A presentation of a Netlogo simulation of mobile / cell network choice.

1. Team Cadel: Simulation
of 4G and 3G Cell
Network
Presentation at Agent Based
Modelling Workshop. University
of Sydney July 28th 2011.

2. Overview of the Research
Problem
• How do managers of networks (cell and
broadband) introduce new technology?
– Sale of Motorola Network see Crockett, (2008)
• New technology may be more expensive and
limited in capacity.
– Mah (2008)
• Consumers may move to another provider (Churn)
if they are not happy with service.
– Dierkes et al. (2011)
• Consumers may make decisions on price and
access to new technology.
– Jack, (2008) and Poynter, (2006).

3. Background research.
• Access to better technology.
– Chang Hyun, J. and J. Villegas (2008) and Colwell, S. R., M.
Aung, et al. (2008).
• Price and Value
– Deng, Z., Lu, Yaobin, Wei, Kwok Kee and Zhang, Jinlong (2010).
• Both factors
– Goode, Davies, Moutinho, and Jamal, (2005).
– Iyengar, et al. (2008).

4. The Netlogo Model: Moving from
a 3G to 4G World
• Network
– 4G- Number of 4G cell access points (0-100)
– 3G- Remaining cell access points
– Capacity of each cell (0-100).
• Price
– Price of 4G (0-50)
– Price 3G (0-50)
• Consumers
– Tolerance (of bad service) – (0-5).

5. Behaviour of Agents
1. Agents are set with a random allocation of bandwidth
requirement and price acceptance.
2. Agents seek to maximise bandwidth at an access
point.
a) Green patch 3G
b) Black patch 4G.
3. Agents seek to mimimize price of each offering.
• Agents who do 1 and 2 are happy (RED) and don’t
move.
• Agents who cannot find a combination of 1 and 2 are
not happy (WHITE) and after 10 turns, leave for
another provider (they die). This decided by Churn
which can be reduced by Tolerance.

6. The Netlogo Model

7. Experimental Design
• Independent variables • Dependent Variables
• ["FourG" 5 10] • % Happy customers
• ["capacity" 5 10]
• Loss of customers
• ["Price4G" 10 20]
• ["Price3G" 10 20]
• Mean use of 3G
• ["tolerance" 0 1] • Mean use of 4G
• ["Customers" 500]
• 32 Runs

8. Descriptive Results
Statistics
countturtles Happy Loss Mean3G Mean4G
N Valid 1008.00 1008.00 1008.00 1008.00 1008.00
Missing .00 .00 .00 .00 .00
Mean 495.59 46.10 4.41 .48 .52
Median 500.00 48.40 .00 .49 .43
Mode 500.00 50.20 .00 .00 .00
Std. Deviation 35.30 18.19 35.30 .25 .36
Skewness -8.11 -.34 8.11 .39 .97
Std. Error of Skewness .08 .08 .08 .08 .08
Kurtosis 65.41 .75 65.41 -.42 .39
Std. Error of Kurtosis .15 .15 .15 .15 .15
Minimum 154.00 .00 .00 .00 .00
Maximum 500.00 100.00 346.00 1.07 1.80
Percentiles 25 500.00 36.65 .00 .28 .26
50 500.00 48.40 .00 .49 .43
75 500.00 57.55 .00 .60 .73

9. Source
FourG
Results Dependent
Variable
Happy
df
1
F
53.16
Sig.
0.00
Partial Eta
Squared
0.05
Mean3G 1 188.75 0.00 0.16
Mean4G 1 881.73 0.00 0.47
Price3G Happy 1 66.24 0.00 0.06
Mean3G 1 55.29 0.00 0.05
Mean4G 1 39.68 0.00 0.04
tolerance Happy 1 118.94 0.00 0.11
Loss 1 69.57 0.00 0.07
Mean3G 1 278.10 0.00 0.22
Mean4G 1 15.46 0.00 0.02
capacity
Mean3G 1 494.02 0.00 0.34
Mean4G 1 559.66 0.00 0.36
FourG * tolerance
Mean3G 1 49.37 0.00 0.05
FourG * capacity
Mean3G 1 5.00 0.03 0.01
Mean4G 1 89.68 0.00 0.08
Price4G * Price3G
Mean4G 1 14.32 0.00 0.01
Price4G * capacity
Mean4G 1 3.83 0.05 0.00
Price3G * tolerance Happy 1 3.97 0.05 0.00
Price3G * capacity
Mean3G 1 4.47 0.03 0.00
Mean4G 1 7.97 0.00 0.01
tolerance * capacity
Mean3G 1 18.43 0.00 0.02
FourG * Price4G *
Price3G
Mean4G 1 9.37 0.00 0.01
FourG * Price4G *
tolerance Mean4G 1 3.15 0.08 0.00

10. ANOVA Results continued
FourG * Price4G *
capacity Mean4G 1 4.86 0.03 0.00
Price4G * Price3G *
capacity Mean4G 1 22.49 0.00 0.02
Dependent Partial Eta
Source Variable df F Sig. Squared
FourG * Price4G *
Price3G * tolerance Mean4G 1 4.59 0.03 0.00
FourG * Price4G *
Price3G * capacity Mean4G 1 11.94 0.00 0.01
FourG * Price4G *
tolerance * capacity Mean4G 1 11.10 0.00 0.01
FourG * Price3G *
tolerance * capacity Mean4G 1 4.64 0.03 0.00

11. Conclusions
• Tolerance, Four G Access points
numbers capacity and only the price of
3G seemed to influence the happiness
of consumers and the mean use of
technology (4G and 3G).
• Loss of customers is determined mainly
by tolerance.
• There are a number of interactions but
the effect sizes are small.

12. Implications for Providers
• Planning for capacity is important but you
don’t have to provide access to all
consumers.
• The price of the old technology is more
important than the price of the new
technology.
• Relationship marketing is important to
increase tolerance and prevent churn.

13. References
Chang Hyun, J. and J. Villegas (2008). "MOBILE PHONE USERS' BEHAVIORS: THE
MOTIVATION FACTORS OF THE MOBILE PHONE USER." International Journal of Mobile
Marketing 3(2): 4-14.
Colwell, S. R., M. Aung, et al. (2008). "Toward a measure of service convenience: multiple-item
scale development and empirical test." Journal of Services Marketing 22(2/3): 160-169
Crockett, R. O. (2008). "MOTOROLA SETS ITS PHONE UNIT FREE." BusinessWeek(4078): 36-
38.
Deng, Z., Lu, Yaobin, Wei, Kwok Kee and Zhang, Jinlong (2010). "Understanding customer
satisfaction and loyalty: An empirical study of mobile instant messages in China."
International Journal of Information Management 30(4): 289-300.
Dierkes, T., Bichler, Martin and Krishnan, Ramayya (2011). "Estimating the effect of word of
mouth on churn and cross-buying in the mobile phone market with Markov logic networks."
Decision Support Systems 51(3): 361-371.
Goode, M. M. H., Davies, Fiona, Moutinho, Luiz and Jamal, Ahmad (2005). "Determining
Customer Satisfaction From Mobile Phones: A Neural Network Approach." Journal of
Marketing Management 21(7/8): 755-778.
Iyengar, R., Jedidi, Kamel and Kohli, Rajeev (2008). "A Conjoint Approach to Multipart Pricing."
Journal of Marketing Research (JMR) 45(2): 195-210.
Jack, L. (2008). "Public gets taste for cut price communication." Marketing Week (01419285)
31(33): 3-3.
Mah, A. (2004). "Product Innovation Case Study: '3' - A Hutchinson Brand." Marketing Review
4(2): 157-188.
Poynter, K. (2006). "Vodafone: 'Stop the clock'." Marketing (00253650): 22-22.

14. Questions?