Fusions of industrialisation and digitalisation (FID) in the digital economy: Industrial system digitalisation, digital technology industrialisation, and beyond

Shi, Yongjiang; Gao, Yibo; Luo, Yining; Hu, Jialun

doi:10.1016/j.jdec.2022.08.005

Cited by 28 publications

(18 citation statements)

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“…The analysis provided a brief profile of each article in terms of its aims, findings, methodologies, and underpinning theories. Scholars have examined the use of digitalization and artificial knowledge in SCM in various industries, such as food and agriculture, ICT, fashion, logistics, marine, textile, tourism, healthcare, fishing, automotive, pharmaceutical, construction, minerals, mining, and manufacturing (Bechtsis et al, 2017;Cherviakova and Cherviakova, 2018;Garcia-Muiña et al, 2018;Pongpanit and Sornsaruht, 2019;Alharthi et al, 2020;Calvão and Archer, 2021;Chen et al, 2022;Griffin et al, 2022;Joshi and Sharma, 2022;Mahroof et al, 2022;Mishra et al, 2022;Oguntegbe et al, 2022;Shamout et al, 2022;Sharma et al, 2022;Shi et al, 2022), and across multiple levels including SMEs, cities, individuals, the government, and the world (Babenko et al, 2020;Bellingan et al, 2020;Wong et al, 2020;Bagloee et al, 2021;Bisogni et al, 2021;Hjaltad ottir and Hild, 2021;Potocka-Sionek, 2021;Nasir et al, 2022;Nudurupati et al, 2022;Reza-Gharehbagh et al, 2022a).…”

Section: Digitalization and Artificial Knowledgementioning

confidence: 99%

Digitalization and artificial knowledge for accountability in SCM: a systematic literature review

Vaio

Latif

Gunarathne

et al. 2023

JEIM

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PurposeIn this study, the authors examine artificial knowledge as a fundamental stream of knowledge management for sustainable and resilient business models in supply chain management (SCM). The study aims to provide a comprehensive overview of artificial knowledge and digitalization as key enablers of the improvement of SCM accountability and sustainable performance towards the UN 2030 Agenda.Design/methodology/approachUsing the SCOPUS database and Google Scholar, the authors analyzed 135 English-language publications from 1990 to 2022 to chart the pattern of knowledge production and dissemination in the literature. The data were collected, reviewed and peer-reviewed before conducting bibliometric analysis and a systematic literature review to support future research agenda.FindingsThe results highlight that artificial knowledge and digitalization are linked to the UN 2030 Agenda. The analysis further identifies the main issues in achieving sustainable and resilient SCM business models. Based on the results, the authors develop a conceptual framework for artificial knowledge and digitalization in SCM to increase accountability and sustainable performance, especially in times of sudden crises when business resilience is imperative.Research limitations/implicationsThe study results add to the extant literature by examining artificial knowledge and digitalization from the resilience theory perspective. The authors suggest that different strategic perspectives significantly promote resilience for SCM digitization and sustainable development. Notably, fostering diverse peer exchange relationships can help stimulate peer knowledge and act as a palliative mechanism that builds digital knowledge to strengthen and drive future possibilities.Practical implicationsThis research offers valuable guidance to supply chain practitioners, managers and policymakers in re-thinking, re-formulating and re-shaping organizational processes to meet the UN 2030 Agenda, mainly by introducing artificial knowledge in digital transformation training and education programs. In doing so, firms should focus not simply on digital transformation but also on cultural transformation to enhance SCM accountability and sustainable performance in resilient business models.Originality/valueThis study is, to the authors' best knowledge, among the first to conceptualize artificial knowledge and digitalization issues in SCM. It further integrates resilience theory with institutional theory, legitimacy theory and stakeholder theory as the theoretical foundations of artificial knowledge in SCM, based on firms' responsibility to fulfill the sustainable development goals under the UN's 2030 Agenda.

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Section: Digitalization and Artificial Knowledgementioning

confidence: 99%

Digitalization and artificial knowledge for accountability in SCM: a systematic literature review

Vaio

Latif

Gunarathne

et al. 2023

JEIM

View full text Add to dashboard Cite

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“…Companies can implement a comprehensive Big Data and Metaverse strategy to do this. This strategy entails collecting data from all of their customer interactions, analyzing it to identify patterns in customer behavior, and then using these patterns to create targeted products and services [8]. For example, by analyzing customer data, Companies can identify which customers have the highest risk for certain types of fraud.…”

Section: Case Study: How Big Data and Metaverse Can Help A Company In...mentioning

confidence: 99%

“…Armed with this information, Companies can create an anti-fraud algorithm that automatically detects fraud before it happens and blocks it. This allows the company to significantly reduce the amount of time it takes to detect and stop fraud, saving them both time and money [8].…”

Section: Case Study: How Big Data and Metaverse Can Help A Company In...mentioning

confidence: 99%

“…Companies should also focus on integrating AI and ML capabilities within their big data applications so they can generate meaningful insights from their data. Blockchain technology is also expected to play a significant role in fintech [8]. It will secure transactions and provide verifiable records for regulatory compliance.…”

Section: Future Of Fintech Using Big Data and Metaversementioning

confidence: 99%

“…Companies must also ensure that they only collect data necessary for their operations and that all collected data is handled securely and ethically [6,8].…”

Section: Potential Risks Of Big Data and Metaverse In Fintechmentioning

confidence: 99%

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Untitled

2023

IJCSIT

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The Fintech industry is no stranger to transformation and disruption. With the emergence of new technologies such as Big Data and the Metaverse, finance companies are quickly leveraging these technologies to revolutionize the virtual fintech sector. Big data transforms how financial institutions gather, analyze, and utilize data. The sheer amount of data available has opened up countless opportunities for better customer understanding and insight into business operations. Companies can use this data to create predictive models that identify emerging trends in customer behavior, market activity, and other aspects of their business. By utilizing these insights, companies can make smarter decisions about products, services, marketing strategies, and more. The Metaverse is another technology with massive potential for disrupting the Fintech sector. The Metaverse enables businesses to offer virtual goods and services without physical stores or retail outlets. This makes it easier for companies to scale their operations across multiple regions and gives customers more options when choosing a financial service provider. Additionally, using digital currencies like Bitcoin helps reduce transaction costs significantly while increasing security compared to traditional payment methods like credit cards or PayPal.

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Revisiting the sustainable industrialization paradigm in Africa: Exploring the influence of digitalization

Ketchoua,

Avenyo,

Tregenna

2024

Sustainable Development

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This research contributes to the ongoing discourse surrounding the sustainable industrialization of African nations, a pivotal aspect emphasized by the United Nations within the Sustainable Development Goals. Drawing inspiration from the burgeoning digitalization trends across Africa, this study examines the role of digitalization in mediating the environmental repercussions of industrialization within the 45 African countries spanning the years 2000–2022. The assessment of environmental sustainability is gauged through ecological footprint and biocapacity. Employing the Environmental Kuznets Curve, and the Stochastic Impacts by Regression on Population, Affluence, and Technology framework, empirical analyses leverage the Generalized Method of Moments and the mediation analysis using structural equation modeling to unveil insightful findings. The research findings highlight the detrimental impact of industrialization on ecological health, evidenced by its correlation with an increase in ecological footprint and a decrease in biocapacity. Conversely, digitalization emerges as a positive influence on environmental well‐being. These findings remain consistent across diverse categorizations of digitalization, and ecological balance. Further examination of their interplay reveals a discernible favorable impact on environmental sustainability, with mediation analysis suggesting that digitalization mitigates approximately 4% and 6% of the overall impact of industrialization on ecological footprint and biocapacity, respectively. Additionally, our analysis lends credence to the Environmental Kuznets Curve hypothesis. As a result, it is imperative for governments to incentivize industries to adopt eco‐friendly practices and technologies in order to mitigate their ecological footprint. At the same time, policies that promote digitalization should be encouraged to further enhance environmental quality.

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Fusions of industrialisation and digitalisation (FID) in the digital economy: Industrial system digitalisation, digital technology industrialisation, and beyond

Cited by 28 publications

References 56 publications

Digitalization and artificial knowledge for accountability in SCM: a systematic literature review

Digitalization and artificial knowledge for accountability in SCM: a systematic literature review

Untitled

Revisiting the sustainable industrialization paradigm in Africa: Exploring the influence of digitalization

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