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? b e Broadband w e e Generation s v d U i e s 5.5M! t e ? e l i o a y f s h e n i l l r u t p p d t a r i w x e g m i t v E i t o i l n D i i i S r M D i g 60’s 90’s 95 00 04 0? 9kbs 512Mbs 2Mbs 56 to 128kbs
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! How to apply Knowledge of this information consumer to produce behaviour Develop forecasts ment of new methodol ogies, 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 Combine to produce consumer • Human characteristics and ICT groups with unique ICT characteristics Technology acceptance (perceptions) Segment using perceptions, 2 Levels confirm segment of HC 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); Perceived Usefulness External Attitude, Use Behavioural Actual Variables of Tech Intention Usage Perceived Ease of Use
• 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) Usefulness All perceptions important, but Ease of Use Internet Usage usefulness more so…. Enjoyment • Where next? – New application of the TAM perceptions…
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, Useful, Easy, Enjoy, Useful, Easy, Comp Comp Comp Net Net Net
Simple Application of Expected ICT Utility Divide up the measure into arbitrary segments. Merge ‘similar’ segments i.e. if demographically similar. Measure known characteristics for each segment. 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 100% Percentage within 80% segment 60% 40% 20% NB: No 0% difference in Seg1 Seg2 Seg3 Seg4 gender… Utility level Age by Utility Level Percentage within 80% Segment 60% 40% 20% 0% Seg1 Seg2 Seg3 Seg4 18 to 29 30 to 39 40 to 49 50 and above
Educational Attainment by Utility Level Percentage within 100% 80% segment 60% 40% 20% 0% Seg1 Seg2 Seg3 Seg4 Level 4 Level 3 Level 2 Other No Qualifications Individual Disposable Income by Utility Level Percentage within 100% 80% Segment 60% 40% 20% 0% Seg1 Seg2 Seg3 Seg4 £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 → Stage 1, fairly common procedure • Estimate consumer choice model – e.g. logit ICT Choice Factors drive the choices… No internet Narrowband Broadband • Use the model to define segments via expected ICT utility – Estimate segmental price sensitivities
How is logit output interpreted? Logit estimates ICT adoption probabilities given a set of inputs, much like regression; β + β + + β ( x x ... x ) exp 1 i 1 2 i 2 k ik = Pr ( j ) Where = Pr ( j ) i i n Probability ∑ β + β + + β ( x x ... x ) 1 i 1 2 i 2 k ik individual i exp purchases = product j given xs j 1 Factor effects Factor effects facing facing consumer x i consumer β
Technology Levels in the Home Narrowband Broadband 50 Odds Ratio 40 30 20 10 0 Tech 2 HH Tech 3 HH Hi-tech HH Compare to Technology Level missing category Household Educational Attainment 0.6 0.5 Odds Ratio 0.4 0.3 0.2 0.1 0 Level 3 Level 2 Other No Qual. Narrowband Broadband
Presence of Children 3 2.5 Odds Ratio 2 1.5 1 0.5 0 Narrowband Broadband Internet Choice Elasticity: +0.2 Point: Overall effects stronger for broadband than for narrowband Insight: Demographic effects dissipate over time…
Segmentation Results Table 2: ICT utility segments ICT Utility Level Household Broadband Computer Description Price Adoption Elasticity Low Low income and -1.77 8% educ., retired, (2.2%) unemployed. Low to Mid Moderately better -1.51 21% (13%) income, slightly better educ. Blue collar. Mid to High Good income and -1.42 65% educ., white collar, (22.7%) possibly kids. High High income and -1.28 83% educ., 25% with kids, (62.1%) love technology.
→ Stage 2, new and experimental procedure • Apply price forecast to the model for each segment Broadband Price Forecast £50 £40 £30 Price £20 £10 £0 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 Broadband Price Forecast − ( 4 . 04 0 . 22 t ) = P exp t
Work resulting segmental adoption probabilities to the Segmental diffusion process. Adoption Probability − + (p q ).t − 1 e s s = N (t) MProb(s | Pr) s t q − + (p q ).t + s 1 e s s p s Segmental Innovation ‘Moving’ Social System and Imitation Size N Parameters
Number of New Adopters in Year Segmental Diffusion Rate 4 3.5 3 2.5 2 1.5 1 0.5 0 2001 2003 2005 2007 2009 2011 2013 2015 Low to Medium Utility Medium to High Utility High Utility Aggregated Segments Low Utility are High Utility the Laggards Adopt First: Innovators
Segmental Diffusion Households, Millions 30 25 Number of 20 15 10 5 0 2000 2002 2004 2006 2008 2010 2012 2014 Low to Medium Utility Medium to High Utility High Utility Aggregated Segments Broadband Actual
Model Comparison Households, Millions 25 Number of 20 15 10 5 0 2000 2002 2004 2006 2008 2010 2012 2014 Bass Aggregate AEUD Segmental AEUD Broadband Actual Bass tends to under perform in presence of limited data
Segmentation approaches: Simple versus Econometric 80% 62.1% Percentage 60% 47.6% 42.1% 40% 13.0% 22.7% 20% 6.9% 3.4% 2.2% 0% Simple Econometric Seg1 Seg2 Seg3 Seg4 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 it = Expected ICT Utility f Socio - economic factors, regulatory framework Where i could be individual or country…
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