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Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-30027
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dc.contributor.authorBarth, Linard-
dc.contributor.authorSchweiger, Lukas-
dc.contributor.authorBenedech, Rodolfo Andres-
dc.contributor.authorEhrat, Matthias-
dc.date.accessioned2024-02-29T13:23:18Z-
dc.date.available2024-02-29T13:23:18Z-
dc.date.issued2023-10-28-
dc.identifier.issn2772-6622de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/30027-
dc.description.abstractThe importance of waste management, including collection, separation, recovery, and recycling, increases with the growing amount of waste. Technological innovations such as smart connected products, the Internet of Things, and digital twins are driving the development of smart management systems. Investments in necessary product-service systems are justified by cost savings and improved service quality, especially in affluent societies like Switzerland. However, there is a trade-off between cost savings and service quality that raises the question of optimal balance. Using a Swiss municipality as an example, this paper models the trade-off between cost savings and service quality using waste bin sensor modules. Simulation results demonstrate the impact of cost savings on service quality reduction and that substantial cost savings are possible without a service quality compromise. We also introduce a digital process twin as a decision support system that is able to leverage a growing database. These results contribute to research, firstly through the field study with 98 waste bins equipped with fill level sensor modules, secondly through the model-based analysis of the trade-off between cost savings and service quality, and thirdly by conceptualizing a digital twin-based decision support system. The results further contribute to practice, firstly by providing benchmarks for implementing similar systems in other municipalities without having to create their own simulations, secondly by presenting an innovative key performance indicator to measure service quality, and thirdly with a model that can be used for simulations to determine the individual optimum between costs and service quality.de_CH
dc.language.isoende_CH
dc.publisherElsevierde_CH
dc.relation.ispartofDecision Analytics Journalde_CH
dc.rightshttp://creativecommons.org/licenses/by-nc-nd/4.0/de_CH
dc.subjectWaste managementde_CH
dc.subjectSmart cityde_CH
dc.subjectInternet of Thingsde_CH
dc.subjectDigital process twinde_CH
dc.subjectDigital twinde_CH
dc.subject.ddc363: Umwelt- und Sicherheitsproblemede_CH
dc.titleFrom data to value in smart waste management : optimizing solid waste collection with a digital twin-based decision support systemde_CH
dc.typeBeitrag in wissenschaftlicher Zeitschriftde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Engineeringde_CH
zhaw.departementSchool of Management and Lawde_CH
zhaw.organisationalunitInstitut für Datenanalyse und Prozessdesign (IDP)de_CH
zhaw.organisationalunitInstitut für Marketing Management (IMM)de_CH
dc.identifier.doi10.1016/j.dajour.2023.100347de_CH
dc.identifier.doi10.21256/zhaw-30027-
zhaw.funding.euNode_CH
zhaw.issue100347de_CH
zhaw.originated.zhawYesde_CH
zhaw.publication.statuspublishedVersionde_CH
zhaw.volume9de_CH
zhaw.publication.reviewPeer review (Publikation)de_CH
zhaw.author.additionalNode_CH
zhaw.display.portraitYesde_CH
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Barth, L., Schweiger, L., Benedech, R. A., & Ehrat, M. (2023). From data to value in smart waste management : optimizing solid waste collection with a digital twin-based decision support system. Decision Analytics Journal, 9(100347). https://doi.org/10.1016/j.dajour.2023.100347
Barth, L. et al. (2023) ‘From data to value in smart waste management : optimizing solid waste collection with a digital twin-based decision support system’, Decision Analytics Journal, 9(100347). Available at: https://doi.org/10.1016/j.dajour.2023.100347.
L. Barth, L. Schweiger, R. A. Benedech, and M. Ehrat, “From data to value in smart waste management : optimizing solid waste collection with a digital twin-based decision support system,” Decision Analytics Journal, vol. 9, no. 100347, Oct. 2023, doi: 10.1016/j.dajour.2023.100347.
BARTH, Linard, Lukas SCHWEIGER, Rodolfo Andres BENEDECH und Matthias EHRAT, 2023. From data to value in smart waste management : optimizing solid waste collection with a digital twin-based decision support system. Decision Analytics Journal. 28 Oktober 2023. Bd. 9, Nr. 100347. DOI 10.1016/j.dajour.2023.100347
Barth, Linard, Lukas Schweiger, Rodolfo Andres Benedech, and Matthias Ehrat. 2023. “From Data to Value in Smart Waste Management : Optimizing Solid Waste Collection with a Digital Twin-Based Decision Support System.” Decision Analytics Journal 9 (100347). https://doi.org/10.1016/j.dajour.2023.100347.
Barth, Linard, et al. “From Data to Value in Smart Waste Management : Optimizing Solid Waste Collection with a Digital Twin-Based Decision Support System.” Decision Analytics Journal, vol. 9, no. 100347, Oct. 2023, https://doi.org/10.1016/j.dajour.2023.100347.


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