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ENTER 2015 Research Track Slide Number 1
Investigating user’s information needs and attitudes towards
proactivity in mobile tourist guidesAdem Sabic
Markus Zanker
Alpen-Adria-Universität Klagenfurt, [email protected] | [email protected]
http://www.aau.at
ENTER 2015 Research Track Slide Number 2
Agenda
• Motivation and Recent Work• Goals and Design• Results• Hypotheses• Conclusions
ENTER 2015 Research Track Slide Number 3
Motivation
User‘s attention is a valuable and
very scarce resource
Credit: Shutterstock.com
ENTER 2015 Research Track Slide Number 4
Proactive Computing
“Ability to act on the user’s behalf in anticipation of future goals or problems without the user’s requests, where a proactive system can trigger itself by capturing a priori what the users want with better service quality”. (Kwon, 2006)
ENTER 2015 Research Track Slide Number 5
Challenges
(How to) „Act with
the right information,
at the right time,
at the right place,
in the right way,
to the right person”(Fischer, 2012)
ENTER 2015 Research Track Slide Number 6
Recent Work 1/2
• Most work done in proactive agents / personal assistant area
• Context-aware systems finally made their way to users (focus mainly on location, time, task etc.)
• Limited range of proactive applications in industry (Google Now, weather warnings, navigation systems etc.)
• Some research prototypes: push-based RS, restaurants/gas stations [Woerndl et al., 2011]
ENTER 2015 Research Track Slide Number 7
Recent Work 2/2• Longer term field study on predicting disruptive
smartphone notifications to include problem of concept drift [Smith et al., 2014]
• Model of smartphone use based on qualitative evidence that categorized activities into communication, entertainment, facilitation and information search [Wang et al., 2014]
• Attitude towards proactive recommendations researched with projective techniques showing a majority eager to adopt them and fears / anxieties of others [Tussyadiah & Wang, 2014]
ENTER 2015 Research Track Slide Number 8
Goal
• Explorative study to generate hypotheses about the relationships between factors that most probably impact the adoption of proactive systems
• Contribute towards model building
ENTER 2015 Research Track Slide Number 9
Factors 1/3• Information need (IN): Different categories of
travel-related information services such as route services, traffic, weather, POIs…
• Tolerance Towards Interruptions (TTI): Degree of disruption for different events such as call, texts
or updates • Openness to share personal data (OP): Which
categories of data the users allows the system to exploit
such as location or personal contacts
ENTER 2015 Research Track Slide Number 10
Factors 2/3
• Trust (TR): Based on continuous use of route navigation even if it makes an error (sole proactive system users experienced)
• Willingness to provide feedback (PF): in order to improve its models
• Willingness to pay (WTP): economic dimension to sustainable service provisioning
ENTER 2015 Research Track Slide Number 11
Factors 3/3
Similarity-attraction hypothesis [Nass et al., 1995]: people prefer to interact with others who are similar
•Proactive Attitude (PA): “is a personality characteristic, [] belief in rich potential of changes that can be made to improve oneself and one’s environment” [Schmitz & Schwarzer, 1999]
Fear that proactive devices distract and create stressful situations•General Self-Efficacy Scale (SE): perceived self-efficacy in
dealing with daily hassles and stressful life events [Schwarzer & Jersualem, 1995]
ENTER 2015 Research Track Slide Number 12
Empirical Study
• Offline paper survey• 65 participants• Aged from 20 to 47 years (M=25.23, SD=5.131)• Females (52.31%)• Highest education level: high-school (50.77%),
bachelor (40.00%) and master degrees (6.15%)• 95.31% of participants use smartphones and
35.94% tablets
ENTER 2015 Research Track Slide Number 13
Information needs and trip phase 1/2
ENTER 2015 Research Track Slide Number 14
Information needs and trip phase 2/2
• More than one device used for finding information in pre- and on-trip phases (mobile devices dominate the latter phase)
• Types of information delivery mechanisms users prefer (while traveling):– notification-based methods (alerts, warnings etc.)
68.42%– voice-based (22.81%) – widget/UI-based (21.05%)* don’t add to 100% due to multiple-choices
ENTER 2015 Research Track Slide Number 15
Events with high priority
• Complementarily intrusiveness is perceived highest for Application updates and lowest for text messages
ENTER 2015 Research Track Slide Number 16
Security and Privacy Concerns
• High interest in having the possibility to see and approve all information that the system analyses
• Mediocre openness to share private data with the system
ENTER 2015 Research Track Slide Number 17
Economic perspective
• Medium interest in paying for services
• General preference for ad-supported versions
• Willingness-to-pay – 9.63 EUR (AVG) per install or – 2.13 EUR for monthly subscription.
ENTER 2015 Research Track Slide Number 18
Personality scales
• The Self-Efficacy Scale (α = .783) (SE)– With Higher SE score users check for more categories of
information in the before and on-trip phases– Trust in proactive systems correlates negatively (p <= 0.01) with
the SE score– For all of the categories of data that can be analysed by the
system, significant negative correlations (mostly at the p < 0.01 level) between openness to allow a system to analyse category data and participant's SE score
• Nicely supports the reasons of the anxious group in [Tussyadiah & Wang, 2014]
• Proactive Attitude (α =.713) (PA)– No correlations with any of the other factors
ENTER 2015 Research Track Slide Number 19
Hypotheses 1/2
• Economic perspective:– Users who are more willing
to provide feedback (invest more to make it useful) are willing to pay more
– Users with a lower tolerance towards interruption (i.e. suffer more from being disturbed) are also willing to pay more
WTP
PF
TTI
+
-
ENTER 2015 Research Track Slide Number 20
Hypotheses 2/2
• Privacy perspective:– The less diverse users‘
information needs were, the more willing they were to let the system exploit their data
– Users who perceive themselves to be more efficient check for more information categories before travel
OP
IN
+
+GSE
-
ENTER 2015 Research Track Slide Number 21
Conclusions• Explorative study with the aim to contribute to hypothesis
and model development
• Similarity-Attraction hypothesis does not seem to apply to proactive system behavior
• For practical system development:– Sensitivity towards privacy concerns of users– Worse experience with status quo makes users more
likely to adopt and pay for proactive systems
ENTER 2015 Research Track Slide Number 22
Thank you for your attention!
Questions?
Questions?Questions?
Markus ZankerIntelligent Systems and Business Informatics
Alpen-Adria-Universität Klagenfurt, Austria
P: +43 463 2700 3753
Skype: markuszanker
W: http://www.isbi.at/mzanker
Visit: http://www.recommenderbook.net
ENTER 2015 Research Track Slide Number 23
Project OSTAR• Development of an innovative online system for
recommending individual tours and trails in alpine regions– Research partners:
• EURAC research, Bolzano, Italy• Free University Bolzano-Bozen, Italy• Autonomous Province of Bolzano – South Tyrol (Dept. for spatial and
statistical informatics)• Alpen-Adria-Universität Klagenfurt
– Application partners:• Tourism regions in Carinthia and South Tyrol
– Runtime: 2012-2014– Programme:
• Interreg IV Italy-Austria