Skip to main content
SpringerLink
Log in

A Knowledge-Graph Based Integrated Digital EA Maturity and Performance Framework

  • Conference paper
  • First Online:
Enterprise Design, Operations, and Computing. EDOC 2022 Workshops (EDOC 2022)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 466))

  • 340 Accesses

Abstract

Digitalisation is gaining considerable attention from enterprises aiming to improve their maturity and performance using digital enterprise architecture (EA). However, the challenge is how to assess and enhance often disconnected but related digital EA maturity and performance outcome elements. To address this research challenge, this paper proposes an integrated digital enterprise architecture maturity and performance (DEAMP) ontology. This ontology aims to assist organisations in understanding and assessing their digital maturity (DM) level and associated performance outcomes. This is important to understand whether there is a positive change in the performance level (effect) through improving a DM level (cause). A design science research (DSR) method, along with a skeletal enterprise modelling approach, have been used to develop and evaluate the proposed DEAMP ontology. Further, this ontology is represented as a knowledge graph (KG), which can be tailored and used by researchers and practitioners to capture and process DM and performance data for better outcomes as appropriate to their enterprise context and scope.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 54.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 69.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Morakanyane, R., O’Reilly, P., McAvoy, J.: Determining digital transformation success factors. In: Proceedings of the Annual Hawaii International Conference on System Sciences, pp. 4356–4365 (2020)

    Google Scholar 

  2. Gimpel, H., Hosseini, S., Huber, R., Probst, L., Röglinger, M., Faisst, U.: Structuring digital transformation: a framework of action fields and its application at ZEISS. J. Inf. Technol. Theory Appl. JITTA. 19, 3 (2018)

    Google Scholar 

  3. Hinings, B., Gegenhuber, T., Greenwood, R.: Digital innovation and transformation: an institutional perspective. Inf. Organ. 28, 52–61 (2018). https://doi.org/10.1016/j.infoandorg.2018.02.004

    Article  Google Scholar 

  4. Parviainen, P., Tihinen, M., Kääriäinen, J., Teppola, S.: Tackling the digitalization challenge: how to benefit from digitalization in practice. Int. J. Inf. Syst. Proj. Manag. 5, 63–77 (2017). https://doi.org/10.12821/ijispm050104

  5. Westerman, G., Bonnet, D., McAfee, A.: Leading Digital: Turning Technology into Business Transformation. Harvard Business Press (2014)

    Google Scholar 

  6. Alsufyani, N., Gill, A.Q.: Digitalisation performance assessment: a systematic review. Technol. Soc. 68, 101894 (2022). https://doi.org/10.1016/j.techsoc.2022.101894

    Article  Google Scholar 

  7. Alsufyani, N., Gill, A.Q.: A review of digital maturity models from adaptive enterprise architecture perspective: digital by design. In: 2021 IEEE 23rd Conference on Business Informatics (CBI), pp. 121–130. IEEE (2021)

    Google Scholar 

  8. Gill, A.Q.: Adaptive Enterprise Architecture as Information. World Scientific Publishing Co., Singapore (2022)

    Book  Google Scholar 

  9. Lee, M.: Enterprise architecture: beyond business and IT alignment. In: Advances in Intelligent Systems and Computing, pp. 57–66 (2013)

    Google Scholar 

  10. Ibrahim Alzoubi, Y.: Distributed agile development communication: an agile architecture driven framework. J. Softw. 681–694 (2015). https://doi.org/10.17706/jsw.10.6.681-694

  11. Uschold, M.: Building ontologies: towards a unified methodology. In: 16th Annual Conf. of the British Computer Society Specialist Group on Expert Systems, pp. 16–18 (1996)

    Google Scholar 

  12. Hogan, A., et al.: Knowledge graphs. ACM Comput. Surv. 54 (2021). https://doi.org/10.1145/3447772

  13. Aslanova, I.V., Kulichkina, A.I.: Digital maturity: definition and model. In: Proceedings of the 2nd International Scientific and Practical Conference “Modern Management Trends and the Digital Economy: from Regional Development to Global Economic Growth” (MTDE 2020), pp. 443–449. Atlantis Press, Paris, France (2020)

    Google Scholar 

  14. Becker, J., Knackstedt, R., Pöppelbuß, J.: Developing maturity models for IT management. Bus. Inf. Syst. Eng. 1, 213–222 (2009). https://doi.org/10.1007/s12599-009-0044-5

    Article  Google Scholar 

  15. Chanias, S., Hess, T.: How digital are we? Maturity models for the assessment of a company’s status in the digital transformation (2016)

    Google Scholar 

  16. Thordsen, T., Murawski, M., Bick, M.: How to measure digitalization? a critical evaluation of digital maturity models. In: Hattingh, M., Matthee, M., Smuts, H., Pappas, I., Dwivedi, Y.K., Mäntymäki, M. (eds.) I3E 2020. LNCS, vol. 12066, pp. 358–369. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-44999-5_30

    Chapter  Google Scholar 

  17. Poeppelbuss, J., Niehaves, B., Simons, A., Becker, J., Pöppelbuß, J.: Maturity models in information systems research: literature search and analysis. Commun. Assoc. Inf. Syst. 29, 505–532 (2011). https://doi.org/10.17705/1CAIS.02927

  18. Cao, M., Zhang, Q.: Supply chain collaboration: impact on collaborative advantage and firm performance. J. Oper. Manag. 29, 163–180 (2011). https://doi.org/10.1016/j.jom.2010.12.008

    Article  Google Scholar 

  19. Wardaya, A., Sasmoko, S. I.G., Bandur, A.: Mediating effects of digital technology on entrepreneurial orientation and firm performance: evidence from small and medium-sized enterprises (SMEs) in Indonesia. Int. J. Eng. Adv. Technol. 8, 692–696 (2019). https://doi.org/10.35940/ijeat.E1098.0585C19

  20. Kaplan, R.S., Norton, D.P.: The balanced scorecard–measures that drive performance. Harv. Bus. Rev. 70, 71–79 (1992)

    Google Scholar 

  21. Cross, K.F., Lynch, R.L.: The “SMART” way to define and sustain success. Natl. Product. Rev. 8, 23–33 (1988). https://doi.org/10.1002/npr.4040080105

    Article  Google Scholar 

  22. Fitzgerald, L, Johnston, R, Brignall, S, Silvestro, R., Voss, C.: Performance measurement in service businesses. Manag. Account. 34–36 (1991)

    Google Scholar 

  23. Hinkelmann, K., Gerber, A., Karagiannis, D., Thoenssen, B., Van Der Merwe, A., Woitsch, R.: A new paradigm for the continuous alignment of business and IT: combining enterprise architecture modelling and enterprise ontology. Comput. Ind. 79, 77–86 (2016). https://doi.org/10.1016/J.COMPIND.2015.07.009

    Article  Google Scholar 

  24. Hazen, B.T., Bradley, R.V., Bell, J.E., In, J., Byrd, T.A.: Enterprise architecture: a competence-based approach to achieving agility and firm performance. Int. J. Prod. Econ. 193, 566–577 (2017). https://doi.org/10.1016/J.IJPE.2017.08.022

    Article  Google Scholar 

  25. Alzoubi, Y.I., Gill, A.Q., Moulton, B.: A measurement model to analyze the effect of agile enterprise architecture on geographically distributed agile development. J. Softw. Eng. Res. Dev. 6(1), 1–24 (2018). https://doi.org/10.1186/s40411-018-0048-2

    Article  Google Scholar 

  26. Zachman, J.A.: A framework for information systems architecture. IBM Syst. J. 26, 276–292 (1987). https://doi.org/10.1147/sj.263.0276

    Article  Google Scholar 

  27. Andrew, J.: TOGAF® Version 9.1 – A Pocket Guide (2016)

    Google Scholar 

  28. Gill, A.Q.: Adaptive cloud enterprise architecture Intelligent Information Systems. World Scientific Publishing Co., Singapore (2015)

    Google Scholar 

  29. Gill, A.Q., Chew, E.: Configuration information system architecture: Insights from applied action design research. Inf. Manag. 56, 507–525 (2019). https://doi.org/10.1016/J.IM.2018.09.011

    Article  Google Scholar 

  30. Gill, A.Q.: Applying agility and living service systems thinking to enterprise architecture. Int. J. Intell. Inf. Technol. 10, 1–15 (1) (2014). https://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijiit.2014010101. https://doi.org/10.4018/IJIIT.2014010101

  31. Gill, A.Q., Beydoun, G., Niazi, M., Khan, H.U.: Adaptive architecture and principles for securing the IOT systems. In: Advances in Intelligent Systems and Computing, pp. 173–182. Springer, Cham (2020)

    Google Scholar 

  32. Westerman, G., Mcafee, A.: A Major Research Initiative at the MIT Sloan School of Management Research Brief the Digital Advantage: How Digital Leaders Outperform Their Peers in Every Industry (2012)

    Google Scholar 

  33. Park, Y., Saraf, N.: Investigating the complexity of organizational digitization and firm performance: a set-theoretic configurational approach. In: AMCIS 2016 Surfing IT Innov. Wave – 22nd Am. Conf. Inf. Syst., pp. 1–10 (2016)

    Google Scholar 

  34. Frederico, G.F., Nailor Pedrini, C., Francisco Frederico, G.: Information technology maturity evaluation in a large brazilian cosmetics industry. Int. J. Bus. Adm. 9, (2018). https://doi.org/10.5430/ijba.v9n4p15

  35. Tamm, T., Seddon, P.B., Shanks, G., Reynolds, P.: How does enterprise architecture add value to organisations? Commun. Assoc. Inf. Syst. 28, 141–168 (2011). https://doi.org/10.17705/1CAIS.02810

  36. Gruber, T.R.: A translation approach to portable ontology specifications. Knowl. Acquis. 5, 199–220 (1993). https://doi.org/10.1006/knac.1993.1008

    Article  Google Scholar 

  37. Guizzardi, G., Wagner, G., Almeida, J.P.A., Guizzardi, R.S.S.: Towards ontological foundations for conceptual modeling: the unified foundational ontology (UFO) story. Appl. Ontol. 10, 259–271 (2015). https://doi.org/10.3233/AO-150157

    Article  Google Scholar 

  38. Guizzardi, G., Halpin, T.: Ontological foundations for conceptual modelling. Appl. Ontol. 3, 1–12 (2008). https://doi.org/10.3233/AO-2008-0049

    Article  Google Scholar 

  39. Bellomarini, L., Fakhoury, D., Gottlob, G., Sallinger, E.: Knowledge graphs and enterprise AI: The promise of an enabling technology. In: Proceedings – International Conference on Data Engineering, pp. 26–37 (2019)

    Google Scholar 

  40. Pokorný, J.: Conceptual and Database Modelling of Graph Databases. (2016). https://doi.org/10.1145/2938503.2938547

    Article  Google Scholar 

  41. Smajevic, M., Bork, D.: From conceptual models to knowledge graphs: a generic model transformation platform. In: Companion Proceedings – 24th International Conference on Model-Driven Engineering Languages and Systems, MODELS-C 2021, pp. 610–614 (2021)

    Google Scholar 

  42. Medvedev, D., Shani, U., Dori, D.: Gaining insights into conceptual models: a graph-theoretic querying approach. Appl. Sci. 11, 765 (2021). https://doi.org/10.3390/app11020765

    Article  Google Scholar 

  43. Vaishnavi, V.K., Kuechler, W.: Design Science Research Methods and Patterns: Innovating Information and Communication Technology. Auerbach Publications, New York (2007)

    Book  Google Scholar 

  44. Smuts, H., Winter, R., Gerber, A., van der Merwe, A.: “Designing” design science research – a taxonomy for supporting study design decisions, pp. 483–495 (2022). https://doi.org/10.1007/978-3-031-06516-3_36

  45. Gregor, S., Hevner, A.R.: Positioning and presenting design science types of knowledge in design science research. MIS Q. 37, 337–355 (2013). https://doi.org/10.2753/MIS0742-1222240302

    Article  Google Scholar 

  46. Winter, R., Albani, A.: Restructuring the design science research knowledge base: a one-cycle view of design science research and its consequences for understanding organizational design problems. Des. Organ. Syst. An Interdiscip. Discourse. 1, 63–81 (2013). https://doi.org/10.1007/978-3-642-33371-2_4/FIGURES/10

    Article  Google Scholar 

  47. Pokorný, J.: Graph databases: their power and limitations. In: Saeed, K., Homenda, W. (eds.) CISIM 2015. LNCS, vol. 9339, pp. 58–69. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-24369-6_5

    Chapter  Google Scholar 

  48. Kaplan, R.S., Norton, D.P., Ansari, S.: The execution premium: linking strategy to operations for competitive advantage. Account. Rev. 85, 1475–1477 (2010). https://doi.org/10.2308/accr.2010.85.4.1475

    Article  Google Scholar 

  49. Yu, Y., Madiraju, S.: Enterprise application transformation strategy and roadmap design: a business value driven and IT supportability based approach. In: Proc. - 2nd Int. Conf. Enterp. Syst. ES 2014, pp. 66–71 (2014). https://doi.org/10.1109/ES.2014.37

  50. Serra, C.E.M., Kunc, M.: Benefits realisation management and its influence on project success and on the execution of business strategies. Int. J. Proj. Manag. 33, 53–66 (2015). https://doi.org/10.1016/J.IJPROMAN.2014.03.011

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. University of Technology Sydney, Ultimo, NSW, 2007, Australia

    Nujud Alsufyani & Asif Qumer Gill

Authors
  1. Nujud Alsufyani
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Asif Qumer Gill
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Nujud Alsufyani .

Editor information

Editors and Affiliations

  1. University of Twente, Enschede, The Netherlands

    Tiago Prince Sales

  2. TU Wien, Vienna, Austria

    Henderik A. Proper

  3. University of Twente, Enschede, The Netherlands

    Giancarlo Guizzardi

  4. Free University of Bozen-Bolzano, Bozen-Bolzano, Italy

    Marco Montali

  5. Free University of Bozen-Bolzano, Bolzano, Italy

    Fabrizio Maria Maggi

  6. University of Twente, Enschede, The Netherlands

    Claudenir M. Fonseca

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Alsufyani, N., Gill, A.Q. (2023). A Knowledge-Graph Based Integrated Digital EA Maturity and Performance Framework. In: Sales, T.P., Proper, H.A., Guizzardi, G., Montali, M., Maggi, F.M., Fonseca, C.M. (eds) Enterprise Design, Operations, and Computing. EDOC 2022 Workshops . EDOC 2022. Lecture Notes in Business Information Processing, vol 466. Springer, Cham. https://doi.org/10.1007/978-3-031-26886-1_13

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-26886-1_13

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-26885-4

  • Online ISBN: 978-3-031-26886-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation