Skip to main content
Springer Nature Link
Log in

Process Modeling Recommender Systems

A Generic Data Model and Its Application to a Smart Glasses-based Modeling Environment

  • Research Paper
  • Published:
Business & Information Systems Engineering Aims and scope Submit manuscript

Abstract

The manual construction of business process models is a time-consuming, error-prone task and presents an obstacle to business agility. To facilitate the construction of such models, several modeling support techniques have been suggested. However, while recommendation systems are widely used, e.g., in e-commerce, these techniques are rarely implemented in process modeling tools. The creation of such systems is a complex task since a large number of requirements and parameters have to be taken into account. In order to improve the situation, the authors have developed a data model that can serve as a backbone for the development of process modeling recommender systems (PMRS). This article outlines the systematic development of this model in a stepwise approach using established requirements and validates it against a data model that has been reverse-engineered from a real-world system. In a last step, the paper illustrates an exemplary instantiation of the data model in a Smart Glasses-based modeling environment and discusses business process agility issues. The authors expect their contribution to provide a useful starting point for designing the data perspective of process modeling recommendation features that support business agility in process-intensive environments.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

References

  • Blinn N, Nüttgens M (2010) Empowering technical customer services with intelligent mobile applications: a contingency theory-based approach. In: Proceedings of the IFIP 8.2 Organizations and Society in Information Systems Pre-ICIS Workshop, St. Louis, Working Papers on Information Systems 10 (107)

  • Born M, Brelage C, Markovic I et al (2009) Auto-completion for executable business process models. Business process management workshops. Springer, Heidelberg, pp 510–515

    Chapter  Google Scholar 

  • Clever N, Holler J, Shitkova M, Becker J (2013) Towards Auto-Suggested Process Modeling Prototypical Development of an Auto-Suggest Component for Process Modeling Tools. In: Proceedings of the 5th International Workshop on Enterprise Modeling and Information Systems Architectures, St. Gallen, pp 133–145

  • Fellmann M, Heitmann C, Metzger D, Nobbe L, Thomas O (2015a) TKD 4.0 – Klassifikation, Einordnung und Bewertung der Einsatzpotenziale von Augmented-Reality-Anwendungen für den Technischen Kundendienst. In: Thomas O (ed): Living Lab Business Process Management Research Report No. 10, Osnabrück

  • Fellmann M, Zarvic N, Metzger D, Koschmider A (2015b) Requirements catalog for business process modeling recommender systems. In: Thomas O, Teuteberg F (eds) Proceedings of the 12th International Conference on Wirtschaftsinformatik, Osnabrück, pp 393-407

  • Fellmann M, Metzger D, Thomas O (2016) Data model development for process modeling recommender systems. In: 9th IFIP WG 8.1 Working Conference on the Practice of Enterprise Modeling, LNBIP 267, Skövde, pp 87–101

  • Henderson S, Feiner S (2011) Exploring the benefits of augmented reality documentation for maintenance and repair. IEEE Trans Vis Comput Graphics 17(10):1355–1368. https://doi.org/10.1109/TVCG.2010.245

    Article  Google Scholar 

  • Hornung T, Koschmider A, Lausen G (2008) Recommendation based process modeling support: method and user experience. In: Li Q, Spaccapietra S, Yu E, Olivé A (eds) Conceptual modeling - ER 2008. Lecture notes in computer science, vol 5231. Springer, Heidelberg

  • Jannaber S, Zobel B, Riehle DM, et al (2017) Development of a domain-specific language for run-time process modelling – making use of wearables in BPM. In: Eibl M, Gaedke M (eds) Informatik. https://doi.org/10.18420/in2017_85

  • Jannach D (2011) Recommender systems: an introduction. Cambridge University Press, New York

    Google Scholar 

  • Jannach D, Zanker M, Ge M, Gröning M (2012) Recommender systems in computer science and information systems – a landscape of research. In: Huemer C, Lops P (eds) E-commerce and web technologies. Springer, Heidelberg, pp 76–87

    Chapter  Google Scholar 

  • Koschmider A (2007) Ähnlichkeitsbasierte Modellierungsunterstützung für Geschäftsprozesse. Universität Karlsruhe, Fakultät für Wirtschaftswissenschaften, PhD thesis. KITopen ID 1000007208

  • Koschmider A, Hornung T, Oberweis A (2011) Recommendation-based editor for business process modeling. Data Knowl Eng 70(6):483–503. https://doi.org/10.1016/j.datak.2011.02.002

    Article  Google Scholar 

  • Kuschke T, Mäder P (2014) Pattern-based auto-completion of UML modeling activities. In: Proceedings of the 29th ACM/IEEE International Conference on Automated Software Engineering. ACM, New York, pp 551–556

    Google Scholar 

  • Lauesen S (2002) Software requirements: styles and techniques. Pearson Education, London

    Google Scholar 

  • Lerchner H, Stary C (2016) Model while you work: towards effective and playful acquisition of stakeholder processes. In: Proceedings of the 8th International Conference on Subject-oriented Business Process Management. ACM, New York, pp 1-10

  • Li Y, Cao B, Xu L et al (2014) An efficient recommendation method for improving business process modeling. IEEE Trans Ind Inform 10(1):502–513. https://doi.org/10.1109/TII.2013.2258677

    Article  Google Scholar 

  • Luftman J, Zadeh HS, Derksen B et al (2012) Key information technology and management issues 2011–2012: an international study. J Inf Technol 27(3):198–212. https://doi.org/10.1057/jit.2012.14

    Article  Google Scholar 

  • Luftman J, Zadeh HS, Derksen B et al (2013) Key information technology and management issues 2012–2013: an international study. J Inf Technol 28(4):354–366. https://doi.org/10.1057/jit.2013.22

    Article  Google Scholar 

  • Matijacic M, Fellmann M, Özcan D, et al (2013) Elicitation and consolidation of requirements for mobile technical customer services support systems – a multi-method approach. In: Proceedings of the 34th International Conference on Information Systems. Milan

  • Mazanek S, Minas M (2009) Business process models as a showcase for syntax-based assistance in diagram editors. In: Schürr A, Selic B (eds) Model driven engineering languages and systems. Springer, Heidelberg, pp 322–336

    Chapter  Google Scholar 

  • Mazanek S, Maier S, Minas M (2008) Auto-completion for diagram editors based on graph grammars. In: IEEE Symposium on visual languages and human-centric computing, pp 242–245

  • Melville P, Sindhwani V (2010) Recommender systems. In: Sammut C, Webb GI (eds) Encyclopedia of machine learning. Springer, New York, pp 829–838

    Google Scholar 

  • Metzger D, Niemöller C, Berkemeier L et al (2017) Vom Techniker zum Modellierer – Konzeption und Entwicklung eines Smart Glasses Systems zur Laufzeitmodellierung von Dienstleistungsprozessen. In: Thomas O, Nüttgens M, Fellmann M (eds) Smart service engineering. Springer Fachmedien, Wiesbaden, pp 193–213

    Chapter  Google Scholar 

  • Nielen A, Költer D, Mütze-Niewöhner S, Karla J, Schlick CM (2011) An empirical analysis of human performance and error in process model development. In: Jeusfeld M, Delcambre L, Ling TW (eds) Conceptual modeling – ER 2011. Lecture notes in computer science, vol 6998. Springer, Heidelberg

  • Niemöller C, Metzger D, Fellmann M, et al (2016) Shaping the future of mobile service support systems–ex-ante evaluation of smart glasses in technical customer service processes. In: Mayr, HC, Pinzger, M, (eds): Informatik von Menschen für Menschen (Informatik 2016) (LNI 259), Klagenfurt, pp 753-770

  • Niemöller C, Zobel B, Berkemeier L, et al (2017) Sind Smart Glasses die Zukunft der Digitalisierung von Arbeitsprozessen? Explorative Fallstudien zukünftiger Einsatzszenarien in der Logistik. In: Leimeister JM, Brenner W (eds): Proceedings of the 13th International Conference on Wirtschaftsinformatik, St. Gallen, pp 410-424

  • Ricci F, Rokach L, Shapira B (2011) Introduction to recommender systems handbook. In: Ricci F, Rokach L, Shapira B, Kantor PB (eds) recommender systems handbook. Springer, Boston, pp 1–35

    Chapter  Google Scholar 

  • Richardson C, Miers D (2013) The Forrester Wave™: business process management suites. Forrester Research

  • Sarshar K, Weber M, Loos P (2006) Einsatz der Informationsmodellierung bei der Einführung betrieblicher Standardsoftware: Eine empirische Untersuchung bei Energieversorgerunternehmen. Wirtschaftsinformatik 48(2):120–127

    Article  Google Scholar 

  • Sen S, Baudry B, Vangheluwe H (2010) Towards domain-specific model editors with automatic model completion. Simul 86(2):109–126. https://doi.org/10.1177/0037549709340530

    Article  Google Scholar 

  • Shahzad K, Elias M, Johannesson P (2010) Requirements for a business process model repository: a stakeholders’ perspective. In: Abramowicz W, Tolksdorf R (eds) Proceedings of the 13th international conference on business information systems. Springer, Heidelberg, pp 158–170

    Google Scholar 

  • Starner T, Mann S, Rhodes B et al (1997) Augmented reality through wearable computing. Presence Teleoper Virtual Environ 6(4):386–398

    Article  Google Scholar 

  • Thomas O (2005) Understanding the term reference model in information systems research: history, literature analysis and explanation. In: Business Process Management Workshops. Springer, Heidelberg, pp 484–496

  • Thomas O (2006) Management von Referenzmodellen: Entwurf und Realisierung eines Informationssystems zur Entwicklung und Anwendung von Referenzmodellen. Logos, Berlin

    Google Scholar 

  • Thomas O, Fellmann M (2009) Semantic process modeling – design and implementation of an ontology-based representation of business processes. Bus Inf Syst Eng 1(6):438–451

    Article  Google Scholar 

  • vom Brocke J, Simons A, Niehaves B, et al (2009) Reconstructing the giant: on the importance of rigour in documenting the literature search process. In: Proceedings of the 17th European Conference on Information Systems, Verona, pp 2206–2217

  • Weber B, Reichert M, Rinderle-Ma S (2008) Change patterns and change support features – enhancing flexibility in process-aware information systems. Data Knowl Eng 66(3):438–466. https://doi.org/10.1016/j.datak.2008.05.001

    Article  Google Scholar 

  • Webster J, Watson RT (2002) Analyzing the past to prepare for the future: writing a literature review. MIS Q 26(2):xiii–xxiii

    Google Scholar 

  • Wieloch K, Filipowska A, Kaczmarek M (2011) Autocompletion for business process modelling. In: Abramowicz W (ed) Proceedings of the 14th international conference on business information systems. Springer, Heidelberg, pp 30–40

    Google Scholar 

  • Wilmont I, Brinkkemper S, Weerd I, Hoppenbrouwers S (2010) Exploring intuitive modelling behaviour. In: Bider I, Halpin T, Krogstie J et al (eds) Enterprise, business-process and information systems modeling: proceedings of the 11th international workshop, and 15th international conference, CAiSE 2010, Hammamet. Springer, Heidelberg, pp 301–313

    Chapter  Google Scholar 

  • zur Muehlen M, Recker J, Indulska M (2007) Sometimes less is more: are process modeling languages overly complex? In: 11th International IEEE EDOC Conference Workshop, pp 197–204

Download references

Author information

Authors and Affiliations

  1. Institute of Computer Science, University of Rostock, Albert-Einstein-Str. 22, 18059, Rostock, Germany

    Michael Fellmann

  2. Information Management and Information Systems, Osnabrück University, Katharinenstr. 3, 49074, Osnabrück, Germany

    Dirk Metzger, Sven Jannaber,  Novica Zarvic &  Oliver Thomas

Authors
  1. Michael Fellmann
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Dirk Metzger
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Sven Jannaber
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Novica Zarvic
    View author publications

    You can also search for this author inPubMed Google Scholar

  5. Oliver Thomas
    View author publications

    You can also search for this author inPubMed Google Scholar

Corresponding author

Correspondence to Michael Fellmann.

Additional information

Accepted after two revisions by the editors of the special issue.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Fellmann, M., Metzger, D., Jannaber, S. et al. Process Modeling Recommender Systems. Bus Inf Syst Eng 60, 21–38 (2018). https://doi.org/10.1007/s12599-018-0517-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12599-018-0517-5

Keywords