1. School of Management and Marketing
Hung up on switching:
Consumer insights into mobile switching in Australia.
An example of an industry / university partnership
Presentation at Swinburne University on 4th
September, 2015.

2. School of Management and Marketing
Significance of the study
• According to Euromonitor in 2011, there were some
25.54 million mobile phone subscriptions in Australia.
• The industry in Australia is worth $20 billion per
annum (IBISWorld 2012) and consumes 1.4% of
household expenditure (derived from - ABS
Household Expenditure Survey 2010).
• Complaints to the (TIO) in 2011 were a record
197,682 up 18% on the previous year.
• 42, 300 in the same year complained to the TIO that
providers did not meet their promises.

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Key research objectives of the research program
2011-2013.
1. What are the effects of push and pull factors that
determine provider choice?
2. What factors moderate the choice of a new mobile phone
provider?
3. Are there any "one -off" or situational factors that trigger
the brand switching process?

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Consumer insights: The six “f”s
1. Fed-up!
• Don’t trust the industry.
2. Frustrated
• They can’t resolve problems, or easily
change providers.
3. Feel powerless
• Sense that they are not valued or taken
seriously by the industry. 2/3 won’t even
challenge a higher than expected bill.
4. Fractious
• Tell friends and others about bad
experiences and gripes
5. Finished with current providers.
• They have no loyalty. Why should they?
6. Fingers are on the triggers.
• They will switch quickly, even if it is difficult.
SO LOOK OUT IN 2015!!

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Key outcomes of the study: Academic…so
far
1. D’Alessandro, Steven, Johnson, Lester, Gray, David and Carter, Leanne (2015) The
market performance indicator: A macro understanding of service provider switching,
Journal of Services Marketing, tier A, 29(4): 302–313, tier A, marketing, impact
factor=.783 QUALITATIVE & LONGDITUINAL SURVEY RESEARCH
2. D’Alessandro, Steven, Johnson, Lester, Gray, David and Carter, Leanne (2014)
Consumer Satisfaction versus churn in the case of upgrades from 3G to 4G cell
networks. Marketing Letters, Available ahead of print online, DOI: 10.1007/s11002-014-
9284-3, (tier A, marketing, impact factor =1.000). SIMULUATION /AGENT BASED
MODELLING
3. Gray, David, D’Alessandro, Steven, Carter, Leanne and Johnson, Lester (2015)
Antecedents of interia and its effect on service provider switching, Journal of Services
Marketing, Tier A (revise and resubmit), marketing. QUALITATIVE & LONGDITUINAL
SURVEY RESEARCH.
4. Carter, Leanne, Gray, David, D’Alessandro, Steven and Johnson, Lester (2015) The “I
love to hate them” relationship with cell phone service providers: The role of customer
inertia, Service Marketing Quarterly, Tier B, marketing (Under review). QUALITATIVE
5. Industry grant of $42 000 (matched by MQ)
6. MQ Research impact award 2014
7. AMI national award finalist, 2012.
8. Significant increase in media profile of researchers and the university.

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An example of an increased media profile

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Key Outcomes: Industry partner amaysim
1. Public relations exposure from media reports of
research worth above $1.0 million dollars.
2. In one year, increased sales of all mobile plans by 25%.
3. The consumer insights from the research clearly showed
that the amaysim product offer of no lock in contracts, a
100% Australian customer service centre and an easy-
to-understand BYO phone policy should resonate with
the Australian public if the public were just aware of it.
4. National finalist AMI awards 2012 for Consumer insights.

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The industry and regulatory practices
1. The State of the Mobile Nation Report, provided to
media and the public provided an evidenced based
response to government policy makers such as ACMA in
respect to the strategies it is pursuing to improve market
performance.
2. Since the publication of the final report it has been
requested by a number of regulatory agencies including
the ACCC and the NSW Office of Fair Trading.
3. Caps on bill shock and changes in industry practices.

9. School of Management and Marketing
An example paper: D’Alessandro, Steven, Johnson, Lester, Gray, David and
Carter, Leanne (2015) The market performance indicator: A macro
understanding of service provider switching, Journal of Services Marketing
Purpose
• While research on service provider switching has focused
on the outcomes of service transactions and the benefits
of switching, there is little research on how consumers
view market conditions as being favorable or not for
switching.
• We adapted the Market Performance Indicator (MPI),
used by the European Commission to evaluate market
conditions, over time, to show that the MPI explains
actual switching behavior better than stated intent and
satisfaction.

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The Market Performance Index (MPI)
• The European Commission (European Commission,
2010) developed a generic market performance indicator
(MPI) of consumer perceptions across all twenty seven
member states. The European Commission defined the
MPI as a composite equally weighted perceptual and
behavioural index. The higher the MPI the better the
market is performing for consumers.
• Can serve as an international benchmark for
telecommunications services

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MPI Components
1. Consumer perceptions of trust /10. A greater score means greater trust in the
market.
2. Ease of comparing goods and services on offer /10. A greater score means it is
easier for consumer to compare competing offers.
3. Problems experienced and the degree to which they have lead to complaints
(this is a score based on the occurrence of problems, how well they are handled
by providers and if respondents complained to third parties, family or friends or a
complaints body) /10. This score is based on the following; (10) a person did not
experience a problem (5) a problem was reported , but the respondent did not
complain, (3) the respondent complained to friends or family, (2) the respondent
complained to the provider and (0) the respondent complained to a third party
complaint body.
4. Consumer satisfaction, or the degree to which consumer expectations have
been met /10. A higher score means the market usually meets consumer
expectations.

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Design/methodology/approach
• We used a mixed methodology of focus groups (7) and
longitudinal survey research 971 mobile phone
consumers over 11 months, to evaluate the effect of the
MPI on satisfaction, perceptions of value, switching
intentions and behaviour.
• Response rate was around 71%, nationally
representative sample.

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Conceptual model

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Variables in the model
Satisfaction People less likely to switch if they are satisfied, up a to a
point at least (Dagger & David, 2012; Dagger & Sweeney, 2007;
Hallowell, 1996; White & Yanamandram, 2004).
Value: It is also likely that as consumer perceptions of value increase
there will be less likelihood of brand switching (Andrews,
Benedicktus, & Brady, 2010; Tseng & Lo, 2011; Wang, 2010).
Note: Switching can still occur as people seek better value.
MPI improved market conditions are associated with and lead to
greater consumer switching intentions and behaviour (Maicas,
Polo and Javier Sese, 2009, Nakamura, 2010, Grzybowski and
Pereira, 2011).
Intent: Seen as an important predictor of future behaviour.
Behaviour: Defined in this model as switching a provider over the 11
month period.

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Qualitative insights
Construct Focus group comments
MPI: Trust “It is the same sort of deceptive advertising. I have done
marketing in the past and you say, "Buy this and you get one
free." It is not free. It is part of the price. Nobody gives
things away.” Switcher, Married with Children > 5yrs.
“I just pick the lesser of two evils.” Switcher, Young
Couple, 20-40
MPI: Ability to compare offers “It was not easy to compare rates. We just compared the
benefits of each provider”. Married with Children < 5yrs
MPI: Problems and complaints “At (one of the telcos) it took 20mins to speak to
someone...always palmed me off to someone
else...I prefer to spend (my money) with a
company that cares about me”. Married with
Children < 5 years old
MPI: Meeting consumer expectations “The plan wasn't right and I got really upset
about it because it wasn't fair. I got talked into
something that really I should have gone to a
more expensive plan where I would have
controlled the cost.” Married Couple with
Children > 5years.
MPI: Ease of Switching “I have gone to the shops and looked on-line. I think the
phones they offer are a big thing. They are restrictive on
what phone you can have with what plan.” Non Switcher
Satisfaction with current provider “Just like extra charges, just silly little things that
you would they ever know about. I was so mad
about it, I even cancelled my Internet with them
and changed to X as well. So all three phones I
now have are with X ” Switcher, Young Single,
18-24
Value of service “They know that we need them. It (cell phones) is an
essential service.” Young Couple
At the end of the day, it comes down to price.” Switcher
Married with children > 5yrs of age, +40.

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Measurement properties
1. The reflective constructs (satisfaction and intent) measured in
this study followed the approach recommended by Gefen and
Straub, 2005 that is reflective factor loadings exceed 0.40 and
have significant t-values. In addition, all variables exceeded the
minimum cut-off of 0.50 on the AVE as recommended by Fornell
and Larcker, (1981). Cronbach alpha measures were above .70
as recommended by Bollen, (1989).
2. The formative measures (value and the MPI at both time
periods) were developed according to procedures recommended
by Cenfetelli and Bassellier, (2009) which included examination
of multicollinearity, the number of indicators specified for a
formatively measured construct and the possible co-occurrence
of negative and positive indicator weights.

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PLS Results
Direct paths
Hypothesis Path Standardized Beta
H1 MPI (wave1)→Satisfaction 0.19**
H2 Satisfaction→ Switching intent -0.51**
H3 Satisfaction→ Switching behavior -0.11
H4 MPI (wave1) →Value 0.50**
H5 Value→ Switching intent -0.17**
H6 Value→ Switching behavior -0.14**
H7 MPI (wave1) → Switching intent 0.03
H8 MPI (wave2) →Switching behavior 0.21**
(+) Switching intention → Switching behavior 0.10
Indirect paths
MPI (wave 1) → MPI (wave2) → Switching behavior 0.09
MPI (wave 1) → Satisfaction→ Switching behavior -0.02
MPI (wave 1) → Value→ Switching behavior -0.07
Satisfaction→ Value→ Switching behavior -0.10
Satisfaction→ Switching intent→ Switching behavior - 0.01
Value-→Switching intent→ Switching behavior -0.02
R2
Satisfaction=0.68, R2
Value=0.25, R2
Switching intent=0.39 & Pseudo R2
Switching behavior =0.06
Note: * p<0.05, **p<0.01.
MPI: Market Performance Indicator.
R2 : R-squared.
Wave 1: Measurement at the time of intention to switch in 2011.
Wave 2: Measurement at the time of actual switching in 2012.

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Findings and conclusions
1. The MPI was found to influence perceptions of satisfaction and value, and
was found to contribute strongly to actual switching behaviour.
2. The results also showed that an improvement in the MPI or market
conditions lead to a much greater relationship between it and actual
switching behaviour, suggesting that there may well be an important
threshold level, upon which greater switching behaviour occurs.
3. The MPI if also measured in the same time period of switching, can capture
improved market conditions, occurring as the result of regulatory, policy and
industry change, and so serves as a useful guide also for directions of
industry policy by various stakeholders.
4. The MPI provides marketers and policy makers with benchmarks to
compare the consumer welfare of different markets in different countries.
Switching studies with MPI figures can be more easily generalized to
different contexts.

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Changes in the MPI over time. Australia and the EU
Note: ** p<.01, with 2010 and 2012 EU benchmarks. Bold results show
significant changes (p<0.01) in the Australian MPI between 2011 and
2012.
MPI Measure EU results
2010
EU results
2012
Australian
results 2011
Australian
results 2012
Trust /10 6.1 6.1 4.1** 4.4**
Ease of comparability
of offers /10 6.9 7.0 5.5** 5.2**
Meet expectations /10 7.3 7.3 5.2** 5.9
Ease of switching /10 7.3 7.3 4.2** 5.8
Problems and
complaints /10 8.5 - 7.1** -

20. School of Management and Marketing
References
Andrews, M. L., Benedicktus, R. L., & Brady, M. K. (2010). The effect of incentives on customer evaluations of service bundles.
Journal of Business Research, 63(1), 71-76.
Cenfetelli, R. T., & Bassellier, G. (2009). Interpretation of formative measurement in information systems research. MIS Quarterly,
33(4), 689-706.
Dagger, T. S., & David, M. E. (2012). Uncovering the real effect of switching costs on the satisfaction-loyalty association: The critical
role of involvement and relationship benefits. European Journal of Marketing, 46(3/4), 447-468.
Dagger, T. S., & Sweeney, J. C. (2007). Service quality attribute weights: How do novice and longer-term customers construct
service quality perceptions? Journal of Service Research, 10(1), 22-42.
European Commission. (2010, 2012 and 2014). Consumer Markets Scoreboard – Making markets work for consumers, 4th Edition
Luxembourg: Office for Official Publications of the European Union Retrieved from http: //ec.europa. eu/ consumers /strategy
/facts _en.htm.
Euromonitor, I. (2011). Mobile phone statistics from http://www.portal.euromonitor.com/Portal/Pages/Statistics/Statistics.aspx
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error.
Journal of Marketing Research, 18(1), 39-50.
Gefen, D., & Straub, D. (2005). A practical guide to factorial validity using PLSGraph: tutorial and annotated example.
Communications of the AIS, 16(25), 91-109.
Grzybowski, L., & Pereira, P. (2011). Subscription choices and switching costs in mobile telephony. Review of Industrial
Organization, 38(1), 23-42Hallowell, R. (1996). The relationships of customer satisfaction, customer loyalty, and profitability: an
empirical study. International Journal of Service Industry Management 7(4), 27-42.
IBISWorld. (2012). Industry report J7122 : Mobile telecommunications carriers in Australia, (Vol. January, pp. 1-48).
Maicas, J. P., Polo, Y., & Javier Sese, F. (2009). Reducing the level of switching costs in mobile communications: The case of Mobile
Number Portability. Telecommunications Policy, 33(9), 544-554.
Nakamura, A. (2010). Estimating switching costs involved in changing mobile phone carriers in Japan: Evaluation of lock-in factors
related to Japan’s SIM card locks. Telecommunications Policy, 34(11), 736-746.
Tseng, F.-M., & Lo, H.-Y. (2011). Antecedents of consumers’ intentions to upgrade their mobile phones. Telecommunications Policy,
35(1), 74-86.
Wang, C.-Y. (2010). Service quality, perceived value, corporate image, and customer loyalty in the context of varying levels of
switching costs. Psychology and Marketing, 27(3), 252-262.
White, L., & Yanamandram, V. (2004). Why customers stay: reasons and consquences of intertia in finanical services. Managing
Service Quality, 14(2/3), 183-194.
.

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Questions?