Just Accepted Manuscripts
Original Research Article

A conceptual knowledge transfer model for blockchain technology adoption in wine supply networks: Special Issue "Transforming wine value chains – Adapting to a changing world"

(Just Accepted)
  • Michael Paul Kramer,
  • Jon H. Hanf
Michael Paul Kramer
Hochschule Geisenheim University
Jon H. Hanf
Hochschule Geisenheim University
DOI: https://doi.org/10.36253/wep-18864

Published 2026-07-03

Keywords

  • Knowledge Transfer,
  • Tacit Knowledge,
  • blockchain,
  • Supply chain,
  • wine industry

How to Cite

Kramer, M. P., & Hanf, J. H. (2026). A conceptual knowledge transfer model for blockchain technology adoption in wine supply networks: Special Issue "Transforming wine value chains – Adapting to a changing world". Wine Economics and Policy. https://doi.org/10.36253/wep-18864

Copyright (c) 2024 Michael Paul Kramer, Jon H. Hanf

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

Effective adoption of blockchain technology in supply networks depends significantly on inter-organizational knowledge transfer, particularly in the pre-adoption phase when stakeholders must be convinced of its perceived benefits. This conceptual study introduces the Evolutionary Knowledge Transfer Model (EKTM), a novel framework which explains how explicit and tacit knowledge about blockchain dynamically evolve across vertically coordinated multi-tier wine supply networks. Different to previous models, it integrates dyadic, firm, and network perspectives while highlighting the essential role of tacit knowledge transfer, two aspects often overlooked in existing frameworks. Methodologically, the study adopts the design approach of Jaakkola for conceptual research combining knowledge management, complex network, and strategic management theories. The study contributes to supply chain management literature, demonstrating the crucial role of tacit knowledge transfer in blockchain adoption. It provides managers with a conceptual tool to assess knowledge flow and balance explicit and tacit knowledge transfer with the objective to accelerate technology adoption across the supply network. This study closes a critical gap in understanding how knowledge about disruptive digital technologies evolves in vertically coordinated supply networks.

(Just Accepted)

References

  1. C. Aggarwal, K. Subbian, Evolutionary network analysis: A survey, ACM Comput. Surv. 47(1) (2014) 1–36.
  2. R. Albert, A.L. Barabási, Statistical mechanics of complex networks, Rev. Mod. Phys. 74(1) (2002) 47.
  3. T. Andreeva, I. Ikhilchik, Applicability of the SECI model of knowledge creation in Russian cultural context: theoretical analysis, Knowl. Process Manag. 18(1) (2011) 1–11.
  4. C. Argyris, D.A. Schön, Organizational learning: A theory of action perspective, Reis 77/78 (1997) 345–348.
  5. J.K. Arnulf, H.C. Dreyer, C.E. Grenness, Trust and knowledge creation: how the dynamics of trust and absorptive capacity may affect supply chain management development projects, Int. J. Logist. Res. Appl. 8(3) (2005) 225–236.
  6. N. Assur, K. Rowshankish, The data-driven enterprise of 2025, Quantum Black – AI by McKinsey, 2022. https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-data-driven-enterprise-of-2025 (accessed 30 August 2023).
  7. Authors. Knowledge Transfer and Diffusion in Vertically Coordinated Agri-Food Supply Networks. Manuscript accepted for publication. Knowledge Management in Business. Palgrave Intersections of Business and the Sciences, in Association with Gnosis Mediterranean Institute for Management Science. Springer Nature. (Forthcoming).
  8. A.L. Barabási, R. Albert, The emergence of scaling in random networks, Science 286 (1999) 509–512.
  9. A. Bastard, A. Chaillet, Blockchain: No pain, no gain? An examination of blockchain technology in the vitivinicultural sector, BIO Web Conf. 68 (2023) 03009.
  10. V. Belaya, J.H. Hanf, Managing Russian agri-food supply chain networks with power, J. Chain Netw. Sci. 12 (2012) 215–230.
  11. J. Botkin, C. Seeley, The knowledge management manifesto, Knowl. Manag. Rev. 3 (2001) 16–21.
  12. A. Capaldo, I. Giannoccaro, Interdependence and network-level trust in supply chain networks: A computational study, Ind. Mark. Manag. 44 (2015) 180–195.
  13. H.W. Chesbrough, Open innovation: The new imperative for creating and profiting from technology, Harvard Business Press, Boston, 2003.
  14. D. Choi, C.Y. Chung, T. Seyha, J. Young, Factors affecting organizations’ resistance to the adoption of blockchain technology in supply networks, Sustainability 12(21) (2020) 8882.
  15. R. Cowan, N. Jonard, Network structure and the diffusion of knowledge, J. Econ. Dyn. Control 28(8) (2004) 1557–1575.
  16. L. Cricelli, R. Mauriello, S. Strazzullo, Exploring blockchain adoption in the Italian wine industry: insights from a multiple case study, Wine Econ. Policy 13(2) (2024) 89–104.
  17. P.R. de Sousa, J.M. de Castro, C.F. Gohr, M.W. Barbosa, Knowledge transfer based on disseminative capacity, absorptive capacity, and learning: a comparative study between Brazil and Germany, Learn. Organ. 30(2) (2023) 181–213. https://doi.org/10.1108/TLO-03-2022-0037.
  18. N. Depetris Chauvin, J.J. Elias, G. Ferro, N. Gatti, E.C. Villanueva, The impact of innovator types on export performance in the Argentine wine industry. Journal of Entrepreneurship in Emerging Economies (2025).
  19. C. Dremel, J. Wulf, M.M. Herterich, J.C. Waizmann, W. Brenner, How AUDI AG established big data analytics in its digital transformation, MIS Q. Execut. 16(2) (2017).
  20. G. Duysters, K.H. Heimeriks, J.A. Jurriëns, An integrated perspective on alliance management, J. Chain Netw. Sci. 4(2) (2004) 83–94.
  21. J.S. Edwards, Knowledge management concepts and models, Adv. Knowl. Manag.: Celebrating Twenty Years Res. Pract. (2014) 25–44.
  22. A. Gardeazabal, T. Lunt, M.M. Jahn, N. Verhulst, J. Hellin, B. Govaerts, Knowledge management for innovation in agri-food systems: a conceptual framework, Knowl. Manag. Res. Pract. 21(2) (2023) 303–315.
  23. F. Garcia, B. Grabot, G. Paché, Creating and sharing interorganizational knowledge through a supply chain 4.0 project: A case study, J. Glob. Inf. Manag. 31(1) (2023) 1–19.
  24. S. Gourlay, Towards conceptual clarity for ‘tacit knowledge’: a review of empirical studies, Knowl. Manag. Res. Pract. 4 (2006) 60–69.
  25. R. Grandinetti, The explicit dimension: What we could not learn from Polanyi, Learn. Organ. 21(5) (2014) 333–346.
  26. R. Grandinetti, Absorptive capacity and knowledge management in small and medium enterprises, Knowl. Manag. Res. Pract. 14 (2016) 159–168.
  27. M.S. Granovetter, The strength of weak ties, Am. J. Sociol. 78(6) (1973) 1360–1380.
  28. R. Gulati, Strategic networks, Strateg. Manag. J. 21(3) (2000) 203–215.
  29. J.H. Hanf, Supply Chain Networks: Analysis based on strategic management theories and institutional economics, Proc. IAMO-Forum, Agric. Food Mark. Cent. East. Eur., Halle (Saale), Germany, 2005.
  30. E.J. Hearnshaw, M.M. Wilson, A complex network approach to supply chain network theory, Int. J. Oper. Prod. Manag. 33(4) (2013) 442–469.
  31. P. Holme, B.J. Kim, Growing scale-free networks with tunable clustering, Phys. Rev. E 65(2) (2002) 026107.
  32. I. Ilvonen, S. Thalmann, M. Manhart, C. Sillaber, Reconciling digital transformation and knowledge protection: A research agenda, Knowl. Manag. Res. Pract. 16(2) (2018) 235–244.
  33. A.C. Inkpen, E.W. Tsang, Social capital, networks, and knowledge transfer, Acad. Manag. Rev. 30(1) (2005) 146–165.
  34. E. Jaakkola, Designing conceptual articles: four approaches, AMS Rev. 10(1) (2020) 18–26.
  35. K.B. Kahn, E.N. Maltz, J.T. Mentzer, Demand collaboration: effects on knowledge creation, relationships, and supply chain performance, J. Bus. Logist. 27(2) (2006) 191–221.
  36. R. Kaipia, H. Hartiala, Information‐sharing in supply chains: five proposals on how to proceed, Int. J. Logist. Manag. 17(3) (2006) 377–393.
  37. V. Knitsch, J. Welz, Digitale Affinität und Einsatz von digitalen Technologien im Wein-und Obstbau in Mitteldeutschland, 2021. https://publica.fraunhofer.de/bitstreams/d5be57d5-412c-430a-bf33-199d2b773125/download (accessed 7 February 2025).
  38. J. Leader, B. Shantz, H. Hall, T. Vinodrai, Disruptive technologies in the agri-food sector: A knowledge synthesis report, Univ. Waterloo, 2020. https://uwaterloo.ca/disruptive-technologies-economic-development/sites/default/files/uploads/documents/omafra_report-final.pdf (accessed 2 February 2025).
  39. M. Lezoche, J.E. Hernandez, M.D.M.E.A. Díaz, H. Panetto, J. Kacprzyk, Agri-food 4.0: A survey of the supply chains and technologies for the future agriculture, Comput. Ind. 117 (2020) 103187.
  40. U. Lichtenthaler, E. Lichtenthaler, Technology transfer across organizational boundaries: absorptive capacity and desorptive capacity, Calif. Manag. Rev. 53(1) (2010) 154–170.
  41. F. Liu, Y. Lu, P. Wang, Why knowledge sharing in scientific research teams is difficult to sustain: An interpretation from the interactive perspective of knowledge hiding behavior, Front. Psychol. 11 (2020) 537833.
  42. M. Lubell, M. Niles, M. Hoffman, Extension 3.0: Managing agricultural knowledge systems in the network age, Soc. Nat. Resour. 27(10) (2014) 1089–1103.
  43. D. Marchiori, M. Franco, Knowledge transfer in the context of inter-organizational networks: Foundations and intellectual structures, J. Innov. Knowl. 5 (2020) 130–139.
  44. M. Massaro, A. Moro, E. Aschauer, M. Fink, Trust, control and knowledge transfer in small business networks, Rev. Manag. Sci. 13 (2019) 267–301. https://doi.org/10.1007/s11846-018-0293-4.
  45. R.E. Mayer, Cognitive theory of multimedia learning, Camb. Handb. Multim. Learn. (2005) 31–48.
  46. F. Nickols, The tacit and explicit nature of knowledge: The knowledge in knowledge management, Knowl. Manag. Yearb. 2000–2001 (2013) 12–21.
  47. I. Nonaka, A dynamic theory of organizational knowledge creation, Organ. Sci. 5(1) (1994) 14–37.
  48. I. Nonaka, H. Takeuchi, The Knowledge-Creating Company: How Japanese Companies Create the Dynamics of Innovation, Oxford Univ. Press, London & New York, 1995.
  49. I. Nonaka, N. Konno, The Concept of 'Ba': Building a Foundation for Knowledge Creation, Calif. Manag. Rev. 40(3) (1998) 1–15.
  50. OIV, Digital trends applied to the vine and wine sector: A comprehensive report on the digitalisation of the sector, OIV Digital Transf. Observ. Hub, 2021. https://www.oiv.int/public/medias/8590/oiv-symposium-digital-observatory-hub-report.pdf (accessed 1 December 2024).
  51. G. Okhuysen, J.P. Bonardi, The challenges of building theory by combining lenses, Acad. Manag. Rev. 36(1) (2011) 6–11.
  52. S. Patare, S.V. Venkataraman, Strategies in supply chain competition: A game theoretic approach, Comput. Ind. Eng. 180 (2023) 109242.
  53. J. Perera, M.G. Bell, M.C. Bliemer, Network science approach to modelling the topology and robustness of supply chain networks: a review and perspective, Appl. Netw. Sci. 2(1) (2017) 1–25.
  54. K. Plangger, M. Montecchi, I. Danatzis, M. Etter, J. Clement, Strategic enablement investments: Exploring differences in human and technological knowledge transfers to supply chain partners, Ind. Mark. Manag. 91 (2020) 187–195.
  55. M. Polanyi, The Tacit Dimension, In Knowledge in organisations (2009) 135-146 Routledge.
  56. J.L. Rice, B.S. Rice, The applicability of the SECI model to multi-organisational endeavours: an integrative review. International Journal of Organisational Behaviour, 9(8), (2005) 671-682.
  57. J.K. Roehrich, K. Selviaridis, J. Kalra, W. Van der Valk, F. Fang, Interorganisational governance: a review, conceptualisation and extension, Production Planning & Control, Vol. 31 No. 6 (2020) 453–469. https://doi.org/10.1080/09537287.2019.1647364
  58. E.M. Rogers, Diffusion of innovations (5th ed.), New York, NY: Free Press (2003).
  59. M.A. Salam, S. Bajaba, The role of supply chain resilience and absorptive capacity in the relationship between marketing–supply chain management alignment and firm performance: A moderated-mediation analysis, J. Bus. Ind. Mark. 38(7) (2023) 1545–1561.
  60. C. Siong Choy, W. Kuan Yew, B. Lin, Criteria for measuring KM performance outcomes in organizations, Ind. Manag. Data Syst. 106(7) (2006) 917–936.
  61. P.F. Skilton, E. Bernardes, M. Li, S.A. Creek, The structure of absorptive capacity in three product development strategies, J. Supply Chain Manag. 56(3) (2020) 47–65.
  62. A.G. Sutcliffe, D. Wang, R.I. Dunbar, Modelling the role of trust in social relationships. ACM Transactions on Internet Technology (TOIT), 15(4) (2015) 1-24.
  63. M. Tantardini, F. Ieva, L. Tajoli, C. Piccardi, Comparing methods for comparing networks. Scientific reports, 9(1), (2019).
  64. D.J. Teece, G. Pisano, A. Shuen, Dynamic capabilities and strategic management, Strateg. Manag. J. 18(7) (1997) 509–533.
  65. G. Vijayan, N.H. Kamarulzaman, A. Mukherjee, S.K. Vaiappuri, Strategic Value Creation in a Supply Chain. In B. Christiansen (Ed.), Handbook of Research on Global Supply Chain Management (2016) 186-204. IGI Global. https://doi.org/10.4018/978-1-4666-9639-6.ch011
  66. R. Vuciterna, G. Ruggeri, S. Corsi, A. Facchi, O. Gharsallah, A bibliometric analysis of scientific literature on alternate wetting and drying (AWD). Paddy and Water Environment, 22(3), (2024) 415-430.
  67. J. Wang, J. Yang, An empirical study of employees’ tacit knowledge sharing behavior, J. Syst. Sci. Inf. 3(3) (2015) 264–278.
  68. J. Wang, H. Zhou, X. Sun, Y. Yuan, A novel supply chain network evolving model under random and targeted disruptions, Chaos Solitons Fractals 170 (2023) 113371.
  69. D. Weir, K. Hutchings, Cultural embeddedness and contextual constraints: knowledge sharing in Chinese and Arab cultures, Knowl. Process Manag. 12(2) (2005) 89–98.
  70. B. Wernerfelt, A resource‐based view of the firm, Strateg. Manag. J. 5(2) (1984) 171–180.
  71. C. Wu, Knowledge creation in a supply chain, Supply Chain Manag.: Int. J. 13(3) (2008) 245–250.
  72. S.A. Zahra, G. George, Absorptive capacity: A review, reconceptualization, and extension, Acad. Manag. Rev. 27(2) (2002) 185–203.
  73. X. Zhang, D.P. Van Donk, T. van der Vaart, The different impact of inter-organizational and intra-organizational ICT on supply chain performance, Int. J. Oper. Prod. Manag. 36(7) (2016) 803–824.