Circular economy for phosphorus supply chain and its impact on social sustainable development goals

Wali, Mohammad El; Golroudbary, Saeed Rahimpour; Krasławski, Andrzej

doi:10.1016/j.scitotenv.2021.146060

Cited by 73 publications

(39 citation statements)

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“…We used the principles of System Dynamics to depict, explicate and comprehend the interplay of these digital technologies and supply chain operations for sustainability and data monetisation (Meadows, 1980 ). System Dynamics has been proven successful in capturing the sustainability impact of food supply chains involving commodities such as phosphorus (El Wali et al, 2021 ), milk (Mangla et al, 2021 ) and wine (Taghikhah et al, 2021 ).…”

Section: Methodsmentioning

confidence: 99%

Artificial intelligence and blockchain implementation in supply chains: a pathway to sustainability and data monetisation?

et al. 2022

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Digitalisation is expected to transform end-to-end supply chain operations by leveraging the technical capabilities of advanced technology applications. Notwithstanding the operations-wise merits associated with the implementation of digital technologies, individually, their combined effect has been overlooked owing to limited real-world evidence. In this regard, this research explores the joint implementation of Artificial Intelligence (AI) and Blockchain Technology (BCT) in supply chains for extending operations performance boundaries and fostering sustainable development and data monetisation. Specifically, this study empirically studied the tuna fish supply chain in Thailand to identify respective end-to-end operations, observe material and data-handling processes, and envision the implementation of AI and BCT. Therefore, we first mapped the business processes and the system-level interactions to understand the governing material, data, and information flows that could be facilitated through the combined implementation of AI and BCT in the respective supply chain. The mapping results illustrate the central role of AI and BCT in digital supply chains’ management, while the associated sustainability and data monetisation impact depends on the parameters and objectives set by the involved system stakeholders. Afterwards, we proposed a unified framework that captures the key data elements that need to be digitally handled in AI and BCT enabled food supply chains for driving value delivery. Overall, the empirically-driven modelling approach is anticipated to support academics and practitioners’ decision-making in studying and introducing digital interventions toward sustainability and data monetisation.

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Section: Methodsmentioning

confidence: 99%

Artificial intelligence and blockchain implementation in supply chains: a pathway to sustainability and data monetisation?

et al. 2022

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“…In addition to poverty indicators, other SDG indicators have been considered in poverty scenario analysis models (Tables 3, 4). Variables for SDG 2 (zero hunger) (El Wali et al, 2021) and SDG 13 (climate change) (Marcinko et al, 2021) were most often used together with poverty. Only iSDG (MI, 2021) and IFs (Hughes, 2019) developed variables for all SDGs and can be used to analyze poverty and SDG 3 (good health and well-being), SDG 9 (industry, innovation, infrastructure), SDG 11 (sustainable cities and communities), or SDG 16 (peace, justice, strong institutions) simultaneously.…”

Section: Overview Of Model Informationmentioning

confidence: 99%

“…Except for some indicators (e.g., maternal mortality for SDG 3, occupational accident rate for SDG 8) that were developed to be completely consistent with SDGs agenda (United Nations, 2021), many models used proxy indicators to measure SDGs (Table 4). For instance, crop yield could be used to measure SDG 2 (El Wali et al, 2021) while agricultural water withdrawal could be used to measure SDG 6 (Byers et al, 2018).…”

Section: Overview Of Model Informationmentioning

confidence: 99%

A review of model-based scenario analysis of poverty for informing sustainability

Liu¹,

Guo²,

Gao³

et al. 2021

Preprint

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Ending poverty in all its forms everywhere is the first goal being targeted by the United Nations 2030 Agenda for Sustainable Development. Poverty eradication is a long-term process that faces the challenges of many uncertainties and complex interactions with other Sustainable Development Goals (SDGs). In order to better understand poverty and contribute to addressing poverty in a sustainable manner, this paper aims to conduct a systematic review of model-based analysis for poverty scenario in the context of SDGs. We first review 144 studies from the perspectives of bibliometric information (i.e., publication types, research topics for poverty, research objects, research scales and geographic locations) and models information for poverty scenario analysis (i.e., model types, purposes, states, temporal and spatial range, sectors considered, poverty and other SDGs indicators). Second, we discuss the pros and cons of different types of models and identify seven representative models. We also discuss the synergies and trade-offs between poverty and other SDGs. Finally, we identify four potential research gaps in model-based poverty scenario analysis and provide suggestions for future research. The review shows that poverty scenario analysis was carried out mainly from a single perspective, such as economic, ecological, and agricultural. Few studies used effective models to analyze poverty under an integrated interactions analysis of multiple sectors. Comprehensive multi-sector models are needed for global and regional poverty scenario analysis over the medium- or long-term to enhance the ability of analyzing the combined effects, synergies, and trade-offs between poverty and a variety of other SDGs.

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“…The adoption of a CE favours two aspects specifically. First, a production system under the CE approach benefits business performance and clean production (Khan et al 2021a ); secondly, the firm improves its efficiency, thereby improving its integration into the sector's supply chain to which it belongs (El Wali et al 2021 ). This situation also generates externalities for all agents in the supply chain since the improvement of the supply chain generates benefits over other firms that comprise it (Khan and Qianli 2017 ).…”

Section: Introductionmentioning

confidence: 99%

The future of industry 4.0 and the circular economy in Chinese supply chain: In the Era of post-COVID-19 pandemic

Wang

Ponce

et al. 2022

Oper Manag Res

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The demand for new productive factors is increasingly required, exacerbated in a scenario in which a linear economy prevails. The circular economy (CE) adoption is a proposal to guarantee environmental sustainability and redirect an obsolete process such as the linear economy. Thus, one of the main factors that allow achieving sustainability is Industry 4.0 (I4.0). In addition, the research aims to evaluate the role of I4.0 during the COVID-19 pandemic in China. The literature review process defines ten future projections with potential for the CE's adoption. The two-round Delphi approach was developed with 54 CE experts to evaluate the projections. In both rounds, the probability of occurrence up to 2030, its impact on the CE and its desirability were evaluated. Likewise, the qualitative criteria of the experts were coded to evaluate the projections. From the ten projections, four are those with the highest probability of occurrence (EP > 70%), with high impact (I > 3.5) and desirability of occurrence (I > 3.5). Expert evaluations make it possible to identify that Industry 4.0 and the digital skills of workers, their financing, and the efficiency of Government policies have a high probability of occurrence in the adoption of the CE in 2030. This research responds to the special call of papers providing evidence favouring the implementation of I4.0 in the CE from a holistic approach to draw a roadmap towards adopting the CE practices.

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Circular economy for phosphorus supply chain and its impact on social sustainable development goals

Cited by 73 publications

References 50 publications

Artificial intelligence and blockchain implementation in supply chains: a pathway to sustainability and data monetisation?

Artificial intelligence and blockchain implementation in supply chains: a pathway to sustainability and data monetisation?

A review of model-based scenario analysis of poverty for informing sustainability

The future of industry 4.0 and the circular economy in Chinese supply chain: In the Era of post-COVID-19 pandemic

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