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Mauritius is a Small Island Development State (SIDS) with limited resources, and it has been witnessed that many containers used for storing household and industrial products are made from plastic. When discarded as waste, those plastic containers pose a serious environmental and economic challenge for Mauritius. Moreover, landfill space is getting increasingly scarce, and plastic waste is contaminating both land and water. Therefore, it is of the utmost necessity to develop solutions for Mauritius' plastic wastes. Due to its abundance and accessibility, plastic waste is a promising material for recycling and energy production. One potential solution is the use of machine learning and artificial intelligence (AI) to predict household plastic consumption, allowing policymakers to design effective strategies and initiatives to reduce plastic waste. Such information is a critical component to be able to efficiently plan for the collection and routing of trucks when collecting recyclable plastics. The development of new strategies for the recycling of plastic waste and development of new industry can address the import and export potential of the country to achieve self-sustainability as well as contribute to reduction in plastic pollution and amount of waste landfilled. These plastics can thereafter be used effectively for recycling and for the making of 3D printing filaments which fall under the SDGs 9 (Industry, Innovation and Infrastructure) and 12 (Responsible consumption and production).

This study aims to investigate the determinants of household behavioural intention towards household reducing, reusing and recycling behaviour of food waste management.

The data were collected from 670 households in Malaysia and analysed by using the partial least square method.

The findings reveal that motivation to participate, ability to participate and perceived benefits are the crucial factors that significantly influence households’ attitudes. Household attitude has a significant impact on household behavioural intention, whilst social influence and perceived behavioural control are not associated with it. Government support is positively related to perceived behavioural control. The result also indicates that household behavioural intention has a significant impact on household reducing, reusing and recycling behaviour.

The participants of this study were involved in home planning and food preparation in Malaysia. The individuals in charge of the household might have more awareness of food planning and waste control. Thus, it is recommended to adopt findings from other countries and learn from the experience of the local and international communities.

The households’ behavioural intentions can lead to the reducing, reusing and recycling behaviour of food waste management. The government policy mechanisms and households’ awareness can work effectively against food waste reduction because evaluations of the food waste programme were found to be scarce.

Food insecurity is one of the major social problems. Many people are not aware of the food waste impacts and consequences; thus, motivation, knowledge and information should be provided to the consumer through forums and campaigns.

The findings contribute to new insights of household behavioural intention towards food waste reduction management by assessing the determinants of household attitude and government support for food waste reduction management programmes towards household reducing, reusing and recycling behaviours.

India generates around two million tonnes of e-waste every year, and it is increasing at a very high rate of 30%. However, due to inefficient handling of infrastructure and limited number of collection centres along with the absence of proper incentive structure for producer and recyclers, 95% of e-waste reaches to unorganized sector for disposal. Consumers are not aware of the need of proper e-waste disposal and in absence of proper motivation and they are not inclined towards recycling process. Therefore, this paper aims to identify the best practices of e-waste take adopted all over the world to implement effective policy interventions for e-waste management in India and other emerging economies.

This paper has recommended preventive as well as curative policy interventions on the basis of best e-waste management practices of Germany, Italy and Japan; life cycle assessment of e-waste; and SWOT analysis of Indian electronic product industry.

Preventive measures include a deposit refund scheme wherein a consumer will be responsible for depositing a refundable fees during the purchase of the product. The amount should be arrived at keeping in mind cost involved in handling e-waste and ensure some motivation for the consumers to give back used product. To ensure proper tracking of the product, Radio frequency identification (RFID) tags can be used which will be activated at the time of sale of product and remain so until product reaches some designated recycling space or recycler and consumer is returned back his deposit fee. Subsidy to the producers and recyclers can also be provided by the government to further incentivize the whole process. An example of mobile phones has been used to understand the proposed deposit fees and associated cost structure. Curative measures to reduce the generation of e-waste in long run for managing the discussed issue have also been proposed.

This study is an initiative for proposing and implementing best e-waste take back techniques in a developing economy like India by acquiring learnings from best/advanced economies in terms of e-waste take back.

A prime objective of the Swachh Bharat Abhiyan (SBA; Clean India Mission) is to motivate people to segregate their household waste. The purpose of this study is to assess the ground reality of waste management behaviour of Delhi residents with the help of a modified Value–Belief–Norm (VBN) model. Past researches point the need to include cost as a variable in the VBN model. This study fulfils this need and tests cost as one of the variables on the gathered data.

The research data were gathered by interacting with the people and the civic staff in the jurisdiction of the three Delhi municipalities through a stratified sampling technique (N = 250). The structural equation modelling was used to analyse the collected data.

The modified VBN model explains the waste management behaviour, but the variables do not follow the exact causal chain. Values, awareness of consequences, ascription of responsibility and personal norms all explain the resident's waste management behaviour. However, cost limits the resident's waste management behaviour.

The study could only achieve a moderate model fit; its sample size was small; and data were collected through self-reported questionnaire.

Three main practical implications of the study are: (1) While designing waste management solutions, due importance must be given to the cost to be borne by people for adopting these solutions. (2) Design such interventions that target residents' values to convince them to make the desired behavioural change. (3) People need be educated about the ways to sort waste and made aware of the importance of waste segregation in eradicating the urban waste mess.

The paper is an original contribution to testing a modified VBN model in predicting waste management behaviour. The modified model includes cost as a variable missing in the previous research. This research is useful in the backdrop of the SBA and provides suggestions for policymakers and pro-environment researchers.

The purpose of this study was to investigate amount of food waste and the number of food packages used in Finnish households with university students. The aim of the paper is to answer the following research questions: How much avoidable food waste is generated in the participating various sized households? How much unavoidable food waste is generated in the participating various sized households? How many food packages are classified as deposit, municipal waste or recycled in the participating various sized households?

The data was collected among the students in Seinäjoki University of Applied Sciences. A total of results from 432 households with 890 persons are presented. The participating households weighed their unavoidable and avoidable food waste and calculated the food packages during one week. The results were analysed in Excel and the statistical significance assessed using a t-test.

The average avoidable and unavoidable food wastages were 498 g/week/person, i.e. 25.9 kg/year/person and 543 g/week/person, i.e. 28.3 kg/year/person, respectively. Single-person households generate more avoidable and unavoidable food waste as well as packages per person than other sized households. The results show that there is no correlation between the amount of avoidable food waste/person, unavoidable food waste/person or packages/person.

This kind of research has sparsely been reported. The food and package wastage definitions vary, and thus it is difficult to compare these results with other reported results.

Waste generated from electrical and electronic equipment, collectively known as E-waste, remains a persistent environmental, economic and social problem. Sustainable E-waste management (EWM) has numerous benefits, such as preventing electronic waste from entering landfills, reducing the need for virgin materials by recovering valuable materials from recycling and lowering greenhouse gas emissions. Circular economy (CE) practices are considered the initial steps toward sustainable EWM, but some hurdles have been reported in the adoption of these practices. Therefore, the current study aims to identify the common CE practices, sustainability of the EWM process and the challenges in EWM, and to develop a conceptual framework for effective EWM.

Very few studies have proposed frameworks that acknowledge the challenges and CE practices of EWM. To fill this gap, a systematic literature review (SLR) was performed, and 169 research articles were explored.

A total of seven challenges in the adoption of effective EWM were identified: rules and policy, infrastructure, consumer behaviour, informal sectors, community culture, technology and economy. Eight common CE practices were also found for effective EWM: reuse, recycle, remanufacturing, refurbishment, repair, reduce, recover and repurpose.

A conceptual framework guiding sustainable EWM was proposed, which includes solutions for the identified challenges, and CE practices with sustainable benefits.

Currently, Mauritius is adopting landfilling as the main waste management method, which makes the waste sector the second biggest emitter of greenhouse gas (GHG) in the country. This presents a challenge for the island to attain its commitments to reduce its GHG emissions to 30% by 2030 to cater for SDG 13 (Climate Action). Moreover, issues like eyesores caused by littering and overflowing of bins and low recycling rates due to low levels of waste segregation are adding to the obstacles for Mauritius to attain other SDGs like SDG 11 (Make Cities & Human Settlements Inclusive, Safe, Resilient & Sustainable) and SDG 12 (Guarantee Sustainable Consumption & Production Patterns). Therefore, together with an optimisation of waste collection, transportation and sorting processes, it is important to establish a solid waste characterisation to determine more sustainable waste management options for Mauritius to divert waste from the landfill. However, traditional waste characterisation is time consuming and costly. Thus, this chapter consists of looking at the feasibility of adopting machine learning to forecast the solid waste characteristics and to improve the solid waste management processes as per the concept of smart waste management for the island of Mauritius in line with reducing the current challenges being faced to attain SDGs 11, 12 and 13.

Smart cities in India are going to be a reality very soon by turning challenges into opportunities for the society. However, due to rapid increase in population burden, fast urbanization and growing demand of advanced services in the smart cities, the quantity of per capita municipal solid waste (MSW) has escalated. Moreover, the COVID-19 pandemic has further challenged the municipal solid waste management (MSWM) system with the increasing amount of infectious wastes coming from households (HHs), quarantine centers, healthcare facilities, vaccination centers, etc. Therefore, the present study attempts to explore and analyze the various dimensions of sustainable MSWM system in the smart cities.

The study identifies 13 factors of sustainable MSWM system from the literature, field surveys and stakeholders' opinions. Thereafter, stakeholders' opinions are collected and analyzed using total interpretive structural modeling (TISM) approach to explore the interrelationships among the factors of sustainable MSWM system. These relationships are further validated through the empirical investigation of the real-life case study of Rourkela Municipal Corporation (RMC), Odisha, India.

The TISM approach places all 13 factors into six levels in the hierarchical digraph depending upon the inputs received from the various stakeholders on their interrelationships. Study also validates the proposed TISM model by collecting the data of RMC, Odisha, on the development of MSWM system over the period of 2015–2021.

The study also highlights various implications for the other developing cities and stakeholders to set up the roadmap for developing the sustainable MSWM system. Study defines “IT platform” and “awareness among citizens” as the base of the sustainable MSWM system in any smart city.

The present study is the first of its kind to explore the interrelationships among the factors of sustainable MSWM system by using TISM approach. Moreover, the proposed TISM framework is further validated through the empirical journey of one of the smart cities in India.