Page 1 of 10
Archives of Business Research – Vol. 9, No. 6
Publication Date: June 25, 2021
DOI:10.14738/abr.96.10348. Pathmananathan, P. R., Aseh, K., & Kenny, K. (2021). An Analysis on Effect of Gender Towards Computer Literacy & E-Commerce.
Archives of Business Research, 9(6). 118-127.
Services for Science and Education – United Kingdom
An Analysis on Effect of Gender Towards Computer Literacy & E- Commerce
P. Ravindran Pathmananathan
Unies Group
Khairi Aseh
Unies Group
Kamal Kenny
Unies Group
ABSTRACT
For its own development and governance, the Internet created a ground-breaking
open model that involved all stakeholders. In an enormously connected world,
Generation Y has been identified as the main consumer group that will bring change
to the internet platform.. The aim of this study is to analyze the attitude and the
Internet usage among the generation. This study was conducted using a
questionnaire that was completed by 432 working professionals in the Kuala
Lumpur Federal Territory and Selangor State, specifically MSC (Multimedia Super
Corridor). It can be concluded that determinants such as gender and computer
literacy influences internet moderators. in addition, as a moderator, the association
between gender and computer literacy is imperative.
Keywords: Internet, Generation Y, gender, computer literacy, MSC, Kuala Lumpur,
Selangor
INTRODUCTION
In the last two decades, a growing pattern of internet use by both organisations and individuals
has had a significant effect on our understanding of the world as a global village, by reducing
spatial separation between regions and allowing more free and rapid information sharing
worldwide. The majority of the world's population now lives and works in a network society
(Castells, 2000). Globalization has influenced nearly every aspect of industries in the market.
The internet is now widely recognised as one of the most critical aspects of business
development and has become an invaluable resource.
Globalization has had a significant impact on almost every area of global society, including
trade, education, healthcare, entertainment, and social interactions. The internet is now widely
acknowledged as one of the most important facets of business growth and has proven to be a
priceless resource. Vendors and operators later entered the open protocol creation process as
the Internet became commercialised, helping to usher in an unparalleled period of growth and
innovation (Oreku & Mtenzi, 2013).
Page 2 of 10
119
Pathmananathan, P. R., Aseh, K., & Kenny, K. (2021). An Analysis on Effect of Gender Towards Computer Literacy & E-Commerce. Archives of Business
Research, 9(6). 118-127.
URL: http://dx.doi.org/10.14738/abr.96.10348
Research Objective
This objective of the study is to analyze the attitude and the Internet usage among the
generation. The research objectives are as follows:
1. To identify the relationship between gender and attitude among internet users in
generation Y
2. To investigate the moderating effect of gender towards attitude in the use of internet
and e-commerce
LITERATURE REVIEW
Gen Y
According to Meier, Austin and crooker (2010), characterized generation Y is a confident
generation, independent and goal oriented. Even though the technology advances was invented
prior to generation Y born, generation Y was born into technology, and surprisingly the member
of generation Y well known as technology savvy. They usually know more than their parents or
even their teachers. Generation Y has grown up in an information age where information is
quickly communicated to everyone.
Generation Y, unlike generation X, is technologically savvy, and is the first generation to have
grown up using the internet for email, instant messaging (IM), and mobile phones (Reisenwitz
& Iyer, 2009).Furthermore, generation Y is known as the multimedia and multi-tasking
generation, with greater ease than previous generations and a full understanding of how to
work, solve, and learn technology in less time (Auby, 2008).Generation Y is known for being the
first generation to have a high internet usage rate and a television consumption rate that
exceeds that of previous generations (Barnikel, 2005).
Attitude towards e-commerce
The growth of Internet penetration in Malaysia has resulted in a new phenomenon: consumers'
increasing interest in online shopping. In Malaysia, online shopping is becoming increasingly
popular and is rapidly expanding. According to a new report by ACNielsen and Paypal
(Marketing Interative.com, 2011), online purchases in Malaysia totaled RM1.8 billion in 2011,
with an estimated 1.1 million online shoppers.
Customers' access to information has increased thanks to technological advancements in print,
broadcast, and electronic media, which make up the Internet. The Internet has become a
popular platform for companies and service providers to communicate information and deliver
goods and services to customers. According to Turban, Lee, King, Liang, and Turban (2009), the
Internet is a valuable tool for disseminating knowledge to consumers since it is versatile,
accessible, informal, and interactive. With the Internet, consumers can receive the most up-to- date information quickly, 24 hours a day, seven days a week, regardless of their geographic
location.
Gen Y and Consumer Behaviour
Generation Y is known for being technologically savvy (Ang, Leong, & Lee, 2009; Kumar & Lim,
2008; Martin, 2005) and highly reliant on complex technology (Evelyn, Eva & Robin,
2011).Generation Y is an avid Internet user who is open to emerging technology and has the
potential to establish and maintain close relationships with others via the Internet (Kumar &
Lim, 2008; Syrett & Lammiman, 2004). According to Retail Research (2012), Generation Y has
Page 3 of 10
120
Archives of Business Research (ABR) Vol. 9, Issue 6, June-2021
Services for Science and Education – United Kingdom
a high purchasing power of nearly 200 billion dollars per year. When it comes to the factors
that influence their buying decisions, Generation Y prioritises product value before purchasing
any good or service from any seller (An Oracle white paper, 2009).This generation will not be
concerned about debt and will simply spend when they have money (Aquino, 2012).
METHODOLOGY
A total of only 432 set of questionnaires collected out of 450 set were distributed In the initial
stage the researcher obtains several procedures to get legal permissions from 10 IT companies
in the Kuala Lumpur and Selangor state. The researcher is not allowed to circulate the
questionnaire by himself. As such, the human resource and general affair department circulated
the questionnaire to respective respondent in particular companies.
RESULT
Demographic Profile of Respondent
Demographic Categories Total Percentage (%)
Gender Male
Female
208
192
52
48
Age 25 and under
26-33
34-40 years
296
80
52
74
20
6
Education High school or equivalent
Diploma
Bachelor Degree
Master Degree
Doctoral Degree
48
28
248
72
4
12
7
62
18
1
Income 0 – MYR 2000
MYR 2001- MYR 4000
MYR 4001- MYR 6000
216
132
52
54
33
13
Frequency using
internet
Several times a day
About once a day
Every few days
380
12
8
95
3
2
Wireless utilization Using wireless
Don’t use wireless
388
12
97
3
Descriptive Statistics
N Minimum Maximum Mean Std. Deviation
AI 400 3.00 7.00 5.0413 .86712
CL 400 2.83 7.00 4.9151 .69533
Ecomm 400 3.24 6.15 4.6997 .64516
Valid N (listwise)
400
Page 4 of 10
121
Pathmananathan, P. R., Aseh, K., & Kenny, K. (2021). An Analysis on Effect of Gender Towards Computer Literacy & E-Commerce. Archives of Business
Research, 9(6). 118-127.
URL: http://dx.doi.org/10.14738/abr.96.10348
Model Summary Gender and Attitude towards Internet
Model Summaryb
Model R R Square Adjusted R
Square
Std. Error of the
Estimate
1 .5772a .333 .272 .71279
a. Predictors: (Constant), Gender
b. Dependent Variable: AI
The R value is 0.5772, and it is indicating positive value, therefore the relationship between two
variables is positive relationship.
ANOVA Gender and Attitude towards Internet
ANOVAa
Model Sum of
Squares
df Mean Square F Sig.
1
Regression .242 1 .242 .3221 .001b
Residual 299.764 398 .753
Total 300.007 399
a. Dependent Variable: AI
b. Predictors: (Constant), Gender
The result shows that there is a significant relationship between gender and attitude towards
internet with prediction equation (F = 0.3221, p < 0.05).
Coefficient of Gender and Attitude towards Internet
Coefficientsa
Model Unstandardized Coefficients Standardized
Coefficients
t Sig.
B Std. Error Beta
1 (Constant) 5.114 .136 37.695 .000
Gender .495 .107 .412 3.160 .001
a. Dependent Variable: AI
The result is positive, significant relationship between gender and attitude towards internet.
Page 5 of 10
122
Archives of Business Research (ABR) Vol. 9, Issue 6, June-2021
Services for Science and Education – United Kingdom
Model Summary Gender Moderate Attitude towards Internet and E-commerce
Model Summaryc
Model R R Square Adjusted R
Square
Std. Error of the
Estimate
1 .3111a .097 .095 .61384
2 .5201b .270 .267 .55251
a. Predictors: (Constant), Gender
b. Predictors: (Constant), Gender, AI
c. Dependent Variable: Ecomm
R value in the model 1 scores 0.3111 and 0.5201 as in the model 2, it means the relationship
between variables are positive.
ANOVA Computer Literacy Moderate Attitude towards Internet and E-commerce
ANOVAa
Model Sum of Squares df Mean Square F Sig.
1
Regression
16.112 1 16.112 42.764 .000b
Residual 149.966 398 .377
Total 166.078 399
2
Regression
44.888 2 22.444 73.525 .000c
Residual 121.190 397 .305
Total 166.078 399
a. Dependent Variable: Ecomm
b. Predictors: (Constant), Gender
c. Predictors: (Constant), Gender, AI
The result indicated there is a significant relationship gender moderating the relationship
between attitude towards internet and e-commerce with prediction equation (F = 42.764, p <
0.05) & (F 73.525, p < 0.05).
Coefficient of Gender Moderate Attitude towards Internet and E-commerce
Coefficientsa
Model Unstandardized Coefficients Standardized
Coefficients
t Sig.
B Std. Error Beta
1 (Constant) 5.294 .096 55.171 .000
Gender .402 .061 .3110 6.539 .000
2
(Constant) 3.710 .185 20.091 .000
Gender .386 .055 .301 6.986 .000
AI .310 .032 .416 9.709 .000
a. Dependent Variable: Ecomm
Page 6 of 10
123
Pathmananathan, P. R., Aseh, K., & Kenny, K. (2021). An Analysis on Effect of Gender Towards Computer Literacy & E-Commerce. Archives of Business
Research, 9(6). 118-127.
URL: http://dx.doi.org/10.14738/abr.96.10348
The result shows a significant relation because gender and e-commerce (β = 0.3110, p <0.05)
and gender moderate attitude towards internet and e-commerce (β = 0.301, p <0.05).
DISCUSSION
According to a study of the literature, gender disparities in internet and computer use do exist
(Chiu, Lin, and Tang, 2005; Dittmar, Long, and Meek, 2004: Garbarino and Strahilevitz, 2004;
Harmon and Hill, 2003; MacGregor and Vrazalic, 2006; Teo and Lim, 1997; Yang and Lester,
2005), however, some historical gender disparities in use are closing (Ono and Savodny (a),
2003; Ono and Zavodny (b), 2005). In the mid-1990s, women were less likely to use the internet
at all; but, by 2000, this gender disparity in being online had disappeared (Ono and Zavodny
(a), 2003; Ono and Zavodny (b), 2005). Ads for e-commerce goods and services represent
women more equitably than they have in the past, perhaps as a result of changing demographics
of women's use of technology and the internet (Koernig and Granitz, 2006). Despite the fact
that the gender gap in internet use rates is narrowing, women clearly use the internet
differently and have different attitudes about information technology in general (Dittmar, et al.,
2004).
People in the technological age, such as today, are extremely reliant on the internet.
Surprisingly, it was discovered in this analysis that the digital divide still exists. Income,
educational level, class, ethnicity, gender, geographic place, and cultural differences are all
factors that contribute to the disparity (Papastergiou & Solomonidou, 2005).Since male and
female socioeconomic status vary on average, a gender difference in internet adoption can
occur. This will affect their computer and internet usage (Bimber, 2000; Ono, 2003). Males, on
average, spend more time on the internet than females (The Broadband Comission Working
Group on Broadband & Gender, 2013).In addition, Ford and Miller (1996) found that women
experienced higher levels of disorientation and disenchantment with internet use than men. In
comparison to men, women spent less time online, spent less time surfing digitally, and used
the internet for a narrower reason (Tsai & Lin, 2007).
As a result of the previous theory, a gender difference exists, which influences their attitudes
toward the internet. As a result, gender moderates attitudes toward the internet and e- commerce. Previous study backs up this conclusion. Many researchers believe that men and
women interpret knowledge differently. The majority of men and women consider stimuli in
the form of graphics or text in their consumption. In addition, women are more likely to respond
to imagery stimuli, while men are more likely to respond to text. Because of this, moderating
roles for attitudes toward the internet and e-commerce might be essential (Holbrook, 1986).
The impact of gender on e-commerce decision-making has been investigated in relation to the
adoption of emerging information technologies. The more optimistic one's attitude toward the
internet, the more exchanges and positive one's attitude toward online shopping (Hernandez,
Jimenez, & Martn, 2009). In conclusion, it was discovered that gender influences consumer
attitudes toward the internet and e-commerce.
CONCLUSION
Gender and computer literacy are two other variables that influence people's attitudes toward
the internet. In this research, factors such as gender and computer literacy play a significant
role as internet moderators. Furthermore, as a moderator, the relationship between gender and
computer literacy is highly important.
Page 7 of 10
124
Archives of Business Research (ABR) Vol. 9, Issue 6, June-2021
Services for Science and Education – United Kingdom
References
Al-Hussaini, S. H., Turi, J. A., Altamimi, A. N. A., Khan, M. A., & Ahmad, M. (2019). Impact of talent management
strategies on employee performance behaviour with the mediating role of talent management outputs. Archives
of Business Research, 7(3).
AC Nielsen. (2006). Baby Boomer Segmentation: Eight Is Not Enough. Schaumburg: AC Nielsen.
Agarwal, R., & Prasad, J. (1999). Are Individual Differences Germane to the Acceptance of New Information
Technologies? Decision Sciences, 30 (2), 361-391.
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50 (2).
Armour, S. (2005, November 7). Generation Y. They arrive in the workplace with a new attitude. Retrieved March
2014, 25, from USA Today: http://usatoday30.usatoday.com/educate/college/careers/Hot/11-7-05b.htm
Auby, K. (2008, August 25). A Boomer's Guide to Communicating with Gen X and Gen Y. Retrieved March 8, 2014,
from Bloomberg Busines Week: http://www.businessweek.com/stories/2008-08-13/a-boomers-guide-to- communicating-with-gen-x-and-gen-y
Ayupp, K., Ling, L. N., & Tudin, A. (2013). An Analysis of Luxury Products Purchasing Behavior of Malaysian
University Students. Asian Journal of Social Sciences and Humanities, 2 (4), 219-227.
Barnikel, M. (2005). Generation Y Media Habits Show Tide is Turning in Favour of Internet. Asia's Media &
Marketing , 12.
Bernstein, L., Alexander, D., & Alexander, B. (2006, October 29). Generations: Harnessing the potential of the
multigenerational worliforce. Retrieved March 25, 2014, from
http://www.visionpoint.com/assets/artic1es/generations%20perspective%20012506.pdf
Biggs, S. (2007). Thinking about Generations: Conceptual Positions. Journal of Social Issues, 63 (4), 695-711.
Bimber, B. (2000). Measuring the Gender Gap on the Internet. Social Science Quarterly, 81 (3), 868.
Blakewell, C., & Mitchell, V. (2003). Gen Y female consumer decision-making styles. International Journal of Retail
and Distribution Management, 31 (2), 95-106.
Borges, N. J., Manuel, R. S., Elam, C. L., & Jones, B. J. (2006). Comparing Millenial and Generation X Medical
Students at One Medical School. Academic Medicine, 81 (6), 571-576.
Brafton Editorial. (2012, February 22). Gen Y spending more than others in ecommerce. Retrieved March 18, 2014,
from Brafton: http://www.brafton.com/news/gen-y-spending-more-than-others-in-ecommerce
Calder, B. J., & Ross, M. (1973). Attitudes and behavior. New York: General Learning Press.
Campbell, K. (2001). Seven steps to success: creating a perfect e-commerce system. Journal of convergence, 62
(2).
Castells, M. (2000). The rise of network society. Oxford: Wiley Blackwell.
Chan, B., & Al-Hawamdeh, S. (2002). The development of e-commerce in Singapore: The impact of government
initiatives. Business Process Management Journal, 8 (3), 278-288.
Chang, S.-L., Shieh, R. S., Liu, E. Z.-F., & Yu, P.-T. (2012). Factors Influencing Women Attitude Toward Computers
In A Computer Literacy Program. The Turkish Online Journal of Educational Technology, 11 (4), 177-187.
Chiu, Y. B. (2005). Gender differs: assessing a model of online purchase intentions in e-tail service. International
Journal of Service Industry Management, 16 (5), 416-435.
Chou, J.-R., & Shieh, C.-J. (2011). The Digital Divide in Taiwanese Unemployed Adult. Scientific Research and
Essays, 6 (7).
Conner, M., & Abraham, C. (2001). Conscientiousness and the theory of planned behavior: Toward a more
complete model of the antecedents of intentions and behavior. Personality and Social Psychology Bulletin .
Crisp, C. B., Jarvenpaa, S. L., & Todd, P. A. (2007). Individual Differences and Internet Shopping Attitude and
Intentions. Retrieved 2 22, 2014, from http://www.informationr.net/ir/12-2/Crisp.html
Page 8 of 10
125
Pathmananathan, P. R., Aseh, K., & Kenny, K. (2021). An Analysis on Effect of Gender Towards Computer Literacy & E-Commerce. Archives of Business
Research, 9(6). 118-127.
URL: http://dx.doi.org/10.14738/abr.96.10348
eMarketer. (2013, May 21). How Digital Behavior Differs Among Millennials, Gen Xers and Boomers. Retrieved
March 19, 2014, from eMarketer: http://www.emarketer.com/Article/How-Digital-Behavior-Differs-Among- Millennials-Gen-Xers-Boomers/1009748
Ethics Resource Center. (2010). Millenials, Generation X and Boomer. Arlington: ERC.
Fah, L. Y., & Hoon, K. C. (2009). Introduction to statistical analysis in social sciences research. Selangor D.E: Venton.
Fishbein, M., & Ajzen, I. (1975). Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research.
New York: Addison-Wesley.
Ford, N., & Miller, D. (1996). Gender differences in Internet perceptions and use. ASLIB Proceeding. London.
Gibbs, S. (2008). Internet use equals computer literacy? Proceedings ascilite . Melbourne.
Grasse, N. (2000). For Teens Dubbed Generation Y, Online Shopping Is as Common as a Can of Coke. Internet
Retailer .
Hawkins, D., & Mothersbaugh, D. (2010). Consumer Behavior: Building Marketing Strategy. Boston: Mc Graw-Hill.
Hawkins, J. (1985). Computers and girls: Rethinking the issues. Journal of sex roles, 13 (3-4), 165-180.
Hernandez, B., Jimenez, J., & Martı ́n, J. (2009). Age, gender and income: do they really moderate online shopping
behavior. Online Information Review, 35 (1), 113-133.
Holley, J. (2008). Generation Y: Understanding the Trend and Planning for the Impact. Generation Y:
Understanding the Trend and Planning for the Impact.
Intenational Data Corporation. (2007). Malaysia Internet and e-commerce report. Kuala Lumpur.
Jackson, B. H. (2011). Baby Boomers are Closing the Digital Divide. Washington D.C.: George Washington
University Press.
Jusoh, Z. M., & Ling, G. H. (2012). Factor Influencing Consumers' Attitude Towards E-commerce. International
Journal of Humanities and Social, 2 (4), 223-230.
Kaifi, B. A., Naefi, W. A., Khanfar, N. M., & Kaifi, M. M. (2012). A Multi-Generational Workforce: Managing and
Understanding Millenials. International Journal of Business and Management, 7 (24).
Behavior on the Internet. Journal of Interactive Marketing, 14 (1), 15-29.
Loudon, D. L., & Bitta, D. (1993). Consumer behavior: Concepts and applications. New York: McGraw-Hill.
Luan, W. S., Fung, N. S., & Atan, H. (2008). Gender Differences in the Usage and Attitudes toward the Internet
among Student. American Journal of Applied Sciences, 10 (2).
Malaysian Communication and Multimedia Corporation. (2005). Household use of the internet survey 2005.
Cyberjaya: SKMM.
Mansoori, S., Liat, C. B., & Shan, L. H. (2012). A Study Of E-Shopping Intention In Malaysia: The Influence Of
Generation X & Y. Australian Journal of Basic and Applied Sciences, 6 (8), 28.
Meier, J., Austin, S. F., & Crocker, M. (2010). Generation Y in the Workforce: Managerial Challenge. The Journal of
Human Resource and Adult Learning, 6 (1), 68.
Mhatre, K. H., & Conger, J. A. (2011). Bridging The Gap Between Generation X and Generation Y. Journal of
Leadership Studies, 5 (3).
Musings, M. (2007, December 6). Digital natives, digital imrnigrants...what about digital Pilgrims? Retrieved
March 20, 2014, from Computerworld Blogs:
http://blogs.computerworld.com/digital_natives_digital_immigrants_what_about_digital_ pilgrims
NaDesh, F. D. (2008). Growing up digital: Gen Y implications for organizations. Pepperdine University.
National Australia Bank. (2013). Online Retail Sales Index. Melbourne: National Australia Bank.
National Research Council. (1990). Being Fluent with Information Technology. Washington, D.C.: National
Academy Press.
Page 9 of 10
126
Archives of Business Research (ABR) Vol. 9, Issue 6, June-2021
Services for Science and Education – United Kingdom
Nielsen Global. (2010). Trends in online shopping. New York.
Norman, K. (2008). Cyberpsychology, an Introduction to Human-Computer Interaction. Cambridge: Cambridge
University Press.
Ono, H. (2003). Gender and the Internet. Social Science Quarterly, 84 (1), 111-121.
Oreku, G. S., & Mtenzi, F. J. (2013). A Viewpoint of Tanzania E-Commerce and Implementation Barriers. ComSIS .
PacNet. (2013, November 12). Baby boomers get comfortable with e-commerce. Retrieved March 25, 2014, from
PacNet Services Ltd.: http://www.pacnetservices.com/index.php/news/read/baby-boomers-get-comfortable- with-e-commerce-534353/
Papastergiou, M., & Solomonidou, C. (2005). Gender issues in Internet access and favourite Internet activities
among Greek high school pupils inside and outside school. Computers & Education, 44 (4), 377-393.
Parahoo, K. (1997). Nursing Research: Principles, Process, and Issue. New York: Palgrave Publications.
Prensky, M. (2001). Digital native, digital immigrants. On the horizon, 9 (5), 1-6.
Pricewaterhouse Cooper. (2009). Malaysia's Gen Y unplugged. Kuala Lumpur: Pricewaterhouse Cooper.
Rafi Nachmias, D. M., & Shemla, A. (2001). Information and Communication Technologies Usage by Medical
Student. Education and Information Technologies .
Rakow, L. F. (1988). Gendered technology, gendered practice. Critical Studies in Mass Communication, 5 (1), 57-
70.
Ratchford, B., Talukdar, D., & Lee, M.-S. (2001). A model of consumer choice of the internet as information source.
International Journal of Electronic Commerce, 5 (3), 7-21.
Reisenwitz, T. H., & Iyer, R. (2009). Differences in Generation X & Generation Y: Implication For The Organization
& Marketers. Marketing Management Journal, 19 (2), 91.
Richard C. Sherman, C. E., & Klausner, J. (2000). The Internet Gender Gap Among College Students: Forgotten But
Not Gone? CyberPsychology & Behavior, 3 (4), 885-894.
Roscoe, J. (1975). Fundamaental Research Statistics for The Behavioral Science. New York: Rinehart and Winston.
Sam, T. L., & Eam, L. H. (2011). Estimating Determinants of B2B E-commerce Adoption Among SME. International
Journal of Business and Society, 12 (1).
Santoso, G. (2005). Fundamental, Metodologi Penelitian Kuantitatif dan Kualitatif. Jakarta: Prestasi Pustaka.
Sekaran, U. (2003). Research Methods for Business: A Skill Building Approach. John Wiley & Sons, Incorporated.
Shelly, G. B., Cashman, T. J., & Vermaat, M. E. (2008). Discovering computers. Boston: Thomson Course
Technology.
Sherman, R., End, C., Kraan, E., Cole, A., Campbell, J., Birchmeier, Z., et al. (2004). The Internet Gender Gap Among
College Students: Forgotten But Not Gone? CyberPsychology & Behavior .
Swanson, E. (1974). Management Information System: Appreciation and Involvement. Management Science, 21
(2), 178-188.
Swinyard, W. R., & Smith, S. M. (2003). Why people (don't) shop online: A lifestyle study of the internet
consumer. Psychology & Marketing, 20 (7), 567-597.
The Broadband Comission Working Group on Broadband & Gender. (2013). Doubling Digital Opportunities:
Enhancing The Inclusion of Women & Girls In The Information Society. New York: UNDP.
Thong, J. Y., Hong, W., & Tam, K. (2002). Understanding user acceptance of digital libraries: What are the roles of
interface. International Journal of Human-Computer Studies, 57 (3), 215-242.
Tsai, C.-C., & Lin, S. (2007). Developing an Internet Attitude Scale for High School Student. Computers Education,
37 (1), 41-51.
Page 10 of 10
127
Pathmananathan, P. R., Aseh, K., & Kenny, K. (2021). An Analysis on Effect of Gender Towards Computer Literacy & E-Commerce. Archives of Business
Research, 9(6). 118-127.
URL: http://dx.doi.org/10.14738/abr.96.10348
Yang, K. (2005). Exploring factors affecting the adoption of mobile commerce in Singapore. Telematics and
Informatics, 22 (3), 257-277.