Proceedings of 28th International Business Research Conference
8 - 9 September 2014, Novotel Barcelona City Hotel, Barcelona, Spain, ISBN: 978-1-922069-60-3
Factors Affecting Online Shopping: An Empirical Study in
Lahore, Pakistan
Khadija Ejaz Khan*1
The study aimed to investigate the factors that Affect online shopping
in Lahore. The study aims to identify key factors influencing
Pakistan’s online shopping purchase behavior, to highlight the
relationship between the key factors and the different group of buyers
and Lastly to examine the impact of different factors on different
group of buyers. Questionnaire survey method was employed to
gather the information in the month of April 2013. For this paper 249
respondents past online purchase experiences were recorded and
were analyzed. Based on the purchase frequency, the respondents
are categorized into four different groups. The study examines the
different dimensions of online shopping trends in Lahore Pakistan.
The 31 attitude based questions reduces to 10 important
uncorrelated dimensions using factor analysis that affect online
shopping in this part of the world. Convenience, retailers web
designs, competitive pricing, Logistics and payment security were
found to be the most important factors in Influencing online shopping.
The vast study of consumer behavior identifies that customers
behave differently based on many factors. Then discriminant analysis
is conducted to see the impact of these extracted factors on different
types of online buyers. Consumers are categorized as Trial,
occasional, frequent and regular buyers. The study states that the
customer service, convenience, reduced purchase related cost are
the variables with greater discriminant ability among different group
of buyers, whereas Product delivery and payment security are the
variables with least discriminating ability.
JEL Codes: Online Shopping, Consumer Behavior, E-retailers, E-Commerce
1. Introduction:
Internet with its ever increasing rate of being adopted as a medium of exchange of
information has recently tapped a new industry of e-tailing. Transforming many
industries it continues to transform the living standards of consumer around the
globe. With its recent advancements in E-Commerce, primarily dealing with Business
to business and stretched out from business to consumer and then consumer to
consumer. Electronic markets have become eminent over the years. This has
become the most recent, quickest, time & cost efficient way of connecting to the
world. This further led to the growth of small and medium entrepreneurship.
Companies and organizations around the world have adopted this medium of
communication with the help of which they reach out to their consumers, market their
products, and are able to deliver to the farthest point of the world. Though
ecommerce is in its infancy, marketing and purchasing products and services online
have become one of the most rapidly growing forms of Shopping. Levi & Weitz
(2001). According to consumer confidence survey – field dates march 8, 2010, only
36% of internet users in Pakistan had experienced shopping online.
As Pakistan’s internet populace is increasing, a tremendous growth of internet users
in Pakistan provides a clear potential in the field of online retailing. Optimism of many
1
* Khadija Ejaz Khan , Centre for Mathematics & Statistics, Lahore School of Economics
Email: khadijaejaz@gmail.com, khadija@lahoreschool.edu.pk
Proceedings of 28th International Business Research Conference
8 - 9 September 2014, Novotel Barcelona City Hotel, Barcelona, Spain, ISBN: 978-1-922069-60-3
researchers in the past about the prospects of online shopping has lead a large
number of businesses to register a prominent presence online, thereby marketing,
communicating, broadcasting information and eventually soaring in sales. According
to ISPAK (internet service providers association of Pakistan) Pakistan’s internet
users have been estimated to be 25 million by march 2014, with an ever increasing
trend of mobile internet usage the mobile internet users have been estimated to be
1.5 million, availing the services of Edge/Gprs. In another research done on behalf of
Google by Pakistan Digital Consumer Survey (PDCS 2014) indicated that by the end
of 2014, the percentage of mobile internet users will surpass the percentage of
internet users by any other gadget. The reasons for this could be accounted to the
availability of smart phones at affordable prices, presence of international smart
phone brands, telecom sectors introducing easy, convenient and affordable
packages and lastly the launching of 3G services that will soon revolutionize the
internet users base in Pakistan.
These facts and figures prove a promising future of online selling and buying. For
businesses and organizations to utilize this medium of sales, it becomes inescapable
to ignore the characteristics and prospects of E-tailing. E-marketers must gain deep
insight of consumers & their orientations or otherwise will face back lash in business
to consumer context says Nunes (2001) A critical understanding of consumer
behavior is required to comprehend the future of E-tailing as more and more
customers are becoming familiar with this medium of exchange. The purpose of this
study is primarily to explore Pakistani online shopping orientation, the key factors
that influence or compel consumers to shop online, it further highlights the
relationship between the identified factors and the different group of buyers as
identified by Shergill and Chen (2005). This is the first study to explore the nature of
Pakistani online consumer base, their orientation and their tendencies. Based on the
purchase frequency, the respondents are categorized into four different groups as
Trial, occasional, frequent and regular buyers. The study examines the different
dimensions of online shopping trends in Lahore Pakistan. The 31 attitude based
questions reduced to 10 important uncorrelated dimensions using factor analysis that
affect online shopping in this part of the world. Convenience, retailers web designs,
competitive pricing, Logistics and payment security were found to be the most
important factors in Influencing online shopping. The vast study of consumer
behavior identifies that customers behave differently based on many factors. Then
discriminant analysis is conducted to see the impact of these extracted factors on
different types of online buyers.
There are several elements of this study that both set it apart as a unique
contribution and mark it as valuable addition to the literature. Primarily, this study
focuses on the purchasing behavior, an altogether new dataset with the latest
diverse demographics of online shoppers. Insights from this research will help
businesses to plan and formulate strategies while keeping in mind the factors
highlighted by the study, marketers can segment and target their customers in an
accurate way.
2. Research Objectives:
E-Tailing is fundamentally changing the pattern of buying and shopping. From the
literature review, it is perceived that there have been minimal researches done about
Pakistan’s online consumer. The purpose of this study is to investigate online
consumer behavior.
1. To identify key factors influencing Pakistan’s online shopping purchase behavior.
Proceedings of 28th International Business Research Conference
8 - 9 September 2014, Novotel Barcelona City Hotel, Barcelona, Spain, ISBN: 978-1-922069-60-3
2. To highlight the relationship between the key factors and the different group of
buyers.
3. To examine the impact of different factors on different group of buyers.
3. Literature Review:
There have been intensive studies of online shopping attitudes and behavior in
recent years. Most of them have attempted to identify factors influencing or
contributing to online shopping attitudes and behaviors. Shergil & Chen (2005) found
that website design, website reliability/fulfillment, web customer service, website
security/privacy are the four dominant factors in influencing the perception of online
purchasing. They categorized the online shoppers for New Zealand in four distinct
groups that were trial buyers, occasional buyers, frequent buyers and regular buyers.
And further pointed that buyers evaluations varied for different factors, had based on
their purchasing frequency. Zhou et al (2007) found significant relationship of online
shopping with Convenience. Electronic markets have majorly reduced the search
related costs in terms of money and time. Most of the online customers refer to
convenience in terms of internets ability to do product comparison, ease of searching
and the in depth information about the products available online. Whereas Kumar et
al. (2005) suggested that the technology by itself does not significantly reduce the
search related costs rather technology in combination with behavioral factors
matters.
Bhatt and Bhatt (2013) identified in their study conducted in Ahmadabad that
ease/attractiveness of website, service quality of website & website security were
most important factors that influence the online purchasing perception. Regular
buyers were most influenced by the ease/attractiveness of website and service
quality of website. Occasional buyers rated security as an important factor over
others. Halimi et al. (2011) investigated the impact of factors affecting consumers’
attitude towards online purchasing among degree holders in Singapore. A significant
relationship was found between perceived usefulness, ease of use, security &
consumers’ attitude towards online purchasing. Moreover a negative but significant
relation existed between privacy concerns and attitude towards online buying.
Panwar & chahal (2013) identified that the online shopping attitudes vary among
different demographic variables of consumers such as age, gender, education and
income. Significant differences were found in consumers attitudes based on the level
of income. Kim & Kim (2004) also indicated that age, educational background,
weekly browser usage, number of years of Internet use significantly impact the
online purchasing.
Nirmala and Dewi (2011) conducted a survey in Indonesia and highlighted that
factors such as consumer innovativeness, online purchase experience, gender and
price consciousness are significant on consumers intentions to shop for fashion
products. Based on their research women had lower intentions to shop for fashion
products online than men. Crisp et al. (1997) also concluded that prior internet
experience, age, household size and frequency of shopping influenced online
purchasing. SriKath and Uma Sailaja (2007) in their study of online purchase trends
in India, found that the most important reasons for the consumer to shop online
were Speed of transaction, Amount of information available online and the variety of
products. Further it was stated that factors that hindered online shopping were
unreliable payment mechanisms, security issues and improper delivery mechanisms
with poor infrastructural facilities.
The technical innovation of Internet and ecommerce has delivered and continues to
bring substantial benefits to the customers. Consumers purchase products online
Proceedings of 28th International Business Research Conference
8 - 9 September 2014, Novotel Barcelona City Hotel, Barcelona, Spain, ISBN: 978-1-922069-60-3
because of convenience, splendid variety, twenty four hours accessibility, no
geographic boundaries, reduced purchase related costs, ease of price comparison.
Hannah and Lybecker (2009) highlighted that the most important determinant for
online purchasing in male gender is having a debit/credit card, an online payment
account, participating in an online auction, listening to podcasts. Further online
content, marketing the right segment based on their gender, needs & interest can
substantially increase the results and can increase the percentage of sales online.
4. Methodology:
4.1 Population and Sampling:
The target population consists of the educated people residing in Lahore, Pakistan
having the availability of internet. The Population was divided into segments and
stratified sample technique was adopted for the data collection. The data was
collected from different shopping malls, universities, banks, computer firms.
4.2 Data Collection:
For Primary data collection, the study used a questionnaire. The existing literature
appeared helpful in identifying many contructs that have already been read under
this topic : Shergil & Chen (2005) and Bhatt and Bhatt (2013), whereas few more
questions were added in order to deal with this specific region. The questionnaire
comprised of a number of Likert scale questions, dichotomous questions and the
basic demographics of consumers. The first question inquired about the number of
times people opted for online shopping in the past year, based on their frequency of
shopping the online consumers are categorized in four different groups.
a. 1-2 times: Trial Buyers (people who rarely shop online during last year)
b. 2-4 times: Occasional buyers (people who sometimes shop online during last
year)
c. 5-10 times: Frequent buyers (people who often shop online during last year)
d. More than 10 times: Regular buyers (people who regularly shop online during
last year )
4.3 Analysis Technique:
10 questionnaires were distributed for the purpose of pre-testing in April 2013. The
questionnaire was pretested and the reliability was checked on 10 respondents who
had experienced online shopping. The Cronbach`s alpha statistic found to be 0.893,
which indicates that the inter-term consistency exists. This signifies that the scales of
all the variables of the questionnaire were properly understood by all the
respondents. However, based on the comments given by the respondents, few
changes were made in the original questionnaire. The questionnaires were
distributed among internet users. Out of 500 questionnaires that were distributed a
total of 360 were returned. Of the returned questionnaires 111 were eliminated
because of not experiencing online shopping in the past one year or ever. After
elimination only 249 questionnaires were coded and analyzed for the empirical
investigation. Depending upon the customers, some questionnaires were
administered in Urdu and some in English. The collected data from the respondents
was coded and then analyzed by using Statistical package of the social science
(SPSS). The demographic profile of the respondents was generated. For the
analysis of first Research question we used exploratory factor analysis, whereas in
Proceedings of 28th International Business Research Conference
8 - 9 September 2014, Novotel Barcelona City Hotel, Barcelona, Spain, ISBN: 978-1-922069-60-3
order to identify the significant impact of extracted factors on four different groups of
buyers, Discriminant analysis technique was applied.
5. Results and Discussion:
5.1 Demographic Profile of the Sample:
The detailed insight of the online buyers in Lahore is explained by the demographic
features exhibited in Table 1. The results clearly indicates that majority of the
respondents were the Trial Buyers who shopped once or twice during past year.
However, the second largest category belongs to Occasional Buyers who shopped
at least few times during the last year. One of the reason could be, the online
shopping phenomenon is not common in developing countries like Pakistan due to
the lack of the knowledge and other cultural constraints. Our argument is further
strengthen if we look at the demographics of Age category, which clearly shows that
majority of the respondents participated in this sample survey were young people,
who were more flexible and keen to adopt new ideas. Majority of the respondents
who experienced online shopping before were male and unmarried. Coming to the
Social status, largest portion of our respondents belong to the Middle class, however
only two respondents who experienced online shopping before classified themselves
from Lower class. Majority of our respondents were Graduate and belongs to English
medium institutions. The survey focuses the target population of Lahore (Capital of
Province of Punjab), so majority of our respondents classified their ethnicity as
Punjabi.
Table 1: Demographics of the respondents
Variables
Online Purchasing Frequency
Categories
Trial Buyers
Occasional Buyers
Frequent buyers
Regular Buyers
Young
Middle aged
Old
Male
Female
Single
Married
Divorced
Widowed
Yes
No
Upper Class
Upper Middle Class
Middle Class
Lower Middle Class
Lower Class
Undergraduate
Graduate
Post Graduate
Percentages
45.1%
35.3%
17%
2.6%
74.4%
16.7%
8.9%
59.3%
40.7%
66%
30%
2.4%
0.4%
28.6%
71.4%
9.5%
29.8%
53.7%
6.2%
0.8%
16.7%
64.1%
16.1%
Medium of Education
English
Urdu
79.4%
20.6%
Ethnicity
Punjabi
Non-Punjabi
75.9%
24.1%
Age in Categories
Gender
Married
Working Couple
Class
Education
Proceedings of 28th International Business Research Conference
8 - 9 September 2014, Novotel Barcelona City Hotel, Barcelona, Spain, ISBN: 978-1-922069-60-3
5.2.1 Exploratory Factor Analysis:
Next to identify the key factors that influence online shopping, an exploratory factor
analysis is performed. The purpose of factor analysis is data reduction and
summarization. The algorithm identifies the smaller set of uncorrelated variables to
replace the original set of correlated variables. We run the algorithm on 31
opinionated statements measured on a 5 point Likert scale, ranging from strongly
disagree to strongly agree.
Although there exists weak or moderate correlation among majority of the
statements indicated by the Correlation Matrix (results can be provided if required),
however the Kaiser-Meyer-Olkin (KMO) statistic value (.730) indicate that it is
appropriate to apply the factor analysis. The (KMO) measure of sampling adequacy
is an index used to examine the appropriateness of factor analysis and values higher
than 0.5 indicates that the factor analysis is appropriate. Further, the significant value
of Bartlett's test of sphericity (BTS) also explains that there exists a correlation
structure among the original variables and the Factor analysis is appropriate. BTS is
a test statistic used to examine the hypothesis that the variables are uncorrelated in
the population and the rejection of null hypothesis implies the existence of correlation
among the variables.
Kaiser-Meyer-Olkin
.730
Measure
of
Sampling
Adequacy
Table 2: KMO and BTS Test Statistics
Value
Initially the factor analysis was conducted
with a total of thirty one variables. The
Bartlett's Test of Sphericity 1223.381
Principle Component Analysis method
with varimax rotation extracted ten
df
0.435
orthogonal factors from 31 variables.
These factors explained 62% variation of
Sig.
0.000
the original dataset (Table 3). However,
depending upon the information conveyed, the factors termed as customer service,
convenience, retailers in depth information, less cheating, customers satisfaction,
product delivery, competitiveness, payment security, reduced purchase related
costs, ease of ordering online. We consider the factor loadings of above 0.5 as
deciding criterion.
Proceedings of 28th International Business Research Conference
8 - 9 September 2014, Novotel Barcelona City Hotel, Barcelona, Spain, ISBN: 978-1-922069-60-3
Table 3: Total Variance Explained
Componen
t
Initial Eigenvalues
Rotation Sums of Squared Loadings
Total
% of
Variance
Cumulative
%
Total
% of
Variance
Cumulative
%
1
5.286
18.228
18.228
2.329
8.031
8.031
2
2.152
7.421
25.649
2.038
7.026
15.057
3
1.632
5.627
31.276
2.022
6.972
22.029
4
1.607
5.542
36.817
1.981
6.830
28.859
5
1.465
5.053
41.870
1.885
6.500
35.360
6
1.346
4.642
46.512
1.709
5.893
41.253
7
1.241
4.281
50.793
1.687
5.817
47.070
8
1.171
4.038
54.831
1.647
5.679
52.749
9
1.083
3.735
58.566
1.443
4.976
57.725
10
1.028
3.544
62.110
1.272
4.385
62.110
Factor 1(Customer services provided by the Online Retailers) loaded four
questions i.e. Online shopping is less time consuming (0.537), online shopping is
having easy payment procedure (0.740), online shopping allows more thought at
choices (0.564) and online shopping saves them from carrying cash (0.653).Factor 2
(Convenience) loaded three questions such as online shopping is convenient
because of 24 hours accessibility (0.712), online shopping provides ease of price
comparison (0.753) and online shopping saves the customers from dealing with
salesperson sweet tongue (0.566). Factor 3 (Retailers in depth information)
loaded four questions such as online shopping provides in-depth information (0.717)
, online shopping provides click and easy transactions (0.590) , better variety is
available online (0.515) and the online discounts are available by the companies
(0.618). Factor 4(Less cheating) includes online shopping prevents cheating with
loading of 0.743 whereas Factor 5(Customers satisfaction) highlighted 3
questions: People like to buy International brands over national brands(0.706) ,
online brands have a better understanding of their customers (0.565) and buying
online gives high satisfaction( 0.609). Factor 6 (Product Delivery) loaded online
shopping provides time delivery (0.603) and the question transaction online is more
secure (0.768). Factor 7(Competitiveness) included online shopping provides
Competitive prices (0.753) and online retailers competitive attitude of responding to
the customers queries (0.524). Factor 8 (Payment security) loaded 2 questions that
customer rate cash on delivery is better (0.775) and that giving credit card
information is not secure (0.775).Finally, Factor 9 (Reduced purchase related
costs ) loaded one question that online shopping reduces purchase related costs
(0.784) and Factor 10 (Ease of ordering online) included the perception question
that it is easy to order Online (0.832)
Proceedings of 28th International Business Research Conference
8 - 9 September 2014, Novotel Barcelona City Hotel, Barcelona, Spain, ISBN: 978-1-922069-60-3
5.2.1.1 Discriminant Analysis:
In order to understand which variables appear to discriminate between the groups,
we conduct discriminant analysis. The purpose is to maximally separate the groups
for which the grouping variable was the frequency of online purchasing (divided into
four categories) and the Independent variables taken under consideration were the
extracted ten factors from the exploratory factor analysis. To test the hypothesis that
the means of the groups on the discriminant function centroids are equal. The
discriminant analysis is carried out on the data of 145 respondents completed the
questionnaire without any missing values.
The group statistics classify 27 buyers as Trial buyers, 48 as occasional, 39 as
frequent and 31 as regular buyers. The respondents’ responses indicate that for Trial
buyers the most important factor is convenience. Similarly occasional buyers rate
customer satisfaction, whereas frequent buyers consider Retailers in-depth
information available as the most influencing factor towards the online shopping.
However for Regular buyers the most essential factor is competitive pricing. The
different mean responses of different groups for the extracted highlights the
importance of discriminant analysis. Discriminant analysis examines the impact of
different factors on different group of buyers.
Since our dependent variable has four categories so we get three discriminant
functions. However, Function 1 appears to be more significant explaining 50.6% of
variations in the Dependent variable (Table 5). Function 2 explains relatively lesser
variation of about 32.3 % and function 3 explains the lowest 17 % variations in the
dependent variable. The eigen values describe the discriminating ability a function
possesses. The magnitude of the eigen value of first function is indicative of the
functions discriminating ability.
Table 5: Eigenvalues computed from Discriminant Analysis
Function
Eigenvalue
% of Variance
Cumulative %
Canonical
Correlation
1
.163a
50.6
50.6
.374
2
.104a
32.3
82.9
.307
3
.055a
17.1
100.0
.228
a. First 3 canonical discriminant functions were used in the analysis
Wilks lambda measures that how well each function separates cases into groups.
The associated chi square statistics test hypothesis that the means of the functions
are equal across the groups however in our analysis the means of the function 1 are
unequal across the groups whereas the function 2 & function 3 are found to be
insignificant as indicated in Table 6. Hence we only consider function 1 for the further
analysis.
Proceedings of 28th International Business Research Conference
8 - 9 September 2014, Novotel Barcelona City Hotel, Barcelona, Spain, ISBN: 978-1-922069-60-3
Table 6: Wilks' Lambda
Test of Function(s)
Wilks' Lambda
Chi-square
df
Sig.
1 through 3
.739
41.475
30
.079
2 through 3
.859
20.832
18
.288
3
.948
7.311
8
.503
The standardized discriminant function coefficients indicate the relative importance
of the independent variables in predicting the dependent variable. In our analysis,
Retailers in-depth information appears to be the most significant factor influencing
the purchase frequency of online shopping across four different categories ( Table
7).
Table 7: Standardized Canonical Discriminant Function coefficients
Similarly customer service, convenience, reduced purchase related cost are the
variables with greater discriminant ability. Product delivery and payment security are
the variable with least discriminating ability. These coefficients can also estimate the
discriminant score for a given case with the help of a linear regression equation.
Purchase frequency = 0.375 (customer service) + 0.412 (Convenience) – 0.621
(Retailers In-depth info) + 0.258 (less cheating) – 0.239 (customer satisfaction)
+0.25 (product delivery) – 0.284(competitive pricing) + 0.55 (payment security)
+0.342 (reduced purchase related costs) – 0.191 (Ease of Online ordering)
Customer service
Convenience
retailers in-depth info
less cheating
customers satisfaction
product delivery
competitive pricing
payment security
reduced purchase related costs
ease of ordering online
Function 1
3.5
.412
-.621
.258
-.239
.025
-.284
.055
.342
-.191
Proceedings of 28th International Business Research Conference
8 - 9 September 2014, Novotel Barcelona City Hotel, Barcelona, Spain, ISBN: 978-1-922069-60-3
Next we examine the structure matrix to see how strongly the factors are correlated
with 1st discriminant function. Retailers in depth information are strongly correlated
with discriminant function. Similarly customer service and convenience are also
Figure 7 :
Structure Matrix
Function
1
retailers indepth info
-.586*
customer service
.394*
reduced purchase related
.317*
costs
payment security
.065
competitive pricing
-.260
less cheating
.256
product delivery
-.005
ease of ordering online
-.152
customers satisfaction
-.208
Convenience
.382
Pooled within-groups correlations between discriminating variables and standardized
canonical discriminant functions, Variables ordered by absolute size of correlation
within function
found to have correlation structure with the discriminant function. Whereas the
lowest correlation of discriminant function is between payment security and product
delivery (Table 8). The validity of the discriminant analysis is established using
classification results which indicate that 46.2 % of cases are correctly classified.
Conclusion:
The ever increasing rate of internet adaptability has led to the new era of online
shopping. Consumers and brand across the globe are adapting and are attracted to
this medium of communicating, marketing, and selling/shopping. Having a wide pool
of potential clients, no operative costs & issues, eliminating geographical boundaries,
companies are utilizing this convenient method to approach their customers globally.
However as the online market becomes competitive, differentiation needs to become
an integral part of operations. Brands these days are continually progressing and
trying to increase their sales by implying new methods and techniques. This
research finds out that customers service and convenience, the accessibility and
competitive pricing, the latest user friendly yet elaborated website designs and
Proceedings of 28th International Business Research Conference
8 - 9 September 2014, Novotel Barcelona City Hotel, Barcelona, Spain, ISBN: 978-1-922069-60-3
payments security are the dominant factors that influence consumers trends of
Online shopping.
The vast study of consumer behavior identifies that customers behave differently
based on many factors. The study examines the different dimensions of online
shopping trends in Lahore Pakistan. The 31 attitude based questions reduced to 10
important uncorrelated dimensions using factor analysis. Then discriminant analysis
is conducted to see the impact of these extracted factors on different types of online
buyers. The different types of online buyers were categorized based on their
frequency of purchasing online in the past one year and their preference for each of
the factors. Consumers are categorized as Trial, occasional, frequent and regular
buyers. The results indicate that out of the three functions generated by the analysis
only discriminant Function 1 appeared to be significant. The significant value of wilks
lambda highlights that the variables appear to discriminate between the different
types of online buyers. The study states that the customer service, convenience,
reduced purchase related cost are the variables with greater discriminant ability
among different group of buyers, whereas Product delivery and payment security are
the variables with least discriminating ability.
Limitations and Suggestions for Future Research
The research findings have brought managerial implications to the various
stakeholders, the study provides some insight and feed back to the E-retailers to
formulate and implement various business strategies to increase the customer online
purchases. E-retailers may offer different deals, market more by providing detailed
information about the company and the products it offers. Also all the electronic
markets must introduce various modes of payment and specially the payment of
cash on delivery.
As this is the first ever research conducted on Lahore Pakistan, it has set some
ground work for further research. Firstly, the study conducted was based on the data
acquired from the online buyers of Lahore; the respondents had a prior experience of
an online purchase. The study did not cover those potential customers who do not
have any experience of online transaction. Secondly, random sampling technique
was not used, since the respondents were limited to only those people who have the
facility to use internet, therefore reducing the factor of generalizability. For further
research the researchers must use Confirmatory Factor Analysis also in order to
explain the robustness of these results.
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Appendix
Figure 1:
Reliability Statistics
Cronbach's
N
Alpha
Items
.893
31
of
Figure 2:
Kaiser-Meyer-Olkin Measure of Sampling Adequacy
.730
Bartlett's Test of Sphericity
Approx. Chi-Square
1223.381
df
435
Sig.
.000
Figure 3:
Proceedings of 28th International Business Research Conference
a
8 - 9 September 2014, Novotel Barcelona
City Hotel,
Barcelona,
Spain,
ISBN: 978-1-922069-60-3
Figure 4 : Rotated
Component
Matrix
Component
1
easyPaymentProce
dure
SavesfromCarrying
Cash
AllowsMoreThoug
htAtchoices
LessTimeConsumi
ng
2
3
4
5
.740
.653
.564
.537
ImpToBuyFromKn
ownWebretailer
EaseofPriceCompa
rison
convinientcozof24h
rsaccess
.753
.712
NotDealingWithSal
espersonSweetTon
.566
gue
RetailersIndepthInf
o
OnlineDiscounts
quickneasyTransact
ion
BettervarietyOnline
lessCheating
.717
.618
.590
.515
.743
Comfortableoverne
t
QualityatArrival
iwouldBuyMoreOn
lineInFuture
ILikeInternationalo
verNational
.706
6
7
8
9
10
Proceedings of 28th International Business Research Conference
8 - 9 September 2014, Novotel Barcelona City Hotel, Barcelona, Spain, ISBN: 978-1-922069-60-3
HighSatisfactionOn
line
.609
OnlineBetterUnder
standingofCustome
.565
rs
OnlineIsSecure
.768
OntimeDelivery
.603
MiantainsPrivacy
OnlineCompetitive
Prices
companyrespondsQ
ueries
CashonDeliveryisB
etter
CardInfoNotsecure
.753
.524
.775
.775
InquiriesansweredP
romptly
ReducedPurchaseR
elatedCosts
easytoOrderOnline
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
a. Rotation converged in 15 iterations.
.784
.832
Proceedings of 28th International Business Research Conference
8 - 9 September 2014, Novotel Barcelona City Hotel, Barcelona, Spain, ISBN: 978-1-922069-60-3
Figure 5
Eigenvalues
Function
Eigenvalue
% of Variance
Cumulative %
Canonical
Correlation
1
.163a
50.6
50.6
.374
2
.104a
32.3
82.9
.307
3
.055a
17.1
100.0
.228
b. First 3 canonical discriminant functions were used in the analysis
Wilks' Lambda
Test of Function(s)
Wilks' Lambda
Chi-square
df
Sig.
1 through 3
.739
41.475
30
.079
2 through 3
.859
20.832
18
.288
3
.948
7.311
8
.503
Proceedings of 28th International Business Research Conference
8 - 9 September 2014, Novotel Barcelona City Hotel, Barcelona, Spain, ISBN: 978-1-922069-60-3
Standardized Canonical Discriminant Function
Coefficients
Figure 6:
customer service
convenience
retailers in-depth info
less cheating
customers satisfaction
product delivery
competitive pricing
payment security
reduced purchase related costs
ease of ordering online
Figure 7 :
Function
1
.375
.412
-.621
.258
-.239
.025
-.284
.055
.342
-.191
Structure Matrix
Function
1
retailers indepth info
-.586*
customer service
.394*
reduced purchase related
.317*
costs
payment security
.065
competitive pricing
-.260
less cheating
.256
product delivery
-.005
ease of ordering online
-.152
customers satisfaction
-.208
convenience
.382
Pooled within-groups correlations between discriminating
variables and standardized canonical discriminant functions,
Variables ordered by absolute size of correlation within function
Proceedings of 28th International Business Research Conference
8 - 9 September 2014, Novotel Barcelona City Hotel, Barcelona, Spain, ISBN: 978-1-922069-60-3
`Factors Affecting Online Purchasing Patterns of Consumers`
Questionnaire
Online purchasing: To shop for products / services online (over Internet) in Pakistan from either
National or International Brands websites.
1. In your view how many times have you bought any product/service online during last one
year?_____________
2. What is the approximate amount you spent on online shopping in the last one
year?_______________
3. What is your Age (in years):
4. Gender :
_____________________________
Male
female
5. Your Marital status is: Single
Married
Divorced
Widowed
6. Number of years of formal education (in years):_______________________________
7. Kindly mention the medium of your early education: English Medium
Urdu Medium
8. Would you identify your ethnicity as: Punjabi
Non- Punjabi
Would you categorize yourself as :
o Self employed/business owner
o Working for some Organization
o Not Working/ student
9. If you circled option (b) above then: Public Sector(Govt Organization)
Private Sector
10. Kindly state your profession:
_______________________________
(e.g Banker, teacher, engineer etc etc)
11. Monthly income / house hold income: _______________________________
13. Do you own a credit card / Supplementary card/Debit card:
Yes
No
14. Do you have availability of Internet connection at home
yes
No
15. Do you have availability of Internet connection at Work
Yes
No
16. Do you have availability of Internet connection on your mobile phone?
Yes
No
17. You are more likely to buy products /services online over:
Desktops/Laptops
mobile phones
other gadgets
18. How much time on average you spend online (on the web) in a day:
___________________________
19. Kindly highlight your current residential location:
DHA
specify
Gulberg
Cantt
Model Town
Inner city
other
20.
You like to take your family members (such as kids) along with you for shopping to the
market/mall:
Yes
No
21.
Are you mobile (have a vehicle):
Yes
No
22.
Do you have a physical disability which makes movement difficult for you: Yes
No
Proceedings of 28th International Business Research Conference
8 - 9 September 2014, Novotel Barcelona City Hotel, Barcelona, Spain, ISBN: 978-1-922069-60-3
23.
Is your family culture Conservative in a way that , going to the market/mall is not looked upon
favorably:
Yes
24.
No
Are you the sole bread winner in the family:
Yes
No
25.
do you consider yourself from a family which has 2 incomes (such as both husband & wife
working)?
Yes
No
26.
do you consider yourself a person who is mostly glued to a screen (Tv, computer, mobile
phone)
yes
No
27.
Do you prefer International/foreign Brands over Local brands?
28.
do you often travel abroad?
Yes
No
29.
Have you ever travelled abroad?
Yes
No
Yes
No
30.
do you believe that in future more & more goods & services would be bought online due to the
advances in ICT(Information Communication Technology)?
Yes
NO
31.
do you feel its only products (but not the services) which should bebought online?
No
Yes
32.
do you feel it is only the products/svices which are not available in the local markets that
should be bought online?
Yes
No
33.
Are you in a situation which restricts you from going to the market & shoppig? Yes
34.
Shopping online earns me bonus points on my credit card which can later be used for buying
stuff from a certain specified outlet?
Yes
No
35.
I live in a locality which doesn’t have good shopping malls, and transportation cost of going to
good markets/malls is too high?
Yes
No
36.
All/most of my friends think it is cool to buy stuff online?
37.
you would classify yourself as :
Upper class
Upper class
38.
Middle Class
Yes
No
lower middle class
Lower class
you would classify, with respect to you general outlook on life, yourself as:
Liberal
Conservative
39.
You consider your lifestyle as:
40.
you consider your self in terms of your religions orientation as :
Devotedly religious
41.
No
Westernized
Eastern
Religious
Not very Religious
Do you believe it is too time consuming to deal with traffic/s to reach mall/market?
No
Yes
42.
your job tyiming/school hurs are such that you are not free at the timings when markets/mall
are open.
Yes
No
43.
do you believe that crowd in the markets/malls is not very civilized?
Yes
No
Proceedings of 28th International Business Research Conference
8 - 9 September 2014, Novotel Barcelona City Hotel, Barcelona, Spain, ISBN: 978-1-922069-60-3
44
do you believe that shopkeepers/sales persons in shops/stores are aggressive in their selling
approaches; and that makes you irritated and uncomfortable?
Yes
45.
No
Shopkeepers/Sales persons in shops/stores usually lies and cheat the customers?
Yes
No
46.
What are the types of products you have bought online in Pakistan / or you intend to buy
online? (number them according to your Priorities e.g1, being top priority-5 being lowest on priority
list)
Books
Clothing/accessories/shoes
Airline tickets
Electronic equipment
Tours/hotel reservations
Others: Please Specify: _________________________________________
47.
What are the names of trusted websites from which you bought stuff or in future you intend to
buy?(you may write more than one)
______________________________________________________________________
48.
How many times have you paid cash on delivery on a purchase you made online?
____________________
Note: - 1-Highly Disagree: 2-Disagree; 3-Neutral(neither agree nor disagree); 4-Agree; 5-Strongly Agree
For Online Purchasers :
To what degree do you agree or disagree with the following
1.
The Online web retailers provide an in-depth information about products/services.
1 2 3 4 5
2.
It is quick and easy to complete a transaction through online shopping.
1 2 3 4
5
3.
Online shopping websites have better collection and variety than to shop in markets.
1 2 3 4
5
4.
Online shopping takes less time than shopping in a makret.
1 2 3 4
5
5.
6.
7.
1 2 3 4
5
1 2 3 4
5
8.
Online shopping has competitive prices.
Online shopping offers better discounts.
I feel comfortable while surfing the internet for shopping online than going shop to shop in a
market.
The products/services on the websites were of good quality at the arrival.
1 2 3 4
5
9.
10.
11.
12.
One gets whatever he/she orders through online shopping, that is less cheating
The product is delivered on time as promised by the website retailer.
The company is willing and ready to respond to customer queries & questions.
Online shopping is secure as compared to walking in a market
1
1
1
1
4
4
4
4
5
5
5
5
13.
14.
1 2 3 4
1 2 3 4
5
5
15.
Online shopping maintains privacy, whereas shopping in a market is in view of public
I feel payment on delivery is better than using credit card for payment of orders I place
online.
I feel my credit card information is not secure if given to a website while shopping online
1 2 3 4
5
16.
Inquiries are answered promptly during online transaction.
1 2 3 4
5
18.
Online websites have better understanding of customer needs.
1 2 3 4
5
19.
Satisfaction of buying products/services online is Higher than shopping in a market
1 2 3 4
5
20.
I would like to buy more products/services Online in future.
1 2 3 4
5
21.
I like to buy International brands more than local Brands.
1 2 3 4
5
22
Online shopping is more convenient because of its 24 hours accessibility.
1 2 3 4
5
23
Online shopping offers Easy payment procedures.
1 2 3 4
5
2
2
2
2
3
3
3
3
Proceedings of 28th International Business Research Conference
8 - 9 September 2014, Novotel Barcelona City Hotel, Barcelona, Spain, ISBN: 978-1-922069-60-3
24.
Online shopping provides Ease of Comparison of prices.
1 2 3 4
5
25.
It is easier to place orders online.
1 2 3 4
5
26.
It is important for me to buy products & services from well known web retailers.
1 2 3 4
5
27.
Internet offers reduced Purchase related costs.
1 2 3 4
5
28.
While doing online shopping, I don’t have to deal with the sweet tongue sales persons
1 2 3 4
5
29.
Shopping online allows me to make more thought at choices unemotionally as compared to
shopping in a market/mall.
Online shopping saves me from the hassle of carrying cash with me from shop to shop.
1 2 3 4
5
1 2 3 4
5
30.