Week 4 Discussion 300 - 500 Words Due Tuesday 08/04 by NOON CST

University of Alberta

The Role o f Skill-Based H a b its o f U se in C on su m er Choice

by

K yle B. M u r ra y

A thesis submitted to the Faculty of Graduate Studies and Research in partial fulfillment of the

requirements for the degree of D o cto r o f P hilosophy

m

M a rk etin g an d P sych ology

F aculty o f Business D ep a rtm en t o f P sych ology

Edmonton, Alberta

Fall 2 0 0 4

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To Colleen.

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Kyle B. Murray, University o f Alberta

A C K N O W L E D G M E N T S

Every member o f the marketing group at the University o f A lberta’s School o f

Business deserves my thanks for their valuable contributions. I am especially thankful to

Gerald Haubl for the advice and counsel that he provided freely in an enthusiastic,

rigorous, and intellectually curious manner, throughout my graduate education. My

examination committee, Ric Johnson, Eric Johnson, Doug Olsen, Peter Dixon, W alter

Bischof, and in particular Norman Brown, deserve special recognition for the time and

effort they invested on my behalf, and for their constructive comments on previous

versions o f this dissertation.

M y thanks also go to Jeanette Gosine and David Cooper for their assistance in

navigating the administrative maze. My research benefited greatly from the generous

financial support provided by the Social Sciences and Humanities Research Council of

Canada (SSHRC grant 410-99-0677), the Social Sciences and Humanities Research

Council o f Canada’s Doctoral Fellowship, the University of Alberta Dissertation

Fellowship, and Teradata Center for Customer Relationship M anagement Research Seed

Grant (Duke University, Fuqua School o f Business).

Finally, I would like to thank my family for their never-ending support and

encouragement, even when I was less than certain. I am especially grateful to my parents

for nurturing my own curiosity and for fostering in me a lifelong love o f learning. To

Colleen, without whom none o f this would be possible, I am eternally indebted.

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TABLE O F C O N T E N T S

CHAPTER 1: INTRODUCTION 1

Consumer Behaviour in Electronic Environm ents....................................................... 7 Switching Costs and Lock-In on the In te rn e t......................................................... 11

The Power Law o f P ractice.............................................................................................. 13

Modern A utom aticity........................................................................................................ 14 Understanding Habit beyond Operant C onditioning..............................................18 The Relationship between Skill Acquisition and Preference F orm ation............ 20

Human Capital and the Household Production M odel............................................. 21 User Skills and Brand L oyalty.................................................................................. 23 Skill Transferability and the Development o f Preference......................................24

Habits o f Use and Consumer L o y a lty ............................................................................25 Lock-in as a Result o f Set-up and Evaluation C osts.............................................. 27 The Link between Learning and P reference........................................................... 27

CHAPTER 2: PRACTICE MAKES PREFERENCE 30

Habits o f Use and Consumer Choice..............................................................................30

P re-T ests............................................................................................................................... 31 Method & Procedure...................................................................................................31 R esults...........................................................................................................................32

Experiment 1 ....................................................................................................................... 34 Hypotheses for Experim ent 1.................................................................................... 35 M ethod & Procedure...................................................................................................37 Results.......................................................................................................................... 40 D iscussion.................................................................................................................... 51

Experiment 2 ....................................................................................................................... 53 Hypotheses for Experiment 2 .................................................................................... 54 M ethod & Procedure.................................................................................................. 55 R esults.......................................................................................................................... 56 D iscussion.................................................................................................................... 59

Experiment 3 ....................................................................................... 61 Hypotheses for Experiment 3 .................................................................................... 62 Method & Procedure.................................................................................................. 62 R esults.......................................................................................................................... 64 R esults.......................................................................................................................... 65 D iscussion.................................................................................................................... 68

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CHAPTER 3: THE MODERATORS 72

The M oderators................................................................................................................... 72

Experiment 4 ....................................................................................................................... 74 Hypotheses for Experim ent 4 - Human Capital and Task C om plexity...............75 Hypotheses for Experim ent 4 - Task Complexity and Ease o f U s e .................... 77 M ethod & Procedure.................................................................................................. 78 R esults.......................................................................................................................... 79 D iscussion.................................................................................................................... 84

Experiment 5 ....................................................................................................................... 85 Hypotheses for Experiment 5.................................................................................... 86 Method & Procedure.................................................................................................. 89 R esults.......................................................................................................................... 91 D iscussion....................................................................................................................95

Genera] D iscussion............................................................................................................. 98 Human Capital and The Principle o f Least E ffo rt................................................102 Managerial Im plications.......................................................................................... 103 A Competitive D ilem m a.......................................................................................... 107 Implications for Consumer W elfare........................................................................108 Dissatisfaction: Loyalty’s A chilles’ H e e l? ...........................................................109 Future R ese arch ........................................................................................................ 110

REFERENCES 112

APPENDIX A 118 Screen Shots............................................................................................................... 118

APPENDIX B 120 Post Experim ent 4 Questionnaire............................................................................ 120 Post Experim ent 5 Questionnaire............................................................................ 121

APPENDIX C 122 Experiment 1 - Task Completion Time Summary Data (in seco n d s)............... 122 Experim ent 4 - Task Completion Time Summary Data (in seco n d s)............... 122

CURRICULUM VITAE - KYLE B. MURRAY 123

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L ist of T a b le s

Table 1: Overview o f E x p erim en ts.............................................................. 6

Table 2: Experim ent 1 - Post-Experiment Q u e stio n s................................ 40

Table 3: Experim ent 1 - Logistic Regression R e s u lts .............................. 48

Table 4: Experiment 2 - Post-Experiment Q u e stio n s............................... 57

Table 5: Experiment 2 - Logistic Regression R e s u lts .............................. 58

Table 6: Experiment 3 - Post-Experiment Q u e stio n s................................ 64

Table 7: Experiment 3 - Logistic Regression R e s u lts .............................. 66

Table 8: Overview o f Experiments and R e s u lts ....................................... 100

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L is t o f F ig u r e s

Figure 1: An Example o f a Habit Knowledge S tru ctu re ........................... 20

Figure 2: Experiment 1: Navigation Learning Curve - 9 Trial Condition 42

Figure 3: Experim ent 1: Navigation Standard Deviation Curve Across Subjects - 9 Trial Condition 42

Figure 4: Distribution of GPC Scores 44 One Incumbent Trial Condition Nine Incumbent Trial Condition

Figure 5: Incumbent Choice Share by Experience with Incumbent 45

Figure 6: Relative Task Completion Times (RTCT) by Num ber of Incumbent Trials 46

Figure 7: Incumbent Choice Share by Experience with Incumbent 48

Figure 8: Experim ent 3 - Goal Activation by the Number o f Trials 64

Figure 9: Experim ent 3 - Goal Activation by the Number o f Trials 67 Panel A: Participants that made No Missteps Panel B: Participants that made Missteps

Figure 10: Experim ent 4 - Incumbent Choice Share by Complexity and Incumbent Trials 80

Figure 11: Experim ent 4 - Mean Graded-Paired-Comparison Scores by Complexity and Incumbent Trials 80

Figure 12: Experim ent 5 - Incumbent Choice Share by Time Pressure and Learning Condition 92

Figure 13: Experim ent 5 - Ratings o f Ease o f Use 97

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C H A P T E R 1: IN T R O D U C T IO N

There are many arts among men, the knowledge o f which is acquired bit by bit by experience. For it is experience that causeth our life to move forward by the skill we

acquire, while want o f experience subjects us to the effects o f chance. Plato

The ability to learn from experience is o f central importance to human existence.

It allows us to acquire the skills we need to complete a wide variety o f tasks. After a

while, we are able to improve our performance at those tasks, reducing the time and

effort required, to the point where they become routine. Learning to drive is a familiar

example. For a beginner, driving can be an overwhelming experience. Steering with

your hands, adjusting your speed with your feet, shifting gears at the appropriate time,

obeying traffic laws, avoiding obstacles, reacting to other drivers, listening to the radio,

navigating towards your destination and numerous other tasks have to be completed

simultaneously and often under time pressure. Initially each o f the requisite skills is

immature or nonexistent, which makes learning to drive a challenge. Nevertheless, with

practice most o f us find driving to be a routine, even simple, task. The truth is that our

everyday lives are filled with tasks that, although initially very difficult, we soon learn to

complete without a second thought. If these routine tasks did not become automatic we

would struggle to complete even a fraction o f what we do in a day.

Habitual behaviour is a rational adaptation to a world with ever-increasing

demands on our time and energy. Habits are a good way to make decisions and complete

routine tasks in a time-starved world. W hether we are driving to work or choosing a

grocery store, it is often most efficient to simply do what we did last time to successfully

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complete the same task. W ith practice, a number o f the requisite activities become

automatic and can be accomplished with little conscious thought or awareness (James,

1890). For example, an experienced typist is able to automatically recognize words and

execute the appropriate keystrokes without having to consciously control the individual

cognitive and physical processes (Salthouse 1986). As the typist becomes more skilled,

and more o f the underlying processes become automatic, the time required to type a page

decreases. In the context o f consum er behaviour, consider the grocery shopper looking to

buy a carton o f orange juice. W ith practice, driving to the store, navigating the aisles,

selecting the right size and paying at the appropriate checkout all become automated and

can be accomplished with little conscious thought. When the same set o f automated

activities reliably leads to the successful achievement o f a goal, the behaviour can be

described as habitual (Aarts and Dijksterhuis 2000a). Habits are a type o f goal-directed

automatic behaviour (Bargh 1990): they are knowledge structures that include a goal and

the actions required to achieve that goal (Aarts and Dijksterhuis 2000a). The more often

the goal is associated with successful actions, the stronger the habit and the more quickly

the goal can be achieved. In other words, we can define habits as repeated behaviour that

results in the increasingly rapid accomplishment o f a particular goal, as compared to

novel behaviour aimed at accomplishing the same goal.

As a result, to continue with our grocery shopping example, habitually buying

orange juice at the familiar store can be accomplished more efficiently and with less

effort than at unfamiliar competing grocery stores. The principle o f least effort (Zipf

1949) has long recognized that people attempt to achieve the results they desire with a

minimum amount o f effort. Having repeatedly practiced completing a task, such as

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buying orange juice, the consumer acquires skills and knowledge that allow him/her to

complete the task with a minimum amount o f effort by doing it the same way as last time.

In this way, the developm ent o f consumption habits creates a cost o f switching from an

incumbent brand, for which specific skills have been acquired, to a competing brand.

When the cost o f switching is high enough, the consumer can become locked-in to the

incumbent brand, unable to switch to competitors without paying a price in terms o f new

skill acquisition (Ratchford 2001; Shaprio and Varian 1999; W em erfelt 1985).

It is important to recognize that I am talking about habits o f use, not habitual

choice. The distinction may be a subtle one. Habits o f use create switching costs that

lead to a preference for an incumbent; habitual choice is about consistently choosing the

same product. Habitual choice, as it has been used in the marketing literature (e.g.,

Ehrenberg 1988; Aaker 1991), is a label for repeatedly making the same choice. Habits

o f use may result in habitual choice, but habitual choice may be the result o f many other

factors as well (Chestnut and Jacoby 1978).

Habits o f use can lead to lock-in (Johnson, Bellman, and Lohse 2000), a form o f

loyalty that differs significantly from traditional notions of brand loyalty because it does

not require a positive attitude towards the product, trust in the product or the objectively

superior functionality o f the product. Instead, lock-in as a result o f brand-specific

training depends only upon the relative cost, in terms o f time and effort, o f using a

competitor. The difference is critical, because it sets limits on where and when habits of

use may be affecting consumer choice. For instance, habits o f use may affect which

grocery store a shopper buys Coca-Cola at because the shopper has become skilled at

navigating the aisles and making the purchase. However, habits o f use cannot explain

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why a shopper chooses to purchase Coke rather than Pepsi, because the skills required to

consume the two products are identical (e.g., opening the can, drinking from the can,

etc.). Nevertheless, a shopper may habitually choose a can o f Coke over a can o f Pepsi.

To put it another way, habitual use is an explanation o f an important type o f consumer

loyalty; habitual choice is a label that describes a type o f consumer loyalty.

This dissertation is an in-depth investigation o f the development o f habitual usage

behaviour as a result o f repeated practice with an incumbent web site interface. I argue

that repeated exposure to a specific interface results in the acquisition o f skill and the

development o f habit that in turn reduces the time required to use that interface to

accomplish consumption goals, relative to competitors. This reduction in the time

required has an economic value - that can be conceptualized as a type o f human capital1

(Ratchford 2001) - to the extent that the consumer values his/her time. As human capital

becomes associated with one specific interface, consumers become loyal to that interface

because switching to a competitor would cost the consumer time in acquiring new

competitor-specific skills. W ith practice consumers become loyal to the incumbent

interface even though, given the same experience with other interfaces, these would be

equally useful. Moreover, I predict that human capital can accrue to the point where

consumers will chose the incumbent over a competitor that was considered superior prior

to experience with either interface. This research is a first step towards examining the

impact o f skill-based habits on consumer choice, and it is the first time that the consumer

behavior predictions o f the human capital model have been tested in a controlled setting.

In addition, this line o f research adds to the literature on consumer behaviour in

1 Human capital is defined as the skill and/or know ledge acquired through training and/or learning by doing. For more detail se e Human C a p ita l a n d the H o u seh o ld P rodu ction M o d e l below .

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Kyle B. Murray, University o f Alberta

electronic environments, and more generally human-computer interaction, by explicitly

testing the effect o f habitual behaviour on interface choice and the impact o f a number of

key moderating factors.

The remainder o f the dissertation is organized as follows. This chapter continues

to develop the theoretical background for the experiments. The next section o f this

chapter explains why consumption on the internet is a practical, relevant and interesting

applied setting in which to investigate habits o f use. This is followed by a brief review of

the power law o f practice and its importance in understanding the value o f repeatedly

practicing a task and acquiring skill. I then examine the adaptive value o f automating

task performance and the important impact o f time pressure on consumer decision

making in modern society. Having demonstrated the psychological value o f automating

behaviour in the time-starved world of internet consumption, I turn to a review o f

economic models that formally link the acquisition o f skill to the developm ent of

consumer preference. The literature review concludes with a brief examination of

research on consumer loyalty and the distinct nature o f loyal behaviour that is driven by

habit. The research hypotheses, as well as the experimental design, methods, procedures,

results and discussion are covered in Chapters 2 and 3. Specifically, Chapter 2 presents

evidence in favour o f the fundamental prediction that repeated practice results in the

development o f habit, which in turn leads to a preference for the incumbent (Experiment

1) and a reluctance to try (search for) alternatives (Experiment 2). In addition, Chapter 2

argues that these habits are goal-activated automated behaviors, directly testing the

impact that the consum er’s operational goal state has on decision making (Experiments 2

and 3). Chapter 3 extends the findings o f Chapter 2 by testing the impact o f three key

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moderating variables: the complexity o f the consumption task (Experiment 4), the

constraints within the learning environment (Experiment 5), and the consum er’s time

value (Experiment 5). Furthermore, the results o f Experiment 5 demonstrate that in

competitive environments, once a consumption habit has been developed, consumers may

choose an incumbent interface over a competitor that was considered superior prior to

experience with either interface. The experimental designs for all five experiments are

summarized in Table 1.

Table 1: Overview o f Experiments

Experiment One Experiment Two Experiment Three

Between Subjects Design 2 (path similarity) x 9 (incumbent trials)

2 (goal-activation) x 2 (incumbent trials)

2 (goal-activation) x 2 (incumbent trials)

Number of Incumbent Trials From 1 to 9 1 vs. 9 1 vs. 9

Time pressure No No No

Learning Environment Constrained Constrained Constrained

Navigation Path Similarity Same vs. Changing Same Same

Goal-activation Same Same vs. Different Same vs.Different

Interface Complexity High High High

Experience with competitor required Yes No Yes

Objective Functionality of competitor Equivalent Equivalent Equivalent

Experiment Four Experiment Five

Between Subjects Design 2 (complexity) x 2 (incumbent trials)

2 (time pressure) x 2 (learning environment)

Number of Incumbent Trials 1 vs. 9 9

Time pressure No No vs. Yes

Learning Environment Constrained Constrained and Free

Navigation Path Similarity Same Same

Goal-activation Same Same

Interface Complexity High vs.Low Low

Experience with competitor required Yes Yes

Objective Functionality of competitor Equivalent Superior

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C o n s u m e r B e h a v io u r in E le c tr o n ic E n v ir o n m e n ts

A web site interface was chosen as the experimental environment/stimuli for both

its external and internal validity. Consumer behaviour on the W orld W ide W eb provides

an interesting opportunity to study habitual consumption, in part because a great deal of

the activity being conducted online lends itself to habitual behaviour. For example,

retrieving stock quotes, scanning news headlines, researching product information or

checking bids at an online auction can all quickly become routine. In fact, the ability to

quickly complete such tasks is one o f the primary advantages o f the internet. It is not

surprising then that a large portion o f internet users can be described as simplifiers - i.e.

users whose primary goal is to simplify their lives and save themselves time. Simplifiers

account for 29% o f internet consumers and over 50% o f all online transactions (Forsyth,

Lavoie and M cGuire 2000). In addition, it seems that the number one predictor o f buying

behaviour online is the amount o f discretionary time internet users have. Bellman, Lohse

and Johnson (1999) surveyed 10,180 internet users on a number o f issues related to web-

based activity. W ith regards to internet shopping they concluded “that W eb consumers

shop online or use online services to save time” and that “convenience rather than cost

savings, may be a key benefit offered by successful online stores” (p. 38). This fact has

not been lost on the leading dot-com companies. The battle between Barnes & Noble and

Amazon over Am azon’s one-click technology is an excellent example o f the importance

being placed on the ability to simplify consum ers’ lives in a proprietary manner.

Being able to provide convenient access to products and services over the internet

appears to be worth the fight as the evidence indicates that consumers are loyal to web

sites that they have learned to use effectively and efficiently. Johnson, Moe, Fader,

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Bellman and Lohse (2003) examined data from a panel o f approximately 10,000

households during a 12-month period from July 1997 to June 1998 to see how many

unique sites were searched by each household for product categories such as books and

CDs. Their findings indicate that the average number o f online stores searched before a

CD is purchased is 1.1, and that 70% o f CD shoppers and 70% o f book shoppers are loyal

to a single site. They conclude that their findings are not the result o f a loyal segment o f

consumers, but rather that all consumers are unlikely to “shop around” before making a

purchase online. In a related study, the authors demonstrate that the duration o f site visits

decreases the more a site is visited and that this decrease adheres to the same pow er law

o f practice that describes learning in a variety o f other domains (Johnson, Bellman and

Lohse 2003). The authors argue their findings suggest that consumers are returning to

the sites that they have learned to use. Preliminary tests o f this explanation have also

been carried out in a laboratory setting (Murray and Haubl 2002), and the results support

Johnson et al’s (2003) theory that the acquisition o f site-specific skills can create loyal

consumers. It is worth noting that these loyal online consumers are on average buying

from the higher priced retailers even for homogeneous products such as CDs and books

(Smith and Brynjolfsson 2001).

W hat is o f particular interest in this early research is the finding that increasing

web site loyalty is closely related to decreasing amounts o f time being spent at the web

site. The initial evidence seems to suggest that skill acquisition may explain this type o f

loyalty (Murray and Haubl 2002). Johnson et al. (2003, p. 62) describe it this way:

Imagine a user visiting a Web site to purchase a compact disc (CD). This user must first learn how to use the W eb site to accomplish this goal. We believe that after the CD has been purchased, having learned to use this site raises its attractiveness relative to competing

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sites for the consumer, and all other things being equal (e.g. fulfillment), the site will be more likely to be used in the future than a competitor. Further use reinforces this difference because practice makes the first site more efficient to use and increases the difference in effort between using any other site and simply returning to the first site, where browsing and buying can be executed at the fastest rate. This reinforcement generates an increasing advantage for the initial site.

As a result, and contrary to popular opinion, it would appear that online shopping is not

living up to its billing as a frictionless marketplace. Although the potential to reduce

costs related to information search and product comparison clearly exists in electronic

markets (Haubl and Trifts, 2000), recent research suggests that online consumers are

engaging in only limited search and comparison shopping.

These observations have not been lost on those seeking to build companies on the

web. Since the early days o f e-commerce, an argument has been made for the importance

o f developing a user base at the expense o f short-term profitability (Rayport and Jaworski

2001). According to Shapiro and Varian (1999), one o f the primary advantages of

building an installed user base in the information age is the ubiquity o f switching costs.

They contend that once a buyer has committed to using a particular brand they become

predisposed to that brand and are much less likely to search for alternatives or switch to

competitors. The importance o f developing an installed base o f users is evident in the

fundamental role played by the “growth over profit” approach in the early business

models o f many o f the w eb’s leading companies from Yahoo to iVillage and from

Amazon to WebMD. Jeff Bezos, founder and CEO o f Amazon.com explains the

com pany’s initial commitment to growth over profit this way: "Our initial strategy was

very focused and very unidimensional. It was GBF: Get Big Fast. W e put that on our

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shirts at the company picnic: They said Get Big Fast, and on the back, Eat Another Hot

Dog” (Brooker 2000).

Closely related to the growth imperative is the desire to be a first-mover. Barnes

and Noble has not been able to catch up to Am azon’s market share in book selling nor

have they been able to successfully switch a significant portion o f Am azon’s customers

over to their web site. This is true even though they had a 122 year head start in the book

selling business and a formidable advantage in terms o f offline resources, including a

better selection o f titles and competitive prices. Other late movers in the book-selling

business such as Borders were forced to abandon their online ambitions in the face o f an

installed and loyal Amazon custom er base. Borders Group president and chief executive

officer, Greg Josefowicz, argued that selling their struggling online operations to Amazon

is necessary if Borders is to “offer our customers the convenience o f an online shopping

option with the added benefits that will emerge through our new association with

Amazon.com, the world's recognized e-commerce leader” (Hansell and Kirkpatrick

2001).

However, the theory o f psychological reactance (Brehm & Brehm 1981) suggests

that there may be a down side to being a first m over and acquiring a dominant market

share. Specifically, consumers who feel that they have had their freedom o f choice

restricted may react negatively towards the source o f that restriction (Fitzsimmons 2000;

G odek and Y ates 2003). The lack o f alternative courses o f action, or decision al control

(Averill 1973), experienced by consumers in monopolistic markets may result in a

reduction in preference for the choice available. In other words, when consumers are

forced to buy from a particular vendor, their loyalty to that vendor may be negatively

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affected. Consider for example Microsoft and the Windows operating system. As the

dominant player in PC operating systems, M icrosoft has sparked substantial negative

reaction to its products and even loyal consumers (as measured by repeat purchases) have

expressed dissatisfaction and dislike for its products. M icrosoft has even gone so far as

to invest in its rivals (such as Apple computer) to ensure that users have choice (and to

appease anti-trust regulators). The point here is that in contrast to the advantages of

“getting big fast” and being a first mover, reactance theory suggests that stronger loyalty

is likely to develop when the consumer feels that they have a choice among products.

All in all, shopping on the internet appears to be an interesting real-world example

o f consumer decision making being influenced by the decreasing task completion times

that result when repeated experience leads to habitual use. Accordingly, it is an attractive

realm o f consumer behaviour within which to study the link between task learning and

consumer preference development. In addition, the growing role o f consumption on the

internet provides the opportunity to study repeated consumer choice behaviour in an

environment that parallels a real-world experience, while preserving the ability to control

key factors within that environment.

Switching Costs and Lock-In on the Internet

The spectre o f the internet as a frictionless marketplace grew from the belief that

in an electronic environment switching costs are almost non-existent and the competition

is always only a “click away” . This follows from classical economic theory, which

argues that lower search and evaluation costs lead to a state o f hyper-competition and

rock bottom prices (Bakos 1997). The idea is that a consumer looking to buy a particular

book can easily search through a number o f online bookstores and buy from the one with

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the lowest price. To be even more efficient, the same consumer can use a shopbot or

electronic recommendation agent to find the retailer with the lowest price on their behalf

(Smith and Brynjolfsson 2001). Especially in the case o f homogenous products such as

books and CDs, the majority o f consumers would consistently buy from the lowest priced

retailer. However, as previously mentioned, this theory has not been supported by the

empirical evidence. In fact, consumers appear to be conducting very little search before

making a purchase (Johnson, Moe, Fader, Bellman and Lohse 2003). Switching costs

seem to be greater and consumers seem more prone to becoming locked-in than many

pundits originally expected.

Lock-in occurs when buyers fail to search out alternatives or comparison shop as

a result o f substantial switching costs. Both lock-in and high switching costs have played

a prominent role in the rise o f the information economy (Shapiro and Varian 1999). For

example, Bell Atlantic became locked-in when it invested $3 billion in digital switches,

to run its telephone network, developed by the proprietary technology o f AT&T. From

that point on they were dependent on AT&T whenever they wanted to add to or expand

their network, and as a result Bell Atlantic became locked-in to buying switches from

AT&T. Another example o f lock-in occurred when millions o f users signed up for

M icrosoft’s Hotmail email accounts. Once Hotmail users had given out their email

addresses to colleagues, friends and family, they faced a switching cost if they moved to

another email provider (i.e., they would have to update all o f their contacts with a new

address).

However, in most cases the online shopper does not face the type o f switching

costs that have locked-in Bell Atlantic or Hotmail users. The internet consumer is not

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Kyle B. Murray, University o f Alberta

limited by contractual commitments, or proprietary technology, or even high search costs.

Nevertheless, it appears that they may become locked-in as a result o f brand-specific

training. Once they have learned to use a particular interface to the point where tasks that

were once time consuming become routine, a cost o f switching does arise (Murray and

Haubl 2002).

The Power Law of Practice

As we have already discussed, current evidence indicates that web site loyalty is

closely tied to decreasing time being spent at a site, which can be closely approximated

by the power law o f practice (Johnson et al 2003). With repeated exposure to a web site,

the consumer has the opportunity to practice using the interface. As the number o f

exposures increases, shoppers spend less time at the site and are able to complete tasks

more rapidly (Murray and Haubl 2002). Given that most online buying is done by

shoppers looking to simplify their lives and the best predictor o f online buying is “time

starvation” (Bellman et al. 1999), the potential exists for lock-in to occur as the consumer

learns about, or acquires skill related to, a particular site. Not surprisingly, this type o f

learning appears to be subject to the same type o f learning curve as the vast majority o f

cognitive and motor skills (for a review, see Newell and Rosenbloom 1981): the

observed reductions in task-completion time follow a pattern that is very closely

approximated by a power function (Johnson et al. 2003). It appears that “time starved”

internet consumers are becoming increasingly loyal as they learn more and more about a

particular site, and as a result become faster and faster at using the site.

It is commonly recognized that, in general, practice at a task results in improved

performance, and that more practice leads to even more improvement, but at a decreasing

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rate. In other words, the biggest gains in performance are made early on, and although

performance continues to improve, the rate o f improvement declines. This pattern of

learning, which adheres to the power law o f practice, is often referred to as a learning

curve. It is so ubiquitous in studies o f skill acquisition that “current theories o f skill

acquisition and automaticity treat the power law as a benchmark prediction that they must

make in order to be taken seriously” (Logan 1992, p. 883). According to the power law,

T = a + bN 'c,

where T is the time required to complete the task, a is the asymptote (the limit on

performance), b is the difference between the initial and the asymptotic performance, N is

the number o f exposures to the task (i.e., the amount o f practice), and the exponent c is

the learning rate.

The value o f practice is captured by changes in the term T, the time required to

complete the task. As the number of exposures to the task increases the time required to

complete the task decreases as a power function. For example, the more practice a driver

has at parallel parking the more quickly s/he is able to parallel park; however, while

practice increases the speed o f performance, the biggest gains are made early on and the

magnitude o f the increase in performance diminishes with additional practice. Similarly,

the more times a shopper buys a book from Amazon.com, the more rapidly s/he is able to

buy a book at Amazon - although, again, the rate o f improvement decreases over time.

Modern Automaticity

Researchers studying judgem ent and decision making have become increasingly

dissatisfied with models that view human behaviour solely as a product o f conscious

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choice (Lowenstein 2002). An alternative perspective argues that many decisions are

made automatically and with little conscious forethought or deliberation (Zaltman 2000).

However, while a great deal o f decision making research has focused on issues such as

the effort-accuracy trade-off (Payne, Bettman and Johnson 1990) and the role of

consumer involvement (Petty, Cacciopo and Schumann 1983), very little attention has

been given to the role o f automatic and habitual behaviour in a consumption context.

Yet, the reality o f human mental activity is that most o f what we do takes place

unconsciously (Bargh 1990; Lynch and Srull 1982). Along these lines, and following E.

J. Langer (1978), Bargh and Chartrand (1999) argue against the predominant view in

psychology that most o f human decision making is based on conscious or systematic

processing o f incoming information. Instead, they contend that the evidence indicates

that “the ability to exercise such conscious, intentional control is actually quite limited, so

that most o f moment-to-moment psychological life must occur through nonconscious

means if it is to occur at all (p. 462).”

Our ability to relegate the majority o f what we do to an unconscious level is an

essential component o f human functionality. This capability is a part o f the adaptive

nature o f human cognition that has allowed us to successfully m aster a wide variety of

tasks and to thrive in a large range o f environments (Anderson 1990). W e do not have to

consciously control basic functions such as breathing and we are able to automate more

complex tasks such as typing or shifting gears while driving, to the point where they

become effortless. We are able to automate these initially complex tasks because with

practice we can minimize the cognitive resources, and the amount o f time, required to

complete them.

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The increasing demands that modern society has placed on our time, in

combination with our ability to automate tasks over time, has resulted in a sort o f modern

automaticity. Cialdini (2001, p. 238) explains it this way:

Because technology can evolve much faster than we can, our natural capacity to process information is likely to be increasingly inadequate to handle the abundance o f change, choice, and the challenge that is characteristic o f modern life. More and more frequently, we will find ourselves in the position o f lower animals - with a mental apparatus that is unequipped to deal thoroughly with the intricacy and richness o f the outside environment. Unlike the lower animals, whose cognitive powers have always been relatively deficient, we have created our own deficiency by constructing a radically more complex world. The consequence o f our new deficiency is the same as that o f the animals’ long-standing one: when making a decision, we will less frequently engage in a fully considered analysis o f the total situation.

Cialdini’s claim that modem society has increased the demands on our time and

resources to the extent that we are unable to “engage in a fully considered analysis”

echoes Stigler and Becker’s (1977) contention that “the costs o f searching for information

and of applying the information to a new situation are such that habit is often a more

efficient way to deal with moderate or temporary changes in the environment than would

be a full, apparently utility-maximizing decision” (p. 82). Stigler and Becker take the

argument a step further and propose that such habits develop because the consumer has

invested time and effort in learning about the choice environment and developing skills

specific to that environment.

As Simon (1955) argued many years earlier, humans are satisficers rather than

maximizers. In other words, we are willing to pay a higher price for a book when the

value o f doing so, in terms o f time and effort, is justified. As we have seen, it appears

that with repeated practice at one site, consumers on the internet are willing to pay a

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Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.

Understanding the CL consumer Part 1 - Buying habits and customer loyalty Ewbank, Alison The Optician; May 3, 2013; 245, 6400; ProQuest Central pg. 38

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.