An Empirical Examination of Customer Retention in Mobile
Telecommunication Services in Australia
Hassan Shakil Bhatti, Ahmad Abareshi and Siddhi Pittayachawan
School of Business IT and Logistics, RMIT University, 445 Swanston Street, Melbourne, Australia
Keywords: Service Quality, Customer Satisfaction, Customer Retention, UTAUT2, ECT, Customer Experience.
Abstract: The service quality has an impact on customer satisfaction and retention. From Telecommunication annual
reports it has been investigated that there are service quality issues due to high complaints in Australia and it
can affect end customers and businesses (TIO, 2013, ACMA, 2013). Factors such as behavioural intention
which leads to customer intention to repurchase the service are measured through the Unified Theory of
Acceptance and Use of Technology (UTAUT2), Marketing Mix Theory and Expectation Confirmation
Theory (ECT). Similarly, researchers have studied the habit, hedonic motivation, customer satisfaction,
customer experience, marketing mix factors relationship by empirical testing. There has been very little
research in the area of customer retention in mobile telecommunication services. Drawing upon theories of
marketing mix, ECT and UTAUT2, this study aims to determine what factors affect customer retention in
mobile telecommunication services in Australia. Data gathering will be done through online surveys from
Australian consumers. Quantitative data analysis techniques, structural equation modelling (SEM) will be
used for data analysis. This study will contribute to the customer retention literature through a theoretical
framework that shows how the customer retention can be generated in mobile telecommunication services.
Additionally, this study will help businesses to have understanding of how to retain their customers which
will result in higher business revenues.
1 INTRODUCTION
The service quality has an impact on customer
satisfaction and retention. Higher complaint rates in
telecommunication annual reports (ACMA, 2013;
TIO, 2013; TIO, 2014) have revealed that there are
service quality issues in this sector in Australia. The
current complaints’ trend can affect mobile customers
and service providers’ businesses. According to
Morgan (2014) there are 16 million mobile phone
customers in Australia. According to Australian
Communication Media Authority (ACMA), mobile
users are as follow;
Table 1: Percentage of Mobile Phone Users (Morgan,
2014).
Mobile
Operators
Telstra Optus Vodafone Others
Market
Percentage
40% 24.8% 20.9% 15.3%
The Telecommunication report TIO (2010) states
that service quality of many telecommunication
operators is very poor due to high number of
complaints, bad customer experiences and customer
satisfaction issue. Service providers are doing service
upgrades and expansions in order to meet these
market challenges. Service providers need to provide
better data services and they need to upgrade
technology from 3G (3rd Generation) to 4G (4th
Generation) mobile technology for provisioning of
faster data services. During the roll-out of network
and services, lack of proper planning leads to poor
customer service to clients (Hopewell, 2014, news,
2012; Taylor, 2013). This can contribute to poor
voice and data services. TIO invoiced Telstra for
$15,273,136 during 2013 for complaint handling fees
(TIO, 2013). Moreover, BigPond was charged an
additional $3,039847 for TIO complaint handling
fees. Optus was invoiced a total of $4,084,414 in
complaint handling fees, AAPT $563,547 and iiNet
just $137,906 (TIO, 2010). Vodafone Hutchison
Australia (VHA) has reported 216,000 customers
leaving the network in the first three months of 2013
(Taylor, 2013). Similarly, Optus had 9.59 million
mobile customers in March 2014, this number
dropped by 160,000 to 9.43 million at the end of first
quarter (News, 2014).
72
Bhatti, H., Abareshi, A. and Pittayachawan, S.
An Empirical Examination of Customer Retention in Mobile Telecommunication Services in Australia.
DOI: 10.5220/0005951900720077
In Proceedings of the 13th International Joint Conference on e-Business and Telecommunications (ICETE 2016) - Volume 2: ICE-B, pages 72-77
ISBN: 978-989-758-196-0
Copyright
c
2016 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
Hence, TIO and (Australian Communication and
Media Authority) ACMA reports can help in
concluding the difference between customer
expectation and service provider performance. From
TIO and ACMA reports (ACMA, 2013; TIO, 2012;
TIO, 2013), the breakdown of most prominent
complaints are network faults including voice calls,
data and billing issues comprises of 52 percent of
complaints. The remaining 47 percent of complaints
are related to contract issues and VAS (Value added
services). The service failure in service industry is
predictable due to the human involvement in the
service delivery process, which eventually creates
vitality for service providers to obtain complaints
from angry or dissatisfied customers, in order to,
retain them by provisioning of quick recovery option
(Kaur and Sharma, 2015). In today’s cutthroat
competitive environment, negligence in customer
service or service quality can lead to business loss,
which is not affordable in terms of cost of acquiring
new customers. It is important to formulate proactive
strategies to retain customers by determining the
antecedents behind customer complaining behaviour
(Karatepe, 2006; Kaur and Sharma, 2015). This
behaviour is developed with experience and direct or
indirect interaction with service (Meyer and
Schwager, 2007). Customer experience is a term that
explains customer collective incident with service
provider and it also helps to determine the durability
of relationship of that customer with service provider
(Islam and Rima, 2013). This research study attempts
to find out the factors that have a significance
influence on customer retention in telecommunica
tion services.
The current study seeks to develop a framework
to assist business using this extended UTAUT2 model
to improve customer retention in mobile
telecommunication services.
To achieve this objective, the primary question is
formulated:
What are the key factors that influence customer
retention in mobile telecommunication services in
Australia?
Sub-questions are:
1. To what extent do these factors affect customer
retention?
2. What is the influence of age, gender and
experience as a moderating factor between
antecedents and dependent variable in the extended
Unified Theory of Acceptance and Use of
Technology model?
The next section will discuss the literature review.
2 LITERATURE REVIEW
This section reviews prior literature on customer
retention and behavioural intention. Table 2 shows a
summary of this literature review. Customer
acquisition which is acquiring a new customer is most
costly when compared to retaining existing customers
(Edward and Sahadev, 2011). Moreover, customers
can be devoted customers if companies can offer
someone who can understand their journey and needs.
The consequent increase in business revenue is
directly related to customer retention (Edward and
Sahadev, 2011; Santouridis and Trivellas, 2010).
Table 2: A Summary of Previous Literature on Customer
Retention.
Dependant
Variable
Author(s)/Year
Theory Used
Behavioural
Intention
(BI)
(Abubakar and Ahmed,
2013, Chomley, 2014, De
Canniere et al., 2009,
Escobar-Rodríguez and
Carvajal-Trujillo, 2013, Ha
and Jang, 2009, Kuo and
Yen, 2009, Lopez-Nicolas
et al., 2008, Venkatesh et
al., 2012, Wu et al., 2008)
Theory of Planned
Behaviour (TPB),
Technology
Acceptance Model
(TAM), Social
Influence, Social
Impact, Theory of
Reasoned Action
(TRA), Trust
Transference, Theory,
Unified Theory of
Acceptance and Use of
Technology (UTAUT,
UTAUT2)
Customer
Loyalty
(Chang and Chong, 2011,
Chou et al., 2014, Deng et
al., 2010, Liu, Guo et al.,
2011, Olsen, 2002, Van
Vuuren et al., 2013)
TAM, TRA, UTAUT,
Expectation
Confirmation Theory
(ECT)
Intention to
Revisit
(Venkatesh et al.
2003,Venkatesh et al. 2012,
Ghalandhari 2012, Fong
andWong 2015)
TRA, TAM, UTAUT
and UTAUT2
Customer
Retention
(Chatura and Jaideep, 2003,
Edward and Sahadev, 2011,
Kassim, 2006, Ray and
Chiagouris, 2009, Roberts-
Lombard, 2009)
TRA, TAM, Social
Influence and TPB
Continuance
Intention
(Lee, 2010, Liang et al.,
2011, Limayem et al., 2007,
Roca et al., 2006,
Vatanasombut et al., 2008,
Wangpipatwong et al.,
2008, Zhao et al., 2012,
Zhou, 2013)
TRA, TAM, TPB,
ECT and Social
Support
2.1 Customer Retention
Customer retention is discussed as the factor which
helps in maintaining the business relationship
between a supplier and a customer (Gerpott et al.,
2001). This is further discussed in different ways. The
An Empirical Examination of Customer Retention in Mobile Telecommunication Services in Australia
73
first one is argued as the customer’s extension of
contract with service provider over a period of time.
The second one is emphasized on intention of
customer to repurchase the service in future from
service provider. Moreover, it is further observed that
customer refraining from terminating or leaving the
contract also refers to customer retention (Gerpott et
al., 2001).
It has been argued by Reichheld et al., (1989) that
reducing the defection rate by 5% will generate 85%
profit. In addition to this, more loyal customers are
less likely to switch their service providers due to
billing and pricing factors. Moreover, loyal customers
or retained customers also tend to recommend the
business to other friends, family and social circle
through positive word of mouth (Reichheld et al.,
1989; Santouridis and Trivellas, 2010).
The study will focus on customer retention with
the main focus on factors influencing retention in
telecommunication industry. While the direct effect
of service quality, trust and perceived value on
customer retention has been the main focus of many
previous studies (Zhou, 2013; Zhou and Lu, 2011),
other factors such as social influence, habit, hedonic
motivation, marketing mix factors, and customer
satisfaction relationship and its effect on customer
retention has not been explored with adequate
empirical and theoretical support (Liu et al., 2011).
This study will determine the factors which can
impact the customer retention.
In different studies, relationships among
marketing mix factors, habit, switching barriers,
social influence, customer experience and
behavioural intention which lead to customer loyalty,
continuance usage and relationship commitment have
been examined (Lee et al., 2008; Yadav et al., 2016).
But less attention has been given to customer
retention in the telecommunication service industry.
There is no empirical study to date that has
investigated these factors in a single framework of
study as all the above mentioned studies investigated
relationship with customer retention in a different
framework. Therefore, very little investigation has
been done to identify factors impacting on customer
retention. This study will help to develop a
comprehensive model which will focus on technical
service quality and customer behavioural issues
which can help businesses improve customer
retention. It will also examine retention with the help
of associated factors in the context of
telecommunication mobile services in Australia.
2.2 Behavioural Intention
The main variable of concern for this study is
behavioural intention to determine customer
retention. Previous studies, such as (Abubakar and
Ahmed, 2013; Mandal and McQueen, 2012;
Venkatesh et al., 2012) determined that behavioural
intention is the most significant measure of actual
behaviour. A further study explains that increasing
customer retention, minimising the rate of customer
defections are primary keys to the capability of a
service provider to make profits (Tsai and Huang,
2007). In addition, behavioural intentions are linked
with service provider’s capability to attain new
customers. Therefore, behavioural intention plays a
vital role in customers’ decision to repurchase the
service.
3 THEORETICAL FRAMEWORK
The theoretical framework for this study is based on
the concepts of selected marketing-mix product,
place, promotion, physical evidence, process and
price along with SERVQUAL model which measures
service quality for customer experience, Unified
Theory of Technology Acceptance (UTAUT 2) and
Expectation Confirmation Theory (ECT). The
following section will discuss the detail of these
theories. The marketing mix concept is one of the
core concepts of marketing theory. McCarthy (1960)
explained the concept of basic marketing mix 4P’s
(product, price, promotion and place) in service
industry. These theories were used for the following
reasons: first, these theoretical approaches and this
model will help to investigate customer retention in
mobile telecommunication services as other studies
focus on customers’ intentions to adopt the mobile
technology such as internet, 3rd and 4th generation
mobile service. Secondly, many studies have utilised
different theoretical approaches to study consumer
attitudes in the marketing, e-commerce and e-service
contexts (Lin and Hsieh, 2011; Straub et al., 2004),
yet marketing mix and expectation confirmation
theory has yet to be used to study customer retention
in the mobile service context. These theoretical
approaches have assisted to identify eleven possible
factors and their relationships that influence customer
retention in mobile telecommunication services.
3.1 Proposed Model and Hypotheses
Based on UTAUT 2 model, marketing mix theory,
expectation confirmation theory and previous studies
ICE-B 2016 - International Conference on e-Business
74
(Venkatesh et al., 2003), the following conceptual
model is proposed. The previous studies (Anaman,
2010) developed customer experience model and
factors affecting customer experience. The
phenomenon of customer retention in light of
customer experience is not very well investigated in
recent studies (Maklan and Klaus, 2011). There is no
single framework which is used to test UTAUT with
customer retention and the factors affecting customer
retention with customer experience. Thus, in this
study age, gender and experience will act as a
moderating factor. Accordingly, this study model has
integrated these constructs along with other
constructs such as customer experience, customer
satisfaction, selected marketing mix factors such as
product price value, behavioural intention, and
UTAUT 2 model factors in order to evaluate
customer retention. The above discussion would lead
to the following conceptual framework and
hypotheses mentioned in Figure 1. There is positive
relationship between the factors is mentioned in
below Figure 1 as hypotheses.
Figure 1: Conceptual Model and Hypothesis.
4 RESEARCH METHODOLOGY
The main drive of the research follows the deductive
method of reasoning. This helps in order to validate
and cover previously agreed hypotheses on
behavioural intention that are very relevant to a
customer purchase intention. This is an essential
characteristic of the positivist paradigm. The
positivist methodology is based on experiments,
hypothesis testing, validity, verifications and
quantitative methods of study. Research questions are
derived from a literature review. The research
instrument for the instrument development process
adopts Churchill’s procedure (Churchill Jr, 1979).
The survey questions are based on existing literature
from previous studies.
This research will focus on all the impacts,
whether technical or behavioural, which can
influence customer retention. In order to achieve the
research objective, a quantitative method will be
employed by utilizing a questionnaire. In this study,
participants will be recruited from all states in
Australia by using marketing company’s databases. It
strengthens the result that can be obtained from a
certain population. The sample size for the main study
is around 2000 (Uma and Roger, 2003). The
conceptual model of this study will be tested using
structural equation modelling (SEM). The SEM
analysis will be used to test the hypothesised
relationships among the factors.
5 CONCLUSION AND FUTURE
WORK
In this study, the underline antecedents of customer
retention will be identified. These antecedents are
based on UTAUT theory, such as behavioural
intention, customer experience, customer
satisfaction, habit, hedonic motivation, social
influence, performance expectancy, effort expectancy
and marketing mix factors. The proposed framework
will be empirically tested from data collection.
Hence, after data analysis, it will be concluded how
these factors affect customer retention in mobile
telecommunication services in Australia. It will help
to decrease customer complaints and improve
customer experience by implementing the
implications derived from this study. It will lead
service providers to improve competitive advantage
and customer retention.
REFERENCES
Abubakar, F. M. and H. Ahmed (2013). The moderating
effect of technology awareness on the relationship
between UTAUT constructs and behavioral intention to
use technology: A conceptual paper. Australian Journal
of Business and Management Research 3(2) 14-23.
ACMA. (2013). Annual report 2012–13 [online]. Available
at: http://www.acma.gov.au/theACMA/annual-report-
2012--13 [Accessed 07/09/2014 2014].
Anaman, M. (2010). Toward a model of customer
experience. Brunel University, School of Information
Systems, Computing and Mathematics.
Chang, P. and H. Chong (2011). Customer satisfaction and
loyalty on service provided by malaysian
An Empirical Examination of Customer Retention in Mobile Telecommunication Services in Australia
75
telecommunication companies. Electrical Engineering
and Informatics (ICEEI), 2011 International
Conference on, IEEE.
Chatura, R. and P. Jaideep (2003). The influence of
satisfaction, trust and switching barriers on customer
retention in a continuous purchasing setting.
International Journal of Service Industry Management
14(4) 374-395.
Chomley, P. M. M. (2014). The relationship between
knowledge sharing and workplace innovation in a
transnational corporation: A behavioral Perspective.
Thesis, School of Management, College of Business
RMIT University.
Chou, P.-F., C.-S. Lu and Y.-H. Chang (2014). Effects of
service quality and customer satisfaction on customer
loyalty in high-speed rail services in Taiwan.
Churchill Jr, G. A. (1979). A paradigm for developing
better measures of marketing constructs. Journal of
marketing research 64-73.
De Canniere, M. H., P. De Pelsmacker and M. Geuens
(2009). Relationship Quality and the Theory of Planned
Behavior models of behavioral intentions and purchase
behavior. Journal of business research 62(1) 82-92.
Deng, Z., et al. (2010). Understanding customer satisfaction
and loyalty: An empirical study of mobile instant
messages in China. International Journal of
Information Management 30(4) 289-300.
Edward, M. and S. Sahadev (2011). Role of switching costs
in the service quality, perceived value, customer
satisfaction and customer retention linkage. Asia Pacific
Journal of Marketing and Logistics 23(3) 327-345.
Escobar-Rodríguez, T. and E. Carvajal-Trujillo (2013).
Online drivers of consumer purchase of website airline
tickets. Journal of Air Transport Management 32(0) 58-
64.
Gerpott, T. J., W. Rams and A. Schindler (2001). Customer
retention, loyalty, and satisfaction in the German
mobile cellular telecommunications market.
Telecommunications policy 25(4) 249-269.
Ha, J. and S. Jang (2009). Perceived justice in service
recovery and behavioral intentions: The role of
relationship quality. International Journal of
Hospitality Management 28(3) 319-327.
Hopewell, L. (2014). http://www.gizmodo.com.au/2014/
07/vodafone-plans-massive-4g-network-expansion/.
Islam, M. B. and A. R. Rima (2013). Factors Affecting
Customer Experience in Telecommunication Services
and its Importance on Brand Equity: A Study on
Telecommunication Companies in Bangladesh.
Karatepe, O. M. (2006). Customer complaints and
organizational responses: the effects of complainants’
perceptions of justice on satisfaction and loyalty.
International Journal of Hospitality Management 25(1)
69-90.
Kassim, N. M. (2006). Telecommunication industry in
Malaysia: demographics effect on customer
expectations, performance, satisfaction and retention.
Asia Pacific Business Review 12(4) 437-463.
Kaur, P. and D. S. K. Sharma (2015). Validating scale on
determinants affecting complaining intentions & its
applicability for indian service industry. International
Journal of Applied Services Marketing Perspectives
3(4) 1365-1372.
Kuo, Y.-F. and S.-N. Yen (2009). Towards an
understanding of the behavioral intention to use 3G
mobile value-added services. Computers in Human
Behavior 25(1) 103-110.
Lee, M.-C. (2010). Explaining and predicting users’
continuance intention toward e-learning: An extension
of the expectation–confirmation model. Computers &
Education 54(2) 506-516.
Lee, Y.-K., W.-K. Ahn and K. Kim (2008). A study on the
moderating role of alternative attractiveness in the
relationship between relational benefits and customer
loyalty. International Journal of hospitality & tourism
administration 9(1) 52-70.
Liang, T.-P., et al. (2011). What drives social commerce:
The role of social support and relationship quality.
International Journal of Electronic Commerce 16(2)
69-90.
Limayem, M., S. G. Hirt and C. M. Cheung (2007). How
habit limits the predictive power of intention: The case
of information systems continuance. MIS quarterly
705-737.
Lin, J.-S. C. and P.-L. Hsieh (2011). Assessing the Self-
service Technology Encounters: Development and
Validation of SSTQUAL Scale. Journal of Retailing
87(2) 194-206.
Liu, C.-T., Y. M. Guo and C.-H. Lee (2011). The effects of
relationship quality and switching barriers on customer
loyalty. International Journal of Information
Management 31(1) 71-79.
Lopez-Nicolas, C., F. J. Molina-Castillo and H. Bouwman
(2008). An assessment of advanced mobile services
acceptance: Contributions from TAM and diffusion
theory models. Information & Management 45(6) 359-
364.
Maklan, S. and P. Klaus (2011). Customer experience: are
we measuring the right things? International Journal of
Market Research 53(6) 771-792.
Mandal, D. and R. J. McQueen (2012). Extending UTAUT
to explain social media adoption by microbusinesses.
International Journal of Managing Information
Technology 4 (4) 1-11.
McCarthy, E. J. (1960). Basic marketing: a managerial
approach. Homewood, IL: Richard D. Irwin. Inc., 1979
McCarthy Basic Marketing: A Managerial Approach
1979.
Meyer, C. and A. Schwager (2007). Understanding customer
experience. Harvard business review 85(2) 116.
Morgan. (2014). Telstra scores biggest gains in consumer
mobile service market share in 2013 with four quarters
of growth [online]. Available at: http://roymorgan.com
/~/media/Files/Findings%20PDF/2014/March/5472-
mobile-phone-services-in-operation-market-shares-
december-2013.pdf [Accessed 21/12/2014 2014].
news (2012). Vodafone has lowest customer satisfaction of
all telcos, study reveals.
News (2014). Optus losing customers and revenue.
ICE-B 2016 - International Conference on e-Business
76
Olsen, S. O. (2002). Comparative evaluation and the
relationship between quality, satisfaction, and
repurchase loyalty. Journal of the academy of
marketing science 30(3) 240-249.
Ray, I. and L. Chiagouris (2009). Customer retention:
Examining the roles of store affect and store loyalty as
mediators in the management of retail strategies.
Journal of Strategic Marketing 17(1) 1-20.
Reichheld, et al. (1989). Zero defections: quality comes to
services. Harvard business review 68(5) 105-111.
Roberts-Lombard, M. (2009). Customer retention strategies
implemented by fast-food outlets in the Gauteng,
Western Cape and Kwazulu-Natal provinces of South
Africa-a focus on Something Fishy, Nandos and Steers.
African journal of marketing management 1(2) 070-080.
Roca, J. C., C.-M. Chiu and F. J. Martínez (2006).
Understanding e-learning continuance intention: An
extension of the Technology Acceptance Model.
International Journal of Human-Computer Studies 64
(8) 683-696.
Santouridis, I. and P. Trivellas (2010). Investigating the
impact of service quality and customer satisfaction on
customer loyalty in mobile telephony in Greece. The
TQM Journal 22(3) 330-343.
Straub, D., M.-C. Boudreau and D. Gefen (2004).
Validation guidelines for IS positivist research. The
Communications of the Association for Information
Systems 13(1) 63.
Taylor, J. (2013). Optus loses customers amid 4G growth.
TIO. (2010). Telecommunications Industry Ombudsman
2010 Annual Report [online]. Available at:
http://www.tio.com.au/__data/assets/pdf_file/0016/14
1262/AR_2010_complete.pdf [Accessed 07/09/2014
2014].
TIO. (2012). Telecommunications Industry Ombudsman
2012 Annual Report [online]. Available at:
http://www.tio.com.au/__data/assets/pdf_file/0017/14
1263/AR_2012_complete.pdf [Accessed 07/09/2014
2014].
TIO. (2013). Telecommunications Industry Ombudsman
2013 Annual Report [online]. Available at:
http://www.tio.com.au/__data/assets/pdf_file/0018/14
1264/2013-AR.pdf [Accessed 07/09/2014 2014].
TIO (2014). Telecommunications Industry Ombudsman
2014 Annual Report
Tsai, H.-T. and H.-C. Huang (2007). Determinants of e-
repurchase intentions: An integrative model of
quadruple retention drivers. Information &
Management 44(3) 231-239.
Uma, S. and B. Roger (2003). Research methods for
business: A skill building approach. John Wiley and
Sons Inc., New York.
Van Vuuren, Roberts-Lombard and Van Tonder (2013).
Customer satisfaction, trust and commitment as
predictors of customer loyalty within an optometric
practice environment. Southern African Business
Review 16(3) 81-96.
Vatanasombut, B., et al. (2008). Information systems
continuance intention of web-based applications
customers: The case of online banking. Information &
Management 45(7) 419-428.
Venkatesh, V., et al. (2003). User acceptance of
information technology: Toward a unified view. MIS
quarterly 425-478.
Venkatesh, V., J. Y. Thong and X. Xu (2012). Consumer
acceptance and use of information technology:
extending the unified theory of acceptance and use of
technology. MIS quarterly 36(1) 157-178.
Wangpipatwong, S., W. Chutimaskul and B. Papasratorn
(2008). Understanding citizen’s continuance intention
to use e-government website: A composite view of
technology acceptance model and computer self-
efficacy. The electronic journal of e-government 6(1)
55-64.
Wu, Y.-L., Y.-H. Tao and P.-C. Yang (2008). The use of
unified theory of acceptance and use of technology to
confer the behavioral model of 3G mobile
telecommunication users. Journal of Statistics and
Management Systems 11(5) 919-949.
Yadav, R., et al. (2016). A multi-analytical approach to
understand and predict the mobile commerce adoption.
Journal of enterprise information management 29(2).
Zhao, L., et al. (2012). Assessing the effects of service
quality and justice on customer satisfaction and the
continuance intention of mobile value-added services:
An empirical test of a multidimensional model.
Decision Support Systems 52(3) 645-656.
Zhou, T. (2013). An empirical examination of continuance
intention of mobile payment services. Decision Support
Systems 54(2) 1085-1091.
Zhou, T. and Y. Lu (2011). Examining Postadoption Usage
of Mobile Services From a Dual Perspective of
Enablers and Inhibitors. International Journal of
Human-Computer Interaction 27(12) 1177-1191.
An Empirical Examination of Customer Retention in Mobile Telecommunication Services in Australia
77