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Predicting Product Choice with Symbolic Regression and Classification

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Genetic Programming Theory and Practice XIII

Part of the book series: Genetic and Evolutionary Computation ((GEVO))

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Abstract

Market researchers often conduct surveys to measure how much value consumers place on the various features of a product. The resulting data should enable managers to combine these utility values in different ways to predict the market share of a product with a new configuration of features. Researchers assess the accuracy of these choice models by measuring the extent to which the summed utilities can predict actual market shares when respondents choose from sets of complete products. The current paper includes data from 201 consumers who gave ratings to 18 cell phone features and then ranked eight complete cell phones. A simple summing of the utility values predicted the correct product on the ranking task for 22.8 % of respondents. Another accuracy measurement is to compare the market shares for each product using the ranking task and the estimated market shares based on summed utilities. This produced a mean absolute difference between ranked and estimated market shares of 7.8 %. The current paper applied two broad strategies to improve these prediction methods. Various evolutionary search methods were used to classify the data for each respondent to predict one of eight discrete choices. The fitness measure of the classification approach seeks to reduce the Classification Error Percent (CEP) which minimizes the percent of incorrect classifications. This produced a significantly better fit with the hit rate rising from 22.8 to 35.8 %. The mean absolute deviation between actual and estimated market shares declined from 7.8 to 6.1 % (p. <0.01). A simple language specification will be illustrated to define symbolic regression and classification searches.

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References

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Author information

Authors and Affiliations

  1. Southwest Baptist University, Bolivar, MO, 65613, USA

    Philip Truscott

  2. Analytic Research Foundation, 2240 Village Walk Drive Suite 2305, Henderson, NV, 89052, USA

    Michael F. Korns

Authors
  1. Philip Truscott
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  2. Michael F. Korns
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Corresponding author

Correspondence to Philip Truscott .

Editor information

Editors and Affiliations

  1. Center for the Study of Complex Systems, University of Michigan, Ann Arbor, Michigan, USA

    Rick Riolo

  2. Evolution Enterprises, Ann Arbor, Michigan, USA

    W.P. Worzel

  3. Evolved Analytics, Midland, Michigan, USA

    Mark Kotanchek

  4. Evolved Analytics LLC, Midland, Michigan, USA

    Arthur Kordon

Appendices

Appendix 1: Questionnaire Text

  1. 1.

    Operating system

    1. a.

      Android

    2. b.

      Symbian

    3. c.

      Windows

    4. d.

      Blackberry

    5. e.

      iOS (iPhone OS)

  2. 2.

    Screen size

    1. a.

      Less than 3 in.

    2. b.

      3.0–3.4 in.

    3. c.

      3.5–3.9 in.

    4. d.

      4.0–4.4 in.

    5. e.

      4.5–4.9 in.

    6. f.

      5 in. and over

  3. 3.

    Camera memory

    1. a.

      Below 2 megapixels

    2. b.

      2–4.9 megapixels

    3. c.

      5–7.9 megapixels

    4. d.

      8 Megapixels and above

  4. 4.

    Memory

    1. a.

      Below 8 GB

    2. b.

      8–15.9 GB

    3. c.

      16–31.9 GB

    4. d.

      32–63.9 GB

    5. e.

      64 GB or more

  5. 5.

    Talk time

    1. a.

      Less than 6 h

    2. b.

      6–11 h

    3. c.

      12–23 h

    4. d.

      24–35 h

    5. e.

      36 h or more

  6. 6.

    Stand by time

    1. a.

      Under 50 h

    2. b.

      50–99 h

    3. c.

      100–199 h

    4. d.

      200–299 h

    5. e.

      300 h or more

  7. 7.

    Price

    1. a.

      5000 Rs or less

    2. b.

      5001–10,000 Rs

    3. c.

      10,001–18,000 Rs

    4. d.

      18,001–35,000 Rs

    5. e.

      35,001 Rs and above

  8. 8.

    Phone thickness

    1. a.

      Less than 6 mm

    2. b.

      6–7 mm

    3. c.

      8–9 mm

    4. d.

      10–11 mm

    5. e.

      12 mm or more

  9. 9.

    CPU speed

    1. a.

      1 GHz or less

    2. b.

      1.0–1.3 GHz

    3. c.

      1.4–1.5 GHz

    4. d.

      1.6–1.9 GHz

    5. e.

      2.0 GHz or more

  10. 10.

    Warranty length

    1. a.

      Free repairs for 6 months

    2. b.

      Free repairs for 1 year

    3. c.

      Free repairs for 1.5 years

    4. d.

      Free repairs for 2 years

    5. e.

      Free repairs for 2.5 years

  11. 11.

    GPS

    1. a.

      Has GPS

    2. b.

      No GPS

  12. 12.

    Wi-Fi

    1. a.

      Has Wi-Fi

    2. b.

      No Wi-Fi

  13. 13.

    Touchscreen

    1. a.

      Has a touchscreen

    2. b.

      No touchscreen

  14. 14.

    SIM format

    1. a.

      Single SIM

    2. b.

      Dual SIM

  15. 15.

    3G

    1. a.

      Has 3G connectivity

    2. b.

      No 3G connectivity

  16. 16.

    Qwerty keyboard

    1. a.

      Has a QWERTY keyboard

    2. b.

      No QWERTY keyboard

  17. 17.

    Brand impression

    1. a.

      Apple

    2. b.

      Samsung

    3. c.

      Blackberry

    4. d.

      XOLO

    5. e.

      Spice

    6. f.

      Micromax

    7. g.

      Nokia

    8. h.

      Lava

Appendix 2: Sources of Feature Data

All feature data for the eight mobile phones were drawn from www.Flipkart.com on September 26th, 2013 except the following items that were missing from the Flipkart comparison screens.

For the iPhone 5 with 32 GB, data was missing for the CPU speed attribute. This was taken from www.GSMArena.com on September 26th 2013.

For the Samsung Galaxy Note 2, data was missing for the talk-time and standby time attributes. This was taken from www.GSMArena.com on September 26th 2013.

For the Blackberry Curve 9220, data was missing for the GPS attribute. This was taken from www.GSMArena.com on September 26th 2013. The CPU speed attribute was missing from both these sources. It was taken from asia.cnet.com on September 26th 2013.

For the XOLO Q1000, data was missing for the GPS attribute. This was taken from www.GSMArena.com on September 26th 2013.

For the Spice MI-495, data was missing for the USB connection attribute. This was taken from www.GSMArena.com on September 26th 2013. The phone thickness attribute was missing from both these sources. It was taken from comapareindia.in.com on November 5th 2013.

For the Micromax Canvas 4 A210, data was missing for the GPS attribute. This was taken from www.GSMArena.com on September 26th 2013.

For the Lava Iris 504Q, data was missing for the GPS attribute. It was taken from comapareindia.in.com on November 5th 2013.

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Truscott, P., Korns, M.F. (2016). Predicting Product Choice with Symbolic Regression and Classification. In: Riolo, R., Worzel, W., Kotanchek, M., Kordon, A. (eds) Genetic Programming Theory and Practice XIII. Genetic and Evolutionary Computation. Springer, Cham. https://doi.org/10.1007/978-3-319-34223-8_12

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  • DOI: https://doi.org/10.1007/978-3-319-34223-8_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-34221-4

  • Online ISBN: 978-3-319-34223-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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