1. Studying the Impact of
Ubiquitous Monitoring
Technology on Office Worker
Behaviours: The Value of
Sharing Research Data
Stuart Moran, Irene Lopez de Vallejo, Keiichi
Nakata, Ruth Conroy-Dalton, Rachael Luck,
Peter McLennan and Steve Hailes

3. Introduction
 Pervasive Computing
 Benefits in the workplace
 Gaps on how to use data
◦ Method/Guide to using data
------------------------------------------------------
 Monitoring changes behaviour
 Undesirable effects
◦ Method for predicting
behavioural responses

4. Mutual
Project 1 Project 2
Aspects
Background Engineering Sociology
Impact of
Motivation
PerCom
Questions Literature Real World
Positivism Interpretivism
Methodology
/Mix.Method /Mix.Method
Interview
Data
Data
Analysis Deduction Induction
Conclusion Conclusions
Predictive
Output Methodology
Model

5. Mutual
Project 1 Project 2
Aspects
Background Engineering Sociology
Impact of
Motivation
PerCom
Questions Literature Real World
Positivism Interpretivism
Methodology
/Mix.Method /Mix.Method
Interview
Data
Data
Analysis Deduction Induction
Conclusion Conclusions
Predictive
Output Methodology
Model

6. Mutual
Project 1 Project 2
Aspects
Background Engineering Sociology
Impact of
Motivation
PerCom
Questions Literature Real World
Positivism Interpretivism
Methodology
/Mix.Method /Mix.Method
Interview
Data
Data
Analysis Deduction Induction
Conclusion Conclusions
Predictive
Output Methodology
Model

7. Mutual
Project 1 Project 2
Aspects
Background Engineering Sociology
Impact of
Motivation
PerCom
Questions Literature Real World
Positivism Interpretivism
Methodology
/Mix.Method /Mix.Method
Interview
Data
Data
Analysis Deduction Induction
Conclusion Conclusions
Predictive
Output Methodology
Model

8. Methodology
 Positivism / Mixed Methods
◦ Reality is believed to be directly observable and measureable
 Thematic Content Analysis
 Questionnaire and Statistical Analysis
 Simulation developed in VenSim
 Triangulate VenSim prediction with Interview Data
 Interpretivism / Mixed Methods
◦ Reality is believed to only be understood through subjective
interpretation
 Interviews and Observation data triangulated to portray
complex socio technical system
 Research allowed to evolve and unfold, rather than constrain
it through structure

9. Mutual
Project 1 Project 2
Aspects
Background Engineering Sociology
Impact of
Motivation
PerCom
Questions Literature Real World
Positivism Interpretivism
Methodology
/Mix.Method /Mix.Method
Interview
Data
Data
Analysis Deduction Induction
Conclusion Conclusions
Predictive
Output Methodology
Model

10. Data
 Six week temporary pilot project (2005)
 Testing of wearable location tracking
technology in office
 Two wearable RFID tags
 28 semi structured interviews
 This data was shared
Buffer
  
  
Cell 2
Cell 1


Sensor
  


11. Mutual
Project 1 Project 2
Aspects
Background Engineering Sociology
Impact of
Motivation
PerCom
Questions Literature Real World
Positivism Interpretivism
Methodology
/Mix.Method /Mix.Method
Interview
Data
Data
Analysis Deduction Induction
Conclusion Conclusions
Predictive
Output Methodology
Model

12. “I don’t understand how the
technology works and what
Analysis will happen at the end of the
trial”
 Deduction
◦ Use factors as coding
 Induction
◦ Allow themes to emerge
Vallejo et al. Themes Moran and Nakata Factors
Understanding and Informed User, and
Communication Application Assumptions
Temporary Nature
Temporal Effects
of the Deployment
Perceived Privacy Invasion,
Privacy and
Device Obtrusion and
Intrusio
Positioning of Device
Perceived Usefulness,
Attitudes and
Undesirable Behaviours and
Organisational Culture
Influencing Attitude

13. Mutual
Project 1 Project 2
Aspects
Background Engineering Sociology
Impact of
Motivation
PerCom
Questions Literature Real World
Positivism Interpretivism
Methodology
/Mix.Method /Mix.Method
Interview
Data
Data
Analysis Deduction Induction
Conclusion Conclusions
Predictive
Output Methodology
Model

14. Interview Conclusions
 Cross Comparison demonstrated very similar
conclusions
 Different approaches adopted by researchers
add confidence to comparison
 Moran and Nakata’s factors confirmed as
effective monitoring based coding scheme

15. Mutual
Project 1 Project 2
Aspects
Background Engineering Sociology
Impact of
Motivation
PerCom
Questions Literature Real World
Positivism Interpretivism
Methodology
/Mix.Method /Mix.Method
Interview
Data
Data
Analysis Deduction Induction
Conclusion Conclusions
Predictive
Output Methodology
Model

16. Output
 Project 1: developed the PSA-BI model for
predicting monitored user behaviour
Exogenous Moderating Variables
Moderating Anchors
Past Computer
Context Age Gender Environment Role Culture
Experience Skill Level
Behavior Based
Social Influence Attitudes
External Variables Object Based
Anchors Beliefs Object Based Attitudes
Application Application Attitude toward
Space Perceptions Application
Attitude toward Behaviour
Behaviour Intention
Technology Technology Attitude toward
Space Perceptions Technology
Adjusters Facilitating
Conditions
New
Experience Time
Information
 Project 2: developed a guide on how to
make use of accurate location data in
understanding flow interaction dynamics in
organisations

17. Conclusions
 Different projects, aims and methods
 Same question, data and conclusions
 Reminder that there is value in sharing
research data between researchers and
across disciplines
 Online repository of qualitative and
quantitative to facilitate the sharing of data

18. Questions?

19. Discussion Questions
 Why is research data not more frequently
and widely shared?
 How can we (in this room) collaborate and
share resources?
 What immediate benefits can really be
gained from Pervasive technology in the
next 5 years?
 What social implications are we already
aware of?