the subjective norm indicates the crucial need to extend TPB with NAT. Collaborating on these two theories better explains Gen Z’s intentions to reduce household food leftovers.
Figures
Figure 1.
Structural model and hypotheses tests from the Lisrel 8.8 output
Descriptive statistics test results
| Construct | Mean | Standard deviation | Skewness | Kurtosis |
|---|---|---|---|---|
| AWCONSE | 4.1082 | 0.69585 | −0.604 | −0.058 |
| ARESPON | 4.0870 | 0.71284 | −0.653 | 0.418 |
| ATTITUDE | 4.1451 | 0.71109 | −0.672 | 0.196 |
| PNORM | 4.1667 | 0.72095 | −0.690 | 0.338 |
| SNORM | 3.6948 | 0.76591 | −0.093 | −0.411 |
| PBCONTRO | 4.0435 | 0.70954 | −0.499 | 0.388 |
| INTENT | 4.2073 | 0.70096 | −0.632 | 0.030 |
Source: Authors’ own work
Multivariate normality test results
| Skewness | Kurtosis | Skewness and kurtosis | |||||
|---|---|---|---|---|---|---|---|
| Value | z-score | p-value | Value | z-score | p-value | Chi-square | p-value |
| 830.93 | 159.32 | 0.00 | 2963.35 | 39.90 | 0.00 | 26974.45 | 0.00 |
Source: Authors’ own work
Confirmatory factor analysis results
| Item | SLF | SLF2 | Error | CR | AVE | √AVE |
|---|---|---|---|---|---|---|
| awc1 | 0.88 | 0.77 | 0.23 | 0.92 | 0.79 | 0.890 |
| awc2 | 0.89 | 0.79 | 0.21 | |||
| awc3 | 0.90 | 0.81 | 0.19 | |||
| are1 | 0.89 | 0.79 | 0.21 | 0.94 | 0.75 | 0.867 |
| are2 | 0.90 | 0.81 | 0.19 | |||
| are3 | 0.90 | 0.81 | 0.19 | |||
| are4 | 0.85 | 0.72 | 0.28 | |||
| are5 | 0.79 | 0.62 | 0.38 | |||
| att1 | 0.91 | 0.83 | 0.17 | 0.95 | 0.79 | 0.889 |
| att2 | 0.96 | 0.92 | 0.08 | |||
| att3 | 0.83 | 0.69 | 0.31 | |||
| att4 | 0.91 | 0.83 | 0.17 | |||
| att5 | 0.83 | 0.69 | 0.31 | |||
| pn1 | 0.88 | 0.77 | 0.23 | 0.96 | 0.82 | 0.904 |
| pn2 | 0.92 | 0.85 | 0.15 | |||
| pn3 | 0.89 | 0.79 | 0.21 | |||
| pn4 | 0.89 | 0.79 | 0.21 | |||
| pn5 | 0.93 | 0.86 | 0.14 | |||
| pn6 | 0.91 | 0.83 | 0.17 | |||
| sn1 | 0.87 | 0.76 | 0.24 | 0.93 | 0.78 | 0.881 |
| sn2 | 0.95 | 0.90 | 0.10 | |||
| sn3 | 0.93 | 0.86 | 0.14 | |||
| sn5 | 0.76 | 0.58 | 0.42 | |||
| pbc1 | 0.95 | 0.90 | 0.10 | 0.96 | 0.83 | 0.911 |
| pbc2 | 0.92 | 0.85 | 0.15 | |||
| pbc3 | 0.96 | 0.92 | 0.08 | |||
| pbc4 | 0.83 | 0.69 | 0.31 | |||
| pbc5 | 0.89 | 0.79 | 0.21 | |||
| int1 | 0.92 | 0.85 | 0.15 | 0.94 | 0.81 | 0.898 |
| int2 | 0.87 | 0.76 | 0.24 | |||
| int3 | 0.89 | 0.79 | 0.21 | |||
| int4 | 0.91 | 0.83 | 0.17 |
Source: Authors’ own work
Modification indices
| No. | Construct | Modified observed variable |
|---|---|---|
| 1. | ARESPON | are2 and are1; are5 and are4; are4 and are1; are4 and are2; are4 and are3, are5 and are1; are5 and are2; are5 and are4 |
| 2. | ATTITUDE | att3 and att1; att3 and att2; att5 and att1; att5 and att2; att5 and att3; att4 and att3; att5 and att4 |
| 3. | PNORM | pn2 and pn1; pn5 and pn1; pn6 and pn2; pn6 and pn5 |
| 4. | SNORM | sn5 and sn1; sn5 and sn2 |
| 5. | PBCONTRO | pbc3 and pbc1; pbc3 and pbc2; pbc4 and pbc1; pbc4 and pbc2; pbc4 and pbc3; pbc5 and pbc1; pbc5 and pbc2; pbc5 and pbc3; pbc5 and pbc4 |
Source: Authors’ own work
Goodness of fit results
| No. | Fit size | Measurement | Structural |
|---|---|---|---|
| 1 | Chi-square (χ2) | 555.99 | 626.61 |
| 2 | Degrees of freedom (DF) | 414 | 419 |
| 3 | DF ratio (χ2/DF) | 1.343 | 1.495 |
| 4 | Goodness of fit index (GFI) | 0.83 | 0.82 |
| 5 | Standardized root mean square residual (SRMR) | 0.045 | 0.058 |
| 6 | Root mean square error of approximation (RMSEA) | 0.030 | 0.036 |
| 7 | Root mean square residual (RMR) | 0.030 | 0.038 |
| 8 | Non-Normed fit index (NNFI) | 1.00 | 1.00 |
| 9 | Normed fit index (NFI) | 0.99 | 0.99 |
| 10 | Relative fit index (RFI) | 0.99 | 0.99 |
| 11 | Incremental fit index (IFI) | 1.00 | 1.00 |
| 12 | Comparative fit index (CFI) | 1.00 | 1.00 |
| 13 | Critical N (CN) | 336.06 | 301.62 |
Source: Authors’ own work
Structural test results
| Path | β | S.E. | t-value | Conclusion | |
|---|---|---|---|---|---|
| H1 | AWCONSE → PNORM | 0.47 | 0.18 | 2.57 | Supported |
| H2 | ARESPON → PNORM | 0.44 | 0.20 | 2.19 | Supported |
| H3 | PNORM → INTENT | 0.33 | 0.05 | 5.64 | Supported |
| H4 | ATTITUDE → INTENT | 0.18 | 0.07 | 2.54 | Supported |
| H5 | SNORM → INTENT | 0.02 | 0.03 | 0.66 | Not supported |
| H6 | PBCONTRO → INTENT | 0.44 | 0.05 | 8.39 | Supported |
Source: Authors’ own work
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Acknowledgements
The authors expressed their gratitude to the National Research and Innovation Agency (BRIN) for facilitating this research through the Postdoctoral program, as outlined in the Decree of the Deputy for Human Resources for Science and Technology, number 15/II/HK/2023.