Acceptance of Mobile Technology in Hedonic Scenarios

Acceptance of Mobile Technology in Hedonic Scenarios

Marina Abad1, Itxaso Díaz2 and Markel Vigo3

3 Laboratory of Human Mobility and Technology

BCS Conference in Human-Computer Interaction – HCI 2010

September 9, Dundee (Scotland)

2 Úbiqa - Social Communication1 Deusto University

0. Outline

1. Introduction to TAM and its relationship with HCI

2. Motivation for a new TAM and research questions

3. Application scenario and contextualization

4. Data analysis and results

5. Discussion on results

6. Outcomes

7. Limitations of the study

Acceptance of Mobile Technology in Hedonic Scenarios BCS HCI 2010

1. Introduction


• Technology Acceptance Models (TAM)- Rooted in the Theory of Reasoned Action (Ajzen and Fishbein, 1980) and

applied to computer usage behaviour- A tool to measure usage intentions of technology after a brief trial- Self reported questionnaires to measure:

Perceived Ease of Use, PEOU Perceived Usefulness, PU (stronger determinant of usage)

- User acceptance of technology in workplace settings

Perceived Usefulness

Perceived Ease of Use

Behavioural Intention to Use

Actual Systems Use

External Variables

1. Introduction• The role of TAM in HCI (or IS vs. HCI)

“one day someone will write a critique of TAM for the HCI community to talk of ‘Perceived Usefulness’ or ‘Perceived Ease of Use’ as determinants of behaviour (or intent) simply says very little to the HCI community, and if they do account for intent to use, they say nothing of actual use.” BCS HCI Paper Reviewer- Focus:

IS tends to be macro, drawing from social and organizational psychology HCI has a more micro focus, drawing from cognitive psychology

- Emphasize: IS highlights the important role of perceived usefulness HCI focuses (not only) on the ease of use

- Weak points: Most IS has not examined the role of design features HCI treats usability as a catchall concept and usefulness may fade away

100% usable systems do not guarantee that people will make use of them


2. Motivation

• TAMs have been applied in workplace settings

•What about technology acceptance on leisure settings?

• Hedonic activities involve fun, pleasure, playfulness

• In addition to Usefulness and Ease of Use (which have proved to be stable) a new hedonic component needs to be included

• In hedonic scenarios the hedonic component and ease of use prevail over usefulness

• Never studied the hedonic component when mobile devices are used


2. Motivation• Research goal: develop a TAM for mobile devices in leisure scenarios

• Research question 1: are mobile devices inherently joyful?

• Research question 2: what prevails when mobile devices are used in leisure activities,

- The leisure component of the mobile device?- Or the playfulness of the environment?


3. Initial proposal for a TAM• Consider prior work on TAMs

- Affective- Mobile

• Take (and adapt) the variables for our application scenario• As a result we have 5 factors and 21 variables/items

- PU: Perceived Usefulness (8) e.g., it made me learn about the activity- PEOU: Perceived Ease of Use (5) e.g., we felt at ease- SAT: Satisfaction (4) e.g., I’m satisfied with this activity- PP: Perceived Playfulness (4) e.g., it was fun- BI: Behavioural Intention (1), I would like to participate again in the same

activity

• Resulting questionnaire was filled out by users after experiencing mobile technology in a hedonic scenario


4. Application scenario

• Event taking place in Cáceres (Spain)- Fostering social cohesion by means of technology - Emphasizing the innovative aspects of the town

• 79 people aged (M=16, sd=1.4)- High school teenagers- Frequent users of mobile technology and familiar with IT

• Had to accomplish a city tour- A number of stages (taking 4 hours)- Making use of most features of the phone:

Online maps + GPS for geolocation Videorecording QR codes SMS and MMS


5. Data processing and results• Applied PCA (Principal Components Analysis) to results

- Detect underlying dimensions- Data reduction


Preliminary approach

PU 8 items

PEOU 5 items

SAT4 items

PP 4 items

21 non-structured items

7 items


21.3%

3 items

Perceived Ease Of Use

17.3%

4 items

Perceived Enjoyment

21.6%

PCA

Resulting scales

5. Results

• Explanatory power: the three factors account for more than 60% of variance- Internal consistency- Balanced distribution

• To an extent resulting model corresponds to the theoretical model except for PE


7 items


21.3%

3 items

Perceived Ease Of Use

17.3%

4 items

Perceived Enjoyment

21.6%

Resulting scales

5. Results• Check the hypotheses:

H1. There is a positive relationship between PU and Behavioural Intentionstandarized β=0.395, p<.001H2. There is a positive relationship between PEOU and Behavioural Intentionstandarized β=0.186, p<.05 H3. There is a positive relationship between PE and Behavioural Intentionstandarized β=0.425, p<.001

• Predictive power: regression analysis proves the strength of the model, R2=0.61



Perceived Ease of Use

Perceived Enjoyment

Behavioural Intention to Use

R2=.61

.395

.186

.425

6. Discussion• The items that explicitly mention the activity and technology

- Load on Perceived Enjoyment

SAT1: I am satisfied with this activity

SAT2: The activity has been agreeable and enriching

- Loads on Perceived Ease of Use

SAT4: I like those activities that require the use of technology

• Results suggest that, in hedonic outdoors scenarios, the activity prevails over the technology- Higher explanatory power of PE where SAT1 and SAT2 load- Outdoors experience is a stronger predictor for technology adoption

• The quality of the outdoors experience has a stronger affective (enjoyment) component than the use of devices


6. Outcomes• A TAM that considers both mobile, enjoyment variables in addition

to traditional variables

• Contributes building a repository of similar studies that can lead to the robustness and extrapolation of similar studies

• Stronger explanatory (60%) and predictive power than state-of-the art approaches. Typically 30%-40% of the variance

• Confirms the relevant role of the affective components for technology adoption


7. Limitations


• Context: mobile devices + outdoors funny activities

• The device was shared in each group

• The sample (N=79) may not be enough

• Homogeneous sample

• Did not operate different kind of devices

• Exploratory rather than confirmatory

Acceptance of Mobile Technology in Hedonic Scenarios

Marina Abad1, Itxaso Díaz2 and Markel Vigo3

3 Laboratory of Human Mobility and Technology

BCS Conference in Human-Computer Interaction – HCI 2010

September 9, Dundee (Scotland)

2 Úbiqa - Social Communication1 Deusto University

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Acceptance of Mobile Technology in Hedonic Scenarios

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