Understanding Consumer Behaviour in Information and Communication - - PowerPoint PPT Presentation

Understanding Consumer Behaviour in Information and Communication Technologies (ICTs)

Alastair W Robertson

A.W.Robertson@lancaster.ac.uk Department of Management Science Lancaster University Management School Lancaster LA1 4YX United Kingdom

What are ICTs?

• ICTs are ‘gadgets’ that people can use to connect to

information and to communicate with one another.

– e.g. Computers and PDA’s. – Focus here is limited to internet adoption.

• But why has research into ICT adoption become so important?

M i l i t a r y U s e S i m p l i f i e d w e b u s e E x p l

• s

i v e i n t e r n e t g r

• w

t h Broadband Generation

5.5M!

D i g i t a l D i v i d e ?

60’s 90’s 95 00 0? 04

9kbs 56 to 128kbs 512Mbs 2Mbs

Discussion highlights a fast changing market

• What do market stakeholders need to know to be

able to forecast the market better?

• Why and Which consumers adopt technologies!

Knowledge of consumer behaviour How to apply this information to produce forecasts Develop ment of new methodol

• gies, or

existing technique s re- applied

The stakeholder positions

• Digital divide highlights missed revenue or

missed development opportunities and cost saving.

– Marketers and Business Planners;

• Missed revenue: Untapped market

– Government and Regulators;

• Missed development opportunities: Countries

with less ICT may grow less.

• Missed cost saving: Those on ‘wrong’ side of

divide use government services more frequently.

Focus of the Research

• Human characteristics and ICT

Combine to produce consumer groups with unique ICT characteristics

Technology acceptance (perceptions) 2 Levels

• f HC

Segment using perceptions, confirm segment validity using socio-economic Socio-Economic (e.g. income, age)

Application of Human Characteristics

• Segmentation;

– measure of the digital divide?

• Model estimation;

– Application of choice modelling. – confirmation of what drives the digital divide.

• Experimentally, applied to the diffusion modelling

process;

– Introduces idea that that segmental diffusion curves can be estimated. – Estimate of how digital divide may evolve over time.

Social Psychological Factors

• Massive literature on TAM;

– Google ‘technology acceptance model’

–

A large number of test applications. Fred Davis (1989);

External Variables Perceived Ease of Use Perceived Usefulness Attitude, Use

• f Tech

Behavioural Intention Actual Usage

• Adams (1992): Usefulness and Ease of Use

perceptions

– Applicable to diagnosis of user acceptance in technologies in general – Especially applicable when adoption is voluntary

• Igbaria et al (1996): TAM research justified due

to extensive expansion into ICTs by businesses, but low final use

– Similar to residential ICT adoption?

Enjoyment and ICT adoption

• An obvious point,

– If computers become more enjoyable to use, their adoption and usage will increase, Igbaria (1996) – Perceived enjoyment distinct from U and EoU – Three perceptions are measurable at the consumer level

• EoU, U and E

First internet test of TAM, Teo (1999)

• Where next?

– New application of the TAM perceptions…

Ease of Use Enjoyment Usefulness Internet Usage All perceptions important, but usefulness more so….

An application of TAM, Survey of UK Households

– Extensive data collected from 1286 HHs. – Data was weighted to minimise non-response bias.

Expected ICT Utility Enjoy, Comp Easy, Comp Useful, Comp Enjoy, Net Useful, Net Easy, Net

Simple Application of Expected ICT Utility

Divide up the measure into arbitrary segments. Measure known characteristics for each segment. Merge ‘similar’ segments i.e. if demographically similar. For each segment, measure their proportion in the data;

This is an estimate of the proportion of consumers in the UK of this utility level.

Computer Adoption by Utility Level

0% 20% 40% 60% 80% 100% Seg1 Seg2 Seg3 Seg4

Utility level Percentage within segment

NB: No difference in gender…

Age by Utility Level

0% 20% 40% 60% 80% Seg1 Seg2 Seg3 Seg4

Percentage within Segment

18 to 29 30 to 39 40 to 49 50 and above

Educational Attainment by Utility Level

0% 20% 40% 60% 80% 100% Seg1 Seg2 Seg3 Seg4

Percentage within segment

Level 4 Level 3 Level 2 Other No Qualifications

Individual Disposable Income by Utility Level

0% 20% 40% 60% 80% 100%

Seg1 Seg2 Seg3 Seg4

Percentage within Segment

£7,500-£11,249 £11,250-£18,749 £18,750-£26,249 £26,250-£33,749 £33,750 and above

• Complex approach

– Incorporate expected ICT Utility with other strategies

• Estimate consumer choice model

– e.g. logit

• Use the model to define segments via expected ICT utility

– Estimate segmental price sensitivities

ICT Choice No internet Narrowband Broadband

Factors drive the choices…

→Stage 1, fairly common procedure

How is logit output interpreted?

Logit estimates ICT adoption probabilities given a set

• f inputs, much like regression;

∑

= + + +

+ + +

=

n j x x x i

ik x k i x i x ik k i i

j

1 ) ... (

) ... 2 2 1 1 ( 2 2 1 1

exp exp ) ( Pr

β β β

β β β

Where = Probability individual i purchases product j given xs

) ( Pr j

i

Factor effects facing consumer β Factor effects facing consumer xi

Technology Levels in the Home

10 20 30 40 50

Tech 2 HH Tech 3 HH Hi-tech HH Technology Level Odds Ratio

Narrowband Broadband

Household Educational Attainment

0.1 0.2 0.3 0.4 0.5 0.6 Level 3 Level 2 Other No Qual. Odds Ratio

Narrowband Broadband

Compare to missing category

Presence of Children

0.5 1 1.5 2 2.5 3 Narrowband Broadband Odds Ratio

Point: Overall effects stronger for broadband than for narrowband Insight: Demographic effects dissipate

• ver time…

Internet Choice Elasticity: +0.2

Segmentation Results

Table 2: ICT utility segments 83%

• 1.28

High income and educ., 25% with kids, love technology. High (62.1%) 65%

• 1.42

Good income and educ., white collar, possibly kids. Mid to High (22.7%) 21%

• 1.51

Moderately better income, slightly better

• educ. Blue collar.

Low to Mid (13%) 8%

• 1.77

Low income and educ., retired, unemployed. Low (2.2%) Computer Adoption Broadband Price Elasticity Household Description ICT Utility Level

• Apply price forecast to the model for each

segment →Stage 2, new and experimental procedure

£0 £10 £20 £30 £40 £50 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 Price

Broadband Price Forecast

Broadband Price Forecast

) 22 . 04 . 4 (

exp

t t

P

−

=

            + − =

+ − + − ).t q (p s s ).t q (p t s

s s s s

e p q 1 e 1 Pr) | MProb(s (t) N

Work resulting segmental adoption probabilities to the diffusion process.

Segmental Adoption Probability Segmental Innovation and Imitation Parameters ‘Moving’ Social System Size N

Segmental Diffusion Rate

0.5 1 1.5 2 2.5 3 3.5 4 2001 2003 2005 2007 2009 2011 2013 2015

Number of New Adopters in Year

Low to Medium Utility Medium to High Utility High Utility Aggregated Segments

High Utility Adopt First: Innovators Low Utility are the Laggards

Segmental Diffusion

5 10 15 20 25 30 2000 2002 2004 2006 2008 2010 2012 2014

Number of Households, Millions Low to Medium Utility Medium to High Utility High Utility Aggregated Segments Broadband Actual

Model Comparison

5 10 15 20 25 2000 2002 2004 2006 2008 2010 2012 2014

Number of Households, Millions Bass Aggregate AEUD Segmental AEUD Broadband Actual Bass tends to under perform in presence of limited data

Segmentation approaches: Simple versus

Econometric

0% 20% 40% 60% 80% Simple Econometric Percentage

Seg1 Seg2 Seg3 Seg4

2.2% 13.0% 22.7% 62.1% 47.6% 42.1% 6.9% 3.4%

Which to choose?

Recap.

• The presentation has introduced

expected ICT utility as a segmentation variable for residential ICTs;

– Created from a sound theoretical foundation. – Applications go some way to confirm validity of the measure.

Issues

• More testing needed to confirm validity;

– New survey is proposed for next year. – Same HHs, two year interval. – Track segmental shifts.

• Wider tests required;

– Different applications (e.g. wireless apps.). – Different countries.

Future Possibilities

– Other applications may exist for this variable also, especially if captured regularly in time;

• Comparable measures across countries.

( )it

framework regulatory factors, economic

• Socio

f Utility ICT Expected

it =

Where i could be individual or country…