Internet use behavior of consumers in pre-purchase stage of online shopping
Nguyen Hoang Tien, Dinh Ba Hung Anh/ MICA 2018 Proceedings
International Conference on Marketing in the Connected Age (MICA-2018), October 6th, 2018
Danang City, Vietnam
Internet Use Behavior of Consumers in Pre-purchase Stage
of Online Shopping
Nguyen Hoang Tiena*, Dinh Ba Hung Anha
aHo Chi Minh City University of Technology, 268 Ly Thuong Kiet, Ho Chi Minh City, Vietnam
A B S T R A C T
The online shopping cannot be considered as an emerging trend because it has become a standard way of
doing business. The focus of online retailers’ interest should be aimed at the customer behavior during
purchasing process. The aim of this paper is to describe and analyze the use of Internet in the pre-purchase
stage of customers in selected countries. We found that there is a significant negative correlation between
development indicators of nations and the use of Internet in pre-purchase stage of shopping. Furthermore,
there is a significant difference between European and Asian consumers using Internet during pre-purchase
stage in several observed activities.
Keywords: Online shopping; consumer behavior; pre-purchase stage
1. Introduction
Although the latest financial crisis has reduced shopping budget and the confidence of consumers, evidence
shows that online retailing continues to be a valuable alternative or complement to the traditional retailing
(Ferencova and Jurkova, 2011). Internet technology has reduced barriers and encourages globalization, helping
outreach the online retailing. Over the past years, Internet has developed into a global marketplace for goods and
service exchange with round-the-clock availability and worldwide coverage. Global online retail industry has
grown significantly and it is possible to notice the flow of international capital pouring into this sector
(Slusarczyk and Kot, 2012). The development of e-commerce has incited the increase of trust in security of
Internet banking as well as the speed and efficiency of order processing. This is reflected in more favorable
prices for consumers (Kot et al., 2012). Convenient and fast shopping is mostly used by young generations since
they are increasingly familiar with the use of Internet banking. Online shopping allows customers to perform a
variety of activities wherever the Internet is available. Retailers are increasingly offering online platforms and
with the use of encrypted, secure gateways they provide risk free and pleasant shopping experience. However, it
is important not only to provide such possibilities, retailers should also be able to determine if these possibilities
are appreciated by consumers. Thus, they should start with understanding consumer behavior, a process that
involves purchasing and using products or services in order to satisfy individual preferences, needs and desires
(Solomon et al., 2013). With rapid movement to online selling, sellers cannot use the knowledge gathered from
in-store customer behavior, as in-store and online customers are influenced by different motivational factors (Liu
et al., 2013). Trenz (2015) differentiated 3 stages of the purchasing process – pre-purchase stage, purchase stage
and post-purchase stage. In our paper, we focus primarily on behavior in the pre-purchase stage of Internet users.
During pre-purchase stage, the customers inform themselves about the product. Since the pre-purchase stage
entails no obligations, customer often changes the vendor in order to find the most suitable deal (Trenz, 2015). In
this phase of the purchasing process, users tend to look for information that can help them select the right
* Corresponding author. E-mail address: vietnameu@gmail.com
106
Nguyen Hoang Tien, Dinh Ba Hung Anh/ MICA 2018 Proceedings
product or seller. Comparison in general plays a certain role at this stage. As consumers can compare products’
price and features online with ease and switch stores until they find the most suitable solution for them, e-service
quality must became a key factor (Bai et al., 2014). Users would also look for product/brand reviews in order to
avoid a purchase of unreliable product or from unreliable source. Hu et al. (2015) claim, that customer loyalty is
influenced by online complaining behavior. So, the focus of this paper is aimed at activities executed prior to
purchase that can help online sellers to improve their online presence in order to provide the right information
and experience to the potential customers.
2. Research objective and methodology
The aim of this paper is to analyze the use of Internet in pre-purchase stage in the selected countries from
Europe to Asia. By decomposition of the main objective, two partial objectives were specified. First partial
objective was to find the dependence between development indicators (proposed by World Bank) and the use of
Internet in the pre-purchase stage. Second partial objective was focused on determination of differences between
continents in terms of the use of Internet during pre-purchase stage.
To accomplish the objective of the paper, secondary data from the Consumer Barometer and from World
Bank was used. The data in the Consumer Barometer is gathered from two sources: core questionnaire that is
focused on the population of adults; customer study that is used to enumerate the total population and is used to
weight the results (Consumer Barometer, 2015). The sample consists of nationally representative population,
online (by phone or email) and offline (by face-to-face interviews), at the age of over 16 in each country
surveyed. The sample consists of nearly two hundreds thousands participants from 44 countries (29 in Europe
and 15 in Asia (Consumer Barometer, 2015). Surveys were conducted by TNS Infratest on behalf of Google
from January to March 2014 and from January to March 2015. The data from the World Bank was gathered from
data section of the World Bank official website (World Bank, 2015). The data gathered from the World Bank‘s
databases consisted of 02 development indicators: GDP per capita and number of Internet users per 100 people.
The data was analyzed using software IBM SPSS and Microsoft Excel. To analyze the data, descriptive statistics
was used (tables, mean, min, max, standard deviation). In order to test the following hypothesis H1 and H2,
Pearson correlation coefficient was used, the hypothesis H3 was tested with the use of F-test and t-test.
It is commonly clear that wealthier countries (with higher GDP per capita) have not only higher rate of
Internet users (also perceived as the volume of Internet users per 100 people) but also better access to Internet in
terms of quality. As a consequence, in those countries, the use of Internet in the pre-purchase stage will be more
frequent compared to countries with a lower level of these indicators. Regretfully, this is only half of the truth. In
emerging, fast developing and very dynamic markets of Asia, both consumers and companies willingly use
technology, especially Internet technology to leverage their economic distance to developed markets in North
America and Europe (Sajda, Lotfollah, 2017). Many researchers see the reason behind this fact in socio-
demographic trend and structure called the “golden age” of population growth in Asia. In fact, Western and
Eastern consumers are very different in diverse aspects (Spelich, 2017; Ali et al, 2006). Eastern consumers
include mainly Chinese, Indian and ASEAN nationals; they are predominantly young, open to Western culture
and living style, eager to discover new things, among others, using available technologies to leverage their lack
of knowledge and experience and financial resource (income) compared to their Western counterparts (Lopez,
Sicillia, 2014; Ward, Lee, 2000). That is the real reason why we must verify scientifically and statistically the
fact which is subjectively perceived as a true, according to our common sense. Thus, based on the objective of
the paper, the following working hypotheses were formulated:
H1: There is a significant association between GDP per capita and the use of the Internet in order to make a
purchase decision in the analyzed countries.
H2: There is a significant association between Internet users per 100 people and the use of the Internet in
order to make a purchase decision in the analyzed countries.
H3: There is a significant difference between European and Asian countries in terms of the use of Internet in
order to make a purchase decision.
3. Research results and discussions
Based on the objective of the paper, we initially analyzed the portions of the Internet users who executed
selected actions in the pre-purchase stage of the buying process. The overview is presented in Table 1. By
comparing means, we can see that users mostly use the Internet for product/price/features comparison (51,73%),
searching of opinions/reviews/ advice (29,02%) and discovery of relevant brands (26,36%). Users in the pre-
purchase stage do not use the Internet to look for redeemed offers, coupons or promotions (11,52%),
contact/request with retailers or brands (8,61%) and investigation of financing options (4,66%).
107
Nguyen Hoang Tien, Dinh Ba Hung Anh/ MICA 2018 Proceedings
Table 1. The overview of actions performed by Internet users
Action
Mean
Min
Max
Standard
Deviation
9,12
7,13
6,68
4,44
6,31
4,25
4,70
(in %) (in %) (in %)
Get ideas/inspiration online
24,27
26,36
51,73
11,89
29,02
11,52
19,95
14,68
8,61
10,00
17,00
35,00
5,00
12,00
5,00
11,00
8,00
3,00
55,00
54,00
66,00
24,00
41,00
23,00
30,00
33,00
19,00
15,00
Discover relevant brands online
Compare products/price/features online
Watch relevant videos online
Look for opinions/reviews/advice online
Look for redeemed offers, coupons or promotions online
Check where to buy/product availability online
Got locations/directions online
Make contact/request contact (with brands, retailers) online
Investigate financing options online
5,43
2,94
3,18
4,66
1,00
In order to accomplish one of our partial goals, the determination of association between World Bank
development indicators and pre-purchase behavior of Internet shoppers, we tested the following statistical
hypotheses:
H0: There is no correlation between GDP per capita and the use of the Internet in the pre-purchase stage.
H0: There is no correlation between the number of Internet users per 100 people and the use of the Internet in
the pre-purchase stage.
GDP per capita and the Internet users per 100 people belonged to indicators that interested us. We used
Pearson correlation to define correlation between those indicators and activities executed during the pre-purchase
stage by Internet shoppers. The results can be found in Table 2.
Table 2. The dependence between WB development indicators and use of Internet in pre-purchase stage (H1,
H2)
Action
Pearson coefficient
GDP per capita Internet users per
100 people
-0,347*
Get ideas/inspiration online
-0,109
Discover relevant brands online
Compare products/price/features online
Watch relevant videos online
Look for opinions/reviews/advice online
Look for redeemed offers, coupons or promotions online
Check where to buy/product availability online
Get locations/directions online
Make contact/request contact (with brands, retailers) online
Investigate financing options online
-0,549**
-0,363*
-0,637**
-0,622**
-0,359*
-0,527**
-0,487**
-0,392**
-0,639**
-0,732**
-0,091
-0,703**
-0,391**
-0,308*
-0,473**
-0,483**
-0,495**
-0,653**
* significant at α = 0,05, ** significant at α = 0,01
It is commonly clear that countries with higher GDP per capita and higher volume of the Internet users per
100 people will use the Internet in the pre-purchase stage more compared to countries with a lower level of these
indicators. However, based on our results, we can see that there is a strong negative correlation between World
Bank development indicators and actions taken with the use of Internet during pre-purchase stage. Especially,
the negative correlation between the Internet users per 100 people and its use during the pre-purchase stage
should be a subject of further discussion. There is presented strongest observed negative correlation between the
Internet users per 100 people and use of the Internet in the pre-purchase stage, concretely the discovery of
relevant brands online (Pearson coefficient -0.732 for Internet users per 100 people) and the watching relevant
videos online (Pearson coefficient -0,703 for Internet users per 100 people). Alternatively, we see two cases of
the strongest observed negative correlation between GDP per capita and use of the Internet in the pre-purchase
stage, concretely watching of relevant videos online (Pearson coefficient -0,637 for GDP per capita) and
investigation of the financing options online (Pearson coefficient -0,639 for GDP per capita). It might be
108
Nguyen Hoang Tien, Dinh Ba Hung Anh/ MICA 2018 Proceedings
assumed there are limitations in the data that distort the results. In addition, further research of conditions that
caused calculated results should be conducted in order to discover the cause of the negative correlation or other
variables that might influence the use of the Internet in the pre-purchase stage.
Based on the available data and calculated statistics, we reject the null hypothesis, except the case of getting
ideas/inspiration online (Pearson coefficient -0,109 for GDP per capita) and the case of comparison of
products/price/features online (Pearson coefficient -0.091 for Internet users per 100 people) and accept both
alternative hypotheses. So, there is a significant correlation between World Bank development indicators and the
use of the Internet in order to make a purchase decision in analyzed countries.
The second partial goal of our paper was focused on a comparison of the Internet use in pre-purchase stage
between European and Asian countries. In order to determine the difference, we tested the following hypotheses:
H0: There is no significant difference between average values of European and Asian countries in the use
of the Internet in order to make a purchase decision.
First, we used two-sample F-test for variances in order to determine if the variance is equal. The results can
be found in Table 3.
Table 3. Results of F-test two-sample for variances action
Action
F
p-value
0,000**
0,001**
0,034*
0,010**
0,475
0,14
0,063
0,024*
0,000**
0,000**
Get ideas/inspiration online
0,15
0,26
0,45
0,36
1,05
0,63
0,51
0,42
0,12
0,22
Discover relevant brands online
Compare products/price/features online
Watch relevant videos online
Look for opinions/reviews/advice online
Look for redeemed offers, coupons or promotions online
Check where to buy/product availability online
Get locations/directions online
Make contact/request contact (with brands, retailers) online
Investigate financing options online
* significant at α = 0,05, ** significant at α = 0,01
Based on the results received in Table 3, we used two-sample T-test assuming equal/unequal variances. As
the results in Table 4 display show, the statistically significant difference between European and Asian
countries during the pre-purchase stage with the use of the Internet was observed in:
Discovery of relevant brands online,
Watching relevant videos online,
Looking for redeemed offers, coupons or promotions online, and
Getting locations/directions online.
In those four cases, we rejected the null hypothesis from c) and accept the alternative hypothesis. In the
remaining activities, we could not reject the null hypothesis from c), assuming there is no statistically significant
difference between European and Asian countries in the use of the Internet in order to make a purchase decision.
However, the actions where the differences were noticed should be the subject of further research. It can be
beneficial in determination of shopping preferences based on the geographic, demographic, behavioral or
psychographic features of the Internet users as well as the development of online environment on European and
Asian markets.
Table 4. Results of two-sample t-test
Action
T-test assuming
equal variances
T-test assuming
unequal variances
T Stat
-
-
-
p-value
T Stat
-1,1
-3,69
-1,01
-2,92
-
-
-
p-value
0,287
0,002*
0,322
0,009*
-
-
-
-
-
Get ideas/inspiration online
Discover relevant brands online
Compare products/price/features online
Watch relevant videos online
Look for opinions/reviews/advice online
Look for redeemed offers, coupons or promotions online
Check where to buy/product availability online
Get locations/directions online
-
-2,02
-2,03
-1,13
-
0,05
0,049*
0,263
-
-
-
-2,81
0,011*
109
Nguyen Hoang Tien, Dinh Ba Hung Anh/ MICA 2018 Proceedings
-
-
-
-
-1,52
-1,6
0,147
0,128
Make contact/request contact (with brands, retailers) online
Investigate financing options online
* significant at α = 0,05, ** significant at α = 0,01
Given the all above mentioned results we come to the following conclusions:
There is a statistically significant negative correlation between GDP per capita and the use of the Internet in
the pre-purchase stage (except the case of getting ideas/inspiration online) and between the Internet users per
100 people and the use of the Internet in pre-purchase stage (except the case of comparison of
product/price/features online) in European and Asian countries.
There is a statistically significant difference between European and Asian countries in discovery of relevant
brands online, watching relevant videos online, looking for redeemed offers, coupons or promotions online
and getting locations/directions online. In the other cases, there was not found a statistically significant
difference between European and Asian users when using the Internet in the pre-purchase stage.
The results might be affected by several limitations: the number and composition of countries included in our
sample, use of aggregated data and the accuracy of data from both databases. Moreover, as Clark and Avery
(1976) discuss in their paper, there are certain bias when using correlation analysis on aggregated data. It is
incorrect to assume that relationship existing at one level of analysis will be the same at another level. This
limitation might be overcome by gathering additional data about users on more granular level.
4. Managerial implications and conclusions
The results of the study can be used by marketing and sales managers and directors of companies that sell
products online to Europe and Asia. In case there was a real causality (not only correlation) between variables
tested in working hypotheses H1 and H2, it would mean the less developed markets are more suitable for
developing online business, thus are more suitable for this kind of business. Companies that are willing to take
this risk can try to reach potential customers on these markets and take over the market share from companies
that are not attracted in these markets. In case these efforts are successful, companies can gain a competitive
advantage as a result of being established on the market before competitors. Moreover, the results obtained by
testing hypothesis H3 didn't show a significant difference between European and Asian online users. This means
that companies that are focused on selling online on both continents are not forced to distinguish their online
promotion activities. We assume these companies should focus more on cultural differences instead of
geographic ones. These implications are valid in cohesion with limitations of this study.
Online shopping has become a regular purchase form in today‘s business (Nguyen Hoang Tien, 2017). As the
online and offline shopping differs, sellers cannot rely on data on offline shopping behavior anymore. The aim of
this paper was to analyze the use of the Internet in the pre-purchase stage in the selected countries in Europe and
Asia. The results of this paper show that there is a significant negative correlation between selected World Bank
development indicators (GDP per capita, Internet users per 100 people) and the use of the Internet in the pre-
purchase stage. Moreover, we have found that there is a significant difference between European and Asian
countries in the use of Internet during pre-purchase stage in the following observed activities: discovery of
relevant brands online, watching relevant videos online, looking for redeemed offers, coupons or promotions
online and getting locations/directions online. There was not found any significant difference in the other
observed activities. The results can be used by managers in the field of marketing and sales as a basis for the
composition of online presence, online marketing campaigns and online reputation management for the
companies that sell products online and offline in Europe and Asia.
References
[1] Ali K. et al, 2006, E-commerce: a Study of Internet Shopping in Malaysia, “Journal of Applied Science”, 6,
pp. 695-705.
[2] Bai P., Cui Y., Ye L., 2014, Research of the Relationship of E-Service Quality, Customer Satisfaction and
Customer Loyalty in C2C Online Shopping, “Contemporary Logistics”, 3(14).
[3] Clark W.A.V., Avery K.L., 1976, Effects of Data Aggregation in Statistical Analysis, “Geographical
Analysis”, 3.
[4] Ferencova M., Jurkova J., 2011, Communication Policy of Selected Educational Institutions In The Context
Of Analysis Of Familiarity And Favorable Attitudes, “Polish Journal of Management Studies”, 3.
[5] Hu M., Rabinovich E., Hou H., 2015, Customers Complaints in Online Shopping: The Role Of Signal
Credibility, “Journal of Electronic Commerce Research”, 16(2).
[6] Kot S., Ferencova M., Karas Ľ., 2012, Price as a Factor Impacting the Choice of Summer Holiday Packages
110
Nguyen Hoang Tien, Dinh Ba Hung Anh/ MICA 2018 Proceedings
by Customers of Tourist Industry, „Marketing and Market”, 19(5).
[7] Liu X., Burns A.C., Hou Y., 2013, Comparing Online and in-Store Shopping Behavior Towards Luxury
Goods, “International Journal of Retail & Distribution Management”, 41(11).
[8] Lopez M., Sicillia M., 2014, Determinants of E-word of mouth Influence: The Role of Consumers’ Internet
Experience, “Journal of Theoretical and Applied Electronic Commerce Research”, Vol. 9, No. 1.
[9] Nguyen Hoang Tien, 2017, Global Strategic Marketing Management. Ementon publisher, Warsaw, 244
pages.
[10]Sajda Q., Lotfollah N., 2017, Information and Communication Technology Use and Income Growth,
Evidence of Multiplier Effect in very Small Islands States, “Journal of Information Technology for
Development”, Vol. 23, No.2., pp. 212-234.
[11]Solomon M., Russell-Bennet R., Previte J., 2013, Consumer Behavior: Buying, Having, Being, Pearson,
Frenchs Forest.
[12]Slusarczyk B., Kot S., 2012, Polish Government Impact On Foreign Direct Investments, “Polish Journal of
Management Studies“, 6.
[13]Spelich J. W., 2017,
7
Key Differences between Chinese and Western Consumers.
https://multichannelmerchant.com/blog/7-key-differences-chinese-western-consumers/ . Date of access:
08.08.18
[14]Trenz M., 2015, Multichannel Commerce: A Consumer Perspective on the Integration of Physical and
Electronic Channels, Springer, New York.
[15]Ward M. R. and M. J. Lee, 2000, Internet Shopping, Consumer Search, and Product Branding, “Journal of
Product and Brand Management”, vol. 9, no. 1, pp. 6-20.
Internet sources:
111
6 trang
14/05/2022
1680
Bạn đang xem tài liệu "Internet use behavior of consumers in pre-purchase stage of online shopping", để tải tài liệu gốc về máy hãy click vào nút Download ở trên
File đính kèm:
- internet_use_behavior_of_consumers_in_pre_purchase_stage_of.pdf
