Drivers of Artificial Intelligence and Their Effects on Supply Chain Resilience and Performance: An Empirical Analysis on an Emerging Market

Abstract

The global supply chain has suffered an unprecedented impact Affected by multiple factors such as anti-globalization, rising trade protectionism and the COVID-19 pandemic. Based on the technology-organization-environment framework and resource-based theory, this study attempts to explore and analyze what drives a firm’s willingness to adopt artificial intelligence technology and how such willingess to adopt artificial intelligence technology may contribute to supply chain resilience and supply chain performance. Using survey data collected from 318 firms in China, we empirically test our arguments and hypotheses through the structural equation modeling approach. The results suggest that the relative advantages of enterprise artificial intelligence technology, supply chain collaboration, and environmental uncertainty are the three major factors affecting the adoption of artificial intelligence technology, which subsequently provide a positive impact on supply chain resilience and supply chain performance. This study expands the application field and scope of artificial intelligence technology, fills the relatively large gap in the research on the behavior of enterprise users adopting artificial intelligence technology in the supply chain field. This provides a useful reference for enterprises to adopt artificial intelligence technology.

Exploring the motivations behind artificial intelligence adoption for building resilient supply chains: a systematic literature review and future research agenda

“…Appropriate skill sets are required for using AI technology. Lack of training, incompetent technical skills and lack of awareness about the technologies are a few challenges (Nitsche et al, 2023;Wang and Pan, 2022;Gupta et al, 2021). Lack of government policies, regulations, transparent data governance, confidentiality, ownership and authenticity hinders the AI implications in SC (Golan et al, 2021).…”

“…The outcome of this exercise is to build a resilient SC. • Assess, compare and select the optimal the supply chain members (Wang and Pan, 2022). AI provides personalized, secured, trusted product delivery (Modgil et al, 2022) and improves customer service (Khan et al, 2023;Qamar et al, 2021).…”

“…During the process of AI adoption, there are many challenges faced by organizations. For example, technical challenges such as lack of hardware and software support, lack of data management tools, lack of trusted databases, scalability issues and difficulty in managing complex systems (Wang and Pan, 2022). Therefore, developing supportive infrastructure is essential to adopt AI technology.…”

“…Different moderating variables such as firm size, industry type, position in the SC, nature of organization, government regulation and policies influence the adoption of AI technology (Mariani and Borghi, 2023;Dey et al, 2023;Belhadi et al, 2021Belhadi et al, , 2022Dohale et al, 2022;Queiroz et al, 2022). For example, multiple authors have conducted their study in a general context (Dubey et al, 2022;Merhi and Harfouche, 2023;Gupta et al, 2021Gupta et al, , 2022Gupta et al, , 2023Modgil et al, 2022;Belhadi et al, 2021Belhadi et al, , 2022Wang and Pan, 2022;Queiroz et al, 2022). In contrast, other authors have conducted their studies for manufacturing industries (Leoni et al, 2022;Dey et al, 2023;Dohale et al, 2022;Lerch et al, 2022) and service industries (Mariani and Borghi, 2023).…”

Transformação Digital Na Indústria De Defesa: Análise Da Adoção Da Inteligência Artificial Na Performance E Resiliência Da Cadeia De Suprimentos

“…Diante deste cenário, dentre as tecnologias trazidas pela I4.0, com aplicação na SCM, a Inteligência Artificial (IA) ganha notoriedade pela diferenciação estratégica que proporciona àqueles que a utilizam, como previsão de demanda, otimização de rotas e logística, redução de custos, tomada de decisão estratégica, melhoria na visibilidade da cadeia de suprimentos, gestão de inventário eficiente, detecção de anomalias e fraudes, aprimoramento da experiência do cliente, adaptação a mudanças rápidas, dentre outras (AL-MAdhrahi et al, 2022;Pournader et al, 2021;Wang & Pan, 2022). Em meio a esse arranjo dinâmico e complexo, a General Purpose Technology (GPT) ganha protagonismo justamente por constituir-se em uma classe de Inteligência Artificial que têm a capacidade de afetar profundamente e de maneira ampla diversos setores da economia e da sociedade (Bresnahan, 2010).…”