An integrated method of life-cycle assessment and system dynamics for waste mobile phone management and recycling in China

Yao, Liming; Liu, Tingting; Chen, Xudong; Moudi, Mahdi; Ni, Jingneng

doi:10.1016/j.jclepro.2018.03.195

Cited by 74 publications

(31 citation statements)

References 39 publications

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“…Pivotal questionsthat should have been addressed in this bookcould have revolved around disposal, recycle, or repurposing strategies that need to be applied to manage the 42,000 tons of waste predicted by 2025 in countries such as China (Tan et al 2017). China is key in addressing waste mobile phone (WMPs) due to it being the largest producer of mobile phones since 2004 as well as being the dumping ground for 70% of waste mobile phones (Yao et al 2018). It is important to address mobile phone waste in this book due to the danger of highly toxic substances as well as opportunities to recycle retrievable elements such as silver, gold, and copper (Yin, Gao and Xu 2014).…”

Section: Resultsmentioning

confidence: 99%

Banerjee, Dholakia and Dholakia, M-Powering Marketing in a Mobile World (2017)

Zambrano¹

2018

MGDR

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Section: Resultsmentioning

confidence: 99%

Banerjee, Dholakia and Dholakia, M-Powering Marketing in a Mobile World (2017)

Zambrano¹

2018

MGDR

View full text Add to dashboard Cite

“…Bringing LCA and SD together is a relatively recent idea as of the development of this article, with earliest attempts dating back to 2011. In the scientific studies published so far, systems thinking was used to pursue the same results generated by either LCA (Onat et al 2016;Halog and Manik 2011;Yao et al 2018;Stasinopoulos et al 2011) or Material Flow Analysis (MFA) (Sprecher et al 2015).…”

Section: Methodsmentioning

confidence: 99%

“…In some of their attempts, previous academics ran both methodologies in parallel and used them as interchangeable sources of endogenous data to each other (e.g. Yao et al 2018;Stasinopoulos et al 2011). In other attempts, series of results originated in MFA or LCA were then used in a SD model, simulating a circular environment for the retrieval of dynamic behaviors (e.g.…”

Section: Methodsmentioning

confidence: 99%

“…Unlike previous studies, in which LCA and SD models ran in parallel and exchanged intermediary outputs or data exogenous to each other (Yao et al 2018;Stasinopoulos et al 2011), the present article brought the entire LCA methodology, in its attributional form, into the SD modelling environment. By doing so, the authors expected to maximize the amount of endogenous dynamics at play.…”

Section: Introductionmentioning

confidence: 99%

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Integrating life cycle analysis into system dynamics: the case of steel in Europe

2019

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Background: Steel is an important material in modern economies but responsible, nevertheless, for substantial environmental impacts throughout its supply chain. During the last couple of decades, this industry has addressed its impacts more incisively with the support of modelling and assessment tools. Methodology: This article used the European steel industry as a case study to explore the potential benefits of integrating life cycle analysis (LCA) into system dynamics (SD) under the scopes of circular economy and industrial ecology. The goal was to explore if this integration could not only reproduce results generated separately by LCA and SD, but also to provide additional support for decision-and policy-making on the biophysical aspects of long-term materials sourcing. Unlike previous studies focused on methodological exchanges between the two, the entire LCA methodology was brought into the SD modelling environment, following ILCD and ISO guidelines and standards. Results: The results indicated that integrating LCA into SD is feasible and capable of contributing to both in different levels, supporting discussions on raw material scarcity and self-sufficiency, and resource ownership retention. Conclusion: Given continued effort is put into supporting the use of environmental impact indicators, this approach has potential to interest policy-makers and industrial decision-makers alike.

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“…Policies can be tested through simulation (Morecroft, 2015). Yao et al (2018) The simulation is composed of 2 stocks, 2 flows and 10 variables. The key variables as mentioned before are "Business Model Design", "Novelty", "Efficiency", and "Performance".…”

Section: Policy Formulation and Validationmentioning

confidence: 99%

Testing successful Business Model using System Dynamics

Ganzarain

Ruiz

Igartua

2019

Int. J. Prod. Manag. Eng.

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In our increasingly globalised economy, managing continuous change whilst remaining competitive and dynamic has become a central issue for firms in the industrial sector. One of the elements for obtaining this competitiveness is the value creation model of the firm. The most important challenges in firms are characterised by dynamic complexity which makes it difficult to understand factors in their context. Consequently management and decision making is hindered (Antunes et al., 2011). Business models are characterised by complexity and dynamism. Performance of the firm is a complex topic determined by the large amount of variables that can be involved in the system, and the different effects that influence the system in the short and long term. Due to this complexity a systemic view is required, that is, an holistic view of the whole system. Such a systemic view enables managers to make decisions based on evidence rather than intuition and personal experiences, as they understand how the whole system works. Thus, the main aim of this research is to use an empirical tool such as System Dynamics (SD), to support and sustain firms in the identification of new constructs related to their Business Model (BM).

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An integrated method of life-cycle assessment and system dynamics for waste mobile phone management and recycling in China

Cited by 74 publications

References 39 publications

Banerjee, Dholakia and Dholakia, M-Powering Marketing in a Mobile World (2017)

Banerjee, Dholakia and Dholakia, M-Powering Marketing in a Mobile World (2017)

Integrating life cycle analysis into system dynamics: the case of steel in Europe

Testing successful Business Model using System Dynamics

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