Secondary Resources in the Bio-Based Economy: A Computer Assisted Survey of Value Pathways in Academic Literature

Davis, Chris; Aid, Graham; Zhu, Ben

doi:10.1007/s12649-017-9975-0

Cited by 28 publications

(38 citation statements)

References 23 publications

(27 reference statements)

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“…x (Yeo, Pepin, and Yang 2017) x Total 13 11 8 7 3 2 1 1 approaches assessing potential value pathways for secondary materials (Davis, Aid, and Zhu 2017;Jose and Ramakrishna 2018) or discovering potential industrial symbioses (Song et al 2017), (ii) to develop open-source tools, procedures, open data, and services for promoting reuse (Franquesa, Navarro, and Bustamante 2016;Franquesa and Navarro 2018) or cloud service platforms for data collection and analytics (Lindström et al 2018), (iii) to assess innovative business models through integrative frameworks (Chiappetta Jabbour et al 2017) or for particular types of companies (Soroka et al 2017), and (iv) to gather or manage data on the lifecycle of products (J. Li et al 2015) or implementing smart manufacturing practices (Kusiak 2018) (see Table 5).…”

Section: Big Data and Analyticsmentioning

confidence: 99%

“…x (Unruh 2018) x (van Wijk and van Wijk 2015) x (Voet et al 2018) x (Woern et al 2018) x (Zhong and Pearce 2018) x Total 9 6 5 4 3 2 1 x (Davis, Aid, and Zhu 2017) x (Franquesa, Navarro, and Bustamante 2016) x (Franquesa and Navarro 2018) x (Ge and Jackson 2014) x (Jose and Ramakrishna 2018) x (Kache and Seuring 2017) x (Kusiak 2018) x (J. Li et al 2015) x (Lin 2018) x (Lindström et al 2018) x (Marconi et al 2018) x (Salminen, Ruohomaa, and Kantola 2017) x (Seele and Lock 2017) x (Song et al 2017) x (Soroka et al 2017) x (Tseng et al 2018) x Total 4 3 3 2 2 1 1 1 1 reduction strategies through remanufacturing (Ge and Jackson 2014), and assessing challenges and opportunities in SCM practices (Kache and Seuring 2017).…”

Section: Big Data and Analyticsmentioning

confidence: 99%

“…Regarding the IoT, the intent is to adopt it to enable new waste management strategies in smart cities (Esmaeilian et al 2018), creating collaborative networks (Romero and Molina 2012;Romero and Noran 2017) or improving the circularity level of metallurgical processes (Reuter, Matusewicz, and van Schaik 2015). BDA, instead, was seen as a good solution for either developing automated approaches assessing potential value pathways for secondary materials (Davis, Aid, and Zhu 2017;Jose and Ramakrishna 2018) or discovering potential industrial symbioses (Song et al 2017). AM can be useful in terms of exploitation of biomaterials (van Wijk and van Wijk 2015;Voet et al 2018).…”

Section: Resource Efficiencymentioning

confidence: 99%

See 2 more Smart Citations

Assessing relations between Circular Economy and Industry 4.0: a systematic literature review

Rosa

Sassanelli

Urbinati

et al. 2019

International Journal of Production Research

456

280

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Industry 4.0 (I4.0) and Circular Economy (CE) are undoubtedly two of the most debated topics of the last decades. Progressively, they gained the interest of policymakers, practitioners and scholars all over the world. Even if they have been usually described as two independent research fields, there are some examples presenting overlaps between these topics, represented by hybrid categories like Circular I4.0 and Digital CE. Starting from these two perspectives, an innovative framework both highlighting the links between I4.0 and CE and unveiling future research fields has been developed. Basing on one of the two perspectives, results show as it is possible to enhance a set of different relations. Depending on a dedicated area of either CE or I4.0 it is possible to see the prevalence of some I4.0 technology than others. However, the influence of I4.0 technologies on CE is always verified.

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Section: Big Data and Analyticsmentioning

confidence: 99%

Section: Big Data and Analyticsmentioning

confidence: 99%

Section: Resource Efficiencymentioning

confidence: 99%

See 1 more Smart Citation

Assessing relations between Circular Economy and Industry 4.0: a systematic literature review

Rosa

Sassanelli

Urbinati

et al. 2019

International Journal of Production Research

456

280

View full text Add to dashboard Cite

show abstract

“…Several examples of platforms are collecting information that could be used to inform the model. Examples vary from the life cycle analyses of one product (Davis et al, 2009;Wu et al, 2017), to the functioning of an Eco-industrial park (Jacobsen, 2006), to open data approaches to build an industrial symbiosis data repository (Davis et al, 2017;ISDATA, 2018). Such datasets, combined with the integration within a GIS (illustrated here by the EPRTR database integration) with interactive capabilities (e.g.…”

Section: Discussionmentioning

confidence: 99%

A spatial agent based model for simulating and optimizing networked eco-industrial systems

Raimbault¹,

Broere

Somveille

et al. 2020

Resources, Conservation and Recycling

Self Cite

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Industrial symbiosis involves creating integrated cycles of by-products and waste between networks of industrial actors in order to maximize economic value, while at the same time minimizing environmental strain. In such a network, the global environmental strain is no longer equal to the sum of the environmental strain of the individual actors, but it is dependent on how well the network performs as a whole. The development of methods to understand, manage or optimize such networks remains an open issue. In this paper we put forward a simulation model of by-product flow between industrial actors. The goal is to introduce a method for modelling symbiotic exchanges from a macro perspective. The model takes into account the effect of two main mechanisms on a multi-objective optimization of symbiotic processes. First it allows us to study the effect of geographical properties of the economic system, said differently, where actors are divided in space. Second, it allows us to study the effect of clustering complementary actors together as a function of distance, by means of a spatial correlation between the actors by-products. Our simulations unveil patterns that are relevant for macro-level policy. First, our results show that the geographical properties are an important factor for the macro performance of symbiotic processes. Second, spatial correlations, which can be interpreted as planned clusters such as Eco-industrial parks, can lead to a very effective macro performance, but only if these are strictly implemented. Finally, we provide a proof of concept by comparing the model to real world data from the European Pollutant Release and Transfer Register database using georeferencing of the companies in the dataset. This work opens up research opportunities in interactive data-driven models and platforms to support real-world implementation of industrial symbiosis.

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“…While the majority of applications focus on data exploration and analysis, few focus on scientific communication in peer‐reviewed research. One of the few examples is given by Davis and colleagues () while exploring automated data analysis approaches to explore potential waste pathways, and this work is complemented by IV tools based on topic modeling and co‐occurrence analysis. These tools are available on a separate website and offer readers the opportunity to interact with the complete set of results.…”

Section: Current and Potential Interactive Visualizations To Illustramentioning

confidence: 99%

Interactive Visualization and Industrial Ecology: Applications, Challenges, and Opportunities

Vivanco

Hoekman

Fishman

et al. 2018

J of Industrial Ecology

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Summary The emergence of increasingly complex data in industrial ecology (IE) has caused scholarly interest in interactive visualization (IV). IV allows users to interact with data, aiding in processing and interpreting complex datasets, processes, and simulations. Consequently, IV can help IE practitioners communicate the complexities of their methods and results, shed light on the underlying research assumptions, and enable more transparent monitoring of data quality and error. This can significantly increase the reach and impact of research, promote transparency, reproducibility, and open science, as well as improve the clarity and presentation of IE research. A review of current IV applications reveals that, while data exploration has received some attention among IE practitioners, IV applications in scientific communication are clearly lacking. With the help of a working example, we explore the value of IV, discuss its operationalization, and highlight challenges that the IE community must face during IV uptake. Such challenges include technical and knowledge limitations, limits on user interaction, and implementation strategies. With these challenges in mind, we outline key aspects needed to lift the IE field to the forefront of scientific communication in the coming years. Among these, we draft the basic principles of a “Hub for Interactive Visualization in Industrial Ecology” (HIVE), a point of encounter where IE practitioners could find an array of data visualization tools that are geared toward IE datasets. IV is here to stay, and its inceptive stage presents many opportunities to IE practitioners to shape its operationalization and benefit from early adoption.

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Secondary Resources in the Bio-Based Economy: A Computer Assisted Survey of Value Pathways in Academic Literature

Cited by 28 publications

References 23 publications

Assessing relations between Circular Economy and Industry 4.0: a systematic literature review

Assessing relations between Circular Economy and Industry 4.0: a systematic literature review

A spatial agent based model for simulating and optimizing networked eco-industrial systems

Interactive Visualization and Industrial Ecology: Applications, Challenges, and Opportunities

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