**6. Conclusion**

seems to be an elements, which provides the BPF input conversion and pre-defined output generation. When quantifying the BPF with use of adequate linguistic set {[BPF (i, j)]}, three subordinated sets (subsets) might be postulated: (a) BPF transformation rule (b) BPF transformation function and (c) BPF external and internal metrics subset, while two types of transformation rules might be postulated: (a) rules overtaken from the firm or company internal or external environment and postulated via text in natural language - *overtaken rules* and (b) rules postulated based on BPF functionality evaluation – *derived rules*. This is the first extension of ARIS methodology. The second one is closely related to BP model views. The ARIS methodology postulates functional, process, data and organizational model view, however the BPLM methodology postulates information and knowledge-based support view (**Figure 5**). When comparing an information support view with standardized data view two principle differences might be observed. *The first difference* is closely related to BPF external and internal metrics, while there is defined so called *primary BPF external and internal metrics* and secondary one, while the primary BPF external and internal metrics deals with detailed data gained within

*Operations Management - Emerging Trend in the Digital Era*

**Figure 5.**

**210**

*Principal layout of BPL PD\_02 component - module d ynamic model. Source: The authors.*

The conclusion facts are concerned with modifying and extension of previously developed ARIS methodology and are described within discussion section. We would like to stress the main practical contribution of that system, which deals with a possibility or transformation rule derivation and presentation in form of TNL text, which might read the business analysts and BP managers as well, what generates an easier communication among them too.

Of course, the reader will not find any facts related to BP and BPF simulation and optimization, while those problems are closely related to our research work in the near future. The same is concerned with BP configuration and execution problems being solved within BP implementation and controlling. All the abovementioned aspects represent objectives of the research work in the near future.

#### **Acknowledgements**

This work was supported by the Grant Agency of Slovak Republic – VEGA grant no. 1/0339/20 " Hidden Markov Model Utilization in Financial Modeling This work was supported by the Grant Agency of Slovak Republic – KEGA grant no. 019EU-4/2020 Support of distance education through a virtual department.This work was supported by the Štefan Kassy Foundation and support for science and education.

**References**

2009

[1] Aldin, L., & Cesare, S.D. A Comparative Analysis Of

Business Process Modelling Techniques.

*DOI: http://dx.doi.org/10.5772/intechopen.95350*

[11] Gruninger Michael, Schlenoff Craig, "Process Specification Language (PSL):

implementation", Proceedings of IMECE: International Mechanical Engineering Congress and Exposition,

[12] Stašák, J. Business Process Quantification and Modelling – Linguistic Approach – Several Theoretical Aspects American

International Journal of Contemporary Research (AIJCR) 2012,(4):85–100

[13] Stasak J. Business Process Linguistic Modeling – Philosophy & Principles. Computer Science and Information Technology. 2015;3(5):198–213.

[14] Stasak J, Vanickova R, Grell M. Business Process Modeling Linguistic Approach – Problems of Business Strategy Design. Universal Journal of Management. 2015;3(7):271–82.

[15] Schmidt P, Stašák J. Business process modelling linguistic approach application in public administration (self-governmental). International Journal of Business Performance Management. 2018;19(2):209.

[16] Stašák, J., Mazùrek, J. System of Data Transfer from and to Social and Economic Processes via Creative Economy Networks created based on Cultural Heritage Administration Processes andvice versa. IntechOpen

[17] Stašák, J., Schmidt , Kultán, J. Mukhammedova U. Business Process Linguistic Modelling –Theory and Practice Part I: BPLM Strategy Creator

[18] Stoklasa J. Linguistic models for decision support [Internet]. Etusivu. Lappeenranta University of Technology; 2014 [cited 2020Nov28]. Available

IntechOpen 2020, In print

2020

results of the first pilot

pp 1–10, 1999.

*Business Process Linguistic Modeling: Theory and Practice Part II: BPLM Business Process…*

[2] Sheer A. ARIS-business process modelling. Springer Verlag; 2000.

[3] Stašák, J. (2010). Modelovanie procesov podnikania s využitím aplikačného programu Aris. Ekonom.

[4] Scheer. Die Prozess-Experten. [Internet]. Scheer GmbH. [cited 2020Nov28]. Available from: http://

[5] Friedrich F, Mendling J, Puhlmann F. Process Model Generation from Natural Language Text. Notes on Numerical Fluid Mechanics and Multidisciplinary Design Active Flow and Combustion

www.ids-scheer.com/

Control 2018. 2011;:482–96.

SBSI'18. 2018;

2005;:83–117.

**213**

1.0 specification. 2000;

[6] Bordignon ACDA, Thom LH, Silva TS, Dani VS, Fantinato M, Ferreira RCB. Natural Language Processing in Business Process Identification and Modeling. Proceedings of the XIV Brazilian Symposium on Information Systems -

[7] Schlenoff C, Gruninger M, Tissot F, Valois J, Lee J. The Process Specification Language (PSL) overview and version

[8] De Nicola A, Lezoche M, Missikoff: M. 3rd IICAI 2007: Pune, India. Pune, India: dblp; 2007. p. 1794–813.

[10] Fengel J. Semantic technologies for aligning heterogeneous business process models. Business Process Management

[9] Engels G, Förster A, Heckel R, Thöne S. Process Modeling using UML. Process-Aware Information Systems.

Journal. 2014;20(4):549–70.
