Studying the Impact of Ubiquitous Monitoring Technology on Office Worker Behaviours: The Value of...

Studying the Impact of Studying the Impact of

Ubiquitous Monitoring Ubiquitous Monitoring

Technology on Office Worker Technology on Office Worker

Behaviours: The Value of Behaviours: The Value of

Sharing Research DataSharing Research Data

Stuart Moran, Irene Lopez de Vallejo, Keiichi Nakata, Ruth Conroy-Dalton, Rachael Luck, Peter McLennan and Steve Hailes

IntroductionIntroduction

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

Background

Motivation

Questions

Methodology

Data

Analysis

Conclusion

Output

Sociology

Impact of

PerCom

Engineering

Interpretivism

/Mix.Method

Positivism

/Mix.Method

Induction

Interview

Data

Deduction

Conclusions

Methodology Predictive

Model

Project 2 Mutual

Aspects Project 1

Real World Literature

MethodologyMethodology

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

Background

Motivation

Questions

Methodology

Data

Analysis

Conclusion

Output

Sociology

Impact of

PerCom

Engineering

Interpretivism

/Mix.Method

Positivism

/Mix.Method

Induction

Interview

Data

Deduction

Conclusions


Model

Project 2 Mutual

Aspects Project 1


Buffer

Sensor

Cell 2Cell 1

DataData 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

Background

Motivation

Questions

Methodology

Data

Analysis

Conclusion

Output

Sociology

Impact of

PerCom

Engineering

Interpretivism

/Mix.Method

Positivism

/Mix.Method

Induction

Interview

Data

Deduction

Conclusions


Model

Project 2 Mutual

Aspects Project 1


AnalysisAnalysis

Deduction

◦ Use factors as coding

Induction

◦ Allow themes to emerge

“I don’t understand how the

technology works and what

will happen at the end of the

trial”

Vallejo et al. Themes Moran and Nakata Factors

Understanding and

Communication

Informed User, and

Application Assumptions

Temporary Nature

of the Deployment Temporal Effects

Privacy and

Intrusio

Perceived Privacy Invasion,

Device Obtrusion and

Positioning of Device

Attitudes and

Organisational Culture

Perceived Usefulness,

Undesirable Behaviours and

Influencing Attitude

Background

Motivation

Questions

Methodology

Data

Analysis

Conclusion

Output

Sociology

Impact of

PerCom

Engineering

Interpretivism

/Mix.Method

Positivism

/Mix.Method

Induction

Interview

Data

Deduction

Conclusions


Model

Project 2 Mutual

Aspects Project 1


Interview ConclusionsInterview 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

Background

Motivation

Questions

Methodology

Data

Analysis

Conclusion

Output

Sociology

Impact of

PerCom

Engineering

Interpretivism

/Mix.Method

Positivism

/Mix.Method

Induction

Interview

Data

Deduction

Conclusions


Model

Project 2 Mutual

Aspects Project 1


OutputOutput

Project 1: developed the PSA-BI model for predicting monitored user behaviour

Project 2: developed a guide on how to make use of accurate location data in understanding flow interaction dynamics in organisations

External Variables

Anchors

Object Based

Beliefs

Behavior Based

Attitudes

Application

Perceptions

Technology

Perceptions

Technology

Space

Application

Space

Attitude toward

Behaviour

Social Influence

Facilitating

Conditions

Behaviour

Intention

Adjusters

Exogenous Moderating Variables

Object Based Attitudes

Attitude toward

Technology

Attitude toward

Application

Past

Experience

Computer

Skill LevelAge Gender Environment Role CultureContext

Moderating Anchors

Experience TimeNew

Information

ConclusionsConclusions

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

Questions?Questions?

Discussion QuestionsDiscussion 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?

Studying the Impact of Ubiquitous Monitoring Technology on Office Worker Behaviours: The Value of...

Technology

Transcript of Studying the Impact of Ubiquitous Monitoring Technology on Office Worker Behaviours: The Value of...