The impact of a ban on slim cigarettes on illicit trade in Romania

The impact of a ban on slim cigarettes on illicit trade in Romania
SKIM | Consumer Research
February 2013
Outline
Background and objectives
Conclusion
Method and sample
Results
Appendix
2
Background
•
3
In EU legislative proposal revising the Tobacco Product Directive
foresees a ban on slim and super slim cigarettes. This means that sale of
slim and super slim cigarettes will no longer be allowed in Romania.
Some academics voiced concerns that a sudden limitation on availability
of slim and super slim cigarettes might unintentionally create
opportunities for illicit trade in tobacco products (Transcrime report
“Crime proofing of the policy for the revision of the Tobacco Product
Directive” January 2012). Philip Morris International commissioned SKIM
to conduct this research with the objective to evaluate the impact of the
unavailability of slim and super slim cigarettes in regulated points of sale
in Romania.
Aim of the study
• Evaluate the impact of removing slim and super slim cigarettes from the
Romanian legal market
• Assess the willingness of consumers to purchase cigarettes from the black
market in a scenario where no slim or super slim cigarettes are available in
the legal market in Romania
4
About SKIM
5
•
SKIM is an international research agency that specializes in developing,
modeling and applying advanced research techniques. For over 30 years, we
have worked with multinational organizations in a variety of industries, as
well as research agencies from across the world.
•
Choice-based Conjoint, also known as Discrete Choice Modeling (DCM),
looks at choices instead of rankings, because choices are considered to be
more life-like. It requires research participants to make a series of trade-offs
by indicating their preferences within a controlled set of potential valuation of
individual elements making up the product or service – e.g. brands, package,
price, or trade channel.
Outline
Background and objectives
Conclusion
Method and sample
Results
Appendix
6
Conclusion
When slim and super slim cigarettes were
removed from the legal market, the preference
for slim and super slim cigarettes sold through
the black market increased significantly
7
When slim and super slim cigarettes were removed from
regular stores (while cigarettes with regular diameter
remain available), consumer preference for slim / super
slim cigarettes sold through the street vendor (black
market) channel increased significantly
Module 1 ScenarioCurrent market situation
Module 2 ScenarioSlim and super slim
cigarettes only available at
street vendors. In regular
stores, only cigarettes with
regular diameter are
available.
8
Regular stores
Street vendors
86% pref.share
14% pref.share
Regular stores
58% pref.share
Street vendors
42% pref.share
Outline
Background and objectives
Conclusion
Method and sample
Results
Appendix
9
Sample consisted of 624 adult smokers, selected from a
Romanian representative online panel
•
Sample consists of 183 men and 441 women
•
Age 18 (min. legal age) – 65 years
•
Smoke 6 or more manufactured cigarettes per day, with at least 3 of them being slim or super slim
•
84% of respondents who smoked slim / super slim, smoked more slim / super slim cigarettes than
cigarettes with regular diameter
•
The participation rate among slim / super slim smokers in the panel is 32%.
•
Are (co-)responsible for household shopping
•
Fieldwork was conducted between January 26, 2013 and February 5, 2013
Age
Sample
%
Sample (N)
Romania
population*
18(min. legal age) – 24 years old
15%
92
15%
25 – 34 years old
47%
292
23%
35 – 44 years old
21%
133
24%
45 – 55 years old
14%
87
19%
56 – 65 years old
3%
20
19%
*Sources: National Statistics, CIA The World Factbook, InternetWorldStats.com, Wikipedia
10
Sample% Romania population*
Male
29%
49%
Female
71%
51%
Daily smoking frequency
Average
15 cigs
Minimum
6 cigs
Maximum
40 cigs
Methodology: Choice-based Conjoint
•
A Choice-based Conjoint (CBC) design was used
• In a CBC study respondents were asked to repeatedly choose the product they would purchase
in different situations
• Each product is defined by pre-set product features such as brand, variant, price and distribution
channel
• By systematically varying the availability of products in regular stores and street vendors, and
asking respondents to make a choice each time, we can infer the importance of and preference
for the different products
•
•
•
11
In a first module, we showed respondents several screens that represent the current
market situation including products sold through street vendors
In a second module, we removed the slim and super slim cigarettes and included only
cigarettes with regular diameter in regular stores
Besides a CBC design, other questions about smoking behaviours and
street vendors were included in the questionnaire
How conjoint works
Virtual shopping trips
(conjoint based)
12
Assess sensitivities to
attributes (brand variants &
sales channel)
Create simulation model:
“predict” choices for different
situations
Methodology: Choice-based Conjoint
13
•
Each choice task offered respondents a choice of 28 SKUs* out of 40 tested:
• 21 domestic cigarette SKUs were randomly selected out of a total of
− 30 in the first module (slim / super slim cigarettes and cigarettes with regular diameter)
− 28 in the second module (only cigarettes with regular diameter)
• 7 SKUs were displayed as sold through street vendors out of a total of
− 10 in the first module (10 SKUs of non-domestic origin, with non-domestic health warnings, both slim
/ super slim cigarettes and cigarettes with regular diameter)
− 12 in the second module (2 equivalents of domestic SKUs, and 10 SKUs of non-domestic origin, with
non-domestic health warnings, both slim / super slim cigarettes and cigarettes with regular diameter)
• There was no “none” option, so respondents were forced to make a choice
•
Choice tasks materialized as screens displaying 4 rows of 7 SKUs: 3 rows for domestic SKUs sold through
regular stores and 1 row for SKUs sold through street vendors. On each screen, each respondent had to
select one SKU
•
Each respondent was requested to complete a total of 12 choice tasks during the survey (6 under the first
module and 6 under the second module)
•
The test variables were the brand and the diameter (slim / super slim cigarettes or cigarettes with regular
diameter). The price was dependent on the distribution channel. Prices for legal cigarettes were provided by
the client; prices for cigarettes sold by street vendors corresponded to observations made by the client on the
field.
*SKU – Stock Keeping Unit ,i.e. an individual product item with specific name,
flavour, size or packaging that distinguishes it from any other product item
Methodology: Choice-based Conjoint
14
•
Sales channels were described briefly and clearly indicated on screen when
respondents were asked to select the product they would buy.
•
The street vendor channel was used as a proxy for the black market.
Subjects were not directly informed that this is an illicit channel, but sufficient
information was provided for them to reach this conclusion. We did not refer
to this specifically as an illicit channel in order to control for social desirability
bias.
•
A confidentiality statement reminded respondents that their responses were
completely anonymous and confidential
In Module 1, the shelves looked like the example
below
Each respondent saw 6 screens
If these were the only products available to you, which one would you buy?
Regular stores
Street vendors
15
In Module 2, the shelves looked like the example
below
Slim and super slim cigarettes were removed from regular stores, and only cigarettes with regular
diameter were shown in regular stores. Each respondent saw 6 screens
If these were the only products available to you, which one would you buy?
Regular stores
Street vendors
16
The brands were presented in the same order in all
tasks. This allowed respondents to evaluate the
screen faster and to make more thoughtful choices.
17
•
Randomizing the brands from screen to screen “tires” respondents and increases “random”
responses.
•
Pilot studies have shown that respondents struggled to find the product they wanted to buy
when products were randomized.
The number of times a SKU appeared on screen in
the “regular stores” channel and in the “street
vendors” channel was independent of preference.
In the regular stores channel, for every
respondent, each SKU was present in 70% of
the screens in module 1, and 75% of the
screens in module 2.
In the street vendors channel, for every
respondent, each SKU was present in 70% of
the screens in module 1, and 58.3% of the
screens in module 2
18
SKUs included in the study Module 1
Domestic SKUs
DUNHILL FINECUT LTK OCT 20 SLI
DUNHILL FINE CUT (BLUE) LTK OCT 20 SLI
DUNHILL FINE CUT (BLACK) LTK OCT 20 SLI
DUNHILL FINE CUT (RED) LTK OCT 20 SLI
KENT HD (BLUE) KS RCB 20
KENT HD (SILVER) KS RCB 20
KENT DELUXE 100 SOF 20
KENT NANOTEK 2.0 (WHITE) KS DSP 20 SSL
KENT NANOTEK 2.0 (BLACK) KS DSP 20 SSL
L&M RED LABEL KS BOX 20
L&M RED LABEL 100 RCB 20
MARLBORO (RED UPGRADE) KS BOX 20
MARLBORO (RED UPGRADE) 100 BOX 20
MARLBORO GOLD TOUCH KS BOX 20 SLI
MONTE CARLO RED KS RCB 20
MORE KS BOX 20
PALL MALL (BLUE) KS RCB 20
PALL MALL PREMBLBL LTK RCB 20 SLI
PALL MALL EXTRA CUT LTK RCB 20 SLI
PALL MALL BLUE 100 BOX 20 SSL
PALL MALL AMBER 100 BOX 20 SSL
VICEROY KS BOX 20
Price in regular
stores
Volume
shares*
13.50
13.50
13.50
13.50
12.50
12.50
12.50
13.00
13.00
11.50
11.00
12.80
12.80
12.80
11.30
10.08
11.50
11.50
11.50
11.80
11.80
11.30
0.9%
1.5%
1.4%
0.5%
13.9%
12.5%
8.1%
0.8%
0.7%
3.5%
1.8%
3.7%
1.6%
0.6%
1.0%
1.8%
4.6%
1.6%
2.1%
0.9%
0.5%
2.4%
*PM estimates based on Nielsen retail audit
19
Domestic SKUs (continued)
VICEROY CLASSIC RED 100 BOX 20
VOGUE AROMEBAL 100 LSR 20 SSL
VOGUE BLEUE 100 BOX 20 SSL
VOGUE LILAS 100 BOX 20 SSL
WINCHESTER KS SOF 20
WINCHESTER 100 SOF 20
WINSTON BLUE KS RCB 20
WINSTON BLUE 100 DSP 20 SSL
Price in regular
stores
Volume
shares*
11.30
13.30
13.00
13.00
11.30
11.30
11.50
12.00
1.8%
0.5%
0.4%
0.5%
3.3%
4.0%
4.1%
0.6%
81.6%
TOTAL
SKUs at street vendors
DOINA KS BOX 20
DUNHILL FINE CUT (BLACK) LTK OCT 20 SLI
FAST (RED) KS BOX 20
JIN LING KS BOX 20
KISS DREAM 100 BOX 20 SSL
MONUS BLUE 100 OCT 20 SSL
PALL MALL BLUE 100 BOX 20 SSL
VICEROY KS BOX 20
WINSTON BLUE KS RCB 20
WINSTON BLUE 100 DSP 20 SSL
Price in street
vendors
6.00
9.00
7.50
6.00
7.50
9.00
8.50
7.00
7.50
9.00
Origin
MOLDOVA
SERBIA
SERBIA
UNSPECIFIED
MOLDOVA
SERBIA
MOLDOVA
UKRAINE
MOLDOVA
MOLDOVA
The SKUs and prices available in street vendors were determined
according to visual observations made by PMI in Romania
SKUs included in the study in Module 2
Domestic SKUs
ASSOS PREMIUM RED KING SIZE BOX 20
CAMEL KING SIZE BOX 20
KENT HD (WHITE) KING SIZE BOX 20
KENT HD (BLUE) KS BOX 20
KENT HD (SILVER) KING SIZE BOX 20
KENT iSWITCH KING SIZE BOX 20
KENT DELUXE 100 BOX 20
KENT HD (BLUE) 100 BOX 20
L&M RED LABEL KING SIZE BOX 20
L&M RED LABEL 100 BOX 20
LUCKY STRIKE ORIGINAL REDKING SIZE BOX 20
MARBLE KING SIZE BOX 20
MARLBORO (RED UPGRADE)KING SIZE BOX 20
MARLBORO GOLD ORIGINAL KING SIZE BOX 20
MARLBORO FILTER PLUS KING SIZE BOX 20
MARLBORO (RED UPGRADE) 100 BOX 20
MARLBORO GOLD ORIGINAL 100 BOX 20
MONTE CARLO RED KING SIZE BOX 20
MORE KS BOX KING SIZE BOX 20
PALL MALL (BLUE) KING SIZE BOX 20
ROTHMANS KING SIZE BOX 20
VICEROY KING SIZE BOX 20
VICEROY CLASSIC RED 100 BOX 20
Price in regular
stores
11.30
12.50
12.50
12.50
12.50
13.00
12.50
12.50
11.50
11.00
11.80
10.20
12.80
12.80
12.80
12.80
12.80
11.30
10.80
11.50
12.50
11.30
11.30
*PM estimates based on Nielsen retail audit
20
Volume
shares*
0.5%
0.5%
1.1%
13.9%
2.5%
0.5%
8.1%
2.4%
3.5%
1.8%
0.7%
0.8%
3.7%
1.0%
0.8%
1.6%
0.5%
1.0%
1.8%
4.6%
0.7%
2.4%
1.8%
Domestic SKUs (continued)
WINCHESTER KING SIZE BOX 20
WINCHESTER 100 BOX 20 SLIM
WINSTON BLUE KING SIZE BOX 20
WINSTON BLUE 100 BOX 20
WINSTON CLASSIC 100 BOX 20
TOTAL
SKUs at street vendors
DUNHILL FINE CUT (BLUE)KING SIZE BOX 20 slim
DUNHILL FINE CUT (BLACK)100 BOX 20 SLIM
FAST (RED)KING SIZE BOX 20
JIN LING KING SIZE BOX 20
KISS DREAM 100 BOX 20 SUPERslim
MONUS BLUE 100 BOX 20 SUPERslim
PALL MALL BLUE 100 BOX 20 SUPERslim
PALL MALL EXTRA CUT KING SIZE BOX 20 slim
VICEROY KING SIZE BOX 20
VOGUE AROMEBAL 100 BOX 20 SUPERslim
WINSTON BLUE KING SIZE BOX 20
WINSTON BLUE 100 BOX 20 SUPERslim
Price in regular
stores
11.30
11.30
11.50
11.50
11.50
Price in street
vendors
9.00
9.00
7.50
6.00
7.50
8.50
8.00
8.00
7.00
9.00
7.50
8.00
Volume
shares*
3.3%
4.0%
4.1%
2.0%
0.6%
70.2%
Origin
ROMANIA
SERBIA
SERBIA
UNSPECIFIED
MOLDOVA
SERBIA
MOLDOVA
ROMANIA
UKRAINE
UKRAINE
MOLDOVA
MOLDOVA
The SKUs and prices available in street vendors were determined
according to visual observations made by PMI in Romania
Each possible SKU was evaluated on average 4.2
times per respondent
•
•
Robust analysis means that each concept should be seen at least 2.5
times per respondent*
In this research we had:
•
For module 1:
• 30 SKUs in regular stores + 10 SKUs in street
vendors = 40 SKUs
• 6 screens * 28 concepts per screen = 168
concept appearances
• So each respondent evaluated each concept
168 / 40 = 4.2 times
• In total, each concept has been seen 4.2 * 624
respondents = 2621 times
•
•
For module 2:
• 28 SKUs in regular stores + 12 SKUs in street
vendors = 40 SKUs
• 6 screens * 28 concepts per screen = 168
concept appearances
• So each respondent evaluated each concept
168 / 40 = 4.2 times
• In total, each concept has been seen 4.2 * 624
respondents = 2621 times
Having each respondent evaluate each concept 4.2 times in each
module can be considered as very robust
*For reference on sample sizes needed in conjoint : http://www.skimgroup.com/images/stories/technicalpapers/General%20conjoint%20analysis/samplesz.pdf
21
The sample size in this study was appropriate for the
number of concepts that needed to be evaluated
•
In terms of relationship between number of respondents, number of
alternatives and number of screens, ideally a study should have*:
Nr of respondents * Nr of tasks * Nr of alternatives per task
Nr of levels in the largest attribute
•
> 500
In this study, we had in each of the 2 modules:
624 respondents * 6 tasks in each module * 28 concepts per screen
40 SKUs per module
*For reference on sample sizes needed in conjoint :
http://www.skimgroup.com/images/stories/technicalpapers/General%20conjoint%20analysis/samplesz.pdf
22
= 2621
Terminology: preference shares
•
23
These represent the preferences of respondents in a given scenario. For
example, if 20% of respondents would choose Marlboro Rosu Scurt in a given
situation then the preference share is 20%.
Outline
Background and objectives
Conclusion
Method and sample
Results
•
Explanation of the scenarios simulated using the data from the CBC module
•
Baseline scenario - Current market situation including slim / super slim cigarettes in regular stores and street vendors
•
Slim / super slim ban scenario – Slim / super slim cigarettes are removed from regular stores where only cigarettes with
regular diameter are left available
Appendix
24
Scenarios analyzed – Explanation
While the survey results allow for the assessment of
as many scenarios as necessary, the 2 scenarios
described here were selected as providing the most
relevant results.
25
The Scenarios
•
Baseline scenario: The current market situation
• Regular stores: 30 SKUs (of which 15 are slim and super slim cigarettes)
• Street vendors: 10 SKUs of foreign origin (of which 5 are slim and super slim cigarettes)
•
Slim / super slim ban scenario
• Regular stores: 28 SKUs of manufactured cigarettes (0 slim and super slim cigarettes)
• Street vendors: 12 SKUs (2 domestic equivalents + 10 brands non-domestic) of which 8 are slim and
super slim cigarettes
See next slides for visual illustration
26
The baseline scenario represents the current market
situation with slim and super slim cigarettes in regular
stores and at street vendors
Baseline scenario visual illustration
Regular stores
Street vendors*
* Refers to situations where packs of cigarettes are sold outside a regular store, such as on a sidewalk, in a fair or in open markets.
27
The slim / super slim ban scenario represents the market
situation with no slim and no super slim cigarettes in
regular stores but with slim / super slim cigarettes still
available in street vendors
Slim / super slim ban scenario visual illustration
Regular stores
Street vendors*
* Refers to situations where packs of cigarettes are sold outside a regular store, such as on a sidewalk, in a fair or in open markets.
28
Baseline scenario – The current market situation
Although 3%* of all respondents state they usually
buy cigarettes from street vendors, 14% indicated a
preference for products sold by street vendors in
conditions corresponding to the actual market
situation, assuming equal access to both regular and
street vendor channels.
*This is limited to ‘street vendors’, and does not include other possible illicit channels
29
Currently 92% of respondents have already seen street
vendors, 51% have purchased from a street vendor and
3% state they usually buy cigarette packs from street
vendors
Ever purchased from a street
vendor
Yes
51%
No
49%
How often do you see street vendors selling cigarette packs?
20%
Everyday
23%
Every other day
Twice a week
5%
Once a week
6%
Every two weeks
Once a month
3%
5%
30%
Less often
Never
8%
N=624
30
92% of
respondents
have already
seen street
vendors
Places where you usually buy cigarettes
Grocery store
Kiosk
Mixed store
Supermarket / minimarket
Hypermarket
Petrol station
Liquor store
Market / market stall
Tobacconist
Discount store
Street vendor
Hotel / restaurant / cafe / discoteque / club
Store from the university campus
Other
50%
67%
61%
80%
66%
60%
10%
8%
24%
3%
3%
28%
8%
0%
N=624
Preference by age and gender groups
Baseline scenario (current situation)
60.0%
Respondents’ preference for street vendors
50.0%
40.0%
30.0%
20.0%
10.0%
14.2%
10.1%
19.0%
13.3%
15.0%
25-34 years
35-45 years
46-65 years
N=292
N=133
N=107
11.4%
15.3%
0.0%
All
N=624
31
18(min. legal
age) -24 years
N=92
Male
N=183
Female
N=441
Summary – Current market dynamics
32
•
92% of adult smokers who buy manufactured tobacco products in Romania are
aware of the street vendor channel.
•
3% usually buy cigarette packs from street vendors while 51% have ever bought a
pack of cigarettes from street vendors.
•
When faced with a situation where access to regular stores and street vendors is
equal, 14% indicated a preference for lower price products from street vendors
even when their preferred product is still available in regular stores.
Slim / super slim ban scenario – No slim or super slim cigarettes
available in regular stores
Removing slim and super slim cigarettes and having
only cigarettes with regular diameter in regular
stores increases preference share of brands sold
through street vendors by 195% (from 14% to 42%)
33
In a market with slim and super slim cigarette packs
available only at street vendors, preference share for the
street vendor channel increases by 195% (from 14% to
42%*).
Respondents’ preference for street vendors
70.0%
60.0%
50.0%
40.0%
30.0%
41.8%*
20.0%
10.0%
14.2%
0.0%
Baseline scenario
Current market situation with slim and
super slim cigarettes available in regular
stores
N=624
34
Slim / super slim ban scenario
No slim or super slim cigarettes available in
regular stores.
N=624
* Difference vs. the baseline
scenario is statistically
significant for a level of
confidence of 99% (p<0.001)
Preference by age and gender groups
Slim / super slim ban scenario
Respondents’ preference for street vendors
60.0%
50.0%
40.0%
30.0%
20.0%
41.8%
46.8%
38.7%
38.4%
18(min. legal age) 24 years
25-34 years
47.7%
44.5%
35.3%
10.0%
0.0%
All
N=624
35
N=92
N=292
35-45 years
46-65 years
N=133
N=107
Male
N=183
Female
N=441
Summary
•
36
Removing slim / super slim cigarettes and having only cigarettes with
regular diameter in regular stores increases preference share of brands
sold through street vendors by 195% (from 14% to 42%)
Details about the chip allocation methodology and results
2 chip allocation questions were included,
independent from the conjoint module.
37
Visual example of the chip allocation questions.
Respondents were first asked to indicate the last 10 packs they actually
purchased (brand and trade channel). Later, they were asked to indicate
which 10 packs they would buy in the future if slim and super slim cigarettes
were removed from the regular stores.
•
38
In the first chip allocation question, the packs correspond to
the current market situation, including slim and super slim
packs of cigarettes in both regular stores and street in
vendors. The preferred SKU of every respondent was
available in the first chip allocation question, but removed in
the second chip allocation question.
•
In the second chip allocation question, regular stores
had only cigarettes with regular diameter. The street
vendors presented a random mixture of slim and super
slim cigarettes and cigarettes with regular diameter.
Regular stores
Regular stores
Street vendors
Street vendors
Results of the chip allocation tasks. After being
introduced to a market where slim and super slim
cigarettes are no longer available in regular stores,
respondents declared intentions of buying significantly*
more packs from street vendors.
% of the last 10 packs bought
% of next 10 packs expected to buy
6.8%
28.4%
Regular
stores
Regular
stores
93.2%
Street
vendors
Thinking of the last 10 cigarette packs
you bought, please indicate how many of
each were from the packs presented.
39
71.6%
* This difference is
statistically different for a
level of confidence of 99%
(p<0.001)
Street
vendors
Thinking of the next 10 cigarette packs you
plan to buy, please indicate how many of
each of the following packs you would buy.
Outline
Background and objectives
Conclusion
Method and sample
Results
Appendix
40
Details about the CBC methodology
41
Number of times each SKU was evaluated in module 1
Domestic SKUs
DUNHILL FINECUT LTK OCT 20 SLI
DUNHILL FINE CUT (BLUE) LTK OCT 20 SLI
DUNHILL FINE CUT (BLACK) LTK OCT 20 SLI
DUNHILL FINE CUT (RED) LTK OCT 20 SLI
KENT HD (BLUE) KS RCB 20
KENT HD (SILVER) KS RCB 20
KENT DELUXE 100 SOF 20
KENT NANOTEK 2.0 (WHITE) KS DSP 20 SSL
KENT NANOTEK 2.0 (BLACK) KS DSP 20 SSL
L&M RED LABEL KS BOX 20
L&M RED LABEL 100 RCB 20
MARLBORO (RED UPGRADE) KS BOX 20
MARLBORO (RED UPGRADE) 100 BOX 20
MARLBORO GOLD TOUCH KS BOX 20 SLI
MONTE CARLO RED KS RCB 20
MORE KS BOX 20
PALL MALL (BLUE) KS RCB 20
PALL MALL PREMBLBL LTK RCB 20 SLI
PALL MALL EXTRA CUT LTK RCB 20 SLI
PALL MALL BLUE 100 BOX 20 SSL
PALL MALL AMBER 100 BOX 20 SSL
VICEROY KS BOX 20
VICEROY CLASSIC RED 100 BOX 20
42
N
2604
2621
2650
2635
2653
2601
2616
2617
2608
2631
2639
2629
2620
2630
2621
2621
2621
2612
2611
2594
2643
2616
2614
Domestic SKUs (continuation)
VOGUE AROMEBAL 100 LSR 20 SSL
VOGUE BLEUE 100 BOX 20 SSL
VOGUE LILAS 100 BOX 20 SSL
WINCHESTER KS SOF 20
WINCHESTER 100 SOF 20
WINSTON BLUE KS RCB 20
WINSTON BLUE 100 DSP 20 SSL
SKUs at street vendors
N
2605
2602
2611
2610
2632
2605
2632
N
DOINA KS BOX 20
2625
DUNHILL FINE CUT (BLACK) LTK OCT 20 SLI
2631
FAST (RED) KS BOX 20
2603
JIN LING KS BOX 20
2617
KISS DREAM 100 BOX 20 SSL
2637
MONUS BLUE 100 OCT 20 SSL
2613
PALL MALL BLUE 100 BOX 20 SSL
2622
VICEROY KS BOX 20
2623
WINSTON BLUE KS RCB 20
2632
WINSTON BLUE 100 DSP 20 SSL
2605
Number of times each SKU was evaluated in module 2
Domestic SKUs
ASSOS PREMIUM RED KING SIZE BOX 20
CAMEL KING SIZE BOX 20
KENT HD (WHITE) KING SIZE BOX 20
KENT HD (BLUE) KS BOX 20
KENT HD (SILVER) KING SIZE BOX 20
KENT iSWITCH KING SIZE BOX 20
KENT DELUXE 100 BOX 20
KENT HD (BLUE) 100 BOX 20
L&M RED LABEL KING SIZE BOX 20
L&M RED LABEL 100 BOX 20
LUCKY STRIKE ORIGINAL REDKING SIZE BOX 20
MARBLE KING SIZE BOX 20
MARLBORO (RED UPGRADE)KING SIZE BOX 20
MARLBORO GOLD ORIGINAL KING SIZE BOX 20
MARLBORO FILTER PLUS KING SIZE BOX 20
MARLBORO (RED UPGRADE) 100 BOX 20
MARLBORO GOLD ORIGINAL 100 BOX 20
MONTE CARLO RED KING SIZE BOX 20
MORE KS BOX KING SIZE BOX 20
PALL MALL (BLUE) KING SIZE BOX 20
ROTHMANS KING SIZE BOX 20
VICEROY KING SIZE BOX 20
VICEROY CLASSIC RED 100 BOX 20
43
N
2819
2845
2800
2804
2808
2806
2826
2799
2798
2800
2808
2820
2801
2825
2810
2826
2799
2798
2798
2800
2802
2785
2817
Domestic SKUs (continued)
N
WINCHESTER KING SIZE BOX 20
2801
WINCHESTER 100 BOX 20 SLIM
2823
WINSTON BLUE KING SIZE BOX 20
2804
WINSTON BLUE100 BOX 20
WINSTON CLASSIC 100 BOX 20
2834
2783
SKUs at street vendors
N
DUNHILL FINE CUT (BLUE) KING SIZE BOX 20 slim
DUNHILL FINE CUT (BLACK) 100 BOX 20 SLIM
FAST (RED)KING SIZE BOX 20
JIN LING KING SIZE BOX 20
KISS DREAM 100 BOX 20 SUPERslim
MONUS BLUE1 00 BOX 20 SUPERslim
PALL MALL BLUE 100 BOX 20 SUPERslim
PALL MALL EXTRA CUT KING SIZE BOX 20 slim
VICEROY KING SIZE BOX 20
VOGUE AROMEBAL 100 BOX 20 SUPERslim
WINSTON BLUE KING SIZE BOX 20
WINSTON BLUE 100 BOX 20 SUPERslim
2174
2182
2168
2201
2190
2171
2184
2188
2198
2196
2181
2168
Demographics, buying and usage behavior
44
Demographics | All respondents
Work situation
Gender
Male
29%
Full-time
78%
Female
71%
Part-time
6%
Housewife
2%
Pensioner
2%
Age
18 – 24 years old
15%
Student
9%
25 – 34 years old
47%
Unemployed
3%
35 – 44 years old
21%
45 – 55 years old
14%
56 – 65 years old
3%
Type of smokers
Light smokers
< 11 cigs per day
Medium smokers
11 – 20 cigs per day
Heavy smokers
> 20 cigs per day
45
N=624
45
37%
29%
34%
Daily smoking frequency
Average
15
Minimum
6
Maximum
40
Household monthly income
Percentage
UP TO 500 RON
501-800 RON
801-1.000 RON
1.001-1.200 RON
1.201-1.400 RON
1.401-1.600 RON
1.601-1.800 RON
1.801-2.000 RON
2.001-2.200 RON
2.201-2.400 RON
2.401-2.600 RON
2.601-2.800 RON
2.801-3.000 RON
3.001-3.200 RON
3.201-3.400 RON
3.401-3.600 RON
3.601-3.800 RON
3.801-4.000 RON
4.001-4.200 RON
4.201-4.400 RON
4.401-4.600 RON
4.601-4.800 RON
4.801-5.000 RON
MORE THAN 5.000 RON
REFUSE TO ANSWER
1.6%
2.4%
2.7%
4.2%
4.3%
3.2%
3.0%
6.4%
4.2%
5.1%
4.2%
3.7%
6.3%
5.6%
2.4%
2.1%
1.4%
5.6%
5.0%
1.9%
1.1%
1.1%
4.2%
11.5%
6.7%
All cigarette brands smoked | All respondents
52.4%
48.1%
All respondents (N = 624)
48.1%
29.3%
17.1%
15.5%
3.4%
Vogue
46
Kent
Pall Mall
Dunhill
Marlboro
Winston
Other
Brand variant smoked most often | All respondents
22%
All respondents (N = 624)
16%
15%
14%
10%
9%
8%
7%
7%
6%
5%
4%
4%
4%
3%
3%
2%
1%
47
1%
0%
1%
0%
1%
Preference share for SKUs in the slim ban scenario
All respondents
14%
13%
Regular stores
7% 7%
7% 6% 6%
6%
5%
Street vendors
4%
4%
3% 2%
2% 2% 2%
1% 1% 1%
1% 1% 1% 1% 1%
0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0% 0%
48
Street vendors
Ever purchased from a street
vendor
N=624
49
Yes
51%
No
49%
Have purchased from a
street vendor
Total
sample
Male
36%
29%
Female
64%
71%
18 – 24 years old
13%
15%
25 – 34 years old
47%
47%
35 – 44 years old
22%
21%
45 – 55 years old
14%
14%
56 – 65 years old
4%
3%
Works full-time
76%
78%
Works part-time
7%
6%
Student
9%
9%
Not working
8%
8%
Street vendors
Reasons to buy from a street vendor
Convenience
33%
Cheaper
47%
Know the vendor
13%
Favorite brand is not available elsewhere
7%
Try a new brand / change brands
13%
Other reason
16%
N=320 (ever purchased from a street vendor)
50
# packs purchased from a street vendor in
last month
0 packs
38%
1 pack
12%
2 packs
14%
3 – 4 packs
9%
5 – 10 packs
21%
More than 10 packs
7%
The questionnaire (English)
51
Questionnaire
52
Questionnaire
53
Questionnaire
54
Questionnaire
55
Questionnaire
56
Questionnaire
57
Questionnaire
58
Questionnaire
59
Questionnaire
60
Questionnaire
61
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62
Questionnaire
63
Questionnaire
64
Questionnaire
65
Questionnaire
66
Questionnaire
67
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68
Questionnaire
69
Questionnaire
70
Questionnaire
71
Questionnaire
72
Questionnaire
73
Questionnaire
74
Questionnaire
75
Questionnaire
76
Questionnaire
77
The questionnaire (Romanian)
78
Questionnaire
79
Questionnaire
80
Questionnaire
81
Questionnaire
82
Questionnaire
83
Questionnaire
84
Questionnaire
85
Questionnaire
86
Questionnaire
87
Questionnaire
88
Questionnaire
89
Questionnaire
90
Questionnaire
91
Questionnaire
92
Questionnaire
93
Questionnaire
94
Questionnaire
95
Questionnaire
96
Questionnaire
97
Questionnaire
98
Questionnaire
99
Questionnaire
100
Questionnaire
101
Questionnaire
102
Questionnaire
103
Questionnaire
104
Evidence of validity and usefulness of conjoint methodology
105
Evidence and validity of conjoint from Sawtooth
technical paper*
“ Choice-based conjoint analysis has been in use for some time now, and evidence is mounting as to its validity
and usefulness.
Earlier in this paper we described our own first use of the method, in a series of studies for Heublein, Inc., nearly
three decades ago. Sometime later, we spoke with David Eickholt, the marketing research manager responsible for
those studies, who at that time was VP Marketing at Heublein. With the benefit of a decade of hindsight, he
reported that the results from those studies were accurate in predicting the switching among brands and prices
resulting from the anticipated tax increase. He said that a critical aspect of those studies was their ability to deal
with interactions, revealing different demand curves for different brands and package sizes as prices changed.
Another commercial experience with choice-based conjoint analysis was a study done for the Chevron Chemical
Company, and described in a paper presented to the American Marketing Association's 1991 Advanced Research
Techniques conference (Johnson and Olberts, 1991). That study was also concerned with price, and considered
multiple brands in each of several different product categories. It revealed that even within a category, different
brands can respond very differently to price changes. Although we haven’t seen follow-up information regarding
ability to predict actual market responses to price changes, an author of the paper, Kathleen Olberts of Chevron,
reported that the results confirmed existing knowledge about the product categories studied. “
Find the full paper and references here:
http://sawtoothsoftware.com/download/techpap/cbctech.pdf
106
Evidence and validity of conjoint from Sawtooth
technical paper*
“ During 1991 and 1992, while developing CBC, we had the opportunity to participate with users of pre-release
versions of the software in several large-scale commercial studies. Those studies dealt with a wide variety of
products including household detergents, magnetic media, computer peripherals, and cable TV services. In each
case the client found CBC's results to be readily interpretable and easy to use, and in each case the research firm
conducting the study expressed satisfaction with the technique.
More evidence has emerged suggesting that CBC can be an effective approach for predicting actual buyer
behavior. We recommend two papers from the 1999 Sawtooth Software Conference, “Forecasting Scanner Data
by Choice-Based Conjoint Models” (Feurstein and Natter), and “Predicting Actual Sales with CBC: How Capturing
Heterogeneity Improves Results” (Orme and Heft). Furthermore, papers from Greg Rogers of Procter & Gamble
are also useful: “Validation and Calibration of Choice-Based Conjoint for Pricing Research” presented at the 2003
conference and “The Importance of Shelf Presentation in Choice-Based Conjoint Studies” presented at the 2004
conference “ (page 24, http://sawtoothsoftware.com/download/techpap/cbctech.pdf)
Find the full paper and references here:
http://sawtoothsoftware.com/download/techpap/cbctech.pdf
107
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