Honey we need to talk - KOS

The Impact of Product Recall Message
Design on Shareholder Reactions
Raoul V. Kübler!
Honey we need to talk
KOS Marketing Camp
Sabanci University, Istanbul
April 25, 2014

KOS Marketing Camp 2014, Sabanci University, Istanbul, April 25, 2014Raoul V. Kübler
Agenda
2
Introduction
Conceptual Framework
Sample, Model and Estimation
Results
Implications & Future Research
I
II
III
IV
V

Product Recalls: a signiﬁcant threat to
public welfare
0
45
90
135
180
2001 2003 2005 2007 2009 2011 2013
Worldwide signiﬁcant increase of
product recalls since 20011
Consequences are tremendous:
In 2011 in the US only defect toys
caused 17 deaths and 250,00
injuries2
Yearly public costs in the US:  
400 million USD
3
1Beamish, P.W., & Bapuji, H. (2008). Toy Recalls and China: Emotion vs. Evidence. Management and Organization Review, 4(2), 197-208.!
2 CPSC (2011), "Toy Related Deaths Calendar 2010," in CPSC Online Report Vol. 2013.!

Recalls also a signiﬁcant threat for
companies
4
Product Recalls exert negative impact on
product image (Mowen et al. 1985), brand
equity (Dawar et al. 2000), perceived product
quality (Mowen 1979) and consideration
(Rhee and Haunschild, 2006)
Decrease in sales (deMattos and Rossi, 2007) and
market share (Cleeren et al. 2008)
Negative impact on marketing effectiveness!
for recalled product and other products of same
manufacturer; cross sensitivities also affected,
competitors proﬁt (van Heerde et al. 2007)

Shareholders anticipate negative
consequences
5
-20
-15
-10
-5
0
5
10
• Recalls lead to significant
drop in financial
performance and firm
value (Chen et al. 2007)
• However significant
differences in magnitude
• Even positive effects
• Recalls bring a severe risk for negative investor reactions
• However ways to minimize or even overcome negative effects

No concrete insights how to minimize
negative consequences
6
Product Recall
The products made by the PCA Blakely,
Georgia facility include peanut butter,
peanut paste, oil roasted and dry roasted
peanuts, granulated peanuts, and peanut
meal. This investigation and subsequent
recall became so widespread and
complicated because some of the
company's products were distributed in
large containers directly to institutions
such as schools and retirement homes
FDA's mission is to
protect and promote
the health of
Americans. FDA does
many things every
day to accomplish
this mission related to
• Recall Message
primary tool to calm
down consumers
and reinstall trust
• Recall Messages
share four Key
Dimensions
• Message content adapted to
recall circumstances (Kübler
and Albers 2010)
• Very limited insight on
consumer reactions
• No insights on shareholder
reactions (Chen et al. 2007)
HOWEVER: Investors have
different interests than
consumers (Financial Value
VS. Consumer Safety)
Speciﬁc Recall Message design DECREASING negative
consumer reactions might simultaneously INCREASE
negative shareholder reactions
1. How do investors react to the design of the recall message!
2. How do investor and company speciﬁc factors moderate
the reaction
Research
Ques+ons

Agenda
7
Introduction
Results
I
II
III
IV
V

1 out of 3 options pays off1
8
Denial
Blame
Pro-Active Communication
Ignorance of market rumors, works
at best only in very short term
Acceptance of defect. But company
blames consumers or suppliers for causing
defect. Works only in the short term
Acceptance of defect. Company pro-
actively communicates defect and
addresses problems. Works in the long term
1Quarantelli, E., L. (1988). Disaster Crisis Managment: A Summary of Research Findings. Journal of Management Studies, 25(4), 373-84.

Recall Message Design Matters
9
Pro-Active Communication1
As an assuring measure of preventive consumer protection
we offer you the possibility of returning the apple slicer
marketed by us for 1.00€ (GER/AUT/SLO) and 29.00 CZK
(CZE). As a matter of course we will refund your purchase
price in full.
Dear customer,
In delivering our services we always place great importance on
product quality and reliability. Especially when it comes to
customer safety one cannot be careful enough. Unfortunately,
in spite of our permanent quality and safety controls mistakes
cannot always be avoided.
Attention! Product Recall
In case of the apple slicer, being distributed under item no
2351700, we detect the risk of breaking and splintering parts
with the use of the product which may cause injuries.
As a matter of course we will refund your
purchase price in full upon presentation of
the corresponding receipt at one of our
stores.
Kind regards,
Your KiK-Team
Social Responsibility Statements
6 levels
1. Security of clients

2. + stressing standards in QA

…

6. + Detailed Information on all installed safety mechanisms
Transparency
4 different levels:
1. Mention the defect
…
4. Mention all possible risks and injuries
Help with Identiﬁcation
6 different levels:
1. Only name of product
…
6. Detailed description and Call Center
Return Convenience
6 different levels:
!
1. Disposal without compensation
…
6. Replacement/ on-site repair
1Kübler, R.V., & Albers, S. (2010). Communication Behavior of Companies in Product Recalls Without Customer Identiﬁcation Information.
Marketing Journal of Research an Management, 6(1), 59-69.

Dissonance and Commitment1
10
mp3mp3
Strong Commitment
Low Commitment
Conﬁrm
ation
otherinfo
ignored
Conﬁrm
ation
otherinfo
rational evaluation
Commitment decides on type of reaction
In case of high commitment information that
helps to reduce regret important
In case of low commitment information that helps to rationally
asses situation, decision based upon consequences
1Cohen, J.B., & Goldberg, M.E. (1970). The Dissonance Model in Post-Decision Product Evaluation. Journal of Marketing Research (JMR), 7(3),
315-21.

Investor commitment driven by
company size1
11
Small Companies Large Companies
Stronger Commitment Lower Commitment
VS.
• No established routines to
assess companies
• Data less likely to be
available
• Takes more time and effort
to make investment
decision
• Established routines
• Data and expertise
publicly available
• Less engaging as
perceived to be
anonymous
• Takes less time and effort
to assess
1Bhattacharya, C.B., & Sen, S. (2003). Consumer--Company Identiﬁcation: A Framework for Understanding Consumers' Relationships with
Companies. Journal of Marketing, 67(2), 76-88.

Effects for smaller companies
12
Small Companies
• Strong Social Responsibility
statements emphasize how strong
the company cared about
customers (H1)
• Strong Identiﬁcation Help
highlights company’s good will
(H2)
• Transparency and Convenience of
Return no impact or even negative
impact (H3 and H4)
Soc. Respon
Transp.
HwI
ConRet
Investor
Reactions
H1
(+)
H2 (+)
H3 (-)
H4(-)
Regret Reduction

Larger Companies: Expertise matters
13
Large Companies
• Lower commitment provokes more rational perspective
• Behavior now driven by expertise, focus, and goal
• Signiﬁcant differences between private and professional
investors
Private Investors
Professional Investors
• Lower expertise
• Invest own money
• More longterm orientated
(pensions, etc.)
• Higher expertise
• Not „playing“ with own money
• More short-term orientated
(bonuses, etc.)

Larger Companies: Expertise matters
14
Private Investors
Cost Reduction Problem Investigation
Lower expertise will set focus on
obvious effects like costs, potential
image and sales losses
Stronger expertise will set focus on
underlying reasons of recall to judge
future risks
Soc. Respon
Transp.
HwI
ConRet
Private
Investor
Reactions
H5
(+)
H6 (+)
H7 (-)
H8(-)
Soc. Respon
Transp.
HwI
ConRet
Prof.
Investor
Reactions
H9
(-)
H10 (-)
H11 (-)
H12(+)

Investors of Small
Companies
Conceptual Model
15
Regret Reduction
Cost Reduction
Problem
Investigation
Soc. Respon.
Transp.
HwI
ConRet
MessageDesign
InvestorReactions
Private Investors of
Larger Companies
Prof. Investors of
Larger Companies
+
+
-
-
-
+
+
+
-
-
-
-

Agenda
16
Introduction
Results
I
II
III
IV
V

Event Study Approach with 2 Stage Model
17
Investors ofSoc.
Trans
H
ConR
MessageDesign
InvestorReactions
Private
Prof.
+
+-
--++
+
---
-
Regret Reduction
Cost
Problem
Investigation
Stage
1

Abnormal

Returns
(AR)

Stage
2

Explain
AR
with

recall
message
design
1 2
Fama/French
Model to
investigate
Abnormal
Returns (AR) for
each product
recall
Expert Based
Content Analysis of
Recall Messages to
measure strength of
each recall
message dimension
Latent Class
Regression Model to
explain differences
in AR through recall
speciﬁc message
design

1st Stage: Estimation of Abnormal Returns
with Fama/French Model1
18
Rit
− Rft
= αij
+ βi
*(Rmt
− Rft
)+ si
* SMBt
+ hi
* HMLt
+ εit
Fama/French 3 factor model
t = time index; i = recall index
Rit = return of i in t; Rmt= average market return in t
SMB = weighted portfolio of small minus big stocks
HML = weighted portfolio of high book to market
minus low book to market stocks
22.5
45
67.5
90
Average Market Recalling Comp SMB
HML
17.5
35
52.5
70
Predicted Return Recalling Comp
Abnormal Return !
due to Recall
Abnormal Returns
Cumulated Abnormal Returns
ARit = Rit −Rft − αi + βi i(Rmt −Rft )+si iSMBt +hi iHMLt + εit( )⎡
⎣
⎤
⎦
CARi = ARit
t=−1
t=1
∑
Abnormal Returns depict difference between
predicted share price and real share price
plus/minus 1 day to account for leaked and
lagged information
1Srinivasan, S., & Hanssens, D.M. (2009). Marketing and Firm Value: Metrics, Methods, Findings, and Future Directions.
Journal of Marketing Research (JMR), 46(3), 293-312.

2nd Stage: Explain AR with Latent-Class
Regression Model1
19
Regret Reduction
Cost
Problem
Investigation
Conceptual model requires
estimation model that accounts
for heterogeneity
!
• Company Size
• Types of Investors
• Types of Recalls
• Industries
• Brand/NoBrand
Latent Class Regression allows
estimating models, which
simultaneously identify homogenous
clusters and estimate effects for
each cluster
DV: CAR
IV: SocResp, Trans, HwI, ConRet
Co-Var: Comp Size, Type of Inv.
Estimation of model with Latent
Gold in V4.0
1Wedel, M., & Kamakura, W.A. (2000). Market Segmentation: Conceptual and Methodological Foundations. Boston: Kluwer Academic.

Sample: All recalls of stock listed companies
in Germany between 2007 and 2010
20
• Identiﬁcation of all recalls from stock
listed companies in Germany,
Switzerland and Austria since 2007
• Exclusion of companies with risk of
confounding events
• In total 60 recalls from 6 industries
• Data from Thomson Reuters
Datastream
• Company data and investor data
from Yahoo Finance Germany
• Original recall messages from all
recalls with the help of semi-
governmental database
• Expert Based Content Analysis
• Daily Fama/French Factors from LM
University Munich F/F dataset for
Germany (data from 1981 to 2010)
-20
-15
-10
-5
0
5
10
Abnormal Returns
Industry Distribution

Agenda
21
Introduction
Results
I
II
III
IV
V

Three different groups: small vs. large
and professional vs. private
22
beta z-‐value
Intercept .150** 5.370
SocR -‐.028** -‐2.686
Trans -‐0.008 -‐1.573
ConRet .004
. 0.121
HwI -‐.014** -‐2.865
Size .001* 1.884
Investor -‐.031** -‐2.312
beta z-‐value
Intercept -‐.030

. -‐0.705
SocR .050** -‐7.619
Trans .012

. 1.502
ConRet .045** 6.825
HwI .001

. 0.003
Size .001** 2.232
Investor .024*
.
1.757
beta z-‐value
Intercept .196** 6.761
SocR 0.42** 9.258
Trans -‐.021** -‐3.773
ConRet -‐.010** -‐2.101
HwI .025** 5.006
Size -‐.001** -‐2.160
Investor .008

. 0.45
Class-R2 = .594
Class Size = 48.4%
Class-R2 = .920
Class Size = 26.9%
Class-R2 = .955
Class Size = 24.2%
Large Companies
Private Investors
Large Companies
Small Companies

Empirical Findings In Line With
Conceptual Model
23
Large Companies
Private Investors
Large Companies
Small Companies
H1: √ (SocR +)
H2: √ (Trans -)
H3: √ (HwI +)
H4: √ (ConRet -)
Regret Reduction
H5: √ (SocR +)
H6: n.e. (Trans -)
H7: n.e. (HwI +)
H8: √ (ConRet +)
Cost & Risk Reduction Problem Investigation
H9: √ (SocR -)
H10: n.e. (Trans -)
H11: √ (HwI -)
H12: n.e. (ConRet +)

Agenda
24
Introduction
Results
I
II
III
IV
V

Address investors separately
25
Reduce Regret!
• High degrees of
social responsibility
and help with
identiﬁcation
• Low degrees of
transparency and
return convenience
Emphasize Actions!
• High degrees of
• High degrees of
return convenience
Avoid Suspicion!
• Low degrees of
• Low degrees of
help with
identiﬁcation

Future Research Opportunities
26
Sample only reﬂects
German behavior
Future research should
address this shortcoming
by investigating how
culture moderates impact
of message design on
shareholder reactions
Current Analysis does
not account for multiple
recalls from same
company
Future research should
account for dynamic and
stock effects from a recall

Honey we need to talk - KOS

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