Abstract
Drawing on numerical cognition research, we identify a set of multi-context numbers (MCN) that originate from the decimal (10), duodecimal (12) and sexagesimal (60) numeral systems frequently used in numerous domains (e.g., 10, 12, 20, 24, 60, 360, 100). We propose and show that inclusion of MCN in alphanumeric brand names (ABN) generates more favorable consumer attitudes and higher preferences for product extensions in different domains. We examine three types of fit, between (1) parent brands and numbers, (2) product categories and numbers and (3) parent brands and product categories. We find that the effects of ABN numbers are mainly mediated by product–number associations. Accordingly, while some numbers that are strongly associated with the product category (e.g., 401 and retirement services) or the parent brand (e.g., Heinz and 57; Levi’s and 501) or that are familiar to consumers (e.g., 18, 21) generate favorable consumer responses in specific contexts, the same numbers fail in other product domains (e.g., 401/57/18/21 taxi service). In four empirical studies, we demonstrate that MCN in ABN can achieve and maintain favorable consumer responses and receive higher preferences than other very familiar numbers in various product extension contexts, regardless of parent brand names or product categories. Our findings suggest that it is ideal to use MCN in new extensions.
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Appendices
Appendix 1
Common numeral system | Uses |
|---|---|
Decimal (10) History/Origins: Dates back to beginning of writing. Written evidence of its use in ancient Egyptian and Cretan hieroglyphs. Based on human anatomy, currently used by all modern civilizations | All metric system measures (height, weight, volume, length, area) Military units, ranks, money bills, rankings, ratings, percentages, pricing, grouping, financial indices Roman, Greek, Brahmi, Chinese, Hindu-Arabic numerals are all based on the decimal system including special notations for 1, 10, 100, 5, 50, 500…etc |
Duodecimal/dozenal (12) History/Origins: Dates back to Sumerians and Babylonians. Based on human anatomy and single-hand counting method using thumb to count 4 × 3 finger bones Widely adopted in Anglo-Saxon cultures and continued even after decimalization | All non-metric measurements of length/area/ weight 1 ft = 12 inches, 1sq ft = 144 sq inches, 12 ounce = 1 tory pound Monetary/Math: 1 shilling = 12 pence, 240 pence = 1 pound sterling (English and Irish), prices quoted as 12ths, Roman fraction system in 12s Packaging/grouping: dozen, 12-pack, 24-pack, gross = 144 (12 dozens), great gross = 123 = 1728 Time: 1 year = 12 months, 1 day = 24 h, day/night (am/pm) = 12 h, ½ year = 6 months, Chinese calendar has 12 year cycles, 12 lunar cycles Babylonians originally had 12 h in a day Other: 12 zodiac signs, 12 apostles, 12 imams, 12 wars, 12 petals, 12 jurors 12 Functional keys on key boards (F1-12) and telephones (0–9,*,#,) 12 notes in an octave, 12 teams in rugby, soccer leagues, finals, etc |
Sexagesimal (60) History/Origins: Dates back to 3100BC Sumerians and Babylonians. It is a combination of the single-hand counting method (12 system) with the right-hand counting (× 5) to reach 60. It became popular in second- and eighteenth-century mathematics and astronomy especially for Hellenistic civilizations | Time: 1 h = 60, 1 min = 60 s (i.e., 2nd order [1/60] of an hour) e.g., 4:22:33 = 4 × 602 + 22 × 601 + 33 × 600 s Chinese calendar has a sexagenary cycle, in which days or years are named by positions in a sequence of ten stems and in another sequence of 12 branches. The same stem and branch repeat every 60 steps throughout this cycle. Geometry/trigonometry, mathematical astronomy (fractions), arcs, circle, angles, degrees, 360, 180, 90, 60, 30 Geographic locations: Degrees of Parallels and Meridians, Seconds French: 70 = soixante-dix (sixty ten) 75 = soixante-quinze (sixty fifteen) Other: 60 mph as a common speed limit and reference for acceleration 0–60 |
Binary (2) History/Origins: Morse code, data processing | In 1617, John Napier’s location arithmetic system. Multiples of 2 are often observed in technology contexts: 32, 64, 128, 256, 512, 1024 |
Appendix 2
Study 1: Experimental scenario and an example for the choice set
“Imagine that some well-known brands are planning to sell certain products that they don’t offer right now. To launch these products, brand managers are going back and forth with using brand name number combinations such as Porsche 911 or Heinz 57. You are asked to evaluate these brands with or without brand name number combinations and pick one of them as your choice.”
Please pick one of the alternatives as your preference.
Intel 10 Game Console | Intel Game Console |
Study 2: stimuli
Number sets rated for each brand/product | Brand/product sets listed in the order of matching associations with numbers | Specific semantic associations |
|---|---|---|
100 (MCN) | Holmes air purifier* | MCN |
69 | Trojan condoms | Has a sexual reference |
86 | Raid bug spray | Means “to terminate” in slang language |
101 | Sushi for Beginners Text Book | Associated with introductory courses |
360 (MCN) | Clif protein bar* | MCN |
312 | Chicago taxi service | Chicago’s area code—participants’ location |
314 | St. Louis limo service | St. Louis’ area code—participants’ location |
401 | H&R Block retirement software | Number used in retirement plans |
24 (MCN) | Cuisinart toaster* | MCN |
21 | Smirnoff vodka | Legal age for drinking |
23 | Nike Jordan shoes | Michael Jordan’s jersey number |
28 | February Fashion Magazine | Total number of days in February |
1000 (MCN) | Ikea sofa bed* | MCN |
1024 | Dell hard disk drive | Bits of data computing |
1040 | TurboTax tax software | Number label on federal tax forms |
1080 | Sony HDTV | Associated with HDTV resolutions |
Study 3: Stimulus example
Which one of these ketchup alternatives would you pick?
Please rate your attitude toward the following brand name number combinations (1–7 Extremely dislike/Extremely like)
Baskin Robbins 31 Ketchup, Baskin Robbins 57 Ketchup
Please indicate your agreement with the following statements:
-
Baskin Robbins is strongly associated with Ketchup
-
Ketchups are strongly associated with number 31
-
Baskin Robbins is strongly associated with number 31
-
Ketchups are strongly associated with number 57
-
Baskin Robbins is strongly associated with number 57
-
Ketchup is a typical product for Baskin Robbins
-
31 is a typical brand name number for Ketchup
-
31 is a typical number for Baskin Robbins brand
-
57 is a typical brand name number for Ketchup
-
57 is a typical number for Baskin Robbins brand
Appendix 4
Detailed results of mediation model 1—based on d1 coding as discussed in “Appendix 3” in ESM (d1=0, d2=0 for 360; d1=1, d2=0 for 401; d1=0, d2=1 for 860, and 360 acts as a control group)
Model 4: Y = Attitude; X = No401; Mediator1 = Product number; Mediator2 = Brand Number; Control = No860
Outcome: product number | R = .3392, R2 = .1150, F(2,290) = 18.8472, p < .001 | |||||
B | Se | T | p | LLCI | ULCI | |
Constant | 3.3535 | .1552 | 21.6110 | .0000 | 3.0481 | 3.6590 |
No401 | 1.3307 | .2218 | 6.0007 | .0000 | .8942 | 1.7671 |
No860 | .4040 | .2195 | 1.8411 | .0666 | − .0279 | .8360 |
Outcome: brand number | R = .2853, R2 = .0814, F(2,290) = 12.8509, p < .0001 | |||||
B | se | T | p | LLCI | ULCI | |
Constant | 3.3131 | .1334 | 24.8332 | .0000 | 3.0505 | 3.5757 |
No401 | .6763 | .1907 | 3.5475 | .0005 | .3011 | 1.0516 |
No860 | − .2626 | .1887 | − 1.3919 | .1650 | − .6340 | .1087 |
Outcome: attitude | R = .3927, R2 = .1542, F(4,288) = 13.1315, p < .001 | |||||
b | Se | T | p | LLCI | ULCI | |
Constant | 3.9390 | .2970 | 13.2609 | .0000 | 3.3544 | 4.5236 |
Product number | .2582 | .0626 | 4.1237 | .0000 | .1350 | .3814 |
Brand number | .2418 | .0728 | 3.3207 | .0010 | .0985 | .3852 |
No401 | − .6500 | .2334 | − 2.7845 | .0057 | − 1.1095 | − .1906 |
No860 | − .6368 | .2203 | − 2.8899 | .0041 | − 1.0705 | − .2031 |
Total effect model
Outcome: attitudes | R = .1551, R2 = .0240, F(2,290) = 3.5724, p < .001 | |||||
B | se | T | p | LLCI | ULCI | |
Constant | 5.6061 | .1644 | 34.0937 | .0000 | 5.2824 | 5.9297 |
No401 | − .1429 | .2350 | − .6082 | .5436 | − .6054 | .3196 |
No860 | − .5960 | .2325 | − 2.5628 | .0109 | − 1.0536 | − .1383 |
Total, direct and indirect effects
Total effect of X on Y
B | SE | t | P | LLCI | ULCI | |
− .1429 | .2350 | − .6082 | .5436 | − .6054 | .3196 |
Direct effect of X on Y
B | SE | t | P | LLCI | ULCI | |
− .6500 | .2334 | − 2.7845 | .0057 | − 1.1095 | − .1906 | |
Indirect effect of X on Y
b | Boot SE | BootLLCI | BootULCI | ||
Total | .5071 | .1204 | .2953 | .7637 | |
Product number | .3436 | .1066 | .1612 | .5803 | |
Brand number | .1636 | .0773 | .0455 | .3594 | |
Contrast | .1800 | .1420 | − .0990 | .4690 | |
Contrast: Product number minus brand number
Detailed results of mediation Model 2 based on d2 coding as explained in “Appendix 3” in ESM (d1 = 0, d2 = 0 for 360; d1 = 1, d2 = 0 for 401; d1 = 0, d2 = 1 for 860, and 360 acts as a control group)
Model 4: Y = Attitude; X = No860; Mediator1 = Product number; Mediator2 = Brand number; Control = No401
Outcome: product number | R = .3392, R2 = .1150, F(2,290) = 18.8472, p < .001 | |||||
B | se | T | p | LLCI | ULCI | |
Constant | 3.3535 | .1552 | 21.6110 | .0000 | 3.0481 | 3.6590 |
No860 | .4040 | .2195 | 1.8411 | .0666 | − .0279 | .8360 |
No401 | 1.3307 | .2218 | 6.0007 | .0000 | .8942 | 1.7671 |
Outcome: brand number | R = .2853, R2 = .0814, F(2,290) = 12.8509, p < .0001 | |||||
B | se | T | p | LLCI | ULCI | |
Constant | 3.3131 | .1334 | 24.8332 | .0000 | 3.0505 | 3.5757 |
No860 | − .2626 | .1887 | − 1.3919 | .1650 | − .6340 | .1087 |
No401 | .6763 | .1907 | 3.5475 | .0005 | .3011 | 1.0516 |
Outcome: attitude | R = .3927, R2 = .1542, F(4,288) = 13.1315, p < .001 | |||||
b | se | T | p | LLCI | ULCI | |
Constant | 3.9390 | .2970 | 13.2609 | .0000 | 3.3544 | 4.5236 |
Product number | .2582 | .0626 | 4.1237 | .0000 | .1350 | .3814 |
Brand number | .2418 | .0728 | 3.3207 | .0010 | .0985 | .3852 |
No860 | − .6368 | .2203 | − 2.8899 | .0041 | − 1.0705 | − .2031 |
No401 | − .6500 | .2334 | − 2.7845 | .0057 | − 1.1095 | − .1906 |
Total effect model
Outcome: attitudes | R = .1551, R2 = .0240, F(2,290) = 3.5724, p < .001 | |||||
B | se | t | p | LLCI | ULCI | |
Constant | 5.6061 | .1644 | 34.0937 | .0000 | 5.2824 | 5.9297 |
No860 | − .5960 | .2325 | − 2.5628 | .0109 | − 1.0536 | -.1383 |
No401 | − .1429 | .2350 | − .6082 | .5436 | − .6054 | .3196 |
Total, direct, and indirect effects
Total effect of X on Y | ||||||
b | SE | t | P | LLCI | ULCI | |
− .5960 | .2325 | − 2.5628 | .0109 | − 1.0536 | − .1383 | |
Direct effect of X on Y | ||||||
b | SE | t | P | LLCI | ULCI | |
− .6368 | .2203 | − 2.8899 | .0041 | − 1.0705 | − .2031 | |
Indirect effect of X on Y | |||||
b | Boot SE | BootLLCI | BootULCI | ||
Total | .0408 | .0954 | − .1389 | .2391 | |
Product number | .1043 | .0641 | .0059 | .2606 | |
Brand number | − .0635 | .0503 | − .1957 | .0089 | |
(C1) | .1678 | .0646 | .0560 | .3082 | |
Contrast: product number minus brand number
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Ozcan, T., Gunasti, K. How associations between products and numbers in brand names affect consumer attitudes: introducing multi-context numbers. J Brand Manag 26, 176–194 (2019). https://doi.org/10.1057/s41262-018-0125-1
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DOI: https://doi.org/10.1057/s41262-018-0125-1