Model for the Incorporation of Big Data in Knowledge Management Oriented to Industry 4.0

Cárdenas, Lizeth Juliana Arenas; Ramírez, Whitney Fernanda Tenjo; Molano, José Ignacio Rodríguez

doi:10.1007/978-3-319-93803-5_64

Cited by 11 publications

(4 citation statements)

References 5 publications

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“…Hence, it is possible to apply different visualization methods and various interfaces with greater interactivity, as well as employ self-operating analytical assets. Cárdenas, et al [47] focused, instead, on the necessity of fully integrating big data logics into organizational and information systems, typically referred to as KM systems. The results of this integration can boost the intellectual capital of personnel, who can then benefit from improved machine-based data collection.…”

Section: B Aqua Clustermentioning

confidence: 99%

Knowledge Management in the Fourth Industrial Revolution: Mapping the Literature and Scoping Future Avenues

Manesh

Pellegrini

Marzi

et al. 2021

IEEE Trans. Eng. Manage.

229

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Due to increased competitive pressure, modern organizations tend to rely on knowledge and its exploitation to sustain a long-term advantage. This calls for a precise understanding of knowledge management (KM) processes and, specifically, how knowledge is created, shared/transferred, acquired, stored/retrieved, and applied throughout an organizational system. However, since the beginning of the new millennium, such KM processes have been deeply affected and molded by the advent of the fourth industrial revolution, also called Industry 4.0, which involves the interconnectedness of machines and their ability to learn and share data autonomously. For this reason, the present study investigates the intellectual structure and trends of KM in Industry 4.0. Bibliometric analysis and a systematic literature review are conducted on a total of 90 relevant articles. The results reveal 6 clusters of keywords, subsequently explored via a systematic literature review to identify potential stream of this emergent field and future research avenues capable of producing meaningful advances in managerial knowledge of Industry 4.0 and its consequences.

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Section: B Aqua Clustermentioning

confidence: 99%

Knowledge Management in the Fourth Industrial Revolution: Mapping the Literature and Scoping Future Avenues

Manesh

Pellegrini

Marzi

et al. 2021

IEEE Trans. Eng. Manage.

229

View full text Add to dashboard Cite

show abstract

“…In this era of digitization, where digitization technologies such as the internet of things, cloud computing, blockchain technologies, assist collection, sharing, and use of information to support KM practices within organizations [42]. Researchers have related KM with digitization [42][43][44] to support the decentralization of information sharing and automation. Digitization combined with information systems such as cloud computing and blockchain technology presents a great opportunity to organizations for improved performance; often dependent on the actual users' readiness to accept and approve the available technology.…”

Section: Related Workmentioning

confidence: 99%

Measuring Impact of Cloud Computing and Knowledge Management in Software Development and Innovation

Gupta

Fernández-Crehuet

Gupta

2022

Systems

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For organizations, knowledge is a valuable intangible asset that should be obtained, preserved, shared, and applied to assist decision-making. Cloud computing and knowledge management systems bring together technology and organizational methods to help organizations manage their knowledge and enhance their performance. This work investigates how organizations adopt software development and distribution innovation models using ubiquitous computing more specifically cloud-based software services appraise knowledge management (KM) practices. A combined hybrid research model has been developed using extended Technology Acceptance Model (TAM) and Technology-Organization-Environment (TOE) with KM practices. Series of statistical results using structural equation modeling performed on data collected through an online survey from 983 professionals working in distributed software development (DSD) and innovation worldwide are used to put hypotheses to the test. The results of the study indicate that KM practices (knowledge accessibility, storage, application, and sharing) along with TOE (complexity, compatibility, relative advantage, security, privacy and trust, and reputation) have a substantial and positive impact on the adoption of cloud-based software services. Coordination and communication concerns are the backbones of successful practicing distributed development and innovation. Furthermore, results indicate acceptance of the moderating role of geographical (cultural) difference in examining the impact of KM practices and cloud services.

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“…1.5. Knowledge Management (KM) in Industry 4.0 and Its Relationship to Employees Competencies in MoOSTs Industry 4.0 implies a revolution where industrial processes integrate computer tools to facilitate the handling of large amounts of data and related information, as well as their transfer and interpretation, because previous means for storing information are restrictive for handling large data that are generated due to, the interconnectivity of most organizations global systems [50]. The rapid advancement and development of information and communication technologies (ICT) and integration of maintenance process within these frameworks, means most organizations are facing challenges and at the same time competency needs [51,52].…”

Section: Experience Transfer In Moostsmentioning

confidence: 99%

Knowledge Management and Experience Transfer in Major Maintenance Activities: A Practitioner’s Perspective

Iheukwumere-Esotu

Yunusa‐Kaltungo

2021

Sustainability

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Major overhauls, outages, shutdowns and turnarounds (MoOSTs) are significant maintenance interventions needed on a periodic basis to optimise the performance of physical industrial assets (PIAs). However, uncertainties in the forms of emergent and discovery work which sometimes cause delays and cost overruns are quite common partly because, MoOSTs are characterised by inherent challenges such as, but not limited to, short execution spans, volatility in ever-evolving schedules, task complexities as well as huge offline production and/or operation costs etc. Furthermore, in the literature, other complex elements which further constrains decision-makers in MoOSTs from satisfactorily achieving predetermined objectives have been identified, one of which is the lack of a formalised approach for capturing tacit knowledge from experienced practitioners. Consequently, because MoOSTs is an applied discipline, significant human endeavours are required in the planning and management, which makes it pertinent to examine and obtain the perspectives of experienced MoOSTs practitioners. Therefore, the aims of this study are two folds; firstly, to examine the extent of alignment between findings from literature as it relates to the challenges encountered during MoOSTs, as well as probe their underlying causes in practice. Secondly, to show how relevant the findings from this study would be in providing a baseline for establishing a proposal for capturing MoOSTs knowledge and the transfer of experience. The research approach adopted; thematic synthesis of themes which emerged from knowledge management challenges in MoOSTs identified via an earlier systematic literature review (SLR); and then, the identified challenges were validated through conducting interviews with practitioners. Demography analysis as well as specific MoOSTs related questions were administered via questionnaires, which were then analysed using frequency analysis method. Additionally, semi-structured interviews were conducted to investigate the perceptions of practitioners on pertinent MoOSTs issues. Both questionnaires and interview questions were formulated by findings obtained from the SLR, so as to examine whether the knowledge management challenges identified in the literature exist in practice, and if they do to what extent. In total, the selected responses of 49 practitioners, with origin across five industries were examined to determine the extent of alignment between literature and the practice-based perspectives. Based on the results, nine challenges were identified as critical themes, six of which were associated with managing knowledge. The study identified not only known constraints from literature but also their underlying causes based on the perspective of practitioners involved in multiple MoOSTs, which is crucial for developing sustainable mitigation. A unique contribution of this research is the mapping of demographic information such as industry, country, job class, years of experience, MoOSTs organization size, frequency for performing MoOSTs, etc., to responses obtained from participants, which has not been shown in literature prior to now. The importance of such rigorous efforts in the research design, is crucial for enabling the adoption of holistic approaches to eliminating the underlying causes of challenges encountered in MoOSTs, based on first hand reporting of people involved. In addition, the relevance of such first-hand analyses of responses obtained from this study; serve as baseline for the introduction of the proposal to adequately manage knowledge management issues in this discipline.

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Model for the Incorporation of Big Data in Knowledge Management Oriented to Industry 4.0

Cited by 11 publications

References 5 publications

Knowledge Management in the Fourth Industrial Revolution: Mapping the Literature and Scoping Future Avenues

Knowledge Management in the Fourth Industrial Revolution: Mapping the Literature and Scoping Future Avenues

Measuring Impact of Cloud Computing and Knowledge Management in Software Development and Innovation

Knowledge Management and Experience Transfer in Major Maintenance Activities: A Practitioner’s Perspective

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