Predictors of illegal dumping at charitable collection points

Assessing and predicting the illegal dumping risks in relation to road characteristics

Using historical data to assess illegal dumping risks has significant potential to enhance the effectiveness of waste management in low-population density counties where the ability to patrol and regulate illegal dumping is limited. Using big data and geographical analysis to identify high-risk areas plays an important role in improving the effectiveness of supervision related to illegal dumping. However, current methods for classifying risk areas have limited accuracy. Taking an area in South Australia as an example, this study aims to improve the accuracy of classifying risk areas by using geo-information technology and machine learning methods. The results show that combining illegal dumping locations with road characteristics allows the high-risk areas to be refined to road sections. Compared with identifying the whole road or area as a high-risk spot, this result could be beneficial for monitoring illegal dumping in real life. Moreover, this model allows the analysis of factors that affect illegal dumping locations. Results show that the influencing factors for different risk levels of illegal dumping vary significantly. The model developed in this research can effectively distinguish risk levels according to these factors, and the model classification accuracy can reach 85%. In addition, there are priorities amongst these factors. This finding could help environmental authorities to allocate equipment and personnel with consideration of varying level of importance of those factors. This study has both technical contributions to identify high risk areas of illegal dumping, and theoretical implications for its management.

Status quo of illegal dumping research: Way forward

Due to the rapid social and economic development, the past decades have witnessed the improvement of human being's quality of life and the speedy development of the construction industry. Meanwhile, the illegal dumping of solid waste has presented a significant issue. By using the method of systematic review, this study critically examined the literature related to illegal dumping that were published since 1990, and analyzed the current status and future trends of related research. Results show that the current studies on illegal dumping mainly focus on four perspectives: environmental science and toxicology, economics, management, and the use of emerging technologies. This critical review revealed that although the issue of illegal dumping has been widely recognized in recent years, some questions remain unanswered. Therefore, a future research agenda is proposed. These include: (1) Identifying the migration of pollutants in the food chain during the illegal dumping; (2) Implementing targeted treatment of illegal dumping pollutants; (3) Improving the stakeholder decision analysis model; (4) Expanding the scope of research on stakeholders of illegal dumping; (5) Formulating an unified evaluation standard for the related costs of illegal dumping; (6) Strengthening the evaluation of the interaction effects of influencing factors; (7) Comparing the effects of different types of factors; (8) the exploration of other influencing factors; (9) Analyzing illegal dumping by combining big data with the amount of solid waste; (10) Combining with monitoring to analyze the illegal dumping of household waste.

Social Advertising Effectiveness in Driving Action: A Study of Positive, Negative and Coactive Appeals on Social Media

Background: Social media offers a cost-effective and wide-reaching advertising platform for marketers. Objectively testing the effectiveness of social media advertising remains difficult due to a lack of guiding frameworks and applicable behavioral measures. This study examines advertising appeals’ effectiveness in driving engagement and actions on and beyond social media platforms. Method: In an experiment, positive, negative and coactive ads were shared on social media and promoted for a week. The three ads were controlled in an A/B testing experiment to ensure applicable comparison. Measures used included impressions, likes, shares and clicks following the multi-actor social media engagement framework. Data were extracted using Facebook ads manager and website data. Significance was tested through a series of chi-square tests. Results: The promoted ads reached over 21,000 users. Significant effect was found for appeal type on engagement and behavioral actions. The findings support the use of negative advertising appeals over positive and coactive appeals. Conclusion: Practically, in the charity and environment context, advertisers aiming to drive engagement on social media as well as behavioral actions beyond social media should consider negative advertising appeals. Theoretically, this study demonstrates the value of using the multi-actor social media engagement framework to test advertising appeal effectiveness. Further, this study proposes an extension to evaluate behavioral outcomes.