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The joint effect of framing and anchoring on internet buyers’ decision-making

Chin-Shan Wu a, Fei-Fei Cheng b,⇑

a Tunghai University, Department of Information Management, No. 181, Section 3, Taichung Port Rd., Taichung City 40704, Taiwan ROC b National Chung Hsing University, Institute of Technology Management, 250 Kuo Kuang Rd., Taichung 402, Taiwan

a r t i c l e i n f o

Article history:

Received 20 August 2009

Received in revised form 12 January 2011

Accepted 12 January 2011

Available online 20 January 2011

Keywords:

Anchor points

Anchoring effect

Cognitive bias

Experimental research

Framing effect

Internet advertising

Message framing

Product attributes

Purchase intention

Willingness to pay

a b s t r a c t

This article reports on an experiment that examines the influence of message framing and anchor points,

and the joint effect of these two information cues on Internet consumers’ judgments regarding attitude,purchase intention and willingness to pay. The role of participants’ subjective knowledge is also evalu-

ated. The experimental results suggest that message framing, which describes a product’s attribute in

positive or negative terms, significantly influences participants’ attitude toward and their intention to

buy the product. In addition, participants’ willingness to pay was significantly influenced by the presen-

tation of anchors embedded in banner advertisements. Further, a significant interaction effect for mes-

sage framing and anchor points indicate that their congruence enhances the effects of information

presentation on people’s responses. Specifically, describing a product attribute in positive terms along

with a high anchor point induces more favorable response than any other framing and anchoring com-

binations. Finally, online shoppers who are low in product knowledge are more susceptible to framing

and anchoring influences. The findings provide guidance for designing appropriate product and price cues

to induce Internet consumer responses that favor online retailers.

2011 Elsevier B.V. All rights reserved.

1. Introduction

The Internet has been growing rapidly. According to a recent re-

port (Internet World States 2010), the number of Internet users is

estimated to have reach 180 million in December 2009, up from 36

million in 2000. In addition, the dollar value of online retail sales

for the third quarter of 2008 was US$34.4 billion (US Census Bu-

reau 2008), an increase of 0.3% from the third quarter of 2007.

The development of e-commerce in Taiwan has expanded fast also.

More than 1.3 million users connected to the Internet in 2009

(TWNIC 2009) and the total online market volume reached

NT$243 million (about US$7.36 million in current exchange rate

terms for January 2011). The growth rate of the e-commerce mar-ket reached 21.9% in 2009, which surpassed the growth rate of the

physical retail channel, which actually declined. This number is

also larger than the growth rate of 15.4% in the US e-commerce

market estimated by Forrester Research. Thus, although Taiwan

is a densely populated country, more and more consumers have

been accepting this new distribution channel and this has pro-

moted the development of e-commerce in Taiwan.

In this context of e-commerce growth, it is important for both

online retailers and researchers to look for factors that influence

Internet consumers’ purchase decisions. Past studies have focused

on this issue froma variety of perspectives. Theseincludethe design

of appropriate online store atmosphere to influence online consum-

ers’ emotional and behavioral responses (Mandeland Johnson2002,

Cheng et al. 2009, Wu et al. 2008a,b), the influence of trust (Shnei-

derman 2000, Pavlou 2003, Jones and Leonard 2008), consumer

decision-making in an online environment (Häubl and Trifts 2000,

Häubl and Murray 2003), as well as the effects of Web site quality

on Internet users’ shopping decisions (Aladwani and Palvia 2002,

Kim and Stoel 2004, Liu et al. 2009, Huang et al. 2009). The current

study introduces a different perspective which draws on cognitivepsychology research and focuses on the influence of web site infor-

mation on Internet shoppers’ purchase responses.

Our research focus is based on the observation that while Inter-

net consumers today are faced with a variety of information when

they browse online retail stores, the information delivered through

Web pages mainly includes product attribute messages and price

information cues. Understanding how to use these two types of

Web site information to influence Internet shoppers’ decision-

making is an important yet overlooked issue. Based on the cogni-

tive psychology research, individual decision-making can be influ-

enced by the way information is presented, which includes two

types of cognitive biases: the framing bias and the anchoring bias.

1567-4223/$ - see front matter 2011 Elsevier B.V. All rights reserved.doi:10.1016/j.elerap.2011.01.002

⇑ Corresponding author.

E-mail addresses: [email protected] (C.-S. Wu), [email protected]

(F.-F. Cheng).

Electronic Commerce Research and Applications 10 (2011) 358–368

Contents lists available at ScienceDirect

Electronic Commerce Research and Applications

j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / e c r a

http://dx.doi.org/10.1016/j.elerap.2011.01.002mailto:[email protected]:[email protected]://dx.doi.org/10.1016/j.elerap.2011.01.002http://www.sciencedirect.com/science/journal/15674223http://www.elsevier.com/locate/ecrahttp://www.elsevier.com/locate/ecrahttp://www.sciencedirect.com/science/journal/15674223http://dx.doi.org/10.1016/j.elerap.2011.01.002mailto:[email protected]:[email protected]://dx.doi.org/10.1016/j.elerap.2011.01.002

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We can understand framing bias based on a well-known exper-

iment by Tversky and Kahneman (1981). They described an Asian

disease in terms of either the likelihood of lives saved (a positive

framing) or the likelihood of lives lost (a negative framing) to a

group of subjects. The results indicated that the relative attractive-

ness of options varies when the same decision problem is framed

in different ways. This phenomenon is referred to as framing effect

or the framing bias

. In addition to the framing bias, another cogni-

tive bias that results from information presentation is called the

anchoring effect . It describes the phenomenon that occurs when

an arbitrarily chosen reference point or anchor influences a deci-

sion-maker’s estimate of value (Slovic and Lichtenstein 1971). In

the online shopping context, framing messages are most likely to

be used in describing a product attribute as positive or negative.

The reference price of the product shown in a Web banner ad

may serve as an anchor point to influence an Internet shopper’s

decision behavior. Because consumers who browse the Web site

tend to perceive all its elements holistically rather than indepen-

dently, we think that the framing message and anchor point will

influence consumer behavior independent of one another, and that

there may also be a joint effect on Internet shoppers’ responses.

The Internet provides an ever-increasing amount of product

information (Lee and Lee 2004), so online consumers often rely

on heuristics to make decisions. Park and Lessig (1981) assert that

subjective knowledge provides information about decision-mak-

ers’ systematic biases in decisions. Thus, we also investigated the

role of Internet consumers’ knowledge level in moderating the

occurrence of the framing effect and the anchoring effect.

Overall then, we argue that Internet shoppers’ purchase deci-

sions may be influencedby theway that product information is pre-

sentedto them– in eithera positiveor a negativeways – suchthata

discernible framing effect will occur. Also, the presentation of price

information is another possible source that may induce the anchor-

ing effect. Internet shoppers perceive productand price information

in a Web site’s banner holistically, rather than independently. So

how these two elements jointly influence consumer decisions is

an important issue. In addition, the role of consumer productknowledge plays a role in their decision-making process. Thus, a

goal of thisresearchto investigate howmessage framing andanchor

points independently and jointly influence Internet shopper deci-

sions, as well as the role of consumer knowledge in this context.

The findings of this research can provide insights regarding how

to present information in Web pages to induce consumer responses

that arefavorable for online retailers. The results can also help us to

understand under what conditions consumers are less likely to be

affected by external reference prices provided by banner ads and

the framing messages they contain for product attributes.

2. Theory

A rational decision-maker is expected to make similar decisionsno matter how the same decision problem is described or framed.

However, human decision-makers usually lack the knowledge,

computational skills or time resources necessary to make decisions

in a manner compatible with Simon’s (1957) economic theory of

rational behavior. Instead, decision-makers tend to adopt heuris-

tics to save effort ( Johnson and Payne 1985, Payne et al. 1988,

Thorngate 1980), but decision biases or cognitive biases may occur

as a result. One way of viewing cognitive biases is that they are sys-

tematic deviations from rationality. There are various kinds of cog-

nitive biases that have been identified by decision theory

researchers. The framing effect and the anchoring effect are both

well-known cognitive biases that have been explored in the re-

search of Tversky and Kahneman (1981), and result based on the

way information is presented to a decision-maker.

2.1. The framing effect

The framing effect can be viewed in terms of three different types

of framing: attribute framing, goal framing, and risky choice fram-

ing effects (Levin et al. 1998). In attribute framing , a single attribute

of a given object is framed positively or negatively. In goal framing ,

the persuasive message is framed to stress the positive or negative

consequences of performing an act or not. Risky choice framing

oc-

curs when the choice between a risky and a riskless option of equal

expected value depend on whether the options are described in po-

sitive terms or in negative terms. We will focus only on attribute

framing because it is the simplest case, and because it is especially

useful for gaining a basic understanding of how the descriptive va-

lence influences information processing (Levin et al. 1998).

The attribute framing effect occurs when individuals’ judgments

vary as a function of the labels used to describe specific object attri-

butes ( Johnson and Levin 1985). For example, Levin et al. (1985)

examined the effect of message framing in three tasks and a statis-

tically reliable framing effect was observed. More favorable ratings

were produced when the key attributes were expressed in positive

terms than when they were expressed in negative terms.

Moreover, in Levin and Gaeth’s (1988) study, the product

‘‘ground beef’’ was framed as either ‘‘75% lean’’ or ‘‘25% fat’’ and

was presented to two groups of subjects. The results indicate that

the participants’ evaluations were more favorable when the beef

was described in percent-lean terms than when it was described

in percent-fat terms. Other studies (Kramer 1989, Loke and Tan

1992, Levin et al. 1998, 2002) also have similar findings that the

same alternative is rated more favorably when a key attribute is

framed in positive terms rather than in negative terms.

Levin (1987) suggested that the framing effect occurs because

positively-framed or negatively-framed information is believed to

be associated with a more favorable or unfavorable encoding in a

person’s memory. Subjects’ favorable associations in memory can

be evoked by labeling a product’s attribute in a positive manner.

In contrast, when the information is labeled negatively, unfavor-

able associations in memory tend to be evoked, and this resultsin less favorable cognitive responses.

The dependent measure of the attribute framing effect is evalu-

ation (Levenet al.1998), whichcan take theformof ratings of favor-

ability. This include perceptions of the quality of the product (Levin

and Gaeth 1988), attitude toward the target product (Shiv et al.

1997) or the advertisement (Smith 1996), willingness to purchase

theproduct (Zhang andBuda 1999), andwillingness to pay (Howard

and Salkeld 2009). We will measure consumer attitudes toward the

product, purchase intention and willingness to pay for the product

in this study to examine the effect of attribute framing messages.

Based on the above discussion, we propose the following

hypotheses:

Hypothesis 1a (The Framing and Product Attitude Hypothesis). Par-ticipants in the positive framing condition will have a more

positive attitude toward the target product than their counterparts

in the negative framing condition.

Hypothesis 1b (The Framing and Intention to Buy Hypothesis). Par-

ticipants in the positive framing condition will reveal a higher

intention to buy the target product than their counterparts in the

negative framing condition.

Hypothesis 1c (The Framing and Willingness to Pay Hypothe-

sis). Participants in the positive framing condition will reveal a

higher willingness to pay for the target product than their counter-

parts in the negative framing condition.

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2.2. The anchoring effect

Anchoring and adjustment is an heuristic that is often employed

to make probability estimates and value predictions (Tversky and

Kahneman 1974). In most studies, anchoring experiments are ini-

tiated by explicitly asking people to compare the anchoring value

to some target (Tversky and Kahneman 1974, Strack and Musswe-

iler 1997, Wong and Kwong 2000, Kristensen and Gärling 2000,

Mussweiler and Strack 2000). Basically, a high-value and a low-va-

lue anchor point typically are provided to two groups of subjects,

which serve as the basis of comparison. Subjects then use an

adjustment process to produce their estimates (Wilson et al.

1996, Strack and Mussweiler 1997). Finally, the adjustment pro-

cess terminates in a range between the upper or lower bound on

value and the actual value (Strack and Mussweiler 1997). People’s

final estimates will be lower if they began with a lower-value an-

chor point than if they began with a high-value anchor point. The

gap between the final estimate and the actual value often arises

because the person who makes the estimate does not make enough

of an adjustment. Lopes (1982) considers this to be one of the pos-

sible sources of the anchoring bias or anchoring effect. (See Chap-

man and Johnson (2002) for additional discussion.)

The anchoring effect is a robust phenomenon that has been ob-

served in many domains. These include numerical estimation

(Tversky and Kahneman 1974, Mussweiler and Strack 2000), spou-

sal preference prediction (Davis et al. 1986), and negotiation (Ritov

1996, Kristensen and Gärling 1997). A general finding in past re-

search suggests that the anchoring value has a pronounced effect

on the subsequent response. A higher anchor point leads to a high-

er final estimate than lower anchor point does (Tversky and Kahn-

eman 1974, Northcraft and Neale 1987, Wilson et al. 1996, Strack

and Mussweiler 1997, Mussweiler and Strack 1999). For example,

participants in Northcraft and Neale (1987) were asked to make

pricing decisions about real estate properties. The listing price for

the property served as anchor point, and different groups of sub-

jects were assigned to four listing price conditions. The results

indicated that the anchor points tended to influence the subjects’value estimates. The higher the anchor points, the higher were

the final estimates.

Consumers form their preferences based on the available infor-

mation, such as reference prices, when there is uncertainty about

product quality (Scitovsky 1944–1945). In general, consumers tend

to infer product quality from the reference price (McConnell

1968a,b, Shapiro 1970). A higher price is believed to be associated

with higher quality than a lower price is. Thus, it is reasonable to

argue that consumers will have more a positive attitude and higher

intention to buy when they are exposed to higher-value anchor

points than those exposed to lower-value anchor points.

In addition, marketing researchers have provided some evi-

dence regarding the anchoring effects on consumers’ price judg-

ments (Ariely et al. 2003, Green et al. 1998, Wu et al. 2008a,b,2011). In this study, we use Internet buyer willingness to pay to

capture the consumer price judgments. Willingness to pay denotes

the maximum price a buyer is willing to pay for a given quantity of

a good. It is a subjective value that the buyer assigns to that

quantity (Wertenbroch and Skiera 2002). External reference prices

provided to consumers through channels such as price advertise-

ments, catalog listings, and consumer price guides often serve as

anchors to influence consumer price perceptions (Biswas and Blair

1991). Thus, we assert the following group of hypotheses:

Hypothesis 2a (The Anchoring Condition and Product Attitude

Hypothesis). Participants in high anchor condition will have a

more positive attitude toward the target product than their

counterparts in the low anchor condition.

Hypothesis 2b (The Anchoring Condition and Intention to Buy

Hypothesis). Participants in high anchor condition will reveal a

higher intention to buy the target product than their counterparts

in the low anchor condition.

Hypothesis 2c (The Anchoring Condition and Willingness to Pay

Hypothesis). Participants in high anchor condition will reveal a

higher willingness to pay than their counterparts in the low anchorcondition.

2.3. The joint effect of framing and anchoring

Message framing is an important aspect of communication

strategy. In contrast, the reference price is an important factor that

influences consumers’ perceived quality of the product, as well as

their willingness to pay. Each topic has been studied in the past

in isolation, but investigations regarding their joint effects are rare.

We extend the previous research by proposing that the joint effect

of message framing and anchor points will be significant with re-

spect to Internet consumers’ attitude, purchase intention and will-

ingness to pay.

When consumers are exposed to positive messages, they arelikely to form a higher expectation for product quality. A positive

message accompanied by a high-value anchor point can deliver a

consistent message that the product is of good quality and worth-

while for consumers to pay a higher price to buy it. Thus, the posi-

tive messages accompanied by a high-value reference price

embedded in a Web banner may result in higher consumer prefer-

ences and higher willingness to pay. By contrast, when consumers

are exposed to negative messages, they may form a lower expecta-

tion about product quality. If the negative messages are accompa-

nied by high-value anchor points, these conflicting elements will

tend to result in a less favorable product attitude and purchase

intention on the consumers’ part.

Based on the above discussion, we assert the following addi-

tional hypotheses:

Hypothesis 3a (The Product Attitude Interaction Hypothesis). The

interaction effect between message framing and anchor point will

be significant with respect to the participants’ attitude toward the

target product.

Hypothesis 3b (The Intention to Buy Interaction Hypothesis). The


be significant with respect to the participants’ intention to buy.

Hypothesis 3c (The Willingness to Pay Interaction Hypothesis). The


be significant with respect to on participants’ willingness to pay.

2.4. Consumers’ product knowledge

The subjective knowledge is the consumers’ degree of confi-

dence in his or her knowledge level (Brucks 1985). The role of

knowledge in anchoring effect studies has resulted in different

conclusions. For example, Wilson et al. (1996) measured partici-

pants’ knowledge by asking them to rate how knowledgeable they

were about the target to be estimated. Their results demonstrated

that the anchor manipulation is moderated by people’s knowledge.

Specifically, the anchoring effect occurred only among people who

with less knowledge. In addition, Northcraft and Neale (1987)

examined the anchoring effect for estimating the price of real

estate properties with students amateurs and real estate agent

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experts. The results indicated that estimations provided by both

subject populations were significantly biased toward the anchor

point that was provided by the experimenter. As a result, we con-

clude that experts are also susceptible to anchoring bias.

When consumers make decisions, they may use price as a cue

for product quality (Monroe and Krishnan, 1985). However, this

price and perceived product quality relationship will be influenced

by consumer knowledge ( Jacoby et al. 1971, Rao 1971, Shapiro

1968). Novice buyers tend to use price as an indicator of quality

to a greater extent than expert buyers. On the Internet, when con-

sumers are planning to buy something, they may look for cues that

are presented on Web pages. It has been suggested that consumers

who have prior knowledge about products they want to purchase

do not need to search for information from external sources

(Brucks 1985), such as banner advertisement. Thus, we expect that

people who know less about the target product are more suscepti-

ble to anchoring bias than their counterparts who have a high level

of product knowledge.

Previous research has asserted that consumers who have less

prior product knowledge tend to make decisions based on incom-

plete experience (Bettman and Park 1980), while consumers with

more product knowledge are able to develop a more complete cog-

nitive structure to process and analyze the data they obtain (Alba

and Hutchinson 1987). Kühberger (1998) suggested that, based

on the meta-analysis results, the influence of message framing

on novices and experts may differ. Experts are less likely to be

influenced by the framing effect. We expect that people who are

less knowledgeable about the target product will be more suscep-

tible to framing bias than their counterparts who have more prior

knowledge.

Based on the above discussion, consumers with lower product

knowledge are more susceptible to both framing and anchoring ef-

fect. Thus, it is reasonable to expect that the joint effect of framing

and anchoring will be different for participants with different prior

knowledge levels. Consumers who are low in product knowledge

will be more susceptible to the joint effect of framing and anchor-

ing. We propose:

Hypothesis 4 (The Knowledge Effect Hypothesis). The interaction

effect between message framing and anchor point will be signif-

icantly different for participants with different prior knowledge

levels.

3. Methods

3.1. Design and subjects

We recruited 318 undergraduate students from a several uni-

versities in Taiwan, who were randomly assigned to one of the four

conditions in a 2 (attribute framing: positive vs. negative) 2 (an-

chor points: high vs. low) between-subjects design. Each partici-pant received a NT$100 (about US$3) McDonald coupon for their

participation. There are 93, 70, 72 and 83 participants in the

respective groups: Group 1 (negative framing, low anchor), Group

2 (negative framing, high anchor), Group 3 (positive framing, low

anchor) and Group 4 (positive framing, high anchor).

3.2. Procedure and experimental manipulation

Our experiment was conducted in a computer laboratory

equipped with forty PCs. All the experimental stimuli and mea-

surements were implemented on an experimental Web site. After

entering the laboratory, the participants were instructed to enter

the experimental Web site, which included three primary pages.

The first page described a fictitious online store selling all types

of electronic appliances. These included mobile phones, PDAs,

and so on. On the second page, information of the target product

is presented. The product is an electronic translator with a fictional

brand name ‘‘YiShen.’’ In addition, the framing messages and an-

chor points were also manipulated on the second page.

We described the electronic translator as follow: ‘‘The YiShen

electronic translator is the latest electronic translator, equipped

with all the functions that can be found in most of the powerful

products on the market. In addition, it offers built-in English-to-

Chinese and Chinese-to-English two-way full-text translation.

You can type in an English sentence and it will be translated into

Chinese. You can also write Chinese in a sentence and YiShen will

translate it into English. This device will serve different groups,

especially students, foreign languages learners, businessmen, sec-

retaries, and travelers.’’

The key attribute of an electronic translator is the accuracy of its

translation capability, and whether this is framed in a positive or a

negative way. In the positive framing condition, the translator was

described as: ‘‘The translator offers built-in English-to-Chinese and

Chinese-to-English two-way full-text translation with up to 80%

translation accuracy.’’ In the negative framing condition, the trans-

lator was described in this way: ‘‘The translator offers built-in Eng-

lish-to-Chinese and Chinese-to-English two-way full-text

translation with up to a 20% error rate. The manipulation of 80%

and 20% in framing message was adopted from the attribute fram-

ing design of Levin et al. (2002), in which ‘‘ground beef’’ was de-

scribed as ‘‘80% lean’’ or ‘‘20% fat.’’ Some other studies use 75%

and 25% (Levin and Gaeth 1988) to describe their product attri-

butes. Krishnamurthy et al. (2001) examined the effectiveness le-

vel (10% vs. 30% vs. 50% vs. 70% vs. 90%) of message framing.

Their results suggest the attribute framing effects are relatively

stable across all of the different effectiveness levels.

We manipulated the anchor in this study with a banner adver-

tisement shown on the top of the product description page. To be

more specific, the participants viewed the Web page, which in-

cludes a description of the electronic translator. A banner embed-

ded in the upper side of the same Web page illustrated anelectronic translator ad with a reference price as its anchor point

of NT$38,800 (a high-value anchor of about US$1140) or NT$900

(a low-value anchor of about US$26), based on the manipulation

of the anchor points. The anchor points were selected based on

the following steps. First, the market prices for the electronic trans-

lator across four popular brands in Taiwan were surveyed. The re-

sults showed that the lowest price was about NT$900, and the

highest price was about NT$9700, with an average price at about

NT$5000.

Second, the target product in this study is an electronic transla-

tor that is able to translate full English sentences into Chinese and

vice versa. Although this translator has not been introduced to the

market yet, the researchers interviewed five experts in electronic

translator manufacturing for their opinions about the suggestedprices, if the translators were equipped with a full-text translation

function. The average price suggested by the five experts was

around NT$38,000.

Third, there has been a study that manipulated the anchor point

in the Internet environment (Wu et al. 2008a,b) and the low-value

and high-value anchor points were NT$900 and NT$38,800, while

the target product in their study was a mobile phone. Because

the lowest price and the average suggested price of the translator

in current study is quite close to the anchor points used in Wu

et al. (2008a,b), in which a significant anchoring effect was ob-

served. Thus, we selected NT$900 and NT$38,800 as the low-value

and high-value anchor points for our current study. (A screen shot

of the experimental Web site with a high-value anchor point and

positive framing condition is shown in Fig. 1.)


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Finally, the participants’ attitude toward the electronic transla-

tor, their intention to buy it and their willingness to pay were mea-

sured on the third page.

After the participants entered the laboratory, they were in-

structed to enter the experimental Web site, which randomly as-

signed each subject to one of the four experimental conditions.

The subjects in the first group were required to read the informa-

tion about the electronic translator that described it in positive

terms. At the same time, these subjects were exposed to a Web

banner that embedded an electronic translator advertisement with

a high-value anchor point of NT$38,800. Likewise, the subjects in

the second group were exposed to positive product information

and a Web banner with a low-value anchor point of NT$900. Par-

ticipants in the third and fourth conditions were exposed to nega-

tive framing treatments with the Web banner embedding either a

high-value or a low-value anchor point.

3.3. Experimental measures

The instrument for this study was mainly based on existing

scales developed in prior studies. Purchase intention was mea-

sured using three items based on Ajzen and Fishbein (1980). Sim-

ilar items were adapted and validated by Moon and Kim (2001)

and Kim et al. (2007). Subjects were asked to rate their intention

to buy the electronic translator on a 7-point Likert scale in terms

of the following three items: (1) I intend to buy this electronic

translator. (2) I will suggest to my friends that they should buy this

electronic translator (3) I will buy this electronic translator even if I

have already have one. In addition, three items that were com-

monly used to measure attitude in Internet shopping-related

(Moon and Kim 2001) and framing-related (Levin et al. 2002) stud-

ies were used in our instruments. Specifically, attitude was mea-

sured by a three-item semantic differential on a seven-point

scale, which included three pairs of adjectives: bad/good, unattrac-

tive/attractive, and unlikable/likable.

For our subsequent analysis, we averaged the ratings of the

three items related to attitude and intention to buy into a singleitem each. In addition, we used an open question to measure the

participants’ willingness to pay by asking the following question:

‘‘How much are you willing to pay for the electronic translator that

you have just seen?’’ Finally, the participants’ subjective knowl-

edge was measured based on the instrument used in Park and

Moon (2003). It includes three questions on a five-point scale:

(1) Compared to other students, how familiar do you think you

are with electronic translators? (2) Do you know what attributes

of an electronic translator determine the functionality of an elec-

tronic translator? (3) Do you think you can make a satisfactory

purchase of a computer based on your own knowledge without an-

other person’s help?

4. Analysis

4.1. Demographic information

Demographic information on the participants in the current

study indicated that the majority were males (62.3%) with a college

or university educational level (98.1%), and 6–10 years of Internet

experience (54.7%). Differences in the demographics of participantsin the above four groups were examined by conducting v2 tests.

The results indicated that there were no significant differences

for all of the demographic variables collected in current study

(gender: v2 = 7.06, not significant; educational level: v2 = 6.61,

not significant; Internet experience: v2 = 12.55, not significant).

In addition, electronic dictionaries are a popular product among

undergraduate students in Taiwan because most of them are using

English textbooks and are required to read English papers. In the

current study, about 92% of our subjects owned an electronic

translator.

4.2. Validity and reliability test

We assessed two types of validity: convergent validity and dis-

criminant validity. Convergent validity of the constructs is assessed

by examining the factor loadings of all indicators and the average

variance extracted (AVE) from the measurements (Hair et al.

1998). First, all of the indicator factor loadings must exceed the

recommended value of 0.7. (See Table 1.) Second, the AVE values

should be greater than the generally recognized 0.5 cut-off point,

indicating that the majority of the variance is accounted for by

the construct (Fornell and Larcker 1981). Table 2 shows that the

average variance extracted by the measurements ranges from

0.77 to 0.82, which is above the acceptable value.

Discriminant validity indicates the extent to which a given con-

struct is different from the other constructs (Bagozzi et al. 1991).

One criterion for adequate discriminant validity is that the square

root of the AVE for each construct should exceed the correlation

shared between the construct and other constructs in the researchmodel (Fornell and Larcker 1981). The diagonal of Table 2 contains

the square root of the AVEs. All AVEs are greater than the off-diag-

onal elements in the corresponding rows and columns, demon-

strating discriminant validity. Thus, the above analysis confirms

the reliability and validity of the survey instrument for further

analysis.

Table 1 provides the reliabilities for each multi-item construct

calculated using Cronbach’s a. The values range from 0.85 (for

intention) to 0.94 (for attitude). The statistics indicate that all

the constructs had a higher reliability coefficient than the bench-

mark of 0.70 and this suggests a high internal reliability of the

data.

Fig. 1. Screen shot of the experimental web site (high-value anchor, positive framing condition).


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4.3. The main and interaction effect of framing and anchoring

A 2 (attribute framing: positive vs. negative) 2 (anchor points:

high vs. low) analysis of variance (ANOVA) was used to test the

hypotheses regarding the main effects of the attribute framing

messages and anchors on participant attitude, intention to buy,

and willingness to pay. The results indicate a significant main ef-

fect for attribute framing on participant attitude and intention tobuy, and a significant main effect for anchor points on participant

willingness to pay (see Table 2). Thus, Hypotheses 1, 2 and 4 were

supported.

The significant main effect for framing manipulation allowed us

to further examine the means in each framing condition. The re-

sults indicate that participants in the positive framing condition

rated the product more favorably (M attitude = 5.11) and revealed a

higher intention to buy (M intention = 4.03) than those in the negative

framing condition (M attitude = 4.67, M intention = 3.72). In addition, a

significant anchoring effect was observed. Participants’ willingness

to pay in the high-value and low-value anchoring conditions was

also examined. The results indicate that participants on average

are willing to pay more (M = 8348.2) in the high-value anchoring

condition than that in the low-value anchoring condition(M = 3098.34).

In addition, we observed a significant framing by anchoring

interaction effect on all of the three dependent variables (see Ta-

ble 3). Thus, we conducted further analysis to examine the signif-

icant interaction effect for framing based on the anchoring effect

(see Fig. 2).

The data presented in Fig. 2 indicate that the positive and neg-

ative framing messages and high and low anchor points jointly

influence the participants’ attitudes, intention to buy, and willing-

ness to pay. Thus, Hypotheses 7–9 were supported by our data.

4.4. The role of product knowledge in the framing and anchoring effect

The next step is to examine the role of the participants’ knowl-edge on the framing and anchoring effects. To analyze the moder-

ating effect of knowledge on the framing and anchoring effect, we

categorized the participants into high and low knowledge levels

according to their scores on the instruments. A participant’s prod-

uct category knowledge level was determined by percentile values.

The overall knowledge scores were divided into two groups of

equal size split by the median, and the value of the cut point was

3.34. Finally, we classified 160 of the participants as low in product

knowledge, and another 158 people as high in product knowledge.The mean score in low knowledge group is 2.50 and 4.45 in high

knowledge group. The difference between two groups is significant

( p < 0.001) and thus demonstrates that participants from two

groups have different levels of product knowledge.

We conducted three independent ANOVA tests for each knowl-

edge level group in which the framing messages (positive and neg-

ative) and anchor points (high and low) were the independent

variables, and participants’ attitude, purchase intention and will-

ingness to pay were the dependent variables. Our data analysis re-

sults are shown in Table 4.

As indicated in Table 4, framing has a significant main effect on

attitude (F = 4.24, p < 0.05), while the main effect of anchoring was

observed on willingness to pay (F = 45.11, p < .001) for the low

knowledge group. In addition, the interaction effect is significantwith respect to attitude (F = 11.49, p < 0.01) and intention

(F = 10.01, p < 0.01) for the low knowledge group. For the high

knowledge group, the main effect of framing is significant with re-

spect to attitude (F = 9.06, p < 0.01) and intention (F = 4.87,

p < 0.05), while a significant anchoring effect was also observed

for willingness to pay (F = 38.24, p < 0.001). The interaction effect

is observed only for attitude (F = 7.19, p < 0.01). These results seem

to indicate that the high knowledge group is less influenced by

framing and anchoring biases.

We further examined the joint effect of different knowledge

groups by drawing a set of figures. Figs. 3 and 4 illustrated the post

hoc analysis for the low and high knowledge groups.

As indicated in Fig. 3, participants who know less about the

electronic translator revealed significant anchoring effects whenthe product was described in positive terms, and high-value anchor

Table 1

Validity and reliability of attitude and intention scales.

Attitude Intention Knowledge

Likable/not likeable 0.94 –

Attractive/unattractive 0.91 –

Good/bad 0.87 –

I will buy this electronic translator even if I have already have one – .85

I intend to buy this electronic translator – 0.91

I will suggest to my friends that they should buy this electronic translator – 0.88

(1) Compared to other students, how familiar do you think you are with electronic translators? – – 0.888

(2) Do you know what attributes of an electronic translator determine its functionality? – – 0.913

(3) Do you think you can make a satisfactory purchase of a computer based on only your own knowledge,

without another person’s help?

– – 0.834

Variance explained (%) 82.64 76.83 77.25

Reliability 0.89 0.85 0.85

Table 2

Average variance extracted and correlations of constructs.

AVEa Attitude Intention Knowledge

Attitude 0.82 0.91b

Intention 0.79 0.635 0.88Knowledge 0.77 0.109 0.207 0.88

a Average variance extracted (AVE) = (Rstandardized loading2)/[(Rstandardized

loading2) +Re j].b The shaded numbers in the diagonal row are square roots of the AVE.

Off-diagonal elements are the correlations among constructs.

Table 3

Results of ANOVA test.

Source Dependent variables

Attitude Intention Willingness to pay

Framing 11.989***

5.825*

0.699Anchoring 0.009 0.899 81.725***

Framing anchoring 15.156*** 5.571* 3.959*

* p < 0.05.*** p < 0.001.


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points resulted in more favorable responses and higher willingnessto pay. When the electronic translator was described in negative

terms, a low-value anchor point in the Web banner induced higher

intention to buy but a lower willingness to pay compared with the

high-value anchor point group.

The results shown in Fig. 4 are clear. The framing and anchoring

messages were lessinfluentialfor participantswith more knowledge

about the electronic translator. No anchoring effect occurs when the

product is describedin positiveway. A lowanchor pointinthebanner

will induce a more positive attitude toward the product but a lower

willingness to pay when it is described in negative terms.

5. Discussion

The current study examines the effects of two well-known cog-nitive biases, the framing effect and the anchoring effect, on Inter-

net buyer responses regarding attitudes, purchase intention andwillingness to pay. The joint influence of message framing and

price anchor information has been rarely discussed in past studies.

To test the proposed hypotheses, we employed a laboratory exper-

iment and presented experimental stimuli via an experimental

Web site. Framing messages that described the key attribute, the

translation accuracy of an electronic translator, were presented

to the participants along with either high-value or low-value an-

chor points displayed in banner advertisements. We obtained sev-

eral interesting findings observed from the experiment.

First, we found a significant framing effect on participants’ atti-

tude and purchase intention. Framing messages that describe the

key attribute of the electronic translator in positive terms resulted

in more favorable responses than negative terms did. This finding

is consistent with the findings of prior studies of the attributeframing effect (Levin and Gaeth 1988, Kramer 1989, Loke and

Fig. 2. Participants’ responses in different conditions.

Table 4

Results of ANOVA test for the different product knowledge level groups.

Product knowledge level group Source Dependent variables

Attitude Intention Willingness to pay

Low Framing 4.238* 2.503 0.122

Anchoring 0.193 0.237 45.111***

Framing anchoring 11.493*** 10.009** 0.337

High Framing 9.058** 4.873* 1.661

Anchoring 0.430 0.942 38.241***

Framing anchoring 7.189** 1.359 3.877

* p < 0.05.** p < 0.01.*** p < 0.001.


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Tan 1992, Levin et al. 1998, 2002) and it provides evidence regard-

ing the influence of framing messages on Internet buyers’ judg-

ment. However, the experimental results reveal no significant

influence of the attribute framing message on the respondents’

willingness to pay. Howard and Salkeld (2009) are among a small

number of researchers who have addressed the influence of attri-

bute framing on consumer willingness to pay. In their study, pa-

tients’ willingness to pay for screening for colorectal cancer

Fig. 3. Participants’ responses in different conditions (low knowledge group).

Fig. 4. Participants’ responses in different conditions (high product knowledge group).


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under different attribute framing conditions was measured. The re-

sults suggested that attribute framing messages influence patients’

willingness to pay for the examination. The experimental context

in Howard and Salkeld (2009) is medical examination. We believe

that medical examination involves more risk-related issues be-

cause it is related to personal health and disease concerns. Thus,

the attribute framing messages are influential in a broader range

than a less risky context like Internet shopping. Even though differ-

ent results have been obtained in different studies, the influence of

attribute framing on people’s willingness to pay is worthy of closer

investigation because the related empirical evidence regarding this

issue is still limited.

Second, participants’ willingness to pay revealed a significant

anchoring effect and this result corresponds to the findings in pre-

vious literature (Ariely et al. 2003, Green et al. 1998). Participants

exposed to a higher anchor condition reveal a higher willingness to

pay than that is seen under the low anchor condition. This result

extends the anchoring literature in two aspects. First, the results

provide direct evidence regarding the influence of the anchoring

effect in the Internet shopping context. Second, most of the anchor-

ing experiments in prior research were initiated by explicitly ask-

ing people to compare the anchoring value to the target (a

comparative judgment) followed by asking them to provide their

estimate of the target value (the absolute estimate) (Tversky and

Kahneman 1974, Strack and Mussweiler 1997, Wong and Kwong

2000, Kristensen and Gärling 2000, Mussweiler and Strack 2000).

However, this experimental design is inappropriate in the online

retailing environment because one can hardly ask consumers to

answer a comparative question before they make their purchase

decisions. The experiment in present study is designed to embed

the anchor points in a banner advertisement. Our results suggest

that there is a significant anchoring effect that can be replicated

by a research design that involves only the absolute estimate pro-

cess. Thus, our research represents an advance in terms of the prac-

tical design of an experiment to assess the influence of the

anchoring effect in the Internet shopping context.

The influence of anchor points on participants’ attitudes andbehavioral intentions was not observed though. We believe this

is another type of evidence regarding anchor–target relevancy.

The anchor point in this study is the reference price of product,

which may actually be relevant or irrelevant to the target product.

Measurements on the participants’ decisions include their attitude,

behavioral intention and willingness to pay. Among these, only

willingness to pay has the same dimension as the anchor, the ref-

erence price. This argument has been supported by various anchor-

ing studies (Chapman and Johnson, 1994, Mussweiler and Strack

2001). For example, Strack and Mussweiler (1997) demonstrated

that the anchoring effect is weak when the anchor and the estimate

focus on different dimensions of the same target (e.g., the height

and the width of Brandenburg Gate).

Further, the significant interaction effect for message framingby anchoring suggests that the congruence between the framing

message and the anchor point strengthens the joint effect on the

participants’ evaluations. For example, describing the product

attribute in positive terms along with a high-value anchor point re-

sults in more favorable responses than any other framing and

anchoring combination. In addition, a negative attribute framing

message together with a low-value anchor point results in more

favorable responses than the combination of negative framing

and a high-value anchoring advertisement. This might be ex-

plained by the argument that consumers’ inferred beliefs about

the product are based on other attribute beliefs (Erickson et al.

1984, Huber and McCann 1982, John et al. 1986). Participants in

our study infer product quality on the basis of price displayed in

the advertisement, and so people who are exposed to a high-valueanchoring condition tend to believe that the electronic translator

must be in high quality too. At the same time, then the electronic

translator was described in positive terms, this seems to strength-

en the participants’ belief regarding the quality of the product.

Thus, we see that it results in the most favorable responses in

terms of attitude, intention to buy and willingness to pay. Simi-

larly, when the participants were exposed to the condition that fo-

cused on the negative attributes of the electronic translator, less

favorable responses are engendered. Under this condition, a low-

value anchoring advertisement seems more plausible than a

high-value anchor point, so more favorable responses are formed.

In addition to the evaluation we offered regarding attitude and

purchase intention, the results of our study also suggest that par-

ticipants’ willingness to pay was mainly influenced by the anchor

points, especially when the product attribute was described in po-

sitive rather than in negative terms.

The above discussion revealed that the attribute framing mes-

sage will only influence consumers’ product attitudes and purchase

intention, but not their willingness to pay. In addition, the adver-

tisement will influence potential consumers’ willingness to pay

but not their product attitudes and purchase intention when the

reference price is the only information that is provided. Therefore,

a better way is to combine the reference price with other positive

attribute messages to strengthen the influence that the reference

price will have on consumers’ responses.

Finally, the results from this study suggest that the joint effect

of framing and anchoring on consumers’ responses varies with

the level of consumer product knowledge. Consumers with less

product knowledge are more susceptible to the joint influence of

framing and anchoring than those with more product knowledge.

Although prior research has suggested that subjects with lowprod-

uct knowledge are more vulnerable to the framing and anchoring

effects, their susceptibility to the joint effect is not fully under-

stood. Our results provide evidence regarding this issue.

6. Conclusion

6.1. Implications

We observed a significant framing effect that suggests the influ-

ence of message framing can be replicated in the Internet purchase

context, which has been neglected in prior research. Further, the

experimental design of anchor manipulation in our experiment of-

fers a practical way to influence participants’ price perception by

embedding the anchor in banner ads without asking them to make

comparative judgments before they make their final value esti-

mates. This experimental design is more appropriate especially in

the online retailing context, where one can hardly ask consumers

to make any specific comparisons at all.

The contributions of this study come from extending previous

research on the framing effect and anchoring effect by considering

the joint effect of these two well-known cognitive biases. The re-sults obtained in our experimental research suggest that the con-

gruence of message framing and the anchor point enhances the

effects of information presentation on consumer responses regard-

ing product attitudes, purchase intention and willingness to pay. In

addition, the results of this study provide evidence that online con-

sumers perceive Web page elements holistically, rather than inde-

pendently. Thus, designing all the elements in a congruent way

(especially by presenting a positive framing message along with

a high reference price) will be more effective in influencing online

consumer responses. In this regard, our findings are helpful for

practitioners to design messages related to product descriptions

and price advertisements that will favor the online retailers.

Further, this study contributes to the existing literature regard-

ing the role of online consumer product knowledge, especially re-lated to the joint effects that have been evaluated in framing and


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anchoring studies. Previous research has suggested that consumers

who are less knowledgeable will be more influenced by either the

framing effect or the anchoring effect. Our results show that they

are also susceptible to the joint influence of message framing and

anchor points. Therefore, it is very important for the online retail-

ers to understand their target consumers’ knowledge level. For

consumers who are low in product knowledge, presenting positive

product information with a high reference price will result in more

favorable responses and higher willingness to pay. However, this

might not be a good strategy with respect to consumers who are

high in product knowledge. According to the elaboration likelihood

model (Petty and Cacioppo 1983, 1986), when individuals are

highly involved or more knowledgeable, a more central route to

persuasion should be particularly effective, while a peripheral

route should be better when consumer involvement is low or they

are less knowledgeable (Petty et al. 1983). The positive and nega-

tive framing messages and high and low anchoring effects in the

current study are all peripheral cues and thus are more influential

for consumers with less knowledge. Further research should incor-

porate this concern into experimental designs that will be able to

provide more insights regarding the joint effect of framing and

anchoring among the different knowledge groups.

6.2. Limitations

There are a few limitations to this study that should be noted.

First, according to Levin et al. (2002), there are three types of fram-

ing effect but we only considered the influence of attribute framing

messages and the joint effect of attribute framing and anchoring.

The second type of framing effect, goal framing, has also been em-

ployed in the marketing area. Thus, we think it will be beneficial to

include the influence of this type of message framing and the joint

effect of goal framing and anchoring on Internet consumers’ re-

sponses in future research.

Second, the anchor points embedded in the advertisement are

anchors that are relevant to the electronic translator. However, will

an irrelevant anchor like a mobile phone advertisement have thesame impact on participants’ responses? The answer to this ques-

tion is worthwhile to understand. This question is derived based on

the argument that some studies suggest that there is some seman-

tic similarity between the comparative and absolute questions that

is critical to the observation of the anchoring effect. For example,

Strack and Mussweiler (1997) show that an anchor induces a very

weak anchoring effect when the anchor and the estimation target

focus on different dimensions of the same target (e.g., the height

of Brandenburg Gate and the width of Brandenburg Gate). In con-

trast, a strong anchoring effect occurs when the two questions

asked about the same dimension of the same target. Thus, further

study is needed to consider the role of anchor–target relevancy.

Third, in the laboratory experiments involving undergraduate

students who participated in our study, a key limitation is thatour findings may not apply to the broader Internet population.

Fourth, although the laboratory experiments are useful to control

for the possible factors that may affect the experimental subjects’

responses, generalizing results to the real-world environment

should only be done with caution. To test the framing effect and

anchoring effect, we used only one product, and we only manipu-

lated one product attribute and embedded one banner in the rele-

vant experimental Web page. However, because online consumers

actually have to deal with much more information in the online

shopping context, future research should incorporate more prod-

uct alternatives and information in their experimental designs.

Finally, we should note that laboratory experiments reflect a

methodology with high internal validity that offers precision for

identifying key theorized relationships among different constructs.However, one of the related drawbacks of experiments is their lack

of external validity. In our case, we only considered a limited num-

ber of variables in our experiment. We focused only on the influ-

ence of the framing and anchoring message on Internet shoppers’

purchase decisions. Our experimental design would have been

weaker if too many variables were included, even though this

would have been more like the real-world setting. Finally, we

should remind the reader that the Chinese–English electronic

translator that we discussed in this article does not currently exist

in the market. So the reader should be especially cautious in inter-

preting the findings of this research for this reason also.

Acknowledgment

Fundingof thisresearchworkis supportedby theNationalScience

Council (grant number, NSC96-2416-H-029-017-MY3), Taiwan.

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