Управление знаниями в производственных сетях: классификация и технологии для повторного использования знаний
Ключевые слова:
трансфер знаний, представление знаний, производственные сети, сети МСПАннотация
Многие исследования в области управления знаниями указывают на то, что предприятия и организации, поддерживающие систематический обмен, передачу и повторное использование знаний, могут рассчитывать на значительные выгоды. Однако не так много исследований выполнено в рамках анализа технологий для повторного использования знаний, которые применяются в организациях. Исходя из классификации подходов к повторному использованию знаний, в статье рассматривается состояние в этой области применительно к производственным сетях (с уделением особого внимания сетям малых и средних предприятий - МСП). Цель статьи двоякая: для производственных сетей это исследование того, какие виды повторно используемых знаний (с точки зрения разрабатываемой классификации) наиболее актуальны для таких сетей; для подхода к классификации методов повторного использования знаний это уточнении данного подхода и его обоснование применительно к производственным сетям. Основными результатами статьи являются: (1) анализ ситуаций повторного использования знаний в сетях МСП, (2) оценка предложенного подхода к классификации методов повторного использования знаний применительно к различным ситуациям и (3) дальнейшее уточнение и валидация предложенного подхода.Литература
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3. Phelps C., Heidl R., Wadhwa A. Knowledge, networks, and knowledge networks a review and research agenda // Journal of Management. 2012. vol. 38(4). pp. 1115–1166.
4. Azizi R., Maleki M., Moradi-Moghadam M., Cruz-Machado V. The Impact of Knowledge Management Practices on Supply Chain Quality Management and Competitive Advantages // Management and Production Engineering Review. 2016. vol. 7. no. 1. pp. 4–12.
5. Jakubowski J., Peterka J. Design for Manufacturing in Virtual Environment using Knowledge Engineering // Management and Production Engineering Review. 2014. vol. 5. no. 1. pp. 3–10.
6. Alavi M., Leidner D.E. Knowledge management systems: issues, challenges, and benefits // Communications of the AIS. 1999. vol. 1(2es). pp. 1.
7. Dalkir K. Knowledge management in theory and practice // Routledge. 2013. 372 p.
8. Studer R., Benjamins V.R., Fensel D. Knowledge engineering: principles and methods. Data & knowledge engineering. 1998. vol. 25(1). pp. 161–197.
9. Lillehagen F., Krogstie J. Active Knowledge Modelling of Enterprises // Springer. 2009. 436 p.
10. Sandkuhl K. Knowledge reuse: survey of existing techniques and classification approach // Business Intelligence. 2015. pp. 126–148.
11. Sandkuhl K., Lillehagen F. The Early Phases of Enterprise Knowledge Modeling: Practices and Experiences from Scaffolding and Scoping // IFIP Working Conference on The Practice of Enterprise Modeling (IFIP PoEM 2008). 2008. pp. 1–14.
12. Fong M. E-Collaborations and Virtual Organizations // Hershey. PA: IRM Press. 2005. 300 p.
13. Möller K., Rajala A., Svahn S. Strategic business nets – their type and management // Journal of Business Research. 2005, vol. 58. no. 9. pp. 1274–1284.
14. Kohtamäki M., Vesalainen J., Varamäki E., Vuorinen T. The governance of partnerships and a strategic network // Management Decision. 2006. vol. 44. no. 8. pp. 1031–1051.
15. Valkokari K., Helander N. Knowledge management in different types of strategic SME networks // Management Research News. 2007. pp. 597–608.
16. Lau T., Sure Y. Introducing Ontology-based Skills Management at a Language Insurance Company // Proceedings of the Modellierung. 2002. pp. 123–134.
17. Sandkuhl K., Billig A. Ontology-based Artefact Management in Automotive Electronics // International Journal for Computer Integrated Manufacturing (IJCIM). 2007. vol. 20(7). pp. 627–638.
18. Lybaert N. The Information Use in a SME: its Importance and Some Elements of Influence // Small Business Economics. 1998. vol. 10(2). pp. 171–191.
19. Levy M., Powell P., Yetton, P. The Dynamics of SME Information Systems // Small Business Economics. 2002. vol. 19(4). pp. 341–354.
20. Probst G., Raub S., Romhardt K. Managing Knowledge – Building Blocks for Success // John Wiley & Sons, 2000. 368 p.
21. Nonaka I., Takeuchi H. The Knowledge-Creating Company: How Japanese Companies Create the Dynamics of Innovation // Oxford university press. 1995. 304 p.
22. Maier R., Hädrich T., Peinl R. Enterprise Knowledge Infrastructures: 2nd Edition // Springer. 2010. 460 p.
23. Lamberts K., Shanks D. Knowledge Concepts and Categories // Psychology Press. 2013. 478 p.
24. Smirnov A., Sandkuhl K., Shilov N. Multilevel Self-Organization and Context-Based Knowledge Fusion for Business Model Adaptability in Cyber-Physical Systems // IFAC Proceedings Volumes. 2013. vol. 46. no. 9. pp. 2045–2050.
25. Markus M. Lynne. Toward a Theory of Knowledge Reuse: Types of Knowledge Reuse Situations and Factors in Reuse Success // Journal of Management Information Systems. 2001. vol. 18. no. 1. pp. 57–93.
26. Delone W. The Delone and Mclean model of information systems success: a ten-year update // Journal of management information systems. 2003. vol. 19(4). pp. 9–30.
27. Jennex M., Olfman L. A model of knowledge management success // International Journal of Knowledge Management (IJKM). 2006. vol. 2(3). pp. 51–68.
28. Sandkuhl K., Stirna J., Persson A., Wißotzki M. Enterprise Modeling: Tackling Business Challenges with the 4EM Method // Springer. 2014. 309 p.
29. Sandkuhl K. Organizational Knowledge Patterns – Definition and Characteristics // Proceedings of the International Conference on Knowledge Management and Information Sharing. 2011. pp. 230–235.
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31. Sandkuhl K. et al. Ontology Construction in Practice – Experiences and Recommendations from Industrial Cases // 9th International Conference on Enterprise Information Systems. 2007. pp. 250–256.
32. Wißotzki M. et al. State of Research in Reuse of Enterprise Models: Systematic Literature Analysis of CAISE, EMMSAD, ICIS and INCOM // IADIS International Conference Information Systems 2012. pp. 82–90.
33. Hammer K., Sandkuhl K. The State of Ontology Pattern Research: A Systematic Review of ISWC. ESWC and ASWC 2005-2009 // Proceedings of the 2nd International Conference on Ontology Patterns. 2010. vol. 671. pp. 5–18.
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44. Skyrme D. The Networked Organization. Management Insights. URL: http://www. skyrme.com/insights/1netorg.htm. (дата обращения: 15.11. 2008).
45. The Generalized Enterprise Reference Architecture and Methodology // Handbook on Enterprise Architectures. 2003. pp. 21–63.
46. Carstensen A. et al. Knowledge Supply for SME Networks: Application Cases and Selected Technical Approaches // E-Business Issues Challenges and Opportunities for SMEs: Driving Competitiveness. IGI Publishing. 2011. pp. 149–172.
47. Zhong H., Levalle R.R., Moghaddam M., Nof S. Collaborative Intelligence – Definition and Measured Impacts on Internetworked E-Work // Management and Production Engineering Review. 2015. vol. 6. no. 1. pp. 67–78.
48. Смирнов А.В., Левашова Т.В., Пашкин М.П. Модели контекстно-управляемых систем поддержки принятия решений в динамических структурированных областях // Труды СПИИРАН. 2009. Вып. 9. С. 116–147.
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51. Alvarado M., Romero M., Sheremetov L. Corporative Memory Based on the User Profiles // Journal of Expert Systems with Applications. Pergamon Press. 2004. vol. 26(1). pp. 87–94.
Knowledge Management in Production Networks: Classification of Knowledge Reuse Techniques
Abstract
Many studies in the field of knowledge management indicate that enterprises and organizations establishing systematic sharing, transfer and reuse of knowledge can expect substantial benefits. Although sharing and transfer of knowledge requires a way to transfer or capture knowledge, not much work has been spent in investigating what kinds of reuse techniques are used in organizations. Starting from a classification of approaches to knowledge reuse, this paper investigates the state of knowledge reuse in production networks with a specific focus on networks of small and medium-sized enterprises (SME). The aim of the paper is twofold: for production networks, the intention is to investigate which kind of reusable knowledge, in terms of the classification developed, is most relevant for such networks; for the approach to the classification of knowledge reuse techniques, the aim is to further refine the approach and validate it in the field of production network research. The main contributions of this paper are (1) an analysis of reuse situations in SME networks, (2) evaluation of the proposed approach to the knowledge reuse classification for use in the reuse situations and (3) further refinement and validation of the classification approach.
Опубликован
2018-02-02
Как цитировать
Зандкуль, К., & Смирнов, А. В. (2018). Управление знаниями в производственных сетях: классификация и технологии для повторного использования знаний. Труды СПИИРАН, 1(56), 5-33. https://doi.org/10.15622/sp.56.1
Раздел
Искусственный интеллект, инженерия данных и знаний
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