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Predicting consumer preference for fast-food franchises: a data mining approach

  • Theoretical Paper
  • Published:
Journal of the Operational Research Society

Abstract

The objectives of the study reported in this paper are: (1) to evaluate the adequacy of two data mining techniques, decision tree and neural network in analysing consumer preference for a fast-food franchise and (2) to examine the sufficiency of the criteria selected in understanding this preference. We build decision tree and neural network models to fit data samples collected from 800 respondents in Taiwan to understand the factors that determine their brand preference. Classification rules are generated from these models to differentiate between consumers who prefer the brand and those who do not. The generated rules show that while both decision tree and neural network models can achieve predictive accuracy of more than 80% on the training data samples and more that 70% on the cross-validation data samples, the neural network models compare very favourably to a decision tree model in rule complexity and the numbers of relevant input attributes.

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Author information

Authors and Affiliations

  1. Meiji University Higashimita, Tama-ku, Kawasaki, Kanagawa, Japan

    Y Hayashi

  2. National Taiwan University, Taipei City, ROC, Taiwan

    M-H Hsieh

  3. National University of Singapore, Singapore, Republic of Singapore

    R Setiono

Authors
  1. Y Hayashi
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  2. M-H Hsieh
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  3. R Setiono
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Corresponding author

Correspondence to R Setiono.

Appendix

Appendix

The questions included in the questionnaire are as follows.

Group A. Brand attributes: if the respondent agrees that the well-known fast-food franchise possesses the following attributes:

  1. 1

    Clean and tidy

  2. 2

    Fresh ingredients are used

  3. 3

    Easy to find seats/tables

  4. 4

    Serves breakfast items I prefer

  5. 5

    Frequent launch of new products

  6. 6

    Fast and efficient service

  7. 7

    Already had a good experience/impression

  8. 8

    Allows mix-and-match set meal menu items

  9. 9

    A store I feel familiar with

  10. 10

    Serves my favourite food items

  11. 11

    Has TV promotions that attract me

  12. 12

    Offers reasonable price and good value

  13. 13

    Has wide menu variety

  14. 14

    Serves tasty milk tea and coffee

  15. 15

    Suitable to go when in a hurry

  16. 16

    Convenient store locations

  17. 17

    Suitable for the whole family

  18. 18

    Menu consists of breakfast, lunch and dinner

  19. 19

    Most menu offerings suit my taste

  20. 20

    Makes me feel comfortable

  21. 21

    Offer freshly prepared food

  22. 22

    A place that reminds me of my childhood

  23. 23

    Good staff attitude

  24. 24

    Food items are not ‘heaty’

  25. 25

    Offers gift/toy redemption that are attractive

  26. 26

    Serves food with consistent quality

  27. 27

    Offers price discount/coupon

  28. 28

    Food is filling

  29. 29

    Has clean bathrooms

  30. 30

    Is a place adults enjoy

  31. 31

    Serves tasty food

  32. 32

    Is a place children enjoyed

  33. 33

    Offers everyday affordable prices

  34. 34

    Has attractive and comfortable decoration

  35. 35

    Serves burgers I like

  36. 36

    Serves chicken products I like

  37. 37

    Serves French fries I like

  38. 38

    Puts me in a good mood

  39. 39

    Is a part of Taiwan life

  40. 40

    Is an energetic place

  41. 41

    Provides employees with a good working environment

Group B. Perceived importance of certain attributes when deciding whether to patronize a fast-food outlet. The 41 questions in this group are the same as those in Group A.

Group C. Demographic information.

  1. 1

    Whether use internet (Yes/No)

  2. 2

    Frequency of internet use

    • less than once a week,

    • 2–6 times a week,

    • than once a day

  3. 3

    Marital status

    • Single

    • Partnered/married

    • Separated/divorced

    • Widowed

  4. 4

    Number of household members

    • 1–3

    • 4

    • 5

    • 6–10

  5. 5

    Financial status

    • You are the only one who is financially supporting the household

    • You are not the only one who is financially supporting the household but is the main one

    • You are neither the only one who is financially supporting the household nor is the main one

    • You do not need to financially support the household

  6. 6

    Education

    • Primary school or below

    • Junior high school

    • Senior high school/vocational training school

    • University/college

    • Graduate school

  7. 7

    Working status

    • Working full-time

    • Working part-time

    • Student

    • Housewife/home-maker

    • Retired

    • Unemployed

  8. 8

    Occupation

    • Professional

    • Corporate director/management

    • Business owner/self-employed/merchant

    • Skilled white collar

    • Unskilled white collar

    • Skilled blue collar

    • Unskilled blue collar

  9. 9

    Personal monthly income

    • Under NT$20 000

    • NT$20 000–NT$29 999

    • NT$30 000–NT$39 999

    • NT$40 000–NT$59 999

    • NT$60 000 or more

  10. 10

    Household monthly income

    • Under NT$40 000

    • NT$40 000–NT$59 999

    • NT$60 000–NT$79 999

    • NT$80 000 or more

  11. 11

    Personal eating out expenditure

    • Under NT$1000

    • NT$1000–NT$1999

    • NT$2000–NT$3999

    • NT$4000–NT$5999

    • NT$6000 or more

  12. 12

    Household eating out expenditure

    • Under NT$4000

    • NT$4000–NT$5999

    • NT$6000–NT$7999

    • NT$8000 or more

  13. 13

    Eating out frequency

    • At least 2 times a day

    • Once a day

    • 4–6 times a week

    • 2–3 times a week

    • Once a week or less often

  14. 14

    Region

    • Greater Taipei

    • Northern Taiwan

    • Central Taiwan

    • Southern Taiwan

  15. 15

    Type of region

    • Metropolitan

    • Non-metropolitan

  16. 16

    Gender

    • Male

    • Female

  17. 17

    Age range

    • 15–19

    • 20–24

    • 24–29

    • 30–34

    • 35–39

    • 40–44

    • 45–54

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Hayashi, Y., Hsieh, MH. & Setiono, R. Predicting consumer preference for fast-food franchises: a data mining approach. J Oper Res Soc 60, 1221–1229 (2009). https://doi.org/10.1057/palgrave.jors.2602646

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  • DOI: https://doi.org/10.1057/palgrave.jors.2602646

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