Consumer Search Behavior in Online Shopping Environments

Proceedings of the 38th Hawaii International Conference on System Sciences - 2005

Consumer Search Behavior in Online Shopping Environments Nanda Kumar, Karl R. Lang and Qian Peng Zicklin School of Business, Baruch College, The City University of New York (CUNY) {nanda_kumar, karl_lang, qian_peng} @ baruch.cuny.edu

Abstract

usually tend to develop some search strategies to better manage the search process and to reduce search cost.

This paper explores search behavior of online

Online consumer search strategies include the choice and

shoppers. Information economics literature suggests that

usage of search engines, query formulation tactics,

search cost in electronic markets has essentially been

stopping and filtering rules, and other heuristics aimed at

reduced to zero as consumers are able to use powerful

coping with the vast amount of information that search

search tools free of charge to easily find and compare

engines typically return.

product and shopping information on the Internet. In the

It is frequently taken for granted that search engines are

present research, however, we present a research model

efficient and effective tools for reducing consumer search

proposing that users need to spend time and effort when

cost because they cover a huge amount of web content,

completing search tasks resulting in significant search cost

provide users with immediate access, present customized

and a trade-off between search cost and search

and personalized consumer information, and do not charge

performance. Preliminary findings from an Internet

for their service. Subjective

experiment indicate that search task complexity, search

satisfaction with the process and outcome of an online

engine capability, search strategy and user experience are

shopping

important

determining success and effectiveness of consumer

factors

determining

search

cost

and

performance.

experience

may

be

factors like personal more

important

in

searches than objective criteria like whether or not an available product with the pre-specified characteristics (price, color, style, functionality etc.) could actually be

1. Introduction

found. Therefore, we posit that technical and behavioral

Since the explosion of World Wide Web in the 1990’s,

search factors cannot be separated when studying search

the Internet has become an increasingly important

cost and online shopping. This study contributes to the

information source for consumers. A shopper may use Web

research of consumer information and product search and

search tools to look up pre-purchase product information

adds to our understanding on the determining factors of

(prices, design, style, reviews, etc.), even if the transaction

search performance. Most existing studies on Internet

is finally executed offline. Competing with Web directories,

search focus on web browsing and searching online library

catalogs and online databases, search engines have quickly

databases. The search task studied is usually some form of

become the primary Web search tool, though they did not

document search where search performance can be

come into public existence until 1994 [9]. Since search

measured by precision and recall. However, product search

cost is an important factor affecting consumers’ purchase

in online shopping is different from document search in

decisions as well as the seller’s pricing [28, 29], consumers

that search cost is a crucial factor affecting purchasing

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decisions and satisfaction also playing an important role in

has a significant influence on heterogeneous product

assessing consumer search performance. Few studies could

offerings in Internet markets [1, 2]. Bakos [2] found that

be found that focus on studying web search cost

reducing search cost for obtaining price and product

empirically. Past research in the information economics

information will typically improve market efficiency but

area indicates that Internet technologies and electronic

will also decrease seller profits in differentiated markets.

markets reduce buyer search costs (e.g. [2, 19, & 25]).

To avoid the loss in market power, sellers may exploit

However, an empirical study of search cost based on an

tactics such as collusion, increasing product differentiation,

explicit IT artifact is still lacking. This study investigates

withholding some information and increasing the difficulty

both behavioral and technological factors affecting search

for buyers to compare prices in an effort to offset the

performance in terms of search cost and satisfaction in the

initially lower search cost. Sellers are more willing to

context of a specific IT artifact – search engines.

submit their product information to search engines, but

The rest of this paper is organized as follows. The next

may hide their price information or provide ambiguous

section reviews the literatures on search cost theory and

prices to the search engines. However, all these studies

search behavior. Section 3 develops a research model for

failed

studying

search

performance on the Internet can be improved with aid of

performance in an online shopping context and also

specific IT tools, and how user-developed web search

proposes four central research hypotheses. Section 4

strategies affect overall search performance.

the

determining

factors

of

web

to

answer

explicitly how consumer

search

describes the research methodology and presents the

The Internet tends to be the initial and primary source

preliminary results from the pilot data. We conclude, in

of information for most consumers who use the Internet on

section 5, with a discussion of the potential implications of

a regular basis, thus decreasing the usage and importance

our research and an outline of future research directions.

of traditional information sources [21]. In addition to search engine technology itself, it is the human-technology

2. Literature Review

interaction that is most important to the usability and effectiveness of search engines in e-commerce [27].

In an

Two streams of literature are particularly relevant to

exploration of the patterns of web search behavior, Choo et

the present research - information economics and

al observed four scanning modes of used in web searches

behavioral research. Search cost is frequently seen as an

[8]:

antecedent or a parameter to influence other variables in

1) Undirected viewing: users have no specific information

information economics studies [2, 19, 25,28, 29]. However, economic studies usually treat the IT/IS artifact as a black-box by simply assuming that it has the capability to

need in mind; 2) Conditioned viewing: users direct attention to certain type of information or related with selected topics;

reduce or eliminate search cost. Smith et al [25] found that

3) Informal search: users actively seek information to

reduced search cost increases Internet market efficiency in

deepen the knowledge and understanding of some

three dimensions: price levels, price elasticity and price

specific topics; and

dispersion. Lower search costs lead to lower prices for both homogeneous [6] and differentiated goods [2, 25].

4) Formal search: users make a deliberate effort to obtain specific information.

Higher price elasticity (absolute values) may also result

Generally, it is considered a formal search when online

from lower search costs for Internet consumers [25]. Price

shoppers search product information with the help of

dispersion arises from high search costs [28,29] and thus

search engines. In addition, the information seeking

reduced search costs lead to lower price dispersion.

behavior exhibited during a formal search can be classified

In addition to the impact on prices, reduced search cost

into the following six categories [12, 13].

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1) Starting activities: including identifying sources of interest;

correctness of the search result is known or objectively verifiable. However, the application of such measurements

2) Chaining activities: follow up on the new leads obtained from initial sources either backward or forward;

has some problems with regard to product and consumer searches. Consumers who perform complex, open-ended

3) Browsing activities: including looking through table of

search tasks don’t know what is out there on the web and

contents, lists of titles, subject heading, abstracts and

may have difficulty verifying the “correctness” of search

summaries;

results. Moreover, users tend to evaluate the search process

4) Differentiating

activities:

including

filtering

and

selecting from sources by identifying differences

and outcome based on their individual satisfaction rather than correctness.

between the nature and quality of the information

User characteristics that have been modeled as independent variables include experience (web experience

offered; 5) Monitoring activities: keep abreast of developments in

or

search

experience),

knowledge,

beliefs,

tactics,

an area by regularly following particular sources; and

perceptions and motivations. Hsieh-Yee [16] found that

6) Extracting activities: systematically work through

users’ search experience affected their use of search tactics,

particular sources in order to identify material of

and subject knowledge had a significant impact on

interest.

experienced users. In another study, Hoischer and Strube

This categorization helps understand how users execute

[15] also observed that the combined effects of web

search processes using search engines. Web search

experience and domain-specific knowledge on web search

activities may start with submitting initial queries to obtain

performance. Yuan [34] investigates the role of search

hints from results and then follow the found URLs or

experience on multiple search process variables --

refine the queries. Additionally, web users may carry out

command and feature repertoire, language usage pattern,

successive information searches across multiple sessions

error pattern, search speed and user attitude over time and

[18, 26, & 27]. They can also start with browsing some

found that search experience impacts all the dependent

directories that may be provided by a search engine.

variables significantly, except error patterns. Most of these

Afterwards, differentiating activities are needed to narrow

studies

down the search scope until satisfactory results are found.

computerized local library databases that were not

If search engines return too many matches, intensive and

connected to the Internet, except for [15], [26] and [27]

complex extraction is required before the results become

that studied online search engines explicitly. Since search

useful.

During

all

these

information-seeking

conducted

laboratory

experiments

using

and

engines have many similarities with online library

processing episodes, the information problems move

databases such as structured schemata and user interfaces,

through such stages as identification, definition, resolution

these studies may theoretically be applicable, at least to

and presentation until uncertainty is sufficiently resolved

some extent, to the study of Internet search engines also.

[27].

However, more research on consumer searches on the web

Most studies of web search behavior focus on two

is clearly needed.

dependent variables: search outcome (performance) and search process. Search processes are the observed search

3. Research Model

paths and patterns that occur with all search interactions (e.g. the six categories of information seeking behavior

Based on the previous literature, we include the three

Search outcomes are the consequences

chief factors user ability, search task, and search engine

of web search behavior, usually measured with precision

capabilities as the independent variables in our own

and recall [5], which are quite appropriate measures if the

research model and use search performance, which is

discussed above).

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modeled as a combination of search cost and user

queries, process search results and find needed products

satisfaction as the dependent variable (Figure 1). Users’

faster. Therefore, it is hypothesized that

employed search heuristic is a moderating variable that

H1: For consumers using search engines, stronger user ability leads to lower search cost.

affects the intensity of the relationships among the main variables.

3.2. Search Engine Capability User Ability

Search Heuristic

Capabilities of search engines refer to the functions or features that search engines provide to improve end-users’

Search Engine Capability

H1

H4

Search Performance

H2

1) Search Cost 2) User H3

Satisfaction

Search Task

usability and effectiveness [26]. Previous studies have explored

both

context-related

(user

interface)

and

content-related (search results) capabilities. Chu et al [9] compared and evaluated retrieval performance based on search capabilities like boolean logic operators, truncation, field search, word and phrase search. Bradlow and Schmittlein [5] investigated the association between overall search performance and a search engine’s structural

Figure 1. Conceptual Research Model

and technical properties including search engine size, depth, frame support, image maps and learning frequency. Both studies found that search engines’ capability affect search performance. In addition to such content-related

3.1. User Ability

capabilities, search engines provide non-search capabilities User ability refers to the users’ experience in using

[30] around the search interfaces to enhance usability.

search engines and to their knowledge of the subject of the

These features include non-personalized features such as

search. User experience [15, 16, & 34] and subject

directories, news, weather, maps, animations, advertising

knowledge [15, 34] have been found to significantly affect

banners, and also personalized features such as emails,

consumer information search. User experience can be more

chat rooms, bulletin boards and personalized home pages.

specifically measured by user’s web experience and search

A recent study [11] finds that animations and advertising

experience [15, 16, & 34]. web experience is the length of

banners impact users’ behavior significantly. Besides, some

time a user has been (regularly) using the Internet.

search engines provide non-personalized features only (e.g.

Likewise, search experience is the length of time a user has

Google), while others embed the search interface within a

been using search engines. A user with more web

web

experience and search experience has a higher ability to

non-personalized features (e.g.Yahoo!). The difference is

find the sought information using search engines. Subject

that personalized features require users to provide the

knowledge is the domain or product-specific knowledge

system with information about their personal identity so

relevant to specific search tasks, which a user has had

that access to the personalized area can be protected,

already when starting a search task. A user with deep

usually with a username and password. Non-search

subject knowledge is better able to formulate effective

features affect users’ preference to search engines [30].

search queries, identify results and filter and interpret found information.

portal

that

contains

both

personalized

and

In addition, some search engines are capable of clustering search results [7]. For example, the search

A user with stronger ability can figure out search

engines Teoma, Vivisimo, and AllTheWeb can categorize

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their search results on the fly, which is assumed to help

or open-ended [3]. For example, when searching for a

users identify and refine search results. Another example is

specific textbook, which is easily and completely specified

Google’s shopping search engine Froogle that, unlike the

with book title, author and edition, the complexity is low.

general Google search engine, searches only shopping sites

But a search task like finding “a nice vacation package” is

and displays product images, prices and brief description

only incompletely specified and is much more complex

directly. This presumably helps consumers comparing and

due to its openness to multiple “correct” answers. Both

selecting products

scenarios are quite common, but high impact search tasks

indicator

of

when shopping online.

search

engine

Another

capabilities

is

its

(e.g. shopping for a product with high financial impact) are

comprehensiveness [32]. Whereas general search engines

often also more complex than low-impact search tasks.

such as Yahoo, Google, AltaVista, Excite and Lycos cover

When search tasks have high complexity, users may spend

almost all kinds of web information, some search engines

more time refining queries, filtering information and

are dedicated to certain types of information. For example,

identifying search results, thus leading to higher search

BookFinder.com is a search engine concentrating on

cost.

searching books. Mp3search.com is tailored for searching

H3: For consumers using a search engine, higher

music online. Such specific search engines may help users

complexity of search tasks leads to higher search cost.

find certain types of products faster than general search engines, but are limited in their coverage and may also

3.4 Search Heuristics

have other restrictions. Since perceived usefulness of web sites and their

Search heuristics are user-predefined rules to determine

particular features have been found to have a strong impact

how a search is initiated, refined, processed and eventually

on online consumer behavior [17], those search engine

terminated. These rules could be explicitly formulated and

features may also empower users and enhance search

documented, but in practice consumers are more likely to

performance.

develop

Furthermore,

capabilities

such

as

heuristics

implicitly,

and

perhaps

even

browsability (ease of finding and understanding displayed

subconsciously. The determining rules are constrained by

results), customizability and relevance are found to impact

budget constraints, desired effort expenditure, desired

end-users’ performance [32]. Hence, we propose that

accuracy, and overall satisfaction with the search results.

H2: For consumers using a search engine, higher search

In a DSS context, desired effort expenditure and accuracy

engine capability leads to lower search cost.

have been found to moderate the impact of IT support on decision-making performance [31]. If a user increases his efforts in searching for products, the quality of his search

3.3. Search Task

results may improve, but the search costs are likely to Users typically perform various search tasks. Some are

increase as well. If a user looks for very satisfying

easy to define and specify, some are complex, some are

products only, the resulting search cost could also be

specific and others are general. The type of the search task

higher than it would be if searching for a product that

given to users has been identified as a significant factor

merely fits the bill. If a user desires to spend more effort or

affecting users’ search behavior in information retrieval

expects higher satisfaction, then his search heuristic will be

settings [4, 15]. Complexity is an important dimension

different. In general, there is a trade-off between search

when measuring differences between types of search tasks

cost and expected satisfaction. Borrowed from the DSS

[3, 15].

A simple task, which could be fact-based or

literature [10], we measure the search heuristics employed

closed, has a known target answer that users intend to find,

by their level of restrictiveness. Higher restrictiveness (i.e.

while the complex tasks are typically more research-based

harder constraints) of search heuristics means more desired

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effort, accuracy and higher satisfaction.

freely controlled and manipulated, as was the case in the

H4: For consumers using a search engine, the impact of

above cited studies. However, since the Internet and the

user ability, search engine capability and search task

web are open systems that run on a public infrastructure

on search cost will be stronger when the employed

that exhibits variations in work load balance and has, at

search heuristic is more restrictive.

any given time, many millions of active users and web sites

whose

content

and

responses

are

changing

continuously, it is difficult, in a strict sense, to design

3.5 Search Performance

rigorous lab experiments to test research models and The concept of search performance refers to the search

hypotheses. Nevertheless, convinced that understanding

outcome, in particular to search cost and user satisfaction,

online behavior requires researchers to study people’s

in our research model. Since search engines’ services are

actions and choices set in real Internet environments,

free of charge, users’ search costs are mainly the amount of

Internet

time spent on searching the Internet for some desired

methodology of lab experiments less strictly, and often call

product or service [2, 6]. Assuming that the consumer

them Internet experiments or virtual field experiments

focuses on a single search task at a time, search cost can be

instead, in order to be able to experiment with real web

measured as the length of the entire search process, starting

sites that are impossible to replicate in the lab [14]. Trading

from initiating a search task to finding the needed results

off some methodological rigor for increased realism and

that completes the search task. This time duration covers

relevance is a choice that appears adequate in our context.

researchers

are

increasingly

using

the

the entire information-seeking process, which may evolve

Our experimental Internet study will utilize a 2x2x3

in one, single session or over several, successive search

design with 2 levels of search task, 2 levels of search

episodes [27].

Alternative measures of search cost

engine capability and 3 levels of search heuristics. Based

include the number of clicks and web pages that are

on a small pilot study, the research constructs have been

navigated in the process [26, 30].

refined and are described below.

The second dimension that needs to be considered when measuring search performance is user satisfaction.

1) Search Task: Two search tasks have been designed. One

It can be modeled with the following five components:

is a task with low complexity such as searching the

content, accuracy, format, ease of use and timeliness [33].

Beatles’ White Album CD, which is basically a

In general, there is a trade-off (negative correlation)

closed-ended task. The other is a task with high

between user satisfaction and search cost. The longer a

complexity, that is, a one-week “nice” vacation

consumer needs to search (high search cost) the less

package, which is open-ended and includes decisions

satisfied she gets, and lowering the required satisfaction

regarding destination, hotel, transportation, special

level will decrease search time and search cost.

events, comfort level, willingness to pay, and other features.

4. Research Design

2) Search Engine Capability:

The clustering capability

has been chosen as the differentiator of search engine Most studies of information search behavior take

capabilities in our study. According to [7] cluster-based

laboratory experiments as their research methodologies,

representations – such as used by the search engine

e.g. [8, 15, 17, & 34]. Using a laboratory experiment is

Vivisimo that we have chosen for our experiments –

generally a reasonable and adequate choice to study search

help users in processing and responding to large

behavior, especially when the information searches are

amounts of information, and thus help them finding

performed on local IT/IS systems and databases that can be

what they want. More specifically, clustering helps

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users sort search results by categories, filter results

2) Online Search: During the actual experimental search

more easily and refine their search queries. Search

processes, computer logs including the user-generated

engines with clustering features are supposed to help

queries, click streams, screens, web pages and time data

consumers with their online shopping searches and

are collected with a freely available shareware tracking

should reduce search cost. We use the construct

software [26, 27, & 30]. We record how much time a

Information Quality [18, 33] as a proxy to measure the

user spends on each visited page as well as the total

capability of the search engine.

amount of time subjects need to complete their assigned

3) Search Heuristic: Three heuristics are proposed for the experiment. One is weakly restrictive (“find the first

search tasks. 3) Post-Search interviews: Immediately after finishing the

available deal”); the second is strongly restrictive

experiment

(”find the best deal available”); and the third falls

questionnaire to evaluate the subjects perception

somewhere in the middle (“find a deal that satisfies

regarding the given search tasks, the search engine

your daily normal expectation”). Note, that all three

capabilities that they use in the experiment, and overall

search heuristics are formulated in qualitative terms

performance. In order to better understand people’s

that to some extent are deliberately vague in order to

actual search behavior we also conduct a short interview

leave some room for the subjects to inject their own,

asking them to tell us how they complete the search tasks

individual behavioral search habits, while at the same

assigned to them and to what degree they would employ

time guaranteeing that everyone follows one of the

search heuristics similar to those prescribed in the

three general strategies when performing actual

experiment when they perform consumer searches in

searches.

their daily lives outside the experiment.

each

participant

is

given

a

second

4) User ability: We are recruiting university students, who have generally high user ability because of their

4.2. Pilot Study Results

Internet experience and computer skills that they have already acquired in school or before at the workplace

The data collected in the experiment include: search

or elsewhere, as our experiment subjects. In addition,

transaction logs; quantitative data from the responses to

students usually have good domain knowledge in the

given questionnaires; the queries that the subjects

chosen search tasks, which in our case fall in the

formulated in the experiment; the URLs clicked; the total

domains of music (Beatles, The White Album) and

duration for completing the search tasks, the spent on each

traveling (vacation package). Students are screened for

visited web page during the search process as well as some

their ability level before admitted to the experiment.

qualitative data from the post-search interviews. Our research is, at the time of this writing, in the stage

Hence, this factor will be controlled in our experiment.

of preparing for the full experiment. A small pilot study has already been completed that helped us refine our research

4.1. Procedures

model and the actual conduct of the experiments. Three stages, pre-search, online search and post-search

The

pilot study also helped us in choosing a particular search

[26, 27], are being conducted in the experiment.

engine to be used in the experiment.

1) Pre-search survey: A questionnaire is given to the

compared seven particular search engines that provide

subjects, prior to the experiment, asking demographic

users with some form of clustering feature, namely Google

data and the users’ self-reported assessment of their

Sets, Vivisimo, AllTheWeb, Teoma, Wisenut, Infonetware

experience, computer skills and domain knowledge of

and

the search tasks.

relevance, ease of use and user satisfaction based on a set

Oingo.

We

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compared

the

In prior testing, we

comprehensiveness,

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of sample search tasks, and decided to use Vivisimo for our

Our tracking data also showed that the participants

pilot study, and in light of the pilot study result also for the

took more time to complete the complex tasks than the

full experiment.

simple tasks.

Vivisimo allows us to modify the user

They also spent a lot more time outside of

interface for our subjects such that the clustering feature

the search engine’s web page for complex tasks thus

can be hidden for some while shown to others.

indicating that while participants used the search engine to

The responses from the survey indicate that the

get a set of possible search results, they needed to spend

manipulation checks for search task and search engine

more time evaluating the information in these web sites to

capabilities were successful. Table 1 reports that on an

complete the task (e.g. say to get the best cruise vacation

average, participants used more search queries to complete

package to Bahamas). We also found that web sites that

complex tasks than simple tasks.

The data obtained from

provide rich, comprehensive, and high-quality information

the log files of tracking software that we used to record the

that is relevant to a given search task attain a certain level

users' interactions with the system during the search

of stickiness with users. They often stay for a while with

process showed that the participants needed to refine the

such a sticky site and perform a number of local follow-up

search queries to get at a more relevant set of results, even

searches before they return to the search engine to continue

with the provision of clustering capability.

and refine their search from there.

Often times,

this entailed participants typing synonyms or trying out

Table 2 indicates that participants seemed to attribute

different combination of search terms to refine the results.

higher information quality, better overall satisfaction and

This indicates that search engines are still weak in

more loyalty for the search interface with clustering

understanding the context of the search query – an

capability.

ontological problem that remains one of the more vexing

statistically significant because of the small sample size (8),

issues facing search engine performance.

the results of the pilot study (both from the tracking

While the results of the pilot study may not be

software and the survey results) as well as the qualitative feedback from the participants provides some support for

Table 1: Results from the Tracking Software

Average Number of Search

Simple

Complex

our research model and research design and will be used to

Task

Task

refine the procedures of our research study.

3.9

8.6

5. Conclusion

Queries Used per participant Average

Time

Spent

at

190

576 The contributions of this paper are several. First, our

Vivisimo.com per participant

proposed research model (presented in Figure 1) breaks

(seconds) Average Time Spent at other

647

2182

open the conventional black box notion of search cost, thus bridging

sites per participant (seconds)

behavioral

research

on

web

search

and

information retrieval and search cost theories in the information economics area. This study gives a more Table 2: Results from the Tracking Software

differentiated account of the concept of search cost, while

Clustered

Non-clustered

most work in economics studies simply assume that the

Computer Experience

6.9

6.4

Internet has reduced consumer search cost to zero or

Information Quality

5.1

4.8

quasi-zero. The present work may also improve our

Overall Satisfaction

5.4

3.6

understanding of how IT artifacts can affect search cost,

Loyalty

4.5

3.1

and search performance in general. In addition, it also helps understand consumer search behavior better by

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studying human interaction with search engines, and thus

[6] Brynjolfsson,

Erik

and

Smith,

Michael

D.(2000).

providing a more complete view of users’ actual search

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search cost. This study posits that behavioral factors and

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e-commerce sites, in particular) play an important role in

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