The Impact of Digital Intelligence Services on Manufacturing Upgrading:Theoretical Framework and Future Trends
Manufacturing upgrade is a crucial component of national economic development strategies,with the sources of competitive advantage evolving from traditional products and technology to data-driven,algorithmic,and service-oriented paradigms.Currently,the study of how Digital Intelligence Services(DIS)influence manufacturing upgrades is in its nas-cent phase,particularly within the Chinese context,where the integration of these elements trails behind advanced enter-prise intelligence practices.The mechanisms through which DIS can enhance competitive advantages are yet to be fully ex-plored and articulated.Given these issues,this study focuses on the following aspects:(1)the definition of DIS and the relationship between"digital"and"intelligence";(2)the impact of DIS on manufacturing upgrades from various perspec-tives,including its driving motivations,mechanisms,outcomes,and underlying knowledge framework;and(3)the fu-ture development directions of DIS in the context of manufacturing upgrades.This study delves into the multifaceted domain of DIS and their influence on the manufacturing industry's transforma-tion.To achieve this,it selects the core collection of the Web of Science(WoS)database as the primary sample source.Through a meticulous literature review,the study identified and clustered foreign scholarly works,ultimately narrowing down the focus to two pivotal research topics:"digital intelligence services"and"manufacturing industry upgrading."The analysis began with the earliest relevant literature,dating back to 1996,and encompassed a comprehensive collection of 542 non-duplicative literature data.Utilizing CiteSpace,this study maps the developmental trajectory,frontier hotspots,and changing trends of DIS's impact on manufacturing upgrades.Through latent semantic analysis(LSI)of keywords,a visual map was created.This approach integrates the individual"S-B-O"model with the product-service system-focused"S-B-O"model,resulting in a comprehensive framework of DIS's impact on manufacturing upgrades across four dimen-sions:motivation,mechanism,performance,and knowledge system.The study reveals several key findings:In terms of motivation,the trend in research indicates that DIS influences manufac-turing upgrades by addressing"user demand responses."Mechanistically,clustering analysis shows that DIS promotes manufac-turing upgrades through a parallel process,achieved via the coordination of manufacturing and service systems.In terms of per-formance,the primary pathways for DIS-driven manufacturing upgrades are efficiency enhancement and model innovation,which are the focus of most studies.Regarding knowledge concepts,the DIS concept and theoretical focus evolve from technology-driven services to personalized services and,ultimately,human-machine interaction services.The research introduces several innovative contributions.First,it delineates the distinctions and interconnections be-tween"digital"and"intelligence"within existing literature,establishing a theoretical groundwork for comprehending the intrinsic mechanisms that underpin DIS's role in advancing manufacturing upgrades.Second,it examines the impact of DIS on manufacturing upgrades from multifaceted perspectives,including user demand and industrial development,extracting coherent,progressive themes from the literature,and formulating a theoretical framework that elucidates causal relation-ships.Third,diverging from conventional technology-driven perspectives on industrial structural changes,this study high-lights the role of DIS in manufacturing upgrades through inter-industry dynamics.This offers invaluable insights into un-derstanding theoretical development trajectories and frontier issues.Future studies should delve into the synergies between new-generation manufacturing and artificial intelligence tech-nologies.This exploration necessitates the development of diverse channels for securing key resources and a deeper com-prehension of the multifaceted motivations that drive the impact of services on manufacturing.Moreover,research should aim to expand the application of knowledge domains based on ontology theory.Efforts should be directed towards advan-cing the standardization of knowledge systems,considering the perspectives of the Internet of Things,platform ecosys-tems,and service ecosystems.Subsequently,on the one hand,there is a need to construct data-driven AI large models that facilitate autonomous learning and intelligent decision-making in service contexts.This development will broaden the range of manufacturing realization methods and operational models.On the other hand,future research should harness blockchain technology to establish open cooperative networks.This will involve creating a management system designed to identify,assess,and mitigate risks to user data security,thereby enhancing the quality and reliability of manufacturing digital intelligence services.
Digital Intelligence ServicesManufacturing UpgradingTheoretical FrameworkAction MechanismFuture Trends
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