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Consumer Informedness

and Firm Information

Strategy Robert J. Kauffman

School of Information SystemsMarch 2013

Some background on me first …

My research is motivated by the waves of technology change, and turbulent waters of industry transformation

MEASURING BUSINESS VALUE (1988)• My PHD thesis had a

similar title to my 1st

coauthored book

• Shared interest: IT value– CIO of Xerox, DOD, NASA– IT SVP, Metropol’tn Life Ins – 1st Editor, INFORMS ISR– IS Dept. Editor, Mgmt. Sci.

Industries Studied

Theories Advanced

Research Area

Problems Addressed

Methods Applied

I have studied a spectrum of other business, consumer and social impacts related to IT

Components (C), Products (P), Infrastructures (I)

Future

Past

• Helps describe product evolution in technology ecosystems

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MP3 Players

Current Research• Strategic necessity vs. strategic advantage of IT,

Internet banking and mobile payments

• C-suite leadership, survival, public/private sectors

• IT services: contracts, risk mgmt, cloud computing, info sec, pricing, competition

• Business, consumer and social insights projects: airlines, banks, telecoms, hotels; banks, digital entertainment (LARC), public sector (A*STAR)

Next, let’s talk aboutconsumer informedness

Research Questions• How do price and product informedness

impact consumer choice?• Do their effects vary by consumer

segment? In what ways?• Can we depict the differences with field

experimental research designs?• What are the implications for firm-level

information strategy?• What industries will help us to understand?

The Market Offers Great Variety• Firms design and differentiate products to

achieve best product fit and consumer delight• They benefit from long-tail demand• Hyperdifferentiation has arrived

• Example: Commodity beers, premium beers, and super-premium craft-brewed beers

Rating Sites Build ProductAttribute Informedness

Information: Strategic for the Firm• New ways to gauge

the ‘taste buds’ of market

• Creates leverage to alter demand, sales and profit

• Enables exploitation of uninformed and informed segments: info is strategic

Toward a Theory ofIT & Consumer Informedness

• New IT support for informedness: blogs, ratings, content-based sites, social media

• Informed consumer demand for: – movies (Dellarocas et al. 2007)

– books (Li and Hitt 2008)

– beer (Clemons et al. 2006)

– airline, hotel services (Granados et al. 2010)

• Uncertainty discount reduced (Akerlof 1979, Salop 1979)

• Compromise discount less (Clemons 2008)

Related Theory• Choices based on product attributes (McFadden

1986)

• Lower search costs increase price sensitivity(Bakos 1997, Degeratu et al. 2000)

• Access to quality info decreases price sensitivity(Lynch and Ariely 2000)

• Noisy price signals distort consumer valuation(Demski 1980)

• Efficacy of price comparisons tied to segments(Granados et al. 2012)

• Value of information matters (Dhar and Sundararajan 2007)

Types of Informedness• Product informedness: Degree to which

consumers know what is available in the marketplace, including precise attributes of different product and service offerings

• Price informedness: Same, but focusing only on market and retailer prices for products

• We expect these to matter in different ways for different consumers, products and services

Trading Down, Trading Out• Information changes consumer behavior, which

in turn affects corporate strategy (Clemons 2008)

– Trading down: Consumers exhibit stronger preferences for choosing the products that provide the best price

– Trading out: Consumers exhibit stronger preferences for choosing products that best fit the needs that they express

Info Strategy by Segment

• Firms tailor information strategy based on targeted consumer segment and their positioning in the marketplace (Li et al. 2013)

– Commodity segment: Consumers who focus on price rather than product fit – have higher price sensitivity

– Differentiated segment: Consumers who focus on product fit rather than price – have lower price sensitivity

Consider the main hypotheses of this research

Key Predictions Related to Willingness-to-Pay

CONSUMERSEGMENT

2 informedness strategies (price / product)and

2 consumer segments (commodity / differentiated)

Price Informedness Hypotheses

• H1a (Commodity Segment, Price Informedness, Trading Down Behavior): In the commodity segment, consumers who are more informed consumers about prices exhibit stronger trading down behavior than consumers who are less informed about prices.

• H1b (Differentiated Segment, Price Informed-ness, Trading Down Behavior ): Greater informedness about prices has a lower impact on the likelihood of trading down for the differentiated segment than for the commodity segment.

Product Informedness Hypotheses• H2a (Differentiated Segment, Product

Informedness, Trading Out Behavior): In the differentiated segment, consumers who are more informed about products exhibit stronger trading out behavior than consumers who are less informed about products.

• H2b (Commodity Segment, Product Informedness, Trading Out Behavior): Greater informedness about products has a lower impact on the likelihood of trading out behavior for the commodity segment than for the differentiated segment.

I will briefly report on field experimental research conducted in two new settings:

urban rail transit and hotels

Let’s look first at the ‘Train Study’ …

Netherlands (NS) HiSpeed

• Explored new rail servicesbooked with mobile ticketing and smart cards

• Co-designed with NS HiSpeed input

• Manipulated Price, Product Informedness

Experimental Design: Trains• NS HiSpeed execs, + 2 urban rail transport

research experts: built the service attributes

More on Design: Trains• 2 x 2 between subjects design with manipulations:

– Price Informedness (High, Low)– Product Informedness (High, Low)

• Empirical method: stated choice model• Consumer choice: related to origin-destination,

travel frequency, travel purpose– choose New Service A or B or Neither

• Choice sets: 12-profile fractional factorial design• Fractional factorial design: to study carefully

chosen subset of variables in a limited number of tests – fraction of effort compared to full factorial design

REALISM

CONTROL

Even More on Design: Trains• Subjects completed pre-test questionnaire to

identify their travel behavior for trips they took• Computer survey of NS HiSpeed professional

survey panel, 1,971 valid responses in Dutch• Between-subject experimental design permitted

us to shorten test to lessen response boredom• Price Informedness:

– High: €9-€11, €10-€12; Low: €8-€12, €10-€14

• Product Informedness:– High: 6 attributes; Low: 4 attributes,

no advanced travel info attributesGENERALITY

Next, here’s the set-up of the ‘Hotel Study’ …

Experimental Design: Hotels• Subjects: chose a hotel for a multi-day vacation• Experimental control: total

– 15 hotel attributes, pre-tested, 200 people– 8 most important attributes kept for experiment

• 2 x 2 between subject design again …– Price Informedness (High, Low)

• High = wider price range; Low = narrower range– Product Informedness (High, Low)

• High = 8 attributes; Low = only 3 attributes – Random subject assignment to 4 conditions

Destination: Bruges, Belgium

More on Design: Hotels• Participants: 12 choice sets with 2 hotel options• Choice set construction:

– 36-profile efficient design, with 3 blocks for the 8-attribute conditions

– 12-profile efficient design for the 3-attribute conditions

• Price Informedness:– High: €50 – €60 €70 – €80 €90 – €100– Low: €30 – €80 €50 – €100 €70 – €120

• 614 valid responses in Dutch• Used an online survey tool available in Europe

Product Informedness

Mixed Logit Models• These models can handle:

– random variation in preferences– unrestricted patterns of attribute substitution – any

distribution, not just normal like probit– correlation in unobserved patterns over time

• Individual i makes choice j in choice set k

• Constants δ0 and ϕ0 : average preferences

• Individual-specific random variations (δ0i and ϕ0i ) supplement effects of variables λ and θ

We used econometric methodsfor estimating

the stated choice models

Mixed Logit Estimation Models

• Train study:

• Hotel study:

WTD and WTO Estimates

• WTD = willingness-to-trade-down– Calculated based on marginal rate of substi-

tution between price and non-price attributes– Divide sum of max range of price attribute by

max range of non-price attribute (Lanscar 2007)

• WTO = willingness-to-trade-out– Computed in a similar way

• WTD and WTO confidence intervals derived using Wald procedure based on delta method for WTP estimation in healthcare economics (Hole 2007)

The results show some new knowledge

Predicted Behavior in Experiments

Overview of the ResultsH

otel

Stu

dyTr

ain

Stu

dy

aaa Price Informedness a Product Informedness a

One Hypothesis Not SupportedTRAINSTUDY

HOTELSTUDY

Price Informedness

Product Informedness

Train Study, Commodity Segment

Low

Low

Low

Low

Low

Train Study, Differentiated Segment

Low Low

Low Low

Hotel Study, Commodity Segment

LowLow

Low Low

Hotel Study, Differentiated Segment

Low Low

Low Low

• Consumer preferences: – More-informed consumers have more extreme

behaviors– Price and product info matter to different extents

• Firm IS and information strategy: – Selectively improve consumer informedness– Overcome switching inertia barriers– Exploit consumer preferences, explore attribute space,

generate higher willingness-to-pay– Apply differential pricing strategies to increase

customer engagement.

Overall

Industries Studied

Theories Advanced

Research Area

Problems Addressed

Methods Applied

The future looks bright for LARC

closed-loop experiments

Some Next Steps• How to shape this consumer informedness

research as living analytics closed-loop experimental research?

• The work developed over years pre-LARC, and is conventional in its conceptualization

• But imagine this: suppose we could manipulate different kinds of informedness with cable TV viewers? Mobile phone users?

Network-centric analytics that:• Combine realism, complexity,

and dynamics • Of business, consumer and

social behavior• Observable in the field • With experimental control • And with the causal inference

capability of the lab

• Consumers make purchase decisions based on many criteria simultaneously, rather than just price, quality (Lynch and Ariely 2000; Kuruzovich et al. 2008)

• Choice theory describes the choice process1.Systematically related to attributes of a product, service2.For each attribute, a customer attaches a psychological

weight as a means of expressing her perceptions3.We aggregate weights of individual attributes to create

overall evaluation of product, service4.Made up of observable, unobservable aspects5.Consumer select the most advantageous product

Choice Theory

Effects Coding• Didn’t use traditional dummy variable coding,

which assigns a 0 to the base level

• Effects coding: assigns ‘-1’ to the base level

• Supports measurement of effects of different attribute levels

• Eliminates a problem: having base attribute level coded as average of means of all attribute levels(Hensher et al. 2005)

Comparing the Experiments

Quasi-Random Number Sequence Generation

• 2-sequence: 1⁄2, 1⁄4, 3⁄4, 1⁄8, 5⁄8, 3⁄8, 7⁄8, 1⁄16, 9⁄16,...

• 3-sequence: 1⁄3, 2⁄3, 1⁄9, 4⁄9, 7⁄9, 2⁄9, 5⁄9, 8⁄9, 1⁄27,...

Halton square: (1⁄2, 1⁄3), (1⁄4, 2⁄3), (3⁄4, 1⁄9), (1⁄8, 4⁄9), (5⁄8, 7⁄9), (3⁄8, 2⁄9), (7⁄8, 5⁄9), (1⁄16, 8⁄9), (9⁄16, 1⁄27), …

Pseudo-random 2,3 Halton

sequence,200 draws