Predecting consumer decisions to adopt mobile commerce

1. Predicting consumer decisions to adopt mobile commerce:
Cross country empirical examination between China and
Malaysia

2. About Author
 1. Alain Yee-Loong Chong,
The Hong Kong Polytechnic University, Hung Hum, Hong
Kong
 2. Keng-Boon Ooi
University of Tunku Abdul Rahman, Malaysia

3. Aim of this presentation
This study aims to investigate the factors that predict
consumer intention to adopt mobile-commerce.

4. INTRODUCTION
 Advancements in wireless communications have
increased the number of people using mobile devices,
and have increased the growth of mobile commerce
(m-commerce). M-commerce is a well adopted
technology in many developed countries such as
Japan, Korea and the United States, it is still at a
growing stage in many developing countries. Users
rarely use their mobile phones to purchase products or
conduct mobile banking.

5. Theoretical Framework

6. Variables
 Dependent Variable:
Consumer intention to adopt m-commerce
 Independent Variables are:
1. Trust
2. Cost
3. Social Influence
4. Variety of Services
5. Perceived Usefulness
6. Perceived Ease of Use
7. Trial-ability
 Control Variables are
1. Gender, 2.Age,3.Educational Level

7. 1. Trust IV
Trust is an important element which affects
consumer decisions to adopt technologies such
as e-commerce.

8. Cost IV

9. Social Influence IV
 The actions, reactions, and thoughts of an individual
are influenced by other people or groups.

10. Variety of Service IV
M-commerce has a great potential in its applications,
m-commerce offers various entertainment such as
allows users to use social networking tools, listen to
music or watch videos and playing mobile games.

11. Perceived usefulness
Perceived usefulness is one of the most important
variables in technology adoption. Different activities
such as internet banking, reserving tickets, playing
online games etc can be conducted through both e-
commerce and m-commerce.

12. Perceived ease-of-use
How users come to accept and use a technology.
Davis defined this as "the degree to which a person
believes that using a particular system would be free
from effort.

13. Trial-ability
 Trial-ability refers to whether users given free trials are
more likely to accept a new technology. Offering free
trials to users also means that m-commerce providers will
have to bear the initial costs.

14. Hypotheses
 H1. Trust has a significant relationship with consumer decisions to
adopt m-commerce.
 H2. Cost has a significant relationship with consumer decisions to
adopt m-commerce.
 H3. Social influence has a significant relationship with consumer
decisions to adopt m-commerce.
 H4. Variety of services has a significant relationship with consumer
decisions to adopt m-commerce.
 H5. Perceived ease of use has a significant with consumer
decisions to adopt m-commerce.
 H6. Trial-ability has a significant with consumer decisions to adopt
m-commerce.

15. Implication
1) The study shows that consumers are more concerned with
the variety of services offered by m-commerce.
2) The result shows consumers are price conscious when it
comes to m-commerce. Service providers should develop
creative promotional and pricing strategies (e.g. cost
reduction) to attract price-conscious customers.
3) This is one of the few studies to offer a comparative study
in m-commerce adoption in fast growing developing
countries.
4) This study focuses on developing countrieswhere the
mobile devices and infrastructure are quite advanced, but
the m-commerce doption remains low.

16. Limitations and future studies
1. Firstly, the study is restricted to comparing the consumers of two
countries.
2. Future studies can extend this scope to include consumers from
other countries.
3. A comparison between various developing and developed countries
will improve the generality of the model.
4. As m-commerce is relatively, this study has the intention of
measuring m-commerce adoption.
5. Future studies can consider measuring of m-commerce across time,
and investigate if the adoption factors change at various stages of
consumer diffusion of m-commerce.
6. Lastly, there is a possibility that additional adoption factors have not
been included in this model, such as self efficacy and perceived
enjoyment for example, and these can be included in future research
models.

17. Finding
 The result allows enable telecommunication and m-
commerce companies to develop strategies that are
appropriate to consumers from developing countries.
 The results show that traditional variables found in
TAM is not sufficient to predict m-commerce
adoption. Instead, m-commerce developers should
focus on cultural elements such as trust and social
influence when targeting Malaysian and Chinese
consumers