1

The Impact of Store-Price Signals on Consumer Search and Store Evaluation

Hillbun (Dixon) Ho* Shankar Ganesan Harmen Oppewal

December, 2010 *Hillbun (Dixon) Ho is an assistant professor in the Division of Marketing and International Business at Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798 (phone 65 6790 4980; fax 65 6792 4217; email dixonho@ntu.edu.sg). Shankar Ganesan is the Office Depot Professor of Marketing at the Eller College of Management, University of Arizona, 320 McClelland Hall, Tucson, Arizona 85721 (phone 520 626 4159; fax 520 621 7483; email sganesan@eller.arizona.edu). Harmen Oppewal is a professor in the Department of Marketing at Monash University, P.O. Box 197, Caulfield East VIC 3145, Australia (phone 61 3 990 32360; fax 61 3 9903 2900; email harmen.oppewal@buseco.monash.edu.au). The authors thank the Department of Marketing at Monash University for funding this research. This research benefited greatly from the helpful comments from Alan Malter, Narayan Janakiraman, Amnon Rapoport, and two anonymous reviewers on previous drafts of the article.

2

Abstract

Always low price (ALP) and low price guarantee (LPG) are store-price signals that retailers

frequently use to induce favorable store-price image and discourage consumers from

comparing prices across stores. Although both policies signal low prices, only LPG is an

obligatory promise to beat rival stores’ prices. Results of two shopping simulations show that

when consumer search costs are relatively low, ALP may effectively discourage consumer

search whereas LPG may trigger more search. Paradoxically, consumers tend to evaluate ALP

stores less favorably (as having lower integrity and higher self-serving intention) than LPG

stores even when both signals appear to be credible. These findings suggest that LPG is a

superior tactic for creating a favorable store image while ALP is more effective for

discouraging consumer search. The results also indicate that consumers visit fewer stores when

the LPG is not a credible signal of lowest market price than when it is credible. This is because

consumers are inclined to either claim discounts or refunds at the non-credible LPG store or to

purchase at the competing store with a lower price rather than continue searching.

Keywords: low price guarantee, price-matching policy, every day low price, consumer search,

retailer motive

3

Facing keen competition in the retail market, especially during the current recessionary

environment, many retailers are positioning themselves as price-competitive to attract

increasingly price-conscious consumers (Kopalle et al. 2009). Retailers seek to create appealing

price images through a myriad of tactics and policies, including price comparison

advertisements, reference price anchoring, semantic cues, price-matching or price-beating

policies, and everyday low pricing (Anderson and Simester 2000). Among these tactics, always

low price (ALP) and low price guarantee (LPG) are popular store-price signals that retailers use

to induce patronage and reduce consumers’ desire to search for lower prices.

ALP is a price signal that mass retailers and discount stores such as Walmart employ to

inform customers of their everyday low pricing policy. ALP refers to retailers’ non-obligatory

promise to offer competitive prices to customers. In contrast, LPG (also known as price-

matching or price-beating) involves an obligatory commitment by the retailer to match or beat

competitors’ prices if customers can prove that lower prices are available elsewhere, either

before or after the purchase. Both policies appear extensively in retailers’ market

communications across a broad spectrum of product markets, including furniture, electronics,

appliances, and hotels.

LPG has drawn increasing attention from marketing researchers in recent years. Previous

research has examined the impact of LPG, together with various market factors, policy content,

and consumer characteristics, on consumers’ store price perceptions and search behavior

(Biswas, Dutta, and Pullig 2006; Kukar-Kinney and Walters 2003; Kukar-Kinney, Walters, and

MacKenzie 2007; Srivastava and Lurie 2004). Although extant literature provides valuable

insights into consumer response to LPG under different competitive environments and policy

characteristics, no study has yet examined whether and how consumers’ responses to LPG

4

differ from those to other store-price signals, such as ALP. In addition, previous research has

not investigated the effects of ALP on consumer search. To address these gaps in the literature,

this study investigates the differing impact of ALP and LPG on consumer search and store

evaluation. In addition, since previous research shows that consumers’ acceptance of pricing

policies as credible signals of low store prices may relate to the level of search costs (Srivastava

and Lurie 2001), we examine the interactive effects of pricing policies (ALP and LPG) and

search costs on consumer responses. Comparing ALP and LPG offers significant managerial

insights because, although both policies aim to discourage consumer search, they have different

implications for store revenues, store image, and administrative costs.

ALP and LPG appear often in retailers’ advertisements and in-store displays. However,

consumers may not always consider these signals to be diagnostic of competitive store prices.

Prior studies suggest that store-price signals appear to be either credible or non-credible, that is,

representing a true or false cue of lowest market price respectively (Dutta, Biswas, and Grewal

2007). Dutta and colleagues described a LPG signal as “non-default” and “default” when it is a

true and false indicator of the lowest market price respectively. However, in this article, we use

the term “credible signal” to refer to an indicator of the lowest market price that has proven true

(no contradictory evidence appears) to consumers and “non-credible signal” to refer to an

indicator of the lowest market price that has proven false. Since non-credible signals may lead

to unfavorable consumer perceptions and reactions, it is important to examine consumer

response to credible versus non-credible ALP and LPG policies. In addition, previous research

suggests that consumers tend to infer the motives behind firms’ actions (e.g., Campbell 1999;

Kukar-Kinney, Xia, and Monroe 2007). Following this research stream, we investigate how

consumers infer retailers’ motives for the deployment of ALP versus LPG. Thus, the present

5

study examines not only the extent to which ALP and LPG discourage consumers from store

visits but also whether these signals generate a favorable or unfavorable store image in the

minds of consumers.

In summary, this study addresses three important but previously unexamined issues

related to store-price signals: (1) the differential responses of consumers to ALP and LPG in

terms of store visits and store evaluations with respect to integrity and motives (customer-

oriented and self-serving); (2) the moderating effects of search costs on consumer responses;

and (3) consumers’ differing responses to credible signals versus non-credible signals. In

addition to making a conceptual contribution, our study provides methodological contribution

through the use of shopping simulations to examine consumers’ simulated search behavior in

response to store-price signals. Examining consumers’ simulated search behavior rather than

their search intentions provides a more refined assessment and prediction of consumer

responses in the actual retail market.

The article is organized as follows. First, we present a review of the theoretical basis for

conceptualizing ALP and LPG as signals of low store prices, and follow with a discussion of

the rationale for the hypotheses. Then we describe the methodology for testing our hypotheses

using two shopping simulation experiments. Finally, we discuss the results of the experiments

and conclude by presenting the theoretical and managerial implications of our findings.

Retailers’ deployment of market signals

Previous research on market signaling focuses mainly on product quality signals.

Typically, manufacturers use “observable” marketing tools to signal unobservable or

indistinguishable product quality to consumers. Observable quality-related signals can take

different forms, such as price, brand name, store name, warranty, and the like (Boulding and

6

Kirmani 1993; Erdem and Swait 1998), and signaling practices usually involve financial

consequences for the signal-sending firm (Singh and Sirdeshmukh 2000). If the signal proves to

be false, the firm sending the false signal would suffer both reputation damage and financial

losses due to reduction in future revenues and costs incurred in the signaling (Rao, Qu, and

Ruekert 1999). Thus, to signal credibly, high-quality firms must use signaling tools that low-

quality firms cannot afford to imitate. If low-quality firms follow suit, they will suffer

significant financial losses when they are caught cheating. Therefore, market signals achieve

credibility only when consumers can rely on them to differentiate superior products from

inferior products.

The concept of signaling applies well to retailers’ store-price signals, such as ALP and

LPG. Signaling theory suggests that consumers’ acceptance of store-price signals as a reliable

indicator of lowest market price hinges on how easily consumers can compare prices across

stores to verify the (un)truthfulness of the signals (Dutta and Biswas 2005; Prabhu and Stewart

2001; Srivastava and Lurie 2004). Consumers in a market with easy access to price information

are more likely to discover a signal’s (un)truthfulness and claim the promised refund. When

consumers find a store’s price signal to be non-credible (i.e., prices are higher than competing

stores’ prices), they may shop elsewhere or request price-matching. As a result, the retailer

loses potential revenues, incurs costs for handling refunds, and has to expend extra effort to

regain store reputation. Consumers may even question the retailer’s integrity and motives for

using non-credible store-price signals, resulting in further harmful consequences for the

retailer. Therefore, only low-priced retailers can afford to use store-price signals. High-priced

retailers will suffer significant financial loss if they use store-price signals to pretend being

price-competitive.

7

Although both ALP and LPG are retailers’ promises to offer competitive prices, these

policies may not necessarily be perfect indicators of the lowest market price.1 As noted earlier,

LPG constitutes retail stores’ obligatory promise of competitive prices—LPG stores will match

or beat rivals’ prices if consumers find cheaper prices elsewhere before or after a purchase.

Thus, LPG stores have stronger incentives to keep their prices competitive to avoid being

perceived as non-credible and increasing the costs of administering price-matching claims. In

contrast, ALP strategy is a retail store’s non-obligatory promise of competitive prices, and

consumers have no legitimate right to expect price-matching refunds. Thus, compared to ALP

stores, LPG stores may incur higher costs for monitoring competitors’ prices and managing

price-matching claims. According to signaling theory, the higher the costs involved in the

practice of signaling, the more credible should be the signal. In this situation, LPG may appear

more credible to consumers than ALP.2

However, the credibility of LPG also depends on the amount of effort and other costs

consumers expect to expend in finding a lower price elsewhere and requesting price-matching

from the LPG store (Chen, Narasimhan, and Zhang 2001; Lurie and Srivastava 2005).

Consumers eligible for LPG may find the process of claiming the refund too onerous or the

transaction costs too great to make the claiming of refunds worthwhile. As a result, by taking

advantage of consumers’ inertia and the high costs associated with claiming refunds, some LPG

stores may avoid being price-competitive all the time. This opportunistic act might lead some

consumers to perceive LPG as retailers’ insincere commitment to low prices. The above

1 The possibility that stores with ALP or LPG offer the lowest market price may depend on a number of factors, such as the store’s intention to beat rivals, knowledge of competitors’ prices and ability to monitor them, and the ease with which shoppers can compare prices of identical items across stores. 2 ALP may possibly entail higher implementation costs, as the retailer must have competitive prices on most of its products most of the time. Therefore, ALP may appear more credible to some consumers. We thank one of the reviewers raising this point.

8

contradictory possibilities suggest the importance of investigating how the impact of LPG on

consumer search and store evaluations may differ from the impact of ALP.

Hypotheses

According to information economics, consumers will keep searching for a better deal as

long as the perceived benefits of the search exceed the perceived costs (Grewal and

Marmorstein 1994; Moorthy, Ratchford, and Talukdar 1997; Urbany, Dickson, and

Kalapurakal 1996). Previous research, however, suggests that consumers often have limited

information about retail stores’ price levels (Ofir et al. 2008). Thus, consumers tend to use

salient and diagnostic cues to infer store price level and decide on the degree of search (Alba et

al. 1994; Bobinski, Cox, and Cox 1996; Kardes, Posavac, and Cronley 2004; Zwick et al.

2003). For instance, when consumers have incomplete knowledge about the price

competitiveness of different retail stores, the presence of store-price signals in the marketplace

reduces their search intention (Biswas et al. 2002). Consumers associate LPG stores with lower

prices, show greater patronage intention, and visit fewer stores for price comparison

(Chatterjee, Heath, and Basuroy 2003; Dutta and Biswas 2005; Lurie and Srivastava 2005).

Srivastava and Lurie (2001), however, find that consumers respond to LPG as if it is a partially

credible signal of lowest market price. That is, consumers believe LPG stores offer lower prices

but not necessarily the lowest market price, owing to regular price fluctuations in the

marketplace. Consequently, when search costs are sufficiently low, consumers visit more stores

when LPG is present in a retail market than when LPG is absent. The authors reason that

consumers search more because they expect the financial rewards from finding a lower price

and claiming refunds to be greater than the low search costs. However, when search costs are

9

high, consumers visit fewer stores in a retail market with LPG, because the financial rewards

might not be sufficient to cover the search costs.

We suggest that the influence of store-price signals on consumer search depends on the

type of signals and the level of search costs. When search costs are high, consumers’ store

visits will be independent of the type of signals available in the marketplace. In such situations,

consumers will find that additional searching to verify the truthfulness of the signal is not worth

the effort. In addition, since high search costs imply low accessibility of price information,

consumers might infer that the high-priced stores would use store-price signals to pretend being

price-competitive. As a result, consumers would tend to ignore the presence of store-price

signals in the retail market and act as if store-price signals are not reflecting price

competitiveness.

In contrast, when search costs are low, store visits will depend on how consumers

interpret the credibility of different store-price signals. As discussed earlier, relative to ALP,

consumers face greater uncertainty and ambiguity in evaluating the credibility of LPG as a

signal of lowest market price. Therefore, we predict that LPG is less effective than ALP in

discouraging consumers from searching, since consumers would perceive LPG to be less

diagnostic and foresee greater likelihood of finding lower prices in the market with LPG. As a

result, consumers will visit more stores in a market with LPG than in a market with ALP.

In a retail market, consumers often come across not only store-price signals but also

signals not focusing on prices. Thus, in addition to comparing how consumers’ search

behaviors differ between ALP and LPG, this study affords greater insights by comparing these

two store-price signals with a non-price-related signal. We predict that consumers will search

more stores in a market where LPG is present than where a non-price signal such as service

10

assurance is present. This increase in search occurs because consumers view LPG as partially

credible, thus anticipating greater acquisition and transaction value for visiting more stores in a

market with LPG (Srivastava and Lurie 2001). Additional search may provide consumers with

opportunities to discover lower prices elsewhere, thus making them eligible for a refund from

the LPG store (Dutta and Biswas 2005). When search costs are relatively low, the anticipated

financial gain from finding a lower price or claiming the refund is likely to outweigh the

anticipated costs involved.3 In contrast, consumers are less likely to respond to service

assurance, as they do not associate this signal with price competitiveness in the marketplace.

In the case of ALP, visiting more stores to find lower prices provides less additional

acquisition and transaction value, since ALP stores have no obligation to issue a refund to

consumers. Therefore, even though consumers may foresee a likelihood of finding lower prices

at other stores, they probably take the ALP at face value and act as if it is a reliable cue of

lowest market price. As a result, we propose that consumers visit fewer stores in a market

where ALP is present than where a non-price signal such as service assurance is present.

H1. Search costs moderate the effect of store-price signals on consumer search. When search

costs are high, types of store-price signals are unrelated to consumer search. When search costs

are low, consumer search depends on the type of store-price signals in the retail market as

follows:

H1a. Consumers visit more stores in a retail market with LPG than in a retail market with ALP.

H1b. Consumers visit more stores in a retail market with LPG than in a retail market with a

non-price-related signal (service assurance).

3 We assume that consumers expect the financial gain from the refund is greater than the additional search costs and the effort involved in claiming refunds. Our experimental procedures reflect this assumption.

11

H1c. Consumers visit fewer stores in a retail market with ALP than in a retail market with a

non-price-related signal (service assurance).

Pricing policies can function both as signals of low store prices that influence consumer

search and as a useful marketing tool to create a positive store image. Previous studies of store-

price signals mainly focus on how these signals affect consumers’ price perceptions—that is,

the extent to which consumers perceive prices at the signal-using store to be lower than prices

at competing stores. Scant research has examined how store-price signals affect consumers’

store evaluations. Although we expect consumers’ search behaviors to differ between retail

markets with ALP and LPG, an important question is whether consumers have differing

evaluations of stores offering different price signals and if so, how they are influenced by the

outcomes of search activities and revealed accuracy of these claims.

Previous examination of various marketing strategy decisions suggest that firms’ motives

can be either self-serving (beneficial to the firm itself) or public-serving (beneficial to external

parties such as customers) (Campbell 1999, 2007; Dutta, Biswas, and Grewal 2007; Forehand

and Grier 2003). Drawing on attribution theory, prior research shows that individuals tend to

evaluate firms’ actions and attribute the above motives to these actions. Extending this

literature, we suggest that consumers make inferences about retail stores’ motives or intentions

regarding the type of store-price signals being used. We posit that these retailer motives can

focus on either taking advantage of consumers or serving consumers’ interest. Consumers

perceive a retailer to have a self-serving motive when they believe the retailer uses price signals

to persuade individuals to purchase at the store rather than undertaking price comparison,

thereby taking advantage of consumers’ lack of concrete price information. In contrast,

consumers perceive a retailer to have a customer-oriented motive when they believe the retailer

12

uses price signals to protect them from price fluctuations in the marketplace. We also suggest

that these two retailer motives are not mutually exclusive (Dutta, Biswas, and Grewal 2007).

Consumers may attribute both motives to retailers but to different degrees, depending on the

type of price signals a retailer uses.

Broadly, ALP is a non-obligatory promise of competitive prices, and thus consumers have

no legitimate right to claim a refund if they find lower prices elsewhere. In other words, while

ALP indicates low store prices, it does not offer consumers protection from price fluctuations.

LPG, however, serves two distinct functions. It acts as a signal of low store price and a promise

of price protection to consumers. Therefore, we predict that consumers perceive the LPG store

as having a stronger customer-oriented intention than the ALP store. In contrast, we predict that

consumers will perceive the ALP store as having a stronger self-serving intention than the LPG

store.4

Previous research offers evidence that consumers’ perception of a firm’s motives affects

their attitude toward the firm and subsequent shopping decisions (Campbell 1999; Forehand

and Grier 2003). Therefore, given that LPG reflects a stronger customer-oriented motive, we

predict that consumers will tend to trust an LPG store more and perceive the LPG store as

having greater integrity than the ALP store.

Following the same logic in deriving H1, we suggest that when search costs are high,

consumers will not consider the implications of store-price signals and infer the retailer’s

motives behind the signals. Therefore, we focus on the low search cost situation and propose:5

4 An alternative argument is that consumers infer retailers’ motives based on the perceived credibility of the store-price signals. This would mean that consumers believe LPG stores have a stronger self-serving intention than ALP stores, since LPG as a cue of lowest market price, is more ambiguous than ALP. This prediction, however, is opposite to our propositions. 5 Note that H2 is qualified by the condition that both signals appear to be credible indicators of the lowest market price (i.e., the accessible price information does not allow consumers to refute these claims), so we can rule out the possibility that consumers base their inferences of store motives on signal credibility.

13

H2. Consumers believe the LPG store has (a) a stronger customer-oriented intention, (b) a

weaker self-serving intention, and (c) greater integrity than the ALP store, when both LPG and

ALP appear to be credible.

So far we have discussed the differing impact of ALP and LPG on consumer responses.

We have indicated that consumers believe prices at the signal-using stores may occasionally be

slightly higher than the prices at competing stores due to price fluctuations. According to

Kirmani and Rao (2000), store-price signals are non-credible when consumers cannot rely

solely on the signal itself to judge the price competitiveness of the signal-using store. As noted

earlier, “non-credible signals” refers to the situation in which consumers discover the price at

the signal-using store to be higher than prices at competing stores their purchase whereas

“credible signals” refers to the situation in which consumers do not discover lower prices at

competing stores. Consumers may assess the credibility of store-price signals either before or

after their purchase. Assessments before purchase involve search for and comparing prices

across stores. Assessments after purchase may occur too, for example, price conscious

consumers would monitor prices to reduce cognitive dissonance. Although consumers may

assess signal credibility at different stages of their purchase, this article focuses on the impact

of non-credible signals on consumers’ pre-purchase search, as no research has yet examined

this aspect. We predict that consumer search differs between retail markets with credible and

non-credible store-price signals.

Imagine that a consumer on a shopping trip has visited a few bricks-and-mortar stores and

one of them offers LPG. The consumer also discovers that the same product is cheaper at a

store without the LPG. Thus, there is clear evidence that the LPG signal is non-credible. In

such a case, some consumers would shop at the store with a lower price right away, as it

14

appears to offer a good deal. Other consumers may shop at the LPG store to take advantage of

the refund, especially when they are more familiar with the LPG store or the LPG offers extra

discounts in the case of price-beating. Both types of consumers are less inclined to search

further, because a continued search will result in increasing search costs. Thus, consumers have

little incentive to keep searching as they expect that the current refunds or savings would

outweigh the uncertain financial gain from searching further. Claiming a refund/discount or

purchasing the merchandise at the lower-priced store instead of searching further enables

consumers to maximize the acquisition value of their purchase, assuming the costs and effort

involved in claiming refunds are negligible (Lichtenstein, Ridgway, and Netemeyer 1993). As a

result, we suggest that regardless of whether consumers would shop at the lower-priced store or

at the non-credible LPG store to claim discounts/refunds, the overall degree of consumer search

would be lower in a market with non-credible LPG.

H3. Provided that the costs and effort in claiming LPG refunds is negligible, consumers

search less in a retail market with a non-credible LPG than in a market with a credible LPG.

As discussed earlier, when search costs are high, store-price signals in the retail market

would not affect consumer store search. Likewise, consumer search would not differ between a

market with credible LPG and a market with non-credible LPG when search costs are high.

Thus, we suggest that H3 applies only to the condition that search costs are relatively low.

Although ALP can also be a non-credible signal of lowest market price, ALP stores have no

obligation to offer any refund or discount to consumers. Thus, consumers would not gain

financially from finding lower prices at non-ALP stores. Therefore, we expect that consumer

search will not differ between credible ALP and non-credible ALP conditions. Since this

prediction represents a null effect, we do not make a formal hypothesis.

15

Consumers are likely to evaluate stores that use credible price signals differently from

stores that use non-credible price signals. We predict that consumers will hold a more favorable

attitude toward the credible ALP or LPG store, as they encounter no contradictory evidence

during their shopping trip. Once consumers discover a lower price at other stores, they may

question the ALP (or LPG) store’s intention behind the use of store-price signals. Attribution

theory suggests that consumers will attribute the disconfirmation of their price expectations

(i.e., lowest market price) to retailers’ negative intent (Forehand and Grier 2003). Previous

research also suggests that even though consumers can claim refunds, the retail store using non-

credible signals may not be able to restore consumers’ confidence (Dutta, Biswas, and Grewal

2007). Therefore, we expect that consumers, even though eligible for refunds at the non-

credible store, will perceive the non-credible ALP (or LPG) store as having a stronger self-

serving motive, a weaker customer-oriented motive, and lower integrity than a credible ALP

(or LPG) store.

H4. Consumers believe the credible LPG store has (a) a stronger customer-oriented intention,

(b) a weaker self-serving intention, and (c) greater store integrity than the non-credible LPG

store.

H5. Consumers believe the credible ALP store has (a) a stronger customer-oriented intention,

(b) a weaker self-serving intention, and (c) greater store integrity than the non-credible ALP

store.

Experiment 1

Participants and procedures

16

We recruited 382 participants from an online consumer panel run by a market research

company. All panel members were at least 18 years old, and the sample was drawn to represent

the demographic characteristics of a major metropolitan area. Panel members received an e-

mail from the research company soliciting their participation and directing them to a website

that informed them of the purpose and duration of the study, the identity of the university

conducting the study, and the details of the monetary rewards for their participation. The e-mail

explained that the panel members were about to participate in a shopping simulation that

resembled their daily offline shopping experience. They then entered the website that hosted

the experiment.

Participants were randomly assigned to one of eight experimental conditions (details of the

design appear below). They were told that they would perform a trial task and a payoff task,

and that they had to finish each task within five minutes. A pretest revealed that the majority of

participants finished the shopping task in five minutes, and we established this time limit to

avoid any interruption of participants during the experiment. The purpose of the trial task was

to familiarize the participants with the interactive functions of the web interface and different

steps involved in the shopping tasks.

In the payoff task, participants were instructed to shop for a specific model of HP

notebook computer from one of twelve stores shown on the webpage. They were told that the

listed stores represented real physical stores located in a specific metropolitan area but that the

store names had been disguised. The price of the computer at each store was based on

prevailing market prices and reflected the price range in the retail market, but the actual range

was not revealed. Participants could visit a store by clicking its corresponding button on the

webpage, a step that revealed the price and product information for that store. Participants

17

could visit as many stores as they wanted within the allotted time. A timer on the webpage

started once the participants had finished reading the instructions and kept them informed of

how much time had elapsed. When participants clicked the button representing a store, after

five seconds a pop-up appeared showing the computer model, selling price, and a store claim.

After each store visit, participants saw additional information on the webpage: (1) the stores

visited, (2) the lowest price found, and (3) the cumulative search expenses. On the basis of this

information, participants decided whether to continue searching or to stop and select the store

for purchase of the notebook computer.

As an incentive to search for the best price among the twelve stores, participants were

notified that their chance of finding a lower price would increase with the number of stores they

visited. Participants also realized that, for each store visit, they incurred search costs similar to

expenses on gas and the expenditure of time and effort in their daily shopping. Participants

were instructed to decide when to stop searching and at which store to shop by considering the

tradeoff between visiting additional stores and minimizing the total search costs. Participants

were told that their compensation could range from $3 to $7. Although the exact compensation

algorithm was not revealed, participants were told that their compensation was proportional to

the amount they saved by searching across stores (i.e., the highest price found minus the price

paid) after deduction of the search expenses. After completing the experiment, participants

responded to a series of questions.

Research design

We used a 4 (non-price signal vs. credible ALP vs. credible LPG vs. non-credible LPG) !

2 (high vs. low search cost) between-subjects design that manipulated search costs and types of

store signals in the retail market. In each experimental condition, participants saw a store ad

18

claim when they visited the second store. No other store displayed any ad. In the control

condition, participants saw a service assurance claim (“We promise the best customer

service!”) unrelated to store prices. We used a non-price-related signal instead of the absence of

signals as the control condition to minimize the possibility of demand artifact in the experiment

and to control for mere exposure effects. In the credible ALP condition, participants saw an

ALP claim (“Always Low Price! You can always find the lowest price at our store”).

Participants were not entitled to claim any refund or discount from the ALP store if they found

a lower price at other stores. In both the credible LPG and non-credible LPG conditions,

participants saw the same LPG claim (“Low Price Guarantee! We guarantee to offer the lowest

price. If you find a lower price at other stores, we will beat the price by 20%”). Participants

were entitled to a refund or discount if they purchased the computer from the LPG store but

found a lower price elsewhere. The LPG was manipulated to be equivalent to a price-beating

policy. To request a discount when making a purchase or a refund after a purchase, participants

had to provide the LPG store the disguised name of the store where they found a lower price

(by inputting this information in the program). The program verified the accuracy of such

information. Then, the LPG store offered an adjusted price (i.e., the lower price found at

another store minus 20% of the price difference) to the participants. And the compensation for

the participants was based on this adjusted purchase price.

To control for variation in price savings across store visits, participants saw the same

sequence of prices regardless of the order of stores they visited. However, to differentiate the

non-credible LPG from the credible LPG conditions, the price sequence shown to the

participants for the first three stores differed between the two conditions. In the credible LPG

condition (and also in the credible ALP and in the non-price signal condition), the price

19

sequence was $1299, $1250, and $1345 for the first three stores. So the price at the store with

the claim (i.e., the second store visited by participants) was the lowest among all stores. The

prices at the rest of the stores were all higher than the price at this second store. Thus, the LPG

and ALP claims should appear to participants as credible signals of lowest market price. In the

non-credible LPG condition, the price sequence for the first three stores was partly reversed

and set to be $1299, $1345, and $1250. Therefore, the price at the LPG store was higher than

the first store participants visited (while the price range remained unchanged), resulting in a

non-credible LPG signal. Note that we manipulated credibility of LPG and ALP by varying the

price sequences encountered by participants at the second and third store. Thus, the price

information revealed to participants either confirmed the second store’s signal to be a true

indicator of the lowest market price or a false indicator of lowest market price.

To manipulate search costs, in the low (high) search cost condition, $6 ($12) was added to

the participants’ total search costs for each store they visited. The search cost levels were based

on a pretest that indicated that the participants expected a large price range (around $200) for

the HP notebook model in the retail market. Thus, the manipulations of the search cost levels

had to be salient to the participants to have any impact on their search decisions.

The payoff task was preceded by a trial task that used an unrelated product category

(digital camera). No advertisement was shown to the participants in the trial task. After

participants had made their purchase decision or used their allotted five minutes for the payoff

task, they were directed to a screen where they responded to sets of questions related to the

manipulation checks, measures for dependent variables and covariates, shopping experiences,

demographic characteristics, and understanding of and involvement in the simulations. In

addition, participants answered an open-ended question that captured their opinions about the

20

purpose of the experiment. The total number of stores individual participants visited was

automatically recorded.

Manipulation checks

We assessed the search cost manipulation with two questions: “How would you

characterize the search expenses for visiting each store?” and “Relative to the money you may

be able to save from shopping around, how would you characterize the search expenses for

visiting each store?” The assessment used a seven-point scale (1 = very low, 7 = very high).

The ANOVA results indicated that only the main effect of search cost was significant (Mhigh cost

= 5.19 and Mlow cost = 4.41; F(1, 359) = 34.78, p < .01). We checked the store signal manipulation

by asking participants to recall the content of the ad they saw in the shopping simulation.

Following previous studies of store-price signals that truncated invalid responses (e.g., Dutta,

Biswas, and Grewal 2007), we discarded responses from participants who failed to recall the

content of the ad and searched only one store and thus did not see the ad manipulation. For the

non-credible LPG condition, participants should have noticed that the price at the LPG store

was higher than at other stores. We checked this manipulation by asking participants after the

shopping simulation whether they recalled the price level at the LPG store, and 89 percent of

participants recalled the price at the LPG store as being more expensive than other stores they

visited. This percentage was comparable to the credible LPG condition, in which 92 percent of

participants recalled the price at the LPG store to be lower than other stores. We discarded

responses from participants who did not accurately recall the price level at the LPG or ALP

store. After discarding the invalid cases, 367 respondents remained from the original 382. To

further ensure our manipulation of signal credibility was valid, we compared participants’ store

price perception between stores with the credible LPG or ALP and stores with the non-credible

21

LPG using two items on a seven-point Likert scale (1 = strongly disagree, 7 = strongly agree):

“The notebook computer at the store with the price claim is the cheapest among all stores,” and

“The notebook computers sold at the store with the price claim are in general cheaper than

other stores.” The one-way ANOVA result indicates that participants perceived the price levels

at the credible stores to be lower (MCredible Stores = 4.54 and MNon-credible LPG Store = 2.65; F(1, 358) =

55.83, p < .01). We assessed participants’ understanding and involvement in the shopping

simulation by asking them the extent to which they agreed with the following two items

measured on a seven-point Likert scale: “I understand the procedures of the study completely”

and “I find the study interesting and engaging.” Participants indicated that they had a

reasonable understanding of the procedures (M = 5.6) and sufficient involvement in the

shopping task (M = 5.8).

Finally, we assessed participants’ responses to an open-ended question asking for their

thoughts on the purpose of the study. No participant guessed the real study purpose correctly.

The majority of participants (72 percent) thought that the study aimed at discovering how

consumers evaluate the costs and benefits of shopping around. These responses provide

evidence that participants’ decision strategies focused on the trade-off between finding a good

price and keeping search costs low.

Measures for dependent variables and covariates

We assessed participants’ perception of the integrity of the store using four items

measured on a seven-point semantic differential scale (" = .95): very dishonest/very honest,

very insincere/very sincere, very undependable/very dependable, and very untrustworthy/very

trustworthy. We assessed participants’ belief that the store’s intention was self-serving through

five items measured on a seven-point Likert scale (" = .87): [The store uses the ad claim] “to

22

give customers the impression that its price is the lowest in the market,” “to attract customers

so that they would not compare prices across stores,” “to take advantage of customers who

lack price information,” “to take advantage of customers who do not have time to shop

around,” and “to lure customers even though it may not have the lowest price in the market.”

We assessed participants’ belief that the store’s intention was customer-oriented by two seven-

point Likert scale items (" = .62): [The store uses the ad claim] “to protect customers from

price fluctuations in the market” and “to assure customers that they can always get the lowest

market price at the store.”

We included price consciousness as a covariate in statistical analysis because previous

studies suggest that consumers’ price consciousness is related to their search propensity in

response to store-price signals. Price consciousness is a trait representing the extent to which an

individual focuses on the price aspect of purchases. Typically, price-conscious people are eager

to maximize the acquisition and transaction value of their purchases (Dutta and Biswas 2005;

Kukar-Kinney, Walters, and MacKenzie 2007). We measured participants’ price consciousness

using the scale from Lichtenstein et al. (1993). The scale consisted of five items (" = .85)

measured on a seven-point Likert scale: “I am willing to make an extra effort to find lower

prices,” “I usually shop at more than one store to take advantage of low prices,” “The money

saved by finding low prices is usually worth the time and effort,” “I never shop at more than

one store to find low prices” (reverse-coded), and “The time it takes to find low prices is

usually not worth the effort” (reverse-coded).

Results

To test H1, we performed a 4 (signal type) ! 2 (search cost) ANCOVA on the number of

store visits using price consciousness as a covariate, followed by planned contrasts. The

23

ANCOVA results show that the store signals ! search cost interaction is significant (F(3, 358) =

6.86, p < .01). The effect of the covariate, price consciousness, is not significant (F(1, 358) = 1.99,

ns). Figure 1 plots the interaction. Further analysis shows that when search cost is high, store

signals have no impact on store search (F(3, 358) = .43, ns). In contrast, when search cost is low,

the effect of store signal is significant (F(3, 358) = 10.72, p < .01), supporting H1. Thus, the

subsequent planned contrast analysis applied to the low search cost condition only.

To test H1a, we compared the number of store visits between the ALP and the LPG

conditions (both signals are credible). The result indicates that the mean difference is

significant (MALP = 4.13 and MLPG = 5.98; F(1, 358) = 16.50, p < .01), suggesting that participants

searched more stores in a market with LPG than in a market with ALP. To test H1b, we

compared the number of store visits between the non-price signal condition and the LPG

condition. The result is significant (MService Signal = 4.61 and MLPG = 5.98; F(1, 358) = 15.98, p <

.01), suggesting that participants searched more when they saw a LPG rather than a service

assurance claim. H1b is supported. To test H1c, we compared store visits between the ALP

condition and the non-price signal condition. The result is significant (MALP = 4.13 and MService

Signal = 4.61; F(1, 358) = 1.66, p < .05), showing that participants searched less when they saw an

ALP rather than a service assurance claim.

As predicted in H2a, participants’ perception of stores’ customer-oriented motive differed

between the ALP store and the LPG store when both signals appeared to be credible and search

costs were low. The planned contrast indicates that participants perceived the LPG store as

having a stronger intention to provide price protection to customers than the ALP store (MLPG =

4.21 and MALP = 3.60; F(1, 358) = 5.10, p < .05). As predicted in H2b, participants perceived the

LPG store as having a weaker intention than the ALP store to persuade customers to shop at it

24

rather than at other stores (MLPG = 4.80 and MALP = 5.98; F(1, 358) = 23.83, p < .01). As predicted

in H2c, participants perceived the LPG store as having greater integrity than the ALP store

(MLPG = 4.76 and MALP = 4.22; F(1, 358) = 6.27, p < .05).

To test H3, we compared participants’ store visits between the credible LPG and the non-

credible LPG conditions. The planned contrast shows that participants visited fewer stores in a

market with non-credible LPG than in a market with credible LPG (MNon-credible LPG = 4.26 and

MCredible LPG = 5.98; F(1, 358) = 20.86, p < .01). Thus, H3 is supported. This result applies to the

low search cost condition as no effect occurs when participants experienced high search costs

(MNon-credible LPG = 3.32 and MCredible LPG = 3.24, ns).

To test H4, we compared participants’ store perceptions between the credible LPG store

and the non-credible LPG store. The planned contrast across the search cost conditions shows

that participants perceived the credible LPG store as having a stronger customer-oriented

intention than the non-credible LPG store (MCredible LPG = 4.25 and MNon-credible LPG = 3.42; F(1, 358)

= 18.31, p < .01). Thus, H4a is supported. The result also indicates that participants perceived

the credible LPG store as having a weaker self-serving intention than the non-credible LPG

store (MCredible LPG = 4.98 and MNon-credible LPG = 5.56; F(1, 358) = 7.32, p < .01), supporting H4b.

As H4c predicted, participants perceived the credible LPG store as having greater integrity than

the non-credible LPG store (MCredible LPG = 4.66 and MNon-credible LPG = 3.54; F(1, 358) = 31.13, p <

.01). We report summary statistics of the dependent measures in Table 1 and present a

summary of the planned contrast analyses in Table 2.

Post hoc analysis

Although no formal hypothesis was developed, we predicted that customers who

purchased at competing stores would evaluate the integrity of the non-credible LPG store as

25

lower than customers who purchased and claimed a discount/refund at that store. We ran a one-

way ANOVA to test this conjecture. The result indicates that perceived store integrity differed

between these two groups of participants irrespective of whether the search cost was low (MBuy

at other stores = 2.80 and MBuy at non-credible LPG store = 4.07; F(1, 358) = 13.09, p < .01) or high (MBuy at other

stores = 2.54 and MBuy at non-credible LPG store = 4.46; F(1, 358) = 33.82, p < .01). We also found that in

the high search cost condition, 67 percent of the participants purchased at the non-credible LPG

store and claimed the discount/refund while in the low search cost condition, 58 percent

purchased there and claimed the discount/refund. The rest of the participants chose to purchase

at other stores instead of claiming the discount/refund at the non-credible LPG store. This result

suggests that a significant proportion of consumers preferred not to shop at the non-credible

LPG store even though they could benefit from claiming the LPG. We speculate that these

consumers may perceive that the discount or refund is not worth the effort to make the claim, or

they may intentionally punish the LPG store for dishonesty.

While we found significant differences between the credible LPG and non-credible LPG

conditions in terms of store visits, perceived store motives, and store integrity, it is also relevant

to know how a non-credible LPG store compares to a store using a non-price signal (service

assurance). Is a non-credible retailer worse off than one using a non-price signal? Our simple

effect analysis shows that store visits did not differ between the two conditions. However,

perceived store integrity and customer-oriented intention were greater in the service assurance

condition (integrity: MService Signal = 4.46 and MNon-credible LPG = 3.66; F(1, 358) = 9.97, p < .01;

customer-oriented intention: MService Signal = 4.08 and MNon-credible LPG = 3.38; F(1, 358) = 5.68, p <

.05) while self-serving intention was lower (MService Signal = 4.72 and MNon-credible LPG = 5.48; F(1,

26

358) = 8.06, p < .01). Thus, these results indicate that retailers would be better off by using a

non-price signal than non-credible LPG.

Conclusion

The results of Experiment 1 provide strong empirical evidence to support our hypotheses.

However, this study has a few limitations that may lessen the generalizability of the findings.

First, only one store carried a signal—no other stores in the simulation displayed claims about

their store characteristics. Second, participants shopped for only one product category. Third,

we compared only credible and non-credible LPG conditions and did not examine differences

between credible and non-credible ALP conditions. Although we expect that consumer search

would not differ between these two ALP conditions, consumers’ store perceptions likely would

differ. Fourth, the observed difference in store search between the credible and non-credible

LPG conditions in support of H3 may result from the unusually significant savings participants

obtained by claiming a discounted price at the non-credible LPG store.

Experiment 2

In this study, we validate the robustness and generalizability of key findings in

Experiment 1 by broadening our investigations in several important ways. First, this study

examines whether the observed differences in consumer store evaluation extend to the credible

and non-credible ALP conditions. Second, the shopping simulation in Experiment 2 resembles

the real retail market in which multiple stores make claims related to store characteristics to

draw customers’ patronage. Third, Experiment 2 avoids a potential demand artifact in the non-

credible LPG condition in Experiment 1 by lowering the financial rewards participants can

obtain from claiming a discount/refund at the non-credible LPG store. Fourth, we assessed

27

participants’ general beliefs of the strength of the ALP/LPG signals based on their own

shopping experience with real stores. We used this measure to rule out the possibility that more

favorable perceptions toward LPG are attributed to its greater perceived signaling strength than

ALP.6

Participants and procedures

We recruited 350 participants from an online consumer panel run by a market research

company. All panel members were at least 18 years old and had had experience in purchasing

computers and televisions within the past three years. The sample corresponded with the

demographic characteristics of a major metropolitan area. At the end of study, we assessed

participants’ awareness of retail stores’ pricing policies in the metropolitan area. Of the

participants, 65 percent indicated their awareness of specific stores’ use of ALP or LPG, while

49 percent indicated that they had experience in requesting a discount or refund at the LPG

stores. The experimental procedures were identical to those in Experiment 1 including the

incentives offered to participants with the exception that the stores were electronics stores and

the product to be purchased was a model of a Samsung high definition television (HDTV).

Research design

We used a 2 (credible ALP vs. non-credible ALP) ! 2 (credible LPG vs. non-credible

LPG) between-subjects design that manipulated the type and credibility of store-price signals to

test a subset of the hypotheses. Since Experiment 1 showed that consumer store search and

evaluations differed only when consumer search costs were low, Experiment 2 examined the

impact of store-price signals in the low search cost condition exclusively. In each experimental

6 Intuitively, LPG would be perceived as having greater signaling strength because it makes an obligatory promise. However, it is also possible that ALP will be perceived as having greater signaling strength because the retailer must have low prices on most of its products most of the time, whereas LPG can get by without being price competitive all the time. We thank one of the reviewers for this suggestion.

28

condition, participants saw either an ALP or LPG claim when they visited the second store. All

other stores displayed a claim about their non-price-related characteristic (e.g., range of

inventory, opening hours, promises of services, etc.) when participants visited them. In the ALP

conditions, participants saw an ALP but could not claim any refund or discount from the store

if they found a lower price elsewhere. In the LPG conditions, participants saw a LPG and could

request price matching plus a 10 percent discount on the price difference at the LPG store if

they found a lower price elsewhere.

To control for variation in price savings across store visits, participants saw the same

sequence of prices regardless of the order in which they visited stores. To differentiate credible

ALP/LPG signals from the non-credible ALP/LPG signals, the price sequence that participants

saw was reversed for the second and third store that they visited. In the credible conditions, the

price sequence was $1259, $1250, and $1275 for the first three stores. The price at the second

store was also the lowest among all stores. Thus, ALP/LPG appeared to be a credible signal to

the participants. In the non-credible conditions, the price sequence for the first three stores was

set to be $1259, $1275, and $1250. Thus, the price at the second store was not the lowest

among all stores, resulting in a non-credible ALP/LPG signal. Compared to the price difference

($95) manipulated in Experiment 1, the price difference manipulated in Experiment 2 was

much lower ($25). Similar to the low search cost condition in Experiment 1, the search cost

was set to be $5 per store visit. After the shopping tasks, participants responded to sets of

questions related to the manipulation checks, dependent measures, shopping experiences,

demographic characteristics, and understanding of the simulations.

Manipulation checks

29

We checked the store signal manipulation by asking participants to recall the content of

the ad they saw in the shopping simulation. We discarded responses from participants who (1)

failed to recall the content of the ad and (2) searched only one store and thus did not see the ad

manipulation. For the non-credible ALP/LPG conditions, participants should have noticed that

the price at the second store was higher than other stores. We checked this manipulation by

asking participants after the shopping simulation whether they recalled the price level at the

ALP/LPG store. Of the participants, 89 percent indicated that they recalled the price at the

ALP/LPG store as being more expensive than other stores in the non-credible conditions, while

92 percent indicated that the price at the ALP/LPG store was less expensive than other stores in

the credible conditions. We discarded responses from participants who did not accurately recall

the price level at the ALP/LPG store. After discarding the invalid cases, 318 respondents

remained from the original 350. We assessed participants’ understanding and involvement in

the shopping simulation using the same measures as in Experiment 1. Participants indicated

that they had a reasonable understanding of the procedures (M = 5.7) and sufficient

involvement in the shopping task (M = 5.9). Finally, a multiple choice question asked

participants what major decision strategy they used in the shopping simulation. Responses

indicated that the majority (81 percent) focused on finding the lowest price and visiting as few

stores as possible.

Measures for dependent variables and covariates

We assessed participants’ perception of store integrity (" = .86) and ALP/LPG stores’

self-serving intentions (" = .87) using the same measures as in Experiment 1. We assessed

ALP/LPG stores’ customer-oriented intentions with three items (" = .78) on a seven-point

Likert scale. Two of these items were the same as in Experiment 1. The additional item read:

30

“The store uses the ad claim to save customers time to shop around as the lowest price is

guaranteed.” In addition to the key dependent measures, we asked participants at the end of the

simulation to report their general beliefs of the strength of the ALP/LPG signals based on their

own shopping experience with real stores. We used this measure to rule out the possibility that

more favorable perceptions toward LPG are attributed to its greater perceived signaling

strength than ALP. The scale consisted of two items on a seven-point Likert scale (" = .94):

“The merchandise at the store with the [ALP or LPG] is in general cheaper than other stores

without such a policy,” and “The [ALP or LPG] credibly signals that the prices at that store are

among the lowest in the retail market.” We included two covariates in the analysis. We

measured participants’ price consciousness by the same scale as in Experiment 1 (" = .85). In

addition, prior to the shopping task we asked participants their expected price range for the

HDTV and we used this information as a covariate.

Results

We performed a 2 (signal type) ! 2 (signal credibility) ANCOVA on the number of store

visits, followed by planned contrasts to test H1a. The covariates were participants’ price

consciousness and expectation of product price range. The ANCOVA results indicate that the

signal type ! credibility interaction is significant (F(3, 312) = 5.64, p < .05) while the effects of

the covariates are not significant. The significant interaction suggests that store visits differed

between ALP and LPG conditions when both signals appeared to be credible (i.e., the

accessible price information did not allow participants to refute these claims) (F(1, 312) = 7.32, p

< .01) but not when both signals were non-credible (F(1, 312) = .43, ns).

To test H1a, we compared the number of store visits between the credible ALP and the

credible LPG conditions using planned contrasts. The result indicates that the mean difference

31

is significant (MALP = 4.41 and MLPG = 5.16; F(1, 314) = 5.44, p < .05), suggesting that

participants searched more stores in a market with LPG than in a market with ALP when both

signals appeared to be credible. H1a is supported. Results of planned contrasts also show that

participants visited fewer stores in a market with non-credible LPG than in a market with

credible LPG (MNon-credible LPG = 4.24 and MCredible LPG = 5.16, F(1, 314) = 21.47, p < .01),

supporting H3. These results are consistent with those in Experiment 1.

We performed a 2 (signal type) ! 2 (signal credibility) ANOVA on participants’

perceptions of customer-oriented intention, self-serving intention, and integrity respectively,

followed by planned contrasts to test the simple effects stipulated in H2 to H5. The ANOVA

results show that the signal type ! credibility interactions are significant for customer-oriented

intention (F(3, 314) = 2.40, p < .05) and self-serving intention (F(3, 314) = 2.14, p < .05) but not for

integrity (F(3, 314) = .54, ns). Thus, these results suggest that participants’ perceptions of store

motives differed between ALP and LPG stores when both signals were credible but not when

they were non-credible.

As predicted in H2a, participants’ perception of retailers’ customer-oriented intention

differed between the LPG store and the ALP store when both appeared to be credible indicators

of lowest market price. The planned contrast indicates that participants perceived the credible

LPG store as having a stronger customer-oriented intention than the credible ALP store, (MLPG

= 4.65 and MALP = 4.17; F(1, 314) = 8.05, p < .01). In addition, participants perceived the credible

LPG store as having a weaker self-serving intention than the credible ALP store (MLPG = 3.68

and MALP = 4.29; F(1, 314) = 8.38, p < .01), supporting H2b. As H2c predicted, participants

perceived the credible LPG store as having greater integrity than the credible ALP store (MLPG

32

= 4.98 and MALP = 4.42; F(1, 314) = 12.30, p < .01). These results are consistent with Experiment

1.

Participants’ store evaluations also differed between the credible and non-credible LPG

conditions. The planned contrasts show that participants perceived the credible LPG store as

having a stronger customer-oriented intention than the non-credible LPG store (MCredible LPG =

4.65 and MNon-credible LPG = 3.67; F(1, 314) = 21.47, p < .01), H4a is supported. As H4b predicted,

participants perceived the credible LPG store as having a weaker self-serving intention than the

non-credible LPG store (MCredible LPG = 3.68 and MNon-credible LPG = 5.42; F(1, 314) = 36.66, p < .01).

As H4c predicted, participants perceived the credible LPG store as having greater integrity than

the non-credible LPG store (MCredible LPG = 4.98 and MNon-credible LPG = 3.78; F(1, 314) = 23.74, p <

.01). Findings were similar for the case of ALP with respect to store evaluations. The planned

contrasts show that participants perceived the credible ALP store as having a stronger

customer-oriented intention (MCredible ALP = 4.17 and MNon-credible ALP = 3.29; F(1, 314) = 22.83, p <

.01), a weaker self-serving intention (MCredible ALP = 4.29 and MNon-credible ALP = 5.76; F(1, 314) =

49.42, p < .01), and greater integrity than the non-credible ALP store (MCredible ALP = 4.42 and

MNon-credible ALP = 3.04; F(1, 314) = 79.27, p < .01). The above results support H5a, H5b, and H5c

respectively and are consistent with Experiment 1.

Compared to the result in Experiment 1, the proportion of participants who chose to shop

at the non-credible LPG store and claim the discount/refund was much lower, only 29 percent.

This difference is possibly because participants perceived the financial gain from claiming the

LPG did not worth the effort in Experiment 2. We report summary statistics of the dependent

measures in Table 3 and summarize the planned contrast analyses in Table 4.

33

The overall findings in Experiment 2 are consistent with those in Experiment 1. Thus, our

results provide empirical support across two product categories and retail markets with

different signaling environments. In addition, we found that participants held more favorable

perceptions toward the credible LPG store than the credible ALP store despite ALP being

perceived as possessing stronger signaling strength. Participants rated the signal strength of

ALP to be greater than LPG (MALP = 4.66 and MLPG = 4.19; F(1, 314) = 6.10, p < .01).7 This result

partly explains why ALP may discourage consumers from searching more effectively.

Finally, we found that H3 holds true even when participants received a much lower

financial gain from claiming a discount/refund at the non-credible LPG store. The maximum

savings participants could gain in the shopping task was $30 (not the actual compensation)

relative to $119 in Experiment 1. About one third of participants claimed the discount/refund at

the non-credible LPG store while the majority shopped at the store that offered a better price.

Therefore, fewer store visits in the case of non-credible LPG was mainly because participants

were drawn to shop at the lower-priced store at their early stage of searching. In conclusion, the

presence of non-credible LPG in a retail market would discourage consumers from visiting

more stores rather than motivating them to search more.

General discussion and managerial implications

Several key findings emerge from our shopping simulation study. First, we find that when

search costs were relatively low and store-price signals appeared to be credible, consumers

searched least after encountering an ALP signal and most after encountering an LPG signal.

The degree of search after encountering a non-price signal fell in between, being higher than

7 We compared this measure between the credible and the non-credible signal conditions. The ANOVA results indicate that signal strength belief is not affected by the manipulation of signal credibility, confirming that respondents refer to their real shopping experiences when answering these questions.

34

ALP and lower than LPG. Hence, when both store-price signals appeared to be credible (i.e., no

contradictory evidence available for refuting the low price claim), ALP more effectively

discouraged consumers from comparing prices across stores than did LPG. When search costs

were high, consumers’ search behavior were not affected by the type of signals they

encountered. Consumers tended to ignore the store-price signals and made no attempt to

interpret the relevance and implications of such signals for their search decisions.

Second, we find that when both ALP and LPG appeared to be credible, consumers

believed that ALP stores had a stronger intention than LPG stores to discourage consumers

from comparing prices across stores and to take advantage of consumers’ lack of price

information. In contrast, LPG stores were believed to have a stronger intention to protect

consumers from price fluctuation and seen as trustworthier than ALP stores. However, note that

our experiments mainly focused on price search and the hassles involved in claiming

discounts/refunds from the LPG store were lower than those in most actual shopping, the

finding that consumers held more favorable perceptions toward LPG stores may be positively

biased.

Third, our findings show that consumers searched less before their purchase when they

encountered a non-credible LPG relative to a credible LPG in the marketplace. This finding

may seem counterintuitive, as the presence of a non-credible LPG could heighten consumers’

price awareness and engender the perception that prices vary more than expected, leading to

more searching. Nevertheless, our finding suggests that consumers visited fewer stores because

requesting a discounted price at the non-credible LPG store rather than continuing the search

could maximize their financial payoff. Another reason is that after visiting the LPG store,

consumers were more inclined to purchase at the competing store that offered a more attractive

35

price. Finding a price lower than that at the LPG store gave consumers a strong reason to make

the purchase more immediately, since the price was deemed to be a good deal. Therefore,

consumers had little incentive to keep searching as they expected that the current refunds or

savings would outweigh the expected financial gain from searching further, which was less

certain.

Fourth, we find that consumers held unfavorable perceptions toward stores using non-

credible ALP or LPG than stores using credible signals. Consumers perceived the non-credible

stores as having a stronger self-serving motive and as being less trustworthy. In addition, the

negative perceptions toward non-credible LPG stores persisted even though consumers could

benefit from the refund, suggesting that the negative impact of defaulting on LPG was not fully

recoverable from the refund promise. We also find that the non-credible LPG store received

less favorable evaluations from consumers than stores using non-price signals such as service

assurance claims.

Fifth, we find that, compared to consumers who shopped at other stores, consumers who

shopped at the non-credible LPG store tended to be more forgiving and believed the store to be

trustworthy. However, a significant proportion of consumers shopped at other stores rather than

at the non-credible LPG store. In other words, although some consumers claimed a refund at

the non-credible LPG store after discovering a lower price elsewhere, a significant number

forewent this opportunity. This may be either because consumers perceived the rewards from

claiming refunds did not worth the hassles or that they intentionally penalized the non-credible

LPG store. In real shopping, since the effort required to return to the LPG store and claim

refunds is greater than as implemented in the shopping simulation, it is likely that the

36

proportion of customers who would shop at the lower-priced competitor is greater than that

observed in this study.

Finally, we found that price-consciousness had no impact on consumer search. We

speculate that the price search tasks in our experiments might heighten the participants’

temporary state of price-consciousness, which overrode the influences of participants’ chronic

price-consciousness. In addition, since the participants who paid minimal attention to price

information were eliminated in the analysis and the search tasks focused mainly on prices, the

effect of price-consciousness as a consumer trait may be understated in this study relative to

real shopping environments.

In conclusion, this research contributes to the retailing literature in several ways. First,

this study is the first to demonstrate the differing impact of LPG and ALP on consumer search

and store evaluations. Second, although previous studies have examined the effect of LPG on

store evaluations concerning service quality and price level, this study is the first to reveal

consumers’ inferences of retailers’ self-serving and customer-oriented motives behind the

deployment of store-price signals. Third, this study is the first to demonstrate how consumer

search and store evaluations differ between credible and non-credible store-price signals.

Managerial implications

This research offers several important managerial implications. First, retailers need to

consider the implications of using store-price signals to simultaneously discourage consumer

search and create a price-competitive image. These two goals do not necessarily align with

each other. For instance, although ALP stores can convince consumers to not engage in price

comparison across stores, consumers tend to perceive ALP stores to be more self-serving and

less trustworthy than LPG stores. Therefore, ALP stores have to devise appropriate marketing

37

communication strategies to complement its ALP policy and leverage its brand reputation to

temper consumers’ negative perceptions toward ALP.

Second, consumers tend to believe LPG stores to have a stronger customer-oriented

motive and to be more trustworthy than ALP stores. Paradoxically, LPG would trigger greater

consumer search under the low search cost situation, since consumers expect to gain financially

by finding a lower price elsewhere and becoming eligible for a refund. Thus, to avoid hefty

administrative costs in handling refunds and losing sales to competing stores arising from

greater consumer search propensity, LPG stores must monitor market prices regularly to ensure

that their prices do not deviate too much from the lowest market price. Compared to a price-

beating policy, a price-matching policy is more effective in discouraging consumers from

searching as the expected gain from claiming refunds is smaller. However, the shortcoming is

that the price-matching policy may be less powerful than the price-beating policy in inducing

positive consumer perceptions.

Third, although the type of signal does not affect consumer search when consumers

encounter high search costs, store-price signals would still have a mild influence on consumers’

store evaluations. Therefore, retailers should use LPG rather than ALP, as LPG would engender

a more favorable store image in the minds of consumers while there will be no increased

consumer search propensity when comparing prices across stores is difficult (e.g., when

product-assortment overlap among stores is low or stores are widely dispersed in a

geographical area). This is particularly relevant when the target segments have high time costs

and cannot afford to shop around.

Fourth, LPG stores must monitor market prices closely and regularly to prevent their

signals from becoming non-credible. If consumers can easily find lower prices elsewhere, they

38

would attribute a negative intention to the store even though they are eligible to claim a refund.

Although some consumers would take advantage of the promised refund, others may be not

sufficiently motivated to claim the refund and simply shop at the lower-priced store. Thus, even

though a non-credible LPG store may not incur substantial costs in administering the price-

matching policy, as not every consumer comes forward to claim a refund, the store would still

suffer long-term financial losses from customer defection, negative word-of-mouth, and poor

store image. Hence, only genuinely low-priced retailers can benefit from issuing LPG. To avoid

customer responses backfiring, high-priced retailers should not use LPG opportunistically.

Limitations and future research

Our study has several limitations that suggest areas for future research. First, caution

should be exercised when generalizing our findings to real offline or online shopping. Our

experiments simulated actual offline shopping in major aspects including costs and benefits of

searching across stores, accessibility to a range of stores, availability of store information and

price signals, and the option of claiming refunds at LPG stores. The prices of the products

(notebook computer and TV set) used in the search tasks also reflected real market prices in a

metropolitan area. However, in our shopping simulations, even though consumers’ mental

processes should be comparable between real shopping and simulated shopping, the incentives

(actual payoff) for participants to evaluate the costs and benefits of store search were much

lower than those for real shopping. The hassles and costs involved in claiming refunds were

also different. Participants could return to the LPG store and claim refunds with little effort, in

contrast, consumers in real shopping have to find lower prices at other stores, bring the proof to

the LPG store, and apply for the refund. Note also that our experiments focused on high-value

durables, it is possible that consumers would be less responsive to store-price signals and their

39

credibility for low-value frequent purchases such as household goods. Therefore, our findings

may not hold true if generalizing them to low involvement items.

Second, we considered signal credibility as true versus false signals of lowest market

price. When a retailer’s signal is true, consumers do not find lower prices elsewhere during

their search, thus the available price information suggests the signals are credible. However,

signal credibility can be operationalized as the extent to which consumers likely associate a

signal with low prices using factors such as geographic distance between competing stores, the

presence of branded variants, accessibility of price information, and restrictions on the refund

policy. Future research should explore the implications of consumers’ use of different cues to

infer signal credibility. Another important consideration is how consumers’ experience with

store-price signals in the real marketplace interacts with the available cues.

Third, although we collected data using an online consumer panel, our experiments

simulated offline shopping rather than online shopping. It is unclear to what extent our findings

generalize to online shopping. Search costs are considerably less for online shopping owing to

the power of search engines, suggesting that our findings for the low search cost condition

could apply to online shopping. On a different note, store-price signals like LPG in the online

versus offline environment may have different implications for consumers’ search behavior.

Consumers may perceive online stores’ LPG to be less believable, since more complicated

procedures would be involved in claiming refunds. Consumers may be less likely to take the

face value of LPG, since the ready accessibility of price information online motivates them to

search more. These issues should be examined further in future research.

Fourth, consumers today tend to use online search to facilitate offline shopping, or vice

versa. For example, consumers might visit physical stores to inspect and choose the right

40

product before buying it online, or surf the Internet to find the right product before buying it at

a physical store. Since shopping behaviors in real life, especially those involved in cross-

channel shopping, are complex and diverse, our simulations were only able to mimic simple

scenarios. Future research should combine laboratory experiments and field studies to

investigate consumers’ cognitive and behavioral responses to store signals in these more

realistic but complex contexts.

Fifth, given that popular discount stores like Wal-Mart use ALP and are widely known as

being price competitive, consumers may tend to view ALP stores as more credible than LPG

stores. Additionally, some LPG stores are perceived as “cheating” because they only carry

exclusive inventory or impose restrictions on the refund policy (e.g., restricting eligible

products, excluding Internet purchases, etc.). Although our findings provide some evidence that

consumers perceive ALP to be a stronger signal of low price, future studies can offer additional

insights by examining the context in which consumers learn about LPG, ALP, and the price

images of retailers that used them.

Finally, although our experiment controlled for a number of extraneous factors such as

price dispersion, store names, product type, content of store signals, and costs involved in

claiming refunds, these factors affect consumers’ perceptions and search behavior in actual

shopping environments. Using simulations to examine consumer responses to store-price

signals without varying the above factors limits the generalization of our findings. For instance,

our finding that consumers have differing perceptions of retailer motives between ALP and

LPG stores may be upward biased, since consumers’ perceptions are also influenced by store

characteristics and image, as well as the costs and hassles involved in getting refunds. Finally,

in our experiments only one retailer uses the price signal. In the actual marketplace, competing

41

stores often use the same type of signal to attract customers. Future research should examine

how consumers respond in such a multiple-signal environment. In addition, retailers frequently

use more than one type of price signal (e.g., price comparison ad, reference prices, etc.) to

project their price image. Understanding how these signals interact to affect consumer

responses is important.

42

References

Alba, Joseph W., Susan M. Broniarczyk, Terence A. Shimp and Joel E. Urbany (1994), “The

Influence of Prior Beliefs, Frequency Cues, and Magnitude Cues on Consumers’

Perceptions of Comparative Price Data,” Journal of Consumer Research, 21 (September),

219-235.

Anderson, Eric T. and Duncan Simester (2003), “Mind Your Pricing Cues,” Harvard Business

Review, 81 (9), 97-103.

Bergen, Mark, Shantanu Dutta and Steven Shugan (1996), “Branded Variants: A Retail

Perspective,” Journal of Marketing Research, 33 (February), 9-19.

Biswas, Abhijit, Chris Pullig, Mehmet I. Yagci and Dwane H. Dean (2002), “Consumer

Evaluation of Low Price Guarantees: The Moderating Role of Reference Price and Store

Image,” Journal of Consumer Psychology, 12 (2), 107-18.

_______, Sujay Dutta and Chris Pullig (2006), “Low Price Guarantees as Signals of

Lowest Price: The Moderating Role of Perceived Price Dispersion,” Journal of Retailing,

82 (3), 245-57.

Bobinski, George S., Dena Cox and Anthony Cox (1996), “Retail ‘Sale’ Advertising,

Perceived Retailer Credibility, and Price Rationale,” Journal of Retailing, 72 (3), 291-306.

Boulding, William and Amna Kirmani (1993), “A Consumer-Side Experimental Examination

of Signaling Theory: Do Consumers Perceive Warranties as Signals of Quality,” Journal

of Consumer Research, 20 (June), 111-23.

Campbell, Margaret C. (1999), “Perceptions of Price Unfairness: Antecedents and

Consequences,” Journal of Marketing Research, 36 (May), 187-99.

43

_______ (2007), “Says Who?! How the Source of Price Information and Affect Influence

Perceived Price (Un)fairness,” Journal of Marketing Research, 44 (May), 261-71.

Chatterjee, Subimal, Timothy B. Heath and Suman Basuroy (2003), “Failing to Suspect

Collusion in Price-Matching Guarantees: Consumer Limitations in Game-Theoretic

Reasoning,” Journal of Consumer Psychology, 13 (3), 255-67.

Chen, Yuxin, Chakravarthi Narasimhan and Z. John Zhang (2001), “Research Note: Consumer

Heterogeneity and Competitive Price-Matching Guarantees,” Marketing Science, 20 (3),

300-14.

Dutta, Sujay and Abhijit Biswas (2005), “Effects of Low Price Guarantees on Consumer Post-

Purchase Search Intention: The Moderating Roles of Value Consciousness and Penalty

Level,” Journal of Retailing, 81 (4), 283-91.

_______, _______ and Dhruv Grewal (2007), “Low Price Signal Default: An Empirical

Investigation of Its Consequences,” Journal of the Academy of Marketing Science, 35,

76-88.

Erdem Tulin and Joffre Swait (1998), “Brand Equity as a Signaling Phenomenon,” Journal of

Consumer Psychology, 7 (2), 131-57.

Forehand, Mark R. and Sonya Grier (2003), “When is Honesty the Best Policy? The Effect of

Stated Company Intent on Consumer Skepticism,” Journal of Consumer Psychology, 13

(3), 349-56.

Grewal, Dhruv and Howard Marmorstein (1994), “Market Price Variation, Perceived Price

Variation, and Consumers’ Price Search Decisions for Durable Goods,” Journal of

Consumer Research, 21 (3), 453-60.

44

Jaccard, James and Robert Turrisi (2003), Interaction Effects in Multiple Regression. Thousand

Oaks, CA: Sage University Press.

Krishnan, Balaji C. Abhijit Biswas, Richard G. Netemeyer (2006), “Semantic Cues in

Reference Price Advertisements: The Moderating Role of Cue Concreteness,” Journal of

Retailing, 82 (2), 95-104.

Kardes, Frank R., Steven S. Posavac and Maria L. Cronley (2004), “Consumer Inference: A

Review of Processes, Bases, and Judgment Contexts,” Journal of Consumer Psychology,

14 (3), 230-256.

Kirmani, Amna and Akshay R. Rao (2000), “No Pain, No Gain: A Critical Review of the

Literature on Signaling and Unobservable Product Quality,” Journal of Marketing, 64

(April), 66-79.

Kopalle, Praveen, Dipayan Biswas, Pradeep K. Chintagunta, Jia Fan, Koen Pauwels, Brian T.

Ratchford, and James A Sills (2009), “Retailer Pricing and Competitive Effects,” Journal

of Retailing, 85 (1), 56-70.

Kukar-Kinney, Monika and Dhruv Grewal (2007), “Comparison of Consumer Reactions to

Price-Matching Guarantees in Internet and Bricks-and-Mortar Retail Environments,”

Journal of the Academy of Marketing Science, 35, 197-207.

_______, Lan Xia, and Kent B. Monroe (2007), “Consumers’ Perceptions of the Fairness of

Price-matching Refund Policies,” Journal of Retailing, 83 (3), 325-37.

_______ and Rockney G. Walters (2003), “Consumer Perceptions of Refund Depth and

Competitive Scope in Price-Matching Guarantees: Effects on Store Patronage,”

Journal of Retailing, 79 (3), 153-60.

45

_______, _______ and Scott B. MacKenzie (2007), “Consumer Responses to Characteristics of

Price-Matching Guarantees: The Moderating Role of Price Consciousness,” Journal of

Retailing, 83 (2), 211-21.

Lichtenstein, Donald R., Nancy M. Ridgway, and Richard G. Netemeyer (1993), “Price

Perceptions and Consumer Shopping Behavior: A Field Study,” Journal of Marketing

Research, 30 (May), 234–45.

Lurie, Nicholas H. and Joydeep Srivastava (2005), “Price-Matching Guarantees and Consumer

Evaluations of Price Information,” Journal of Consumer Psychology, 15 (2), 149-58.

Moorthy, Sridhar, Brian T. Ratchford and Debabrata Talukdar (1997), “Consumer Information

Search Revisited: Theory and Empirical Analysis,” Journal of Consumer Research, 23

(March), 263-77.

Ofir, Chezy, Priya Raghubir, Gili Brosh, Kent B. Monroe and Amir Heiman (2008), “Memory-

Based Store Price Judgments: The Role of Knowledge and Shopping Experience,” Journal

of Retailing, 84 (4), 414-23.

Prabhu, Jaideep and David W. Stewart (2001), “Signaling Strategies in Competitive

Interaction: Building Reputations and Hiding the Truth,” Journal of Marketing Research,

38 (February), 62-72.

Rao, Akshay R., Lu Qu and Robert Ruekert (1999), “Signaling Unobservable Product Quality

through a Brand Ally,” Journal of Marketing Research, 36 (May), 258-68.

Singh, Jagdip and Deepak Sirdeshmukh (2000), “Agency and Trust Mechanisms in Consumer

Satisfaction and Loyalty Judgments,” Journal of the Academy of Marketing Science, 28

(1), 150-67.

46

Srivastava, Joydeep and Nicholas H. Lurie (2001), “A Consumer Perspective on Price-

Matching Refund Policies: Effect on Price Perceptions and Search Behavior,” Journal of

Consumer Research, 28 (September), 296-307.

_______ and _______ (2004), “Price-matching Guarantees as Signals of Low Store

Prices: Survey and Experimental Evidence,” Journal of Retailing, 80 (2), 117-28.

Urbany, Joel E., Peter R. Dickson and Rosemary Kalapurakal (1996), “Price Search in the

Retail Grocery Market,” Journal of Marketing, 60 (April), 91-104.

Zwick, Rami, Amnon Rapoport, Alison King Chung Lo and A. V. Muthukrishnan (2003),

“Consumer Sequential Search: Not Enough or Too Much?” Marketing Science, 22 (4),

503-19.

47

Table 1 Experiment 1: Mean and standard deviation of dependent measures Independent variable

Service assurance claim (control

condition)

Always low price claim

Credible low price guarantee claim

Non-credible low price guarantee

claim

Low search cost

4.61(1.97)1

4.46(.73)2 4.72(1.16)3 4.08(1.30)4

4.13(1.50)1

4.22(.83)2 5.98(1.01)3 3.60(1.43)4

5.98(2.32)1

4.76(1.09)2 4.80(1.32)3 4.21(1.07)4

4.26(1.68)1

3.66(1.54)2 5.48(1.37)3 3.38(1.42)4

High search cost

3.50(1.17)1

4.24(.52)2 4.71(1.14)3 3.20(1.38)4

3.65(1.31)1

4.33(.90)2 5.77(1.16)3 3.78(1.33)4

3.24(1.05)1

4.54(.88)2 5.18(1.45)3 4.30(1.14)4

3.32(1.22)1

3.41(1.54)2 5.64(1.50)3 3.45(1.61)4

1Store visits, 2Perceived store integrity, 3Perceived self-serving intention, 4Perceived customer-oriented intention Note: Standard deviations are given in parentheses.

49

Table 3 Experiment 2: Mean and standard deviation of dependent measures Independent variables

Always low price claim Low price guarantee claim

Credible signal

4.41(1.78)1

4.42(1.02)2 4.29(1.33)3 4.17(1.00)4

5.16(1.88)1

4.98(1.02)2 3.68(1.41)3 4.65(1.22)4

Non-credible signal

4.49(1.80)1

3.04(1.16)2 5.76(1.36)3 3.29(1.30)4

4.24(1.73)1

3.78(1.33)2 5.42(1.25)3 3.67(1.40)4

1Store search, 2Perceived store integrity, 3Perceived self-serving intention, 4Perceived customer-oriented intention Note: Standard deviations are given in parentheses.

50

Table 4 Experiment 2: summary of planned contrast analysis

Hypo. Dependent variable

Store visits Self-serving intention

Customer-oriented intention

Store integrity

Means F !2 Means F !2 Means F !2 Means F !2

H1a/H2 Credible ALP vs. Credible LPG

4.41 5.16 5.44 .04 4.29 3.68 8.38 .05 4.17 4.65 8.05 .05 4.42 4.98 12.30 .07

H3/H4 Credible LPG vs. Non-credible LPG

5.16 4.24 21.47 .06 3.68 5.42 36.66 .31 4.65 3.67 21.47 .18 4.98 3.78 23.74 .21

H5 Credible ALP vs. Non-credible ALP

4.41 4.49 *.55 .00 4.29 5.76 49.42 .23 4.17 3.29 22.83 .12 4.42 3.04 79.27 .29

Note: all the F-values are significant at p<.01 except*

51

Figure 1. Interaction between types of signals and search cost (Experiment 1)

!"#$

!"%$

&"#$

&"%$

'"#$

'"%$

%"#$

%"%$

("#$

("%$

)*+,-./01$023/4$

567$ 8.19/:21$67;$ )*+,0.19/:21$67;$

)<4:1.$*=$$>?*.1$@/>/?>$

6*A$>13.0B$0*>?$

C/DB$>13.0B$0*>?$