A Refereed Monthly International Journal of Management
A Model of Factors Affecting Adoptions of Mobile Services in India
Author
|
Sorabh Puri
Research Scholar
Amity Business School
Amity University Uttar Pradesh
Noida, India
E-mail:- puri.sorabh@gmail.com
|
R.S. Rai
Professor- Decision Sciences
Amity Business School & Deputy Director- Research
Planning & Statistical Services
Amity University, India, Noida UP
E-mail:- rsrai@amity.edu
|
Karunesh Saxena
Professor
Faculty of Management Studies
Mohanlal Sukhadia University
Udaipur, India
E-mail:- karuneshsaxena@gmail.com
|
Abstract
Fast-paced economic development, ever-growing population, rises in per capita income,
better and cheaper communicating connectivity had made India a highly competitive
market for telecom companies. Technological development and government policies
have made it possible to avail mobile services in far flung regions, particularly
in rural locations of the nation. In light to the largely used mobile services across
the nation, the present study aims to understand and analyze the factors impacting
on the adoption of mobile services in India with respect to the well-known framework
of Technology Acceptance Model (TAM) for understanding the external influencing
for mobile voice services and data usage on the basis of perception of ease of use
and perceived usefulness is discussed. A survey analysis was conducted among 500
customers from Delhi NCR who have been associated with the selected telecom companies
for more than the period of 5 year. Using regression analysis, it was found that
there was much ease in using data services while for voice calling service the customers
found it simply useful. However there was a negative influence of the attitude of
customers with respect to the services provided by the telecom companies.
Keywords: Data, Voice, TAM, Ease of Use, Attitude, Telecom Companies and Regression
Analysis
Research Context
India is amongst the fastest growing economies in the world, currently ranking as
fifth largest economy (IBEF, 2018).The high growth in mobile technology sector has
contributed in making the country an attractive market for telecom companies. Currently,
India has the second largest number of mobile phone users, only next to China (Dey,
2015). The number of smart phone users is expected to reach 491 million by 2022
(eMarketer Editors, 2018). This high growth in telecom sector can be accredited
to affordable and far searching penetration of mobile services in the nation. The
main focus of the mobile service providing telecom companies is to reach out to
the customers irrespective of their geographical location (Sangwan and Pau, 2005).
However in Indian context, the complete potential of mobile services is yet to be
achieved (Venkatram and Zhu, 2012). Therefore this study aims to analyses the mobile
services adoption driving factors with respect to technological adoption model.
To do so, external factors such as, technological infrastructure, quality and availability
of support services, market structure and mechanism, cost of handsets and services
and modes of bill payments, brand reputation and flexible technology relevant to
India are evaluated in this research study.
2) Need for the study
Technological revolution through decades of mobile services has contributed in creating
potential customers wanting to adopt new technology (Hundal and Jain, 2011). The
generation of mobile phones for 2G to 3G and now 4G has seen tremendous growth in
the adoptability of mobile services (Sundar and Kanimozhi, 2017). Further, efficient
and affordable technology has made customers eager to try different telecom services.
In this context, the present research study is focused on investigating the factors
impacting on the adoption of mobile services in India. Additionally, a proper understanding
of factors impacting adoption of mobile services is useful for both telecom companies
and the customers; it provides customers personalized information for adopting any
service and gives telecom companies a possibility to be unique. Thus, a better understanding
of factors impacting mobile services adoption is significant.
3) Aim of the study
The main aim of this study is to investigate the factors influencing the adoption
of mobile services in India.
4) Literature Review
a) Factors affection adoption of mobile services in India
- Technological competence: Many studies have shown that having a
superior technological infrastructure provides telecom companies relative advantage
and is considered to have direct influence on the adoption intention towards the
mobile services. Use of standard based technology and efficient technological infrastructure
provides reliability, accuracy and security to mobile services (Kalba, 2008; Hundal
and Jain, 2011). Thus, it is a huge influencing factor behind adoption of mobile
services in India. Relative advantage over others services as well as perceived
utility of the mobile services, is a related factor to the use of superior technology
than the previous one, which influences the adoption of mobile services in India(Makhal,
2015).
- Quality and availability of support services: The impact of availability
and quality of service provided by the telecom companies both online and offline,
on the adoption of mobile services had been elucidated in many of the existing studies.
This factor is subjective to expectation of every customer, many comparisons have
been made between expectation from the services and real performances, and this
factor is considered by customers before becoming a beneficiary of the mobile service
(Hundal and Jain, 2011; Islam and Gronlud, 2011). There is also exists a link between
ease of use, customer satisfaction and quality of service provided, which is significant
for analyzing adoption of mobile services.
- Market structure and mechanism: The structure of the market and
its mechanism for any technological product are largely dependent on the government
policies, human resource availability, degree of openness towards trade, acceptance
level of existing technologies to name a few (Commin, 2004; Islam and Gronlud, 2011).
This factor is crucial for determining the speed of adoption of mobile services
in a developing country like India.
- Cost of handsets and services and Modes of bill payments: Many
of the telecom service providers offers cost and deployment benefits over the competing
companies (Kalba, 2008). The cost of the services, mobile handsets and overall usage
cost is a crucial factor for the customer and influences the adoption decision significantly.
Developing countries generally have lower-income level per person as compared to
the developed countries nations (Islam and Gronlud, 2011). Thus, the cost of mobile
services a vital factor in the decision-making process of whether or not to adopt
mobile service. In addition to this, the latest trend of digitization in the country
has shown mixed results. A section of society have adopted digitization with ease
and enthusiasm whereas, other is still far from reaping its benefits. Thus, mode
of bill payment, both online and offline availability is a considerable factor for
customers adopting any mobile service (Swaroop Debasish and Dey, 2015).
- Brand reputation, Flexible technology: As per Kalba (2008)brand
reputation is a crucial feature as it represents the social influence of the brand
and its willingness to adopt newer innovation in the technological sector. Brand
reputation can be considered analogous to social influence and customer’s perception
on the brand name, which has behavioral influence on the decision of adopting mobile
services. Telecom companies can have a unique position, if they embrace new and
flexible technologies such as Internet of things. It will provide them to support
various utilities such as licensed spectrum, better security, scalable networks
and such more(Islam and Gronlud, 2011; Allil and Khan, 2016).
b) Technology Acceptance Model (TAM)
TAM model is based theory of Reasoned Action (TRA), which was developed by Fishbein
& Ajzen in the year 1980 and are generally used to tackle key challenges related
to the field of information technology (Geroski, 1999). It also details one aspect
that determines behavioral intention of the person’s attitudes toward that behavior
as shown in Figure 1.
The first two factors are the same as Theory of Reasonable Action, the third factor
that is perceived control behavior that users perceive and which may limit their
behavior (e.g: Can I apply for the credit card and what are the requirements?).Technology
adoption is a decision taken by an individual or group to make use of the innovation
in their lives, the decision-making process is complicated and end results is the
adoption or rejection of the technology (Sangwan and Pau 2005). Many researchers
have applied TAM model for gaining better insight on technological adoption (Seneler,
Basoglu and Daim, 2008; Cowen and Kowalczyk, 2009; Makhal, 2015). Additionally,
this model had been used in many studies to understand the diffusion and acceptance
of mobile technology in a global perspective(Phan and Daim, 2011; Abu-Dalbouh, 2013;
Osman, 2013). All the crucial parameters, which are self-explanatory, of TAM model
are presented in the following block diagram depicted in figure 1.
Figure 1: The Theory of Planned Behavior (Ajzen, 1991)
Figure 2: The final version of TAM model (Venkateshand Davis, 1996)
c) Conceptual Framework
Based on the findings of the existing literature and a conceptual research model
was developed which is presented in the following figure1.
Figure 3: Conceptual framework for external factors impacting on adoption of mobile
services.
5) Research Methodology
Research methodology is a plan of action developed using scientific procedure applications
for resolving the research issue in a systematic manner (Kothari, 2004). The main
aim of the study is to understand and study the factors that are impacting the adoption
of mobile services in India. A descriptive and explanatory research approach was
conducted as per the theme undertaken. The descriptive method aided in understanding
the adoption of diffusion of mobile services and explanatory purpose had used for
testing hypothesis formed. Following this, the study used deductive research approach
that determines theory after analyzing the results of hypothesis constructed. Therefore
this approach is much more appropriate in addition to the quantitative study being
conducted.
Based on quantitative analysis, the primary data was collected from the customers
of four telecom service providers namely, Bharti, Reliance, Vodafone, Idea. This
aided the researcher in understanding the external factors impacting adoption of
mobile services. . Survey strategy was used here and 500 customers living in Delhi
NCR region of aforementioned companies, who have been associated with the company
for more than 5 years were surveyed using a well-structured close-ended questionnaire.
6) Data Analysis
a) Demographic Profile
Figure 4: Demographic Analysis
Out of 498 respondents, about 59 % were males and the rests were females. In regards
to the association with their respective companies, about 41% respondents were found
to be associated for 8-10 years. Further in terms of educational qualification,
approximately 54 % respondents were graduates. Lastly in regards to the annual income
of the respondents, 30% respondents were earning an annual income of 2 to 5 lakh
per annum followed with 18% respondents earning 10 to 12 lakh per annum. Therefore,
it can be inferred there was not much difference as to the gender of respondents
in the dataset. Majorly the respondents were highly associated with their telecom
industries and earned fair annual income.
b) General background
Next the respondents were asked on different aspects related to the services provided
by telecom services.
a) Perception on different aspects of mobile services
Figure 5: General Background
On being asked about that their telecom service provider are economical and suits
their requirement, about 87 % of the respondents supported to this, further on being
asked about facilitation of services in your day to day activities, around 60 %
respondents agreed. In context of the quality of service provided, approximately
79 % respondents were of the view that the services improved their standard and
quality of life. However about 48 % of the respondents were not able to discover
whether these telecom service providers have innovated the services. Lastly about
58 % of the respondents were of the view that mobile services have a bright future.
Therefore, it can be viewed that mostly the customers are satisfied with the services
provided by their telecom service provider but they are not sure that whether these
telecom companies have made some effort to innovate their existing services.
b) Perception on experience and satisfaction of mobile services
Figure 6: Perception on experience and satisfaction of mobile services
Next, the respondents were inquired on their experience and satisfaction of using
mobile services. About 39 % of the respondents strongly agreed with the fact that
they get satisfactory roaming services. Further about 36 % strongly agree that they
get satisfactory voice clarity. In context of the data services provided by the
telecom companies, 38% respondents strongly agreed that they are satisfied with
the speed of the internet. About 36 % respondents strongly agreed that they are
satisfied with the quality of data services. Further, about 35% respondents strongly
agreed that they are satisfied with the network quality and uninterrupted services
provided by the telecom service provider. Overall there were mixed results attained
in respect to data and voice services provided by telecom companies.
c) Inferential analysis
In order to determine factors of adopting mobile services, the TAM model encompasses
following broad factors: External factors; perceived usefulness; perceived ease
of use; attitude and behavioral intention. Following this correlation and regression
analysis were undertaken such that the dependent variable is adoption of mobile
service whereas the set of independent variables are the mean of the above mentioned
factors underlying TAM model. The proposed broad hypothesis is:
H0: There is no significant impact of factors underlying Technology Acceptance
Model on adoption of mobile services in India.
Following are the sub hypothesis based on two aspects of services provided: Data
and voice services.
a) HA: There is no significant impact of data services on adoption
of mobile services in India
b) HB: There is no significant impact of voice process on adoption
of mobile services in India.
Analysis on Data services
For the analysis on data services, half of the sample size that is 249 respondents
provided their responses.
1.6.c.1 Correlation Analysis
HA: There is no significant impact of data services on adoption of mobile services
in India
|
|
mean1(External Factors)
|
mean2 (Perceived Usefulness)
|
mean3(Perceived ease of use)
|
mean4 (Attitude)
|
mean5(Behavioral Intention)
|
|
Adoption of mobile service
|
Pearson Correlation
|
.646**
|
.780**
|
.843**
|
.578**
|
.592**
|
|
Sig. (2-tailed)
|
0
|
0
|
0
|
0
|
0
|
|
N
|
249
|
249
|
249
|
249
|
249
|
A Pearson’s correlation coefficient was used to assess the relationship of factors
underlying TAM model that is external factors, perceived usefulness, and perceived
ease of use, attitude, and behavioral intention, with adoption of mobile service
in India. It can be identified from the table above, there was quite high correlation
for all of the variables being significant at p<0.05. However the most strongly
related variables were ‘ Perceived ease of use’ (.843**) followed by application
of ‘ Perceived Usefulness’ (.780**). This means that perceived ease of usein respect
to data services have a major impact on adoption of mobile services in India. This
can be due to the fact that the technological innovation and services are much easier
to use now and much preferred among all age groups.
In this regard, the study by Lai (2017), indicated that the perceived ease of use
refers to the extent to which the users expect the target system to be effortless
when using mobile services. Further in context to perceived usefulness, the study
conducted by Talukder( 2012) reveals that perceived usefulness is one of the dominant
factors affecting the adoption of mobile service because the behavioural intention
is determined by the usefulness of a factor that is users adopt a particular innovation
due to its usefulness.
1.6.c.2 Regression Analysis
Regression analysis is undertaken including all the variables due to high and significant
correlation of independent variables with that of the dependent variable.
|
ANOVAa
|
|
Model
|
Sum of Squares
|
Df
|
Mean Square
|
F
|
Sig.
|
|
|
Regression
|
260.889
|
5
|
52.178
|
161.090
|
.000b
|
|
Residual
|
78.709
|
243
|
.324
|
|
|
|
Total
|
339.598
|
248
|
|
|
|
The model summary of the regression in the table above reflects that the hypothesis
i.e. there is no significant impact of data services on adoption of mobile services
in India is rejected since F value is significant at p<0.005. In addition the
F-value is high (161.090) so the probability for accepting alternative hypothesis
results to be quite high and hence the hypothesis is rejected.
|
Model Summary
|
|
Model
|
R
|
R Square
|
Adjusted R Square
|
Std. Error of the Estimate
|
|
1
|
.876a
|
.768
|
.763
|
.56913
|
Further R square (87.6 %) and adjusted R square (76.3%) are quite high for the model
regressed. So, this indicates that around 87 % variation is contributed by the independent
variables in the dependent variable.
|
Model
|
Unstandardized Coefficients
|
Standardized Coefficients
|
t
|
Sig.
|
|
B
|
Std. Error
|
Beta
|
|
|
(Constant)
|
.181
|
.107
|
|
1.693
|
.092
|
|
mean1(External Factors)
|
.191
|
.039
|
.192
|
4.892
|
.000
|
|
mean2(Perceived Usefulness
|
.151
|
.059
|
.158
|
2.543
|
.012
|
|
mean3(Perceived ease of use)
|
.553
|
.061
|
.577
|
9.066
|
.000
|
|
mean4(Attitude)
|
-.272
|
.083
|
-.279
|
-3.286
|
.001
|
|
mean5(Behavioral Intention)
|
.330
|
.082
|
.330
|
4.036
|
.000
|
Further the coefficient regression analysis in the table above shows that all the
variables are significant at p<0.05. However, out of all significant variables,
‘Perceived ease of use’ contributed a major change to the adoption of mobile service
in India since its standardized beta coefficient was highest of all being significant
at p<0.05. This meant that there was ease in services now provided by telecom
providers in consideration to this factor underlying TAM thereby leading to adoption
of the mobile services among consumers. In this regard, the study conducted by He,
Chen, & Kitkuakul (2018) discussed that perceived ease of use can be determined
by a particular system which does not require much effort. With reference to TAM
model, perceived ease of use was related to the use of e-commerce and search of
information thereby reflecting a significant impact on customers.
It was also seen that ‘ Attitude ’ showed a negative impact on adoption of mobile
services (-0.279) via the standardized beta coefficient, significant at p<0.05.
This meant that this factor underling TAM can depict a negative outcome on consumers
for not using the mobile services since the services of telecom providers are not
user friendly and complicated for the consumers. This results in no confidence or
favorable attitude towards with adoption of mobile services by the consumers. In
this context, the study conducted by Baile (2010) examined that attitude is a significant
factor which affects the behavior of accepting or rejecting an innovation in technology.
Also the study found that factors underlying TAM especially with regards to the
negative attitude towards technology driven systems, discourages customers to use
a particular system.
Analysis on Voice process
For the analysis on voice process, other half of the sample size that is 249 respondents
provided their responses.
1.6.c.3 Correlation Analysis
HB: There is no significant impact of voice process on adoption of mobile services
in India.
|
|
mean1(External Factors)
|
mean2 (Perceived Usefulness)
|
mean3(Perceived ease of use)
|
mean4 (Attitude)
|
mean5(Behavioral Intention)
|
|
Adoption of mobile service
|
Pearson Correlation
|
.723**
|
.864**
|
.805**
|
.628**
|
.650**
|
|
Sig. (2-tailed)
|
0
|
0
|
0
|
0
|
0
|
|
N
|
249
|
249
|
249
|
249
|
249
|
The most strongly related variables were ‘ Perceived usefulness’ (.864**) followed
by application of ‘ External factors’ (.723**). In regards to voice processes in
association to TAM, there is perceived usefulness leading to adoption of mobile
services in India. This means that the customers were much influenced by the fact
of using the voice process thereby adopting mobile services. Further the external
factors such as technological infrastructure, cost of services, bill payments also
influenced the customer’s in adoption of mobile services. In this regard, the study
of Lai (2017) viewed that perceived usefulness to the customer improves their experience
by using a particular technology. The process of social interaction and collecting
information affects user’s intention to adopt the mobile services.
1.6.c.4 Regression Analysis
Regression analysis is undertaken including all the variables due to high and significant
correlation of independent variables with that of the dependent variable.
|
ANOVAa
|
|
Model
|
Sum of Squares
|
df
|
Mean Square
|
F
|
Sig.
|
|
|
Regression
|
305.614
|
5
|
61.123
|
198.003
|
.000b
|
|
Residual
|
75.013
|
243
|
0.309
|
|
|
|
Total
|
380.627
|
248
|
|
|
|
As per the model summary given above, the hypothesis i.e. there is no significant
impact of voice process on adoption of mobile services in India, is rejected since
F value is significant at p<0.005. In addition the F-value is high (198.003)
so the probability for accepting alternative hypothesis results to be quite high.
|
Model Summary
|
|
Model
|
R
|
R Square
|
Adjusted R Square
|
Std. Error of the Estimate
|
|
|
.896a
|
0.803
|
0.799
|
0.5556
|
Further R square (80.3 %) and adjusted R square (79.9%) are quite high for the model
regressed. So, this indicates that around 80% variation is contributed by the independent
variables in the dependent variable.
|
Coefficients
|
|
Model
|
Unstandardized Coefficients
|
Standardized Coefficients
|
T
|
Sig.
|
|
B
|
Std. Error
|
Beta
|
|
|
(Constant)
|
.200
|
.100
|
|
1.995
|
.047
|
|
mean1(External Factors)
|
.210
|
.040
|
.209
|
5.238
|
.000
|
|
mean2(Perceived Usefulness
|
.557
|
.061
|
.585
|
9.115
|
.000
|
|
mean3(Perceived ease of use)
|
.126
|
.059
|
.132
|
2.147
|
.033
|
|
mean4(Attitude)
|
-.325
|
.087
|
-.336
|
-3.724
|
.000
|
|
mean5(Behavioral Intention)
|
.381
|
.087
|
.387
|
4.369
|
.000
|
The coefficient regression table above depicts that all the variables are significant
at p<0.05. However, out of all significant variables, ‘Perceived usefulness’
shared a major change to adoption of mobile service in telecom sector in India since
its standardized beta coefficient (.585)was highest of all being significant at
p<0.05. This is due the fact that the consumers are well known to the fact that
mobile services are widely used in association to voice process. In this context,
the study conducted by Naiwumbwe (2012) showed that perceived usefulness is one
of the major variables in Technology Acceptance model(TAM) with respect to calling
and its quality. This study presented the development of new system and planning
with respect to voice processes in terms of its quality. Likewise the adoption of
mobile services is also negatively influenced by the attitude of customers since
its beta coefficient is -.336, being significant at p<0.05. The customers feel
unconfident and unsatisfied with some of the voice processes services provided by
the telecom providers. This will affect their decision on adoption to mobile services.
7) Results of hypotheses
|
Hypothesis
|
Results
|
|
Null Hypothesis: There is no significant impact of factors underlying Technology
Acceptance Model on adoption of mobile services in India.
|
Rejected
|
|
HA: There is no significant impact of data services on adoption of mobile services
in India
|
Rejected
|
|
HB: There is no significant impact of voice process on adoption of mobile services
in India.
|
Rejected
|
8) Conclusion
In the past few years, the telecom industry in India is experiencing intense competition
in terms of the cost of the services, speed of data, voice clarity, network quality,
roaming services and other technological innovations. This has resulted into the
exit of various telecom companies as well. For instance Aircel left the industry
due to disruptive price war with free voice calls and cheap data offered by market
leaders like Reliance Jio (Street, 2018). Therefore there is a need for companies
to compete in terms of understanding the customer’s requirement and acting to give
maximum value to them in order to gain high reputation in the industry. Following
this, the telecom companies need a framework like Technology Acceptance Model (TAM)
to identify such requirements. This model is beneficial for identifying the customer’s
need and forecasting the application of mobile services both in terms of data services
and voice processes.
Overall the results identified via the aforementioned analysis indicate that the
customers considered usefulness and the perceived ease of using the mobile services
in adoption of any mobile service. For voice process, the adoption of mobile services
depends on the quality of network, productivity and effectiveness for the users.
Further, the services which are easy to understand and operate are preferred by
the users. However for data services, the external factors such as services related
to technological infrastructure, cost of services, bill payments etc. were quite
considered by the consumers before availing the services provided by telecom companies.
Other factors like attitude of customers depicted a negative impact on adoption
of the telecom services. This indicates that users follow an unfavorable attitude
towards the adoption of mobile services and don’t enjoy their mobile services. Therefore
the telecom sector should focus on the user’s experiences and behavior to offer
better quality of services. This can be done by regular update on feedback and suggestions
from the users.
In addition, the technological changes that are based on user’s requirement offer
advantage to the companies that in turn would be adopted by customers. The companies
use modern tools and techniques that aid in deriving transparency on the network
quality and voice clarity aspects to the users. For instance, Bharti Airtel delivers
a truly transparent system for its users. It has opened up its entire mobile network
information through a new interface which displays the coverage and strength of
network across India in addition to the development status. Also, the company has
a server based platform where users can check the network coverage in their area
(Operator et al., 2017). This develops trust among the users. Therefore, companies
need to undertake innovations in their operational process that are easy to use,
transparent and improve user’s experience.
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