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Data-driven analytical framework for waste dumping behaviour analysis to facilitate policy regulations

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26210%2F20%3APU136012" target="_blank" >RIV/00216305:26210/20:PU136012 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.sciencedirect.com/science/article/pii/S0956053X19307950?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0956053X19307950?via%3Dihub</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.wasman.2019.12.041" target="_blank" >10.1016/j.wasman.2019.12.041</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Data-driven analytical framework for waste dumping behaviour analysis to facilitate policy regulations

  • Original language description

    Waste sorting at the source is a vital strategy of waste management and to improve urban sustainability. If the strategy is implemented by relying solely on publicity and civic awareness, the impact is less significant. Proactive measures, such as policy regulations, supervisory guidance, and stimulating incentives, play essential roles for better management. The unknown waste-dumping behaviour of residents is a great challenge for decision-makers to allocate resources for waste-collection operations and to refine regulations. Traditional behaviour analysis methods such as questionnaire surveys and simulation methods have limitations considering the population size and the complexity of individual behaviour. This study aims to design a data-driven analytical framework to analyse household waste-dumping behaviour and facilitate policy regulations by using the Internet of Things (IoT) and data mining technologies. The analytical framework is further developed into a four-step management cycle. A case study in Shanghai is employed to demonstrate the effectiveness of the analytical framework and management cycle. The results of behaviour analyses reveal that (1) waste-dumping frequency is high in the evening but negligible in the early afternoon; (2) compared to working days, peak-value time at weekends occurs later in the morning and earlier in the evening; (3) residents require longer waste-dumping time windows than those empirically recommended by administrators. Managerial insights and decision support based on these research results have been presented for decision-makers to guide operations management and facilitate policy regulations. © 2019

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    20701 - Environmental and geological engineering, geotechnics

Result continuities

  • Project

    <a href="/en/project/EF15_003%2F0000456" target="_blank" >EF15_003/0000456: Sustainable Process Integration Laboratory (SPIL)</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2020

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Waste Management

  • ISSN

    0956-053X

  • e-ISSN

  • Volume of the periodical

    neuveden

  • Issue of the periodical within the volume

    103

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    11

  • Pages from-to

    285-295

  • UT code for WoS article

    000547367900030

  • EID of the result in the Scopus database

    2-s2.0-85077333545