Innovation in Human-Machine Interaction Agenda: 5:45 - 6:00: Welcome & Networking 6:00 - 6:15: News and Introduction 6:15 – 7:00: The value of applied research in human-system interaction in B2B environment 7:00 - 7:30: Panel: Review of new human-system interaction seen at CHI 2018 7:30 - 8:00: Networking

1. Data Science | Design | Technology
(May 1, 2018)
https://www.meetup.com/DSDTMTL
1

2. Agenda
5:45 - 6:00: Welcome
6:00 - 6:15: News & Introduction
6:15 - 7:00: The value of applied research in
human-system interaction
6:15 - 7:00: Panel CHI 2018
7:30 - 8:00: Networking + Q&A
2
Innovation in Human-Machine
Interaction

3. Other
events…….
• May 7: Montreal-Python meetup (Burning Yeti)
• May 14: Kubernetes meetup
• May 14: HackerNest Montreal
….. And much more…
• June 5: Next DSDT meetup
• Artificial Intelligence
• Guest speaker: Ubisoft La Forge
3

4. Prof. Pierre-Majorique Léger, Ph.D..
Titulaire de la Chaire de recherche industrielle
CRSNG-Prompt en expérience utilisateur
Co-directeur Tech3Lab, Directeur ERPsim Lab
The value of applied
research in human-system
interaction in B2B environment
Innovation in Human-Machine Interaction
Meetup, JDA Labs, Tuesday May 1st, 2018, Montréal, Canada

5. © Copyright Léger (2018)
Prof. Pierre-Majorique Léger, Ph.D.
Full Profess0r
Director ERPsim Lab
Co-direct0r Tech3Lab
pml@hec.ca
Graduate studies
Post-Doctorate
Laboratories & chairs Financial support
Guest Professor
Lab Serious games to learn
enterprise systems and
business analytics
https://www.researchgate.net/profile/Pierre-Majorique_Leger

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10. © Copyright Léger (2018)

11. © Copyright Léger (2018)
cognition
attention
Émotions
1 Gb/hour
encyclopedia
encyclopedia
encyclopedia
encyclopedia
encyclopedia
encyclopedia
encyclopedia
encyclopedia

12. © Copyright Léger (2018)
Using neurophysiological data
to optimize user experience (UX)
cognition
attention
emotions
Eyetracking
Neurophysiological measures
1 Gb/participant per hour
Help designers
Autoadapt interface
A B

13. © Copyright Léger (2018)© Copyright Léger et al.(2018)
Powered by:

14. Powered by:
© Copyright Léger et al.(2018)

15. Powered by:
© Copyright Léger et al.(2018)

16. Powered by:
© Copyright Léger et al.(2018)

17. est fier partenaire de
SEVERAL RESEARCH GRANTS
FOR ALL ACADEMICS LEVELS:
chaire_ux.hec.ca
SUBSCRIBE NOW AS PARTICIPANTS
IN OUR RESEARCH PROJECTS:
panel.hec.ca
Proud Partner of
Powered by: Funding Organisations:

18. SEVERAL RESEARCH GRANTS
FOR ALL ACADEMICS LEVELS:
chaire_ux.hec.ca
SUBSCRIBE NOW AS PARTICIPANTS
IN OUR RESEARCH PROJECTS:
panel.hec.ca
Proud Partner of
Powered by: Funding Organisations:

19. est fier partenaire de
SEVERAL RESEARCH GRANTS
FOR ALL ACADEMICS LEVELS:
chaire_ux.hec.ca
SUBSCRIBE NOW AS PARTICIPANTS
IN OUR RESEARCH PROJECTS:
panel.hec.ca
Proud Partner of
Powered by: Funding Organisations:

20. est fier partenaire de
SEVERAL RESEARCH GRANTS
FOR ALL ACADEMICS LEVELS:
chaire_ux.hec.ca
SUBSCRIBE NOW AS PARTICIPANTS
IN OUR RESEARCH PROJECTS:
panel.hec.ca
Proud Partner of
Powered by: Funding Organisations:

21. est fier partenaire de
SEVERAL RESEARCH GRANTS
FOR ALL ACADEMICS LEVELS:
chaire_ux.hec.ca
SUBSCRIBE NOW AS PARTICIPANTS
IN OUR RESEARCH PROJECTS:
panel.hec.ca
Proud Partner of
Powered by: Funding Organisations:
SEVERAL RESEARCH GRANTS
FOR ALL ACADEMICS LEVELS:
chaire_ux.hec.ca
SUBSCRIBE NOW AS PARTICIPANTS
IN OUR RESEARCH PROJECTS:
panel.hec.ca
Proud Partner of
Powered by: Funding Organisations:

22. est fier partenaire de
SEVERAL RESEARCH GRANTS
FOR ALL ACADEMICS LEVELS:
chaire_ux.hec.ca
SUBSCRIBE NOW AS PARTICIPANTS
IN OUR RESEARCH PROJECTS:
panel.hec.ca
Proud Partner of
Powered by: Funding Organisations:

23. est fier partenaire de
SEVERAL RESEARCH GRANTS
FOR ALL ACADEMICS LEVELS:
chaire_ux.hec.ca
SUBSCRIBE NOW AS PARTICIPANTS
IN OUR RESEARCH PROJECTS:
panel.hec.ca
Proud Partner of
Powered by: Funding Organisations:

24. est fier partenaire de
SEVERAL RESEARCH GRANTS
FOR ALL ACADEMICS LEVELS:
chaire_ux.hec.ca
SUBSCRIBE NOW AS PARTICIPANTS
IN OUR RESEARCH PROJECTS:
panel.hec.ca
Proud Partner of
Powered by: Funding Organisations:

25. est fier partenaire de
SEVERAL RESEARCH GRANTS
FOR ALL ACADEMICS LEVELS:
chaire_ux.hec.ca
SUBSCRIBE NOW AS PARTICIPANTS
IN OUR RESEARCH PROJECTS:
panel.hec.ca
Proud Partner of
Powered by: Funding Organisations:
FINANCING.
TECHNOLOGICAL INNOVATION.
PARTNERSHIPS.

26. © Copyright Léger (2018)
Please
test!

27. © Copyright Léger (2018)

28. © Copyright Léger (2018)
Ease of use?

29. © Copyright Léger (2018)
3 of 5
Ease of use?

30. © Copyright Léger (2018)
Conclusion?
?

31. © Copyright Léger (2018)

32. © Copyright Léger (2017)

35. © Copyright Léger (2018)
frontalis
Corrugator
Zygomaticus

36. © Copyright Léger (2018)
NEUTRAL
HAPPY
SAD
DISCUSTED
ANGRY
SURPRISED
SCARED

37. © Copyright Léger (2018)
NEUTRAL
HAPPY
SAD
ANGRY
SURPRISED
SCARED
DISCUSTED

38. © Copyright Léger (2018)

39. © Copyright Léger (2018)

40. © Copyright Léger (2018)

41. © Copyright Léger (2018)

42. © Copyright Léger (2018)
Tobii EyeTracker X60
© Copyright Tech3Lab 2016

43. © Copyright Léger (2018)
densité de la
fixation oculaire

44. © Copyright Léger (2018)
Émotions positives
Émotions négatives

45. © Copyright Léger (2018)

47. Testing, testing,
1, 2, 3 !

48. 100x

49. © Copyright Tech3Lab 2016
If you are going to fail,
fail fast. But learn quickly!

50. © Copyright Léger (2018)
MOOC Gratuit en Mai 2017 :
Introduction à l'expérience utilisateur
Début 15 mai 2018
Plus d'information :
https://cours.edulib.org/courses/course-v1:HEC+UX-101.1+P2018/about

52. © Copyright Léger (2018)

54. To Trust or Not to Trust
the Recommendation Agents?

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Objectives
Determine the extent to which the
visual representations of a recommendation
agent influence the perceptions and behaviors
of retail professionals in assortment
planning decision.

56. © Copyright Léger (2018)
Experimental
Design Task 1 Task 2
Task 3
Richness
Effort
low
low
high
high
Image (I)
Attributes (A)
Score (S) Name (N) Sales (SA)

57. © Copyright Léger (2018)
Task 1
Low Richness
and Low Effort
Image (I)
Score (S) Name (N)

58. © Copyright Léger (2018)
Task 2
high Richness
and Low Effort
Attributes (A)
Image (I)
Score (S) Name (N)

59. © Copyright Léger (2018)
Task 3 high Richness and high Effort
Image (I)
Score (S) Name (N)
Sales (SA)

60. © Copyright Léger (2018)
Experimental protocol
Total time: 120 minutes

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Behavioral Measures
Visual attention
(Eye tracking – Smart Eye Pro)
▪▪ Number and duration
of ocular fixations

62. © Copyright Léger (2018)
Area of Interest

63. © Copyright Léger (2018)
Psychometric Measures
Credibility of the
recommendation agent
(Ohanian, 1990)
▪▪ Trustworthiness
▪▪ Expertise
Satisfaction
(Sirdeshmukh et al., 2002)
▪▪ Highly satisfactory – Highly
satisfactory
▪▪ Very unpleasant – Very pleasant
▪▪ Terrible – Delightful
Type of future usage
(Komiak and Benbasat, 2006)
▪▪ Delegated Agent
▪▪ Decision Aid

64. © Copyright Léger (2018)
Experimental Setup

65. © Copyright Léger (2018)
Experimental Setup

66. © Copyright Léger (2018)
3.1
3.8
3.7
0 1 2 3 4 5 6 7
Task 1
Task 2
Task 3
Average Credibility per Task
Results
Credibility
Ohanian, 1990 Task 3
Task 2
Task 1
Ohanian (1990)
*Significantly different
*
*

67. © Copyright Léger (2018)
2.7
3.5
3.2
0 1 2 3 4 5 6 7
Task 1
Task 2
Task 3
Average of the Intention to Adopt the RA as a
DelegatedAgent per Task
Results
Type of future usage
Komiak and Benbasat, 2006
Komiak and Benbasat (2006)
Task 1
Task 2
Task 3
4.4
5.5
5.4
0 1 2 3 4 5 6 7
Average of the Intention to Adopt the RA as a
Decision Aid per Task
*Significantly different
*
*
*
*

68. © Copyright Léger (2018)
Results
Satisfaction
Sirdeshmukh et al., 2002 Task 3
Task 2
Task 1
Sirdeshmukh et al., 2002
5.9
6.5
6.4
0 1 2 3 4 5 6 7 8 9 10
Task 1
Task 2
Task 3
Average Satisfactionper Task
*Significantly different
*
*

69. © Copyright Léger (2018)
945
247
64
1833
1129
115
63
1193
232
103
2862
0 500 1000 1500 2000 2500 3000 3500
Image
Name
Score
Attributes
Image
Name
Score
Image
Name
Score
Sales
123
Duration(sec)
Total Durationper AOI Type and Task
Task 1
Task 2
Task 3
Results
Eye Tracking
*Significantly different
1890
126
47
561
2011
70
38
2351
129
71
514
0 500 1000 1500 2000 2500 3000 3500
Numberof Fixations
Total Count per AOI Type and Task
*
*
*
*
*
*
*
*
*

70. © Copyright Léger (2018)
Results
Eye Tracking
*Significantly different
1.9
0.6
0.9
2.7
2.2
0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0
Attributes
Image
Name
Score
Sales
Duration(sec)
Average Durationper AOI Type
*
*
**
* *
*
*
0.6
1.2
0.6
1.8
0.4
0.0 0.5 1.0 1.5 2.0 2.5
Numberof Fixations
Average Count per AOI Type
*
**
* *
*

71. © Copyright Léger (2018)
Results
Eye Tracking
*Significantly different
553
214
904
676
222
150
46
77
821
374
0 200 400 600 800 1000
First
Last
First
Last
First
Last
First
Last
First
Last
AttributesImageNameScoreSales
Duration(sec)
ComparisonTotal DurationBetween the Firstand Last 1/4 Period per AOI Type
*
*
*
153
74
1727
1207
98
62
36
43
151
90
0 200 400 600 800 1000 1200 1400 1600 1800 2000
Numberof Fixations
ComparisonTotal Count Between the Firstand Last 1/4 Period per AOI Type
*
*

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Conclusion
Retail Professionals' Perceptions
▪▪ The effort required to access the additional
information does not have an impact on users’
perceptions.
▪▪ Information richness positively affects users’
perceptions.
▪▪ Users are more willing to adopt the RA as a
decision aid than as a delegated agent for all
three conditions.
Retail Professionals' Behaviors
▪▪ Users are referring more to the additional
information at the beginning of their
decision-making process.
▪▪ When additional information is available,
users consult more frequently the information
easily accessible.

73. © Copyright Léger (2018)
Thank you!

74. Merci / Thank You
1
@jdalabsmtl
Data Science | Design | Technology
(Check for next DSDT meetup at https://www.meetup.com/DSDTMTL)