This document summarizes research investigating how cultural context impacts representations of business process concepts in diagrams. Novice users from Slovenia and Ukraine were asked to draw depictions of concepts like "process", "message", and "error" based on definitions. Their drawings were analyzed qualitatively by clustering similar representations and quantitatively using measures like the number of unspecified depictions and average distance between drawings and standard representations. The results showed cultural differences in depictions of concepts like "cancel" and "error" that were less semantically transparent. The research aims to improve diagram design by understanding which representations are most intuitive across cultures.

1. An Empirical Investigation of the
Cultural Impacts on the Business
Process Concepts’ Representations
Gregor Polančič, Pavlo Brin, Saša Kuhar, Gregor Jošt, Jernej Huber
@ BPM CEE 2019

2. About Business Process Diagrams
• A business process diagram serves
several purposes including process
analysis, process-related
communication, and process
automation.
• Considering communication, modelers
must ensure that all participants
understand a process diagram in the
same way (i.e. effectiveness).

3. Do we communicate effectively?
Effective communication Still effective?
Communication is the act of conveying meanings from one entity or group to another
through the use of mutually understood signs, symbols, and semiotic rules.
https://ipfs.io/ipfs/QmXoypizjW3WknFiJnKLwHCnL72vedxjQkDDP1mXWo6uco/wiki/Models_of_communication.html

4. … in the context od diagrammatic communication
e.g. analyst e.g. process
participant
Interpreted
process
Interpreted
process
Level of matching
(Effectiveness)
Sign (i.e. elements) should be clear from its appearance alone!

5. … yet this is not always the case
5
Obelisk Fountain in
Schönbrunn errected in 1777 is
covered in hieroglyphs
purporting to tell the history of
the Habsburg dynasty.
However, these are spurious,
as hieroglyphs were not in
fact deciphered until 1822.

6. Semantic transparency
• “Very little is documented about why particular graphical conventions are used. Texts generally
state what a particular symbol means without giving any rationale for the choice of symbols or
saying why the symbol chosen is to be preferred to those already available. The reasons for
choosing graphical conventions are generally shrouded in mystery” (Hitchman,2002).
• “The key to designing visual notations that are understandable to naïve users is a property
called semantic transparency” (Caire et al.,2013), which means that the meaning (semantics) of a
sign is clear (i.e. intuitive, transparent) from its appearance alone.
Caire, P., Genon, N., Heymans, P., & Moody, D. L. (2013). Visual notation design 2.0: Towards user comprehensible
requirements engineering notations. In 2013 21st IEEE International Requirements Engineering Conference, RE 2013 -
Proceedings (pp. 115-124). [6636711] https://doi.org/10.1109/RE.2013.6636711

7. Objective of our research
• To investigate the intuitiveness of the representations of common
Business Process Concepts …
• … in a way that subjects were asked to visualize stated process
modeling concepts.
• RQ1: How would a ‘novice user’ visualize a common process model concept?
• E.g. message, escalation, error, cancel, process, time, etc.
• RQ2: How does the subjects’ (cultural) context impact the visualizations?
• Due to sings they meet in their environment.

8. Research approach
• A name and a definition of a process model concept were provided to subjects,
where their task was to draw a depiction for the stated process model concept.
• This „direction“ enabled us to receive alternative depictions (i.e. open question).
The concept of a:
message,
escalation, error,
cancel, process,
etc.
N. Goodman, Languages of Art: An Approach to a
Theory of Symbols. Oxford University Press, 1968.

9. Questionnaire (part 2 of 4)
Slovenian group of subjects
(n=87)
Ukrainian group of subjects
(n=23)
Students with no formal
training in process
modeling notations were
chosen, representing
proxies for novice users.

10. Qualitative data analysis
A cluster was established in the case that at least two signs (depictions) of the same concept
indicated a visual similarity (as specified subjectively by two experts).
1. acquiring individual
drawings
3. Combining drawings
of the same concept
4. Clustering of similar
representations
2. adding
subject s ID
Cluster A
Cluster B
|Cluster A| = 4
|Cluster B| = 3 Cardinality of a cluster

11. 3rd phase

12. 4th phase

13. Results

14. Depictions of the „Process“ concept
0% 10% 20% 30% 40% 50% 60% 70%
Shapes connected with arrows
Other
Shapes connected with lines
Arrow
Line with markers
Shapes
Stairs
Checklist
ALL [%] CG2 [%] CG1 [%]
Winner:
65% of
depictions
The most
common
single sign13% were
not
classified in
any cluster
Consistent
responses
CG1, CG2

15. Depictions of the „Message“ and „Time“ concepts
0% 20% 40% 60% 80%
Envelope
Callout
Postcard
Two communicating
persons
Other
ALL [%] CG1 [%] CG2 [%]
0% 20% 40% 60% 80%
Analog clock
Calendar
Date fields
Phrase "H:M:S"
Sand clock
Other
ALL [%] CG2 [%] CG1 [%]
Clear winner
61%
Consistent
with BPMN
Clear winner
58%
Consistent
with BPMN
Consistent
responses
CG1 and CG2

16. Depictions of the „Error“ and „Cancel“ concepts
0% 10% 20% 30% 40%
Bordered Xsign
Exclamation
X sign
Bordered exclamation
Phrase "Error"
Other
Question mark
Sad smiley
ALL [%] CG2 [%] CG1 [%]
0% 10% 20% 30% 40%
Bordered X sign
Other
X sign
Crossed arrow
Stop sign
Gap in line
Bordered exclamation
Pause sign
Crossed shape
Slash
Line drawn half of space
Persons with arrow
Exclamation
ALL [%] CG2 [%] CG1 [%]
/
No clear
winner
19% of
depictions
were
unclasiffied
Overlapping
depictions
No BPMN
depiction
Inconsistenc
ies between
CG1 and
CG2

17. Depictions of the „User“ and „Manual“ task concepts
0% 20% 40% 60%
Personal computer
Person and computer
Other
Computer and checkmark
Phrase "PC"
Computer mouse
Person
Magnifier
Document
ALL [%] CG2 [%] CG1 [%]
0% 10% 20% 30% 40%
Palm
Hand tool
Other
Crossed computer
Person
Pen and page
Person with hand tool
Pen
Crossed computer with
human
ALL [%] CG2 [%] CG1 [%]
Clear winner
Here is the
BPMN
depiction
Here is the
winning
BPMN
depiction
Inconsistencies
between
CG1 and CG2

18. Depictions of the „Automated service“ and „Program/script“ concepts
0% 10% 20% 30% 40% 50%
Other
Globe
Computer
Phrase "www" or "online"
Phrase "Auto"
Arrows in circle
Wheel
Application window
Shopping cart
Wifi
Chrome icon
Network of computers
Person and computer
ALL [%] CG2 [%] CG1 [%]
0% 10% 20% 30% 40%
Document with code
Other
Display with code
Tag symbol
Phrase ".exe"
Phrase "C++", "Script"
Application window
Code
Wheel
Square
Flowchart
ALL [%] CG2 [%] CG1 [%]
Inconsistent
depictions
The majority
were
unclassified
Here is
BPMN
depiction
BPMN
depiction
BPMN
depiction
for service!

19. How can we quantify these (qualitative) results?
• Which results are better / worse?
M1: Number [%] of unspecified depictions
M2: Number [%] of alternative representations (i.e. clusters)
M3: Average Distance 𝐴𝐷 = 𝑘=1
𝑆
𝑆 𝑘 − 𝑃
𝑆

20. Quantitative measures
Measures
Process
Message
Time/Date
Error
Cancel/
Interruption
Usertask
Manualtask
Automated
service
Program/
Script
Number of depictions CG1 83 90 107 97 87 87 86 84 87
CG2 23 23 28 23 23 23 23 23 23
CG1+CG2 106 113 135 120 110 110 109 107 110
M1: Number of unspecified
depictions
(less is preferred)
CG1 0 0 0 0 2 2 2 0 5
CG1 [%] 0% 0% 0% 0% 2% 2% 2% 0% 6%
CG2 0 0 0 0 0 0 1 3 2
CG2 [%] 0% 0% 0% 0% 0% 0% 4% 13% 9%
CG1+CG2 0 0 0 0 2 2 3 3 7
CG1+CG2 [%] 0% 0% 0% 0% 2% 2% 3% 3% 6%
M2: Number of alternative
representations (i.e. clusters)
(less is preferred)
CG1 5 4 4 5 8 8 4 10 8
CG2 3 4 4 5 4 2 5 3 4
CG1 ꓴ CG2 7 4 4 7 12 8 8 12 10
CG1 ∩ CG2 1 3 3 4 3 2 1 2 3
M3: Average Distance
(more is preferred)
CG1 53,3 45 44,7 10 15,2 50,9 20 6 31
CG1 [%] 64% 50% 42% 10% 17% 59% 23% 7% 36%
CG2 9,3 8 8 7 6,3 4 3 1 2
CG2 [%] 40% 35% 29% 30% 27% 17% 13% 4% 9%
CG1+CG2 65 57,3 58,3 22 15 62 28 6 36
CG1+CG2 [%] 61% 51% 43% 18% 14% 56% 26% 6% 33%
𝐴𝐷 = 𝑘=1
𝑆
𝑆 𝑘 − 𝑃
𝑆

21. Answering research questions
• RQ1: How would a ‘novice user’ visualize a common process model concept?
[16] N. Genon, P. Heymans, and D. Amyot, “Analysing the Cognitive Effectiveness of the BPMN 2.0 Visual Notation,” in
Proceedings of the Third International Conference on Software Language Engineering, Berlin, Heidelberg, 2011, pp. 377–396.

22. Answering research questions and implications
• RQ2: How does the subjects’ (cultural) context impact the visualization?
• In general, the symbols that were deemed semantically transparent
demonstrante a higher consensus between different cultural groups in
the case of most of the proposed symbols.
• High discrepancy between subjects groups (CG1, CG2)
• Cancel („gap in line“ vs. „X“)
• Error („X“ vs. „!“)
• Manual task („hand tool“ vs. „pen and page“)
In general, these were
less consistent
responses (low AD
values)
High AD values

23. Validity threats and Future work
• Specification of concepts (naming, translations, …).
• Clustering of depictions based on visual similarity.
• Validity of „quality“ measures (M1, M2, M3).
• Risks of generalization beyond the sample.
• This paper investigates only ¼ of the questionnaire.
• Drawing part, comprehension part, other concepts, open questions (why).
• Search for proper statistical analysis.
• Investigation of the effectiveness of „Tripple crown“ notations.

24. Thank you for your attetion!
Gregor.Polancic@um.si
Full paper is available as a Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 361).