Industry 4.0: a supply chain innovation perspective

Hahn, Gerd J.

doi:10.1080/00207543.2019.1641642

Cited by 286 publications

(182 citation statements)

References 64 publications

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“…SCI includes all activities aiming to deal with the environment's uncertainty through the generation of information processing and technology innovation to provide solutions for supply chain issues and identify new ways to improve processes (Kwak et al 2018 ; Lee et al 2011 ). Notably, supply chain innovation relies heavily on advanced technologies and processes alongside radical changes in product, service, or process that improve efficiency and enhance value delivery to the end customer (Akter et al 2020 ; Hahn 2020 ). For instance, businesses are increasingly making use of AI techniques to overcome information processing constraints inherent to SCI, resulting in innovative paths of designing new products, solving supply chain issues and satisfying customers, and eventually, potentially establishing new ways to deal with uncertainty (Lee 2018 ).…”

Section: The Conceptual Background Of the Studymentioning

confidence: 99%

Artificial intelligence-driven innovation for enhancing supply chain resilience and performance under the effect of supply chain dynamism: an empirical investigation

et al. 2021

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Supply chain resilience (SCRes) and performance have become increasingly important in the wake of the recent supply chain disruptions caused by subsequent pandemics and crisis. Besides, the context of digitalization, integration, and globalization of the supply chain has raised an increasing awareness of advanced information processing techniques such as Artificial Intelligence (AI) in building SCRes and improving supply chain performance (SCP). The present study investigates the direct and indirect effects of AI, SCRes, and SCP under a context of dynamism and uncertainty of the supply chain. In doing so, we have conceptualized the use of AI in the supply chain on the organizational information processing theory (OIPT). The developed framework was evaluated using a structural equation modeling (SEM) approach. Survey data was collected from 279 firms representing different sizes, operating in various sectors, and countries. Our findings suggest that while AI has a direct impact on SCP in the short-term, it is recommended to exploit its information processing capabilities to build SCRes for long-lasting SCP. This study is among the first to provide empirical evidence on maximizing the benefits of AI capabilities to generate sustained SCP. The study could be further extended using a longitudinal investigation to explore more facets of the phenomenon.

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Section: The Conceptual Background Of the Studymentioning

confidence: 99%

Artificial intelligence-driven innovation for enhancing supply chain resilience and performance under the effect of supply chain dynamism: an empirical investigation

et al. 2021

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“…The increased digitalisation of manufacturing operations is expected to cause disruptive changes in industrial manufacturing. It can enable new and more efficient processes and new products and services (OECD 2017), and it is expected to lead to significant changes in organisational structures, business models, supply chains, and the manufacturing environment (Kagermann et al 2013;Lasi et al 2014;Hahn 2020). Emerging digital technologies will provide disruptive changes to the technologies we know today and will especially improve the integration between the different systems (Liao et al 2017;Xu, Xu, and Li 2018;Winkelhaus and Grosse 2020).…”

Section: Digitalisation Of Manufacturing and Operational Performancementioning

confidence: 99%

The complementary effect of lean manufacturing and digitalisation on operational performance

Buer

Semini

Strandhagen

et al. 2020

International Journal of Production Research

198

146

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The most recent trend manufacturers have embraced to seek operational performance improvements is the use of a wide range of digital technologies typically associated with Industry 4.0. However, few studies have investigated the relationship between such technologies and the long-established lean manufacturing domain, and how they, together, influence operational performance. Based on data from a cross-sectional survey of manufacturing companies, this study investigates the relationships between the use of lean manufacturing, factory digitalisation, and operational performance using hierarchical multiple regression analysis. While simultaneously controlling for the effects of production repetitiveness, company size, and length of lean manufacturing implementation, the findings show that both lean manufacturing and factory digitalisation individually contribute to improved operational performance. Furthermore, it is found that when used together, they have a complementary (or synergistic) effect that is greater than their individual effects combined. These research findings provide both theoretical and practical insights into how lean manufacturing and factory digitalisation affect the operational performance of manufacturing firms. In light of the upcoming fourth industrial revolution, these findings suggest that lean manufacturing is not obsolete but rather is more important than ever in order to reap the benefits from emerging technologies and translate them into improved operational performance.

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“…While the technology evolves rather fast and it requires organizations to be adapted in a fast pace. There are a very large set of publications digging in different types of applications [45][46][47][48].…”

Section: Manufacturing Casementioning

confidence: 99%

Digitalization: An Opportunity for Contributing to Sustainability From Knowledge Creation

2020

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This paper aims at exploring the perspective of sustainability when digital transformation is adopted by one organization, although it was not the first goal targeted. Two different cases are analyzed, covering manufacturing and service industries. In those cases different factors will be analyzed, mainly focused on the positive effects of knowledge creation facilitated by direct or indirect application of digitalization. Specific analysis of different cases were carried out to identify different initiatives and the impact on environmental performance. The positive effects of the institutional dimension were also assessed.

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Industry 4.0: a supply chain innovation perspective

Cited by 286 publications

References 64 publications

Artificial intelligence-driven innovation for enhancing supply chain resilience and performance under the effect of supply chain dynamism: an empirical investigation

Artificial intelligence-driven innovation for enhancing supply chain resilience and performance under the effect of supply chain dynamism: an empirical investigation

The complementary effect of lean manufacturing and digitalisation on operational performance

Digitalization: An Opportunity for Contributing to Sustainability From Knowledge Creation

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