Hierarchies and eBay

Hierarchies, also called taxonomies, directories, and subject directories, are one of the

most familiar ways to organize information. From directories on the web such as Yahoo!

to the local yellow pages, users are well versed in how to locate information using a

hierarchical construct. A hierarchy is a system “of usually manually constructed

categories through which the use can browse starting from broader categories through

which the user can browse starting from broader categories and navigating down the

hierarchy (directory) to more specific ones” (Dennis, Bruza, and McArthur, 2002 ).

Generally speaking, a hierarchy is an organization scheme that establishes parent child

relationships between items in a list, where all children have all or most of the

characteristics of the parent. With this scheme, users can predict what items will be

contained in the main categories by determining the characteristics of the parent and

assume that all children will be more specific and unique in nature.

Hierarchies have been around for thousands of years and appear prominently in the

works of Aristotle and early scientists. The idea of constructing the hierarchy revolves

around two ideas: information can be organized in many ways but the two most common

ways hierarchies are constructed revolve around consensus of education or scientific

consensus. Respectively, these organize information around the manner in which they

are taught in education or in the way the subject is approached by specialists in the field

(Spiteri, 2000 ).

As the web has evolved into a very large, unorganized information source, many have

tried to construct hierarchies to provide access to users. Directories such as Yahoo! and

the Open Web Project have experienced various degrees of success and continue to

evolve. More importantly however is the use of the hierarchy as a navigation tool on

discrete sites. Hierarchies are many times embraced by designers because of their

familiarity to users and their ease of use. However, construction of hierarchies is usually

manual and can be time-consuming as well as expensive to create and maintain.

One electronic commerce site that has received attention from media and investors

alike is the auction site eBay. eBay is a marketplace where sellers post their items on the

site and buyers bid electronically on items. The items for sale are organized into a preset

hierarchy where sellers place their items according to their own determination. Buyers

can then browse through the categories of the hierarchy looking for items or can use the

simple search engine to retrieve items. The hierarchy itself contains twenty-four top level

categories with varying degrees of depth in each category. For example, the top level

category “Books” has ten second-level classes and each of those classes have anywhere

from four to thirty categories, with many of these having subcategories as each topic

becomes more and more specific.

The hierarchy is constructed with pre-defined categories by eBay staff. Sellers, when

posting the description of their item are asked to categorize their item in one of the eBay

categories and can pay and additional fee to have it listed in more than one category. The

hierarchy has undergone much transformation over the past years from twelve main

categories in 1997 to its current twenty-three. Categories that included many different

types of items such as “Books, Movies, and Music” have been separated into distinct

categories and new categories have been added to reflect new items such as automobiles

and real estate for sale in later iterations of the site.

This transformation indicates that eBay is continually monitoring the use of the

hierarchy and making adjustments where it sees fit. The importance of the hierarchy on

eBay is two-fold. The hierarchy can enhance browsing and lead buyers to serendipitous

discovery of items to buy or can find items of a similar nature to ones they may already

be interested in buying. The hierarchy, because of its straightforward nature and

familiarity to users can also serve new users who may not know enough about the site to

effectively use the search engines and their filtering abilities. Taxonomies can provide “a

means for designing vastly enhanced searching, browsing, and filtering systems. They

can be used to relieve the user from the burden of sifting specific information from the

large and low-quality response of most popular search engines (Chakrabarti, Dom,

Agrawal, and Raghaven, 1998 ).

Literature on Hierarchies and Browsing

Because browsing behavior is closely tied to the use of subject hierarchies, a

review of the literature of browsing as an information retrieval strategy can shed light on

why people use hierarchies and how they use them. With these studies, designers can

determine the best ways to construct these tools to meet the needs of the browser. In

addition to studies of user behaviors, much research has been conducted to effectively

create meaningful hierarchies automatically to reduce the time and expense generally

associated with constructing a subject hierarchy.

Browsing is an activity that has increasingly been studied as the World Wide Web

has emerged as a popular, accessible information tool. In 1997, browsing accounted for

61.27% of web activity (Fu and Salvendy, 2002). Browsing has been defined in many

ways in context of its purpose and its nature by many in the information science field.

Marchionini and Schneidermann (1988) who have done extensive studies of the user

interface and browsing define the activity as “an exploratory, information seeking

strategy that depends on serendipity. Elaine Toms (2000) defines browsing as ‘an activity

in which one gather information while scanning an information space without an explicit

purpose.” Strategies are heuristic and require users to recognize relevant information

through scanning and for determining interesting words which catch the eye (Cothey,

2002 Bates, 1996 ). O’Connor (1993) believes that the subject category does not support

browsing because ” browsing consists of a wide spectrum of idiosyncratic processes for

searching, sampling, and evaluating documents when significant attributes of a target or

goal are not full articulated or evident. When the librarian puts ‘related’ works nearby on

the shelf, they are said to be supporting browsing. Yet, by determining which

connections establish relatedness, they are supplying the pasture and tending to the user;

they are supporting grazing.” While scholars may differ on the particular nature of

browsing, many consistently cite user awareness of the information environment or the

nature of the task as being the underlying motivation in browsing as a user strategy

(Marchionini and Shneidermann 1988, Fu and Salvendy 2002, Toms, 2000, Cothey,

2002, Chen, Houston, Sewell, and Schatz, 1998, Chang and Rice, 1993, Qui, 1993).

Problems with browsing have also been well documented in the literature,

including missing pertinent items, longer search paths, missing pertinent items, and a

sense of feeling lost in the information space. Although some researchers believe that

hierarchies and browsing make “access easier and less-time consuming” (Griffiths,

1999), many studies have shown that the search time is longer than use of analytical

search tools such as search engines (Fu and Salvendy, 2002 ). Dennis et al. (2002)

contend that “direcctory based search using Yahoo does not seem to offer increased

relevance over keyword-based search and also takes longer .” Getting lost in hyperspace

is a well-documented phenomena where the user “does not have a clear conception of

relationships within the system, does not know his present location in the system relative

to the display structure, and finds it difficult to decide where to look next within the

system (Elm and Woods, 1985 ). Because of this disorientation, the user may experience

art museum phenomenon which is defined as “spending a great deal of time while

learning nothing specific” (Carmel, Crawford, and Chen, 1992 ). For new users to a

system, the likelihood they will miss pertinent information is demonstrated in the fact that

“users browse a selected topic using a depth-first search and miss other links at higher or

lateral levels” and that users familiar with the system may miss new items (Lai and Yang,

2000 ). Many designers have responded by providing concept maps, breadcrumb trails,

and site maps. These tools are used often when browsing and new users tend to use them

more than experienced users (McDonald and Stevenson, 1998).

Marchionini (1995) summarizes the limitations of browsing as follows: high

attention demand, inefficient for well-defined retrieval, possible distraction, possible

information overload, influences of various biases and cognitive inertia, systems not

designed to assist browsing, and subject to diminishing returns. Because browsing is

highly dependent on scanning the information environment, fatigue is also a major

limitation of browsing. Marchionini points to earlier studies by Wiberley and Daugherty

and Lee and Whalen where the upper limit of items users can browse without fatigue has

an upper limit of 200 items. In Lee and Whalen’s study of an automated mug shot

system, researcher’s concluded that accuracy fell rapidly between 100 and 200 images.

In addition to fatigue, browsers also fall prey to distractions and information overload, an

area where Marchionini believes is one of the areas where useful tools can be designed

for minimizing these problems. In an e-commerce setting, however, this remains to be

seen if this is an actual goal of the online retailer who may want to encourage impulse

buying and display his products strategically as he may in a physical store, designed to

catch the buyers eye and increase sales.

The hierarchy as a tool to assist browsers has been around for centuries. Much of

our classification in a hierarchy dates backs to Artistotle’s genus-species systems where

all species must contain the characteristics of the genus (Spiteri, 2000). Because of this

long history in information organization, many users are comfortable with this schema.

As Chen, Houston, Sewell, and Schatz (1998) note “browsing is frequently used in new

or relatively unknown information spaces, users typically rely on pre-existing mental

models of information organization as they explore. The most common mental models

are either alphabetically-based or based in hierarchical categories.” Kim and Allen

(2002) support the importance of the hierarchy as an information retrieval stating,

“Subject directories appear to be crucial to flexibility in information retrieval and helps

users with different characteristics and tasks find information they want.” Withstanding

all of the problems in browsing, the hierarchy is still a dependable tool that new users and

people unfamiliar with the search environment will find invaluable.

However, the goal of the designer should be to design the hierarchy in such a way

that the user intuitively understands the structure and will have little need of aids.

Drawing from the field of human-computer interaction, there are many guidelines offered

in the construction of hierarchies to make them more user-friendly and effective. The

breadth and depth argument regarding menu structure could possibly shed light on

designing hierarchies but there is inconclusive data to suggest that there is an optimal

formula for breadth of categories and depth of the hierarchy (Parkinson, Hill, Sisson, and

Viera, 1988). In most studies however, breadth is usually favored over depth, as long as

display crowding does not occur (Larson and Czerwinski, 1998). User studies with web

hierarchies of varying breadth and width still support the theory that breadth is better as

users in hierarchies with three levels performed poorly in experiments. However, the

same users also performed only slight better and complained of feeling lost in hierarchies

that had 32 categories at the top level (Larson and Czerwinski, 1998). In a large

hierarchy such as eBay or Yahoo!, it would be difficult to adequately represent the

information available by restricting the number of top categories and the depth to which

these categories could increase specificity of the topic.

There are characteristics that a well-defined hierarchy should have. Categories

should be mutually exclusive and homogenous (Spiteri, 2000 ). This means that

categories should not overlap when possible and that all items in a category should be

alike and share the characteristics of the class. Interfaces should “support scanning and

have good textual affordances. They must also provide salient cues that encourage

meandering and diversion which for ultimate success will facilitate serendipity” (Toms,

2000 ). Browsers must readily recognize topics and should be designed with novices in

mind and provide topics related to everyday, common sense knowledge (Carmel,

Crawford, and Chen, 1992).

Overall, the designer must keep in mind the needs of the user. As previously

stated, the traditional browser is either a novice searcher or does not have a well-defined

task in mind. As a result, the interface must recognize “the inherent ability of the human

eye to spot interesting words. The eye is much better than a computer for intellectually

scanning a mass of information, making associations among related or synonymous

topics, and choosing those of interest for further perusal (Bates, 1996 ). In the design,

the developer must design with visual recognition and spatial reasoning in mind as

opposed to linguistic specification (Chang and Rice, 1993 ). From the world of

information architecture come the recommendations that designers “recognize the danger

of overloading users with too many options, group and structure information at the page

level, and subject your design to rigorous user testing (Rosenfeld and Morville, 2002).

E-commerce activities at eBay also present additional problems in the sense that

topics generally do not lend themselves to one of the consensus model of education or

science. Categories are based loosely on products and services for sale that do not readily

align themselves with organization structures of traditional information retrieval

hierarchies. Miles, Howes, and Davies (2000) warn that “e-commerce should not be

assumed to be information retrieval” and that the interface must meet the needs of

consumer behavior which consist of need identification, product brokering, merchant

brokering, negotiation, purchase and delivery, and service and evaluation.

In his study of “The Dynamics of Mass Online Marketplaces”, Jungpil Hahn

(2001) discusses his idea of “market navigation design” which is a set of rules derived

from information architecture for a market setting. He discusses the aspects of breadth

versus depth, noting that fewer clicks with a breadth has the advantage of leading the

buyer quickly to a product but may result in more items meeting the buyers needs and

lead to information overload. Hahn also discusses the construction of hierarchies in

terms of the ability to list one item in more than one category. The advantage being an

increased likelihood of the buyer finding the single product versus confusion on the part

of the buyer due to inconsistent categorization.

In their study of browsing in a multidimensional framework, Chang and Rice

(1993) note that Bloch and Richins define browsing differently from a consumer behavior

point of view as “the in-store examination of a retailer’s merchandise for informational

and/or recreational purposes without an immediate intent to but. Consumer browsing

may be pleasurable in itself and can be done for various reasons. Again the impetus for

browsing seems to be a lack of goal-oriented search motivation and takes on an aspect of

recreation, instead of information retrieval.”

The results of browsing in an e-commerce situation are similar to those in a

traditional information system with minor differences. Besides enjoyment, browsers may

gain product knowledge and succumb to impulse buys (Chang and Rice, 1993 ).

Shoppers may also encounter new products whose existence of which they were unaware.

Whether these results do or should have any effect on the user’s experience with the

hierarchy remains to be seen.

Of further concern to those constructing hierarchies for web development is the

amount of time and personnel needed to create and update hierarchies manually. Chen, et

al (1998), argue for automatic means for constructing hierarchies because the “process of

creating the categories and connecting homepages to them is manual, slow, and

cumbersome”. Chen (2002), who has conducted research in creating classification

systems based on previous user activities notes that manual classification “can deal with

different types of data and can deal with different types of data and has high accuracy”.

However, he also notes that the “drawback of manual classification is the inefficiency in

dealing with a large number of objects in a complicated category structure” (Chen 2002).

Because of the exponential growth in the volume of on-line textual information it is

nearly impossible to maintain such taxonomic organization for large, fast-changing

corpora by hand (Chakrabarti, Dom, Agrawal, and Raghavan, 1998) because the

“semantic judgements required to select quality resources and the cognitive processes

necessary to classify and catalogue resources all take time (Worsfold , 1998). Another

issue to be considered is that the “human editor’s decision on taxonomy construction is

not only highly subjective but also its subjectivity is inconsistent over time (Kim and

Allen, 2002 ). Marchionini (1995) agrees by stating that “cognitive inertia, which is a

tendency to continue following paths or lines of evidence rather than examining contrary

or alternative directions” may exist. In response to this need to automate, there have

been many attempts at creating systems that will generate and classify documents into

hierarchies. Although these are many times applied to the results of a query or to a small

set of pre-defined documents, they are worth investigating.

Sanderson and Croft (1999) defined five principles of design that their

automatically generated hierarchy must contain: terms had to reflect the topics covered in

them, the organization had to be such that a parent term would refer to a more general

concept than its child, the child would cover a sub-topic of the parent, a strict hierarchy

where there was a one to one relationship between child and parent was not considered

important, and ambiguous terms would be expected to have separate entities in the

hierarchy. Selecting terms for the hierarchy if they are not the result of a query can be

problematic. According to Lawrie and Croft (2003), “topical terms are the content

bearing terms with respect to a particular topic. These are not necessarily the most

frequent words”. Instead they are terms which are “both about the topic and predictive of

other terms” (Lawrie and Croft, 2003).

Completely automated generated hierarchies generally fall into two categories,

those created through subsumption and those that are created lexically. (Lawrie, 2000 ).

Another approach to automatic classification is the automated analysis of documents filed

into pre-existing categories of a manually constructed hierarchy using Bayesian

classifiers. A drawback to this method is that they are not adaptable to varying interests

or to changes in the document collection (Lawrie, 2000). The other methods aim to

display the contents of a document collection and remain flexible.

Subsumption is the notion that some terms will frequently occur among

documents, while others will only occur in a few documents and that some of these terms

will be terms that broadly define a topic and that some will co-occur with a general term

and explain aspects of a topic (Lawrie, 2000 ). Terms are selected that are ‘unusually

frequent’ and sorted so that the top scores are designated for use in the hierarchy (Lawrie,

2000 ). The assumption here is based on Forsyth and Rada’s hypothesis that the more

documents a term appears in the more general the term is assumed to be (Nanas, Uren,

and DeRoeck, 2003). Once all of the subsuming relationships are discovered, the

hierarchy is constructed in a bottom-up fashion (Lawrie and Croft, 2001 ). Redundant

subsumptions and relations where terms only co-occur two or fewer times are eliminated.

Lexical hierarchies rely on the lexical nature of documents and relationships

between phrases and noun-adjective relationships are the basis for this method of

automatically creating a hierarchy. Nevill-Manning, Witten, and Paynter (1999) created a

lexically-generated hierarchy depends highly on the lexical notion of keywords in

context. Users are presented instances of phrases in which their keyword appear and can

browse from that point forward. However, because of the large amount of information

returned, the authors had concerns for it availability on the web due to design factors and

download times.

The lexical dispersion hypothesis states that “a word’s lexical dispersion-the

number of different compounds that a word appears in within a given document set- can

be used as a diagnostic for automatically identifying key concepts of the document set”

(Lawrie, 2000). Once phrases are identified and ranked and anomalies are identified in

documents that use a phrase frequently that could potentially skew the importance of the

phrase, the hierarchy is constructed in a top down manner. High level terms are selected

as the top level of the hierarchy and terms that occur with these terms are then ranked

according to the frequency in which they occur. (Lawrie, Croft, and Rosenburg, 2001 ).

Other research focuses around automatically classifying items into a preset

hierarchy. Many times the hierarchy is created manually to represent the information

space and various clustering algorithms are used to place the item in the correct level of

the hierarchy. One novel approach to this problem was introduced by Chen, LaPaugh,

and Singh (2002). These researchers analyzed access behaviors of users to determine the

paths they took through the sites in a one day period. The assumption was made that

pages that users traversed or visited were somehow related. Taking this information with

the known structure of the hierarchy, researchers were able to assess the functionality of

their hierarchy as well as predict topic placement based on the user patterns of a group of

users who had accessed the object.

The problems with automatically generated hierarchies generally result from the

size of the document set being processed and the nature of the algorithms chosen.

Subsumption seems to be the more effective tool for creating hierarchies and is used in

research of Croft, Lawrie, Roesenberg, Chakabarti, Nanas and others. Some of the

problems associated with subsumption is it inconsistency (Lawrie, Croft, and Rosenburg,

2001 ). Subsumption paid little attention to themes and documents and can be

demonstrate by a drop in relevant documents contained in the hierarchy (Lawrie, 2000).

Lexical hierarchies may possibly be skewed in the selection of topical terms

because the occurrence of terms in a long document may skew the importance of the

word in relation to the entire document set (Lawrie, 2000). In addition to some words

appearing more frequently in a long document, the idea that some words naturally occur

more often in phrases and sometimes result in useless or low-meaning phrases (Lawrie,

2000). Overall, “the strength of subsumption lies in separating documents into small

groups, whereas lexical hierarchies do a much better job of including all documents in the

hierarchy” (Lawrie, 2000). Other concerns exist in the computer’s ability to determine

specificity of a topic and to stop at a broader level of the hierarchy if necessary for

classification (Nanas, Uren, and DeRoeck, 2003).

The Current Hierarchy on eBay

The current hierarchy on eBay serves to facilitate browsing the items for auction

on the site. As an e-commerce site, eBay makes most of its revenue by providing access

to the products of sellers to a wide audience of buyers. As a result, the effectiveness of

its information retrieval devices in the form of its search engine and subject hierarchy is

of paramount importance. If buyers cannot find the items they wish to purchase, fewer

bids are placed, fewer sellers will list their items, and eBay revenue will fall.

The hierarchy serves two purposes that the literature has clearly defined. It can

support the novice user who may be uncomfortable constructing search phrases for the

search engine and using the various filters available in the advanced search area to

narrow the results of said queries. Novice users may be more comfortable browsing

through the categories of interest to get a feel for the information space and to see the

breadth of items available for purchase.

The other purpose the hierarchy may satisfy is the buyer without a specific goal in

mind. This might be a buyer who is “window shopping” as in a traditional brick and

mortar store, with no purpose of buying, but looking for serendipitous discovery,

pleasure, or for product information gathering. In this case, the searcher could be both

potential sellers and buyers.

The hierarchy itself does not follow one of the classic modes of hierarchical

organization as Spiteri (2000) predicted. There is not an apparent scheme for organizing

a very broad array of products for sale in an educational or scientific way. Instead, eBay

has picked broad categories of items for sale and put those at the top level. Sublevels or

categories maintain the parent-child nature of a hierarchy and are constructed mainly on

an increasing degree of specificity as one meanders down a hierarchical path. Main

topics are arranged alphabetically and currently number twenty-three.

The structure of the hierarchy is determined by eBay personnel and a request for

insight into the criteria for inclusion as categories was not answered. An area to request

new categories exists in the help section but there is no indication given how requests are

evaluated and eventually incorporated into the hierarchy or ultimately discarded. One

would surmise that as categories grew in membership they would be analyzed for new

subcategories. However, this is difficult to confirm since many of the lowest levels of the

hierarchy still have a large number of entries. For example, the category

BooksMysteries and ThrillersDetectivesWomen Sleuths still contains over 2,000

items. An analysis of this path in the hierarchy suggests that the addition of new

categories is haphazard and directly related to user requests. Other subcategories in the

detective path include two other options, short stories and other. There is no relation to

each other and distinguishing where an item might fall is difficult. In this example, an

book of short stories featuring female detectives would be difficult to classify. At this

low level of high specificity, one could argue that the effectiveness of this level is

compromised if an item is place in two of the three options.

When analyzed in relation to Spiteri’s model for hierarchies (2000), eBay falls

short in many of the areas of constructing an effective hierarchy for e-commerce. eBay

generally fails to provide homogenous categories, mutually exclusive categories,

consistent structure, and provide very few tools for comparing products. The hierarchy

seems to be haphazardly constructed without little thought to the principles of designing

hierarchies. Because eBay is not burdened by the tasks of placing documents in the

correct level of the hierarchy, there should be more attention paid to its construction for

more efficient browsing.

The main issue where homogeneity fails in the ubiquitous “Everything else”

category. Second level topics such as genealogy, health and beauty, metaphysical, and

personal security have little to do with the other. It is in this area that the hierarchy

provides no context to the buyer and categories such as “Test Auctions” are difficult to

define and determine the purpose. Because the rule of homogeneity has been ignored,

this area is really just a chaotic mish mash of items and do not benefit from the many

positive attributes of hierarchical browsing. Within this category there are also

meaningless category headings that do not have well defined characteristics for

membership in the class. The best example being “Weird Stuff”. This vague labeling

combined with its location in a poorly constructed node of the hierarchy make it difficult

for the user to predict what items or subcategories may be included.

Exclusivity of the categories in eBay is one of the main drawbacks to the current

structure. Because there is no apparent plan for designing the categories of the hierarchy

and for incorporating new categories, the problem of exclusivity plagues the hierarchy at

all levels. Examples of this problem are easily identified at the top level of the hierarchy.

One might wonder how dolls and bears is an exclusive category of toys and hobbies. The

existence of a top level categories for stamps and one for coins is also confusing. In

relation to the other categories at this level, one specific item that is widely collected

seems incongruous with the rest of the organizational scheme. Stamps and coins may fit

better in categories such as collectibles or hobbies. Upon seeing these inconsistencies in

labels, the user may be confused as what to expect in the hobby section if stamps and

coins are not included.

Vague labeling also results in categories that appear to be inclusive or

heterogeneous. Categories such as “Collectibles” give no indication of what might be

included, especially when other categories at the same level such as antiques, stamps,

coins, toys and hobbies, dolls and bears, and pottery and glass seem to over a wide area

of what might be expected to fall in the collectible category. Because the hierarchy is

arranged alphabetically, a novice browser may scan the hierarchical tree and see

“Collectibles” first and never get to the lower levels where collectible items like

glassware and stamps are included.

Along with the vague labeling is an inconsistency of specificity at the different

levels. As mentioned before there is a contrast in specificity between categories such as

the generic collectibles and the specific collectible stamp. Other category names are even

more broad and troublesome for the novice user or the browsing buyer. Under the home

category one might be surprised to find pet supplies and welding but not health and

beauty. One might be surprised to find items such as sewing machines under “Business

and Industry” instead of “Clothing, Apparel, and Accessories”, which incidentally does

not include the most common category of accessories, jewelry.

From a usability standpoint, eBay attempts to give browsers a glimpse of the

information space in which they can shop. The broad categories do invite users to

explore the possible items for sale in the hierarchy. However, the presentation of the

hierarchy and its apparent usability could potentially affect the browser’s satisfaction as

predicted by Fu and Salvendy (2002).

In addition to labeling problems there are other problems with the usability and

organization of the hierarchy. The space allocated to the hierarchy is not sufficient to

allow for ease of scanning which is so important to effective browsers as discussed

earlier. Only one-fourth of the screen is dedicated to the hierarchical listings. In this

space that measures approximately two inches by eight inches on a monitor set at

800x600, eBay has inserted the twenty three top levels as well as a random sampling of

subcategories numbering thirty eight. As a result, the text is very dense, difficult to

recognize as separate entities in a glance, and the relative font sizes used to accomplish

this density of information are hard to read. From a design standpoint, this does not

encourage “the inherent ability of the human eye to spot interesting words”(Bates, 1996) .

Because of the manner in which the hierarchy is presented there are additional

concerns with the usability of the site. As mentioned previously, eBay has also included

random subcategories underneath the main categories on the front page. It is difficult to

determine what criteria were used to choose these subcategories that receive more

prominent display than other categories at the same level of the hierarchy. This

inconsistency could lead novice users to miss the other subcategories further down the

hierarchy or to become frustrated when it appears that the item they are looking for

doesn’t fit into one of these lower categories that are displayed on the front page.

The final usability issue to be discussed is the problematic way in which eBay has

presented the lowest levels of the hierarchy. Once a user picks a main category from the

front page of the site, they are presented a page with all of the second-level categories.

When a user selects one of these options, they are then presented with the items that fall

in that level of the category. Because this includes all items that stop at this level of

specificity as well as all of the children items that are inheriting the parent class, the

number of items returned is immense. The resulting set is usually too large to navigate

easily. What many users might not notices is that eBay has continued the hierarchical

structure for the category in the right column under the search box. Because this area is

so cluttered with search options, the more specific subcategories are not even viewable on

the first screen of a standard monitor set at 800x600. The user would have to scroll down

to see the continuation of the hierarchy and many novice users will not know to do this

and will lose the power of the hierarchy as an information retrieval tool.

There are some things that eBay has implemented to address problems with

browsing and hierarchies. At all lower levels, breadcrumbs are provided where browsers

can easily jump up one or two levels in the hierarchy without having to return all the way

to the homepage. This represents an attempt to keep the user from feeling lost which is

well documented in browsing literature. An overview map also provides browsers a

limited view of the top levels of the hierarchy with more detail than the frontpage for

constructing a better mental map of the entire information space. Also eBay must

recognize some of its fallacies in the construction of its hierarchy because on most of the

pages where second levels of the hierarchy are presented, they also provide a listing of

“Related categories” to encourage browsers to discover items in other areas that might

rightly belong in the category they are currently viewing. For example, if a user selects

Clothing, Shoes, and Accessories as the main topic, the related categories at the bottom

of the page would also direct them to other categories such as Jewelry and Health and

Beauty.

Because eBay does not manually classify all of the items in the database using

their own personnel, the need to automate classification schemes is not as important to

the company as it may be to other internet based hierarchies. The time issues is

adequately solved as sellers provide the category for the item as part of the process of

listing it on eBay. However to improve the quality of product placement by sellers, eBay

may consider some of the algorithms for testing the quality of its hierarchy or offer

assistance to sellers in deciding which category may be best for a seller, especially novice

sellers who may not be familiar with the entire scope of the selling environment. Chen’s

analysis of previous user traffic to certain categories or document clustering techniques

used in Lawire’s (2000) discussion of hierarchies may provide insight into the

organizational scheme of eBay. Once the seller has submitted the description of their

item for sale, an analysis of the content could be compared to other items in categories or

to model items in categories for suggested placement. From eBay’s standpoint this also

may be a money making idea as it may encourage sellers to list their item in multiple

categories as they are being presented potential selling areas they had not previously

considered.

On a related note, the many automated techniques for creating hierarchies could

potentially be applied to improve granularity of the lower levels of the hierarchy. Even

at the lowest levels, there are still large membership sets for certain levels. For example,

in the category of Toys & Hobbies > Action Figures > Star Wars > Vintage (1977-89)

>Return of the Jedi > Figures, there are still over 500 items for sale in this very specific

category. From a browsing standpoint, this number may still overwhelm the user and

they may not be able to find the item they were looking for. eBay could potentially

expand the depth of the hierarchy but this may make it more problematic for sellers to

place items in the correct categories or discourage browsing buyers from continuing

down a long path. Also maintaining these categories at this level of detail could also be

time consuming and expensive for eBay. For a person to sit down and derive categories

at this level, say by character name, would require quite a lot of attention to detail and

expand the structure of the hierarchy significantly. However, eBay could employ one of

the automated hierarchy schemes to group items at the low, detailed levels for those

searchers who do have more specific needs. Either through clustering or lexical analysis,

users could be presented with additional navigation aids that generate new categories by

term clustering. So in this example, the automatically generated hierarchy might contain

a list of characters’ names that appear in descriptions. This could also be added as an aid

to the search engine where users would get a hierarchical listing of categories their search

terms were contained in.

Improvements on eBay

In response to the literature and some of the problems previously discussed, eBay

needs to dedicate the time and the money to revamp its hierarchy and optimize it for new

browsers and for recreational shoppers. Organizational changes as well as usability

issues need to be addressed and finally the new interface needs to be tested for usability.

Organizationally speaking, eBay needs to refine its hierarchy to meet the two

important aspects of hierarchical design, exclusivity and homogeneity. Categories at the

top level that have established child relationships to categories at the top level must be

subsumed by the parent category. According to Patricia Billingsley (1982), “problems

created by ambiguity in menu choices are compounded when users are unaware of the

hierarchical structure of data organization”. To make the structure less ambiguous, the

hierarchy should adhere to the strict parent/child relationships that are established in the

organizational structure.

The second recommendation would be to make the entire structure of the

hierarchy viewable in the “View all eBay categories” section or in the site map. All of

the categories do not need to be on one page, but users should have the ability to browse

through the entire depth of the hierarchy assigned. The idea that a seller places the item

in a lower category in the hierarchy where the user might never encounter due to the

constraints of the design. If eBay has determined that the hierarchy is necessary to

facilitate browsing and window shopping behaviors, then it needs to make the entire

information space accessible through the hierarchy.

Once these changes to the organizational structure have been user testing would

need to be conducted to ensure that the recommendations from the literature are effective

in this environment. Because browsing behavior is difficult to study and quantify

because of its lack of directed goal, the design of the study would need to be designed to

emulate real browsing situations. Elaine Toms (2000) notes that “few studies have

assessed browsing, analyzed the characteristics or factors that influence browsing,

experimentally manipulated the browsing environment or attempted to measure browsing

outcomes.”

One possible way of studying the changes to the interface would be to have users

spend a set amount of time browsing for items they might be interested in buying,

Instruct them that there is no goal in mind, simply to spend time looking at items as if

they were “just looking” in a store. With two groups of browsers, one group could use

the old interface and one group could use the new interface. At the end of the study, both

groups could answer a survey on user satisfaction centered on the ideas of apparent

usability and compare results with those of Fu and Salvendy ( 2002 ).

Another approach would be to conduct a traditional user study and ask one set of

users to browse certain categories for certain types of items in each of the interfaces and

ask them to speak their thoughts as they navigate through the structure. Comments

would be recorded by investigators and analyzed for information at a later date. Also

times would be recorded for each time a user encountered an item they might consider

buying. Because this is highly subjective to individual differences, a large sampling of

users would be needed to get a better idea of how effective this benchmark would be.

From a different perspective another interesting aspect to investigate would be to

tests the cognitive models of different hierarchies and see if hierarchies in an e-commerce

setting were negatively affected by the lack of a mental model that is many times

establish by the models of education and science as discussed by Spiteri ( 2000). Users

could be given a specific item to locate in each of the hierarchies at the same depth in the

hierarchy. For example, the search task may be something like find a website on the

platypus using the Yahoo! directory and a DVD of a pop band on eBay. Both of these

items are five levels deep in the hierarchy. The same user will be asked to browse

through the hierarchy with the loosely designed search task and users will be evaluated

on time and accuracy in identifying the resources requested. Results will be compared to

see which hierarchy performed better and qualitative data from user responses will be

analyzed for any information regarding feelings of lostness or disorientation. Information

on which hierarchy was more usable from the user’s standpoint may shed light on which

hierarchy is preferred if any and why.

Conclusions

As demonstrated through the literature and analysis of the eBay site, e-commerce

does bring new challenges to the designer to implement traditional information retrieval

mechanisms in an online commercial setting. The use of the hierarchy to present options

to the potential buyer is still a solid decision because the hierarchical scheme is such a

familiar cognitive model for potential buyers. However, the traditional ways of creating

hierarchies must be re-examined with the user in mind. Categories of commerce do not

easily align themselves with the traditional educational and scientific models of creating

hierarchies. Instead, designers must be innovative and aware of their customer’s

expectations to design efficient hierarchies. User-testing and periodic data collection will

insure that the categories of the hierarchy accurately depict the information space, in this

case, the products available for sale.

With over $45 billion in online sales in 2002 (Business Journal Online, ), e-

commerce retailers must strive to make their site easy to use and to locate items if they

are to remain competitive. The five aspects of consumer behavior outlined by Miles and

Howes must be met using adaptations to the traditional ways of constructing hierarchies.

More studies need to be conducted on how online consumers browse in relation to their

traditional information seeking counterparts. A difference in search task and context of

search may lend itself to new design standards for online commerce sites to increase

usability and access for online buyers and sellers.

One additional area of study to pursue is the study of browsing itself.

Methodologies and evaluation tools need to be developed to evaluate user’s behaviors in

browsing situations. This presents many difficulties due to the nature of the task. Users

generally do not have a well-defined information need or a strongly-formulated idea of

what they are looking for. In a quantitative study, these types of motivations are difficult

to quantify due to the large influence of personal preferences, emotions, and motivations.

Equally troubling is the lack of a formulated query as noted by Dennis, Bruza, and

McArthur (2002.) Marchionini (1995) and Bates (1989) would argue that browsing is a

constant reformulation of a search query, however loosely understood by the searcher.

Regardless of which view one subscribes to, the environment is difficult to study in a

laboratory setting. The motivation for browsing in a laboratory setting may harder to

emulate than task-oriented searching because a browser generally will look for

information when he has time and the inclination to do so. In a task-oriented search,

participants have well-defined goals to reach and will try to reach that goal. When no

goals are given, some participants may flounder and not exhibit the behaviors the

investigators are trying to study.

All of these issues are critical concepts, worthy of further study due to the nature

of browsing and the growth of electronic commerce. Browsing is an everyday activity

that everyone participates in whether it be scanning documents for information, using the

yellow pages to look up a telephone number, or locate an item on an online auction.

Combined with a natural tendency to categorize items according to hierarchical

relationships, browsing is a behavior that information retrieval specialists as well as e-

commerce designers must understand in order to optimize the online experience for users.