Digital Communication Innovation of Food Waste Using the AISAS Approach: Evidence from Indonesian Adolescents

Abstract

The Attention, Interest, Search, Action, and Share (AISAS) model describes consumer behavior in the era of the Internet and technological advances. This study aimed to analyze the effects of attention, interest, information seeking, and action on knowledge sharing on the issue of food waste. The respondents in this study were 302 students aged between 16 and 25 years across 11 universities in Indonesia, who were either members of a food waste community or not. Respondents were selected using the voluntary sampling method. Data were collected using an online self-administered questionnaire, and analyzed using structural equation modeling through the LISREL 8.80 software. The results of this study reinforce the theory of the AISAS model, which sometimes operates linearly. Our findings revealed that attention had a direct effect on interest and information search; interest had a direct effect on information search and action; information search had a direct effect on knowledge sharing; and actions had a direct effect on knowledge sharing. Suggested government measures include providing advertisements related to food waste that incorporate designs, sounds, visuals, and content to reflect emerging trends. Communities need to increase awareness to reduce food waste through concrete actions or knowledge sharing to rouse public interest.

1. Introduction

Food waste is a decrease in food consumption caused by the decisions and actions of consumers, businesses, and other food service providers [1]. The world’s growing population renders it challenging not only to produce more food but to feed more people while wasting less. However, in everyday life, most individuals are believed to have thrown food away at some point. The most common habits observed include placing more food on the plate than the stomach can hold or leaving milk in the fridge for too long, causing it to spoil [2]; food wastage was further exacerbated during the COVID-19 pandemic due to restrictions on consumer movement and transportation [1,3,4].

In 2019, approximately 931 million tons of food, or 17 percent of the total food available to consumers, was reported to end up in the trash [5]. Indonesia ranks first among countries with the highest food waste production in Southeast Asia, amounting to 20.93 million tons annually [5]. Vegetables, rice, meat, fish, and dairy products are the five most common types of food waste in Indonesia [6]. According to a study conducted in China, 74% of the 9192 university students had produced plate waste in the canteens and each student had produced 61.03 g of food waste [7]. The results of a study conducted on students at a university in the United States also showed that at least 80.5% of students often throw away food waste with an average of 17.9 g of food waste [8] A large amount of food waste is not only a social and economic problem but also an environmental and health concern [9]. Food that goes to landfills and decomposes produces methane, an even more potent greenhouse gas than carbon dioxide [10], and excess greenhouse gases, such as methane, carbon dioxide, and chlorofluorocarbons, heat the Earth’s atmosphere, causing global warming and climate change [8,11,12]. This can cause the Earth’s average temperature to rise, and the liquids to start to evaporate. High temperatures can cause glaciers and sea ice to actively melt over short periods of time. The melting of the polar ice caps can cause sea levels to rise and submerge coastal lands [13]. Such large amounts of food waste will have a significant impact on the environment. In 2012, the Barilla Center for Food & Nutrition (BCFN) further explained the negative impact of food waste on the environmental, economic, and social fields. The negative environmental impacts of food waste include greenhouse-gas emissions, soil degradation, water resource waste, and excess energy consumption. The negative impact of food waste on the economy causes the value of food to depreciate and increases the cost of agricultural land. limited access to food is the negative social impact of food waste [14].

The problem of food waste has yet to receive special attention in Indonesia [15]. Spending habits and low consumer knowledge and awareness of the economic, environmental, and other consequences of food waste further exacerbate this phenomenon [16,17]. Studies conducted in China revealed that the majority of university students’ diets contributed to their tendency to throw away remaining food [18]. Previous research states that one method that can be used by university canteens to minimize food waste is to serve food without using trays [8,19]. However, the most important thing is how to raise consumer awareness of the dangers of food waste. An effort to increase consumer knowledge and awareness involves campaigns on the Internet through social media [20]. Data from the Association of Indonesian Internet Providers (APJII) for 2021–2022 show that the number of Indonesians connected to the Internet has reached 210 million out of a total population of approximately 272 million. This number was dominated by the age group of 19–34 years, given students’ predominant reliance on online resources for their academic work [21].

The high number of Internet users in the student age group provides an opportunity to increase the knowledge and awareness regarding food waste. One way of engaging the masses in the current era is, therefore, to use digital technology to disseminate knowledge through electronic word-of-mouth (eWOM) communication [22,23,24]. EWOM refers to oral or written communication in which information is shared through digital social media with the wider community [25].

Consumers play an important role in knowledge dissemination [26]. Apart from social media, campaigns to share knowledge and information about food waste in Indonesia are also conducted by consumers through commercial and non-commercial organizations and communities. Garda Pangan, EcoBali, The Hunger Bank, the Brotherhood, the Foodbank of Indonesia, and the International Association of Students in Agricultural and Related Sciences (IAAS) are some of them. The IAAS is one of the communities closest to students because it is located in an on-campus environment. The IAAS has spread across 11 universities in Indonesia with more than 1000 active members. Knowledge sharing within an organizational environment can affect the competence and discipline of members and create values that will be embraced by members within [27,28,29].

The increasing number of Internet users and the sharing of knowledge and information by consumers encourages the development of a consumer behavior model from the traditional Attention, Interest, Desire, Memory, and Action (AIDMA) model to an Attention, Interest, Search, Action, and Share (AISAS) one. These processes in the AISAS model accommodate the emergence of interactive media in activities related to searching for and sharing information [30]. Transforming conventional campaigns into digital campaigns is an effective task in this era of sophisticated technological development. Environmental issues that are developing due to factual conditions, one of which is the issue of food waste, need to be accommodated effectively by carrying out a digital campaign to produce an impact on sustainable consumption behavior patterns. The AISAS model analyzes changes in multimedia and online communication to anticipate the various behaviors of a person in the current era [31]. In this case, the AISAS model has been proven to be capable of effectively approaching the target audience by observing changes in behavior using technological advances. Thus, the AISAS model is appropriate for examining the effectiveness of digital campaigns on knowledge sharing related to the issue of food waste.

Research on the AISAS model has been conducted in several fields. In previous research, the AISAS model was used to examine the effectiveness of communication in e-commerce [32], the role of influencers on social media [33], and online tourist behavior [34]. The results of previous studies indicate that the linear path of the AISAS model is noteworthy and has a significant effect. However, in previous research, the use of the AISAS model in social marketing campaigns was notably limited, especially in the environmental sector—and most notably, in the realm of food waste. The stages of the AISAS model process, from attention to sharing, can proceed sequentially. One process is likely repeatedly passed or skipped [30]. The AISAS model used in previous research also tended to analyze the data in sequential order; therefore, Conducting research on food waste knowledge sharing using the AISAS model with both linear and non-linear sequencing is vital for a broader, comprehensive understanding of its influence and utility for reducing food waste. Therefore, this study aimed to analyze the effects of attention, interest, search, and action on knowledge sharing related to the issue of food waste.

2. Overview of the Literature

2.1. The AISAS Model

AISAS (Attention, Interest, Search, Action, and Share) is a form of transformation from the AIDMA model, which is considered to be anomalistic with technological developments in the modern era. AIDMA is a non-linear model that is considered to be able to explain only one-way information flow [35], while in the current era, consumer information search is not merely limited to a single source, including through communication with other consumers, and obtaining product/service provider contact information as well as results of comparisons between products from various information media [36]. The change from the AIDMA model to the AISAS model occurred through a condensed psychological transformation process and an expanded Action process into a Search, Action, and Sharing process [30].

Figure 1 represents both the models.

AISAS is a model developed by Dentsu that helps to understand shifts in consumer behavior and technological development [30]. The AISAS model describes the process by which consumers buy products/services, which begins by drawing attention to the products, services, or advertisements to generate interest. This interest encourages them to collect product information. The collected information becomes the basis for consumer decision-making when buying a product. After purchasing, consumers share their experiences with other consumers. The AISAS model does not need to move sequentially through each of the five stages. These steps can be skipped or repeated (Figure 2).

2.2. AISAS Non-Linear Models

The attention and interest stages are two stages that cannot be separated. Interest is activated if an individual pays attention to things that are considered interesting. One form of attention, visual attention, is an attention process that includes subconscious, selective, and repetitive processing controlled by the brain’s nervous system [37]. Consumers would be interested in a campaign if it contains interesting content in the form of photos, videos, or descriptions [38]. Previous research has shown that attention and interest have a positive correlation, where the attention that is built can lead to a feeling of interest [33,39,40,41]. Attention to something encourages people to seek deeper information about it. Information search is a way for individuals to guide their attention to objects that are relevant to the goals to be achieved [42]. When faced with several choices, people pay attention to certain attributes to make a decision that encourages them to seek more information [43].

One desire to seek further information is driven by interest in the noticed product/service. This interest would subsequently drive them to look for further information using the search feature or ask for it via the comment or contact feature [31,44]. Previous studies have found that people tend to seek interesting information through various media sources [33,39,40,41].

Information search helps consumers make decisions [42]. Accurate and credible sources must support effective information searches to encourage potential consumers to believe the information obtained [43]. Information search significantly influences subsequent action because it requires more information to reduce the risks resulting from the decisions and actions taken [44]. This phenomenon is also corroborated by previous research, which has shown that information search influences consumers’ subsequent action [33,39,40,41,45].

Information search encourages individuals to share the information obtained with others. Social media makes it easy to obtain and share information; information-search support features on Instagram, such as hashtags and geotags help disseminate information and support descriptions of the visual content that advertisers want to convey [46].

Those who have taken action or engaged in some activity share information and experiences in the form of photos, videos, or details of the activities on social media [31]. In this sense, consumer actions trigger knowledge sharing [33,39,40,41,45,47]. Based on the above explanation, we propose ten hypotheses as follows. Figure 3 displays the framework of this study.

H1. 

Attention influences the sense of interest in the issue of food waste.

H2. 

Attention affects the search for information on the issue of food waste.

H3. 

Attention influences action with regard to the issue of food waste.

H4. 

Attention to food waste influences knowledge sharing about the issue of food waste.

H5. 

Interest affects the search for information on the issue of food waste.

H6. 

Interest affects action on the issue of food waste.

H7. 

Interest related to food waste influences knowledge sharing on the issue of food waste.

H8. 

Information search influences action on the issue of food waste.

H9. 

Information searching related to food waste affects knowledge sharing on food waste issues.

H10. 

Actions to reduce the issue of food waste affect knowledge sharing on the issue of food waste.

3. Research Method

3.1. Design and Location

This study used a cross-sectional design and a survey method. This research was conducted at two universities with the International Association of Students in Agricultural and Related Sciences (IAAS) student activity units located on and outside Java Island. The IAAS was chosen as the research setting because it is an international-scale student organization in agriculture that was running a campaign program on reducing food waste, at the time of this study.

3.2. The Sampling Technique

The population in this study comprised student members and non-members of the IAAS community at two universities selected based on randomization. In this study, members of the IAAS community are referred to as food waste community members, whereas non-IAAS community members are referred to as non-food waste community members. Universities with the IAAS communities were categorized into two groups: those in Java Island and those outside Java Island. Furthermore, one university from each group was selected to represent its location. The sampling technique used in this study was voluntary sampling because the participants voluntarily filled out a questionnaire given to the head of each community. The IAAS member student group was obtained by voluntary sampling of 93 students, whereas the non-member IAAS student group at the same university was randomly selected from three communities each. Non-IAAS members were also obtained through voluntary sampling of 209 students. In this study, the sample size was adjusted to the structural equation modeling (SEM) analysis model used. The sample in this study finally amounted to 302 students because the limit for the sample size in the SEM was 200–800 persons.

3.3. The Research Instrument

Data were collected through a questionnaire developed with a five-point Likert scale. The AISAS model which includes the variables of attention, interest, search, action, and knowledge-sharing behavior (share) was employed to examine participant behaviors regarding the five variables. The attention and interest variable questionnaire was developed and modified by Sugiyama and Andree [30] and Abdurrahim et al. [38] and has six indicators. The search variable questionnaire was developed and modified from Sugiyama and Andree [30] and Abdurrahim et al. [38], and has six indicators. The action variable questionnaire was developed and modified by Sugiyama and Andree [30] and Abdurrahim et al. [38] and has four indicators. The behavioral knowledge sharing (shares) variable questionnaire was developed and modified by Sugiyama and Andree [30] and Abdurrahim et al. [38] and has five indicators.

3.4. Data Collection

Primary data were used in this study and were obtained directly from the sample through self-administration. Data regarding the variables studied were collected using an online questionnaire created using the Google Forms platform. The questionnaire was distributed to selected samples through various applications such as Line, WhatsApp, or email. The questionnaire contained an informed consent form so that there was agreement without coercion. The primary data included the five variables: attention, interest, search, action, and knowledge sharing (share), while the supporting variables included the demographic characteristics of the respondents (gender, age, ethnic origin, monthly allowance, individual monthly food expenses, and number of family members); reasons for joining or not participating in food waste communities; frequency of food waste in the past week; amount of food waste in one meal; and the main reasons for food waste behavior.

3.5. Data Analysis

The collected data were processed using Microsoft Office Excel, SPSS, and SEM PLS analysis using LISREL 8.80 software. SEM determines the effects of endogenous and exogenous latent variables, either directly or indirectly. Tests were conducted to analyze the influence of attention, interest, search, and action on knowledge sharing (share) related to food waste. The results for each variable were transformed into an index using the following formula [48]:

$$\mathrm{Index}=\frac{(\mathrm{s}\mathrm{c}\mathrm{o}\mathrm{r}\mathrm{e} \mathrm{e}\mathrm{a}\mathrm{r}\mathrm{n}\mathrm{e}\mathrm{d}-\mathrm{m}\mathrm{i}\mathrm{n}\mathrm{i}\mathrm{m}\mathrm{u}\mathrm{m} \mathrm{s}\mathrm{c}\mathrm{o}\mathrm{r}\mathrm{e})}{(\mathrm{m}\mathrm{a}\mathrm{x}\mathrm{i}\mathrm{m}\mathrm{u}\mathrm{m} \mathrm{s}\mathrm{c}\mathrm{o}\mathrm{r}\mathrm{e}-\mathrm{m}\mathrm{i}\mathrm{n}\mathrm{i}\mathrm{m}\mathrm{u}\mathrm{m} \mathrm{s}\mathrm{c}\mathrm{o}\mathrm{r}\mathrm{e})}\times 100$$

Description:

Index = indexed variable score,

Score earned = score obtained through examples based on measurement results,

Minimum score = minimum score on the instrument, and

Maximum score = maximum score on the instrument.

Variables that already had an index were then grouped into three categories based on the class interval of each variable, namely the low, medium and high categories. The cut offs in grouping the scale measurement were: the low category (index score < 60), the medium category (index score 60–80), and the high category (index score > 80).

The numbers resulting from the five variables were multiplied to obtain the Customer Response Index (CRI). This technique shows the audience’s reaction step by step, from the point of consumer awareness to the point at which it is possible to persuade them to act (in typical cases, to purchase) [49]. The CRI model was considered effective if the response stage exceeded 50 percent [50]. The following is a calculation formula and a representation of the CRI stage model [51], which was adapted to the AISAS model (Figure 4):

• Attention;
• Unattention;
• Uninterested = Attention × No Interest;
• Unsearch = Attention × Interest × No Search;
• Unaction = Attention × Interest × Search × No Action;
• Unshare = Attention × Interest × Search × Action × No Share;
• CRI = Attention × Interest × Search × Action × Share.

4. Results

4.1. Demographic Background

Table 1. Demographic background of the respondents.

Characteristics	n	%
Gender
Men	113	37.42
Women	118	62.58
Age
16–20 years	213	70.53
21–25 years	89	29.47
Mean ± Std	19.98 ± 1.50
Min–Max	17–25
Origin
Banjar	113	37.42
Batak	3	1.32
Bugis	12	3.97
Chinese	4	1.32
Dayaks	15	4.97
Java	132	43.71
Other	23	7.62
Income
IDR < 500,000	73	24.17
IDR 500,001–1,000,000	147	48.68
IDR 1,000,001–3,000,000	74	24.50
IDR 3,000,001–5,000,000	7	2.32
IDR > 5,000,001	1	0.33
Monthly food expenses
IDR < 500,000	101	33.44
IDR 500,001–1,000,000	157	51.99
IDR 1,000,001–3,000,000	43	14.24
IDR 3,000,001–5,000,000	1	0.33
Number of family members
≤4 people	160	52.98
5–7 people	129	42.72
≥8 people	13	430

presents the demographic section of the questionnaire.

4.2. Frequency of Food Waste

In this study, the frequency of food waste was calculated by food portions eaten in the past week. Food types were divided into 11 groups. The frequency of food waste was then grouped into four groups: never, rarely (<6 meals), often (6–10 meals), and always (>10 meals). The distribution of the sample based on the frequency of food waste is presented in

Table 2. Frequency distribution of food waste.

Food Types	Frequency of Food Waste (%)
	Never	Rarely (<6 Meals)	Often (6–10 Meals)	Always (>10 Meals)
Rice	51.32	36.42	6.62	5.63
Vegetables	50.99	38.74	8.94	1.32
Fruit and preparations	66.23	27.15	5.63	0.99
Sources of vegetable protein and processed products	64.57	26.82	6.29	2.32
Fish/chicken/beef/other meat	63.25	27.81	5.63	3.31
Processed meat products	77.15	19.87	1.99	0.99
Eggs and their preparations	68.21	23.18	6.29	2.32
Dairy products	70.53	24.17	4.64	0.66
Cake, bakery, snack, and cereal products	57.95	35.76	5.30	0.99
Root products	57.95	35.76	5.30	0.99
Pasta products	64.90	28.81	4.64	1.66

.

Most respondents reported never having discarded all types of food groups in the past week. Vegetables were the food most discarded by consumers, at least in the frequency of 6–10 meals (38.74% and 8.94%, respectively). Only a small proportion of respondents reported having thrown vegetable protein sources and their preparations (2.32%) and eggs and their preparations (2.32%) (

Table 3. The distribution of respondents based on the category of food waste frequency.

Category	N	%
Low (<60)	290	96.03
Moderate (60–80)	12	3.97
High (>80)	0	0
Mean ± SD	15.27 ± 17.54
Min–max	0.00–75.76

).

The results showed that respondents only threw away food sometimes in the past week. The behavior of wasting food was included in the low category for most respondents (96.03%). The respondents rarely discarded food in the past week.

4.3. Reasons for Food Waste Behaviors

Students did not finish their food mainly because the portion was too big (39.07%) and they did not like the taste (33.44%). Other reasons included health (4.97%), short eating time (3.64%), and lack of knowledge about the negative impact of food waste (2.32%). The main reason students did not waste their food was that it is a shame if they do not finish it (30.46%), they liked the taste of the food (25.17%), and the size of the portion was according to their capacity (21.19%).

4.4. Amount of Food Waste

The amount of food discarded in this study was calculated using tablespoons per serving. Food types were divided into 11 groups. The amount was then divided into four groups: 0 tablespoons, 1–2 tablespoons, 3–4 tablespoons, and >4 tablespoons (

Table 4. Distribution of the amount of food waste.

Food Type	Total Food Waste (%)
	0	1–2	3–4	>4
Rice	56.95	25.17	9.27	8.61
Vegetable	51.99	36.75	7.95	3.31
Fruit and preparations	72.52	19.87	4.30	3.31
Sources of vegetable protein and processed products	70.20	23.18	4.64	1.99
Fish/chicken/beef/other meat	71.52	22.52	3.97	1.99
Processed meat products	80.13	15.89	3.31	0.66
Eggs and their preparations	76.49	17.22	4.97	1.32
Dairy products	74.50	18.21	4.30	2.98
Cake, bakery, snack, and cereal products	65.56	24.83	6.62	2.98
Root products	66.56	26.49	4.97	1.99
Pasta products	71.19	19.87	5.63	3.31

).

Most respondents reported never having discarded any type of food group within the last week (zero spoons). Vegetables (36.74%), tubers (26.49%), and rice (25.17%) were the most discarded types of food with 1–2 tablespoons. Only a small proportion of respondents reported throwing away 3–4 cakes, bakery items, snacks, and cereals (6.62%). Meanwhile, more than four tablespoons of processed meat were discarded in one serving (0.66%) (

Table 5. The distribution of respondents based on the number of categories of food waste.

Category	n	%
Low (<60)	294	97.35
Moderate (60–80)	7	2.32
High (>80)	1	0.33
Mean ± SD	14.16 ± 16.49
Min–max	0.00–100

).

Based on the study results, only 0.33 percent of respondents wasted greater quantities of food. Most of the respondents’ total food waste indices (97.35%) were in the low category. In addition, the average index for the amount of food waste was also in the low category, indicating that only a small amount of food per meal was discarded by respondents.

4.5. AISAS

The AISAS model describes the development of consumer behavior influenced by technology-based social media [30]. Significant differences were found for each variable, based on the type of student community.

Table 6. AISAS categories based on community type.

Category	Community Type (%)		p-Values
	IAAS	Non-IAAS
Attention
Low (<60)	34.41	50.24	0.001 **
Moderate (60–80)	46.24	38.28
High (>80)	19.35	11.48
Mean ± SD	65.77 ± 16.55	58.33 ± 19.92
Min–max	25.00–100	0.00–100
Interest
Low (<60)	5.38	23.44	0.000 **
Moderate (60–80)	55.91	47.37
High (>80)	38.71	29.19
Mean ± SD	76.28 ± 14.54	68.13 ± 21.67
Min–max	33.33–100	0.00–100
Search
Low (<60)	37.63	50.24	0.039 *
Moderate (60–80)	46.24	43.06
High (>80)	16.13	6.70
Mean ± SD	60.93 ± 20.14	55.95 ± 18.80
Min–max	0.00–100	0.00–100
Action
Low (<60)	9.68	39.23	0.000 **
Moderate (60–80)	36.56	30.14
High (>80)	53.76	6.70
Mean ± SD	80.11 ± 16.94	66.43 ± 23.08
Min–max	33.33–100	0.00–100
Share
Low (<60)	76.34	87.08	0.000 **
Moderate (60–80)	17.20	9.57
High (>80)	6.45	3.35
Mean ± SD	40.07 ± 24.39	23.54 ± 25.32
Min–max	0.00–100	0.00–100

* p < 0.05; ** p < 0.01.

shows that most IAAS member students exhibited moderate attention, interest, search, high action, and low knowledge-sharing behavior regarding food waste. Most non-IAAS students had low levels of attention, search, action, and knowledge sharing, while their interest in food waste was moderate.

The effectiveness of a campaign can be seen through the CRI model. The percentage of CRI values in the AISAS model can be determined by analyzing the dimensions of attention, uninterest, research, unaction, and unshare. As shown in Figure 5, the AISAS CRI flow model for the food waste campaign has a value of 7 percent up to the sharing stage, which is smaller than the values for unattention (29.33%), uninterest (10.7%), research (20.7%), unaction (7.6%), and unshare (24.6%). These findings show that the food waste campaigns that have been conducted have tended to be ineffective, and knowledge sharing among students is still low and needs to be improved.

4.6. The Structural Model Test

This study proposed ten hypotheses that examined the effect of one variable on another. Hypothesis testing was performed by testing the structural model, which included path coefficient values and their t-values. The coefficient tested is said to be significant if the t-values are ≥1.96 [52]. The hypothesis was accepted if the p-values were <0.05 or the t-values were >1.96 (|z| > 1.96) [52]. The results of the structural model test are presented in

Table 7. Structural model test results.

Path	Path Coefficient	t-Values	Conclusion
Attention → Interests	0.431	6.950	H1 is accepted
Attention → Search	0.245	3.750	H2 is accepted
Attention → Actions	0.120	1.748	H3 is rejected
Attention → Share	0.205	0.252	H4 is rejected
Interest → Search	0.205	3.213	H5 is accepted
Interest → Action	0.279	3.487	H6 is accepted
Interest → Share	−0.055	1014	H7 is rejected
Search → Action	0.108	1.751	H8 is rejected
Search → Share	0.294	6.627	H9 is accepted
Action → Share	0.205	3.828	H10 is accepted

.

Based on the structural model test results, six of the ten hypotheses tested in this study were accepted and found to have a significant positive effect, with t-values of more than 1.96 (H1, H2, H5, H6, H9, and H10). Attention had the greatest influence on interest, with a t-value of 6.95. The more respondents paid attention to online food waste media campaigns, the greater was the interest. Sharing behavior or knowledge sharing was more influenced by the search variable than action, with a t-value of 6.627. The greater the exchange of information about food waste on the Internet, the greater the sharing behavior of the respondents. The structural test results of the PLS-SEM model are shown in Figure 6.

The validity test in the SEM model was conducted using construct validity, also called factorial validity, by comparing the square root of the average variance extracted (AVE) for each construct with the correlation value between the constructs in the model. The AVE value in the validity test must be >0.5, which indicates that 50 percent or more of the variance in the indicator can be explained. In addition to the validity test, a reliability test of the SEM model was carried out to prove the accuracy of the instrument in measuring a construct. Construct reliability (CR) was used to test construct reliability. The CR value commonly used in reliability tests of a construct must be greater than 0.7. All variables (attention, interest, search, action, knowledge sharing behavior (share), eWOM, and emotions) in this study met the reliability requirements with a CR value greater than 0.7 and an AVE value greater than 0.5. Overall, this shows that all variables describe their latent constructs well. The results of The AVE and CR values are listed in

Table 8. Value of construct reliability and average variance extracted.

Latent Variables	Construct Reliability (CR)	Average Variance Extracted (AVE)
Attention	0.83	0.55
Interest	0.92	0.67
Search	0.86	0.51
Action	0.85	0.59
Knowledge Sharing Behavior (Share)	0.93	0.72
eWOM (electronic word of mouth)	0.85	0.55
Emotion	0.87	0.63

.

4.7. Direct and Indirect Effects

The total effect value was obtained by adding the path coefficient values of the exogenous variables to the mediator variable with the indirect effect value. Based on the calculation results presented in

Table 9. The results of the direct, indirect, and total influence of the variables.

Path Variables	Influence
	Direct	Indirect	Total
Attention → Interest	0.431	-	0.431
Attention → Search	0.245	0.088	0.333
Attention → Action	-	0.156	0.156
Attention → Share	-	0.131	0.131
Interest → Search	0.205	-	0.205
Interest → Action	0.279	0.022	0.301
Interest → Share	-	0.122	0.122
Search → Share	0.294	0.022	0.316
Action → Share	0.205	-	0.205

, the direct effect of interest on attention has the greatest value compared to the other pathways. Attention indirectly influences search through interest, and thus interest strengthens the influence of attention on search. The values of the direct effects of all variables were greater than those of the indirect effects. The indirect effect of the intermediary variable was not sufficiently strong to influence the endogenous variable. By contrast, exogenous variables are stronger and thus more able to directly influence endogenous variables without requiring the contribution of intermediary variables.

5. Discussion

5.1. The Effect of Attention on Interest (H1)

The results show that attention, has a significant and positive effect on interest; therefore, Hypothesis 1 (H1) was accepted. The appearance of campaign delivery media drove the awakening of attention. The beauty of design, color composition, sound clarity, stillness of photo posters, and video media can encourage students to pay attention to food waste campaigns. When students pay attention to a food waste campaign they see on the Internet, it positively encourages their interest in the information conveyed in the campaign. Interest automatically arises when viewing and paying attention to interesting content on social media [31]. The appearance of the campaign media, such as layout or image capturing, also drove interest among participants in our study. In addition, the information contained, suitability of the topic, and ease of understanding the information contained in the campaign also contributed to the emergence of a sense of interest in food waste campaigns. These results align with the research by Abdurrahim et al. [38] that interesting content can attract individuals interested in a campaign. Greater attention is likely to increase the appearance of interest in a campaign [33,39,40,41]. Interest or disinterest in information is based on certain reasons. Attention and interest are the most important stages to be able to proceed to the next stage [53].

5.2. The Effect of Attention on Search (H2)

The results showed that attention had a significant and positive effect on search; thus, Hypothesis 2 (H2) was accepted. Attention to the campaign’s food waste attributes affects students’ curiosity; to fulfill their curiosity, students conduct information searches. An information search is a way for individuals to guide their attention to objects that are relevant to the goals to be achieved [40]. The beauty of design, color composition, sound clarity, and duration of time are attributes of food waste campaigns that attract students’ attention, thus encouraging them to seek further information. Anyone who pays attention to an object will make that person want to know more and attempt to find information about the object of concern at the time [54]. However, it was found that the search category for IAAS member students was in the medium category, and that for non-member students was in the low category. This is similar to the attention category patterns of IAAS member and non-member students.

5.3. The Effect of Attention on Action (H3)

The results showed that attention did not significantly influence action; therefore, Hypothesis 3 (H3) was rejected. The results of the distribution show that the attention of IAAS member students and non-IAAS members towards food waste campaigns is lower than actions or efforts to reduce food waste. Several factors influence actions taken; accordingly the influence test results showed that attention indirectly affects action. Needs recognition, information search, and evaluation processes have become important parts of behavior and can predict the actions that individuals may take [55]. These results align with the research by Xue et al. [34]), which showed that attention is a crucial factor needed to encourage individuals to seek further information. However, attention does not directly influence action. Several other factors can also influence actions towards food waste reduction. An individual’s pro-environmental behavior is determined by psychological factors such as perceived behavioral control, attitudes, values, norms, morals, intentions, and factors that impact action through the indirect influence of beliefs and motivation [56]. However, the results of this study showed that the action category was high for IAAS member students. In addition, the action category of non-members of the IAAS was in the medium category.

5.4. The Effect of Attention on Knowledge Sharing (Share) (H4)

The results showed that attention did not significantly influence knowledge sharing (share); thus, Hypothesis 4 (H4) was rejected. The results of the distribution show that the attention that IAAS member students and non-IAAS members have towards the food waste campaign is greater than the knowledge sharing of food waste issues carried out by students with other people. Based on this category, students who were members and non-members of the IAAS were in the low category in terms of knowledge sharing. The attention paid to the food waste campaign is good enough, but students tend to be reluctant to share their knowledge regarding aspects that attract their attention–in this case, the issue of food waste. People typically share experiences with others after they use or carry out an action/activity. Those who have taken action share information and experiences in the form of photos, videos, or details of the actions/activities on social media [31]. In this study, attention indirectly affected knowledge sharing, because students were yet to show any interest in taking action on the issue of food waste. These results are reinforced by research conducted in Xue et al. [34], which stated that individuals only share their knowledge in the form of information or comments after they have direct experience.

5.5. The Effect of Interest on Search (H5)

The results show that interest has a significant and positive effect on search; thus, Hypothesis 5 (H5) is accepted. The presence of the Internet is believed to speed up the process of people’s interest in things because information can be obtained using the search feature and comments section on social media [31]. This result is in line with previous studies that found that people tend to seek interesting information through various media [33,39,40,41]. If an individual is interested in something, they will look for additional information as a form of interest; the higher the attractiveness, the more the person will look for information to satisfy their interest [44]. Students reported being interested in the issue of food waste; therefore, they actively searched for information on the Internet regarding programs and communities engaged in food waste. Information related to nutrition and health is the most sought-after information on the Internet, which is related to the types of food allowed according to health conditions and levels of nutritional adequacy according to daily needs. With awareness of their own bodies, students can choose the food they consume to reduce food waste. If food is not finished, students tend to look for information related to ways of processing the food to avoid throwing it away. However, in this study, students still felt that it was not important to seek information related to efforts to reduce food waste.

5.6. The Effect of Interest on Action (H6)

The results show that interest has a significant and positive effect on action; therefore, Hypothesis 6 (H6) is accepted. Interest in the issue of food waste influences students to make efforts to reduce it. This interest encourages students to look for information on nutrition and health on the Internet and then implement it, one form of which is related to the types of food allowed based on health conditions and levels of nutritional adequacy according to daily needs. Interest is an important factor in encouraging action. Interest is needed to attract attention so that an individual takes action, and the higher the level of interest a person has towards an object, the greater the action that will be taken. Students’ interest in the issue of food waste makes them sort the food they will consume to minimize the occurrence of food waste that cannot be consumed [57]. Previous research states that messages conveyed through the media can attract attention, arouse further curiosity, generate desire, and stimulate real action [47].

5.7. The Effect of Interest on Knowledge Sharing (Share) Behavior (H7)

The results showed that interest did not significantly influence knowledge sharing (share); therefore, Hypothesis 7 (H7) was rejected. The distribution results showed that the IAAS and non-IAAS member students’ interest in the issue of food waste was higher than their knowledge sharing on food waste issues. The average interest held by students was in the moderate category, whereas the average knowledge sharing (share) was in the low category. In this study, interest indirectly affected knowledge sharing; this could be because students have yet to take action to reduce food waste [58]. These results are reinforced by the research conducted by Xue et al. [34], which states that individuals will only share their knowledge in the form of information or comments after having had direct experience. According to Cheng, Ho, and Lau, the factors that influence a person’s decision to share information or knowledge (knowledge sharing) are divided into three groups: organizational, individual, and technological factors. Organizational factors are caused by the environment or other people sharing knowledge. Individual factors come from within the individual (internal) in the form of beliefs, perceptions, expectations, attitudes, and feelings. Technological factors include software (media and applications) and hardware (smartphones and computers) that can be used in sharing activities [59].

5.8. The Effect of Search on Action (H8)

The results showed that search had no significant effect on action; therefore, Hypothesis 8 (H8) was rejected. The results of the distribution show that the search for information related to food waste by students who are members or non-members of the IAAS is less than the actions or efforts to reduce food waste carried out by students. This research is not in line with the AISAS linear model. Information obtained from search results typically push a person’s actions owing to the decision-making process and sorting of information [60]. However, this study shows that actions or efforts to reduce food waste were not directly influenced by seeking information related to food waste. Several other factors can influence the actions to reduce food waste, as mentioned above. The results of this study are not in line with previous research, which states that information seeking strongly influences the chosen action decision because a person needs more information to reduce the risks arising from the decisions and actions taken [44]. This action is supported by previous research, which has shown that information search influences consumers’ potential actions [33,39,40,41,45].

5.9. The Effect of Search on Knowledge Sharing (Share) Behavior (H9)

The results showed that search had a significant and positive effect on knowledge sharing (share); thus, Hypothesis 9 (H9) was accepted. Searching for information related to food waste on the Internet can encourage students to share the information they receive via the Internet. Share occurs when individuals obtain information from their search results and retell this information to people so that word of mouth is created [61]. After searching for information related to food waste on the Internet, the students decided to share the information they received with others. Experiences that students can share on the Internet related to efforts to reduce food waste can take the form of photos, videos, etc. Experiences can be conveyed directly face-to-face or through writing, pictures, or videos) [62]. The application of behaviors to reduce food waste obtained from the recommendations of others can also generate a desire to share experiences, and satisfaction with the activities carried out will make it easier for someone to share experiences related to these activities [63]. The search for information continues until a person feels that they have enough information to accurately increase their knowledge, so that the information is passed on to a wider audience [42].

5.10. The Effect of Action on Knowledge Sharing (Share) Behavior (H10)

The study results show that the action variable significantly and positively influenced the knowledge-sharing variable. Consumers’ actions encourage them to share knowledge with others [33,39,40,41,45,47]. Students reported implementing food waste reduction behaviors to invite others to participate in reducing food waste by sharing information and experiences via the Internet. The experiences shared were in the form of photos or videos about their contribution to food waste reduction programs and their applications in everyday life. Students who implemented food waste reduction behaviors are typically willing to provide positive testimonials via the comments section or upload them to personal social media accounts by sharing their experiences [38]. In addition, the students recommended ways to reduce food waste, such as taking food portions according to their capacity or buying food as needed. Knowledge sharing is effective because it not only shares knowledge and experience but also encourages the spread of good values to the wider community [64]. However, the extent of knowledge sharing on the issue of food waste is still low.

6. Research Implications

The results showed that information seeking and action directly influenced knowledge sharing regarding food waste issues. These linkages directly influence actions taken to reduce food waste. Searching for information related to the issue of food waste is directly influenced by attention and interest, and interest is directly influenced by attention. The results show that the AISAS model runs linearly as well as non-linearly; therefore, all components in the model must be considered because they greatly influence one another.

Based on the findings of this study, activist organizations such as Garda Pangan, EcoBali, The Hunger Bank, the Brotherhood, the Foodbank of Indonesia, the International Association of Students in Agricultural and Related Sciences (IAAS), and other activists must make further efforts to address the issue of food waste, both commercial and non-commercial. The dissemination of information on the existence of a community of activists on environmental issues, especially food waste, needs to be carried out more intensively because, from the distribution of research results, 71.29 percent of students were not aware of the existence of the IAAS as a community on campus that focuses on environmental issues. In this era of technological development, food waste issue activists must understand that digital campaigns are very effective because they target various groups and are not limited by time and distance. This approach needs to be undertaken continuously to attract public attention, apart from the intensity of variations in content packaged through audiovisual methods and inviting various influencers to engage in eWOM [65]. Information provided by well-known influencers can become increasingly trusted and attract more attention, if it is effectively conducted to attract the attention of consumers. Consumer attention is the key to attracting consumers, driving them to seek further information, take action to reduce food waste, and share knowledge and experience, to contribute to the issue of food waste. Consumer attention is the key to attracting consumers, corroborating the findings that attention directly affects interest. Seeking further information is thus a form of attention and interest that affects information-seeking. Furthermore, taking action to reduce food waste corroborates the fact of interest directly affecting action. Sharing knowledge or experience of contributing to the issue of food waste corroborates the findings that information search and interest directly affect knowledge sharing. In addition, when purchasing products that generate waste, socialization is necessary for better waste management [66].

Knowledge sharing on food waste issues appears to be extremely low; consumers tend to be reluctant to share their knowledge or experience of food waste issues. Education for consumers regarding the emphasis on environmental issues and the role of consumers as agents of change needs to be strengthened. Consumers need to realize that small actions such as sharing their knowledge and experiences regarding environmental issues will impact and attract the attention of other consumers to be equally sensitive to the environment and bring about changes in consumption patterns in a more sustainable manner. This is an implication of the results, which show that actions directly affect knowledge sharing. The role of the regulator, in this case the Ministry of Environment and Forestry as the government, is needed for collaborating with all environmental activists to oversee the issue of food waste by issuing well-packaged programs. Awareness and education campaigns can lower the demand for purchases and the amount of waste dumped in landfills [67]. Massive campaigns in the form of advertising on the issue of food waste are effectively carried out by elaborating campaign issues into trends that are currently developing among the public and are presented attractively, starting from campaign content, audio, and visuals, to persuasive slogans that can attract public attention. Additionally, campaigns are conducted to build public curiosity so that people seek further information as well as informative campaigns that can inspire the public to contribute to the reduction in food waste through their actions. Thus, campaigns are not just to attract the attention of the public but as a source of driving change in people’s lifestyles in a sustainable direction. This implication is a necessary response to the result that attention and interest directly influence information seeking. In addition, attention directly influences interest, and interest directly influences action—a finding that must be leveraged in order to induce more concrete behaviors against food wastage.

7. Research Limitations

The limitations of this study, namely voluntary sampling, mean that the results cannot be generalized. The scope of this study on food waste is limited to the consumption stage and does not include the purchasing, processing, and preparation stages. The intensity of exposure to information on food waste and the form of information obtained by students were not elaborated upon in the research. Therefore, the extent to which the information exposure students received regarding attention, attractiveness, information seeking, action, and knowledge sharing students in overseeing the issue of food waste was not perfectly illustrated.

8. Conclusions

This study found significant differences in attention, interest, search, action, and sharing between community members in the fields of food and non-food waste. Student community members in the food waste field were found to pay attention, feel interested, seek further information, and exchange information related to food waste on the Internet. The execution of behaviors to reduce daily food waste was also conducted. Research shows that students are exposed to a large amount of information on food waste and are sufficiently concerned with the information contained in the exposure. This attention has also aroused interest in finding deeper information about the food waste obtained. After extracting information, students were encouraged to apply it in their daily lives by consuming the food that is served, taking food portions according to their abilities, and buying food according to their needs. The experience gained from implementing behaviors to reduce food waste is sufficient to encourage students to share knowledge on the Internet, even though it is still in the low category.

The results showed that attention has a direct effect on interest and information seeking; interest has a direct effect on information seeking and action; information seeking has a direct effect on knowledge sharing on food waste issues; and action has a direct effect on knowledge sharing on food waste issues. The results of this study prove that the AISAS model can be executed both linearly and non-linearly. AISAS non-linearity is established from the findings of the effect of attention on search and interest in action. Attention was found to have a significant positive direct effect on search without the need to go through an interesting process. Interest was also found to have a significant positive direct effect on action without the need to go through the information search process. Consumers’ knowledge sharing can provide new information to many people and can be reached more widely through digital communication innovations. This can enable digital communication innovation to grow through the delivery of information in the form of digital media, which is attractive and easy to understand. In addition, it can measure the performance of the information conveyed, and whether it can be received and responded to properly through the growing features of digital communication.

Recommendations

The results showed that the attention and search of student members in the non-food waste community was low. Additionally, knowledge sharing (share) among students of the two communities could be higher. Attention can be generated through the design attractiveness of various food waste campaign media. Based on the results of this study, many students sought information on nutritional adequacy according to their daily needs. Therefore, search can be encouraged by increasing the information related to nutritional adequacy on the Internet. A food waste campaign up to the sharing stage still needs to be more effective. This can be improved by increasing knowledge sharing related to food waste by enriching the experiences and information on reducing food waste, so that more information can be shared with others. The inculcation of food values has been reported to not be widely accepted by students from an early age. There needs to be an inculcation of value towards food so that they can be accustomed to appreciating food and minimizing food waste from an early age.