e-Shop Visitors’ Burstiness as a Predictor of Performance

The Case of eBay

Andreas Ahrens

and Jeļena Zaščerinska

Hochschule Wismar, University of Applied Sciences - Technology, Business and Design,

Philipp-Müller-Straße 14, 23966 Wismar, Germany

Centre for Education and Innovation Research, Kurzemes prospekts 33, Riga LV-1069, Latvia

Keywords: Binary Customer Behaviour, e-Shop Visitor, Buyer, Burstiness, Frequency, Performance in e-Business,

Selling/Buying, e-Business Process.

Abstract: Burstiness serves as a predictor of performance in the management sciences. However, burstiness has not

been examined as a predictor of performance in e-business process. The research question is as follows:

Does burstiness serve as the predictor of performance in e-business process? The aim of the research is to

analyse burstiness as a predictor of performance in e-business process underpinning elaboration of a new

research question on burstiness functions. The meaning of the key concepts of burstiness and performance

is studied. Moreover, the analysis demonstrates how the key concepts are related to the idea of e-business

process and shows a potential model for development, indicating how the steps of the process are related

following a logical chain: conceptual framework → empirical analysis →conclusions. The results of the

research show that e-shop visitors’ burstiness does not always serve as the predictor of item on-line

selling/buying. The novel contribution of the paper is revealed in the newly created research question: What

are reasons that e-shop visitors’ burstiness does not serve as the predictor of performance in e-business

process despite the common background such as social grounding in both sciences, namely management

and e-business? Directions of further research are proposed.

1 INTRODUCTION

Currently, the phenomenon of burstiness is in the

research focus as burstiness is used

 On the one hand, to designate the tendency in the

field of investigation (Pierrehumbert, 2012), and

 On the other hand, to permanently optimize the

flow of e-business process in order to increase

the profit (Ahrens et al., 2016).

For designating the tendency in a field of scientific

investigation, burstiness functions as a predictor of

performance in the management science (Riedl and

Woolley, 2017). For the optimization of the flow of

e-business process, burstiness acts as a characteristic

of the flow of e-business process. This finding as

well as common background such as social

grounding in both sciences, namely management and

e-business, allow identifying the functions of

burtsiness shown in Table 1.

Table 1: Function of burstiness.

Phenomenon

Scientific

direction

Function

Burstiness

Mana

ement Predicto

e-Business Characteristic

Table 1 demonstrates that burstiness has not been

examined as a predictor of performance in e-

business process. However, burstiness serving as a

predictor of performance in e-business process could

assist in optimizing the flow of e-business process in

order to increase the profit (Ahrens et al., 2016).

The research question is as follows: Does

burstiness serve as the predictor of performance in e-

business process?

The aim of the research is to analyse burstiness

as a predictor of performance in e-business

underpinning elaboration of a new research question

on burstiness functions. The meaning of the key

concepts of burstiness and performance is studied.

Moreover, the analysis demonstrates how the key

concepts are related to the idea of e-business process

Ahrens, A. and Zaš

cerinska, J.

e-Shop Visitors’ Burstiness as a Predictor of Performance - The Case of eBay.

DOI: 10.5220/0006407900780082

In Proceedings of the 14th International Joint Conference on e-Business and Telecommunications (ICETE 2017) - Volume 2: ICE-B, pages 78-82

ISBN: 978-989-758-257-8

and shows a potential model for development,

indicating how the steps of the process are related

following a logical chain: conceptual framework →

empirical study →conclusions.

2 CONCEPTUAL FRAMEWORK

The present research adopts the definition of

burstiness that refers to burstiness in human

behaviour as e-shop visitors who are human beings

are the focus of the present investigation. Therein,

burstiness means periods of very high activity that

are followed by rest periods (Gandica et al., 2016).

The period of high activity means a period where at

least one activity is performed, and the rest period is

identified as a period without any activity

implemented (Ahrens et al., 2015).

A typical scenario in which

burstiness could be

considered as a predictor of performance in e-

business process can be described as following:

every day lots of items are offered in on-line shops.

Many of these items receive “viewed”. Later some

of the viewed items are sold/bought. The act of

selling/buying is understood as e-business process.

By e-business process, the process of buying and/or

selling of goods and/or services through Information

and Communication Technologies (ICT) is meant

(Ahrens and Zaščerinska, 2016). The act of

selling/buying is realized as performance in the

present research. Then, on-line viewing an item is

determined to be the predictor of selling/buying or,

in other words, performance. Understanding of

performance and its predictor described in the

present paper extended the definition of e-business

process from the act of selling/buying only to the e-

business process of two phases, namely

 Phase 1 Viewing and

 Phase 2 Selling/Buying.

Figure 1 reveals the two elaborated phases of e-

business process.

Figure 1: Two phases of e-business process.

A customer is discussed within the paradigm of

binary customer behaviour as illustrated in Figure 2

(Ahrens and Zaščerinska, 2016). If e-business

process ends with a purchase, the customer becomes

a buyer. In turn, by e-shop visitor, any customer who

seeks and examines a product without buying it is

understood (Ahrens and Zaščerinska, 2016).

Figure 2: Elements of customers’ binary option.

Table 2 describes the newly elaborated two

phases’ e-business process.

Table 2: Description of the two-phases’ business process.

Phase of

e-business

process

Focus of the

phase of

e-business

process

Participants in

the phase of

e-business

process

Function of

burstiness in the

phase of

e-business process

Phase 1 Viewing e-shop visitors

Predictor of

performance

(selling/buying)

Phase 2

Selling/

buying

Buyers

Characteristic of

performance

(selling/buying)

The focus of the present research is put on Phase

1 Viewing of the e-business process. In Phase 1

Viewing burstiness serves as the predictor of

performance. Burstiness is closely inter-connected

with frequency (Pierrehumbert, 2012) as depicted in

Figure 3.

Figure 3: The inter-relationship between frequency and

burstiness.

Traditionally, a frequency is defined as the

number of times a given datum (views of an item by

e-shop visitors in the present paper) occurs in a data

set (Dean and Illowsky, 2010). Consequently,

frequency is regarded in terms of a number of item’s

views by e-shop visitors in the present work.

Analysis of the research results shown by

Pierrehumbert (Pierrehumbert, 2012) allows

Not to bu

Fre

uenc

Burstiness

e-Business process

Phase 1

Viewing

Phase 2

Selling/Buying

Not to bu

Binary customer behaviour

To buy

Not to bu

e-Shop Visitors’ Burstiness as a Predictor of Performance - The Case of eBay

determining that frequency and burstiness are found

to be inter-related in order to quantify burstiness

(Pierrehumbert, 2012). Then, frequency of e-shop

visitors’ views of an item means e-shop visitors’

burstiness in the present investigation.

For the purposes of the present work, frequency

is determined to be an indicator of burstiness as

shown in Table 3.

Table 3: Indicator of burstiness as the predictor of

performance.

Phenomenon Indicator

Burstiness Frequency

3 EMPIRICAL ANALYSIS

The present part of the paper demonstrates the

design of the empirical study, results of the

empirical study and findings of the study.

The design of the present empirical study

comprises the purpose and question, materials and

methodology of the present empirical study.

The empirical study was aimed at evaluating e-

shop visitors’ burstiness as the predictor of item

on-line selling/buying in Phase 1 Viewing of e-

business process.

The case study research has been applied as

"case studies […] are generalizable to theoretical

propositions and not to populations or universes. In

doing a case study, your goal will be to generalize

theories (analytical generalization) and not to

enumerate frequencies (statistical generalization)"

(Yin, 2003, p. 10). Case study research is a

qualitative research design (Kohlbacher, 2005).

The exploratory type of the case study research has

been applied (Zainal, 2007) in the present empirical

study as case studies have an important function in

generating new research questions, hypotheses and

building theory (Kohlbacher, 2005). Exploratory

case studies set to explore any phenomenon in the

data which serves as a point of interest to the

researcher (Zainal, 2007). The exploratory

methodology proceeds from exploration in Phase 1

through analysis in Phase 2 to hypothesis/research

question development in Phase 3.

The qualitatively oriented empirical study

allows the construction of only few cases

(Mayring, 2004). The cases themselves are not of

interest, only the conclusions and transfers we can

draw from these documents (Flyvbjerg, 2006).

Selecting the cases for the case study comprises use

of information-oriented documents, as opposed to

random documents (Flyvbjerg, 2006). This is

because an average case is often not the richest in

information. In addition, it is often more important

to clarify the deeper causes behind a given problem

and its consequences than to describe the

symptoms of the problem and how frequently they

occur (Flyvbjerg, 2006).

Interpretive research paradigm was used in the

present empirical study. The interpretive paradigm

aims to understand other cultures, from the inside

through the use of ethnographic methods such as

informal interviewing, participant observation and

establishment of ethically sound relationships

(Taylor and Medina, 2013).

For the empirical study’s purposes, eBay has

been chosen as eBay provides reports on activities

that were carried out that can be considered as

naturally occurring data set.

eBay is the global online marketplace.

(Comberg and Velamuri, 2017). Founded in 1995,

eBay quickly became popular for its innovative

auction style shopping format (Comberg and

Velamuri, 2017). In 1998, eBay was already a

publicly traded company with over two million

registered users and over $47 million in annual

revenue (eBay Inc., 1999). It should be noted that

after an item has been sold eBay offers to evaluate

the item quality and delivery. This evaluation is

considered as Phase 3 in e-business process as

shown in Figure 4.

Figure 4: Three phases of e-business process.

Table 4 describes the newly elaborated three

phases’ e-business process.

The empirical study’s question was as follows:

Does e-shop visitors’ burstiness serve as the

predictor of item on-line selling/buying?

The present empirical study was carried out

from December 2016 to January 2017. Analysis of

statistical documents provided by eBay to an

account holder was implemented.

e-Business process

Phase 1

Viewing

Phase 2

Selling/Buying

Phase 3

Evaluation

ICE-B 2017 - 14th International Conference on e-Business

Table 4: Description of the three-phases’ business process.

Phase of

e-business

process

Focus of the

phase of

e-business

process

Participants in

the phase of

e-business

process

Function of

burstiness in the

phase of

e-business process

Phase 1 Viewing e-Shop visitors

Predictor of

performance

(selling/buying)

Phase 2

Selling/

buying

Buyers

Characteristic of

performance

(selling/buying)

Phase 3 Evalua-tion Buyers

Predictor of

performance

(selling by owner

who sold the item)

Characteristic of

performance

(selling by owner

who sold the item)

Analysis of documents of 10 items listed for sale

on eBay within December 2016 - January 2017 on

an account holder was carried out. Each of 10 items

is usually offered for selling during one week or

seven days. During this period, e-shop visitors can

view an item of their interest and get this item via

auction-style buying process. Table 5 demonstrates

the summary of the observed results of 10 items

listed for sale on eBay on an account holder.

Structuring content analysis (Mayring, 2004)

shows that two items, namely hand-made

candlestick (14 views) and cocktail set (6 views) had

a higher number of views and, consequently

burstiness, in comparison to paper shredder (3

views), tea metal boxes (empty) (4 views) and

stationary telephone for elderly people (3 views).

However, all the five items have been sold despite a

different number of views and, consequently, level

of burstiness.

On the other hand, three items, namely hand-

made candlestick (14 views), work trousers (34

views) and UK adapter (17 views), had a higher

level of burstiness in terms of number of views by

eBay shop visitors. However, these three items had

not been sold/bought. On contrary, three other items,

namely paper shredder (3 views), tea metal boxes

(empty) (4 views) and stationary telephone for

elderly people (3 views) had a lower level of

burstiness. Against this background, all the thee

items had been sold/bought.

Table 5: Results of document analysis of 10 items listed

for sale on eBay on an account holder.

Nr. Item

Frequency of

views

Sold/

Not Sold

1 Two loudspeakers 7 times viewed Not Sold

2 A wine set in a box 5 times viewed Not Sold

Hand-made

candlestick

4 Work trousers 34 times viewed Not Sold

5 UK adapter 17 times viewed Not Sold

6 Hand meat grinder 11 times viewed Sold

7 Paper shredder 3 times viewed Sold

Tea metal boxes

(empty)

9 Cocktail set 6 times viewed Sold

Stationary

telephone for

elderly people

Summarizing content analysis (Mayring, 2004)

of the data reveals that e-shop visitors’ burstiness

does not always serve as the predictor of item on-

line selling/buying.

5 CONCLUSIONS

The theoretical findings of the present research

allow identifying such a function of burstiness in e-

business process as the predictor of performance.

Against this background, the empirical findings of

the research allow drawing the conclusions that e-

shop visitors’ burstiness does not always serve as the

predictor of item on-line selling/buying.

The theoretical analysis also allows defining

frequency as an indicator of burstiness. The

theoretical investigations contributed to the

development of three-phase e-business process,

namely

 Phase 1 Viewing;

 Phase 2 Selling/Buying; and

 Phase 3 Evaluation.

The following research question has been

formulated: What are reasons that e-shop visitors’

burstiness does not serve as the predictor of

performance in e-business process despite the

common background such as social grounding in

both sciences, namely management and e-business?

Validity and reliability of the research results

e-Shop Visitors’ Burstiness as a Predictor of Performance - The Case of eBay

have been provided by involving other researchers

into several stages of the conducted research.

External validity has been revealed by international

co-operation as following:

 the research preparation has included individual

interdisciplinary consultations given by other

researchers,

 the present contribution has been worked out in

co-operation with international colleagues and

assessed by international colleagues, and

 the research has been partly presented at

international conferences.

Therein, the findings of the present research are

validated by other researchers.

The present research has limitations. The inter-

connections between e-business process, binary

customer behaviour, the e-shop visitors’ burstiness,

and frequency have been set. Another limitation is

the empirical study based on one case only, namely

eBay. Therein, the results of the study cannot be

representative for the whole area. Nevertheless, the

results of the research, namely the three phases of

the newly elaborated e-business process, namely

Phase 1 Viewing, Phase 2 Selling/Buying and Phase

3 Evaluation, may be used as a basis of analysis of

burstiness in e-business process. If the results of

other cases had been available for analysis, different

results could have been attained. There is a

possibility to continue the study.

Investigation of further functions of burstiness

are in the focus of future research. Further research

tends to search for other indicators of e-shop

visitors’ burstiness that can serve as the predictor of

performance in e-business process. Empirical studies

on burstiness in a variety of e-business sectors are to

be implemented. The search for relevant methods,

tools and techniques for the analysis of burstiness in

e-business process is proposed. A comparative

research on analysis of burstiness in other scientific

fields could be carried out, too.

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