Digital Economy and Intelligent Supply Chain Management: International Experience

Doan, Karine; Carrino, Stefano; Ivanova, Natalya; Evtodieva, T. E.

doi:10.1007/978-3-030-47458-4_86

Cited by 6 publications

(8 citation statements)

References 2 publications

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“…Our review confirms Min’s (2010) findings that “AI has not been fully exploited to solve SC problems whose solutions are either too expensive or difficult to produce due to their inherent complexity (Abdelaziz et al , 2020) and the ill-structured nature of implementation aspects in SCM.” Even after a decade of research from Min (2010) findings to Evtodieva (2020), Abbasi et al (2020), our findings conclude that AI in their form of predictive and learning capabilities within SCRM research is still in its infancy stage. However, the interest among researchers in the past two years seems to have steadily increased as confirmed by Di Vaio et al (2020), Doan et al (2021) and Riahi et al (2021).…”

Section: Methodsmentioning

confidence: 99%

Applications of artificial intelligence and machine learning within supply chains:systematic review and future research directions

Younis

Sundarakani

Alsharairi

2021

JM2

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Purpose The purpose of this study is to investigate how artificial intelligence (AI), as well as machine learning (ML) techniques, are being applied and implemented within supply chains (SC) and to develop future research directions from thereof. Design/methodology/approach Using a systematic literature review methodology, this study analyzes the publications available on Web of Science, Scopus and Google Scholar that linked both AI and supply chain from one side and ML and supply chain from another side. A total of 388 research studies have been identified through the before said three database searches which are further screened, sorted and finalized with 50 studies. The research thoroughly reviews and analyzes the final lists of 50 studies that were found relevant and significant to the theme of AI and ML in supply chain management (SCM). Findings AI and ML applications are still at the infant stage and the opportunity for them to elevate supply chain performance is very promising. Some researchers developed AI and ML-related models which were tested and proved to be effective in optimizing SC, and therefore, the application of AI and ML in supply chain networks creates competitive advantages for firms. Other researchers claim that AI and ML are both currently adding value while many other researchers believe that they are still not fully exploited and their tools and techniques can leverage the supply chain’s total value. The research found that adoption of AI and ML have the ability to reduce the bullwhip effect, and therefore, further supports the performance of supply chain efficiency and responsiveness. Research limitations/implications This research was limited in terms of scope as it covered AI and ML applications in the supply chain while there are other dimensions that could be investigated such as big data and robotics but it was found too lengthy to include these additional dimensions, and therefore, left for future research studies that other researchers could explore and pursue. Practical implications This study opens the door wide for other researchers to explore how AI and ML can be adopted in SCM and what are the models that are already tested and proven to be viable. In addition, the paper also identified a group of research studies that confirmed the unexploited avenues of AI and ML which could be of high interest to other researchers to explore. Originality/value Although few earlier research studies touch based on the AI applications within manufacturing and transportation, this study is different and makes a unique contribution by offering a holistic view on the AI and ML implications within SC as a whole. The research carefully reviews a number of highly cited papers classifying them into three main themes and recommends future direction.

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Section: Methodsmentioning

confidence: 99%

Applications of artificial intelligence and machine learning within supply chains:systematic review and future research directions

Younis

Sundarakani

Alsharairi

2021

JM2

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“…The digital transformation of supply chains represents a paradigm shift, driven by the integration of advanced technologies such as the Internet of Things (IoT), Artificial Intelligence (AI), blockchain, and cloud computing. These technologies have been pivotal in enhancing operational efficiency, transparency, and resilience across global supply chains [1][2][3][4]. Gupya (2023) and Ning & Yao (2023) discuss the transformative potential of digital technologies in streamlining operations and improving visibility within the complex landscape of supply chain management [1,3].…”

Section: Transformative Potential Of Digital Technologiesmentioning

confidence: 99%

“…Infrastructure constraints, skill gaps, and security concerns are significant barriers to the widespread adoption of digital solutions [6,7]. Doan et al (2021) and Bejlegaard et al (2021) discuss the critical need for addressing these challenges to fully realize the benefits of digital technologies in supply chains [6,7].…”

Section: Overcoming Digital Transformation Challengesmentioning

confidence: 99%

“…While the pursuit of cost savings has traditionally been a primary driver behind the adoption of digital technologies in supply chains, this focus offers a limited perspective on the multifaceted value proposition of digital transformation. Beyond mere cost reduction, digital transformation holds the potential to significantly enhance customer satisfaction, foster innovation, improve supply chain visibility, and facilitate the transition towards more sustainable and resilient supply chain practices [4,5].…”

Section: Introductionmentioning

confidence: 99%

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Measuring the Broader Value Proposition of Digital Transformation in Supply Chains

Singh

2024

IJSCM

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The advent of digital transformation within supply chains heralds a new era of efficiency, innovation, and resilience. This paper explores the multifaceted impact of digital technologies—such as the Internet of Things (IoT), artificial intelligence (AI), blockchain, and cloud computing—on supply chain management. Through a comprehensive review of current literature, we identify the challenges and opportunities presented by digital transformation, emphasizing the importance of overcoming infrastructural constraints, skill gaps, and security concerns to harness the full potential of these technologies. Furthermore, we delve into the ethical considerations and social impacts, highlighting the imperative for sustainable and responsible practices in the digital age. The paper also forecasts future directions and emerging technologies, underscoring the need for supply chains to adapt to and capitalize on these advancements for sustainable growth and competitive advantage. Our analysis concludes that while digital transformation presents significant challenges, it also offers unparalleled opportunities for supply chains to become more agile, transparent, and customer centric. The successful integration of digital technologies not only enhances operational efficiency but also drives innovation, fosters sustainability, and strengthens resilience against global disruptions. This paper contributes to the ongoing discourse on digital transformation in supply chains, providing insights for academics, practitioners, and policymakers on navigating the complexities of this digital revolution.

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“…This can effectively reduce the geographical boundaries and barriers of goods and services. Consumers' shopping needs can be met faster and safer, and the time per purchase is shortened [44].…”

Section: The Impact Of Consumption Expansionmentioning

confidence: 99%

The impact of digital economy on high-quality economic development: Research based on the consumption expansion

Li,

2023

PLoS ONE

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Studies have found that the digital economy plays a positive role in promoting high-quality economic development. Meanwhile, the digital industrialization and industrial digitalization have given rise to new demands and supply modes of consumption. It is necessary to analyze the role of consumption expansion in the impact of digital economy on high-quality economic development. Based on Chinese provincial panel data, we first applied the entropy weight method to construct the digital economy index and the high-quality economic development index. And on this basis, it was verified that the digital economy can positively promote the high-quality development of the inverted U-shaped structural economy. Then we separately used the mediation and the threshold effect models to analyze the role of consumption expansion in empowering high-quality development in the digital economy. Regional heterogeneity was further taken into account. The results dedicate that consumer demand and the digital economy have a partial or complete mediating effect. The promotion of high-quality development by the digital economy can be affected by the threshold of consumption expansion, which is manifested in the marginal incremental effect due to the growth of consumption supply. On the contrary, the growth of consumer demand has led to the inverted U-shape of the digital economy to promote high-quality economic development. In the heterogeneity analysis, the threshold effect also varied greatly. This research enriches the theoretical achievements and reveals the impact of consumption expansion on the digital economy affecting the high-quality development, which may provide certain reference for other countries and regions.

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Digital Economy and Intelligent Supply Chain Management: International Experience

Cited by 6 publications

References 2 publications

Applications of artificial intelligence and machine learning within supply chains:systematic review and future research directions

Applications of artificial intelligence and machine learning within supply chains:systematic review and future research directions

Measuring the Broader Value Proposition of Digital Transformation in Supply Chains

The impact of digital economy on high-quality economic development: Research based on the consumption expansion

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