Table 2 List of publications with KM...

Table 2

List of publications with KM challenges and identified gaps from the SLR

No.	Author details	KG	KC	KS	KU	Key KM Challenges and identified gaps
1	Frank et al. (2024)	✔	✔		✔	Lack of strategic vision, trust issues, cultural resistance, lack of standardized semantic models and interoperable ontologies
2	Rejeb et al. (2025)	✔		✔		Fragmentation and heterogeneity of data sources often generated in isolation using different formats, standards and semantics
3	Lista Rossetti et al. (2024)	✔	✔	✔	✔	Organizational resistance to change, learning levels, lack of clear processes or frameworks for codification
4	Zhang et al. (2025)	✔			✔	Underutilization of human tacit knowledge, lack of tools or infrastructure to effectively utilize the knowledge
5	Karimi et al. (2025)	✔		✔		Lack of integration between old and new systems, lack of time and resources for knowledge sharing activities, inadequate support or commitment from leadership for knowledge sharing
6	Alonso et al. (2024)	✔	✔	✔	✔	Data security and privacy concern, lack of time and resources for knowledge codification, limited interdepartmental collaboration
7	Ferreira et al. (2024)	✔		✔	✔	Rapid technology change, Data security and privacy concern, lack of familiarity with I4.0 knowledge sharing, creation and application
8	Kuyken and Schropp (2023)			✔		Lack of Intergenerational knowledge transmission, degree of standardization with several risks and sharing tacit knowledge
9	Tortorella et al. (2024)	✔		✔	✔	I4.0 design principles positively moderate the relationship between KM practices and innovation performance
10	Lepore et al. (2022)			✔		Technological challenges include limited interoperability, incompatible communication protocols, and semantic inconsistencies
11	Ribeiro et al. (2022)	✔	✔	✔	✔	Lack of integration between old and new systems, difficulty of codifying tacit and process-specific knowledge, communication, cultural, and trust challenges
12	Entezarian and Mehraeen (2024)	✔			✔	Lack of human resources and their digital skills and competencies. Organizational culture and operational efficiency
13	Manesh et al. (2021)	✔		✔	✔	Data overload and integration challenges, rapid technology change, lack of understanding or familiarity with I4.0 technologies
14	Gupta et al. (2022)		✔	✔	✔	Interoperability, data governance and skills, inadequate codification and sharing structures weaken collaborative decision mechanisms
15	Hafeez et al. (2025)	✔	✔	✔	✔	Individual change dynamic capabilities, technological infrastructure operational challenges, and misaligned collaboration goals
16	Bettiol and Micelli (2020)	✔	✔	✔	✔	Heterogeneous data formats and absence of shared semantics impede knowledge codification, data fusion, and coordination
17	Idrees et al. (2023)			✔	✔	Poor knowledge transfer mechanisms across cross-functional teams translate into coordination inefficiencies
18	Anshari et al. (2022)	✔		✔	✔	Gaps in tacit knowledge capture and sharing structures, limited trust in AI and analytics-driven knowledge, lack of vertical and horizontal coordination in I4.0
19	Tabim et al. (2024)			✔		Human–machine KS remains problematic, as machine-generated knowledge is often difficult for humans to interpret and trust
20	Oks et al. (2024)	✔	✔		✔	Poor integration of domain knowledge, lack of standardized semantic models and interoperable ontologies
21	Bresciani et al. (2021)	✔				Lack of understanding or familiarity with I4.0 technologies, Data overload when utilizing knowledge from I4.0 technologies
22	Mohanty et al. (2024)	✔		✔	✔	Insufficient feedback and learning loops, cultural resistance to knowledge sharing, organizational resistance to change, rapid technology change
23	Palacios Osma et al. (2020)	✔		✔		Lack of innovation processes, lack of infrastructure to support knowledge sharing
24	Celino et al. (2025)	✔		✔		Trustworthiness and reliability issue to change and innovate business by leveraging digital technologies and tools
25	Sherif et al. (2024)		✔	✔	✔	Data privacy, the burden of information overload, and the rapid obsolescence of knowledge in such a dynamic environment

No.	Author details	KG	KC	KS	KU	Key KM Challenges and identified gaps
1	Frank et al. (2024)	✔	✔		✔	Lack of strategic vision, trust issues, cultural resistance, lack of standardized semantic models and interoperable ontologies
2	Rejeb et al. (2025)	✔		✔		Fragmentation and heterogeneity of data sources often generated in isolation using different formats, standards and semantics
3	Lista Rossetti et al. (2024)	✔	✔	✔	✔	Organizational resistance to change, learning levels, lack of clear processes or frameworks for codification
4	Zhang et al. (2025)	✔			✔	Underutilization of human tacit knowledge, lack of tools or infrastructure to effectively utilize the knowledge
5	Karimi et al. (2025)	✔		✔		Lack of integration between old and new systems, lack of time and resources for knowledge sharing activities, inadequate support or commitment from leadership for knowledge sharing
6	Alonso et al. (2024)	✔	✔	✔	✔	Data security and privacy concern, lack of time and resources for knowledge codification, limited interdepartmental collaboration
7	Ferreira et al. (2024)	✔		✔	✔	Rapid technology change, Data security and privacy concern, lack of familiarity with I4.0 knowledge sharing, creation and application
8	Kuyken and Schropp (2023)			✔		Lack of Intergenerational knowledge transmission, degree of standardization with several risks and sharing tacit knowledge
9	Tortorella et al. (2024)	✔		✔	✔	I4.0 design principles positively moderate the relationship between KM practices and innovation performance
10	Lepore et al. (2022)			✔		Technological challenges include limited interoperability, incompatible communication protocols, and semantic inconsistencies
11	Ribeiro et al. (2022)	✔	✔	✔	✔	Lack of integration between old and new systems, difficulty of codifying tacit and process-specific knowledge, communication, cultural, and trust challenges
12	Entezarian and Mehraeen (2024)	✔			✔	Lack of human resources and their digital skills and competencies. Organizational culture and operational efficiency
13	Manesh et al. (2021)	✔		✔	✔	Data overload and integration challenges, rapid technology change, lack of understanding or familiarity with I4.0 technologies
14	Gupta et al. (2022)		✔	✔	✔	Interoperability, data governance and skills, inadequate codification and sharing structures weaken collaborative decision mechanisms
15	Hafeez et al. (2025)	✔	✔	✔	✔	Individual change dynamic capabilities, technological infrastructure operational challenges, and misaligned collaboration goals
16	Bettiol and Micelli (2020)	✔	✔	✔	✔	Heterogeneous data formats and absence of shared semantics impede knowledge codification, data fusion, and coordination
17	Idrees et al. (2023)			✔	✔	Poor knowledge transfer mechanisms across cross-functional teams translate into coordination inefficiencies
18	Anshari et al. (2022)	✔		✔	✔	Gaps in tacit knowledge capture and sharing structures, limited trust in AI and analytics-driven knowledge, lack of vertical and horizontal coordination in I4.0
19	Tabim et al. (2024)			✔		Human–machine KS remains problematic, as machine-generated knowledge is often difficult for humans to interpret and trust
20	Oks et al. (2024)	✔	✔		✔	Poor integration of domain knowledge, lack of standardized semantic models and interoperable ontologies
21	Bresciani et al. (2021)	✔				Lack of understanding or familiarity with I4.0 technologies, Data overload when utilizing knowledge from I4.0 technologies
22	Mohanty et al. (2024)	✔		✔	✔	Insufficient feedback and learning loops, cultural resistance to knowledge sharing, organizational resistance to change, rapid technology change
23	Palacios Osma et al. (2020)	✔		✔		Lack of innovation processes, lack of infrastructure to support knowledge sharing
24	Celino et al. (2025)	✔		✔		Trustworthiness and reliability issue to change and innovate business by leveraging digital technologies and tools
25	Sherif et al. (2024)		✔	✔	✔	Data privacy, the burden of information overload, and the rapid obsolescence of knowledge in such a dynamic environment

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