Identifying Key Behaviour Patterns that Influence Plastic Bag Refusal Decisions

The increasing environmental crisis has made the issue of plastic waste a major topic in global discourse. Although many studies have investigated broader aspects of sustainability, few have investigated the specific behavioral patterns that lead individuals to make environmentally conscious decisions, such as refusing to use plastic bags. This study aims to fill the research gap by identifying the main behavioral patterns that influence the decision to refuse the use of plastic bags. To methodically achieve this goal, this research uses the CRISP-DM (Cross-Industry Standard Process for Data Mining) framework as its guiding analytical paradigm. Data was collected through a carefully designed questionnaire, involving a sample size of 268 respondents. The decision tree algorithm was applied to the data, allowing detailed exploration of behavioral patterns that significantly contribute to plastic bag use aversion. Preliminary findings reveal the interaction of behavior, attitude and actions factors that collectively guide individuals in making sustainable choices. These insights not only contribute to the existing literature but also offer actionable avenues for future policy interventions.


Introduction
The widespread use of plastic has become a significant global concern and poses a major threat to environmental sustainability.Plastic waste has inundated a variety of ecological habitats-from deserts and oceans to mountainous areas-exacerbating existing environmental challenges [1], [2].As a persistent pollutant, plastic waste is not only difficult to decompose but also causes various adverse impacts, including but not limited to, soil degradation, water pollution, and damage to aquatic life [3], [4].
Given the magnitude of this problem, there is increasing scientific attention aimed at examining broader paradigms of environmental sustainability [5]- [8].Despite this, there remains a striking gap in the literature: the specific behavioral determinants that influence individuals' decisions to undertake environmentally friendly practices, such as refusing the use of plastic bags, remain largely unexplored.[9]- [11]Consumer choice is key in the fight against plastic pollution [12], [13], therefore understanding the underlying behavioral patterns is an urgent need.
The urgency of this research is underscored by the escalating environmental crisis and the pressing need for effective policy interventions [14].Especially, after the new norm, the waste management becoming concern, due to the increasing of waste production [15].To date, legislative measures aimed at limiting plastic use have had little success, due in part to a lack of insight into the complex interactions 1324 (2024) 012081 IOP Publishing doi:10.1088/1755-1315/1324/1/012081 2 between cognitive, social, and environmental factors that determine individual behavior.Therefore, this study aims to fill this critical gap by identifying the main behavioral patterns that influence the decision to refuse the use of plastic bags.
Using the CRISP-DM (Cross-Industry Standard Process for Data Mining) framework as a guide for analysis, this research used a robust methodology involving a carefully designed questionnaire and a sample size of 268 respondents.By utilizing a decision tree algorithm, this study offers a differentiated exploration into the behavioral patterns that significantly contribute to plastic bag aversion.Through this investigation, this research aims to explore whether there are certain patterns related to environmental sustainability behavior and insight, which lead to actions to reject the use of plastic bags.In addition, this research also aims to provide actionable insights that can form the basis of future policy interventions designed to encourage sustainable consumer behavior.

Theoretical Foundations
The use of plastic bags is a global problem that contributes to the increase in the amount of plastic waste [14], [16].based on data, the largest plastic pollutan comes from packaging, reaching 142.6 million tonnes per year in 2019 [17].This plastic waste problem is an urgent matter that must be followed up immediately.it requires the contribution of various parties, including academics.Research on the use of plastic bags, conducted by Monsserate & Milano, emphasizes plastic bag consumption behavior.This research tries to explore the factors that influence the decision to use deposable plastic or reusable bags [16].The researcher believes that heads of households has significant role in deciding whether use the deposable or reusable bags.Efforts to reduce the use of plastic bags in several countries are carried out by charging prices.This policy is expected to reduce and change the behavior of using plastic bags.Research on behavior and attitudes of people regarding plastic bag charges was conducted in England [18].The research results show that there has been a reduction in the use of plastic bags and this charge policy has received support from people.The same policy is implemented in China, as part of the Chinese government's efforts plastic bag to reduce the use of plastic bags.Research was conducted to measure the effectiveness of implementing this policy [11].Unfortunately, this policy actually boomeranged.The research results showed that there was a 44% decrease in the use of plastic carrier bags, whereas there was a sharp increase in the use of plastic inner bags, which were provided free of charge.Research on factors that might influence the behavior of using plastic bags was carried out to be able to contribute to reducing the use of plastic bags.One of the studies was conducted in Malaysia to identify what factors can contribute to reducing plastic consumption [19].This research shows that attitudes and behavior to reduce the use of single-use plastic are closely related.This means that if you want to result in a reduction in the use of single-use plastic, then attitudes towards this reduction must be strengthened.Similar research was conducted in Indonesia to look for factors that could support interest in using ecofriendly plastic [20].The research results show that if someone feels a sense of comfort, convenience, and at the same time has the opportunity to use environmentally friendly reusable bags, then this will increase willingness to buy eco-friendly bag.Despite the increasing body of literature on plastic waste management and consumer behavior, there exists a notable gap in understanding the specific behavioral patterns that lead individuals to refuse the use of plastic bags.Most existing studies have either focused on the effectiveness of policy interventions like charging for plastic bags or have explored consumer behavior in a limited geographical context.Furthermore, these studies often employ traditional statistical methods and lack a comprehensive analytical framework that considers the complex interplay of cognitive, social, and environmental factors.This study aims to fill these gaps by employing the CRISP-DM framework and decision tree algorithms to provide a nuanced understanding of the behavioral patterns influencing plastic bag refusal.Moreover, this research aims to offer actionable insights for future policy interventions, thereby contributing to both academic literature and practical applications.

Research Method
This study adopts the CRISP-DM (Cross-Industry Standard Process for Data Mining) framework as its guiding analytical paradigm.The CRISP-DM framework provides a structured methodology for planning, organizing, and executing data-driven research, making it particularly suitable for investigating complex behavioral patterns.

Business Understanding
Based on the research gap, there has been no research that examines what patterns can lead to a decision to reject the use of plastic bags.The aim of this research is to find out the pattern of decisions to refuse the use of plastic bags.

Data understanding
To be able to answer this research question, appropriate data is needed according to the context of this research.In this case, research data was collected through a questionnaire distributed to 268 entrepreneurship students taking the sustainability short course.The data collected includes the following: specific statement about attitude toward sustainability, specific statement about behavior related to sustainability and the actions they choose to reject the use of plastic bags.The data shows on the table bellow:

Data Processing
The collected data is prepared for modeling.At this stage, data is cleaned so that there are no missing values.Data transformation is carried out in the attribute and answer columns to make it easier to read the results

Modelling
To answer this research question, a decision tree algorithm was implemented.The following is a display of the operators used for this modelling:

Evaluation
After processing the decision tree model, the results are obtained in the form of a decision tree.The full discussion of this part will be discussed in the results and discussion section

Deployment
The results of modeling with a decision tree will be analysed to produce implementation.The discussion of this section will be discussed in the results and discussion section

Result and Discussion
The decision tree model, constructed using RapidMiner, revealed a complex interplay of behaviors and attitudes that influence the decision to refuse the use of plastic bags.The model identified several key behaviors and attitudes, such as turning off lights, closing a tap, switching off electricity, and attitudes towards sustainability, as significant predictors.

Attitudinal Indicators
• Care About Sustainability Issues: This attitude was a recurring factor in the decision tree, affecting outcomes in combination with various behaviors.It suggests that a general concern for sustainability can influence specific actions like plastic bag refusal.
• Small Participant Make Changes: The belief that one's small actions can make a difference was another significant attitudinal factor.This was especially true when combined with specific behaviors like using reusable items.
The decision tree revealed that no single behavior or attitude could predict plastic bag refusal decisively.Instead, it is the combination of multiple behaviors and attitudes that guide this decision.For instance, individuals who both switch off electricity and care about sustainability issues show a complex pattern of responses towards plastic bag refusal.The findings suggest that interventions aimed at promoting plastic bag refusal should consider both behavioral and attitudinal factors.Simple behavioral nudges, combined with education on the importance of sustainability, could be more effective than focusing on either aspect alone.The decision tree model exhibits a moderate level of effectiveness, with an overall accuracy of 62.36%.This suggests that the model correctly predicts the outcome-whether respondents would refuse plastic bags-in approximately 62% of the cases.However, the model's performance varies across different classes.It is particularly strong in identifying instances where the answer is "Yes," boasting a recall rate of 74.39%.This indicates that the model is adept at correctly identifying most of the actual "Yes" cases.
On the other hand, the model demonstrates high precision in predicting "Maybe" and "No" outcomes, with rates of 72.16% and 70.21%, respectively.These high precision rates suggest that the model is less likely to produce false positives for these classes.Despite these strengths, the model's weakest point is its precision in identifying "Yes" cases, which stands at 51.26%.This lower precision indicates that the model often misclassifies instances from other classes as "Yes," leading to a higher number of false positives.Given these varying performance metrics, it may be beneficial to consider additional features or a more complex modeling approach to improve the model's predictive power, particularly for the "Yes" class.

Conclusion
The urgency of addressing the environmental crisis, particularly the issue of plastic waste, cannot be overstated.This study aimed to contribute to this critical discourse by identifying key behavioral and attitudinal patterns that influence individuals' decisions to refuse the use of plastic bags.Utilizing the CRISP-DM framework and a decision tree algorithm, the study revealed a complex interplay of multiple factors that guide such decisions.The study's decision tree model achieved a moderate level of accuracy at 62.36%, indicating that while the model is a useful tool for understanding behavioral patterns, there is room for improvement.The model was particularly adept at identifying instances where individuals were likely to refuse plastic bags, with a recall rate of 74.39%.However, the model's precision varied, suggesting that additional features or a more complex modeling approach could enhance its predictive power.
The findings of this study have several implications for both academic research and practical policy interventions.Academically, the study fills a notable gap in the literature by employing a data-driven approach to understand the specific behaviors and attitudes that influence plastic bag refusal.Practically, the insights gained could inform more effective policy interventions.For instance, educational programs could be designed to target specific behaviors and attitudes identified as significant predictors in the model.this research not only enriches the existing literature on sustainability and plastic waste management but also provides actionable insights for shaping future policies.While the model's moderate accuracy suggests the need for further refinement, its ability to identify key behavioral and attitudinal indicators holds promise for the development of more targeted and effective sustainability interventions.

Fig 2 .
Fig 2. Result of decision tree 4.1.Behavioral Indicators • Turning Off Lights: The model indicates that individuals who do not engage in the behavior of turning off lights when not in use are more likely to refuse plastic bags.This finding suggests that even basic energy-saving behaviors can be indicative of broader environmental attitudes.• Closing a Tap: The act of closing a tap, especially when combined with turning off lights, emerged as another significant behavioral indicator.Individuals who neglect both these actions are more likely to refuse plastic bags, pointing to a pattern of general environmental indifference.• Switching Off Electricity: This behavior was significant in multiple branches of the decision tree.Those who switch off electricity when leaving a room, particularly when combined with other behaviors, show varying tendencies towards plastic bag refusal.

Table 2 .
Performance result