Skip to main content
Log in

CMMN evaluation: the modelers’ perceptions of the main notation elements

  • Regular Paper
  • Published:
Software and Systems Modeling Aims and scope Submit manuscript

Abstract

Case Management Model and Notation (CMMN) has been introduced as a graphical modeling language targeting the modeling of human-centric processes. Despite its growing reputation since 2016, when the OMG standant was released, the usage and the adoption potential of CMMN is not yet evaluated. The goal of this paper is to evaluate CMMN language and the contribution of its main notation elements to its future adoption, based on the experience of modelers. A CMMN workshop was conducted, where groups of modelers modeled two different human-centric, real-world processes with CMMN. The effectiveness and efficiency of the language and modelers’ usage experience were evaluated. Their perception of the role of the CMMN notation elements to their future adoption CMMN have been recorded through a survey. A multi-criteria decision making method (Analytic Hierarchy Process–AHP) was utilized for analyzing the answers and generating the results. The evaluation results showed that CMMN language could be adopted for modeling non-structural processes and the study participants showed a positive attitude towards adopting CMMN driven by the fact that they overall perceived it as useful. To the best of our knowledge, this is the first attempt to evaluate CMMN language’s usability and prospects of adoption. Moreover, this is the first empirical study that explores the syntax of a process modeling language and its effect on its usage and adoption. Overall, since interest in CMMN is increasing, this work could inspire future researchers and practitioners to further explore the CMMN usage and adoption potential.

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

Access this article

Subscribe and save

Springer+ Basic
EUR 32.99 /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.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

Notes

  1. https://github.com/ioannisroutis/SoSyM_Journal_CMMN.

  2. https://github.com/gdede-hua/decision-survey-platform.

References

  1. Alexopoulou, N., Nikolaidou, M., Kanellis, P., Mantzana, V., Anagnostopoulos, D., Martakos, D.: Infusing agility in business processes through an event-centric approach. Int. J. Bus. Inf. Syst. 6(1), 58–78 (2010). https://doi.org/10.1504/IJBIS.2010.034005

    Article  Google Scholar 

  2. Bider, I.: Towards process improvement for case management: an outline based on viable system model and an example of organizing scientific events. Lecture Notes Bus. Inf. Process. 256, 96–107 (2016). https://doi.org/10.1007/978-3-319-42887-1_9

    Article  Google Scholar 

  3. Birkmeier, D., Overhage, S.: Is BPMN really first choice in joint architecture development? an empirical study on the usability of BPMN and UML activity diagrams for business users. In: International Conference on the Quality of Software Architectures, Springer, pp 119–134 (2010)

  4. Breitenmoser, R., Keller, T.: Case management model and notation-a showcase. Eur. Sci. J. 11(25), (2015)

  5. Bruno, G.: Tasks and assignments in case management models. Proc. Comput. Sci. 100, 156–163 (2016), https://doi.org/10.1016/j.procs.2016.09.135, http://linkinghub.elsevier.com/retrieve/pii/S1877050916323031

  6. Bruno, G.: Extending CMMN with entity life cycles. Proc. Comput. Sci. 121, 98–105 (2017)

    Article  Google Scholar 

  7. Bule, M.K., Polančič, G., Huber, J., Jošt, G.: Semiotic clarity of case management model and notation (CMMN). Comput. Stand. Interfaces (2019)

  8. Cabała, P.: Using the analytic hierarchy process in evaluating decision alternatives. Oper. Res. Decis. 20(1), 5–23 (2010)

    MathSciNet  Google Scholar 

  9. de Carvalho, R.M., Mili, H., Boubaker, A., Gonzalez-Huerta, J., Ringuette, S.: On the analysis of CMMN expressiveness: revisiting workflow patterns. In: 2016 IEEE 20th International Enterprise Distributed Object Computing Workshop (EDOCW), IEEE, pp 1–8, (2016)

  10. Cortes-Cornax, M., Dupuy-Chessa, S., Rieu, D., Mandran, N.: Evaluating the appropriateness of the BPMN 2.0 standard for modeling service choreographies: using an extended quality framework. Softw. Syst. Model. 15(1), 219–255 (2016)

    Article  Google Scholar 

  11. Czepa, C., Tran, H., Zdun, U., Kim, T.T.T., Weiss, E., Ruhsam, C.: Towards structural consistency checking in adaptive case management. Lect. Notes Bus. Inf. Process. 256, 90–95 (2016). https://doi.org/10.1007/978-3-319-42887-1_8

    Article  Google Scholar 

  12. Dede, G., Kamalakis, T., Varoutas, D.: Evaluation of optical wireless technologies in home networking: an analytical hierarchy process approach. IEEE/OSA J. Opt. Commun. Network. 3(11), 850–859 (2011)

    Article  Google Scholar 

  13. Dede, G., Kamalakis, T., Sphicopoulos, T.: Convergence properties and practical estimation of the probability of rank reversal in pairwise comparisons for multi-criteria decision making problems. Eur. J. Oper. Res. 241(2), 458–468 (2015)

    Article  MathSciNet  Google Scholar 

  14. Dede, G., Kamalakis, T., Sphicopoulos, T.: Theoretical estimation of the probability of weight rank reversal in pairwise comparisons. Eur. J. Oper. Res. 252(2), 587–600 (2016)

    Article  Google Scholar 

  15. van Der Aalst, W.M.: Workflow patterns. Encyclopedia of Database Systems pp 3557–3558, (2009)

  16. Dikici, A., Turetken, O., Demirors, O.: Factors influencing the understandability of process models: A systematic literature review. Inf. Softw. Technol. 93, 112–129 (2018)

    Article  Google Scholar 

  17. Estrada, H., Rebollar, A.M., Pastor, O., Mylopoulos, J.: An empirical evaluation of the i* framework in a model-based software generation environment. In: International Conference on Advanced Information Systems Engineering, Springer, pp 513–527, (2006)

  18. Figl, K.: Comprehension of procedural visual business process models. Bus. Inf. Syst. Eng. 59(1), 41–67 (2017)

    Article  Google Scholar 

  19. Gemino, A., Wand, Y.: A framework for empirical evaluation of conceptual modeling techniques. Requir. Eng. 9(4), 248–260 (2004)

    Article  Google Scholar 

  20. Gruhn, V., Laue, R.: Adopting the cognitive complexity measure for business process models. In: Cognitive Informatics, 2006. ICCI 2006. 5th IEEE International Conference on, IEEE, vol 1, pp 236–241, (2006a)

  21. Gruhn, V., Laue, R.: Complexity metrics for business process models. In: 9th international conference on business information systems (BIS 2006), Citeseer, vol 85, pp 1–12, (2006b)

  22. Guizzardi, R.S., Franch, X., Guizzardi, G., Wieringa, R.: Ontological distinctions between means-end and contribution links in the i* framework. In: International Conference on Conceptual Modeling, Springer, pp 463–470, (2013)

  23. Hasić, F., De Craemer, A., Hegge, T., Magala, G., Vanthienen, J.: Measuring the complexity of DMN decision models. In: International Conference on Business Process Management, Springer, pp 514–526, (2018)

  24. Herzberg, N., Kirchner, K., Weske, M.: Modeling and monitoring variability in hospital treatments: a scenario using CMMN. In: International Conference on Business Process Management, Springer, pp 3–15, (2014)

  25. Hewelt, M., Wolff, F., Mandal, S., Pufahl, L., Weske, M.: Towards a methodology for case model elicitation. In: Enterprise, Business-Process and Information Systems Modeling, pp. 181–195. Springer (2018)

  26. Horkoff, J., Yu, E., Ghose, A.: Interactive goal model analysis applied–systematic procedures versus ad hoc analysis. In: IFIP Working Conference on The Practice of Enterprise Modeling, Springer, pp 130–144, (2010)

  27. Horkoff, J., Aydemir, F.B., Li, F.L., Li, T., Mylopoulos, J.: Evaluating modeling languages: an example from the requirements domain. In: International Conference on Conceptual Modeling, Springer, pp 260–274, (2014)

  28. Houy, C., Fettke, P., Loos, P.: On the theoretical foundations of research into the understandability of business process models. In: ECIS, (2014)

  29. Kleppe, A.: A language description is more than a metamodel. In: Fourth international workshop on software language engineering, megaplanet. org, vol 1, (2007)

  30. Kluza, K.: Measuring complexity of business process models integrated with rules. In: International Conference on Artificial Intelligence and Soft Computing, Springer, pp 649–659, (2015)

  31. Kocbek, M., Jost, G., Hericko, M., Polancic, G.: Business process model and notation: the current state of affairs. Comput. Sci. Inf. Syst. 12(2), 509–539 (2015)

    Article  Google Scholar 

  32. Krogstie, J.: Evaluating UML using a generic quality framework. In: UML and the Unified Process, IGI Global, pp 1–22, (2003)

  33. Kurz, M., Schmidt, W., Fleischmann, A., Lederer, M.: Leveraging CMMN for ACM: examining the applicability of a new omg standard for adaptive case management. In: Proceedings of the 7th International Conference on Subject-Oriented Business Process Management, ACM, p 4, (2015)

  34. Marin, M.A., Lotriet, H., Van Der Poll, J.A.: Metrics for the case management modeling and notation (CMMN) specification. In: Proceedings of the 2015 Annual Research Conference on South African Institute of Computer Scientists and Information Technologists, ACM, New York, SAICSIT ’15, pp 28:1–28:10, (2015), https://doi.org/10.1145/2815782.2815813

  35. Marin, M.A., Hauder, M., Matthes, F.: Case management: an evaluation of existing approaches for knowledge-intensive processes. In: International Conference on Business Process Management, Springer, pp 5–16, (2016)

  36. Matulevičius, R., Heymans, P.: Comparing goal modelling languages: An experiment. In: International Working Conference on Requirements Engineering: Foundation for Software Quality, Springer, pp 18–32, (2007)

  37. Moody, D.L., Heymans, P., Matulevicius, R.: Improving the effectiveness of visual representations in requirements engineering: An evaluation of i* visual syntax. In: 2009 17th IEEE International Requirements Engineering Conference, IEEE, pp 171–180, (2009)

  38. Motahari-Nezhad, H.R., Swenson, K.D.: Adaptive case management: Overview and research challenges. In: 2013 IEEE 15th Conference on Business Informatics, IEEE, pp 264–269, (2013)

  39. Mu, E., Pereyra-Rojas, M.: Understanding the analytic hierarchy process. In: Practical decision making, Springer, pp 7–22, (2017)

  40. Mundbrod, N., Kolb, J., Reichert, M.: Towards a system support of collaborative knowledge work. In: International Conference on Business Process Management, Springer, pp 31–42, (2012)

  41. Object Management Group (2015) Unified Modeling Language v2.5. https://www.omg.org/spec/UML/2.5/About-UML/

  42. Object Management Group (2016) Case Management Model and Notation v1.1. http://www.omg.org/spec/CMMN/1.1

  43. Recker, J., Indulska, M., Green, P.: Extending representational analysis. BPMN user and developer perspectives. In: International Conference on Business Process Management, Springer, pp 384–399, (2007)

  44. Recker, J.C.: Understanding process modelling grammar continuance: a study of the consequences of representational capabilities. PhD thesis, Queensland University of Technology, (2008)

  45. Rolón, E., García, F., Ruiz, F., Piattini, M., Visaggio, C.A., Canfora, G.: Evaluation of BPMN models quality - a family of experiments. In: International Conference on Evaluation of Novel Approaches to Software Engineering, SCITEPRESS, Vol, 2, pp. 56–63 (2008)

  46. Rolón, E., Chavira, G., Orozco, J., Soto, J.P.: Towards a framework for evaluating usability of business process models with BPMN in health sector. Proc. Manuf. 3, 5603–5610 (2015)

    Google Scholar 

  47. Routis, I., Nikolaidou, M., Anagnostopoulos, D.: Using CMMN to model social processes. In: International Conference on Business Process Management, Springer, pp 335–347, (2017)

  48. Routis, I., Nikolaidou, M., Anagnostopoulos, D.: Modeling collaborative processes with CMMN: success or failure? an experience report. In: Enterprise, Business-Process and Information Systems Modeling, pp. 199–210. Springer (2018)

  49. Routis, I., Nikolaidou, M., Alexopoulou, N.: Exploring business process agility from the designer’s perspective: The case of CMMN. In: New Perspectives on Information Systems Modeling and Design, IGI Global, pp 20–40, (2019)

  50. Routis, I., Nikolaidou, M., Anagnostopoulos, D.: Empirical evaluation of CMMN models: a collaborative process case study. Softw. Syst. Model. (2020). https://doi.org/10.1007/s10270-020-00802-9

    Article  Google Scholar 

  51. Rubinstein, R.Y., Kroese, D.P.: Simulation and the Monte Carlo method, vol. 10. Wiley, New York (2016)

    Book  Google Scholar 

  52. Saaty, T.L.: Decision making with the analytic hierarchy process. Int. J. Serv. Sci. 1(1), 83–98 (2008)

    Google Scholar 

  53. Saaty, T.L., Vargas, L.G.: Inconsistency and rank preservation. J. Math. Psychol. 28(2), 205–214 (1984)

    Article  MathSciNet  Google Scholar 

  54. dos Santos Soares, M., Vrancken, J.L.: Evaluation of UML in practice-experiences in a traffic management systems company. In: ICEIS (3), pp 313–319, (2009)

  55. Schalles, C.: Usability evaluation of modeling languages: an empirical research study. PhD thesis, Cork Institute of Technology, (2013), https://doi.org/10.1007/978-3-658-00051-6

  56. Scheit, S., Ploom, T., O’Reilly, B., Glaser, A.: Automated Event Driven Dynamic Case Management. Proceedings - IEEE International Enterprise Distributed Object Computing Workshop, EDOCW 2016-Septe:62–71, (2016), https://doi.org/10.1109/EDOCW.2016.7584350

  57. Si-Saïd, S., Akoka, J., Comyn-Wattiau, I.: Measuring UML conceptual modeling quality-method and implementation. Actes des 18èmes Journées Bases de données Avancées (BDA02), (2002)

  58. Siau, K.: An analysis of unified modeling language (UML) graphical constructs based on bww ontology. J. Database Manage. 21(1), 1–8 (2010)

    Article  Google Scholar 

  59. Silver, B.: CMMN Method and Style: A Practical Guide to Case Management Modeling for Documentation and Execution. Cody-Cassidy Press, (2020), https://books.google.gr/books?id=bmh7zQEACAAJ

  60. Stake, R.E.: The art of case study research. Sage, (1995)

  61. Teruel, M.A., Navarro, E., López-Jaquero, V., Montero, F., Jaen, J., González, P.: Analyzing the understandability of requirements engineering languages for cscw systems: A family of experiments. Inf. Softw. Technol. 54(11), 1215–1228 (2012)

    Article  Google Scholar 

  62. Vogel-Heuser, B., Braun, S., Kormann, B., Friedrich, D.: Implementation and evaluation of UML as modeling notation in object oriented software engineering for machine and plant automation. IFAC Proc. Vol. 44(1), 9151–9157 (2011)

    Article  Google Scholar 

  63. Wahl, T., Sindre, G.: An analytical evaluation of BPMN using a semiotic quality framework. In: Advanced Topics in Database Research, Volume 5, IGI Global, pp. 94–105, (2006)

  64. Wand, Y., Weber, R.: On the ontological expressiveness of information systems analysis and design grammars. Inf. Syst. J. 3(4), 217–237 (1993)

    Article  Google Scholar 

  65. Wiemuth, M., Junger, D., Leitritz, M., Neumann, J., Neumuth, T., Burgert, O.: Application fields for the new object management group (omg) standards case management model and notation (CMMN) and decision management notation (DMN) in the perioperative field. Int. J. Comput. Assist. Radiol. Surg. 12(8), 1439–1449 (2017)

    Article  Google Scholar 

  66. Wohed, P., van der Aalst, W.M., Dumas, M., ter Hofstede, A.H., Russell, N.: On the suitability of BPMN for business process modelling. In: International conference on business process management, Springer, pp 161–176, (2006)

  67. Yin, R.K.: Case study research: Design and methods 4th edition. In: United States: Library of Congress Cataloguing-in-Publication Data, (2009)

  68. Yin, R.K.: Case study research and applications: Design and methods. Sage publications, (2017)

  69. Zensen, A., Küster, J.: A comparison of flexible BPMN and CMMN in practice: a case study on component release processes. In: 2018 IEEE 22nd International Enterprise Distributed Object Computing Conference (EDOC), IEEE, pp 105–114, (2018)

Download references

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Ioannis Routis or Thomas Kamalakis.

Additional information

Communicated by Timothy Lethbridge.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendices

Appendix A: Cases description

1.1 A.1 Patient treatment

To begin with, the patient is admitted to a hospital’s Medicine Clinic if he/she needs to be hospitalized, a decision that is taken at the Emergency Department. The Emergency Department personnel provide the physicians of the clinic with information regarding the clinical status of the patient, such as medical history and any examinations that have been done or scheduled.

Based on this initial information, the physicians of the Medicine Clinic start the treatment of the patient. They specify a diagnosis for the patient and prescribe the medication accordingly. Such information is registered into the patient’s file. During treatment, a clinical examination takes place every morning by the physicians, aiming at monitoring the patient’s clinical course. To this end, laboratory and/or imaging examinations may be scheduled. The results, which are also registered into the patient’s file, are evaluated by the physicians and if necessary the diagnosis and medication are revised. There may be cases that the physicians will need to consult a specialist in order to conclude about the patient’s health problem or about the way the patient should be treated.

The nursing personnel aids in the treatment process through operations regarding, for example, the preparation and administration of the specified medication, blood drawing and measurements of vital signs. Medication administration and measurements are performed at the times specified by the physician. The measured values are written in the patient’s chart. Moreover, the nursing personnel keeps notes of anything remarkable regarding the patient, for example, a sign they observed, as well as of any action they performed by their own initiative, for example any ad-hoc medication they may have administered to the patient.

During treatment, several unexpected situations may arise, which may lead to ad hoc clinical, laboratory or imaging examinations, as well as to reconsideration of the medication administered or even of the diagnosis specified so far. The patient may need to be transferred to the Intensive Care Unit or to undergo an urgent surgery.

The need for a patient to remain hospitalized is daily examined after the morning clinical examination based on the data gathered up to that point. If it is decided that the patient does not need further hospitalization, the treatment process ends and the patient is discharged.

1.2 A.2 Product exchange

First of all, there are two types of users, i.e., guest and registered users that differentiate themselves in the permissions that they get granted regarding the use of the platform.

More specifically, when someone visits the web platform for the first time, he gets prompted to register, by creating a user account. This account can be created either by signing up via an email and a password or via a social network account. After a successful registration, the, from now on, registered platform user, is able to submit an advertisement donating or exchanging an item, to declare interest for an existing EE product and propose an offer to acquire it, as well as to communicate with any other user who owns a desirable electric device.

Moreover, a registered user is not only able to search a product based on some conditions, namely, filters like item categories, item state, donating-user region, but also to either suggest changes regarding the item’s category for which he/she is searching, or even to comment in an advertisement that he/she had expressed interest for. That way, the appropriate users will be notified for either the category change proposal or the commenting in an advertisement.

Finally, registered users have a profile in which they are able to be notified for any recycling actions taken via a news-feed as well as being informed for general topics regarding recycling and its benefits. Within each user’s profile, a calendar exists via which a user can be informed for any recycling events taking place.

Appendix B: Analytic hierarchy process

1.1 B.1 Methodology description

The AHP adopts a hierarchical form using three conceptual levels, as it is projected in Fig. 5. In the first level, the objective of the decision making process is defined. In the next level, the number of elements on which the evaluation will be based is identified. The various elements are denoted by \(E_{k}\), where k is an integer with \(1 \le k \le N\), and N is the total number of elements. In this paper we consider the CMMN elements. In the last level of the hierarchy we have the factors, denoted by \(F_{i}\), where i is an integer with \(1 \le i \le J\) and J the total number of factors. [12].

According to the AHP, in order to explore which of the CMMN elements contributes most towards the intention to adopt CMMN, then one must perform pairwise comparisons and evaluate the weights of importance of each CMMN element. In the same context, we have to explore the scores of each factor \(F_i\) for serving \(E_k\) Pairwise comparisons is a fundamental part of the AHP, according to which the participants compare the elements/factors in pairs instead of assigning their weights in a single step. This reduces the influence of subjective points of views, associated with eliciting the weights directly.

Each participant m (\(1 \le m \le M\), where M is the group of participants), compares all possible combinations of CMMN elements by filling out the N x N pairwise comparison matrix \(\mathbf{P} ^{( m )}\)=\([P_{ij}^{(m)}]\), the elements of which signify the importance of a CMMN element \(E_{i}\) compared to another CMMN element \(E_{j}\) towards Intention to Adopt CMMN, assigning values from the nine-level scale[12]. The participants need to complete only the upper triangular elements since PWC is a reciprocal matrix. The weights \(w_{k}^{(m)}\) of a CMMN element \(E_{k}\) according to participant m are calculated by solving the eigenvalue problem, according to which the eigenvalues of \(\mathbf{P} ^{( m )}\) are calculated and the eigenvector \(\mathbf{x} _1^{( m )}\) = \([ x_{1k}^{( m )} ]\) associated with the largest eigenvalue \(\lambda _{max}^{( m )}\) is determined [52]. The weight \(w_k^{( m )}\) are obtained normalizing the sum of the eigenvectors \(\mathbf{x} _1^{( m )}\) of the matrix to unity,

$$\begin{aligned} w_k^{(m)}=x_{1k}^{(m)}\left[ \sum _{l=1}^{N}x_{1l}^{(m)}\right] ^{-1} \end{aligned}$$
(1)

After all the comparisons have been completed, the average weight \(w_{k}\) for each element \(E_{k}\) is calculated by averaging out the weights \(w_{k}^{(m)}\) obtained by the M participants.

$$\begin{aligned} w_{k}=1/M\sum _{m=1}^{M}w_{k}^{(m)} \end{aligned}$$
(2)

Care should be taken so that the pairwise comparison matrices produced by the participants are as consistent as possible in terms of proportionality and transitivity [8]. The PWC matrix \(\mathbf{P} ^{(m)}\) is said to be perfectly consistent if all its elements are of the form \(P_{ij}^{(m)} = q_i^{(m)}/q_j^{(m)}\), where \(q_i^{(m)},q_j^{m}\) are positive real numbers.The consistency ratio (C.R.) is one measure for consistency can be readily obtained from the pairwise comparison matrices as described in [8]. In our case, the C.R. values were less than 0.1 (ranged between 0.015 to 0.076) which is considered acceptable [39].

The same procedure is followed for the factors of the second level of hierarchy. Towards this end, the factors are pairwise compared with respect to each element and for each factor \(F_{i}\) one obtains the relative scores \(S_{ik}\) under element \(E_{k}\), depicting the score of \(F_i\) for serving \(E_k\). Finally, one can evaluate to what extent each acceptance factor contribute to the Intention to Adopt CMMN, by multiplying the relative scores \(S_{ik}\) by the weight \(w_{k}\) of the corresponding element and estimate the overall weight \(R_i\).

$$\begin{aligned} R_{i}=\sum _{k=1}^{N}S_{ik}w_{k} \end{aligned}$$
(3)

1.2 B.2 AHP results verification

Changes of the group of participants. The AHP decision process, performed for the quantitative evaluation, involves pairwise comparisons commonly used in evaluation problems with a limited number of participants, since by augmenting the size of the participants beyond 15 there is no significant change in the final outcome [13]. As in our case there are 24 participants, it is very interesting to investigate the impact of modifying the group size of participants, from 24 to 15, on the AHP results. More specifically, it would be interesting to investigate the consistency of AHP results regarding the importance of elements towards the modelers intention to adopt CMMN, namely the results calculated with Eqs. 1 and 2. Such a verification would be very important as it is related with the objective of the evaluation, as it is projected in Fig. 5. In this context, we perform Monte Carlo simulations [51] of \(N_{MC}=10^5\) iterations. For each iteration z (\(z\le N_{MC}\)) we randomly ignore a group of 9 participants and estimate the average weights of elements \(W_k^{(z)}\) for the new group of \(M=15\) participants. Finally, we estimate the average weights from all iterations \(W_k\).

$$\begin{aligned} w_k= \frac{1}{N_{MC}}\sum _{z=1}^{N_{MC}}W_k^{(z)} \end{aligned}$$
(4)

Changes of elements and factors weights. In order to further validate the reliability of the final ranking of the factors for intention to adopt, given the level of uncertainties involved by carrying out a sensitivity analysis, Monte Carlo simulations are performed by simultaneously changing more than one parameters. The weights of all elements and the relative scores of factors are perturbed from \(w_k\), \(S_{ik}\) to \(w_{k}(1+\varDelta w_k)\), \(S_{ik}(1+\varDelta S_{ik})\), respectively, where the perturbations \(\varDelta w_k\), \(\varDelta S_{ik}\) are assumed zero mean, identically distributed, independent random variables uniformly distributed inside [\(-s s\)] [12]. Such random perturbation may be due to inconsistencies of the pairwise comparison matrices [53].

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Routis, I., Bardaki, C., Dede, G. et al. CMMN evaluation: the modelers’ perceptions of the main notation elements. Softw Syst Model 20, 2089–2109 (2021). https://doi.org/10.1007/s10270-021-00880-3

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10270-021-00880-3

Keywords

Navigation